CLIMATE -SMART AGRICULTURE INVESTMENT PL AN MALI PAGE A MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN PAGE B MALI CLIMATE -SMART AGRICULTURE INVESTMENT PL AN THE W ORLD B A NK l A RMED A ND SECURIT Y FORCES OF M A LI l INITI ATIV E FOR THE A DA PTATION OF A FRIC A N AGRICULTURE l INTERN ATION A L CENTER FOR TROPIC A L AGRICULTURE l CLIM ATE CH A NGE , AGRICULTURE A ND FOOD SECURIT Y PAGE C © 2019 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this work is subject to copyright. Because The World Bank encourages dissemination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. Any queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@worldbank.org. Cover illustration and design by Brad Amburn Foreword Climate change threatens to bring substantial impacts to the economic productivity, job creation and food security provided by Mali’s agriculture sector. Climate change impacts on Mali aren’t unique; they also pose challenges for countries across Africa. This was recognized at the United Nations Framework Convention on Climate Change (UNFCCC) 22nd Conference of Parties (COP22; 2016) in Marrakech, Morocco, where the Moroccan government launched the Adaptation of African Agriculture (AAA) Initiative, highlighting the investment needs for helping African countries cope with climate change risks to agriculture and best position themselves for a future of higher temperatures and uncertain precipitation. The AAA Initiative also builds on the Comprehensive African Agriculture Development Programme (CAADP), first launched in 2003 through the African Union. Mali is a signatory to the UNFCCC Paris Agreement and has submitted its Nationally Determined Contributions (NDC), committing to take action both on adaptation to climate change and on reducing greenhouse emissions. Mali is a minor emitter of greenhouse gases (GHG) compared with the high-emitting countries; however, interventions in agriculture and associated land use change (e.g., reducing deforestation) that increase productivity and resilience to climate change can also contribute to reduce greenhouse gas emissions. The NDC provides targets that Mali is aiming to meet; however, it is not intended to provide the specifics on what investments are necessary or how these investments should be implemented. This document provides an investment plan for climate-smart agriculture (CSA) in Mali, developed with support of the AAA Initiative and the World Bank, and technical assistance of the International Center for Tropical Agriculture, the World Agroforestry Centre and the CGIAR Research Program on Agriculture, Climate Change and Food Security (CCAFS). It identifies specific interventions that define on-the-ground action that are consistent with Mali’s NDC and national agricultural strategy, which can be funded by public and private-sector partners. CSA interventions are designed to increase agricultural productivity, to help farmers, livestock keepers and fisher-people adapt and build resilience to climate risks, and, where appropriate, to reduce greenhouse gas emissions that cause climate change. Examples of these CSA interventions range from on-farm technologies such as stress- tolerant crop varieties and livestock breeds, to agricultural management activities (related to water, soil, fertilizer, pests, etc.), to agricultural services such as insurance, credit and weather advisories. This plan includes a set of 12 key CSA investments for Mali that were developed with strong stakeholder engagement, expert input and scientific evidence. This plan is not intended to be comprehensive but can further include additional projects when more funds will be available. The plan presents a situation analysis of Mali’s national policies, plans and programs in relation to key climate risks, which form the context for key prioritized interventions. Designed project concepts are developed for each of these key investments, including the main project objectives, components and implementation arrangements. These provide a tangible set of project concepts for potential investors and donors to consider for funding. Finally, a general framing for developing a monitoring and evaluation (M&E) framework for the CSA investment plan (CSAIP) is provided, showing how CSA outcomes relate to other M&E frameworks and other monitoring activities for national-level development priorities. As a member of the AAA Initiative that is also committed to delivering on its NDC commitments, Mali now has an investment plan including a set of specific climate-smart projects that improve productivity, build resilience to climate change and, as appropriate, reduce greenhouse gas emissions in the agriculture sector. The CSAIP provides the context and evidence for the importance of these projects, and details how they can be economically beneficial and provide food security to the people of Mali. This can help spur investment and funding for CSA to help Mali deliver on its NDC and other national targets. PAGE I Abbreviations AAA Adaption of African Agriculture ACMAD African Centre of Meteorological Application for Development AEDD Environment and Sustainable Development Agency AfSIS Africa Soil Information Service AGCC-Mali Global Alliance on Climate Change–Mali AGRHYMET Regional Center for Training & Application of Agrometeorology & Applied Hydrology AMEDD Malian Association of Awakening to Sustainable Development adoption rate AR Adoption rate ATI Land Development and Irrigation Water Supply Agency BAU Business as usual BN Bayesian networks CAADP Comprehensive Africa Agriculture Development Program CAS Country Assistance Strategy CC Climate change CCAFS Climate Change, Agriculture, and Food Security (part of CGIAR) CFA West African franc CGIAR Consultative Group on International Agricultural Research CIAT International Center for Tropical Agriculture CIIFAD Cornell International Institute for Food, Agriculture, and Development CIS Climate information services CREDD Strategic Framework for Economic Recovery and Sustainable Development CREWS Climate Risk and Early Warning Systems Project CSA Climate-Smart Agriculture CSCRP Malian Strategic Framework for Growth and Poverty Reduction CSAIP Climate-Smart Agriculture Investment Plan DNH National Hydraulics Directorate DNPIA National Industrial Animal Production Directorate DSU Dutch Sustainability Unit ECOWAP ECOWAS Regional Agricultural Policy of West Africa ECOWAS Economic Community of West African States GSIS Geospatial Information Science ICT Information Communication Technology IDA International Development Association IER Institute for Energy Research IMPACT International Model for Policy Analysis of Agricultural Commodities and Trade IRI International Research Institute for Climate and Society Mali-PRIA Malian Food Security Resilience Program MDG Millennium Development Goal MIRAH Ministry for Livestock and Fisheries MRV Forest Surface and GHG Emissions Monitoring NAIP National Agriculture Investment Plan NAPA Mali’s National Adaption Program of Action NBSAP National Biodiversity Strategy and Action Plan NGO Non-Governmental Organization NDC Nationally determined contributions No-CC No climate change scenario NPV Net Present Value NTFP Non-timber forest products ODD Sustainable Development Objectives (English translation from French) P2RS Multinational Reinforcing Resilience Against Food & Nutritional Insecurity Project PADEPA-KS Project for the Development of Animal Production in the South Kayes Zone PDA Agricultural Development Policy of Mali PDIRAAM Integrated Development of Livestock and Fisheries Resources Projects PDO Proposed development outcome/objective PI Proximity irrigation PICSA Participatory Integrated Climate Services for Agriculture PLW Pregnant and lactating women PNCC National Program for Greenhouse Gas Mitigation & Adaptation to Climate Change PNISA National Agricultural Sector Investment Plan PNUD United Nations Development Program in Mali PRRO Protracted relief and recovery operations PSAV Political stability and absence of violence RCP Representative Concentration Pathway REDD Reducing Emissions from Deforestation and Forest Degradation Program ROI Return on investment RIMA Resilience Index Measurement and Analysis SCAP Joint Country Assistance Strategy SDG Sustainable development goal PAGE III SIS Soil Information System SMS Short message service SNDI National Irrigation Development Strategy SNPGRC National Strategy for the Prevention and Management of Disaster Risk Management SRI System of rice intensification SSP Shared socioeconomic pathway SWI System of Wheat Intensification TBEA Tree-based ecosystem approaches T-ICSP Transitional Interim Country Strategic Plan UNCCD United Nations Convention to Combat Desertification UNDP United Nations Development Program UNFCCC United Nations Framework Convention on Climate Change UNHCR United Nations High Commissioner for Refugees UNISDR United Nations International Strategy for Disaster Reduction USAID United States Agency for International Development WAAPP West African Agricultural Productivity Program WFP World Food Programme WFS World Food Summit Table of Contents Executive Summary 1 Section 1: Why Climate-Smart Agriculture 9 1.1 The Climate Smart Agricultural Investment Planning framework 10 Section 2: Situation analysis of livelihoods, agriculture, and climate change 13 2.1 Mali’s rural and agricultural sector in brief 13 2.2 Mali’s rural and agricultural sector in brief 19 2.3 Climate change impacts on Mali’s agricultural Economy 23 2.4 Climate change impacts likely aggravated by shifting economic incentives 26 2.5 Climate change impacts potentially offset through shifting market incentives 27 2.6 Climate adaptation has the potential to reduce import dependency 28 Section 3: Prioritizing interventions for Climate Smart Agriculture in Mali 31 3.1 The Climate-Smart Investment Plan for Malian agriculture 31 3.2 National-Scale Climate-Smart Agriculture Service Investment summaries 33 3.3 Climate-Smart Crop and Livestock Investment summaries 34 Section 4: Guiding CSA investments in Mali from concepts to programs 39 4.1 What Mali gains from CSAIP: an overview 39 4.2 Climate-Smart Analysis for four select investments 40 4.3 Constraints to design and implementation 44 4.4 Opportunities for design and implementation 47 4.5 Financing opportunities for CSA expansion 50 4.6 CSA Investments and contributions to supporting national policies 51 4.7 CSA Investments and Contributions to Supporting National Policies 52 Section 5: Monitoring and evaluation: assessing results from Malian CSA investments 55 ANNEX 75 ANNEX A: Climate–Smart Agriculture Investment Plan methodology 75 ANNEX B: Situation analysis: policy and programmatic context for CSA in Mali 80 B-1 International and regional commitments, frameworks, and plans 80 B-2 National policies and plans 80 B-3 Other legal frameworks 82 B-4 Select donors and projects with potential links to CSA investments 83 B-5 Select World Bank projects with potential links to CSA investments 84 ANNEX C: Prioritizing interventions: the process from long-lists to finalists 86 C-1 Producing a long list of investments 86 C-2 Producing a short list of investments 88 C-3 CSA investment practices, location, risks and institutions 90 PAGE V MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN C-4 Participants at prioritizing workshop 90 ANNEX D: Structure and results of the scenario modeling analysis (RCP + SSPS) 91 D-1 About shared socioeconomic pathways (SSPs) 91 D-2 Combinations of Representative Concentration Pathways (RCPs) and SSPs 92 D-3 Impact model and modeling combinations of RCPs and SSPs 93 D-4 Scenarios purpose for modeling 93 D-5 Methodology 93 D-6 Standard measuring and interpreting the results 94 D-7 Preliminary data for Mali from IIASA database 95 D-8 Results: Heatmaps 98 ANNEX E: Climate-Smart Economic Appraisal: Methodology and extended results 100 E-1 Model design 101 E-2 Parameter estimation 105 E-3 NPV and ROI results for the four priority projects under various risk scenarios 109 E-4 Value of mitigation benefits from four priority investments 110 ANNEX F: Climate-Smart Agricultural Investment Plans in Mali 112 F-1 Remote sensing and applied geomatics program 113 F-2 National extension system program 118 F-3 Agroclimatic information services 122 F-4 National Soil Fertility Monitoring program 127 F-5 Non-Timber Forest Product Value Chains Program 131 F-6 Flood Recession Agriculture Program 136 F-7 Crop-Livestock Integration Program 141 F-8 Millet-Sorghum-Legume Integration Program 146 F-9 Climate-Smart Vegetable Production, Storage, and Processing Program 150 F-10 Restoring Degraded Lands Program 154 F-11 Rice Intensification System Promotion Program 157 F-12 Climate Smart Wheat Development Program 161 Bibliography by sections 166 PAGE VI ES Executive Summary Agriculture is Mali’s most important sector and serves as the foundation of the national economy, contributing over 38% of Mali’s gross domestic product (GDP) and employing over 80% of its economically active population. This is striking because although more than two-thirds of Mali’s land is desert or semi-desert, and only 5.3% of the land is arable, over one-third of the land is used for agriculture. Over half of the population (58%) lives in rural areas, and nearly 90% of the rural population is poor. The majority (68%) of Mali’s farmers grow basic subsistence crops on small farms, and over 85% of the agricultural households produce livestock, which provides a source of income to nearly one-third of the population. While there has been agricultural sector growth in Mali (10% in the period 2010–2016), overall productivity is low and population growth is high, threatening food security. Food production in Mali is generally unsustainable, with pressure on land increasing, the per capita land area steadily declining, and land degradation increasing. Yields for most crops (except rice) haven’t improved in 50 years. Major cereals, for example, have yield gaps of over 60%. Farmers lack inputs, extension, credit and banking, and agricultural interventions have failed to meet increasing demand for food cropsi. In 2018 about a quarter of Malians, or 4.6 million people, were food insecure and require assistance1; estimates suggest that severe food insecurity was 55% higher than in 2017. Climate change in Mali is clear and widespread, having already changed weather patterns and increased weather variability, with impacts on food security, livelihoods, conflict and migration. Mali has already experienced warmer temperatures, greater weather variability, changed rainfall patterns and more extreme weather events, such as longer dry seasons and droughts, or more intense rainfall. In the period 1980–2014, nearly 7 million people were affected by 28 droughts and floods with an economic cost of these extreme events valued at US$140 million. Erractic rainfall alone was responsible for reducing primary sector growth from 7.6% in 2016 to 4.8% in 2017. Most (over 72%) of Mali’s population is in the medium-to-high vulnerability category for climate hazards. These patterns disproportionately affect the rural poor and can lead to changes in traditional transhumance patterns, greatly increasing pressure on limited forage resources and causing conflict. 1 United Nations Press Release 31 August 2018 PAGE 1 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Mali is involved in a multicountry effort coordinated by the World Bank to develop a national Climate-Smart Agriculture Investment Plan (CSAIP). Climate-smart agriculture (CSA) increases productivity in an environmentally and socially sustainable way, strengthens farmers’ resilience to climate change and reduces agriculture’s contribution to climate change by reducing greenhouse gas emissions and increasing carbon storage in farmland. CSA focuses on agriculture, but is multisectoral, and also includes commitments to enhancing livelihood benefits, ensuring food security and promoting sustainability. This CSAIP uses an established framework and process and builds on Malian programs, policies and strategic plans (such as Mali’s NDC) and the work of numerous local, national, regional and international institutions. Mali’s national CSAIP prioritized a set of 12 investments and actions needed to boost crop resilience and enhance yields for over 1.8 million beneficiaries and their families2, helping them adapt to climate change. The CSA investments were identified based on a situation analysis of Mali’s plans and policies, the current context of agriculture, and analysis and scenario development of climate change impacts on different crops and livestock under a variety of warming scenarios for different time points out to 2050. The CSAIP relied on analysis and prioritization of investments by Malian stakeholders. This CSAIP also includes elements of program design and implementation, with economic analysis, priority setting and an analysis of barriers and opportunities. The process used to develop this plan also supports engagement and capacity strengthening. Climate modeling shows that the shifting economic landscape from climate change could exacerbate biophysical damages for key food security and commercial crops. Climate impacts do not affect all commodity groups uniformly, but for most commodity groups losses roughly double every decade. Climate change effects increase over time for all commodity groups. The top five most impacted commodity groups in the short term (2030) are (in order from greatest), maize, groundnut, vegetables, cotton, and tropical fruit, but by 2050 the order of greatest losses is different: maize, groundnut, vegetables, cowpeas, and cotton. The top five most impacted commodity groups in the short term (through 2030) are oilseeds, vegetables, sugar crops, cereals and cotton;by 2050, the order of greatest losses is: vegetables, oilseeds, cereals,sugar crops and cotton. This is concerning for food security, given the importance of maize, rice, millet and sorghum. Cotton is Mali’s largest cash crop and a source of livelihood for over 25% of the population, and its yield is expected to decline. Some of these commodities warrant protective action because of their importance for food security, nutrition or the national economy. CSA practices supporting resilience are essential to anticipate climate impacts and stop yields from declining. Climate modeling scenarios for other crops show that some are climate resilient, so CSA emphasis should be on promoting practices that emphasize and maintain their resilience. In general, livestock, fruits, and roots and tubers show the least impact from climate change. For these crops and livestock, a higher investment commitment supporting resilience and yield-enhancing technologies could expand and increase yields and production. Adaptation addressing climate change, coupled with strong economic development, should foster both food security and some agriculture-led economic development for Mali. Though relatively high levels of productivity are possible in Mali’s arable southern zone, such anticipated productivity increases could be partially offset by expected population growth. 2 Assuming all 12 investments are made and with no beneficiary overlap. PAGE 2 The CSAIP emphasizes strengthening agriculture across Mali, with four national-level investments, seven commodity-specific investments and one restoration project, taking place in all major agrozones. The geographic reach matters from an equity perspective, given the high levels of poverty and regional inequality in agriculture, and also introduces CSA practices across the country. The four national-scale initiatives represent the fundamental components of an adaptive and climate-smart agricultural sector: remote-sensing monitoring capability, CSA inclusion in national agricultural extension services, agroclimatic information systems and monitoring soil fertility. These initiatives are foundational in understanding and monitoring the agricultural sector by supporting programs in remote sensing, agroclimatic information and soil fertility monitoring. These three programs, all based in proven technologies, have the potential to provide vital, real- time guidance to both decision-makers and farmers themselves. For example, integrating CSA practices into the national extension system helps farmers directly, and also creates a mechanism for transferring the information from the three national technology-based investments to farmers and other users. The proposed development outcomes, and the beneficiary estimates (which also often extend to households) for the four-national scale investments are: • Remote sensing and applied geomatics: Increase capacity to effectively manage natural resource areas, evaluate farm productivity and address climate-related risks by providing land managers, agricultural producers, farm advisors and policymakers with timely, accurate geospatial information science (GSIS), benefitting 200,000 agricultural workers. • Extension system: Increase farm productivity and minimize climate-related risks by improving the quality and quantity of CSA-informed recommendations made to producers by farm advisors, benefitting 186,048 agricultural workers. • Agroclimatic information system: Increase farm productivity and mitigate climate-related risks by providing producers, extension agents and agribusiness with timely, accurate agrometeorological information, benefitting 400,000 agricultural workers. • Soil fertility monitoring: Increase agricultural producers’ ability to practice CSA by providing producers and extension agents with location-tailored information on soil characteristics and best management practice recommendations, and the tools, products, partnerships and policy environment to implement those recommendations, benefitting 103,360 agricultural workers. Eight climate-smart crop and livestock investments were prioritized to support adaptation of agricultural production systems by introducing a variety of climate-smart practices into the different investments. The eight CSA investments, their proposed development outcomes, and the beneficiary estimates (which also often extend to households) are: • Non-timber forest product (NTFP) value chains: Bolster Malian economic growth, food security and climate resilience through developing the agroforestry NTFP sector, benefitting 122,400 women producers and processors. • Flood recession agriculture: Increase farm productivity and minimize climate risks by providing producers, extension agents and agribusiness with technical support and improved infrastructure for optimized flood recession agricultural practices, benefitting 224,000 smallholders. PAGE 3 BANGLADESH CLIMATE SMART AGRICULTURE INVESTMENT PLAN • Livestock: Increase farm productivity and minimize climate risks by providing producers, extension agents and agribusiness with best management practices and tools for crop-livestock integration, benefitting 97,000 smallholders. • Millet-sorghum-legume integration: Increase the climate resilience and productivity of millet- sorghum systems by planting in conjunction with legumes to improve nutritional and economic outcomes of smallholders, benefitting 199,495 women farmers. • Vegetables: Increase productivity and climate resilience of vegetable production while fostering economic opportunities for producers, especially women and youth, while minimizing environmental impact, benefitting 52,747 women and youth. • Restoring degraded lands: Build national capacity to restore degraded lands at scale to increase climate resilience, ecosystem services and agricultural productivity, benefitting 106,461 agricultural producers. • Rice intensification (SRI): Increase rice productivity and climate resilience by scaling SRI to improve economic and nutritional outcomes, benefitting 72,480 producers in unflooded rice production zone. • Wheat: Increase wheat productivity and climate resilience by scaling CSA practices to improve economic and nutritional outcomes, benefitting 71,856 smallholders. The CSAIP focuses on ensuring resilience for some commodities, growth for others and a dual emphasis of resilience and growth where appropriate. Combining Putting together the results of the situation analysis (including , the climate modeling impacts) on commodities,the target beneficiaries,and Mali’s national objectives from national plans and programs provides insights on what the eight crop and livestock investments hope to achieve. Table ES-1 below demonstrates the value of the commodities within the Malian economy and society, the response to climate change, likely trends without interventions and the intended emphasis of the response. Moving from the CSA investment plans to implementation requires a strong operational framework with solid economic analysis, as well as the identification of opportunities, constraints and financing opportunities with stakeholders. The economic analysis, as well as an assessment of productivity, resilience, risks and greenhouse gas mitigation, is necessary to move from proposed investment and project design to implementation. The CSAIP identified a preliminary set of barriers and opportunities to the proposed investments that form a baseline for design considerations. Stakeholders identified four investments as high priority, and detailed economic modeling analyzes the potential economic performance of these investments, subject to expected costs, project and climate risks, and potential outcomes. Priority investments targeted three specific high-potential production systems—non-timber forest products, crop-livestock integration and flood recession agriculture—and one program of national scope, a remote sensing system. The four investments are predicted to provide significant benefits to smallholder farmers in Mali, with return on investment with CSA management of from 46%–126% compared to business as usual, as shown in Table ES-2. These substantial gains are a result of conservative estimates of both potential and rates of adoption, excluding risks. PAGE 4 Table ES.1 Overview of agriculture sector goals across CSA Rationale for all crop and livestock investment On-Farm Projected Scenario without Investment CSA investment Malian Importance response to Value climate change investment objective Decreased agricultural Non-timber forest 26%–73% of annual Economic ok production, exacerbat- Growth products revenue ed climate risks Economic 25% of total pro- Decreased food secu- Flood recession Resilience and & food ductive land under ok rity, market destabili- agriculture growth security flood recession zation 10% of national Conflict, reduced food Nutrition GDP, 85% of Malian Crop-livestock security, exacerbated Resilience and & food farmers own live- ok integration environmental degra- growth security stock, 30% primary dation livelihood Millet-sorghum- Nutrition 63% of national Remains at current low Resilience and legume & food poor integration cereal consumption production rates growth security Nutrition, Reliably high and Decreased production, food & Resilience and Vegetables growing market poor increased postharvest economic growth demand losses security Continuing loss of for- Most effective ests and arable land, Restoring method for ad- Resilience and Economic poor resulting in conflict degraded lands dressing desertifi- growth and reduced ag pro- cation ductivity Rice Economic Net exporter Continuing high water intensification & food seeking to improve ok use and relatively high Growth (SRI) security efficiency GHG emissions Economic Net importer with Decreased productivity Wheat & food poor Growth growing demand and increased imports security The Malian context presents some circumstances that could manifest as risks or barriers to the investments. Many of these barriers to CSA design and implementation stem from, or are aggravated by, policy issues, and a few that were identified as potentially affecting the success of investments were: (i) political or security crises; (ii) farmer-pastoralist conflicts; (iii) systematically excluding women from capacity building and extension; and (iv) lack of donor support or funding. Other risks are contextual, such as drought, floods, pest, disease or extreme temperatures. Specific investments face specific risks, as the preliminary analysis in Table ES–3 shows. CSAIP project design and implementation can maximize project outcomes, build on existing capacities and opportunities, and leverage CSA investment to support national policies. In particular, there are at least 13 Malian policies or programs identified that address climate change, with many also explicitly addressing adaptation. There is also strong alignment with Mali’s NDC both in terms of higher-level objectives (e.g., national planning) and for meeting specific adaptation activities (e.g., water management). There is strong correspondence between the CSAIP and its PAGE 5 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN individual investments, and support to other sectors and enabling conditions for development that are contained in Mali’s national policy documents, such as building resilience, supporting vulnerable populations (e.g., women and youth), contributing to enabling policies and others, as shown in table ES-4. A robust and well-designed M&E system, using an evidence-based results framework, is an essential component of the CSA implementation process. Such monitoring and evaluation systems are important to insure that Mali’s agriculture and food system become more climate-smart. It is also essential to provide reliable and up-to-date information to track progress on investment activities, output, outcomes and impact against target; raise flags when adaptive actions may be necessary; and serve as the basis for reporting on international agreements. Four key elements identified as part of the M&E system are increasing incomes, reducing exposure to climate risks, reducing sensitivity and vulnerability to climate risks, and increasing adaptive capacity. Table ES.2 Performance of the four priority investments Number of Impact Ben-1 Cost Cost Ben-1 NPV* Prob. Of ROI Project beneficiaries (% ± st dev) (m $) ($) (m $) + NPV* (%) (%) Non-timber 122,400 41 ± 12 40.5 331 21.3 57 53 forest pr. Crop-livestock 97,000 45 ± 15 24.9 257 21.9 62 88 int. Flood 224,000 46 ± 59 61.4 274 37.1 53 46 recession ag. Remote 200,000 10 ± 15 16.0 80 20.2 92 126 Sensing *NPV and ROI using baseline scenario without including major risks and using conservative adoption estimates. PAGE 6 Table ES.3 Barriers to adoption of proposed CSA investments in Mali NATIONAL INVESTMENT RISKS Lack of funding and/or institutional accountability to acquire and maintain equipment Soil information service Lack of land rights deters producers from medium and long term investments Lack of fertilizer and fallow subsidies Extension services Low support structure capacity Remote sensing system Risks are not well understood pending greater investment in farmer capacity Agroclimatic system Current program does not include crops grown by women REGIONAL INVESTMENTS RISKS Labor shortages at time of transplant Long timeline for establishment of deomonstration plots Rice intensification (SRI) Smallholder preference for large, lower investment plots Sandstorms Mismanagement of water Community conflict related to development of irrigated perimeters Flood recession Sandstorms Occurs outside primary agricultural season, exacerbating farmer-pastoralist land use conflict Limited feed availability for livestock Crop livestock integration Increasingly limited grazing area as environmental degradation progresses; encroachment on new areas furthers degradation Poor seed availability; lack of infrastructure drives seasonal oversupply and Vegetable production, overdemand storage, and processing Faulty irrigation equipment; poor transport, cold chain, and storage infrastructure Community conflict related to development of irrigated perimeters Wheat development High price volatility High international market volatility Non-timber forest value Bush fires chains Cultural norms against investing in indigenous tree species Lack of national and international markets Millet-sorghum Legume Restrictions on staple crop exports constraints farmers to subsistence production integration Poor road network precludes commercial development Restoration of degraded Lack of land rights deter producers from medium and long term investments lands Low barriers to adoption Medium barriers to adoption High barriers to adoption PAGE 7 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Table ES.4 Links between CSA investments and national priorities CSA SUPPORT BUILD BOOST CSA 3 PILLARS OTHER SECTORS RESILIENCE AGRICULTURE INFRASTRUCTURE & CONNECTIVITY RISK MANAGEMENT MECHANISMS AGRICULTURAL PRODUCTIVITY & RESEARCH & DEVELOPMENT MARKET INTEGRATION AGRICULTURE VALUE FARMER NETWORKS ENABLING POLICIES GENDER & YOUTH DIVERSIFICATION HUMAN CAPITAL PRODUCTIVITY FOR CLIMATE ADAPTATION MITIGATION EXTENSION FINANCE NATIONAL PRIORITY CLIMATE-SMART INVESTMENTS National remote sensing National extension eystem National agroclimatic system National soil fertility monitoring PRIORITY CROP & LIVESTOCK CSA INVESTMENTS Non-timber forest products Flood recession agriculture Livestock Millet-sorghum with legumes Vegetables Restoring degraded lands Rice intensification (SRI) Wheat PAGE 8 Section 1 Why Climate-Smart Agriculture Mali is already affected by climate change that is adversely affecting agricultural production, and in the future it will adversely affect most crops. Changes in precipitation amounts and patterns and increased temperatures are stressing crop production in many ways, both directly (e.g., less rainfall for crops) and indirectly (e.g., crop pests reproduce more quickly). Climate change will affect Mali’s many different sectors of economy and population, but it will place particular stress on its poor and vulnerable population and on food security. While climate change will cause food security challenges for many countries, Mali faces additional stresses from high population growth, poverty and relatively low institutional and business capacity. To address these current and future climate change impacts, a robust and broad-scale package of rural development initiatives is needed to help Mali’s agricultural sector address these challenges and meet food demand under climate change. This document outlines a portfolio of investments to support Mali’s rural sector in addressing climate change through climate-smart agriculture. Climate-smart agriculture (CSA) increases productivity in an environmentally and socially sustainable way, strengthens farmers’ adaptation and resilience to climate change, and supports mitigation efforts3 (see Figure 1)4. CSA recognizes that economic investments that account for climate change can increase agricultural productivity and sustainability while having direct climate benefits to agriculture that supports adaptation, builds resilience and reduces emissions. CSA focuses on agriculture, but it is multisectoral and also includes commitments to enhancing livelihood benefits, ensuring food security and promoting sustainability. While CSA aims to create triple-wins across productivity, resilience and adaptation, it recognizes trade-offs among the three pillars based on the biophysical, agricultural and socioeconomic context of a given place at a given time. This CSAIP emphasizes the two pillars of sustainable productivity and resilience/adaptation. This is the consequence of the outsized challenge to meet food security under a changing climate in Mali 3 Supports mitigation by reducing greenhouse gas emissions and increasing carbon storage in farmland. 4 FAO 2013 PAGE 9 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN and Mali’s relatively minor contribution to annual global greenhouse gas emissions of 0.06%. Targeting two of the three pillars is consistent with CSA’s flexible approach to agricultural development under climate change. CSA aims to create triple-wins across pillars, programs and policies, and investments are site- and time-specific; thus the relative importance of these objectives is not fixed. One group of stakeholders in one place might place greater relative value on any of the objectives. This is not to say that mitigation is unimportant in the Malian context. Indeed, Mali has committed to reducing emissions in its NDC. This CSAIP considers mitigation a co-benefit to investments with primary goals of increasing productivity and building resilience. A focus is put on lowering greenhouse gas emissions per unit of food produced—known as lowering greenhouse gas intensity—whereby food production increases at a greater rate than greenhouse gas emissions. Figure 1 Climate-smart agriculture: The triple win of sustainability, resilience and lower emissions5 Reduces agriculture’s contribution to Ssutainably increases Strengthens Resilience climate change 1.1 The Climate Smart Agricultural Investment planning framework Mali has planned investments for climate-smart agriculture based on four components of CSA planning and implementation: (i) situation analysis, (ii) prioritizing interventions, (iii) program design and (iv) monitoring, evaluation and learning6. All four of these components depend on strong engagement with key decision-makers and experts, as well as capacity strengthening of key people and institutions involved. This framework (Figure 2 and in detail in Annex A) guided the development of Mali’s CSAIP and the organization of this document. This CSAIP is focused on the first two components: the situation analysis and prioritizing interventions, although elements of both implementation and monitoring and evaluation are discussed. The process used to develop this plan also supports engagement and capacity strengthening, other components of the CSA planning framework. Mali is involved in a multicountry, coordinated effort to develop a national CSAIP (see Annex B). The World Bank coordinated this plan though the Adaptation of African Agriculture (AAA) Initiative, launched at COP22 (Marrakech, Morocco). This plan is directly in support of Mali’s NDC, national agricultural investment plan (NAIP) and other national and regional (such as Economic Community of West African States, or ECOWAS) plans, programs and policies. 5 Lipper et al. 2014 6 Girvetz et al. 2017. PAGE 10 Mali is a member of the global Nationally Determined Contribution Partnership, and Mali’s NDC targets guide efforts for mobilizing support to achieve climate goals while enhancing sustainable development. Mali’s NDC report relates its formal COP21 engagements, intending to lower emissions by 2030 of 29%, 31% and 21% for agriculture, energy and forests, respectively, compared to the baseline scenario (business as usual, or BAU). This CSAIP contributes to reducing emissions in Mali’s agricultural sector through investments that reduce emissions and sequester carbon in biomass and soils (such as rice intensification system, fertilizer microdosing, producing organic manure and reducing forest conversion to agriculture or pasture). Mali’s national CSAIP builds on its national initiatives and priorities, NDC and other international commitments, and the work of numerous local, national, regional and International institutions. A solid foundation of programs, policies and strategic plans supports scaling-up CSA in Mali (see Annex B). These include the National Climate Change Policy (2012), the National Agriculture Sector Investment Plan (2014); the National Strategy on Climate Change (2011); and the National Strategy for the Prevention and Management of Disaster Risk Management (SNPGRC). Multiple international and regional initiatives and projects, including those by the World Bank, UNDP, GEF, Green Climate Fund and USAID and other bilateral development partner institutions provide a foundation for the CSAIP. A CSA profile was developed to highlight CSA investment entry points with support from the Food and Agricultural Organization (FAO) of the United Nations and the Consortium of International Agricultural Research Center’s (CGIAR) Program on Climate Change, Agriculture and Food Security (CCAFS). PAGE 11 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Figure 2 Components of a CSA planning framework used for Mali7 SITUATION ANALYSIS Target Setting, Climate Risks & Enabling Conditions Stocktaking for CSA Action Vulnerability, Impacts & Readiness CAPACITY STRENGTHENING PRIORITIZING INTERVENTIONS Practices, Programs and Policies CSA Investment ENGAGEMENT Portfolios Value for Money & Trade-offs PROGRAM DESIGN & IMPLEMENTATION Development & Deployment Taking CSA to Scale Knowledge into Action MONITORING & EVALUATION Access Scales & Systems Learning from Experience Evidence Based Results Framework 7 Girvetz et al. 2017 PAGE 12 Section 2 Situation analysis of livelihoods, agriculture and climate change 2.1 Mali’s Rural and Agricultural Sector in Brief Mali is one of the world’s least developed countries, with a large, rapidly growing, impoverished rural population. An estimated 43.1% of Mali’s population of 18.54 million lives below the poverty line8. Poverty is concentrated in rural areas, in 2017, 58.6% of people lived in rural areas9, and over 90% of them were poor. Poverty densities and rates are highest in southern Mali10. In 2015, Mali’s per capita gross national income was US$76011. Poverty persists in part because of the high population growth rate (3% per annum) and gender disparities; women have limited access to land, education and credit and have a low labor force participation rate (51% of women compared to 81% of men). Mali had a remarkable drop in poverty from 60% to 51% from 2000–2012, but drought and conflict in 2012 worsened poverty. While a presidential election was held in 2013, and peace accords were signed in 2016, conflict and instability continue. By virtually all measures of welfare, poverty and human development, Mali is one of the world’s poorest countries13. 8 World Bank, April 2018, Mali Poverty and Equity Brief 9 World Development Indicators 10 Mali has registered high (4.4%) urbanization rate 11 World Bank, WDI, 2018 12 World Bank 2015. Mali Systematic Country Diagnostic 13 World Bank 2018 Mali Drylands Development Project PAGE 13 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Only 5.3% of Mali’s total land is arable, with over 66% classified as desert or semi-desert. While the arable area is small, 34% of the land is used for agriculture, yet less than 0.1% is in permanent cropland14. Mali is divided into two broad agro-ecological regions, northern and southern15. The drier northern region, largely desert, has some livestock production of cattle, sheep and goat under pastoral systems (extensive production for cattle and small ruminants). The southern region, which receives relatively higher rainfall, has greater crop production, mostly millet, sorghum and rice, often mixed with livestock. In the center of Mali is an inland delta of the Niger River, a unique ecological area with important wetlands for wildlife that also are critical for food security. In the dry season, the inland delta is the largest pasture area in West Africa, and is also Mali’s main fishery. Four broad agroclimatic zones (Figure 3; Table 1) served as a key input to this CSAIP (see Annex C). Mali’s agricultural16 sector is its largest, providing 38% of the GDP17 and employing over 80% of the economically active population. Smallholder farmers produce food for subsistence on farms less than 5 ha, and they dominate the sector (68%), with 90% producing millet, sorghum, maize and/or rice18. Food crop production represents 45% of total agricultural production19, and paddy rice, maize, millet and sorghum are all produced for local consumption, providing around 35% of daily caloric intake20. Millet occupies the greatest amount of land (29%), providing the third-highest production despite low yields per hectare and the highest food availability per person daily. Sorghum has the second-biggest footprint, also with low yields, but ranks fourth in overall production food availability and third for daily caloric intake (Table 2). Millet and sorghum have had much smaller increases in production levels over time. Maize has had the highest change in production over nearly 60 years, increasing by over 2000%, and occupies the third-greatest land area and has the second-highest production levels, but is not in the top four for food availability of calories. Paddy rice has both the highest production and represents the second-greatest change (over 1,200%) after maize, although it occupies the least land of the four major food security crops. Cereals constitute 64% (1,812 kcal per person per day) of food supply. As shown in Table 2, the key crops produced in Mali that matter for food security are rice, millet, sorghum, maize and vegetables. 14 Mali FAO Stat, http://mali.opendataforafrica.org/yuxwhaf/mali-fao-stat-land-use-and-agricultural-inputs 15 Some analyses designate 5 agro-ecological zones the Sahara, Sahel, Sudano-Sahel, Sudan-Guinean and the Delta; FEWSNET identifies 13 livelihood zones based on economic activity (USAID, 2010) 16 Includes crops, livestock, fisheries and forestry 17 2017 World Development Indicators 18 MAFAP, 2013 19 FAO 2013b 20 FAO 2013b PAGE 14 Figure 3 Agroclimatic Zones in Mali21 Table 1 Agroclimatic Zones in Mali % Of Zones Agroclimatic Zone Characteristics area Saharan 51% Desert with caravan trade, nomadic herding and gathering. Dry northern and more agricultural, southern area growing rice and sorghum, with nomadic and Sahelian 26% transhumant raising of camels, cattle, goats and sheep. Subsistence farmers growing millet, sorghum, maize and cowpea, as well as livestock and Sudanese 17% groundnut and sesame as cash crops. Important fodder resources for northern transhumant herders during drought years and lean seasons. Subsistence farmers growing sorghum, cowpea, fruits, tubers and vegetables (cabbages, okra, to- Suda- mato, onion), with groundnut and maize for food and cash. Wild fruit gathering (shea22, tamarind, 6% no-Guinean nere23) and livestock raising (cattle, sheep, goats) are common with dry-season use by northern, transhumant herders. 21 Mali NAPA 2007, page 9 22 Vitellaria paradoxa (formerly Butyrospermum parkii) is used to produce shea butter, used in cosmetic products 23 Parkia biglobosa is a multipurpose tree whose fruits can be used for food, manure and traditional medicines PAGE 15 BANGLADESH CLIMATE SMART AGRICULTURE INVESTMENT PLAN Table 2 Key agricultural products for food security in Mali (2011–2016)24 (darker colors show higher values for each indicator)24   % Of cultivated land Yield Production (1000 Food Availability Kcal/ (Tons/HA) Tons) (Kg/person) Capita /Day Rice 10.8 3.2 2,267 48 567 Maize 12.1 2.5 1,977 27 313 Millet 29.2 9.3 1,784 56 472 Vegetables 0.9 5.3 303 45 28 Sorghum 20.7 1.0 1,397 39 400 Wheat 0.1 5.1 38 7 92 Sesame 0.9 5.3 32 N/A 8 Groundnut 6.2 1.2 480 1 51 Legumes* 0.01 1.0 0 N/A 125 Livestock** N/A N/A 165 8 40 *Pulses used as proxy for legumes **Bovine meat used as proxy for livestock The livestock subsector is of great importance to Mali, both at household and macro scales. Over 85% of the agricultural households produce livestock, and the World Bank estimates that there are more than 15 million cattle, 32 million small ruminants (sheep and goats), 37 million poultry and nearly 1 million camels25. These animals are a major source of income to nearly one-third of the population, and important to food security. The livestock subsector ranks third after cotton and gold in wealth creation and accounts for 19% of the national GDP, with almost 4.2% coming from the growing aquaculture and fisheries sectors26. The agricultural sector grew by more than 10% in the period 2010–2016, but overall productivity remains low27. Major cereals have yield gaps of over 60%; maize (63%), millet (72%) and sorghum (67%) 28. Crop yields have remained unchanged for the past 50 years (except for rice), and agricultural interventions have failed to meet increasing demand for food crops despite attempts29. Few farmers have access to mechanization30, although the government has promoted a program for tractor purchase by farmers groups, and even fewer (20%) use improved seeds. Fertilizer use is at 11 kg/ha compared to the target of 50kg/ha. Farmers lack both the money to buy inputs (because of poverty and low purchasing power) and physical access to inputs (only 24.5% of Mali’s roads are paved). Mali’s farmers also have high postharvest losses (over 35%) for legumes and cereals. Only 3% of the crop area is irrigated (approximately 14% of the irrigation potential) 31, and is limited to rice production along the Niger River. 24 FAOSTAT 2018 25 World Bank Mali Livestock Padel-M, page 2 26 World Bank, 2018; Mali Livestock 27 World Bank Mali Drylands Development Project 28 Mali is a net food importer, with the food deficit growing at rate of 15% per year (UNDP, 2012). 29 NCEA, 2015 and Esipisu 2017 30 FAO, 2010 page 30 31 Irrigation potential is estimated at 2.2 million hectares PAGE 16 Off-season farming is common among one-third of households and includes market gardening (26% of households), cultivation of flood recession crops (9%) and irrigated cereal agriculture (9%)32. Lack of access to inputs, banking systems, credit and extension seriously limits productivity gains. Private-sector investment in agriculture is only 5.5%, mostly going to cotton production33. Mali’s government mainly provides subsidies to specific commodities, and 25% of agriculture spending is for rice (mostly on irrigation and input subsidies). The National Fund for Agricultural Modernization and Development has not yet improved access to credit in the country. While marginalization limits small- farmer investments in inputs, a 2011 survey shows that with more credit, farmers could potentially increase yields and use of hired labor, fertilizer and chemical inputs34. Food production in Mali is generally unsustainable, with pressure on land increasing and the per capita land area steadily declining35. With climate change impacts increasing, there are greater productivity losses and worsening land degradation. In the period 1975–2013, the crop area increased by a factor of 2.3, (an annual increase of 3.5%), largely by encroaching into forest area. Only a small percentage (5.3%) of land is arable, even though 34% of Mali’s land area is classified as agricultural. Area under irrigated agriculture has also increased by 400%. Steppes (30%), Sudanian savannas (18.5%) and Sahelian short grass (15%) remain the predominant land cover (see Table 3 below), although growing aridity has decreased the area of steppes and savannas, and sandy areas have increased. These changes are largely driven by the need to produce more food for Mali’s growing population (which also requires more space for settlement; land converted to settlement has significantly increased), competing land uses, poverty and weak local governance on environment. Poorly defined land tenure disincentivizes farmers from adopting sustainable production methods, while a long dry season means that Mali has among the highest demands for agricultural water in sub-Saharan Africa. Mali is highly vulnerable to food insecurity, ranking 173rd out of 181 countries for food vulnerability by the ND-GAIN Index for 201736. Findings for 2018 indicate that a quarter of Malians, or 4.6 million people, will be food insecure37, even though Mali achieved both the Millennium Development Goal (MDG 1.C) and the World Food Summit (WFS) targets of, respectively, halving the proportion and the number of hungry people by 201538. These gains resulted from an improved policy environment and legal framework for food security and nutrition, improved water management, and support to vulnerable groups. Yet bad weather, conflict and insecurity in northern Mali, as well as increasing food prices, have worsened 2018 food security. One analysis suggests that by the end of the 2018 lean season, 4.6 million people will require food assistance39, and that severe food insecurity is 55% higher than in 2017, with nearly a million people considered as “severely insecure”40. 32 WFP 2015 33 World Bank 2015 34 Beaman et al., 2014 35 Mali FAO Stat, 2018 36 ND-GAIN Country Index 2017 37 Assistant Secretary-General for Humanitarian Affairs Ursula Mueller
Statement to the Press
Bamako, Mali, 31 August 2018 38 FAO 2016. 39 WFP Mali Country Brief, June 2018 40 Assistant Secretary-General for Humanitarian Affairs Ursula Mueller
Statement to the Press
Bamako, Mali, 31 August 2018 PAGE 17 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Agricultural exports account for 26.6% of total exports, mainly cotton, cattle and sheep products, pepper, sesame and fruits. Cotton, the major cash crop, accounts for 33% of agricultural export earnings and is a source of livelihood to more than 25% of the population, while livestock supported 28% in 201641. The government gives policy and price incentives to cotton farmers, yet production and export has dropped due to declining fertility and fluctuations in yields and market prices. Less than 1% of the cereals produced are exported, and Mali imports significant quantities of rice, wheat, sugar, milk and oils42 (Table 4). Mali’s total greenhouse gas (GHG) emissions are only 0.06% of the global total, with the agricultural sector producing 77% of Mali’s total GHG emissions, with one-quarter from crop production and the rest from livestock. Enteric fermentation (42%) and manure left on pastures (30%) are the major sources of GHG emissions in livestock, while burning savannah (17%) is the major source in crop production. The recent increase in converting forests to fields through slash-and-burn (see Figure 4 above) reduced forest cover by 11.8% from 1990–2011. Much of this deforestation has been driven by an increase in cereal production. The Malian government ambitiously aims to reduce emissions from agriculture by 29% through improving performance of agricultural production, reducing deforestation and promoting intensive reforestation. Land use change and forestry is the second largest source of GHG after agriculture (18.52%), with low levels of GHGs in Mali coming from energy and waste (3.7% and 0.9%, respectively). Table 3 Land cover changes (1975–2015). Area estimated based graph digitizer software43 Area (km2) Land Use 1975 2005 Percent change over 30 years Steppe 236,187 219,327 -7 Savannah 172,957 139,346 -19 Sahelian short grass 135,003 113,003 -16 Sandy area 41,619 56,518 36 Agriculture 39,255 91,620 133 Irrigated agriculture 1,281 5,843 356 Gallery forest 9,554 7,473 -22 Swamp forest 2,642 2,374 -10 Settlements 471 923 96 41 World Bank Drylands page 5 42 FAO 2016 43 USGS PAGE 18 Table 4 Import, export, production and total demand for key commodities in Mali   PRODUCTION (1000 TOTAL DEMAND (1000 EXPORT (1000 tons) IMPORTS (1000 tons) tons) mt) Rice 0.0 174.6 2,266.6 1,021.3 Maize 1.0 6.2 1,977.2 788.3 Millet 0.0 0.0 1,784.1 1,430.8 Vegetables 1.6 4.2 302.8 930.2 Sorghum 0.4 1.8 1,396.7 975.5 Wheat 1.4 198.6 37.8 133.5 Sesame 15.2 0.0 32.5 N/A Groundnut 4.2 3.6 479.9 248.1 Legumes* 0.0 0.2 0.4 N/A Livestock** 0.0 0.2 165.3 154.2 *Pulses used as proxy for legumes **Bovine meat used as proxy for livestock 2.2 Climate Change in Mali’s Agriculture Climate change in Mali is evident and widespread, and has already changed weather patterns and increased weather variability, with impacts on food security, livelihoods, conflict and migration. Mali has already experienced overall warming temperatures (see Figure 4), and climate change has both decreased rainfall and changed rainfall patterns. The north has experienced warming of about 0.5°C per decade, and the frequency of hot nights has increased significantly in all seasons except for winter. The changes in rainfall and decreased food production disproportionately affect the rural poor, mainly subsistence farmers. But In an arid country like Mali, these climate impacts also can lead to changes in traditional transhumance patterns, greatly increasing pressure on limited forage resources and causing conflict44. Figure 4 Average annual rainfall and temperature in East and West Mali, 1900-200945 2 +0.8°C Rainfall - East Standard Deviations 1 Rainfall - West 0 Temperatures - East Temperatures - West -1 -12% -2 1900 1955 2009 44 Umotoni and Ayantunde, 2018 45 Funk et al. 2012 PAGE 19 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Most agriculture in Mali depends on rainfall, which is becoming increasingly variable, with frequent floods and droughts. Mali’s rainfall patterns are erratic, but it generally rains for two months in the Sahara, three months in the north, and five or six months in the two southern regions46. The average rainfall from 2000–2009 was 12% less than from 1920–196947. Rains start and end earlier, and growing seasons now end sooner than historic norms. As rainfall timing and quantity have changed, and growing seasons change, food production has declined. Timing issues exist when farmers may sow seeds expecting rains that are then delayed, or when rains end before crops are fully mature. Quantity issues exist when there is too little rain or when intense rainfall leads to flooding, which can cause crop failure, soil erosion, crop and transport infrastructure destruction, and even loss of lives. Aggregate statistics may mask these changes. For example, total rainfall may not change, but large amounts of rain may fall in a short period of time rather than over a period of months. This can be disastrous for crops. Precipitation is likely to remain highly variable in both temporal and spatial dimensions—when, where and how much it rains. Models are not conclusive but tend to show a general increase in precipitation in the northern and western parts of the country and decreases in the far eastern part. By 2050 the northern parts of the country—namely Timbuktu, Kidal, Gao and Mopti—are projected to experience an increase of 14.2%, 24.8%, 22.5% and 9.7%, respectively, while Kayes in the east is projected to experience a decrease of about -5.4 %48 (Figure 5). The high levels of warming (and the low precipitation levels) are likely to adversely affect agricultural production. It should be noted that the high percent change in the north is in part due to it being so dry, such that even a relatively small 100 mm increase in precipitation is a fairly large percentage change. Figure 5 Projected changes in temperature (left) and precipitation (left) and precipitation (right) in Mali by 205049 46 MET, 2007 47 Funk et al. 2012 48 Data source: WorldClim. Downscaling process was done as in Ramirez and Jarvis (2008) 49 FAO/CCAFS CSA profile Page 12 PAGE 20 Annual temperatures have already increased by 0.8°C since 1960 (an average of 0.15°C per decade50), and are expected to increase by 1.2°C–3.6°C by 2060, and 1.8°C–5.9°C by 209051. The north is expected to experience more warming relative to the other parts of the country, increasing 2.5°C by 2050 (Figure 5). Mali is predicted to experience greater weather extremes and more frequent climate events and hazards. Evidence suggests that more frequent extreme weather events, such as longer dry seasons and droughts, or longer or more intense rainfall, are already happening52. In the period 1980–2014, nearly 7 million people were affected by 28 droughts and floods; the economic cost of the extreme events was valued at US$140 million53. Primary sector growth declined from 7.6% in 2016 to 4.8% in 2017 due to erratic rainfall54. Urban areas, and areas along the Niger Delta, are prone to flooding, while the northern Kayes, northern Koulikoro, northern Segou, Mopti and the north are most vulnerable to drought. Even in the dry Sahel, rainfall events have increased in magnitude leading to flooding55. As shown in Figure 6, USAID analysis shows that over 72% of Mali’s population is in the medium to high vulnerability category for climate hazards (note that northern Mali was excluded from the analysis)56. Figure 6 Mali’s human vulnerability to climate change59 Area Pop. Density Population % of Vulnerability index (Sq. Km) (Pop/sq, km) pop. Low (0-20) 600 3,623 2,116,524 14.2 Med - Low (21-40) 11,034 104 1,107,342 7.4 Medium (41-60) 194,493 32 6,073,534 40.8 Med-High (61-80 307,357 16 4,727,328 31.8 Map Credit: CIESIN Columbia University, May 2014 High (81-100) 133,711 7 849,869 5.7 50 Warner et al. 2015 51 USAID, 2014 52 Halimatou et al. 2017 53 GCF, 2016 54 World Bank-Mali 2018 55 Aich et al. 2016 56 USAID 2014 59 USDA-FAS 2018 PAGE 21 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Climate change has already reduced both agricultural productivity and livestock production, as well as increasing pressure on fodder resources in central and southern Mali. In southern Mali, warmer temperatures and more days without rainfall significantly increased in reducing cotton yields57. Drought reduced yields of coarse grains by 27.46% in the 2016–2017 planting season58. The trends are the same for available pastures for livestock, which should serve as an impetus for rethinking agricultural production in Mali. Most models of climate change impacts on biophysical suitability hold management and technology constant at current levels. In reality, of course, ongoing investments in agricultural research are not likely to completely stagnate. Farmers also exercise adaptive agency—intentionally switching to an improved variety or an alternative crop, or changing levels of inputs or farming methods—in response to shifting economic incentives induced by climate change. Figure 7 Projected percentage change in suitable area in Mali, 2040–2069 P. Millet Sorghum Cassava Groundnut F.millet Banana Maize -100 -75 Projected change in suitable area [2040-2069] (%) -50 -25 0 25 50 75 100 125 150 Models looking at one crop and one factor, such as temperature or precipitation, can show divergent results. In southern Mali, a 2.0°C temperature increase reduced maize and sorghum yields much more than a 1.5°C warming scenario60. This shows thresholds may exist that seriously affect production. For all crops studied, intensification doubled or tripled yields. However, because intensification raised yields, yield losses were also higher given climate change. Another study looking at maize, millet and sorghum under rainfed cultivation systems within the Niger Basin, including Mali, 57 USAID 2014 58 Traore et al. 2015 60 Faye et al. 2018 PAGE 22 found that temperature had a larger effect on crop yields than rainfall; however, the study also found strong differences between yields in northern and southern zones61. Other models show that yields of maize, millet, sorghum and rice are likely to decline. One model shows that by 2050, under current farming practices, predicted maize grain yield losses are between 51% and 57%, while millet average yield losses are between 7% and 12%62. Crop modeling of climate change impacts on the area that is suitable for cultivation of different crops show that with the exception of pearl millet, all key crops declines in suitable areas (Figure 7). Maize, banana and finger millet may not be able to be grown in the country as of 2040–2069. Fodder availability and quality will also decline by 5%–36%), affecting livestock farmers and pastoralists. Hotter temperatures are also likely to enhance the spread of diseases (e.g., Rift Valley fever) and reduce the nutritional value of some crops, given higher carbon dioxide concentration. The combined effects of lower crop and forage yields and reduced animal weight will reduce overall production and food security and raise prices. 2.3 Climate Change Impacts on Mali’s Agricultural Economy Climate change will impact the production of key agricultural goods globally, which in turn will impact each country’s economic activity. Climate change will drastically alter what crops are suitable for a given place, reducing suitability across large areas (e.g., entire countries) but also creating pockets of increased suitability. At a global scale, these shifts will be very significant in determining what countries can grow what crops, which in turn will affect international trade. At the same time, demographic changes in countries will impact demand and consumption. Taken together, these demographic shifts and climate change impacts will result in a global rebalancing of comparative advantages in agricultural production. Modeling conducted with the International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) 64 suggests that the landscape of economic incentives will change, offsetting suitability loss for some crops while exacerbating it for others. To understand the impact of climate change on global agricultural production and trade, IMPACT simulates a climate change (CC) scenario from the present to 2050. The scenario is an average of five IMPACT model runs, each run incorporating a distinct global climate model. An IMPACT “no climate change” (No-CC) scenario holds climate constant at its current levels to establish a baseline point of comparison. Both the CC and No-CC scenarios were modeled under different assumptions regarding population growth, growth in GDP, and different levels of greenhouse gas emissions. Scenarios for changes in population and GDP were determined by the shared socioeconomic pathways (SSPs; see Figure 8, Table 5 and Annex D), and variations in GHG emissions scenarios were determined by the representative concentration pathways (known as RCPs). 61 Akumaga et al. 2018 62 Traore et al. 2015 64 IMPACT is a model of the global agricultural sector that takes account of climate change as well as economic agency. See Robinson et al. (2015) for model documentation PAGE 23 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Figure 8 and Table 5 Description of select shared socioeconomic pathways (SSPs) modeled using IMPACT (SSP3, SSP4 and SSP5 used in this analysis)63 Socio-economic challenges for mitigation SSP 5 SSP 3 Shared Scosioeconomic DESCRIPTION (Mit. Challenges Dominate) (High Challenges) Pathways Fossil-fueled Regional Highly fractured, countries Development Rivalry pushing apart, high prob- Taking the Highway A Rocky Road SSP 3 lems both with mitigation and adaptation SSP 2 (Intermediate Challenges) High inequality, low chal- Middle of the SSP 4 lenges to mitigation, high challenges to adaptation Road Competitive markets, fossil SSP 1 SSP 4 fuel led, high challenge to SSP 5 (Low Challenges) (Adapt. Challenges Dominate) mitigation, low challenges to Sustainability Inequality adaptation Taking the Green Road A Road Divided Socio-economic challenges for adaptation Note that SSP 3 and SSP 4 both have high challenges with adaption, whereas SSP 5 has low challenges. See Annex D for a complete description of all scenarios. Although it appears that, for most commodity groups, yields will increase both with and without climate change, climate change strongly limits yield over time (compared with no climate change). Percentage point differences between yield and area trajectories under CC and No-CC scenarios are presented for rainfed (Table 6) and irrigated (Tables 7) commodities. For detailed information on the model and scenarios, including an explanation of percentage point difference as opposed to percentage difference, see appendix D. Climate change negatively affects every commodity group, both in the short term (2030) and over the longer term (2050) (see Tables 6 and 7) for both rainfed and irrigated commodities. The percentage point difference between the CC and No-CC yield change trajectories is negative for most commodities. Climate impacts do not affect all commodity groups uniformly, but a rough pattern for most commodity groups is that losses roughly double every decade. Climate change effects increase over time for all commodity groups. In general, livestock, fruits, and roots and tubers show the least impacts from climate change. The top five most impacted commodity groups in the short term (2030) are (in order from greatest), oilseedsmaize, vegetablesgroundnut, vegetables, sugar cropscotton, and cerealstropical fruitandcotton, but by 2050 the order of greatest losses is different: vegetablesmaize, groundnut, vegetables, cowpeas, and cottonoilseeds, cereals,sugar crops and cotton. 63 Graphic from: O’Neill, B.C., et al., The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century. Global Environ. Change (2015), http://dx.doi.org/10.1016/j.gloenvcha.2015.01.004 PAGE 24 Table 6 Percentage point difference in yield and area of production with different levels of climate change for rainfed crops in Mali (shown as percentage point differences over the baseline No-CC). Difference in area of production Difference in yield (SSP3) (SSP3) RCP 4.5 RCP 8.0 RCP 4.5 RCP 8.5 Rainfed crops 2030 2050 2030 2050 2030 2050 2030 2050 Banana -1.7 -4.5 -1.0 -2.7 0.3 1.0 0.8 2.8 Cassava -1.2 -3.3 -1.2 -3.2 0.1 0.5 0.1 0.7 Cotton -2.5 -7.7 -2.7 -7.2 -0.8 -2.1 -0.3 -0.8 Cowpeas -1.6 -5.5 -1.7 -5.6 0.1 0.4 0.5 1.4 Groundnut -3.4 -9.3 -4.6 -12.4 1 .2 3.6 2.0 6.1 Maize -5.9 -17.2 -7.6 -21.7 -0.1 -0.5 0.2 -0.3 Millet -1.7 -8.5 -2.4 -9.2 0.1 0.2 0.4 1.1 Potato -1.5 -4.7 -1.0 -3.7 1.1 1.1 2.2 2.8 Rice -1.7 -5.9 -2.3 -7.6 0.4 0.9 0.8 1.9 Sorghum -1.4 -5.4 -2.3 -9.0 0.4 1.2 0.3 0.8 Soybean -2.3 -5.1 -3.7 -7.8 0.0 -0.1 -0.2 -0.4 Tea -2 -5.5 -1.3 -3.6 -0.1 -0.1 0.4 1.3 Tropical fruit -2.7 -7.1 -2.8 -7.0 -0.3 -0.8 0.0 0.0 Yams -0.9 -2.3 -1.0 -2.4 0.2 0.5 0.1 0.4 Table 7 Percentage point difference in yield and area of production with different levels of climate change for irrigated crops in Mali (shown as percentage point differences over the baseline No-CC). Difference in area of production Difference in yield (SSP3) (SSP3) RCP 4.5 RCP 8.0 RCP 4.5 RCP 8.5 Rainfed crops 2030 2050 2030 2050 2030 2050 2030 2050 Cowpeas -1.9 -7.9 -1.9 -8.2 0.7 2.4 1.1 3.7 Groundnut -3.6 -11.5 -4.5 -14.2 1.6 7.9 2.7 13.3 Maize -6.3 -21.2 -8.0 -26.7 0.0 -1.0 0.4 -0.6 MIllet -1.4 -5.3 -2.2 -8.2 0.7 2.1 0.9 2.9 Rice -1.7 -6.0 -2.2 -8.1 1.0 3.2 1.4 4.8 Sorghum -1.3 -5.0 -2.2 -8.3 1.0 3.4 0.6 1.9 Sugarcane -2.8 -7.3 -3.6 -9.5 1.7 4.3 2.5 5.9 Sweet Potato -1.3 -3.7 -1.5 -4.3 -0.1 0.1 -0.2 0.0 Vegetables -2.9 -11.3 -3.7 -14.2 -1.4 -5.3 -1.8 -6.8 Wheat -2.6 -6.9 -4.4 -11.3 -2.8 -6.7 -4.3 -9.3 PAGE 25 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN 2.4 Climate Change Impacts Likely Aggravated by Shifting Economic Incentives Climate change will impact the production of key agricultural goods globally, which in turn will impact each country’s economic activity. Climate change will drastically alter what crops are suitable for a given In Mali, modeling shows that the shifting economic landscape induced by climate change could exacerbate biophysical damages for key commercial and food security crops. Most notably from a commercial standpoint, cotton yield is projected to fall 7 percentage points below its No-CC baseline in 2050, and cotton exports are projected to be 8.4% lower in 2050 than they would be without climate change (Figure 9)65. Cereals, Mali’s most important crops for food security, have yield trajectories exhibiting vulnerability to climate change out to 2050, although there is important variation within the group (Tables 6 and 7). Climate change impacts on cereals are of particular relevance in Mali, where they constitute 68% of all daily caloric intake and 70% of cultivated area. Rice, millet, sorghum and maize are especially predominant on farms and plates, accounting for 14%, 45%, 29% and 11% of all cereal cultivation, and 31%, 29%, 20% and 15% of all cereal calorie intake, respectively. Mali is moderately dependent upon imports to meet its internal cereal demand, especially for maize. Maize is projected to be hardest hit by climate change, with rainfed and irrigated yields falling by as much as 22 and 27 percentage points, repectively, below their No-CC baselines in 2050. Rice, millet and sorghum yields are also hard hit, but considerably less so, exhibiting resilience relative to maize. Climate change impacts on area under cereal cultivation are slight for rainfed systems (Table 6), but there is a marked increase in area under irrigated cereal cultivation relative to the No-CC baseline (Table 7). Modeling suggests that reliance on maize imports may increase at an alarming rate with or without climate change, such that half of the domestic demand may have to be imported by 2050. Meanwhile, current dependence upon rice imports is projected to diminish to less than 10% of domestic rice demand over the same period; and import quantities are projected to be 30.5% less with climate change than without it. Mali could develop a comparative advantage in sorghum and millet by 2050, with export quantities that are 15% and 10% of internal demand, respectively. Moreover, these export quantities are 21.2% and 32.5% lower, respectively, than what they would be without climate change (Figure 9), suggesting that CC adaptive measures could substantially increase these trade benefits66. IMPACT projects that in 2050, under climate change, the area under rainfed potato cultivation could rise as much as 2.8 percentage points above its No-CC baseline (SSP3, Table 6). In a high climate change scenarios (RCP 8.5, SSP3), vegetable and pulse yields also exhibit vulnerability, falling by 14 and 6 percentage points below their No-CC baselines. IMPACT projects that in 2050, under climate change, area under vegetable cultivation could fall by as much as 6.8 percentage points below the No-CC baseline and wheat could fall -9.3 percentage points—the largest negative area differential of any crop (SSP3, Table 7). Although currently consumed in relatively lower quantities, vegetables and pulses are a fundamental source of nutrients and proteins that will 65 These numbers are based on RCP 8.5, SSP3. Also see this CSAIP’s Climate Smart Cotton Development Program 66 For example, proposed CSA Millet-Sorghum Systems with Legumes and Promoting System of Rice Intensification (SRI) in Mali; and proposed CSA Flood Recession Agriculture in Northern Mali (maize, sorghum, sweet potato and market gardening crops such as okra) PAGE 26 likely see increasing promotion in Mali as incomes rise over the next thirty years. However, campaigns to promote the complementary role of pulses and vegetables in the country’s starch-heavy diets will not be successful unless they can address this vulnerability67. Figure 9 Percentage difference between imports/exports in 2050 with and without climate change (RCP 8.5, SSP 3). Note that percentage differences are with respect to the No-CC value for the same year (2050), and thus do not necessarily indicate a positive or negative change over the 2020 baseline year (details in Annex D-6) Potential impacts of climate change on trade in Mali 2.5 Climate Change Impacts Potentially Offset Through Shifting Market Incentives Shifting economic incentives brought about by climate change, however, could play out favorably for Mali in some key commodity areas. In particular, roots and tubers such as sweet potatoes exhibit relatively resilient yield trajectories out to 2050, falling below their No-CC baselines by less than 5 percentage points, even under pessimistic scenarios (RCP 8.5, SSP3). Root and tuber consumption is currently low in Mali, so this may not be an immediate priority, but the potential resilience of these crops in the face of climate change suggests they could be positioned as an important alternative source of carbohydrates in the future, especially given likely climate change impacts on cereals. Livestock productivity also exhibits resilience to climate change, diverging from its No-CC trajectory by less than a percentage point. IMPACT projections suggest that Mali may begin exporting substantial quantities of lamb by 2050 and that these quantities may be 2.5% greater with climate change than without it. Over the same period, Mali is projected to become heavily dependent upon imports to meet domestic beef demand, and IMPACT projects that this dependence will be aggravated by climate change. In addition to building resilience of beef production in Mali, effective PAGE 27 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN strategies can leverage the potential commercial resilience of lamb and small ruminants to address the steepening trade deficit in beef68. There are significant opportunities to increase yields and improve food security, even as climate change increases the variability of rainfall and the vulnerability of populations. Farmers themselves, in one region in Mali, have been adapting agricultural and livelihood practices for 50 years. But given increased temperatures and erratic rainfall over the past few decades, they now want outside financial and technical assistance because their adaptation strategies no longer work69. Given how large yield gaps are for Mali’s key crops, intensification strategies can greatly offset climate change if investments are climate-smart and tailored to respond to national needs70. 2.6 Climate Adaptation has the Potential to reduce Import Dependency Adaptation addressing climate change, coupled with strong economic development, should foster both food security and some agriculture-led economic development for Mali. Though Mali has the potential for relatively high levels of productivity in its arable southern zone, anticipated increases in agricultural productivity are at least partially offset by expected population growth. This suggests that while Mali has the potential to realize some agricultural-led economic development, many of the benefits of adaptation to climate change are potentially mitigated by anticipated increases in population. However, this participation will be substantially more influenced by local and regional economic development trajectories as well as the intensity of climate change. Modeling of future shared socioeconomic pathways (SSPs) (Figure 8, Table 5) shows that adaptation approaches can improve Malian participation in the global marketplace. In the SSP 5, Mali agriculture grows and benefit from economically led, adaptation-friendly development scenarios; in addition, the growth in imports and exports is fairly similar, showing that import dependency is affected little (Figure 10). However, under SSP 3 and SSP 4, where adaptation challenges are high, import growth outpaces export growth by a factor of two to three, showing that import dependency would increase. As such, economically led, adaptation-friendly agricultural development would help keep import dependency from increasing and help improve Malian trade. For the agricultural economy to thrive under economically led, adaptation-friendly agricultural economic growth trajectories (SSP 5), GDP will need to grow generally, population growth will need to level off rapidly and slow over time, and high levels of urbanization would be expected. High GDP growth is expected under SSP5-style economic growth, but given the concentration of productive land and the population in Mali, the relative contribution of agriculture to economic development is perhaps lower than would be expected given the size of the country. 68 The numbers in this paragraph are based on RCP 8.5, SSP3. Also see proposed Program for the Development and Integration of Livestock in Farming Systems in Mali’s Soudanian Zone 69 Kergna and Dembele 2018 70 Falconnier 2018, Ukumaga et al. 2018 PAGE 28 Figure 10 IMPACT model results showing changes in total imports and total exports over time. Note that SSP 5 (blue line) with low adaptation challenges has lower increases in imports and greater increases in exports, showing the benefits adaptation can bring to import dependency PAGE 29 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN PAGE 30 Section 3 Prioritizing interventions for Climate-Smart Agriculture in Mali 3.1 The Climate-Smart Investment Plan for Malian Agriculture Climate-smart agriculture aims to increase productivity, resilience and mitigation but requires understanding what is climate-smart in different locations and designing projects to fit the varied contexts. What is climate-smart for one group of farmers or agro-ecological context may not be appropriate for another. There may also be trade-offs among the three pillars, so what is good for one pillar, such as resilience, may not be good for another, such as productivity. Projects are designed to meet the three of CSA pillars—increasing productivity, resilience and mitigation—but priority may be given based on the context, such as increasing the emphasis on productivity and adaptation/ resilience. The process described below generally follows the CSA Prioritization Framework (see Annex A). The first step in developing the CSA investment portfolio process was a technical review by CSA specialists of Malian national documents (policies, strategies, plans) related to agriculture and climate change, identifying a long list of 26 potential CSA investments consistent with these documents. Mali has engaged in many analyses that provide input to the situation analysis (detailed in prIor sections) that are fundamental for planning and identifying CSA investments, setting targets, identifying climate risk and enabling conditions. This builds on a variety of Malian plans and programs that provide analyses and targets for this CSAIP, including: the National Climate Change Policy (2012), the National Agriculture Sector Investment Plan (2014); the National Strategy on Climate Change (2011); and the National Strategy for the Prevention and Management of Disaster Risk Management (SNPGRC); and the Country Partnership Framework for Mali. Multiple international and regional initiatives and projects, including those by the World Bank, UNDP, GEF, Green Climate Fund, USAID and other bilateral institutions provide a foundation for the CSAIP. Additionally, a CSA profile was developed with support of FAO and the CGIAR research program on Climate Change Agriculture PAGE 31 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN and Food Security (CCAFS) partners. The investment plan proposed in this document builds on these initiatives and priorities and the work of various local institutions, including the CCAFS partners. The long list of potential investments identified through the literature review and key stakeholder discussions were organized into “groups of practices” or investments that were then organized into four categories: agriculture; fishery and livestock; forest and sustainable management of water and soils; and CSA services (e.g., extension, information services, financial services, etc.). The second step was a prioritizing workshop that identified a final short list of 12 proposed investments from the original long list and then selected four of these for more detailed economic assessment. This occurred with local experts from Malian national organizations supported by CGIAR and national stakeholder expertise at a meeting in Mali, June 19–22, 2018. The long list of 26 potential investments supporting CSA (Annex C-1) that were directly relevant to national needs were assessed against their potential impact on: (i) climate smartness (productivity, adaptation, mitigation); (ii) co- benefit outcomes (employment, GDP, contribution to other national commitments and strategies); (iii)  likelihood of success  (farmer adoption likelihood, scaling-out potential and sustainability after project ends); (iv) alignment with AAA pillars and priorities; (v) likelihood of mobilizing funds from specific sources; and (vi) alignment with NDC adaptation strategies. The investments also were assessed for their distribution by geographic zone (see Annex C), beneficiaries, value for money and trade-offs. Participants had the ability to make this prioritization since many represented likely implementing agencies, such as the Ministries of Environment, Agriculture, and Livestock and Fisheries, as well as other government organizations representing food security, animal production and industries, hydrology, meteorology, and land management and irrigation. Technical experts from important Malian research organizations were involved, such as the Institute for Rural Economy and the Malian Association of Awakening to Sustainable Development (AMEDD). The list of technical experts involved at the workshop, and in supporting the development of the more detailed investment plans, are provided in Annex C. The final CSAIP portfolio of 12 CSA investments—including four national-scale CSA services and eight for specific crop combinations—would support overall food production/food security improvements for over 1.8 million beneficiaries, assuming all investments target different beneficiaries and all investments were made. The plan accomplished this by providing a fundamental technological base for the agricultural system with real-time monitoring of weather, improved soil information, a climate-smart extension service, restoration of degraded lands, and promotion of a range of key climate-smart value chains. As shown in Table 8 below, in additional to national coverage by four investments, there is good balance in strengthening agriculture in all parts of country. This is important not only from an equity perspective but also because it introduces climate- smart agricultural practices across the country. The project concepts are highlighted and summarized below, and Chapter 4 describes the more detailed economic analyses that were developed for the four selected investments. Table 8 CSAIP investment priority by zone Saharo-Sahelian zone Sudano-Sahelian zone Guineo-Sudanian zone Nationwide Flood recession agriculture Rice intensification (SRI) Non-timber forest product value Soil information service chains Restoration of degraded Vegetable production, storage Millet-sorghum-legume inte- Extension services lands and processing gration Wheat development Crop-livestock integration Remote sensing system Agroclimatic system PAGE 32 3.2 National-scale Climate-Smart Agriculture Service Investment Summaries The four national-scale initiatives represent the fundamental components of an adaptive and climate-smart agricultural sector: remote sensing monitoring capability, CSA inclusion in national agricultural extension services, agroclimatic information systems, and monitoring soil fertility. These initiatives are foundational in understanding and monitoring of the agricultural sector by supporting programs in remote sensing, agroclimatic information, and soil fertility monitoring. These three programs, all based in proven technologies, have the potential to provide vital, real time guidance to both decision-makers and to farmers themselves. Furthermore, the remote sensing and agroclimatic systems can support a range of other development objectives. For example, understanding potential weather related impacts (e.g., heavy rainfall), is useful to minimize impacts on everything from people to infrastructure. Integrating CSA practices into the national extension system not only helps farms directly, but helps insure that there is a mechanism for transferring the information from the three national technology-based investments to farmers and other users. These four national-scale investments, the beneficiaries, and the Proposed Development Outcomes are shown in Table 9 below, and described in greater detail in Annex F. • Remote sensing: This project aims to increase capacity to effectively manage natural resource areas, evaluate farm productivity and address climate-related risks by providing land managers, agricultural producers, farm advisors and policymakers with timely, accurate geographic information systems. Timely, accurate and accessible geomatics information is foundational to climate-smart agriculture. Well-designed geospatial information systems translate geomatics data into practical advisories, transmit them over accessible communication channels and invest in the capacity of end users to understand and leverage the information. Such systems inform research, policy and land management decisions. This project will develop geospatial information systems to support climate-smart environmental and agriculture management. It will directly benefit 200,000 rural agriculturalists and their households and indirectly benefit all Malian agricultural producers through climate-conscious policy, land management and extension recommendations. It can also be used for ongoing monitoring and evaluation of land use and land cover change, thereby supporting emissions monitoring and reduction. • Extension: This project aims to increase farm productivity and minimize climate-related risks by improving the quality and quantity of CSA-informed recommendations made to producers by farm advisors. Farm advisors play a crucial role in translating scientific information into practical recommendations, promoting CSA by supporting technology development, strengthening farmers’ capacity, facilitating conversations between producers and other stakeholders (e.g., researchers, processors, cooperatives), and advocating for pro-CSA policy. Increasing the production and dissemination of high-quality agricultural technologies through the research and extension systems is a key investment priority for the Malian government. This project will increase the capacity of the extension system to provide recommendations to producers that are informed by and promote CSA practices. It will directly benefit 186,048 rural agricultural workers and their households, and indirectly benefit smallholders across the country via improved agricultural productivity, economic outcomes, nutritional security, and climate resilience. • Climate services: This project aims at increasing farm productivity and mitigating climate- related risks by providing producers, extension agents and agribusiness with timely, accurate agrometeorological information. Effective climate information services reduce the uncertainty surrounding erratic climatic patterns, allowing producers and agribusiness to anticipate and manage adverse weather conditions, take advantage of favorable ones, and adapt to change. They PAGE 33 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN also support climate-informed policy, planning and extension agent recommendations. Mali has been a pioneer in climate information services, and the government and its allies have prioritized scaling of their early successes. This project will strengthen public sector systems and technical capacity to produce and convey climate information, as well as producer technical ability to access and leverage the information. This will be done by addressing physical infrastructure; data aggregation, synthesis and dissemination; and national capacity for maintaining and leveraging the information system. It will directly benefit 400,000 agricultural workers and their households, and indirectly benefit producers across the country via improved extension, agribusiness and policy outcomes as a result of improved access to timely, accurate climate information. It will also be invaluable for hazard monitoring and prevention. Table 9 National-scale investments in climate-smart services   Beneficiaries Proposed Development Outcome (PDO) 200,000 agricultural workers Increase capacity to effectively manage natural resource areas, evaluate Remote sensing and their households farm productivity, and address climate-related risks by providing land and applied nationally managers, agricultural producers, farm advisors and policymakers with geomatics timely, accurate GSIS. 186,048 agricultural workers Increase farm productivity and minimize climate-related risks by Extension and their households improving the quality and quantity of CSA-informed recommendations system nationally made to producers by farm advisors. Agroclimatic 400,000 agricultural workers Increase farm productivity and mitigate climate-related risks by information and their households providing producers, extension agents and agribusiness with timely, system nationally accurate agrometeorological information. 103,360 agricultural workers Increase agricultural producers’ ability to practice CSA by providing and their households producers and extension agents with location-tailored information on Soil fertility nationally soil characteristics and best management practice recommendations, monitoring and the tools, products, partnerships and policy environment to implement those recommendations. Soil services: This project aims to increase agricultural producers’ ability to practice CSA by providing producers and extension agents with location-tailored information on soil characteristics and best management practice recommendations, and the tools, products, partnerships and policy environment to implement those recommendations. Healthy soils regulate nutrient and water cycles, increasing soil fertility while contributing to carbon sequestration and agricultural productivity and also buffering climate change and variability. Malian soils show potential for high agricultural productivity under ISFM, and the Malian government and its partners have prioritized addressing soil quality and fertility. This project will support producer’s soil management decisions via development and implementation of a national soil information system. It will directly benefit 103,360 rural agricultural workers and their households, and indirectly benefit smallholders across the country via improved agricultural productivity, economic outcomes, nutritional security and climate resilience. 3.3 Climate-Smart Crop and Livestock Investment Summaries • There are eight climate-smart crop and livestock investments identified to support adaptation of agricultural production systems for important crops that will be affected by climate change, while also supporting the expansion and development of climate-resilient crops and livestock. This dual perspective of including both adaptation of climate-sensitive crops and expansion of resilient crops provides a way for Malian farmers to adapt to climate change. The proposed crop and livestock investments all introduce climate-smart practices into the different investments. All of these site-specific investments are well supported by the four PAGE 34 national-scale foundational investments. Note that although cotton is important commercially, it was not selected by Malian stakeholders, who instead emphasized food security.These eight crop and livestock specific investments, the beneficiaries and the proposed development outcomes are shown in Table 10 and described below and in Appendix F. Table 10 Crop and livestock climate-smart investments Beneficiaries Proposed Development Outcomes (PDO) Non-timber for- Bolster Malian economic growth, food security and climate 122,400 women producers and est product value resilience through developing the agroforestry NTFP sector. processors in Koutiala region chains Increase farm productivity and minimize climate risks by Flood recession 224,000 smallholders in floodplain providing producers, extension agents and agribusiness with agriculture region technical support and improved infrastructure for optimized flood recession agricultural practices. Increase farm productivity and minimize climate risks by 97,000 smallholders in Segou providing producers, extension agents and agribusiness Livestock region with best management practices and tools for crop-livestock integration. Millet-sor- Increase the climate resilience and productivity of millet- 199,495 women farmers in ghum-legume sorghum systems to improve nutritional and economic Koulikoro and Segou regions integration outcomes of smallholders. Increase productivity and climate resilience of vegetable 52,747 women and youth in Niono, production while fostering economic opportunities for Vegetables Kati and Bandiagara Cercles producers, especially women and youth, while minimizing environmental impact. 106,461 agricultural producers in Build national capacity to restore degraded lands at scale to Restoring de- Nioro, Yelimand and Kayes Cercles increase climate resilience, ecosystem services and agricultural graded lands (Sahel, Karakor and Koussane productivity. Communes) 72,480 producers in unflooded Increase rice productivity and climate resilience by scaling SRI to rice production zone, between improve economic and nutritional outcomes. Rice intensifica- Mopti and Segou cities, and parts tion (SRI) of Tenenkou, Macine and Segou Cercles 71,856 smallholders in Niono Increase wheat productivity and climate resilience by scaling Wheat region CSA practices to improve economic and nutritional outcomes. • Non-timber forest value chains: This project aims to bolster Malian economic growth, food security, and climate resilience through development of the non-timber agroforestry product sector. Deforestation has undermined Malian climate resilience; development of climate- smart non-timber agroforestry product value chains can support and promote reforestation. Multipurpose agroforestry parkland also plays an important role in the nutritional and economic outcomes of farmers. Further developing the non-timber agroforestry sector is a priority for the Malian government and its allies. This project will promote non-timber agroforestry product value chains by bolstering research and development, supporting production, augmenting postharvest processes and developing value chains. It will directly benefit 122,400 women producers and processors and their households and indirectly benefit producers and processors throughout the Koutiala region through improved economic outcomes, climate resilience and nutritional security. • Floodplain: This project aims to increase farm productivity and minimize climate-related risks by providing producers, extension agents and agribusiness with technical support and improved PAGE 35 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN infrastructure for optimized flood recession agricultural practices. The Malian Sahel has a well-established flood recession production sector to fully leverage its scarce water resources; this practice, and consequently the livelihoods and nutritional security of smallholders in the region, are threatened by the variability associated with climate change. Producers have already demonstrated effective practices to make flood recession production more climate resilient, and scaling these practices is a priority for the Malian government and its allies. This project will bolster the productivity and resilience of producers in the region by addressing research, capacity, infrastructure and civil and private-sector engagement. The project will directly benefit 224,000 smallholders and their households and indirectly benefit smallholders throughout the Sahelian zone via improved climate resilience, economic outcomes and nutritional security. • Crop-livestock integration: This project aims to increase farm productivity and minimize climate-related risks by providing producers, extension agents and agribusiness with best management practices and tools for crop-livestock integration. Livestock, a core economic sector in Mali, is challenged by increasing climate variability and degrading natural resources. Climate- smart crop-livestock integrated systems show significant promise for improving livestock climate resilience and, consequently, the nutritional and economic outcomes of smallholders. The Malian government and its allies have prioritized increasing the efficiency and productivity of the livestock sector. This project will increase the climate resilience and productivity of producers through crop-livestock integration. It will directly benefit 97,000 farmers, including 228,000 rural woman farmers and their households. Smallholders throughout Segou may be indirectly benefitted by improved climate resilience and nutritional security. • Millet-sorghum legume integration: This project aims to increase the climate resilience and productivity of millet-sorghum systems to improve nutritional and economic outcomes of smallholders. Millet-sorghum systems are mainstays of smallholder nutritional security in the semi-arid Sudo-Sahelian zone of Mali, and are among the most climate-resilient crops. Nevertheless, production has lagged as more economically viable crops have been prioritized for research, innovation and mechanization. Climate-smart systems for the intensification of millet and sorghum production in conjunction with legumes have been shown to significantly improve productivity; this implies improved nutritional security for smallholders throughout semi-arid regions of Mali. The Malian government and its allies are committed to improving the resilience and productivity of millet-sorghum systems through scaling of CSA practices. This project will improve the nutritional and economic security of millet-sorghum producers by addressing extension agent capacity, producer association strength, farmer technical support, research efforts and policy environs. It will directly benefit 199,495 women farmers and their households and indirectly benefit smallholders throughout the cereal production region through improved economic and nutritional outcomes. • Vegetables: This project aims to increase the productivity and climate resilience of vegetable production while fostering economic opportunities for producers, especially women and youth, while minimizing environmental impact. Vegetables are staples of the Malian diet and economy, and improved production, storage and processing offers significant economic opportunity as well as health and environmental benefits. This project is particularly relevant to women and youth, who are the primary producers, processors and salespeople of vegetable products. This project will increase the resilience and productivity of vegetable production in Mali by addressing extension agent capacity, producer technical assistance, research efforts, producer organizational PAGE 36 strength and infrastructure development. It will directly benefit 52,747 women and youth farmers and their households, and indirectly benefit all farmers in the vegetable-producing regions of Mali via improved climate resilience and economic and nutritional outcomes. • Restoration: This project aims to build national capacity to restore degraded lands at scale to increase climate resilience, ecosystem services and agricultural productivity. Decades of drought and unsustainable land management in the Sahel has resulted in large-scale environmental degradation and, consequently, reduced nutritional and economic security for farmers and a greater national dependence on imports. Climate-smart agricultural techniques have been successfully adapted to land restoration in the Sahel and successfully implemented in Mali. The Malian government and its allies are heavily invested in restoring degraded lands. This project will scale land restoration practices by addressing the capacity of extension agents and other promoters; research efforts; policy environs; private-sector engagement; and farmer capacity to restore land, benefitting 106,461 agricultural producers and their households. • System of rice intensification: This project aims to increase rice productivity and climate resilience by scaling the system of rice intensification (SRI) to improve economic and nutritional outcomes. Climate-smart agricultural practices such as SRI can significantly improve rice climate resilience, reduce production costs and bolster yields. SRI has shown significant promise in Malian rice systems, and the government has invested heavily in bolstering the sector. Given the important role of the Office du Niger (OduN) for rice production, project design and implementation will need to be closely coordinated with OduN. This project will increase capacity for SRI in Mali by strengthening research and development, training extension agents, engaging the public and private sectors, and bolstering producer organizational strength. It directly benefits 72,480 rural agricultural workers and their households and indirectly benefits all Malian rice producers via improved economic and nutritional outcomes. • Wheat: This project aims to increase wheat productivity and climate resilience by scaling CSA practices to improve economic and nutritional outcomes. Wheat, which is quickly becoming a staple crop in sub-Saharan Africa, is particularly sensitive to the effects of climate change. Climate-smart agriculture has been shown to significantly improve Malian wheat production. The sustained and growing demand for wheat represents an important opportunity to improve nutritional and economic outcomes by moving domestic production toward self-sufficiency. The Malian government and its allies have made this effort a key priority. This project will improve the climate resilience and productivity of wheat systems by addressing extension services, producer associations, infrastructure development, search and development, private-sector engagement and enabling policies. It will directly benefit 71,856 smallholders and their households and indirectly benefit wheat producers throughout the central cereal production region of Mali through improved economic and nutritional outcomes. PAGE 37 Section 4 Guiding CSA Investments in Mali from Concepts to Programs 4.1 What Mali gains from CSAIP: An Overview Climate-smart agriculture (CSA) is based on the idea that what works for one farmer in one location may not work for another; thus actions within investments are tailored to the setting. Thorough context-specific innovation is necessary to maximize benefits. This approach makes CSA extremely effective, but its scalability through simple replication is not possible. However, the process for building CSA within a country is well known, and it requires ensuring that enabling conditions are right and that strong capacity-building and stakeholder involvement mechanisms are clearly identified. The CSAIP has been based on a great deal of situational analysis and prioritization, as described in prior chapters. There has also been a strong review of the national context to ensure that CSA design and implementation wholly build on and become integrated into policies, programs and projects. These are all of the early steps in moving from concepts to concrete actions. An operational framework to guide CSA programming into practice is thus crucial to project success. Effective frameworks support planning and implementation by producing concrete information through situational analysis (e.g., enabling conditions, goal, constraints), targeting and prioritizing (e.g., of high-interest options such as capacity building), design and implementation (e.g., field testing, scale-out planning), and M&E to facilitate iterative learning. In this chapter, the first steps of an operational framework and elements needed for project design and implementation are applied to the priority investments to identify opportunities, constraints and financing opportunities. See Annex A for more information on CSA planning and implementation frameworks. PAGE 39 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Table 11 Gains from CSA implementation: Rationale for investments Projected CSA On-Farm response Scenario without Investment Malian Importance Investment Value to Climate investment objective Change Non-timber Decreased agricultural 26%–73% of annual forest Economic revenue ok production, exacerbated Growth products climate risks Flood Economic 25% of total Decreased food security, Resilience and recession and food productive land under ok market destabilization growth agriculture security flood recession 10% of national GDP, Conflict, reduced food Crop-livestock Nutrition and 85% of Malian farmers security, exacerbated Resilience and ok integration food security own livestock, 30% environmental growth primary livelihood degradation Millet- Resilience and sorghum- Nutrition and 63% of national cereal Remains at current low poor growth legume food security consumption production rates integration Nutrition, Reliably high and Decreased production, Resilience and Vegetables food security, growing market poor increased postharvest growth economic demand losses Restoring Continuing loss of Most effective method forests and arable land Resilience and degraded Economic for addressing poor resulting in conflict and growth lands desertification reduced ag productivity Rice Economic Continuing high water Net exporter seeking intensification and food to improve efficiency ok use and relatively high Growth (SRI) security GHG emissions Economic Net importer with Decreased productivity Wheat and food growing demand poor and increased imports Growth security Promoting CSA in Mali must not be simply a collection of agricultural practices in different parts of the country, but instead should integrate and align climate change scenario planning, economic analysis, priority setting of regional areas, and barriers and opportunities. Decision-makers at all levels, from national ministries to farmers making planting decision, must understand the purpose and the bottom lines. Table 11 below demonstrates, for each of the crop and livestock investments, why that commodity was selected, what the climate change impacts will be for the commodity, and what the objective is of the CSA investment. 4.2 Climate-Smart Analysis for Four Select Investments Four investments were identified to be of high priority to increase productivity, strengthen resilience and mitigate climate change. More than 40 stakeholders representing diverse group from government, civil society and research identified these priorities during the initial workshops. Priority investments targeted three specific high potential production systems—non-timber forest products, crop-livestock integration and flood recession agriculture—and one program of national scope, a remote sensing system (see synopses above and detailed concept notes in the appendix). PAGE 40 Detailed modelling was conducted to predict the potential performance in terms of productivity, resilience and mitigation potential of these investments, subject to expected costs, social and climate risks, and the magnitude of potential outcomes. The model uses a probabilistic approach (Bayesian networks, or BN)) to estimate the net present value (NPV) and return on investment (ROI) for the four investments71. A BN model was used for two reasons. First, providing accurate estimates for project costs, returns and adoption is a primary challenge in project evaluation. The parameter uncertainty of all of these variables can be explicitly modelled and taken into account via BN. That is, instead of assigning a point value for the targeted number of beneficiaries or their income, in BN we assign a probability distribution that represents our degree of confidence around this estimate. Probability distributions are used for all variables in the model. Second, different risk scenarios— climate and non-climate—and their uncertainty can be simulated. The model takes the likelihood (frequency) and impact (severity) of risk factors into account when modelling project performance. A full description of the model, sources of parameter values and additional results can be found in Annex E. Productivity Estimates of changes in income for farmers implementing CSA are the core of the modelling. As such, this analysis was conducted using the most comprehensive and state-of-the-art dataset available, the CSA Compendium. The CSA Compendium is compiled from more than 1,500 peer- reviewed articles and contains more than 150,000 data points that compare 45 different outcomes of productivity, resilience and mitigation for 100 different farm practices in Africa72. This includes data on the changes in yield, costs and net returns with adoption of CSA (see examples in Table 12 and Annex E). This unique resource provides a rich evidence base for estimating the performance of practices across a wide range of agroecological conditions and farm management scenarios. Each of the four investments will more likely than not provide benefits to Malian smallholder farmers; however, the scales (i.e., number of beneficiaries) and magnitudes (i.e., impact per beneficiary) differ greatly (Table 13). The number of beneficiaries likely to be reached with each investment ranged from 97,000 to over 200,000. These values represent reasonable estimates of beneficiaries given census data in target areas and adoption rate estimates (innovation and impersonation) subject to the inherent challenges of the investment derived from experience implementing similar initiatives elsewhere. These values represent 10%–40% of the total possible farm households, suggesting significant opportunity to reach more people and scale up successes after the programs. However, the magnitude of impacts each beneficiary may receive differs across the investments. Participants in remote sensing and monitoring, who often may receive information remotely but rarely act, gain a 10% increase over current practice on average, while those engaging in improved flood recession agriculture through new varieties, soil management and other techniques would on average improve net returns by 46%. For example, an eight-year study of improved agricultural practices in the Segou region of Mali found that sorghum and millet yields increased by 20% when rotated with cowpea, 32% by incorporating green manures and 8% by reducing tillage via ridging73. 71 Yet B, et al..2016 72 Rosenstock TS, et al. 2015 73 Kouyate Z, et al. 2000 PAGE 41 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Investments that build on technology are typically the most cost effective because of the potential scale of impact. Investments in remote sensing and monitoring have potential to affect production of all commodities and value chains and in every part of Mali. When that flexibility is coupled with leveraging technological systems such as mobile devices for information dissemination and satellite systems for data acquisition, the result is a very large pool of potential beneficiaries. Costs per beneficiary of such programs are only a quarter of the costs of more ground-intensive programs. Such technology-dependent investments, however, can miss vulnerable population groups. Portfolios combining various implementation pathways reduce the risk of such eventualities. While further details are needed to validate the cost figures here, the existing calculations suggest these investments are cost-effective in terms of the number of beneficiaries reached. Table 12 Data from the CSA Compendium for Africa used as inputs into the climate-smart appraisal of proposed CSAIPs Investments Change in Change in Change in Climate-Smart Agricultural No. Of yield b income b costs b practice studies b FRAa CLI NTFP RSM (% ± SD) (% ± SD) (% ± SD) Agroforestry alleycropping ✔ 22 15 ± 97 Improved crop varieties ✔ ✔ ✔ 21 36 ± 85 Crop rotation ✔ 38 52 ± 68 -40 ± 44 Intercropping ✔ 33 -2 ± 62 -18 ± 52 Mulch ✔ 57 46 ± 81 -55 ± 33 Inorganic fertilizer ✔ 165 68 ± 68 51 ± 37 -48 ± 83 Organic fertilizer ✔ ✔ 56 73 ± 101 42 ± 10 -63 ± 89 Reduced tillage ✔ 49 -8 ± 75 -19 ± 10 Terracing, ridging, bunds ✔ 29 44 ± 92 30 ± 14 -30 ± 25 Livestock diet improvement ✔ 83 14 ± 114 -3 ± 77 8 ± 15 Improved livestock breeds ✔ 6 -14 ± 104 -75 ± 44 -2 ± 3 a Checkmarks indicate technologies included under investment projects according to their concept notes. FRA = flood recession agriculture, CLI = crop-livestock integration, NTFP= non-timber forest products and RSM = remote sensing and monitoring. b Crop data shown for cereal crops (maize, millet, sorghum and rice) in West Africa; livestock data is for all livestock (cattle, goats, sheep, chickens) in West Africa. Impact. The less expensive investments are likely to generate the smallest relative improvements for each beneficiary. For example, remote sensing offers an average of 10% improvement per beneficiary, while more resource-intensive investments—such as non-timber forest products, crop-livestock integration and flood recession agriculture—offer approximately 40% improvement per beneficiary. Thus, the added investment per beneficiary in terms of training, research, marketing and the like may translate into relatively larger gains for households. Consideration of change effected, in addition to the number of beneficiaries, is warranted. Return on investment is positive for all four investments, suggesting these will be sound investments. These calculations reflect data on the relative changes in income with CSA management practices as compared to conventional management, as well as assumptions about the pace of adoption and the relative costs defined for the investment. Though the model accounts for uncertainty PAGE 42 in each of these factors, actual implementation may deviate significantly from data and assumption underlying this modeling approach. Thus, this analysis can best be thought of as a first appraisal. Subsequent efforts need to bring in a diverse set of opinions to increase precision on the estimates underlying the models. The investments are expected to create positive NPV; however, the investments show different degrees of resilience to risks. Under more uncertain conditions and considering the potential interactions of all risks, the remote sensing investment far outperforms the rest, with NPV equal to US$46.6 ± US$42 million. This translates to a 92% chance of success of having a positive NPV given the risks. Indeed, NPV of the remote sensing investment actually increases when considering climate risks, as farmers are likely to see more benefit from correct information about climatic events, and adoption rates may also increase. For example, in Senegal farmers saw up to an 80% increase in yields when climate information correctly predicted a dry year compared to not utilizing climate information74. The investment in non-timber forest products is the most sensitive to climatic risks, as tree health and production are most closely tied to environmental conditions. Crop-livestock integration and flood recession agriculture both saw only slightly reduced NPV under climate risk scenarios, as technologies in those investments are meant to ameliorate exposure to climate risks. All projects were equally susceptible to political and social risks (see Annex E for detailed results). Non-timber forest products offer among the best bets for increasing incomes in Mali. Native tree species and shrubs contribute 26%–73% of farmers’ annual revenue75. Further investment in this area has a moderate likelihood of producing a positive ROI and is resilient to both social and natural risks. While climate risks can reduce the NPV of NTFP projects (trees are less productive in drought years), the most pronounced risk to this investments was political instability and community conflict that reduced the average ROI from 53% to 15%. Social and political conflict can reduce access to land, particularly for certain groups such as women, and reduce land productivity. For example, in Uganda land under conflict has less than half the productivity of similar land not under conflict76. Work with NTFPs often falls within the domain of women; thus, regardless of the lower ROI, investments in NTFP value chains can have add-on effects through women’s income and empowerment. Return on investment for integrating crops and livestock systems together was among the highest (mean 88%, assuming no risks). The predicted performance of this investment is conditioned on the nearly 50 percent changes in expected impacts with improved livestock practices by comparison to improved crop practices (see table above) in combination with assumptions about the relatively slow rate of adoption because of the challenges faced with integration and diversification of farming systems77 and the relatively significant cost of implementation for the investment (greater than US$25 million). Adding livestock to cropping systems can produce synergistic benefits (e.g., producing manure for crop fertilization), but it can also produce trade-offs (e.g., crop residues fed to livestock cannot be used as a soil amendment to maintain soil health). Appropriate choice of livestock and crop systems for integration could ameliorate the poor performance predicted for this project. For example, in a study across seven countries in sub-Saharan Africa, increasing cereal production by including fertilizer application or other intensification practices relieved the trade-off between having sufficient crop residues for both livestock and soil amendment in integrated crop-livestock systems78. 74 Sultan B, et al. 2010 75 Faye MD, et al. 2010. C 76 Deininger and Castagnini 2006 77 Kouyate Z, et al. 2000 78 Valbuena D, et al. 2015 PAGE 43 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Table 13 Performance of the four priority investments Prob. Of Number of Impact Ben-1 Cost Cost Ben-1 NPV* ROI Project + NPV** beneficiaries (% ± ST DEV) (M $) (S) (M $) (%) (%) Non-Timber forest 122,400 41 ± 12 40.5 331 21.3 57 53 Products Crop-livestock lnt. 97,000 45 ± 15 24.9 257 21.9 62 88 Flood recession ag. 224,000 46 ± 59 61.4 274 37.1 53 46 Remote sensing 200,000 10 ± 15 16.0 80 20.2 92 126 NPV and ROI based on baseline scenario without inclusion of major project risks. ** Probability of a positive NPV is a measure of resilience of the investment as it estimates NPV when faced with six prevailing risks: drought, flood, pests, political instability, community conflict and poor project governance. Flood recession farming will be an ambitious investment reaching more than 224,000 beneficiaries at modest costs. Flood recession agriculture had the highest NPV under a no-risk scenario among the four investments we tested. Although this investment is likely to produce significant gains, the risks have potential to dramatically reduce the likelihood of positive returns. When risks are considered individually, mean ROI for the investment drops from 24% with no risks to -16.8% to -3.1% mean ROI with political instability and flood, respectively. However, the majority of risk exposure for flood recession agriculture is from political and social risks in the region of the Niger River. While climate risks do decrease NPV on average from US$37.1–US$32.2 million, the implementation of many technologies that mitigate the effect of droughts, floods and pests on agriculture mean that climate risks only reduce NPV by about 13%. Remote sensing and monitoring is the most robust and highest-performing investment. Given the low investment costs, high numbers of potential beneficiaries and the relatively high return per beneficiary, remote sensing and monitoring (digital agriculture) has great potential to increase the climate-smartness of the landscape and farms. Practices such as climate information and soil services will be able to provide farmers more and better information at the time when it is needed most. The project is also extremely resilient to risks, as climate risks may actually increase project NPV and the remote nature of information delivery may expose the project less to political and social risks. 4.3 Constraints to Design and Implementation The Malian context presents some circumstances that could manifest as barriers to all of the investments. Many of these barriers to CSA design and implementation stem from, or are aggravated by, policy issues. Possible barriers of greater threat to investment success of all projects are: (i) political or security crises; (ii) farmer-pastoralist conflicts; (iii) having women systematically excluded from capacity building and extension; and (iv) donor unwillingness to support investments. Potential barriers of medium significance to CSA include: (i) drought, floods, pests, disease and extreme temperatures; (ii) poor information access; and (iii) disincentivizing policy. Table 14, below, summarize possible risks confronting each of the national and regional priority investments. Investments are listed in order from highest to lowest severity of potential barriers within each grouping, with orange indicating potentially severe barriers, yellow medium barriers, and green low barriers. Information and information-sharing systems around CSA remain to be developed in Mali. CSA as a concept is not well known among decision-makers, technical experts or farmers themselves. The body of knowledge on CSA practices optimized specifically for the Malian context is still under PAGE 44 development. Mechanisms for information exchange are disjointed or have not yet been established. These barriers impact CSA adoption most notably in terms of policy making and extension services. In addition, there are significant on-farm barriers, including low producer literacy rates, lack of knowledge of environmental issues, and youth urban migration79. Poor access to financial services at the farm level is a major hindrance to uptake and scaling of CSA practices. Short-term credit and risk reduction instruments are crucial for smallholders’ shift from subsistence farming to business farming. However, only a few financial institutions operate in Mali, and they are mostly concentrated in urban areas. These institutions offer only limited short-term products that come with excessively high interest rates80. Risk factors outside of farmers’ control—such as erratic weather, irregular seasons, unclear land tenure and lack of on-farm collateral systems— result in the rejection of 70% of Malian farmers’ loan applications81. Microfinance institutions, farmer cooperatives and group lending organizations have lost their credibility with farmers as viable alternatives to traditional banking institutions; farmers cited a lack of transparency, poor management and higher interest rates82. Security crises disrupt farmer productivity, preclude access to basic services and instigate high levels of food insecurity. In June 2018, 20% of Malians (4.1 million individuals) were food insecure and in need of humanitarian assistance83. Conflicts in the north reduce human mobility and availability of labor, thus increasing transportations costs and pressures on land and water resources. Reduced access to markets and support services due to the impacts of conflict and insecurity also limit income and reduce incentives to produce a marketable surplus84. Poor infrastructure severely limits agricultural market potential. Few paved roads and long distances to markets have made transportation excessively expensive85. Consequently, value chains are often disorganised or nonexistent. Wholesalers and intermediaries leverage producers’ disconnect from regional and international market prices to apply high margins86. A lack of value-added processing facilities, cold-chain infrastructure and storage facilities further inhibit market diversification and stabilization. 79 Malian government 2014 80 FAO 2013 81 World Bank 2015 82 FAO 2013 83 World Bank 2018 84 CIAT 2018 85 FAO 2013 86 Interview PAGE 45 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Table 14 Barriers To adoption of proposed CSA investments In Mali NATIONAL INVESTMENT RISKS Lack of funding and/or institutional accountability to acquire and maintain equipment Soil information service Lack of land rights deters producers from medium and long term investments Lack of fertilizer and fallow subsidies Extension services Low support structure capacity Remote sensing system Risks are not well understood pending greater investment in farmer capacity Agroclimatic system Current program does not include crops grown by women REGIONAL INVESTMENTS RISKS Labor shortages at time of transplant Long timeline for establishment of deomonstration plots Rice intensification (SRI) Smallholder preference for large, lower investment plots Sandstorms Mismanagement of water Community conflict related to development of irrigated perimeters Sandstorms Flood recession Occurs outside primary agricultural season, exacerbating farmer-pastoralist land use conflict Limited feed availability for livestock Crop livestock integration Increasingly limited grazing area as environmental degradation progresses; encroach- ment on new areas furthers degradation Poor seed availability; lack of infrastructure drives seasonal oversupply and overde- Vegetable production, stor- mand age, and processing Faulty irrigation equipment; poor transport, cold chain, and storage infrastructure Community conflict related to development of irrigated perimeters Wheat development High price volatility High international market volatility Non-timber forest value Bush fires chains Cultural norms against investing in indigenous tree species Lack of national and international markets Millet-sorghum Legume Restrictions on staple crop exports constraints farmers to subsistence production integration Poor road network precludes commercial development Restoration of degraded Lack of land rights deter producers from medium and long term investments lands Low barriers to adoption Medium barriers to adoption High barriers to adoption PAGE 46 4.4 Opportunities for Design and Implementation CSA investments enjoy strong support in Mali. This is evidenced by the breadth and depth of stakeholders who engaged in developing the CSAIP discussed here. Strong national representation and international support have been crucial to this process. Involvement took place as consultation prior to the workshop, attendance at workshops, or both. Although CSA is not well known in Mali, climate services and extension services enjoy broad recognition and support. Mali is an international pioneer in implementing climate services; its first program, the Rural Agrometeorological Assistance Project, began in 1982 and continues today. The national investment plan and policies, regional alliances and international donors have unified in support of the expansion of extension services. The private sector represents an important opportunity for the implementation of CSAIP for agriculture, particularly in terms of private-sector-driven service provisions. For example, the private sector is best poised to launch credit and lending and bolster services available through agrodealers. In many cases, they also have the liquidity and business case to invest in infrastructure, advisory services, training of subject matter experts and other factors that support expanded production, improved quality and greater market reliability. These services are a critical and integral part of the project concepts presented in this CSAIP. Public-private partnerships may also be important when the private sector cannot make a business case on its own. Mali’s existing large-scale cotton and rice input subsidies offer opportunities to bolster markets. Notably, fertilizer subsidies for these two crops indirectly boost the production of other staples. For example, women traditionally grow crops including millet, fonio and sorghum87 for home consumption but do not benefit from fertilizer subsidies themselves. But these crops are produced in rotation with rice and cotton, so their productivity increases as a result of residual fertilizer in the soil. Recent policy developments represent important opportunities to tackle inequality and engage vulnerable populations. Inequality currently drastically hinders the development of CSA and the Malian agricultural sector. For example, women currently make up 65% of the agricultural labor force, but only a fraction of them are landowners88. Those who do own land often receive smaller and less fertile parcels89. Only 20% of Malian women have access to extension services, and 53% are able to access to agricultural inputs90. Policymakers have begun to lay the foundation to address these issues. The Agricultural Development Policy for 2011–2020 explicitly aims to promote the economic advancement of women and youth91. The revised Agricultural Land Law, which went into force in April 2017, requires that 15% of irrigated land be allocated to women and youth, although this is not yet consistently applied in practice92. Building out additional policy and enforcement mechanisms for the same will further support full economic participation of vulnerable Malian populations. 87 FAO 2013; Interview 88 CARE 2017 89 Nhliziyo 2015; Interview 90 CIAT, 2018 91 FAO 2018 92 CARE 2017; Nhliziyo 2015 PAGE 47 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN The West African Alliance for Climate-Smart Agriculture is a key opportunity for Mali to develop water management infrastructure. Launched in 2015 by the Economic Community of West African States, this alliance serves as a platform to actively promote the mainstreaming of CSA, particularly in terms of vulnerable population resilience. As part of the alliance, the West African Monetary and Economic Union contributes to developing both water resource infrastructure and financial and policy mechanisms related to irrigation for agriculture93. Given the degree of water scarcity in Mali, water management in the context of climate change is key to continued growth of the agricultural sector. Furthermore, the Office du Niger is a key actor in Malian irrigation. Careful coordination at the national level will help engage these multinational actors behind a climate-resilient Malian agenda. The agricultural sector has seen significant growth as a result of active governmental prioritization. Public expenditures in agriculture increased 82% between 2004 and 2010; agriculture constituted an average of 12% of the national governmental budget between 2010 and 2016 in accordance with the Maputo protocol. As a result of these investments, the agricultural sector grew an average of 11% annually during the same period94, yet 90% of Malian smallholders still engage in only subsistence farming. This represents a tremendous opportunity to continue Mali’s remarkable growth toward its full commercial potential as an agricultural powerhouse. There is significant opportunity to better align agricultural policies with national objectives. While national objectives have indicated an intention to increase exports and diversify production since 2005, in many cases policy remains counterproductive to these objectives. Exports on staple crops such as millet, sorghum and livestock have been restricted while tariffs on imported rice were lifted95. The rice and cotton subsectors have received inordinate government investments in comparison to other subsectors of equivalent GDP contributions96. Rice subsidies aiming to outcompete imports and tackle food insecurity have favored wealthier farmers97 who can access irrigation and inputs, and also have held farmgate sale prices artificially lower than they would be in the absence of the policy98. Disjointed value chains, poor market information access and an absence of producer organizations further penalize smallholders. Limits on exporting staples were established in the wake of the 2008 food crisis; these have since been formally lifted but in practice remain in force as a result of onerous legacy customs processes99. Decades of heavy cotton subsidies have precluded diversified agriculture100, making the country vulnerable to price fluctuations and climate change. The five-year Cotton Development Plan is due to end in 2018, which, along with other policy reforms, offers an excellent opportunity to put national agricultural objectives, including climate-smart agriculture, into practice. Agricultural research in Mali remains underfunded, even though some funding streams already exist, largely financed by donors and development banks via short-term projects. This is an excellent opportunity for Mali to develop an overarching research agenda that would ensure that short- term projects inform and support long-term strategies, efficiency and cross-project coordination. A strategic research framework would also help encourage additional agricultural research funding by serving as a metric for progress and next steps. 93 FAO 2017 94 FAO 2017 95 FAO 2013 96 World Bank 2018 97 FAO 2018 98 FAO 2013 99 FAO 2018 100 CIAT 2018 PAGE 48 Many recent national policies support climate change action and adaptation, while a few directly support CSA. Recent policies, discussed further below, have increasingly supported agricultural development (Table 15). There are many earlier efforts that can be built upon and complementary activities underway to support this Malian CSAIP, as identified in Annex B. The Law on Agriculture promulgated in 2006 opened the path to improving the land tenure regime. Land tenure currently constitutes the main impediment to widespread adoption of CSA in Mali; producers who don’t own the land they farm are reluctant to make long-term investments. While land legally belongs to the state, religious leaders and village chiefs are able to manage lands and grant ownership rights101. Greater enforcement of ownership rights will protect smallholders from expropriation, reduce farmer-pastoralist conflicts and incentivise CSA investments102. Mali’s National Adaptation Plan highlights the role of agriculture in reducing greenhouse gas emissions. This commitment sets the stage for international support, multistakeholder coordination and public-private partnerships in achieving CSA innovations. Other ongoing initiatives, including the United Nations High Commissioner for Refugees (UNHCR) and World Food Programme (WFP) humanitarian assistance, could also benefit from coordination with CSAIP efforts. Furthermore, there is strong alignment with the NDC, as described below. Table 15 Recent Malian plans, policies and frameworks supporting climate change, CSA pillars or CSA CLIMATE POLICY, PLAN OR FRAMEWORK ABBREVIATION DATE ADAPTATION MITIGATION CSA CHANGE Agricultural Orientation Law LOA 2006         National Adaptation Program of NAPA 2007         Action Strategic Framework for a Green & EVRCC 2011         Climate Resilient Economy National Climate Change Action PANC 2014         Plan National Food and Nutrition Policy PPN 2014         National Agricultural Sector In- PNISA 2014         vestment Plan National Agricultural Investment PNISA 2015         Program Intended NDC iNDC 2015       ECOWAS Climate-Smart Agricul-   2018         ture Framework Agricultural Development Policy PDA 2011–20         National Policy on Climate Change PNCC 2015–20         Strategic Framework for Econonic Recovery & Sustainable Develop- CREDD 2016–18         ment Investment Plan for the Imple-   2018–20         mentation of the NDC Agricultural Land Tenure Policy & pend-           Agricultural Land Tenure Law ing 101 FAO 2017 102 FAO 2017 PAGE 49 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN 4.5 CSAIP Alignment with NDC Partnership Investment Plan The CSAIP aligns with and supports Mali’s NDC Partnership investment plan, both in terms of higher-level objectives (e.g., national planning), and for meeting specific adaptation activities (e.g., water management). Under the auspices of the NDC partnership, the World Bank is supporting Mali to develop this CSAIP and shared adaptation strategies that directly align with the NDC. Given the ongoing development of the NDC Partnership investment plan, it will be important to ensure alignment and complementarity between these processes as specific planning for CSAIP implementation is underway. The NDC’s higher level objectives, include, for example: • National and rural spatial planning to develop agriculture and the forestry sector; • Agricultural development that reduces deforestation and GHG emissions; • Sustainable intensification (agriculture, livestock, fisheries) that reduces deforestation; and • Sustainable forest management. Table 16 Alignment of CSA crop and livestock investments with NDC Partnership Investments POTENTIAL ALIGNMENT WITH NDC PARTNERSHIP INVESTMENTS Forest man- Rainwater Assisted Intelligent Organic Irrigated and Pastoral de- agement for harvesting natural re- agriculture manure intensive rice velopment restoring and stor- generation develop- and urea by farming sys- project degraded age ment micro dose tem (IRS) ecosystems Non-timber forest prod- ucts Flood recession agriculture Livestock Millet-sor- ghum- legume integration Vegetables Restoring degraded lands Rice Inten- sification (SRI) Wheat The CSAIP contribution to these objectives are strong, especially at the national scale. For example, the remote sensing and geomatics capacity will provide a sound basis for all four of the NDC objectives, by helping to provide timely and accurate GIS information to inform decision-making. Introducing CSA into the national extension system supports agricultural development that reduces emissions and promotes sustainable intensification and sustainable forest management. The agroclimatic weather information system helps with all four objectives by providing timely information for project implementation, and also by laying a foundation for understanding how systems are changing over PAGE 50 time. Similarly, soil fertility monitoring also supports all four objectives, for example by helping to determine where agriculture can be developed or intensified, where restoration is needed, and where agroforestry might best be implemented. These examples demonstrate how well CSAIP investments in agriculture can help Mali meet its NDC commitments, as well as the need to integrate the planning for both. Many proposed adaptation activities in the NDC are also strongly supported by the CSA crop and livestock investments. For example, NDC project objectives include: (i) building resilience in the agriculture sector; (ii) climate-smart hydro-agriculture (water management); (iii) adoption of improved crop cultivars and livestock breeds; (iv) grain banks and storage; (v) small-scale agricultural development; and (vi) perennial agriculture, particularly fruit trees. The Mali NDC for reducing agriculture-sector emissions identified include: (i) reducing emissions from rice cultivation; (ii) promoting sustainable land management on 92,000 ha, and (iii) increasing rural, renewable electrification, including solar irrigation. The practices within the CSA investments are aligned with many NDC investments. For instance the “organic manure and microdose” is an NDC investment but also practices part of several CSA investments (see Table 16). This is also the case for many other CSAIP practices. 4.6 Financing Opportunities for CSA Expansion An operational framework to guide CSA programming into practice is crucial to project success. Effective frameworks support planning and implementation by producing concrete information. Although Mali is eligible for multiple international finance instruments, funding for CSA in the country has been limited. Greater effort needs to be placed on accessing international climate finance instruments while also ensuring availability of local-level public and private financing instruments for investments in CSA. However, there are many potential private, public and international funders and financing instruments, as shown in Figure11. Figure 11 CSA financing activities in Mali103 103 Mali CSA Profile PAGE 51 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN 4.7 CSA Investments and Contributions to Supporting National Policies While many Malian national policies support CSA, CSA investments support many of the policies mentioned in Table 15 and described in section 4-4 above. All investments strongly support at least two of the three CSA pillars, and many also support national policies and help to overcome barriers identified in earlier sections (see Table 17 below). All investments lead to increased agricultural productivity. As strongly demonstrated in chapter 2, climate change is already affecting production in Mali, and scenarios show that climate change will have significant and negative impacts on many crops, especially those that are vital for food security. Therefore, if the investment returns are to be positive and sustainable, all agricultural investments countrywide need to consider climate change and CSA practices. All of the investments also must contribute to adaptation and enhancing agricultural sector resilience. While there is less emphasis on supporting mitigation, it is still addressed by most of the investments. Many of the investments also play a strong role in supporting gender equality, reducing poverty, enhancing food security, and reducing vulnerability. Given the harsh climate change impacts Mali is already experiencing, enhancing resilience across productive sectors, as well as more broadly, is vital. Table 17 Links between CSA Investments and national priorities CSA 3 CSA SUPPORT BUILD BOOST PILLARS OTHER SECTORS RESILIENCE AGRICULTURE INFRASTRUCTURE & CONNECTIVITY RISK MANAGEMENT MECHANISMS AGRICULTURAL PRODUCTIVITY & RESEARCH & DEVELOPMENT MARKET INTEGRATION AGRICULTURE VALUE FARMER NETWORKS ENABLING POLICIES GENDER & YOUTH DIVERSIFICATION HUMAN CAPITAL PRODUCTIVITY FOR CLIMATE ADAPTATION MITIGATION EXTENSION FINANCE NATIONAL PRIORITY CLIMATE-SMART INVESTMENTS National remote sensing National extension eystem National agroclimatic system National soil fertility monitoring PRIORITY CROP & LIVESTOCK CSA INVESTMENTS Non-timber forest products Flood recession agriculture Livestock Millet-sorghum with legumes Vegetables Restoring degraded lands Rice intensification (SRI) Wheat PAGE 52 All CSA Investments directly support many national priorities (cited in Table 17 and Annex B). The investments support national priorities in different ways, but such support should be considered in moving from concept (presented in this plan) to the actual design and implementation of the investments. For example, aspects of supporting agriculture value diversification, a Malian country goal, would include (i) improving agricultural productivity and market integration, (ii) strengthening infrastructure and (iii) potentially building risk management mechanisms to increase farmer willingess to diversify. As shown in Table 17 above, all of the investments directly support improving agricultural productivity, with the exception of remote sensing, where the links are indirect. Yet these investments span a range of commodities and practices, all with an eye toward making them climate smart, and will have positive ripple effects across other elements listed in the table. These investments can all be seen as supporting Mali’s key national policies and its future development in agriculture and food security in the face of climate change. The 12 investments offer support to many other sectors. The four national-scale investments are critical at a foundational level, providing the basic supportive infrastructure needed for good agricultural decision-making. All four support broader decision-making that is valuable for strategic planning at national scales, and also provide valuable contributions to the crop and livestock sector investments directly. The four national investments have the strongest links to building reslilience through human capital, risk mitigation, infrastructure development and adaptation. The eight priority crop and livestock investments support increasing agricultural productivity, and most support increasing adaptation, especially increasing productivity, extension, research and development, human capital, risk management and infrastructure development. This is because components of CSA investments rely on changing elements of other sectors. In moving from concepts to design and implementation, it is possible to undertake actions that maximize the benefits from CSA implementation and to ensure that the projects themselves, and the processes associated with how they are implemented, are designed to further support Mali’s desired policy outcomes. PAGE 53 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN PAGE 54 Section 5 TOWARD A MONITORING AND EVALUATION SYSTEM FOR MALI’S CSA INVESTMENT PLAN Monitoring and evaluation (M&E) is an essential component of the CSAIP implementation; it lays out the assumptions of how change will occur (theory of change) and provides the evidence and information to implement results-based management (results framework, indicators and M&E systems)104. Monitoring and evaluation of the CSAIP will deliver reliable and real-time information in an easily accessible dashboard, allowing the Government of Mali, development partners and implementing agencies to track progress on activities, outputs, outcomes and impact (box 1) against targets, and also to raise flags when adaptive actions may be necessary105. The M&E activities will also create a mechanism for learning lessons, increase accountability and generate information to tell data-driven stories of successes. Monitoring and evaluation under the CSAIP are paired activities that contribute to collective knowledge of how investments are performing and how the actions are influencing processes of change. Monitoring is the systematic and repeated collection and analysis of data. CSAIP will monitor both processes (i.e., tracking program implementation against work plans and budgets) and results (i.e., tracking indicators of products and changes in behavior)106. Complementary to monitoring, evaluation rates the performance of the investments in terms of effectiveness, impact and sustainability. These indicators allow a comprehensive understanding of delivery and value for money. In addition, targeted ‘impact evaluations’ will be conducted to ascertain the effectiveness of specific interventions, quantitatively describing the factors or chain of events that allowed certain activities to achieve objectives (or not)107. 104 International Finance Corporation. 2018. Working with smallholders: A handbook for firms building sustainable supply chains. World Bank Group: Washington, DC, USA. 327 pg. 105 Lamhauge N, Lanzi ER, Agrawala S. 2012. Monitoring and evaluation for adaptation: Lessons from development co-operation agencies. OECD Environment Working Paper No 38. Paris, France: OECD Publishing. 106 Independent Evaluation Group. 2012. Designing a results framework for achieving results: A how-to guide. World Bank Group: Washington DC, USA. 45 pgs. 107 Banerjee, A. V. & Duflo, E., 2009. The Experimental Approach to Development Economics. Annual Review of Economics, 1(1), pp.151–178. PAGE 55 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Monitoring and evaluation of the CSAIP will cross institutions, administrative jurisdictions and scales. The CSAIP targets improvements in agriculture, environment and finance outcomes, which are currently managed separately by various institutions. With the contribution of CSAIP to multiple agendas, designing the CSAIP M&E system to be interoperable with existing systems is paramount for efficiency and coherence. Furthermore, M&E under the CSAIP will have actions that occur at the individual investment level and for the entire portfolio of investments. This will enable stakeholders at different levels to take evidence-based actions while the system as a whole is internally consistent. This coherence extends beyond CSAIP M&E. Many of the CSAIP objectives are also relevant to national and international targets, for example, the Comprehensive African Agriculture Development Program (CAADP), NDC and Bonn Challenge to the United National Convention to Combat Desertification UNCCD). Therefore, the operations to be put in place for the CSAIP will support national monitoring and reporting needs. Theory of Change The CSAIP’s objective is to sustainably increase agricultural productivity and build resilience of farms, farmers, ranches, landscapes and the food system generally. This goal targets only two pillars of CSA, which typically includes a third (mitigation). The CSAIP emphasizes productivity and resilience because (i) Mali’s agriculture, forest and land-use sector has had relatively limited historical and current contribution to the emissions causing global climate change and (ii) the program is designed to address national food security priorities. This CSAIP, however, will also contribute to climate change mitigation as a co-benefit. Many of the interventions—such as improving livestock diets in the Abidjan Food Basin investment and reducing food waste across the value chains in mango, cacao and other commodity investments—will decrease GHG emissions per unit of product. Furthermore, investments in agroforestry and soil management will accumulate carbon and reduce emissions from farms and landscapes. Therefore, despite targeting resilient productivity, these mitigation co-benefits make this CSAIP contribute to all three CSA goals and to national mitigation commitments made in the NDC. The portfolio of investment aims to work with diverse beneficiaries across the food system. A significant amount of the effort in the investment is directed toward farmers and livestock keepers. In addition, the CSAIP plans activities that affect the functioning of markets and value chains with the private sector. The program will support government institutions in terms of policy setting and implementation, as well as in research, knowledge development and capacity building. In this way, all the major types of actors in the food system will be engaged by and benefit from the CSAIP. The CSAIP’s objectives of increasing productivity and resilience will be achieved through four primary pathways: increasing incomes, reducing exposure to climate risks, reducing sensitivity and vulnerability to climate risks, and increasing adaptive capacity. This theory emphasizes the importance of both reactive actions (absorb, react, restore and learn) and preventative actions that build robustness while being consistent with a fundamental theory of resilience in social and ecological systems108. 108 Walker B, Holling CS, Carpenter SR, and A Kinzig. 2004. Resilience, adaptability and transformability in social-ecological systems. Ecology and Society, 9:5; Tendall DM, Joerin J, Kopainsky B, Edwards P, Shrek A, Le QB, Krueti PK, Grant M, and J Six. 2015. Food system resilience: Defining the concept. Global Food Security, 6:17-23. PAGE 56 Glossary Outputs: tangible products of project activities including trainings, publications, partnerships, new technologies, policies and infrastructure such as weather stations, etc. Outcomes: changes in behavior including knowledge, attitudes and skills of stakeholder groups as a result of project activities and outputs. Impact: high-level objectives identified by stakeholders during the development investment plan (i.e., the project development objective). Indicators: information used to document current state and changes of activities, outputs, outcomes or impact. Theory of change: a description and/or diagram of why and how the desired change and objectives are expected to occur. Impact pathway: built on the theory of change, this visualizes the plausible pathways for change to take place. Results framework: management tool that is an explicit graphical summary of results expected from particular interventions such as investments, development plans or policies. Monitoring: continuous/regular data collection to track implementation of budgets and activities (planned vs. achieved). Evaluation: occasional and in-depth data collection for assessing outcomes and impact and the intervention strategy (e.g., effectiveness). • Increasing productivity and incomes. Increasing on-farm productivity and strengthening market mechanisms (input and output), both existing and new, can have cascading effects through the value chain down to producers, and also have a positive effect on distributors, processors and vendors. Additional incomes lead to accumulation of assets and wealth, both raising persons out of poverty and buffering against natural or social shocks that reinforce poverty traps. Investment in making financial services available will further reinforce the ability to sustain productivity and asset levels. Many of this CSAIP’s investments name specific types of management practices and technologies that can raise on-farm productivity (e.g., rice, livestock and sorghum, etc.) or investments along the value chain that increase the amount of food that ultimately reaches the market, such as improving postharvest storage of the fruits of the zaban shrub. • Reducing exposure to climate hazards109. The ability to predict and prepare prior to minor and major weather events can greatly improve the ability of individual farmers, communities and value chains to react. Even simple responses by farmers such as planting at optimal times can have significant impacts on the resilience of production, especially when weather is highly uncertain. This CSAIP reduces exposure by providing information on climate and weather by strengthening the agrometeorological services and through specific investments in rural advisory services using traditional face-to-face training, leveraging information and communications technologies (ICTs). In addition, the CSAIP invests in remote sensing and agricultural statistical capacity for improved programmatic and policy decisions. 109 Hansen J, Helin J, Rosenstock T, Fisher E, Cairns J, Stirling C, Lamanna C, van Etten J, Rose A and B Campbell. 2018. Climate risk management and rural poverty reduction. Agricultural Systems (in press). PAGE 57 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN • Reduced sensitivity and vulnerability to climate hazards. Mitigating or buffering the effects of climate events when they happen is critical to maintaining livelihoods and economic prosperity. Many CSA investments specifically target ways to buffer and absorb shocks and to restore the ability of farms and value chains to rebound from them. For example, improving soil fertility increases productivity (e.g., as found in the National Remote Sensing Program), in turn Increasing incomes that can lead to increased assets, which typically translate to improved resilience. • Increasing adaptive capacity. The ability of farmers and value chains to adjust to shocks as they occur is often a function of the available resources (social, physical and capital) and state of being. The CSAIP investments provide a platform for stronger responses to systemic, climate and other perturbations. This CSAIP aims to strengthen the linkages among providers of information, input and output markets, community groups and others. The increase in social connectivity and access to resources, information and assets serves as a platform to strengthen the entire food and production system. The CSAIP will enable this across all of the investments by strengthening the functioning of institutions and markets; however, investments in value chains specifically target improved adaptive capacity. Presented above as distinct, the four pathways are in fact expected to influence each other and produce complementary effects. Complementarities occur when actions directed toward one pathway inadvertently influence another in a positive way110. Trade-offs, by contrast, occur when one pathway improves while another degrades. Expected complementarities include (but are not limited to): increasing income and assets builds resilience by providing resources to buffer against or rebound from perturbations (e.g., health concerns or climate shocks); reducing the sensitivity and vulnerability to such systemic perturbations provides the platform to sustain and grow incomes and wealth. The four pathways will be realized through changes in understanding, skills, attitudes and behavior of actors throughout the rural landscape, government, private sector and food systems generally. This includes five primary routes: adoption of new technologies by farmers; use of risk mitigation strategies; strengthening information delivery systems; building an enabling environment including both financial services and policies; and engagement of the private sector. Therefore, the CSAIP creates a comprehensive program inclusive of the principal actors in order to catalyze transformative change in the country. The CSAIP M&E system provides a framework to track the implementation of Mali’s NDC, where Mali targets adaptation and mitigation actions in the agricultural sector. CSAIPs M&E theory of change and results framework include impact indicators that are able to quantify the adaptation and mitigation benefits derived from programmatic interventions. The framework, built up on fundamental data characterizing farm, household and value-chain activities, will track productivity, resilience, adaptive capacity and greenhouse gas emissions. This approach will allow it to be extended to agricultural interventions outside the CSAIP. 110 Duguma L, Minang PA and M van Noordwijk. 2014. Climate change mitigation and adaptation in the land use sector: From complementarity to synergy. Environmental Management, 54: 420-432. PAGE 58 Results framework and indicators Investment success will be monitored against activities, outputs and outcomes that will feed into the four pathways to impact derived from the theory of change (see Figure 12). This results framework links the twelve investments through six cross-cutting activity areas including (i) finance, (ii) institutions and infrastructure, (iii) on-farm practices, (iv) market functioning, (v) research and knowledge generation and capacity building and (vi) advisory services. Each of the individual investments emphasizes or targets actions within these areas, with an average of four activity areas per investment. Activities funded under the investments will produce countless and diverse types of tangible outputs. Outputs of the activities will be revised and finalized during the next stages of investment development. Types of outputs are already evident in the concept notes (Annex F). Individually and together, the outputs form the foundation for the human capacity, physical infrastructure and enabling conditions for change in the country’s rural landscape and food system. Within the timeframe of this investment, it can be expected that the outputs will produce changes in behavior: by farmers, such as adoption of CSA technologies and use of climate information and purchase of insurance; by institutions, including though development of new weather forecasting capacities and information and communication technology-based advisory services; by the private sector, through stimulating both new investments by small-, medium- and large-scale enterprises in inclusive and resilient business models; and by supporting institutions with harmonized policies; as well as other potential changes. These changes all contribute to the four intermediate impacts and the overall climate-smartness of agriculture and food systems in Mali. A fifth category of actions will also be monitored: the process of implementation. Process implementation is critical to understand bottlenecks in delivery against the results framework. Monitoring activities and relevant indicators will be established at the portfolio and individual investment levels. Some indicators will be specifically required to be able to be aggregated to the investment portfolio level, such as number of beneficiaries, budget expenditure, etc. Most often, indicators will be selected for the individual investment according to pre-established criteria: specificity (the indicator needs to be specific); measurability; relevance (there is a clear relationship between the indicator and CSAIP component); usefulness (the indicator captures information that helps move forward the implementation of the CSAIP); feasibility (data can be collected with reasonable and affordable effort); credibility (the indicator has been used and tested previously by other stakeholders); and distinctiveness (the indicator does not measure something already capturedby other indicators). This approach allows portfolio-level indicators to provide a high-level readout on CSAIP performance, whereas individual investment-level indicators can be tailored to specific programmatic goals. Portfolio-level, cross-investment results will be monitored against a limited number of primary indicators. These indicators will be (i) direct project beneficiaries; (ii) percentage change in productivity of selected agricultural commodities supported by the project; (iii) change in resilience using the Resilience Index Measurement and Analysis (RIMA-II) 111 approach; (iv) percentage change in mitigation using GHG intensity of the investment; and (v) execution of work plan and budget. These indicators will capture the progress toward the three pillars of climate-smartness through the four pathways to CSA in the results framework with internationally recognized indicators. 111 FAO. 2016. Resilience Index Measurement and Analysis-II (RIMA-II). Food and Agriculture Organization of the United Nations: Rome. 80 pgs PAGE 59 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Figure 12 Impact pathway for this CSAIP. Twelve investments (those selected for economic analyses in dark green) using five action areas lead to four intermediate outcomes and climate-smart (productive, resilient and low-emission) agriculture Robust, sustainable, resilient and low emission agricultural development IMPACT Increased Reduced Reduced Increased adaptive productivity exposure sensitivity capacity Adoption Use of risk Investment High Coherent of climate- management in inclusive performing, and OUTCOMES smart tools business modern and coordinated agricultural including models inclusive policy technologies insurance, markets and information environment by land climate info., viable value delivery managers and financial chains systems services Human capacity, physical infrastructure and enabling conditions strengthened ILLUSTRATIVE OUTPUTS Climate- Inclusive Training Seed Smart business Monitoring curriculum/ systems Livestock models systems programs Policy Climate- Value Centres of Capacitated analyses smart chain research & rural farms maps innovation advisory service Capacity ACTIVITIES Research Institutions & On-farm Market and building & infrastructure practices functioning knowledge advisory generation services Flood Recession Remote Non-Timber Crop-Livestock Sensing and Forest Products Agriculture Integration INVESTMENTS Program Geoinfomatics Soil Climate- Rice Restor- Climate- Millet- Climate Exten- Fertility Smart Intensi- ing de- Smart Sor- Services sion Wheat fication graded Veg. ghum- systems land Legume PAGE 60 Selection for individual investment indicators will take place during the full proposal development phase, dependent upon the investments funded. Indicators will track progress on all parts of the results framework above (impact, outcomes, output and activities) as well as the process of implementation (Table 12). Indicators will be selected based on expert and stakeholder consultation according to the road map detailed below. This gives potential opportunities to leverage existing capacities and efforts. Building synergies with existing systems would position this CSAIP to improve long-term sustainability of M&E efforts in Mali and contribute to cross-ministry data needs, such as reporting on progress toward the NDC. When necessary, additional indicators will be detailed, consulting existing lists first such as the CCAFS Programming and Indicator Tool112 to understand what other programs have been successfully implemented, and then creating unique indicators when necessary. Indicators of productivity and climate change mitigation, two of CSA’s three pillars are well established. Yields, profitability, and area under specific types of management, GHG emissions, etc. Are all commonly used to describe the state and changes in these outcomes. In many cases, Mali already collects this information. Thus, the CSAIP M&E strengthens and will be able to build upon the efforts when possible. Of the three CSA pillars, resilience is particularly challenging to monitor. Monitoring and evaluation activities under this CSAIP proposes to use the RIMA-II. The RIMA-II methodology groups 18 variables into four categories that reflect different facets of resilience and is a systematic approach for characterizing resilience to food insecurity. It collects information on five pillars: access to basic services, assets, social safety nets, sensitivity and adaptive capacity. These factors align well with three of the four pathways of impact with the CSAIP and are consistent with best practice for measurement of resilience113. Data collected with RIMA-II also align with many other indicators commonly associated with resilience such as the Coping Strategy Index and Food Consumption Score. The RIMA-II approach has the additional benefit that it has been adopted by the African Union for reporting under the AU Scorecard. With use of RIMA-II, this CSAIP will introduce and contribute to Mali’s broader reporting requirements. Furthermore, RIMA-II has an additional benefit: it may become integrated into other investments across Africa, and thus resilience would be measured in a consistent and comparable way. However, RIMA-II focuses solely on households. It does not measure anything related to ecological or institutional resilience. Additional indicators such as soil carbon (Mg/ha), tree cover (%) and perceptions of institutional capacity may be used to complement the RIMA-II for quantification of resilience 112 https://ccafs.cgiar.org/csa-programming-and-indicator-tool#.XBa2EBNKjUL 113 FSIN. 2014. Resilience Measurement Principles. World Food Program: Rome. 35 pgs PAGE 61 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Table 18 Modified logical framework for monitoring the CSAIP with select indicators for CSA objectives and relevant Investments RESULTS RELEVANT FRAMEWORK INDICATOR MEASURE CSA OBJECTIVE INVESTMENT COMPONENT Cross-Investment (program) indicators Beneficiaries c1.1 Number of beneficiaries # of women Triple-win All investments (disaggregated by gender and project and # of men component) beneficiaries Increased c2.1 Productivity of agricultural kg/ha Productivity All investments productivity commodities supported by the project; overlapping with i1.3 Improved c3.1 Farm resilience to food insecurity Resilience Resilience All investments resilience (RIMA-II) capacity index Contribution to c4.1 Greenhouse gas intensity of kg emission per Mitigation All investments climate change production (per investment) unit product mitigation Impact indicators (examples) Extension; soil services; non- timber forest value chains; floodplain; crop-livestock i1.1 Increased average farm income (dis- West African franc Productivity integration; aggregated by gender) (CFA)/year millet-sorghum system with legumes; vegetables; restoration; SRI; wheat Increased incomes Extension; climate services; floodplain; crop-livestock integration; i1.2 Increased productivity (by val- kg/ha Productivity millet-sorghum ue-chain commodity) system with legumes; vegetables; restoration; SRI; wheat i1.3 Reduced postharvest losses (by kg Productivity Vegetables target value-chain commodity) i2.1 Improved effectiveness of agro- meteorological services and extension Resilience, pro- Extension, cli- Qualitative scale systems in reducing exposure to climate ductivity mate services Reduced exposure risks (perceptions) to climate risks i2.2 Improved remote sensing and Resilience, pro- statistical governmental capacity for Qualitative scale Remote sensing ductivity programmatic and policy decisions Reduced sensitivity Resilience, pro- and vulnerability i3.1 Improved coping strategy index* Weighted score All investments ductivity to climate risks Increased adaptive Resilience, pro- i4.1 Improved adaptive capacity index Composite score All investments capacity ductivity PAGE 62 RESULTS RELEVANT FRAMEWORK INDICATOR MEASURE CSA OBJECTIVE INVESTMENT COMPONENT Outcome indicators (examples by action area) o1.1 Coherent and coordinated institu- tional arrangements bringing together climate information providers, agricul- qualitative scale Triple-win All investments tural research and extension, national policymakers and farmer representatives o1.2 Increased number of policies and National agro- plans incorporating climate information # of policies Triple-win meteorological and predictions (by policy type) system for CSA Crop-livestock Improved o1.3 Strengthened capacity of producer integration; mil- institutions and organizations to ensure farmers’ access let-sorghum-le- qualitative scale Triple-win infrastructure to resources and markets (by value gume systems; chain) vegetables; SRI; wheat o1.4 Improved infrastructure for op- timized flood recession agricultural qualitative scale Triple-win Floodplain practices Non-timber for- o1.5 Improved physical infrastructure est value chains; for postharvest processes (including qualitative scale Triple-win vegetables; processing) wheat Crop-livestock o2.1 Increased number of producers, % of total pro- integration; mil- land managers and agribusinesses ducers, land man- let-sorghum-le- Triple-win adopting CSA technologies (by val- agers, agribusi- gume systems; ue-chain product and by gender) nesses vegetables; SRI; wheat Crop-livestock integration; mil- o2.2 Increased area under CSA practices % of total agricul- let-sorghum-le- Triple-win and technologies tural land gume systems; vegetables; SRI; wheat o2.3 Increased number of producers % of total pro- and land managers using integrated soil ducers and land Triple-win Soil services Increased adoption fertility management (ISFM) strategies managers of on-farm CSA (by gender) technologies o2.4 Increased number of producers and % of total pro- land managers using land restoration ducers and land Triple-win Restoration practices on their farms (by gender) managers o2.4 Increased number of producers and % of total rice land managers using systems of rice producers and Triple-win SRI intensification (by gender) land managers Non-timber for- est value chains; # of hectares cov- crop-livestock o2.5 Increased territory covered by ered by forests; integration; mil- Mitigation forests % of total land in let-sorghum-le- the country gume systems; vegetables; SRI; wheat PAGE 63 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN RESULTS FRAME- RELEVANT IN- WORK COMPO- INDICATOR MEASURE CSA OBJECTIVE VESTMENT NENT Non-timber for- est value chains; Investments in crop-livestock inclusive business o3.1 Increased investments in inclusive # of investments, integration; mil- models, markets business models, markets and value value of invest- Triple-win let-sorghum-le- and viable value chains (by value chain) ment (CFA) gume systems; chains vegetables; SRI; wheat o4.1 Improved national capacity for Resilience, pro- maintaining and leveraging available qualitative scale Climate services ductivity climate information systems Non-timber for- Effective research est value chains; and knowledge o4.2 Improved R&D systems for develop- Resilience, pro- millet-sor- mechanisms and qualitative scale ing climate-smart value chains ductivity ghum-legume tools integration; vegetables o4.3 Improved R&D systems for opti- Resilience, pro- qualitative scale Floodplain mized flood recession infrastructure ductivity o5.1 Improved quality and quantity of # of recommen- Resilience, pro- Extension, soil CSA-informed recommendations deliv- dations; qualita- ductivity services ered to producers by farm advisors tive scale o5.2 Improved capacity of advisory offi- Extension, Resilience, pro- cers to deliver relevant, timely informa- qualitative scale climate services, ductivity tion to farmers (by information type) soil services, crop-livestock o5.3 Improved capacity of producers, integration, mil- land managers and agribusinesses to Resilience, pro- let-sorghum-le- qualitative scale use the information delivered (regarding ductivity gume systems, climate, soils, etc.) vegetables Effective capacity building and advi- o5.4 Beneficiaries’ satisfaction with infor- Likert scale (very sory services mation services provided (disaggregated unsatisfied, un- Extension, Resilience, pro- by gender and service type; referring to satisfied, neutral, climate services, ductivity timeliness, usefulness, relevance and satisfied, very soil services frequency of services) satisfied) o5.5 Improved national capacity (ex- tension, research, producers) to restore qualitative scale Triple-win Restoration degraded lands (by actor type) o5.6 Improved national capacity (exten- sion, research, producers) to scale SRI qualitative scale Triple-win Restoration (by actor type) Outputs/results indicators (examples) r1.1 Number of new varieties/breeds on Resilience, pro- Millet-sorghum, # market (by value-chain commodity) ductivity vegetable pro- Seed systems r1.2 Number of users of new varieties/ Resilience, pro- duction, wheat # breeds (by value-chain commodity) ductivity r2.1 Number of producers, land man- Resilience, agers and/or agribusinesses using # productivity, crop-livestock integrated systems (by mitigation actor and gender) Crop-livestock Climate-smart r2.2 Proportion of producers, land man- integration livestock agers and/or agribusinesses receiving Resilience, training on climate-smart practices % productivity, and tools for crop-livestock integrated mitigation systems (by actor and gender) PAGE 64 RESULTS FRAME- RELEVANT IN- WORK COMPO- INDICATOR MEASURE CSA OBJECTIVE VESTMENT NENT r3.1 Number of value-chain maps devel- Resilience, pro- # oped (by value-chain commodity) ductivity Non-timber for- % women; % est value chains, o3.2 Proportion of women and youth en- youth (from total crop-livestock Inclusive business gaged in climate-smart value chains (by Resilience, pro- women and youth integration, models value-chain commodity and value-chain ductivity engaged in agri- millet-sorghum, stage) culture) vegetable pro- duction, wheat r3.2 Ownership structure of the business Resilience, pro- qualitative (by gender) ductivity r4.1 Coverage of national climate obser- % of national Resilience, pro- vation network territory ductivity r4.2 Number of weather stations in- Resilience, pro- # stalled and maintained ductivity r4.3 System to integrate historical weath- Resilience, pro- er data with new weather data as well as # of systems ductivity agricultural and phenological data r4.4 Number of services available to Remote sensing, communicate information to farmers (by national agrocli- Monitoring sys- Resilience, pro- service type, such as SMS or voice call # matic informa- tems ductivity via mobile, radio broadcasting, web-GIS tion system, soil portal,newsletters, etc.) services r4.5 Number of producers using in- formation services (disaggregated by Resilience, pro- # gender and service type, such as mobile ductivity vs. non-mobile) r4.6 Frequency of access to information services by producers (disaggregated by times/month or Resilience, pro- gender and service type, such as mobile times/season ductivity vs. non-mobile) Resilience, pro- r5.1 Ratio of advisory officer to producers ratio ductivity r5.2 Number of trainings and number Resilience, pro- of farm advisors attaining trainings in #, type ductivity cutting-edge CSA Training/curricu- r5.3 Number and type of systems avail- Extension lum programs able for dissemination of CSA infor- Resilience, pro- #, type mation to producers (field schools, ICT, ductivity additional advisory satellite offices, etc.) r5.4 Frequency of access to CSA infor- times/month or Resilience, pro- mation by producers (disaggregated by times/season ductivity gender) PAGE 65 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN RESULTS CSA OBJEC- RELEVANT FRAMEWORK INDICATOR MEASURE TIVE INVESTMENT COMPONENT Outputs/results indicators (examples by investment) ir1.1 Functional geospatial information # of functional Triple-win National remote system (GIS) to support climate-smart systems in place sensing and ap- environmental and agriculture manage- plied geomatics ment ir.1.2 Proportion of producers, land man- % of all produc- Triple-win agers and agribusiness receiving training ers/ land man- Remote sensing on understanding and leveraging the agers/ agribusi- information nesses ir1.3 Proportion of active users of geomat- # Triple-win ics information (by information system type and by user type: land managers, agricultural producers, farm advisors and policymakers) ir2.1 Ratio of farm advisors (extension ratio Resilience, pro- Extension officers) to producers ductivity ir2.2 Number of trainings and number of #, type Resilience, pro- farm advisors (extension officers) attain- ductivity ing trainings in cutting-edge CSA aspects Extension ir2.3 Frequency of access to CSA infor- times/month or Resilience, pro- mation by producers (disaggregated by times/season ductivity gender) ir2.4 Number and type of systems avail- #, type Resilience, pro- able for dissemination of CSA information ductivity to producers (field schools, ICT, additional advisory satellite offices, etc.) ir3.1 Coverage of national climate obser- % of national Resilience, pro- Climate services vation network territory ductivity ir3.2 Number of weather stations installed # Resilience, pro- and maintained ductivity ir3.3 Proportion of producers using % of agricultural Resilience, pro- National agrocli- climate advisory services (disaggregated producers ductivity matic information by gender and service type: e.g., mobile system (SMS, call) services; radio broadcasting; web-GIS portal; newsletters, etc.) ir3.4 Frequency of access to climate advi- times/month or Resilience, pro- sory services by producers (disaggregated times/season ductivity by gender and service type: mobile vs. non-mobile) ir4.1 Functional soil information services # Resilience, pro- Soil services (SIS) developed for rapid and low-cost ductivity analysis of soil properties and plant nutrients and for recommending loca- tion-based management practices Soil services ir4.2 Proportion of producers using SIS for % of all agricultur- Resilience, pro- implementing location-based farm man- al producers ductivity agement practices (by SIS type: mobile, non-mobile) PAGE 66 RESULTS CSA OBJEC- RELEVANT FRAMEWORK INDICATOR MEASURE TIVE INVESTMENT COMPONENT ir5.1 Number and area of multipurpose #, ha Triple-win Non-timber for- agroforestry parklands established est value chains ir5.2 Number and type of species of trees #, type Triple-win available and accessible to producers and land managers for establishing parklands Non-timber forest ir5.3 Number and type of actors (individ- #, actor type Triple-win value chains uals, private companies, etc.) engaged in non-timber forest value chains (by value-chain product) ir5.4 Number of women producers and # Triple-win processors engaged in non-timber forest value chains (by value-chain product) ir6.1 Number and type of infrastructure #, type Resilience, pro- Floodplain projects developed for optimized flood ductivity recession agricultural practices ir6.2 Proportion of producers and/or % Resilience, pro- agribusinesses benefiting from improved ductivity infrastructure for optimized flood reces- Floodplain sion agricultural practices (by actor type and infrastructure type) ir6.3 Number and type of actors (civil and #, type of actor Resilience, pro- private sector) engaged in improved infra- ductivity structure for optimized flood recession ag- ricultural practices (infrastructure project) ir7.1 Number of producers, land managers # Triple-win Crop-live- and/or agribusinesses using crop-live- stock-integra- stock integrated systems (by actor and tion gender) Crop-livestock integration ir7.2 Proportion of producers, land man- % Triple-win agers and/or agribusinesses receiving training on climate-smart practices and tools for crop-livestock integrated sys- tems (by actor and gender) ir8.1 Number of producers, land managers # Resilience, pro- Millet-sor- and/or agribusinesses using millet-sor- ductivity ghum-legume ghum-legume integrated systems (by integration actor and gender) Millet-sor- ghum-legume ir8.2 Proportion of producers, land man- % Resilience, pro- integration agers and/or agribusinesses receiving ductivity technical assistance related to millet-sor- ghum-legume integrated systems (pro- duction, storage, processing) (by actor) ir9.1 Proportion of women and youth re- % women; % Resilience, pro- Vegetable ceiving technical assistance in vegetable youth (from total ductivity production, storage and/or processing women and youth engaged in vege- table production) Vegetable pro- ir9.2 Number of vegetable post-produc- # Resilience, pro- duction tion (processing) facilities available and ductivity functional ir9.3 Number of vegetable producer # of producer Resilience, pro- organizations established or strength- organizations; # ductivity ened and number of members of each of members/orga- producer organization nizations PAGE 67 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN RESULTS FRAME- RELEVANT IN- WORK COMPO- INDICATOR MEASURE CSA OBJECTIVE VESTMENT NENT ir10.1 Number and proportion of extension #, % out of total officers benefiting from training on land Triple-win extension officers restoration practices/methods ir10.2 Proportion of producers/ land managers benefiting from training on land % Triple-win restoration practices/methods Restoration Restoration ir10.3 Value of investments in land resto- CFA Triple-win ration # of hectares, % of restored ir10.4 Area and proportion of degraded land out of total Triple-win land restored agricultural land degraded ir11.1 Proportion of extension agents bene- % Triple-win fiting from training on SRI ir11.2 Proportion of producers/ land man- System of rice agers benefiting from technical assistance % Triple-win SRI intensification on SRI (SRI) ir11.3 Number of SRI producer organiza- # of producer tions established or strengthened and organizations; Triple-win number of members of each producer # of members/ organization organization ir12.1 Proportion of producers/ land man- agers receiving training on climate-smart Resilience, pro- % practices and tools for wheat production ductivity and processing Wheat Wheat ir12.2 Number of wheat producer organi- # of producer zations established or strengthened and organizations; Resilience, pro- number of members of each producer # of members/ ductivity organization organization M&E process indicators p1.1 Number of investments and projects # - All investments approved for implementation Organizational p1.2 Number of units/divisions with M&E # - All investments structure responsibilities in place p1.3 Number of M&E frameworks developed # - All investments (for each investment area and project) p2.1 Number of staff carrying out work # - All investments related to M&E of CSAIP p2.2 Level of human capacity to carry out M&E activities (design work plan, carry out Human and Qualitative scale - All investments routine monitoring, compile and manage technical ca- databases, disseminate information) pacity p2.3 Level of technical capacity to carry out M&E activities (design work plan, carry out Qualitative scale - All investments routine monitoring, compile and manage databases, disseminate information) p3.1 Total budget allocated for M&E of CFA - All investments CSAIP Budget execu- tion rate p3.1 Percentage of M&E budget spent on % out of total - All investments M&E activities M&E budget PAGE 68 The M&E information will be relevant for government agencies, financial institutions, subnational agencies and communities, and other decision makers. The diversity of types of information and stakeholders using the information will dictate the creation of a CSAIP-specific information management system (IMS). On the back end, the system will contain secure storage for data and data-collection protocols and other documentation. On the front end, accessible through the internet, will be a dashboard to enable easy access to data and information for decision-making. The IMS will be implemented in a flexible way via principles of human-centered design114, with users of the information at the center of the development process. In this way, the IMS can account for the diversity of information needs and the diversity of actors, local to global. The CSAIP M&E system will be consistent with the M&E systems used under the Strategic Framework for Growth and Poverty Reduction and the National Agricultural Investment Plan (NAIP). Proposed outcome areas of the CSAIP align with the affected areas described in the two policies. Outcome in the CSAIP are targeted to specific issues that map under the wider agricultural outcomes in the existing programs. The SFGPR and NAIP and outcome areas are supported by at least one of the five outcome areas of the CSAIP. It is not possible to map outputs/products between the two policies and the CSAIP because the components of the CSAIP are only concepts at this time. However, based on the activities and component areas described already, it is reasonable to envisage that much of, if not all, of the CSAIP outputs will contribute to the products targeted by these other policies. 114 IDEO. 2015. The field guide to human-centered design. IDEO: Canada PAGE 69 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Table 19 Coherence among the Strategic Framework for Growth and Poverty Reduction, National Agricultural Investment Plan and Climate-Smart Agriculture Investment Plan Outcomes STRATEGIC FRAMEWORK FOR CLIMATE-SMART AGRI- GROWTH AND POVERTY REDUC- NATIONAL AGRICULTURE INVESTMENT PLAN CULTURE INVESTMENT TION 2012–2017 (SFGPR; FRENCH: 2015–2025 (NAIP; FRENCH: PNISA) PLAN (CSAIP) CSCRP) Outcome (objec- Outcome Outputs (results) Outputs (results) Outcome tives) Axis 1: Accel- o1.1 Developed o3. Improved 3.1-3.3 Developed and strength- o2. Increased adop- erated eco- and diversified productivity and ened crop, livestock, fisheries tion of on-farm cli- nomic growth agricultural pro- competitiveness of and aquaculture value chains mate-smart agricultural with diversi- duction agro-silvopastoral (improved access to inputs, (CSA) technologies fied bases sectors economic valuation, advisory support, production and income o3. Investments in in- diversification) clusive business models, markets and viable value 3.5.1-3.5.3 Certification and label- chains ing standards developed o4. Effective research 3.6.1 Climate change mitigation and knowledge mecha- and adaptation measures devel- nisms and tools oped and adopted 3.7.1-3.7.3 Institutional framework for agropoles management de- veloped and agribusiness clusters made operational o1.3 Improved o2. Increased agri- 2.2.1 Operational national, coverage of and cultural investments, regional and local funds for agri- access to credit especially in land cultural support (microfinance) tenure systems, natu- and diversified ral resource manage- 2.2.2 Improved credit access finance options ment and irrigation mechanisms (credit products, and water manage- guarantees, bonuses, etc.) ment systems 2.1.2 Improved rural cadaster (planning, registration) 2.3.1 Restored soils and conserved water sources 2.3.2 Forests and wildlife reserves preserved and established 2.4.1–2.4.10 Agriculture infrastruc- tures established and managed (e.g., for irrigation schemes, sanitation, processing, marketing, etc.) 2.5.1 Improved access to mecha- nized farm equipment o1.4 Universal o1. Strengthened 1.6.1 Functional mechanisms and access to quality capacity of actors in tools of information, communi- information and agricultural develop- cation and documentation (SIFA, communication ment SIFOR) technologies PAGE 70 STRATEGIC FRAMEWORK FOR CLIMATE-SMART AGRI- GROWTH AND POVERTY REDUC- NATIONAL AGRICULTURE INVESTMENT PLAN CULTURE INVESTMENT TION 2012–2017 (SFGPR; FRENCH: 2015–2025 (NAIP; FRENCH: PNISA) PLAN (CSAIP) CSCRP) Outcome (objec- Outcome Outputs (results) Outputs (results) Outcome tives) Axis 2: Access o2.3 Improved ac- o4. Consolidated 4.1.1-4.1.5 Improved agricultural o4. Effective research to quality cess to technical training and research research and technology and knowledge mecha- social services and professional in support of agri- nisms and tools (equitable training cultural production 4.2.1-4.2.3 Improved profession- access and systems al and continuous training and o5. Effective capacity strengthened agricultural employment building and advisory long-term services bases) o2.4 A satisfactory o5. Improved social 5.1.1 Food and nutrition security nutritional status protection to respond policy developed for every Malian to the problem of food and nutritional 5.2.1 Operational food safety insecurity committees and early warning system 5.2.2 Diversified food stocks established 5.3.1 Improved practices for man- aging food insecurity 5.3.2 Nutritional education pro- grams implemented Axis 3: o3.4 Coordina- o1. Strengthened 1.1–1.4 Strengthened human and o1. Improved institutions Strengthened tion, formulation capacity of actors in financial capacity of public agri- and infrastructure institutions and implemen- agricultural develop- cultural structures, professionals, and gover- tation of policies ment activities, with civil society and communities o5. Effective capacity nance and sectoral particular emphasis to carry out agriculture-related building and advisory development on monitoring and activities services programs, and evaluation improved moni- 1.5.1-1.5.4 Operational sectoral re- toring and evalu- sults-bases M&E system (SEGOR) ation systems o3.6 Improved 2.2.1-2.2.3 Sector financing mech- mobilization, sec- anisms established tor allocation and management of public resources PAGE 71 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN A road map Investment success will be monitored against activities, outputs and outcomes that will feed into the four pathways to impact derived from the theory of change (see Figure 12). This results framewo Additional information is needed to define the components of the M&E system, outline the roles and responsibilities of participating institutions (i.e., make institutional arrangements), create the tools for implementation, establish data management protocols, and refine logistics. A recent multicountry analysis recommends 11 activities to elaborate the M&E (Figure 13) 115. These action help define the space for the M&E system and ensure long-term sustainability. Here the suggested activities are formed into a road map to create and implement the CSAIP M&E system. The list of indicators in Table 13 shows a first appraisal of potential opportunities for Mali based on current levels of elaboration in the concept notes. The next steps require that the list of indicators be refined and aligned according to the needs of users of the information. This needs to take place in a participatory way using both one-on-one interviews with key informants and workshops with government, donors and implementation partners such as local government authorities and persons expected to collect, compile and analyze the information. As part of the assessment, a detailed analysis of existing data systems describing the implementation arrangements and information flows (workflows and permissions, etc.) will be outlined. The results of the assessment—describing user needs, indicators and existing systems—provide the input to elaborate the CSAIP M&E systems, which will be formalized in an M&E manual. The manual will describe the who, what, how and when of data collection, analysis and reporting. By and large, it is expected that M&E activities will be conducted by staff working on/with CSAIP implementation and implementers including extension agents, local government agencies, staff and others, with operation being overseen by an M&E coordinator. External evaluators will be engaged for auditing and to conduct specific evaluations such as impact evaluations. The CSAIP will use a set of M&E approaches (farm trials, surveys, qualitative assessments) that mix repeated measurements of progress and specific impact evaluations using experimental and quasi-experimental approaches on key questions. Monitoring for both types will be based on initial baselines set by household surveys, field sampling and earth observation with remote sensing, depending on the indicator and user need. This baseline, which will be differentiated based on stakeholder group, will characterize the initial state of households, farms, landscapes and value-chain actors and provide an understanding of local perceptions of current systems, services and tools for improved productivity and resilience. The process to carry out the M&E activities will need to be formalized into data collection templates and then codified into the M&E online database system, both of which will need to be designed, iteratively field tested, validated by investment partners and revised when needed. The capacity assessment will also identify gaps, including where it will be necessary to recruit CSAIP-specific M&E staff and when it will be possible to simply strengthen capacities of existing personnel. The manual describes the structure of the M&E system; specific actions are needed to move into practice. First, an initial capacity assessment will be carried out with CSAIP staff (including extension agents, local government agencies, etc.) to understand existing capacities to track and report on planned outcomes, outputs and aligned indicators. This will help ensure a results-based reporting 115 Rosenstock TS, Wilkes A, Nowak A et al. 2018. Measurement, reporting and verification of climate-smart agriculture: Change of perspective, change of possibilities? Findings from a country-driven assessment of needs, systems and opportunities. CCAFS InfoNote. PAGE 72 approach throughout the CSAIP implementation period. The capacity assessment will explore: (i) organizational structures (existing or potential specialized M&E units, M&E work plans and guidelines formulated for each investment, etc.); (ii) technical and human capacities (full-time staff available to carry out M&E functions, clear M&E responsibilities and division of labor, M&E knowledge and competencies, etc.); (iii) financial resources available for preparatory activities, data collection and management, data quality control and reporting; and challenges and weaknesses regarding M&E capacity. Findings from the M&E capacity assessment survey tool will guide and strengthen the implementation, monitoring and evaluation of CSAIP activities, expected results and impacts. With improved capacity, CSAIP participants will be ready to implement M&E. Assessment activities will guide subsequent capacity building efforts in monitoring and evaluation and beyond for the relevant ministries and implementing partners. Though the funds for establishment of CSAIP M&E activities (assessments, capacity strengthening, data systems and data collection, etc.) will be derived from the CSAIP budget, CSAIP M&E will track and analyze costs and benefits of improved M&E to build the case for investment in such activities beyond the scope of the program. Governments and development partners require information on activities and effectiveness. Nearly all institutions track key performance indicators of various types and use these values to allocate effort. Given that the indicators for the CSAIP intersect with other institutional needs such as budget allocations to agriculture, GHG emissions of the agriculture, land use and forestry sector, etc., it is envisaged that the CSAIP M&E will play a catalytic role in strengthening the use of data in decision-making. Specific analyses that investigate the value of the information for identifying effective programming and reducing the data collection burden will be embedded in the M&E systems. Figure 13 Eleven steps to create a coherent CSA M&E system based on finding from a country-centric assessment of needs, systems and opportunities Conclusion The CSAIP provides direction for M&E activities, but additional time and actions are needed to detail the M&E systems and approaches that will be used. This is in part due to the lack of clarity regarding which investments will be funded. Once these decisions are made, subsequent activities—including assessing complementary systems, indicators, capacities and implementation arrangements; detailing a manual of who, how and when; strengthening capacity; and making the financial case for M&E—will help build long-term sustainability of the investments in M&E under the CSAIP, contributing to improved value for money and ultimately the efficiency and efficacy of the PAGE 73 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN CSAIP. It should be noted that the CSAIP M&E system will serve purposes beyond CSA. The systems— including indicators, roles and responsibilities and the information monitoring system (IMS)— will align with those of other programs and policies such as the NDP, NAIP and NDC. In this way, the investments in M&E will build the institutional and human capacity for using data for decisions and helping the Government of Mali tell robust and evidence-based stories of change with the CSAIP. PAGE 74 Annex A: Climate Smart Agriculture Investment Plan Methodology Article 2 Agriculture for Development, 30 (2017) ‘CSA-Plan’: strategies to put Climate-Smart Agriculture (CSA) into practice Evan Girvetz, Caitlin Corner-Dolloff, Christine Lamanna and Todd Rosenstock Evan Girvetz is a senior scientist at the International Centre for Tropical Agriculture (CIAT), leading projects for the CGIAR Research Programme on Climate Change, Agriculture and Food Security (CCAFS). His research spans climate-smart agriculture (CSA), sustainable agricultural intensification, ecosystem services, environmental decision support, water resources management, and nature conservation planning. e.girvetz@cgiar.org Caitlin Corner-Dolloff was a climate change adaptation specialist at the International Centre for Tropical Agriculture (CIAT) while conducting the research related to this publication. She is now an international agriculture development programme manager at the United States Department of Agriculture. C.cornerdolloff@gmail.com Dr Christine Lamanna is a climate-change ecologist and decision analyst at the World Agroforestry Centre (ICRAF), based in Nairobi, Kenya. Her work is focused on targeting climate-smart agricultural interventions throughout Africa to inform national policies. C.Lamanna@cgiar.org Dr Todd Rosenstock is an environmental scientist with the World Agroforestry Centre (ICRAF) where he investigates how smallholder agriculture affects the environment and society and vice versa. Dr. Rosenstock currently works on smallholder farming systems in East Africa and Latin America. t.rosenstock@cgiar.org Abstract that promotes three objectives: sustainably increasing productivity; building the resilience of farming systems; and Large-scale investment is needed to create climate-smart reducing greenhouse gas emissions, where possible (FAO, agriculture (CSA) systems. While many government and 2013). CSA does not prescribe interventions: instead, climate development agencies are integrating CSA into their policies, risks are addressed through tackling trade-offs and synergies programmes, plans and projects, there is little guidance for between the three objectives (Rosenstock et al, 2016). This operational planning and implementation on ways to be then separates CSA from other approaches to agricultural climate-smart. Here we present ‘CSA-Plan’. CSA-Plan frames development that either specify practices or technologies, such actions needed to design and execute CSA programmes into as conservation agriculture or agroforestry. Thus, CSA four components – (i) situation analysis, (ii) targeting and requires identifying what is climate-smart for the biophysical, prioritising, (iii) programme design, and (iv) monitoring and agricultural, and socio-economic context of a given place. evaluation. Each component yields concrete information to Major development investors are rallying behind CSA, with operationalise CSA development, separating it from traditional large investments being planned or made by the international agriculture development. Already, CSA-Plan has shown the financial institutions and aid organisations, including the capacity to change the discussion around CSA Green Climate Fund, the International Fund for Agricultural implementation. With iterative co-development, the Development (IFAD), and international aid agencies such as approaches will become ever more useful, relevant and the United Kingdom Department for International legitimate to governments, civil society and the private sector Development (DFID) and the United States Agency for alike. International Development (USAID). National governments and their development partners are looking to move forward with large-scale CSA implementation. The private sector is Introduction also recognising the importance of making their supply and value chains climate-smart, as evidenced by the engagement Climate-smart agriculture (CSA) is an approach to agriculture of the World Business Council for Sustainable Development in 12 PAGE 75 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Agriculture for Development, 30 (2017) Article 2 CSA. New multi-sector CSA partnerships have formed, such policies, and initiatives, a fundamental understanding is as the Global Alliance for Climate Smart Agriculture (GACSA) needed of the context where they will be implemented. This and seven regional/national alliances, with goals of sharing includes not only information on the farming activities, but knowledge, supporting investments, and scaling-up on stakeholders’ goals, constraints, livelihood strategies, etc. implementation. A CSA situation analysis should provide information on the climate risks and impacts, but more widely the agricultural, Putting CSA into practice requires knowing what is climate- political, social, and economic conditions for which CSA smart in different locations and designing projects to fit the actions are being taken. The situation analysis specifically context for implementation. What works for one type of farmer identifies the entry points for CSA actions by looking at: (i) the may not work for another (eg related to labour availability), importance of agriculture in society; (ii) risks and and a CSA practice with desirable outcomes in one location vulnerabilities of the agricultural sector; (iii) existing and does not necessarily deliver desirable outcomes under all agro- promising CSA practices and services; (iv) institutional and ecological conditions. There are often trade-offs amongst the policy environment related to CSA – both barriers and three goals of CSA – sustainable productivity, resilience, and enabling; and (v) finance opportunities and challenges for CSA mitigation – so stakeholder priorities are important to consider initiatives. An engagement plan is needed to ensure key when selecting which CSA practice to implement. There is a stakeholders are part of the process from the beginning, and need for assessing value-for-money, climate-smartness, that it is inclusive. At this stage, a long list of current and development impact, and scaling potential to establish effective promising CSA practices and services relevant to specific CSA programmes. One major problem is that decision-makers agricultural systems and agro-ecological conditions can be do not have frameworks in place that link science and identified for further analysis. Identification of finance stakeholder engagement to plan, implement, and monitor CSA mechanisms and institutional and policy entry points to achieve impact at the scale needed. demonstrates current alignment with public and private sector This paper presents an operational guide for putting CSA policies and investment plans with CSA. A range of different programming into practice – ‘CSA-Plan’ – which contains four specific CSA approaches that have been/can be used for main components for CSA planning and implementation situation analysis include the International Centre for Tropical (Figure 1): (i) situation analysis; (ii) prioritising interventions; Agriculture (CIAT)/CCAFS CSA Profiles, which summarise the (iii) programme design and implementation; and (iv) CSA context at national or sub-national levels (World Bank & monitoring, evaluation, and learning. A suite of approaches CIAT, 2015) and FAO’s scoping studies for CSA East Africa are available for each component, and can be used to answer (FAO, 2015), among many others. The commonality being specific challenges that obstruct planning and progress. The that they provide a foundation for CSA actions that can address components of CSA-Plan can be implemented sequentially or climate risks, engage stakeholders, and enable further analyses by themselves depending on stakeholder needs. Underlying and planning (Figure 2). CSA-Plan is a suite of CSA indicators to provide an evidence base to the decision-making, implementation, and monitoring components. Moreover, given the participatory nature of the approaches, capacity strengthening is critical for success and broad use. Figure 2. National stakeholder workshop in Nairobi on responding to climate shocks at community level. New climate-smart profiles offer Kenya a roadmap to implement climate-smart agriculture at country level. (Photo: Georgina Smit (CIAT)) Figure 1. CSA-Plan Framework includes Situation Analysis, Prioritising Interventions, Programme Design and Implementation; Monitoring and Evaluation. Different types of Indicators are important to utilise across the Targeting and prioritising to identify CSA-Plan components to measure climate-smartness, development outcomes, readiness and scaling potential, and project/programme process. Engagement CSA investment portfolios and capacity strengthening are needed for application of the CSA-Plan information and approaches within the context of agricultural development. A range of technological, institutional, and policy options for climate-smart interventions exist that have varying impacts on the CSA goals and economic costs and benefits. CSA-Plan’s Situation Analysis targeting and prioritising component builds on this premise by using advanced analytical techniques, nested within Before any decisions can be made on CSA programmes, participatory processes, to narrow down an extensive list of 13 PAGE 76 Article 2 Agriculture for Development, 30 (2017) possible practices, services, and policies to a range of best-fit mechanism for facilitating uptake of CSA interventions. options that provide value for money and can be scaled-out. Innovative agricultural business models, such as outgrower or The outcome of this step is a stakeholder-selected and contract farming schemes, can be a mechanism for scaling of evidence-based portfolio of high-interest CSA options. CSA interventions, such as has occurred in Kenyan tea outgrower schemes (Milder et al, 2015). Climate services, CSA-Plan puts forward a general prioritisation approach based warning systems, and agro-advisory services provide means on the CIAT/CCAFS CSA Prioritisation Framework (Campbell for providing timely and site-specific information to farmers et al, 2016; Sain et al, 2016; Corner-Dolloff et al, 2017). to help them respond to weather and climate (Hewitt et al, Stakeholders first assess the context for the CSA intervention 2012). Technical guides and manuals for implementation are in question and set criteria for prioritisation. This includes a needed for guiding development projects in how to implement set of specific measurable indicators under each of the three interventions on the ground under different conditions (Rioux CSA goals. A long list of potential CSA interventions – et al, 2016). Climate risk can be offset using weather-based practices, services, and policies – is then established to provide index insurance products for crops and livestock (Miranda & a starting point for prioritisation. Next, through stakeholder and expert interrogation of indicator analyses of the potential Mulangu, 2016). Depending on the social, environmental and outcomes of CSA interventions, the long list is narrowed down economic context of the location, different programme models to a short list of high interest interventions for further analysis. and tools will be useful or not. All in all, programme design is a wide area of work focused on engaging stakeholders in Then, the selected practices are evaluated for their economic designing interventions that work for them. costs and benefits, implications for gender and social inclusiveness, adaptability, and scalability. And finally, through stakeholder and expert input, ensuring inclusivity, investment portfolios are developed either for different farmer types, Monitoring, evaluation, and learning different implementers, or different scales, aiming to maximise CSA-Plan’s monitoring, evaluation, and learning (ME&L) or minimise specific synergies and tradeoffs across the component develops strategies and tools to track progress of portfolio. implementation, evaluate impact, as well as facilitate iterative A range of specific CSA prioritisation tools and approaches learning to improve CSA planning and implementation. have been developed that can be used (Shikuku et al, 2017; CSA-Plan’s ME&L delivers processes and products to support Mwongera et al, 2017; Notenbaert et al, 2017). Different tools achieving and documenting programme goals and adaptively and processes can be used for different types of stakeholders managing implementation. However, there are many challenges and levels of decision-making (eg national vs community), in measuring CSA. It has multi-objective complexity, given the allowing implementers to tailor their prioritisation approach multiple goals of CSA. The scale of impact can range from the and successfully engage target stakeholders. farm to the national or international level. There are often multiple institutions involved in ME&L, each of whom might Programme design and implementation bring their own priorities and approaches. The CSA-Plan approach considers various aspects of ME&L to Programme design and implementation supports taking address these challenges. The programme and stakeholder prioritised CSA actions to scale. It provides specific priorities are used to determine specifically what the ME&L is information that underlies the implementation of the addressing. Then specific indicators must be selected and interventions selected. It is important to have a 'theory of linked to priority outcomes using tools such as the CSA change' for how the intervention will lead to positive impact; Indicators Database (Quinney et al, 2016). There are CSA a common pitfall is to simply come up with a list of outcome indicators needed to measure medium/long-term interventions rather than strategically designed interventions impact on the three CSA objectives – sustainable productivity, that can be scaled-up to many beneficiaries. The diversity of adaptation/resilience, and greenhouse gas mitigation. There products, users, and implementation conditions dictates are indicators related to broader development outcomes (eg equally diverse approaches and models. Principles of co-design Sustainable Development Goals), such as incomes, nutrition, can be useful to innovate in product design, iterate with end- markets, etc. There are readiness and scaling potential users to field test, refine and improve materials, and share indicators reflecting the capacity to plan, implement and products on learning platforms to facilitate access by others. monitor investments and activities related to CSA implementation that help measure the ability for the There are a range of approaches and tools to use for programme design and implementation, including climate- intervention to be scaled-up. Finally, there are project and programme process indicators to monitor programmes for smart value chain models, outgrower models, extension, meeting implementation process objectives. It is important to farmer field schools, early-warning systems, financial note that even though indicators clearly are important for the mechanisms, weather-based insurance, and technical guides ME&L, these indicator sets are important across the different for technology implementation, among others. For example, components of CSA-Plan. the Link 2.0 methodology (Lundy et al, 2014) is one such approach that has been used for designing innovative and Specific tools and instruments have been developed for inclusive climate-smart value chain business models. monitoring sets of indicators. The CGIAR-CCAFS Monitoring Financial savings approaches, such as village savings and loan Instrument for Resilience can be used for tracking changes in associations (Allen & Staehle, 2007), provide simple savings resilience in agricultural projects and programmes (Hills et al, and loan facilities in a community that can provide a 2015). Operationalising the concept of resilience (ie the ability 14 PAGE 77 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Agriculture for Development, 30 (2017) Article 2 to withstand change, stresses and shocks) is a challenge, and Kenya CSA Project. Prioritisation of CSA intervention areas this tool demands tracking and reporting changes efficiently is then being developed within counties, and specific and using the information commonly available within interventions being designed and implemented within the development initiatives. Similarly, the Toolkit for the county Common Interest Groups and Public-Private indicators of resilience in socio-ecological production Partnerships developing innovative implementation plans. landscapes and seascapes provides practical guidance for Responding to the needs of the stakeholders and decision- engaging local communities in adaptive management and can makers is critically important if evidence is to be translated increase their capacity to respond to pressures and shocks. into policies and programmes, but this is also a challenge to Monitoring CSA can also be done in a holistic, multi-objective accomplish. Each set of stakeholders requires slightly different way. For example, the Rural Household Multi-Indicator information and processes. For this reason, the CSA-Plan Survey (RHoMIS) provides a rapid and cost-effective components are not static, but rather CSA-Plan provides a instrument to track changes in poverty, gender equity, range of information, tools, and approaches that can be nutrition, climate and productivity outcomes – all measures modified to address the needs of the specific stakeholders, with of climate-smartness (van Wijk et al, 2016). RHoMIS is new tools and approaches added as they become available. modular, so implementers can select or add indicators which Capacity strengthening of key institutions is also needed as fit their context and needs, and has been used in Africa, Latin evidence presented is only helpful if decision-makers are able America and Asia. Specific attention should be paid to gender, to use it. Training manuals and workshops are useful starting a critical cross-cutting part of CSA, and monitoring can also points for capacity building interventions. Given that famers be done using approaches such as the Woman’s and others at the local level are the ones actually taking Empowerment in Agriculture Index (Johnson & Diego-Rosell, decisions, there is a need for information, tools and approaches 2015). to be accessible across levels to operationalise mainstreaming of CSA into both on-farm business planning and larger-scale Engagement and capacity investments aimed at catalysing action. While the number of examples is growing, there is great opportunity for increased strengthening uptake of the CSA-Plan approach by governments, NGOs, and the private sector to mainstream CSA into agricultural Engagement and capacity strengthening are critical to help development globally. governments and others implementing agricultural development to integrate CSA into their policies, programmes, plans and projects (eg National Agriculture Investment Plans, Acknowledgements Nationally Determined Contributions, and Climate Change Action Plans). CSA-Plan provides operational approaches that CSA-Plan is the culmination of years of research by dozens of can be directly integrated into the planning processes, but the researchers on various teams working on the different sub- CSA-Plan process must be owned by the stakeholders and components. The development of the CSA-Plan framework decision-makers involved. was funded by the CGIAR Research Programme on Climate Capacity strengthening is also critical for mainstreaming CSA, Change, Agriculture and Food Security (CCAFS) through the and the CSA-Plan approach, in institutions, policies and Partnerships for Scaling CSA Project. We would especially like businesses across levels (community to national to global). to recognise contributions by our colleagues at CIAT (A Jarvis, This can be accomplished by working through the National C Mwongera, M Lizarazo, A Nowak), ICRAF (C Lamanna), Agriculture Research Systems (NARS), through academia, CCAFS (B Campbell, AM Loboguerrero, D Martinez, O Bonilla- government, NGO, or the private sector. There are various Findji, R Zougmore, L Sebastian, J Kinyangi, P Aggarwal), as alliances forming to provide formal engagement, knowledge, well as the numerous consultants and partners who worked and training, for example GACSA and the Africa CSA Alliance. with us to implement the decision-support tools and CSA The bottom line is that without good engagement and capacity programmes. strengthening, CSA-Plan lacks purpose. References Conclusions Allen H, Staehle M, 2007. Village savings and loan associations (VSLAs) With the growing demand by governments, NGOs, and the program guide: Field operations manual. VSL Associates. private sector for integrating climate into agricultural Campbell BM, Vermeulen SJ, Aggarwal PK, Corner-Dolloff C, Girvetz E, development, there are many opportunities for CSA-Plan Loboguerrero AM, Ramirez-Villegas J, Rosenstock T, Sebastian L, Thornton P, components to be applied from regional to sub-national levels. 2016. Reducing risks to food security from climate change. Global Food Security, 11, 34-43. [http://dx.doi.org/10.1016/j.gfs. 2016.06.002] The CSA-Plan components – situation analysis, prioritising interventions, programme design and implementation, and CIAT, CCAFS, 2017. CSA Profiles. [https://ccafs.cgiar.org/publications/csa- country-profile] monitoring, evaluation, and learning – have already been applied in many countries with partners including the World Corner-Dolloff C, Nowak AC, Lizarazo M, Parker L, Trinh MV, Nghia TD, 2016. Multi-stakeholder prioritization approach for climate-smart agriculture Bank, USAID and DFID, among others. For example, climate planning and investment in Vietnam. In: Percy E Sajise, Maria-Celeste H Cadiz, risk profiles are being developed for 24 Kenyan counties to Rosario B Bantayan,eds. Learning and coping with change: case stories of provide technical support to the US$ 250 million World Bank climate change adaptation in Southeast Asia, 2017. SEARCA: Philippines. 15 PAGE 78 Article 2 /News from the Field 2 Agriculture for Development, 30 (2017) FAO, 2013. Climate-smart agriculture sourcebook. Food and Agriculture Quinney M, Bonilla-Findji O, Jarvis A, 2016. CSA programming and indicator Organization of the United Nations. Rome, Italy. tool: 3 steps for increasing programming effectiveness and outcome tracking of CSA interventions. CCAFS Tool Beta version. CGIAR Research Programme FAO, 2015. Eastern Africa climate-smart agriculture scoping study: Ethiopia, on Climate Change, Agriculture and Food Security. Copenhagen, Denmark. Kenya and Uganda. Food and Agriculture Organization of the United Nations. Rome, Italy. Rioux J, Gomez San Juan M, Neely C, Seeberg-Elverfeldt C, Karttunen K, Rosenstock T, Kirui J, Massoro E, Mpanda M, Kimaro A, Masoud T, Mutoko M, Hewitt C, Mason S, Walland D, 2012. The global framework for climate services. Mutabazi K, Kuehne G, Poutouchidou A, Awagyan A, Tapio-Bistrom M-L, Nature Climate Change. 2, 831-832. Bernoux M. 2016. Planning, implementing and evaluating Climate-Smart Hills T, Pramova E, Neufeldt H, Ericksen P, Thornton P, Noble A, Weight E, Agriculture in smallholder farming systems: the experience of the MICCA pilot Campbell B, McCartney M, 2015. A monitoring instrument for resilience. projects in Kenya and the United Republic of Tanzania. FAO, Rome, Italy. CCAFS Working Paper No 96. CGIAR Research Programme on Climate Rosenstock TS, Lamanna C, Chesterman S, Bell P, Arslan A, Richards M, Rioux Change, Agriculture and Food Security. Copenhagen, Denmark. J, Akinleye AO, Champalle C, Cheng Z, Corner-Dolloff C, Dohn J, English W, Johnson KB, Diego-Rosell P, 2015. Assessing the cognitive validity of the Eyrich AS, Girvetz EH, Kerr A, Lizarazo M, Madalinska A, McFatridge S, Morris women’s empowerment in agriculture index instrument in the Haiti multi- KS, Namoi N, Poultouchidou N, Ravina da Silva M, Rayess S, Ström H, Tully sectoral baseline survey. Survey Practice, 8(2). KL, Zhou W, 2016. The scientific basis of climate-smart agriculture: a Lundy MA, Amrein JJ, Hurtado G, Becx N, Zamierowski F, Rodriguez, systematic review protocol. CCAFS Working Paper No 138. CGIAR Research Mosquera EE, 2014. 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Prioritizing climate-smart livestock technologies Miranda MJ, Mulangu FM, 2016. Index insurance for agricultural in rural Tanzania: A minimum data approach. Agricultural Systems, 151, transformation in Africa. Background paper for African transformation report 204-16. 2016: Transforming Africa’s agriculture. African Centre for Economic van Wijk M, Hammond J, van Etten J, Pagella T, Ritzema R, Teufel N, Transformation and Japan International Cooperation Agency Research Rosenstock T, 2016. The Rural Household Multi-Indicator Survey (RHoMIS): institute. https://www.jica.go.jp/jica-ri/publication/other/l75nbg0000004aet- A rapid cost-effective and flexible tool for farm household characterisation, att/6_Index_ Insurance.pdf. targeting interventions and monitoring progress toward climate-smart Mwongera C, Shikuku KM, Twyman J, Läderach P, Ampaire E, Van Asten P, agriculture. CCAFS InfoNote [http://rhomis.net]. Twomlow S, Winowiecki LA, 2017. 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News from the Field Climate information use implications for climate risk mitigation in West Africa The necessity for climate While the Paris Agreement places great emphasis on reducing greenhouse gas emissions and creating carbon sinks, the impact information services in West Africa on climate change mitigation will not be seen immediately even if the most effective mitigation measures are implemented. With projections of a 70 percent increase in demand for staple cereals by 2050 in order to feed the growing human population As vulnerable farmers in West Africa experience greater climate (FAO, 2010), combined with the current declining per capita food variability (Cooper et al, 2008) it is important that climate- production and a dwindling natural resource base, ‘feeding West smart agricultural (CSA) technologies that reduce vulnerability Africa’ and increasing the resilience of livelihood systems may be to climate risks are prioritised. The establishment of the Global well beyond reach. This has been attributed to multiple factors Framework for Climate Services (WMO, 2013) by the World such as land tenure challenges, declining soil fertility, poor Meteorological Organisation (WMO) clearly confirms climate markets, climate hazards and variability, inadequate funding and information services (CIS) as one opportunity for managing poor infrastructural development (Ouedraogo et al, 2016; Partey climate change and variability risks. With increased drought, et al, 2016). The current state of food insecurity and poor rural unpredictable rainfall patterns, destructive flooding and the livelihoods are expected to be further exacerbated by climate growing evidence of climate change negatively impacting farm change and variability which has emerged as one of the major production systems, access and use of climate information threats to development in West Africa (Zougmoré et al, 2016). should help farmers make crucial decisions that enable them 16 PAGE 79 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Annex B: Situation analysis: Policy and programmatic context for CSA in Mali SITUATION ANALYSIS Target Setting, Climate Risks & Enabling Conditions Stocktaking for CSA Action Vulnerability, Impacts & Readiness A supportive policy context and the existing enabling conditions are a critical component of the situation analysis for CSA investments. This section briefly highlights: B-1 International and Regional Commitments, Frameworks, and Plans B-2 National Policies and Plans B-3 Other Legal Frameworks B-4 Select Donors and Projects With Potential Links To CSA Investments B-5 Select World Bank Projects With Potential Links To CSA Investments B-1 International and Regional Commitments, Frameworks, and Plans • UN Framework Convention on Climate Change (UNFCCC) • ECOWAS Regional Agricultural Policy of West Africa (ECOWAP) ECOWAP + 10 • 2014 Malabo Declaration On The Transformation Of Agriculture • Sustainable Development Goals (SDGs) • Sahel Alliance (initially the G5 Sahel) to assist Mali, (with Mauritania, Niger, Burkina Faso, and Chad)in supporting the National Development Plans priorities, supported by multi and bilaterals. • Comprehensive Africa Agriculture Development Program (CAADP): Mali received US$37.21 million from the Global Agriculture and Food Security Program (GAFSP), to support (i) investment in water control to raise productivity and reduce climatic risks to farmers; (ii) increased income in key agricultural sectors by improving farm productivity and adopting a value-chain approach; and (iii) capacity building for local authorities and farmer organizations. • West Africa Agricultural Productivity Program (WAAPP) objective is to increase productivity in West Africa’s major agricultural sectors, aligned with national and regional priorities. B-2 National Policies and Plans Transitional Interim Country Strategic Plan (T-ICSP) begun in January 2018, is based on seven strategic outcomes and aims to support the Government in achieving its National Development Plan (CREDD 2016–2018), the Sustainable Development Goal (SDG) 2, Zero Hunger and SDG 17, Partnerships for the Goals. The outcomes and activities have been designed on the basis of existing protracted relief and recovery operations (PRRO) and special operation (SO) projects.   . The ICSP strategic outcomes are: PAGE 80 • Crisis-affected populations meet their basic food and nutrition requirements during and after crises; • Vulnerable people in food-insecure and post-crisis areas are able to meet their basic food and nutrition requirements throughout the year; • Targeted populations (children 6-59 months and pregnant and lactating women (PLW) have reduced malnutrition in line with national targets; • Populations in targeted areas, including vulnerable smallholder farmers, have enhanced livelihoods and resilience to better support food security and nutrition needs all year-round; • Government (at the local and national levels) and civil society have strengthened capacity to manage food security and nutrition policies and Programs by 2023; • Government efforts towards achieving Zero Hunger by 2030 are supported by effective and coherent policy frameworks • Humanitarian partners have access to common services, (including transportation,  logistics, emergency telecommunications and food security analysis) throughout the year. Mali’s Strategic Framework for Growth and Poverty Reduction (CSCRP) Provides a framework for Mali to formulate and implement economic and social policies and strategies, while and identifying the financial needs and means to cover them. The CSCRP vision is articulated around: (i) a united nation on a diversified and rehabilitated cultural base; (ii) a political and institutional organization guaranteeing development and social peace; (iii) a strong, diverse and open economy; (iv) an improved environmental framework; (v) better quality of human resources. Joint Country Assistance Strategy (SCAP II—2016–2018) is the partnership framework document specifying the principles and modalities of development cooperation between the Government of Mali and its technical and financial partners for the period 2016–2018, focused on Mali’s recovery from crisis. This JAS follows JAS I (2008–2011), which allowed significant progress. National Livestock Development Policy The livestock subsector occupies an important place in Mali’s the national economy, shown by its contribution to GDP and export earnings. Mali’s Ministry of Agriculture, Livestock and Fisheries initiated this strategic document to identify the best interventions to support the livestock sector. National Aquaculture and Fisheries Development Policy identifies how to operationalize the Fisheries and Aquaculture Development Master Plan programs that were adopted by the Government in April 1997 and updated in 2006. National Irrigation Development Strategy (SNDI) was developed by the Government of Mali with the support of World Bank, FAO and other international development partners, to standardize the approaches and identify the priority actions to best use of available human and financial resources. National Proximity Irrigation Program (PNIP) irrigated agriculture, especially local irrigation, supports much of Mali’s farmers, and plays a central role in achieving poverty reduction and for job creation. The target group of the PNIP is composed of the local hydro-agricultural development operators, the processors of the Proximity Irrigation (PI) products and certain actors of their commercialization. Agricultural Land Tenure Policy and Agricultural Land Tenure Law (submitted for approval): Is a clear land policy document showing a very strong commitment to ensuring overall consistency on one of the fundamental factors of production. PAGE 81 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN B-3 Other Legal Frameworks Strategic Framework for Economic Recovery and Sustainable Development (Cadre Stratégique pour la Relance Economique et le Développement Durable, CREDD) (2016–2018) aims at achieving the Sustainable Development Goals (SDGs) by 2030 by promoting intensive, diversified and sustainable agriculture with a goal of guaranteeing and improving food and nutritional security for all, especially the most vulnerable. The Technical Unit of the Strategic Framework for the Fight Against Poverty have driven the consultation, design and finalization of the process that led to the validation of CREDD. The responsibility for the implementation of the CREDD lies with government ministries through their sectoral programing, to implement the CREDD action plan. The National Policy for Climate Change (PNCC) Politique Nationale sur les Changements Climatiques 2015–2020 was adopted at the end of 2011. Its overall objective is addressing climate change and ensuring Mali’s sustainable development. Key objectives are to: • facilitate better consideration of climate challenges in policies and sectoral strategies for national socioeconomic development and to guide interventions by public, private and civil society actors for sustainable development in a context of climate change; • increase the resilience of ecological systems, production systems and social systems to climate change effects through integrating adaptation measures as a priority in the most vulnerable sectors; • contribute to the global effort to stabilize concentrations of greenhouse gas emissions in the atmosphere, including promoting clean and sustainable projects • promote national research and technology transfer in climatic changes; • strengthen national capacities on climate change. There are key elements that affect the agricultural sub-sector, such as the use of meteorological information, and seasonal forecast, the use of adapted varieties, rainwater harvesting, better efficiency of irrigation systems are suggested. For the livestock sub-sector, measures such as preserving transhumance corridors, developing pastoral perimeters, or promoting intensive livestock breeding are suggested. For the fishery sub-sector, actions such as developing pisciculture and aquaculture, or conservation actions for wild species in rivers and lakes, are suggested. For the forestry sector, actions such as tree planting or reducing firewood use are suggested. There is also support for measures to implement CC policy at regional levels (e.g., capacity building, financial resources, project development). Mali submitted its UNFCCC Nationally Determined Contributions (NDC) in 2015, reaffirming the country’s commitment to both climate change adaptation and mitigation. Agriculture and forestry are key areas for both mitigation and adaptation in the NDC. The NDC proposes three main practices for mitigation in the agricultural sector: microdosing of fertilizers, development on SRI (System of Rice Intensification), and producing organic manure. In the forestry sector, measures such natural regeneration of trees, protected area management and tree planting were mentioned. For adaptation, suggested measures include improved and adapted seeds, breeds and fodder crops; cereal banks, use of weather information, land planning and conservation, capacity strengthening, and management of natural resources. The Pilot Program to develop climate smart and resilient agriculture is explicitly mentioned in the NDC. PAGE 82 Investment Plan for the Implementation of the NDC in Mali (2018–2020) was funded by the United Nations Development Program and GIZ in collaboration of the Ministry of Environment and the Agency for Environment and Sustainable Development. It provides a reference at national level and a tool to find resources with national and international partners for the implementation of project and Programs that aim at improving the living conditions of the most vulnerable populations by better adapting to the adverse effects of climate change and honoring its commitments to reduce greenhouse gas emissions as contained in its NDC. The investment plan includes sectors such as Energy, Agriculture, Land-Use Change and Forestry and is made up of programs and projects linked with the NDC that allow for reducing greenhouse gas emissions and implementing adaptation measures such as the Rainwater Harvesting and Storage Project; the Assisted Natural Regeneration Program; the Forest Management Project for Restoring Degraded Ecosystems, the Program to Promote Intermittent Irrigation, Deep Placement of Fertilizers in Irrigated Rice Farming and Intensive Rice Farming System (SRI). National Agricultural Investment Program (NAIP) (Plan National d’Investissement dans le Secteur Agricole) provides a coherent framework for programming public and private investment in the agricultural sector for the next eight years (2015–2025). The NAIP is aligned with Mali’s regional and international commitments. The NAIP covers the sub-sectors of agriculture, livestock, fisheries, aquaculture and environmental management. Its overall objective is to support agricultural development planning in Mali and operationalize agricultural investment. Its aim is allowing the rural sector to participate in the national economy, providing nutritional and food security for urban and rural populations and generating significant income and employment from a sustainable development perspective. Five main programs are defined: • Capacity strengthening of the different agriculture actors (from civil society to public sector); • Investment in production and transformation infrastructures; • Production and competiveness of agricultural value chains (including crop, livestock, fisheries, tree values chains); • Training and research (better use of research outputs, development of technologies); • Food security (by elaborating a food and nutrition security policy or implementing early warning systems. Adaptation and mitigation measures are explicitly mentioned in the third program and associated to the implementation of the national plan of adaptation and to the fight against desertification. B-4 Select Donors and Projects With Potential Links To CSA Investments There are many donors (bilaterals, multilaterals, NGOs) working in Mali on issues related to climate change, agriculture, water or food security. Here are a sample of projects that have recently, or are currently, being implemented in Mali. The agricultural CSAIP investments that are potentially relevant are shown in italics. • Global Climate Change Alliance’s project on mainstreaming REDD including reforestation NTFP CN, programs and studies on carbon sequestration (6.215 million Euros, 2010- 2017); 
 restoration CN • IFAD (International Fund for Agricultural Development) projects including microfinance in rural areas for adaptation agriculture and fostering agricultural productivity (about $534.9 million USD); PAGE 83 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Livestock CN, Restoration CN, • The EU support for peace and security that also acknowledges climate change related issues, including a project to support food security in the North (€30 million, to start in 2015) and 1.28 billion Euros to Mali in 2013. Floodplain recession agriculture CN, Rice CN. • Africa Hydromet Program - Strengthening Climate Resilience in sub-Saharan Africa: Mali Country Project UNDP- NAS and Mali Met support via USAID. Climate Services CN. • The German Ministry of Environment and the Malian Ministry of Environment and Sanitation’s project on climate change adaptation (10 million Euros, started in 2011);
 GIZ is active in Mali with programs as Supporting the National Strategy for Adaptation to Climate Change (2014- 2019) and Supporting the national program for sustainable small- scale irrigation (2008- 2023); Vegetables CN. • Netherlands Embassy in Mali supporting the Integrated Water Resources Program (2015- 2019); 
and the Great Green Wall financed by Multi Trust Fund (GEF), SCCF, World Bank, AfDB, NTFP CN, Water Resources CN, Vegetable CN, Floodplain Recession Agriculture CN. • Islamic Development Bank (IDB) - Integrated Development of Livestock and Fisheries Resources Project (PDIRAAM), Livestock CN. • African Development Bank - Project for the Development of Animal Production in the South Kayes Zone (PADEPA- KS), Livestock CN. • USAID Mali’s Climate Change Adaptation Activity, with objectives relating to information on climate change, climate change in communal governance systems, and adoption of climate change adaptive practices by households. • USAID’s Feed the Future focusing on millet and sorghum, rice, and livestock for food security and poverty alleviation. Millet and sorghum CN, SRI/rice CN; Livestock CN.  • Global Environment Facility has supported Mali’s National Adaptation Program of Action (NAPA), National Biodiversity Strategy and Action Plan (NBSAP) and country self- assessment, and since 1994, Mali has received US$13.7 million for biodiversity projects, $32.4 million for climate change projects, $8.1 million for land degradation projects and $11.2 million for multi focal area projects. Restoration CN, NTFP CN. B-5 Select World Bank Projects With Potential Links To CSA Investments Potentially relevant CSA Investments for each of these projects are shown in bold. • Mali’s Agricultural Productivity Growth Project (P095091: PAPAM, US$70 million, ending in July 2018); Livestock CN, Restoration CN. • West Africa Agricultural Productivity Program (P129565: WAAPP, US$60 million, ending in December 2018); Rice CN, Vegetables CN (Tomato). • Mali’s Agro-industrial Competitiveness Support Project animal feed value chain for livestock, including poultry and fish (P151449: PACAM, US$30 million, which started in late 2016 and runs until July 2022); Livestock CN. PAGE 84 • West Africa Regional Disease Surveillance System Enhancement Program Phase 3 (P161163: REDISSE 3). PAPAM, PROCEJ, and WAAPP dedicate funding to both traditional and improved livestock systems. Livestock CN. • Drylands Development Project (P164052: FY19), which is designed to reinforce the resilience of rainfed cereal production. Wheat CN, Millet and Sorghum CN, Rice CN. • Rural Mobility and Connectivity Project (P160505: approved early FY18) will finance rural roads,Vegetable CN, Livestock CN, Millet and Sorghum CN. • PADEL-M will also build on two upcoming irrigation projects that address irrigated production, potentially of fodder crops (P159765), Livestock CN. • PADAIC in the Alatona area in Niger’s inland delta, and the Sahel Irrigation Initiative Support Project–SIIP/P154482), Vegetable CN, Rice CN, Floodplain Recession Agriculture CN. • Regional Sahel Pastoralism Support Project (P147674: PRAPS-ML, US$45 million, ending in December 2021); Livestock CN. PAGE 85 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Annex C: Prioritizing interventions: The process from long-lists to finalists PRIORITIZING INTERVENTIONS Practices, Programs and Policies CSA Investment Portfolios Value for Money & Trade-offs This section summarizes the process used in prioritizing investments, with sections on: C-1 Producing a Long List of Investments C-2 Producing a Short List of Investments C-3 CSA Investment Practices, Location, Risks and Institutions C-4 Participants at Prioritizing Workshop C-1 Producing a Long List of Investments To develop the long list of CSA investments, key strategic national documents (plan, strategy, policy) such as the National Investment Plan in the Agricultural Sector (“Plan National d’Investissement dans le Secteur Agricole”- PNISA), the NDC report and investment Plan, the Climate Change National Policy (“Politique Nationale sur les Changements Climatiques”- PNCC), and other documents and programs were evaluated (see Annex B). Then, the practices mentioned in these documents with a potential impact on CSA pillars (adaptation, mitigation and productivity) were identified, and practices were grouped into belonging either to a national category, or to a specific agroecological zone. Specifically, the long list of investments was identified prior to this workshop, and additional potential investments identified by workshop stakeholders. This process was done with local experts supported by CGIAR expertise at a meeting in Mali from June 19-22, 2018 (see end of this annex for Participant List). The long list of investments identified is shown in Figure C-1, showing the groupings used to categorize potential investments. These investments were divided into 4 categories: agricultural system, fishery and livestock system, Forest and Sustainable Management of Water and Soils and CSA services: PAGE 86 AGRICULTURAL SYSTEMS 1 System of Rice Intensification Promotion 2 Sustainable irrigated lowlands promotion 3 Climate-smart Maize Development 4 Climate-smart Mil-Sorgho System Development 5 Climate-smart Cotton Development 6 Climate-Smart Development and Postharvest Management of Legumes (Peanut- Niebe) 7 Climate-smart Fonio Development 8 Development of the Mango and other fruits Value Chains 9 Climate-smart Gardening (maraîchage Development) 10 Climate-Smart Development of Flood Recession Agriculture in Northern Mali (maize, sorghum, sweet potato, market gardening like okra) 11 Redynamization of the Wheat Value Chain in Mali through CSA Practices and Value-Added Processing 12 Dune development (cumin, anise, watermelon, shallot) 13 Oasis development (market gardening: potato, tomato, onion, sweet potato, date, camel watering) FISH AND LIVESTOCK SYSTEMS 14 Climate-Smart Development and Integration of Livestock and Agricultural Systems 15 Climate-Smart Development of Fishery and Fish Farming (communal fish farming and aquaculture) FOREST AND SUSTAINABLE MANAGEMENT OF WATER AND SOILS 16 Bio-char/Green Charcoal Develop 17 Restoration of Degraded Areas 18 Watershed Management 19 Non-Timber Forest Product Value Chains Development (including Shea, Baobab, and Gum Value Chain) CSA SERVICES 20 Gap Identification and Strengthening of an Agroclimatic Information System 21 Financial Services and Insurance for Agriculture 22 CSA Integration in the National Extension System 23 Forest Surface Monitoring and GHG Emissions Development (MRV) 24 National Soil Fertility 25 Monitoring and evaluating ecosystem dynamics and agricultural statistics through remote sensing and applied geomatics 26 Improve the nutritional status of women and children CSA services were considered for national-level investment (for national implementation), while the other were divided into the three agroecological zones; Saharo- Sahelian (northern zone), Sudano- Sahelian (central zone) and Guineo-Sudanian (southern zone) (see FigureC-1). PAGE 87 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Figure C-1 Map of Mali’s Agroclimatic zones (left, used in main text of this report; right, from NDC and used in Workshop C-2 Producing a Short List of Investments To reduce this long list of potential investments to a shorter list, two main steps were followed. First, participants were divided into 4 groups (Saharo-Sahelian zone, Sudano-Sahelian zone, Guineo- Sudanian zone and national zone) and asked to prioritize 5 to 6 investments based on the specificity of their zone. (Names for these have been abridged from those in the workshop for simplicity.) The priorities for each of the zones are the Program for: Saharo-Sahelian Zone 1. Climate-Smart Development of Flood Recession Agriculture in Northern Mali 2. Development and Integration of Livestock in Farming Systems 3. Redynamization of the Wheat Value Chain in Mali through CSA Practices and Value-Added Processing 4. Climate Smart development of Fishery and fish farming (communal fish farming and aquaculture) 5. Restoration of Degraded Lands in the Sahelian Zone 6. Development of Non-Timber Forest Product Value Chains Sudano-Sahelian Zone 1. Promotion of the System of Rice Intensification (SRI) 2. Scale Climate-Smart Millet-Sorghum Systems with Legumes 3. Development of the Mango and other fruits Value Chains 4. Climate Smart development of Fishery and fish farming (communal fish farming and aquaculture) 5. Climate Smart Gardening (maraîchage) Development 6. Development and Integration of Livestock in Farming Systems PAGE 88 Guineo-Sudanian Zone 1. Development of Non-Timber Forest Product Value Chains 2. Scale Climate-Smart Millet-Sorghum Systems with Legumes 3. Climate Smart Gardening Development 4. Development of the Mango and other fruits Value Chains 5. Livestock development program (small ruminants, milk, fodder) 6. Climate Smart Cotton Development National-Scale Programs 7. CSA Integration in the National Extension System 8. Monitoring and evaluation of ecosystems and agriculture through remote sensing and applied geomatics 9. Improve the nutritional status of women and children 10. Strengthening of an agroclimatic information system 11. National soil fertility monitoring 12. Forest Surface Monitoring and GHG Emissions Development (MRV) Participants were then asked to prioritize the top six investments using a point system, producing the ranking shown in Table C-1. Table C-1: Final Participant Ranking of Projects INVESTMENTS POINTS RANK SCOPE 19 1 Regional Development of Non-Timber Forest Product Value Chains in Mali (Shea, Baobab, Gum, Zaban, Ronier) Climate-Smart Development of Flood Recession Agriculture in Northern Mali 17 2 Regional (maize, sorghum, sweet potato, market gardening like okra) Monitoring and evaluation of ecosystem dynamics and agricultural statistics 15 3 National through remote sensing and applied geomatics Development and Integration of Livestock in Farming Systems in Mali’s Soudanian 12 4 Regional Zone Scale Climate-Smart Millet-Sorghum Systems in Association with Legumes 12 5 Regional CSA Integration Program in the National Extension System 11 6 National Climate Smart Gardening (maraîchage) Development Program 10 7 Regional Strengthening of an agroclimatic information system 9 8 National Restoration of Degraded Lands in the Sahelian Zone of Mali 9 9 Regional Promotion of the System of Rice Intensification (SRI) in Mali 9 10 Regional National soil fertility monitoring program 6 11 National Redynamization of the Wheat Value Chain in Mali through CSA Practices and Val- 3 12 Regional ue-Added Processing Forest Surface Monitoring and GHG Emissions Development (MRV) 2 13 National Climate Smart development of fishery and fish farming (communal fish farming 2 14 Regional and aquaculture) Development of the Mango and other fruits Value Chains 1 15 Regional Climate Smart Cotton Development 1 16 Regional PAGE 89 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN C-3 Investment CSA Practices, Location, Risks and Institutions Participants then considered each of the 12 CSA investments to inform the development of the concept notes, discussing leading institutions, the needed CSA practices that were needed, the needed scope of the project, proposed geographic reach, risks, and other relevant information. They also involved key actors in fostering the adoption of the CSA practices. For each actor, needed changes in knowledge, skills and practices and related activities were identified. This information was used to make more detailed proposed project, and develop outcomes, activities and component of each investment/Program. All of these were used to develop the project concepts found in Annex F, and workshop information was included, and supplemented in the development of these concepts. In addition, alignment of these proposed investments with those proposed by the NDC Partnership was considered (see Chapter 3). C-4 Participants at Prioritizing Workshop Climate-Smart Agriculture Investment Plan Development for Mali was held 19-22 June 2018. NAME INSTITUTION Lassina Traoré L ’Agence d’Aménagement Des Terres Et De Fourniture De L’eau d’Irrigation (ATI) Mohamed Adideye Maiga L’Agence De l’Environnement Et Du Développent Durable (AEDD) Aissata Keita USAID/ Ministère de l’environnement et de l’Assainissement) Daouda Z. Diarra Agence Nationale De La Météorologie Du Mali Chaka Traoré Direction Nationale De l’Hydraulique (DNH) Ibrahima Diakité Commissariat à la Sécurité Alimentaire Bougouna Sogoba Malian Association Of Awakening To Sustainable Development (AMEDD) Kadari Traoré Fadiala Dembélé Université De Bamako Kalifa Traoré Institut D’economie Rurale Moussa Sacko World Agroforestry Centre (ICRAF) Djalal Arinloye World Agroforestry Centre (ICRAF) Samba Traoré Institut D’economie Rurale Kalifa Traoré Institut D’economie Rurale Aly Boubacar Institut D’economie Rurale Toumany Diallo Alliance Globale Sur Le Changement Climatique Au Mali (AGCC-Mali) Amidou Sako Drylands Coordination Group In Mali (GCOZA-Mali) Doumbia Zan Diarra Expert Otogolo Kone Direction Nationale Des Productions Et Des Industries Animales (DNPIA) Mariam Sawadoya CTESA Amadou Diallo Direction Nationale des Eaux et Forêts Issa Traoré Ministry For Livestock And Fisheries (MEP) PAGE 90 Annex D: Structure and results of the scenario modeling analysis (RCP + SSPS) D-1 About Shared Socioeconomic Pathways (SSPs) D-2 Combinations of Representative Concentration Pathways (RCPs) and SSPs D-3 IMPACT Model And Modeling Combinations Of RCPs And SSPs. D-4 Scenarios Purpose For Modeling D-5 Methodology D-6 Standard Measuring And Interpreting The Results D-7 Preliminary Data For Mali From IIASA Database D-8 Results: Heatmaps D-1 About Shared Socioeconomic Pathways (SSPs) Shared Socioeconomic Pathways (SSPs) are scenarios of global development and contain many elements. Each scenario was given an evocative name to describe a development path the world might take and how this path would affect society’s ability to respond to climate change. The following figure shows how the five SSPs were envisioned with respect to society’s ability to deal with climate change116. The SSPs are future scenarios with narratives, which include quantitative elements such as population, urbanization, rates of technological change, income, human development index, income distribution, etc. Using the narratives obtained from Riahi et al. (2016), the next table displays the narratives for each Shared Socioeconomic Pathways-SSP scenario. 116 Robinson et al., 2015 PAGE 91 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Table D-1: Summary of SSP narratives. Sustainability – Taking the Green Road (Low challenges to mitigation and adaptation). The world shifts gradually, but pervasively, toward sustainability, emphasizing more inclusive development that respects per- SSP1 ceived environmental boundaries. Management of the global commons slowly improves, educational and health investments accelerate the demographic transition, with the emphasis on economic growth shifting toward a broader emphasis on human well-being. Middle of the Road (Medium challenges to mitigation and adaptation). The world follows a path in which so- cial, economic, and technological trends do not shift markedly from historical patterns. Development and income growth proceeds unevenly, with some countries making relatively good progress while others fall short of expec- SSP2 tations. Global and national institutions work toward but make slow progress in achieving sustainable develop- ment goals. Environmental systems experience degradation, although there are some improvements and overall the intensity of resource and energy use declines. Global population growth is moderate, leveling off after 2050. Regional Rivalry – A Rocky Road (High challenges to mitigation and adaptation). A resurgent nationalism, concerns about competitiveness and security, and regional conflicts push countries to increasingly focus on domestic or, at most, regional issues. Policies shift over time to become increasingly oriented toward national and SSP3 regional security issues. Countries focus on achieving energy and food security goals within their own regions at the expense of broader-based development. Investments in education and technological development decline. Economic development is slow, consumption is material-intensive, and inequalities persist or worsen over time. Population growth is low in industrialized and high in developing countries. Inequality – A Road Divided (Low challenges to mitigation, high challenges to adaptation). Highly unequal investments in human capital, and increasing disparities in economic opportunity and political power, lead to increasing inequalities and stratification both across and within countries. A widening gap exists between an internationally-connected society that contributes to knowledge - and capital-intensive sectors of the global SSP4 economy, and a fragmented collection of lower-income, poorly educated societies with labor intensive, low-tech economies. In the high-tech economy and sector, technology development is high and the globally connected energy sector diversifies, with investments in both carbon-intensive fuels like coal and unconventional oil, and low-carbon energy sources. Environmental policies focus on local issues around middle and high income areas. Fossil-fueled Development – Taking the Highway (High challenges to mitigation, low challenges to ad- aptation). This world places increasing faith in competitive markets, innovation and participatory societies to produce rapid technological progress and development of human capital as the path to sustainable develop- ment. Global markets are increasingly integrated, with strong investments in health, education, and institutions SSP5 to enhance human and social capital. At the same time, the push for economic and social development is cou- pled with the exploitation of abundant fossil fuel resources and the adoption of resource and energy intensive lifestyles around the world. All these factors lead to rapid growth of the global economy, while global population peaks and declines in the 21st century. Local environmental problems like air pollution are successfully managed. D-2 Combinations of Representative Concentration Pathways (RCPs) and SSPs Each cell in the matrix indicates a combination of combination of socioeconomic development pathway and climate outcome based on a particular forcing pathway that current Integrated Assessment Model (IAM) runs have shown feasible117 Table D-2: Scenario Matrix Architecture And RCP Future Pathways SSP1 SSP2 SSP3 SSP4 SSP5 Refer- x x x x x ence RCP Replication 8.5 Wm.2 x 6.0 Wm.2 x x x x 4.5 Wm.2 x x x x x 2.6 Wm .2 x x x 117 Riahi et al., 2016 PAGE 92 D-3 Impact Model and Modeling Combinations of RCPs and SSP IPCC has developed a measure of the compatibility of SSPs and RCPs. Table D-3 summarizes this compatibility matrix. The square with an X represents an SSP-RCP combination that is not considered plausible. The darker the shading, the higher would be the costs to society that would be needed to mitigate greenhouse gas emissions to allow for the compatibility of an SSP with an RCP. For example, if no climate policies are pursued to mitigate climate change under SSP 2 we would expect somewhere between RCP 6.0 and 8.5. However, with some mitigation RCP 6.0 is possible, and with heavier investment 4.5 and 2.6 may also be possible118 Table D-3: RCP and SSP compatibility matrix and cost of mitigation. Scenario Specifications SSP1 SSP2 SSP3 SSP4 SSP5 RCP 8.5 RCP 6.0 RCP 4.5 RCP 2.6 Each RCP represents global climate change through the role of greenhouse gas emissions and radiative forcing. This is just one physical dynamic that determines climate and weather. To simulate all of these systems that determine climate and to provide weather as inputs to crop models, the RCPs must be simulated in Earth System Models (ESMs or formerly called General Circulation Models. The ESMs are complex models that simulate earth’s biogeochemical cycles and combine modules that simulate physical climate, atmospheric circulation, and ocean and ice dynamics. Each ESM has somewhat different assumptions about how each of these complex dynamics works and interacts, which means that each ESM’s realization of the RCP will be somewhat different. This diversity of results creates model uncertainty, as it is not possible to determine which ESM realization is more likely. To better handle this uncertainty, and to expand the climate possibility space in which IMPACT scenarios can be tested, it was decided to use multiple ESM realizations of each RCP and allow the use of a multimodel ensemble to test climate uncertainty. The ESMs, which are currently used to provide climatic data to the Decision Support System for Agrotechnology Transfer crop models are the following: GFDL-ESM2M , HADGEM2-ES , IPSL-CM5A-LR , MIROC-ESM , NORESM1-M. D-4 Scenarios Purpose for Modeling Each scenario to analysis is integrated for a) General Circulation Model (GCM) b) Representative Concentration Pathways (RCP), and c) Shared Socioeconomic Pathways (SSPs). These combinations were explained on the prior tables, however, the modeling allow to aggregated future climate conditions as precipitation and temperature. D-5 Methodology It is important to remember that IMPACT model results are not predictions, but rather scenarios that describe the future potential performance of crops under specific climate and policy conditions. IMPACT model results factor in several key assumptions regarding the structure of the socioeconomic system, national investment in agriculture, and climate. Thus, in interpreting the results that follow, it 118 Robinson et al. 2015. PAGE 93 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN is important to think of the modeled trends as plausible, not predicted, futures. As the IMPACT model is a partial equilibrium model of the agriculture sector, it is largely driven by supply and demand of the modeled commodities. Moreover, the Table D-4 displays some outcomes variables for each scenario modelled for a period from 2020 to 2050. Table D-4: Based on IMPACT model description version 3 (Robinson et al., 2015) No Variable Name 1 Total production (000 mt) 2 Total demand for commodity (000 mt) 3 Crop yields (mt/ha) 4 Total area (000 ha) 5 Net trade (000 mt) 6 Exports for each country and traded commodity(000 mt) 7 Export share of production (%) 8 Imports for each country and traded commodity(000 mt) 9 Net trade share of production (%) 10 Net trade share of demand (%) 11 Solution total commodity supply D-6 Standard Measuring and Interpreting the Results The impacts of climate change (include SSPs pathways) on a given indicator of interest are calculated as the difference in percentage changes in 2050 over the baseline year 2020 with and without climate change. For example, the impact of climate change on yield ( Ydiff(pp) ) is assessed as follows. Ydiff(pp) = %∆yCC — %∆yNoCC (1) Where %∆yCC = YCC2050 — YCC2020 (2) Ycc2020 %∆yNoCC = YNoCC2050 — YNoCC2020 (3) YNocc2020 When calculated in this way, impacts are reported in terms of a percentage point difference. Impacts can also be assessed as a percentage difference of the indicator’s 2050 value under CC with respect to its 2050 value under the NoCC scenario. For yield this would be: Ydiff(%) = yCC2050 — yNoCC2050 (4) YNocc2050 When calculated in this way, impacts are reported in terms of percentages. PAGE 94 D-7 Exploration of preliminary data for Mali from IIASA database Population change under different scenarios PAGE 95 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN GDP Change under different SSPs PAGE 96 Urban Population Change under different SSPs PAGE 97 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN D-8 Results: Comprehensive Heatmap tables PAGE 98 PAGE 99 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Annex E: Climate-Smart economic appraisal: methodology and extended results E-1 Model design E-2 Parameter Estimation E-3 NPV and ROI Results for the Four Priority Projects Under Various Risk Scenarios E-4 Value Of Mitigation Benefits From Four Priority Investments D-8 Results: Heatmaps We modeled project performance using Bayesian Networks (BN), which excel when the goal is to predict outcomes of investments with high degrees of uncertainty, nonlinearity, and feedback between components. These characteristics are common features of climate, agriculture and rural development projects. Specifically, we used a BN model for two reasons. First, providing accurate estimates for project costs, returns and adoption is a main challenge in project evaluation is to provide accurate estimates for project costs, returns and adoption. The parameter uncertainty of all of these variables can be explicitly modelled in the BN and is taken into account. That is, instead of assigning a point value for the targeted number of beneficiaries or their income, in BN we assign a probability distribution that represents our degree of confidence around this estimate. Probability distributions are used for all variables in the model. Second, different risk scenarios, climate and non-climate, and their uncertainty can be simulated. The model takes the likelihood (frequency) and impact (severity) of risk factors into account when modeling project performance. In the following sections, we describe the structure, parameterization and simulation of the model. Figure E-1: BN Overview in Time t Year t Adoption Costs & Productivity Climate Budget Impact Impact Project Value PAGE 100 E-1 Model Design The BN model aims to prioritize project alternatives based on their Net Present Value (NPV) and discounted Return on Investment (ROI). The project’s impact is monetized, discounted and calculated considering the gradual adoption of the project by the target beneficiaries. Figure E-1 shows an overview of the model. Each node in FigureE-1 represents a fragment of BN that contains multiple nodes and relations. The BN assumes that the project is evaluated over five years, common lengths of projects. The cumulative NPV and ROI distribution of the project is calculated accounting for the adoption, impact and costs that incur in each year. In the remainder of this section, we describe the content of each fragment in FigureE-1. Adoption. In the model, a project’s scope is defined by the targeted total number of beneficiaries. Both of these measures are uncertain and defined by a probability distribution. Interventions, in this case climate-smart agriculture, are gradually adopted over a period of time. The percentage of targeted beneficiaries that adopt the project is modelled by the Bass model119. The Bass model uses rate of innovation p and rate of imitation q to estimate the adoption rate (AR) over a specified time period t to reach the target beneficiary total as: (1) Project risks, such as lack of community acceptance or drought, can affect the adoption rate. To reflect this, the rate of innovation and imitation are modelled as mixture distributions conditioned on the risk factors in the model. (2) (3) Where pi is the adoption rate when adoption risk i is present. The adoption rate was modelled with a Beta or a similar probability distribution to reflect its parameter uncertainty. The total number of beneficiaries and area that adopts the project changes every year due to adoption rate. Figure E-2 shows the BN fragment modelling adoption. (4) (5) 119 Bass FM. 1969 PAGE 101 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Figure E-2: Adoption BN Fragment A project’s impact is evaluated as the difference between a beneficiary’s income before the project and after adopting the project. (6) Several natural risk factors, such as drought and pests, can affect beneficiary income and the performance of CSA interventions. Moreover, the effect of these risk factors could be different for project adopters and non-adopters. For example, while a drought can decrease the income for both project beneficiaries and other farmers, its impact can be more severe for the farmers who did not adopt CSA practices. To model this, we first adjust project and baseline income estimates based on risk factors that realize in different years. Let IB and IP, respectively, be the income of a beneficiary before and after adopting the project, EBt and EPt be the combined effect of natural risk factors at t. The adjusted income for before and after adopting project at t, i.e. IPtadj and IBtadj are: (7) (8) The combined effect of risk factors for project beneficiaries and other farmers are modelled as a mixture distribution conditioned on the natural risk factor: PAGE 102 (9) (10) Where P (NaturalRisk = i)t is the probability that natural risk factor i realises at time t, and EPi and EBi are the effect of the risk factor i for project beneficiaries and other farmers, respectively. Figure E-3 shows the BN fragment that estimates the productivity impact for different years. Figure E-3: Productivity Impact BN Fragment Costs are estimated on a yearly basis and modelled by probability distributions that represents the degree of uncertainty around these estimates. The standard deviation around the cost estimates are increased each to reflect higher uncertainty regarding long-term estimates. The project costs and budget can be adjusted based on relevant risk factors. For example, a donor’s unwillingness risk factor decreases the project budget. Figure E-4: Project Cost and Budget Estimates PAGE 103 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN The project’s present value in year t is calculated in the project value fragment using the above adoption, productivity and cost estimates calculated in the previous sections. (11) NPV is the sum of discounted benefit over the project duration k and ROI is the ratio of NPV over total discounted cost of the project. (12) (13) Figure E-5 shows the BN fragment that calculates Rt. Note that, the parts that are linked to other BN fragments are coloured red in this figure. Figure E-5: Project Value in Year 1 BN Fragment PAGE 104 E-2 Parameter Estimation The parameters of the BN model were defined based on a combination of domain expert knowledge and external data sources where available. Expert knowledge was elicited through an online questionnaire of participants following the in-person workshops (Annex C). The responses of multiple experts were combined with available external data to elicit the distribution of the BN parameters (Table E-1). Table E-1: Sources of information on model parameters PARAMETER EXPERT KNOWLEDGE EXTERNAL DATA Number Beneficiaries x x Adoption Rates x Income before project x x Income after project x x Project Costs x Risk Frequency x x Risk Impact on Project x We used a multistep process to guide experts in estimating project parameters with as little bias as possible. Domain experts were recruited from assessment workshop participants, and parameter estimation took place via online questionnaires after the workshop due to time constraints. The questionnaire followed a tested format for parameter elicitation in BNs120, and used two types of questions: interval questions and multiple choice questions. Interval questions were used to elicit the distributions of continuous parameters, such as income, after project and target beneficiaries. Participants were asked to define an interval that would include the highest and lowest possible estimates, as well as a best guess for the real value. Multiple Choice Questions were used to elicit the probability and effect of discrete risk factors. Questionnaire respondents were trained in these elicitation methods by first explain common biases and heuristics in estimation, and then giving them a sample parameter to estimate. The elicitation questionnaires were sent to multiple experts, and weighted linear pooling was used on their answers. In this approach, the pooled parameter estimated f (θ) is the weighted average of individual estimates of the domain experts where wi and f(θ) are respectively the weight and parameter estimate of expert i: (14) The weight given to each expert was defined based on accuracy of their response. In the questionnaire, we elicited beneficiary income before and after the project. From this, the domain expert’s estimate on productivity impact of the project could be calculated. We also obtained the same parameter for each project from the scientific literature and, used this parameter as a seed parameter for assessing experts’ accuracy. We used Bojke et al.’s approach121 to assign weights to experts based on the seed parameter, sampling from the distribution elicited from the experts and 120 Yet et al. 2016. 121 Bojke L, et all 2010 PAGE 105 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN the distribution from the scientific literature. In every sample, the expert closest to the CSA sample is given one point. The weight of each expert is calculated by dividing their points to the total number of samples. Finally, we fit a probability distribution to the pooled parameter estimates, and used these distributions as inputs to the BN model. In addition to expert knowledge, we also incorporated external data sources, to improve the accuracy of estimates and consistency of estimates across projects. Number of Beneficiaries. We used census data from the specified project regions to estimate A. potential number of beneficiaries. However, not all potential beneficiaries will adopt any given technology. So the number of beneficiaries were scaled by adoption rates relevant to the complexity of the system. In addition to the total number of beneficiaries reached, we also estimated implementation curves for each project (Table E-2). Projects with slow implementation curves take longer to develop technologies, materials, and begin implementation so they are slower reaching the full number of beneficiaries. In contrast, fast projects can quickly begin to reach beneficiaries with technologies that are readily available and/or simple to implement. Projects were assigned to one of the three implementation curves based on experts’ judgement of the time needed to implement planned project activities. Table E-2: Implementation Curves Used to Estimate Annual Adoption % BENEFICIARIES REACHED (PER YEAR) SPEED YEAR 1 YEAR 2 YEAR 3 YEAR 4 YEAR 5 Slow 5 10 30 60 100 Medium 10 20 40 70 100 Fast 15 30 50 75 100 B. Adoption Rates were estimated based on expert opinion. Roughly estimated as Low (10-30%), Medium (30-50%), or High (50-70%) adoption rates. In general, projects that involve complex technologies or multiple changes to current practices will have low adoption rates, whereas projects that require few changes will have higher adoption rates. C. Income before project was based on expert estimation of household income across all projects in country to calculate a mean and variance in household income used for each project. Income post project. For projects which rely primarily on farm-management practices, we D. estimated change in income after project implementation using the Climate-Smart Agriculture Compendium, a dataset, compiled from more than 1,500 peer-reviewed articles, contains more than 150,000 data points that compare 45 different outcomes of productivity, resilience and mitigation for 100 different farm practices in Africa122. This includes data on the changes in yield, costs and net returns with adoption of CSA (see example in Table E-3). This one of a kind resource provides a rich evidence base for estimating the performance of practices across a wide range of agroecological conditions and farm management scenarios. 122 Rosenstock TS, Lamanna C et al. 2015 PAGE 106 • National Flood Recession Agriculture impact was estimated through a meta-analysis of data on change in yield, income, and costs in the West Africa region for CSA practices {improved varieties, organic and inorganic fertilizers, mulching, reduced tillage} and key crops {maize, sorghum, cassava, tomatoes} specified in the concept note. • Crop-Livestock Integration analysis of change in yield, income, and costs for implementation of climate-smart livestock practices {e.g., diet management, improved breeds} for key livestock species {cattle, goats, sheep, chickens} in West Africa. • Non-Timber Forest Products (NTFPs) Impacts of incorporating NTFPs on rural household income were estimated based on reported changes in household income. • National Remote-Sensing and Geoinformatics Program implementation impact was estimated based on potential use of the resulting information by farmers, particularly by improving planting dates based on weather forecasts and by improving variety choice based on soil and weather information. Mean and variation in impact of agrometeorological information on crop yield and household income was taken from a modeling study of the benefits of climate information for millet growers in Niger123. E. Costs: Detailed project budgets and costs were developed in consultation with investment ‘champions’ after the stakeholder workshop. These champions included experts and government officials with specific domain information relevant for the concept note. Budgets aimed to target US$20–60 million sized programs to be of rapidly bankable size. F. Risk Frequency: We used a multistep process to identify risks and estimate likelihood and impact parameters from multiple sources. During the Assessment workshops, participants listed risks to each project and gave a qualitative estimation (Low, Medium, High) of the risk likelihood and risk impact to project (see above). This generated a list of risks that was used to elicit quantitative risk parameters from domain experts and external data sources. Both the domain expert estimations and the external data were used to generate final probability distributions for risk likelihood and impact to the project in the Bayesian Network. Approach used to estimate the parameters for each of the six modeled risks are described below. • Drought. We estimated drought likelihood from the historic drought frequency in Mali over the period 1991–2010124. Drought events were defined as periods where the actual rainfall over the preceding 12 months was more than one standard deviation below the long-term average (Standardized Precipitation Index SPI-12 < -1) based on globally gridded precipitation data. A drought period would begin in a month where the SPI-12 reached -1 and ended in a month where the SPI-12 reached 0, or average rainfall conditions again. The number of such events between 1991–2010 was the reported drought frequency. We calculated mean and variance in number of drought events in each country by dividing the country (for Mali only the southern crop growing regions were used) into 16 grid cells and measuring the mean number of droughts per cell. Drought likelihood was then the average number of drought events per year. For example, if the area averaged 1 drought per decade, then we estimated a 10% chance of drought in any given year. 123 Roudier P, et al. 2016 124 Spinoni J, et al. 2014 PAGE 107 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN • Floods. Similar to drought likelihood, we estimated flood likelihood from historic flood data in Mali. Reported flood frequency was obtained from the United Nation’s International Strategy for Disaster Reduction (UNISDR) knowledge platform PreventionWeb125 for the period 2005–2014. Although some flooding occurs annually in Mali during the rainy season, flood events recorded in PreventionWeb are Internationally Reported Losses, and thus would be potentially disruptive to project activities. As in drought, flood likelihood was estimated based on the number of observed flood disaster events per year. • Pests. Data on the frequency of major (and thus project-disrupting) pest outbreaks in Africa is difficult to find. We assessed the likelihood of pest outbreaks using several data sources. In Mali, the most common crop pest is the Desert Locust. Locust plagues occurred on 5 occasions between 1900–2000126, which yields a conservative (because outbreaks may last from one to many years) estimate of likelihood of 5% in any given year. Additionally, novel or “shock” pest and disease outbreaks have occurred in sub-Saharan Africa approximately 5 times in the past 20 years127, including the most recent outbreak of Fall Army Worm across the continent. This gives a conservative upper limit estimate of 25% likelihood of a significant pest outbreak in any given year. These estimates were combined to yield the final likelihood of a disruptive pest outbreak in any given year. • Political Instability. Mali has experienced a political coup and ongoing conflict in the last decade, suggesting a relatively high risk of political instability. To estimate the likelihood of political instability, we used the World Bank’s World Governance Indicator128 Political Stability and Absence of Violence (PSAV). We converted WGI PSAV scores to likelihood of political instability by establishing a linear scale of 100% chance of instability for a score of -3 (generally those countries in active conflict without functioning governments) and a 0% chance of instability to a score of 2 (the highest given in the dataset). We computed the mean and sd in PSAV score in Mali over the 1996–2017 period and converted this to a mean and sd in likelihood of political instability using our linear scale. • Poor Governance. Similar to Political Instability, we estimated the likelihood of poor governance affecting project implementation using the World Bank’s World Governance Indicator10 Government Effectiveness (GE). GE Scores were converted to likelihood of poor governance using a linear scale; the lowest score (-2.5) corresponded to a 100% chance of poor governance affecting the project and the highest score (+2.5) corresponded to a 0% poor governance chance. We computed the mean and standard deviation in GE score for Mali over the 1996–2017 period and converted this to a mean and standard deviation in likelihood of poor governance using our linear scale. • Community Conflict. Community conflict, particularly between agriculturalists and pastoralists, or different ethnic groups, is a potential project risk identified by stakeholders in Mali. We estimated likelihood of community conflict using the Institutional Profiles Database129 indicators of Social Conflict (A203). The Social Conflict variable includes estimations of ethnic and religious conflict, conflict over land in rural areas, and other types of social conflict. We converted Social 125 www.preventionweb.net 126 United Nations Food and Agriculture Organization. Locust Watch. www.fao.org/ag/locusts 127 Smith J. 2015. 128 World Bank Group. Worldwide Governance Indicators. http://info.worldbank.org/governance/wgi/ 129 Institutional Profiles Database: http://www.cepii.fr/institutions/EN/ipd.asp PAGE 108 • Conflict scores to likelihood of conflict using linear scale, where a score of 0 (serious social conflict) was a 100% chance of conflict and a score of 4 (no social conflict) was a 0% chance of conflict. We used the standard deviation of a country’s scores across the five variables that contribute to the Social Conflict indicator to estimate the uncertainty around the likelihood of conflict. G. Risk Impact was estimated as both the potential effect of the occurrence of a risk on a project beneficiary’s income, as well as the effect on project adoption. While some risks such as drought will primarily affect project impact (e.g., reducing yields), others such as community conflict will primarily affect project participation (e.g., inability to access project sites or activities). Table E-4: Risk Frequency and Impact Estimates RISK IMPACT ON INCOME/ADOPTIONa ANNUAL RISK CHANCE CROP- NON- BUSINESS FLOOD RECES- REMOTE (% ± SD) LIVESTOCK TIMBER FOR- AS USUALb SION AGRIC. SENSING INTEGR. EST PRO. Drought 25 ± 7 --/NA -/+ --/0 -/0 0/++ Flood 20 ± 10 --/NA -/+ -/0 -/0 0/+ Pests 15 ± 10 --/NA -/0 --/0 -/- -/+ Political Instability 49 ± 19 0/NA 0/- 0/- 0/- 0/- Poor Governance 67 ± 3 0/NA 0/- 0/- 0/- 0/- Community Conflict 65 ± 22 0/NA 0/- 0/- 0/- 0/- a Symbols represent probability distributions for impact on beneficiary income and adoption rates in the analysis. For income: -- up to complete loss of income, - up to a moderate loss of income, 0 small gain to small loss, + up to moderate gain in income, ++ up doubling or more of income. For adoption -- up to complete loss of participation, - small to moderate loss of participation, 0 small loss to small gain in participation, + small to moderate gain in participation, ++ moderate to large gain in participation. b Business as usual represents the impact of risks on a farmer similar to project beneficiaries, but who does not participate in the project, e.g., a without-project scenario. E-3 NPV and ROI Results for the Four Priority Projects under Various Risk Scenarios Each project was run under four risk scenarios: no risks, climate risks only, social risks only, and all risks possible. If a risk was not included in a scenario, its likelihood of occurrence was explicitly set to zero for that run. Otherwise, all risks were allowed to occur according to their frequencies in Table E-4. For each scenario and project, we calculated the mean and variance in NPV and ROI, as well as the likelihood of a positive NPV given the risks (Table E-5). PAGE 109 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Table E-5: NPV and ROI For CSA Projects Under Various Risk Scenarios RISK SCENARIO NPV ROI % POSITIVE (M$ ± SD) (% ± SD) NPV Flood Recession Agriculture No Risks 37.1 ± 71.8 46 ± 88 70 Climate Risks Only 32.2 ± 67.9 40 ± 84 67 Social Risks Only 11.0 ± 54.8 14 ± 67 57 All Risks 7.4 ± 51.8 9 ± 64 53 Crop-Livestock Integration No Risks -6.8 ± 61.2 -27 ± 246 45 Climate Risks Only -8.2 ± 49.5 -33 ± 199 41 Social Risks Only -9.9 ± 44.9 -40 ± 181 40 All Risks -10.8 ± 37.2 -44 ± 150 35 Non-Timber Forest Products No Risks 21.3 ± 11.4 53 ± 28 98 Climate Risks Only 17.6 ± 21.7 44 ± 54 80 Social Risks Only 6.2 ± 9.3 15 ± 23 74 All Risks 3.5 ± 16.4 9 ± 41 57 Remote Sensing and Monitoring No Risks 20.2 ± 21.9 125 ± 137 84 Climate Risks Only 60.0 ± 47.5 374 ± 299 93 Social Risks Only 14.2 ± 17.8 88 ± 112 80 All Risks 46.6 ± 38.2 291 ± 239 92 E-4 Value of Mitigation Benefits from Four Priority Investments Economic value of mitigation benefits for each investment were estimated using the social costs of carbon (40 USD$/ton CO2). This analysis was based on best available data for likely changes in emissions based on the types of actions the interventions would stimulate for the expected number of project beneficiaries. The analysis suggests the value of mitigation benefits are not trivials at this price, with total value ranging between 5.4 m USD$ to 18.6 m US$ depending on intervention and risks (Table E-6). Value at the prevailing market rate would be nearly an order of magnitude lower. It must be noted that these analysis are very uncertain given the lack of information on emissions and sequestration rates in the targeted agroecosystems and the lack of information concerning the number of beneficiaries implementing each type of intervention. PAGE 110 Table E-6: Value of mitigation benefits assuming carbon price of 40 US$/ton CO2 VALUE (MILLION US$) Investment NO RISKS ALL RISK Flood recession agriculture 7.7 ± 0.9 5.7 ± 0.9 Crop-livestock integration 7.4 ± 3.1 5.4 ± 2.4 Non-timber forest products 18.6 ± 2.7 13.5 ± 2.4 Remote sensing and monitoring 12.0 ± 3.8 9.7 ± 3.2 PAGE 111 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Annex F: Climate-Smart economic appraisal: methodology and extended results NATIONAL-SCALE CLIMATE-SMART INVESTMENTS F-1 Remote Sensing and Applied Geomatics Program F-2 National Extension System Program F-3 Agroclimatic Information Services Program F-4 National Soil Fertility Monitoring   BENEFICIARIES PROPOSED DEVELOPMENT OUTCOME (PDO) 200,000 agricultural workers Increase capacity to effectively manage natural resource areas, evalu- Remote Sensing and their households ate farm productivity, and address climate-related risks by providing and Applied Geo- nationally land managers, agricultural producers, farm advisors, and policymak- matics ers with timely, accurate GSIS. 186,048 agricultural workers Increase farm productivity and minimize climate-related risks by im- Extension System and their households proving the quality and quantity of CSA-informed recommendations nationally made to producers by farm advisors. 400,000 agricultural workers Increase farm productivity and mitigate climate-related risks by Agroclimatic Info and their households providing producers, extension agents, and agribusiness with timely, System nationally accurate agrometeorological information. 103,360 agricultural workers Increase agricultural producers’ ability to practice CSA by providing and their households producers and extension agents with location-tailored information Soil Fertility Mon- nationally on soil characteristics and best management practice recommenda- itoring tions, and the tools, products, partnerships, and policy environment to implement those recommendations. CLIMATE-SMART CROP AND LIVESTOCK INVESTMENTS F-5. Non-Timber Forest Product Value Chains Program F-6. Flood Recession Agriculture Program F-7. Crop-Livestock Integration Program F-8. Millet-Sorghum-Legume Integration Program F-9. Climate-Smart Vegetable Production, Storage, and Processing Program F-10. Restoring Degraded Lands Program F-11. Rice Intensification System Promotion Program F-12. Climate Smart Wheat Development Program PAGE 112 BENEFICIARIES PROPOSED DEVELOPMENT OUTCOME (PDO) Non-Timber Forest 122,400 women producers and Bolster Malian economic growth, food security, and climate Product Value processors in Koutiala region resilience through developing the agroforestry NTFP sector. Chains 224,000 smallholders in flood- Increase farm productivity and minimize climate risks by Flood Recession plain region providing producers, extension agents, and agribusiness with Agriculture technical support and improved infrastructure for optimized flood recession agricultural practices. 97,000 smallholders in Segou Increase farm productivity and minimize climate risks by pro- Livestock region viding producers, extension agents, and agribusiness with best management practices and tools for crop-livestock integration. 199,495 women farmers in Kou- Increase the climate resilience and productivity of millet-sor- Millet-Sorghum Le- likoro and Segou regions ghum systems to improve nutritional and economic outcomes gume Integration of smallholders. 52,747 women, youth in Niono, Increase productivity and climate resilience of vegetable pro- Kati, and Bandiagara Cercles. duction, while fostering economic opportunities for produc- Vegetables ers, esp. women and youth, while minimizing environmental impact. 106,461 agricultural producers Build national capacity to restore degraded lands at scale to Restoring Degraded Nioro, Yelimand, and Kayes increase climate resilience, ecosystem services, and agricultural Lands Cercles (Sahel, Karakor, and productivity. Koussane Communes, resp) 72,480 producers in unflooded Increase rice productivity and climate resilience by scaling SRI rice production zone, Niger basin to improve economic and nutritional outcomes. Rice Intensification between Mopti and Segou cities, (SRI) and part of Tenenkou, Macine, and Segou Cercles 71,856 smallholders in Niono Increase wheat productivity and climate resilience by scaling Wheat region CSA practices to improve economic and nutritional outcomes. F-1 Remote Sensing and Applied Geomatics Program Introduction and Strategic Context: Geospatial information and geoinformatics for climate-smart agriculture Timely, accurate, and accessible information and statistics on agriculture and the environment is foundational to CSA. Stakeholders ranging from Ministries of Finance to in-the-field extension officers require the information to track key performance indicators and plan national budgets to that make site-specific recommendations for improved agricultural management to farmers, respectively. Availability of information facilitates evidence-based decisions and accountability in programming. In short, data helps increase efficiency in CSA programming (value for money) and countries and project developers tell their story, robustly with data. Resulting transparency and accountability helps to stimulate investment by public and private-sector actors. Geoinfomatics includes a range of data collection, analysis and interpretation tools that aid in decision making. For example, geoinfomatics can quickly compile and convey information on changes in soil moisture, plant health, and vegetative stress that allows land managers and producers to anticipate and manage adverse conditions, take advantage of favorable ones, and adapt to change. Year-to-year mapping supports land and forestry management decisions, and provides feedback on the outcomes of management decisions. Services such as index insurance and famine early warning systems are increasingly using remote sensing. Crop and land use mapping enable informed policy, cutting-edge research, and optimized extension agent recommendations at the regional and national levels. PAGE 113 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Increased variability associated with climate change has made informed land management decision-making increasingly difficult. Unpredictably and extremes—in pest and disease outbreaks, natural resource degradation, agricultural productivity, and weather, among other things—are hallmarks of climate change. Resource-poor smallholder farmers, especially in sub-Saharan Africa, are particularly vulnerable to loss from extreme events. Without advance notice, unpredictable changes can lead to significant loss and contribute to persistent poverty and food insecurity130. Geographic information systems (GIS) provide a tool for translating geographic data into practical advisories, transmit them over accessible communication channels, and invest in the capacity of end users to understand and leverage the information. Practical advisories are actionable and directly inform decision making. Examples may include crop production forecasts and recommendations, pest and disease forecasts, forest cover change advisories, and information on new CSA practices and technologies. In general, mass media and ICT are the most effective communication channels for short-term information, such as sudden events; structured in-person participatory processes are most effective for longer-term production strategizing and for building capacity of end users to understand information and act effectively131. Socioeconomically- and culturally-informed design of geospatial information delivery processes help ensure access for the most vulnerable potential beneficiaries. Factors such as age, gender, and socioeconomic status can affect an individual’s ability to access advisories and join participatory and capacity building processes. For example, extension services are often biased toward male farmers, and women’s household responsibilities often preclude them from listening to radio broadcasts or attending community gatherings. Communication strategies that leverage multiple channels have proven to be effective in this regard, as well as making geospatial information available in places and processes that are already part of the most vulnerable populations’ routines, such as health centers, boreholes, and women’s groups132. Country Context for Geoinformatics Mali is experiencing unpredictable variations and extremes due to climate change. The region suffers drought, extreme temperatures, high winds, and irregular rainfall as a result of climate change. Bush fires have become increasingly common during periods of drought, extreme temperatures, and high winds133. Shortages in fodder and fuel resources drive deforestation, further exacerbating shortages, natural resource degradation, and the effects of climate change. Mali has relatively good existing capacity for agricultural statistics but lacks funding. Mali ranked 21st out of 52 in the African Development Banks Capacity Assessment for Agricultural Statistics134. While institutional infrastructure was there, the assessment suggests that rarely is sufficient resources available. 130 CCAFS, “10 Best Bet Innovations for Adaptation in Agriculture: A Supplement to the UNFCCC NAP Technical Guidelines 131 CCAFS, “Agricultural Advisory Services at a Global Scale.” 132 Huyer et al., “What We Know about Gender and Rural Climate Services.” 133 Expert Panel Workshop, Non-Timber Forest Product Value Chains Project Components. African Development Bank. 2014. Country Assessment of Agricultural Statistical Systems in Africa: Measuring the Capacity of African 134 Countries to Produce Timely, Reliable, and Sustainable Agricultural Statistics. African Development Bank: Abidjan. PAGE 114 Geoinformatics have already proven viable in Mali. Remote sensing has been used successfully as part of famine early warning systems, agricultural development planning, crop type classification, land preparation characterization, landscape characterization, and reforestation monitoring135. These large-scale projects empower policymakers, service providers, and researchers. Further development of the resulting information into practical GSIS advisories will extend such decision support tools to land managers, extension agents, and farmers. Institutional and Sectoral Alignment Implementing a geoinformatics Program is a priority for the Malian government. The 2018 National Investment Plan prioritizes forest management and redevelopment, dissemination of information on forest resources, protection of natural resources, and agricultural productivity136. The 2013 National Policy for Agricultural Development highlights the need to assess and monitor natural and agricultural resources and invest in wildlife, forest management, and sustainability137. This investment also aligns with NDC interests and AEDD priorities. This national priority aligns with the goals of international alliances to which Mali belongs. As part of the Nationally Determined Contributions plan under the Paris Accord, Mali has invested in projects addressing rainwater harvesting and storage, assisted natural regeneration, and intelligent agricultural development for water management138. The African Union Agenda on Agricultural Growth and Transformation aims to promote sound management of natural resources as well as agricultural, livestock, and forest productivity139. The West African Economic and Monetary Union Amended Treaty and the Economic Community of West African States Vision 2020 both prioritize the sustainable economic development and climate resilience of their member states, including Mali140. This project also addresses Sustainable Develop Goal 12: Sustainable Consumption, Goal 13: Combat Climate Change, Goal 15: Protect Ecosystems; and indirectly addresses Goal 2: End Hunger and Goal 8: Sustainable Economic Growth141. Multiple international organizations have collaborated with Mali in addressing this priority issue. The Global Climate Change Alliance in Mali dedicated 5.65 million EUR142 to conducting forest inventories and utilized geo-referencing tools to monitor community reforestation projects. Continuing efforts will include improving the operational capacity of the Forest Information System and establishing a national Measurement Reporting and Verification System143. 135 Dodo, “Examining the Potential Impacts of Climate Change on International Security”; Famine Early Warning Systems Network, “FEWS NET Data Center”; Gumma et al., “Prioritization of Watersheds across Mali Using Remote Sensing Data and GIS Techniques for Agricultural Development Planning”; Clevers, “Remote Sensing and Crop Recognition: Improving the Information System around Smallholders in Mali.” 136 GiZ, “National Investment Plan for the Implementation of the Determined Contributions.” 137 Rural Development Directorate, “Agricultural Development Policy.” 138 Expert Panel Workshop, Non-Timber Forest Product Value Chains Project Components. 139 Department of Rural Economy and Agriculture, “Livestock Development Strategy for Africa 2015-2035.” 140 West African Economic and Monetary Union, “The Amended Treaty”; Economic Community of West African States, “Vision 2020.” 141 Knoema, “Sustainable Development Goals of Mali.” 142 Dodo, “Examining the Potential Impacts of Climate Change on International Security.” 143 Global Climate Change Alliance+, “GCCA in Mali.” PAGE 115 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN USAID’s FEWS NET provides early warning famine services based on the geospatial data and satellite imagery provided by the United States Geologic Services144. Africa RISING, in coordination with CGIAR, IITA, and USAID, have prioritized Malian watersheds as part of agricultural development planning using remote sensing data145. The Spurring Transformation for Agriculture Through Remote Sensing project focuses on crop type classification, including crop variability, crop similarity at various growing stages, different land preparation practices, and landscape characteristics146. Proposed Development Objective and Results Proposed Development Objective: This project aims to increase capacity to effectively manage natural resource areas, evaluate farm productivity, and address climate-related risks by providing land managers, agricultural producers, farm advisors, and policymakers with timely, accurate geospatial information and advisories. Beneficiaries: The mobile-based advisories subcomponent of this project will directly benefit up to 200,000 rural agricultural workers ages 15 and up147 and their households during the 10-year project duration. Integration of geospatial information and advisories into radio station programs, health centers, women’s groups, and/or extension agent advisory services would significantly increase the potential beneficiary population by accessing non-mobile subscribers. Indirect benefit via resulting climate-conscious policy and extension recommendations could feasibly reach all Malian agricultural producers. Project Description: This project is designed to provide land use managers and policymakers with geospatial information and advisories to inform environmental and agricultural outcomes and resilience in the face of climate change. Activities will aim to develop: (i) infrastructure, (ii) capacity, (iii) practical advisories, (iv) institutions, and (v) enabling policy. Project Components COMPONENT 1: Develop Infrastructure Key Actors: AMEDD, CIDEX, SIFOR, INSAT, MEADD, MA, AMM, APCAM This component will augment the quality and accessibility of infrastructure necessary to support a timely, accurate geospatial database and information system. Specifically, this will include: (i) conduct a network optimization study of existing national infrastructure, (ii) acquire and install necessary equipment (e.g., Liddar, processors, high-resolution imagery, drones) based on study outputs and available financing, (iii) develop and operationalize a national maintenance plan, (iv) apply inventory practices to use and maintenance of equipment, and (v) determine funding scheme for maintenance and replacement of equipment. 144 Famine Early Warning Systems Network, “FEWS NET Data Center.” 145 Gumma et al., “Prioritization of Watersheds across Mali Using Remote Sensing Data and GIS Techniques for Agricultural Development Planning.” 146 Clevers, “Remote Sensing and Crop Recognition: Improving the Information System around Smallholders in Mali.” 147 Mobile subscriber penetration in Mali is 60.5%, representing about 11.5 million unique subscribers. Assuming penetration among the 18.6% of the population (3.54/19 million) that resides in the capital is 100%, then penetration outside the capital is about 52%, or 8 million unique subscribers. 80% of all Malians identify themselves as farmers. Assuming that 0% of residents of the capital identify as farmers, then approximately 96% of the population outside the capital is employed by agriculture. About 52% of the population is ages 15 and up. This implies that approximately 4 million individuals are employed by agriculture and subscribe to mobile services. World Population Review, “Mali Population 2018”; Index Mundi, “Mali Demographics Profile 2018”; GSMA, “The Mobile Economy: West Africa.” PAGE 116 COMPONENT 2: Build Remote Sensing and Geoinfomatics System (GIS) Key Actors: AMEDD, CIDEX, SIFOR, INSAT, MEADD, MA, AMM, IPR, IFRA, ICRAF, CIAT This component will establish a spatial and temporal monitoring program for ecosystem agricultural statistics to support productivity and resilience148. Specifically, this will include: (i) implement continuous remote sensing returns of geospatial and temporal data by region and resource, (ii) develop agricultural production and forest and rangeland status evaluation mechanisms, (iii) clean and consolidate historical geospatial data, (iv) operationalize a system to continuously integrate incoming geospatial, temporal, and evaluation data, and (v) analyze data for actual and predicted patterns. COMPONENT 3: Institutional Mapping and Enabling Policy Key Actors: AMEDD, CIDEX, MEADD, MA, CENI In this component, key players in system management, information communication, and decision- making are identified and organized in order to ensure the system is both maintained and fully leveraged for national welfare149. Subcomponents may include: (i) institutional arrangements to bring together geomatic information manager, agricultural research and extension, national policymakers, and farmer representatives to complete Components 1-4, (ii) creation of a MultiDisciplinary Working Group to guide the project, (iii) identification of roles, communication flow, chain of command, and operating procedures for sharing and decision-making regarding geomatic information outputs, (iv) incorporation of resulting information and predictions into planning and policy, and (v) funding availability for the establishment and maintenance of a national agroclimatic network. COMPONENT 4: Build Capacity Key Actors: AMEDD, CIDEX, SIFOR, INSAT, MEADD, MA, AMM This project component will build capacity of a critical mass of staff (identified in Component 3) to use and maintain the system, to leverage information outputs in decision-making processes, and to support land use managers in using the information to inform decision making processes150. Subcomponents will include: (i) training of relevant staff in equipment use and maintenance, (ii) training relevant decision-makers on interpreting and applying geoinfomatics information, (iii) train- the-trainer model for relevant staff in data collection applications and information dissemination processes to ensure organizational knowledge development, (iv) integrating use of geoinfomatics tools into CSA advisory and technical assistance curricula, and (v) training extension staff on recognizing when age, gender, or socioeconomic status may affect an individual’s ability to access and leverage geoinfomatics tools. COMPONENT 5: Develop and Disseminate Advisories Key Actors: AMEDD, CIDEX, MA, MEADD, APCAM, NGOs This component will translate data into immediately applicable information and recommendations and share them through channels that are socially, culturally, and economically appropriate and inclusive. This will include: (i) revision of existing resources (e.g., agroclimatic maps) and development 148 Expert Panel Workshop, Remote Sensing and Geomatics Project Components. 149 Expert Panel Workshop 150 Expert Panel Workshop. PAGE 117 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN of new advisories (e.g., crop production and forest management recommendations, pests and disease risks), (ii) establishment of decentralized geo-service access centers, (iii) integration into existing extension structures, (iv) integration into places frequented by producers (e.g., boreholes, health offices, and women’s groups), and (v) development of ICT channels (e.g., mobile (SMS, call) services, radio broadcasting, and web portals). Risks: The primary risks associated with this project are as follows151: RISK PROBABILITY SEVERITY Political and Security Crises Medium High Institutional Instability Medium Medium Inclement Weather Medium Low Discord between National and Regional Policies/Actors Low Low Poor Information sharing among Key Stakeholders/Limited Access to Information Low Low F-2 National Extension System Program Introduction and Strategic Context High-quality extension services are foundational to climate-smart agriculture (CSA). Climate and agricultural science is at the heart of CSA. Nevertheless, scientific information alone is not generally beneficial to agricultural producers. The translation of climate information into practical recommendations tailored to local conditions is crucial to enabling farmers to prepare for, adapt to, and mitigate climate variability and change. Concomitantly addressing productivity, adaption, and mitigation in order to seize trade-off opportunities, e.g., mitigation through adaption co- benefits, optimizes farmer resilience152. Extension systems are the means by which this translation occurs. Furthermore, farm advisors play a major role in promoting CSA by supporting technology development, strengthening farmers’ capacity, facilitating conversations between producers and other stakeholders (e.g., researchers, processors, cooperatives), and advocating for pro-CSA policy153. Extension systems can also serve as institutional mechanicams to facilitate across-scale interaction and consequent cross-fertilization, such as through co-testing and developing of CSA options with communities and use of the same for information district and national science-policy platforms154. Extension services that are prepared to take on these highly interdisciplinary roles are the outgrowth of substantial investment in the institutional capacity of national meteorological services, agricultural research organizations, and farm advisory service providers155. Extension services in West Africa are undergoing significant change. Climate change has created an increasing need for highly customized extension services provided through a variety of channels by extension agents well trained in cutting edge research and technology. As a result, there is a strong movement toward decentralization, pluralistic provision of services, and privatization. The majority of countries now feature a blend of public, non-governmental, and private organizations offering extension services to smallholders. Information-communication technologies, such as mobile phone, 151 Expert Panel Workshop 152 Zougmore, CCAFS ICRISAT Africa Program Leader; Bamako, Mali. 153 Napolitano, “Supporting Agricultural Extension towards Climate-Smart Agriculture.” 154 Zougmore, CCAFS ICRISAT Africa Program Leader; Bamako, Mali; CCAFS, “New Knowledge Sharing Platform Helps Mali Rig Better Defense against Climate Change.” 155 CCAFS, “10 Best Bet Innovations for Adaptation in Agriculture: A Supplement to the UNFCCC NAP Technical PAGE 118 radio, and television, have become increasingly common tools for service delivery. Holistic extension services, including traditional farmer field schools and new climate-smart villages156 and farms-of- the-future157, are also becoming increasingly common. In spite of this diversification, women remain proportionally underserved by extension service providers. The rapidly growing Malian agricultural sector has challenged the national extension service. The Ministry of Agriculture employs approximately 646 field extension staff158 to serve the approximately 7.72 million agricultural workers ages 15 and up159, or 1 farm advisor for every 11,950 farmers. Even assuming family units of 4 adults, this amounts to a formidable 2,998 families, or 15-16 villages160, per farm advisor. In contrast, the World Bank’s standard ratio is 800 farmers per advisor161, and the Malian government-set rate is 6-8 villages per advisor162. Given this ratio, extension staff increasingly rely on relay farmers to disseminate extension recommendations. Approximately half of the field staff have a 2-3 year agricultural diploma, with the remaining having a high school diploma. Senior management, subject matter specialists, in-service training staff, and ICT support staff generally hold 4-year degrees163. The National Agriculture Directorate’s Agricultural and Rural Education Division hosts occasional continuing education programs. Bolstering extension services is a priority for the Malian government. The 2018 National Investment Plan prioritizes forest management and redevelopment, dissemination of information on forest resources, protection of natural resources, and agricultural productivity164. The 2013 National Policy for Agricultural Development highlights the need to assess and monitor natural and agricultural resources and invest in wildlife and forest management and sustainability165. ECOWAS’ West Africa CSA Alliance supports member countries, including Mali, the implementation of the Alliance’s CSA Framework166. Mali has engaged with international organizations such as World Bank167, IFAD168, and the UNDP169 in fostering agricultural productivity through producer capacitation. Most recently, the Develop Local Extension Capacity Project, implemented by Digital Green in coordination with USAID, IFPRI, CARE, and GFRAS, to mobilize communities around improved advisory services170. This national priority aligns with the goals of international alliances of which Mali is a part. As part of the Nationally Determined Contributions plan under the Paris Accord, Mali has invested in projects addressing intelligent agricultural development171. The African Union Agenda on Agricultural Growth 156 CCAFS, “Climate-Smart Villages: An AR4D Approach to Scale up Climate-Smart Agriculture.” 157 Ouedraogo et al., “L’Approche « fermes Du Futur » Pour Accélérer l’adaptation Au Changement Climatique.” 158 USAID, “Mali: In-Depth Assessment of Extension and Advisory Services.” 159 Index Mundi, “Mali Demographics Profile 2018”; World Population Review, “Mali Population 2018.” 160 USAID, “Mali: In-Depth Assessment of Extension and Advisory Services.” 161 Feder, Ganguly, and Anderson, The Rise And Fall Of Training And Visit Extension. 162 USAID, “Mali: In-Depth Assessment of Extension and Advisory Services.” 163 USAID. 164 GiZ, “National Investment Plan for the Implementation of the Determined Contributions.” 165 Rural Development Directorate, “Agricultural Development Policy.” 166 The West Africa CSA Alliance, “Regional CSA Alliances and Platforms: Information Sheet.” 167 World Bank, “Projects : Mali-Fostering Agricultural Productivity.” 168 IFAD, “Rural Youth Vocational Training, Employment and Entrepreneurship Support Project.” 169 UNDP, “PAPAM.” 170 USAID, “Mali: In-Depth Assessment of Extension and Advisory Services.” 171 Expert Panel Workshop, Non-Timber Forest Product Value Chains Project Components. PAGE 119 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN and Transformation strongly supports extension services as part of its aim to promote sound management of natural resources and efficient agricultural productivity172. The West African Economic and Monetary Union Amended Treaty and the Economic Community of West African States Vision 2020 both prioritize the sustainable economic development and climate resilience of their member states, including Mali!73. This project also directly addresses Sustainable Development Goal 2: Zero Hunger, Goal 5: Gender Equality, Goal 8: Economic Growth, Goal 9: Innovation, Goal 12: Responsible Production, Goal 13: Climate Action, and indirectly addresses Goal 10: Reduced Inequalities, Goal 11: Sustainable Communities, Goal 15: Life on Land, and Goal 16: Strong Institutions174. Proposed Development Objective and Results Proposed Development Objective: This project aims to increase farm productivity and minimize climate-related risks by improving the quality and quantity of CSA-informed recommendations made to producers by farm advisors. Beneficiaries: The project will directly benefit 186,048 rural agricultural workers ages 15 and up175 and their households during its 8-year term176. Diverse dissemination channels, including farmer field schools, climate-smart villages177, farm-of-the-futures178, radio station programs, health centers, women’s groups, and/or mobile services, would significantly increase the potential beneficiary population179. For example, approximately 4 million agricultural producers are mobile subscribers180; these individuals are poised to directly benefit from SMS and/or call-based extension services. Indirect benefit via improved agricultural productivity, economic outcomes, nutritional security, and climate resilience could feasibly reach all Malian agricultural producers. Project Description: This project is designed to increase the capacity of the extension system to provide recommendations to producers that are informed by and promote CSA practices. The project will address (i) demand-driven development of new CSA technologies and information as well as (ii) timely, effective dissemination of the same to producers. Activities will aim to develop (i) capacity for multistakeholder CSA research, (ii) capacity of extension agents to effectively reach producers with high-quality CSA recommendations, and (iii) developing communication channels and policy environmental to support effective extension services. 172 Department of Rural Economy and Agriculture, “Livestock Development Strategy for Africa 2015-2035.” 173 West African Economic and Monetary Union, “The Amended Treaty”; Economic Community of West African States, “Vision 2020.” 174 Knoema, “Sustainable Development Goals of Mali.” 175 We assume the current extension field staff of approximately 646 could each directly reach 800 farmers, per the World Bank standard ratio. USAID, “Mali: In-Depth Assessment of Extension and Advisory Services”; Feder, Ganguly, and Anderson, The Rise And Fall Of Training And Visit Extension. 176 Expert Panel Workshop, Extension Services Project Components. 177 CCAFS, “Climate-Smart Villages: An AR4D Approach to Scale up Climate-Smart Agriculture.” 178 Ouedraogo et al., “L’Approche « fermes Du Futur » Pour Accélérer l’adaptation Au Changement Climatique.” 179 CCAFS, “10 Best Bet Innovations for Adaptation in Agriculture: A Supplement to the UNFCCC NAP Technical Guidelines.” 180 Mobile subscriber penetration in Mali is 60.5%, representing about 11.5 million unique subscribers. Assuming penetration among the 18.6% of the population (3.54/19 million) that resides in the capital is 100%, then penetration outside the capital is about 52%, or 8 million unique subscribers. 80% of all Malians identify themselves as farmers. Assuming that 0% of residents of the capital identify as farmers, then approximately 96% of the population outside the capital is employed by agriculture. About 52% of the population is ages 15 and up. This implies that approximately 4 million individuals are employed by agriculture and subscribe to mobile services. GSMA, “The Mobile Economy: West Africa”; Index Mundi, “Mali Demographics Profile 2018”; World Population Review, “Mali Population 2018.” PAGE 120 Project Components COMPONENT 1: Increase Technical Capacity of Extension Agents in CSA Key Actors: MA, DNA, AMASSA-Afrique Verte, CAEB, Sahel Eco, Stop Sahel, CCAFS This component will train farm advisors in cutting-edge CSA181. Specific subcomponents will include: (i) integration of CSA module into (a) all training centers’ curricula, (b) University of Bamako and IPR- FRA curricula, and (c) in particular agriculture-based M.S and Ph.D. programs, (ii) CSA-focused field trips for mid-level staff (iii) establishment of a continuous training system for all extension agents with a focus on (a) newly generated technical and scientific knowledge and (b) emerging concepts in CSA, (iv) discontinuation of promotion of any practices found to not be climate-smart under current and anticipated climate conditions, and (v) revision of curriculum and training materials to integrate CSA. COMPONENT 2: Systematize CSA Technology Dissemination Key Actors: MA, DNA, MEP, MEADD This project component will operationalize systems for timely dissemination of information to producers182. Specifically, this will include: (i) leveraging existing regional science-policy innovation platforms as a means for extension support delivery183, (ii) development of new education tools and guides with a focus on (a) climate smart villages and farms-of-the future, (b) co-testing and developing CSA options with communities, (c) use of resulting science and lessons learned in regional innovation platform decision-making, and (d) functional literacy, (iii) technical capacitation of relay farmers to broaden reach,(iv) development and implementation of multiple ICT dissemination channels, including radio and mobile, and (v) fostering decentralization of the advisory system through creation of additional satellite offices. COMPONENT 3: Establish Feedback Channels to Researchers Key Actors: MA, DNA, DLCA, AMASSA-Afrique Verte, CAEB, Sahel Eco, Stop Sahel This component will operationalize systems for timely feedback receipt by research organizations to ensure practical, demand-driven research. Namely, this will include: (i) integration of data collection into extension activities in order to inform needs prioritization, (ii) leveraging the existing national science-policy innovation platform to consider success and evidence from district level platforms in Component 2184, (iii) funding of multistakeholder and public-private research grants, financing contracts, and research prizes, (iv) full use of national and international research sites for instructional demonstration, and (v) establishing strong multistakeholder ties between research institutions, private industry, NGOs and advisory services through shared staff, regional workshops, strategic plan development, scientific journal publications, evaluation of scientific results, etc. COMPONENT 4: Bolster Scientific Research Key Actors: MA, DNA, MEP, AMASSA-Afrique Verte, CAEB, Sahel Eco, Stop Sahel This component will promote effective research conducted by highly skilled professionals. Specific steps will include: (i) renovate research centers and equipment as needed, (ii) promote researchers 181 Expert Panel Workshop, Extension Services Project Components. 182 Expert Panel Workshop 183 Zougmore, CCAFS ICRISAT Africa Program Leader; Bamako, Mali 184 Zougmore PAGE 121 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN and research centers that produce meaningful results via a system of bonuses, awards, grants, and media publications, (iii) institute research “incubators” in universities (iv) establish research clusters in each region, and (v) create a national database of current skills that will enable identification of missing skill for prioritization in recruitment, training, and organizational cooperative agreements. COMPONENT 5: Create Enabling Policy Environment Key Actors: MA, DNA, MEP, MEADD This component will foster strong extension services via a supporting policy environment185. Specifically, this will include: (i) establishing a national system of CSA extension services, (ii) developing a pluralistic business model approach to extension services with a focus on ICT, (iii) developing tools and systems to monitor and evaluate the implementation of CSA in extension services, (iv) earmarking funding for CSA extension services, and (v) decentralizing the national extension system. Risks: The primary risks associated with this project are summarized below186: RISK PROBABILITY SEVERITY Political and Security Crises Medium Medium Discord between National and Regional Policies/Actors Low Low Low Support Structure Capacity Medium Medium Poor Information sharing among Key Stakeholders/Limited Access to Informa- Low Low tion F-3 Agroclimatic Information Services Introduction and Strategic Context Weather is a primary risk for agricultural production, and climate change has made weather significantly more variable, extreme, and difficult to predict. Resource-poor smallholder farmers, especially in sub-Saharan Africa187, are particularly vulnerable to loss from extreme weather events. Without advance notice of near term weather, impending hazards, or access to technologies (e.g., irrigation systems) to buffer crops and livestock against unfavorable conditions, climate fluctuations can cripple production and contribute to persistent poverty and food insecurity188. Timely, accurate, accessible agrometeorological information is foundational to CSA. Climate information services (CIS) communicate climate knowledge to farmers and other end users. Effective CIS reduce the uncertainty surrounding erratic climactic patterns, allowing producers and agribusiness to anticipate and manage adverse weather conditions, take advantage of favorable ones, and adapt to change189 to better manage climatic risks. They also support climate-informed policy, planning, and extension agent recommendations190. 185 Expert Panel Workshop, Extension Services Project Components. 186 Expert Panel Workshop. 187 Welle, “Extreme Weather.” 188 CCAFS, “Climate Services in Agriculture”; CCAFS, “Agricultural Advisory Services at a Global Scale”; CCAFS, “Putting Farmers at the Centre of Climate Information Services”; Tesfaye et al., “Estimating the Economic Benefits of Alternative Options for Investing in Agricultural Climate Services in Africa: A Review of Methodologies”; CCAFS, “Participatory Integrated Climate Services for Agriculture (PICSA).” 189 CCAFS, “10 Best Bet Innovations for Adaptation in Agriculture: A Supplement to the UNFCCC NAP Technical Guidelines.” 190 CCAFS; CCAFS, “Building Climate Services Capacity in Rwanda”; Zougmore, CCAFS ICRISAT Africa Program Leader; Bamako, Mali. PAGE 122 Well-designed CIS translate data into practical advisories, transmit them over accessible communication channels, and invest in the capacity of end users to understand and leverage the information191. Practical advisories are actionable and directly inform decision making; examples may include crop production forecasts and recommendations, pest and disease forecasts, extreme weather advisories, information on new CSA practices and technologies, and actionable tactical development choices based on future climatic scenarios192. In general, mass media and ICT are the most effective communication channels for short-term information, such as in-season forecasts and major weather events; structured in-person participatory processes are most effective for longer- term production strategizing and for building capacity of end users to understand information and act effectively193. Socioeconomically- and culturally-informed design of CIS delivery processes help ensure access for the most vulnerable potential beneficiaries.. Factors such as age, gender, and socioeconomic status can affect an individual’s ability to access advisories and join participatory and capacity building processes194. For example, extension services are often biased toward male farmers, and women’s household responsibilities often preclude them from listening to radio broadcasts or attending community gatherings. Communication strategies that leverage multiple channels have proven to be effective in this regard, as well as making CIS available in places and processes that are already part of the most vulnerable populations’ routines, such as health centers, boreholes, women’s groups195, and Mali’s sub-national multidisciplinary working groups196. Mali is experiencing extreme weather events due to climate change. In the Sahelian region, temperatures are projected to increase, and rainfalls have been continuously decreasing since 2001 (DSU, 2016). Precipitation variability makes annual flooding increasingly difficult to predict (DSU, 2016; Nenkam, 2017). These changing weather patterns are shifting productive regions southward, putting more pressure on an already intensive agricultural region (DSU, 2016). Without reliable CIS, Malians are caught unaware by such extreme weather events; impoverished individuals are more likely to live in vulnerable areas, and are less able to invest in recovery following loss197. Mali has been a pioneer in implementing CIS. In 1982, the Mali National Meteorological Directorate introduced the Rural Agrometeorological Assistance Project to supply rural communities with climate information to support agricultural management decision processes. This Program was envisioned as a collaborative process between farmers, extension agents and the government (CCAFS, 2014). 191 Expert Panel Workshop, Agromet Theorie du Changement; CCAFS, “Participatory Integrated Climate Services for Agriculture (PICSA)”; CCAFS, “10 Best Bet Innovations for Adaptation in Agriculture: A Supplement to the UNFCCC NAP Technical Guidelines”; CCAFS, “Rwanda Establishes a National Framework for Climate Services”; CCAFS, “Climate Services for Farmers.”as part of  the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS 192 CCAFS, “Agricultural Advisory Services at a Global Scale”; Tesfaye et al., “Estimating the Economic Benefits of Alternative Options for 191 Investing in Agricultural Climate Services in Africa: A Review of Methodologies”; CCAFS, “Participatory Integrated Climate Services for Agriculture (PICSA)”; Expert Panel Workshop, Agromet Theorie du Changement; Huyer et al., “What We Know about Gender and Rural Climate Services”; CCAFS, “Rwanda Establishes a National Framework for Climate Services”; CCAFS, “Building Climate Services Capacity in Rwanda”; Zougmore, CCAFS ICRISAT Africa Program Leader; Bamako, Mali. 193 CCAFS, “10 Best Bet Innovations for Adaptation in Agriculture: A Supplement to the UNFCCC NAP Technical Guidelines”; CCAFS, “Participatory Integrated Climate Services for Agriculture (PICSA).” 194 Partey et al., 2018 (a) 195 Huyer et al., “What We Know about Gender and Rural Climate Services”; CCAFS, “Climate Services for Farmers.” 196 Partey et al., 2018(b) 197 Welle, “Extreme Weather.” PAGE 123 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Participating farmers were provided with rain gauges and weather forecasts along with technical support in pesticide use, seed application, etc. Participants’ yields were significantly higher than that of their non-participant counterparts. Evidence showed that the adoption rates were high, suggesting that Malian farmers are willing and able to adopt CIS, and that they consider it to be a credible source of information (Tall, 2014; Hellmuth, 2010). Some challenges remain in scaling the early success CIS in Mali. Foundational advisory services on staple food crops, soil conditions and water availability (Hellmuth, 2010) would provide context for effective use of CIS services. Expansion of the CIS program to other crops, in coordination with culturally-informed dissemination channels, would increase the currently very low adoption rate among women; the program does not currently include the crops primarily grown by women (Carr, 2015). A system of monitoring and evaluation would enable quantitative assessment of impacts, as well as direct links between approach and outcomes, thus allowing for tool optimization according to farmer’s needs (Tall, 2014). Developing CIS is a priority for the Malian government and its allies. The Participatory Integrated Climate Services for Agriculture project, implemented by CGIAR, seeks to provide farmers with local climate information in a participatory setting. In 2017, the Green Climate Fund awarded a grant of US$22 million to foster the capacity of domestic hydro-meteorological services in the country under the Africa Hydromet Program (DSU, 2016). The upcoming ECOWAS Hydromet program, valued at 65 million USD, will support the National Meteorological and Hydrological Services to improve service delivery198. The Climate Risk and Early Warning Systems Project (CREWS), USD$22.75 million, is supported by IDA and the Green Climate Fund to enhance the country’s hydro-meteorological and warning capabilities199. This initiative will directly address Sustainable Development Goal 2: Zero Hunger, Goal 8: Economic Growth, and Goal 13: Climate Action; it also indirectly supports Goal 9: Innovation and Infrastructure, Goal 15: Life on Land, and Goal 16: Strong Institutions. This investment also aligns with NDC interests and AEDD priorities. Proposed Development Objective and Results Proposed Development Objective: This project aims to increase farm productivity and mitigate climate-related risks by providing producers, extension agents, and agribusiness with timely, accurate agrometeorological information. Beneficiaries: The mobile-based advisories subcomponent of this project will directly benefit 400,000 rural agricultural workers ages 15 and up200 and their households. Integration of CIS into radio station programs, health centers, women’s groups, and/or extension agent advisory services would significantly increase the potential beneficiary population by accessing non-mobile subscribers. Indirect benefit via resulting climate-conscious policy and extension recommendations could feasibly reach all Malian agricultural producers. 198 Zougmore, CCAFS ICRISAT Africa Program Leader; Bamako, Mali. 199 https://reliefweb.int/report/mali/mali-seeks-strengthen-climate-risk-and-early-warning-systems 200 Mobile subscriber penetration in Mali is 60.5%, representing about 11.5 million unique subscribers. Assuming penetration among the 18.6% of the population (3.54/19 million) that resides in the capital is 100%, then penetration outside the capital is about 52%, or 8 million unique subscribers. 80% of all Malians identify themselves as farmers. Assuming that 0% of residents of the capital identify as farmers, then approximately 96% of the population outside the capital is employed by agriculture. About 52% of the population is ages 15 and up. This implies that approximately 4 million individuals are employed by agriculture and subscribe to mobile services. World Population Review, “Mali Population 2018”; Index Mundi, “Mali Demographics Profile 2018”; GSMA, “The Mobile Economy: West Africa. PAGE 124 Project Description: This project is designed to scale CIS in Mali such that agricultural producers, extension agents, agribusiness, and policymakers have access to timely, accurate agrometeorological data. The project will address (i) public sector systems and technical capacity to produce and convey agromet information, (ii) producer technical ability to access and leverage agromet information, (iii) physical infrastructure, (ii) data aggregation, synthesis, and dissemination systems, and (iii) capacity for maintaining and leveraging CIS. Project Components COMPONENT 1: Produce and Process Data Key Actors: MALI-METEO, MA This component will lay the foundation for an effective CIS by producing and storing accurate meteorological data at the appropriate spatial resolution. The public sector will (i) conduct a network optimization study, and acquire, install, and maintain weather stations based on results and current financing, (ii) automate collection and processing of new weather data, including satellite-derived data, (iii) clean and consolidate historical weather data, as well as agricultural and phenological data, on comparable scales as the monitored meteorological data (iv) integrate these three datasets, and (v) analyze data for actual and predicted patterns201. COMPONENT 2: Translate Data into Practical Advisories Key Actors: MA, MALI-METEO, research institutions, universities, MEADD, CCAFS, FEWSNET This project component will translate data into immediately applicable information and recommendations, such as: (i) revision of national agroclimatic measures, e.g., seasonal calendars and agroclimatic maps202 (ii) crop production forecasts203 and recommendations per degree of risk and potential gain204, (iii) agroclimatic modeling of pests and disease risk205 (iv) an early warning system for unfavorable events, such as dry spells, heat waves, and storms206 (v) information regarding new CSA practices and technologies, e.g., stress-tolerant seed varieties207, agroforestry systems, and climate-smart soil and water conservation measures208. 201 Tesfaye et al., “Estimating the Economic Benefits of Alternative Options for Investing in Agricultural Climate Services in Africa: A Review of Methodologies”; CCAFS, “Rwanda Establishes a National Framework for Climate Services”; Expert Panel Workshop, Agromet Theorie du Changement. 202 Expert Panel Workshop, Agromet Theorie du Changement. 203 Tesfaye et al., “Estimating the Economic Benefits of Alternative Options for Investing in Agricultural Climate Services in Africa: A Review of Methodologies.” 204 CCAFS, “Participatory Integrated Climate Services for Agriculture (PICSA).” 205 Expert Panel Workshop, Agromet Theorie du Changement; CCAFS, “Building Climate Services Capacity in Rwanda”; CCAFS, “Rwanda Establishes a National Framework for Climate Services.” 206 Expert Panel Workshop, Agromet Theorie du Changement; Huyer et al., “What We Know about Gender and Rural Climate Services”; CCAFS, “Rwanda Establishes a National Framework for Climate Services.” 207 CCAFS, “Agricultural Advisory Services at a Global Scale.” 208 Zougmoré et al., 2014; Zougmoré et al., 2018 PAGE 125 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN COMPONENT 3: Develop Products and Services to Communicate Advisories Key Actors: MA, MALI-METEO, research institutions, universities, NGOs, MEADD, CCAFS In this component, dissemination channels for the advisories developed in Component 2 are created that are socially, culturally, and economically appropriate and inclusive209. Channels may include: (i) mobile (SMS, call) services (ii) radio broadcasting, (ii) a web-GIS portal, (iii) periodic and special newsletters, (v) integration into places frequented by producers (e.g., boreholes, health offices, women’s groups, sub-national multidisciplinary working groups210)), and (v) integration into existing extension structures211. COMPONENT 4: Train Farmers on Using Data Key Actors: MEADD, MA, NGOs, CCAFS This component will focus on increasing capacity for CIS. Namely, this will consist of (i) train-the-trainer model for relevant staff in data collection applications and information dissemination processes, Examples: PICSA, CCAFS, various African countries; Climate Services for Agriculture, CGIAR, Rwanda (ii) training of relevant staff in equipment maintenance, (iii) integrating a weather and climate module into CSA technical assistance curricula (iv) training extension staff on recognizing when age, gender, or socioeconomic status may affect an individual’s ability to access CIS, and (v) ongoing training on use of CIS for producers and agribusiness. Example: PICSA, CCAFS, various African countries212. COMPONENT 5: Institutional Capacity and Systematized Collaboration Key Actors: MA, MALI-METEO, research institutions, universities, NGOs, MEADD, CCAFS This component will help ensure that the technical capacity and communication networks are in place to scale CIS via Components 1-4. Specifically, this will include: (i) establishing partnerships with national (e.g., IER), regional (e.g., AGRHYMET Centre, ACMAD) and international (e.g., CCAFS, IRI, FEWSNET) research institutions, (ii) creation of a national multidisciplinary working group to guide the project213, including climate information providers, researchers, extension agents, policymakers, farmers, and NGOs, Example: National Consultative Workshop, Rwanda; (iii) incorporation of climate information and prediction into planning and policy via the national science-policy dialogue platform on CSA facilitated by AEDD-Mali214 (iv) funding availability for the establishment and maintenance of a national agroclimatic network215, and (v) training all relevant stakeholders in leveraging CIS in their work, including (a) extension agents, (b) policy-makers, (c) regional governance, and (d) researchers. 209 Tesfaye et al., “Estimating the Economic Benefits of Alternative Options for Investing in Agricultural Climate Services in Africa: A Review of Methodologies”; CCAFS, “Rwanda Establishes a National Framework for Climate Services”; Huyer et al., “What We Know about Gender and Rural Climate Services.” 210 Partey et al. 2018(b) 211 Expert Panel Workshop, Agromet Theorie du Changement; CCAFS, “Climate Services for Farmers”; CCAFS, “10 Best Bet Innovations for Adaptation in Agriculture: A Supplement to the UNFCCC NAP Technical Guidelines”; Tesfaye et al., “Estimating the Economic Benefits of Alternative Options for Investing in Agricultural Climate Services in Africa: A Review of Methodologies”; CCAFS, “Building Climate Services Capacity in Rwanda”; Huyer et al., “What We Know about Gender and Rural Climate Services”; CCAFS, “Climate Services for Farmers.” 212 CCAFS, “Participatory Integrated Climate Services for Agriculture (PICSA)”; Expert Panel Workshop, Agromet Theorie du Changement; CCAFS, “Building Climate Services Capacity in Rwanda”; Huyer et al., “What We Know about Gender and Rural Climate Services”; CCAFS, “Rwanda Establishes a National Framework for Climate Services.” 213 Expert Panel Workshop, Agromet Theorie du Changement. 214 Andrieu, et al. 2017. 215 Expert Panel Workshop; CCAFS, “Rwanda Establishes a National Framework for Climate Services”; Tesfaye et al., “Estimating the Economic Benefits of Alternative Options for Investing in Agricultural Climate Services in Africa: A Review of Methodologies.” PAGE 126 Risks: The main risks for this project are as follows: RISK PROBABILITY SEVERITY Political and security crises Medium High Discord between national and regional policies/actors Low Low Limited information sharing/access to information Low Low F-4 National Soil Fertility Monitoring Program Introduction and Strategic Context Soil health is essential to climate-smart agriculture. Healthy soils regulate nutrient and water cycles increasing the soil fertility while contributing to carbon sequestration, agricultural productivity and buffering climate change and variability. Agriculture typically has negative effects on soils. Continuous cropping and tillage depletes nutrients when they are exported off the field in crop biomass and reduces carbon. There is a general trend of nutrient loss in sub-Saharan cropping systems. Even with current rates of manure and fertilizer applications, African agriculture falls short of replenishing nutrient uptake by crops by at least 20kg/ha N, 10kg/ha P, and 20kg/ha K every year216. As a result, soil degradation threatens at least 25% of African arable land and impedes agricultural production and intensification217. African smallholders have limited access to amendments to improve soil fertility. Lack of subsidies, poor infrastructure, low biomass production and limited opportunities to acquire credit put the quantities of fertilizers necessary to optimize crop productivity out of reach for most smallholders. As such, optimizing crop productivity through via integrated soil fertility management (ISFM)—that is, targeted, location-specific optimization of interactions between fertilizers, organic inputs, and improved varieties--are crucial to achieving soil fertility and crop productivity. Identifying ISFM best practices for a given farm require significant location-specific knowledge of soil characteristics, such as soil type, depth, texture, fertility, organic matter content, etcetera. Soil information systems (SIS) have been shown to enable ISFM on a large scale. The World Agroforestry Center (ICRAF) has developed spectral diagnostics218 using infrared and x-ray technology that allow for rapid and low-cost analysis of soil properties and plant nutrients, which can then be applied at scale for digital mapping219. The level of detail, accuracy, and geographic scale that this technology offers at low cost promises to shift the soil management paradigm220. The Africa Soil Information Service (AfSIS)221 has applied this technology to generate detailed national SIS in Ethiopia, Ghana, Nigeria, and Tanzania and at smaller scales in Ivory Coast. Organizations such as SoilCares222, 216 Stoorvogel and Smaling, “Assessment of Soil Nutrient Depletion in Sub-Saharan Africa: 1983-2000.” 217 Vanlauwe et al., “Looking Back and Moving Forward”; Jones et al., Soil Atlas of Africa. 218 Soil-Plant Spectral Diagnostics Lab, “Network of Dry Spectroscopy Laboratories.” 219 World Agroforestry Centre, “Soil-Plant Spectral Diagnostics Laboratory.” 220 World Agroforestry Centre, “Testimonials.” 221 Africa Soils, “Africa Soil Information Service.” 222 SoilCares, “Soil analysis for farmers.” PAGE 127 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN the Crop Nutrition Services Laboratory, the Gates Foundation, One Acre Fund223, and FoodAfrica have leveraged ICRAF’s spectral diagnostic technology to generate soil maps224, plan projects, and conduct testing services across Africa. Malian soils can be very agriculturally productive under ISFM. The Sudano-Guinean region primarily features low-fertility Ultisols, which can be productive given significant fertilizer inputs. The Sudanian region consists primarily of Alfisols, which have naturally high fertility and good potential for agriculture. Nevertheless, this region has seen a steady decline in soil fertility due to increasing population pressure, an increase of livestock production, and a decrease in fallow periods as climate change has pushed productive regions southward225. The Sahel is generally characterized by Aridisols, which have high salt content and are only agriculturally productive when irrigation water is available 226. Malian smallholder’s degree of access to fertilizers creates demand for IFSM efforts. Ongoing efforts on the part of governments, NGOs, and international organizations have significantly improved fertilizer access and usage in the last decade. Average fertilizer consumption has increased from 6 kg/ha of arable land in 2009 to 29 kg/ha in 2015227. This remains far below the global average of 133kg/ha228, as well as the amounts necessary to optimize crop productivity (i.e. fertilizer industry- recommended application rates). Nonetheless, the nearly 500% improved accessibility presents an important opportunity for implementation of ISFM practices using targeted dosing of inorganic fertilizers as informed by a national SIS. Protecting and enhancing soil resources is a priority of the Malian government and its partners. The Economic Community of West African States has partnered with the International Fertilizer Development Center and the West Africa Fertilizer Program to model and map site-specific fertilizer recommendations for major food crops across West Africa229. USAID has invested heavily in soil modeling and mapping in Mali through the West Africa Fertilizer Program230. A range of donors and research institutions, including the Bill & Melinda Gates Foundation, ISRIC World Soil Information, and Wageningen University, are engaged in development of the African Soil Information Service (AfSIS). The European Commission’s Joint Research Centre, in collaboration with the African Union and FAO, have brought together soil experts from Europe and Africa to produce the first ever Soil Atlas of Africa with the aim of raising awareness among the general public and across disciplines of the significance of soil to human existence in Africa231. The 4 pour Mille Initiative launched by the French Government in 2015 promotes the implementation of agricultural practices that enhance organic matters in soils. This project directly addresses Sustainable Development Goal 2: Zero Hunger, Goal 12: Responsible Production, Goal 13: Climate Action, and Goal 15: Life on Land, and indirectly supports Goal 8: Economic Growth and Goal 10: Reduced Inequalities232. 223 One Acre Fund, “2017 Annual Report.” 224 ISRIC, “SoilGrids”; Africa Soils, “Africa Soil Information Service.” 225 FAO, 2017; Groundswell, 2011 226 University of Idaho, 2018. 227 World Bank Data 2015 228 ibid 229 ISRIC, “Taking Fertilizer Recommendations to Scale for Major Crops in West Africa.” 230 ISRIC 231 Jones et al., Soil Atlas of Africa 232 Knoema, “Sustainable Development Goals of Mali.” 232 We assume the current extension field staff of approximately 646 could each directly reach 800 farmers, per the World Bank standard ratio. USAID, “Mali: In-Depth Assessment of Extension and Advisory Services”; Feder, Ganguly, and Anderson, The Rise And Fall Of Training And Visit Extension. PAGE 128 Proposed Development Objective and Results Proposed Development Objective: This project aims to increase agricultural producers’ ability to practice CSA by providing producers and extension agents with location-tailored information on soil characteristics and best management practice recommendations, as well as the tools, products, partnerships, and policy environment to implement those recommendations. Beneficiaries: The project will directly benefit 103,360 rural agricultural workers ages 15 and up233 and their households during its 5-year term. Across time, diversification of SIS channels, such as radio station programs, health centers, women’s groups, and/or mobile services, would significantly increase the potential beneficiary population234. For example, approximately 4 million agricultural producers are mobile subscribers235; these individuals are poised to directly benefit from SMS and/or call-based SIS. Indirect benefit via improved agricultural productivity, economic outcomes, nutritional security, and climate resilience could feasibly reach all Malian agricultural producers. Project Description: This project is designed to support producer’s soil management decisions with a national SIS. This will contribute to the goal of promoting CSA practices in Mali. The project will address (i) development of an SIS (ii) development and dissemination of decision-support tools and products, including via stakeholder partnerships, (iii) extension agent capacity to utilize and recommend these tools and products, and (iv) producer capacity to fully leverage these tools and products in management decision support. Project Components COMPONENT 1: Support Soil Management Research Key Actors: LABOSEP, MA, MALI-METEO, universities, INSAT, CGIAR, research institutions This component will gather the foundational knowledge necessary to establish a national SIS. Subcomponents will include: i) conduct soil fertility management optimization trials in all soil regions, ii) conduct soil biological soil process management optimization trials in all soil regions, iii) employ spectral technology to characterize soil profiles nationally at 1km specificity, iv) develop and communicate best management practice recommendations for each 1km area based on results of i-iii, and v) develop tools and products (e.g., fertilizer blends, lab analyses, field test kits, hedge saplings, clean cover crop seed, soil amendments) to support recommended management practices236 . 233 We assume the current extension field staff of approximately 646 could each directly reach 800 farmers, per the World Bank standard ratio. USAID, “Mali: In-Depth Assessment of Extension and Advisory Services”; Feder, Ganguly, and Anderson, The Rise And Fall Of Training And Visit Extension. 234 CCAFS, “10 Best Bet Innovations for Adaptation in Agriculture: A Supplement to the UNFCCC NAP Technical Guidelines.” 235 Mobile subscriber penetration in Mali is 60.5%, representing about 11.5 million unique subscribers. Assuming penetration among the 18.6% of the population (3.54/19 million) that resides in the capital is 100%, then penetration outside the capital is about 52%, or 8 million unique subscribers. 80% of all Malians identify themselves as farmers. Assuming that 0% of residents of the capital identify as farmers, then approximately 96% of the population outside the capital is employed by agriculture. About 52% of the population is ages 15 and up. This implies that approximately 4 million individuals are employed by agriculture and subscribe to mobile services. GSMA, “The Mobile Economy: West Africa”; Index Mundi, “Mali Demographics Profile 2018”; World Population Review, “Mali Population 2018.” 236 Expert Panel Workshop; Africa Soils, “Africa Soil Information Service”; ISRIC, “Taking Fertilizer Recommendations to Scale for Major Crops in West Africa.” PAGE 129 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN COMPONENT 2: Develop National Soil Information Service Key Actors: LABOSEP, MA, MEADD, universities, CGIAR, research institutions This component will develop a national SIS tool to support producer management decisions. Specifically, this will involve: i) establishing and training governmental staff dedicated to developing and maintaining the SIS ii) generate publicly accessible SIS, including digital soil maps and soil aptitude maps, based on the results of Component 1 iii) maintain and update SIS based on new research findings, iv) formalize a communication channel between staff and research organizations to ensure up-to-date information and recommendations are integrated into the SIS in a timely fashion, and v) establish private industry partnerships (e.g., agribusiness, analysis laboratories, research facilities) to create or significantly increase availability of the tools and products recommended by research organizations to producers and extension agents237. Examples: AfSIS’ EthioSIS, Ethiopia; GhaSIS, Ghana; NiSIS, Nigeria, and TanSIS, Tanzania238. COMPONENT 3: Extension Worker Technical Assistance and Linkages Key Actors: LABOSEP, MA, MEADD, APCAM This component will increase extension agent capacity to use the SIS to support producer best management practices. Subcomponents include: i) technical assistance on accessing and navigating the SIS ii) orientation on accessing and utilizing the tools and products developed by research organizations and made available through private industry collaborations iii) formalizing a multiway communication system between extension agents, research organizations, and producers239. COMPONENT 4: Producer Technical Assistance Key Actors: LABOSEP, MA, MEADD, APCAM This component will increase producer capacity to leverage the SIS to support management decision making. Specifically, this will include i) conduct public awareness campaigns on general good management practices (e.g., composting, biofertilizers, targeted fertilizer microdosing, crop rotation, crop association, improved fallow, leguminous cover cropping, intercropping, agroforestry), ii) integrate best management practice recommendations by soil region into existing communication and technical assistance channels (e.g., participatory training, extension advising, climate information systems) iii) develop practical decision making support tools based on the SIS for use by producers and extension agents (e.g., mobile information system, national call center, participatory training tools), and iv) via all channels specified in i-iii, ensure producer awareness of tools and products recommended by research institutions and practical steps for accessing them240. COMPONENT 5: Support Producer Long-term Decision Making Key Actors: LABOSEP, MA, MEADD, APCAM, private sector This component will increase producer likelihood to invest in long-term soil health. Specific steps include: i) strengthening property rights and registries to increase producer willingness to invest in their land, ii) conducting public awareness campaigns of soil as a nonrenewable resource, iii) increasing producer access to credit via means 237 Expert Panel Workshop; World Agroforestry Centre, “Soil-Plant Spectral Diagnostics Laboratory”; Hengl et al., “Soil Nutrient Maps of Sub-Saharan Africa”; Soil-Plant Spectral Diagnostics Lab, “Network of Dry Spectroscopy Laboratories.” 238 Africa Soils, “Africa Soil Information Service.” 239 ibid 240 Expert Panel Workshop. PAGE 130 such as: (a) strengthening microfinance sector performance via greater regulation241, (b) regulating banking agents to improve the percentage of rural adults with access to formal financial service points, and (c) allowing and encouraging the use of crops, inventory, or equipment as collateral242. Risks: The main risks for this project are as follows: RISK PROBABILITY SEVERITY Political and security crises Medium High Lack of funding and/or institutional accountability to acquire and maintain equip- High High ment Discord between national and regional policies, actors Low Low Poor information sharing among key stakeholders Low Low F-5 Non-Timber Forest Product Value Chains Program Introduction and Strategic Context Deforestation exacerbates the effects of climate change and reduces the resilience of smallholders. Trees support many ecosystem functions, including temperature regulation; carbon sequestration; soil stabilization, structure, moisture regulation, and fertility; wind breaks; and shade for other species. Removing trees from the landscape destabilizes soil, making it more susceptible to wind and water erosion. The reduction in soil organic matter inputs negatively impacts soil structure, fertility, and water holding capacity. Full sun exposure reduces the ability of other plant and animal species to regulate their temperature and retain water; it also rapidly depletes soil moisture and can negatively impact soil biota. The release of carbon sequestered in wood directly contributes to the causes of climate change243. Deforestation also causes fuel shortages, degrades productive land areas, and exposes crops to greater climate variability. Non-timber agroforestry product value chains support and promote climate-smart agriculture (CSA) practices. Integrating multipurpose trees into agricultural landscapes diversifies smallholder livelihoods, thus improving resilience, productivity, economy, and nutritional security. It also contributes to climate change mitigation through carbon sequestration, improved soil quality, temperature control, soil moisture regulation, and reduced erosion. Importantly, the value of non- timber forest products also serves as a direct incentive to communities to reduce deforestation or even expand forest area, thus preventing and mitigating the effects of climate change244. 241 World Bank, “Atelier de Restitution, Diagnostic de Finance Agricole et Plan d’Action.” 242 Palmer, “Making Climate Finance Work in Agriculture”; CCAFS, “10 Best Bet Innovations for Adaptation in Agriculture: A Supplement to the UNFCCC NAP Technical Guidelines.” 243 Oakland Institute, “Agroforestry to Improve Farm Productivity in Mali”; Sidibe, Myint, and Westerberg, “An Economic Valuation of Agroforestry and Land Restoration in the Kelka Forest in Mali”; Kandji, Verchot, and Mackensen, “Climate Change and Variability in the Sahel Region:”; Zomer et al., “Global Tree Cover and Biomass Carbon on Agricultural Land”; Iiyama et al., “Tree-Based Ecosystem Approaches (TBEAs) as Multi-Functional Land Management Strategies—Evidence from Rwanda.” 244 Iiyama et al., “Tree-Based Ecosystem Approaches (TBEAs) as Multi-Functional Land Management Strategies—Evidence from Rwanda. PAGE 131 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Practices such as assisted natural regeneration and contouring farming increase the climate resilience of agroforestry systems. Contour strips can be formed by trees, shrubs, grasses, and/or other plants, and is very cost effective compared with other methods245. The improved soil cover and shading, erosion control, and water use maximization that contouring offers is particularly crucial in water-scarce regions and under the increased climate variability associated with climate change. Assisted natural regeneration supports the establishment of secondary forests by protecting and nurturing mother trees and their saplings that occur naturally in the area246. West African women play a key role in agroforestry production and processing. Women are traditionally responsible for growing seedlings, planting, watering and weeding. In terms of harvesting and processing, women are generally responsible for subsistence products such as fodder, firewood, and fruits. Women also own some product processing and marketing. For example, women produce butter, nuts, and kernels from the shea tree247. The fruit, leaves, flowers, bark, seeds, branches, and roots of the baobab are harvested to create a variety of products, including dye, juice, jam, rope, gum, seed oil, dishes, and water storage containers248. The fruit and leaves of zaban shrubs are prized for juice and jam production249. In addition to its highly valued gum, the leaves and pods of the gum arabic tree are excellent fodder250. Country Context for Non-Timber Forest Product Value Chains Multipurpose trees play an important role in the Malian landscape and nutritional security. Agroforestry parkland helps mitigate the effects of climate change through dune and soil stabilization, improved soil quality, and acting as a wind break. Within agroforestry systems, tree crops are frequently combined with millet, sorghum, sesame, and groundnuts, and frequently increase crop yields and improve soil quality. Agroforestry improves smallholder farm resilience by creating an additional source of forage for livestock, firewood for the home, and regulated microclimates for crops and livestock251. Forage trees are especially important toward the end of the dry season and during droughts since their deep roots can access water and continue to feed livestock252. Agroforestry represents an important economic opportunity for Mali. Many smallholder households engage in shea, baobab, zaban, and gum arabic value chains to supplement income from crop and livestock production. The shea and gum arabic markets are particularly well developed both locally and internationally. Mali is the world’s second largest producer of shea, and a major producer of gum arabic. These markets imply significant opportunity to expand the Malian value- added agricultural sector. Given that most Malian agroforestry producers and processors are women, this project also offers improved gender equality in work opportunity253. 245 Xu, An Agroforestry Guide for Field Practitioners 246 FAO, “Assisted Natural Regeneration of Forests.” 247 Kiptot, “Gender Roles, Responsibilities, and Spaces: Implications for Agroforestry Research and Development in Africa.” 248 Gebauer et al., “Africa’s Wooden Elephant.” 249 Daily Mail, “The Juice Startup Putting Mali in a Bottle.” 250 “The Gold in Acacia Trees.” 251 Iiyama et al., “Tree-Based Ecosystem Approaches (TBEAs) as Multi-Functional Land Management Strategies—Evidence from Rwanda.” 252 Kandji, Verchot, and Mackensen, “Climate Change and Variability in the Sahel Region:” 253 Tadesse, “Natural Gums and Resins: Potential Dryland Non Timber Forest Products of Ethiopia”; Boffa, “Opportunities and Challenges in the Improvement of the Shea (Vitellaria Paradoxa) Resource and Its Management.” PAGE 132 Agroforestry in Mali is not without challenges. The region suffers drought, extreme temperatures, and irregular rainfall as a result of climate change. Bush fires can quickly damage or destroy large swaths of parkland. High winds are common and particularly risky during tree crop flowering254. Continuous harvesting for firewood, charcoal, fodder, and large-scale land development has reduced existing stands of trees considerably. This deforestation has instigated significant soil degradation. Persistent drought has shifted the shea suitable growing region southward255. Culturally, it is uncommon for producers to invest in planting indigenous tree species. Access to improved planting material is very limited. Where it is available, planting of improved shea is often seen as a long-term land claim, and is thus restricted on rented or borrowed plots. Prices for internationally traded goods, such as shea butter, can vary significantly, and wholesale prices of raw products are oftentimes too low to make a profit. Agroforestry product processing is labor intensive, and often requires a sustained heat source; this fuelwood demand can instigate deforestation256. Climate-smart agricultural practices can foster greater resilience in Malian agroforestry. Practices such as intercropping, cover cropping, mulching, and contour farming help retain soil and water resources. Assisted natural regeneration, incentivized planting campaigns, and raising awareness of the benefits and importance of forest resources can help ensure fodder, fuelwood, and other tree resources are planted at replacement rates. Supporting farmer groups, bolstering product value chains, and negotiating trade agreements help ensure sustainable livelihoods and reliable markets for smallholders. Institutional and Sectoral Alignment Developing non-timber forest product value chains is a priority for the Malian government. The 2018 National Investment Plan prioritizes maximizing value added processing of Malian raw materials, establishing an enabling investment environment for value chains that empower smallholders and processors, and protecting and sustaining natural resources257. The 2013 National Policy for Agricultural Development highlights significant investments in sustainble wildlife and forest management258. This also aligns with priority projects on agriculture and forestry identified by the AEDD259. This national priority aligns with the goals of international alliances of which Mali is a part. As part of the Nationally Determined Contributions plan under the Paris Accord, Mali has invested in projects addressing rainwater harvesting and storage, assisted natural regeneration, and strategic agricultural development for water management260. The African Union Agenda on Agricultural Growth and Transformation aims to promote sound management of natural resources as well as agricultural productivity261. The West African Economic and Monetary Union Amended Treaty and the Economic Community of West African States Vision 2020 both prioritize the economic and financial competitiveness of their member states, including Mali262. 254 Expert Panel Workshop, Non-Timber Forest Product Value Chains Project Components. 255 Venturini et al., “Cultivating Climate Resilience: The Shea Value Chain.” 256 Boffa, “Opportunities and Challenges in the Improvement of the Shea (Vitellaria Paradoxa) Resource and Its Management”; Rousseau, Gautier, and Wardell, “Coping with the Upheavals of Globalization in the Shea Value Chain.” 257 GiZ, “National Investment Plan for the Implementation of the Determined Contributions.” 258 Rural Development Directorate, “Agricultural Development Policy.” 259 Programme quinquennal d’aménagement forestiers (2018-2022)  260 Expert Panel Workshop, Non-Timber Forest Product Value Chains Project Components. 261 Department of Rural Economy and Agriculture, “Livestock Development Strategy for Africa 2015-2035.” 262 West African Economic and Monetary Union, “The Amended Treaty”; Economic Community of West African States, “Vision 2020.” PAGE 133 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN This project also directly addresses Sustainable Development Goal 2: Zero Hunger, Goal 5: Gender Quality, Goal 8: Economic Growth, Goal 12: Sustainable Consumption and Production, and Goal 13: Combat Climate Change, and indirectly addresses Goal 9: Sustainable Industrialization, and Goal 15: Protect Ecosystems263. Multiple international organizations have collaborated with Mali in addressing this priority issue. Agronomists and Veterinarians Without Borders has worked to develop the gum arabic sector in Kayes. The FAO and the National Directorate collaborate on commercialization of non-timber forest products264. The World Agroforestry Centre has completed many agroforestry projects in Mali, and has two ongoing projects; Scaling up Climate-Smart Agroforestry Technologies for Improved Market Access, Food, and Nutritional Security in Mali is funded by USAID, and Reversing Land Degradation by Scaling-up Evergreen Agriculture is funded by the European Commission265. The start-up Zabbaan has begun marketing natural juices made from local Malian products266. Proposed Development Objective and Results Proposed Development Objective: This project aims to bolster Malian economic growth, food security, and climate resilience through development of the non-timber agroforestry product sector. Beneficiaries: The project will directly benefit 122,400267 women producers and processors, as well as their households, in the rural Koutiala region268 of the Guinea-Soudanian zone269. The initial project term will be 5 years. Across time, indirect benefit via improved economic outcomes, climate resilience, and nutritional security could feasibly reach all Malian agricultural producers in the Soudanian and Guinea-Soudanian zones. Project Description: This project is designed to promote the non-timber forest product sector through establishment of fundamental foundations for the same. The project will address: (i) research and development, (ii) production, (iii) postharvest, and (iv) value chains. Project Components COMPONENT 1: Agroforestry Park Renewal Key Actors: MEADD, NGOs, IPR, IER, Aboriginal Land Authorities This component will support development and adoption of an agroforestry park renewal strategy270 Specifically, this includes: (i) establishing an assisted natural regeneration program, (ii) raising public 263 Knoema, “Sustainable Development Goals of Mali.” 264 Expert Panel Workshop, Non-Timber Forest Product Value Chains Project Components. 265 World Agroforestry Centre, “Projects | Mali.” 266 Daily Mail, “The Juice Startup Putting Mali in a Bottle.” 267 Approximately 815,000 Malians live in specified region. 80% of all Malians identify themselves as farmers. Assuming that the 18.6% of the population (3.54/19 million) that resides in Bamako does not identify as farmers, then approximately 96% of the population outside the capital is employed by agriculture. This implies that about 783,000 people in the target region are farmers. About 52% of the population is ages 15 and up, and about 50% of the population is female, meaning that there are approximately 204,000 woman agriculturalists in the target region. Earth Institute, “Segou Population Data”; Index Mundi, “Mali Demographics Profile 2018”; Nations Online Project, “Political Map of Mali”; Socioeconomic Data and Applications Center, “Population Density Grid”; Statoids, “Mali Regions”; World Population Review, “Mali Population 2018.” 268 Oakland Institute, “Agroforestry to Improve Farm Productivity in Mali.” 269 Expert Panel Workshop, Non-Timber Forest Product Value Chains Project Components. 270 Expert Panel Workshop. PAGE 134 awareness on regeneration process, importance of forest resources, and benefits of planting indigenous tree species at replacement rates, (iii) establishing a resource center for extension agents, land managers, and other decision makers, (iv) multistakeholder convenings to discuss priorities, action steps, progress, research outputs, and the results of Components 4-6; and (v) operationalizing an incentive system for planting of indigenous varieties and improved varieties from Component 6. COMPONENT 2: Contouring for Rainwater Conservation and Harvest Key Actors: MEADD, NGOs, IPR, IER This project component will promote the use of agroforestry contouring for soil and water resource conversation271. Specific components will include: (i) research on best management practices in contouring for each agro-region, (ii) extension agent training on the benefits of contouring and best management practices identified through research, (iii) integration of these recommended practices into extension and field school modules, (iv) raising public awareness of the benefits of contour agriculture, and (v) financial assistance (e.g., grants, subsidies, loans, credit) for cooperatives and smallholders to invest in contour agriculture establishment. COMPONENT 3: Strengthen Value Chains Key Actors: MEADD, Chamber of Commerce, private sector This component will strengthen the commercial processing of agroforestry products by offering technical assistance to women’s groups and formalizing trade and market agreements272. Specifically, this will include: (i) improving access to appropriate mechanization tools, and technical assistance in their use to increase efficiency and decrease cost, e.g., hydraulic presses, solar distillers and evaporators, mechanical filters, non-wood sources of heat; (ii) training in new processing techniques to diversify product options, (iii) establishing fair trade agreements with shea processing companies (iv) facilitating working agreements between cooperatives and private-sector business partners (e.g., storage facilities, store fronts, packaging producers, etc.) to stabilize prices and service availability, and (v) entrepreneurship training and mentorship programs for cooperatives (e.g., with private industry business partners). COMPONENT 4: Stand Mapping and Integration Key Actors: MEADD, IPR, IER, NGOs This component will focus on mapping agroforestry regions and leveraging this information in decision-making, research, and policy decisions273. Project subcomponents will consist of: (i) employ remote sensing to map stands, (ii) update existing resources with new data, (iii) operationalize an information service to enable land managers, extension agents, policymakers, and other stakeholders to access and use data, (iv) develop research priorities in collaboration with various stakeholders for mapping services, and (v) provide technical assistance to extension agents and policymakers in leveraging mapping information in their work. 271 Expert Panel Workshop 272 Expert Panel Workshop 273 Expert Panel Workshop PAGE 135 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN COMPONENT 5: Construct Postharvest Storage and Processing Units Key Actors: MEADD, Chamber of Commerce, private sector This component will support postharvest value chains via the creation of storage and processing units274. Specifically, this includes: (i) customized financial services (e.g., grants, subsidies, credit and loan) for cooperatives to construct storage and processing facilities and/or acquire processing equipment, (iii) technical assistance for cooperatives to meet requirements for receiving financial services, (iii) regional storage facility construction, and (iv) operationalization of warehouse receipts system. COMPONENT 6: Develop and Disseminate Improved Varieties Key Actors: MEADD, IPR, IER, NGOs, ICRAF This component will support the development of improved agroforestry varieties275. Specifically, this will include: (i) research and development of improved varieties of shea, baobab, gum acacia, and zaban, (ii) research and publication of best management practices for each new variety, (iii) training of extension agents in improved varieties and best management practices, (iv) training of nurseries and cooperatives in seedling production best management practices, and (v) production and distribution of seedlings. Risks: The main risks identified for this investment are summarized below. RISK PROBABILITY SEVERITY Extreme Weather (wind, drought, irregular rainfall) Medium Medium Bush Fires Medium Medium Insecurity Medium High Poor Governance Low High Low Community Engagement Low High Lack of Financing High High F-6 Flood Recession Agriculture Program Introduction and Strategic Context Flood recession agriculture is a crucial component of food security in regions of very limited precipitation, such as the West African Sahel. Flood recession agriculture leverages moisture and sediments left behind by floods to produce crops. Flood recession agriculture has been practiced in the seasonal floodplains of West Africa since at least 1,500 BC276. Common crops grown in seasonal floodplains include sorghum, maize, forage, potatoes, yams, cassava, tomato, onion, okra, and cucumber277. 272 Expert Panel Workshop. 273 Expert Panel Workshop. 274 Barbier et al., “Irrigation in West-African Sahel.” 275 Expert Panel Workshop, Flood Recession Crops Project Components 276 Barbier et al., “Irrigation in West-African Sahel.” 276 Expert Panel Workshop, Flood Recession Crops Project Components. PAGE 136 In spite of the traditional importance of this practice, research and policy on flood recession agriculture to date remains minimal278. This implies significant opportunity for optimization of flood recession agricultural practices for improved production and climate resilience. Flood recession agriculture is significantly affected by climate change. Even in years with adequate rainfall, most rivers in Mali stop flowing during the dry season. Extreme temperatures and strong winds induced by climate change drastically increase the rate of evapotranspiration from floodplains, thus reducing the soil moisture available to crops. Erratic rainfall and drought up river can eliminate flooding and the flood recession crop season altogether, bringing nutritional and economic insecurity to many smallholders. Climate-smart agricultural practices (CSA) can significantly improve flood recession production outcomes. Practices to conserve soil moisture, increase fertility, prevent erosion, and speed the production cycle help make crops more climate resilient in the face of rapidly drying floodplains, extreme temperatures, and strong winds279. Infrastructure development, such as that of low- maintenance irrigation systems, boreholes, and mechanical pumps, empowers producers to actively conserve and manage water resources during the flood recession production season. Community organization and engagement helps ensure good management of infrastructure and water resources, and mitigates conflict between pastoralists and flood recession farmers280. Country Context for Flood Recession Crops Mali has a well-established flood recession production sector that is threatened by the effects of climate change. Approximately 2 million hectares281 of land along the Niger and Senegal rivers in the Kayes, Tombouctou, and Gao regions are subject to seasonal flooding. Approximately 75,000 hectares in these areas (25% of Mali’s total productive land) is under flood recession agricultural production282. Mali is among the largest flood recession agriculture producing countries in West Africa283. Given the long history of flood recession agriculture in Mali, producers in the region have developed sophisticated techniques that are adapted to variations in flood height, soil texture, wildlife presence284, nutritional needs, and food preferences285. Nevertheless, climate change has brought new challenges that require further adaptation. Producers in the region have already demonstrated effective CSA practices in flood recession production. The Malian Institute for Rural Economies conducted flood recession agriculture trials from 2011–2016 in the Yélimané Cercle of northern Kayes. Farmers found significant benefit from CSA practices such as composting crop residues with manure and urea, mechanized sowing, soaking and transplanting seed, using improved maize (Djorobana, Sotubaka, Dembagnouma vs. landrace Maka) and sorghum (S23, S8, and S32 vs. landrace SAME) varieties, increasing sorghum planting density, and soil mounding286. 278 Minten et al., “Flood Recession Agriculture for Food Security in Northern Ghana.” 279 Traore, Aune, and Traore, “Effect of Organic Manure to Improve Sorghum Productivity in Flood Recession Farming in Yelimane, Western Mali.” 280 Expert Panel Workshop, Flood Recession Crops Project Components. 281 Thom and Wells, “Farming Systems in the Niger Inland Delta, Mali.” 282 Delaney, “Challenges and Opportunities for Agricultural Water Management in West and Central Africa.” 283 Minten et al., “Flood Recession Agriculture for Food Security in Northern Ghana.” 284 dangerous wildlife congregate in the few remaining watering holes toward the end of the dry season. Barbier et al., “Irrigation in West-African Sahel.” 285 Harlan and Pasquereau, “Décrue Agriculture in Mali.” 286 Traore, Aune, and Traore, “Effect of Organic Manure to Improve Sorghum Productivity in Flood Recession Farming in Yelimane, Western Mali.” PAGE 137 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Continued research on best CSA management practices for Malian flood recession production zones, in combination with scaled capacity and infrastructure development, will help these producers build resilience in the face of climate change, augment their productivity, and improve regional economic and nutritional outcomes. CSA in the flood recession zones is not without challenges. The region has increasingly suffered drought, extreme temperatures, high winds, and irregular rainfall287 that cripple or halt agricultural production in the floodplains288. Because flood recession takes place outside the main agricultural season, competition for land use with pastoralists increases significantly, and conflict can arise. Institutional and Sectoral Alignment Scaling flood recession cropping is a priority for the Malian government. The 2018 National Investment Plan prioritizes agricultural productivity, as well as CSA practices to protect and sustain natural resources289. The 2013 National Policy for Agricultural Development highlights significant investments in agricultural productivity and environmental sustainability290. This national priority aligns with the goals of international alliances of which Mali is a participant. As part of the Nationally Determined Contributions plan under the Paris Accord, Mali has invested in projects addressing rainwater harvesting and storage and appropriate agricultural development for improved water management291. The African Union Agenda on Agricultural Growth and Transformation aims to promote sound management of natural resources as well as agricultural productivity292. The West African Economic and Monetary Union Amended Treaty and the Economic Community of West African States Vision 2020 both prioritize the sustainable economic development and climate resilience of their member states, including Mali293. This project also directly addresses Sustainable Development Goal 2: Zero Hunger, Goal 8: Economic Growth, Goal 9: Innovation, Goal 12: Responsible Production, Goal 13: Climate Action, and indirectly addresses Goal 10: Reduced Inequalities, Goal 11: Sustainable Communities, Goal 15: Life on Land, and Goal 16: Strong Institutions. However, international organizations have not generally engaged with Mali in addressing this priority issue. Investments in flood recession agriculture have historically been sparse in general, and when they do occur, neighboring West African countries have more often been the beneficiaries. Recent political instability and the relatively sparse regional population in Mali, along with the longstanding and complex traditions of flood recession agriculture in general, may have been possible deterrents for project implementation. The overall lack of research and investment in this agricultural sector suggests that major gains could be seen by efforts to collaborate with the Malian government in CSA implementation for improved productivity and climate resilience in flood recession agricultural practices 287 Expert Panel Workshop, Non-Timber Forest Product Value Chains Project Components. 288 citation 289 GiZ, “National Investment Plan for the Implementation of the Determined Contributions.” 290 Rural Development Directorate, “Agricultural Development Policy.” 291 Expert Panel Workshop, Non-Timber Forest Product Value Chains Project Components. 292 Department of Rural Economy and Agriculture, “Livestock Development Strategy for Africa 2015-2035.” 293 West African Economic and Monetary Union, “The Amended Treaty”; Economic Community of West African States, “Vision 2020 PAGE 138 Proposed Development Objective and Results Proposed Development Objective: This project aims to increase farm productivity and minimize climate-related risks by providing producers, extension agents, and agribusiness with technical support and improved infrastructure for optimized flood recession agricultural practices. Beneficiaries: The project will directly benefit approximately 224,000294 smallholders ages 15 and up and their households during the 5-year term. Over time, indirect benefit via improved climate resilience, economic outcomes, and nutritional security could feasibly reach all Malian smallholders. Figure F-1: Flood region shown in light blue295 Project Description: This project is designed to support national economic growth and food security by developing the productivity and resilience of agricultural producers in flood recession cropping zones. The project will address: (i) research, (ii) capacity, (iii) infrastructure, and (iv) civil and private- sector engagement. Project Components COMPONENT 1: Build Producer Capacity Key Actors: IER, MEADD, RPI, DNA, MA This component will bolster farmer capacity to more efficiently manage available water resources and implement CSA to increase yields296. Specifically, training will include: (i) soil moisture regulation practices such as (a) mounding, (b) planting density, (c) mulching (d) Zai holes, and (e) shading, (ii) soil fertility practices such as (a) composting using crop residues and animal wastes, (b) fertilizer microdosing, and (c) agroforestry to prevent erosion, (iii) production acceleration practices such as (a) seed soaking, (b) mechanized planting, and (c) transplanting, (iv) best management practices for and accessing improved varieties developed in Component 4, and (v) water resource management practices such as (a) channel management to clear blockages and allow water to fill seasonal lakes, (b) installation of thresholds at the entrance of ponds, (c) rainfall collection through water retention basins, and (d) development of flood channel systems. 294 This number developed through expert opinion, but is currently under review and may be adjusted to be smaller based on the population size of the region being targeted. 295 Republic of Mali, “Second National Communication to UNFCCC.” 296 Expert Panel Workshop, Flood Recession Crops Project Components. PAGE 139 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN COMPONENT 2: Training of Extension Agents Key Actors: IER, MEADD, RPI, DNA, MA This project component will prepare farm advisors to integrate CSA practices into their recommendations on recession agriculture297. Specifically, training will include: (i) soil moisture regulation practices such as (a) mounding, (b) planting density, (c) mulching, and (d) shading, (ii) soil fertility practices such as (a) composting using crop residues and animal wastes, (b) fertilizer microdosing, and (c) agroforestry to prevent erosion, (iii) production acceleration practices such as (a) seed soaking, (b) mechanized planting, and (c) transplanting, (iv) best management practices for and accessing improved varieties developed in Component 4, and (v) water resource management practices such as (a) channel management to clear blockages and allow water to fill seasonal lakes, (b) installation of thresholds at the entrance of ponds, (c) rainfall collection through water retention basins, and (d) development of flood channel systems. COMPONENT 3: Technical Assistance to Cooperatives Key Actors: IER, MEADD, DNA, MA, NGOs In this component, cooperatives and other producer groups will receive technical assistance in both group management and value-added processing, with a focus on women’s groups298. Specifically, training will include: (i) technical assistance in value-added processing of the target flood recession crops, (ii) maintenance of government-installed infrastructure (e.g., irrigation systems), (iii) coordination between farmer groups and pastoralists for prevention of crop damage, (iv) cooperative management techniques, (v) meeting minimum transparency standards to access accounting services (e.g., risk reducing instruments, warehouse receipts, bulk purchase rates, credit, savings, loan, and other group services); and (vi) knowledge-sharing and regional coordination plans. COMPONENT 4: Bolster Research Programs Key Actors: IER, RPI, universities, NGOs, ATI This component will research and develop improved varieties and optimized farming practices to support improved climate resilience and productivity299. Namely, this will consist of: (i) research and development of improved varieties of target crops, (ii) best management recommendations for each of the improved varieties, (iii) research and development of optimized flood recession land management practices, (iv) create a system for transferring newly developed technology to producers and communicating producer priorities to researchers in a timely manner. COMPONENT 5: Develop Infrastructure Key Actors: IER, MEP, private sector, ATI, municipalities This component will develop and improve infrastructure to support productive and resilient flood recession agriculture300. This may include construction of: (i) water retention basins, (ii) flood channels systems, (iii) irrigation ditches, (iv) pond entrance thresholds, and (v) tree planting along channels, which reduces evaporation by providing shade. 297 Expert Panel Workshop 298 Expert Panel Workshop 299 Expert Panel Workshop 300 Expert Panel Workshop PAGE 140 COMPONENT 6: Civil and Private Industry Engagement Key Actors: IER, private industry, NGOs, APCAM, municipalities This component will engage NGOs, the public, and private industry in Components 1-5301. Namely, this will consist of: (i) training of local NGO employees in CSA flood recession practices, (ii) establishment of cooperative-private industry partnerships for mentorship, ongoing training, and sales and service agreements, (iii) public awareness campaigns on the benefits of flood recession agriculture, (iv) incentivization of development of financial services customized for smallholder producers and producer groups, and (v) NGO partnership agreements for continued research and development. Risks: The primary risks associated with this project are as follows302: RISK PROBABILITY SEVERITY Extreme weather (temperature, sand storms) High Low Irregular rainfall and drought High Medium Political and security crises High High Community conflict related to new irrigation infrastructure Medium High Farmer-Herder Conflict Low Medium F-7 Crop-Livestock Integration Program Introduction and Strategic Context Smallholder livestock production in sub-Saharan Africa directly impacts climate change and is impacted by climate change. The livestock sector is a significant contributor of global greenhouse gas emissions, primarily through landuse change and ruminant digestion. The developing world accounts for about ⅔ of this figure, or 12% of global emissions303. Sub-Saharan Africa is a hotspot of emissions intensity due to low animal productivity and lower animal health. The effects of climate change threaten the nutritional security of smallholder livestock farmers. Precipitation variability makes the availability of forage and water unpredictable, affecting livestock productivity and pushing pastoralists to travel longer distances and exploit more land in order to sustain their flocks304. Drought, flood, and extreme heat increases livestock mortality and destabilize markets305. Poor market access to inputs and financing, widespread animal disease, and weak policy and infrastructure further challenge the livelihoods of livestock farmers306. Climate-smart agriculture reduces the impacts of livestock systems on climate, and makes livestock systems more resilience in the face of climate change. Climate-smart approaches in livestock systems improve productivity through breeding, disease prevention, integrated crop- livestock systems to optimize feed and forage, and improved water supply and shade resources307. 301 Expert Panel Workshop 302 Expert Panel Workshop 303 Amole and Ayantunde, “Climate-Smart Livestock Interventions in West Africa: A Review.” 304 GiZ, “National Investment Plan for the Implementation of the Determined Contributions.” 305 306 Williams et al., “Agriculture Climate Smart Facing the African Context.” 307 Williams et al PAGE 141 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Animal manure is used to produce biogas and to improve soil fertility by composting crop residues308. Residues of cover crops and intercrops, such as mucuna and pigeon pea, can be used as highly nutritious fodder309. Crops already in production for human consumption, such as sorghum, groundnut and cowpea, can also be used as highly nutritious livestock feed. Improved livestock nutrition increases survival rates, as well as improving quality and quantity of animal products such as milk, meat, and hides310. The opportunities for improvement in livestock production are particularly relevant to women farmers. Women are traditionally in charge of fetching water, of which higher producing animals typically consume more. They are also responsible for milk production and sales; again, higher producing animals such as improved breeds generally produce higher quantities of milk. In addition, small ruminants, such as sheep and goats, and foul, such as chickens and ducks, are typically owned and managed by women311. Forage production can support improved feed for resilience, especially during dry seasons. Agroforestry-based forage production in particular can offer multiple production, adaption, and mitigation benefits. Trees offer crucial nutrition to maintain livestock health and productivity during the long dry season. Organic matter inputs from both tree leaves and livestock manure improve soil quality, which can mitigate degradation and improve crop yields. Trees provide habitat for beneficial insects such as crop pest predators, and protect both crops and livestock from direct sun, strong winds, high evaporation rates, and extreme temperatures. An addition to fodder, agroforestry also provides fuelwood and income diversification through forest product harvesting and sales312. Finally, tree growth mitigates climate change by sequestering carbon. Approaches to agroforestry establishment such as farmer-managed natural regeneration minimize labor and input costs and require very little training. Country Context for Crop-Livestock Integration Livestock is a core economic sector in Mali, accounting for 10% of the national GDP313. Approximately 85% of Malians own ruminant livestock and 30% rely on animal production as their primary livelihood314. There are over 9 million sheep and goats, 25 million cattle, and 1 million dromedaries on approximately 30 million hectares of pasture land, in addition to approximately 35 million poultry315. Popular local breeds include Djallonke sheep, N’dama cattle, Northern dwarf goats, and Moorish zebis. Mali is one of the largest livestock producers in the subregion316, and a major exporter of live animals in West Africa. There is a strong and growing demand for sheep and goat meat in the domestic market317. The Malian livestock sector is challenged by increasing climate variability and degrading natural resources. The primary constraint on Mali’s livestock sector is limited feed availability. Large portions of Mali’s rangelands offer limited forage with low nutritive value, protein content, and dry matter content, particularly during the dry season. Low forage availability is exacerbated by the effects of climate change, including drought, floods, extreme heat, strong winds, and degraded natural resources. 308 FAO, “Climate-Smart Livestock Production.” 309 Best Practices Note, “Selecting Legumes as Green Manure/Cover Crops.” 310 IFAD, “Overview.” 311 Expert Panel Workshop, Crop-Livestock Integration Project Components. 312 Zougmore, CCAFS ICRISAT Africa Program Leader; Bamako, Mali. 313 GIZ, “National Investment Plan for the Implementation of the Determined Contributions.” 314 GIZ 315 Rural Development Directorate, “Agricultural Development Policy.” 316 Rural Development Directorate. 317 Fall, “Mali Small Ruminant Value Chains: Where Are We?” PAGE 142 As a result, pastoral livestock have increasingly encroached on farm land, resulting in violent conflict318. Limited access to inputs and financing, recurrent disease, and weak infrastructure have further challenged livestock smallholders. Crop-livestock systems show significant promise in Sudano-Sahelian Mali, as well as other Malian agro-ecological zones. Recent research in Mali has demonstrated the viability of dual-purpose sorghum and cowpea varieties, which produce sufficient quality grains for both human consumption and animal feed. Improved cowpea varieties offer similar environmental benefits as landrace varieties, including reduced soil evaporation and improved nitrogen content. The hybrid Fadda and improved Tiandougou Coura sorghum varieties were more digestible and had significantly higher yields than the local variety Tiéblé319. Agroforestry systems and FMNR are also well suited to the Malian context320. Institutional and Sectoral Alignment Development of the livestock sector is a priority for the Malian government. The 2018 National Investment Plan prioritizes increasing the efficiency of livestock systems in order to improve nutritional security and reduce emissions per kilogram of animal product, as well as CSA practices to protect and sustain natural resources321. The 2013 National Policy for Agricultural Development highlights significant investments in pastoral resource management, processing, storage, marketing infrastructure, mechanization, and environmental sustainability322. This national priority aligns with the goals of international alliances of which Mali is a participant. As part of the Nationally Determined Contributions plan under the Paris Agreement, Mali is investing in projects addressing pastoral development and agriculture-livestock association. The African Union 2015-35 Livestock Development Strategy for Africa aims to accelerate equitable growth toward Africa’s full potential in the livestock sector323. The West African Economic and Monetary Union Amended Treaty, the Economic Community of West African States Vision 2020, and the Economic Community of West African States’ Agricultural Policy all prioritize the economic and financial competitiveness of their member states, including Mali324. This project also directly addresses Sustainable Development Goal 2: Zero Hunger, Goal 5: Gender Equality, Goal 8: Economic Growth, Goal 9: Innovation, Goal 12: Responsible Production, Goal 13: Climate Action, and indirectly addresses Goal 10: Reduced Inequalities, Goal 11: Sustainable Communities, Goal 15: Life on Land, and Goal 16: Strong Institutions. Multiple international organizations have collaborated with Mali in addressing this priority issue. The 20-year Multinational Reinforcing Resilience Against Food and Nutritional Insecurity Project (P2RS), funded by the African Development Bank, will provide Mali with 32 billion FCFA (56.6 million USD) to develop value chains and infrastructure in rural areas325. The Sahel Pastoralism Regional Support Project, funded by the World Bank and West African Economic and Monetary Union, works to improve access to essential production facilities, services, and markets for Malian livestock farmers326. 318 Expert Panel Workshop, Crop-Livestock Integration Project Components; Rural Development Directorate, “Agricultural Development Policy.” 319 Collaborative Crop Research Program, “Dual-Purpose Sorghum and Cowpeas.” 320 World Agroforestry Centre, “Farmer-Managed Natural Regeneration”; FMNR Hub, “The Spread of FMNR in Niger.” 321 GiZ, “National Investment Plan for the Implementation of the Determined Contributions.” 322 Rural Development Directorate, “Agricultural Development Policy.” 323 Department of Rural Economy and Agriculture, “Livestock Development Strategy for Africa 2015-2035.” 324 West African Economic and Monetary Union, “The Amended Treaty”; Economic Community of West African States, “Vision 2020.” 325 Niarela, “Projet-1 P2RS.” 326 PRAPS, “Projet Régional d’Appui Au Pastoralisme Au Sahel.” PAGE 143 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN The World Bank also funds the Mali Livestock Sector Development Support Project to enhance productivity and commercialization of non-pastoral animal production at 78.4 million USD327, and the Mali Natural Resources Management in a Changing Climate Project at 12 million USD328. The Mali National Directorate of Agriculture partners with UNDP to strengthen agricultural communities in the face of climate change as part of the Malian Women’s Project329. The Islamic Development Bank funds, among other things, livestock feed warehouses and watering ponds, as part of the Food Security Resilience Program (Mali-PRIA) valued at 60 billion FCFA (33.9 million USD)330. Proposed Development Objective and Results Proposed Development Objective: This project aims to increase farm productivity and minimize climate-related risks by providing producers, extension agents, and agribusiness with best management practices and tools for crop-livestock integration. Beneficiaries: The project will directly benefit 97,000 farmers smallholders and their households331 in the Segou circle of the Guinea-Soudanian zone during its 5-year term332. Indirect benefit via scaling of improved practices, and the resulting climate resilience and nutritional security, could feasibly reach many more Malian producers in the Soudanian and Guinea-Soudanian zones. Project Description: This project is designed to support national economic growth and food security by developing the productivity and resilience of agricultural producers to climate risks through crop- livestock integration. The project will address: (i) research, (ii) capacity, (iii) infrastructure, and (iv) civil engagement. Project Components COMPONENT 1: Technically Support Producers Key Actors: MEP, MEADD, IER, RPI, universities This component will increase livestock producers’ technical capacity by offering training333 in: (i) benefits of CSA in livestock production, (ii) best management practices for local and improved livestock breeds from Component 4, (iii) use and benefits of integrated crop-livestock systems, including (a) use of dual-purpose crops (e.g., sorghum, cowpea, groundnut, mucuna, bracharia, bourgou), (b) micro-climate control, and (c) integrated soil fertility management, (iv) cow and sheep fattening practices and associated milk production; and (v) disease prevention and treatments. 327 World Bank, “Mali Livestock Sector Development Support Project.” 328 World Bank, “Mali Natural Resources Management in a Changing Climate Project.” 329 United Nations Development Program, “Supporting Mali’s Women to Adapt to Climate Change.” 330 Niarela, “PRIA-MALI.” 331 The population of the Segou circle is approximately 912,000. About 80% of all Malians identify themselves as farmers. Assuming that the 18.6% of the population (3.54/19 million) that resides in Bamako does not identify as farmers, then approximately 96% of the population outside the capital is employed by agriculture. This implies that about 875,500 people in the target region are farmers. About 52% of the population is ages 15 and up, and about 50% of the population is female, meaning that there are approximately 228,000 woman agriculturalists in the target region. Nations Online Project, “Political Map of Mali”; City Population, “Mali: Administrative Division (Cercles and Communes)”; World Population Review, “Mali Population 2018.” 332 Expert Panel Workshop, Crop-Livestock Integration Project Components. 333 Expert Panel Workshop PAGE 144 COMPONENT 2: Increase Capacity of Extension Agents Key Actors: MEP, MEADD, IER, RPI This component will increase farm advisors’ capacity to integrate CSA best practices into their recommendations for livestock systems333. Specifically, this will include training in: (i) benefits of CSA in livestock production, (ii) best management practices for local and improved livestock breeds from Component 4, (iii) use and benefits of integrated crop-livestock systems, including (a) use of dual- purpose crops (e.g., sorghum, cowpea, groundnut, mucuna, bracharia, bourgou), (b) micro-climate control, and (c) integrated soil fertility management, (iv) cow and sheep fattening practices and the associated milk production, and (v) disease prevention and treatments. COMPONENT 3: Support Cooperatives and Producer Organizations Key Actors: MEP, APCAM, private sector This component will strengthen the commercial processing of crop-livestock system products by offering technical assistance and formalized relationships with private industry partners to women’s groups334. Specifically, this will include: (i) development of customized financial services (e.g., subsidies, loan, credit, grants) and rental services for cooperatives to access and/or invest in equipment, infrastructure, and improved processing facilities, (ii) training in new processing techniques to diversify product options, (iii) technical assistance in improved processing efficiency (i.e. mechanization), (iv) systemization of the creation of working agreements with private-sector business partners (e.g., store fronts, packaging producers, etc.), and (v) entrepreneurship training and mentorship programs (e.g., with private industry business partners). COMPONENT 4: Bolster Research Key Actors: MEP, IER, RPI, universities This component will bolster livestock research initiatives. Specific components will include: (i) research and development of improved sheep, goat, and poultry breeds, (ii) best management recommendations for the improved breeds, as well as local breeds (e.g., Djallonke sheep, N’dama cattle, Northern dwarf goats, Moorish zebis), (iii) research and development of dual-purpose forage crop varieties, including sorghum, cowpea, groundnut, and other leguminous cover crops, (iv) health and disease prevention studies and recommendations, (v) operationalization of a system for transferring newly developed technology to producers and communicating producer priorities to researchers in a timely manner. COMPONENT 5: Promote Civil and Private-sector Engagement Key Actors: MEP, APCAM, private sector This component will support engagement of NGOs, finance organizations, and public sector bodies in the successful implementation of the aforementioned components334. Specifically, subcomponents will include: (i) build capacity of local NGO staff on CSA practices for crop-livestock integration, (ii) piloting of various business models for livestock agribusiness development, (iii) support cooperatives in meeting standards to access financial services, (iv) establish policy which promotes and enables 333 Expert Panel Workshop 334 Expert Panel Workshop PAGE 145 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN agricultural cooperatives to access financial instruments that reduce risk, leverage collateral, and safeguard savings, and (v) partner with private industry veterinarians to provide vaccine, check-up and other organized clinic services. COMPONENT 6: Resource Access and Infrastructure Development Key Actors: MEP, APCAM, private sector This component will improve the quality and accessibility of livestock-related resources and infrastructure335. Specific subcomponents will include: (i) defining transhumant pastoralist corridors, pastoral perimeters, and quarantine zones, (ii) creating night facilities, (iii) developing new points of safe water access, (iv) constructing feed storage and vaccination facilities, and (v) distribution of improved dual-purpose crop varieties, including sorghum, cowpea, groundnut, mucuna, bracharia, and bourgou. F-8 Millet-Sorghum-Legume Integration Program Introduction and Strategic Context Millet and sorghum are long-standing staple food crops in semi-arid West Africa. Both crops— and particularly millet—are very resilient under high temperatures and arid conditions, and can even withstand salty and waterlogged soils. Their ability to produce under such harsh environments with limited water and input resources has made them a mainstay of smallholder farmers throughout semi-arid regions of the world336. Both crops are also extremely nutrient rich, good sources of protein, and free of gluten337. Sorghum is one of the most photosynthetically efficient plants, and has a very high dry matter accumulation rate. It is also one of fastest-maturing food plants, and can be harvested a many as three times per year. Many smallholders have exchanged millet production for that of the more economically profitable but more climate-sensitive maize338. Both crops have a very limited presence on the international market and are often not even sold in local markets; this discourages surplus production339 as well as research investments340. However, unlike maize, which is projected to experience drastic declines in suitable growing area under the effects of climate change, millet and sorghum are expected to minimally impacted or even gain suitable growing area341. Millet-sorghum systems are mainstays of smallholder nutritional security in the semi-arid Sudo- Sahelian zone of Mali. Millet and sorghum account for 41% and 22% of Malian cereal consumption, respectively342. Millet production is found primarily in the sandy zones of Mopti, Ségou, and northern Koulikoro. Sorghum is concentrated in Ségou, northern Koulikoro, and northern Sikasso. Millet and sorghum are produced almost exclusively for home consumption, and as a result are primarily managed by female farmers. 335 Expert Panel Workshop 336 National Academics of Science Engineering and Medicine, “Sorghum”; National Academics of Science Engineering and Medicine, “Pearl Millet.” 337 ICRISAT, “Millets and Sorghum.” 338 National Academics of Science Engineering and Medicine, “Pearl Millet.” 339 FAO, “Sorghum and Millets in Human Nutrition.” 340 Read “Lost Crops of Africa. 341 CCAFS, “Projected Change in Suitable Area in Mali for Numerous Crops under Climate Change (2040-2069).” 342 Traore, “Intensification of Production of Millet and Sorghum: Dual Purpose Sorghum and Cowpea Intercropping in Mali.” PAGE 146 Millet-sorghum systems in Sudo-Sahelian Mali face multiple challenges. Low soil fertility is a primary limiting factor in both millet and sorghum production343. Farmers renting or otherwise lacking land tenure are unlikely to invest in management practices to improve long-term soil quality344. Pests such as Spanish fly, grasshoppers, and birds also affect yield345. High input prices and low market rates limit the adoption of new crop production technologies, including equipment that would improve work efficiency and productivity346. Due to inequalities between men’s and women’s crops in terms of access to inputs and education, the degree of mechanization and innovation in millet and sorghum production and processing remains low347. Climate-smart agriculture (CSA) practices have been shown to significantly improve millet- sorghum systems. Several systems for the intensification of millet and sorghum production in conjunction with legumes have been recently developed by CCAFS at the Cinaza research station in Mali. These systems focus on optimizing soil and water resource management, and have demonstrated the potential for significant increases in productivity. A number of other CSA practices and innovations for millet-sorghum systems have been tested and refined at the center as well, including348: • improved varieties • use of compost and microdosing • optimized rotation and association practices • integrated soil fertility management • contour bunds • tied ridges • crop residues applications • integration of tree species e.g., gliricidia, moringa, acacia albida, and sesbania To date, uptake of most of these practices has been modest349; this suggests significant opportunity for improving millet-sorghum systems through scaling and dissemination of existing technologies350. The Malian government and its allies are committed to improving the resilience and productivity of millet-sorghum systems through scaling of CSA practices. The 2014 National Investment Plan for the Agricultural Sector prioritizes ensuring the availability of quality grain seed through producer organizations and private-sector actors351. The World Bank also recognizes cereal production as a primary driver of poverty reduction in Mali352. The SADC/ICRISAT Sorghum and Millet Improvement Program was primarily funded by USAID and spanned 20 years (1983–2003); this program worked closely with national research programs and other stakeholders to develop and disseminate innovations in sorghum and millet production systems353. ICRISAT continues this work, as well as value-chain development, through the Smart Food Initiative in partnership with Feed the Future354. 343 Traore. 344 Expert Panel Workshop, Millet-Sorghum-Legume Integration Project Planning. 345 Expert Panel Workshop. 346 Traore et al., “Optimizing Yield of Improved Varieties of Millet and Sorghum under Highly Variable Rainfall Conditions Using Contour Ridges in Cinzana, Mali.” 347 The World Bank, “Mali - Country Partnership Framework for the Period FY16-19.” 348 Traore et al., “Optimizing Yield of Improved Varieties of Millet and Sorghum under Highly Variable Rainfall Conditions Using Contour Ridges in Cinzana, Mali.” 349 Traore and al, “Optimizing Yield of Improved Varieties of Millet and Sorghum under Highly Variable Rainfall Conditions Using Contour Ridges Is Cinzana, Mali.” 350 ICRISAT, “Millets and Sorghum.” 351 Rural Development Directorate, “Agricultural Development Policy.” 352 The World Bank, “Mali - Country Partnership Framework for the Period FY16-19.” 353 FAO, “The SADC/ICRISAT Sorghum and Millet Improvement Program.” 354 ICRISAT, “Millets and Sorghum.” PAGE 147 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN This work directly addresses Sustainable Development Goal 2: Zero Hunger, Goal 8: Economic Growth, Goal 9: Innovation, Goal 12: Responsible Production, Goal 13: Climate Action, and indirectly addresses Goal 10: Reduced Inequalities, Goal 11: Sustainable Communities, Goal 15: Life on Land, and Goal 16: Strong Institutions355. Proposed Development Objective and Results Proposed Development Objective: This project aims to increase the climate resilience and productivity of millet-sorghum systems to improve nutritional and economic outcomes of smallholders.   Beneficiaries: The project will directly benefit 199,495 women farmers of millet-sorghum ages 15 and up and their households356 during the 5-year project term. Across time, indirect benefit via improved economic and nutritional outcomes could feasibly reach smallholders throughout the Koulikoro and Segou regions. Project Description: This project is designed to improve the productivity, resilience, and nutritional and economic security of millet-sorghum producers in Mali. The project will address (i) extension agent capacity, (ii) producer association capacity, (iii) farmer technical support, (iv) research efforts, and (v) policy environs. Project Components COMPONENT 1: Technically Support Producers Key Actors: MA, MEADD, IER, IPR, universities, producer associations This component will increase producers’ technical capacity by offering training in357: (i) benefits of legume integration into millet and sorghum production, (ii) best management practices for improved varieties from Component 4, (iii) accessing the improved varieties developed in Component 4, (iv) functional literacy with a focus on CSA practices, inputs, equipment, etc., and (v) additional CSA practices for millet-sorghum systems, including (a) preparation and use of compost, (b) microdosing, (c) mulching, (d) agroforestry, (e) crop rotation, and (f) water and soil conservation practices. COMPONENT 2: Increase Capacity of Extension Agents Key Actors: MA, MEADD, IER, IPR This component will increase farm advisors’ capacity to integrate CSA best practices into their recommendations for millet-sorghum systems358. Specifically, this will include training in: (i) benefits of legume integration into millet and sorghum production, (ii) best management practices for improved varieties from Component 4, (iii) accessing the improved varieties developed in Component 4, (iv) functional literacy with a focus on CSA practices, inputs, equipment, etc., and (v) additional CSA practices for millet-sorghum systems, including (a) preparation and use of compost, (b) microdosing, (c) mulching, (d) agroforestry, (e) crop rotation, and (f) water and soil conservation practices. 355 Knoema, “Sustainable Development Goals of Mali.” 356 Total population of the target region is 797,910. 80% of all Malians identify themselves as farmers. Assuming that the 18.6% of the population (3.54/19 million) that resides in Bamako does not identify as farmers, then approximately 96% of the population outside the capital is employed by agriculture. This implies that about 765,993 people in the target region are farmers. About 52% of the population, or 398,317, is ages 15 and up, and approximately half the population, or 199,160, is female.. City Population, “Mali: Administrative Division (Cercles and Communes)”; World Population Review, “Mali Population 2018”; Index Mundi, “Mali Demographics Profile 2018.” 357 Expert Panel Workshop, Millet-Sorghum-Legume Integration Project Planning. 358 Expert Panel Workshop. PAGE 148 COMPONENT 3: Support Cooperatives and Producer Organizations Key Actors: MA, APCAM, private sector This component will strengthen the commercial processing of millet-sorghum-legume system products by offering technical assistance to producer groups359. Specifically, this will include: (i) improved access to appropriate mechanization tools, (ii) training in new processing techniques to diversify product options, (iii) technical assistance in improved processing efficiency (i.e. mechanization), (iv) systemization of the creation of working agreements with private-sector business partners (e.g., store fronts, packaging producers, etc.), and (v) entrepreneurship training and mentorship programs (e.g., with private industry business partners). COMPONENT 4: Bolster Research Key Actors: MA, IER, IPR, ICRISAT, universities This component will bolster millet-sorghum-legume system research initiatives. Specific components will include360: (i) research and development of improved varieties, (ii) best management recommendations for the improved varieties, including Tisndougou Coura, Djacumbe, Toronious, and Soxsat, (iii) development of accessible, low-maintenance mechanization equipment, (iv) ongoing testing of optimum CSA practices for various agrozones and varieties, such as associations, rotations, cover crops, conservation techniques, etc, and (v) operationalization of a system for transferring newly developed technology to producers and communicating producer priorities to researchers in a timely manner. COMPONENT 5: Foster Enabling Policy Environment Key Actors: MA, DNA, SOCAFON, Food Security Commission, OMA, WFP / PAM This component will support integration of legumes into millet-sorghum systems by fostering an enabling environment in terms of policy and private industry engagement361. Specific subcomponents will include: (i) further development of existing financial services (e.g., subsidies, loan, credit, grants) for producers and cooperatives (ii) incentivization of private-sector providers to improve access to inputs and equipment, particularly those developed in Component 4, (iii) streamline land tenure processes and accessibility to encourage investment in natural resource quality, (iv)revision of purchase and storage policies, and (v) general public awareness campaign of the benefits of legume integration into millet-sorghum systems. Risks: The main risks for this project are as follows: RISK PROBABILITY SEVERITY Severe Drought and Rainfall Variability Medium High High Winds Medium Low Poor Information Availability/Transfer Medium Medium Lack or Delay of Funding Medium High Farmer-Pastoralist Conflict Medium Low Ethnic Conflict (Peul-Dogon) Medium Low Political Instability Low Medium 360 Expert Panel Workshop. 361 Expert Panel Workshop. PAGE 149 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN F-9 Climate-Smart Vegetable Production, Storage, and Processing Program Introduction and Strategic Context Vegetable demand in West African has burgeoned in recent years. This trend has primarily been driven by sharp increases in urban demand as a consequence of increasing wealth and diet diversification3362. Peri-urban production to meet this demand has created significant employment opportunities in the production, storage, and processing of both exotic and indigenous vegetables. Production and health standards have not kept pace, however; producers frequently use banned or inappropriate pesticides in excess and/or polluted irrigation water363. Climate-smart agriculture (CSA) practices have been shown to significantly improve vegetable production, storage, and processing. Compost production and targeted application improves soil fertility, structure, and moisture; this not only supports crop productivity but also prevents and mitigates soil degradation. Water conservation practices, including rainwater harvesting, irrigation systems, and solar pumps, reduce labor inputs and foster resilience in the face of water scarcity and extreme temperatures364. Infrastructure development, such as that of low-maintenance irrigation systems, boreholes, and mechanical pumps, empowers producers to actively conserve and manage water resources during the dry season365. Improved storage reduces postharvest losses and also enables farmers to fetch higher rates for their harvest by holding it until off-season. Community organization and engagement helps facilitate access to processes, equipment, and infrastructure that increase efficiency, improve resilience, and reduce losses. This may include, for example, solar dryers, storage facilities, cold chains, transportation, credit and loan, warehouse receipting, and bulk purchasing and sales366. Women and youth play crucial roles in the production, storage, and processing of vegetables. Women are the primary producers, processors, and salespeople of vegetables. Young men are also actively engaged in production of vegetables and other short-duration crops during the dry season. There are numerous opportunities for youth engagement in value-added processing, logistical transport, and commercialization as markets develop, both in rural areas and peri-urban regions367. Vegetables are a staples of the Malian diet and economy. Onions, shallots, tomatoes, chili peppers, eggplants, and okra are traditional components of Malian cuisine, and consequently have reliably high demand in both local and markets. Vegetables are among the top export products and a strategic focus for economic growth368. Local and international markets are characterized by alternating periods of excess demand and excess supply369. Vegetables are produced almost exclusively in the south of the country, with Dogon Plateau, Baguineda, and Niono Cercle being notable epicenters370. Most vegetable production occurs under irrigation during the dry season, with some exceptions (e.g., okra)371. 362 Blein et al., “Agricultural Potential of West Africa (ECOWAS).” 363 Levasseur et al., “A Review of Urban and Peri-Urban Vegetable Production in West Africa.” 364 Partey et al., “Developing Climate-Smart Agriculture to Face Climate Variability in West Africa.” 365 Andrieu et al., “Prioritizing Investments for Climate-Smart Agriculture.” 366 CCAFS, “Climate-Smart Agriculture in Mali.” 367 Expert Panel Workshop, Vegetable Production, Processing, and Storage Project Planning. 368 Rural Development Directorate, “Agricultural Development Policy.” 369 Josserand, “Assessment of Volume and Value of Regionally Traded Staple Commodities.” 370 Expert Panel Workshop, Vegetable Production, Processing, and Storage Project Planning. 371 CCAFS, “Climate-Smart Agriculture in Mali.” PAGE 150 Malian vegetable production is not without challenges. Extreme heat, particularly in combination with drought, can result in insufficient availability of irrigation-quality water in wells and dams during the dry season372. Chemical inputs may be used incorrectly and/or in excess373. Soil degradation, in combination with limited access to fertilizers, significantly limits yields374. A lack of reliable transportation methods, optimized storage facilities, and cold chains implies very high postharvest losses375. Improved vegetable production, storage, and processing offers significant economic opportunity. Greater production resilience and postharvest loss reduction would significantly improve the efficiency of Malian vegetable production. An expanded capacity for medium-term storage would enable supply outside the normal production period and the associated premium pricing376. Effective storage and/ or processing would also reduce reliance on costly imports during periods of low domestic supply. The Malian government has heavily invested improved vegetable production. The 2018 National Investment Plan prioritizes agricultural productivity, as well as CSA practices to protect and sustain natural resources377. The 2013 National Policy for Agricultural Development highlights significant investments in agricultural productivity and environmental sustainability, and in particular articulates the importance of improving the available of high-quality seed to support the vegetable sector378. This project also supports Sustainable Development Goal 2: Zero Hunger, Goal 5: Gender Equality, Goal 8: Economic Growth, Goal 9: Innovation, Goal 12: Responsible Production, Goal 13: Climate Action, and indirectly addresses Goal 10: Reduced Inequalities, Goal 11: Sustainable Communities, Goal 15: Life on Land, and Goal 16: Strong Institutions. Various international organizations and alliances are collaborating with Mali on this priority issue. As part of the Nationally Determined Contributions plan under the Paris Accord, Mali has invested in projects addressing rainwater harvesting and storage and appropriate agricultural development for improved water management379. The African Union Agenda on Agricultural Growth and Transformation aims to promote sound management of natural resources as well as agricultural productivity380. The West African Economic and Monetary Union Amended Treaty and the Economic Community of West African States Vision 2020 both prioritize the sustainable economic development and climate resilience of their member states, including Mali381. The Gardens Against Climate Change project, implemented by the Malian MEADD, the UNDP, and GIZ, installs drip irrigation for vegetable production during drought382. The World Vegetable Center partners with Mali’s Institute of Rural Economy in the USAID Improving Vegetable Production and Consumption in Mali project to augment the quality, availability, accessibility, and affordability of improved vegetable variety seed383. 372 Expert Panel Workshop, Vegetable Production, Processing, and Storage Project Planning. 373 Levasseur et al., “A Review of Urban and Peri-Urban Vegetable Production in West Africa.” 374 Andrieu et al., “Prioritizing Investments for Climate-Smart Agriculture.” 375 CCAFS, “Climate-Smart Agriculture in Mali.” 376 Josserand, “Assessment of Volume and Value of Regionally Traded Staple Commodities.” 377 GiZ, “National Investment Plan for the Implementation of the Determined Contributions.” 378 Rural Development Directorate, “Agricultural Development Policy.” 379 Expert Panel Workshop, Vegetable Production, Processing, and Storage Project Planning. 380 Department of Rural Economy and Agriculture, “Livestock Development Strategy for Africa 2015-2035.” 381 West African Economic and Monetary Union, “The Amended Treaty”; Economic Community of West African States, “Vision 2020.” 382 Vollmer, “Vegetable Gardens against Climate Change.” 383 World Vegetable Center, “Highlighting Horticulture in Mali.” PAGE 151 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Proposed Development Objective and Results Proposed Development Objective: This project aims to increase the productivity and climate resilience of vegetable production, while fostering economic opportunities for producers, especially women and youth, while minimizing environmental impact. Beneficiaries: The project will directly benefit 52,747 women farmers (ages 25 and up) and male and female youth (ages 15-24)384 and their households during the 5-year project term. Across time, indirect benefit via improved economic and nutritional outcomes could feasibly reach all vegetable farmers in the Niono, Kati, and Bandiagara Cercles. Project Description: This project is designed to increase the resilience and productivity of vegetable production in Mali in order to improve nutritional and economic outcomes. The project will address (i) extension agent capacity, (ii) producer technical assistance, (iii) research, (iv) producer organizational strength, and (v) infrastructure development. Project Components COMPONENT 1: Technical Assistance for Producers Key Actors: MA, DNA This component will build vegetable producer capacity to integrate climate-smart practices into their agricultural management decisions385. Specifically, training will include: (i) access and best management practices for improved varieties developed in Component 4, (ii) soil and water conservation techniques, including (a) zaï pits, (b) half-moon technique, (c) contour bunding, and (d) mulching, (iii) production and use of compost, (iv) integrated pest and disease management, including safe use of chemical inputs as needed, and (v) best irrigation practices, including (i) water quality standards, (ii) use of drip irrigation, and (iii) use of solar/mechanical pumps. COMPONENT 2: Increase Capacity of Extension Agents Key Actors MA, DNA In this component will prepare farm advisors to integrate CSA practices into their recommendations386. Specifically, training will include: (i) access and best management practices for improved varieties developed in Component 4, (ii) soil and water conservation techniques, including (a) zaï pits, (b) half- moon technique, (c) contour bunding, and (d) mulching, (iii) production and use of compost, (iv) integrated pest and disease management, including safe use of chemical inputs as needed, and (v) best irrigation practices, including (i) water quality standards, (ii) use of drip irrigation, and (iii) use of solar/mechanical pumps. 383 The populations of the target regions are: Bandiagara 412,195, Baguineda (Kati) 68,145, and Dogofry (Niono) 42, 938, for a total of 523,278 individuals. 80% of all Malians identify themselves as farmers. Assuming that the 18.6% of the population (3.54/19 million) that resides in Bamako does not identify as farmers, then approximately 96% of the population outside the capital is employed by agriculture. This implies that about 502,348 people in the target regions are farmers. About 26% of the population female ages 15 and up; approximately 9% is male ages 15-24. Hence, women farmers ages 25+ and youth farmers ages 15-24 account for 35% of the total population of the target regions, or 175,822. City Population, “Mali: Administrative Division (Cercles and Communes)”; World Population Review, “Mali Population 2018”; Index Mundi, “Mali Demographics Profile 2018”; City Population, “Mali: Administrative Division (Cercles and Communes).” 385 Expert Panel Workshop, Vegetable Production, Processing, and Storage Project Planning. 386 Expert Panel Workshop. PAGE 152 COMPONENT 3: Support Producer Associations Key Actors: MA, DNA, IER, AVRDC, NGOs This component will strengthen the commercial processing of millet-sorghum-legume system products by offering technical assistance to producer groups387. Specifically, this will include: (i) training on use of improved production, storage, and processing equipment, including (a) storage boxes, (b) irrigation equipment, (c) solar ovens, (d) cold chain equipment, and (e) transportation vehicles; (ii) financial services to facilitate access to such equipment, including, (a) credit, (b) loan, (c) subsidies, and (d) grants; (iii) technical assistance in new and/or more efficient value-add processes and products (e.g., tomato paste), (iv) systemization of the creation of working agreements with private- sector business partners (e.g., store fronts, packaging producers, etc.), and (v) entrepreneurship training and mentorship programs (e.g., with private industry business partners). COMPONENT 4: Strengthen Research Efforts Key Actors: MA, DNA, IET, IRP, IFRA, AVRDC This component will focus on supporting producer’s priorities through applied research and development388. Namely, this will consist of (i) improving quality and accessibility of laboratory equipment in national research institutions, (ii) development of improved seed varieties offering disease resistance and climate resilience (e.g., micro tubers) and best management practices for the same, (iii) development of best management practice recommendations for vegetable storage and preservation techniques, with a focus on correct use of chemical inputs and water quality standards (iv) development of CSA best management practices for vegetable production in the target region (e.g., soil and water conservation techniques, compost use, mulching), and (v) investigation of implications of chemical residues and best practices for use of chemical inputs in vegetable systems. COMPONENT 5: Bolster Infrastructure Networks Key Actors: MA, DNA, MEADD, AVRDC, IER, IET, IFRA, private sector This component will develop infrastructure to support an expanding and sustainable vegetable market389. Namely, this will include: (i) constructing storage facilities in wholesale markets designed to minimize postharvest losses (e.g., cold chain) (ii) construction of irrigation networks for dry season vegetable production (iii) fostering availability of the equipment promoted in Component 1 for purchase and rental by producer associations, (iv) building cold chain infrastructure, and (v) identifying and training cooperatives and professional organizations to use, manage, and maintain this infrastructure. 387 Expert Panel Workshop. 388 Expert Panel Workshop. 389 Expert Panel Workshop. PAGE 153 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Risks: The main risks for this project are as follows390: RISK PROBABILITY SEVERITY Severe Drought Medium High Extreme and/or Variable Temperatures Medium High Poor Seed Availability High High Ethnic Conflict (Peul-Dogon) Medium Low Insecurity (Office du Niger) Medium Low Faulty Irrigation Equipment Medium Medium Pests and Disease Medium Medium F-10 Restoring Degraded Lands Program Introduction and Strategic Context The effects of climate change and a rapidly growing population have significantly impacted West African ecosystems. Between 1975 and 2013, 48,000 sq km of land was deforested, primarily due to agricultural expansion391. In the Sahel region, decades of drought and unsustainable land management practices by an ever-growing population have instigated large-scale land degradation392. This has resulted in large-scale reduced nutritional and economic security for farmers, as well as reduced national economic growth and capacity to meet domestic food demands. Leading regional governments have considered a range of actions, including the Great Green Wall, to halt encroachment of the Sahara Desert393. Climate-smart agriculture (CSA) practices tailored to arid climates—specifically, agroforestry, assisted natural regeneration, soil and water conservation technologies, and conservation agriculture--have proven to be the most effective approaches to Sahelian land restoration to date394. Climate-smart agriculture techniques have been successfully adapted to the arid Sahelian zones for land restoration. The scarcity of water and biomass in the Sahel makes some of the CSA practices used in area of greater water abundance infeasible395. Instead, the focus is on targeted water and biomass concentration. For example, zaï is a practice in which holes of approximately 30 cm diameter and 15 cm depth are dug and filled with organic matter396. Crescent-shaped basins (half-moons) filled with organic matter along the contour397 and contour ridging398 offer similar benefits. These techniques have been key to recovering encrusted soils, collecting surface water, reducing runoff- associated erosion, increasing filtration, attracting soil fauna, improving soil fertility, and supporting vegetative regrowth. 390 Expert Panel Workshop. 391 USAID & USGS, “Landscape Restoration and Re-Greening | West Africa.” 392 Partey et al., “Developing Climate-Smart Agriculture to Face Climate Variability in West Africa: Challenges and Lessons Learned.” 393 Morrison, “The ‘Great Green Wall’ Didn’t Stop Desertification, but It Evolved Into Something That Might.” 394 Zougmore, “Promotion of Conservation Agriculture in the Context of the CCAFS Research Program in West Africa”; USAID & USGS, “Landscape Restoration and Re-Greening | West Africa.” 395 World Resources Institute, “Scaling up Regreening: Six Steps to Success”; Andrieu, “Prioritizing Investment for Climate Smart Agriculture: Lessons Learned from Mali.” 396 Bayala et al., “Conservation Agriculture with Trees in the West African Sahel – a Review.” 397 Bayala et al.; Zougmoré, Zida, and Kambou, “Role of Nutrient Amendments in the Success of Half-Moon Soil and Water Conservation Practice in Semiarid Burkina Faso.” 398 Birhanu et al., “A Watershed Approach to Managing Rainfed Agriculture in the Semiarid Region of Southern Mali.” PAGE 154 Arid CSA practices have been successfully implemented in Mali. As a result of a governmental restoration project of 500,000 hectares in the Seno Plain, on-farm tree densities have increased by approximately 900% over the past decade. The project primarily employed farmer-managed natural regeneration with the shrub Combretum glutinosum399. In this system, farmers prune the trees early in the rainy season (June); this provides organic matter soil inputs as well as a source of firewood. The Malian government has heavily invested in restoring degraded lands. Restoration of degraded lands features prominently in the Planned National Contributions under the Paris Accord. The Forest Management Project for the Restoration of Degraded Ecosystems, the Forest Plantation Program, the System of Rice Intensification Project, and the Pastoral Development Project all explicitly aim to restore or prevent land degradation400. This investment aligns with the goals of several international alliances of which Mali is participant. As part of the Nationally Determined Contributions plan under the Paris Accord, Mali has invested in projects addressing rainwater harvesting and storage, assisted natural regeneration, and strategic agricultural development for water management401. The African Union Agenda on Agricultural Growth and Transformation aims to promote sound management of natural resources as well as agricultural productivity402. The West African Economic and Monetary Union Amended Treaty and the Economic Community of West African States Vision 2020 both prioritize the economic and financial competitiveness of their member states, including Mali403. This project also directly addresses Sustainable Development Goal 2: Zero Hunger, Goal 5: Gender Quality, Goal 8: Economic Growth, Goal 12: Sustainable Consumption and Production, and Goal 13: Combat Climate Change, and indirectly addresses Goal 9: Sustainable Industrialization, and Goal 15: Protect Ecosystems404. Various international organizations are collaborating with Mali on this priority issue. The USAID Landscape Restoration and Re-greening Project has promoted assisted natural regeneration in Mali, Burkina Faso, and Niger405. World Bank has a long history of addressing land restoration in Mali, including the Reconstruction and Economic Recovery Project, aimed at supporting recovery from the 2012 crisis, which has a landscape management and biodiversity component406. The European Commission Global Alliance for Climate Change has promoted climate-smart restoration technologies in Mali as part of the Global Public Good and Challenges Project407. The World Agroforestry Centre’s Restoration of degraded land for security and poverty reduction in East Africa and the Sahel establishes communities of practice for restoration of degraded lands in Mali, among other countries408. The World Food Program has been working with YAGTU to restore degraded lands and improve management and conservation of water in the Dogon region of Mali409. The Action Against Desertification program by FAO is scaling a model to recover degraded lands across the Sahel, including Mali410. 399 World Resources Institute, “Scaling up Regreening: Six Steps to Success.” 400 Framework Convention on Climatic Changes, “Contribution Amount Determined at the National Level.” 401 Expert Panel Workshop, Non-Timber Forest Product Value Chains Project Components. 402 Department of Rural Economy and Agriculture, “Livestock Development Strategy for Africa 2015-2035.” 403 West African Economic and Monetary Union, “The Amended Treaty”; Economic Community of West African States, “Vision 2020.” 404 Knoema, “Sustainable Development Goals of Mali.” 405 USAID & USGS, “Landscape Restoration and Re-Greening | West Africa.” 406 World Bank, “Projects : Mali Reconstruction and Economic Recovery.” 407 Global Alliance for Climate Change, “Global Public Good and Challenges.” 408 World Agroforestry Centre, “Restoration of Degraded Land for Food Security and Poverty Reduction in East Africa and the Sahel: Taking Successes in Land Restoration to Scale.” 409 Aspe, “Restoring Hope in the Heart of Mali’s Sahel.” 410 FAO, “Making Land Fertile Again  | Action Against Desertification.” PAGE 155 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Proposed Development Objective and Results Proposed Development Objective: This project aims to build national capacity to restore degraded lands at scale to increase climate resilience, ecosystem services, and agricultural productivity. Beneficiaries: The project will directly benefit 106,461411 agricultural producers ages 15 and up and their households in the Nioro, Yelimand, and Kayes (Sahel, Karakor, and Koussane Communes) Cercles during the 5-year project term. Across time, indirect benefit via improved economic and nutritional outcomes could feasibly reach all Sahelian agricultural producers. Project Description: This project is designed to scale degraded land restoration in the Malian Sahel. The project will address (i) capacity of extension agents and other promoters to recommend climate- smart restoration practices, (ii) research efforts to develop and disseminate best restoration practices, (iii) an enabling policy environment for restoration, (iv) private-sector engagement in land restoration, and (v) raising farmer capacity to restore land. Project Components COMPONENT 1: Farmer Technical Support Key Actors: MEADD, MA, DNA, DCG Mali This component will increase the capacity of producers to restore degraded lands412. Specifically, this will include training on: (i) assisted natural regeneration, (ii) use of the varieties, equipment, and techniques developed in Component 3, (iii) soil and water management practices, (iv) selection of appropriate tree species for given purposes, and (v) mechanical and vegetative stabilization of dunes and riverbanks. COMPONENT 2: Raise Extension Agent, Private Sector, and NGO Capacity Key Actors: MEADD, MA, DNA, IRE, METP, private sector This project component will increase the capacity of farm advisors and NGO staff to integrate restoration techniques into their recommendations for degraded lands413. Subcomponents will include training on(i) assisted natural regeneration, (ii) use of the varieties, equipment, and techniques developed in Component 3, (iii) soil and water conservation practices, (iv) selection of appropriate tree species for given purposes, and (v) mechanical and vegetative stabilization of dunes and riverbanks. COMPONENT 3: Strengthen Research Efforts Key Actors: MEADD, IER, IPR, universities, CCAFS, ICRAF, ICRISAT This component will bolster research and development efforts to support restoration of degraded lands414. Namely, this will consist of (i) optimization of cost- and labor-efficient restoration practices for the Malian context, (ii) selection, testing, and/or development of species for restoration (e.g., tree, 411 The population of the given target region is 533,158. About 80% of Malians identify as agriculturalists; assuming that the 18.5% of the population residing in the capital does not work in agriculture, then 96% of the population outside the capital is employed by agriculture. This implies that 511,831 individuals in the target area are employed by agriculture. 52% of the population, or 266,152, is ages 15 and up. Index Mundi, “Mali Demographics Profile 2018”; City Population, “Mali: Administrative Division (Cercles and Communes)”; Nations Online Project, “Political Map of Mali.” 412 Expert Panel Workshop, Degraded Land Restoration Project Planning. 413 Expert Panel Workshop. 414 Expert Panel Workshop. PAGE 156 grass, shrub, groundcover, etc.), (iii) identification of best management practice recommendations for each improved variety, (iv) development of less expensive, lower maintenance, and/or more efficient mechanization tools, and (v) operationalization of a system for timely dissemination of new technologies to producers and timely reception of feedback from producers on priorities for research. COMPONENT 4: Enabling Policy Environment Key Actors: MEADD, MA, DNA, IRE, METP This component will foster large-scale degraded land restoration through development of an enabling policy environment. Specifically, this will include: (i) financial services, including (a) grants, (b) loans, (c) credit, and (d) subsidies, for cooperatives, communities, and farmers for land restoration, (ii) budgeting for infrastructure development to mitigate and/or prevent major occurrences of degradation in targeted areas, (iii) establishment of regional service centers where recommendations, information, and the equipment and varieties developed in Component 3 are available at low or no cost, and (iv) leveraging the national science-policy dialogue platform for scientific and technical knowledge sharing, awareness raising and policy advocacy415. COMPONENT 5: Private-sector Engagement Key Actors: MEADD, private industry This component will support active engagement of the private sector in scaling land restoration. Specific subcomponents will include: (I) incentivization to maintain stock of equipment and varieties developed in Component 3, (ii) incentivization to open additional service points (complementary to the governmental services centers in Component 4) where they techniques, equipment, and varieties developed in Component 3 are available from trained staff, (iii) grants to implement large-scale and/ or high-input restoration projects, and (iv) and incentivization for staff to attend training sessions. Risks: The main risks for this project are as follows: RISK PROBABILITY SEVERITY Rainfall Variability, Drought, and Flood Medium High Political and Security Crises High High High Winds Medium High High Temperatures Medium High Smallholder Risk Aversion Medium High F-11 Rice Intensification System Promotion Program Introduction and Strategic Context Rice is foundational to the diets and livelihoods of smallholders across sub-Saharan Africa. The popularity of rice among African consumers has skyrocketed over the past three decades, particularly in urban areas416. About 100 million African depend directly on rice farming for their livelihoods. Nevertheless, Asian rice continues to dominate African markets. This is attributable primarily to poor technology access; the improved varieties and best management practices developed in Asia during 415 Sogoba et al., “How to Establish Dialogue between Researchers and Policymakers for Climate Change Adaptation in Mali: Analysis of Challenges, Constraints and Opportunities.” 416 WARDA, “Africa Rice Trends.” PAGE 157 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN the Green Revolution do not translate well to African climates. As a result, African rice systems remain costly and highly sensitive to climate variability, and yields and profit remain low. At 1.4 tons/ha, average rice yields on the subcontinent are the lowest in the world, versus Asia’s average of 4 tons/ ha117. With per-capita rice consumption continuing to grow at 2% per year, the African rice deficit will reach 10 million tons by 2020418. Climate-smart agriculture (CSA) practices have been shown to significantly improve African rice productivity.Green house gas emissions from irrigation rice production are known to be very high. Significant research in the rice sector has produced methodologies to reduce emissions, climate- resilient varieties, revised production calendars to account for climate change, and low-cost soil erosion control practices. For instance, the Alternate Wetting and Drying Technique is being tested as a method for reducing emissions and increasing resilience. The System of Rice Intensification (SRI) has shown 37-105% (average 67%) increase in yields over conventional practices across West Africa419. SRI differs from conventional systems in that420: • Seed soaking before planting • Unflooded nurseries • Transplantation of a single seedling per hill • Early transplantation (8-12 days) • Wide spacing in rows (25x25cm) • Alternate wetting and drying, using minimal water application • Mechanical weeding and soil aeration • Organic matter as primary fertilizer Benefits of SRI include a higher tiller number per plant, significantly improved yields, drastically reduced seed use, water savings of 25-50%, greater drought resilience, improved soil fertility, reduced use of agrichemical inputs, reduced production costs, and reduced greenhouse gas emissions421. Mechanization as part of SRI offers improved working conditions, in particular for women farmers. Some of the most physically taxing aspects of rice production, including transplanting, weeding, and harvesting, are the responsibilities of women. SRI systems produce higher yields per plant, thus reducing the overall workload per unit harvest. Appropriate mechanization further reduces this labor burden. Making rice production less labor-intensive and more cost effective also help reduce the number of individuals who leave the agricultural sector in favor of urban employment422. The Malian government has heavily invested in bolstering the rice sector. Since 2008, the government began subsidizing seed, inputs, and equipment such as tractors. They have made financial services such as credit and loan available to farmers and cooperatives as well. As a result, Malian rice production has grown from 0.9 MT in 2008 to 2.7 MT in 2016423. This meets and exceeds the domestic consumption rate of 1.1 million MT424, and opens an important export market opportunity. Extensive areas of irrigated rice are under the Office du Niger, and coordination with them will be a key part of design and implementation. Mali has explicitly identified continued development of the rice sector through SRI as part of the Nationally Determined Contributions under the Paris Accord425. 417 F Nwanze et al., “Rice Development in Sub-Sahara African.” 418 Lancon and Erenstein, “Potential and Prospects for Rice Production in West Africa.” 419 Styger, “Scaling Up Climate Smart Rice Production in West Africa.” 420 CIIFAD, “System of Rice Intensification - Frequently Asked Questions (FAQs).” 421 Styger, “Producing More Rice with Less Inputs- Three Years of Experience in Mali.” 422 Expert Panel Workshop, System of Rice Intensification Project Components. 423 ReliefWeb, “As Africa’s Need for Food Grows, Mali’s Rice Turnaround Shows a Way Forward - Mali.” 424 ReliefWeb. 425 République du Mali, “Contribution Prévue Déterminée Au Niveau National (CPDN).” PAGE 158 Further improvements in production efficiency and climate resilience could help make Mali’s rice export prices more competitive with Asian rice products. SRI has shown significant promise for improving the productivity and climate resilience of Malian rice systems. Trials in the Tombouctou region in 2008 showed average yield increases of 66% (ranging from 34-87%), with water savings of at least 32%426. Various international organizations and alliances are collaborating with Mali on this priority issue. Rice self-sufficiency is of strategic importance across sub-Saharan Africa427. Mali is a member of the African Rice Center, which is both a CGIAR research center and an intergovernmental association of African countries dedicate to global research for a food-secure future428. The West and Central African Council for Agricultural Research and Development supports SRI in Mali through the West Africa Agricultural Productivity Program429. The Economic Community of West African States, of which Mali is a member, also promotes reform the African rice sector to attain self-sufficiency, alleviate poverty, and improve nutritional and economic outcomes430. Various NGOs and research institutions, including Grow Africa431, the Cornell International Institute for Food, Agriculture, and Development432, the Alliance for Food Sovereignty in Africa433, and Africare434, are collaborating with Mali in strengthening the rice sector using SRI. This work directly addresses Sustainable Development Goal 2: Zero Hunger, Goal 5: Gender Equality, Goal 8: Economic Growth, Goal 9: Innovation, Goal 12: Responsible Production, Goal 13: Climate Action, and indirectly addresses Goal 10: Reduced Inequalities, Goal 11: Sustainable Communities, Goal 15: Life on Land, and Goal 16: Strong Institutions. Proposed Development Objective and Results Proposed Development Objective: This project aims to improve nutritional and economic outcomes by scaling SRI to increase rice productivity and climate resilience.   Beneficiaries: The project will directly benefit up to 72,480 rural agricultural workers ages 15 and up and their households435 during the 5-year project term. The focus region will be the unflooded rice production zone of the Nigerian basin in Sahel region between Mopti and Segou, including portions of Tenenkou, Macine, and Segou Cercles. Across time, indirect benefit via improved economic and nutritional outcomes could feasibly reach all Malian rice producers. 426 Styger, “Producing More Rice with Less Inputs- Three Years of Experience in Mali.” 427 WARDA, “Africa Rice Trends.” 428 CGIAR, “Africa Rice Center.” 429 CORAF, “WAAPP.” 430 Economic Community of West African States, “Vision 2020.” 431 ReliefWeb, “As Africa’s Need for Food Grows, Mali’s Rice Turnaround Shows a Way Forward - Mali.” 432 Styger, “Producing More Rice with Less Inputs- Three Years of Experience in Mali.” 433 FAO, “System of Rice Intensification (SRI) in Mali.” 434 Styger et al., “Application of System of Rice Intensification Practices in the Arid Environment of the Timbuktu Region in Mali.” 435 80% of all Malians identify themselves as farmers. Assuming that the 18.6% of the population (3.54/19 million) that resides in Bamako does not identify as farmers, then approximately 96% of the population outside the capital is employed by agriculture. This implies that about 464,600 people in the target region are farmers. About 52% of the population, or 241,600, is ages 15 and up. City Population, “Mali: Administrative Division (Cercles and Communes)”; World Population Review, “Mali Population 2018”; Index Mundi, “Mali Demographics Profile 2018”; City Population, “Mali: Administrative Division (Cercles and Communes).” PAGE 159 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Project Description: This project is designed increase capacity for SRI in Mali. The project will address (i) research and development, (ii) extension services, (iii) policy and private-sector engagement, (iv) producer technical assistance, and (v) cooperative organizational strength. Project Components COMPONENT 1: Producer Technical Assistance and Organizational Capacity Key Actors: DNA, NGOs This component will raise the capacity of rice producers in SRI and bolster their organization into cooperatives436. Specifically, this will include: (i) targeted awareness campaigns regarding potential yields and climate resilience, (ii) field school training on SRI best management practices, (iii) capacity building of producer associations for nursery management, division of labor, storage, and other community-based activities, (iv) technical assistance to producer associations in organizational management and meeting minimum requirements for financial services, and (v) training in accessing and using services e.g., input subsidies, bulk purchasing and sales, credit and loan, etc. COMPONENT 2: Build Capacity of Extension Agents and other Promoter Key Actors: DNA, research institutions, NGOs, Office du Niger This project component will increase the capacity of farm advisors and other promoters, including (i) Office du Niger staff, (ii) NGO staff, (iii) ATI staff, and (iv) private industry representatives, to integrate SRI practices into their recommendations for rice producers437. Specifically, this will include training in: (i) climate change and benefits of SRI in rice systems, (ii) improved rice varieties, their advantages, and recommended best management practices (iii) best practices for effectively building producer capacity in SRI, including comparison plots, field schools, inter-farmer visits, and technical training, (iv) production of training manuals, reference guides, modules for integration into general training curricula, and (v) producing or accessing SRI system inputs. COMPONENT 3: Streamline Infrastructure Development Key Actors: DNA, ATI, Office du Niger, SOCAFON This component will focus on ensuring the infrastructure and equipment to support a thriving national rice sector is in place438. Namely, this will consist of (i) the development and rehabilitation of irrigated perimeters and water pumps, (ii) promotion of irrigated areas by ATI for agricultural development, (iii) creating additional machine purchase and loan centers, (iv) bolstering supply of mechanized equipment available at centers, and (v) continued subsidization of on-farm technology to mechanize production processes. COMPONENT 4: Strengthen Research Efforts Key Actors: DNA, IER, NGOs, SOCAFON, research institutions This component will bolster research and development efforts to support SRI439. Specifically, this will include: (i) testing of existing improved rice varieties for SRI in Mali, (ii) as needed, development of new varieties optimized for SRI in Mali, (iii) identification of best management practice recommendations 436 Expert Panel Workshop, System of Rice Intensification Project Components. 437 Expert Panel Workshop 438 Expert Panel Workshop 439 Expert Panel Workshop PAGE 160 for each improved variety, in particular regarding minimization of greenhouse gas emissions, (iv) development of less expensive, lower maintenance, and/or more efficient mechanization tools, and (v) operationalization of a system for timely dissemination of new technologies to producers and timely reception of feedback from producers on priorities for research. COMPONENT 5: Foster Enabling Policy and Private-sector Environments for Scaling Key Actors: DNA, SOCAFON This component will support scaling of SRI by fostering an enabling environment in terms of policy and private industry engagement440. Specific subcomponents will include: (i) further development of existing financial services (e.g., subsidies, loan, credit, grants) for producers and cooperatives investing in SRI, (ii) incentivization of private-sector providers of seeds, fertilizer, and equipment to improve access to SRI inputs and equipment, particularly those developed in Component 4, (iii) supporting SOCAFON in establishing new groups in various production zones and expanding their equipment rental services with a focus on SRI equipment, training of community-based seed producers, (iv) explicitly addressing SRI in the national agricultural development budget and policy, and (v) completing a comprehensive analysis of market dynamics, business models, and financial mechanisms to support innovative rice value chains. Risks: The main risks for this project are as follows441: RISK PROBABILITY SEVERITY Low and Irregular Rainfall, Floods High Low Mismanagement of Water High Low Extreme Temperatures High Low Sandstorms High Medium Political and Security Crises Medium Medium Smallholder Risk Aversion Medium High Producer Preference for Large, Lower Investment Plots High High Long Timeline for Establishment of Demonstration Plots High Medium Labor Shortages at Time of Transplant High High F-12 Climate Smart Wheat Development Program Introduction and Strategic Context Wheat is quickly becoming a staple crop in sub-Saharan Africa. The consumption rate of wheat in the area is growing faster than that of any other grain, primarily due to rising incomes, population growth, and women’s increasing participation in the labor force in urban centers442. Demand has outpaced production, and the region is highly dependent on imports from Europe and the United States. Given that such imports are subject to rising and highly volatile prices, meeting demand with domestic production is a strategic priority in the region443. 440 Expert Panel Workshop 441 Expert Panel Workshop 442 Mason, 2012 443 El Sohl, 2012 PAGE 161 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Wheat production is particularly sensitive to the effects of climate change. Warmer average temperatures impede the vernalization period required by the plant to fruit. Yields are also sensitive to variations in rainfall, excessive heat, periods of drought, and weathered soils. Various pests and diseases, such as yellow rusts, Hessian fly, and termites, also threaten the crop444. Climate-smart agriculture (CSA) has been shown to significantly improve Malian wheat production. The System of Wheat Intensification (SWI) has successfully delivered increased yields of 66-87% in the Timbuktu region of Mali445 along with significantly reduced labor, water requirements, and input costs446. The methodology is similar to that of the System of Rice Intensification; seed preparation, greater seed spacing, row planting, single plants per mound, alternate wet-drying cycles, and mechanized seeding and weeding are hallmark features. The development of improved varieties with greater disease, pest, and climate resilience has also proven to be a crucial component of improving the reliability and productivity of wheat systems447. Mali is a net importer of wheat. Between 2000 and 2009, the country imported 99,000 tons of wheat and consumed over 103,000448. Production has quadrupled since 2010, reaching 40,000 tons in 2016, but the consumption gap continues to widen. This may be in part because wheat is often not sold commercially; rather, smallholders produce it primarily for household consumption. Thus, although cereal production accounts for the largest share of Mali’s agriculture sector449, wheat remains a small percentage of the cereal sub-sector450. Mali’s rapidly growing and urbanizing population will likely continue to drive wheat demand upward; urban residents are expected to represent more than half of the total population of 25.5 million by 2025451. This sustained and growing demand represents an important opportunity to scale existing domestic production toward self-sufficiency. Significant opportunities exist to increase the efficiency and productivity of Malian wheat production. Women are traditionally responsible for production of food crops such as wheat452. Due to inequalities between men’s and women’s crops in terms of access to inputs and education, the degree of mechanization and innovation in wheat production and processing remains low453. The Malian government and its allies have prioritised the development of the wheat sector. Mali aims to position its agricultural sector as the agro-industrial leader of the region and the primary vehicle for national GDP growth. The 2014 National Investment Plan for the Agricultural Sector prioritizes reaching wheat production rates of 70,000 tons annually by 2025 through sustainable innovation and intensification of production, with the ultimate goal of reducing reliance on imported cereals and improving food security. The World Bank also recognizes cereal production as a primary 444 El Sohl, 2012; http://www.ipcc.ch/ipccreports/sres/regional/ 445 Styger, 2009 446 Rana et al. 2017 447 El Sohl, 2012 448 Mason, 2012 449 PDA, 2013 450 PNISA, 2014 451 PNISA, 2014; PDA, 2013 452 World Bank, 2015 453 World Bank, 2015 PAGE 162 driver of poverty reduction in Mali (2015). The Support Agricultural Research for Development of Strategic Crops in Africa projects, funded by the African Development Bank in partnership with the Institute of Rural Agriculture and managed by ICARDA, supports scientists from 12 African countries, including Mali, in sharing knowledge and experiences in address wheat production challenges, use new technologies, and develop improved varieties454. This work directly addresses Sustainable Development Goal 2: Zero Hunger, Goal 5: Gender Equality, Goal 8: Economic Growth, Goal 9: Innovation, Goal 12: Responsible Production, Goal 13: Climate Action, and indirectly addresses Goal 10: Reduced Inequalities, Goal 11: Sustainable Communities, Goal 15: Life on Land, and Goal 16: Strong Institutions. Proposed Development Objective and Results Proposed Development Objective: This project aims to increase wheat productivity and climate resilience by scaling CSA practices to achieve national self-sufficiency.   Beneficiaries: The project will directly benefit 71,856 smallholders ages 15 and up and their households455 in the Niono region during the 5-year project term. Across time, indirect benefit via improved economic and nutritional outcomes could feasibly reach wheat producers throughout the central cereal production region of Mali. Project Description: This project is designed to improve the climate-resilience and productivity of wheat systems in Mali. Activities will address: (i) farmers technical assistance, (ii) extension services, (iii) producer associations, (iv) infrastructure development, (v) research and development, (vi) private- sector engagement, and (vii) enabling policies. Project Components COMPONENT 1: Producer Technical Assistance and Organizational Capacity Key Actors: MA, DNA, NGOs This component will raise the capacity of wheat producers in climate-resilient agricultural practices, and bolster their organization into cooperatives. Specifically, this will include: (i) targeted awareness campaigns regarding potential yields and climate resilience, (ii) field school training on best management practices, (iii) technical assistance for associations in cooperative activities such as storage, purchasing, and service access, (iv) technical assistance to producer associations in organizational management and meeting minimum requirements for financial services, and (v) training in accessing and using services e.g., input subsidies, bulk purchasing and sales, credit and loan, etc. 454 SciDevNet 2018 455 There are approximately 479, 810 residents of the target region. 80% of all Malians identify themselves as farmers. Assuming that the 18.6% of the population (3.54/19 million) that resides in Bamako does not identify as farmers, then approximately 96% of the population outside the capital is employed by agriculture. This implies that about 460,615 people in the target region are farmers. About 52% of the population, or 239,520, is ages 15 and up. City Population, “Mali: Administrative Division (Cercles and Communes)”; World Population Review, “Mali Population 2018”; Index Mundi, “Mali Demographics Profile 2018”; City Population, “Mali: Administrative Division (Cercles and Communes).” PAGE 163 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN COMPONENT 2: Build Capacity of Extension Agents and other Promoters Key Actors: MA, DNA, research institutions, NGOs, Office du Niger This project component will increase the capacity of farm advisors and other promoters, including (i) Office du Niger staff, (ii) NGO staff, (iii) ATI staff, and (iv) private industry representatives, to integrate CSA practices into their recommendations for wheat producers. Specifically, this will include training in: (i) climate change and benefits of SRI in rice systems, (ii) improved rice varieties, their advantages, and recommended best management practices (iii) best practices for effectively building producer capacity in SRI, including comparison plots, field schools, inter-farmer visits, and technical training, (iv) production of training manuals, reference guides, modules for integration into general training curricula, and (v) producing or accessing SRI system inputs. COMPONENT 3: Streamline Infrastructure Development Key Actors: DNA, ATI, Office du Niger, SOCAFON This component will focus on ensuring the infrastructure and equipment to support a thriving national rice sector is in place. Namely, this will consist of (i) developing and rehabilitating irrigated perimeters and water pumps, (ii) promoting irrigated areas by ATI for agricultural development, (iii) creating additional machine purchase and loan centers, (iv) bolstering supply of mechanized equipment available at centers, and (v) continued subsidizing on-farm technology to mechanize production processes. COMPONENT 4: Strengthen Research Efforts Key Actors: DNA, IER, NGOs, SOCAFON, research institutions This component will bolster research and development efforts to support CSA in wheat production. Specifically, this will include: (i) testing of existing improved varieties in the target region of Mali, (ii) as needed, development of new varieties optimized for the target region of Mali, (iii) identification of best management practice recommendations for each improved variety, (iv) development of less expensive, lower maintenance, and/or more efficient mechanization tools, and (v) operationalization of a system for timely dissemination of new technologies to producers and timely reception of feedback from producers on priorities for research. COMPONENT 5: Foster Enabling Policy and Private-sector Environments for Scaling Key Actors: DNA, SOCAFON This component will support scaling of CSA practices in wheat by fostering an enabling environment in terms of policy and private industry engagement. Specific subcomponents will include: (i) further developing existing financial services (e.g., subsidies, loan, credit, grants) for producers and cooperatives investing in production of wheat for sale, (ii) incentivizing private-sector providers of seeds, fertilizer, and equipment to improve access to improved inputs and equipment, particularly those developed in Component 4, (iii) supporting SOCAFON in establishing new groups in various production zones and expanding their equipment rental services with a focus on SWI equipment, training of community-based seed producers, (iv) explicating addressing CSA in the national agricultural development budget and policy, and (v) general public awareness campaign of SWI practices and benefits. PAGE 164 Risks: The main risks for this project are as follows: RISK PROBABILITY SEVERITY Severe drought and high temperatures High Low Political and security crises High High Community conflict (related to the development of new irrigated perimeters) Medium High Conflicts over land use (herders-farmers) Low Medium PAGE 165 MALI CLIMATE SMART AGRICULTURE INVESTMENT PLAN Annex G: Bibliography by sections CHAPTERS 1- 4 • Aberman, Noora-Lisa and Ali, Snigdha and Behrman, Julia and Bryan, Elizabeth and Davis, Peter and Donnelly, Aiveen and Gathaara, Violet and Koné, Daouda and Nganga, Teresiah and Ngugi, Jane and Okoba, Barrack and Roncoli, Carla, Climate Change Adaptation Assets and Group-Based Approaches: Gendered Perceptions from Bangladesh, Ethiopia, Mali, and Kenya (January 30, 2015). IFPRI Discussion Paper 01412. 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