Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 1 @2022 International Bank for Reconstruction and Development/ The World Bank 1818 H Street NW, Washington DC 20422 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. 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Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas TABLE OF CONTENTS LIST OF FIGURES...........................................................................................................7 LIST OF TABLES.............................................................................................................9 LIST OF BOXES.............................................................................................................12 ABBREVIATIONS ......................................................................................................... 13 PREFACE AND ACKNOWLEDGEMENTS................................................................ 15 1. INTRODUCTION...................................................................................................... 17 1.1 OBJECTIVES....................................................................................................................................................................... 19 1.2 REPORT STRUCTURE................................................................................................................................................ 19 2. NATURAL CAPITAL AND ECOSYSTEM SERVICES APPROACH.................... 21 2.1 DEFINITIONS................................................................................................................................................................... 22 2.2 BENEFITS OF A NATURAL CAPITAL APPROACH................................................................................. 23 2.3 COASTAL FOREST ASSETS.................................................................................................................................... 24 3. NATURAL CAPITAL VALUATION FRAMEWORK ............................................ 30 3.1 PILOTING OF APPROACHES............................................................................................................................... 33 3.1.1 Location selection rationale............................................................................................................................. 35 3.1.2 Spatial representation of pilot provinces.................................................................................................. 35 4. UNDERSTANDING ASSETS................................................................................... 37 4.1 ECOSYSTEM EXTENT ACCOUNTS................................................................................................................. 38 4.1.1 Recommended approach................................................................................................................................. 38 Supporting Resilient Coastal Economies in Vietnam 4 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 4.2 ECOSYSTEM CONDITION ACCOUNTS..................................................................................................... 46 4.2.1 Recommended approach................................................................................................................................. 47 5. ECOSYSTEM SERVICES........................................................................................... 54 5.1 COASTAL FOREST SERVICES ADDRESSED................................................................................................ 55 5.1.1 Ecosystem service accounts............................................................................................................................. 60 5.2 PROVISIONING SERVICE ACCOUNTING PRINCIPLES (FOR CAPTURE FISHERIES AND AQUACULTURE SUPPORT).............................................................. 60 5.3 CAPTURE FISHERIES.................................................................................................................................................... 62 5.3.1 Recommended approach................................................................................................................................. 62 5.4 AQUACULTURE SUPPORT................................................................................................................................... 64 5.4.1 Recommended approach................................................................................................................................. 64 5.5 CARBON STORAGE................................................................................................................................................... 65 5.1.1 Recommended approach................................................................................................................................. 66 5.6 COASTAL PROTECTION........................................................................................................................................ 71 5.6.1 Recommended approach................................................................................................................................. 71 5.7 RECREATION AND TOURISM............................................................................................................................ 72 5.7.1 Recommended approach................................................................................................................................. 72 5.8 IMPROVING ESTIMATES.......................................................................................................................................... 77 5.8.1 Limits of benefit transfer.................................................................................................................................... 78 6. POLICY AND PLANNING IMPLICATIONS OF COASTAL FOREST NATURAL CAPITAL ACCOUNTING........................................................................ 79 6.1 PLANNING IMPLICATIONS................................................................................................................................... 80 6.2 POLICY IMPLICATIONS............................................................................................................................................ 82 7. CONCLUSIONS AND RECOMMENDATIONS..................................................... 84 Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 5 ANNEXES........................................................................................................................87 A. COASTAL FOREST ASSETS IN VIETNAM...................................................................................................... 87 B. UN SEEA-EEA ECOSYSTEM ACCOUNTING TABLES............................................................................. 93 C. PROVINCIAL CONTEXTUAL DATA................................................................................................................. 96 D. GADM MAPS.................................................................................................................................................................. 103 E. ECOSYSTEM EXTENT ACCOUNT EXAMPLES........................................................................................ 104 F. FOREST COVERAGE SPATIAL ANALYSIS.................................................................................................... 119 G. ECOSYSTEM CONDITION ACCOUNT EXAMPLES............................................................................ 120 H. LONG LIST OF ECOSYSTEM SERVICES SPECIFIC TO COASTAL FOREST ASSETS IN VIETNAM....................................................................................................................................................... 128 I. SCOPING EXERCISE FOR ADDITION OF FURTHER ECOSYSTEM SERVICES .................... 134 J. ECOSYSTEM SERVICE ACCOUNT EXAMPLES.......................................................................................... 135 K. SUMMARY VALUES FOR PILOT ACCOUNTS.......................................................................................... 149 L. INTENSIVE AND SEMI-INTENSIVE AQUACULTURE FARMING, QUANG NINH PROVINCE......................................................................................................................................... 153 M. CARBON STORAGE AND SEQUESTRATION ESTIMATES FOR QUANG NINH COMMUNES.................................................................................................................................... 155 N. CARBON STORAGE AND SEQUESTRATION ESTIMATES FOR TT-HUE............................ 167 O. CARBON VALUE BY FOREST TYPE IN QUANG NINH AND TT-HUE................................. 171 P. COASTAL PROTECTION METHODOLOGIES......................................................................................... 172 REFERENCES..................................................................................................................... 187 Supporting Resilient Coastal Economies in Vietnam 6 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas LIST OF FIGURES Figure 2‑1. Natural capital cascade.................................................................................................................................. 22 Figure 2‑2. Schematic of how the benefits of a natural capital approach (turquoise) can be used strategically to address (blue) policy and planning issues faced in Vietnam (green)..... 23 Figure 3‑1. Schematic of the sequence of the biophysical and economic accounts under the SEEA-EEA, with an example of aquaculture production from mangrove forest (adapted from Rawlins et al., 2020)..................................................................................................................................................................... 33 Figure 3‑2. Study area – Quang Ninh Province....................................................................................................... 34 Figure 3‑3. Study area – Tam Giang - Cau Hai lagoon, TT-Hue Province............................................... 34 Figure 4‑1. Relationship between the three types of spatial units within the SEEA-EEA accounts............................................................................................................................................................................................. 39 Figure 5‑1. Count of references to ecosystem services in documents reviewed.................................. 55 Figure 5‑2. Average economic value of services delivered by coastal forests in Vietnam................ 56 Figure 0‑1. Map of mangrove species, aquaculture and other dominant land cover classes, Ca Mau Province........................................................................................................................................................................... 90 Figure 0‑2. Satellite imagery of southern Ca Mau Province from 1984 (a) and 2016 (b)............... 91 Figure 0‑3. Study area (Tam Giang - Cau Hai lagoon), TT-Hue province................................................ 99 Figure 0‑4. [Left to right] Quang Ninh province, Quang Ninh districts (Mong Cai), Mong Cai communes................................................................................................................................................................103 Figure 0‑5. [Left to right] TT-Hue province, TT-Hue districts (Quang Dien), Quang Dien communes..........................................................................................................................................................103 Figure 0‑6. Mangrove and sandy forest areas in Quang Ninh province, 2018.....................................105 Figure 0‑7. Total area (2015/18) of special-use, protection and production forests for Quang Ninh province (ha).....................................................................................................................................................108 Figure 0‑8. Map of constituent ecosystems, Tam Giang - Cau Hai............................................................113 Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 7 Figure 0‑9. Map of protection and production forests, Tam Giang - Cau Hai 2015.........................115 Figure 0‑10. Map of protection and production forests, Tam Giang - Cau Hai 2018......................115 Figure 0‑11. Map of forest change (2015-18), Quang Ninh province.......................................................122 Figure 0‑12. Canopy coverage of mangrove plots, Quang Ninh province districts 2015/18.......123 Figure 0‑13. Maps of forest change (2015-18) Tam Giang - Cau Hai, TT-Hue province, including stable forest...............................................................................................................................................................126 Figure 0‑14. Maps of forest change (2015-18) Tam Giang - Cau Hai, TT-Hue province, excluding stable forest..............................................................................................................................................................127 Figure 0‑15. Carbon value share among the coastal forest function types in Quang Ninh (left) and TT-Hue (right) Provinces......................................................................................................143 Figure 0‑16. Summary values of coastal forest ecosystem services, Quang Ninh and Tam Giang - Cau Hai................................................................................................................................................................150 Figure 0‑17. Annual value of coastal forest ecosystem services, Quang Ninh Province..................151 Figure 0‑18. Five core steps to estimating coastal protection benefits under process-based approaches.....................................................................................................................................................173 Figure 0‑19. Vulnerability maps produced by the Coastal Vulnerability Module in ArcGIS..........179 Figure 0‑20. Coastal protection values in Quang Ninh and Thua Thien Hue......................................186 Supporting Resilient Coastal Economies in Vietnam 8 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas LIST OF TABLES Table 2‑1. Global valuation of coastal wetland ecosystem services (Int. $/ha/yr, 2007 price level)................................................................................................................................................ 25 Table 2‑2. Local and regional mangrove valuations................................................................................................ 25 Table 2‑3. Mangrove system valuations in Vietnam............................................................................................... 26 Table 4‑1. Datasets for compilation and corresponding analysis procedures for the construction of coastal forest extent accounts............................................................................................................. 42 Table 4‑2. FORMIS forest type codes........................................................................................................................... 47 Table 4‑3. Framework for forest change matrix...................................................................................................... 50 Table 5‑1. Five ‘key’ services and valuation approach taken.............................................................................. 58 Table 5‑2. Statistical indicators for economic assessment of capture fishery services delivered by mangrove forests............................................................................................................................................... 62 Table 5‑3. Statistical indicators for economic assessment of aquaculture support services delivered by mangroves............................................................................................................................................................. 64 Table 5‑4. Criteria for accuracy assessment of coastal forest biomass estimates.................................. 66 Table 5‑5. Estimated biomass and biomass increment of coastal forest species in Vietnam........... 68 Table 5‑6. Data requirements of the ZTCM............................................................................................................. 76 Table 6‑1. Spatial scale of economic assessment of ecosystem services under recommended approaches...................................................................................................................................................... 81 Table 0‑1. UN SEEA-EEA Extent and condition account table....................................................................... 93 Table 0‑2. UN SEEA-EEA Ecosystem service account table (physical flows) by units to be measured.............................................................................................................................................................................. 94 Table 0‑3. UN SEEA-EEA Expected ecosystem service flows table (benefits)....................................... 95 Table 0‑4. Socioeconomic and geographical contextual data presented in trial accounts............... 96 Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 9 Table 0‑5. Area and population of Tam Giang - Cau Hai districts..............................................................100 Table 0‑6. Production value structure by administrative unit.........................................................................102 Table 0‑7. Mangrove and sandy forest areas (ha) within Quang Ninh districts, for 2015/18........104 Table 0‑8. Area of protection, special-use and production forest for Quang Ninh districts 2015/18 (ha)..................................................................................................................................................................................107 Table 0‑9. Changes in forest land (ha) in Quang Ninh under land use planning Decision 15/NQ-CP from 2016-2020............................................................................................................................109 Table 0‑10. Area of planted mangrove species 2018, Quang Ninh province (ha).............................110 Table 0‑11. Area of planted sandy forest species 2018, Quang Ninh province (ha).........................111 Table 0‑12. Constituent ecosystems, Tam Giang - Cau Hai TT-Hue province....................................112 Table 0‑13. Area of district mangrove and sandy forests, Tam Giang - Cau Hai 2015/18.............114 Table 0‑14. Area of protection and production forest in Tam Giang - Cau Hai districts, 2015/18............................................................................................................................................................................................116 Table 0‑15. Area of planted mangrove species, Tam Giang - Cau Hai 2018........................................117 Table 0‑16. Area of planted sandy forest species, Tam Giang - Cau Hai 2018....................................118 Table 0‑17. Matrix of forest change (2015-18) for Quang Ninh province..............................................120 Table 0‑18. Matrix of forest change (2015-18) for Tam Giang - Cau Hai, TT-Hue province......124 Table 0‑19. Ecosystem service scoping exercise....................................................................................................134 Table 0‑20. Statistical indicator values for economic assessment of capture fishery services delivered by mangroves, Quang Ninh province.........................................................................................................135 Table 0‑21. Capture fisheries (Tam Giang - Cau Hai lagoon) headline statistics.................................138 Table 0‑22. Aquaculture support (Tam Giang - Cau Hai lagoon) headline statistics........................140 Table 0‑23. Carbon stock and increment estimates for mangrove species in Quang Ninh and Tam Giang - Cau Hai, TT-Hue province..............................................................................................................141 Supporting Resilient Coastal Economies in Vietnam 10 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Table 0‑24. Carbon stock and sequestration of coastal forests in Quang Ninh and TT-Hue....................................................................................................................................................................................142 Table 0‑25. Estimated value of coastal forest carbon storage and sequestration in Quang Ninh and TT-Hue Provinces.................................................................................................................................143 Table 0‑26. Economic value of coastal protection services delivered by coastal forest assets, Quang Ninh and Tam Giang - Cau Hai, TT-Hue province.................................................................................145 Table 0‑27. Average visitor TCs from each departure zone...........................................................................146 Table 0‑28. Summary values of coastal forest ecosystem services, Quang Ninh and Tam Giang - Cau Hai (USD thousands).........................................................................................................................150 Table 0‑29. Modeling framework identifying key steps and critical data needed for the EDF approach.......................................................................................................................................................................174 Table 0‑30. Seven variables used in the Coastal Vulnerability Module and relevant data sources...................................................................................................................................................................................180 Table 0‑31. User defined inputs used in the Coastal Protection Module and relevant data sources...................................................................................................................................................................................182 Table 0‑32. Inputs used in the Coastal Protection Module to produce economic values of costs/benefits and relevant data sources..................................................................................................................182 Table 0‑33. Inputs used in ARIES and relevant data sources..........................................................................184 Table 0‑34. Coastal protection values of coastal forest assets in Vietnam.............................................185 Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 11 LIST OF BOXES Box 1. UN SEEA Central Framework land cover accounts................................................................................. 40 Box 2. The FORMIS database............................................................................................................................................. 40 Box 3. Condition account timescale................................................................................................................................ 51 Box 4. Assessment of mangrove coverage through time..................................................................................... 53 Box 5. Coverage assessment for other forest types............................................................................................... 53 Box 6. Carbon prices................................................................................................................................................................ 70 Box 7. FORMIS ‘forest type’ extent data.....................................................................................................................106 Box 8. Species-level extent data......................................................................................................................................109 Box 9. Coverage assessment, Quang Ninh Province............................................................................................123 Box 10. Scale of the capture fisheries assessment..................................................................................................137 Box 11. Scale of the carbon storage assessment.....................................................................................................144 Box 12. Carbon storage values.........................................................................................................................................144 Box 13. Welfare-based and exchange values............................................................................................................152 Supporting Resilient Coastal Economies in Vietnam 12 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas ABBREVIATIONS ARIES Artificial Intelligence for Ecosystem Services BSU Basic Spatial Unit DEFRA Department for Environment, Food and Rural Affairs EAU Ecosystem Accounting Unit EDF Expected Damage Function ERPA Emissions Reduction Purchase Agreement FORMIS Vietnamese Forestry Sector Management Information System GADM Database of Global Administrative Areas GDP Gross Domestic Product GHG Greenhouse Gases GIS Geographic Information System GRDP Gross Regional Domestic Product GSO General Statistics Office of Vietnam ha hectare InVEST Integrated Valuation of Ecosystem Services and Tradeoffs IPCC International Panel on Climate Change ISPONRE Vietnamese Institute of Strategy and Policy on Natural Resources and Environment km kilometer LCEU Land Cover/Ecosystem Function Unit LCU Local Currency Units Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 13 MARD Ministry of Agriculture and Rural Development MONRE Ministry of Natural Resources and Environment NCA National Climate Assessment NDVI Normalized Difference Vegetation Index SEEA UN System of Environment-Economic Accounting SEEA-EEA UN SEEA-Experimental Ecosystem Accounting SNA System of National Accounts (Z)TCM (Zonal) Travel Cost Methodology tCO2e Tons of carbon dioxide equivalent TDM Total Dry Matter TGCH Tam Giang - Cau Hai (lagoon system) TT-Hue Thua Thien Hue province UN United Nations UNFCCC UN Framework Convention on Climate Change USD US Dollars VND Vietnamese Dongs VNFOREST Vietnamese Administration of Forestry VR Visitation Rate WTP Willingness To Pay Supporting Resilient Coastal Economies in Vietnam 14 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas PREFACE AND ACKNOWLEDGEMENTS Inclusive and environmentally sound sustainable development requires managing natural resources that societies depend on for the long term. In the context of marine and coastal resources which provide an important source of income for large numbers of households and revenue for countries, this implies balancing the economic, social, and environmental dimensions of the use of the natural resources in marine and coastal areas. The term “blue economy” is increasingly being used to describe this balanced approach. For coastal countries such as Vietnam, the importance of its marine economy is well known. The country has used the goods and services provided by the natural assets in its near-shore and coastal areas – including fisheries, mangroves, wetlands, lagoons, and sandy beaches – for tourism, production of seafood, and controlling climate events that cause erosion and weathering. It has also used offshore resources such as petroleum and minerals for revenue generation. Vietnam’s 12th Party Central Executive Committee has recognized the importance of sustainable development of the marine economy and has approved ambitious growth and revenue targets in the strategy for the sustainable development of Vietnam’s marine economy by 2030, with a vision to 2045 (herein referred to as the Marine Strategy), promulgated in Resolution No. 36-NQ/TW in 2018. In Vietnam, the World Bank is actively supporting the Government of Vietnam with the coastal development agenda by informing its policy and investment decisions regarding integrated coastal area management, marine economy (including fisheries, energy, tourism, logistics, and coastal city development), resilience to climate change, and institutional strengthening. This support aims to strengthen the development of sustainable and climate smart economic activities in coastal areas in an integrated way, in other words, to facilitate a blue economy growth agenda in Vietnam. This report is part of a series of World Bank-led studies that aim to contribute to Vietnam’s efforts to boost its marine/coastal economy in a sustainable and climate resilient manner. This report focuses on adapting guidance for the valuation of key natural assets in coastal areas to Vietnam’s context, considering data availability and the nature of the natural assets in the country. The content of the report was developed following efforts to value natural assets in coastal areas in selected locations in Vietnam with the intention of providing relevant guidance for scaling out such efforts and ensuring they are done in a systematic manner and can inform the implementation of the Marine Strategy to 2030 with a view to 2045. This report has been prepared under the oversight of Diji Chandrasekharan Behr (Senior Natural Resource Economist) and Thu Thi Le Nguyen (Senior Environmental Specialist) from the World Bank Vietnam office in Hanoi. The consultant team was from JBA Consulting and included: Mark Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 15 Lawless, Anne-Marie Moon and Angus Pettit. The content of the report was informed by written input, dialogue and consultation with a team from the Institute of Strategy and Policy on Natural Resources and Environment (ISPONRE). The financing of this work was provided by the Wealth Accounting and Valuation of Ecosystem Services (WAVES) Trust Fund. WAVES is a World Bank-led global partnership that aims to promote sustainable development by ensuring that natural resources are mainstreamed in development planning and national economic accounts. WAVES is now part of the broader World Bank umbrella initiative, the Global Program for Sustainability (GPS). Supporting Resilient Coastal Economies in Vietnam 16 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Photo: Simon Dannhauer - shutterstock.com 1. Introduction 1. INTRODUCTION 17 The 2017 Planning law of Vietnam (which became effective in 2019) has a requirement that all master plans must include a consideration of ecosystem values and services. Under the law, the national system of master plans has five levels, which include national, regional and provincial master plans, master plans of special administrative-economic units, and master plans of urban and rural areas. A national masterplan acts as an overall basis for the formulation of all other master plans, which must conform accordingly. Master plans have a planning period of ten years, with a vision for 30-50 years for national plans, or 20-30 years for provincial plans. The law became effective as of January 2019, and thus applies to any plans for which the planning period starts beyond this date. The new requirements under this law present a unique opportunity to assist provinces and regions to consider ecosystem values in their planning process. Ecosystem values can facilitate better integration of concerns around climate, and the use of natural assets in climate change adaptation, into planning processes. There are three key ways in which planning can achieve this: ● In establishing coastal setback lines1 (in coastal provinces); ● In determining the optimal mix between nature-based investments and hard infrastructure investments to address flood protection and erosion control; ● In determining the spatial distribution of different sectoral activities in order to optimize synergies and reduce trade-offs. To effectively integrate ecosystem values into planning, it would be optimal to have an integrated statistical framework for organizing biophysical data, measuring ecosystem services, tracking changes in ecosystem assets and linking this information to economic and other human activities. A centralized framework such as this would help to address the following: ● The need to move from sectoral-based planning to a more integrated approach; ● The need to raise awareness about the value and contribution of coastal assets to different sector objectives, and the opportunities for natural assets to support economic growth and wealth; ● The need to develop a practical and replicable approach to informing planning processes with respect to the value of natural assets. The United Nations (UN) System of Environment-Economic Accounting (SEEA) is an internationally- agreed framework for organizing and presenting statistics on the environment and its relationship with the economy. The framework follows the structure of the System of National Accounts (SNA), which is an international standard set of recommendations in the form of a series of macroeconomic accounts, which help to compile measures of economic progress, such as Gross Domestic Product (GDP). The SEEA shares concepts, definitions, classifications and accounting rules with the SNA and provides frameworks for producing accounts across various thematic areas, such as air emissions, land and water accounts. Each of these accounts can be used to generate statistics on the role of the various aspects of the environment in the economy. 1 A line which defines a coastal zone in which certain development activities are prohibited or, at least, significantly restricted, typically to mitigate the impacts of storm tides, coastal erosion and sea level rise. Supporting Resilient Coastal Economies in Vietnam 18 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Most crucially, the SEEA accounts facilitate the proper accounting of wealth. Wealth accounts comprise an important part of the SNA, however, these accounts are not used nearly as widely as measures of production and income, such as GDP, which is the typical indicator of economic progress. GDP, as an indicator of growth, is flawed in that the value of asset liquidation is considered in addition to the production of goods and services in determining the product of the nation. As such, a country can deplete its stocks of natural capital and correspondingly, increase its GDP. Evidently, this is not a sustainable approach. Wealth accounts, on the other hand, account for both current and future wellbeing, i.e., sustainable growth (World Bank, 2011). Truly sustainable growth, by definition, requires the consideration of all forms of capital, including natural capital. The SEEA-Experimental Ecosystem Accounting (SEEA-EEA) is a framework complementary to the SEEA, specifically for organizing biophysical data and linking this to measures of economic activity through the medium of ecosystem services.2 The SEEA-EEA tends to focus on non- market ecosystem services which aren’t already captured in the SNA. Crucially, the series of accounts within the SEEA-EEA help to place biophysical data within the context of the SNA valuation principles, enabling users to see environmental assets through the same economic lens through which human and manufactured capital would be observed. This raises questions on how effectively provinces and the national government will take on board ecosystem values in their planning process as well as questions related to the capacity in the country to carry out such work. The guidance in this report aims to address these questions and the issues raised above, at least in part, by providing a framework for provinces to carry out natural capital valuation of coastal forest assets in Vietnam in a manner that is closely aligned with approaches for developing satellite accounts for ecosystems. The structure of the framework is aligned with that of the SEEA-EEA to ensure that the approach both provides a comprehensive view of ecosystems and is easily replicable. The framework has been trialed for application in two provinces in Vietnam, with the results of this process presented as an example application herein. 1.1 Objectives The aim of this report is twofold. The first is to present practical guidance on natural capital valuation using the framework provided by the SEEA-EEA. The aim is to provide technical staff in relevant agencies of Vietnam with methods that are implementable and provide a consistent approach for assessing of the value of mangroves and lagoons in coastal areas. This report provides a framework for valuing ecosystem services of coastal forests and lagoons. This will help to raise awareness of the contribution of natural capital assets to economic activity in Vietnam and to frame natural capital assets in a way in which they can be effectively integrated into the planning processes. The second aim is to inform the drafting of the decree and guidance on valuing natural assets being prepared by MONRE following the revision of the law on environmental protection. 2 It should be noted that a new version of the SEEA-EEA is due for release in March 2021 with a revised title, which will reflect its elevation to an accounting standard for the incorporation of environmental values into national wealth accounts. The new version of the SEEA will likely drop the “experimental” label. 1. Introduction 19 1.2 Report structure This guidance report is structured as follows: ● Section 1 provides background and context for the work. ● Section 2 introduces the concept of using a natural capital approach and its benefits. This section also emphasises the importance of Vietnam’s coastal forest assets and the threats to these systems. ● Section 3 provides an overview of the natural capital accounting framework and its structure, as presented in this guidance. ● Sections 4 and 5 comprise the main body of guidance on the compilation of data for natural capital valuation for coastal forest assets. Section 4 presents the guidance for compiling the data on coastal forest ecosystem extent and condition in a manner that is aligned with the SEEA- EEA accounts, whilst Section 5 presents the guidance for the completion of ecosystem service supply and valuation for five key ecosystem services following the framework of SEEA-EEA. The examples of extent, condition and ecosystem service data compilation for the two pilot provinces can be found in Annex E, G and J, respectively. The guidance for aggregating the ecosystem service value outputs from the data compilation, alongside summary values from these ‘accounts’ can be found in Annex K. ● Section 6 reviews the implications for policy and planning of the natural capital accounting framework presented. ● Section 7 concludes the report and presents recommendations for future work. Supporting Resilient Coastal Economies in Vietnam 20 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 2. NATURAL CAPITAL AND Photo: DreamArchitect - shutterstock.com ECOSYSTEM SERVICES APPROACH 2. Natural capital and ecosystem services approach 21 2.1 Definitions ● Natural capital: The elements of nature that either directly or indirectly provide value to people. This can include both the living and non-living aspects of ecosystems. ● Natural capital assets: The stocks of renewable and non-renewable natural capital and the natural processes that underpin them. For example, soils, forests, farmlands, rivers, minerals, and oceans. ● Ecosystem services: The flows of benefits obtained from natural capital assets. Benefits are often obtained in combination with other forms of capital, e.g., human and manufactured capital. Direct, provisioning ecosystem services can have obvious economic benefits; for example, timber, food production and the provisioning of clean water. These services are often captured in conventional measures of economic activity, such as those presented under the SNA. However, ecosystem services are often indirect and ‘invisible.’ A coastal mangrove forest, for example, may store many thousands of tonnes of carbon in biomass, which indirectly benefits society by mitigating the impacts of climate change. Coastal forests may also provide social and cultural benefits, which can be more abstract and thus harder to quantify and monetize. For example, these natural environments can create a sense of remoteness and detachment from busy urban environments and thus have a tranquility value, with secondary benefits for mental wellbeing. The ‘cascade’ from natural capital stocks to ecosystem service benefits is portrayed in Figure 2-1. Figure 2‑1. Natural capital cascade3 Natural capital accounting is a method of assessing the contribution of natural ecosystems’ to the economy to help governments understand their economies’ reliance upon natural systems, track changes in these systems that may have implications for economic activities (e.g., industries), and manage natural resources and ecosystems to ensure their economic benefits are sustained into the future. There is a standard framework for natural capital accounting developed by the United Nations and partner organizations that describes several categories of natural capital accounts including ecosystem accounts. 3 Source: Natural Capital Coalition (n.d.) Supporting Resilient Coastal Economies in Vietnam 22 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Ultimately, by viewing the environment through a natural capital lens, we can understand how the various elements of the natural world contribute to achieving the outcomes sought by both the individual and wider society (Defra, 2020). 2.2 Benefits of a natural capital approach Seeing nature as an asset that delivers numerous benefits to society enables us to better manage the natural environment to meet economic and welfare needs, while also promoting its value and, thus, its careful conservation. By using language to describe the natural environment that aligns with conventional economic decision making, decision makers can better consider how the environment contributes to societal goals and the trade-offs surrounding investments that impact the quantity or quality of natural capital assets. Natural capital as a concept encourages a balanced consideration of environmental assets in terms of their ecological function and the social and economic opportunities which these assets present. Figure 2‑2 presents some of the benefits of a natural capital approach, as detailed in Defra (2020), alongside some of the issues identified in Section 1 surrounding planning and policy in Vietnam. These ‘benefits’ and ‘problems’ are linked in a schematic, which demonstrates how a natural capital approach (and, in turn, the framework presented in this report) may help toward solving some of these issues. Benefit Link Problem (natural capital approach) (solution) (policy and planning in Vietnam) Facilitates a more innovative Highlights the potential of less Intergration of climate considerations approach to identifying policy conventional nature-based solutions to and the effective use of natural assets solutions issues in the planning and policy arena in the planning process is limited Facilitates recognition of optimal Declining effectiveness of hard Helps to identify priorities for solutions which maximise benefits engineering solutions to adapt to investment climate change A common framework for Provides a common framework Need to move from a sectoral-based inter-disciplinary analysis provides a to bring together economic an to a more integrated approach to foundation greater consistency and social evidence and analysis planning collaboration Describing natural assets in Low awareness about the contribution Enables a more comprehensive conventional economic terms increases of coastal assets to supporting societal cost benefit analysis awareness amongst decision-makers objectives and economic growth Framing natural assets in the same Reduces the risk of the value of economic context as artificial assets Value of natural assets is not the natural environment being promotes their integration into considered in the planning process ignored in decision-making conventional planing processes Figure 2‑2. Schematic of how the benefits of a natural capital approach (turquoise) can be used strategically to address (blue) policy and planning issues faced in Vietnam (green). 2. Natural capital and ecosystem services approach 23 In addition to the benefits listed above, by identifying the flows of benefits obtained from natural assets and framing natural assets in economic terms, a natural capital approach can also help to identify those coastal assets which are of the highest value in terms of meeting societal objectives. This spatial analysis can help to inform priorities in terms of development, and crucially, the development of coastal setback lines. 2.3 Coastal forest assets In this section, we briefly review the value of coastal forest assets at the global scale and in Vietnam and summarize some of the major threats in Vietnam to these natural capital assets. While mangroves are the primary coastal forest asset in Vietnam and thus comprise the major focus of this analysis, other assets of importance within this category include Melaleuca forests and sandy forests, e.g., Casuarina equisetifolia, or Whistling Pine, and are referenced. For the sake of conciseness, this section is mainly a quantitative summary. More qualitative, contextual data on coastal forest assets can be found in Annex A, including information on: coastal forest services; the economic sectors to which coastal forests contribute in Vietnam; threats to coastal forest assets in Vietnam and the growing importance of coastal forest services in Vietnam. With the aim of producing a state-of-the-art guidance framework for the monetary assessment of coastal ecosystem services for both policy makers and researchers, Mehvar et al. (2018) reviewed multiple natural capital accounting studies, including two global scale and thirty local and regional case studies in which different coastal services were assessed. Mehvar et al. found that coral reefs and mangrove systems are amongst the most frequently valued ecosystems in natural capital accounting studies. Due to this, and the fact that mangroves are the primary coastal forest in Vietnam, a majority of this review will focus on the value, and threats to, these systems. However, some consideration is given to both Melaleuca and sandy forests in the review of values within Vietnam. Mangrove systems provide a range of valuable ecosystem services due to their unique ecological structure and their high biodiversity. The diagram below details the use-values of mangrove systems, across the globe, as reviewed in the Millennium Ecosystem Assessment (MEA) (2005) and supplemented by expert knowledge. One of the global studies reviewed by Mehvar et al., carried out by Groot et al. (2012), delivered estimates of the economic value of a bundle of ecosystem services for ten key biomes, including four coastal systems and, crucially, coastal wetlands (defined as mangroves and tidal marshes). Value estimates for ecosystem services for each biome were obtained from four databases of ecosystem service values and multiple other valuation studies. In total, 320 publications were screened, which concerned 300 different case study locations across the ten biomes. The mean value for each ecosystem service across the relevant publications for each biome was calculated and these values were then summed to provide an estimate of the total mean value of the bundle of all services which could potentially be delivered by the biome, sustainably. Accordingly, the mean value of coastal wetlands was 193,845 (Int. $/ha/year[yr], 2007 price level). It should be noted that this value was skewed significantly by the value of the ‘waste treatment’ service delivered by mangroves, which was valued at 162,125 (Int. $/ha/yr, 2007 price level) alone. Nonetheless, this gives an indication as to the significant value of mangrove (and tidal marsh) systems at the global scale. Further details of the results are provided in the table below. Supporting Resilient Coastal Economies in Vietnam 24 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Table 2‑1. Global valuation of coastal wetland ecosystem services (Int. $/ha/yr, 2007 price level) No. of Mean total Median total Minimum Maximum total estimates value value total value value 139 193,845 12,163 300 887,828 Of the thirty local and regional valuation studies reviewed by Mehvar et al., five studies valued the services from mangrove forest systems. These studies were selected carefully as a representative sample of current valuation studies, distinguished based on the ecosystems and services considered, the valuation methods and the final estimated values. The summary results for the mangrove valuation studies are presented below to give a further indication as to the value of these systems, globally. Table 2‑2. Local and regional mangrove valuations Source Location Valuation Ecosystem service/ Estimated methods good value (USD) Vo et al., Vietnam Market price, Fishery, timber, carbon 3,000 (ha/yr) 2015 replacement cost sequestration and storm protection Barbier et Thailand Avoided damage Coastal protection, 10,158 – 12,392 al., 2007 cost wood, habitat support (ha)/1 for fishery Brander et Odisha Avoided damage Storm (wind) 177 (ha) (1999 al., 2012 region, cost protection price level) India Das et al., Southeast Benefit transfer Fisheries, fuel wood, 4,185 (ha/yr) 2013 Asia (from 48 selected coastal protection, (2007 price level) studies) water quality Hussain India Replacement cost Nutrient retention value 232 (ha) and Badola, 2008 1/This appears to be an asset value 2. Natural capital and ecosystem services approach 25 The results in Table 2‑2 show that the lowest values are reported for mangroves in India, while higher values are reported for systems in Thailand. Clearly, spatial variability exerts a considerable control on the benefits obtained from ecosystem services and services delivered by mangrove systems. Due to the high spatial variability of the values delivered by mangrove systems, we carried out of a review of studies which reported such values for mangrove systems specific to Vietnam. Fifteen studies in total were sourced, which reported economic values for various ecosystem services delivered by Vietnamese mangrove systems. For five of these studies, comparable annual values per hectare of multiple bundled services could be extracted. The results of this review are presented in Table 2‑3. Further detail on the relative value of the individual services within these studies, and thus the priority services delivered by mangrove forests in Vietnam, is provided in Section 5.1. Table 2‑3. Mangrove system valuations in Vietnam Source Location Ecosystem service Valuation 2019 value approach (USD/ha/yr)4 ISPONRE Ngoc Hien, Timber, firewood and Market price 207 (2015) Ca Mau advantage firewood (production + protection forest avg.) Recreation Travel cost 23 Carbon storage Market price 347 Aquaculture production Benefit transfer 223 Capture fisheries Market price 53 Total n/a 854 4 Original values have been uplifted to 2019 values using a GDP deflator (https://data.worldbank.org/indicator/ NY.GDP.DEFL.ZS.AD?end=2019&locations=VN&start=2000&view=chart) Supporting Resilient Coastal Economies in Vietnam 26 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Source Location Ecosystem service Valuation 2019 value approach (USD/ha/yr)4 Juenzer and Can Gio, Ho Fishing Market price 2914 Tuan (2013) Chi Minh Timber and firewood Market price 414 Tourism Travel cost 3393 Carbon storage Benefit transfer 2062 Erosion control Benefit transfer 4466 Total n/a 13249 Do and Ca Mau Capture fisheries Market price 234 Bennett (without opportunity (2006) cost) Aquaculture production Market price 579 (without opportunity cost) Timber (without Market price 17 opportunity cost) Fuelwood Market price 8 Nypa fruticans leaves Market price 0 (construction materials) Medicinal plants Market price 9 Total (with n/a 637 opportunity costs) Total (without n/a 849 opportunity costs) 2. Natural capital and ecosystem services approach 27 Source Location Ecosystem service Valuation 2019 value approach (USD/ha/yr)4 Tri et al. Can Gio, Ho Timber Market price 123 (2000) Chi Minh Fishing catches Market price 6 Tourism Surrogate travel 18 cost Biodiversity Contingent 0 valuation Total n/a 148 Vo et al. Ca Mau Timber Market price 2215 (2015) Erosion control Replacement 753 cost Carbon storage Benefit transfer 255 Fishery-related products Market price 94 Total n/a 3317 The average value of mangroves in the studies listed in Table 2‑3 is USD 3,662 (per ha), not dissimilar to the average value of those systems listed in Table 2‑2 (USD 3,768 per ha), demonstrating the importance of the ecosystem service benefits delivered by these systems in Vietnam. While we recognize the large range in values reported in Table 2-2. impacts the validity of such a comparison, as discussed above, there is a shortage of studies that report comparable ecosystem service values for mangrove systems in Vietnam. It should also be noted that some of the studies listed in Table 2-3. report ecosystem service values using incompatible approaches. For example, study #1 reports some ecosystem services using market prices approaches, which use exchange values, while recreation values are assessed using a travel cost methodology, which uses welfare values. These values are not directly comparable. Other coastal forest types are also of economic importance in Vietnam. However, the literature of the services delivered by such coastal forest types is far more limited. It should be noted that Supporting Resilient Coastal Economies in Vietnam 28 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas the valuation by Juenzer and Tuan (2013) in Table 2‑3 was actually a valuation of the bundled services delivered by both mangrove and Melaleuca forests. Notably, this corresponded with the highest total ecosystem service value within the review. We extended the literature search to find comparable valuation studies for other coastal forest types within Vietnam. In doing so, we were able to find only a single study which reported ecosystem service values for sandy forests. Phuong et al. (2012) assessed the value of timber, tourism, carbon storage and protection (from blowing sand) services from Casuarina equisetifolia plantations in Ninh Thuan and Binh Thuan Provinces. The total annual economic value of these services was estimated at USD 543 per ha. Despite the demonstrable value of services delivered by coastal forest systems in Vietnam, a historical trend which continues to the present day is the exploitation and destruction of these systems due to anthropogenic drivers. Over a fifty-year period between 1943 and 1993, forest cover in Vietnam declined from an estimated 43 percent to 28 percent (World Bank, 2019a). In the case of mangrove forest, large declines in coverage have been driven primarily by conversion to large-scale, intensive aquaculture. By 2011, sea and brackish water aquaculture had covered 730,000 ha (Orchard et al., 2016). Additionally, coastal forest systems such as Melaleuca forest are under comparable pressure, being exploited for materials, rice cultivation and non-rice production (Do and Bennett, 2016). Furthermore, much of Vietnam’s tourist industry is concentrated in and around its coastal assets, with waste and pollution also posing a considerable threat. While efforts have been made to recover forested land across Vietnam, (forest extents recovered to 41.65 percent in 2017, according to the World Bank [2019a]), most natural forest cover has been replaced by plantation forest. The UN Framework Convention on Climate Change (UNFCCC) in 2016 found that closed-canopy forest now only constitutes 5 percent of total forest cover, and consequently, in excess of two thirds of Vietnam’s natural forests are in either poor or regenerating condition (World Bank, 2019a). We recognize that the patterns observed in historical forest cover in Vietnam do not necessarily directly reflect the changes observed in coastal forest cover, specifically. However, there is a lack of reliable, historical coverage data for coastal forest assets in Vietnam; hence, this analysis is presented to demonstrate the scale of some of the forest change in Vietnam, which is also being felt in coastal systems. 2. Natural capital and ecosystem services approach 29 Photo: Nguyen Quang Ngoc Tonkin - shutterstock.com 3. NATURAL CAPITAL VALUATION FRAMEWORK Supporting Resilient Coastal Economies in Vietnam 30 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas When using a natural capital framing to valuing the services from natural assets, it is useful to draw on the framework approach used in natural capital accounting – specifically for ecosystem accounts. The UN SEEA- EEA offers a standardized approach for tracking the extent and condition of ecosystem assets and the flows of ecosystem services they provide to people and the economy. This can be useful for valuing ecosystem service and enabling a consistent methodological application for valuation that can facilitate more effective integration of the results into planning and decision-making processes. Additionally, drawing on a natural capital accounting framework can assist with replication especially if there is a national commitment to set up natural capital accounts5. With a national system for natural capital accounts the approaches to valuation, including data collection and analysis, will be less costly because the data collection will have been formalized and some biophysical data can be readily transferred. The framework presented in this study is designed to inform planning processes with information on the value of key coastal assets in a manner which is replicable across all provinces. As such, the methodology used for some parameters in this framework aligns with that use in SEEA-EEA. The reader is reminded that the objectives of the SEEA-EEA are to: ● Organize information on the natural environment in a spatial context, providing information on the linkages to social and economic systems; ● Applying common, agreed classifications, concepts and terminology to provide a consistent platform for organization, testing and analysis of data; ● Allowing connections to be made to the wider environmental-economic data compiled under the central SEEA; ● Identifying key data gaps and requirements. The structure of the SEEA-EEA comprises a series of accounts which compile to present a coherent and comprehensive view of ecosystems. These accounts comprise both biophysical accounts, which measure the biophysical stocks and the ecosystem services these deliver, and monetary accounts6 (see Figure 3‑1). The accounts first begin by identifying the stocks of natural capital assets and their condition or quality, which influences their capacity for service delivery. This is followed by an overview and quantification of the flows of services they provide, culminating in the estimation of the value of these flows in a manner which is comparable with other economic activities. The full system of accounts included within the SEEA-EEA framework is detailed below, while examples of the tables which comprise these accounts, presented in the UN SEEA-EEA guidance, can be observed in Annex B. ● Ecosystem extent account: Organize information on the extent of different biophysical stocks in terms of area. ● Ecosystem condition account: Records the quality of a natural capital asset and captures, in a 5 National natural capital accounts would be state accounts that the Ministry of Finance can use for reflecting on national wealth. Natural capital accounts, in addition to other physical and financial accounts provide a more comprehensive view of wealth, and subsequently, a country’s growth, as opposed to traditional indicators such as GDP (see Section 1 for further detail of this rationale in the context of the SEEA-EEA) 6 Note that, while the guidance on physical accounts is now well established (and will likely lose the ‘experimental’ label soon), the guidance on valuation is still a work in progress, and hence bespoke valuation guidance, such as that presented in this report, is required. 3. Natural Capital Valuation Framework 31 set of indicators, its functioning in relation to naturalness and the delivery of ecosystem services. ● Ecosystem service accounts: Measures the supply of ecosystem service and the corresponding beneficiaries, classified by broad national accounting categories. ● Monetary asset account: Records monetary value of opening and closing stocks of all natural capital assets in an ecosystem accounting area, and additions and reductions to those stocks. ● Thematic accounts: A set of standalone accounts which cover land, water, carbon and biodiversity, which are of relevance in the measurement of ecosystems and in assessing policy response. The valuation framework presented in this report follows the same structure of accounts as detailed above, although thematic accounts are not included. The four accounts prior are structured in such a way that the information provided should be in an appropriate context for linking to economic, environmental and social data available from both wider sources and that from under the SEEA central framework to help understand: ● How ecosystem services contribute to economic production and; ● How the management of ecosystems influences various aspects of economy. The economic value of a given ecosystem at any spatial scale, is estimated as the aggregated value of the various flows of benefits delivered by the system. The Present Value (PV) of these benefits expected over a given appraisal period can then be compared with the value of other assets in the standard national accounts. Photo: Nguyen Quang Ngoc Tonkin - shutterstock.com Supporting Resilient Coastal Economies in Vietnam 32 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Biophysical assessment Economic valuation Ecosystem Ecosystem services supply Ecosystem services use and use values Ecosystem Ecosystem service and benefits (e.g monetary extent conditon supply (e.g production value of mangrove- (e.g mangrove (e.g forest (e.g aquaculture support by supported forest area) coverage) (%) production) mangrove production) (£/ha (ha) (tons) forest) (t/ha of of aquaculture) aquaculture) Figure 3‑1. Schematic of the sequence of the biophysical and economic accounts under the SEEA-EEA, with an example of aquaculture production from mangrove forest (adapted from Rawlins et al., 2020) The accounting approaches presented forthwith are designed specifically for the assessment of coastal forest assets. However, the successful design of these methods should demonstrate the potential for the creation of further, full natural capital accounts for Vietnam’s many, precious ecosystems. Likewise, while the data used in these approaches is also asset specific, the approaches demonstrate and indicate as to the readily available data sources that can be accessed to establish comprehensive natural capital accounts for better accounting of wealth within the state. 3.1 Piloting of approaches The approaches presented in this report have been developed and trialed by the Vietnamese Institute of Strategy and Policy on Natural Resources and Environment (ISPONRE) for the following provinces: ● Quang Ninh Province: Located in the northeast of the country, this province has 120km of coastline and is relatively heavily urbanized (55 percent). ● Thua Thien Hue (TT-Hue) Province, Tam Giang – Cau Hai (TGCH) Lagoon: Located on Vietnam’s central coastline, TGCH represents the largest coastal lagoon system in Southeast Asia, supporting a population of over 200,000 people. Maps of the two provinces are provided in the Figures below. 3. Natural Capital Valuation Framework 33 Figure 3‑2. Study area – Quang Ninh Province Figure 3‑3. Study area – Tam Giang - Cau Hai lagoon, TT-Hue Province Supporting Resilient Coastal Economies in Vietnam 34 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas While approaches have been developed and applied for the assessment of coastal forest assets in the two pilot locations, they have been designed with replicability in mind, with the intention that they can be readily applied to coastal forest assets in other provinces across the country. 3.1.1 Location selection rationale Quang Ninh province and TT-Hue province are two provinces with distinct coastal ecosystems that are both rapidly growing. Quang Ninh is the most competitive province in terms of opportunities for private sector investment. With its proximity to China, Quang Ninh is also an attractive location for recreation and tourism for Chinese tourists. It is also an important province in terms of connectivity. In the period of 2015-18, the average economic growth rate of the agricultural, forestry and fishery sector, industries often associated with the exploitation of mangrove systems, was 4 percent. More widely, the average economic growth rate (GRDP) for the same period for the province across all industries was 9.95 percent, which is 3.25 percent more than the national average growth rate. Thua Thien Hue, similarly, has a lot of opportunities for tourism expansion along its coastal locations. The TGCH lagoon system is the largest coastal lagoon system in Southeast Asia, covering 21,620 ha. As such, the site is growing as a tourist hotspot along with significant growth in tourism in the Thuan An beach area in recent years. At the same time, the biodiversity and associated productivity of the lagoon system means it is an ideal nursery habitat for both inland and marine fish species. The area is intensively used for aquaculture, fisheries and agriculture, which are the main providers of local livelihoods for approximately 100,000 people. Furthermore, the diversity of fish species and aquatic resources means the site is exploited for capture fisheries. While the capture fisheries present are of relatively small scale and are artisanal in nature, this is another dependency that communities have on the natural capital of the lagoon system, which is useful to assess. TT-Hue is also one of the provinces tagged by the Prime Minister to optimize the blue economy of the province. These provinces are representative of the emerging reality of coastal provinces in Vietnam – locations where there is significant interest in rapid growth, which often occurs at the expense of natural resources. Furthermore, there are few in-depth analyses attempting to value natural resources in coastal areas in these locations, relative to the number of studies on mangroves in the Mekong Delta and southern part of Vietnam. 3.1.2 Spatial representation of pilot provinces Many of the natural capital accounting approaches detailed in the following sections collate data at the commune level (although several of the final results (e.g., economic values) are aggregated at the provincial scale). For Quang Ninh Province, all coastal communes and some additional communes connected to the Bach Dang River estuary system have been included within the study. This totals to 103 communes within 11 districts. For TT-Hue Province, all communes connected to the TGCH lagoon system have been included, which covers most of the coastal area. This area covers 45 communes within 5 districts. 3. Natural Capital Valuation Framework 35 In the following sections (Chapters 4-5), the main body of the guidance is presented. This includes guidance on the completion of the ecosystem extent and condition (Chapter 4) and service (Chapter 5) accounts. Worked examples of the pilot extent, condition and service accounts from Quang Ninh province and TGCH, TT-Hue are presented in Annex E, G and J, respectively. Annex C includes guidance (sources) for the collation of contextual biophysical and socioeconomic data, which was collected by ISPONRE and was included within the pilot natural capital accounts (the data from the pilot accounts is also presented). The collation of this data does not necessarily align with standard natural capital accounting frameworks, nor the SEEA-EEA system of accounts, and as such is not included within the main body of guidance presented forthwith. However, collecting such data prior to completing a natural capital account for a given province can be useful for the following reasons: ● Socioeconomic context: Provides an indication as to the beneficiaries of ecosystem services delivered by local natural capital assets. This can also provide an indication of the demand for ecosystem services, i.e., those relied upon by the local population. Additionally, by understanding the trajectory of economic development, some of the potential anthropogenic threats to natural capital assets, and thus service delivery, can be ascertained. ● Geographical context: This is a determinant of ecosystem structure and composition and thus the capacity for natural capital assets to deliver ecosystem services. This can also be an indicator of the vulnerability of natural capital assets to both natural and anthropogenic threats. Possible sources of such data are thus provided in Annex C as a point of reference. Photo: CravenA - shutterstock.com Supporting Resilient Coastal Economies in Vietnam 36 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Photo: 578foot - shutterstock.com 4. UNDERSTANDING ASSETS 4. Understanding assets 37 4.1 Ecosystem extent accounts This section describes the recommended approach for the completion of the coastal forest asset extent accounts. This approach is derived from the methodologies used in the trial provinces, developed by ISPONRE, and is considered the most appropriate approach for replication in other provinces. Additionally, the approach is designed to closely align with SEEA-EEA guidance (UN, 2014) on assessing ecosystem extent. A summary of the methods and results for the ecosystem extent accounts in each of the trial provinces is presented as an example of the application of the recommended approach in Annex E. 4.1.1 Recommended approach The quantity and location of natural capital assets are key determinants of the service delivered by them. As such, the purpose of ecosystem extent accounts is to present data on the stocks of natural capital assets within a given accounting area. Natural capital assets can be conceptualized in different ways. Typically, in extent accounts, and as recommended by SEEA-EEA guidance, ecosystem extent generally focuses on measuring landcover, i.e., broad habitat types. Here, we describe the spatial units used for accounting in SEEA-EEA guidance and how our extent accounts align with this approach. The SEEA-EEA uses three types of spatial units for ecosystem asset accounts (Figure 4‑1): 1. Basic Spatial Units (BSUs): Small spatial areas of around 1 km2 with basic info on the land they contain. 2. Land Cover/Ecosystem Function Units (LCEUs): BSUs can, theoretically, be aggregated into areas which reflect relatively homogenous ecosystems.7 The EEA suggests using the UN Food and Agriculture Organisation (FAO) Land Cover Classification System (LCCS) – a framework designed for the consistent classification and mapping of landcover comprised of eight major land cover types – for defining LCEUs. 3. Ecosystem Accounting Units (EAUs): LCEUs can be further aggregated into EAUs. These take into account aspects such as administrative boundaries and natural features, which are of particular management interest, to create cohesive units. 7 Note that, in practice, data is often only available for LCEUs, or even for EAUs, rather than for BSUs. Therefore, the challenge often is not in aggregating data, but in finding a way to differentiate the different parts of what from the data appear to be homogeneous LCEUs/EAUs. Supporting Resilient Coastal Economies in Vietnam 38 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas LCEU type A Ecosystem Accounting Unit BSU LCEU type C LCEU type B LCEU type A Note: The light blue represents the wider EAU, disaggregated by the dark blue, LCEUs. Grid squares (dashed) represent the BSUs. Figure 4‑1. Relationship between the three types of spatial units within the SEEA- EEA accounts The most common and arguably most practical approach to assessing natural capital is to capture its various elements in the distinctive spatial units comprised by (relatively) homogenous classifications of land cover (habitat type) (UN, 2014). While the UN recommends focusing on measuring land cover for the creation of extent accounts, it is flexible as to the definition of the spatial areas (habitats) used for accounting. Broad habitat types, as spatial units, should have an appropriate level of consistency in terms of ecological structure and function across their area. This should lead to consistency in the ecosystem services delivered and the factors which influence the delivery of ecosystem services. By bundling natural capital assets into broad habitat types, as opposed to assessing individual assets, natural capital accounts can be completed for wider spatial areas with much greater time efficiency. 4. Understanding assets 39 Box 1. UN SEEA Central Framework land cover accounts Listed below are the land cover (habitat) types as included within the UN SEEA Central Framework physical (extent) account for land cover, for the purpose of reference and application to other natural capital accounts in Vietnam, should they be developed following successful implementation of the coastal forest asset accounting framework presented here. It is recommended, however, within the SEEA-EEA guidance (UN, 2014) that “for ecosystem accounting purposes, the definition of the categories of land cover should align with the definition of the types of LCEU,” and that the SEEA Central Framework provides a “starting point.” As such, there is flexibility in the habitat types for inclusion within a given accounting framework, depending on the frame of reference. Artificial surfaces Regularly flooded areas Crops Sparse natural vegetated areas Grassland Terrestrial barren land Tree-covered area Permanent snow, glaciers and inland water bodies Mangroves Coastal water and inter-tidal areas Shrub-covered area The extent account should examine the extent and changes in extent over time of both mangrove forest and sandy forest areas. Mangrove and sandy forest areas can be partitioned into sub-classes relevant to ecosystem service supply. The scale of the spatial units (habitat types) assessed as part of the extent account, further detailed in Table 4‑1, aligns with the scale of the SEEA-EEA LCEUs. Box 2. The FORMIS database In 2009, the Vietnamese Forestry Sector Management Information System (FORMIS) was launched with the objective of establishing a fully integrated management information system to facilitate effective decision making concerning forest management. FORMIS provides a unified platform where over 750 forest administration agencies can integrate their data. FORMIS’ resource database and forest resource monitoring system have since been adopted for official use by the Vietnam Administration of Forestry (VNForest), an agency under the Ministry of Agriculture and Rural Development (MARD). As such, FORMIS spatial datasets can be downloaded as shapefile (.shp) files, ready for analysis and application to a coastal forest extent account from the VNForest Forestry Data Sharing System. More information on the datasets which comprise the FORMIS database can be found via the VNForest (2020) Forestry Data Sharing System. Supporting Resilient Coastal Economies in Vietnam 40 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas As the habitat extent is a direct determinant of the extent of the service delivered, these accounts will be an indication of service delivery and some of the outputs will be directly utilized in calculations as part of the ecosystem service accounts. Table 4‑1 details the FORMIS data to be collated from the VNFOREST Forestry Data Sharing System platform (see Box 2) and the data analysis required to produce the outputs that should comprise the ecosystem extent account. The table is ordered by chronology in terms of the outputs that comprised the pilot accounts. Each output is broken down to guide the user as to the specific location of the target data required to produce the output, followed by the necessary steps in terms of analysis. The key below explains what information is included within each column of the table: ● Dataset: Location of the classification of the target data. ● Classification: Location of the target data. ● Data: The target spatial data for extraction. ● Analysis: Summary of the analysis approach to produce the output. ● Output: Information forming part of the extent account. ● Purpose: Function of the output in the extent account. All data should be extracted from the VNFOREST platform in ESRI shapefile (.shp) format (or similar) for the analysis process. The outputs should be collated in a series of summary tables which comprise the final extent account. Where possible, results should also be spatially represented to understand the patterns of extent and thus potential for service delivery. For a number of outputs, the analysis process involves an overlay with a vector shapefile of the district boundaries in each province to obtain the spatial data with a higher level of granularity at the district level. It is recommended to extract the shapefiles of district boundaries from the Database of Global Administrative Areas (GADM) database (GADM, 2020). The GADM project aims to map the administrative areas of all countries at all levels of sub-division, using a high spatial resolution and extensive set of attributes. Maps can be browsed by country – for Vietnam, vector files can be accessed for both districts and communes within each province. The GADM maps for Quang Ninh and TT-Hue provinces can be seen in Annex D. 4. Understanding assets 41 42 Table 4‑1. Datasets for compilation and corresponding analysis procedures for the construction of coastal forest extent accounts Compo‑ Extent Component Dataset Classification Data Analysis nent No. account purpose component 1 Mangrove Ecosystem Forest Forest type Wetland forest/ Data extracted area by district extent is a direct Resource Mangrove forest and overlaid 2015 (ha) determinant of Data 2015 with shapefile service delivery. of district boundaries. 2 Mangrove Ecosystem Forest Forest type Wetland forest/ Data extracted area by district extent is a direct Resource Mangrove forest and overlaid 2018 (ha) determinant of Data 2018 with shapefile service delivery. of district boundaries. 3 Change in Indicates Forest Forest type Wetland forest/ Clip operation mangrove trajectory of Resource Mangrove forest to determine area by district service delivery. Data difference in 2015 – 2018 2015/18 area between (ha/%) Outputs 1 and 2. Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Compo‑ Extent Component Dataset Classification Data Analysis nent No. account purpose component 4 Sandy forest Ecosystem Forest Site condition Sandy soil Extract area by district extent is a direct Resource overlapping area 4. Understanding assets 2015 (ha) determinant of Data 2015 between layers. service delivery. Overlay shapefile Forest Forest type Evergreen of district Resource broadleaved boundaries.8 Data 2015 forest (all conditions) 5 Sandy forest Ecosystem Forest Site condition Sandy soil As above. area by district extent is a direct Resource 2018 (ha) determinant of Data 2018 service delivery. Forest Forest type Evergreen Resource broadleaved Data 2018 forest (all conditions) 6 Change in Indicates Forest Site condition Sandy soil Clip operation sandy forest trajectory of Resource to determine area by district service delivery. Data difference in 2015 – 2018 2015/18 area between (ha/%) Outputs 4 and 5. Forest Forest type Evergreen Resource broadleaved Data forest (all 2015/18 conditions) 8 As Casuarina equisetifolia is an evergreen species, an overlay of these layers will extract the relevant forest area. 43 44 Compo‑ Extent Component Dataset Classification Data Analysis nent No. account purpose component 7 Area of Indicates the use Forest Forest function Protection forest, Data extracted protection, value and services Resource Special use forest, and overlaid special use and delivered (see Data 2015 Production forest with shapefile production below for further of district forest 2015 by detail). boundaries. district (ha) 8 Area of Indicates the use Forest Forest function Protection forest, Data extracted protection, value and services Resource Special use forest, and overlaid special use and delivered (see Data 2018 Production forest with shapefile production below for further of district forest 2018 by detail). boundaries. district (ha) 9 Change in Indicates Forest Forest function Protection forest, Clip operation protection, trajectory of Resource Special use forest, to determine special use and service delivery. Data Production forest difference in area production 2015/18 of raster files. forest area 2015 – 2018 by district (ha/%) 10 Area of Indicates the Forest Forest origin Plantation Extract planted extent of Resource overlapping area mangrove compensation for Data 2018 between layers. forest by natural mangrove Overlay shapefile district 2018 forest loss and Forest Forest type Wetland forest/ of district Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas (ha) trajectory of Resource Mangrove forest boundaries. service delivery. Data 2018 Compo‑ Extent Component Dataset Classification Data Analysis nent No. account purpose component 11 Area of Indicates the Forest Forest origin Plantation Extract planted sandy extent of Resource overlapping 4. Understanding assets forest 2018 compensation Data 2018 area between (ha) for natural sandy ‘sandy soil’ forest loss and Forest Site condition Sandy soil and ‘evergreen trajectory of Resource broadleaved service delivery. Data 2018 forest’ layers. Overlay Forest Forest type Evergreen ‘plantation’ Resource broadleaved layer, followed Data 2018 forest (all by shapefile conditions) of district boundaries.9 12 Area of Further level of n/a Forest plot Planted species Data on planted granularity on the relevant mangrove compensatory (mangrove) species (ha) by habitat creation species extracted district with implications and overlaid for service with shapefile delivery. of district boundaries. 13 Area of Further level of n/a Forest plot Planted species Data on the planted sandy granularity on relevant (sandy forest species compensatory forest) species (ha) by district habitat creation extracted with implications and overlaid for service with shapefile delivery. of district boundaries. 9 As Casuarina equisetifolia is an evergreen species, overlaying the evergreen forest and sandy soil layers should extract the sandy forest ecosystem of interest. 45 With regards to Outputs 7–9, ascertaining the area of these levels of forest protection provides a spatial indicator as to the types of service delivered by forest areas and extent of service delivery. The three types of forest are defined under Vietnam’s Forest Protection and Development Law 2004, which lays out the management, protection and use rules of Vietnam’s forests. The three forest types are classified as follows: ● Protection Forest: Predominantly used strategically to protect water resources and land, to prevent erosion and desertification, to prevent natural hazards and to regulate climate. ● Special-use Forest: Mainly designated for conservation, primarily for conservation of biodiversity, but also for areas of cultural significance. ● Production Forest: Designed for timber and non-timber forest product production. This classification still has a degree of environmental protection – the State has the power to set forest assignment quotes and use terms for operators, as well as the power to decide when to convert a forest to another land use. 4.2 Ecosystem condition accounts Condition accounts for natural capital assets are designed to record the condition at specific points in time and the changes in condition over time (i.e., relative to a point of reference). The condition of an asset is multi-faceted and includes many aspects such as habitat connectivity and the extent of disturbance. These aspects can be assessed through the use of various indicators, depending on data availability. Ultimately, however, these aspects determine the ecological functioning of the natural capital asset and as a result, the capacity for the asset to deliver ecosystem services. Aspects of condition can be affected by various background pressures including drivers of demand and management practices. As such, the SEEA-EEA guidance (UN, 2014) states that there are two stages to compiling an ecosystem condition account: ● Selecting the key characteristics of condition (e.g., vegetation, biodiversity, soil) and the indicators which will be used to assess these ● Assessing the indicators and relating these to a reference condition (e.g., baseline condition in time). The comprehensiveness of the condition assessment is here limited by the availability of condition data which can be obtained for multiple provinces (i.e., from FORMIS). As such, the ‘characteristics’ of condition to be assessed are limited to ‘vegetation’, which will be assessed using the following two sets of indicators: ● Forest type ● Forest (canopy) coverage10. 10 At this point, the approach to assessing canopy coverage has been designed for application to mangrove forest only, and not other coastal forest types, e.g., sandy forests (see Section 4.2.1.2). Supporting Resilient Coastal Economies in Vietnam 46 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas As in section 4.1, this section provides a description of the recommended approach for the completion of coastal forest condition accounts. The recommended approach is broken down into two sections, corresponding to the assessment of each of the condition indicators. Both indicator assessment approaches, as recommended by the SEEA-EEA, examine the changes in the respective indicators relative to a reference condition (i.e., over a selected time frame). The approaches detailed are derived from the methodologies used in the pilot provinces, developed by ISPONRE, and are considered the most appropriate approach for replication in other provinces based on data availability. A summary of the methods and results for the ecosystem condition accounts in each of the pilot provinces is presented as an example of the application of the recommend approach in Annex G. 4.2.1 Recommended approach 4.2.1.1 Forest change matrix The FORMIS ‘Forest type’ spatial dataset contains data on the area of distinct land use categories for multiple years. Assessing how coastal forest areas either transition between forest types or remain static in their typology can indicate as to the trajectory of the condition of the natural capital asset. For example, should a given area change from ‘plantation mangrove’ to ‘agricultural crop’, it can be implied that this area has been deforested and thus the capacity for the coastal forest that was present to deliver ecosystem services has been lost. For the years of 2015 and 2018, spatial data on tens of forest types can be extracted from the VNFOREST Forestry Data Sharing System. The forest type codes deemed useful for a condition assessment of coastal forest assets have been identified and presented in the table below. Table 4‑2. FORMIS forest type codes Forest type code Forest type 11 Primary mangrove forest 39 Rich secondary mangrove forest 40 Medium secondary mangrove forest 41 Poor secondary mangrove forest 42 Natural rehabilitation secondary mangrove forest 4. Understanding assets 47 Forest type code Forest type 62 Plantation mangrove 64 Plantation on sandy soil 74 New plantation mangrove 77 New plantation on sandy soil 80 Regeneration on mangrove 82 Open land on hill land 83 Open land on rocky mountain 84 Open land on saline wetland 85 Open land on alkaline wetland 86 Open land on sandy soil 87 Open land with scattered trees on sandy soil 88 Agricultural crop on hill land 90 Agricultural crop on saline wetland 92 Other freshwater wetland 93 Other land Having extracted the forest type data for the specific points in time, between which changes in condition are being assessed (2015/18) for the study site(s), the data can then be included in a matrix of forest change for the given time period, which will comprise the first part the condition account, as presented in Table 4‑3. Note that this forest change assessment need only consider coastal forest changes, and not all changes in other forest categories. Using simple geoprocessing techniques and the individual layer files for each of the forest types, the matrix should be filled out. Supporting Resilient Coastal Economies in Vietnam 48 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas The matrix records the area of forest which has changed from one forest type at the start of the time period (2015) to another by the end of the time period (2018). Accordingly, a number of ‘change type’ categories have been defined for each type of habitat change (i.e., from forest type X to forest type Y), which define the change in condition. It is useful to summarize the total forest area which has undergone each ‘change type’ to assess how condition has changed for the total area across the time period. The ‘change type’ categories are presented below the matrix in Table 4‑3 as a key. The forest change matrix can be completed at a range of spatial scales. For example, district boundaries can be overlaid with the forest type raster layers for 2015/18 to ascertain forest change for each commune. Examples of the matrix for the two pilot areas are provided in Annex G. It should also be noted that there is the potential to expand this matrix, should additional condition data become available, to provide an added level of granularity. For example, land use types (e.g., mangrove) could be sub-divided into land use types of different condition grades (e.g., mangrove – “good”, “poor” condition, etc.) and the matrix framework be used to rapidly identify spatial trends in condition change at a more detailed level. We are not aware of any standard, spatial condition indicator datasets currently; however, the forest coverage data discussed in 4.2.1.2. could be useful in this regard. Photo: ZOOMATIONS - shutterstock.com 4. Understanding assets 49 Table 4‑3. Framework for forest change matrix 50 2018 42 62 64 74 77 80 82 83 84 85 86 87 88 90 92 93 Total 42 Natural rehabilitation secondary mangrove forest 62 Plantation mangrove 64 Plantation on sandy soil 74 New plantation mangrove 77 New plantation on sandy soil 80 Regeneration on mangrove 82 Open land on hill land 2015 83 Open land on rocky mountain 84 Open land on saline wetland 85 Open land on alkaline wetland 86 Open land on sandy soil 87 Open land with scattered trees on sandy soil 88 Agricultural crop on hill land 90 Agricultural crop on saline wetland 92 Other freshwater wetland 93 Other land Total Change type Characteristic Change type Characteristic Restoration Change from existing coastal forest to a Deforestation Change of mangrove forest to other land forest with better condition, e.g., newly use type planted forest to closed canopy forest Stable forest Stable forest Reforestation Change from non-forest to coastal forest, e.g., new plantation Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Stable non forest Stable non forest Degradation Change from exiting coastal forest to a forest with poorer condition Annex forest change matrix can also be represented spatially (e.g., Figure 0‑14 in Annex G), to understand the arial patterns in condition change and correspondingly, potential consequences for service delivery on a spatial scale. Box 3. Condition account timescale It is recognized that the timescale for the forest change matrix is narrow considering the historical changes in forest type that have been observed in Vietnam (see Section 2.3 and Annex A.3 for further detail on the large-scale conversion of natural forest to plantation forest throughout the past half century). The current timescale for the forest change matrix is based on the availability of data from FORMIS. It is recommended that a review is carried out to assess whether additional historical data is available, and thus whether it is possible to extend the time frame of the condition account. This will provide a more accurate indication of the trends in condition and, should more significant changes in forest condition be revealed as a result, provide a stronger case for intervention. Should historical data not be available from alternative sources, it is recommended that the extent and condition data are reviewed periodically to better establish current and future trends, as these will have direct impact on service delivery (see Section 7). The forest change matrix provides an indication of the trajectory of the forest condition and the results can thus be used to make some assumptions regarding the impact of forest changes observed on coastal forest ecosystem service delivery, presently and in the future. On the other hand, while this analysis demonstrates how the condition is presently changing, it does not indicate as to why these changes are occurring. It is recommended that the matrix of forest change is used as a baseline analysis and that further work is carried out to understand the drivers of change, as without this data, robust assumptions regarding the future patterns of forest condition cannot be made. Should clear evidence be obtained for both the continued degradation of forest assets, and a supporting explanation for this decline, then more weight is added to the argument for the conservation of coastal forest assets. 4. Understanding assets 51 4.2.1.2 Forest coverage The forest (canopy) coverage assessment takes a remote sensing approach to quantify the extent of gaps in the canopy cover of existing mangrove forest. A higher canopy coverage is likely to be indicative of a better ecosystem condition, while a partial or patchy forest cover could be indicative of disturbance and lower ecosystem functioning. Disturbance could be natural or anthropogenic. The approach should be applied to all plots of mangrove forest identified in each province in the ecosystem extent account. The approach should also be applied across different points in time as a proxy assessment for changes in condition, as with the other approaches to the condition account. While we recognize that other factors of ecosystem structure such as stand age would also be a good indicator of condition, and potentially disturbance, the assessment of canopy coverage is one which can be readily applied using available high-resolution satellite data available and does not require additional, primary data collection. A large proportion of the imagery that is commonly available is not adequate for measuring changes in canopy cover and thus care must be taken to acquire suitably high-resolution data, which may also require further processing costs. Gaps in canopy cover are measured using the Normalized Difference Vegetation Index (NDVI), which indicates the presence of live green vegetation. More specifically: ● Sentinel 2 imagery for the year of 2018 ● Landsat 8 imagery for the year of 2015. For each plot of mangroves identified in the FORMIS data for each year, the NDVI imagery should be obtained and a threshold NDVI score of 0.4 applied. This threshold has been defined as indicative of mangrove presence/coverage – a score of less than 0.4 should be identified as non-mangrove (i.e., water, soil and sparse vegetation). As such, for each plot, the actual mangrove area can be determined and then reported as a coverage percentage. For example, if within a 10 ha plot, 8 ha has a NDVI value greater than 0.4, the percentage coverage can be assumed to be 80 percent. A coverage percentage close to 100 will represent dense mangrove forest, while a value below 50 for a single plot would suggest a mangrove plot with substantial gaps and sparse vegetation cover. As such, the coverage percentage gives a good indication of condition. Observing the change in percentage coverage between the 2015 and 2018 satellite images will provide a valuable indication as to the trajectory of condition. Plot coverage results can then be aggregated (averaged) at the commune and district levels. Examples of the NDVI satellite imagery, forest plot overlays and resultant percentage coverage maps for the two pilot studies can be observed in Annex F. The coverage results for each district and year should be presented in a simple plot from which analysis can be made regarding the spatial and temporal patterns of canopy coverage with corresponding assumptions regarding condition. Supporting Resilient Coastal Economies in Vietnam 52 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Box 4. Assessment of mangrove coverage through time The growth stage of the vegetation in the satellite imagery exerts a considerable control on the results of the coverage analysis. As such, if images from different months of the year were compared, there would be a notable difference in the results and inaccurate conclusions could be drawn regarding the trajectory of condition. If results are to be compared over time, as much consistency should be assured as is possible with regards to the time of the year from which images are selected and the threshold NDVI value. Box 5. Coverage assessment for other forest types In its current state, this approach has been developed as part of the condition assessment for mangrove forest plots only, as the NDVI threshold of 0.4 has been defined specifically for this forest type. However, this approach could be expanded to facilitate the assessment of other coastal forest types. A review would need to be carried out to investigate how the threshold NDVI value would need to be adjusted to identify the coverage of other forest types. The work of Baloloy et al. (2020) could be useful to review in this regard. Baloloy et al. have produced a new Mangrove Vegetation Index for the rapid and accurate mapping of mangrove plots from remotely-sensed images based on the distinct greenness and moisture of this forest type. A similar approach could be derived for alternative forest types. 4. Understanding assets 53 Photo: Luna Linghting - shutterstock.com 5. ECOSYSTEM SERVICES Supporting Resilient Coastal Economies in Vietnam 54 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 5.1 Coastal forest services addressed To establish an understanding of the types of ecosystem services applicable to mangroves and coastal forests in Southeast Asia and Vietnam, a preliminary literature review of over 40 documents was completed. The review consisted of primary research (often focused on a single or selected ecosystem service(s) specific to coastal forest assets or a particular site of interest), metadata analysis research (that aims to collate and synthesis data from multiple studies), research that identifies methodological approaches, and guidance documents. Documents were reviewed to identify the ecosystem services that would be most relevant for incorporation into the framework presented in this study. The review identified that many of the standard ecosystem services listed in the Millennium Ecosystem Assessment could be applicable. A very basic assessment of the number of references to particular services was used as a proxy to begin to understand the relative importance of these services (see Figure 5‑1). The assessment indicated that in coastal forest habitats, biodiversity, coastal protection, food and recreation are priority services delivered by these assets. It should be noted that while the literature review concerned a range of coastal forest habitat types in Vietnam, including sandy soil forest, mangrove forest habitats dominated the literature and literature concerning services delivered by other coastal forest habitat types was relatively scarce. 20 18 16 14 12 10 8 6 4 2 0 Natural hazards and... Biodiversity and habitat Climate regulation Coastal and soil erosion Spiritual and Religious Cultural heritage Inspirational Minerals Nutrient Cycling Primary production Recreation and tourism Sense of place Soil formation Water purification Water regulation Aesthetic Biogeochemicals Disease regulation Educational Fiber Food Fresh water Fuelwood Genetic resources Figure 5‑1. Count of references to ecosystem services in documents reviewed To further investigate the relative importance of the ecosystem services, a preliminary analysis of the relative monetary value was completed. Five economic valuation studies11 were identified which 11 Sources: ISPONRE (2015), Juenzer and Tuan (2013), Do and Bennett (2006), Tri et al. (2000) and Vo et al. (2015) 5. Ecosystem services 55 reported comparable per hectare, annual values for ecosystem services delivered by coastal forest assets in Vietnam specifically. Figure 5‑2 illustrates the average value of each of the services valued in the studies. The data labels represent the number of sources in the review that reported values for the given service. All ecosystem service values reported in the studies have been updated to 2019 values using a GDP deflator.12 3000 2 2500 USD/ha/yr (2019) 2000 1500 3 1000 3 3 4 500 2 2 1 1 1 1 1 0 r d s ge d be s ne n n oo ty ism s) rie ts oo io tio ra rsi m ici uc at elw ct he ur ew sto uc Ti ive ed m od te to fis od Fu fir M ro n od pr on io e d pr lp nd ur Bi an ct rb ed ta pt re ra tru Ca lat n as Ca ltu tio be ns -re Co cu ea co m ry ua Ti cr s( he Re Aq ve Fis ea al yp N Mean Median Figure 5‑2. Average economic value of services delivered by coastal forests in Vietnam Figure 5‑2 shows that coastal protection services represent the highest value services by some margin, with a mean value of approximately 1,000 USD/ha/yr greater than the service with the second highest mean value. Following this, timber, aquaculture production, carbon storage, recreation and capture fisheries services fall within a mean value range of between approximately 350 – 1150 USD/ ha/yr, although it should be noted that the median values of timber, carbon storage, recreation and capture fisheries services are much lower than the mean values. While services such as biodiversity and habitat were assessed as priority services previously (see Figure 5‑1) their relative economic value is low. This result reflects the many inaccuracies of applying a monetary value to an intangible concept such as biodiversity. 12 https://data.worldbank.org/indicator/NY.GDP.DEFL.ZS.AD?end=2019&locations=VN&start=2000&view=chart Supporting Resilient Coastal Economies in Vietnam 56 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Following from the above, a range of ecosystem services are considered applicable to coastal forest ecosystems in Vietnam. The full list of services, developed over the course of the study and following an initial review of research and in consultation with ISPONRE, was developed and subject to a ranking exercise to ascertain the most important services for inclusion within the framework. The full list of services and ranking exercise are presented in Annex H. From the long list of services, five key services were selected to be incorporated into the valuation framework: ● Capture fisheries ● Aquaculture support ● Carbon storage ● Coastal protection ● Recreation and tourism. Each of the services ranked as ‘must do’ and ‘should do’ in the ranking exercise were included within the framework: ‘coastal protection’ services include both mitigating the effects of coastal erosion and storm surge hazards associated with typhoons; and the water purification service described in the long list in Annex H is reframed as ‘aquaculture support.’ The exception from this list is biodiversity and habitat services, as there is not considered to be an adequate approach to the economic assessment of these services, which relates to the inaccuracies of assessing biodiversity monetarily. Additionally, with the exception of timber and firewood services, the key services selected represent those which have the highest economic value (accounting for both mean and median values) in Figure 5‑2. The table below summarizes, for each of the five key services, the reasons for inclusion within the framework and the valuation approaches taken to assess them in economic terms. Photo: Nguyen Quang Ngoc Tonkin - shutterstock.com 5. Ecosystem services 57 Table 5‑1. Five ‘key’ services and valuation approach taken Service Reason for inclusion Valuation approach13 Capture High dependency amongst some coastal communities in Market price fisheries Vietnam on the income generated from inland fisheries of largely non-migratory crustacean and mollusk species. Mangrove habitat is crucial to the production from these systems. Direct market price approaches can capture these values in a robust manner. Average economic value rank – 4th Aquaculture Mangrove systems provide spawning and nursery grounds Market price support for aquatic species and are thus crucial in providing suitable conditions for production from aquaculture systems. Production from aquaculture systems comprises well over half of Vietnam’s fisheries exports. Direct market price approaches can capture these values in a robust manner. Average economic value rank – 2nd Carbon Coastal forest assets are vital ecosystems in sequestering Benefit storage carbon. This is particularly true for mangroves and their transfer14 capacity for sequestration in both their biomass and soil. Vietnam’s vulnerability to climate change makes this a priority service. Additionally, standard approaches to carbon accounting and readily available data make this service relatively simple to assess. Average economic value rank – 5th 13 Some of the methods are based on exchange value, and some on welfare value, which are different concepts of value, and result in estimates that cannot be added together. For comparison with other values in national accounts, exchange values are preferred. However, welfare value is useful for decision-making. For purposes of this report, both values are reported as suggested by La Notte et al. (2017) [ref: La Notte, A., Vallecillo, S., Polce, C., Zulian, G., & Maes, J. (2017). Implementing an EU system of accounting for ecosystems and their services. EUR 28681 EN; Publications Office of the European Union, Luxembourg, doi:10.2760/214137, JRC107150)]. 14 The carbon content of the mangroves can be assessed in the field. However, for replicability purposes, as the carbon content of the mangrove species is well known and measurements are reasonably robust, we are assuming the carbon storage and ‘transferring’ estimates from primary studies. Supporting Resilient Coastal Economies in Vietnam 58 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Service Reason for inclusion Valuation approach13 Coastal Vietnam’s extensive coastline makes it vulnerable to coastal Benefit transfer protection hazards. A relatively high incidence of tropical cyclones (awaiting and coastal erosion threatens properties, infrastructure development and livelihoods. Coastal forest assets help to stabilize the of damage- coastline and buffer against these hazards, delivering a costs avoided valuable service. method) Average economic value rank – 1st Recreation Vietnam’s tourist industry is seeing exponential growth and Benefit transfer and tourism the appeal of its natural capital assets are a significant driver (awaiting of this demand. The tourist industry here simultaneously development threatens the condition of coastal natural capital assets and of travel-cost so it is paramount to recognize the recreation value of these methodology) systems. Approaches to the assessment of this service are relatively well developed. Average economic value rank – 3rd It is recognized that the inclusion of more services within the valuation framework would lead to a broader assessment of the benefits delivered by coastal forest assets. However, a balance needs to be struck that is proportional to the relative importance of the services selected and is workable from a practitioner’s perspective. Producing replicable and reliable approaches for the monetary assessment of services across a wide range of ecosystem services is challenging and is often limited by data availability. As such, a phased approach is recommended, starting with the priority services highlighted herein. Over time, as the approaches in this framework are applied across the country’s national boundaries, this framework can be evolved to encompass a greater range of services that are identified as relevant. As suggested, it is recommended that in further work, the assessment of wider benefits is considered where these are significant and likely to contribute significantly to the total valuation. Annex I details suggestions for a scoping exercise for the inclusion of additional services within the framework in the future. Should efforts be made to expand the framework to encompass a wider range of ecosystem services, it is recommended that a scoping exercise to determine whether the service(s) of interest is (are) appropriate for economic valuation. 5. Ecosystem services 59 5.1.1 Ecosystem service accounts For each ecosystem service, this section provides guidance for the completion of the ecosystem service account, including both the method for estimating the supply of the individual service and the estimation of its monetary value (i.e., the latter three stages in the schematic of accounts presented in Figure 3‑1). The guidance is presented for estimation of both supply and value for each service together as this approach better reflects the biophysical flow of services, the subsequent benefits to human wellbeing and the resultant economic contribution of benefits to society (as opposed to examining the ecosystem service and monetary accounts as separate entities). Additionally, the presentation of approaches in this way is more coherent and, as a result, more accessible. For each service, a summary of the methods used for the completion of the pilot ecosystem service account and results from the account are provided for each of the pilot provinces in Annex J. The methods described in the following sections are those which have been found to be most appropriate for the specific case of coastal forests in the case study areas of Vietnam, in light of the nature of the ecosystems involved and of the available data. These methods might not always be feasible, however, even in other parts of Vietnam. In some cases, some possible alternative approaches are mentioned; however, as alternatives would be driven by the availability of data, this is not always possible. 5.2 Provisioning service accounting principles (for capture fisheries and aquaculture support) A standard market price approach is taken to the assessment of these services, which measures the benefits by examining the market price, consumer surplus and producer surplus in the market. The value of the service is calculated as the sum of the consumer and producer surplus. However, as this approach concerns the benefits that coastal ecosystems deliver to people, only the producer surplus is accounted for, i.e., the surplus local people obtain from the ecosystem and provide to the market. The values of the capture fisheries or of aquaculture production are easy to estimate by subtracting the cost of collection from the revenue. As mangroves serve as spawning grounds and provide other benefits to both capture fisheries and aquaculture, it is likely that both would be less productive, at any given level of effort, if the area of mangroves is reduced or lost. The challenge is to determine what portion of this benefit is attributable to the presence of mangroves. Several studies have shown that there is a correlation between the area of mangroves and production in capture fisheries and aquaculture. Here, we use this correlation coefficient, ρ, to adjust the value of capture fisheries and aquaculture to obtain that which is generated by mangroves.15 15 Note that this parameter might change; if mangroves are degraded, for example, their contribution to capture fisheries might also decline; changes in sea level or water temperature might also affect their contribution. Therefore, it would be important to assess this parameter regularly. Supporting Resilient Coastal Economies in Vietnam 60 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas The formula which summarizes this approach is presented below: NV = ρ ∑(Pi Qi ― Ci ) Where: NV = net value of the ecosystem (USD) Pi = price of good or service i from the ecosystem (USD) Qi = amount of product i being collected (unit, e.g., tons) Ci = costs involved in collection of product i (USD) ρ = correlation parameter of mangroves and capture fisheries or aquaculture.16 This formula is applied, in principle, in the recommended approaches to the assessment of both the capture fisheries and aquaculture support services. In turn, the principles of this approach underpin the example approaches taken to the assessment of these services delivered by mangrove forests in Quang Ninh province. However, for the wetland ecosystem in TGCH lagoon, parameter ρ cannot be determined. This is because there is not comparable literature available for the wetland ecosystem at present, as there is for mangrove forest. As such, the value of these services in the TGCH lagoon area are estimated based on the net incomes generated for local people in the wetland. This, and the bespoke approaches taken to the assessment of these services in this location, are explained further in Appendices J.1.1 and J.1.2. Due to the ongoing pandemic and associated travel restrictions, primary data collection for the assessment of these services was not feasible. Consequently, the recommended approaches and the approaches employed in the example accounts utilize secondary data. Data sources include the General Statistics Office of Vietnam (GSO), provincial reports and literature. Restrictions did, however, permit one validation trip to both sites to ensure that parameter values and data employed in the calculations accurately reflected the ongoing practices within local capture fisheries and aquaculture systems. The validation trips involved direct meetings and discussion with local authorities, including: ● Department of Natural Resources and Environment ● Department of Agricultural and Rural Development ● Department of Industry and Trade ● Department of Investment and Planning ● Commune People’s Committee. Others consulted included local farmers on the validation trips and telephone consultations with local experts on aquaculture activities and management and forest management. 16 This correlation parameter is explained, and the principles of this parameter discussed, in greater depth in forthcoming sections when applied to the individual provisioning services. 5. Ecosystem services 61 5.3 Capture fisheries Mangrove ecosystems provide habitats for certain aquatic species, which can be harvested directly by local people. As such, the existence of mangroves facilitates the production and revenue obtained from inland capture fisheries. We recognize that the highest value fish species in Vietnam are harvested from offshore fisheries, and that mangroves do not directly contribute to this service. The species of concern in the estimation of this service are non-migratory species, which reside in and around the mangrove system and thus their harvested value is directly dependent to an extent on mangrove presence. Typically, these are mollusk species, including small crabs, small-scale clam, shrimp and sesarmidae, as well as seaworm, sipunculus nudus, and some small fish. The capture fisheries ecosystem service provided by coastal forests can be monetized using relatively simple market price approaches once concepts such as the cost of labor from harvesting seafood products and the opportunity cost of the time involved in this labor have been captured. 5.3.1 Recommended approach The table below details a series of statistical indicators used in the calculation of an annual capture fisheries value for a given location, i.e., district, which subsequently can be translated to a per unit area of mangrove value. The table also details the source of the data and thus how it can be obtained for replicating the subsequent calculations of the ecosystem service value in other provinces. Table 5‑2. Statistical indicators for economic assessment of capture fishery services delivered by mangrove forests Symbol Statistical indicator Data source D Average income from capture fisheries Obtained through surveys at the district level across the province (Vietnamese Dongs of the commune’s People Committee. We [VND]/ day/person) recommend surveying multiple districts and averaging a single value for the province. H Number of households in selected district Obtained through surveys at the district level of the commune’s People Committee. B Number of households benefiting from Obtained through surveys at the district level capture fisheries in the district of the commune’s People Committee. C Opportunity cost of labor (minimum wage Data available from the provincial statistics for province) (VND/month/person) office. ρ Correlation of mangrove presence and Literature (World Bank, 1996, p. 57; Nguyen, capture fisheries production (0.7) 2015). A Mangrove area within the district (ha) Ecosystem extent account Supporting Resilient Coastal Economies in Vietnam 62 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas The average income data from capture fisheries should be collected specifically for the province as both the capture products and socioeconomic conditions of provinces can vary markedly. However, the data collection should be carried out across a number of sample districts and the average income should be assumed to apply across the province. This is because data cannot necessarily be obtained for each individual district. Regardless of the fact that it is costly to obtain data for each district, locals typically change their catching areas over time and season, making the value of mangrove areas change over time. Thus, it is more sensible to estimate one value for the entire mangrove forest. In practice, the value obtained by one commune depends strongly on their ability with regards to fish capture as opposed to the area of mangroves in the commune, a factor which should be excluded from this natural capital assessment. It should be recognized that the legal minimum wage may be quite different from the typical wage for unskilled labor. If this is the case, the latter value would best represent an opportunity cost. It is possible that primary data on local wages for unskilled labor could be obtained from sources such as the commune’s People Committee; however, if such data cannot be obtained, then it is reasonable practice to assume the state minimum wage. The correlation between mangrove presence and the production of capture fisheries is taken from a large-scale study by the World Bank, which found that a loss of 100 ha of mangroves correlated with a decline in the yield of capture fisheries by approximately 70 tons (World Bank, 1996, p. 57). Thus, a correlation of mangrove presence and capture fisheries is assumed at 0.7, which theoretically would translate to a potential increase in inland fish stocks/resources of 0.7 tons for each additional 1 ha of mangrove habitat. While this correlation parameter is also supported by Nguyen (2015), it is a correlation, and not a causal relationship. As such, it may not reliably predict the effect of large changes in mangroves (in either direction). This parameter was validated on the Quang Ninh validation trip and through expert interviews. Thus, while this parameter was employed for the determination of the value of this service in Quang Ninh province, we suggest that it is validated locally, as has been done, if this approach is to be applied to calculate the value of this service in other provinces. Alternatively, it may be more appropriate to apply a range of values for the purpose of sensitivity analysis and thus to account for potential variability as a result of local ecological conditions (for example, variable conditions for mangrove growth), depending on the outcome of the validation process. Having obtained the relevant statistical indicators from both primary and secondary sources, the annual value of capture fisheries per ha of mangrove at the district level can be determined using the equation below, employing the indicators listed in Table 5-2: ((D x 15) – C) x ρ x 12 x (H x B) [/ A] The average income from fisheries per person per day value (D) should then be multiplied by the number of days that fishers work per month. Typically, fishers can only work 15-20 days per month as standard. In the pilot study, the lower value was employed to obtain the most conservative estimate. While we recognize that certain species harvested in inland capture fisheries have different 5. Ecosystem services 63 catching seasons (e.g., the catching season of black Sesarmid crab is only six months of the year), the validation trip confirmed that there is such a diversity of species available for capture in the mangrove forest that local people can harvest from the fisheries all year round. Ideally, however, efforts should be made to validate the number of working days for fishers locally, to account for any geographical variability in this parameter. 5.4 Aquaculture support Mangrove forests provide spawning and nursery grounds for aquatic species and thus directly, positively influence the production value of aquaculture systems. Much like capture fisheries, this provisioning service can be readily estimated using market price approaches. It is worth noting that sandy forest systems can directly benefit aquaculture systems through protection from blowing sand. This value is accounted for within the coastal protection analysis (see Annex P.1.3). 5.4.1 Recommended approach The table below details a number of statistical indicators used in the calculation of an annual value for aquaculture support value for mangroves in a given province. The table also details the source of the data and thus how it can be obtained for replicating the value calculation. Table 5‑3. Statistical indicators for economic assessment of aquaculture support services delivered by mangroves Statistical indicator Data source Aquaculture production for province (t) General Statistics Office of Vietnam – Statistical Data Aquaculture production value for province General Statistics Office of Vietnam – (VND) Statistical Data Mangrove presence – aquaculture production Literature (Do and Bennett, 2006) correlation Production cost Expert interviews Supporting Resilient Coastal Economies in Vietnam 64 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas The annual volume and value of aquaculture production in each province going back to the year 2000 can be accessed online through the General Statistics Office of Vietnam statistical data platform for agriculture, forestry and fisheries (GSO, 2020). The net value obtained from these systems can then be calculated by subtracting the production costs of the aquaculture systems. Lastly, the correlation parameter which identifies the contribution of mangrove presence to the production value can then be applied to isolate the benefit from this ecosystem service. We recommend the application of the 0.5 correlation factor, taken from Do and Bennet (2006). In their study, it was found that one ha of mangrove forest had the potential to increase aquaculture production in-site by 0.5 tons. Accordingly, a correlation factor of 0.5 is derived to isolate the ecosystem service contribution from mangrove forests to obtaining aquaculture benefits. While the 0.5 correlation factor from Do and Bennet (2006) has been peer-reviewed, this factor may be subject to local conditions and thus have a degree of variability. Conditions which should be considered in this regard include: ● Whether local aquaculture farms are inside mangrove systems (the service only applies to the benefit obtained from these farms); and ● Whether local aquaculture systems are intensively farmed and use synthetic inputs to negate reliance on the support of local mangrove systems. As such, as is done with correlation factor ρ (see Section 5.3.1), which links the presence of mangrove habitats with the support of inland capture fishery productivity, we recommend that a validation study is carried out to verify that the mangrove presence – aquaculture production correlation applies to local aquaculture systems. Section 5.2 should be referred to for an idea of the experts who could be consulted to verify this information. The example application of this approach to Quang Ninh (Annex J.2.1) gives an indication as to the sort of factors which could affect the validity of the correlation factor. Multiplying the annual value of aquaculture production at the provincial level by the mangrove- aquaculture correlation factor (0.5) will provide an estimate as to the economic value of this provisioning service. This value can be divided by the area of mangrove to obtain a per unit area value for the ecosystem. 5.5 Carbon storage Coastal forests have a significant carbon storage potential in their above and below ground biomass, the latter being true in particular for the root systems of mangrove forests. With the development of established carbon markets, this storage potential can now be readily assigned an economic value. It needs to be stressed that there are major unresolved questions about how carbon storage should be valued, affecting both the quantity that should be used and the appropriate price. The questions include whether only the entire stock of carbon stored at any given time be used as the basis of valuation, for example, or only the part that is liable to be released? Or perhaps only the incremental changes in stocks should be used? On the price side, carbon could be valued using actual market prices (as specified in an Emissions Reduction Purchase Agreement (ERPA), for example, or as observed in carbon markets) or at the estimated social value of carbon (SVC) (see Box 6). The approach used here is only one possible approach. 5. Ecosystem services 65 5.1.1 Recommended approach To ascertain a carbon storage value for a given mangrove or sandy forest ecosystem, an estimate of the system’s carbon storage potential must be made. To facilitate this, ISPONRE carried out a literature review of the biomass of the various species which comprise the different types of mangrove system and sandy forest along Vietnam’s coasts. In total, results were extracted from 16 peer-reviewed papers and reports on mangrove biomass and carbon stock estimates across Vietnam, of which 11 were journal articles, 3 were reports and 3 were doctoral theses. The results of the review are presented in Table 5‑5. The accuracy assessment of the biomass estimates presented is based on the study method of the respective references. The criteria for each of the accuracy levels is presented in Table 5‑4. The criteria are based on the International Panel for Climate Change (IPCC) guidelines for the creation of national greenhouse gas (GHG) inventories, which define three tiers of accuracy regarding carbon stock assessments. Table 5‑4. Criteria for accuracy assessment of coastal forest biomass estimates Reliability and Summary of accuracy assessment accuracy level High Use a destructive method to carry out direct estimates of biomass. Sufficient samples are taken for the development of allometric equations for the estimation (with validation) of both real above and below-ground biomass estimates. Medium Use a non-destructive method. Regional equations for biomass estimates and other default values (carbon fractions, root to shoot ratio) are used. Local plot measurements of common variables such as Diameter at Breast Height (DBH), height, and width are carried out to calculate biomass estimates using selected equations. Low Use non-destructive method but without application of allometric equations for biomass estimates. Biomass estimates are converted from stem wood stock using wood density, then are expanded to above-ground biomass using IPCC conversion factors (estimates of branch and leaf biomass). Finally, estimates of below-ground biomass are calculated using a root to shoot ratio. Supporting Resilient Coastal Economies in Vietnam 66 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas The appropriate biomass estimates to transfer to the study area can be selected from those presented in Table 5‑5 using the following criteria: ● Similar species and plant dominance ● Characteristics of the eco-region (location) ● Selecting the most conservative estimate of the feasible values ● Employing only medium to high accuracy assessment results. Species level spatial data is available from FORMIS for planted mangrove areas (see section 4.1.1) and thus the appropriate biomass values can be transferred easily from Table 5‑5. Should there be no available data on the species present for a given area, we recommend a review is carried out of the appropriate values to apply. A viable option is to assume average ‘all mangrove’ values as proxy. Alternatively, an average of multiple applicable values to a given area may be more appropriate. The example carbon storage account for Quang Ninh Province in Annex J.3.1 should be referred to for an example of this deliberation process. As there are only two estimates available for sandy forest species, selection of the appropriate value should depend on the nearest eco-region to the study location. Photo: Phuong D. Nguyen - shutterstock.com 5. Ecosystem services 67 68 Table 5‑5. Estimated biomass and biomass increment of coastal forest species in Vietnam Species Eco-region Forest Age n Average SD Biomass SD Accuracy Reference type (year) total increment level biomass (tdm/ha/yr) (tdm/ ha) 1 Rhizophora SW Planted 5-35 6 266.2 110.5 15.8 3.7 High [1], [2], [3], [4] apiculata 2 Rhizophora SE Planted 4-32 3 171.4 108.3 10.5 2.8 High [5] apiculata 3 Avicennia alba, SW Planted 5-20 4 200.0 67.5 25.1 9.5 High [3], [5], [6] A. officinalis 4 Senneratia SW Planted 20 3 252.3 12.0 12.6 3.6 High [5] caseolaris 5 Kandelia RRD Planted 5-15 5 134.1 68.6 11.9 0.8 High [7], [8] obovata 7 Senneratia RRD Planted 5-23 4 140.5 112.5 13.5 10.2 Medium [9], [10], [11] caseolaris 8 Rhizophora RRD Planted NA 1 6.4 NA NA  NA Medium stylosa 9 S. caseolaris, K. RRD Planted NA 1 48.7 43.5 NA NA Medium [11] avata, Bruguiera gymnorrhiza (mixture) 10 K. ovata and RRD Planted 16 1 108.7 NA 6.8 NA Medium [12] S. caseolaris (mixture) Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 11 Kandelia NCC Planted 5-15 3 72.6 35.4 6.7 2.6 Medium [8] obovata Species Eco-region Forest Age n Average SD Biomass SD Accuracy Reference type (year) total increment level biomass (tdm/ha/yr) (tdm/ 5. Ecosystem services ha) 12 All mangrove NE, NCC, NA NA 1 74.9 NA NA NA Medium [13] SCC 13 All mangroves SW, SE NA NA 1 137.0 NA NA NA Medium [13] 14 All mangrove National NA NA 1 123.4 NA NA NA Medium [13] 15 All mangrove NE (Quang NA NA 1 53.13 NA NA NA Medium [14] Ninh) 16 All mangrove – RRD, NCC Planted < 20 1 40.4 NA  1.1 NA  Low [15] FORMIS data 17 Production NE (Quang NA NA 1 53.2 NA  2.3 NA  High [15] forest Ninh) 18 Protection NE (Quang NA NA 1 61.7 NA  3.6 NA  High [15] forests Ninh) 19 Special use NE (Quang NA NA 1 46.8 NA  3.4 NA  High [15] forest Ninh) 23 Casuarina SCC Planted 6-34 1 349.7 110.9 20.7 4.5 Medium [12] equisetifolia 24 Acacia NCC Planted 10-12 1 290.5 47.9 26.5 4.7 Medium [16] crassicarpaa Sources: [1] Tri, H.N, 1986; [2] Tan, D.T, 2002; [3] Vu Tan Phuong et al, 2012; [4] Nguyen Thi Ha, 2017; [5] Vien Ngoc Nam 2010; [6] Binh, C.H and Nam, V.N, 2010; [7] Ha Thanh Nguyen et al. 2004; [8] Okimoto, Y. et al, 2013; [9] Tien Dat Pham et al. 2016; [10] Vu Manh Hung et al. 2015; [11] Luu The Anh et al. 2020; [12] Tien Dat Pham 2018; [13] Vu Tan Phuong et al. 2012; [14] Tien Dien Vu 2014; [15] Bernal et al. 2019a; [16] Nguyen Thi Lieu 2017. 69 Having applied the relevant biomass data presented in Table 5‑5 to the study area, and thus obtained the estimates of biomass (Total Dry Matter [tdm]/ha) and biomass increment (tdm/ha/yr), these values can then be converted to estimates of carbon stock (t/ha) and carbon sequestration rates (t/ ha/yr), respectively, using a standard carbon fraction factor of 0.47. This carbon fraction factor is the default value used in the IPCC’s guidelines on national GHG inventories, Chapter 4 (IPCC, 2006) and is a widely used and accepted value for the conversion of biomass to carbon stocks. Carbon stock (t/ha) and carbon sequestration estimates (t/ha/yr) for species, transferred to the study location, should be multiplied by their respective areas and summed to obtain a total carbon stock and carbon sequestration rate for the study location. These values can then be monetized using relevant market prices for carbon. The REDD+ scheme is a mechanism developed by parties to the UN Framework Convention on Climate Change (UNFCCC) which creates a financial value for the carbon stored in forests by offering incentives for developing countries to reduce emissions through schemes which use forested lands to sequester carbon. The REDD+ scheme incentives value a single ton of carbon sequestered in forested lands at USD 5. This is also the accepted price of carbon for verified emissions reductions as part of the Green Climate Fund, a fund for piloting REDD+ results for REDD+ countries that generate emission reductions during the period of 2013-2018. As such, the USD 5/ton value should be applied to estimates of total carbon stock/sequestration rates to monetize the carbon storage service delivered by coastal forest assets. Box 6. Carbon prices The pricing of carbon is a controversial process and there is no standard approach for natural capital accounting processes. Many carbon markets are not fully established, and the associated prices are thus flawed in reflecting the ‘true’ value of carbon. In recent years, the volunteer carbon market has shown a significant decrease in carbon transaction volume and prices. From 2007-2018, the transaction carbon price declined by around 50 percent (Donofrio et al., 2020). This is especially true in the forestry sector, where carbon prices have been criticized for not comprehensively covering the costs associated with emissions reduction and thus the carbon price being underestimated. In the Forestry and Land Use Sector, the average transacted values for 2017 and 2018 were 3.4 and 3.2 USD per ton of carbon dioxide equivalent (tCO2e) (Forest Trend’s Ecosystem Marketplace, 2019). Consequently, the carbon price under the REDD+ scheme is employed as this is an established emissions trading scheme in Vietnam, supported by the World Bank and the Ministry of Agriculture and Rural Development. While recognizing that other approaches to the valuation of carbon are available, such as the Shadow Price of Carbon (replacing the Social Value of Carbon in 2017) (World Bank, 2017), the REDD+ approach is deemed appropriate as per other studies in Vietnam. Supporting Resilient Coastal Economies in Vietnam 70 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 5.6 Coastal protection Coastal forest assets help to stabilize the coastline by facilitating sediment accumulation and thus protect against erosion, which threatens much of the country’s coastal infrastructure, including transport, industry and residences. Additionally, through this stabilization mechanism and attenuation effects, mangrove forests can reduce the level of inundation and wave energy encountered during typhoons and thus help to mitigate against the damages caused by such events. By assessing the sum costs of damages avoided due to the presence of mangroves, this service can be assessed monetarily. 5.6.1 Recommended approach There are a number of approaches that are applicable to coastal protection. Each approach varies in terms of effort required and quality of output. These can be summarized as follows: Process-based approach: These are approaches for valuing the coastal protection service delivered by mangroves by quantifying the change in risk using a suite of wave and flood models and simulating “with” and “without” mangroves scenarios under different storm conditions. These simulations are used to estimate the annual expected benefits of mangroves for protecting people and property in social and economic terms. These approaches are detailed and can be bespoke to the location of interest, thus providing the most detailed level for the estimation of this service. However, they are also costly, require specialist modeling skills, and are time consuming (a typical study, for instance, may take six months to complete). While it might be ideal that process-based approaches are used, this may only be practical where modeling already exists, and can be recycled, or where a National Climate Assessment (NCA) study is coupled with other flood modeling or coastal setback work. Additional detail on the methods required for process-based approaches is provided in Annex P. Index-based approach: Index-based approaches are an alternative method for estimating the coastal protection benefits resulting from coastal forests in Vietnam. This approach combines values from raw data sets relating to hydrodynamic processes, geophysical processes, socioeconomic components and management interventions, to estimate exposure and vulnerability to the Vietnamese coast. This either provides economic values of benefit, or proxies from which an estimate of the coastal protection benefits can be produced. Benefit transfer approach: Benefit transfer methodologies can also be applied, should data availability or resource constraints limit the application of the above approaches. This approach was applied to estimate the protection benefits delivered by coastal forest assets in Quang Ninh and TT-Hue Provinces as part of the pilot accounts, presented in Annex J.4.1. While this approach is not the preferred method, data availability did not facilitate the application of process-based modeling in the pilot accounts. Each of the above approaches is discussed in more detail in Annex P. Given the potential expected loss of mangrove area due to continued urbanization, it is important to accurately understand the potential damages to local areas and the nation as a whole. The process-based approach implicitly 5. Ecosystem services 71 represents the nearshore and offshore dynamics to quantify flooding and the effect of mangroves. From this, expected damages to people and property from flooding can also be determined for different scenarios: e.g., current mangrove cover versus total loss, partial loss, or even regeneration and protection. The annual expected damage is then calculated as a combined average of all the scenarios. By estimating the economic value of exposed assets, the expected damage functions for the direct damages caused by flooding due to mangrove loss can be produced. These do not account for indirect benefits such as those from fisheries, tourism and other disruptions due to storms. The benefit transfer approach presented and tested in the pilot regions provides an indicative assessment of the coastal protection service using available data. While the approach requires significantly less information and data to undertake the analysis, there are a number of drawbacks: ● There are a limited number of studies for which coastal protection values are reported and thus values available for transfer. ● There is an absence of robust criteria for the selection of the ‘most similar’ study location in terms of the features of coastal assets. As such, and where data, time and appropriate budgets exist, a process-based modeling approach is recommended. However, it is recognized that this may not be practical, and index-based or benefit transfer approaches may need to be used. 5.7 Recreation and tourism With almost 40 percent of Vietnam’s special-use forests participating in tourism and 2 million tourists visiting the country’s National Parks and National Nature Reserves (NNRs), Vietnam’s natural assets and coastal forest assets hold a significant value in generating revenue for the local economy through tourism and recreation. Travel cost methodologies (TCMs) are a frequently used approach for the economic assessment of this service, calculating the costs incurred by individuals traveling to a recreational site and using this price paid as a proxy for the recreational or tourism value of the green space. This approach relies on the assumption that the welfare value obtained by visiting the site is greater than, or at least equal to, the cost of traveling to visit the site. As there is no official tourism in mangrove forest in Quang Ninh Province, the service was not assessed for this location. However, the Zonal TCM (ZTCM) recommended is applied to assess the value of tourism services delivered by natural capital assets in TGCH lagoon. This example account is presented in Annex J.5.1. 5.7.1 Recommended approach Tourism is not directly linked to ecosystem extent. Rather, tourism in coastal forest ecosystems is linked to various factors including the quality and accessibility of the forest area. As such, only a select number of coastal forest systems will deliver a tourism and recreation service. The FORMIS datasets Supporting Resilient Coastal Economies in Vietnam 72 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas should help to identify the relevant ecosystems for which this service can be assessed. Using the ‘Forest Function’ field in the VNFOREST data sharing platform, the areas of Protection and Special- use Forest can be identified, as is done in Section 4.1.1. The FORMIS ‘Forest Function sub-class’ field can also be used as this dataset identifies national parks and nature reserves. An overlay of these datasets with mangrove and other coastal forest areas (see Section 4.1.1 on how to obtain these spatial datasets) would delineate the areas of interest in terms of coastal forest assets which deliver recreation and tourism services. This should be verified with further investigation prior to conducting local surveys as part of the economic assessment. Following the identification of the coastal forest assets relevant to tourism values, a ZTCM is recommended to assess the tourism value of a given asset, following a five-step procedure. Step 1: Defining questionnaires Questionnaires are constructed and comprised of two main parts: ● Part A: The collection of general information about the activities in which visitors participated. The information should focus on the expenses that were incurred during both the travel and the visit (expenditures while at the asset or park). ● Part B: The collection of general information including age, gender, means of transport, etc. The information on expenses to be collected as part of Part A can be grouped as follows: ● Transportation cost: This includes the costs of fuel, car/motor’s insurance, depreciation of the vehicle, and road charges, when taken for a round-trip. The transportation cost per visitor should be determined by multiplying the total cost by the number of vehicle occupants. This cost is separate from the costs of visitors charged for those traveling on a tour. ● Opportunity cost: This cost is determined by the wage rate of visitors to the given asset, whether for a long or short visit. The wage rate is the wage paid to a worker per unit of time. This is assumed to be an opportunity cost since the visitor exchanged working time in order to visit the site. The wage rate reflects the opportunity cost of time and is consequently used as an approximate shadow price of time. The value of time is estimated using a full wage rate. ● Additional charges during the visit: This should include any additional costs of travel (e.g., if the visit was part of a tour) and consumption expenditures (costs of food, drinks, accommodation, etc.). If there are existing entrance fees or parking fees these should also be included. Together, these three costs comprise the total Travel Cost (TC) of an individual. All relevant information should be obtained for a given individual in Part A of the questionnaire process. At this stage, the ‘departure zones’ will also need to be defined and identified in a Geographic Information System (GIS). The departure zones are defined as set radius (distance) ranges from which visitors to the asset travel to reach it. Cost and visitation rates will be calculated for these zones, hence a ‘Zonal’ TCM. 5. Ecosystem services 73 Step 2: Defining sample size The sample size, i.e., population which needs to be surveyed via the TC questionnaire to obtain an appropriate volume of data, can be determined using the formula from Scott Smith (2013), which is detailed as follows: Z2p(1-p) n (total > 50,000) = c2 n (total > 50,000) n (indentified total < 50,000) = n (total > 50,000) ― 1 1+( ) Pop Where: Z = a parameter interval (1.96, confidence level of 95%); P = the probability of making a choice (0.5 [standard deviation]); C= the marginal of error (chosen at 0.95); Pop = the identified total population (i.e., estimated annual number of visitors). Step 3: Calculating the visitation rate for each departure zone Using the data gathered from the questionnaires, the Visitation Rate (VR) per 1,000 of population for each zone should be calculated using the following formula. Vi ( n ) x N x 12 x100 VRi = P Where: VRi = Visitation Rate for zone i (visitors/1,000 of population /year) Vi = the number of visitors from zone i (person) N = sample size (person) N = the total number of visitors per year (person) P = population of zone i (thousand people). Step 4: Constructing the demand function The average TC of each zone should be determined. Having calculated this, and the VR for each zone, a demand function can then be derived to estimate the number of visitors from each zone. This can be done by simply carrying out a simple, linear regression between the average TC and the VR of each zone. Corresponding to the changed travel cost, sets of the estimated number Supporting Resilient Coastal Economies in Vietnam 74 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas of visitors corresponding to different TCs are returned, which generates a demand curve. The function for the number of estimated visits is regressed against the hypothetical increase in cost travel in the following form: V = β * ΔTC + e Where: V = the number of visitors to an area when travel costs increase ΔTC VND (person) ΔTC = the travel cost of visitors increased per a visit (VND) β = the coefficient of estimation (the slope), when the independent variable (ΔTC changes one unit, the corresponding value of the dependent variable changes |β| unit e = the y-intercept, stands for the other factors not mentioned in the model. When the independent variable (ΔTC equals 0, the corresponding value of the dependent variable (VR) equals e unit. A second regression analysis can then be carried out between the V function from the equation above and the Increased cost (∆TC) to estimate the number of visitors to the natural capital asset, using the following equation: 4 4 V = ∑VRi * Pi = ∑[―0.000204 * (TCi + ΔTC)] + 118.72 * Pi i=1 i Where: V = the number of visitors to the cultural service when the travel cost of zones simultaneously changes in an amount of ΔTC (person) VRi = the visitation rate of zone i/1,000 of population TCi = denotes the travel cost of zone I (VND) ΔTC= the level of increased travel cost of visitors per visit (VND) Pi = the population of zone i I = zone number. The results of the regression analysis between V and ΔTC can then be used to calculate the total recreational value of the asset by calculating the area under the resultant demand curve, which represents the total number of visitors and the associated cost. This can be mathematically expressed as: TWTP = 1/2 * TCmax * Vmax Where: TWTP = the total recreational value of the area per year (VND) TCmax = the maximum limitation point for the demand (i.e., the price at which no more visitors are willing to travel to cultural service) Vmax = a limit which represents that maximum number of visits for which estimated travel cost falls to zero (person). 5. Ecosystem services 75 Step 5: Calculating the value of tourism Following the steps taken in Step 3, the value of tourism can be determined as follows: Value of tourism = Expense + Consumer surplus In summary, the data requirements for this five-step approach are detailed below. Table 5‑6. Data requirements of the ZTCM Input data Data source Number of visitors GSO, 2019 Expenditure per visitor Survey Photo: Nguyen Quang Ngoc Tonkin - shutterstock.com Supporting Resilient Coastal Economies in Vietnam 76 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 5.8 Improving estimates To improve the estimates of ecosystem values, the primary challenge lies in improving the available data. This can take the form of improving and expanding regular data collection efforts and, in some cases, undertaking one-time studies to estimate key parameters. ● Forest cover. In general, forest cover is relatively easy to measure, but needs to be done at sufficient resolution and to be updated regularly to be useful. The main challenges are dealing with cloud cover and seasonal changes. The type of forest, if not known, can then be ascertained by field visits, and as this is unlikely to change rapidly, it need not be repeated frequently. It would be useful to find a way to also assess condition. This could be done using techniques such as LIDAR, or by field visits (to a representative sample of spots within forest areas). Percentage of canopy or similar measures are likely useful; measures of composition (e.g., percentage of trees above a certain size, or species composition) might also be useful, but additional work is likely needed to see how they relate to flows of various environmental services. ● Agricultural area is again relatively easy to measure, but precise land use may not be (e.g., if crops have been harvested at times with limited cloud cover). Many calculations depend critically on certain parameters. For example, the contribution that mangroves make to fisheries is embodied in the parameter r. It would be important to obtain better estimates of these parameters. This can often be achieved with targeted, one-time studies. For example, determining the relationship between tree cover and biomass and carbon stocks is relatively easily accomplished by one-time studies, thus avoiding having to rely on IPCC coefficients (and receiving higher payments if an ERPA is in place). However, where there is potential for these parameters to change over time, it would be important to monitor them for any changes. For example, the relationship between mangroves and fisheries embodied in the parameter r may well change over time, for example if mangrove degradation reduces its contribution to fish stocks. In general, it would be desirable to move towards more spatially-explicit approaches, i.e., rather than calculating a single estimate of the value of an ecosystem, y, we should try to estimate how that value varies based on local characteristics, y = f[x], where x is a vector of local characteristics. To the extent possible, it would also be desirable to move towards estimates that recognize variability and trends in value. ● Actual benefits often vary substantially from year to year (e.g., erosion protection and flood reduction benefits provided by a forest vary substantially depending on rainfall in a given year). In this context, an estimate of value could either: (a) reflect conditions in a specific reference year; or (b) reflect ‘average’ conditions. Neither is ‘right’ or ‘wrong’, but they must be interpreted appropriately. A one-time study should try to arrive at an estimate under average conditions. On-going measurements should aim to estimate value under the specific conditions experienced in each year (which will also, of course, provide an estimate of average benefits when averaged over a sufficiently long time). 5. Ecosystem services 77 ● Many benefits may experience a long-term trend, because of the effect of other trends (e.g., the protection function provided by coastal forests may increase because of climate change increasing the intensity of storms), or because of poor management (e.g., current rates of harvest may be depleting stocks and so resulting in lower future harvests). 5.8.1 Limits of benefit transfer Many of the estimates in this report rely on benefit transfer, which consists of taking an estimate of value from one context (the study site) and using at an estimate of value elsewhere (the policy site). This method can provide an estimate when no other data is available, but is subject to significant limitations. ● The values of many ecosystems are both spatially heterogeneous and variable over time. The protection service of a mangrove forest, for example, varies substantially from place to place, depending on the value of what is being protected, and its vulnerability. The actual value provided also varies from year to year, depending on the intensity and location of storms in that year, and may change over time, as climate change affects the intensity of storms and raises sea levels. ● Any benefit transfer estimate is dependent on the quality of the original estimate. Many estimates in the literature are limited by data constraints and methodological problems; many estimates are also partial, in the sense that they only measure part of the benefits of an ecosystem; and many estimates may not reflect the variability of benefits. ● Note that even well-measured estimates may be non-comparable if they are framed differently (e.g., a value for a given year is not comparable to one for average conditions). ● Even a perfect estimate of the value at the study site may be different from the value at the policy site. ● Many studies are undertaken at locations where the given benefit is expected to be important, and so are unrepresentative. Moreover, because there are often a wide range of estimates generated at different study sites, which estimate should be used is often not obvious. ● It is tempting to use a simple mean of the available estimates, but there is no reason to think this is meaningful. A median value may well be more meaningful. ● Identifying an estimate from a site that is similar to the policy site could also be useful. ● The best approach would be to undertake a meta-analysis of available estimates, i.e., estimate how the value estimates, y, depend on the characteristics of the study sites, x, that is estimate y = f[x], and then use this relationship to estimate the value at the policy site, yp, based on the specific characteristics of the policy site, xp, using yp = f[xp]. However, this is a challenging undertaking, as most studies provide inconsistent and partial information on their characteristics (i.e., the elements of xi for the study site i) and may have measured the value itself in ways that is non-comparable to other estimates. (Such a meta-analysis has been prepared for the non-timber forests, for example, see Siikamaki et al., 2015.) Supporting Resilient Coastal Economies in Vietnam 78 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 6. POLICY AND PLANNING IMPLICATIONS OF COASTAL FOREST Photo: Jimmy Tran - shutterstock.com NATURAL CAPITAL ACCOUNTING 6. Policy and planning implications of coastal forest natural capital accounting 79 6.1 Planning implications For effective planning that accounts for natural assets, it is important to know the spatial relations among natural assets as this can influence the ecosystem services. As such, to integrate the ecosystem service values of coastal forests into the development of plans, zones, and investment decisions, it is recommended that ultimately the ecosystem service values obtained at various spatial scales from the valuation framework are used to digitize maps of ‘high’ to ‘low’ value ecosystems. Such maps will help to identify high priority ecosystems, which deliver maximum net environmental gain and thus contribution to wealth, and ensure they are duly accounted for when formulating a plan or making an investment decision. Correspondingly, the maps can highlight those ecosystems which are a priority for green infrastructure investments. In Annex O we have mapped the data from the tables presented in Annex M and Annex N on the carbon stock and carbon sequestration values of coastal forests (mangrove and sandy forests) within each commune for both Quang Ninh and TT-Hue. While this is not a map of the monetized carbon value, the monetary value is linearly related to the stocks and sequestrations rates and thus this is a valid proxy for prioritization17. These maps demonstrate the potential spatial application of the output data from the monetary accounts for the various ecosystem services delivered by coastal forest assets. The mapping of values at the finer, commune level can help to inform more detailed planning priorities. Additionally, overlaying value maps of multiple ecosystem services can help to identify those ecosystems which deliver, simultaneously, individual ecosystem services to an optimal magnitude and multiple ecosystem service benefits, and thus maximum environmental gain and wealth. Clearly, the finer the level of granularity in the mapping of high value ecosystems, the more useful the data becomes. This greater level of granularity in mapping ecosystems will also require a greater level of granularity in estimating ecosystem value. As long as a single value is used to value a hectare of mangrove forest, the benefit of improved mapping will be limited. The valuation of coastal forest assets at the provincial level, for example, is a coarse level of analysis and while this information can be integrated into the development of setback lines, valuation data at the district or commune level, or a finer a level, is much desired. The table below summarizes the level at which each of the coastal forest services has been assessed under the valuation framework presented in this report. 17 It should be noted that this is not sufficient to assess specific trade-offs. Supporting Resilient Coastal Economies in Vietnam 80 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Table 6‑1. Spatial scale of economic assessment of ecosystem services under recommended approaches Ecosystem service Level of monetary account (recommended approach) Capture fisheries Provincial level Aquaculture support Provincial level Carbon storage Species level* Coastal protection Variable Recreation and tourism Asset level** *Biomass and thus carbon stock/increment data is available for most native coastal forest (mangrove and sandy forest) species. As such, theoretically, this analysis can be carried out at the species level. However, FORMIS only contains species-level spatial data for planted mangrove areas (see Section 4.1.1) and thus for other coastal forest plots, the granularity of the analysis is limited. Should species- level spatial data be obtainable from alternative sources which have not yet been identified, a finer level of analysis would be possible. **The recommended ZTCM approach for the assessment of tourism values calculates a value for the given asset. In the case of the application of the methodology to TGCH lagoon, the result was at a provincial scale; however, the method has the capacity to be scaled and assess the tourism value of much smaller assets. All that is required is an estimate of annual visitor numbers. It is recognized that a current limitation of the coastal forest asset valuation framework is that much of the analysis is presented at the provincial level. We recommend that further work is undertaken to refine the analysis and capture the value of ecosystems at a district or commune level, or finer. The current approach to the assessment of capture fisheries is at the provincial level, primarily because it is recommended to average the income obtained from capture fisheries at the district level and assume this applies to the whole mangrove forest (provincial level) due to the fact that locals often move between catching areas and seasons. Theoretically, however, with more time and resources available for the validation of local fishing incomes and the contribution of coastal (mangrove) forest assets, this approach could be applied at the district level. Likewise, the approach to the economic assessment of aquaculture support services is also currently limited to the provincial level, due to its reliance on secondary aquaculture production data obtained from the Vietnam General Statistics Office (GSO, 2020). However, via surveys with groups such as the People’s Committees 6. Policy and planning implications of coastal forest natural capital accounting 81 of individual communes and local experts, data could be obtained on production at the district level, and the approach scaled accordingly. Standard market prices could be applied to convert the local estimates of production to a market value, should local data on incomes not be directly available. Depending on the approach selected, the assessment of coastal protection values delivered by coastal forest assets could be viable at the commune level. The process-based approaches which employ detailed hydrodynamic modeling can be applied to local scales and thus again, the resources available determine the level of granularity to which the analysis can be carried out. In summary, with some additional data collection efforts, the majority of the key ecosystem services assessed in the natural capital valuation framework can be assessed at the district/ commune level, or finer, with benefits for the development of precise setback lines and integration into the planning process. 6.2 Policy implications While in this report we have been able to demonstrate the significant benefits delivered by coastal forest assets, these assets currently remain unaccounted for in their contribution to Vietnam’s economy. Consequently, unsustainable use of forest resources and poor forest management continues to be the norm. True sustainable development requires a careful balance between three key aspects: ● Economic development (economic growth). ● Social development (social justice, poverty reduction and employment creation). ● Environmental protection (maintaining, restoring and improving the quality of the natural environment while exploiting natural resources economically). It needs to be stressed that these aspects are often tightly inter-related. Environmental protection is to some extent an end in itself, but it is also necessary to ensure that economic and social development are possible (for example, the role of mangroves in fisheries) and not vulnerable to disasters and climate change (for example, the role of mangroves in coastal protection). NCA is useful precisely because it allows us to see the links between environmental and economic (and to some extent also social) development. Vietnam is at a critical stage in its development, which is putting a significant strain on its pool of natural capital through exploitation of natural resources. This will cause consequences for its economy in the future and as long as the environmental impacts are not understood in economic terms, the over-exploitation is likely to continue. Recognition of the economic impacts of this resource use is needed now to provide an evidence base for the development of policies and plans which can halt this unsustainable approach to development. The issues of unsustainable development and resource exploitation are particularly pronounced in coastal areas and this trend is set to continue. Socioeconomic development is seeing the conversion Supporting Resilient Coastal Economies in Vietnam 82 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas of coastal forests into a range of different land uses, including urbanization, industrial development, intensive agriculture (aquaculture) and infrastructure. Additionally, the pollution resulting from these practices threatens the remaining coastal ecosystems. Balancing the supposed trade-off between socioeconomic development and environmental protection will be one of the most significant challenges faced by policy makers in the next decade. The natural capital accounts presented in this study have clearly demonstrated that the conversion of degradation of coastal forest assets will result in the loss of significant economic value. Furthermore, it should be noted that these natural capital accounts do not account for the full economic potential that the assets can deliver, as they account for only a small proportion of the ecosystem service benefits which could be obtained by society. In light of these results, a number of policy recommendations have been put forward by our partners, ISPONRE: ● Develop and issue regulations and guidelines on the consideration and integration of natural capital assets into planning processes and development plan preparation. Consideration of natural capital assets is deemed mandatory for the process of planning preparation with sufficient consultation and participation of line sectors, management agencies, research organizations and socio-civil organizations. ● Full natural capital accounts must be produced and considered for the analysis of impacts associated with development plans, particularly when concerning the conversion of natural ecosystems (including coastal forest ecosystems) for urbanization, industrial zone and infrastructure development. Compensation payment for any conversion activities is required and is based on its impacts and loss value of ecosystem services. ● (Provincial) Development plans must detail feasible measures for mitigating (minimizing) any potential damages to and negative impacts on natural ecosystems and local communities. ● Ensure (provincial) development plans are published and the impacts on natural capital assets made transparent through the development of an open-access platform on which they are reported. ● Implement a program of education and understanding around the principles of natural capital and natural capital accounting for line management agencies and organizations who are responsible for planning and development plan preparation and the monitoring of development plans during the implementation phase. ● Prepare a robust monitoring program for the implementation phase of development plans with adequate stakeholder participation. The monitoring plan should cover different aspects regarding the impact on natural capital assets, livelihood and the consequences for natural disaster mitigation (under climate change) to be caused by the development plan’s implementation. 6. Policy and planning implications of coastal forest natural capital accounting 83 Photo: Julia Moiseenko - shutterstock.com 7. CONCLUSIONS AND RECOMMEN‑ DATIONS Supporting Resilient Coastal Economies in Vietnam 84 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas With its expansive coastline, Vietnam is a country exposed to the increasing threat of climate change. With the effectiveness of its coastal dike systems waning, the benefits of alternative approaches to improving climate change resilience, such as coastal forest afforestation, have become more apparent. Additionally, a new planning law has required the integration of ecosystem values into all master plans and thus it is pertinent that the values of natural capital assets are recognized. Vietnam does not have a central framework, such as the SEEA-EEA, for organizing biophysical data and assessing ecosystem services in a way that aligns their value with standard economic measures. This raises questions as to how well planning authorities will integrate ecosystem values into their work. This report attempts to address this gap, in part, by providing a natural capital accounting framework for coastal forest assets in Vietnam, which is aligned with the SEEA-EEA. Five key services were assessed as part of the trial ecosystem service accounts for devising reliable and replicable approaches to the monetary assessment of ecosystem services across multiple spatial contexts, which is a challenging process. It is recommended that a phased approach to the application of this framework is taken; i.e., where and when application is extended to multiple provinces and localities, more ecosystem services delivered by coastal forest assets are included in the monetary assessment. The scoping exercise detailed in Annex I will be valuable in this regard. Key ecosystem services for consideration can be identified through the priority assessment of coastal forest services in Annex H. While a primary, market price approach is recommended for the assessment of both capture fisheries and aquaculture production, a TCM and hydrodynamic modeling approach is suggested for the assessment of tourism and coastal protection services, respectively. A benefit transfer approach is recommended for the assessment of carbon storage services by coastal forests. While benefit transfer approaches are typically assumptive and less accurate, this is a standard approach to the assessment of this service in natural capital accounting frameworks as it is non-intrusive and relatively reliable. In some instances in the pilot accounts, the recommended approach is not applied due to resource constraints and factors concerning local conditions. While the recommended approaches presented for the economic assessment of each of the services are viable, some additional data gathering would refine certain approaches: ● With regards to the assessment of aquaculture support services, we recommend that data is obtained on production from aquaculture systems at the district level so this method can be applied at a finer scale as currently only provincial-level data is available from the GSO. Additional data gathering to confirm the validity of the mangrove presence-aquaculture production correlation would also be valuable. ● Secondly, local surveys on production values in various locations with and without mangrove presence combined with additional regression modeling could be carried out to obtain a locally- specific mangrove presence-aquaculture production correlation factor, as there is some evidence that this value varies depending on location. Regardless, validation studies are required to ensure that the correlation factor applies to local conditions. 7. Conclusions and recommendations 85 ● Additionally, while the method recommended for the assessment of carbon storage services has the capacity for analysis at the individual species-level, spatial species-level data is lacking for coastal forest assets other than planted areas in the VNFOREST data sharing platform. As such, average carbon stock and sequestration values must be applied to coastal forest assets. Were species-level data available, this would facilitate a much finer level of analysis. The outputs of this natural capital accounting framework have clear implications for planning in Vietnam. Likewise, the outputs of the accounting framework have repercussions for policy development. Conservation and proper use of natural resources can have benefits for socioeconomic development and thus a framework, such as has been presented, is required to increase awareness of the economic benefits obtained from natural capital assets. As such, some clear policy recommendations have been made around the integration of natural capital accounting and natural capital principles into the planning arena. Theoretically, this framework could form the basis of the first national-scale natural capital account of coastal forests in Vietnam. As such, it is advised that the results of the accounts are periodically reviewed and updated. Photo: Nguyen Quang Ngoc Tonkin - shutterstock.com Supporting Resilient Coastal Economies in Vietnam 86 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas ANNEXES A. Coastal forest assets in Vietnam A.1. Coastal forest assets and services The coastal forests of Vietnam deliver a vast range of ecosystem services, which many livelihoods depend upon, including those of both local and distant populations. The delivery of many of these services is underpinned by the biodiversity of these natural capital assets. The mangrove forests of Vietnam are of global importance for their biodiversity and are some of the most productive ecosystems in the world (Veettil et al., 2018). Mangrove forests support local populations in Vietnam directly through provisioning services, including the harvesting of fish and other seafood for both nutrition and income (Orchard et al., 2016), timber, firewood, charcoal and even medicine (Kuenzer and Tuan, 2013). However, the indirect services these forests provide to both local and wider populations are as, if not more, valuable. For example, mangroves provide hydrological services by filtering out sediments and pollutants, maintain a high biodiversity in coastal zones and wetlands, provide vital protection from natural hazards (storm surges) and coastal erosion, and stabilize climate and moderate extreme temperatures by removing pollutants from our atmosphere (Kuenzer and Tuan, 2013). Mangrove forests are the primary coastal forest system in Vietnam. However, there are other forest systems which also provide a range of ecosystem service benefits. Malalueca forests (another wetland component), for instance, deliver a similar range of services to mangroves, including provisioning of firewood and construction material (Do and Bennett, 2006), while sandy forests (e.g., Casuarina equisetifolia, Whistling Pine) provide an additional service of protection from blowing sand. A.2 Economic importance of coastal forest assets in Vietnam In 2019, the total GDP of Vietnam reached USD 262 billion with a GDP per capita of USD 2,700 (World Bank, 2020a). It is one of the fastest growing nations in economic terms. Many of the sectors which have driven this growth are directly, or at least indirectly, supported by the services provided by coastal forest assets. As of 2019, agriculture in Vietnam represented 13.96 percent of total GDP (GSO, 2020) and employed just less than 40 percent of the country’s total workforce (Santander, 2020). The seafood industry plays a large part in this economic contribution and the GoV has set out its aim to turn the country into a leading seafood exporter as part of its fisheries development strategy plan for 2020. Under this plan, the seafood industry is anticipated to account for 30-35 percent of the country’s total agro-forestry-fisheries GDP (Nguyen, 2017). Furthermore, since 2006, Vietnam has been ranked among the top 10 leading countries for fisheries exports. While the most high-value fisheries in Vietnam are offshore fisheries and concern species such as tuna fish, mangrove ecosystems support the seafood industry by: Annexes 87 ● Providing habitat for aquatic species, largely non-migratory mollusk species, thus increasing the production of inland capture fisheries; ● Providing spawning and nursery grounding for aquatic species, thus increasing the productivity of aquaculture systems within mangrove areas. Production from capture fisheries in 2019 in Vietnam was estimated at 3.8MT (GSO, 2019). In 2017, the estimated total value of exported seafood products was USD 7.7 billion (Ojamaa, 2018), thus constituting a vital source of income for the country. Production from aquaculture in 2019 was estimated to be greater, at just less than 4.5MT produced from over 500,000 aquaculture farms nationally (although a majority of aquaculture farms are concentrated in the Mekong Delta to the South), covering an area of almost 47,000 ha (GSO, 2019). In 2015, the economic value of aquaculture production was estimated at USD 4.26 billion, constituting 65 percent of the value of Vietnam’s total fisheries exports and supporting around 4 million jobs in the Vietnamese economy. Another major export which contributes to Vietnam’s economic growth is the wood and timber industry. In 2019, wood production in the country reached almost 16,500 m3 (GSO, 2019), while the total value of wood and timber products the year prior was estimated at USD 9.4 billion. The wood and timber products sector thus represents almost 4 percent of national GDP and Vietnam is now the second largest furniture exporter in Asia and fifth largest worldwide. Timber from coastal forests is largely harvested for firewood and charcoal and used in local industry for the construction of the likes of dwellings, boats and fishing gear and is thus invaluable to local communities. Vietnam’s tourist industry is seeing exponential growth, with the country consistently ranking as one of the fastest growing tourist destinations in the world in recent years. In 2019, 18 million foreign visitors came to Vietnam (GSO, 2019) and the tourist industry contributed 6 percent of the nation’s GDP (Vietnam Briefing, 2020). In 2018, the total revenue generated by the tourist industry was USD 26.75 billion (Vietnam Briefing, 2020). These revenues have grown rapidly in the last decade. Between 2013 and 2017, the absolute value of revenues from visitor spending almost doubled. By the end of this period, the tourism sector directly employed 750,000 workers, accounting for 1.4 percent of the national workforce. Vietnam’s natural capital assets, including its coastal forest assets, are a major driver for the industry’s growth. In 2016, around 2 million people visited the country’s national parks and National Nature Reserves (NNRs). The ecotourism industry is expected to continue to grow – the number of visitors to National Parks and NNRs was 178 percent higher than the equivalent figure in 2015 (World Bank, 2019a). Vietnam’s coastal forests provide a vital role in terms of coastal protection. Vietnam is frequently affected by tropical cyclones – these storms account for around 80 percent of the disasters which affect the country (Nguyen et al., 2014). Between 2001 and 2010, 28 cyclones made landfall on the coast of Vietnam. The frequency of cyclones increases toward the north of the country: from 1951 – 2010, 43 percent of cyclones that made landfall in the country did so in the north, 32 percent in the central region and 25 percent in the south (Nguyen et al., 2014). However, 70 percent of the country’s populations reside in the low-lying river flood plains, deltas and coastal margins, which are most vulnerable to such hazards (Van Ledden et al., 2020). The low-lying flood plains and deltas most typify the center and south of the country, while the north is typically characterized Supporting Resilient Coastal Economies in Vietnam 88 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas by more upland terrain. Tropical cyclones are associated with storm surges. Storm surges of a relatively modest height are unlikely to cause a significant degree of inundation in the central or northern parts of the country, whereas they could devastate communities in the naturally low- lying flood plains, such as the Mekong Delta, in the south. Mangrove and sandy soil forests have a crucial, protective role in mitigating the threat of high-energy storms by decreasing wind power, dissipating wave energy and thus reducing the level of inundation. These forests have been found to provide protection for defense systems such as coastal dikes, estuarine areas and agricultural fields (World Bank, 2019a). The economic importance of this service becomes clear when the potential damage costs avoided due to coastal forest protection are considered. Tropical Storm Linda, which struck Vietnam in October 1997, destroyed 200,000 homes, left 383,000 homeless, killed 3,111 people and was estimated to cost USD 385 million in damages (Nguyen et al., 2014). While it is difficult to quantify the exact extent to which coastal forests mitigate damages from cyclones and associated storm surges, attempts have been made to do so. Vo et al. (2015) use market price and replacement cost approaches to estimate the coastal protection services provided by mangroves in Ca Mau province. The value of mangroves across the province was estimated at USD 600 million/ yr or USD 3,000/ha/yr. Lastly, coastal erosion is a significant problem faced by communities along Vietnam’s extensive coastline. This is particularly true in the southern reaches of the country, where erosion is threatening embankment works and residential areas, causing floods and saline intrusion which are risks to food security, and threatening both lives and economic development in these coastal areas. Mangroves and coastal forests, akin to cyclones and their associated hazards, act to mitigate these risks, and likewise when the potential damage costs avoided are considered, the economic benefits of these coastal forest assets become apparent. The fallen leaves of mangrove forests provide a substantial source of detritus, thus facilitating greater and faster sediment accumulation. The roots also help to dissipate waves, mitigating the impacts of currents, and by trapping sediment, help to stabilize the land. A.3 Threats to coastal forest assets in Vietnam It is becoming increasingly important to understand the benefits delivered by the coastal forests of Vietnam, as rapid development across the country is resulting in their degradation; a trend which is becoming increasingly consistent across southeast Asia. Over a fifty-year period between 1943 and 1993, forest cover in Vietnam declined from an estimated 43 percent to 28 percent. Due to widespread policy reform and forest programs to address this decline, forest extents recovered to 41.65 percent in 2017 (World Bank, 2019a). However, the areas of decline and recovery do not necessarily align. This is particularly the case for mangrove forest, for which recovery has been limited. Large swathes of mangrove forest have been converted into large- scale, intensive aquaculture (Orchard et al., 2016). By 2011, sea and brackish water aquaculture had spread to cover an area of approximately 730,000 ha. The conversion has been driven by economic and policy reform in the country in a bid to spur development and has had profound ecological and social consequences. This trend is particularly pertinent in the south of the country, Annexes 89 specifically in and around the Mekong Delta region where the majority of aquaculture farms are now concentrated. Here, conversion has led to coastal erosion, saltwater intrusion, significant decline in water quality and in some cases production collapses (World Bank, 2019a). Figure 0‑1 is a land cover map of the south of Ca Mau province. The figure indicates the extent of the mangrove forest conversion to shrimp farming problem when the extent of the light blue (‘Mangrove/Aquaculture’) area is considered. This is also illustrated in Figure 0‑2, which shows time lapse imagery, sourced from Google Earth TM, from 1984 (a) and 2016 (b) of the same region. The spread of shrimp farming ponds and extent of deforestation over time is clearly evident. Source: Gebhardt et al., (2012) Figure 0‑1. Map of mangrove species, aquaculture and other dominant land cover classes, Ca Mau Province Supporting Resilient Coastal Economies in Vietnam 90 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Source: Google Earth TM (2020) Figure 0‑2. Satellite imagery of southern Ca Mau Province from 1984 (a) and 2016 (b) Moreover, despite the recovery in total forest area on a national scale, much of what was native forest cover has been replaced by plantation forests. In terms of coastal forests, this is relevant to sandy soil forests, a significant proportion of which (although not all) have been replaced by plantations. Additionally, the quality of the remaining native forests has continued to deteriorate. According to the forest reference emission levels that Vietnam submitted to the UN Framework Convention on Climate Change (UNFCCC) in 2016, rich and closed-canopy forest now constitutes only 5 percent of total forest cover, and in excess of two-thirds of Vietnam’s natural forests are in either poor or regenerating condition (World Bank, 2019a). This trend of degradation is threatening the capacity for Vietnam’s forests to deliver the ecosystem services many communities greatly depend upon. The demand for resources is also taking its toll on other coastal forest ecosystems. Melaleuca forest has seen comparable losses to mangrove due to pressures for materials, rice cultivation and non-rice production (Do and Bennett, 2006). Additionally, the growth of the tourist industry itself threatens the condition of these natural capital assets, with destinations where natural assets represent the main tourist attraction particularly at risk. In the Mekong Delta region, coastal forest ecosystems are vulnerable as river tourism has resulted in much greater concentrations of waste and pollution in and along the basin, which is a significant threat to the livelihoods of indigenous species and the functioning of ecosystems (World Bank, 2019b). Annexes 91 A.4 Growing importance of coastal forest assets in Vietnam Drivers of demand, such as population growth, economic reform and environmental pressures (e.g., climate change), are increasing the demand for, and importance and value of, ecosystem services delivered by coastal forest assets. Despite this, the degradation of these assets continues to be the reality. With global climate change, we are expecting to observe sea level rise and an increase in climate variability and severe storms. As such, inundation associated with tides and storm surges, coastal erosion and major weather events (e.g., typhoons) is likely to increase along the vulnerable coastal regions of Vietnam. Already, local evidence is emerging. For instance, Vietnam’s Ministry of Natural Resources and Environment (MONRE) has recorded a greater frequency of high intensity typhoons in recent years (Nguyen et al., 2014). As such, the protective services delivered by coastal forest assets are becoming ever more valuable. The GoV has recognized this and is prioritizing coastal forests in a bid to improve the country’s climate change resilience (World Bank, 2019a). Additionally, mangroves and coastal forests have a carbon storage value, which continues to grow in importance with efforts to mitigate the impacts of global climate change. Vietnam has a current population of 97.5 million and continues to grow at a rate of 1.0 percent per annum. This means that Vietnam’s population is expected to peak at approximately 110 million by the year 2054. More specifically, the population in many of Vietnam’s coastal areas continues to grow. The coastal province of Quang Ninh, of relevance in this study (see Section 3.1), where many of its communities rely on the services delivered by coastal forest assets, had population growth rate in 2019 of 1.6 percent (GSO, 2020). As such, demands for resources such as timber for construction and charcoal from mangrove ecosystems will continue to grow. Additionally, with the expansion of aquaculture and capture fisheries production at the core of the Government’s current plans for economic growth, the sustainable management of coastal forest assets is crucial. This is particularly pertinent if the Government intends to continue to grow its tourist industry. A GSO survey in 2013 and 2017, investigating the sentiments of international visitors regarding their experience in Vietnam, revealed that 62.9 percent and 71.2 percent of visitors regarded it as an ‘attractive site’, and this was a key reason for visiting in these years, respectively (World Bank, 2019b). The importance of this is underlined by the fact that, as mentioned, tourism itself is an increasing threat to natural capital assets. Supporting Resilient Coastal Economies in Vietnam 92 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas B. UN SEEA-EEA Ecosystem Accounting Tables This section presents some of the UN SEEA-EEA ecosystem accounting tables that may be used in this work. The tables/accounting frameworks presented are taken directly from the SEEA-EEA guidance (UN, 2014). The example tables are presented in the context of an assessment of an EAU that comprises medium to large fields of rain-fed herbaceous cropland. B.1 Ecosystem condition and extent account at the end of accounting period The extent and condition accounts are structured by the type of LCEU (in a given EAU there will be multiple LCEU types [see Figure 4‑1]). In addition to the indicators presented, relevant benchmarks and thresholds for the different indicators could also be presented as to provide a basis or frame of reference for the changes in condition observed. The data on each indicator will be collected using measurement units unique to the indicator, but this may be adjusted for the purpose of comparison. Table 0‑1. UN SEEA-EEA Extent and condition account table Type of Eco‑ Characteristics of ecosystem condition LCEU system extent Vegetation Biodiversity Soil Water Carbon Examples of indicators Area Leaf area Species Soil organic River flow, Net carbon index, richness, matter water balance, biomass, relative content, quality, fish primary mean abundance soil carbon, species productivity annual groundwater increment table Forest tree cover Agricultural land Urban and developed areas Open wetlands Annexes 93 B.2 Ecosystem service account (physical flows) The table below provides a framework for reporting data on the physical flows of ecosystem services delivered by the assessment area (EAU). The number of ecosystem services for which data is reported will depend on the type of ecosystem concerned and its use. Two ecosystems identical in terms of ecological structure may deliver different services depending on the surrounding population and the benefits they choose to prioritize: for example, a remote coastal forest may not deliver recreation/tourism services, whereas the same type of forest close to a population center or tourist hub is likely to do so. The ecosystem services for which flows are reported will be measured using different units. Examples of flow types are included in the table to provide an understanding of the sort of the data reported within the account for different services. Table 0‑2. UN SEEA-EEA Ecosystem service account table (physical flows) by units to be measured Ecosystem Type of LCEU service type Forest tree Agricultural Urban and Open cover land associated wetlands developed areas Provisioning Tonnes of timber Tonnes of wheat services Regulating Tonnes of CO2 Tonnes of CO2 Tonnes of CO2 Tonnes of services stored/released stored/released stored/released phosphorous absorbed Cultural Number of visitors Hectares of Hectares of services and hikers parkland habitat for ducks B.3 Expected ecosystem service flows at end of accounting period The table below illustrates a basic structure for presenting data on the expected ecosystem service flows (benefits). Akin to the measures (physical flows) of ecosystem services that are presented in Table 0‑2, the measurement units will vary depending on the service for which they are reported. Benefits can be aggregated and reported: ● For the period of the ‘ecosystem life’, i.e., the period for which the ecosystem can continue to sustainably deliver the benefit, e.g., the volume of timber that can be harvested from a forest before it is completely cleared. Supporting Resilient Coastal Economies in Vietnam 94 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas ● For a standard asset life or appraisal period, such as 25 years, over which analytical assumptions are not expected to change. ● As an annual flow, with the understanding that this may be greater or less than an independently derived estimate of a sustainable flow. Table 0‑3. UN SEEA-EEA Expected ecosystem service flows table (benefits) Type of LCEU Ecosystem service type Forest tree Agricultural Urban and Open cover land associated wetlands developed areas Provisioning services Regulating services Cultural services Photo: Zac Crush - shutterstock.com Annexes 95 C. Provincial contextual data C.1 Sources of contextual data The table below summarizes the contextual data which was collated in the pilot natural capital accounts for the two provinces, prior to the extent, condition and ecosystem accounts, and the sources of this data. Table 0‑4. Socioeconomic and geographical contextual data presented in trial accounts Category Quang Data TT-Hue Data source Ninh source Biophysical Dominant FORMIS Area and ISPONRE (2017) land covers database coastline length Primary ISPONRE (2017) constituent ecosystems Species richness ISPONRE (2017) Social Provincial Quang District GSO rural and Ninh populations urban Statistics populations Office District areas GSO (2019) (km2) District GSO population densities Economic Economic Quang Main industries GSO growth rate Ninh and workforces by sector Statistics Office Percentage of Report on Implementation of (2019) workers in each Socio-Economic Development sector (localities) Mission in 2017 and Socio- Economic Development Plan 2018 of Quang Dien, Phong Dien, Phu Loc, Phu Vang, and Huong Tra Town Supporting Resilient Coastal Economies in Vietnam 96 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas C.2 Quang Ninh Province Located in the northeast of the country, Quang Ninh Province has an onshore area of more than 6,000 km2 and a sea area of more than 6,000 km2, along with 120 km of coastline and more than 2,000 islands. In 2019, Quang Ninh province had four cities, one township, and ten district towns classified as urban category IV and V. The urbanization rate of Quang Ninh is 55 percent compared to 32 percent at the national level. In 2020, the urbanization rate is expected to reach 65 percent. Quang Ninh Province includes forests, plains, sea and the international border gate of Mong Cai (to the People’s Republic of China). Quang Ninh has access to many inland waterways and marine transport routes, including Cai Lan, the only deep-sea port in northern Vietnam. Because of its proximity to two of the county’s biggest cities, Hanoi and Haiphong, Quang Ninh province also plays an important role in regional socioeconomic development, especially the regional economic cooperation frameworks. Approximately 80 percent of the area of the province is mountainous, of which 64 percent is forest. Agriculture land accounts for 8.26 percent of the land, of which about half is rice land. The province has 15 basins grouped into three main categories: mountain, hilly and coastal. The coastal area is around 121,717 ha with three main ecosystems: mangrove, seagrass, and coral reefs. The population in 2018 was nearly 1.3 million people. The urban population makes up approximately 64 percent of the province’s residents, while the rural population is approximately 36 percent. In recent years, Quang Ninh has had strong economic development. The average economic growth rate (GRDP) during 2015-2018 was close to 10 percent, more than 3 percentage points higher than the national average growth rate (of 6.7 percent). The agricultural, forestry and fishery sector increased by 4 percent from the previous year; while manufacturing and construction sector increased by nearly 11 percent compared to the previous year. The GRDP at current price in 2018 reached VND 152.250 billion and GRDP per capita was VND 118.9 million (equal to USD 5,260). In 2018, the agricultural, forestry and fishery sector accounted for 6 percent of the economy, the manufacturing and construction sector approximately 49 percent, and the service sector approximately 33.2 percent. Located in the northeast region of Vietnam, Quang Ninh province and its mangrove species are quite diverse. According to Sam et al. (2005), there are 16 “true mangroves species” distributed across the coastal area of the northeast region, particularly Quang Ninh. Of those, the following are the predominant species: Avicennia marina (Mam bien), Kandelia obovata (Trang), Rhizophora stylosa (Duoc voi), Bruguiera gymnorrhiza (Vet du), and Aegiceras corniculatum (Su). C.3 Tam Giang - Cau Hai lagoon, TT-Hue Province Located along the coast of Thua Thien Hue (TT-Hue) province in central Vietnam and covering an area of 21,620 ha, Tam Giang - Cau Hai (TGCH) is considered the largest coastal lagoon system in Southeast Asia. The lagoon system runs parallel to the East Sea for about 70 km and includes diverse habitat types from river deltas to estuaries with inlets surrounded by sand dune barriers as well as Annexes 97 shallow open waters and seagrass beds. There are two main outlets to the East Sea, the Thuan An opening to the north and the Tu Hien opening to the south. The Huong, Dai and O Lau rivers all feed into this lagoon system. TGCH is an extremely dynamic system characterized by high levels of diversity due to spatial and temporal variation in ecological conditions across the lagoon complex, particularly differences in salinity levels and between dry and rainy seasons. Under the Ramsar wetlands classification systems, TGCH is classified as a brackish coastal lagoon (J type) comprising four major wetland habitat types: (i) vegetated wetlands, that consist mainly of marshes/swamps; (ii) non-vegetated wetlands, that comprise mudflats and sandflats; (iii) non-vegetated wetlands, that comprise mudflats and sandflats; and (iv) permanently submerged wetlands, some of which support seagrass beds; artificial wetlands, comprising aquacultural ponds and rice fields. In terms of species richness, 921 species have been documented in TGCH so far, including 287 phytoplankton species and 223 fish species, including one species that is endemic to Vietnam, Cyprinus centralis, and six that are recorded in the Red Book of Vietnam, which lists nationally threatened species. The lagoon is an important nursery area for both inland and marine fish species and is also important for birds: 73 species of waterfowl have been recorded here, including 34 migratory species, with one species, the Asian Dowitcher, (Limnodromus sesmipalmatus), a migratory wader that is near-threatened globally and nationally endangered. TGCH is an extremely productive and intensively used lagoon system. Aquaculture, fisheries and agriculture are the main sources of local livelihood, with some seasonal and full-time employment in the trade, construction and services sector. At least, 300,000 people live in and around the lagoon, distributed between one town and 236 villages grouped into 32 communes spread over five districts. It is estimated that around 100,000 people depend directly on the lagoon and engage in capture fisheries and/or various forms of brackish water aquaculture (mainly intensive and semi-intensive tiger shrimp cultivation and some other shrimp, fish, mollusk and crab culture). Aquaculture was introduced in the 1980s, as the lagoon was identified as ideal for this, particularly in areas near the two openings to the sea and in areas connected to muddy low-lying swamps. Extensive areas of soft substrate combined with shallow water are especially favorable for aquaculture, and large areas of the land along the edge of the lagoon have been converted to aquaculture ponds along with farming cages. The varied ecological conditions across the lagoon complex have also resulted in a diversity of economically useful, naturally occurring fish species and other aquatic resources. Capture fisheries are of a small-scale artisanal nature, using many different types of fishing gear according to location, season and target species. Capture fisheries take place mainly in the lagoon, but communities living near rivers and closer to the sea also engage in fishing these areas. The livelihoods of another 200,000 people are based on a combination of coastal agriculture (mainly rice cultivation) and part-time or occasional aquaculture and capture fisheries, as well as some animal husbandry. Some 17,700 ha of land is cultivated around the lagoon, 64 percent of which is rice and other food-grains. Other crops include cassava, potato, peanut, green melon, chilis and coriander. Soil suitability for agriculture varies around the lagoon and agriculture is concentrated in areas where soil is not affected by salinity or high levels of aluminum. Supporting Resilient Coastal Economies in Vietnam 98 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Figure 0‑3. Study area (Tam Giang - Cau Hai lagoon), TT-Hue province Tam Giang - Cau Hai lagoon is located in the administrative boundaries of four districts: Phong Dien, Quang Dien, Phu Vang, Phu Loc and Huong Tra town of Thua Thien Hue province. Of these, 33 communes and towns are close to the lagoon’s water bodies. The total population of the coastal lagoon communes is 265,248 people, accounting for nearly 44 percent of the total population of the four districts and towns along the lagoon (Table 0-5). The population density of communes along the lagoon is quite high (381 people/km2), which is much higher than the average population density of the five districts and towns in the lagoon (294 people/km2) as well as the population density of the whole province (229 people/km2). The districts with a high population living in the communes along the lagoon are: Phu Vang district with 13 communes located in the center of the TGCH lagoon, with 121,151 people out of a total of 178,603 people (accounting for 68 percent) and a fairly dense population of 769 people/ km2; Phu Loc district, including 8 communes with 65,650 people out of a total of 140,011 people (accounting for 47 percent) and an average population density of 283 people/km2, higher than the district average of 194 people/km2; and Quang Dien district with 8 communes along the lagoon, with 54,394 people out of a total of 80,142 people (accounting for 68 percent), and a population Annexes 99 density of 523 people/km2, equivalent to the population density of the whole district (514 people/ km2) (according to the Statistical Yearbook in 2017). The industry structure has changed a lot as the proportion of non-agricultural sectors has increased, and the port and seafood processing services also attract a lot of labor. Tourism activities have recently developed strongly in Thuan An beach area. Moreover, the life of people living on the fishing and aquaculture in the lagoon has been stabilized and developed better after various projects to improve livelihoods and restore ecosystems and resources of the lagoon. Table 0‑5. Area and population of Tam Giang - Cau Hai districts No. Districts/communes along Area Population Population the lagoon (km2) (people) density (people/km2) 1 Phong Dien District (2/13) 948.23 91754 98 1 Dien Hai Commune 12.77 5062 396 2 Dien Hoa Commune 13.78 4130 300 2 Huong Tra District (2/13) 517.10 115852 225 1 Hai Duong Commune 10.29 5649 549 2 Huong Phong Commune 15.70 9212 587 3 Phu Vang Districts (13/20 xã) 278.24 178603 660 1 Thuan An town 17.03 21797 1280 2 Phu Thuan Commune 7.41 7912 1068 3 Phu Hai Commune 3.33 7233 2172 4 Phu Dien Commune 13.95 10716 768 5 Vinh Xuen Commune 18.48 4265 231 6 Vinh Thanh Commune 10.57 9262 876 7 Vinh An Commune 15.25 7496 492 8 Phu An Commune 11.30 9333 826 9 Phu My Commune 11.61 9501 818 Supporting Resilient Coastal Economies in Vietnam 100 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas No. Districts/communes along Area Population Population the lagoon (km2) (people) density (people/km2) 10 Phu Xuan Commune 30.23 8160 270 11 Phu Da town 29.66 12542 423 12 Vinh Phu Commune 7.46 3382 453 13 Vinh Ha Commune 29.72 9552 321 4 Quang Dien District (8/11) 163.05 80142 514 1 Quang Ngan Commune 11.10 4830 435 2 Quang Cong Commune 12.52 4775 381 3 Quang Thai Commune 18.04 4617 256 4 Quang Loi Commune 32.88 5776 176 5 Sia Town 11.93 10824 907 6 Quang Phuoc Commune 12.68 6488 512 7 Quang An Commune 11.87 7887 664 8 Quang Thanh Commune 10.75 9197 856 5 Phu Loc Town (8/13) 720.36 140011 194 1 Vinh Hung Commune 16.04 8343 520 2 Vinh Giang Commune 18.93 4581 242 3 Vinh Hien Commune 22.00 7714 351 4 Loc Binh Commune 27.40 2217 81 5 Loc Tri Commune 62.60 6260 100 6 Phu Loc Commune 27.70 10791 390 7 Loc Dien Commune 115.35 13245 115 8 Loc An Commune 26.78 12499 467 Average of 33 communes along the lagoon 697.1 265,248 380.5 Annexes 101 Industry: The construction and service industries account for a high proportion of the economy, at 38.1 percent and 39.1 percent respectively, while the agriculture, forestry and fishery sector accounts for the smallest proportion, at 22.8 percent. However, the proportional distribution of the economic structure among districts and towns is not homogeneous due to the geographical location and natural resources of each locality. Table 0‑6. Production value structure by administrative unit No. Administrative units Agriculture, forestry Industry and Service and fishery (%) construction (%) (%) 1 Phu Loc 6.8 34.1 59.1 2 Phu Vang 25.7 31.7 42.6 3 Huong Tra 13.7 48.8 37.5 4 Quang Dien 43 18 39 5 Phong Dien 25 58 17 Average 22.8 38.1 39.1 In general, the economy of the project area has tended to shift from agriculture towards services and industry in the past five years. This is consistent with the economic development orientation of the districts and town in particular and Thua Thien Hue province in general. However, the production value of some economic sectors, including agriculture, forestry and fishery, have not yet fully developed their potential to make a major contribution to the province’s GDP structure. Thua Thien Hue has a small area of mangroves (47 ha) and the mangroves are mainly distributed across Lap An (Lang Co town), Tam Giang - Cau Hai (Thuan An Town and Huong Phong commune) lagoons, and Bu Lu estuary (Pham Ngoc Dung 2015). In Lap An lagoon, main woody mangroves species are: Lumnitzera racemosa (Coc vang), Rhizophora apiculata (Duoc doi), Avicennia marina (Mam bien), Aegiceras corniculatum (Su), and Excoecaria agallocha (Gia), which account for about 60 percent. The density is about 1,500 tree/ha. In Tan My, the main mangrove species are: Aegiceras corniculatum (Su), Bruguiera sexangular (Vet khang), Excoecaria agallocha (Gia) and Lumnitzera racemosa (Coc vang) which account for about 86 percent, with a density of 10,000 tree/ha. In Huong Phong commune, predominant plant species are Excoecaria agallocha, Rhizophora apiculata and Dolichandrone spathacea (Quao nuoc), which account for about 87 percent, with a density of 1,800 trees/ha. In Bu Lu estuary, main mangrove species are Rhizophora apiculata, Avicennia marina, Bruguiera sexangular and Lumnitzera racemosa. Overall mangroves in Thua Thien Hue cover a small area and density ranges from 1,500 to 10,000 trees/ha. Like in Quang Ninh province, most mangroves in Thua Thien Hue are not more than five meters high. Supporting Resilient Coastal Economies in Vietnam 102 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas D. GADM Maps Figure 0‑4. [Left to right] Quang Ninh province, Quang Ninh districts (Mong Cai), Mong Cai communes Figure 0‑5. [Left to right] TT-Hue province, TT-Hue districts (Quang Dien), Quang Dien communes Annexes 103 E. Ecosystem extent account examples E.1 Quang Ninh The ‘Forest Type’ classification was used to extract the ‘Wetland forest/Mangrove forest’ shapefile for the years 2015 and 2018 from the respective Forest Resource datasets available from FORMIS. These datasets were overlaid with a shapefile of district boundaries for Quang Ninh Province obtained from GADM to ascertain the area of mangrove forest in each district for each year (outputs 1 and 2 in Table 4‑1). Corresponding analysis was also carried out to ascertain the area of sandy forest for each district for each of these years. Firstly, the ‘Site Condition’ classification was used to extract the shapefile of all ‘Sandy Soil’ areas for both 2015 and 2018. This was then overlaid with the shapefile of ‘Evergreen broadleaved forest’ for 2015 and 2018 obtained using the ‘Forest Type’ classification and using a simple clip function, a new shapefile of sandy forest area was obtained for each year (outputs 4 and 5 in Table 4‑1). The results of these operations are presented in the table below. Table 0‑7. Mangrove and sandy forest areas (ha) within Quang Ninh districts, for 2015/18 District Mangrove Sandy 2015 2018 Change 2015 2018 Change (%) (%) Cô Tô 118 118 -1 108 100 -7 Đầm Hà 2519 2535 1 0 0 0 Hải Hà 2027 1543 -24 2 47 2533 Hoành Bồ 698 567 -19 0 0 0 Quảng Yên 2043 2400 17 0 0 0 Thành phố Cẩm Phả 926 1035 12 0 0 0 Thành phố Hạ Long 291 632 117 0 0 0 Thành phố Móng Cái 7036 6656 -5 172 168 -2 Thành phố Uông Bí 134 134 0 0 0 0 Supporting Resilient Coastal Economies in Vietnam 104 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas District Mangrove Sandy 2015 2018 Change 2015 2018 Change (%) (%) Tiên Yên 3519 3860 10 0 0 0 Vân Đồn 2310 2494 8 79 127 61 Grand Total 21622 21973 2 361 442 23 Additionally, the shapefiles of mangrove and sandy forest for the year of 2018 (outputs 2 and 5 in Table 4‑1) were presented spatially in the extent account, as is presented in the figure below. Source: FORMIS (2020) Figure 0‑6. Mangrove and sandy forest areas in Quang Ninh province, 2018 Annexes 105 A further clip operation was used on the overlain shapefiles for 2015 and 2018 for each of the forest types, to ascertain the change in area (both in hectares and as a percentage) for each district over the given timeframe. Some of the headline results are presented below: ● The area of the mangrove forests increased by 352 ha from 21,621 ha in 2015 to 21,973 ha in 2018, equivalent to a 2 percent increase. ● Sandy forest area increased by 81 ha from 361 ha to 442 ha, equivalent to 22 percent growth. ● At the district level, the mangrove forests are mainly distributed across Mong Cai, Tien Yen, Van Don, Quang Yen, Hai Ha, Dam Ha district. ● The sandy forests are mainly distributed across three districts and cities, including Co To, Mong Cai city, and Van Don. Box 7. FORMIS ‘forest type’ extent data It should be noted that some of the data presented in Table 0‑7 is erroneous, resulting in unusual patterns in the data (for example, over a doubling of mangrove cover between 2015 and 2018 in districts such as Thành phố Hạ Long). There was a glitch in the FORMIS database for Quang Ninh Province due to data synchronization issues between the provincial and central levels which has resulted in errors in the reported data. ISPONRE has since contacted the relevant district authorities across Quang Ninh to collect their 2019 data; however, we have not yet been able to update these results. Regardless, the results are presented to demonstrate the data gathering and presentation process as part of the pilot extent accounts. Following this, the ‘Forest Function’ classification was used on the relevant Forest Resource datasets to obtain the breakdown for protection, special-use and production forest areas in both 2015 and 2018. These files were overlain with the shapefile of district boundaries to ascertain the area of each forest type at the district level (outputs 7 and 8 in Table 4‑1). The results are presented in the table below. Additionally, Figure 0‑7 illustrates the total area of each forest type across Quang Ninh for 2015/18. Supporting Resilient Coastal Economies in Vietnam 106 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Table 0‑8. Area of protection, special-use and production forest for Quang Ninh districts 2015/18 (ha) Annexes District Special use Protection Production 2015 2018 % 2015 2018 % 2015 2018 % change change change Cô Tô 0 0 0 118 214 81 0 4 n/a Đầm Hà 0 0 0 2498 2050 -18 21 485 2179 Hải Hà 0 0 0 1622 1337 -18 405 254 -37 Hoành Bồ 0 0 0 698 517 -26 0 50 n/a Quảng Yên 0 0 0 2043 1006 -51 0 1395 n/a Thành phố Cẩm Phả 0 0 0 918 949 3 8 87 955 Thành phố Hạ Long 0 0 0 291 385 32 0 247 n/a Thành phố Móng Cái 0 0 0 7036 6468 -8 0 356 n/a Thành phố Uông Bí 0 0 0 134 127 -5 0 7 n/a Tiên Yên 0 0 0 3276 3420 4 243 440 81 Vân Đồn 51 30 -41 2207 2505 13 52 86 67 Total 51 30 -41 20842 18976 -9 730 3410 367 107 25000 20000 Total forest area (ha) 15000 10000 5000 0 Special use Protection Production 2015 2018 Figure 0‑7. Total area (2015/18) of special-use, protection and production forests for Quang Ninh province (ha) The extent analysis of forest function in Quang Ninh Province revealed the following insights: ● The area of special use forest in the coastal area declined by approximately 41 percent, although this was a marginal loss of 21 ha from 2015 to 2018. ● From 2015 to 2018, 1,866 ha of mangrove forest was converted from protection to production forest, a loss of protection forest of approximately 9 percent. ● Production forest areas increased from 730 to 3,410 ha from 2015 to 2018, equivalent to approximately a 367 percent increase. ● The reclassification (change in forest function planning) from protection forest to production forest is most significant in Quang Yen, Ha Long, Tien Yen and Dam Ha district. The change in special use forest occurred in Van Don district. Supporting Resilient Coastal Economies in Vietnam 108 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Box 8. Species-level extent data Species-level spatial data can be useful in providing an added level of granularity in the ecosystem service accounts. Since the species present exert a significant control on the carbon sequestration capacity of a given coastal forest ecosystem, species-level data facilitates the calculation of more accurate carbon storage assessments in particular. Thus, species-level data is recommended for use in the carbon storage accounts presented later in this report, when available. Unfortunately, species-level data is only available for planted mangrove and sandy forest areas in the FORMIS database, as opposed to natural habitats where species may be more varied. Consequently, species-level data can only be obtained for a subset of the total coastal forest extent accounts. The changes observed in forest function can at least partly be attributed to Decision 15/NQ-CP, which concerns the administration of land use planning to 2020 in Quang Ninh Province. In this plan, the area of protection forest is planned to be reduced by 1,714 ha and production forest reduced by 20,207 ha. Within the same plan, however, 21,168 of un-used land is allocated to forest land and thus total forest area is only to be reduced by 839 ha. While the plan does not detail specifically where the forest function change is to occur, it clearly evidences the conversion observed. The changes under the plan are detailed further in the table below. Table 0‑9. Changes in forest land (ha) in Quang Ninh under land use planning Decision 15/NQ-CP from 2016-2020 Protection Special use Production Total Forest to non- 1,259 86 18,779 20,124 agricultural land Forest to 455 0 1,428 1,883 agricultural land Total forest loss 1,714 86 20,207 22,007 Un-used land to 15,792 839 4,537 21,168 forest Net forest change 14,078 753 -15,670 -839 Annexes 109 Finally, species-level data is extracted from the FORMIS forest plot data on planted mangrove species and sandy forest species for 2018. In Quang Ninh, spatial data was available for four main species used for mangrove plantation in Quang Ninh. In sandy areas across Vietnam, plantations can be established with native species, Acacia spp., and most commonly, the evergreen species, Casuarina equisetifolia. The poor site conditions locally in Quang Ninh, however, mean that only C. equisetifolia could be used to establish plantations in sandy areas. Of the total 449 ha of sandy forest, 371 ha is C. equisetifolia. The species-level spatial data for plantation sites within the province was overlaid with the shapefile of district boundaries to obtain the area (ha) of planted mangrove and sandy forest species for each district. As in Table 4‑1, it is recommended to extend this analysis to examine changes in planted forest (species) area over time if the data exists. The results of the Quang Ninh planted forest species analysis are presented in Table 0‑10 and Table 0‑11. Table 0‑10. Area of planted mangrove species 2018, Quang Ninh province (ha) Tree species Area (ha) Aegiceras corniculatum (Sú) 174 Hoành Bồ 109 Tiên Yên 65 Kandelia candel (L.) Druce (Trang) 424 Hải Hà 191 Tiên Yên 233 Rhizophora stylosa Griff. (Đước vòi) 22 Thành phố Móng Cái 22 Sonneratia caseolaris (L.) Engl. (Bần Chua) 141 Quảng Yên 99 Thành phố Uông Bí 43 Grand Total 761 Supporting Resilient Coastal Economies in Vietnam 110 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Table 0‑11. Area of planted sandy forest species 2018, Quang Ninh province (ha) Forest Year Hương Phong Phú Lộc Phú Quảng Total type Trà Điền Vang Điền Mangrove 2015 (ha) 13 0 0 1 36 50 forests 2018 (ha) 13 0 0 1 54 69 % change 0 0 0 0 52 37 Sandy 2015 (ha) 187 2650 246 850 679 4611 forests 2018 (ha) 187 2652 246 850 679 4613 % change 0 0 0 0 0 0 Coastal 2015 (ha) 200 1061 78 564 144 2047 forests 2018 (ha) 200 514 67 319 163 1262 %change 0 -52 -15 -43 13 -38 E.2 Tam Giang - Cau Hai lagoon, TT-Hue Province The TGCH lagoon system covers an area of approximately 22,000 ha which follows the coastline for approximately 70 km. While the system, which comprises three main lagoons, is very diverse, the area of mangrove forest is relatively small. As such, ISPONRE has supplemented the extent account with an additional mapping and assessment exercise of the multiple ecosystem types in and around the lagoon area. This exercise is supplementary to the main extent account of coastal forests and uses bespoke mapping data from a recent ISPONRE study. Thus, the exercise is not readily replicable for other provinces or locations and thus is not recommended for the coastal forest extent accounts elsewhere. However, this approach illustrates how variations to the approach are applicable in some coastal zones with more varied habitats. The TGCH development plan up to 2030 by ISPONRE (unpublished) provides an ecosystem mapping of the region, which classifies the study area into six ecosystem categories for the lagoon and eight ecosystem categories adjacent to the lagoon. The extent of each ecosystem classification is presented in the table below. Annexes 111 Table 0‑12. Constituent ecosystems, Tam Giang - Cau Hai TT-Hue province System Ecosystem Area (ha) Lagoon system Seagrass 4,226 Aquaculture 6,051 Beach 4,451 Mangrove 190 Lagoon 15,353 Sand dune 8,387 Other system Natural forest 2,895 Annual crop 2,181 Grass and shrubland 4,119 Plantation forest 2,833 Residential 13,220 River 3,527 Urban 2,213 Water rice 27,954 All Total 97,604 Ecosystem classifications have also been presented spatially to understand the distribution of ecosystem types and provide a spatial indication as to the delivery of ecosystem services (see Source: ISPONRE (2017), Figure 0‑8). Supporting Resilient Coastal Economies in Vietnam 112 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Source: ISPONRE (2017) Figure 0‑8. Map of constituent ecosystems, Tam Giang - Cau Hai Following this, the approach presented in section 4.1.1 was repeated, first by extracting the mangrove and sandy forest type shapefiles for 2015 and 2018 from the FORMIS forest resource datasets and then overlaying these with the GADM district boundaries for the region to ascertain the area of these coastal forest types (outputs 1 and 3 in Table 4‑1). The results presented in Table 0‑13 ‘Coastal forests’ represent the sum area of both mangrove and sandy forests. It should be noted that there were no mangrove forests in Phong Dien and Phu Loc district, thus the sandy forest area represents the total area of coastal forest in these districts. Annexes 113 Table 0‑13. Area of district mangrove and sandy forests, Tam Giang - Cau Hai 2015/18 Forest Year Hương Phong Phú Phú Quảng Total type Trà Điền Lộc Vang Điền Mangrove 2015 (ha) 13 0 0 1 36 50 forests 2018 (ha) 13 0 0 1 54 69 % change 0 0 0 0 52 37 Sandy 2015 (ha) 187 2650 246 850 679 4611 forests 2018 (ha) 187 2652 246 850 679 4613 % change 0 0 0 0 0 0 Coastal 2015 (ha) 200 1061 78 564 144 2047 forests 2018 (ha) 200 514 67 319 163 1262 %change 0 -52 -15 -43 13 -38 The summary results of the coastal forest extents are as follows: ● There was no discernable change in the area under sandy soil forests or mangroves in between the years of 2015 and 2018. ● This is in contrast with Quang Ninh province, where sandy forest areas increased in extent by around 25 percent. On the other hand, Quang Ninh did see an overall loss in coastal forest habitat (2,445 ha, or 11 percent) due to a significant area of mangrove loss (2,533 ha). Secondly, the ‘Forest Function’ classification was again used to obtain the spatial distribution for 2015 and 2018 of protection, special-use and production forest areas from the relevant Forest Resource datasets. The results are presented in Figure 0-9 (Source: FORMIS (2020) and Figure 0-10 (Source: FORMIS (2020). Supporting Resilient Coastal Economies in Vietnam 114 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Source: FORMIS (2020) Figure 0‑9. Map of protection and production forests, Tam Giang - Cau Hai 2015 Source: FORMIS (2020) Figure 0‑10. Map of protection and production forests, Tam Giang - Cau Hai 2018 Annexes 115 The area of protection, special-use and production forest for the province was then overlaid with the GADM district boundaries layer to obtain the area of the forest function classifications within each district. The results are summarized in the table below. It should be noted that there are no special-use forests in TGCH and hence this forest function type is not included within the analysis. Table 0‑14. Area of protection and production forest in Tam Giang - Cau Hai districts, 2015/18 District 2015 2018 Total Protection Production Total Protection Production coastal forest forest coastal forest forest forests forests Hương Trà 200 200 0 200 200 0 Phong 2650 1061 1588 2652 514 2138 Điền Phú Lộc 246 78 168 246 67 180 Phú Vang 851 564 288 851 319 532 Quảng 714 144 570 733 163 570 Điền Grand 4661 2047 2614 4682 1262 3420 Total The analysis of the forest function type extents can be summarized as follows: ● Between 2015 and 2018, the total forest area remained stable with the exception of a 21 ha (0.4 percent) increase. The possibility exists that the observed change, considering the very small scale, could be a function of measurement error. ● However, there was a significant shift in forest function zoning, with 785 ha (38.3 percent) of protection forest converted to production forest. This reflects the active economic development in the TGCH, opening more of the forest for use by various economic activities. Production forest is designated for the production of both timber and non-timber products and the state retains the power to convert production forest for alternative uses. The change in zoning is decided by the Provincial People’s Committee and for large scale conversions, ultimately by the Prime Minister. Supporting Resilient Coastal Economies in Vietnam 116 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Lastly, the species-level data on planted mangrove and sandy forest areas was obtained for the year of 2018 from the FORMIS forest plot data. In TGCH, three main mangrove species have been planted, in contrast to the four species present in Quang Ninh Province. Additionally, two species have been used for forest plantation on sandy soil as opposed to only Casuarina equisetifolia in Quang Ninh. Once again, the GADM district boundaries were overlaid to obtain the species area for each district. Additionally, it is recommended to extend this analysis to examine changes in planted forest (species) over time. The results for planted mangrove and sandy forest species extent in TGCH are presented in Table 0‑15 and Table 0‑16, respectively. Table 0‑15. Area of planted mangrove species, Tam Giang - Cau Hai 2018 District Latin name Local Area 2015 Area 2018 Area name (ha) (ha) change (%) Quảng Kandelia candel (L.) Trang 0 19 n/a Điền Druce Quảng Sonneratia caseolaris Bần chua 0 36 n/a Điền (L.) Engl. Phú Vang Rhizophora Đưng (Đước 1 1 0 mucronata Lam. bộp) Hương Trà Rhizophora Đưng (Đước 9 9 1 mucronata Lam. bộp) Hương Trà Others Loài khác, 0 4 n/a mọc nhanh Hương Trà Cocos Dừa 4 0 -100 Total 14 69 383 Annexes 117 Table 0‑16. Area of planted sandy forest species, Tam Giang - Cau Hai 2018 District Latin name Local Area 2015 Area 2018 Area name (ha) (ha) change (%) Hương Trà A. aulacocarpa Keo lá bạc 83 83 0 Casuarina Phi lao equisetifolia 104 104 0 Phong Điền A. aulacocarpa Keo lá bạc 547 121 -78 Casuarina Phi lao equisetifolia 144 141 -2 Phú Lộc A. aulacocarpa Keo lá bạc 2 2 25 Casuarina Phi lao equisetifolia 77 65 -15 Phú Vang A. aulacocarpa Keo lá bạc 77 28 -63 Casuarina Phi lao equisetifolia 385 267 -31 Quảng A. aulacocarpa Keo lá bạc 32 32 -1 Điền Casuarina Phi lao equisetifolia 36 36 0 In total 1487 878 -41 Supporting Resilient Coastal Economies in Vietnam 118 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas F. Forest coverage spatial analysis F.1 Example of mangrove forest plot overlay onto Sentinel 2 image (left, natural color; right, NDVI) F.2 Example of plot-based mangrove forest cover (%) Annexes 119 G. Ecosystem condition account examples G.1 Quang Ninh Province The ‘Forest Type’ shapefiles for Quang Ninh Province were extracted for the years 2015/18 and the areas (ha) of forest change between forest code types (Table 4‑2) calculated. Areas of forest change were input into a forest change matrix, as in Table 4‑3, for 2015-2018, as presented below. It should be noted that not all forest type codes presented in Table 4‑2 are relevant to the land cover in Quang Ninh Province and thus the matrix of forest type change does not include all the codes presented. The results of the forest change matrix are presented spatially in Figure 0-11 to show the geographical patterns of forest condition change with time. The sum areas of forest change for each change type are also presented in Figure 0-11. Table 0‑17. Matrix of forest change (2015-18) for Quang Ninh province 2018 42 62 64 74 80 84 86 90 Total 42 16742 214 0 19 0 56 0 7 17038 62 0 692 0 0 0 0 0 0 692 64 0 0 344 0 0 0 0 0 344 74 0 0 0 34 0 0 0 0 34 2015 80 0 0 0 10 427 0 0 0 437 84 0 0 0 3 0 2241 0 0 2244 86 0 0 0 0 0 0 1 0 1 90 0 0 0 0 0 0 0 0 0 Total 16742 906 344 65 427 2297 1 7 20789 KEY: 42 Natural rehabilitation secondary mangrove forest 62 Plantation mangrove 64 Plantation on sandy soil 74 New plantation mangrove 80 Regeneration on mangrove 84 Open land on saline wetland 86 Open land on sandy soil 90 Agricultural crop on saline wetland Supporting Resilient Coastal Economies in Vietnam 120 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Change type Characteristic Restoration Change from existing coastal forest to a forest with better condition, e.g., newly planted forest to closed canopy forest Reforestation Change from non-forest to coastal forest, e.g., new plantation Degradation Change from exiting coastal forest to a forest with poorer condition Deforestation Change of mangrove forest to other land use type Stable forest Stable forest Stable non Stable non forest forest Photo: Nguyen Quang Ngoc Tonkin - shutterstock.com Annexes 121 Figure 0‑11. Map of forest change (2015-18), Quang Ninh province The following results were concluded from the forest change analysis: ● Of the 18,075 ha of coastal designated forest, 98 percent is stable forest. ● There were 0 ha of restoration compared to 214 ha of degradation. ● There were 0 ha of reforestation compared to 83 ha of deforestation. The deforestation is mainly observed in Quang Yen, Van Don, Hai Ha district and Mong Cai city. The Landsat 8 and Sentinel 2 NDVI images of the province’s mangrove plots identified in the extent account were then analyzed for areas of non-forest (NDVI < 0.4) for 2015 and 2018, respectively. In doing so, the percentage canopy coverage for mangrove plots within each district, and the corresponding change in this value between the two years, was determined as an indicator of mangrove forest condition and condition change. Percentage coverage figures for each district’s mangrove plot are presented in Figure 0‑12. As can be seen in this figure, there were significant declines in percentage canopy cover across the period for the forest present in two districts in particular, Mong Cai and Hai Ha. This would indicate degradation of mangrove forest in these areas. Supporting Resilient Coastal Economies in Vietnam 122 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Uong Bi City Quang Yen City Ha Long City Cam Pha City Mong Cai City Van Don district Tien Yen district Hoanh Bo district Hai Ha district Dam Ha district 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 Values Cover % 2018 Cover % 2015 Figure 0‑12. Canopy coverage of mangrove plots, Quang Ninh province districts 2015/18 Box 9. Coverage assessment, Quang Ninh Province It should be noted that it has been stated by ISPONRE that the satellite-based coverage assessment for Quang Ninh was completed ‘without much calibration nor comprehensive investigation into the variation of the relationship between the vegetation stage and image value.’ While we present the output in the graphic above as it is useful for the purpose of example, as to how the analysis results could be presented, the results may be subject to measurement error. This should be considered particularly when interpreting the changes in mangrove coverage between years which are particularly small. Annexes 123 G.2 Tam Giang - Cau Hai, TT-Hue Province As in section 4.2.1, ‘Forest Type’ shapefiles were extracted for TGCH for the years 2015/18 and the areas (ha) of forest change between forest code types (Table 4‑2) calculated. Areas of forest change were again input into a forest change matrix for 2015-2018, which is presented below. As above, not all forest type codes presented in Table 4‑2 are relevant to the land cover in TGCH and thus the matrix of forest type change does not include all the codes presented. Table 0‑18. Matrix of forest change (2015-18) for Tam Giang - Cau Hai, TT-Hue province 2018 42 62 64 74 77 85 86 87 88 92 93 Total 42 0 0 0 0 0 0 0 0 0 0 0 0 62 0 10 0 0 0 0 0 0 0 0 0 10 64 0 0 2502 0 170 0 3 0 0 2 2677 74 0 36 0 5 0 0 0 0 0 0 0 40 77 0 0 137 0 889 0 3 0 0 0 0 1029 2015 85 0 0 0 0 0 0 0 0 0 0 0 0 86 0 0 1 0 0 0 446 0 0 0 0 447 87 0 0 0 0 0 0 0 455 0 0 0 456 88 0 0 0 0 0 0 0 0 7 0 0 7 92 0 0 0 0 0 0 0 0 0 43 0 44 93 0 0 2 19 0 0 1 0 0 0 1604 1626 Total 0 45 2642 23 1059 0 453 456 7 44 1606 6335 KEY: 42 Natural rehabilitation secondary mangrove forest 62 Plantation mangrove 64 Plantation on sandy soil 74 New plantation mangrove 77 New plantation on sandy soil 85 Open land on alkaline wetland 86 Open land on sandy soil 87 Open land with scattered trees on sandy soil 88 Agricultural crop on hill land 92 Other freshwater wetland 93 Other land Supporting Resilient Coastal Economies in Vietnam 124 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Change type Characteristic Restoration Change from existing coastal forest to a forest with better condition, e.g., newly planted forest to closed canopy forest Reforestation Change from non-forest to coastal forest, e.g., new plantation Degradation Change from exiting coastal forest to a forest with poorer condition Deforestation Change of mangrove forest to other land use type Stable forest Stable forest Stable non Stable non forest forest The areas of forest change types are summed and subsequently presented spatially in Figure 0‑13 and Figure 0‑14. The maps, including and excluding areas of stable forest respectively, are presented separately to better delineate the crucial areas of changing condition. The figures also include the sum area values of each forest type change. The following results were concluded from the analysis: ● The key trend in TGCH lagoon is that most of the forest land remained unchanged. ● Of the total 3,776 ha of coastal forest, 3,405 ha (90.2 percent) is stable forest. ● There were 172 ha of forest restoration equivalent to 4.6 percent of forest area and 170 ha of forest degradation equivalent to 4.5 percent. ● Deforestation accounted only for 0.2 percent of the forest area, while reforestation accounted for 0.6 percent. ● The main area of forest degradation was in Quang Dien district and the coastal area of Phong Dien district. It must be kept in mind, however, that the TGCH lagoon area in TT-Hue Province has had a long history of deforestation and while forest coverage remains fairly stable now, the current ecosystem condition may be misleading if this historical context is failed to be taken into account. Ideally, the analysis of forest change would be extended much further in time to more comprehensively understand the changes in condition and that while most forest areas are currently stable, this result is in the context of a sub-optimal baseline. Natural and planted forest cover data is available extending back to 2008 from the GSO; however, this data is available only for the whole province and not for the multiple forest types included within the forest change matrix. Nonetheless, some assumptions can be made on the basis of this analysis regarding the impact of forest change on coastal forest ecosystem service delivery presently and in the future. Annexes 125 A forest (canopy) coverage assessment was not carried out for TGCH due to the relatively small area of mangrove coverage. Despite the small coverage extent, a canopy coverage assessment can still feasibly be carried out and it is recommended that a canopy coverage assessment is carried out as part of the condition accounts for other provinces (as long as there are mangrove plots present). Figure 0‑13. Maps of forest change (2015-18) Tam Giang - Cau Hai, TT-Hue province, including stable forest Supporting Resilient Coastal Economies in Vietnam 126 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Figure 0‑14. Maps of forest change (2015-18) Tam Giang - Cau Hai, TT-Hue province, excluding stable forest Annexes 127 128 H. Long list of ecosystem services specific to coastal forest assets in Vietnam Below is a list of the ecosystem services, considered from our literature review and consultation process, deemed as relevant to coastal forest assets in Vietnam. The ranking exercise to ascertain the most valuable services for inclusion within the framework, comprised of two main components: ● Prevalence – this concerns the prevalence of the service amongst the literature (Figure 5‑1) ● Importance – this concerns the perceived value of the service to beneficiaries and considers both monetary and non-monetary benefits. Ecosystem Impact Rank on Rank on Rank on Comment Overall Service importance prevalence ability to rank value Fishery Habitat for juvenile Medium High Low Difficult to assess Must do habitats aquatic species but high magnitude and supporting of of impact. Some aquaculture methods and data available. Inland capture fisheries Medium High Medium Direct market values Must do of non-migratory available from a range mollusk and other small of sources. aquatic species (food and supporting local livelihoods) Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Ecosystem Impact Rank on Rank on Rank on Comment Overall Annexes Service importance prevalence ability to rank value Climate Carbon sequestration by Medium High High Identified as an Must do regulation mangroves important benefit and one that has suitable data to support the assessment. Coastal Indirect coastal High Medium Low A number of potential Must do erosion protection benefits approaches to assess control & Reduced maintenance of this. More research Storm surge coastal dike protection needed to determine mitigation the most appropriate methods based on available data. Silt accretion (lower Low Low Low Possible benefit N/A issue) in terms of sand extraction, but difficult issue to quantify with limited information and methods. Natural Wind break services Medium Medium Low Methods, applicability Must do hazards and (sheltering) (damage to and data needs to be extreme buildings/agriculture, cost researched. events of removing sand, health issues). Applicable to Some research sandy forests. is understood to be available from ISPONRE. 129 130 Ecosystem Impact Rank on Rank on Rank on Comment Overall Service importance prevalence ability to rank value Recreation The main focus of this Medium High Medium Applicability of this Must do and tourism is on coastal wetland aspect will depend sites and mangrove eco- heavily on the type of tourism habitat, development of eco-tourism and local population. While we will need to review these, standard approaches are available for assessment. Biodiversity Appreciation and Medium High Low Valuation is difficult Could do preservation of species but important to diversity consider. Review of international studies is needed. Alternative approaches to quantification may be required if monetary valuations unavailable. Timber Construction wood Low High High Market values and Could do (used in south for approaches available construction) where from a range of forests are not protected studies to evaluate this ecosystem service. Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Ecosystem Impact Rank on Rank on Rank on Comment Overall Annexes Service importance prevalence ability to rank value Fuelwood Wood for fuel and Medium Low High A number of research Could do energy (charcoal) projects have valued (becoming less this ecosystem service important) using market values and estimates of extraction volumes. Habitat Supporting bee farming Low Low Medium Methods developed Could do by ISPONRE to assess this aspect. To be reviewed. Water Water quality and Medium Medium Low No specific research Could do purification nutrient filtering identified, but services by mangroves. need to consider. Believed to be a benefit, Value transfer from particularly in areas of international studies intensive aquaculture. may be needed. Aesthetic and Aesthetic, spiritual and Low Low Low Possible overlap with Not inspirational cultural values associated recreation. Links with required with mangroves historical sites and growing tourism. Unlikely to be significant impact. 131 132 Ecosystem Impact Rank on Rank on Rank on Comment Overall Service importance prevalence ability to rank value Cultural Supporting local Low Low Low Important for inland Not heritage livelihoods and tourism. forestry but unlikely required to be significant in mangroves. Disease Pest control Medium Medium Low The benefits of Not regulation offsetting the influence required of intensive fisheries may be important. General lack of evidence that requires additional research/ investigation. Educational Educational value of pilot Low Low Medium Educational benefits Not sites are likely to be highly required site specific and short term. Benefits may be included within recreational service. Genetic Genetic and medicinal Low Low Low Include in biodiversity Not resources plants required Include in direct use value (dye, medicine) Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Ecosystem Impact Rank on Rank on Rank on Comment Overall Annexes Service importance prevalence ability to rank value Nutrient Processing pollutants, Low Low Low Overlap with water Not Cycling absorb heavy metals and quality. required other toxic substances. Sense of Household valuations Low Low Medium Not believed to me Not place enhanced by coastal a major benefit of required protection/aesthetics coastal mangroves. Some benefits in specific protected habitats perhaps. Salinity Saline intrusion Low Low Low Mentioned as a Not possible risk but not required directly related to mangroves. Water Reduction in flood risk N/A N/A N/A Related to inland Not regulation woodland rather than required coastal woodlands. 133 I. Scoping exercise for addition of further ecosystem services Should efforts be made to expand the framework to encompass a wider range of ecosystem services, it is recommended that a scoping exercise be conducted to determine whether the service(s) of interest is (are) appropriate for economic valuation. Detailed below are a series of scoping questions for consideration when assessing the feasibility of a new service for inclusion within the coastal forest asset valuation framework. Table 0‑19. Ecosystem service scoping exercise Who are the The delivery of ecosystem services is highly spatially dependent. A mangrove beneficiaries? forest ecosystem which runs along the coastline of a densely populated area which is highly vulnerable to storm surges would likely have a significant natural hazard mitigation value, which should be accounted for as part of a natural capital accounting process. However, a mangrove system which buffers the coastline in an area which is remote from human population, even if it is highly susceptible to storm surges, will not have a hazard mitigation value. An ecosystem service, by its definition, must have beneficiaries to be scoped into an assessment. Can the Some services may be relevant to the coastal forest assets concerned; however, service be robust monetary evidence may not be sufficiently available to account for the quantified in service as part of an accounting process. This is likely to be the case for cultural physical and services e.g., spiritual services, which are highly subjective and difficult to monetize. monetary terms? Secondly, sufficient biophysical evidence may not be available to quantify the supply of the service delivered. Services such as water purification can be highly dependent on multiple localized factors, for example, the pollutant profile of the water source and the ecological functioning of the mangrove system. Ultimately, a wealth of data is needed to accurately assess the delivery of this service. In both cases, the available methods for monetizing the service, and thus the data requirements, should be reviewed to determine whether the service can be quantified. Is the service Ecosystem services assessed should be delivered by natural capital only. The delivered by delivery of some services may depend on inputs of human and manufactured the natural capital. For example, most of the foods we consume have been manufactured environment? and processed to add value. These inputs should not be accounted as part of a natural capital accounting process, only the contribution from the natural environment should be included. Only if this can be achieved, should the service be scoped into the assessment. Supporting Resilient Coastal Economies in Vietnam 134 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas J. Ecosystem service account examples J.1 Capture fisheries J.1.1 Quang Ninh Province The inland capture fisheries of the mangrove ecosystem in Quang Ninh Province include a variety of non-migratory mollusk and aquatic species. A series of statistical indicators were collated concerning capture fisheries production, as in the approach detailed in section 5.3.1 and Table 5‑2. These statistical indicators and their sources are described in the table below. Table 0‑20. Statistical indicator values for economic assessment of capture fishery services delivered by mangroves, Quang Ninh province Symbol Statistical indicator 2018 Value Data source AVGDAILYREV Average revenue from 200,000 Focus group capture fisheries in discussions conducted mangrove area (VND/day/ by Thuy et al. (2019) person), 15 days per month POPULATION Number of people in 372,018 Quang Ninh Statistics communes that have access Office/FORMIS to mangrove forest PERCENTUSERS Percentage of people 6.99% Expert interviews benefiting daily from capture fisheries in a commune COSTLABOR Cost of labor (minimum 2,760,000 Quang Ninh Statistics wage for Quang Ninh Office Province) (VND/month/ person) COSTEQUIPMENT Cost of equipment (VND/ 50,000 Expert interviews month/person) ρ Correlation parameter ρ 0.7 Literature (World (of mangroves – capture Bank, 1996, p. 57; fisheries) Nguyen, 2015) Total mangrove area (ha) 21,973 Extent account Exchange rate (Local 22,602.05 Period average Currency Units [LCU] per USD, period average) Annexes 135 Thuy et al. (2019) carried out focus group discussions and found that at least a single family member goes to the mangrove forest daily from 68-83 percent of communes’ households nearby mangrove areas to benefit from inland capture fisheries. The focus group discussions also revealed that the mean revenue obtained from the inland capture fisheries in mangrove areas was VND 200,000 per day per person. ISPONRE carried out a validation study in Dong Rui commune, Tien Yen District. This commune was chosen as a ‘typical’ commune with mangrove forest within Quang Ninh Province. The validation study revealed that 500 households of the commune’s 715 households usually benefit from the mangrove forest fisheries. This value is equivalent to 70 percent of households and is thus in line with the findings of 68-83 percent in Thuy et al. (2019). However, the study by ISPONRE found that there are around 200 persons per day on average in the mangrove forest, not 500. Accordingly, the percentage of people benefiting from the inland capture fisheries each day within the commune is 200 of the total commune population of 2,860 or 6.99 percent. The validation study did, however, confirm that mean revenue from capture fisheries was no less than VND 200,000 per day per person. It was also found that, on average, those benefiting from the fisheries work 15-20 days per month. In order to avoid overestimation, the lower bound value of 15 days per month is used in the value estimation calculation. To calculate the number of people living in communes that have access to mangrove forest, the relevant communes were identified using the FORMIS mangrove forest extent data. The population data for these identified communes was then obtained from the Quang Ninh Statistics Office. To account for opportunity costs of capture fisheries harvest (i.e., the potential earnings should that time be spent carrying out alternative renumerated practices), the minimum wage for Quang Ninh Province, VND 2,760,000, was obtained from the Quang Ninh Statistics Office. Additionally, the costs of equipment were accounted for, to obtain a true net benefit. Harvest in capture fisheries in mangrove forest in Quang Ninh required some simple hand tools, such as flashlights, hooks, and sticks, many of which are made by the local people themselves. The cost of equipment, therefore, is fairly low at VND 50,000 per person per month on average. To calculate the value of the capture fisheries service delivered by mangroves, the following formula, employing the statistical indicators listed in Table 0‑20, was applied. ρ *[AVGDAILYREV*15 – COSTLABOR – COSTEQUIPMENT]*POPULATION*PERCENTUSERS*12 Thus, the value of mangrove ecosystem in capture fisheries is VND 41.502 billion per year, equivalent to USD 1.84 million per year. On average, one hectare of mangrove generates a net benefit of VND 1.89 million per hectare per year, equivalent to USD 83.57 per hectare per year. Supporting Resilient Coastal Economies in Vietnam 136 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Box 10. Scale of the capture fisheries assessment While the example from the trial capture fisheries account in Quang Ninh employs the recommended approach presented in Section 5.3.1, the data employed is at the provincial scale. As in the recommended approach, it is suggested that efforts are made to obtain data at the district level for a more detailed level of assessment, which facilitates better integration into planning approaches (see Section 6.1). Theoretically, should statistical indicator data on the number of households and the number of households benefiting from capture fisheries be available, this approach would be transferrable to the commune level. However, this would require a significant data gathering efforts. J.1.2 Tam Giang - Cau Hai, TT-Hue Province Inland capture fisheries production at TGCH includes shrimp, fish, crab, oyster, squid and some seasonal aquatic products, with shrimp and fish being the most stable sources of income for local households. To estimate the value of TGCH capture fisheries, ISPONRE employed a direct value transfer. While this approach is included as an example, this is not a recommended approach for capture fisheries accounts in other provinces. Few provinces are likely to have up-to-date and reliable previous studies from which a benefit transfer can be carried out with an appropriate degree of validity. The benefit transfer in TGCH was employed due to: ● Ease of access to the data – the value transfer comes from a very recent ISPONRE study conducted in the area and thus the data can also be verified. ● The relatively small area of mangroves at the study site and resource constraints. ● Lack of available literature on the relationship between the wetland habitats present and the supporting of inland fisheries. Focusing only on shrimp and fish, Tuan et al. (2009) conducted a large survey of 1,189 households and for the year of 2005, estimated that capture fisheries created a net benefit of VND 10 million/ household/year. The net benefits were determined by subtracting the costs of catching (e.g., fuel, equipment depreciation and labor) from the benefits (measured by the market price of shrimp and fish). ISPONRE (2017) employed a similar method to assess the net benefits of capture fisheries within the TGCH lagoon area. Note that the method by ISPONRE (2017) only estimates the value of inland, lagoon fisheries and thus does not include sea catch. ISPONRE (2017) found the value of capture fisheries to be VND 43.78 million/household/year for the year of 2016, with 1,635 households involved in the capture. Accordingly, the total net benefit of capture fisheries was estimated at VND 71,587.31 million or USD 3.20 million, with a cost/benefit ratio of 0.42. While the cost/benefit ratio of capture fisheries tends to increase gradually and this was confirmed in the recent validation study by ISPONRE, the validation study also confirmed that the cost/benefit ratio was no more than 0.45 for capture fisheries in TGCH in the year of 2018. Annexes 137 The headline statistics concerning the value of capture fisheries in the TGCH lagoon area are summarized in the table below. Table 0‑21. Capture fisheries (Tam Giang - Cau Hai lagoon) headline statistics Statistical data Year of Year of Source 2016 2018 Production of inland 8,583 7,994 Thua Thien Hue Statistics Office (2019), capture fisheries (ton) validated in the meeting with Department of Agriculture and Rural Development Value of capture 8.34 ISPONRE (2017) fisheries (million VND/ ton) GDP deflator 147.415 158.625 World Bank (2020b) Cost/benefit ratio of 0.42 0.45 ISPONRE (2017), validated in the meeting capture fisheries with Department of Agriculture and Rural Development Water surface area of 21,600 lagoon (ha) Exchange rate (LCU 22,602.05 World Bank (2020c) per USD period average) Applying the GDP deflator to uplift the 2016 value from ISPONRE (2017), the value of capture fisheries in 2018 is estimated at VND 8.97 million per ton. Given that the production of inland capture fisheries in 2018 was 7,994 tons, the total value of capture fisheries in TGCH lagoon wetland is VND 71,706.18 million or USD 3.17 million. With a water surface area of 21,600 ha, this value can be disaggregated to VND 3.32 million/ha/yr of wetland or USD 146.9/ha/yr. While the approach taken here is valid in assessing the value of capture fisheries in the TGCH wetland, the relatively small area of mangrove forest means that the contribution of coastal forest assets to the value of this ecosystem service is negligible. Should there be little evidence that coastal forest assets directly contribute to local capture fisheries production in other provinces, the value of coastal forest assets, in terms of the delivery of this service, should assumed to be null. Supporting Resilient Coastal Economies in Vietnam 138 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas J.2 Aquaculture support J.2.1 Quang Ninh Province The presence of aquaculture farming inside mangrove forest in Quang Ninh is fairly limited, with a lack of official data on the production of such farming in the area. Overall, there are 60 intensive aquaculture farms over an area of 301.27 ha of Dong Rui commune, Tien Yen District. These farms generated an annual production of 357 tons with a net economic benefit of VND 13.06 billion (USD 595,200) in 2018 (Quang Ninh PPC, 2019). The expert interviews carried out by ISPONRE confirmed that the production costs of aquaculture farming comprise of two main categories of cost: ● Direct costs including seeds, feeds, electricity, and chemical inputs (direct costs account for 85 percent of the total costs); ● Depreciation costs of ponds. The average production cost, ascertained from the interviews, is approximately VND 150 million per ha of farm. Multiplying the value of aquaculture production inside mangrove ecosystems by the mangrove- aquaculture correlation factor of 0.5 (see section 5.4.1), the total value of aquaculture support services delivered by mangroves in Quang Ninh province would appear preliminarily to be VND 6.53 billion, or USD 297,600 in 2018. However, the validation study concluded that in reality, there is very little correlation between the presence of mangroves within the communes assessed and the production value of local aquaculture systems. This is because most of the aquaculture systems in the province are semi-intensive and intensive farming systems. Consequently, the artificial farming environment created has little reliance on the supporting value of the surrounding ecosystems due to the large quantity of artificial inputs (this is evidenced in the photos presented in Annex L. The contribution of mangroves to the production value from the aquaculture systems is therefore negligible. As such, to avoid over-estimation of the ecosystem service value, the correlation parameter of mangrove presence to aquaculture production is assumed to be 0. This was justified in the expert interviews. Accordingly, the value of aquaculture support from mangroves in Quang Ninh Province is VND 0. J.2.2 Tam Giang - Cau Hai lagoon, TT-Hue Province As in Annex J.1.2, a direct value transfer approach is used to estimate the value the support of the wetland ecosystem in facilitating the productivity of local aquaculture systems in TGCH. A benefit transfer approach is employed for the same reasons as listed in Section 5.2. As the approach is bespoke to the area (i.e., there are few such reliable and recent studies from which economic valuation evidence can be transferred for other provinces/study locations and it concerns the valuation of wetland ecosystem types other than coastal forest assets), we do not recommend the replication of this approach for the coastal forest asset aquaculture support accounts for other locations. Annexes 139 The ISPONRE (2017) economic valuation of the TGCH lagoon system estimated the aquaculture support of the lagoon wetland at VND 235.89 million per ha of aquaculture in 2016. Using a GDP deflator, this value was reassessed for the year of 2018 and estimated at VND 253.82 million per hectare per year, or USD 11,200 per hectare per year. Below is a summary of the statistics which underpin the valuation approach. Table 0‑22. Aquaculture support (Tam Giang - Cau Hai lagoon) headline statistics Statistical data Year of 2016 Year of 2018 Source GDP deflator 147.415 158.625 World Bank (2020b) Area of aquaculture 6,799 4,200 ISPONRE (2017), validated (ha) in the meeting with Department of Agriculture and Rural Development Exchange rate (LCU N/A 22,602.05 World Bank (2020c) per USD, period average) With the total area for aquaculture in the lagoon of 7.375 ha in 2018 (Thua Thien Hue Statistics Office, 2019), the total value of the service is estimated at VND 1,871.9 billion, or USD 82.82 million. J.3 Carbon storage J.3.1 Quang Ninh Province and Tam Giang - Cau Hai lagoon, TT-Hue Province Firstly, the appropriate biomass estimates for transferring to coastal forest assets in Quang Ninh and TGCH were selected from Table 5‑5 using the four criteria presented in section 5.5.1. Average total biomass and biomass increment values selected from Table 5‑5 were converted to estimates of carbon stock and carbon increment using the IPCC carbon fraction factor (0.47), with the results presented in the table below. Supporting Resilient Coastal Economies in Vietnam 140 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Table 0‑23. Carbon stock and increment estimates for mangrove species in Quang Ninh and Tam Giang - Cau Hai, TT-Hue province # Species Applicable Average total SD Biomass SD province carbon stock carbon (tC/ha) increment (tC/ha/yr) 1 Protection Quang Ninh mangroves 29.0 N/A 1.7 N/A 2 Production Quang Ninh mangroves 25.0 N/A 1.1 N/A 3 Special use Quang Ninh mangroves 22.0 N/A 1.6 N/A 4 Kandelia Thua Thien Hue 34.12 16.64 3.15 1.22 obovata 5 Senneratia Quang Ninh and 66.04 52.88 6.35 4.79 caseolaris Thua Thien Hue 6 All mangrove Quang Ninh and 33.08 12.5 1.5 0.25 species Thua Thien Hue 7 Casuarina Quang Ninh and 45.0 34.7 2.8 1.2 equisetifolia Thua Thien Hue 8 Acacia Thua Thien Hue 37.2 13.1 3.4 1.1 crassicarpaa By applying the relevant values from Table 5‑5 to the respective areas of mangrove and sandy forest identified within the extent accounts, it was determined that in Quang Ninh, total carbon stock for existing coastal forest in 2018 was 2.3 million tons of carbon dioxide equivalent (tCO2e). Correspondingly, the annual carbon sequestration rate is 120,777 tCO2e. Details of the carbon stock and sequestration rates by commune and district are provided in the summary tables in Annex M. In TT-Hue, total carbon storage of coastal forest is 1.2 million tCO2e and annual carbon sequestration is 52,815 tCO2e. Details of the carbon stock and sequestration rates by commune and district are provided in the summary tables in Annex N. The table below summarizes the carbon stock and sequestration values for the various forest types for both Quang Ninh and TT-Hue Provinces. Annexes 141 Table 0‑24. Carbon stock and sequestration of coastal forests in Quang Ninh and TT-Hue Category Coastal forest types Quang Ninh Thua Thien Hue (tCO2e) (tCO2e) Carbon storage by Total 2,352,661 1,263,129 forest type Mangrove forests 2,332,757 567,920 Forest on sandy area 19,904 695,209 Carbon storage by Total 2,352,661 1,263,129 forest function Protection mangroves 2,017,781 153,084 Production mangroves 312,556 414,835 Special use mangroves 2,420 0 Protection forest on sands 19,904 695,209 Annual Total 120,777 52,815 sequestration Mangrove forests 118,167 378 Forest on sandy area 2,610 52,437 Applying a value of USD 5 tCO2e, the carbon stock and sequestration estimates were monetized. In Quang Ninh, the total carbon storage value of coastal forests is USD 11.7 million and the annual value of carbon sequestration is USD 0.6 million. These figures for coastal forests in TT-Hue are USD 6.3 and 0.3 million, respectively. In Quang Ninh, the highest carbon value is recorded in protection mangroves (86 percent), followed by production mangroves (13 percent). Forests on sandy areas account for 1 percent of the total value. However, in TT-Hue, the highest carbon value is generated by protection forests in sandy areas (55 percent), followed by production mangroves (33 percent) and protection mangroves (12 percent). The full summary of these values is provided in the table below and Figure 0‑15 presents a summary of the proportional contribution of each forest type to the total value in each province. Supporting Resilient Coastal Economies in Vietnam 142 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Table 0‑25. Estimated value of coastal forest carbon storage and sequestration in Quang Ninh and TT-Hue Provinces Category Coastal forest types Carbon value Thua Thien Hue Quang Ninh (USD) (USD) Carbon storage by Total 11,763,305 6,315,645 forest type Mangrove forests 11,663,785 2,839,600 Forest on sandy area 99,520 3,476,045 Carbon storage by Total 11,763,305 6,315,645 forest function Protection mangroves 10,088,905 765,420 Production mangroves 1,562,780 2,074,175 Special use mangroves 12,100 0 Protection forest on 99,520 3,476,045 sands Annual sequestration Total 603,885 264,075 Mangrove forests 590,835 1,890 Forest on sandy area 13,050 262,185 1% 13% 12% 55% 33% 86% Protection mangrove Production mangrove Protection forest on sandy areas Figure 0‑15. Carbon value share among the coastal forest function types in Quang Ninh (left) and TT-Hue (right) Provinces Annexes 143 Box 11. Scale of the carbon storage assessment While the carbon storage account applies average carbon stock and sequestration values for all mangroves to mangrove areas, the recommended approach presented in Section 5.5.1 recommends that the species-level estimates of these values are used where possible. Currently, species-level spatial data is only available for planted forest areas in the FORMIS datasets (see Section 4.1.1), which limits the application of species-level estimates. Should resource constraints permit, it is recommended that efforts are made to collate species-level spatial data for coastal forest areas across Vietnam to refine the level of analysis as this would facilitate the identification of higher-value mangrove areas (in terms of carbon storage services) and the integration of ecosystem values into planning processes (see Sections 6 and 7). Box 12. Carbon storage values We recognize that the carbon storage values would be much changed were a different carbon pricing approach to be applied. If the 2018 ‘high’ shadow price of carbon (USD 77, World Bank, 2017) were to be employed, the carbon storage and sequestration values for Quang Ninh Province would be USD 180.2 million and 9.2 million, respectively. For TGCH, TT- Hue, these values would be 97.0 million and 4.6 million. Alternatively, if the ‘low’ shadow price of carbon for 2018 (USD 38, World Bank, 2017) were to be employed, the carbon storage and sequestration values for Quang Ninh Province would be USD 88.9 million and 4.6 million, respectively. For TGCH, TT-Hue, these values would be 47.9 million and 2.3 million. Nonetheless, we stand by the conservative carbon price of USD 5 employed in the REDD+ emissions trading scheme for the valuation of carbon storage services. J.4 Coastal protection J.4.1 Quang Ninh Province and Tam Giang - Cau Hai, TT-Hue Province The approach taken to the estimation of coastal protection services in both Quang Ninh and TGCH was the benefit transfer methodology detailed in Section P.1.3. The study locations of each of the coastal protection values presented in Table 0‑34 were reviewed in terms of their similarity of the features of coastal forest assets to the study locations to which values were to be transferred (Quang Ninh and TGCH). Based on this similarity, the mean protective values of mangroves in Nam Dinh and forests on sandy areas in Ninh Thuan and Binh Thuan are used for transferring to the respective forest types in Quang Ninh and TT-Hue provinces. These mean values are summarized as follows: ● The average protective value of mangrove forests in Nam Dinh is USD 712.2/ha/yr (USD 68.7 – 1,886.5/ha/yr). Supporting Resilient Coastal Economies in Vietnam 144 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas ● The average protective value of mangroves in the South (Ca Mau and Ho Chi Minh City) is 3,578.3 (504.6 – 3,896.6) USD/ha/year. ● The average protective value of coastal forest on sandy area is USD 646/ha/yr (USD 645.9 – 800.7/ha/yr). Accordingly, the estimates of the annual protective value of coastal forests for Quang Ninh and TT- Hue Provinces are USD 12.9 million and USD 3.0 million, respectively. A summary of the results is provided in the table below. Table 0‑26. Economic value of coastal protection services delivered by coastal forest assets, Quang Ninh and Tam Giang - Cau Hai, TT-Hue province Coastal forest type State Quang Ninh Thua Thien Hue (USD) (USD) Mangroves Natural forests 12,541,842 0 Planted forests 3,107,329 49,142 Total 15,649,171 49,142 Sandy forests Natural forests 0 0 Planted forests 285,532 2,979,998 Total 285,532 2,979,998 Mangroves + Sandy forests Total 15,934,703 3,029,140 J.5 Recreation and tourism The preliminary analysis showed that there was no official tourism in the mangrove forest in Quang Ninh province because there was no data available on tourism. As such, the ZTCM was applied to calculate the value of tourism services delivered by the natural capital assets in the TGCH lagoon system, TT-Hue Province. J.5.1 Tam Giang - Cau Hai lagoon, TT-Hue Province Following the four-step process detailed in Section 5.7.1, questionnaires were first designed to ascertain information on the TC of visitors, which did not require in excess of 15 minutes for respondents to complete. It should be noted that, as per the recommended approach, information was obtained from visitors on their individual transportation costs, opportunity costs and additional charges. However, in Annexes 145 the additional charges, consumption expenditures were excluded and as there is no entrance fee nor parking fee for the site, these were not included. The formula from Scott Smith (2013) was employed, as per the recommended approach, to determine the appropriate sample size for the survey process. According to data reported by the Department of Culture, Sports and Tourism, which was obtained during the validation trip to TGCH lagoon, in 2019, 100,000 visitors were recorded for the lagoon system. As such, this was the value assumed for the population variable in the equation. Consequently, the preliminary sample size was 383. At a confidence level of 95 percent and a margin of error of 5 percent, the sample size was determined to be 385. The average costs for visitors from each of the departure zones are detailed in the table below: Table 0‑27. Average visitor TCs from each departure zone Zone Average Travel time Transport Time costs Other costs distance (days) cost (VND) (VND) (VND) (km) 1 <60 1.49 104,103 290,550 343,570 2 60-120 1.22 180,370 283,040 150,500 3 120-150 1.00 225,500 250,000 102,500 4 150-180 1.00 255,945 245,000 100,000 The results illustrate that the farther the departure zone, the greater the transportation cost. The analysis results also showed that time cost, additional charge at the site and other costs do not depend on distance and location. As per the recommended approach, the basic demand function was calculated by plotting the VR against the average TC for each zone. The method of ordinary least square (OLS) was used for the estimation of the linear regression model. The linear function was constructed as follows: V = β * TCi + e V = ‒0.000204 * TC + 118.72 V = 344,375 Supporting Resilient Coastal Economies in Vietnam 146 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas The linear function has: V = total number of visitors with the travel cost in the current four zones β = - 0.000204 <0. The negative sign of this variable’s coefficient suggests a downward slope in the demand curve, i.e., VR declines as TC increases, which is consistent with theory and practice. e = 118.72 stands for the remaining elements that were not mentioned in the model. The correlation coefficient R2 = 0.8978 shows that the independent variable explained 89.78 percent of the dependent variable value, and the error cause of other factors (interference) was 10.22 percent. The P-value ≈ 0.05. It implies that the assumption of the linear function was appropriate and the confidence interval of this model (between TC and VR) was found to be 95 percent. Considering that the TC of all zones change in an amount of ∆TC , the number of visitors (V) to the TGCH lagoon was then estimated using the following equation: 4 4 V = ∑VRi * Pi = ∑[―0.000204 * (TCi + ΔTC)] + 118.72 * Pi i=1 i It was calculated from the equation that the number of visitors to the National Park equals the total number of visitors from each zone. If the calculated number of visitors from a certain zone returns a negative number, it means that there are no visitors from that area to the National Park (the actual travel cost exceeded the demand price, so the number of visitors from the zone was equal to 0, not a negative number of visitors). The increased level of ∆TC represents the relationship between the increased costs and the number of visitors to TGCH lagoon, which is the relationship between the price and quantity demanded. The function that expressed this relationship is the function for visits to TGCH lagoon. The OLS regression method was used to establish this demand function: V = β * ∆TC + e V = ‒2.4923 * ∆TC + 320105.6 β = - 2.4923 e = 320105.6 The correlation coefficient R2 = 0.9796 shows that the independent variable explained 97.96 percent of the dependent variable value. The error associated with other factors (interference) was 2.04 percent. The P-value ≈ 0.000<0.01 represents that the assumption of the linear function was appropriate and the confidence interval of this model, between the travel cost and visitation rate was to 95 percent. Annexes 147 The total value of tourism in TGCH lagoon was measured by the whole area under the demand curve for visits to the lagoon and above the horizontal axis. This area was also the area below the demand curve and above the original TC. This was also the consumer surplus of visitors. The total consumer surplus of visitors was estimated at VND 20.56 billion per year. With 100,000 visitors in 2018, the consumer surplus of each visitor was VND 120,800. The average travel cost of a visitor was VND 458,627. Accordingly, the total annual value of tourism in TGCH lagoon was VND 458,627*100,000 + VND 20.56 billion = VND 66.42 billion. Thus, the lagoon provided supporting services for tourism with a total value at VND 66.42 billion per year, equivalent to USD 2.844 million per year. The total area of the TGCH lagoon (including water surface area and area of 33 communes surrounding the lagoon) is 99,789 hectares (Thua Thien Hue Statistics Office, 2019). Thus, the value of tourism was VND 665,640 per hectare per year, equivalent to USD 29.45 per hectare per year, on average. Photo: Jeroen Mikkers - shutterstock.com Supporting Resilient Coastal Economies in Vietnam 148 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas K. Summary values for Pilot Accounts In this section, summary values from the pilot ecosystem service accounts for both Quang Ninh Province and TGCH are presented. These summary (total) values can be used to develop maps of high and low value areas in terms of coastal forest asset delivery, as detailed in Sections 6 and 7. It is recommended that the approach taken in this section, for the trial ecosystem accounts, is followed to aggregate and summarize the results of the economic assessment when this framework is applied to other provinces. While the sum values in this section are aggregated at the provincial level, the same approach can be taken to the summary of district-level data or data at a finer scale (i.e., commune level), should it be available. Aggregating the ecosystem service values at this finer scale, and developing high and low value area maps with a higher level of granularity, will better facilitate the development of coastal setback lines and the integration of values into planning processes. This is further discussed in Sections 6 and 7. K.1 Sum ecosystem service values, Quang Ninh Province and Tam Giang - Cau Hai The table below summarizes the annual economic value of each of the ecosystem services assessed in Quang Ninh and TGCH, TT-Hue Province. Figure 0‑16 also illustrates this, graphically. The aggregate value of these services is also reported. The following points should be considered when interpreting these summary values: ● The capture fisheries value for TGCH captures the monetary value of fishery systems within the lagoon system (regardless of the presence of coastal forest systems), due to the benefit transfer approach applied. As such, this value does not reflect a service delivered by coastal forest (mangrove) assets, which would be negligible due to the small area of mangroves in this area. ● The above also applies to aquaculture services for TGCH lagoon, with no correlation factor included in the calculation to identify the contribution of natural capital assets. ● In contrast, there are aquaculture systems present in Quang Ninh; however, these intensive and semi-intensive systems have a minimal (or zero) reliance on mangrove support due to the artificial inputs into these systems. Thus, the value of aquaculture support from coastal forests is negligible. ● There is no official tourism in Quang Ninh Province and thus this service has not been valued in this location, while in TGCH lagoon, the ZTCM is successfully applied. ● As the values represent an annual aggregate value of the services delivered, the carbon storage included within the summary tables does not include the economic value of the carbon stocks comprised of the existing coastal forest biomass. The carbon storage value represents the annual carbon increment (sequestration) value only. ● The carbon storage values are fairly modest. Were a higher price of carbon to be used, for example the World Bank Shadow Price of Carbon (World Bank, 2017), these values would be much greater relative to the values of the other ecosystem services (see Box 12). Annexes 149 Table 0‑28. Summary values of coastal forest ecosystem services, Quang Ninh and Tam Giang - Cau Hai (USD thousands) Ecosystem service Quang Ninh TGCH, TT-Hue Provisioning services (capture 1,836 85,994 fisheries and aquaculture support, per year) Carbon storage 11,763 6,316 Carbon sequestration (per 604 264 year) Coastal protection (per year) 15,935 3,029 Cultural services (tourism, per 0 847 year) Total 30,138 96,450 100 90 80 Ecosystem service value 70 (USD thous./year) 60 50 40 30 20 10 0 Quang Ninh TGCH Capture fisheries and Aquaculture Carbon sequestration Coastal protection Recreation and tourism Note: Carbon storage is omitted because the value is not USD/year and therefore not comparable. Figure 0‑16. Summary values of coastal forest ecosystem services, Quang Ninh and Tam Giang - Cau Hai Supporting Resilient Coastal Economies in Vietnam 150 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas The total value of coastal forest ecosystem services in TGCH lagoon clearly outweighs that in Quang Ninh province. However, as explained above, the value of many of these ‘coastal forest’ services in the TGCH lagoon system are inflated due to the benefit transfer approaches applied. This includes the value of aquaculture support, which accounts for most of the total value of services in TGCH lagoon and does not distinguish the contribution of natural capital assets from the total value of aquaculture systems in the region. Figure 0‑17 is presented below to give a clearer breakdown of the total value of individual ecosystem services delivered by coastal forest assets in Quang Ninh province – as the value of each of these services was determined using the ‘recommended’ approaches for the assessment of these services, with the exception of coastal protection values. 18 16 14 12 Ecosystem service value (USD thous./year) 10 8 6 4 2 0 Capture fisheries and Carbon Coastal Recreation and Aquaculture sequestration protection tourism Note: Carbon storage is omitted because the value is not USD/year and therefore not comparable. Figure 0‑17. Annual value of coastal forest ecosystem services, Quang Ninh Province Annexes 151 Coastal protection services represent the highest value services delivered by coastal forest assets in Quang Ninh Province, with an annual value of USD 15.9 million. This is followed by a substantial drop down to an annual value of USD 1.8 million for capture fisheries and aquaculture support. It should be kept in mind, however, that the coastal protection value of mangroves is estimated through a value transfer and thus the result relies on a greater degree of assumption compared to the bespoke approaches developed for the assessment of the other services in Quang Ninh. The annual carbon storage value of coastal forests is Quang Ninh is USD 0.6 million; however, were the value of the carbon stocks within existing biomass to be accounted for, which have a value equivalent to USD 11.7 million, this value of this service would be substantially higher. Aquaculture and recreation and tourism services were not assessed for Quang Ninh Province. The five key services from coastal forest assets in Quang Ninh Province combine to deliver an annual sum value of approximately USD 30.1 million. Box 13. Welfare-based and exchange values We recognize that while the approaches taken to value the capture fisheries, aquaculture, carbon storage and coastal protection services have measured the value of these services as an exchange value, the ZTCM approach to estimating the value of recreation and tourism services does so by estimating a consumer surplus, or welfare-based measure. Welfare-based measures are not compatible with exchange values and thus cannot be directly compared. We, however, include the welfare-based recreation and tourism values within the summary of accounts, as demonstrating these potential values is valuable in a policy context (see Section 6). According to Smith et al. (2017), policy audiences are, “less conscious of the need to be fully aligned with SNA concepts of exchange value,” (pg. 4) and recognize the value of “soft” natural capital accounting estimates, which make use of welfare estimates to the detriment of being compatible with the SNA, which requires values to be based on exchange values. Thus, while the recreation and tourism values are included here, this point may need to be considered should the aim be to integrate the output values from this framework into national wealth accounts. Supporting Resilient Coastal Economies in Vietnam 152 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas L. Intensive and semi-intensive aquaculture farming, Quang Ninh Province Annexes 153 Supporting Resilient Coastal Economies in Vietnam 154 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas M. Carbon storage and sequestration estimates for Quang Ninh Communes Annexes ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 1 Thành phố Hà Khánh 38,695 880 0 0 39,575 2,009 0 2,009 Hạ Long 2 Thành phố Hà Phong 2,212 2,356 0 0 4,568 250 0 250 Hạ Long 3 Thành phố Hà Khẩu 0 3,144 0 0 3,144 184 0 184 Hạ Long 4 Thành phố Cao Xanh 0 0 0 0 0 0 0 0 Hạ Long 5 Thành phố Giếng Đáy 0 0 0 0 0 0 0 0 Hạ Long 6 Thành phố Hà Tu 0 0 0 0 0 0 0 0 Hạ Long 7 Thành phố Hà Trung 0 0 0 0 0 0 0 0 Hạ Long 8 Thành phố Hà Lầm 0 0 0 0 0 0 0 0 Hạ Long 155 156 ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 9 Thành phố Bãi Cháy 0 0 0 0 0 0 0 0 Hạ Long 10 Thành phố Cao 0 0 0 0 0 0 0 0 Hạ Long Thắng 11 Thành phố Hùng 0 0 0 0 0 0 0 0 Hạ Long Thắng 12 Thành phố Yết Kiêu 0 0 0 0 0 0 0 0 Hạ Long 13 Thành phố Trần 0 0 0 0 0 0 0 0 Hạ Long Hưng Đạo 14 Thành phố Hồng Hải 0 0 0 0 0 0 0 0 Hạ Long 15 Thành phố Hồng Gai 0 0 0 0 0 0 0 0 Hạ Long 16 Thành phố Bạch 0 0 0 0 0 0 0 0 Hạ Long Đằng Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual Annexes protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 17 Thành phố Hồng Hà 0 0 0 0 0 0 0 0 Hạ Long 18 Thành phố Tuần 0 0 0 0 0 0 0 0 Hạ Long Châu 19 Thành phố Việt Hưng 0 0 0 0 0 0 0 0 Hạ Long 20 Thành phố Đại Yên 0 16,243 0 0 16,243 953 0 953 Hạ Long 21 Thành phố Ninh 4,275 0 0 0 4,275 216 0 216 Móng Cái Dương 22 Thành phố Trà Cổ 38,971 0 0 50 39,021 1,965 6 1,972 Móng Cái 23 Thành phố Hải Đông 104,749 403 0 0 105,152 5,321 0 5,321 Móng Cái 24 Thành phố Hải Tiến 64,183 0 0 0 64,183 3,246 0 3,246 Móng Cái 157 158 ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 25 Thành phố Hải Yên 94,594 248 0 0 94,842 4,799 0 4,799 Móng Cái 26 Thành phố Quảng 90,266 541 0 0 90,807 4,596 0 4,596 Móng Cái Nghĩa 27 Thành phố Hải Hoà 50,019 14,520 0 0 64,539 3,381 0 3,381 Móng Cái 28 Thành phố Hải Xuân 6,986 0 0 0 6,986 353 0 353 Móng Cái 29 Thành phố Vạn Ninh 176,886 11,018 0 0 187,904 9,592 0 9,592 Móng Cái 30 Thành phố Bình Ngọc 15,705 2,466 0 3,830 22,001 481 502 983 Móng Cái 31 Thành phố Vĩnh 36,472 3,153 0 1,580 41,205 1,841 207 2,048 Móng Cái Trung 32 Thành phố Vĩnh Thực 4,636 266 0 2,097 6,999 0 275 275 Móng Cái Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual Annexes protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 33 Thành phố Cửa Ông 0 0 0 0 0 0 0 0 Cẩm Phả 34 Thành phố Cẩm Sơn 0 0 0 0 0 0 0 0 Cẩm Phả 35 Thành phố Cẩm 0 0 0 0 0 0 0 0 Cẩm Phả Đông 36 Thành phố Cẩm Phú 0 0 0 0 0 0 0 0 Cẩm Phả 37 Thành phố Quang 3,339 0 0 0 3,339 169 0 169 Cẩm Phả Hanh 38 Thành phố Cẩm 0 0 0 0 0 0 0 0 Cẩm Phả Thịnh 39 Thành phố Cẩm Thủy 0 0 0 0 0 0 0 0 Cẩm Phả 40 Thành phố Cẩm 0 0 0 0 0 0 0 0 Cẩm Phả Thạch 159 160 ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 41 Thành phố Cẩm 0 0 0 0 0 0 0 0 Cẩm Phả Thành 42 Thành phố Cẩm 0 0 0 0 0 0 0 0 Cẩm Phả Trung 43 Thành phố Cẩm Bình 0 0 0 0 0 0 0 0 Cẩm Phả 44 Thành phố Cộng Hòa 96,700 7,929 0 0 104,629 5,356 0 5,356 Cẩm Phả 45 Thành phố Cẩm Hải 851 0 0 0 851 43 0 43 Cẩm Phả 46 Thành phố Yên 7,890 605 0 0 8,495 435 0 435 Uông Bí Thanh 47 Thành phố Phương 32 0 0 0 32 2 0 2 Uông Bí Nam 48 Tiên Yên Đông Ngũ 6,986 8,846 0 0 15,832 872 0 872 49 Tiên Yên Đông Hải 86,119 15,446 0 0 101,565 5,262 0 5,262 Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas 50 Tiên Yên Hải Lạng 55,304 3,538 0 0 58,842 3,005 0 3,005 ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual Annexes protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 51 Tiên Yên Tiên Lãng 35,271 2,521 0 0 37,792 1,932 0 1,932 52 Tiên Yên Đồng Rui 179,937 9,983 0 0 189,920 9,686 0 9,686 53 Đầm Hà Tân Bình 52,454 10,542 0 0 62,996 3,272 0 3,272 54 Đầm Hà Dực Yên 0 1,705 0 0 1,705 100 0 100 55 Đầm Hà Đầm Hà 43,522 7,682 0 0 51,204 2,652 0 2,652 (Xã) 56 Đầm Hà Tân Lập 24,340 13,081 0 0 37,421 1,998 0 1,998 57 Đầm Hà Đại Bình 97,635 11,486 0 0 109,121 5,612 0 5,612 58 Hải Hà Quảng Hà 0 0 0 0 0 0 0 0 59 Hải Hà Quảng 5,030 92 0 0 5,121 260 0 260 Thành 60 Hải Hà Quảng 11,495 3,126 0 27 14,647 761 4 765 Thắng 61 Hải Hà Quảng 17,747 92 0 0 17,839 903 0 903 Minh 161 162 ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 62 Hải Hà Đường 20,108 101 0 0 20,208 1,023 0 1,023 Hoa 63 Hải Hà Quảng 80,154 9,185 0 14 89,353 4,590 2 4,592 Phong 64 Hải Hà Quảng 0 0 0 0 0 0 0 0 Trung 65 Hải Hà Phú Hải 0 0 0 0 0 0 0 0 66 Hải Hà Quảng 0 5,363 0 0 5,363 315 0 315 Điền 67 Hải Hà Tiến Tới 6,816 733 0 0 7,549 388 0 388 68 Hải Hà Cái Chiên 787 4,620 0 2,093 7,499 60 274 335 69 Vân Đồn Cái Rồng 0 0 0 0 0 0 0 0 70 Vân Đồn Đài 114,734 248 0 0 114,981 5,817 0 5,817 Xuyên 71 Vân Đồn Bình Dân 60,344 0 0 0 60,344 3,052 0 3,052 Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual Annexes protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 72 Vân Đồn Vạn Yên 1,765 257 0 0 2,022 104 0 104 73 Vân Đồn Minh 946 477 2,420 198 4,041 213 26 239 Châu 74 Vân Đồn Đoàn Kết 11,856 220 0 0 12,076 613 0 613 75 Vân Đồn Hạ Long 0 963 0 347 1,309 15 45 60 76 Vân Đồn Đông Xá 0 0 0 0 0 0 0 0 77 Vân Đồn Bản Sen 10,006 312 0 0 10,318 524 0 524 78 Vân Đồn Thắng Lợi 532 0 0 0 532 27 0 27 79 Vân Đồn Quan Lạn 57,282 3,236 0 3,051 63,569 2,722 400 3,122 80 Vân Đồn Ngọc 8,847 2,209 0 2,102 13,158 326 276 601 Vừng 81 Hoành Bồ Trới 0 0 0 0 0 0 0 0 82 Hoành Bồ Vũ Oai 0 1,018 0 0 1,018 60 0 60 163 164 ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 83 Hoành Bồ Thống 43,533 3,529 0 0 47,062 2,409 0 2,409 Nhất 84 Hoành Bồ Lê Lợi 11,452 0 0 0 11,452 579 0 579 85 Quảng Yên Quảng 1,319 0 0 0 1,319 67 0 67 Yên 86 Quảng Yên Đông Mai 0 248 0 0 248 15 0 15 87 Quảng Yên Minh 383 7,682 0 0 8,064 470 0 470 Thành 88 Uông Bí City Điền 5,604 0 0 0 5,604 283 0 283 Công 89 Quảng Yên Sông 0 3,208 0 0 3,208 188 0 188 Khoai 90 Quảng Yên Hiệp Hòa 0 2,301 0 0 2,301 135 0 135 91 Quảng Yên Cộng Hòa 0 0 0 0 0 0 0 0 92 Quảng Yên Tiền An 0 0 0 0 0 0 0 0 Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual Annexes protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 93 Quảng Yên Hoàng 2,488 35,860 0 0 38,348 2,230 0 2,230 Tân 94 Quảng Yên Tân An 0 1,943 0 0 1,943 114 0 114 95 Quảng Yên Yên Giang 2,478 394 0 0 2,872 148 0 148 96 Quảng Yên Nam Hoà 7,156 0 0 0 7,156 362 0 362 97 Quảng Yên Hà An 18,364 14,758 0 0 33,122 1,795 0 1,795 98 Quảng Yên Cẩm La 691 0 0 0 691 35 0 35 99 Quảng Yên Phong Hải 3,147 0 0 0 3,147 159 0 159 100 Quảng Yên Yên Hải 3,381 788 0 0 4,170 217 0 217 101 Quảng Yên Liên Hòa 15,301 3,575 0 0 18,876 984 0 984 102 Quảng Yên Phong 38,408 8,140 0 0 46,548 2,419 0 2,419 Cốc 103 Quảng Yên Liên Vị 5,030 44,156 0 0 49,185 2,845 0 2,845 104 Quảng Yên Tiền 8,794 4,794 0 0 13,588 726 0 726 Phong 165 166 ID District Com‑ Carbon Carbon Carbon Carbon Total Annual Annual Total mune storage in storage in storage storage carbon carbon carbon annual protection production in spe‑ in sandy stor‑ seques‑ seques‑ carbon mangroves mangroves cial-use forests age in tration tra‑ seques‑ (tCO2e) (tCO2e) forest (tCO2e) coastal in man‑ tion in tra‑ man‑ forests groves sandy tion in groves (tCO2e) (tCO2e/ forests coastal (tCO2e) year) (tCO2e/ forests year) (tCO2e/ year) 105 Cô Tô Cô Tô 2,552 0 0 324 2,876 91 42 133 106 Cô Tô Đồng 19,980 330 0 4,091 24,401 541 536 1,077 Tiến 107 Cô Tô Thanh Lân 245 0 0 104 348 0 14 14 Total 2,017,781 312,556 2,420 19,904 2,352,661 118,167 2,610 120,777 Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas N. Carbon storage and sequestration estimates for TT-Hue Annexes ID District Commune Carbon Carbon Carbon Carbon Total Annual Annual Total storage storage storage storage carbon carbon carbon annual in pro‑ in pro‑ in spe‑ in sandy stor‑ seques‑ seques‑ carbon tection duction cial-use forests age in tration tration seques‑ man‑ man‑ forest (tCO2e) coastal in man‑ in sandy tration in groves groves man‑ forests groves forests coastal (tCO2e) (tCO2e) groves (tCO2e) (tCO2e/ (tCO2e/ forests (tCO2e) year) year) (tCO2e/ year) 1 Hương Trà Hải Dương 22,633 0 0 28,121 50,754 0 2,121 2,121 2 Hương Trà Hương Phong 1,589 0 0 0 1,589 72 0 72 3 Phong Điền Điền Hải 0 23,240 0 28,874 52,114 0 2,178 2,178 4 Phong Điền Điền Hòa 6,501 25,605 0 39,890 71,997 0 3,009 3,009 5 Phong Điền Điền Hương 10,977 23,519 0 42,844 77,340 0 3,232 3,232 6 Phong Điền Điền Lộc 9,861 27,946 0 46,973 84,780 0 3,543 3,543 7 Phong Điền Điền Môn 22,233 32,167 0 67,589 121,989 0 5,098 5,098 8 Phong Điền Phong Bình 7,302 4,803 0 15,040 27,145 0 1,134 1,134 9 Phong Điền Phong 4,100 117,885 0 151,559 273,544 0 11,431 11,431 Chương 10 Phong Điền Phong Hải 1,371 4,148 0 6,857 12,376 0 517 517 11 Phú Lộc Lộc An 0 0 0 0 0 0 0 0 167 168 ID District Commune Carbon Carbon Carbon Carbon Total Annual Annual Total storage storage storage storage carbon carbon carbon annual in pro‑ in pro‑ in spe‑ in sandy stor‑ seques‑ seques‑ carbon tection duction cial-use forests age in tration tration seques‑ man‑ man‑ forest (tCO2e) coastal in man‑ in sandy tration in groves groves man‑ forests groves forests coastal (tCO2e) (tCO2e) groves (tCO2e) (tCO2e/ (tCO2e/ forests (tCO2e) year) year) (tCO2e/ year) 12 Phú Lộc Lộc Bổn 0 0 0 0 0 0 0 0 13 Phú Lộc Lộc Bình 0 315 0 392 707 0 30 30 14 Phú Lộc Lộc Điền 0 0 0 0 0 0 0 0 15 Phú Lộc Lộc Sơn 0 0 0 0 0 0 0 0 16 Phú Lộc Lộc Trì 0 0 0 0 0 0 0 0 17 Phú Lộc Lộc Vĩnh 0 10,189 0 12,659 22,847 0 955 955 18 Phú Lộc Lăng Cô 0 509 0 633 1,142 0 48 48 19 Phú Lộc Phú Lộc 0 0 0 0 0 0 0 0 20 Phú Lộc Vinh Giang 0 667 0 829 1,496 0 63 63 21 Phú Lộc Vinh Hải 1,686 0 0 2,095 3,781 0 158 158 22 Phú Lộc Vinh Hiền 2,159 388 0 3,180 5,727 0 240 240 23 Phú Lộc Vinh Hưng 0 0 0 0 0 0 0 0 24 Phú Lộc Vinh Mỹ 4,233 9,716 0 17,331 31,279 0 1,307 1,307 Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas ID District Commune Carbon Carbon Carbon Carbon Total Annual Annual Total storage storage storage storage carbon carbon carbon annual Annexes in pro‑ in pro‑ in spe‑ in sandy stor‑ seques‑ seques‑ carbon tection duction cial-use forests age in tration tration seques‑ man‑ man‑ forest (tCO2e) coastal in man‑ in sandy tration in groves groves man‑ forests groves forests coastal (tCO2e) (tCO2e) groves (tCO2e) (tCO2e/ (tCO2e/ forests (tCO2e) year) year) (tCO2e/ year) 25 Phú Vang Phú An 0 0 0 0 0 0 0 0 26 Phú Vang Phú Đa 0 1,892 0 2,351 4,243 0 177 177 27 Phú Vang Phú Diên 9,643 0 0 11,981 21,623 0 904 904 28 Phú Vang Phú Hải 1,504 0 0 1,869 3,373 0 141 141 29 Phú Vang Phú Mỹ 0 0 0 0 0 0 0 0 30 Phú Vang Phú Thuận 1,710 0 0 2,125 3,835 0 160 160 31 Phú Vang Phú Xuân 5,555 5,713 0 14,000 25,268 0 1,056 1,056 32 Phú Vang Thuận An 2,280 0 0 2,622 4,902 8 198 205 33 Phú Vang Vinh An 6,441 17,199 0 29,356 52,996 0 2,214 2,214 34 Phú Vang Vinh Hà 0 0 0 0 0 0 0 0 35 Phú Vang Vinh Phú 0 0 0 0 0 0 0 0 36 Phú Vang Vinh Thanh 4,027 8,745 0 15,869 28,641 0 1,197 1,197 169 170 ID District Commune Carbon Carbon Carbon Carbon Total Annual Annual Total storage storage storage storage carbon carbon carbon annual in pro‑ in pro‑ in spe‑ in sandy stor‑ seques‑ seques‑ carbon tection duction cial-use forests age in tration tration seques‑ man‑ man‑ forest (tCO2e) coastal in man‑ in sandy tration in groves groves man‑ forests groves forests coastal (tCO2e) (tCO2e) groves (tCO2e) (tCO2e/ (tCO2e/ forests (tCO2e) year) year) (tCO2e/ year) 37 Phú Vang Vinh Xuân 7,520 31,015 0 47,862 86,397 0 3,610 3,610 38 Quảng Quảng An 0 0 0 0 0 0 0 0 Điền 39 Quảng Quảng Công 7,447 4,585 0 14,949 26,982 0 1,128 1,128 Điền 40 Quảng Quảng Lợi 6,586 30,178 0 37,494 74,258 299 2,828 3,127 Điền 41 Quảng Quảng Ngạn 5,725 15,065 0 25,830 46,620 0 1,948 1,948 Điền 42 Quảng Quảng Phước 0 0 0 0 0 0 0 0 Điền 43 Quảng Quảng Thái 0 19,346 0 24,037 43,383 0 1,813 1,813 Điền 44 Quảng Quảng Thành 0 0 0 0 0 0 0 0 Điền 45 Quảng Sịa 0 0 0 0 0 0 0 0 Điền Supporting Resilient Coastal Economies in Vietnam PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Total 153,084 414,835 0 695,209 1,263,129 378 52,437 52,815 O. Carbon value by forest type in Quang Ninh and TT-Hue O.1. Carbon value share (%) by coastal forest type in Quang Ninh 0% 1% 13% Protection mangroves Production mangroves Special use mangroves Protection forest on sandy areas 86% O.2. Carbon value share (%) by coastal forest types in TT-Hue 12% Protection mangroves Production mangroves 55% 33% Special use mangroves Protection forest on sandy areas 0% Annexes 171 P. Coastal protection methodologies P.1. Estimating coastal protection services The Guidelines for the Valuation of Natural Coastal Protection (World Bank 2016) reviews two approaches for estimating coastal protection: index-based and process-based approaches. The guidance recommends using process-based approaches in general and further recommends an Expected Damage Function (EDF) approach for valuing the coastal protection services from mangroves. We here describe both process-based and index-based approaches as possible methods for valuing the coastal protection services delivered by mangroves and coastal forests. P.1.1. Process-based approaches Process-based approaches vary from general approaches to highly detailed numerical models. There are five core steps to estimating coastal protection benefits: 1. Estimate offshore hydrodynamics (waves, storm surge, astronomical tide, mean sea level and tropical cyclones) (estimates available in the Dike Design Guidelines [TVCN]); 2. Transform offshore conditions to the nearshore; 3. Estimate effects of coastal structures (e.g., habitats and physical structures) on hydrodynamics (mangrove characteristics under different scenarios); 4. Estimate flooding or erosion (topography), and; 5. Assess expected and averted damage (value coastal protection benefits, e.g., population, stock and roads). Supporting Resilient Coastal Economies in Vietnam 172 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Figure 0‑18. Five core steps to estimating coastal protection benefits under process-based approaches This multi-step methodology has been applied at both a local and national scale for the Philippines (Menèndez et al. 2019), as well as globally (Menèndez et al. 2020; Beck et al. 2017). The critical data required for each step, along with potential models and tools that could be used for Vietnam, are given in Table 0‑29. It is important to highlight that available global topography/bathymetry data sources are suitable for province-level ecosystem services assessments, but their use for the assessment of design of critical infrastructure, and the protection provided by key ecosystems such as mangroves, are not as precise as would be needed. Annexes 173 Table 0‑29. Modeling framework identifying key steps and critical data needed for the EDF approach Details STAGE 1: Data Needs Tropical Cyclones (IBTrACS) Estimate (Data offshore Sources) Astronomical Tide (Global Ocean Tides database) dynamics Mean Sea Level (Church et al. 2004) Waves (Global Ocean Waves 2, Perez et al., 2017) Storm Surge (Dynamic Atmospheric Correction database, Cid et al. 2017) Models & Hindcast (waves & surge) Tools Forecast (Astronomical Tide) Observations (MSL and Tropical Cyclones) STAGE 2: Data Needs Bathymetry (GEBCO, Weatherall et al. 2015) Estimate (Data nearshore Sources) dynamics Models & SWAN (Waves) Tools Delft3D (Waves and surge) MDA (clustering method) STAGE 3: Data Needs Bathymetry (GEBCO, Weatherall et al. 2015) Estimate (Data effect of Sources) Mangroves (1960s, Defence Mapping Agency; 2010, Giri et al., habitat 2011) Models & Profile Traces (cross-shore profiles) Tools Xbeach (waves & surge) Delft3D (waves & surge) Supporting Resilient Coastal Economies in Vietnam 174 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Details STAGE 4: Data Needs Topography (SRTM, Farr et al. 2007) Estimate (Data flooding Sources) level Models & GIS Tools Pareto Poisson distribution STAGE 5: Data Needs Population (General Statistics Office of Vietnam) Assess (Data damages Sources) Capital Stock (GAR15, UNISDR 2015) Residential Stock (GAR15, UNISDR 2015) Roads Network (OpenStreetMap) Damage Functions (HAZUS, Scawthorn et al., 2006) Models & Annual Expected Function Tools Application of multi-step methodology to Vietnam Flood risks and benefits can be assessed at a range of different scales. If high resolution bathymetry (~5 m resolution) is available for regions around Vietnam, it is recommended that a few key sites be chosen to undertake local scale modeling. The results of the national and local scales can then be compared to ascertain the accuracy of the national model. It is also important to differentiate how mangroves’ protective function differs between waves and surge. The way these are to be assessed also requires differentiation from a modeling perspective. It might be that enclosed lagoons only have to consider waves generated within the fetch limited surface area of the lagoon itself for example. Stage 1: Offshore dynamics Due to the climatic variability that occurs in Vietnam, there is a need to distinguish between flooding induced by typhoons and flooding caused by more frequently occurring storms and seasonal fluctuations. Therefore, the offshore dynamics for both regular climate conditions and tropical cyclones should be derived. The following data is available to undertake this step although the level of detail needed for an assessment of design characteristics for infrastructure, for instance, is higher than that required for determining ecosystem value: Annexes 175 Regular (non-cyclonic) climate: 10-30 years of offshore wave, surge data and seal level data are available from the following global datasets; GOW 2.0 (Global Ocean Waves), GOT (Global Ocean Tides) and DAC (Global Storm Surge). Note that any tropical storm signals should be removed from these datasets prior to modeling. Alternatively, the TVCN guidelines can be used to source data that is uniformly applicable nationally. Tropical cyclones: International Best Track Archive for Climate Stewardship (IBTrACS) provided by the National Oceanic and Atmospheric Administration (NOAA) is a database that includes information about all tropical storms since 1945 including six-hourly information about tropical cyclones’ center, location and intensity. If few cyclones occur (likely if assessing at a local scale), a stochastic method based on the Monte Carlo method can be used to create a synthetic dataset with enough observations to assign return periods. Offshore waves and storm surge for historical tropical cyclones or synthetic tropical cyclones can then be generated for offshore locations using a coupled 2D numerical model (e.g., Delft3D-FLOW and DELFT3D-WAVE). For example, Menèndez et al. (2019), used a 2D grid of 5 km resolution and 30s timestep, forced with hourly wind data and sea level pressure fields for the Philippines to obtain offshore inputs for the profiles derived in Stage 2. This step may not be needed for some mangroves that are located inside existing lagoons and protected to some degree by the outer beach/dune system. Where this is the case and only the assessment of nearshore wave attenuation is required, this step can be omitted as the waves fetch length will be limited. In these circumstances, a small local wave model of the lagoon would suffice to determine the design wave height. Stage 2: Nearshore dynamics To obtain nearshore dynamics, the offshore wave condition must be transformed to the nearshore. This can be done by using either 1D numerical models such as Xbeach or Delft3D, or 2D models. This has been done routinely in the provinces with 2D models for the definition of setback lines, so some existing information may be available in some provinces to assist with this. A set of cross-shore profiles needs to be created parallel to the shoreline (bathymetric gradient) about every 300 meters along the coast of Vietnam. The elevation profiles of these cross-shore transects can be extracted from GEBCO, a global gridded bathymetry with an average resolution of 1 km. A set of offshore regular climate conditions and tropical cyclone conditions can then be assigned to each profile. Regular climate conditions can be assigned by taking the closest point of the wave database (GOW 2), meteorological tide (20CR reanalysis), astronomical tide (GOT) and mean sea level. Tropical Cyclone conditions can be extracted for each profile from the coupled tide and wave model (Step 1). To simulate 10 years of hourly historical regular climate conditions would be extremely time consuming, thus the number of regular climate conditions can be reduced by grouping the conditions into representative families by applying a clustering technique (e.g., K-MEANS). Similarly, for local scale assessments using synthetic tropical cyclone data, offshore conditions can be grouped into representative families by applying a clustering technique. Supporting Resilient Coastal Economies in Vietnam 176 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Stage 3: Effect of mangroves To understand the effect of mangroves on flood risk, a range of mangrove cover scenarios should be modeled, for example: ● Current mangrove cover: Mangrove extent derived from the ecosystem extent service. ● Without mangroves: Assumes a hypothetical situation where all mangrove forests have been destroyed. To simulate every profile obtained in Stage 2 for all three mangrove scenarios would require a large computational effort. Thus, to reduce the number of numerical simulations a K-MEANS clustering technique (or similar) can be implemented to group the profiles into representative families based on a range of attributes (such as mangrove width, bed elevation, etc.). As mentioned in stage two, numerical models such as Xbeach and Delft3D can be used to transform the offshore conditions to the coastline over nearshore bathymetry and mangrove habitats, for the three mangrove scenarios (historic, current and total loss). The numerical modeling package Xbeach includes a vegetation module which allows wave attenuation and flow reduction associated with mangroves to be modeled. Similarly, vegetation can also be represented in the FLOW module of Delft3D whereby vegetation is represented as a collection of rigid vertical cylinders (Menèndez et al. 2019, 2020). Stage 4: Estimate flood levels and wave characteristics In Stage 3, waves and sea levels from regular (non-cyclonic) storms and tropical cyclones are propagated to the coastline over nearshore bathymetry and mangrove habitats, for the two mangrove scenarios (current and total loss) using the numerical model (e.g., Delft 3D or Xbeach). From these results, interpolation tables can be created to correlate the sea state at seaward side of the profile (e.g., Hs, Tp, WL) and the characteristics of the mangroves (width and average depth) with total water level at the coast. Using the interpolation tables, a total water level can be obtained for every profile (300m interval) across the coastline for all historical offshore wave conditions (e.g., hourly from 1979). Flood elevation return period curves for each mangrove scenario and storm condition (regular or cyclonic) can then be obtained by applying a threshold to the total water level data and fitting a Generalized Pareto-Poisson distribution. Thus, flood height can be estimated across the Vietnam coastline for a range of return periods for the two mangrove scenarios. The coastline flood heights can then be translated inland. At the national scale, the flood extents can be estimated using a simple bathtub model with 30m resolution topography (Shuttle Radar Topography Mission, SRTM). It should be noted that SRTM will generally represent the surface of the top of the canopy and will underestimate flood risk in mangroves. At the local scale, more detailed topography may be needed to deal with this and used alongside a more sophisticated flooding model (e.g., TUFLOW). Annexes 177 Stage 5: Assess damages and benefit value The assessment of the consequences of the loss of mangroves can be estimated using people and property. Available global, national and local databases can be used to estimate the population (WorldPop, http://www.worldpop.org.uk/), population below poverty level (local sources), residential stock (GAR15, UNISDR 2015), industrial stock (GAR15, UNISDR 2015), and length of roads (OpenStreetMap) for the country. This information can be combined with empirical damage curves to estimate the damage from flooding under different return periods. Thus, giving the damages to population, stock and roads for regular storm conditions and tropical cyclones across the two mangrove cover scenarios, at local and national scales for Vietnam. P.1.2 Index-based approaches An index-based approach is an alternative method for estimating the coastal protection benefits resulting from coastal forests in Vietnam. This approach combines values from raw data sets relating to hydrodynamic processes, geophysical processes, socioeconomic components and management interventions, to estimate exposure and vulnerability to the Vietnamese coast. This either provides economic values of benefit, or proxies from which an estimate of the coastal protection benefits can be produced. A number of approaches are discussed below. Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) InVEST is a free, open-source tool (in the form of a suite of software models) that maps and values ecosystem services in order to evaluate the benefits to society from the ecosystem. It has been developed by the Natural Capital project to enable decision makers to use relevant spatial data in order to assess quantified trade-offs associated with alternative management choices and to identify areas where investment in natural capital (nature-based solutions) can enhance human development, conservation and ensure risk-informed coastal planning with a focus on priority areas (Stanford, 2020). InVEST studies are most effective when used as part of an iterative science policy process. This requires a baseline understanding of the coastal forests’ services, such as reducing flooding risk, and the development of various policy and land management changes than could affect the flow of these services. This ecosystem services approach follows the recommendations from January 2020’s ‘Vietnam multi-sectoral risk assessment’ (van Ledden et al. [World Bank], 2020). From this, the benefits and value can be synthesized using InVEST. Although the tool has proven to be successful in various locations, it is very dependent on available data and has not been tested in Vietnam. Therefore, its use has a strong potential for providing an appropriate estimation of ecosystem services; however, it should be used in conjunction with proven fieldwork-based methods, such as the previously mentioned process-based models, for validation. The tool includes 19 ecosystem services models covering terrestrial, freshwater, marine, and coastal ecosystems. The tools produce spatially explicit models; using maps as data sources and producing maps as outputs. The results are generated in either biophysical terms or economic terms. The coastal vulnerability and protection modules are reviewed further below. Supporting Resilient Coastal Economies in Vietnam 178 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Coastal vulnerability module (InVEST) The Coastal Vulnerability Module is an appropriate start for evaluating the benefits of ecosystem services of coastal forests in Vietnam. This model maps areas of high or low vulnerability to coastal hazards, such as storm surges, given different management scenarios, through expected risks of coastal erosion and flooding. The tool does not provide quantitative valuation of protection (for example, economic values for shoreline protection from coastal forests), however, the outputs can be used as proxies for estimating economic gains or losses. Raw data sets for seven variables are input into the program. The index scores each of these variables on a scale of one to five to indicate exposure of the shoreline. From this, outputs, in the form of maps and/or comparable exposure scores, are produced. The coastal vulnerability map is coded by color to signify areas of low to extreme (high) vulnerability (as seen in Figure 7-19). The change in shoreline exposure score can be determined for just the geophysical and natural habitat characteristics of coastal forests (Stanford, 2020) or examined in relation to the risks to people and property in different areas of coastal Vietnam when using coastal population density data (Arkema et al., 2013). Figure 0‑19. Vulnerability maps produced by the Coastal Vulnerability Module in ArcGIS18 The table below lists the seven variables scored to indicate exposure and potential sources for the data to input (using georeferenced rasters where available) (Chung et al., 2015). 18 Source: Jackson and Littles (2020) Annexes 179 Table 0‑30. Seven variables used in the Coastal Vulnerability Module and relevant data sources Variable Data Source(s) Habitats (land use) https://data.opendevelopmentmekong.net/dataset/rural- environment-and-land-use Vietnam national forest inventory (2015) Vietnam annual forest monitoring result (2018) Landsat-8 OLI 30 m resolution, 199 scenes (2015) Some global data can be provided as default in some areas. Relief (DEM (Digital https://data.opendevelopmentmekong.net/dataset/digital- Elevation Model) with elevation-model-dem?type=dataset a minimum 30-meter resolution) http://www.gps-vietnam.net/eng/dem.html Geomorphological data Data relating to carbon storage, rooting depth, nutrient loading and evapotranspiration coefficients in tabular data format (Bagstad et al., 2013) Sea Level Rise (SLR) (sea Projection (raster format), NOAA level change between high and low tide) http://www.tidetablechart.com/tides/region/Vietnam https://datacatalog.worldbank.org/dataset/world-sea-level-rise- dataset) Wind exposure Included within InVEST https://datacatalog.worldbank.org/dataset/vietnam-wind-speed- and-wind-power-potential-maps Wave exposure (average Included within InVEST depth of the adjacent seas) South China Sea (1212m) and Gulf of Tonkin (1060m) Surge (distance between the Included within InVEST program coastline and the edge of the continental margin) Supporting Resilient Coastal Economies in Vietnam 180 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas As referenced, some data can be found through Marine InVEST. However, this is a global data set. Therefore, to have more detailed and accurate results, other data sources should be used, although this would require longer computation times (World Bank, 2016). In order to evaluate the protective services, different scenarios are run and the resultant outputs compared. These scenarios include those with management (protecting coastal forests) and scenarios without management (no change to degradation of the coastal forests), given changing sea level (given by the climate scenario). The index weights all variables equally based on methods proposed by Gornitz (1990) and Hammar-Klose and Thieler (2001). Habitat ranking is already pre-determined by ‘type’ in InVEST and is based on extensive literature review (Jackson and Littles, 2020). An Exposure Index (EI), or the geometric mean, is calculated as a function of these seven variables: EI = (R GeomorphologyR ReliefR HabitatsR SLRR Wind ExposureR Wave ExposureR Surge) 1/5 Equation 1: Exposure Index This will provide the coastal vulnerability for each coastline segment or pixel. This value indicates coastal protection benefits of the regulating coastal forest systems. ‘R’ in this function represents the rank/score of each variable as provided by the user. These ranks are assigned from 0-5 (lowest to highest risk) and are used to calculate exposure similarly to weighted average (Jackson and Littles, 2020). Coastal protection module (InVEST) Similar to the Coastal Vulnerability Module, the Coastal Protection Module from InVEST also allows for user-defined scenarios in order to assess different management scenarios. However, there are a few key differences. The first, is that this module is process based, accounting for local processes and therefore providing relatively more specific outputs. Another is that this module does require ArcGIS to run. The use of this module has been tested in examining vulnerability changes from the destruction of mangrove forests in the Bahamas (Sharp et al. 2014). As 86 percent of the coastal forest protection arises from mangrove forests in Vietnam, this tool is therefore particularly relevant in assessing how these mangroves attenuate waves and reduce erosion or flooding. As mentioned, the model allows the user to develop various scenarios and examine impacts on coastal protection benefits. The output is produced in the following stages: 1. Run the sub-model Profile Generator to obtain a cross-shore profile. A DEM that contains spatial data on bathymetry and topography, with vertical elevation referenced to Mean Lower Low Water is required. A potential source of this is: https://data.opendevelopmentmekong.net/dataset/digital-elevation-model-dem?type=dataset OR http://www.gps-vietnam.net/eng/dem.html. Input more detailed information on bathymetry and coastal habitats to produce a cross-shore transect from GIS. Annexes 181 2. Run the sub-model for nearshore waves and erosion. Here the user can alter the inputs. These and potential data sources are listed in the table below. Table 0‑31. User defined inputs used in the Coastal Protection Module and relevant data sources Input Data Source(s) Wave Height - NOAA Wavewatch III Database6 - Different wave re-analyses available worldwide e.g., Reguero et al., 2012 Wave Period Values - NOAA Wavewatch III Wind speed - https://datacatalog.worldbank.org/dataset/vietnam-wind-speed- and-wind-power-potential-maps Fetch distance - Distance measurement (Google Earth or similar GIS) Water depth - NOAA World Ocean Database 3. Produce economic values for accrued costs avoided due to coastal forests (given available data). The required data and potential sources are in the table below. Table 0‑32. Inputs used in the Coastal Protection Module to produce economic values of costs/benefits and relevant data sources Variable Data Source(s) Land Use (length of https://data.opendevelopmentmekong.net/dataset/rural- habitat type, coverage and environment-and-land-use OR Landsat-8 OLI 30 m resolution, management actions) 199 scenes (2015) Local property values Some people and property asset data are available through Marine InVEST (more detailed data set use is encouraged) 27.7% of the coastline in urbanized Land Valuation Tax (local property value) Supporting Resilient Coastal Economies in Vietnam 182 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas Variable Data Source(s) Typical return period of Variable according to province/region, with higher return periods storms in the area in the north of the country. Regional data should be available from the Vietnam Disaster Management Authority. Appropriate discount rate Discount rates are not standardized in Vietnam. Suitable discount rate will require deliberation. Number of years the user N/A intends to value coastal protection provided by the coastal forest With regards to property values, prices for each land type were recorded in the 2014 Qualitative Study (World Bank - Vietnam Affordable Housing, 2015) as follows: ● Agricultural land: VND 10 million/500m2 = VND 20,000/m2 ● Informal subdivision (no Land Use Regulation Exemptions [LURC], no infrastructure): VND 30 million/30m2 = VND 1 million/m2 ● Semi-formal subdivision (No LURC but infrastructure): VND 8 million/m2 ● Formal land (LURC and infrastructure): VND 500 million/30m2 = VND 16.6 million/m2 These price estimations could be used to represent local property values. Artificial Intelligence for Ecosystem Services (ARIES) ARIES is a relatively recent modeling platform, largely still in development. It is an index approach, based on Bayesian modeling; however, the use of proxies and artificial intelligence are also used in order to assess vulnerability through the Coastal Flood Regulation Module. From this model, the statistical relationships between wave exposure, coastal forests and the impact on people and property are computed for potential future meteorological events in Vietnam. It is available to download in an early release form, in addition to training sessions being taught by the developers. The user side of the system, known as ARIES Explorer, is free for individual and non-profit use (aries.integratedmodelling.org, 2020). ARIES includes several approaches, dependent on the values entered, to estimate the economic value of Vietnam’s coastal forests. The first approach is for the user to enter values for multiple services (for example, flood protection from mangroves) and pair these with user-defined, priority-based weights in an online Web tool. The second approach is to incorporate previously assessed economic values for coastal protection. Annexes 183 ARIES differs fundamentally in its approach from InVEST because it does not use biophysical relationships to model coastal risk reduction. Instead, it uses probabilistic relationships based on historical data to spatially link biophysical units (for example, tons of sediment) and abstract units (for example, soil retention). ARIES is flexible enough to accommodate multiple ecosystem services, and it allows the user to spatially map the uncertainty associated with the model output, a feature not available in many of the other ecosystem service tools. ARIES has been implemented in several project sites located in America, Europe, and Africa (Ocean Studies Board, 2013). ARIES, although less vetted than InVEST, is more appropriate for areas with data scarcity due to the few inputs required. Table 0‑33. Inputs used in ARIES and relevant data sources Variable Data Source(s) Wind data https://datacatalog.worldbank.org/dataset/vietnam-wind-speed- and-wind-power-potential-map Barometric Pressure NOAA NCDC Water Depth NOAA Values for services User-defined and priority-based weighting Previously assessed economic values for coastal protection Multiscale Integrated Models of Ecosystem Services (MIMES) The MIMES model is another spatially explicit, general ecosystem service tool, although it is comparatively more conceptually complex than InVEST and ARIES (Ocean Studies Board, 2013). It uses an interaction matrix of subsystems pertaining to natural, economic and social capital and processes, synthesized in various system models (e.g., SHIRAZ) using georeferenced data sets (toolkit.climate.gov, 2018). It is publicly available, however is not as well documented as InVEST and ARIES (Bagstad et al. 2013). It is place specific and so a highly technical user or a consultant needs to program it when it is first run in a new location (World Bank, 2016). To date, no documentation exists for the use of MIMES to specifically estimate coastal protection services from natural habitats in Vietnam; therefore, it is not likely to be feasible locally due to the specialist programming and tools required. Supporting Resilient Coastal Economies in Vietnam 184 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas P.1.3 Benefit transfer approach A literature review of thirty papers that valued coastal forests in Vietnam was carried out to obtain data which could be transferred to the trial provinces. Most papers reported on the economic benefits of direct use values, but only seven studies reported economic values for the protective services of mangroves and other coastal forest assets. The studies identified used cost-based methods to estimate protective values, including erosion control of the coastline and the protection of agriculture production, houses, health and shrimp farming from various hazards. The results of these studies are presented in the table below. Table 0‑34. Coastal protection values of coastal forest assets in Vietnam ID Study location Forest types Report Reported Protection Sources year Protection value value at 2020 (USD/ha/ (discount yr) rate 10%, USD/ha/yr) 1 Xuan Thuy NP, Mangroves 1998 231.7 1,886.5 [1] Nam Dinh 2 Xuan Thuy NP, Mangroves 2010 26.5 68.7 [2] Nam Dinh 3 Nam Dinh Mangroves 2007 52.7 181.9 [3] 4 Can Gio, Ho Chi Mangroves 2012 3,896.5 8,352.6 [4] Minh City 5 Ca Mau Mangroves 2012 504.6 1,081.6 [5] 6 Ca Mau Mangroves 2013 3,335.0 6,499.0 [6] 7 Ca Mau Mangroves 2015 728.2 1,172.8 [7] 8 Kien Giang Mangroves 2012 366.4 785.4 [5] 9 Ninh Thuan and Forest on 2012 301.3 646.0 [5] Binh Thuan sandy areas Sources: [1] Tri, N.H et al. 1998; [2] Truong, D.D. 2010; [3] Phuong et al. 2007; [4] Tuan, V.Q. and C. Kuenzer. 2012; [5] Phuong et al. 2012; [6] Vo Quoc Tuan. 2013; [7] Nam Hoang Nguyen 2015. Annexes 185 When applying the benefit transfer methodology to other provinces in Vietnam, it is recommended that an assessment first be made as to which of the study locations listed in Table 0‑34 is most similar (i.e., in terms of the features of the coastal assets present) to the location to which values are to be transferred. Once the most similar study location has been decided, an average of the coastal protection values reported for that location should be taken as the value to be transferred to coastal forest assets locally. Only a single study has reported the economic value of coastal protection services from sandy forests and hence this value can be assumed for sandy forest assets, regardless of location. Figure 0‑20. Coastal protection values in Quang Ninh and Thua Thien Hue Supporting Resilient Coastal Economies in Vietnam 186 PART A: Practical Guidance for Assessing the Value of Key Natural Assets in Coastal Areas REFERENCES • Arkema, K. 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