In this report, we update and extend the methodology developed for the previous CWON 2021 report to assess the economic value of non-wood ecosystem services from forests (Siikamäki et al. 2021). Like the earlier assessment, we develop a meta-analytic predictive model using regression and machine learning techniques to spatially estimate the value of the following three ecosystem services: (1) recreation, hunting, and fishing; (2) non-wood forest products; and (3) watershed protection (hereafter, “water services”). These values are produced using 0.1º by0.1º (approximately 10km by 10km) spatial resolution and then combined and spatially aggregated to estimate country-wealth from non-wood forest products. In addition, we develop an operational method to estimate the contribution of protected areas to the value of non-wood forest productions.
Authors
- Citation
- “ World Bank . 2024 . The Changing Wealth of Nations - Global Assessment of the Economic Value of Non-Wood Forest Ecosystem Services: Technical Report . © Washington, DC: World Bank . http://hdl.handle.net/10986/42324 License: CC BY-NC 3.0 IGO . ”
- Collection(s)
- Other papers
- DOI
- https://doi.org/10.1596/42324
- Identifier externaldocumentum
- 34403646
- Identifier internaldocumentum
- 34403646
- Pages
- 220
- Published in
- United States of America
- Report
- 194078
- Rights
- CC BY-NC 3.0 IGO
- Rights Holder
- World Bank
- Rights URI
- https://creativecommons.org/licenses/by-nc/3.0/igo
- UNIT
- Planet - GLOBAL ENR PM (SENGL)
- URI
- https://hdl.handle.net/10986/42324
- date disclosure
- 2024-10-29
- region geographical
- World
- theme
- Adaptation,Mitigation,Economic Policy,Economic Growth and Planning,Environment and Natural Resource Management,Climate change
Files
Table of Contents
- CONTENTS 4
- TABLES 6
- FIGURES 6
- ACRONYMS AND ABBREVIATIONS 8
- 1 Introduction 9
- 2.1 LITERATURE REVIEW AND 12
- DATA EXTRACTION 12
- 2 Development of Database of 12
- Non-Wood Forest Ecosystem 12
- Service Valuation Studies 12
- 2.2 VALUE ESTIMATES BY 15
- ECOSYSTEM SERVICE AND 15
- ESTIMATION METHOD 15
- 2.3 GEOGRAPHICAL 18
- DISTRIBUTION OF VALUES BY 18
- ECOSYSTEM SERVICE 18
- 2.4 VALUE ESTIMATES 20
- 2.5 LINKAGES WITH THE SYSTEM OF ENVIRONMENTAL- 21
- ECONOMIC ACCOUNTING 21
- ECOSYSTEM ACCOUNTING 21
- 3.1 OVERVIEW 27
- 3.2 ESTIMATION METHODS 27
- 3 Methods for the Spatial 27
- Estimation of the Value of Non- 27
- Wood Forest Ecosystem Services Globally 27
- Regression 29
- Random forest 29
- Bayesian Additive Regression Trees 29
- Automated ML 29
- Y Y Y 31
- TRAINING DATA 31
- 3.3 GLOBAL PREDICTIONS 34
- 4.1 CONSTRUCTION OF GLOBAL VARIABLES 38
- 4 Database Construction and Descriptive Analysis 38
- 4.2 LINKING THE WORLD GRID TO THE STUDY SITE LOCATIONS 42
- 4.3 DESCRIPTIVE ANALYSIS 42
- 5.1 ESTIMATION RESULTS 47
- 5 Estimation Results and 47
- Global Predictions 47
- 5.2 GLOBAL PREDICTIONS 59
- 5.3 RESULTS COMPARISON WITH THE PREVIOUS ASSESSMENTS 64
- 6 Contribution of Protected Areas to the Value of Non-Wood Forest Ecosystem Services 67
- 7 Discussion 70
- References 73
- Appendix 1 77
- Update the metadata analysis by incorporating newly available studies 77
- A1.1 IDENTIFYING POTENTIALLY RELEVANT STUDIES TO 77
- UPDATE THE PREVIOUS 77
- DATABASE 77
- A1.2 STUDY REVIEW PROTOCOL 79
- A1.3 DETERMINING THE 80
- APPLICABILITY OF VALUE 80
- ESTIMATES FOR THIS 80
- ASSESSMENT 80
- A1.4 VALUE ESTIMATES BY 84
- ECOSYSTEM SERVICES AND 84
- ESTIMATION METHOD 84
- A1.5 GEOGRAPHICAL 86
- DISTRIBUTION OF VALUES BY 86
- ECOSYSTEM SERVICE 86
- A1.6 SUMMARY OF VALUE 90
- ESTIMATES 90
- Appendix 2 91
- List of studies included and excluded 91
- A2.1 LIST OF STUDIES INCLUDED IN THE META-ANALYSIS 91
- A2.2 PAPERS REVIEWED AND 106
- NOT INCLUDED IN THE 106
- META-ANALYSIS 106
- A2.3 PAPERS UNABLE TO BE 161
- RETRIEVED 161
- Appendix 3 163
- Study review quality controlquality assurance protocol 163
- Appendix 4 164
- Currency conversion 164
- Regression 166
- Random forest 166
- Bayesian Additive Regression Trees 166
- Automated ML 166
- A5.1 GENERAL APPROACH 166
- Appendix 5 166
- Statistical methods 166
- A5.2 META-REGRESSION ANALYSIS 168
- A5.3 MACHINE LEARNING ALGORITHMS 169
- References 174
- A6.1 WORLD GRID DATA 175
- A6.2 GIS DATA PROCESSING DATA DESCRIPTION AND SOURCES 175
- Appendix 6 175
- GIS data processing and variables construction 175
- A6.3 CONSTRUCTING DATA ON ACCESSIBLE FOREST 190
- Appendix 7 191
- Resultsadditional tables and figures 191
- Appendix 8 204
- Global predictions by model 204
- Appendix 9 209
- Regional and country-level average predictions per hectare 2020 and total wealth 209
