Methods for economic assessment of forest resource degradation: A systematic review

Robert Sourokou, Fifanou G. Vodouhe, Jacob A. Yabi

Article ID: 4353
Vol 7, Issue 1, 2024

VIEWS - 325 (Abstract) 285 (PDF)

Abstract


Forest degradation is one of the challenges facing the planet today. Several methods have been used to measure forest degradation, including spatiotemporal model analysis, satellite analysis, remote sensing, time series data, geospatial techniques, and most recently aerial drone imagery. However, few studies have used economic valuation methods to assess forest degradation. Therefore, this research aimed to identify the methods used the economic assessment of forest degradation. This systematic review was carried out using PRISMA guidelines. Research articles on the economic valuation of forest resource loss, published from 2015 to 2022, were electronically collected from three databases. Three independent reviewers, with the third acting as referee, inventoried articles, extracted data, and assessed the risk of bias in the articles included in the study. A total of 10,095 articles were identified, including one article from the grey literature. Only five articles met the eligibility criteria. A qualitative content analysis was performed on the extracted data. The selected articles used various methods. However, only a few articles used the contingent valuation method, even though this is indicated for estimating the highest economic value of forests. Based on forest functions, the articles evaluated erosion due to the absence of trees, wood loss, recreation areas and externalities due to forest loss, air quality, water regulation, food supply, and wildlife. The main limitation of this review was the small number of studies included, which may have affected the findings. The study protocol is registered in PROSPERO under the number CRD42021223242


Keywords


economic assessment; deforestation; contingent valuation; natural resources; PRISMA

Full Text:

PDF


References


1. Ojea E, Loureiro ML, Alló M, et al. Ecosystem Services and REDD: Estimating the Benefits of Non-Carbon Services in Worldwide Forests. World Development. 2016; 78: 246-261. doi: 10.1016/j.worlddev.2015.10.002

2. Taye FA, Folkersen MV, Fleming CM, et al. The economic values of global forest ecosystem services: A meta-analysis. Ecological Economics. 2021; 189: 107145. doi: 10.1016/j.ecolecon.2021.107145

3. Saha D, Taron A. Economic valuation of restoring and conserving ecosystem services of Indian Sundarbans. Environmental Development. 2023; 46: 100846. doi: 10.1016/j.envdev.2023.100846

4. Biaou S, Houeto F, Gouwakinnou G, et al. Spatio-temporal dynamics of land use in the Ouénou-Bénou classified forest in northern Benin 2019 (French).

5. Harris NL, Brown S, Hagen SC, et al. Baseline Map of Carbon Emissions from Deforestation in Tropical Regions. Science. 2012; 336(6088): 1573-1576. doi: 10.1126/science.1217962

6. Yesuf G, Brown KA, Walford N. Assessing regional‐scale variability in deforestation and forest degradation rates in a tropical biodiversity hotspot. Pettorelli N, Wegmann M, eds. Remote Sensing in Ecology and Conservation. 2019; 5(4): 346-359. doi: 10.1002/rse2.110

7. Jeminiwa OR, Jeminiwa MS, Taiwo DM, et al. Assessment of Forest Degradation Indices in Mokwa Forest Reserve, Niger State, Nigeria. Journal of Applied Sciences and Environmental Management. 2020; 24(8): 1351-1356. doi: 10.4314/jasem.v24i8.7

8. Soliño M, Raposo R. Contributing to healthy forests: Social preferences for pest and disease mitigation programs in Spain. Forest Policy and Economics. 2022; 140: 102754. doi: 10.1016/j.forpol.2022.102754

9. de Groot R, Brander L, van der Ploeg S, et al. Global estimates of the value of ecosystems and their services in monetary units. Ecosystem Services. 2012; 1(1): 50-61. doi: 10.1016/j.ecoser.2012.07.005

10. Dimobe K, Ouédraogo A, Soma S, et al. Identification of driving factors of land degradation and deforestation in the Wildlife Reserve of Bontioli (Burkina Faso, West Africa). Global Ecology and Conservation. 2015; 4: 559-571. doi: 10.1016/j.gecco.2015.10.006

11. Sloan S, Sayer JA. Forest Resources Assessment of 2015 shows positive global trends but forest loss and degradation persist in poor tropical countries. Forest Ecology and Management. 2015; 352: 134-145. doi: 10.1016/j.foreco.2015.06.013

12. Akalin G, Erdogan S. Does democracy help reduce environmental degradation? Environmental Science and Pollution Research. 2020; 28(6): 7226-7235. doi: 10.1007/s11356-020-11096-1

13. Borges J, Higginbottom TP, Cain B, et al. Landsat time series reveal forest loss and woody encroachment in the Ngorongoro Conservation Area, Tanzania. Disney M, Levick S, eds. Remote Sensing in Ecology and Conservation. 2022; 8(6): 808-826. doi: 10.1002/rse2.277

14. Eastwood N, Stubbings WA, Abou-Elwafa Abdallah MA, et al. The Time Machine framework: monitoring and prediction of biodiversity loss. Trends in Ecology & Evolution. 2022; 37(2): 138-146. doi: 10.1016/j.tree.2021.09.008

15. Fernández-Díaz VZ, Canul Turriza RA, Kuc Castilla A, et al. Loss of coastal ecosystem services in Mexico: An approach to economic valuation in the face of sea level rise. Frontiers in Marine Science. 2022; 9. doi: 10.3389/fmars.2022.898904

16. Hiltner U, Huth A, Fischer R. Importance of the forest state in estimating biomass losses from tropical forests: combining dynamic forest models and remote sensing. Biogeosciences. 2022; 19(7): 1891-1911. doi: 10.5194/bg-19-1891-2022

17. Ouattara TA, Sokeng VCJ, Zo-Bi IC, et al. Detection of Forest Tree Losses in Côte d’Ivoire Using Drone Aerial Images. Drones. 2022; 6(4): 83. doi: 10.3390/drones6040083

18. López S. Deforestation, forest degradation, and land use dynamics in the Northeastern Ecuadorian Amazon. Applied Geography. 2022; 145: 102749. doi: 10.1016/j.apgeog.2022.102749

19. Nguyen H, Trung TH, Phan DC, et al. Transformation of rural landscapes in the Vietnamese Mekong Delta from 1990 to 2019: a spatio-temporal analysis. Geocarto International. 2022; 37(26): 13881-13903. doi: 10.1080/10106049.2022.2086623

20. Sugimoto R, Kato S, Nakamura R, et al. Deforestation detection using scattering power decomposition and optimal averaging of volume scattering power in tropical rainforest regions. Remote Sensing of Environment. 2022; 275: 113018. doi: 10.1016/j.rse.2022.113018

21. Sesnie SE, Tellman B, Wrathall D, et al. A spatio-temporal analysis of forest loss related to cocaine trafficking in Central America. Environmental Research Letters. 2017; 12(5): 054015. doi: 10.1088/1748-9326/aa6fff

22. Nicolau AP, Herndon K, Flores-Anderson A, et al. A spatial pattern analysis of forest loss in the Madre de Dios region, Peru. Environmental Research Letters. 2019; 14(12): 124045. doi: 10.1088/1748-9326/ab57c3

23. Di Fulvio F, Forsell N, Korosuo A, et al. Spatially explicit LCA analysis of biodiversity losses due to different bioenergy policies in the European Union. Science of The Total Environment. 2019; 651: 1505-1516. doi: 10.1016/j.scitotenv.2018.08.419

24. Abdullah HM, Islam I, Miah MdG, et al. Quantifying the spatiotemporal patterns of forest degradation in a fragmented, rapidly urbanizing landscape: A case study of Gazipur, Bangladesh. Remote Sensing Applications: Society and Environment. 2019; 13: 457-465. doi: 10.1016/j.rsase.2019.01.002

25. Wu J, Chen B, Reynolds G, et al. Monitoring tropical forest degradation and restoration with satellite remote sensing: A test using Sabah Biodiversity Experiment. Tropical Ecosystems in the 21st Century. Published online 2020: 117-146. doi: 10.1016/bs.aecr.2020.01.005

26. Bullock EL, Woodcock CE, Olofsson P. Monitoring tropical forest degradation using spectral unmixing and Landsat time series analysis. Remote Sensing of Environment. 2020; 238: 110968. doi: 10.1016/j.rse.2018.11.011

27. Chen S, Woodcock CE, Bullock EL, et al. Monitoring temperate forest degradation on Google Earth Engine using Landsat time series analysis. Remote Sensing of Environment. 2021; 265: 112648. doi: 10.1016/j.rse.2021.112648

28. Dawson G. Book reviews. Forest Policy and Economics. 2008; 10(4): 270-271. doi: 10.1016/j.forpol.2007.11.001

29. Sukhdev P, Kumar Sharma P. The Economics of Ecosystems and Biodiversity (TEEB): An Interim Report 2008.

30. Förster J, Schmidt S, Bartkowski B, et al. Incorporating environmental costs of ecosystem service loss in political decision making: A synthesis of monetary values for Germany. Linkov I, ed. PLOS ONE. 2019; 14(2): e0211419. doi: 10.1371/journal.pone.0211419

31. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Journal of Clinical Epidemiology. 2009; 62(10): e1-e34. doi: 10.1016/j.jclinepi.2009.06.006

32. Higgins JP, Green S. Cochrane Handbook for Systematic Reviews of Interventions in Cochrane Handbook for Systematic Reviews of Interventions, Chichester, UK: John Wiley & Sons, Ltd, 2008, p. i‑xxi. doi: 10.1002/9780470712184.fmatter

33. Daily. Nature’s services: societal dependence on natural ecosystems in Island Press, Washington DC. Available online: http://books.google.com/books? (accessed on 27 March 2024).

34. Pearce. Economic Values and the Natural World. Travel &Tourism Analyst. The MIT Press, Cambridge in Earthscan Publications Ltd, London. 1993.

35. Pullin AS, Knight TM. Effectiveness in Conservation Practice: Pointers from Medicine and Public Health. Conservation Biology. 2001; 15(1): 50-54. doi: 10.1111/j.1523-1739.2001.99499.x

36. Fazey I, Salisbury JG, Lindenmayer DB, et al. Can methods applied in medicine be used to summarize and disseminate conservation research? Environmental Conservation. 2004; 31(3): 190-198. doi: 10.1017/s0376892904001560

37. Deeks JJ, Higgins JP, Altman DG. Analysing data and undertaking meta‐analyses. Cochrane Handbook for Systematic Reviews of Interventions. Published online September 20, 2019: 241-284. doi: 10.1002/9781119536604.ch10

38. Majdalawi MI, Raedig C, Al-Karablieh EK, et al. Integration of different environmental valuation methods to estimate forest degradation in arid and semi-arid regions. International Journal of Sustainable Development & World Ecology. 2016; 23(5): 392-398. doi: 10.1080/13504509.2015.1124934.

39. Durán-Medraño R, Varela E, Garza-Gil D, et al. Valuation of terrestrial and marine biodiversity losses caused by forest wildfires. Journal of Behavioral and Experimental Economics. 2017; 71: 88‑95. doi: 10.1016/j.socec.2017.10.001.

40. Sadowska B, Grzegorz Z, et Stępnicka N. Forest Fires and Losses Caused by Fires – An Economic Approach. Wseas Transactions on Environment And Development. 2021; 17: 181‑191. doi: 10.37394/232015.2021.17.18.

41. Knoke T, Gosling E, Thom D, et al. Economic losses from natural disturbances in Norway spruce forests—A quantification using Monte-Carlo simulations. Ecological Economics. 2021; 185: 107046. doi: 10.1016/j.ecolecon.2021.107046

42. Unsworth R, Petersen T. A manual for conducting natural resource damage assessment: The role of economics. Cambridge (MA): Industrial Economics, Incorporated, 2002. Available online: http://www.fws.gov/policy/NRDAManualFull.pdf (accessed on 27 March 2023).

43. Roach B, Wade WW. Policy evaluation of natural resource injuries using habitat equivalency analysis. Ecological Economics. 2006; 58(2): 421-433. doi: 10.1016/j.ecolecon.2005.07.019

44. Lescuyer G. Economic valuation and sustainable management of tropical forests (French). Available online: https://tel.archives-ouvertes.fr/tel-00007987/document (accessed on 20 January 2024).

45. Brahic E, Terreaux JP. Economic valuation of biodiversity: Methods and examples for temperate forests (French). Editions Quae 2009.

46. Daly Hassen H, Croitoru L. Economic evaluation of goods and services from Tunisian forests (French). Association Forêt Méditerranéenne, 14 rue Louis Astouin, 13002 MARSEILLE, France (FRA), 2013.

47. Roslinda E. Economic valuation of the Danau Sentarum National Park, West Kalimantan, Indonesia. Biodiversitas Journal of Biological Diversity. 2019; 20(7). doi: 10.13057/biodiv/d200726

48. Tao Z, Yan H, Zhan J. Economic Valuation of Forest Ecosystem Services in Heshui Watershed using Contingent Valuation Method. Procedia Environmental Sciences. 2012; 13: 2445-2450. doi: 10.1016/j.proenv.2012.01.233

49. Ojeda MI, Mayer AS, Solomon BD. Economic valuation of environmental services sustained by water flows in the Yaqui River Delta. Ecological Economics. 2008; 65(1): 155-166. doi: 10.1016/j.ecolecon.2007.06.006

50. Gibson JM, Rigby D, Polya DA, et al. Discrete Choice Experiments in Developing Countries: Willingness to Pay Versus Willingness to Work. Environmental and Resource Economics. 2015; 65(4): 697-721. doi: 10.1007/s10640-015-9919-8

51. Arabomen OJ, Chirwa PW, Babalola FD. Willingness-to-pay for Environmental Services Provided By Trees in Core and Fringe Areas of Benin City, Nigeria 1. International Forestry Review. 2019; 21(1): 23-36. doi: 10.1505/146554819825863717

52. Azadi H, Van Passel S, Cools J. Rapid economic valuation of ecosystem services in man and biosphere reserves in Africa: A review. Global Ecology and Conservation. 2021; 28: e01697. doi: 10.1016/j.gecco.2021.e01697

53. Wangai PW, Burkhard B, Müller F. A review of studies on ecosystem services in Africa. International Journal of Sustainable Built Environment. 2016; 5(2): 225-245. doi: 10.1016/j.ijsbe.2016.08.005

54. Sukhdev P, Kumar P. The Economics of Ecosystems and Biodiversity (TEEB). An interim report. Brussels 2008.

55. Sukhdev P, Wittmer H, Schröter-Schlaack C. The Economics of Ecosystems and Biodiversity. Mainstreaming the economics of nature: A Synthesis of the approach, conclusions and recommendations of TEEB, Gland (Suiza). Progress Press. 2010; 36.

56. Wüstemann H, Meyerhoff J, Rühs M, et al. Financial costs and benefits of a program of measures to implement a National Strategy on Biological Diversity in Germany. Land Use Policy. 2014; 36: 307-318. doi: 10.1016/j.landusepol.2013.08.009

57. Pata UK, Kartal MT, Erdogan S, et al. The role of renewable and nuclear energy R&D expenditures and income on environmental quality in Germany: Scrutinizing the EKC and LCC hypotheses with smooth structural changes. Applied Energy. 2023; 342: 121138. doi: 10.1016/j.apenergy.2023.121138




DOI: https://doi.org/10.24294/nrcr.v7i1.4353

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Robert Sourokou, Fifanou G. Vodouhe, Jacob A. Yabi

License URL: https://creativecommons.org/licenses/by/4.0/

This site is licensed under a Creative Commons Attribution 4.0 International License.