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Understanding how opportunity cost affects multi-objective conservation investment in the Central and Southern Appalachian Region (USA)

Published online by Cambridge University Press:  04 June 2021

Seong-Hoon Cho Open the ORCID record for Seong-Hoon Cho [Opens in a new window] ,
Young Gwan Lee  and
Gengping Zhu
Seong-Hoon Cho*
Affiliation:
Department of Agricultural and Resource Economics, The University of Tennessee, 2621 Morgan Circle Drive, 314D Morgan Hall, Knoxville, TN37996-4518, USA
Young Gwan Lee
Affiliation:
Division of Resource Economics and Management, West Virginia University, Morgantown, WV26506, USA
Gengping Zhu
Affiliation:
Department of Entomology, Washington State University, Pullman, WA99164, USA
*
Corresponding author: Professor Seong-Hoon Cho, Email: scho9@utk.edu
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Summary

Consensus does not exist for which cost forms (i.e., one accounting solely for explicit cost and the other for both explicit and opportunity costs as in relative opportunity cost) are used in calculating return on investment (ROI) for conservation-related decisions. This research examines how the cost of conservation investment with and without inclusion of the opportunity cost of the protected area results in different solutions in a multi-objective optimization framework at the county level in the Central and Southern Appalachian Region of the USA. We maximize rates of ROI of both forest-dependent biodiversity and economic impact generated by forest-based payments for ecosystem services. We find that the conservation budget is optimally distributed more narrowly among counties that are more likely to be rural when the investment cost measure is relative opportunity cost than when it is explicit cost. We also find that the sacrifice in forest-dependent biodiversity per unit increase in economic impact is higher when investment cost is measured by relative opportunity cost rather than when measured by explicit cost. By understanding the consequences of using one cost measure over the other, a conservation agency can decide on which cost measure is more appropriate for informing the agency’s decision-making process.

Keywords

conservation investmenteconomic impactforest-dependent biodiversitymulti-objective optimizationopportunity cost
Type
Research Paper
Information
Environmental Conservation , Volume 48 , Issue 3 , September 2021 , pp. 192 - 199
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Foundation for Environmental Conservation

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References

Adams, VM, Pressey, RL, Naidoo, R (2010) Opportunity costs: who really pays for conservation? Biological Conservation 143: 439–448.CrossRefGoogle Scholar
Armsworth, PR (2014) Inclusion of costs in conservation planning depends on limited datasets and hopeful assumptions. Annals of the New York Academy of Sciences 1322: 61–76.CrossRefGoogle ScholarPubMed
Baker, JS, Galik, CS (2009) Policy Options for the Conservation Reserve Program in a Low-Carbon Economy. Durham, NC, USA: Climate Change Policy Partnership, Duke University, 27 pp.Google Scholar
Bode, M, Wilson, KA, Brooks, TM, Turner, WR, Mittermeier, RA, McBride, MF et al. (2008) Cost-effective global conservation spending is robust to taxonomic group. Proceedings of the National Academy of Sciences of the United States of America 105: 6498–6501.CrossRefGoogle ScholarPubMed
Bremer, LL, Farley, KA, Lopez-Carr, D (2014) What factors influence participation in payment for ecosystem services programs? An evaluation of Ecuador’s SocioPáramo program. Land Use Policy 36: 122–133.CrossRefGoogle Scholar
Buongiorno, J (2001) Generalization of Faustmann’s formula for stochastic forest growth and prices with Markov decision process models. Forest Science 47: 466–474.Google Scholar
Cho, S, Lee, YG, Sharma, BP, Hayes, DJ (2021) Do ecological–economic tradeoffs triggered by budget allocations for forest carbon sequestration change under different market conditions? Sustainability Science 16: 69–84.CrossRefGoogle Scholar
Cho, S, Soh, M, English, BC, Yu, TE, Boyer, CN (2019) Targeting payments for forest carbon sequestration given ecological and economic objectives. Forest Policy and Economics 100: 214–226.CrossRefGoogle Scholar
Eklund, J, Arponen, A, Visconti, P, Cabeza, M (2011) Governance factors in the identification of global conservation priorities for mammals. Philosophical Transactions of the Royal Society B: Biological Sciences 366: 2661–2669.CrossRefGoogle ScholarPubMed
Ferraro, PJ (2003) Assigning priority to environmental policy interventions in a heterogeneous world. Journal of Policy Analysis and Management 22: 27–43.CrossRefGoogle Scholar
Hanski, I (2011) Habitat loss, the dynamics of biodiversity, and a perspective on conservation. Ambio 40: 248–255.CrossRefGoogle Scholar
Hayes, DJ, McGuire, AD, Kicklighter, DW, Gurney, KR, Burnside, TJ, Melillo, JM (2011) Is the northern high-latitude land-based CO2 sink weakening? Global Biogeochemical Cycles 25.Google Scholar
IMPLAN (2020) IMPLAN Pro: V3.1 Download [www document]. URL https://implanhelp.zendesk.com/hc/en-us/articles/115003083594-IMPLAN-Pro-V3-1-Download Google Scholar
Lubowski, RN, Plantinga, AJ, Stavins, RN (2006) Land-use change and carbon sinks: econometric estimation of the carbon sequestration supply function. Journal of Environmental Economics and Management 51: 135–152.CrossRefGoogle Scholar
Lv, X, Zhou, G (2018) Climatic suitability of the geographic distribution of Stipa breviflora in Chinese temperate grassland under climate change. Sustainability 10: 3767.CrossRefGoogle Scholar
Massey, FJ Jr (1951) The Kolmogorov–Smirnov test for goodness of fit. Journal of the American Statistical Association 46: 68–78.CrossRefGoogle Scholar
Messer, KD (2006) The conservation benefits of cost-effective land acquisition: a case study in Maryland. Journal of Environmental Management 79: 305–315.CrossRefGoogle ScholarPubMed
Messer, KD (2013) Incorporating Climate Change with Conservation Planning: A Case Study for Tidal Marsh Bird Conservation in Delaware, USA [www document]. URL http://udspace.udel.edu/handle/19716/17120 Google Scholar
Milder, JC, Scherr, SJ, Bracer, C (2010) Trends and future potential of payment for ecosystem services to alleviate rural poverty in developing countries. Ecology and Society 15: 4.CrossRefGoogle Scholar
Moilanen, A, Leathwick, JR, Quinn, JM (2011) Spatial prioritization of conservation management. Conservation Letters 4: 383–393.CrossRefGoogle Scholar
Moore, J, Balmford, A, Allnutt, T, Burgess, N (2004) Integrating costs into conservation planning across Africa. Biological Conservation 117: 343–350.CrossRefGoogle Scholar
Moritz, RLV, Reich, E, Bernt, M, Middendorf, M (2014) The influence of correlated objectives on different types of P-ACO algorithms. In: Blum, C, Ochoa, G (eds), Evolutionary Computation in Combinatorial Optimisation. EvoCOP 2014. Lecture Notes in Computer Science, Vol. 8600. Berlin, Germany: Springer.Google Scholar
Murdoch, W, Polasky, S, Wilson, KA, Possingham, HP, Kareiva, P, Shaw, R (2007) Maximizing return on investment in conservation. Biological Conservation 139: 375–388.CrossRefGoogle Scholar
Naidoo, R, Adamowicz, WL (2006) Modeling opportunity costs of conservation in transitional landscapes. Conservation Biology 20: 490–500.CrossRefGoogle ScholarPubMed
Naidoo, R, Ricketts, TH (2006) Mapping the economic costs and benefits of conservation. PLoS Biology 4: e360.CrossRefGoogle ScholarPubMed
Peterson, AT, Soberón, J, Pearson, RG, Anderson, RP, Martínez-Meyer, E, Nakamura, M, Araújo, MB (2011) Ecological Niches and Geographic Distributions. Princeton, NJ, USA: Princeton University Press.CrossRefGoogle Scholar
Pickering, J, Kays, R, Meier, A, Andrew, S, Yatskievych, R (2003) The Appalachians. Wilderness Earth’s Last Wild Places. Washington, DC, USA: Conservation International [www document]. URL https://www.discoverlife.org/co/ Google Scholar
Polasky, S, Nelson, E, Camm, J, Csuti, B, Fackler, P, Lonsdorf, E et al. (2008) Where to put things? Spatial land management to sustain biodiversity and economic returns. Biological Conservation 141: 1505–1524.CrossRefGoogle Scholar
Porras, I, Barton, D, Miranda, M, Chacón-Cascante, A (2013) Learning from 20 years of payments for ecosystem services in Costa Rica. London, UK: International Institute for Environment and Development [www document]. URL https://pubs.iied.org/16514IIED/ Google Scholar
Psaltopoulos, D, Balamou, E, Thomson, KJ (2006) Rural–urban impacts of CAP measures in Greece: An inter-regional SAM approach. Journal of Agricultural Economics 57: 441–458.CrossRefGoogle Scholar
Ragsdale, CT (2006) Spreadsheet Modeling & Decision Analysis. Edinburgh, UK: Thomson Nelson.Google Scholar
Rodewald, AD, Strimas-Mackey, M, Schuster, R, Arcese, P (2019) Tradeoffs in the value of biodiversity feature and cost data in conservation prioritization. Scientific Reports 9: 1–8.CrossRefGoogle ScholarPubMed
Sims, KR, Alix-Garcia, JM, Shapiro-Garza, EL, Fine, LR, Radeloff, VC, Aronson, G et al. (2014) Improving environmental and social targeting through adaptive management in Mexico’s payments for hydrological services program. Conservation Biology 28: 1151–1159.CrossRefGoogle ScholarPubMed
Soh, M, Cho, S (2019) Spatial targeting of payments for ecosystem services to achieve conservation goals and promote social equity and economic impact. Natural Resource Modeling 32: e12219.CrossRefGoogle Scholar
Sullivan, P, Hellerstein, D, Hansen, L, Johansson, R, Koenig, S, Lubowski, RN et al. (2004) The Conservation Reserve Program: Economic Implications for Rural America. USDA-ERS Agricultural Economic Report. Washington, DC, USA: USDA-ERS.Google Scholar
Sutton, NJ, Cho, S, Armsworth, PR (2016) A reliance on agricultural land values in conservation planning alters the spatial distribution of priorities and overestimates the acquisition costs of protected areas. Biological Conservation 194: 2–10.CrossRefGoogle Scholar
US Bureau of Economic Analysis (2020) Interactive Data Tables – Regional Data: GDP and Personal Income [www document]. URL https://apps.bea.gov/itable/iTable.cfm?ReqID=70&step=1 Google Scholar
US Geological Survey (2016) Multi-Resolution Land Characteristics Consortium (MRLC): National Land Cover Database (NLCD) [www document]. URL http://www.mrlc.gov/data Google Scholar
US Geological Survey, Gap Analysis Project (2016) Protected Areas Database of the United States (PAD-US), Version 1.4, Combined Feature Class. Reston, VA, USA: US Geological Survey.Google Scholar
Wegner, GI (2016) Payments for ecosystem services (PES): a flexible, participatory, and integrated approach for improved conservation and equity outcomes. Environment, Development and Sustainability 18: 617–644.CrossRefGoogle Scholar
Willis, DB, Straka, TJ (2016) The economic contribution of natural resources to South Carolina’s economy [www document]. URL https://www.clemson.edu/cafls/departments/fec/news/files/fw_13-economic_contributions_of_natural_resources_2.pdf Google Scholar
Wu, J, Yu, J (2017) Efficiency–equity tradeoffs in targeting payments for ecosystem services. American Journal of Agricultural Economics 99: 894–913.CrossRefGoogle Scholar
Zhu, G, Papeş, M, Giam, X, Cho, SH, Armsworth, PR (2021) Are protected areas well-sited to support species in the future in a major climate refuge and corridor in the United States? Biological Conservation 255: 108982.CrossRefGoogle Scholar
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