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Spatial and taxonomic diversification for conservation investment under uncertainty

Published online by Cambridge University Press:  16 May 2022

Nawon Kang
Affiliation:
Department of Agricultural and Resource Economics, The University of Tennessee, Knoxville, TN, USA
Charles Sims
Affiliation:
Howard H. Baker Jr. Center for Public Policy, Department of Economics, The University of Tennessee, Knoxville, TN, USA
Seong-Hoon Cho*
Affiliation:
Department of Agricultural and Resource Economics, The University of Tennessee, Knoxville, TN, USA
*
Author for correspondence: Professor Seong-Hoon Cho, Email: [email protected]

Summary

Conservation organizations often need to develop risk-diversification strategies that identify not just what species to protect but also where to protect them. The objective of this research is to identify optimal conservation investment allocations for both target sites and species under conditions of uncertainty. We develop a two-step approach using modern portfolio theory (MPT) to estimate percentages of conservation investment (referred to as ‘portfolio weights’) for counties and taxonomic groups in the central and southern Appalachian region under climate and market uncertainties. The portfolio weights across the counties and taxonomic groups from the two steps entail both spatial and taxonomic diversification strategies. Conservation decisions that allow for selecting sites for risk diversification fit the purpose of the first step. Likewise, conservation investments that benefit the biodiversity of particular taxonomic groups for the selected sites are made based on the relative importance of diversifying risk among species in a given area, fitting the purpose of the second step. The two-step MPT approach as a whole allows the greatest flexibility on where and what to protect for conservation investment under uncertainty, and thus would be applicable for the distribution of general conservation funds without predisposition towards protecting either specific sites or species.

Type
Research Paper
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Foundation for Environmental Conservation

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References

Anderson, MG, Clark, M, Sheldon, AO (2014) Estimating climate resilience for conservation across geophysical settings. Conservation Biology 28: 959970.10.1111/cobi.12272CrossRefGoogle ScholarPubMed
Ando, AW, Fraterrigo, J, Guntenspergen, G, Howlader, A, Mallory, M, Olker, JH, Stickley, S (2018) When portfolio theory can help environmental investment planning to reduce climate risk to future environmental outcomes – and when it cannot. Conservation Letters 11: e12596.10.1111/conl.12596CrossRefGoogle Scholar
Ando, AW, Mallory, ML (2012) Optimal portfolio design to reduce climate-related conservation uncertainty in the Prairie Pothole Region. Proceedings of the National Academy of Sciences of the United States of America 109: 64846489.CrossRefGoogle ScholarPubMed
Bai, L, Xiu, C, Feng, X, Liu, D (2019) Influence of urbanization on regional habitat quality: a case study of Changchun City. Habitat International 93: 102042.CrossRefGoogle Scholar
Beyer, HL, Kennedy, EV, Beger, M, Chen, CA, Cinner, JE, Darling, ES et al. (2018) Risk-sensitive planning for conserving coral reefs under rapid climate change. Conservation Letters 11: e12587.CrossRefGoogle Scholar
Boland, C, Burwell, B (2020) Ranking and mapping the high conservation priority bird species of Saudi Arabia. Avian Conservation and Ecology 15: 18.CrossRefGoogle Scholar
Chemini, C, Rizzoli, A (2014) Land use change and biodiversity conservation in the Alps. Journal of Mountain Ecology 7: 17.Google Scholar
Chen, X, Lupi, F, Viña, A, He, G, Liu, J (2010) Using cost-effective targeting to enhance the efficiency of conservation investments in payments for ecosystem services. Conservation Biology 24: 14691478.CrossRefGoogle ScholarPubMed
Cho, S, Lee, J, Roberts, R, Yu, ET, Armsworth, PR (2018) Impact of market conditions on the effectiveness of payments for forest-based carbon sequestration. Forest Policy and Economics 92: 3342.CrossRefGoogle Scholar
Cuesta, F, Peralvo, M, Merino-Viteri, A, Bustamante, M, Baquero, F, Freile, JF et al. (2017) Priority areas for biodiversity conservation in mainland Ecuador. Neotropical Biodiversity 3: 93106.CrossRefGoogle Scholar
Dale, S (2018) Urban bird community composition influenced by size of urban green spaces, presence of native forest, and urbanization. Urban Ecosystems 21: 114.10.1007/s11252-017-0706-xCrossRefGoogle Scholar
Eaton, MJ, Yurek, S, Haider, Z, Martin, J, Johnson, FA, Udell, BJ et al. (2019) Spatial conservation planning under uncertainty: adapting to climate change risks using modern portfolio theory. Ecological Applications 29: e01962.10.1002/eap.1962CrossRefGoogle ScholarPubMed
GCF (2021) Global Conservation Fund [www document]. URL https://www.conservation.org/about/global-conservation-fund Google Scholar
Gordon, ER, Butt, N, Rosner-Katz, H, Binley, AD, Bennett, JR (2020) Relative costs of conserving threatened species across taxonomic groups. Conservation Biology 34: 276281.CrossRefGoogle ScholarPubMed
IUCN (2012) Guidelines for Application of IUCN Red List Criteria at Regional and National Levels: Version 4.0. Gland, Switzerland and Cambridge, UK: IUCN.Google Scholar
IUCN (2021a) Species Threat Abatement and Restoration (STAR) Metric [www document]. URL https://www.iucn.org/resources/conservation-tools/species-threat-abatement-and-restoration-star-metric Google Scholar
IUCN (2021b) The Mediterranean Red List of Species [www document]. URL https://www.iucnredlist.org/regions/mediterranean Google Scholar
IUCN Standards and Petitions Committee (2019) Guidelines for Using the IUCN Red List Categories and Criteria. Version 14. Prepared by the Standards and Petitions Committee [www document]. URL http://www.iucnredlist.org/documents/RedListGuidelines.pdf Google Scholar
Keyser, TJ, Malone, J, Cotton, C, Lewis, J (2014) Outlook for Appalachian–Cumberland forests: a subregional report from the Southern Forest Futures Project. Gen. Tech. Rep. SRS-GTR-188. Asheville, NC, USA: USDA Forest Service, Southern Research Station.CrossRefGoogle Scholar
Koellner, T, Schmitz, OJ (2006) Biodiversity, ecosystem function, and investment risk. BioScience 56: 977.CrossRefGoogle Scholar
Mallory, ML, Ando, AW (2014) Implementing efficient conservation portfolio design. Resource and Energy Economics 38: 118.CrossRefGoogle Scholar
Moore, JW, McClure, M, Rogers, LA, Schindler, DE (2010) Synchronization and portfolio performance of threatened salmon. Conservation Letters 3: 340348.CrossRefGoogle Scholar
Moritz, C, Agudo, R (2013) The future of species under climate change: resilience or decline? Science 341: 504508.CrossRefGoogle ScholarPubMed
Northrup, JM, Rivers, JW, Yang, Z, Betts, MG (2019) Synergistic effects of climate and land-use change influence broad-scale avian population declines. Global Change Biology 25: 15611575.10.1111/gcb.14571CrossRefGoogle ScholarPubMed
Pacifici, M, Visconti, P, Butchart, SHM, Watson, JEM, Cassola, FM, Rondinini, C (2017) Species’ traits influenced their response to recent climate change. Nature Climate Change 7: 205208.CrossRefGoogle Scholar
Power, RP, Jetz, W (2019). Global habitat loss and extinction risk of terrestrial vertebrates under future land-use-change scenarios. Nature Climate Change 9: 323329.CrossRefGoogle Scholar
Salzman, J, Bennett, G, Carroll, N, Goldstein, A, Jenkins, M (2018) The global status and trends of payments for ecosystem services. Nature Sustainability 1: 136144.CrossRefGoogle Scholar
Sanchirico, JN, Smith, MD, Lipton, DW (2008) An empirical approach to ecosystem-based fishery management. Ecological Economics 64: 586596.CrossRefGoogle Scholar
Schindler, DE, Hilborn, R, Chasco, B, Boatright, CP, Quinn, TP, Rogers, LA, Webster, MS (2010) Population diversity and the portfolio effect in an exploited species. Nature 465: 609612.CrossRefGoogle Scholar
Schuster, R, Hanson, JO, Strimas-Mackey, M, Bennett, JR (2020) Exact integer linear programming solvers outperform simulated annealing for solving conservation planning problems. PeerJ 8: e9258.CrossRefGoogle ScholarPubMed
Scroggie, MP, Preece, K, Nicholson, E, McCarthy, MA, Parris, KM, Heard, GW (2019) Optimizing habitat management for amphibians: from simple models to complex decisions. Biological Conservation 236: 6069.CrossRefGoogle Scholar
Shah, P, Mallory, ML, Ando, AW, Guntenspergen, GR (2017) Fine-resolution conservation planning with limited climate change-change information. Conservation Biology 31: 278289.CrossRefGoogle Scholar
Sharma, BP, Cho, SH (2020) Using portfolio theory in spatial targeting of forest carbon payments: an effective strategy to address spatiotemporal variation in land-use opportunity costs? Canadian Journal of Forest Research 50: 170184.CrossRefGoogle Scholar
Urban, MC (2015) Accelerating extinction risk from climate change. Science 348: 571573.CrossRefGoogle ScholarPubMed
Vinent, OD, Johnston, RJ, Kirwan, ML, Leroux, AD, Martin, VL (2019) Coastal dynamics and adaptation to uncertain sea level rise: optimal portfolios for salt marsh migration. Journal of Environmental Economics and Management 98: 102262.CrossRefGoogle Scholar
Wear, DN, Greis, JG (2013) The Southern Forest Futures Project: Technical Report. Gen. Tech. Rep. SRS-GTR-178. Asheville, NC, USA: USDA Forest Service, Southern Research Station.CrossRefGoogle Scholar
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