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Examining how risk diversification for conservation is influenced by the probability assigned to uncertainty scenarios

Published online by Cambridge University Press:  15 September 2023

Seong-Hoon Cho Open the ORCID record for Seong-Hoon Cho [Opens in a new window] ,
Nawon Kang  and
Gengping Zhu
Seong-Hoon Cho*
Affiliation:
Department of Agricultural and Resource Economics, University of Tennessee, Knoxville, TN, USA
Nawon Kang
Affiliation:
Department of Agricultural Economics, Texas A&M University, College Station, TX, USA
Gengping Zhu
Affiliation:
Department of Entomology, Washington State University, Pullman, WA, USA
*
Corresponding author: Seong-Hoon Cho; Email: scho9@utk.edu
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Summary

Despite the progress in conservation risk management, conservation organizations are reluctant to interface usable risk-diversification strategies with their decision-making processes. One reason for this reluctance is that the empirical models used to develop risk-diversification strategies need the expected returns on investment (ROIs) of target assets and their variances and covariances, and the probabilities of occurrence of the scenarios needed to calculate those statistics are almost always unknown. We examine how risk diversification for conservation is influenced by the probabilities assigned to uncertainty scenarios using a case study involving the conservation of biodiversity at the county level in the central and southern Appalachian region within the framework of modern portfolio theory. A comparison of risk-mitigating portfolios with bootstrapped and fixed probability distributions shows that introducing the flexibility of an unknown probability distribution of uncertainty scenarios allows conservation organizations to spread bets more than with the inflexibility of the fixed probability distribution, while also achieving higher expected ROIs per unit of risk on average. The improvement becomes more significant when conservation organizations are less risk averse.

Keywords

Biodiversity conservationconservation risk managementmodern portfolio theoryprobability distributionsuncertainty scenarios
Type
Research Paper
Information
Environmental Conservation , Volume 50 , Issue 4 , December 2023 , pp. 220 - 229
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Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of Foundation for Environmental Conservation

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