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The Ghost of Extinction: Preservation Values and Minimum Viable Population in Wildlife Models

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  • van Kooten, G. Cornelis
  • Eiswerth, Mark E.

Abstract

The inclusion of a minimum viable population in bioeconomic modeling creates at least two complications that are not resolved by using a modified logistic growth function. The first complication can be dealt with by choosing a different depensational growth function. The second complication relates to the inclusion of the in situ benefits of wildlife into the analysis. Knowledge about the magnitude of the in situ benefits provides no guide for policy about conservation management. Simply knowing that people are willing to pay a large amount each year to protect a species says nothing about whether one should manage habitat to protect or enhance the species’ numbers, unless the species is in imminent danger of extinction. If willingness to pay is to be a guide, it needs to be better tied to population numbers, especially the minimum viable population.

Suggested Citation

  • van Kooten, G. Cornelis & Eiswerth, Mark E., 2008. "The Ghost of Extinction: Preservation Values and Minimum Viable Population in Wildlife Models," Working Papers 37912, University of Victoria, Resource Economics and Policy.
    • Handle: RePEc:ags:uvicwp:37912
    DOI: 10.22004/ag.econ.37912
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    References listed on IDEAS

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    1. Bulte, Erwin H. & van Kooten, G. Cornelis, 2001. "Harvesting and conserving a species when numbers are low: population viability and gambler's ruin in bioeconomic models," Ecological Economics, Elsevier, vol. 37(1), pages 87-100, April.
    2. Léonard,Daniel & Long,Ngo van, 1992. "Optimal Control Theory and Static Optimization in Economics," Cambridge Books, Cambridge University Press, number 9780521331586, October.
    3. Loomis, John B. & White, Douglas S., 1996. "Economic benefits of rare and endangered species: summary and meta-analysis," Ecological Economics, Elsevier, vol. 18(3), pages 197-206, September.
    4. Erwin Bulte & G. van Kooten, 1999. "Marginal Valuation of Charismatic Species: Implications for Conservation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 14(1), pages 119-130, July.
    5. David J. Bjornstad & James R. Kahn (ed.), 1996. "The Contingent Valuation of Environmental Resources," Books, Edward Elgar Publishing, number 731.
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    Cited by:

    1. Yuzhakov, Vladimir (Южаков, Владимир) & Startsev, Y (Старцев, Я.), 2015. "Development of a Concept of an Interdisciplinary Research Program of Formation of Complex Methodologies and Techniques of Management Development in Public Administration [Разработка Концепции Межди," Published Papers mn37, Russian Presidential Academy of National Economy and Public Administration.
    2. Abbott, Brant & van Kooten, G. Cornelis, 2011. "Can domestication of wildlife lead to conservation? The economics of tiger farming in China," Ecological Economics, Elsevier, vol. 70(4), pages 721-728, February.
    3. Naald, Brian Vander & Cameron, Trudy Ann, 2011. "Willingness to pay for other species' well-being," Ecological Economics, Elsevier, vol. 70(7), pages 1325-1335, May.
    4. Adrian A. Lopes & Shady S. Atallah, 2020. "Worshipping the Tiger: Modeling Non-use Existence Values of Wildlife Spiritual Services," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(1), pages 69-90, May.
    5. Donovan, Pierce & Springborn, Michael, 2022. "Balancing conservation and commerce: A shadow value viability approach for governing bycatch," Journal of Environmental Economics and Management, Elsevier, vol. 114(C).

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    More about this item

    Keywords

    Environmental Economics and Policy;

    JEL classification:

    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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