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Quasiextinction Probabilities as a Measure of Impact on Population Growth

Author

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  • Lev R. Ginzburg
  • Lawrence B. Slobodkin
  • Keith Johnson
  • Andrew G. Bindman

Abstract

A probabilistic language based on stochastic models of population growth is proposed for a standard language to be used in environmental assessment. Environmental impact on a population is measured by the probability of quasiextinction. Density‐dependent and independent models are discussed. A review of one‐dimensional stochastic population growth models, the implications of environmental autocorrelation, finite versus “infinite” time results, age‐structured models, and Monte Carlo simulations are included. The finite time probability of quasiextinction is presented for the logistic model. The sensitivity of the result with respect to the mean growth rate and the amplitude of environmental fluctuations are examined. Stochastic models of population growth form a basis for formulating reasonable criteria for environmental impact estimates.

Suggested Citation

  • Lev R. Ginzburg & Lawrence B. Slobodkin & Keith Johnson & Andrew G. Bindman, 1982. "Quasiextinction Probabilities as a Measure of Impact on Population Growth," Risk Analysis, John Wiley & Sons, vol. 2(3), pages 171-181, September.
    • Handle: RePEc:wly:riskan:v:2:y:1982:i:3:p:171-181
    DOI: 10.1111/j.1539-6924.1982.tb01379.x
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    Cited by:

    1. Grant G. Thompson & Lynn A. Maguire & Tracey J. Regan, 2018. "Evaluation of Two Approaches to Defining Extinction Risk under the U.S. Endangered Species Act," Risk Analysis, John Wiley & Sons, vol. 38(5), pages 1009-1035, May.
    2. Peter L. Boveng & Jay M. Ver Hoef & David E. Withrow & Josh M. London, 2018. "A Bayesian Analysis of Abundance, Trend, and Population Viability for Harbor Seals in Iliamna Lake, Alaska," Risk Analysis, John Wiley & Sons, vol. 38(9), pages 1988-2009, September.
    3. Christopher A. Mebane, 2010. "Relevance of Risk Predictions Derived from a Chronic Species Sensitivity Distribution with Cadmium to Aquatic Populations and Ecosystems," Risk Analysis, John Wiley & Sons, vol. 30(2), pages 203-223, February.
    4. Charles Sims & David Finnoff & Jason F. Shogren, 2018. "Taking One for the Team: Is Collective Action More Responsive to Ecological Change?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 70(3), pages 589-615, July.
    5. Charles Sims & David Finnoff & Alan Hastings & Jacob Hochard, 2017. "Listing and Delisting Thresholds under the Endangered Species Act," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 549-570.
    6. Karim, Md Aktar Ul & Aithal, Vikram & Bhowmick, Amiya Ranjan, 2023. "Random variation in model parameters: A comprehensive review of stochastic logistic growth equation," Ecological Modelling, Elsevier, vol. 484(C).
    7. Mark Burgman & James Franklin & Keith R. Hayes & Geoffrey R. Hosack & Gareth W. Peters & Scott A. Sisson, 2012. "Modeling Extreme Risks in Ecology," Risk Analysis, John Wiley & Sons, vol. 32(11), pages 1956-1966, November.

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