Journal article
On estimating critical population size for an endangered species in the presence of environmental stochasticity
Mathematical biosciences, v 85(2)
1987
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
A stationary second order autoregressive process with Gaussian noise, which was linked to survivorship and reproductive success by logistic transformations, was used as a model for an environmental process. Computer experiments in Monte Carlo integration, with the objective of exploring the sensitivity of estimates of mean critical population size to variations in the parameters of the environmental process, were then conducted. These experiments suggest that estimates of mean critical population size are very sensitive to the form of the autocorrelation function of the stationary environmental process. For the most part, those experiments in which the autocorrelation function was strictly positive not only resulted in the largest estimates of mean critical population size but also led to the highest levels of environmental stochasticity as measured by its coefficient of variation. As in previous work, these experiments suggest that concerted efforts should be made to model those environmental factors that are critical to the survivability of an endangered species in assessing its chances for continued existence.
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Details
- Title
- On estimating critical population size for an endangered species in the presence of environmental stochasticity
- Creators
- Charles J. Mode - Drexel UniversityMarc E. Jacobson - University of Pennsylvania
- Publication Details
- Mathematical biosciences, v 85(2)
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- [Retired Faculty]
- Web of Science ID
- WOS:A1987K531700004
- Scopus ID
- 2-s2.0-38249033509
- Other Identifier
- 991019173517804721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Biology
- Mathematical & Computational Biology