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A. York (1994)
THE POPULATION DYNAMICS OF NORTHERN SEA LIONS, 1975‐1985Marine Mammal Science, 10
R. Methot (1989)
Synthetic Estimates of Historical Abundance and Mortality for Northern Anchovy
S. Haig, J. Belthoff, D. Allen (1993)
Population Viability Analysis for a Small Population of Red-Cockaded Woodpeckers and an Evaluation of Enhancement StrategiesConservation Biology, 7
N. Bonner, G. Donovan (1990)
The Comprehensive assessment of whale stocks : the early yearsJournal of Applied Ecology, 27
G. Mace, R. Lande (1991)
Assessing Extinction Threats: Toward a Reevaluation of IUCN Threatened Species CategoriesConservation Biology, 5
M. Belsky (1984)
Environmental Policy Law in the 1980's: Shifting Back the Burden of ProofEcology Law Quarterly, 12
Mark Boyce (1992)
Population Viability AnalysisAnnual Review of Ecology, Evolution, and Systematics, 23
P. Armbruster, R. Lande (1993)
A Population Viability Analysis for African Elephant (Loxodonta africana): How Big Should Reserves Be?Conservation Biology, 7
R. Deriso, T. Quinn, P. Neal (1985)
Catch-Age Analysis with Auxiliary InformationCanadian Journal of Fisheries and Aquatic Sciences, 42
J. Barlow, P. Boveng (1991)
MODELING AGE‐SPECIFIC MORTALITY FOR MARINE MAMMAL POPULATIONSMarine Mammal Science, 7
I examine whether or not it is appropriate to use extinction probabilities generated by population viability analyses, based on best estimates for model parameters, as criteria for listing species in Red Data Book categories as recently proposed by the World Conservation Union. Such extinction probabilities are influenced by how accurately model parameters are estimated and by how accurately the models depict actual population dynamics. I evaluate the effect of uncertainty in parameter estimation through simulations. Simulations based on Steller sea lions were used to evaluate bias and precision in estimates of probability of extinction and to consider the performance of two proposed classification schemes. Extinction time estimates were biased (because of violation of the assumption of stable age distribution) and underestimated the variability of probability of extinction for a given time (primarily because of uncertainty in parameter estimation). Bias and precision in extinction probabilities are important when these probabilities are used to compare the risk of extinction between species. Suggestions are given for population viability analysis techniques that incorporate parameter uncertainty. I conclude that testing classification schemes with simulations using quantitative performance objectives should precede adoption of quantitative listing criteria.
Conservation Biology – Wiley
Published: Jun 1, 1995
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