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Factors leading to different viability predictions for a grizzly bear data set

Conservation Biology

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Abstract

Population viability analysis programs are being used increasingly in research and management applications, but there has not been a systematic study of the congruence of different program predictions based on a single data set. We performed such an analysis using four population viability analysis computer programs: GAPPS, INMAT, RAMAS/AGE, and VORTEX. The standardized demographic rates used in all programs were generalized from hypothetical increasing and decreasing grizzly bear (Ursus arctos horribilis) populations. Idiosyncracies of input format for each program led to minor differences in intrinsic growth rates that translated into striking differences in estimates of extinction rates and expected population size. In contrast, the addition of demographic stochasticity, environmental stochasticity, and inbreeding costs caused only a small divergence in viability predictions. But, the addition of density dependence caused large deviations between the programs despite our best attempts to use the same density-dependent functions. Population viability programs differ in how density dependence is incorporated, and the necessary functions are difficult to parameterize accurately. Thus, we recommend that unless data clearly suggest a particular density-dependent model, predictions based on population viability analysis should include at least one scenario without density dependence. Further, we describe output metrics that may differ between programs; development of future software could benefit from standardized input and output formats across different programs.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Factors leading to different viability predictions for a grizzly bear data set
Series title:
Conservation Biology
Volume
10
Issue:
3
Year Published:
1996
Language:
English
Contributing office(s):
Forest and Rangeland Ecosystem Science Center
Description:
p. 863-873
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Conservation Biology
First page:
863
Last page:
873
Number of Pages:
11