Modeling demographic processes in an endangered population of bighorn sheep

Esther S. Rubin, Walter M Boyce, Edward P. Caswell-Chen

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


We developed a demographic simulation model to explore how population vital rates, initial size, and the addition of animals influenced the viability of an endangered population of bighorn sheep (Ovis canadensis) consisting of 8 subpopulations. Perturbation analyses indicated that quasi-extinction risk was more sensitive to changes in adult female survival than to changes in reproduction or survival of young animals. This pattern was similar in 8 subpopulations that had different initial sizes, survival rates, and recruitment rates. Subpopulation viability was related to the initial number of females and to adult female survival, but not reproduction. Management actions that increase adult survival may be most effective when implemented in the largest subpopulations, whereas actions involving the addition of animals may be most effective if implemented in subpopulations with high survival rates. Subpopulation augmentation in yearly increments was more effective at reducing quasi-extinction risk than was adding the same total number of animals at the beginning of the simulation. The level of augmentation needed to substantially reduce quasi-extinction risk exceeded reported levels of female movement among populations or subpopulations. This finding led us to speculate that rescue effects, which are uncommon events for bighorn sheep, may be too rare or of inadequate magnitude under current conditions to effectively reverse bighorn sheep population declines.

Original languageEnglish (US)
Pages (from-to)796-810
Number of pages15
JournalJournal of Wildlife Management
Issue number3
StatePublished - Jul 2002
Externally publishedYes


  • Bighorn sheep
  • California
  • Demographic model
  • Mountain sheep
  • Ovis canadensis
  • Peninsular Ranges
  • Population viability

ASJC Scopus subject areas

  • Animal Science and Zoology
  • Ecology


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