Assessment of predictive habitat models for bighorn sheep in California's peninsular ranges

Esther S. Rubin, Chris J. Stermer, Walter M Boyce, Steven G. Torres

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


We developed predictive habitat models for a bighorn sheep (Ovis canadensis) population in the Peninsular Ranges of southern California, USA, using 2 Geographic Information System modeling techniques, Ecological Niche Factor Analysis (ENFA) and Genetic Algorithm for Rule-set Production (GARP). We used >16,000 Global Positioning System locations from 34 animals in 5 subpopulations to develop and test ENFA and GARP models, and we then compared these models to each other and to the expert-based model presented in the United States Fish and Wildlife Service's Recovery Plan for this population. Based on a suite of evaluation methods, we found both ENFA and GARP to provide useful predictions of habitat; however, models developed with GARP appeared to have higher predictive power. Habitat delineations resulting from GARP models were similar to the expert-based model, affirming that the expert-based model provided a useful delineation of bighorn sheep habitat in the Peninsular Ranges. In addition, all 3 models identified continuous bighorn sheep habitat from the northern to southern extent of our study area, indicating that the Recovery Plan's recommendation of maintaining habitat connectivity throughout the range is an appropriate goal.

Original languageEnglish (US)
Pages (from-to)859-869
Number of pages11
JournalJournal of Wildlife Management
Issue number6
StatePublished - Aug 2009


  • Bighorn sheep
  • Biomapper
  • California
  • Expert-based model
  • GARP
  • Habitat model
  • Ovis canadensis

ASJC Scopus subject areas

  • Nature and Landscape Conservation
  • Ecology
  • Ecology, Evolution, Behavior and Systematics


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