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Multi-taxa population connectivity in the Northern Rocky Mountains

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  • Cushman, Samuel A.
  • Landguth, Erin L.

Abstract

Effective broad-spectrum biodiversity conservation requires that conservation strategies simultaneously meet the needs of multiple species. However, little is known about how maintaining habitat connectivity for one species or species group may also act as an umbrella for other species. We evaluated the degree to which predicted connected habitat for each of 144 different hypothetical organisms expressing range of dispersal abilities and ecological responses to elevation, roads and land cover function as an indicators of connected habitat for the others in the U.S. Northern Rocky Mountains. We used resistant kernel modeling to map the extent of the study area predicted to be connected by dispersal for each species. At relatively large dispersal abilities there was extensive overlap between connected habitat for most organisms and much of the study area is predicted to provide connected habitat for all hypothetical organisms simultaneously. In contrast, at low to medium dispersal abilities there was much less intersection of habitat connected by dispersal. We found that habitat specialists with limited dispersal ability are weak indicators of others, and likewise are weakly indicated by others. We evaluated the effectiveness of three carnivores as connectivity umbrellas for many species. All three carnivore species performed significantly worse as connectivity umbrellas than the average across the simulated species. These species are associated with high elevation forested habitats. It is the low elevation and non-forest habitats that are most at risk of habitat loss and fragmentation in the study area, suggesting that a carnivore umbrella may miss many species most at risk.

Suggested Citation

  • Cushman, Samuel A. & Landguth, Erin L., 2012. "Multi-taxa population connectivity in the Northern Rocky Mountains," Ecological Modelling, Elsevier, vol. 231(C), pages 101-112.
  • Handle: RePEc:eee:ecomod:v:231:y:2012:i:c:p:101-112
    DOI: 10.1016/j.ecolmodel.2012.02.011
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    Cited by:

    1. Drielsma, Michael J. & Love, Jamie & Taylor, Subhashni & Thapa, Rajesh & Williams, Kristen J., 2022. "General Landscape Connectivity Model (GLCM): a new way to map whole of landscape biodiversity functional connectivity for operational planning and reporting," Ecological Modelling, Elsevier, vol. 465(C).
    2. Ibagon, I. & Furlan, A.P. & Dickman, Ronald, 2022. "Reducing species extinction by connecting fragmented habitats: Insights from the contact process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).

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