Abstract
The Point Arena mountain beaver (Aplodontia rufa nigra) is a federally listed endangered species, but has been the subject of few studies. Mountain beavers use burrows that include a single subterranean den. Foremost among the information needs for this subspecies is a description of the above-ground habitat features associated with dens. Using telemetry we located dens of 23 individuals in Manchester State Park, Mendocino County, California. We measured vegetation and topographic variables directly above the dens and at two available sites within the same burrow system. Alternative resource selection functions, based on multivariate expressions of important ecological characteristics, were developed to model features associated with dens. The best model contained three variables: MEANDENS (mean vegetation density), PAMBTOP4 (cover of the four plant species most frequently used), and COSASPECT (cosine aspect). Interestingly, PAMBTOP4 was negatively associated with dens, indicating that dens were not chosen for their proximity to important plant species. Topography plays an important role in that western and northern aspects were favored and SLOPE was included in the second-highest ranked model. Cross validation indicated moderate stability for the top model suggesting that potentially important predictors that were excluded from the analysis (e.g., soil characteristics, social context) may be influential. Nonetheless, we demonstrated that dense vegetation and aspect/slope considerations are more important predictors of Point Arena mountain beaver den selection than proximity to cover of important plant species. Our results apply to Point Arena mountain beaver populations in coastal shrub communities; den selection may be different farther inland, in forests.
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