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16 April 2010 Habitat selection of rodents along a piñon–juniper woodland–savannah gradient
Thomas J. Rodhouse, Robert P. Hirnyck, R. Gerald Wright
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The biodiversity of piñon–juniper (P-J) woodlands of western North America has received increasing attention from conservationists because of concerns about woodland invasion into adjacent shrub-steppe communities. Small mammals contribute substantially to the faunal diversity of P-J woodlands, but the responses of small mammals to the inherent structural complexity of these woodlands have not been well described. We used occupancy modeling and ordination to describe habitat selection along a woodland–savannah gradient of 4 species of rodents, including 2 putative P-J woodland specialists, Peromyscus truei and Tamias dorsalis. We accounted for the influences of season and prior conspecific capture on detectability. P. truei and T. dorsalis preferred old-growth woodland sites near rock outcrops with high canopy and bare-ground cover and low herb and shrub cover. Tamias minimus preferred savannah sites with high shrub and grass cover farther from rock outcrops. We found no evidence of resource selection along the gradient by Perognathus parvus. Our results provide insight into the role of habitat selection in facilitating coexistence among closely related species within P-J woodlands and suggest that management efforts that better discriminate between old, presettlement stands and young, invasive stands may enhance regional biodiversity. We demonstrate an effective application of occupancy modeling for describing habitat selection of cryptic rodents, which are particularly prone to imperfect detection.

Thomas J. Rodhouse, Robert P. Hirnyck, and R. Gerald Wright "Habitat selection of rodents along a piñon–juniper woodland–savannah gradient," Journal of Mammalogy 91(2), 447-457, (16 April 2010).
Received: 18 February 2009; Accepted: 1 August 2009; Published: 16 April 2010
detection probability
habitat selection
occupancy modeling
Peromyscus truei
piñon–juniper woodland
principal component analysis
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