Population Estimates of Snowshoe Hares in the Southern Rocky Mountains

Abstract In 1999 Canada lynx (Lynx canadensis) were reintroduced to the southern Rocky Mountains and in 2000 the species was listed as threatened under the Endangered Species Act in the contiguous United States (Colorado Division of Wildlife 2000, U.S. Fish and Wildlife Service 2000). To better evaluate the progress of this reintroduction, we conducted field studies to estimate population densities of snowshoe hares (Lepus americanus), the primary prey of lynx in Colorado, USA. We conducted our field studies in southwestern Colorado in winters 2002 and 2003. We estimated population densities in forested stands of mature Engelmann spruce (Picea engelmannii)–subalpine fir (Abies lasiocarpa) and mature lodgepole pine (Pinus contorta) using mark–recapture data and 3 methods for estimating effective area trapped: half trap interval, mean maximum distance moved (MMDM), and half MMDM. In Engelmann spruce–subalpine fir, we found density estimates ranged from 0.08 ± 0.03 (SE) hares/ha to 1.32 ± 0.15 hares/ha and in lodgepole pine, density estimates ranged from 0.06 ± 0.01 hares/ha to 0.34 ± 0.06 hares/ha, depending on year and method used for estimating effective area trapped. Our density estimates are similar to those reported at the low phase of the hare cycle in populations to the north (<0.1–1.1 hares/ha), where Canada lynx persist (Hodges 2000a). Although density estimates are a useful comparative tool, they depend upon methods used to estimate effective area trapped. Therefore, we urge caution in comparing our density estimates with those from other areas, which may have used dissimilar methods. We also examined effects of temperature and moon phase on capture success of snowshoe hares; extremely low temperatures affected capture success but moon phase did not. Capture success can be improved by trapping snowshoe hares at temperatures above their lower critical temperature (Tlc). If abundance estimates are derived from mark–recapture studies then effects of temperature should be included when modeling capture probabilities.