Woodrow L. Myers | Search USGS

USGS2017

Attributes of seasonal home range influence choice of migratory strategy in white-tailed deer

Partial migration is a common life-history strategy among ungulates living in seasonal environments. The decision to migrate or remain on a seasonal range may be influenced strongly by access to high-quality habitat. We evaluated the influence of access to winter habitat of high quality on the probability of a female white-tailed deer ( Odocoileus virginianus ) migrating to a separate summer range and the effects of this decision on survival. We hypothesized that deer with home ranges of low quality in winter would have a high probability of migrating, and that survival of an individual in winter would be influenced by the quality of their home range in winter. We radiocollared 67 female white-tailed deer in 2012 and 2013 in eastern Washington, United States. We estimated home range size in winter using a kernel density estimator; we assumed the size of the home range was inversely proportional to its quality and the proportion of crop land within the home range was proportional to its quality. Odds of migrating from winter ranges increased by 3.1 per unit increase in home range size and decreased by 0.29 per unit increase in the proportion of crop land within a home range. Annual survival rate for migrants was 0.85 ( SD = 0.05) and 0.84 ( SD = 0.09) for residents. Our finding that an individual with a low-quality home range in winter is likely to migrate to a separate summer range accords with the hypothesis that competition for a limited amount of home ranges of high quality should result in residents having home ranges of higher quality than migrants in populations experiencing density dependence. We hypothesize that density-dependent competition for high-quality home ranges in winter may play a leading role in the selection of migration strategy by female white-tailed deer.

Journal of Mammalogy↗

USGS2010

Revisions of rump fat and body scoring indices for deer, elk, and moose

Because they do not require sacrificing animals, body condition scores (BCS), thickness of rump fat (MAXFAT), and other similar predictors of body fat have advanced estimating nutritional condition of ungulates and their use has proliferated in North America in the last decade. However, initial testing of these predictors was too limited to assess their reliability among diverse habitats, ecotypes, subspecies, and populations across the continent. With data collected from mule deer ( Odocoileus hemionus ), elk ( Cervus elaphus ), and moose ( Alces alces ) during initial model development and data collected subsequently from free-ranging mule deer and elk herds across much of the western United States, we evaluated reliability across a broader range of conditions than were initially available. First, to more rigorously test reliability of the MAXFAT index, we evaluated its robustness across the 3 species, using an allometric scaling function to adjust for differences in animal size. We then evaluated MAXFAT, rump body condition score (rBCS), rLIVINDEX (an arithmetic combination of MAXFAT and rBCS), and our new allometrically scaled rump-fat thickness index using data from 815 free-ranging female Roosevelt and Rocky Mountain elk ( C. e. roosevelti and C. e. nelsoni ) from 19 populations encompassing 4 geographic regions and 250 free-ranging female mule deer from 7 populations and 2 regions. We tested for effects of subspecies, geographic region, and captive versus free-ranging existence. Rump-fat thickness, when scaled allometrically with body mass, was related to ingesta-free body fat over a 38–522-kg range of body mass ( r 2 = 0.87; P < 0.001), indicating the technique is remarkably robust among at least the 3 cervid species of our analysis. However, we found an underscoring bias with the rBCS for elk that had >12% body fat. This bias translated into a difference between subspecies, because Rocky Mountain elk tended to be fatter than Roosevelt elk in our sample. Effects of observer error with the rBCS also existed for mule deer with moderate to high levels of body fat, and deer body size significantly affected accuracy of the MAXFAT predictor. Our analyses confirm robustness of the rump-fat index for these 3 species but highlight the potential for bias due to differences in body size and to observer error with BCS scoring. We present alternative LIVINDEX equations where potential bias from rBCS and bias due to body size are eliminated or reduced. These modifications improve the accuracy of estimating body fat for projects intended to monitor nutritional status of herds or to evaluate nutrition's influence on population demographics.

Journal of Wildlife Diseases↗