JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. Allen Press is collaborating with JSTOR to digitize, preserve and extend access to The Journal of Wildlife Management.Abstract: Kernel methods for estimating home range are being used increasingly in wildlife research, but the effect of sample size on their accuracy is not known. We used computer simulations of 10-200 points/ home range and compared accuracy of home range estimates produced by fixed and adaptive kernels with the reference (REF) and least-squares cross-validation (LSCV) methods for determining the amount of smoothing. Simulated home ranges varied from simple to complex shapes created by mixing bivariate normal distributions. We used the size of the 95% home range area and the relative mean squared error of the surface fit to assess the accuracy of the kernel home range estimates. For both measures, the bias and variance approached an asymptote at about 50 observations/home range. The fixed kernel with smoothing selected by LSCV provided the least-biased estimates of the 95% home range area. All kernel methods produced similar surface fit for most simulations, but the fixed kernel with LSCV had the lowest frequency and magnitude of very poor estimates. We reviewed 101 papers published in The Journal of Wildlife Management (JWM) between 1980 and 1997 that estimated animal home ranges. A minority of these papers used nonparametric utilization distribution (UD) estimators, and most did not adequately report sample sizes. We recommend that home range studies using kernel estimates use LSCV to determine the amount of smoothing, obtain a minimum of 30 observations per animal (but preferably -50), and report sample sizes in published results. JOURNAL OF WILDLIFE MANAGEMENT 63(2):739-747

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Understanding herd organization is important when considering management alternatives designed to benefit or manipulate elk (Cervus elaphus) populations. We studied the seasonal and annual herd organization of cow elk in Custer State Park, South Dakota from 1993–1997 by examining seasonal subherd range size, spatial arrangement, overlap, and site fidelity. Based on social interaction analyses, we combined locations of radiocollared cow elk to delineate subherds. We computed 95% kernel home ranges with least‐squares cross validation for each subherd by season and year. Subherd overlap and fidelity by season and year were computed using the Volume of Intersection Index (VI) statistic. We identified 5 relatively discrete, resident cow‐calf subherds. We observed little overlap in utilization distributions of adjacent subherds. The mean VI score across all subherds and time points (n=140) was 0.06 (SE=0.009), indicating an average 6% overlap in subherd area utilization. Subherd overlap between pairs was 0.08 in fall (SE=0.021), 0.06 in winter (SE=0.018), 0.06 in spring (SE=0.2), and 0.05 in summer (SE=0.016). Range sizes were not different between any pairs of seasons or years (F13,52=0.7, P=0.75). Subherd fidelity ranged from 0.41 (SE=0.033) to 0.60 (SE=0.018) overall, indicating differential use within the subherd boundary across years. The ability to distinguish discrete cow‐calf subherd units is consistent with other studies and may aid elk management in Custer State Park. However, use patterns within subherd boundaries were inconsistent across years and may reflect human disturbances (e.g., hunting and logging activities), differences in our sampling approach, or changes in matriarchal leadership. Further evaluation into factors affecting space‐use patterns is necessary to predict changes in range use within the subherd boundary.

We used cohort analysis to reconstruct a Columbian black‐tailed deer (Odocoileus hemionus columbianus) population from 1979 to 1999 in the western Cascade Range, Washington, USA. We used reconstructed population estimates and age‐class representations to analyze relationships among fawn recruitment, deer density, forage availability, and weather influences during the fawning period. Fawn recruitment was found to be significantly correlated with deer density the previous year as well as available forage in the previous year. Weather variables that described cold temperatures early in the fawning period and high precipitation levels during the prime fawning period were found to negatively affect fawn recruitment. Models could be used to assist with management of black‐tailed deer by providing an estimate of cohort strength when productivity survey methods prove difficult.