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.

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Most wild Rocky Mountain big-horn sheep (Ovis canadensis canadensis) in northern latitudes are infected with lungworms. Indirect effects of lungworms on bighorn sheep are unknown, but high pulmonary burdens might increase stress (i.e., elevated glucocorticoid levels), and chronic stress could in turn decrease fitness. We hypothesized that high lungworm burdens in Rocky Mountain bighorn ewes increase stress, thereby increasing lamb mortality. To test our hypothesis, one subherd of bighorn sheep in Custer State Park, South Dakota was provided a free-choice loose mineral mix containing the anthelmintic fenbendazole every six weeks from March 1999 to August 2000 to eliminate lungworms; another subherd served as the control. Daily, individually marked ewes were located telemetrically from the ground and uniquely marked animals were observed until they defecated. After the herd moved from the area, fecal samples were collected and stored at Ϫ23 C. A consistent number of samples per season per herd (xϭ16.56Ϯ3.99 samples) were collected. Fecal larval lungworm levels (LPG) in the treatment subherd were lower than levels in the control subherd; however, there was no difference in fecal glucocorticoid metabolite (FGM) levels between the two subherds. Fecal glucocorticoid metabolite levels varied by season in both subherds, with levels in winter lower than during the other three seasons. Lamb:ewe ratios were not different between the control and treatment subherds at the end of summer 1999. In contrast, the treatment group had a lower lamb:ewe ratio at the end of summer 2000 despite having lower LPG. However, this result was attributed to lower ewe production, not lower lamb survival. The LPG levels were not correlated with FGM concentrations; instead, FGM levels might reflect normal seasonal patterns. Other factors, including contagious ecthyma, were more important for determining lamb mortality than LPG and FGM levels during our study. We suggest further experimental work over a longer duration to address these relationships.

You may order additional copies of this publication by sending your mailing information in label form through one of the following media. Please specify the publication title and series number. Fort Collins Service Center AbstractWildlife habitat modeling is increasingly important for managers who need to assess the effects of land management activities. We evaluated the performance of a spatially explicit deterministic habitat model (Arc-Habcap) that predicts habitat effectiveness for elk. We used five years of radio-telemetry locations of elk from Custer State Park (CSP), South Dakota, to test predicted habitat effectiveness by the model. Arc-Habcap forage and coverforage proximity components predicted elk distribution in CSP. However, the cover component failed to predict elk distribution in CSP. Habitat effectiveness calculated as the geometric mean of the model components failed to predict elk distribution and resulted in under-utilization of habitats predicted to be good and over-utilization of habitats predicted to be poor. We developed a new formula to calculate habitat effectiveness as an arithmetic average of the model components that weighted forage more than cover or cover-forage proximity. The new formula predicted actual elk distribution across categories of habitat effectiveness. Elk selected cover and forage areas ≤100 m from cover-forage edges. Arc-Habcap predicted that areas adjacent to roads were not usable by elk. Elk used areas adjacent to primary roads, but use was less than the proportional area comprised for primary roads, and about equal to proportional area adjacent to secondary roads and primitive roads. All sapling/pole and mature structural stages of ponderosa pine (Pinus ponderosa) were considered as both forage and cover by Arc-Habcap and consequently considered optimal in the cover-forage model component. We suggested revisions for both the cover-forage proximity component and areas adjacent to roads.