Abstract. Kernel density estimators are becoming more widely used, particularly as h?I?e range estimators. Despite extensive interest in their theoretical properties, little empmcal research has been done to investigate their performance as home range estimators. We used computer simulations to compare the area and shape of kernel density estimates to the true area and shape of multimodal two-dimensional distributions. The fixed kernel gave area estimates with very little bias when least squares cross validation was used to se_lect the smoothing parameter. The cross-validated fixed kernel also gave surface estimates with the lowest error. The adaptive kernel overestimated the area of the distribution and had higher error associated with its surface estimate.

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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Studying one of two bear species not experiencing widespread population decline, provides insight into the population responses of the six bear species that are in decline and into responses of other long‐lived species for which data are difficult to collect. Black bear (Ursus americanus) sanctuaries were established in North Carolina (U.S.) in 1971 to protect core populations of bears and to provide dispersing bears for hunting. Population index values, derived from counts of bears visiting bait stations, were significantly greater inside the Pisgah Bear Sanctuary than outside and were greater along trails than along roads. Survivorship of bears outfitted with transmitter collars was greater for sanctuary bears alone than for sanctuary plus non‐sanctuary bears. Monte Carlo analyses of Leslie matrices showed that the bear population in the sanctuary would be stable if cub survivorship, p0, was about O.7, and the population in the sanctuary plus the surrounding area would be stable if p0 was about 0.83. Estimates of litter survivorship in North Carolina indicate, however, that p0 can not exceed O.71. Overall, the matrix analyses indicated an ultimate population decline in the total bear population (sanctuary plus surrounding area). The population index of the bait station did not show a discernible decline. The Pisgah Bear Sanctuary provides dispersing bears for hunters and provides some protection for the resident bears. The sanctuary may not, however, provide resident bears with enough protection to maintain a viable breeding population within its boundaries. Reducing human access to bears and their habitat appears crucial, either by making large sanctuaries or by eliminating roads.

We analyzed likely patterns of distribution and persistence of northern spotted owls (Strix occidentalis caurina) on the Olympic Peninsula. Analysis focused on the effects of Federal habitat under provisions of the Northwest Forest Plan; additional benefits to the owl population of different levels of habitat retention on non-Federal lands; effects of establishing a habitat connection between the Olympic Peninsula and other parts of the owl's range; the likely rate of habitat regrowth in the National Forest and its effect on the owl population; and the likely effect of a worst-case fire. We used a spatially explicit population model for northern spotted owls for the analysis and also reviewed current information on demographics and likely owl population numbers on the Olympic Peninsula. We concluded that it is likely, but not assured, that a stable population of northern spotted owls would be maintained in portions of the Olympic National Forest and the Olympic National Park in the absence of any non-Federal contribution of habitat, and that the retention of non-Federal habitat would make a biologically significant contribution to the maintenance of the population. Finally, we concluded that a habitat connection across southwestern Washington, based on the design proposed by the Northern Spotted Owl Recovery Team, would have little effect on the status of the owl population on the peninsula if that population was stable or nearly stable.

Loss of genetic variability in isolated populations is an important issue for conservation biology. Most studies involve only a single population of a given species and a single method of estimating rate of loss. Here we present analyses for three different Red‐cockaded Woodpecker (Picoides borealis) populations from different geographic regions. We compare two different models for estimating the expected rate of loss of genetic variability, and test their sensitivity to model parameters. We found that the simpler model (Reed et al. 1988) consistently estimated a greater rate of loss of genetic variability from a population than did the Emigh and Pollak (1979) model. The ratio of effective population size (which describes the expected rate of loss of genetic variability) to breeder population size varied widely among Red‐cockaded Woodpecker populations due to geographic variation in demography. For this species, estimates of effective size were extremely sensitive to survival parameters, but not to the probability of breeding or reproductive success. Sensitivity was sufficient that error in estimating survival rates in the field could easily mask true population differences in effective size. Our results indicate that accurate and precise demographic data are prerequisites to determining effective population size for this species using genetic models, and that a single estimate of rate of loss of genetic variability is not valid across populations.

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