Roger A. Powell

An Evaluation of the Accuracy of Kernel Density Estimators for Home Range Analysis

Kernel density estimators are becoming more widely used, particularly as home range estimators. Despite extensive interest in their theoretical properties, little empirical 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 select 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. See full-text article at JSTOR

Animal ecology meets GPS-based radiotelemetry: a perfect storm of opportunities and challenges

Global positioning system (GPS) telemetry technology allows us to monitor and to map the details of animal movement, securing vast quantities of such data even for highly cryptic organisms. We envision an exciting synergy between animal ecology and GPS-based radiotelemetry, as for other examples of new technologies stimulating rapid conceptual advances, where research opportunities have been paralleled by technical and analytical challenges. Animal positions provide the elemental unit of movement paths and show where individuals interact with the ecosystems around them. We discuss how knowing where animals go can help scientists in their search for a mechanistic understanding of key concepts of animal ecology, including resource use, home range and dispersal, and population dynamics. It is probable that in the not-so-distant future, intense sampling of movements coupled with detailed information on habitat features at a variety of scales will allow us to represent an animals cognitive map of its environment, and the intimate relationship between behaviour and fitness. An extended use of these data over long periods of time and over large spatial scales can provide robust inferences for complex, multi-factorial phenomena, such as meta-analyses of the effects of climate change on animal behaviour and distribution.

The home-range concept: are traditional estimators still relevant with modern telemetry technology?

Recent advances in animal tracking and telemetry technology have allowed the collection of location data at an ever-increasing rate and accuracy, and these advances have been accompanied by the development of new methods of data analysis for portraying space use, home ranges and utilization distributions. New statistical approaches include data-intensive techniques such as kriging and nonlinear generalized regression models for habitat use. In addition, mechanistic home-range models, derived from models of animal movement behaviour, promise to offer new insights into how home ranges emerge as the result of specific patterns of movements by individuals in response to their environment. Traditional methods such as kernel density estimators are likely to remain popular because of their ease of use. Large datasets make it possible to apply these methods over relatively short periods of time such as weeks or months, and these estimates may be analysed using mixed effects models, offering another approach to studying temporal variation in space-use patterns. Although new technologies open new avenues in ecological research, our knowledge of why animals use space in the ways we observe will only advance by researchers using these new technologies and asking new and innovative questions about the empirical patterns they observe.

Building the bridge between animal movement and population dynamics

While the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through ‘spatially informed’ movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission–fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra- and interspecific interaction.

Habitat–performance relationships: finding the right metric at a given spatial scale

The field of habitat ecology has been muddled by imprecise terminology regarding what constitutes habitat, and how importance is measured through use, selection, avoidance and other bio-statistical terminology. Added to the confusion is the idea that habitat is scale-specific. Despite these conceptual difficulties, ecologists have made advances in understanding ‘how habitats are important to animals’, and data from animal-borne global positioning system (GPS) units have the potential to help this clarification. Here, we propose a new conceptual framework to connect habitats with measures of animal performance itself—towards assessing habitat–performance relationship (HPR). Long-term studies will be needed to estimate consequences of habitat selection for animal performance. GPS data from wildlife can provide new approaches for studying useful correlates of performance that we review. Recent examples include merging traditional resource selection studies with information about resources used at different critical life-history events (e.g. nesting, calving, migration), uncovering habitats that facilitate movement or foraging and, ultimately, comparing resources used through different life-history strategies with those resulting in death. By integrating data from GPS receivers with other animal-borne technologies and combining those data with additional life-history information, we believe understanding the drivers of HPRs will inform animal ecology and improve conservation.

AN EVALUATION OF LONG-TERM CAPTURE EFFECTS IN URSIDS: IMPLICATIONS FOR WILDLIFE WELFARE AND RESEARCH

Abstract The need to capture wild animals for conservation, research, and management is well justified, but long-term effects of capture and handling remain unclear. We analyzed standard types of data collected from 127 grizzly bears (Ursus arctos) captured 239 times in western Alberta, Canada, 1999–2005, and 213 American black bears (U. americanus) captured 363 times in southwestern North Carolina, 1981–2002, to determine if we could detect long-term effects of capture and handling, that is, effects persisting ≥1 month. We measured blood serum levels of aspartate aminotransferase (AST), creatine kinase (CK), and myoglobin to assess muscle injury in association with different methods of capture. Serum concentrations of AST and CK were above normal in a higher proportion of captures by leghold snare (64% of 119 grizzly bear captures and 66% of 165 black bear captures) than capture by helicopter darting (18% of 87 grizzly bear captures) or by barrel trap (14% of 7 grizzly bear captures and 29% of 7 black bear captures). Extreme AST values (>5 times upper reference limit) in 7 (6%) grizzly bears and 29 (18%) black bears captured by leghold snare were consistent with the occurrence of exertional (capture) myopathy. We calculated daily movement rates for 91 radiocollared grizzly bears and 128 radiocollared black bears to determine if our activities affected their mobility during a 100-day period after capture. In both species, movement rates decreased below mean normal rate immediately after capture (grizzly bears: X̄ = 57% of normal, 95% confidence interval = 45–74%; black bears: 77%, 64–88%) and then returned to normal in 3–6 weeks (grizzly bears: 28 days, 20–37 days; black bears: 36 days, 19–53 days). We examined the effect of repeated captures on age-related changes in body condition of 127 grizzly bears and 207 black bears and found in both species that age-specific body condition of bears captured ≥2 times (42 grizzly bears and 98 black bears) tended to be poorer than that of bears captured once only (85 grizzly bears and 109 black bears), with the magnitude of effect directly proportional to number of times captured and the effect more evident with age. Importantly, the condition of bears did not affect their probability of capture or recapture. These findings challenge persons engaged in wildlife capture to examine their capture procedures and research results carefully. Significant capture-related effects may go undetected, providing a false sense of the welfare of released animals. Further, failure to recognize and account for long-term effects of capture and handling on research results can potentially lead to erroneous interpretations.

Internal structure of home ranges of black bears and analyses of home-range overlap

Eight black bears ( Ursus americanus ) outfitted with motion-sensitive transmitter collars were radiotracked from May through December 1984 in the Pisgah Bear Sanctuary in the mountains of western North Carolina. Activities and movement patterns within areas of overlap among neighboring bears were analyzed to determine whether neighbors exhibited spatial or temporal avoidance. The distributions of locations within home ranges were clumped but bears did not use specific areas for specific activities. Home ranges overlapped extensively, and even core areas (areas of high-intensity use) overlapped. Neighboring bears often used areas of overlap for the same activities and at the same time. The clumped or patchy use of areas within home ranges requires analyses that emphasize internal structure of home ranges and not merely outlines or total-area measures.

ECOLOGICAL ENERGETICS AND FORAGING STRATEGIES OF THE FISHER (MARTES PENNANTI)

SUMMARY (1) This paper presents a model for the daily energy budget of free-living solitary mammals and applies the model to the fisher. Energy expenditure of mammals is the sum of the energies expended in different activities, the most important of which for carnivores are sleeping, running (hunting) and prey capturing. Energy expenditure for a carnivore in each of these activities is a linear function of the mammals weight to a specified power and its running speed. Two fishers were trained to run on a treadmill to determine the values of the equation parameters for this species. The energy available to a fisher from common prey items is presented. (2) Wild fishers were tracked in the snow and were live-trapped, outfitted with radio transmitters and monitored for activity. Inserting time active and inactive and distance run into the energy budget model yields estimates of energy expended during periods of radio contact and estimates of daily energy expenditure. Daily energy expenditure is estimated to be of the same order of magnitude as, but less than, daily energy acquired from kills and scavenges. (3) The energy budget model and field data are used to develop a simple optimal foraging strategy model for the fisher. A fishers optimal foraging strategy depends on estimated search times for each prey relative to estimated energy obtained from each prey but does not depend on handling times and handling energy expenditures.

Optimal use of resources structures home ranges and spatial distribution of black bears

Research has shown that territories of animals are economical. Home ranges should be similarly efficient with respect to spatially distributed resources and this should structure their distribution on a landscape, although neither has been demonstrated empirically. To test these hypotheses, we used home range models that optimize resource use according to resource-maximizing and area-minimizing strategies to evaluate the home ranges of female black bears, Ursus americanus, living in the southern Appalachian Mountains. We tested general predictions of our models using 104 home ranges of adult female bears studied in the Pisgah Bear Sanctuary, North Carolina, U.S.A., from 1981 to 2001. We also used our models to estimate home ranges for each real home range under a variety of strategies and constraints and compared similarity of simulated to real home ranges. We found that home ranges of female bears were efficient with respect to the spatial distribution of resources and were best explained by an area-minimizing strategy with moderate resource thresholds and low levels of resource depression. Although resource depression probably influenced the spatial distribution of home ranges on the landscape, levels of resource depression were too low to quantify accurately. Home ranges of lactating females had higher resource thresholds and were more susceptible to resource depression than those of breeding females. We conclude that home ranges of animals, like territories, are economical with respect to resources, and that resource depression may be the mechanism behind ideal free or ideal preemptive distributions on complex, heterogeneous landscapes.

Development of survival skills in captive-raised Siberian polecats ( Mustela eversmanni ) II: predator avoidance

We exposed naive Siberain polecats (Mustela eversmanni) (aged 2, 3, and 4 months) to a swooping stuffed great horned owl (Buho virginianus) and a stuffed badger (Taxidae taxus) mounted on a remote control toy automobile frame. The first introduction to each was harmless, the second was accompanied by a mild aversive stimulus, the third (1 day after attack) was harmless, and the fourth (30 days after attack) was harmless. Alert behavior increased after a single attack by either predator model. Escape responses of naive polecats did not differ between ages when exposed to the badger, but 4 month old polecats reduced their escape times after a single badger attack. When exposed to the swooping owl, naive 4 month old polecats redponded more quickly than the other two age groups, and 3 and 4 month old polecats reduced escape times after a single owl attack. This indicates an innate escape response to the owl model at 4 months of age, and a short-tert ability to remember a single mild aversive encounter with the badger and owl models at 3 or 4 months of age.