Kimberly Titus

Consumption of salmon by Alaskan brown bears: a trade-off between nutritional requirements and the risk of infanticide?

The risk of infanticide may alter foraging decisions made by females, which otherwise would have been based on nutritional requirements and forage quality and availability. In systems where meat resources are spatially aggregated in late summer and fall, female brown bears ( Ursus arctos) would be faced with a trade-off situation. The need of reproductive females to accumulate adequate fat stores would likely result in a decision to frequent salmon streams and consume the protein- and lipid-rich spawning salmon. In contrast, aggregations of bears along salmon streams would create conditions of high risk of infanticide. We investigated consumption of salmon by brown bears on Admiralty and Chichagof Islands in Southeast Alaska from 1982 to 2000 using stable isotope analysis and radiotelemetry. While nearly all males (22 of 23) consumed relatively large amounts of salmon (i.e., >10% relative contribution to seasonal diet), not all females ( n =56) did so. Five of 26 females for which we had reproductive data, occupied home ranges that had no access to salmon and thus did not consume salmon when they were mated or accompanied by young. Of females that had access to salmon streams ( n =21), all mated individuals ( n =16) had δ15N values indicative of salmon consumption. In contrast, 4 out of 16 females with cubs avoided consuming salmon altogether, and of the other 12, 3 consumed less salmon than they did when they were mated. For 11 of 21 females with access to salmon streams we had data encompassing both reproductive states. Five of those altered foraging strategies and exhibited significantly lower values of δ15N when accompanied by young than when mated, while 6 did not. Radiotelemetry data indicated that females with spring cubs were found, on average, further away from streams during the spawning season compared with females with no young, but both did not differ from males and females with yearlings and 2-year-olds. Females with young that avoided salmon streams were significantly lighter indicating that female choice to avoid consumption of salmon carries a cost that may translate to lower female or cub survivorship. The role of the social hierarchy of males and females, mating history, and paternity in affecting the risk of infanticide and foraging decisions of female brown bears merit further investigation.

A comparison of 3 methods for assessing raptor diet during the breeding season

Abstract Video recording of prey deliveries to nests is a new technique for collecting data on raptor diet, but no thorough comparison of results from traditional methods based on collections of prey remains and pellets has been undertaken. We compared data from these 3 methods to determine relative merits of different methods for assessing raptor diet as part of a study of the breeding-season diet of northern goshawks (Accipiter gentilis) in Southeast Alaska. We applied these methods to 5 nests during each of the northern goshawk breeding seasons of 1998 and 1999 and identified 1,540 prey from deliveries, 209 prey from remains, and 209 prey from pellets. The proportions of birds and mammals varied among techniques, as did relative proportions of prey groups and age groups. Prey remains and pellets gave the least-similar diet descriptions. Over 2-day intervals during which data were collected using all 3 methods, prey-delivery data gave more individual prey and prey categories than the 2 other sources of information. We found that prey were not directly tracked in either prey remains or pellets compared with prey delivery videography. Analysis of prey-delivery videography provided the most complete description of diet, and we recommend that studies attempting to describe diet use this technique, at least as part of their methodology.

Stability and bias of classification rates in biological applications of discriminant analysis

We assessed the sampling stability of classification rates in discriminant analysis by using a factorial design with factors for multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. Simulation results indicated strong bias in correct classification rates when group sample sizes were small and when overlap among groups was high. We also found that stability of the correct classification rates was influenced by these factors, indicating that the number of samples required for a given level of precision increases with the amount of overlap among groups. In a review of 60 published studies, we found that 57% of the articles presented results on classification rates, though few of them mentioned potential biases in their results. Wildlife researchers should choose the total number of samples per group to be at least 2 times the number of variables to be measured when overlap among groups is low. Substantially more samples are required as the overlap among groups increases. J. WILDL. MANAGE. 54(2):331-341 Researchers often analyze biological data with discriminant analysis, a statistical method useful for classifying individuals into groups and for highlighting group differences. Necessary features for applications are the separability of samples into distinct groups and the measurement of 1 or more attributes on each sample unit. Typical applications by wildlife biologists involve the identification of groups of distinct animal or plant species and the examination of group differences based on habitat attributes (Edge et al. 1987). Other applications include morphometric analysis of species differences (Troy 1985) and analysis of plant or animal assemblages based on species abundances (Matthews 1979). Williams (1981, 1983) characterized ecological applications of the methodology by their grouping indices and attributes, and Williams and Titus (1988) described more recent applications in terms of sample sizes, system dimensions, and other statistical attributes. In many biological applications of discriminant analysis, the classification functions are characterized by substantial variability associated with small sample sizes and high multivariate dimensionality. There have been several theoretical assessments of the statistical properties of classification rates, especially asymptotic properties under various distributional assumptions (Anderson 1973, Gordon and Olshen 1978). However, the few studies that focused on small sample properties were limited in scope (Van Ness 1979, Page 1985) and generally focused on biases in apparent classification rates (Moran 1975, McLachlan 1976). Because wildlife studies often are hindered by an inability to collect a large number of independent samp es, the sources of variability in classification rates based on small sample sizes need to be examined. We report classification success as part of a simulation study of discriminant analysis (see Williams and Titus [1988] for canonical variates analysis). Our objective was to identify sources of variability in classification rates and to determine minimum sample sizes necessary for es imating these rates. Our study focused on assessment of discriminant analysis in representing system structure known to underlie the data under investigation. Our results compliment the work of Rexstad et al. (1988), who used data with no apparent underlying system structure to document a tendency, under certain conditions, for discriminant analysis to generate spurious relationships. We thank G. W. Pendleton, E. F. Burton, and K. Boone for technical support. D. E. Capen, D. W. Sparling, and J. S. Hatfield provided preliminary reviews and helpful comments. 1 Present address: Office of Migratory Bird Management, U.S. Fish and Wildlife Service, 18th and C Street NW, Washington, DC 20240. 2 Present address: Alaska Department of Fish and Game, Division of Wildlife Conservation, P.O. Box 20, Douglas, AK 99824.

Northern Goshawk Diet During the Nesting Season in Southeast Alaska

Abstract

Mark–recapture using tetracycline and genetics reveal record-high bear density†

ABSTRACT We used tetracycline biomarking, augmented with genetic methods to estimate the size of an American black bear (Ursus americanus) population on an island in Southeast Alaska. We marked 132 and 189 bears that consumed remote, tetracycline-laced baits in 2 different years, respectively, and observed 39 marks in 692 bone samples subsequently collected from hunters. We genetically analyzed hair samples from bait sites to determine the sex of marked bears, facilitating derivation of sex-specific population estimates. We obtained harvest samples from beyond the study area to correct for emigration. We estimated a density of 155 independent bears/100 km2, which is equivalent to the highest recorded for this species. This high density appears to be maintained by abundant, accessible natural food. Our population estimate (approx. 1,000 bears) could be used as a baseline and to set hunting quotas. The refined biomarking method for abundance estimation is a useful alternative where physical captures or DNA-based estimates are precluded by cost or logistics.