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K.A. Keating

Publications and source records attributed to K.A. Keating.

7 recordsLinked to original sources
USGS2010

Evaluation of rules to distinguish unique female grizzly bears with cubs in Yellowstone

The United States Fish and Wildlife Service uses counts of unduplicated female grizzly bears (Ursus arctos) with cubs-of-the-year to establish limits of sustainable mortality in the Greater Yellowstone Ecosystem, USA. Sightings are dustered into observations of unique bears based on an empirically derived rule set. The method has never been tested or verified. To evaluate the rule set, we used data from radiocollared females obtained during 1975-2004 to simulate populations under varying densities, distributions, and sighting frequencies. We tested individual rules and rule-set performance, using custom software to apply the rule-set and duster sightings. Results indicated most rules were violated to some degree, and rule-based dustering consistently underestimated the minimum number of females and total population size derived from a nonparametric estimator (Chao2). We conclude that the current rule set returns conservative estimates, but with minor improvements, counts of unduplicated females-with-cubs can serve as a reasonable index of population size useful for establishing annual mortality limits. For the Yellowstone population, the index is more practical and cost-effective than capture-mark-recapture using either DNA hair snagging or aerial surveys with radiomarked bears. The method has useful application in other ecosystems, but we recommend rules used to distinguish unique females be adapted to local conditions and tested.

Journal of Wildlife Management↗
USGS2009

Modeling utilization distributions in space and time

W. Van Winkle defined the utilization distribution (UD) as a probability density that gives an animal's relative frequency of occurrence in a two-dimensional (x, y) plane. We extend Van Winkle's work by redefining the UD as the relative frequency distribution of an animal's occurrence in all four dimensions of space and time. We then describe a product kernel model estimation method, devising a novel kernel from the wrapped Cauchy distribution to handle circularly distributed temporal covariates, such as day of year. Using Monte Carlo simulations of animal movements in space and time, we assess estimator performance. Although not unbiased, the product kernel method yields models highly correlated (Pearson's r - 0.975) with true probabilities of occurrence and successfully captures temporal variations in density of occurrence. In an empirical example, we estimate the expected UD in three dimensions (x, y, and t) for animals belonging to each of two distinct bighorn sheep {Ovis canadensis) social groups in Glacier National Park, Montana, USA. Results show the method can yield ecologically informative models that successfully depict temporal variations in density of occurrence for a seasonally migratory species. Some implications of this new approach to UD modeling are discussed. ?? 2009 by the Ecological Society of America.

Ecology↗
USGS2007

Sequence analysis of the msp4 gene of Anaplasma ovis strains

Anaplasma ovis (Rickettsiales: Anaplasmataceae) is a tick-borne pathogen of sheep, goats and wild ruminants. The genetic diversity of A. ovis strains has not been well characterized due to the lack of sequence information. In this study, we evaluated bighorn sheep ( Ovis canadensis ) and mule deer (Odocoileus hemionus ) from Montana for infection with A. ovis by serology and sequence analysis of the msp4 gene. Antibodies to Anaplasma spp. were detected in 37% and 39% of bighorn sheep and mule deer analyzed, respectively. Four new msp4 genotypes were identified. The A. ovis msp4 sequences identified herein were analyzed together with sequences reported previously for the characterization of the genetic diversity of A. ovis strains in comparison with other Anaplasma spp. The results of these studies demonstrated that although A. ovis msp4 genotypes may vary among geographic regions and between sheep and deer hosts, the variation observed was less than the variation observed between A. marginale and A. phagocytophilum strains. The results reported herein further confirm that A. ovis infection occurs in natural wild ruminant populations in Western United States and that bighorn sheep and mule deer may serve as wildlife reservoirs of A. ovis . ?? 2006.

Veterinary Microbiology↗
USGS2007

Evaluating estimators for numbers of females with cubs-of-the-year in the Yellowstone grizzly bear population

Current management of the grizzly bear ( Ursus arctos ) population in Yellowstone National Park and surrounding areas requires annual estimation of the number of adult female bears with cubs-of-the-year. We examined the performance of nine estimators of population size via simulation. Data were simulated using two methods for different combinations of population size, sample size, and coefficient of variation of individual sighting probabilities. We show that the coefficient of variation does not, by itself, adequately describe the effects of capture heterogeneity, because two different distributions of capture probabilities can have the same coefficient of variation. All estimators produced biased estimates of population size with bias decreasing as effort increased. Based on the simulation results we recommend the Chao estimator for model M h be used to estimate the number of female bears with cubs of the year; however, the estimator of Chao and Shen may also be useful depending on the goals of the research.

Wyoming↗
USGS2001

Estimating numbers of females with cubs-of-the-year in the Yellowstone grizzly bear population

For grizzly bears ( Ursus arctos horribilis ) in the Greater Yellowstone Ecosystem (GYE), minimum population size and allowable numbers of human-caused mortalities have been calculated as a function of the number of unique females with cubs-of-the-year ( F CUB ) seen during a 3- year period. This approach underestimates the total number of F CUB , thereby biasing estimates of population size and sustainable mortality. Also, it does not permit calculation of valid confidence bounds. Many statistical methods can resolve or mitigate these problems, but there is no universal best method. Instead, relative performances of different methods can vary with population size, sample size, and degree of heterogeneity among sighting probabilities for individual animals. We compared 7 nonparametric estimators, using Monte Carlo techniques to assess performances over the range of sampling conditions deemed plausible for the Yellowstone population. Our goal was to estimate the number of F CUB present in the population each year. Our evaluation differed from previous comparisons of such estimators by including sample coverage methods and by treating individual sightings, rather than sample periods, as the sample unit. Consequently, our conclusions also differ from earlier studies. Recommendations regarding estimators and necessary sample sizes are presented, together with estimates of annual numbers of F CUB in the Yellowstone population with bootstrap confidence bounds.

Wyoming↗
USGS1998

Estimating species richness: The Michaelis-Menten model revisited

The Michaelis-Menten model has been widely used to estimate the richness (S) of species pools, but is largely untested. We tested whether (1) species accumulation curves follow the form predicted by the model, (2) the model gives unbiased estimates (Ŝ and B̂, respectively) of S and of the sample size, B, needed to detect S/2 species, and (3) performance is robust to community structure. Performance varied with community structure. For model communities with species-abundance distributions based on MacArthur's broken-stick model with 100 or 1000 species, deviations from predicted accumulation curves were slight, and Ŝ and B̂ were unbiased (P ≥ 0.18). For broken-stick communities with 10 species, Ŝ and B̂ overestimated S and B by an average of 17% and 63%, respectively (P < 0.001). For model communities with species-abundance distributions based on Tokeshi's (1990) random-fraction model with 10, 100, or 1000 species, deviations from predicted accumulation curves were large; on average, Ŝ underestimated S by 7-37% (P < 0.001), and (for S = 100 or 1000) B̂ underestimated B by 67-80% (P < 0.001). Vascular plant inventories (S = 42 to 99 species) also showed large deviations from predicted curves; on average, Ŝ underestimated S by 35% (P < 0.001) and B̂ underestimated B by 72% (P < 0.001). Because most natural communities are better described by the random-fraction than the broken-stick model, we suggest the Michaelis-Menten model will typically yield poor estimates of S. Moreover, we argue that accepted criteria for evaluating estimators of S are inadequate.

Oikos↗