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Wayne F. Kasworm

Publications and source records attributed to Wayne F. Kasworm.

7 recordsLinked to original sources
USGS2026

An energetic tradeoff best explains parturition timing in grizzly bears

Timing of grizzly bear ( Ursus arctos ) parturition during hibernation has been explained by ancestral traits (delayed implantation, altricial young, obligate maternal denning), but the ultimate driver underlying precise timing has not been fully explored. Capitalizing on an observed latitudinal increase in denning duration among four populations in interior North America, we tested two alternative hypotheses. First, that birth timing results from a physiological cue that synchronizes implantation with the onset of hibernation, allowing females to forgo reproduction should they lack adequate fat stores. Alternatively, that parturition is optimally timed relative to den exit to balance an energetic tradeoff between minimizing lactation time to protect the mother and maximizing developmental time to increase cub survival. Using parturition dates previously predicted from accelerometer data (27 Dec–28 Feb), we classified 115 females according to apparent litter survival when first visually observed after den exit: 57% successful (with cubs), 22% unsuccessful (alone), and 21% unknown (not observed). The number of days between birth and den exit showed no association with latitude ( p = 0.29). It averaged 103 days among successful females but only 77 days among unsuccessful females ( p < 0.001) owing to later births and earlier exit. With each increasing degree of latitude, birth date increased by 1.0 and number of days between den entry and birth increased by 2.5 ( p < 0.001). Implantation dates were not centered on den entry dates ( p < 0.001). These results supported the energetic tradeoff hypothesis and suggested natural selection has favored a consistent number of days between parturition and den exit under average body conditions and shifts toward later or earlier births for females with lower or higher levels of bodily stored energy, respectively. This flexible tradeoff may support resilience to climate change and present a possible mechanism explaining reduced natality and cub survival in high-density populations.

Alaska, British Columbia, Idaho, Montana, Wyoming↗
USGS2026

Per- and polyfluoroalkyl substances and pesticides in black bears (Ursus americanus) and grizzly bears (Ursus arctos horribilis) from Montana's Cabinet-Yaak ecosystem: A baseline assessment of emerging and legacy contaminants

Per- and polyfluoroalkyl substances (PFAS) and pesticides are globally distributed contaminants that persist in terrestrial food webs, yet baseline data for large omnivores in the continental U.S. remain limited. This study quantified PFAS and pesticides in whole blood from free-ranging black bears ( Ursus americanus , n = 15) and grizzly bears ( Ursus arctos horribilis , n = 9) in the Cabinet-Yaak Ecosystem of northwestern Montana. Using high-resolution mass spectrometry-based methods (GC-MS/MS and LC-MS/MS), 52 PFAS and 186 pesticides were analyzed. PFAS were detected in all bears, with total PFAS concentrations ranging from 79.5 to 317 pg/mL. PFAS profiles were dominated by long-chain perfluoroalkyl carboxylic acids, particularly PFOA, PFDA, and PFUnDA, with minimal contribution from short-chain compounds. Species was the strongest ecological predictor of PFAS concentrations, although variability across age, sex, and capture location were observed. Only two pesticides, piperonyl butoxide and permethrin, were detected at quantifiable concentrations (2070–12,600 pg/mL), and no correlations were observed between pesticide and PFAS concentrations, indicating independent exposure pathways. The predominance of long-chain PFAS suggests diffuse environmental sources and bioaccumulation within terrestrial food webs. Although measured concentrations were generally low relative to other wildlife toxicological studies, the persistence and protein-binding properties of long-chain PFAS warrant continued monitoring, particularly for long-lived omnivores. These results establish baseline contaminant concentrations for two apex omnivores in a remote ecosystem and highlight the utility of large mammals as integrative sentinels of environmental contaminant exposure for regional monitoring and wildlife conservation. Continued monitoring in the Cabinet-Yaak and across western North America will be critical for assessing temporal trends, identifying new contaminant sources, and evaluating ecological health in bear populations.

Montana↗
USGS2026

Detecting occurrence and timing of grizzly bear parturition based on anomalies in accelerometer data

Documenting natality of brown (grizzly) bears ( Ursus arctos ) is an important component of many population monitoring and research programs. Brown bears give birth during hibernation, so observation of litters is generally not feasible until females exit dens, and detection of litters can be compromised by poor observability. Using triaxial accelerometer activity data stored on radiocollars, we developed a technique that predicts births by the presence of brief upsurges in activity likely associated with postnatal maternal behaviors. We developed presence criteria with a training sample of known parturient females ( n = 22) to detect anomalies within time-series of daily motion-counts (i.e., activity readings >0 measured at 10-min intervals) during 25 December–7 March. To test performance, we applied criteria to a blinded sample of activity data obtained from female grizzly bears (captured and collared during 2012–2022) in 4 populations in interior North America ( n = 295). We assigned predicted status and compared assignments to reproductive status at first visual observation. The true positive rate was 91% ( n = 47 females observed with cubs of the year) and the false-positive rate was 17% ( n = 65 females observed with older offspring). Births were predicted for 50% of females with unknown reproductive status ( n = 48), 21% of females observed without offspring ( n = 114), and 10% of subadult females considered too young to reproduce ( n = 21). Dates of predicted births varied from 27 December to 28 February. Our anomaly detection technique was successful at estimating parturition events, and despite some error, indicated that a number of litters were born but not observed, presumably due to mortality in or shortly after den emergence. This technique provides an additional tool for supplementing visual observations for natality estimation and population modeling, provided that potential biases stemming from increased detection rates are considered.

Alaska, British Columbia, Idaho, Montana↗
USGS2025

A summary of grizzly bear distribution in the lower-48 US states in 2024

Understanding the distribution of grizzly bear populations in the lower-48 states, is important for their conservation and management, and for public safety. Previously, our research teams working in grizzly bear ecosystems in the lower-48 states used varying methods to estimate distribution of grizzly bear populations. In the Greater Yellowstone Ecosystem (GYE) and Northern Continental Divide Ecosystem (NCDE), zonal analysis and ordinary kriging were applied to an array of grid cells with or without verified presence of grizzly bears, however the parameters of the methods varied between the two ecosystems. In the Cabinet-Yaak Ecosystem (CYE) and the Selkirk Ecosystem (SE), population distribution was mapped as the Recovery Zone plus “bears outside of Recovery Zone” areas (Allen 2011). Additionally, the U.S. Fish and Wildlife Service developed a method for estimating areas where grizzly bears “may be present” to help agencies or prospective applicants evaluate whether or not proposed actions may affect grizzly bears (U.S. Fish and Wildlife Service 2020). Since the mid 2010s, cooperating agencies have collaborated in documenting and maintaining a database of verified outlier observations that occur between or well outside of grizzly bear Recovery Zones and these data inform the “may be present” mapping.

lower 48 states↗
USGS2024

Gene flow prevents genetic diversity loss despite small effective population size in fragmented grizzly bear (Ursus arctos) populations

Genetic monitoring is important in small, fragmented populations that rely on gene flow to maintain genetic diversity. The Selkirk, Yaak, and Cabinet grizzly bear ( Ursus arctos ) populations are among the smallest in North America and are near the southernmost extent of the species’ range. These populations received little to no effective migration for generations but have recently experienced increased gene flow through natural migration and a population augmentation program. A long-term dataset of grizzly bear microsatellite genotypes from 1973 to 2021 presented a unique opportunity to examine genetic trends in these populations over time. We used this dataset of 464 bears to evaluate if gene flow affected observed heterozygosity ( H O ), expected heterozygosity ( H E ), allelic richness ( A R ), and average pairwise relatedness ( r ) in each of these populations. We also estimated effective population size ( N e ) using the temporal and linkage disequilibrium (LD) methods. Post gene flow, A R increased in the Selkirk and Cabinet populations and r decreased in all three populations. We did not observe any significant changes in H E or H O , but H E values in our populations were significantly higher than those estimated using a model without gene flow. Our N e estimates were consistent between the temporal and LD methods and ranged from 15.2 to 15.8, 15.4–17.5, and 5.6–8.9 for the Selkirk, Yaak, and Cabinet populations, respectively. Overall, our findings indicate that gene flow is increasing or maintaining genetic diversity in these populations. However, N e remains low and additional connectivity or augmentation may be needed, particularly in the Cabinet population.

Idaho, Montana, Washington↗
USGS2015

Density, distribution, and genetic structure of grizzly bears in the Cabinet-Yaak Ecosystem

The conservation status of the 2 threatened grizzly bear ( Ursus arctos ) populations in the Cabinet-Yaak Ecosystem (CYE) of northern Montana and Idaho had remained unchanged since designation in 1975; however, the current demographic status of these populations was uncertain. No rigorous data on population density and distribution or analysis of recent population genetic structure were available to measure the effectiveness of conservation efforts. We used genetic detection data from hair corral, bear rub, and opportunistic sampling in traditional and spatial capture–recapture models to generate estimates of abundance and density of grizzly bears in the CYE. We calculated mean bear residency on our sampling grid from telemetry data using Huggins and Pledger models to estimate the average number of bears present and to correct our superpopulation estimates for lack of geographic closure. Estimated grizzly bear abundance (all sex and age classes) in the CYE in 2012 was 48–50 bears, approximately half the population recovery goal. Grizzly bear density in the CYE (4.3–4.5 grizzly bears/1,000 km 2 ) was among the lowest of interior North American populations. The sizes of the Cabinet ( n = 22–24) and Yaak ( n = 18–22) populations were similar. Spatial models produced similar estimates of abundance and density with comparable precision without requiring radio-telemetry data to address assumptions of geographic closure. The 2 populations in the CYE were demographically and reproductively isolated from each other and the Cabinet population was highly inbred. With parentage analysis, we documented natural migrants to the Cabinet and Yaak populations by bears born to parents in the Selkirk and Northern Continental Divide populations. These events supported data from other sources suggesting that the expansion of neighboring populations may eventually help sustain the CYE populations. However, the small size, isolation, and inbreeding documented by this study demonstrate the need for comprehensive management designed to support CYE population growth and increased connectivity and gene flow with other populations.

Idaho, Montana↗