Toxic elements in arctic and sub-arctic brown bears: Blood concentrations of As, Cd, Hg and Pb in relation to diet, age, and human footprint.

Contamination with arsenic (As), cadmium (Cd), mercury (Hg) and lead (Pb) is a global concern impairing resilience of organisms and ecosystems. Proximity to emission sources increases exposure risk but remoteness does not alleviate it. These toxic elements are transported in atmospheric and oceanic pathways and accumulate in organisms. Mercury accumulates in higher trophic levels. Brown bears (Ursus arctos), which often live in remote areas, are long-lived omnivores, feeding on salmon (Oncorhynchus spp.) and berries (Vaccinium spp.), resources also consumed by humans. We measured blood concentrations of As, Cd, Hg and Pb in bears (n = 72) four years and older in Scandinavia and three national parks in Alaska, USA (Lake Clark, Katmai and Gates of the Arctic) using high-resolution, inductively-coupled plasma sector field mass spectrometry. Age and sex of the bears, as well as the typical population level diet was associated with blood element concentrations using generalized linear regression models. Alaskan bears consuming salmon had higher Hg blood concentrations compared to Scandinavian bears feeding on berries, ants (Formica spp.) and moose (Alces). Cadmium and Pb blood concentrations were higher in Scandinavian bears than in Alaskan bears. Bears using marine food sources, in addition to salmon in Katmai, had higher As blood concentrations than bears in Scandinavia. Blood concentrations of Cd and Pb, as well as for As in female bears increased with age. Arsenic in males and Hg concentrations decreased with age. We detected elevated levels of toxic elements in bears from landscapes that are among the most pristine on the planet. Sources are unknown but anthropogenic emissions are most likely involved. All study areas face upcoming change: Increasing tourism and mining in Alaska and more intensive forestry in Scandinavia, combined with global climate change in both regions. Baseline contaminant concentrations as presented here are important knowledge in our changing world.

Survey for Selected Parasites in Alaska Brown Bears (Ursus arctos).

To assess infection with or exposure to endo- and ectoparasites in Alaska brown bears (Ursus arctos), blood and fecal samples were collected during 2013-17 from five locations: Gates of the Arctic National Park and Preserve; Katmai National Park; Lake Clark National Park and Preserve; Yakutat Forelands; and Kodiak Island. Standard fecal centrifugal flotation was used to screen for gastrointestinal parasites, molecular techniques were used to test blood for the presence of Bartonella and Babesia spp., and an ELISA was used to detect antibodies reactive to Sarcoptes scabiei, a species of mite recently associated with mange in American black bears (Ursus americanus). From fecal flotations (n=160), we identified the following helminth eggs: Uncinaria sp. (n=16, 10.0%), Baylisascaris sp. (n=5, 3.1%), Dibothriocephalus sp. (n=2, 1.2%), and taeniid-type eggs (n=1, 0.6%). Molecular screening for intraerythrocytic parasites (Babesia spp.) and intracellular bacteria (Bartonella spp.) was negative for all bears tested. We detected antibodies to S. scabiei in six of 59 (10.2%) individuals. The relatively low level of parasite detection in this study meets expectations for brown bear populations living in large, relatively undisturbed habitats near the northern edge of the range. These results provide a contemporary understanding of parasites in Alaska brown bears and establish baseline levels of parasite presence to monitor for changes over time and relative to ecologic alterations.

Correlating gut microbial membership to brown bear health metrics.

The internal mechanisms responsible for modulating physiological condition, particularly those performed by the gut microbiome (GMB), remain under-explored in wildlife. However, as latitudinal and seasonal shifts in resource availability occur, the myriad micro-ecosystem services facilitated by the GMB may be especially important to wildlife health and resilience. Here, we use brown bears (Ursus arctos) as an ecological model to quantify the relationship between wildlife body condition metrics that are commonly used to assess individual and population-level health and GMB community composition and structure. To achieve these aims, we subsampled brown bear fecal samples collected during United States National Park Service research activities at three National Parks and Preserves (Katmai, Lake Clark, and Gates of the Arctic) and extracted microbial DNA for 16S rRNA amplicon sequencing and microbial taxonomic classification. We analyzed GMB communities using alpha diversity indices, subsequently using Spearman's correlation analysis to examine relationships between alpha diversity and brown bear health metrics. We found no differences in GMB composition among bears with differing body conditions, nor any correlations between alpha diversity and body condition. Our results indicate that GMB composition reflects diverse foraging strategies while allowing brown bears to achieve similar body condition outcomes.

Intrinsic and extrinsic factors influence on an omnivore's gut microbiome.

Gut microbiomes (GMBs), complex communities of microorganisms inhabiting the gastrointestinal tracts of their hosts, perform countless micro-ecosystem services such as facilitating energy uptake and modulating immune responses. While scientists increasingly recognize the role GMBs play in host health, the role of GMBs in wildlife ecology and conservation has yet to be realized fully. Here, we use brown bears (Ursus arctos) as an ecological model to (1) characterize GMB community composition associated with location, season, and reproductive condition of a large omnivore; (2) investigate how both extrinsic and intrinsic factors influence GMB community membership and structure; and (3) quantify differences in GMB communities among different locations, seasons, sex, and reproductive conditions. To achieve these aims, we subsampled brown bear fecal samples collected during United States National Park Service research activities at three National Parks and Preserves (Katmai, Lake Clark, and Gates of the Arctic) and extracted microbial DNA for 16S rRNA amplicon sequencing and microbial taxonomic classification. We analyzed GMB communities using alpha and beta diversity indices, subsequently using linear mixed models to examine relationships between alpha diversity and extrinsic and intrinsic factors. Katmai brown bears hosted the greatest alpha diversity, whereas Gates brown bears hosted the least alpha diversity. Our results indicate that location and diet drive GMB variation, with bears hosting less phylogenetic diversity as park distance inland increases. Monitoring brown bear GMBs could enable managers to quickly detect and assess the impact of environmental perturbations on brown bear health. By integrating macro and micro-ecological perspectives we aim to inform local and landscape-level management decisions to promote long-term brown bear conservation and management.

Splitting hairs: dietary niche breadth modelling using stable isotope analysis of a sequentially grown tissue.

Stable isotope data from durable, sequentially grown tissues (e.g. hair, claw, and baleen) is commonly used for modelling dietary niche breadth. The use of tissues grown over multiple months to years, however, has the potential to complicate isotopic niche breadth modelling, as time-averaged stable isotope signals from whole tissues may obscure information available from chronologically resolved stable isotope signals in serially sectioned tissues. We determined if whole samples of brown bear guard hair produced different isotopic niche breadth estimates than those produced from subsampled, serially sectioned samples of the same tissue from the same set of individuals. We sampled guard hair from brown bears (Ursus arctos) in four regions of Alaska with disparate biogeographies and dietary resource availability. Whole hair and serially sectioned hair samples were used to produce paired isotopic dietary niche breadth estimates for each region in the SIBER Bayesian model framework in R. Isotopic data from serially sectioned hair consistently produced larger estimates of isotopic dietary niche breadth than isotope data from whole hair samples. Serial sampling captures finer-scale changes in diet and when cumulatively used to estimate isotopic niche breadth, the serially sampled isotope data more fully captures dietary variability and true isotopic niche breadth.

EXPOSURE OF ALASKA BROWN BEARS (URSUS ARCTOS) TO BACTERIAL, VIRAL, AND PARASITIC AGENTS VARIES SPATIOTEMPORALLY AND MAY BE INFLUENCED BY AGE.

We collected blood and serum from 155 brown bears (Ursus arctos) inhabiting five locations in Alaska, US during 2013-16 and tested samples for evidence of prior exposure to a suite of bacterial, viral, and parasitic agents. Antibody seroprevalence among Alaska brown bears was estimated to be 15% for Brucella spp., 10% for Francisella tularensis, 7% for Leptospira spp., 18% for canine adenovirus type 1 (CAV-1), 5% for canine distemper virus (CDV), 5% for canine parvovirus, 5% for influenza A virus (IAV), and 44% for Toxoplasma gondii. No samples were seropositive for antibodies to Trichinella spp. Point estimates of prior exposure to pathogens among brown bears at previously unsampled locations generally fell within the range of estimates for previously or contemporaneously sampled bears in Alaska. Statistical support was found for variation in antibody seroprevalence among bears by location or age cohort for CAV-1, CDV, IAV, and T. gondii. There was limited concordance in comparisons between our results and previous serosurveys regarding spatial and age-related trends in antibody seroprevalence among Alaska brown bears suggestive of temporal variation. However, we found evidence that the seroprevalence of CAV-1 antibodies is consistently high in bears inhabiting southwest Alaska and the cumulative probability of exposure may increase with age. We found evidence for seroconversion or seroreversion to six different infectious agents in one or more bears. Results of this study increase our collective understanding of disease risk to both Alaska brown bear populations and humans that utilize this resource.

Nest use dynamics of an undisturbed population of bald eagles.

Management or conservation targets based on demographic rates should be evaluated within the context of expected population dynamics of the species of interest. Wild populations can experience stable, cyclical, or complex dynamics, therefore undisturbed populations can provide background needed to evaluate programmatic success. Many raptor species have recovered from large declines caused by environmental contaminants, making them strong candidates for ongoing efforts to understand population dynamics and ecosystem processes in response to human-caused stressors. Dynamic multistate occupancy models are a useful tool for analyzing species dynamics because they leverage the autocorrelation inherent in long-term monitoring datasets to obtain useful information about the dynamic properties of population or reproductive states. We analyzed a 23-year bald eagle monitoring dataset in a dynamic multistate occupancy modeling framework to assess long-term nest occupancy and reproduction in Lake Clark National Park and Preserve, Alaska. We also used a hierarchical generalized linear model to understand changes in nest productivity in relation to environmental factors. Nests were most likely to remain in the same nesting state between years. Most notably, successful nests were likely to remain in use (either occupied or successful) and had a very low probability of transitioning to an unoccupied state in the following year. There was no apparent trend in the proportion of nests used by eagles through time, and the probability that nests transitioned into or out of the successful state was not influenced by temperature or salmon availability. Productivity was constant over the course of the study, although warm April minimum temperatures were associated with increased chick production. Overall our results demonstrate the expected nesting dynamics of a healthy bald eagle population that is largely free of human disturbance and can be used as a baseline for the expected dynamics for recovering bald eagle populations in the contiguous 48 states.

Navigating snowscapes: scale-dependent responses of mountain sheep to snowpack properties.

Winters are limiting for many terrestrial animals due to energy deficits brought on by resource scarcity and the increased metabolic costs of thermoregulation and traveling through snow. A better understanding of how animals respond to snow conditions is needed to predict the impacts of climate change on wildlife. We compared the performance of remotely sensed and modeled snow products as predictors of winter movements at multiple spatial and temporal scales using a data set of 20,544 locations from 30 GPS-collared Dall sheep (Ovis dalli dalli) in Lake Clark National Park and Preserve, Alaska, USA from 2005 to 2008. We used daily 500-m MODIS normalized difference snow index (NDSI), and multi-resolution snow depth and density outputs from a snowpack evolution model (SnowModel), as covariates in step selection functions. We predicted that modeled snow depth would perform best across all scales of selection due to more informative spatiotemporal variation and relevance to animal movement. Our results indicated that adding any of the evaluated snow metrics substantially improved model performance and helped characterize winter Dall sheep movements. As expected, SnowModel-simulated snow depth outperformed NDSI at fine-to-moderate scales of selection (step scales < 112 h). At the finest scale, Dall sheep selected for snow depths below mean chest height (<54 cm) when in low-density snows (100 kg/m3 ), which may have facilitated access to ground forage and reduced energy expenditure while traveling. However, sheep selected for higher snow densities (>300 kg/m3 ) at snow depths above chest height, which likely further reduced energy expenditure by limiting hoof penetration in deeper snows. At moderate-to-coarse scales (112-896 h step scales), however, NDSI was the best-performing snow covariate. Thus, the use of publicly available, remotely sensed, snow cover products can substantially improve models of animal movement, particularly in cases where movement distances exceed the MODIS 500-m grid threshold. However, remote sensing products may require substantial data thinning due to cloud cover, potentially limiting its power in cases where complex models are necessary. Snowpack evolution models such as SnowModel offer users increased flexibility at the expense of added complexity, but can provide critical insights into fine-scale responses to rapidly changing snow properties.