Corridor-based approach with spatial cross-validation reveals scale-dependent effects of geographic distance, human footprint and canopy cover on grizzly bear genetic connectivity.

Understanding how human infrastructure and other landscape attributes affect genetic differentiation in animals is an important step for identifying and maintaining dispersal corridors for these species. We built upon recent advances in the field of landscape genetics by using an individual-based and multiscale approach to predict landscape-level genetic connectivity for grizzly bears (Ursus arctos) across ~100,000 km2 in Canada's southern Rocky Mountains. We used a genetic dataset with 1156 unique individuals genotyped at nine microsatellite loci to identify landscape characteristics that influence grizzly bear gene flow at multiple spatial scales and map predicted genetic connectivity through a matrix of rugged terrain, large protected areas, highways and a growing human footprint. Our corridor-based modelling approach used a machine learning algorithm that objectively parameterized landscape resistance, incorporated spatial cross validation and variable selection and explicitly accounted for isolation by distance. This approach avoided overfitting, discarded variables that did not improve model performance across withheld test datasets and spatial predictive capacity compared to random cross-validation. We found that across all spatial scales, geographic distance explained more variation in genetic differentiation in grizzly bears than landscape variables. Human footprint inhibited connectivity across all spatial scales, while open canopies inhibited connectivity at the broadest spatial scale. Our results highlight the negative effect of human footprint on genetic connectivity, provide strong evidence for using spatial cross-validation in landscape genetics analyses and show that multiscale analyses provide additional information on how landscape variables affect genetic differentiation.

Protein biomarkers in serum as a conservation tool to assess reproduction: a case study on brown bears (Ursus arctos).

Monitoring the reproductive characteristics of a species can complement existing conservation strategies by understanding the mechanisms underlying demography. However, methodology to determine important aspects of female reproductive biology is often absent in monitoring programs for large mammals. Protein biomarkers may be a useful tool to detect physiological changes that are indicative of reproductive state. This study aimed to identify protein biomarkers of reproductive status in serum collected from free-ranging female brown bears (Ursus arctos) in Alberta, Canada, from 2001 to 2018. We hypothesized that the expression of proteins related to reproduction in addition to energetics and stress can be used to answer specific management-focused questions: (i) identify when a female is pregnant, (ii) detect if a female is lactating, (iii) determine age of sexual maturity (i.e. primiparity) and (iv) assess female fertility (i.e. reproduction rate). Furthermore, we investigated if silver spoon effects (favourable early life conditions provide fitness benefits through adulthood) could be determined using protein expression. A target panel of 19 proteins with established relationships to physiological function was measured by peptide-based analysis using liquid chromatography and multiple reaction monitoring mass spectrometry and their differential expression was evaluated using a Wilcoxon signed-rank test. We found biomarkers of pregnancy (apolipoprotein B-100 and afamin), lactation (apolipoprotein B-100 and alpha-2-macroglobulin) and sexual maturity (corticosteroid-binding globulin), but there were no statistically significant relationships with protein expression and fertility. The expression of proteins related to reproduction (afamin) and energetics (vitamin-D binding protein) was associated with the nutritional quality of the individual's present habitat rather than their early life habitat. This study highlights potential biomarkers of reproductive status and provides additional methods for monitoring physiological function in wildlife to inform conservation.

Correcting for enzyme immunoassay changes in long term monitoring studies.

Enzyme immunoassays (EIAs) are a common tool for measuring steroid hormones in wildlife due to their low cost, commercial availability, and rapid results. Testing technologies improve continuously, sometimes requiring changes in protocols or crucial assay components. Antibody replacement between EIA kits can cause differences in EIA sensitivity, which can hinder monitoring hormone concentration over time. The antibody in a common cortisol EIA kit used for long-term monitoring of stress in wildlife was replaced in 2014, causing differences in cross reactivity and standard curve concentrations. Therefore, the objective of this study was to develop a method to standardize results following changes in EIA sensitivity. We validated this method using cortisol concentrations measured in the hair of brown bears (Ursus arctos).•We used a simple linear regression to model the relationship between cortisol concentrations using kit 1 and kit 2.•We found a linear relationship between the two kits (R2 = 0.85) and used the regression equation (kit2 = (0.98 × kit1) + 1.65) to predict cortisol concentrations in re-measured samples.•Mean predicted percent error was 16% and 72% of samples had a predicted percent error <20%, suggesting that this method is well-suited for correcting changes in EIA sensitivity.

Landscape condition influences energetics, reproduction, and stress biomarkers in grizzly bears.

Environmental change has been shown to influence mammalian distribution, habitat use, and behavior; however, few studies have investigated the impact on physiological function. This study aimed to determine the influence of landscape condition on the expression of target proteins related to energetics, reproduction, and stress in grizzly bears. We hypothesized that changes in landscape condition explains protein expression. Skin biopsies were collected from free-ranging grizzly bears in Alberta, Canada from 2013-2019 (n = 86 individuals). We used an information theoretic approach to develop 11 a priori candidate generalized linear mixed models to explain protein expression. We compared models using Akaike Information Criteria (AICc) weights and averaged models with ΔAICc < 2 for each protein. Food resources, represented by increased distance to coal mines and decreased crown closure, positively influenced energetic proteins (adiponectin and alpha-1-acid glycoprotein). Proteins related to reproduction (ceruloplasmin and serpin B5) were positively associated with increased wetland and upland food resources in addition to movement, but negatively associated with increased distance to roads. One stress related protein, complement C3, was positively influenced by increased percent conifer. Given the need to detect emerging threats to wildlife, we suggest the assessment of physiological function will lead to improved monitoring of species in rapidly changing landscapes.

Cortisol levels in blood and hair of unanesthetized grizzly bears (Ursus arctos) following intravenous cosyntropin injection.

Hair cortisol concentration (HCC) is being used increasingly to evaluate long-term stress in many mammalian species. Most of the cortisol is assumed to passively diffuse from circulating blood into hair follicles and gradually accumulate in growing hair. However, our research with free-ranging grizzly bears (Ursus arctos) suggests HCC increases significantly within several hours following capture, a time too brief to be explained by this mechanism alone. In this study with captive grizzly bears, we sought to determine if a brief spike in blood cortisol concentration, thus mimicking a single stressful event, would cause an increase in HCC over a 7-day period. To do this, we administered a single intravenous dose (5 µg/kg) of cosyntropin to three captive unanaesthetised adult female grizzly bears on two occasions, during April when hair growth was arrested and during August when hair was growing. In both trials, the cosyntropin caused a two-fold or greater increase in serum cortisol levels within 1 hr but did not appear to influence HCC at 1, 48, and 168 hr following cosyntropin administration. We conclude the cosyntropin-induced cortisol spike was likely insignificant when compared to the adrenocortical response that occurs in free-ranging bears when captured. We suggest further study with a larger sample of captive bears to evaluate the combined effects of anaesthesia and multiple doses of cosyntropin administered over several hours would better simulate the adrenocortical response of free-ranging grizzly bears during capture.

Quantifying energetic costs and defining energy landscapes experienced by grizzly bears.

Animal movements are major determinants of energy expenditure and ultimately the cost-benefit of landscape use. Thus, we sought to understand those costs and how grizzly bears (Ursus arctos) move in mountainous landscapes. We trained captive grizzly bears to walk on a horizontal treadmill and up and down 10% and 20% slopes. The cost of moving upslope increased linearly with speed and slope angle, and this was more costly than moving horizontally. The cost of downslope travel at slower speeds was greater than the cost of traveling horizontally but appeared to decrease at higher speeds. The most efficient walking speed that minimized cost per unit distance was 1.19±0.11 m s-1 However, grizzly bears fitted with GPS collars in the Greater Yellowstone Ecosystem moved at an average velocity of 0.61±0.28 m s-1 and preferred to travel on near-horizontal slopes at twice their occurrence. When traveling uphill or downhill, grizzly bears chose paths across all slopes that were ∼54% less steep and costly than the maximum available slope. The net costs (J kg-1 m-1) of moving horizontally and uphill were the same for grizzly bears, humans and digitigrade carnivores, but those costs were 46% higher than movement costs for ungulates. These movement costs and characteristics of landscape use determined using captive and wild grizzly bears were used to understand the strategies that grizzly bears use for preying on large ungulates and the similarities in travel between people and grizzly bears that might affect the risk of encountering each other on shared landscapes.

Response of grizzly bears (Ursus arctos) to pipelines in Alberta.

This research provides the first in-depth analysis of fine-scale grizzly bear habitat selection and movement patterns in response to the linear footprints cleared for below-ground pipelines in Alberta. Using an extensive set of GPS location data from collared grizzly bears, we were able to determine that grizzly bears selected for younger pipelines (mean age since last construction~6.5 years), which are known to have a greater abundance of important bear foods. Bears also selected for wider corridors that were disturbed for construction more than once. During the spring season, sex/age class was an important predictor of grizzly bear use of pipelines, with adult female bears more likely to use these features than other sex/age classes. Examination of movement patterns revealed that pipeline density influenced grizzly bears' movement rates and path straightness, particularly in the spring, when bears moved more slowly and movement paths were more tortuous in areas with higher pipeline densities. These movement patterns are consistent with foraging behavior and further indicate that bears are not exhibiting avoidance behaviors or displacement by pipeline features, and pipelines may be functioning as seasonally important foraging areas for grizzly bears in Alberta.

Changing spring snow cover dynamics and early season forage availability affect the behavior of a large carnivore.

Changing climates are altering wildlife habitats and wildlife behavior in complex ways. Here, we examine how changing spring snow cover dynamics and early season forage availability are altering grizzly bear (Ursus arctos) behavior postden emergence. Telemetry data were used to identify spring activity dates for 48 individuals in the Yellowhead region of Alberta, Canada. Spring activity date was related to snow cover dynamics using a daily percent snow cover dataset. Snow melt end date, melt rate, and melt consistency explained 45% of the variation in spring activity date. We applied this activity date model across the entire Yellowhead region from 2000 to 2016 using simulated grizzly bear home ranges. Predicted spring activity date was then compared with a daily spring forage availability date dataset, resulting in "wait time" estimates for four key early season forage species. Temporal changes in both spring activity date and early season forage "wait times" were assessed using non-parametric regression. Grizzly bear activity date was found to have either remained constant (95%) or become earlier (5%) across the study area; virtually no areas with significantly later spring activity dates were detected. Similarly, the majority of "wait times" did not change (85%); however, the majority of significant changes in "wait times" for the four early season forage species indicated that "wait times" were lessening where changes were detected. Our results show that spring activity date is largely dictated by snow melt characteristics and that changing snow melt conditions may result in earlier spring activity. However, early season food stress conditions are likely to remain unchanged or improve as vegetation phenology also becomes earlier. Our findings extend the recent work examining animal movement in response to changing phenology from migratory birds and ungulates to an apex predator, further demonstrating the potential effects of changing climates on wildlife species.

Development and validation of protein biomarkers of health in grizzly bears.

Large carnivores play critical roles in the maintenance and function of natural ecosystems; however, the populations of many of these species are in decline across the globe. Therefore, there is an urgent need to develop novel techniques that can be used as sensitive conservation tools to detect new threats to the health of individual animals well in advance of population-level effects. Our study aimed to determine the expression of proteins related to energetics, reproduction and stress in the skin of grizzly bears (Ursus arctos) using a liquid chromatography and multiple reaction monitoring mass spectrometry assay. We hypothesized that a suite of target proteins could be measured using this technique and that the expression of these proteins would be associated with biological (sex, age, sample location on body) and environmental (geographic area, season, sample year) variables. Small skin biopsies were collected from free-ranging grizzly bears in Alberta, Canada, from 2013 to 2019 (n = 136 samples from 111 individuals). Over 700 proteins were detected in the skin of grizzly bears, 19 of which were chosen as targets because of their established roles in physiological function. Generalized linear mixed model analysis was used for each target protein. Results indicate that sample year influenced the majority of proteins, suggesting that physiological changes may be driven in part by responses to changes in the environment. Season influenced the expression of proteins related to energetics, reproduction and stress, all of which were lower during fall compared to early spring. The expression of proteins related to energetics and stress varied by geographic area, while the majority of proteins that were affected by biological attributes (age class, sex and age class by sex interaction) were related to reproduction and stress. This study provides a novel method by which scientists and managers can further assess and monitor physiological function in wildlife.

Grizzly bear response to fine spatial and temporal scale spring snow cover in Western Alberta.

Snow dynamics influence seasonal behaviors of wildlife, such as denning patterns and habitat selection related to the availability of food resources. Under a changing climate, characteristics of the temporal and spatial patterns of snow are predicted to change, and as a result, there is a need to better understand how species interact with snow dynamics. This study examines grizzly bear (Ursus arctos) spring habitat selection and use across western Alberta, Canada. Made possible by newly available fine-scale snow cover data, this research tests a hypothesis that grizzly bears select for locations with less snow cover and areas where snow melts sooner during spring (den emergence to May 31st). Using Integrated Step Selection Analysis, a series of models were built to examine whether snow cover information such as fractional snow covered area and date of snow melt improved models constructed based on previous knowledge of grizzly bear selection during the spring. Comparing four different models fit to 62 individual bear-years, we found that the inclusion of fractional snow covered area improved model fit 60% of the time based on Akaike Information Criterion tallies. Probability of use was then used to evaluate grizzly bear habitat use in response to snow and environmental attributes, including fractional snow covered area, date since snow melt, elevation, and distance to road. Results indicate grizzly bears select for lower elevation, snow-free locations during spring, which has important implications for management of threatened grizzly bear populations in consideration of changing climatic conditions. This study is an example of how fine spatial and temporal scale remote sensing data can be used to improve our understanding of wildlife habitat selection and use in relation to key environmental attributes.

Natural regeneration on seismic lines influences movement behaviour of wolves and grizzly bears.

Across the boreal forest of Canada, habitat disturbance is the ultimate cause of caribou (Rangifer tarandus caribou) declines. Habitat restoration is a focus of caribou recovery efforts, with a goal to finding ways to reduce predator use of disturbances, and caribou-predator encounters. One of the most pervasive disturbances within caribou ranges in Alberta, Canada are seismic lines cleared for energy exploration. Seismic lines facilitate predator movement, and although vegetation on some seismic lines is regenerating, it remains unknown whether vegetation regrowth is sufficient to alter predator response. We used Light Detection and Ranging (LiDAR) data, and GPS locations, to understand how vegetation and other attributes of seismic lines influence movements of two predators, wolves (Canis lupus) and grizzly bears (Ursus arctos). During winter, wolves moved towards seismic lines regardless of vegetation height, while during spring wolves moved towards seismic lines with higher vegetation. During summer, wolves moved towards seismic lines with lower vegetation and also moved faster near seismic lines with vegetation <0.7 m. Seismic lines with lower vegetation height were preferred by grizzly bears during spring and summer, but there was no relationship between vegetation height and grizzly bear movement rates. These results suggest that wolves use seismic lines for travel during summer, but during winter wolf movements relative to seismic lines could be influenced by factors additional to movement efficiency; potentially enhanced access to areas frequented by ungulate prey. Grizzly bears may be using seismic lines for movement, but could also be using seismic lines as a source of vegetative food or ungulate prey. To reduce wolf movement rate, restoration could focus on seismic lines with vegetation <1 m in height. However our results revealed that seismic lines continue to influence wolf movement behaviour decades after they were built, and even at later stages of regeneration. Therefore it remains unknown at what stage of natural regeneration, if any, wolves cease to respond to seismic lines. To reduce wolf response to seismic lines, active restoration tactics like blocking seismic lines and tree planting, along with management of alternate prey, could be evaluated.

Using spatial mark-recapture for conservation monitoring of grizzly bear populations in Alberta.

One of the challenges in conservation is determining patterns and responses in population density and distribution as it relates to habitat and changes in anthropogenic activities. We applied spatially explicit capture recapture (SECR) methods, combined with density surface modelling from five grizzly bear (Ursus arctos) management areas (BMAs) in Alberta, Canada, to assess SECR methods and to explore factors influencing bear distribution. Here we used models of grizzly bear habitat and mortality risk to test local density associations using density surface modelling. Results demonstrated BMA-specific factors influenced density, as well as the effects of habitat and topography on detections and movements of bears. Estimates from SECR were similar to those from closed population models and telemetry data, but with similar or higher levels of precision. Habitat was most associated with areas of higher bear density in the north, whereas mortality risk was most associated (negatively) with density of bears in the south. Comparisons of the distribution of mortality risk and habitat revealed differences by BMA that in turn influenced local abundance of bears. Combining SECR methods with density surface modelling increases the resolution of mark-recapture methods by directly inferring the effect of spatial factors on regulating local densities of animals.

Functional macronutritional generalism in a large omnivore, the brown bear.

We combine a recently developed framework for describing dietary generalism with compositional data analysis to examine patterns of omnivory in a large widely distributed mammal. Using the brown bear (Ursus arctos) as a model species, we collected and analyzed data from the literature to estimate the proportions of macronutrients (protein, carbohydrate, and lipid) in the diets of bear populations. Across their range, bears consumed a diversity of foods that resulted in annual population diets that varied in macronutrient proportions, suggesting a wide fundamental macronutrient niche. The variance matrix of pairwise macronutrient log-ratios indicated that the most variable macronutrient among diets was carbohydrate, while protein and lipid were more proportional or codependent (i.e., relatively more constant log-ratios). Populations that consumed anthropogenic foods, such agricultural crops and supplementary feed (e.g., corn), had a higher geometric mean proportion of carbohydrate, and lower proportion of protein, in annual diets. Seasonally, mean diets were lower in protein and higher in carbohydrate, during autumn compared to spring. Populations with anthropogenic subsidies, however, had higher mean proportions of carbohydrate and lower protein, across seasons compared to populations with natural diets. Proportions of macronutrients similar to those selected in experiments by captive brown bears, and which optimized primarily fat mass gain, were observed among hyperphagic prehibernation autumn diets. However, the majority of these were from populations consuming anthropogenic foods, while diets of natural populations were more variable and typically higher in protein. Some anthropogenic diets were close to the proportions selected by captive bears during summer. Our results suggest that omnivory in brown bears is a functional adaptation enabling them to occupy a diverse range of habitats and tolerate variation in the nutritional composition and availability of food resources. Furthermore, we show that populations consuming human-sourced foods have different dietary macronutrient proportions relative to populations with natural diets.

Can concentrations of steroid hormones in brown bear hair reveal age class?

Although combining genetic and endocrine data from non-invasively collected hair samples has potential to improve the conservation of threatened mammals, few studies have evaluated this opportunity. In this study, we determined if steroid hormone (testosterone, progesterone, estradiol and cortisol) concentration profiles in 169 hair samples collected from free-ranging brown bears (Ursus arctos) could be used to accurately discriminate between immature and adult bears within each sex. Because hair samples were acquired opportunistically, we also needed to establish if interactions between hormones and several non-hormone factors (ordinal day, year, contact method, study area) were associated with age class. For each sex, we first compared a suite of candidate models by Akaike Information Criteria model selection, using different adult-age thresholds (3, 4 and 5 years), to determine the most supported adult age. Because hair hormone levels better reflect the endocrine state at an earlier time, possibly during the previous year, then at the time of sampling, we re-analysed the data, excluding the records for bears at the adult-age threshold, to establish if classification accuracy improved. For both sexes, candidate models were most supported based on a 3-year-old adult-age threshold. Classification accuracy did not improve with the 3-year-old bear data excluded. Male age class was predicted with a high degree of accuracy (88.4%) based on the concomitant concentrations of all four hormones. Female age class was predicted with less accuracy (77.1%) based only on testosterone and cortisol. Accuracy was reduced for females, primarily because we had poor success in correctly classifying immature bears (60%) whereas classification success for adult females was similar to that for males (84.5%). Given the small and unbalanced sample used in this study, our findings should be viewed as preliminary, but they should also provide a basis for more comprehensive future studies.

Space-time clusters for early detection of grizzly bear predation.

Accurate detection and classification of predation events is important to determine predation and consumption rates by predators. However, obtaining this information for large predators is constrained by the speed at which carcasses disappear and the cost of field data collection. To accurately detect predation events, researchers have used GPS collar technology combined with targeted site visits. However, kill sites are often investigated well after the predation event due to limited data retrieval options on GPS collars (VHF or UHF downloading) and to ensure crew safety when working with large predators. This can lead to missing information from small-prey (including young ungulates) kill sites due to scavenging and general site deterioration (e.g., vegetation growth). We used a space-time permutation scan statistic (STPSS) clustering method (SaTScan) to detect predation events of grizzly bears (Ursus arctos) fitted with satellite transmitting GPS collars. We used generalized linear mixed models to verify predation events and the size of carcasses using spatiotemporal characteristics as predictors. STPSS uses a probability model to compare expected cluster size (space and time) with the observed size. We applied this method retrospectively to data from 2006 to 2007 to compare our method to random GPS site selection. In 2013-2014, we applied our detection method to visit sites one week after their occupation. Both datasets were collected in the same study area. Our approach detected 23 of 27 predation sites verified by visiting 464 random grizzly bear locations in 2006-2007, 187 of which were within space-time clusters and 277 outside. Predation site detection increased by 2.75 times (54 predation events of 335 visited clusters) using 2013-2014 data. Our GLMMs showed that cluster size and duration predicted predation events and carcass size with high sensitivity (0.72 and 0.94, respectively). Coupling GPS satellite technology with clusters using a program based on space-time probability models allows for prompt visits to predation sites. This enables accurate identification of the carcass size and increases fieldwork efficiency in predation studies.

Recognizing the importance of an all-inclusive approach to brown bear conservation now and into the future.

In their critique of our recent article in Oecologia (Pigeon et al. Oecologia 181:1101-1116, 2016a) investigating the influence of ambient temperature on brown bear habitat selection, Ordiz et al. (2017, current issue) argue that we downplay the role of human disturbance on bear behavior, and that we wrongly report on the findings of Ordiz et al. (Oecologia 166:59-67, 2011). We argue that our previous article in Oecologia (Pigeon et al. 2016a) by no means downplays the influence of human factors on bear behavior, and that we correctly stated that Ordiz et al. (2011) did not adequately consider the potential influence of temperature on their findings. Finally, we stress the relevance of considering all-inclusive approaches to the common goal of successful wildlife conservation.

The quantification of reproductive hormones in the hair of captive adult brown bears and their application as indicators of sex and reproductive state.

Recognizing the potential value of steroid hormone measurements to augment non-invasive genetic sampling, we developed procedures based on enzyme-linked immunoassays to quantify reproductive steroid hormone concentrations in brown bear (Ursus arctos) hair. Then, using 94 hair samples collected from eight captive adult bears over a 2-year period, we evaluated (i) associations between hair concentrations of testosterone, progesterone, estradiol and cortisol; (ii) the effect of collecting by shaving vs. plucking; and (iii) the utility of reproductive hormone profiles to differentiate sex and reproductive state. Sample requirements (125 mg of guard hair) to assay all hormones exceeded amounts typically obtained by non-invasive sampling. Thus, broad application of this approach will require modification of non-invasive techniques to collect larger samples, use of mixed (guard and undercoat) hair samples and/or application of more sensitive laboratory procedures. Concentrations of hormones were highly correlated suggesting their sequestration in hair reflects underlying physiological processes. Marked changes in hair hormone levels during the quiescent phase of the hair cycle, coupled with the finding that progesterone concentrations, and their association with testosterone levels, differed markedly between plucked and shaved hair samples, suggests steroids sequestered in hair were likely derived from various sources, including skin. Changes in hair hormone concentrations over time, and in conjunction with key reproductive events, were similar to what has been reported concerning hormonal changes in the blood serum of brown bears. Thus, potential for the measurement of hair reproductive hormone levels to augment non-invasive genetic sampling appears compelling. Nonetheless, we are conducting additional validation studies on hair collected from free-ranging bears, representative of all sex, age and reproductive classes, to fully evaluate the utility of this approach for brown bear conservation and research.

Comparison of methanol and isopropanol as wash solvents for determination of hair cortisol concentration in grizzly bears and polar bears.

Methodological differences among laboratories are recognized as significant sources of variation in quantification of hair cortisol concentration (HCC). An important step in processing hair, particularly when collected from wildlife, is the choice of solvent used to remove or "wash" external hair shaft cortisol prior to quantification of HCC. The present study systematically compared methanol and isopropanol as wash solvents for their efficiency at removing external cortisol without extracting internal hair shaft cortisol in samples collected from free-ranging grizzly bears and polar bears. Cortisol concentrations in solvents and hair were determined in each of one to eight washes of hair with each solvent independently. •There were no significant decreases in internal hair shaft cortisol among all eight washes for either solvent, although methanol removed detectable hair surface cortisol after one wash in grizzly bear hair whereas hair surface cortisol was detected in all eight isopropanol washes.•There were no significant differences in polar bear HCC washed one to eight times with either solvent, but grizzly bear HCC was significantly greater in hair washed with isopropanol compared to methanol.•There were significant differences in HCC quantified using different commercial ELISA kits commonly used for HCC determinations.

A Double-Blinded, Randomized Comparison of Medetomidine-Tiletamine-Zolazepam and Dexmedetomidine-Tiletamine-Zolazepam Anesthesia in Free-Ranging Brown Bears (Ursus Arctos).

We compared anesthetic features, blood parameters, and physiological responses to either medetomidine-tiletamine-zolazepam or dexmedetomidine-tiletamine-zolazepam using a double-blinded, randomized experimental design during 40 anesthetic events of free-ranging brown bears (Ursus arctos) either captured by helicopter in Sweden or by culvert trap in Canada. Induction was smooth and predictable with both anesthetic protocols. Induction time, the need for supplemental drugs to sustain anesthesia, and capture-related stress were analyzed using generalized linear models, but anesthetic protocol did not differentially affect these variables. Arterial blood gases and acid-base status, and physiological responses were examined using linear mixed models. We documented acidemia (pH of arterial blood < 7.35), hypoxemia (partial pressure of arterial oxygen < 80 mmHg), and hypercapnia (partial pressure of arterial carbon dioxide ≥ 45 mmHg) with both protocols. Arterial pH and oxygen partial pressure were similar between groups with the latter improving markedly after oxygen supplementation (p < 0.001). We documented dose-dependent effects of both anesthetic protocols on induction time and arterial oxygen partial pressure. The partial pressure of arterial carbon dioxide increased as respiratory rate increased with medetomidine-tiletamine-zolazepam, but not with dexmedetomidine-tiletamine-zolazepam, demonstrating a differential drug effect. Differences in heart rate, respiratory rate, and rectal temperature among bears could not be attributed to the anesthetic protocol. Heart rate increased with increasing rectal temperature (p < 0.001) and ordinal day of capture (p = 0.002). Respiratory rate was significantly higher in bears captured by helicopter in Sweden than in bears captured by culvert trap in Canada (p < 0.001). Rectal temperature significantly decreased over time (p ≤ 0.05). Overall, we did not find any benefit of using dexmedetomidine-tiletamine-zolazepam instead of medetomidine-tiletamine-zolazepam in the anesthesia of brown bears. Both drug combinations appeared to be safe and reliable for the anesthesia of free-ranging brown bears captured by helicopter or by culvert trap.

Heading for the hills? Evaluating spatial distribution of woodland caribou in response to a growing anthropogenic disturbance footprint.

Anthropogenic landscape change (i.e., disturbance) is recognized as an important factor in the decline and extirpation of wildlife populations. Understanding and monitoring the relationship between wildlife distribution and disturbance is necessary for effective conservation planning. Many studies consider disturbance as a covariate explaining wildlife behavior. However, we propose that there are several advantages to considering the spatial relationship between disturbance and wildlife directly using utilization distributions (UDs), including objective assessment of the spatially explicit overlap between wildlife and disturbance, and the ability to track trends in this relationship over time. Here, we examined how central mountain woodland caribou (Rangifer tarandus caribou) distribution changed over time in relation to (i) anthropogenic disturbance, baseline range (defined using telemetry data from 1998 to 2005), and alpine habitat; and (ii) interannual climate variation (North Pacific Index; NPI). We developed seasonal UDs for caribou in west-central Alberta and east-central British Columbia, Canada, monitored with GPS collars between 1998 and 2013. We mapped the cumulative annual density of disturbance features within caribou range and used indices of overlap to determine the spatial relationship and trend between caribou UDs, anthropogenic disturbance, baseline range, alpine habitat, and the NPI. Anthropogenic disturbance increased over time, but the overlap between caribou UDs and disturbance did not. Caribou use of alpine habitat during spring, fall, and late winter increased over time, concurrent with a decrease in use of baseline range. Overlap between caribou UDs and disturbance increased during spring and fall following relatively cold, snowy winters (high NPI), but overall, climate did not explain changes in caribou distribution over time. We provide evidence supporting the hypothesis that caribou populations adjust their spatial distribution in relation to anthropogenic landscape change. Our findings could have implications for population persistence if distributional shifts result in greater use of alpine habitat during winter. Monitoring long-term changes in the distribution of populations is a valuable component of conservation planning for species at risk in disturbed landscapes.