Explore the vast range of titles available.

Popular frameworks for studying habitat selection include resource‐selection functions (RSFs) and step‐selection functions (SSFs), estimated using logistic and conditional logistic regression, respectively. Both frameworks compare environmental covariates associated with locations animals visit with environmental covariates at a set of locations assumed available to the animals. Conceptually, slopes that vary by individual, that is, random coefficient models, could be used to accommodate inter‐individual heterogeneity with either approach. While fitting such models for RSFs is possible with standard software for generalized linear mixed‐effects models (GLMMs), straightforward and efficient one‐step procedures for fitting SSFs with random coefficients are currently lacking. To close this gap, we take advantage of the fact that the conditional logistic regression model (i.e. the SSF) is likelihood‐equivalent to a Poisson model with stratum‐specific fixed intercepts. By interpreting the intercepts as a random effect with a large (fixed) variance, inference for random‐slope models becomes feasible with standard Bayesian techniques, or with frequentist methods that allow one to fix the variance of a random effect. We compare this approach to other commonly applied alternatives, including models without random slopes and mixed conditional regression models fit using a two‐step algorithm. Using data from mountain goats (Oreamnos americanus) and Eurasian otters (Lutra lutra), we illustrate that our models lead to valid and feasible inference. In addition, we conduct a simulation study to compare different estimation approaches for SSFs and to demonstrate the importance of including individual‐specific slopes when estimating individual‐ and population‐level habitat‐selection parameters. By providing coded examples using integrated nested Laplace approximations (INLA) and Template Model Builder (TMB) for Bayesian and frequentist analysis via the R packages R‐INLA and glmmTMB, we hope to make efficient estimation of RSFs and SSFs with random effects accessible to anyone in the field. SSFs with individual‐specific coefficients are particularly attractive since they can provide insights into movement and habitat‐selection processes at fine‐spatial and temporal scales, but these models had previously been very challenging to fit. The authors provide a coherent framework for fitting resource‐selection functions (RSFs) and step‐selection functions (SSFs) with random effects. To allow fitting of SSFs, the authors reformulate the conditional logistic regression model as a (likelihood‐equivalent) Poisson model, where stratum‐specific intercepts are included as a random effect with a fixed large prior variance.

Fitness costs of reproduction are expected when resources are limited. Costs drive the evolution of life‐history strategies and can affect population dynamics if females change their allocation of resources to reproduction. We studied fitness costs of reproduction in mountain ungulates in Alberta, Canada. We monitored two populations of bighorn sheep (Ovis canadensis) for 44 and 30 years, and one of mountain goats (Oreamnos americanus) for 30 years. Both species are highly iteroparous. Heterogeneity in individual reproductive potential makes fitness costs of reproduction difficult to detect and quantify without manipulations. In capital breeders, individual differences can be partly accounted for by considering body mass and other correlates of reproductive potential. Long‐term monitoring can reveal costs that only manifest under stressful conditions such as disease or resource scarcity. Despite individual differences in reproductive potential, we detected fitness costs of reproduction in females. Costs, in terms of mass gain and survival, are almost entirely born by subsequent offspring, as mothers prioritize their own maintenance and survival. Costs are greater for primiparous females, decrease with increasing body mass and increase as resource availability declines, and sons are costlier than daughters. Costs may increase for senescent females that appear to reduce allocation to reproduction. In bighorn sheep, costs mostly involve reduced mass gain and lower survival of subsequent offspring. In mountain goats, costs include reductions in mass gain, subsequent fecundity and juvenile survival. In males, fitness costs derive mostly from attempts to reproduce rather than from siring success and likely depend upon individual competitiveness. In the absence of selective harvests, dominant males may enjoy high fitness and possibly lower costs compared to subordinates. The conservative reproductive tactic of mountain ungulate females likely explains why density dependence mostly involves later primiparity and lower recruitment, but rarely affects adult survival. Future research will seek to better account for heterogeneity in reproductive potential, assess cumulative reproductive costs and investigate the potential effects of fathers on maternal allocation tactics. Fitness costs of reproduction affect the evolution of life histories, morphology and population dynamics of wild species. They are key to the consequences of different forms of exploitation. The authors combine 104 population‐years of monitoring two species of mountain ungulates to show that fitness costs are mostly transferred to subsequent offspring. Résumé Les coûts de la reproduction émergent lorsque les ressources sont limitées et influencent l’évolution des stratégies d’histoire de vie. Si les femelles modifient l’allocation des ressources dans la reproduction pour mitiger ces coûts, ils peuvent aussi affecter la dynamique de population. Nous avons étudié les coûts de la reproduction chez des ongulés en Alberta, Canada. Nous avons suivi deux populations de mouflons d’Amérique (Ovis canadensis) pour 44 et 30 ans, et une de chèvre de montagne (Oreamnos americanus) pour 30 ans. Ces deux espèces sont itéropares. L’hétérogénéité dans le potentiel reproducteur des individus peut masquer les coûts en fitness liés à la reproduction. Ils sont donc plus souvent détectables à l’aide de manipulation expérimentale. Chez les espèces avec reproduction « sur capital », il est possible de contrôler pour les différences individuelles en incluant des variables liées au potentiel reproducteur telles que la masse corporelle. Les suivis à long terme permettent de détecter des coûts qui se manifestent seulement lors de conditions environnementales défavorables. Malgré les différences en potentiel reproducteur, nous avons détecté des coûts chez les femelles. Ces coûts, tels qu’une réduction en croissance ou en survie, sont presque toujours subis par les jeunes nés lors d’épisodes de reproduction subséquents. En effet, les mères priorisent leur propre maintien et leur survie. Les coûts sont supérieurs pour les femelles primipares et dans les conditions défavorables. Ils sont plus faibles pour les femelles plus lourdes et il semble que les fils soient plus coûteux que les filles. Les coûts augmentent aussi chez les femelles sénescentes qui semblent réduire leur allocation dans la reproduction. Chez les mouflons, les coûts impliquent une réduction du gain en masse et une survie plus faible des jeunes nés lors de reproductions subséquentes. Chez les chèvres de montagne, ces coûts sont accompagnés d’une réduction de la fécondité future. Chez les mâles, les coûts sont surtout influencés par l’investissement en temps et en énergie dans le rut plutôt que par le succès d’accouplement. Ces coûts devraient donc surtout dépendre de l’habileté compétitive individuelle. En absence de chasse sélective, les mâles dominants devraient avoir un fort succès reproducteur avec des coûts potentiellement plus faibles comparativement aux subordonnées. La tactique conservative adoptée par les ongulés de montagne femelles peut expliquer pourquoi les effets densité‐dépendant mènent à un retard dans l’âge à la primiparité et à un recrutement plus faible, mais affectent rarement la survie adulte. Nos recherches futures tenteront de mieux quantifier l’hétérogénéité individuelle, évalueront les coûts cumulatifs à la reproduction et investigueront l’effet potentiel des pères sur les tactiques d’allocation maternelles.

Climate change disproportionately affects northern and alpine environments, with faster rates of warming than the global average. Because alpine and northern species are particularly well adapted to cool temperatures, most species must modify their behavior when temperatures exceed a critical threshold. Evaluating how temperature increases affect species inhabiting northern and alpine environments is therefore essential to understand the effects of projected climate change on these ecosystems. We analyzed the influence of temperature on the activity patterns and habitat selection of four populations of a cold-adapted, mountain specialist, the mountain goat (Oreamnos americanus). We collected GPS location and activity sensor data during 2010–2019 from 223 mountain goats from two distinct ecotypes: coastal and continental. Using a resource selection modeling approach, we determined that mountain goats of both ecotypes decreased selection for alpine meadows when temperatures increased. Reduced selection for open, forage rich habitat was associated with increased selection for habitat dominated by snow/ice patches in coastal areas, and by forests in continental sites. Mountain goats in continental environments selected higher elevation habitats only when temperature increased, whereas goats in coastal environments selected higher elevation habitat at all temperatures. Mountain goats of both ecotypes reduced the proportion of time spent active when temperatures increased during the middle of the day. Our study reveals that mountain goats use diverse tactics to mitigate thermal stress, and that these tactics vary between ecotypes, highlighting the need for considering adaptation to specific environments within a species when assessing climate change impacts on populations.

Non‐consumptive effects of predation can strongly impact reproduction and demography of prey species. Still, the underlying mechanisms that drive non‐consumptive effects are not fully understood, and the circumstances under which chronic physiological stress may mediate these effects remain unclear. Benefiting from over 23 years of environmental, physiological and demographic data, we tested the hypothesis that predation risk may impair reproduction of mountain goats through chronic elevation of physiological stress. We conducted path analyses to assess the relationships between predation risk, faecal glucocorticoid metabolites and hair cortisol concentration, and reproduction, while taking into account the potential effects of age class, sex, body mass, season and within individual variation in glucocorticoid concentration. Predation risk had a direct positive effect on the average annual faecal glucocorticoid concentration in the population, which, in turn, negatively affected the proportion of reproductive females. The same pattern was observed with hair cortisol concentration, but these results were inconclusive potentially due to methodological challenges in estimating annual average of hair cortisol at the population level. Our study presents one of the first robust evidence that stress‐mediated breeding suppression can occur in a wild ungulate following increased predation risk, thereby providing a major insight on the mechanisms underlying non‐consumptive effects of predation in wild mammals. A free Plain Language Summary can be found within the Supporting Information of this article. A free Plain Language Summary can be found within the Supporting Information of this article.

In sexually dimorphic and polygynous mammals, sexual selection often favours large males with well- developed weaponry, as these secondary sexual characters confer advantages in intrasexual competition and are often preferred by females. Little is known, however, about the effects of sexually selected paternal traits on offspring phenotype in wild mammals, especially when considering that shared phenotypic traits and selection can also differ greatly between genders. Here, we conducted molecular parentage analyses in a long-term study population of mountain goats (Oreamnos americanus), an ungulate exhibiting high sexual dimorphism in mass, to first assess the determinants of yearly reproductive success (YRS) in males. We then examined the effects of paternal characteristics on offspring mass at 1 year of age. Paternity was highly skewed, with 9 per cent of 57 males siring 51 per cent of 96 offspring assigned over 12 years. Male YRS increased with age until apparent reproductive senescence at 9 years, but mass was a stronger determinant of siring success than age, horn length or social rank. Mass of sons increased with paternal mass, but the mass of daughters was negatively related to that of their father, a finding consistent with recent theory on intralocus sexual conflict. Because early differences in mass persisted to early adulthood, sex-specific effects of paternal mass can have important fitness consequences, as adult mass is positively linked with reproduction in both sexes. Divergent father-offspring phenotypic correlations may partly explain the maintenance of sexual dimorphism in mountain goats and the large variance observed for this homologous trait within each gender in polygynous mammals.

Climate change is expected to disproportionately affect species occupying ecosystems with relatively hard boundaries, such as alpine ecosystems. Wildlife managers must identify actions to conserve and manage alpine species into the future, while considering other issues and uncertainties. Climate change and respiratory pathogens associated with widespread pneumonia epidemics in bighorn sheep (Ovis canadensis) may negatively affect mountain goat (Oreamnos americanus) populations. Mountain goat demographic and population data are challenging to collect and sparsely available, making population management decisions difficult. We developed predictive models incorporating these uncertainties and analyzed results within a structured decision making framework to make management recommendations and identify priority information needs in Montana, USA. We built resource selection models to forecast occupied mountain goat habitat and account for uncertainty in effects of climate change, and a Leslie matrix projection model to predict population trends while accounting for uncertainty in population demographics and dynamics. We predicted disease risks while accounting for uncertainty about presence of pneumonia pathogens and risk tolerance for mixing populations during translocations. Our analysis predicted that new introductions would produce more area occupied by mountain goats at mid-century, regardless of the effects of climate change. Population augmentations, carnivore management, and harvest management may improve population trends, although this was associated with considerable uncertainty. Tolerance for risk of disease transmission affected optimal management choices because translocations are expected to increase disease risks for mountain goats and sympatric bighorn sheep. Expected value of information analyses revealed that reducing uncertainty related to population dynamics would affect the optimal choice among management strategies to improve mountain goat trends. Reducing uncertainty related to the presence of pneumonia-associated pathogens and consequences of mixing microbial communities should reduce disease risks if translocations are included in future management strategies. We recommend managers determine tolerance for disease risks associated with translocations that they and constituents are willing to accept. From this, an adaptive management program can be constructed wherein a portfolio of management actions are chosen based on risk tolerance in each population range, combined with the amount that uncertainty is reduced when paired with monitoring, to ultimately improve achievement of fundamental objectives.

The community of microorganisms in the gut is affected by host species, diet and environment and is linked to normal functioning of the host organism. Although the microbiome fluctuates in response to host demands and environmental changes, there are core groups of microorganisms that remain relatively constant throughout the hosts lifetime. Ruminants are mammals that rely on highly specialized digestive and metabolic modifications, including microbiome adaptations, to persist in extreme environments. Here, we assayed the fecal microbiome of four mountain goat (Oreamnos americanus) populations in western North America. We quantified fecal microbiome diversity and composition among groups in the wild and captivity, across populations and in a single group over time. There were no differences in community evenness or diversity across groups, although we observed a decreasing diversity trend across summer months. Pairwise sample estimates grouped the captive population distinctly from the wild populations, and moderately grouped the southern wild group distinctly from the two northern wild populations. We identified 33 genera modified by captivity, with major differences in key groups associated with cellulose degradation that likely reflect differences in diet. Our findings are consistent with other ruminant studies and provide baseline microbiome data in this enigmatic species, offering valuable insights into the health of wild alpine ungulates.

The development, evaluation, and refinement of effective and humane capture methods for wildlife studies is important for increasing our capacity to understand and effectively manageand conserve wildlife populations. Carfentanil has been the primary agent used to chemically immobilize mountain goats (Oreamnos americanus) during the past 40 years. However, carfentanil is no longer commercially available for wildlife captures in North America. To investigate viable alternatives for mountain goat capture, we conducted field trials using thiafentanil to immobilize free-ranging mountain goats via aerial darting methods; thiafentanil responses were then compared to a standard and widely used carfentanil dose. During June–October, 2005–2020, we immobilized mountain goats with either 2.4–3.0 mg carfentanil (n = 444) or 6.0–7.0 mg thiafentanil (n = 68) across a range of different field conditions at 6 different study sites in coastal Alaska. Induction and recovery times were more rapid (and subsequent immobilization times reduced) using thiafentanil compared to carfentanil. In most other respects, however, immobilization characteristics (i.e., body temperature, pulse rate, relative oxygen saturation) were virtually indistinguishable between individuals immobilized with carfentanil or thiafentanil. During typical immobilizations, mean rectal temperature increased 1.8° C, but increased as much as 3.0° C in some extreme cases. Administration of supplemental oxygen resulted in substantial, potentially clinically significant increases in peripheral capillary oxygen saturation, arterial oxygen, and pH in immobilized mountain goats. Our findings indicate that thiafentanil is an effective alternative to carfentanil for chemical immobilization of mountain goats and may offer some important advantages, particularly when immobilizing mountain goats and other species in difficult and potentially dangerous capture environments.

Anthropogenic activity imposes increasing pressure on wildlife populations globally; these pressures can affect habitat suitability and function, modify wildlife space use, and influence population viability. Native mountain goat (Oreamnos americanus) populations can be negatively affected by anthropogenic disturbance and modify their space use in response to land development and recreational activity. From 2018 to 2020, we studied space use of mountain goats northeast of Smithers, British Columbia, Canada, an area that is subject to increasing anthropogenic development and yearlong recreational activities. We aimed to generate models that would improve our ability to identify habitat for mountain goats relative to existing survey data and established ungulate winter ranges. Using resource selection function (RSF) analyses generated from global positioning system (GPS) collar data, we identified influential habitat covariates and compared these covariates and RSF values to existing habitat models. Additionally, we compared the extent to which our models were congruent with existing resource selection probability functions, were congruent with aerial survey data, and overlapped existing ungulate winter ranges previously derived from predictive models inside and outside of the study area. Overall, our models noted higher RSF values among GPS data relative to aerial survey data for winter months, while results for summer habitats were comparable. In extending our RSFs outside of the study area and evaluating the overlap with ungulate winter ranges in adjacent areas, values were similar, albeit lower, as is expected given that the models were developed elsewhere. Ultimately, these models, combined with existing methods, improve the accuracy and reliability of identified, important areas of habitat for mountain goats. We recommend that the RSF models generated here be used in conjunction with aerial survey data and existing methods to delineate ungulate winter ranges for mountain goats in similar eco-regions in British Columbia. The models developed here support existing methods that have been used to delineate or validate ungulate winter ranges for mountain goats in British Columbia and help facilitate mitigation measures to support the continued use of important winter habitat and significant landscape features that play a role in ensuring population viability and resilience through time.

Although ungulates are the main prey of wolves (Canis lupus) throughout their range, substantial dietary diversity may allow wolves to persist even when ungulates are declining or rare. Alexander Archipelago wolves (Canis lupus ligoni) inhabit distinct mainland and island biogeographic units, each with a unique assemblage of available prey. We quantified biogeographic variability in wolf diets across the archipelago using DNA metabarcoding of prey in 860 wolf scats collected during 2010–2018 in 12 study sites. We hypothesized that wolves would increase their dietary diversity and niche breadth as the proportion of ungulate species in their diets decreased, but that this could be mediated by the availability of coastal resources. Application of DNA metabarcoding achieved fine taxonomic resolution of prey remains and identified 55 diet items representing species from 42 genera and 29 families, many previously undetected in coastal wolf diets. Overall, ungulates made up the largest proportion of wolf diets but were also most variable between study sites (occurrence per item index [O/I] = 0.130–0.851). On islands, Sitka black‐tailed deer (Odocoileus hemionus) were the most consumed ungulate species, whereas moose (Alces alces) and mountain goats (Oreamnos americanus) contributed more to mainland wolf diets. Wolves responded to biogeographical variation in availability of their primary prey by altering their foraging patterns. Wolves increased the number and diversity of species consumed and widened their dietary niche as the proportion of ungulates in their diet declined rather than prey switch to one or few individual diet items. Across all study sites combined, beaver (Castor canadensis; O/I = 0.125), marine mammals (O/I = 0.113), and black bears (Ursus americanus; O/I = 0.067) were important alternate prey. In areas where ungulates had become scarce, sea otters (Enhydra lutris) were particularly important, in one case even becoming the primary diet item suggesting that the ongoing expansion of sea otter populations postreintroduction restores an important food source for these cryptic predators. Here, we show extensive variation in the diet of wolves and elucidate regional consumer–resource interactions across an archipelagic landscape.