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Elucidating patterns of adult survival rates is key to understanding population dynamics of large mammals. We used data from 7 separate studies of mountain goats (Oreamnos americanus) conducted from 2002 through 2022 in western Washington, USA, to quantify survival rates in relation to key biotic and abiotic factors using known fate models implemented in program MARK. We monitored 324 (206 females, 118 males) radio‐marked mountain goats for 178,339 days. A substantial number of mountain goats in our sample (n = 217) had been translocated from the Olympic Peninsula to the Cascade Mountains on Washington's mainland, providing an added opportunity to examine translocation effects. We adopted a sequential modeling approach, first building a set of models to examine fundamental survival patterns by age, sex, season, study area, and translocated status. We used variables retained from the top model in a second set to investigate relationships between annual survival and local weather covariates hypothesized by previous studies to influence mountain goat behavior, habitat selection, and vital rates. Survival among adult females in spring was slightly lower than other sex and age categories, but seasonal patterns were otherwise not evident. There were significant negative relationships between survival and winter snow depth, an index of the previous year's drought, and mean daily temperature during the previous May, and a positive relationship with previous year's precipitation. Weather effects were similar among resident and translocated animals. By the end of the study period, weather effects had evidently contributed to reductions in mountain goat survival to a level low enough that population stability was unlikely. Because the frequency of droughts and warm spring temperatures are expected to increase with climate change, mountain goat populations in Washington will likely be increasingly challenged as the atmosphere warms. [ABSTRACT FROM AUTHOR]

Potential negative artificial selection on horn size is a concern for many harvested ungulates. The mountain goat (Oreamnos americanus) has distinct black horns, but targeting animals based on horn size in the field can be challenging. We analyzed over 23,000 horn records that included base circumference and total length, from which we also derived horn volume, from mountain goats harvested in Alaska, British Columbia, and the Northwest Territories from 1980 to 2016. We tested 3 potential drivers of horn size variation: geographical location, environmental conditions, and artificial selection. We found no support for a latitudinal effect with surprisingly little variation across the sampling distribution. The Pacific Decadal Oscillation had the largest effect outside age in the model, suggesting a role of climate in shaping variation. Mountain goats harvested closer to roads had larger horns, indicating that ease of access might allow hunters to be more selective, though the effect size was small. Our findings reinforce the value of accurate and complete record keeping on horn size, age, and sex of harvested animals, and highlight the importance of explicitly considering climate and accessibility when devising management strategies for the mountain goat. [ABSTRACT FROM AUTHOR]

Understanding patterns of animal space use and range fidelity has important implications for species and habitat conservation. For species that live in highly seasonal environments, such as mountain goats (Oreamnos americanus), spatial use patterns are expected to vary in relation to seasonal changes in environmental conditions and sex‐ or age‐specific selection pressures. To address hypotheses about sex, age, and seasonality influence on space‐use ecology, we collected GPS location data from 263 radio‐collared mountain goats (males, n = 140; females, n = 123) in coastal Alaska during 2005–2016. Location data were analyzed to derive seasonal and sex‐specific fixed‐kernel home range estimates and to quantify the degree of seasonal range and utilization distribution overlap. Overall, we determined that home range size was smallest during winter, expanded coincident with the onset of green‐up and parturition, and was largest during summer. Home range size of males and females did not differ significantly during winter, but females had larger home ranges than males during summer, a relationship that was switched during the mating season. Pairwise comparisons involving individual females across subsequent years indicated home ranges were significantly smaller during years when they gave birth to offspring. Mountain goats exhibited a strong degree of range fidelity, and 99% (n = 138) of individual animals returned to their previous year's seasonal range with an average annual Bhattacharyya's affinity utilization distribution overlap index of 68%. Similarity of seasonal home range utilization distributions varied in relation to sex and season in some respects. Home range overlap was highest during the summer vegetation growing season, particularly among females. These findings advance our understanding about how environmental variation and sex‐ and age‐related reproductive constraints influence space use and range fidelity among alpine ungulates. Documentation of the high degree of range fidelity among mountain goats has important conservation implications in landscapes increasingly altered by anthropogenic activities. [ABSTRACT FROM AUTHOR]

Acquisition of field data and analytical methods needed for conservation and management of wildlife populations represent significant challenges, particularly for species that inhabit landscapes that are difficult to access or species that persist in small, isolated populations. In such instances, integrating diverse and complementary data streams, such as genetic and non‐genetic data, can advance our understanding of population dynamics and associated management implications. We examined how genetic and morphologic data can be used to articulate population structure of a low‐density, peninsular population of mountain goats (Oreamnos americanus) on the Cleveland Peninsula, Alaska, USA, and surrounding areas, 2005–2018. We then use a population demographic modeling approach to examine how the use of population structure information influences sustainable harvest quotas, as compared to a panmictic, null model. Specifically, we conducted extensive field sampling of genetic (n = 446) and morphologic (i.e., horn length, n = 371) data to characterize population structure. We conducted demographic analyses and examined harvest modeling scenarios using a sex‐ and age‐specific matrix population modeling approach. Genetic and morphologic data analyses suggested peninsular subpopulations were demographically isolated, relative to surrounding mainland populations. Specifically, genetic structuring was evident and followed an isolation‐by‐distance, stepping‐stone pattern indicating limited interchange, low effective population sizes, and reduced genetic diversity along a peninsular extremity to mainland gradient. Harvest modeling indicated that overharvest would likely occur if the panmictic, null model was used to guide harvest because the smallest genetically defined population at the peninsular extremity was too small to permit any level of sustainable harvest. Our analyses illustrate the importance of using genetic and morphologic data, in combination with demographic modeling, to quantitatively delineate population boundaries and dynamics for ensuring viability of small, isolated populations. © 2020 The Wildlife Society. We integrated population genetic data and demographic modeling to facilitate conservation of small, peninsular mountain goat populations in coastal Alaska. Our findings illustrate how population genetic data can represent a key resource for delineating populations and, when integrated in a rigorous and quantitative harvest modeling framework, can significantly advance our ability to sustainably manage populations. [ABSTRACT FROM AUTHOR]

Minimum counts are commonly used to estimate population size and trend for wildlife conservation and management; however, the scope of inference based on such data is limited by untestable assumptions regarding the detection process. Alternative approaches, such as distance sampling, occupancy surveys, and repeated counts, can be employed to produce detection‐corrected estimates of population parameters. Unfortunately, these approaches can be more complicated and costly to implement, potentially limiting their use. We explored a conceptual framework linking datasets collected at different spatial scales under different survey designs, with the goal of improving inference. Specifically, we link landscape‐scale distance sampling surveys with local‐scale minimum counts in an integrated modeling framework to estimate mountain goat (Oreamnos americanus) abundance at both the local and regional scale in south‐central Alaska, USA, and provide an estimate of detection probability (i.e., sightability) for the minimum counts. Estimated sightability for the minimum count surveys was 0.67 (95% credible interval [CrI] = 0.52–0.83) and abundance for the entire area was 5,600 goats (CV = 9%), both in broad agreement with estimates from previous studies. Abundance estimates at the local scale (i.e., individual min. count unit) were reasonably precise (CV̅ = 18%), suggesting the integrated approach can increase the amount of information produced at both spatial scales by linking minimum count approaches with more rigorous survey designs. We propose that our integrated approach may be implemented in the context of a modified split‐panel monitoring design by altering survey protocols to include frequent minimum counts within local count units and intermittent but more rigorous survey designs with inference to the entire study area or population of interest. Doing so would provide estimates of abundance with appropriate measures of uncertainty at multiple spatial scales, thereby improving inference for population monitoring and management. © 2019 The Wildlife Society. We demonstrate how data collected under 2 different survey protocols, distance sampling and minimum counts, can be jointly analyzed in an integrated modeling framework. The ability to formally link datasets through analysis provides a critical link between legacy data and more recently developed, rigorous approaches. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In contrast to broad range expansion through translocations, many mountain goat (Oreamnos americanus) populations have shown signs of decline. Recent documentation of pneumonia in mountain goats highlights their susceptibility to bacterial pathogens typically associated with bighorn sheep (Ovis canadensis) epizootics. Respiratory pathogen communities of mountain goats are poorly characterized yet have important implications for management and conservation of both species. We characterized resident pathogen communities across a range of mountain goat populations as an initial step to inform management efforts. Between 2010 and 2017, we sampled 98 individuals within three regions of the Greater Yellowstone Area (GYA), with a smaller sampling effort in southeast Alaska, US. Within the GYA, we detected Mycoplasma ovipneumoniae in two regions and we found at least two Pasteurellaceae species in animals from all regions. Mannheimia haemolytica was the only pathogen that we detected in southeast Alaska. Given the difficult sampling conditions, limited sample size, and imperfect detection, our failure to detect specific pathogens should be interpreted with caution. Nonetheless, respiratory pathogens within the GYA may be an important, yet underappreciated, cause of mountain goat mortality. Moreover, because of the strong niche overlap of bighorn sheep and mountain goats, interspecific transmission is an important concern for managers restoring or introducing mountain ungulates within sympatric ranges. [ABSTRACT FROM AUTHOR]

Landscape heterogeneity plays an integral role in shaping ecological and evolutionary processes. Despite links between the two disciplines, ecologists and population geneticists have taken different approaches to evaluating habitat selection, animal movement, and gene flow across the landscape. Ecologists commonly use statistical models such as resource selection functions (RSFs) to identify habitat features disproportionately selected by animals, whereas population genetic approaches model genetic differentiation according to the distribution of habitat variables. We combined ecological and genetic approaches by using RSFs to predict genetic relatedness across a heterogeneous landscape. We constructed sex- and season-specific resistance surfaces based on RSFs estimated using data from 102 GPS (global positioning system) radio-collared mountain goats (Oreamnos americanus) in southeast Alaska, USA. Based on mountain goat ecology, we hypothesized that summer and male surfaces would be the best predictors of relatedness. All individuals were genotyped at 22 microsatellite loci, which we used to estimate genetic relatedness. Summer resistance surfaces derived from RSFs were the best predictors of genetic relatedness, and winter models the poorest. Mountain goats generally selected for areas close to escape terrain and with a high heat load (a metric related to vegetative productivity and snow depth), while avoiding valleys. Male- and female-specific surfaces were similar, except for winter, for which male habitat selection better predicted genetic relatedness. The null models of isolation-by-distance and barrier only outperformed the winter models. This study merges high-resolution individual locations through GPS telemetry and genetic data, that can be used to validate and parameterize landscape genetics models, and further elucidates the relationship between landscape heterogeneity and genetic differentiation. [ABSTRACT FROM AUTHOR]

Ecological theory predicts that individual survival should vary between sex and age categories due to differences in allocation of nutritional resources for growth and reproductive activities. During periods of environmental stress, such relationships may be exacerbated, and affect sex and age classes differently. We evaluated support for hypotheses about the relative roles of sex, age, and winter and summer climate on the probability of mountain goat (Oreamnos americanus) survival in coastal Alaska. Specifically, we used knownfates analyses (Program MARK) to model the effects of age, sex, and climatic variation on survival using data collected from 279 radio-marked mountain goats (118 M, 161 F) in 9 separate study areas during 1977-2008. Models including age, sex, winter snowfall, and average daily summer temperature (during Jul-Aug) best explained variation in survival probability of mountain goats. Specifically, our findings revealed that old animals (9+yr) have lower survival than younger animals. In addition, males tended to have lower survival than females, though differences only existed among prime-aged adult (5-8 yr) and old (9+yr) age classes. Winter climate exerted the strongest effects on mountain goat survival; summer climate, however, was significant and principally influenced survival during the following winter via indirect effects. Furthermore, old animals were more sensitive to the effects of winter conditions than young or prime-aged animals. These findings detail how climate interacts with sex and age characteristics to affect mountain goat survival. Critically, we provide baseline survival rate statistics across various age, sex, and climate scenarios. These data will assist conservation and management of mountain goats by enabling detailed, model-based demographic forecasting of human and/or climate-based population impacts. [ABSTRACT FROM AUTHOR]