Reproductive Fate of Brucellosis-Seropositive Elk (Cervus canadensis): Implications for Disease Transmission Risk.

Brucellosis is a disease caused by the bacterium Brucella abortus that infects elk (Cervus canadensis) and cattle (Bos taurus). There is the potential for transmission from wildlife to livestock through contact with infected material shed during abortions or live births. To understand the impact of exposure on pregnancy rates we captured 30-100 elk per year from 2011 through 2020, testing their blood for serologic exposure to B. abortus. Predicted pregnancy rates for seropositive animals were 9.6% lower in prime-age (2.5-15.5 yr; 85%, 95% confidence interval [CI]: 74-91%) and 37.7% lower in old (>15.5 yr; 43%, 95% CI: 19-71%) elk as compared with seronegative animals. To understand the risk of seropositive elk shedding B. abortus bacteria and the effects of exposure on elk reproductive performance, we conducted a 5-yr longitudinal study monitoring 30 seropositive elk. We estimated the annual probability of a seropositive elk having an abortion as 0.06 (95% CI: 0.02-0.15). We detected B. abortus at three abortions and two live births, using a combination of culture and PCR testing. The predicted probability of a pregnant seropositive elk shedding B. abortus during an abortion or live birth was 0.08 (95% CI: 0.04-0.19). To understand what proportion of seropositive elk harbored live B. abortus bacteria in their tissues, we euthanized seropositive elk at the end of 5 yr of monitoring and sampled tissues for B. abortus. Assuming perfect detection, the predicted probability of a seropositive elk having B. abortus in at least one tissue was 0.18 (95% CI: 0.06-0.43). The transmission risk seropositive elk pose is mitigated by decreased pregnancy rates, low probability of abortion events, low probability of shedding at live birth events, and reasonably low probability of B. abortus in tissues.

Wherever I may roam-Human activity alters movements of red deer (Cervus elaphus) and elk (Cervus canadensis) across two continents.

Human activity and associated landscape modifications alter the movements of animals with consequences for populations and ecosystems worldwide. Species performing long-distance movements are thought to be particularly sensitive to human impact. Despite the increasing anthropogenic pressure, it remains challenging to understand and predict animals' responses to human activity. Here we address this knowledge gap using 1206 Global Positioning System movement trajectories of 815 individuals from 14 red deer (Cervus elaphus) and 14 elk (Cervus canadensis) populations spanning wide environmental gradients, namely the latitudinal range from the Alps to Scandinavia in Europe, and the Greater Yellowstone Ecosystem in North America. We measured individual-level movements relative to the environmental context, or movement expression, using the standardized metric Intensity of Use, reflecting both the directionality and extent of movements. We expected movement expression to be affected by resource (Normalized Difference Vegetation Index, NDVI) predictability and topography, but those factors to be superseded by human impact. Red deer and elk movement expression varied along a continuum, from highly segmented trajectories over relatively small areas (high intensity of use), to directed transitions through restricted corridors (low intensity of use). Human activity (Human Footprint Index, HFI) was the strongest driver of movement expression, with a steep increase in Intensity of Use as HFI increased, but only until a threshold was reached. After exceeding this level of impact, the Intensity of Use remained unchanged. These results indicate the overall sensitivity of Cervus movement expression to human activity and suggest a limitation of plastic responses under high human pressure, despite the species also occurring in human-dominated landscapes. Our work represents the first comparison of metric-based movement expression across widely distributed populations of a deer genus, contributing to the understanding and prediction of animals' responses to human activity.

Evaluating the summer landscapes of predation risk and forage quality for elk (Cervus canadensis).

The recovery of carnivore populations in North American has consequences for trophic interactions and population dynamics of prey. In addition to direct effects on prey populations through killing, predators can influence prey behavior by imposing the risk of predation. The mechanisms through which patterns of space use by predators are linked to behavioral response by prey and nonconsumptive effects on prey population dynamics are poorly understood. Our goal was to characterize population- and individual-level patterns of resource selection by elk (Cervus canadensis) in response to risk of wolves (Canis lupus) and mountain lions (Puma concolor) and evaluate potential nonconsumptive effects of these behavioral patterns. We tested the hypothesis that individual elk risk-avoidance behavior during summer would result in exposure to lower-quality forage and reduced body fat and pregnancy rates. First, we evaluated individuals' second-order and third-order resource selection with a used-available sampling design. At the population level, we found evidence for a positive relationship between second- and third-order selection and forage, and an interaction between forage quality and mountain lion risk such that the relative probability of use at low mountain lion risk increased with forage quality but decreased at high risk at both orders of selection. We found no evidence of a population-level trade-off between forage quality and wolf risk. However, we found substantial among-individual heterogeneity in resource selection patterns such that population-level patterns were potentially misleading. We found no evidence that the diversity of individual resource selection patterns varied predictably with available resources, or that patterns of individual risk-related resource selection translated into biologically meaningful changes in body fat or pregnancy rates. Our work highlights the importance of evaluating individual responses to predation risk and predator hunting technique when assessing responses to predators and suggests nonconsumptive effects are not operating at a population scale in this system.

Non-invasive monitoring of multiple wildlife health factors by fecal microbiome analysis.

Fecal microbial biomarkers represent a less invasive alternative for acquiring information on wildlife populations than many traditional sampling methodologies. Our goal was to evaluate linkages between fecal microbiome communities in Rocky Mountain elk (Cervus canadensis) and four host factors including sex, age, population, and physical condition (body-fat). We paired a feature-selection algorithm with an LDA-classifier trained on elk differential bacterial abundance (16S-rRNA amplicon survey) to predict host health factors from 104 elk microbiomes across four elk populations. We validated the accuracy of the various classifier predictions with leave-one-out cross-validation using known measurements. We demonstrate that the elk fecal microbiome can predict the four host factors tested. Our results show that elk microbiomes respond to both the strong extrinsic factor of biogeography and simultaneously occurring, but more subtle, intrinsic forces of individual body-fat, sex, and age-class. Thus, we have developed and described herein a generalizable approach to disentangle microbiome responses attributed to multiple host factors of varying strength from the same bacterial sequence data set. Wildlife conservation and management presents many challenges, but we demonstrate that non-invasive microbiome surveys from scat samples can provide alternative options for wildlife population monitoring. We believe that, with further validation, this method could be broadly applicable in other species and potentially predict other measurements. Our study can help guide the future development of microbiome-based monitoring of wildlife populations and supports hypothetical expectations found in host-microbiome theory.

Sex-Specific Elk Resource Selection during the Anthrax Risk Period.

Anthrax, caused by the spore-forming bacterium Bacillus anthracis, is a zoonosis affecting animals and humans globally. In the United States, anthrax outbreaks occur in wildlife and livestock, with frequent outbreaks in native and exotic wildlife species in Texas, livestock outbreaks in the Dakotas, and sporadic mixed outbreaks in Montana. Understanding where pathogen and host habitat selection overlap is essential for anthrax management. Resource selection and habitat use of ungulates may be sex-specific and lead to differential anthrax exposure risks across the landscape for males and females. We evaluated female elk (Cervus canadensis) resource selection in the same study areas as male elk in a previous anthrax risk study to identify risk of anthrax transmission to females and compare transmission risk between females and males. We developed a generalized linear mixed-effect model to estimate resource selection for female elk in southwest Montana during the June to August anthrax transmission risk period. We then predicted habitat selection of female and male elk across the study area and compared selection with the distribution of anthrax risk to identify spatial distributions of potential anthrax exposure for the male and female elk. Female and male elk selected different resources during the anthrax risk period, which resulted in different anthrax exposure areas for females and males. The sex-specific resource selection and habitat use could infer different areas of risk for anthrax transmission, which can improve anthrax and wildlife management and have important public health and economic implications.

Elk migration influences the risk of disease spillover in the Greater Yellowstone Ecosystem.

Wildlife migrations provide important ecosystem services, but they are declining. Within the Greater Yellowstone Ecosystem (GYE), some elk Cervus canadensis herds are losing migratory tendencies, which may increase spatiotemporal overlap between elk and livestock (domestic bison Bison bison and cattle Bos taurus), potentially exacerbating pathogen transmission risk. We combined disease, movement, demographic and environmental data from eight elk herds in the GYE to examine the differential risk of brucellosis transmission (through aborted foetuses) from migrant and resident elk to livestock. For both migrants and residents, we found that transmission risk from elk to livestock occurred almost exclusively on private ranchlands as opposed to state or federal grazing allotments. Weather variability affected the estimated distribution of spillover risk from migrant elk to livestock, with a 7%-12% increase in migrant abortions on private ranchlands during years with heavier snowfall. In contrast, weather variability did not affect spillover risk from resident elk. Migrant elk were responsible for the majority (68%) of disease spillover risk to livestock because they occurred in greater numbers than resident elk. On a per-capita basis, however, our analyses suggested that resident elk disproportionately contributed to spillover risk. In five of seven herds, we estimated that the per-capita spillover risk was greater from residents than from migrants. Averaged across herds, an individual resident elk was 23% more likely than an individual migrant elk to abort on private ranchlands. Our results demonstrate links between migration behaviour, spillover risk and environmental variability, and highlight the utility of integrating models of pathogen transmission and host movement to generate new insights about the role of migration in disease spillover risk. Furthermore, they add to the accumulating body of evidence across taxa that suggests that migrants and residents should be considered separately during investigations of wildlife disease ecology. Finally, our findings have applied implications for elk and brucellosis in the GYE. They suggest that managers should prioritize actions that maintain spatial separation of elk and livestock on private ranchlands during years when snowpack persists into the risk period.

How sure are you? A web-based application to confront imperfect detection of respiratory pathogens in bighorn sheep.

The relationships between host-pathogen population dynamics in wildlife are poorly understood. An impediment to progress in understanding these relationships is imperfect detection of diagnostic tests used to detect pathogens. If ignored, imperfect detection precludes accurate assessment of pathogen presence and prevalence, foundational parameters for deciphering host-pathogen dynamics and disease etiology. Respiratory disease in bighorn sheep (Ovis canadensis) is a significant impediment to their conservation and restoration, and effective management requires a better understanding of the structure of the pathogen communities. Our primary objective was to develop an easy-to-use and accessible web-based Shiny application that estimates the probability (with associated uncertainty) that a respiratory pathogen is present in a herd and its prevalence given imperfect detection. Our application combines the best-available information on the probabilities of detection for various respiratory pathogen diagnostic protocols with a hierarchical Bayesian model of pathogen prevalence. We demonstrated this application using four examples of diagnostic tests from three herds of bighorn sheep in Montana. For instance, one population with no detections of Mycoplasma ovipneumoniae (PCR assay) still had an 6% probability of the pathogen being present in the herd. Similarly, the apparent prevalence (0.32) of M. ovipneumoniae in another herd was a substantial underestimate of estimated true prevalence (0.46: 95% CI = [0.25, 0.71]). The negative bias of naïve prevalence increased as the probability of detection of testing protocols worsened such that the apparent prevalence of Mannheimia haemolytica (culture assay) in a herd (0.24) was less than one third that of estimated true prevalence (0.78: 95% CI = [0.43, 0.99]). We found a small difference in the estimates of the probability that Mannheimia spp. (culture assay) was present in one herd between the binomial sampling approach (0.24) and the hypergeometric approach (0.22). Ignoring the implications of imperfect detection and sampling variation for assessing pathogen communities in bighorn sheep can result in spurious inference on pathogen presence and prevalence, and potentially poorly informed management decisions. Our Shiny application makes the rigorous assessment of pathogen presence, prevalence and uncertainty straightforward, and we suggest it should be incorporated into a new paradigm of disease monitoring.

Wave-like Patterns of Plant Phenology Determine Ungulate Movement Tactics.

Animals exhibit a diversity of movement tactics [1]. Tracking resources that change across space and time is predicted to be a fundamental driver of animal movement [2]. For example, some migratory ungulates (i.e., hooved mammals) closely track the progression of highly nutritious plant green-up, a phenomenon called "green-wave surfing" [3-5]. Yet general principles describing how the dynamic nature of resources determine movement tactics are lacking [6]. We tested an emerging theory that predicts surfing and the existence of migratory behavior will be favored in environments where green-up is fleeting and moves sequentially across large landscapes (i.e., wave-like green-up) [7]. Landscapes exhibiting wave-like patterns of green-up facilitated surfing and explained the existence of migratory behavior across 61 populations of four ungulate species on two continents (n = 1,696 individuals). At the species level, foraging benefits were equivalent between tactics, suggesting that each movement tactic is fine-tuned to local patterns of plant phenology. For decades, ecologists have sought to understand how animals move to select habitat, commonly defining habitat as a set of static patches [8, 9]. Our findings indicate that animal movement tactics emerge as a function of the flux of resources across space and time, underscoring the need to redefine habitat to include its dynamic attributes. As global habitats continue to be modified by anthropogenic disturbance and climate change [10], our synthesis provides a generalizable framework to understand how animal movement will be influenced by altered patterns of resource phenology.

Evaluating wildlife translocations using genomics: A bighorn sheep case study.

Wildlife restoration often involves translocation efforts to reintroduce species and supplement small, fragmented populations. We examined the genomic consequences of bighorn sheep (Ovis canadensis) translocations and population isolation to enhance understanding of evolutionary processes that affect population genetics and inform future restoration strategies. We conducted a population genomic analysis of 511 bighorn sheep from 17 areas, including native and reintroduced populations that received 0-10 translocations. Using the Illumina High Density Ovine array, we generated datasets of 6,155 to 33,289 single nucleotide polymorphisms and completed clustering, population tree, and kinship analyses. Our analyses determined that natural gene flow did not occur between most populations, including two pairs of native herds that had past connectivity. We synthesized genomic evidence across analyses to evaluate 24 different translocation events and detected eight successful reintroductions (i.e., lack of signal for recolonization from nearby populations) and five successful augmentations (i.e., reproductive success of translocated individuals) based on genetic similarity with the source populations. A single native population founded six of the reintroduced herds, suggesting that environmental conditions did not need to match for populations to persist following reintroduction. Augmentations consisting of 18-57 animals including males and females succeeded, whereas augmentations of two males did not result in a detectable genetic signature. Our results provide insight on genomic distinctiveness of native and reintroduced herds, information on the relative success of reintroduction and augmentation efforts and their associated attributes, and guidance to enhance genetic contribution of augmentations and reintroductions to aid in bighorn sheep restoration.

An improved understanding of ungulate population dynamics using count data: Insights from western Montana.

Understanding the dynamics of ungulate populations is critical given their ecological and economic importance. In particular, the ability to evaluate the evidence for potential drivers of variation in population trajectories is important for informed management. However, the use of age ratio data (e.g., juveniles:adult females) as an index of variation in population dynamics is hindered by a lack of statistical power and difficult interpretation. Here, we show that the use of a population model based on count, classification and harvest data can dramatically improve the understanding of ungulate population dynamics by: 1) providing estimates of vital rates (e.g., per capita recruitment and population growth) that are easier to interpret and more useful to managers than age ratios and 2) increasing the power to assess potential sources of variation in key vital rates. We used a time series of elk (Cervus canadensis) spring count and classification data (2004 to 2016) and fall harvest data from hunting districts in western Montana to construct a population model to estimate vital rates and assess evidence for an association between a series of environmental covariates and indices of predator abundance on per capita recruitment rates of elk calves. Our results suggest that per capita recruitment rates were negatively associated with cold and wet springs, and severe winters, and positively associated with summer precipitation. In contrast, an analysis of the raw age ratio data failed to detect these relationships. Our approach based on a population model provided estimates of the region-wide mean per capita recruitment rate (mean = 0.25, 90% CI = 0.21, 0.29), temporal variation in hunting-district-specific recruitment rates (minimum = 0.09; 90% CI = [0.07, 0.11], maximum = 0.43; 90% CI = [0.38, 0.48]), and annual population growth rates (minimum = 0.83; 90% CI = [0.78, 0.87], maximum = 1.20; 90% CI = [1.11, 1.29]). We recommend using routinely collected population count and classification data and a population modeling approach rather than interpreting estimated age ratios as a substantial improvement in understanding population dynamics.

Characterizing population and individual migration patterns among native and restored bighorn sheep (Ovis canadensis).

Migration evolved as a behavior to enhance fitness through exploiting spatially and temporally variable resources and avoiding predation or other threats. Globally, landscape alterations have resulted in declines to migratory populations across taxa. Given the long time periods over which migrations evolved in native systems, it is unlikely that restored populations embody the same migratory complexity that existed before population reductions or regional extirpation.We used GPS location data collected from 209 female bighorn sheep (Ovis canadensis) to characterize population and individual migration patterns along elevation and geographic continuums for 18 populations of bighorn sheep with different management histories (i.e., restored, augmented, and native) across the western United States.Individuals with resident behaviors were present in all management histories. Elevational migrations were the most common population-level migratory behavior. There were notable differences in the degree of individual variation within a population across the three management histories. Relative to native populations, restored and augmented populations had less variation among individuals with respect to elevation and geographic migration distances. Differences in migratory behavior were most pronounced for geographic distances, where the majority of native populations had a range of variation that was 2-4 times greater than restored or augmented populations. Synthesis and applications. Migrations within native populations include a variety of patterns that translocation efforts have not been able to fully recreate within restored and augmented populations. Theoretical and empirical research has highlighted the benefits of migratory diversity in promoting resilience and population stability. Limited migratory diversity may serve as an additional factor limiting demographic performance and range expansion. We suggest preserving native systems with intact migratory portfolios and a more nuanced approach to restoration and augmentation in which source populations are identified based on a suite of criteria that includes matching migratory patterns of source populations with local landscape attributes.

Native forage mediates influence of irrigated agriculture on migratory behaviour of elk.

Ungulates migrate to maximize nutritional intake when forage varies seasonally. Populations of ungulates often include both migratory and non-migratory individuals, but the mechanisms driving individual differences in migratory behaviour are not well-understood. We quantified associations between hypothesized drivers of partial migration and the likelihood of migration for individual ungulates that experienced a range of environmental conditions and anthropogenic influences. We evaluated the effects of forage variation, conspecific density, and human land uses on migratory behaviour of 308 adult female elk in 16 herds across western Montana. We found irrigated agriculture on an individual's winter range reduced migratory behaviour, but individuals were more likely to migrate away from irrigated agricultural areas if better forage was available elsewhere or if they experienced high conspecific density on their winter range. When the forage available during the summer growing season varied predictably between years, elk were more likely to migrate regardless of whether they had access to irrigated agriculture. Our study shows that predictable availability of beneficial native forage can encourage migration even for ungulates with irrigated agriculture on their winter range. Perturbations that can affect the forage available to ungulates include wildfires, timber harvest, livestock grazing and changing weather patterns. If these or other disturbances negatively affect forage on summer ranges of migrants, or if they cause forage to vary unpredictably across space and time, our results suggest migratory behaviour may decline as a result.

Simulation-based validation of spatial capture-recapture models: A case study using mountain lions.

Spatial capture-recapture (SCR) models have improved the ability to estimate densities of rare and elusive animals. However, SCR models have seldom been validated even as model formulations diversify and expand to incorporate new sampling methods and/or additional sources of information on model parameters. Information on the relationship between encounter probabilities, sources of additional information, and the reliability of density estimates, is rare but crucial to assessing reliability of SCR-based estimates. We used a simulation-based approach that incorporated prior empirical work to assess the accuracy and precision of density estimates from SCR models using spatially unstructured sampling. To assess the consequences of sparse data and potential sources of bias, we simulated data under six scenarios corresponding to three different levels of search effort and two levels of correlation between search effort and animal density. We then estimated density for each scenario using four models that included increasing amounts of information from harvested individuals and telemetry to evaluate the impact of additional sources of information. Model results were sensitive to the quantity of available information: density estimates based on low search effort were biased high and imprecise, whereas estimates based on high search effort were unbiased and precise. A correlation between search effort and animal density resulted in a positive bias in density estimates, though the bias decreased with increasingly informative datasets. Adding information from harvested individuals and telemetered individuals improved density estimates based on low and moderate effort but had negligible impact for datasets resulting from high effort. We demonstrated that density estimates from SCR models using spatially unstructured sampling are reliable when sufficient information is provided. Accurate density estimates can result if empirical-based simulations such as those presented here are used to develop study designs with appropriate amounts of effort and information sources.

Plasticity in elk migration timing is a response to changing environmental conditions.

Migration is an effective behavioral strategy for prolonging access to seasonal resources and may be a resilient strategy for ungulates experiencing changing climatic conditions. In the Greater Yellowstone Ecosystem (GYE), elk are the primary ungulate, with approximately 20,000 individuals migrating to exploit seasonal gradients in forage while also avoiding energetically costly snow conditions. How climate-induced changes in plant phenology and snow accumulation are influencing elk migration timing is unknown. We present the most complete record of elk migration across the GYE, spanning 9 herds and 414 individuals from 2001 to 2017, to evaluate the drivers of migration timing and test for temporal shifts. The timing of elk departure from winter range involved a trade-off between current and anticipated forage conditions, while snow melt governed summer range arrival date. Timing of elk departure from summer range and arrival on winter range were both influenced by snow accumulation and exposure to hunting. At the GYE scale, spring and fall migration timing changed through time, most notably with winter range arrival dates becoming almost 50 days later since 2001. Predicted herd-level changes in migration timing largely agreed with observed GYE-wide changes-except for predicted winter range arrival dates which did not reflect the magnitude of change detected in the elk telemetry data. Snow melt, snow accumulation, and spring green-up dates all changed through time, with different herds experiencing different rates and directions of change. We conclude that elk migration is plastic, is a direct response to environmental cues, and that these environmental cues are not changing in a consistent manner across the GYE. The impacts of changing elk migration timing on predator-prey dynamics, carnivore-livestock conflict, disease ecology, and harvest management across the GYE are likely to be significant and complex.

EFFECTS OF BRUCELLOSIS SEROLOGIC STATUS ON PHYSIOLOGY AND BEHAVIOR OF ROCKY MOUNTAIN ELK ( CERVUS CANADENSIS NELSONI) IN SOUTHWESTERN MONTANA, USA.

Brucellosis, caused by bacteria in the genus Brucella, is an infectious zoonosis affecting animals and humans worldwide. Free-ranging Rocky Mountain elk ( Cervus canadensis nelsoni) and bison ( Bison bison) in the Greater Yellowstone Ecosystem (areas of southwestern Montana, eastern Idaho, and northwestern Wyoming, US) are the self-sustaining reservoirs of bovine brucellosis ( Brucella abortus) and elk are considered the primary source of livestock infections. It has been hypothesized that Brucella-exposed elk might have different physiologic status (pregnancy rates and body condition) and migration behaviors than would healthy elk. Here we tested the effects of brucellosis serologic status on pregnancy rates and winter ingesta free body fat of 100 female elk in southwestern Montana. We also evaluated the effects of serologic status on two characteristics of spring migration behavior, migration types (migrant, mixed migrant, resident, disperser, nomad, and undetermined type) and timing (start and end dates and duration). The migration behaviors were quantified using a model-driven approach based on the relative net squared displacement. We detected a significant difference (P=0.003) in pregnancy rates between seropositive and seronegative elk, with about a 30% drop in seropositive individuals. However, we did not detect differences in body fat between seropositive and seronegative elk or differences in either migration type or timing of spring migration. These results confirmed that the major effect of brucellosis in free-ranging elk is associated with reproduction.

Respiratory pathogens and their association with population performance in Montana and Wyoming bighorn sheep populations.

Respiratory disease caused by Mycoplasma ovipneumoniae and Pasteurellaceae poses a formidable challenge for bighorn sheep (Ovis canadensis) conservation. All-age epizootics can cause 10-90% mortality and are typically followed by multiple years of enzootic disease in lambs that hinders post-epizootic recovery of populations. The relative frequencies at which these epizootics are caused by the introduction of novel pathogens or expression of historic pathogens that have become resident in the populations is unknown. Our primary objectives were to determine how commonly the pathogens associated with respiratory disease are hosted by bighorn sheep populations and assess demographic characteristics of populations with respect to the presence of different pathogens. We sampled 22 bighorn sheep populations across Montana and Wyoming, USA for Mycoplasma ovipneumoniae and Pasteurellaceae and used data from management agencies to characterize the disease history and demographics of these populations. We tested for associations between lamb:ewe ratios and the presence of different respiratory pathogen species. All study populations hosted Pasteurellaceae and 17 (77%) hosted Mycoplasma ovipneumoniae. Average lamb:ewe ratios for individual populations where both Mycoplasma ovipneumoniae and Pasteurellaceae were detected ranged from 0.14 to 0.40. However, average lamb:ewe ratios were higher in populations where Mycoplasma ovipneumoniae was not detected (0.37, 95% CI: 0.27-0.51) than in populations where it was detected (0.25, 95% CI: 0.21-0.30). These findings suggest that respiratory pathogens are commonly hosted by bighorn sheep populations and often reduce recruitment rates; however ecological factors may interact with the pathogens to determine population-level effects. Elucidation of such factors could provide insights for management approaches that alleviate the effects of respiratory pathogens in bighorn sheep. Nevertheless, minimizing the introduction of novel pathogens from domestic sheep and goats remains imperative to bighorn sheep conservation.

Assessing respiratory pathogen communities in bighorn sheep populations: Sampling realities, challenges, and improvements.

Respiratory disease has been a persistent problem for the recovery of bighorn sheep (Ovis canadensis), but has uncertain etiology. The disease has been attributed to several bacterial pathogens including Mycoplasma ovipneumoniae and Pasteurellaceae pathogens belonging to the Mannheimia, Bibersteinia, and Pasteurella genera. We estimated detection probability for these pathogens using protocols with diagnostic tests offered by a fee-for-service laboratory and not offered by a fee-for-service laboratory. We conducted 2861 diagnostic tests on swab samples collected from 476 bighorn sheep captured across Montana and Wyoming to gain inferences regarding detection probability, pathogen prevalence, and the power of different sampling methodologies to detect pathogens in bighorn sheep populations. Estimated detection probability using fee-for-service protocols was less than 0.50 for all Pasteurellaceae and 0.73 for Mycoplasma ovipneumoniae. Non-fee-for-service Pasteurellaceae protocols had higher detection probabilities, but no single protocol increased detection probability of all Pasteurellaceae pathogens to greater than 0.50. At least one protocol resulted in an estimated detection probability of 0.80 for each pathogen except Mannheimia haemolytica, for which the highest detection probability was 0.45. In general, the power to detect Pasteurellaceae pathogens at low prevalence in populations was low unless many animals were sampled or replicate samples were collected per animal. Imperfect detection also resulted in low precision when estimating prevalence for any pathogen. Low and variable detection probabilities for respiratory pathogens using live-sampling protocols may lead to inaccurate conclusions regarding pathogen community dynamics and causes of bighorn sheep respiratory disease epizootics. We recommend that agencies collect multiples samples per animal for Pasteurellaceae detection, and one sample for Mycoplasma ovipneumoniae detection from at least 30 individuals to reliably detect both Pasteurellaceae and Mycoplasma ovipneumoniae at the population-level. Availability of PCR diagnostic tests to wildlife management agencies would improve the ability to reliably detect Pasteurellaceae in bighorn sheep populations.

Assessing the importance of demographic parameters for population dynamics using Bayesian integrated population modeling.

To successfully respond to changing habitat, climate or harvest, managers need to identify the most effective strategies to reverse population trends of declining species and/or manage harvest of game species. A classic approach in conservation biology for the last two decades has been the use of matrix population models to determine the most important vital rates affecting population growth rate (λ), that is, sensitivity. Ecologists quickly realized the critical role of environmental variability in vital rates affecting λ by developing approaches such as life-stage simulation analysis (LSA) that account for both sensitivity and variability of a vital rate. These LSA methods used matrix-population modeling and Monte Carlo simulation methods, but faced challenges in integrating data from different sources, disentangling process and sampling variation, and in their flexibility. Here, we developed a Bayesian integrated population model (IPM) for two populations of a large herbivore, elk (Cervus canadensis) in Montana, USA. We then extended the IPM to evaluate sensitivity in a Bayesian framework. We integrated known-fate survival data from radio-marked adults and juveniles, fecundity data, and population counts in a hierarchical population model that explicitly accounted for process and sampling variance. Next, we tested the prevailing paradigm in large herbivore population ecology that juvenile survival of neonates <90 d old drives λ using our Bayesian LSA approach. In contrast to the prevailing paradigm in large herbivore ecology, we found that adult female survival explained more of the variation in λ than elk calf survival, and that summer and winter elk calf survival periods were nearly equivalent in importance for λ. Our Bayesian IPM improved precision of our vital rate estimates and highlighted discrepancies between count and vital rate data that could refine population monitoring, demonstrating that combining sensitivity analysis with population modeling in a Bayesian framework can provide multiple advantages. Our Bayesian LSA framework will provide a useful approach to addressing conservation challenges across a variety of species and data types.

Linking landscape-scale differences in forage to ungulate nutritional ecology.

Understanding how habitat and nutritional condition affect ungulate populations is necessary for informing management, particularly in areas experiencing carnivore recovery and declining ungulate population trends. Variations in forage species availability, plant phenological stage, and the abundance of forage make it challenging to understand landscape-level effects of nutrition on ungulates. We developed an integrated spatial modeling approach to estimate landscape-level elk (Cervus elaphus) nutritional resources in two adjacent study areas that differed in coarse measures of habitat quality and related the consequences of differences in nutritional resources to elk body condition and pregnancy rates. We found no support for differences in dry matter digestibility between plant samples or in phenological stage based on ground sampling plots in the two study areas. Our index of nutritional resources, measured as digestible forage biomass, varied among land cover types and between study areas. We found that altered plant composition following fires was the biggest driver of differences in nutritional resources, suggesting that maintaining a mosaic of fire history and distribution will likely benefit ungulate populations. Study area, lactation status, and year affected fall body fat of adult female elk. Elk in the study area exposed to lower summer range nutritional resources had lower nutritional condition entering winter. These differences in nutritional condition resulted in differences in pregnancy rate, with average pregnancy rates of 89% for elk exposed to higher nutritional resources and 72% for elk exposed to lower nutritional resources. Summer range nutritional resources have the potential to limit elk pregnancy rate and calf production, and these nutritional limitations may predispose elk to be more sensitive to the effects of harvest or predation. Wildlife managers should identify ungulate populations that are nutritionally limited and recognize that these populations may be more impacted by recovering carnivores or harvest than populations inhabiting more productive summer habitats.

Elk Resource Selection and Implications for Anthrax Management in Montana.

Anthrax, caused by the spore-forming bacterium Bacillus anthracis, is a zoonotic disease that affects humans and animals throughout the world. In North America, anthrax outbreaks occur in livestock and wildlife species. Vaccine administration in wildlife is untenable; the most effective form of management is surveillance and decontamination of carcasses. Successful management is critical because untreated carcasses can create infectious zones increasing risk for other susceptible hosts. We studied the bacterium in a re-emerging anthrax zone in southwest Montana. In 2008, a large anthraxepizootic primarily affected a domestic bison (Bison bison) herd and the male segment of a free-ranging elk (Cervus elaphus) herd in southwestern Montana. Following the outbreak, we initiated a telemetry study on elk to evaluate resource selection during the anthrax season to assist with anthrax management. We used a mixed effects generalized linear model (GLM) to estimate resource selection by male elk, and we mapped habitat preferences across the landscape. We overlaid preferred habitats on ecological niche model-based estimates of B. anthracis presence. We observed significant overlap between areas with a high predicted probability of male elk selection and B. anthracis potential. These potentially risky areas of elk and B. anthracis overlap were broadly spread over public and private lands. Future outbreaks in the region are probable, and this analysis identified the spatial extent of the risk area in the region, which can be used to prioritize anthrax surveillance.