Population Trends of Bighorn Sheep and Mountain Goats in the Greater Yellowstone Area

Bighorn sheep (Ovis canadensis) and mountain goats (Oreamnos americanus) are important components of the large mammal community in the Greater Yellowstone Area (GYA) and are of considerable public interest. However, foundational ecological research concerning these species is limited. We analyzed historic bighorn sheep and mountain goat population counts collected by management biologists using ln-linear regression to estimate herd growth rates (?). The analyzed dataset consisted of 538 bighorn sheep counts since 1971 and 120 mountain goat counts since 1966. Most mountain goat count units experienced a positive growth rate and increased their distributions over recent decades. Bighorn sheep growth rates were more variable among the 26 recognized herd units in the GYA. We used the historic count data to evaluate the hypothesis that sympatry of non-native mountain goats with bighorn sheep adversely affected bighorn sheep populations. This was accomplished by comparing the growth rates of sympatric herds with that of allopatric herds. There was no evidence that sympatric herd growth rates were significantly lower than allopatric herd growth rates. We caution, however, that many counts in consecutive years suggested larger changes in abundance than what would be reasonable to expect from biological processes. We suspect that variability in counts likely reflects varying detection probability and the overall difficulty of counting mountain ungulates. Therefore, conclusions derived from these data should be further evaluated with more detailed demographic studies in the future

Telemetry Studies of Mountain Ungulates in the Greater Yellowstone Area: A Progress Report

We report on the progress that has been made on initiating long-term telemetry studies of mountain goats (Oreamnos americanus) and bighorn sheep (Ovis Canadensis) in the GYA to better understand spatial ecology, demography, potential competition, and disease ecology. Six study areas representing a variety of ecological settings have been established throughout the GYA that include areas where bighorn sheep and mountain goats are sympatric as well as where each species exists in the absence of the other. We are employing a novel dual radio collar strategy and have successfully evaluated the use of drop net systems to capture groups of bighorn attracted to bait as an economical alternative to standard helicopter-based single animal capture techniques. Chemical immobilization of bighorn using BAM as an alternative to carfentanil was also tested and evaluated. A break-down Clover trap was designed for ease of transportation via horse for backcountry trapping and summer salt baiting for bighorn sheep and mountain goats was evaluated. We have initiated the first systematic disease sampling of mountain goats in the GYA using the standard protocols employed for bighorn sheep health assessments to evaluate the potential for mountain goats to influence the disease ecology of bighorn sheep in areas where they are sympatric. The research goals, strategies, and methodologies developed, tested, and employed on the collaborative GYA mountain ungulate research program are similar to those proposed for a long-term bighorn sheep research program in Montana

An Initial Assessment of the Potential of Genomic Analysis to Help Inform Bighorn Sheep Management

Genetic research may be a useful approach for understanding factors that could impact productivity and restoration of bighorn sheep (Ovis canadensis) herds.  For example, genetic consequences of inbreeding in small populations can impact recruitment and local adaptations can influence translocation success.  This modest pilot study quantified genetic attributes of bighorn sheep populations with a range of different herd histories in Montana and Wyoming to investigate genetic similarity and differences, genetic heterogeneity and genetic distance.  Employing an Ovine array containing about 700,000 single nucleotide polymorphisms (SNPs) with approximately 24,000 markers that are informative for Rocky Mountain bighorn sheep, we used whole genome genotyping to analyze genetic material.  This technique represents a significant advancement in genetic analysis of bighorn sheep, as most previous studies have used microsatellites and less than 200 genetic markers.  We analyzed approximately fifteen individuals from each of four different populations that we predicted would differ in genetic characteristics, due to population dissimilarities that potentially impacted their genetics, including origin (native/reintroduced), population size, bottleneck history, degree of connectivity, and augmentation history.  We selected four populations that provided a spectrum of these herd attributes, including the Tendoys, Stillwater and Glacier National Park in Montana and the northeastern Greater Yellowstone Area in Wyoming.  We present the results of this effort and examine expected and observed heterogeneity and genetic distance estimates to evaluate the potential for links between genetics and herd demography.  We discuss the utility of genetic analyses in improving knowledge of bighorn sheep populations and potential implications for bighorn sheep management

Imperfect Tests, Pervasive Pathogens, and Variable Demographic Performance: Thoughts on Managing Bighorn Sheep Respiratory Disease

Respiratory disease (pneumonia) has been a persistent challenge for bighorn sheep (Ovis canadensis) conservation and its cause has been attributed to numerous bacteria including Mycoplasma ovipneumoniae and several Pasteurellaceae family species. This study sought to investigate efficacy of diagnostic protocols in detecting Pasteurellaceae and Mycoplasma ovipneumoniae, generate sampling recommendations for different protocols, assess the distribution of these disease agents among 17 bighorn sheep populations in Montana and Wyoming, and evaluate what associations existed between detection of these agents and demographic performance of bighorn sheep populations. Analysis of replicate samples from individual bighorn sheep revealed that detection probability for regularlyused diagnostic protocols was generally low (<50%) for Pasteurellaceae and was high (>70%) for Mycoplasma ovipneumoniae, suggesting that routine pathogen sampling likely mischaracterizes respiratory pathogen communities. Power analyses found that most pathogen species could be detected with 80% confidence at the population-level by conducting regularly-used protocols multiple times per animal. Each pathogen species was detected in over half of the study populations, but after accounting for detection probability there was low confidence in negative test results for populations where Pasteurellaceae species were not detected. Seventy-six percent of study populations hosted both Mycoplasma ovipneumoniae and Pasteurellaceae pathogens, yet a number of these populations were estimated to have positive population growth rates and recruitment rates greater than 30%. Overall, the results of this work suggest that bighorn sheep respiratory disease may be mitigated by manipulating population characteristics and respiratory disease epizootics could be caused by pathogens already resident in bighorn sheep population

Development and application of the Demands for Population Health Interventions (Depth) framework for categorising the agentic demands of population health interventions

Background: The ‘agentic demand’ of population health interventions (PHIs) refers to the capacity, resources and freedom to act that interventions demand of their recipients to benefit, which have a socio-economical pattern. Highly agentic interventions, e.g. information campaigns, rely on recipients noticing and responding to the intervention and thus might affect intervention effectiveness and equity. The absence of an adequate framework to classify agentic demands limits the fields’ ability to systematically explore these associations. Methods: We systematically developed the Demands for Population Health Interventions (Depth) framework using an iterative approach: (1) Developing the Depth framework by systematically identifying examples of PHIs aiming to promote healthier diets and physical activity, coding of intervention actors and actions and synthesising the data to develop the framework; (2) Testing the Depth framework in online workshops with academic and policy experts and a quantitative reliability assessment. We applied the final framework in a proof-of-concept review, extracting studies from three existing equity focused systematic reviews on framework category, overall effectiveness and differential socioeconomic effects and visualised the findings in Harvest Plots. Results: The Depth framework identifies three constructs influencing agentic demand: exposure - initial contact with intervention (2 levels), mechanism of action - how the intervention enables or discourages behaviour (5 levels), and engagement - recipient response (2 levels). When combined, these constructs form a matrix of twenty possible classifications. In the proof-of-concept review, we classified all components of 31 interventions according to the Depth framework. Intervention components were concentrated in a small number of Depth classifications; Depth classification appeared to be related to intervention equity but not effectiveness. Conclusions: This framework holds potential for future research, policy and practice, facilitating the design, selection and evaluation of interventions and evidence synthesis

Development and application of the DePtH framework for categorising the agentic demands of population health interventions [Pre-print]

The ‘agentic demand’ of population health interventions may influence intervention effectiveness and equity, yet the absence of an adequate framework to classify agentic demands limits the fields’ advancement. We systematically developed the DEmands for PopulaTion Health Interventions (DePtH) framework identifying three constructs influencing agentic demand - exposure (initial contact with intervention), mechanism of action (how the intervention enables or discourages behaviour), and engagement (recipient response), combined into twenty classifications. We conducted expert qualitative feedback and reliability testing, revised the framework and applied it in a proof-of-concept review, combining it with data on overall effectiveness and equity of dietary and physical activity interventions. Intervention components were concentrated in a small number of classifications; DePtH classification appeared to be related to intervention equity but not effectiveness. This framework holds potential for future research, policy and practice, facilitating the design, selection, evaluation and synthesis of evidence

Predicting Bison Migration out of Yellowstone National Park Using Bayesian Models

Long distance migrations by ungulate species often surpass the boundaries of preservation areas where conflicts with various publics lead to management actions that can threaten populations. We chose the partially migratory bison (Bison bison) population in Yellowstone National Park as an example of integrating science into management policies to better conserve migratory ungulates. Approximately 60% of these bison have been exposed to bovine brucellosis and thousands of migrants exiting the park boundary have been culled during the past two decades to reduce the risk of disease transmission to cattle. Data were assimilated using models representing competing hypotheses of bison migration during 1990–2009 in a hierarchal Bayesian framework. Migration differed at the scale of herds, but a single unifying logistic model was useful for predicting migrations by both herds. Migration beyond the northern park boundary was affected by herd size, accumulated snow water equivalent, and aboveground dried biomass. Migration beyond the western park boundary was less influenced by these predictors and process model performance suggested an important control on recent migrations was excluded. Simulations of migrations over the next decade suggest that allowing increased numbers of bison beyond park boundaries during severe climate conditions may be the only means of avoiding episodic, large-scale reductions to the Yellowstone bison population in the foreseeable future. This research is an example of how long distance migration dynamics can be incorporated into improved management policies

An Ontological Approach to Inform HMI Designs for Minimizing Driver Distractions with ADAS

ADAS (Advanced Driver Assistance Systems) are in-vehicle systems designed to enhance driving safety and efficiency as well as comfort for drivers in the driving process. Recent studies have noticed that when Human Machine Interface (HMI) is not designed properly, an ADAS can cause distraction which would affect its usage and even lead to safety issues. Current understanding of these issues is limited to the context-dependent nature of such systems. This paper reports the development of a holistic conceptualisation of how drivers interact with ADAS and how such interaction could lead to potential distraction. This is done taking an ontological approach to contextualise the potential distraction, driving tasks and user interactions centred on the use of ADAS. Example scenarios are also given to demonstrate how the developed ontology can be used to deduce rules for identifying distraction from ADAS and informing future designs