THE RELATIONSHIP BETWEEN HARVEST MANAGEMENT AND CHRONIC WASTING DISEASE PREVALENCE TRENDS IN WESTERN MULE DEER (ODOCOILEUS HEMIONUS) HERDS

Predicting chronic wasting disease in white-tailed deer at the county scale using machine learning

Continued spread of chronic wasting disease (CWD) through wild cervid herds negatively impacts populations, erodes wildlife conservation, drains resource dollars, and challenges wildlife management agencies. Risk factors for CWD have been investigated at state scales, but a regional model to predict locations of new infections can guide increasingly efficient surveillance efforts. We predicted CWD incidence by county using CWD surveillance data depicting white-tailed deer (Odocoileus virginianus) in 16 eastern and midwestern US states. We predicted the binary outcome of CWD-status using four machine learning models, utilized five-fold cross-validation and grid search to pinpoint the best model, then compared model predictions against the subsequent year of surveillance data. Cross validation revealed that the Light Boosting Gradient model was the most reliable predictor given the regional data. The predictive model could be helpful for surveillance planning. Predictions of false positives emphasize areas that warrant targeted CWD surveillance because of similar conditions with counties known to harbor CWD. However, disagreements in positives and negatives between the CWD Prediction Web App predictions and the on-the-ground surveillance data one year later underscore the need for state wildlife agency professionals to use a layered modeling approach to ensure robust surveillance planning. The CWD Prediction Web App is at https://cwd-predict.streamlit.app/ .

Where we stand on chronic wasting disease: A systematic literature review of its prevalence patterns, impacts, and management interventions

With high fatality and no cure, chronic wasting disease (CWD) has infected cervids in multiple regions, including the United States, Canada, Europe, and South Korea. Despite the rapid growth of literature on CWD, the full scope of its ecological, social, and economic impacts and the most effective and socially acceptable management strategies to mitigate the disease is unclear. Of 3008 initially identified published peer-reviewed papers, 134 were included in a final systematic literature review to synthesize the current knowledge on CWD transmission patterns, impacts, and the effectiveness of management interventions. The number of publications on CWD has increased steadily since 2000 with an average of six papers per year. Most papers were related to CWD prevalence (39 %), human behavior (33 %), CWD impacts (31 %), and management interventions (16 %). Environmental factors such as soil, water, and plants were identified as the most common transmission medium, with a higher prevalence rate among adult male cervids than females. Hunters showed a higher risk perception and were more likely to change hunting behavior due to CWD detection than non-hunters. Ecological impacts included the decreased survival rate accompanied by lower population growth, eventually leading to the decline of cervid populations. Culling was found to be an effective and widely implemented management strategy across countries, although it often was associated with public resistance. Despite potentially high negative economic impacts anticipated due to CWD, studies on this subject were limited. Sustained surveillance, ongoing research, and engagement of affected stakeholders will be essential for future disease control and management.

Mule deer fawn recruitment dynamics in an energy disturbed landscape

Wildlife population dynamics are modulated by abiotic and biotic factors, typically climate, resource availability, density-dependent effects, and predator-prey interactions. Understanding whether and how human-caused disturbances shape these ecological processes is helpful for the conservation and management of wildlife and their habitats within increasingly human-dominated landscapes. However, many jurisdictions lack either long-term longitudinal data on wildlife populations or measures of the interplay between human-mediated disturbance, climate, and predator density. Here, we use a 50-year time series (1962-2012) on mule deer (Odocoileus hemionus) demographics, seasonal weather, predator density, and oil and gas development patterns from the North Dakota Badlands, USA, to investigate long-term effects of landscape-level disturbance on mule deer fawn fall recruitment, which has declined precipitously over the last number of decades. Mule deer fawn fall recruitment in this study represents the number of fawns per female (fawn:female ratio) that survive through the summer to October. We used this fawn recruitment index to evaluate the composite effects of interannual extreme weather conditions, energy development, and predator density. We found that density-dependent effects and harsh seasonal weather were the main drivers of fawn fall recruitment in the North Dakota Badlands. These effects were further shaped by the interaction between harsh seasonal weather and predator density (i.e., lower fawn fall recruitment when harsh weather was combined with higher predator density). Additionally, we found that fawn fall recruitment was modulated by interactions between seasonal weather and energy development (i.e., lower fawn fall recruitment when harsh weather was combined with higher density of active oil and gas wells). Interestingly, we found that the combined effect of predator density and energy development was not interactive but rather additive. Our analysis demonstrates how energy development may modulate fluctuations in mule deer fawn fall recruitment concurrent with biotic (density-dependency, habitat, predation, woody vegetation encroachment) and abiotic (harsh seasonal weather) drivers. Density-dependent patterns emerge, presumably due to limited quality habitat, being the primary factor influencing fall fawn recruitment in mule deer. Secondarily, stochastic weather events periodically cause dramatic declines in recruitment. And finally, the additive effects of human disturbance and predation can induce fluctuations in fawn fall recruitment. Here we make the case for using long-term datasets for setting long-term wildlife management goals that decision makers and the public can understand and support.

A call to action: Standardizing white-tailed deer harvest data in the Midwestern United States and implications for quantitative analysis and disease management

Recreational hunting has been the dominant game management and conservation mechanism in the United States for the past century. However, there are numerous modern-day issues that reduce the viability and efficacy of hunting-based management, such as fewer hunters, overabundant wildlife populations, limited access, and emerging infectious diseases in wildlife. Quantifying the drivers of recreational harvest by hunters could inform potential management actions to address these issues, but this is seldom comprehensively accomplished because data collection practices limit some analytical applications (e.g., differing spatial scales of harvest regulations and harvest data). Additionally, managing large-scale issues, such as infectious diseases, requires collaborations across management agencies, which is challenging or impossible if data are not standardized. Here we discuss modern issues with the prevailing wildlife management framework in the United States from an analytical point of view with a case study of white-tailed deer (Odocoileus virginianus) in the Midwest. We have four aims: (1) describe the interrelated processes that comprise hunting and suggest improvements to current data collections systems, (2) summarize data collection systems employed by state wildlife management agencies in the Midwestern United States and discuss potential for large-scale data standardization, (3) assess how aims 1 and 2 influence managing infectious diseases in hunted wildlife, and (4) suggest actionable steps to help guide data collection standards and management practices. To achieve these goals, Wisconsin Department of Natural Resources disseminated a questionnaire to state wildlife agencies (Illinois, Indiana, Iowa, Kentucky, Michigan, Minnesota, Missouri, Ohio, Wisconsin), and we report and compare their harvest management structures, data collection practices, and responses to chronic wasting disease. We hope our “call to action” encourages re-evaluation, coordination, and improvement of harvest and management data collection practices with the goal of improving the analytical potential of these data. A deeper understanding of the strengths and deficiencies of our current management systems in relation to harvest and management data collection methods could benefit the future development of comprehensive and collaborative management and research initiatives (e.g., adaptive management) for wildlife and their diseases.

Spatio-temporal changes in chronic wasting disease risk in wild deer during 14 years of surveillance in Alberta, Canada

Disease risk modeling is a key first step to understand the spatio-temporal dynamics of wildlife disease and to direct cost-effective surveillance and management. In Alberta, active surveillance for chronic wasting disease (CWD) in wild cervids began in 1998 with the first case detected in free-ranging cervids in 2005. Following the detection, a herd reduction program was implemented during 2005-2008 and in 2006 the ongoing hunter-based CWD Surveillance Program became mandatory in high-risk Wildlife Management Units (WMU). We used data collected during the CWD surveillance program to 1) document growth in sex-specific CWD prevalence (proportion of deer in sample that is CWD-positive) in hunter-harvest deer in 6 WMUs consistently monitored from 2006 to 2018, 2) document landscape features associated with where CWD-positive compared to CWD-negative deer were removed during hunter harvest and herd reduction in an early (2005-2012) and in a late period (2013-2017), and 3) to map the spatial risk of harvesting a deer infected with CWD in the prairie parklands of Alberta. In the 6 continuously monitored WMUs, risk of a harvested deer being CWD positive increased from 2006 to 2018 with CWD prevalence remaining highest in male mule deer whereas overall growth rate in CWD prevalence was greater in female mule deer, but similar to male white-tailed deer. We found no evidence that the 3-year herd reduction program conducted immediately after CWD was first detected affected the rate at which CWD grew over the course of the invasion. Risk of deer being CWD-positive was the highest in animals taken near small stream drainages and on soils with low organic carbon content in the early period, whereas risk became highest in areas of agriculture especially when far from large river drainages where deer often concentrate in isolated woody patches. The change in the influence of proximity to known CWD-positive cases suggested the disease was initially patchy but became more spatially homogeneous over time. Our results indicate that a targeted-removal program will remove more CWD positive animals compared to hunter harvest. However, the discontinuation of targeted removals during our research program, restricted our ability to assess its long term impact on CWD prevalence.