Mule Deer Research Articles

Variation in white‐tailed and mule deer dental metrics is associated with precipitation gradients in the Americas

AbstractInvestigating the relationship between the physical environment and organismal adaptation is crucial to understanding the selective pressures that drive mammalian evolution. Of the varied approaches to exploring this relationship, macroscopic tooth wear analyses have become widely used due to their economic and simple methodologies. However, more work is needed to understand how assessments of wear patterns operate within finer levels of dietary and environmental contexts. It is specifically unclear if and how tooth wear differs inter‐ and intraspecifically between geographically widespread, large‐bodied mammalian populations. This project characterizes molar hypsodonty indices and mesowear scores of white‐tailed deer (Odocoileus virginianus) and mule deer (Odocoileus hemionus) populations across North and Central America, investigating if and how molar wear and morphology vary over the deer's large and ecologically variable geographic distribution. While mesowear scores generally do not strongly track environmental signals within and between Odocoileus species, hypsodonty indices reveal a strong correlation between crown height and aridity, which likely represents an adaptive response to abrasive diets in areas with low precipitation.

Linking summer nutrition to behavior and performance of black‐tailed deer

AbstractMany large‐herbivore populations are regulated at least in part by bottom‐up forces, and thus relationships between herbivores and their habitat are of fundamental importance to wildlife managers. Variation in nutritional resources—and how herbivores respond to that variation—influences rates of nutrient intake, which directly affect nutritional condition, pregnancy rates, timing of parturition, offspring birth mass, and survival. Accordingly, nutrition‐focused research holds great potential for uncovering the mechanisms that govern population performance of large herbivores and for assessing the nature and magnitude of bottom‐up limitations. We quantified relationships between the foodscape (i.e., spatiotemporal variation in forage quality and abundance) in southwestern Oregon, USA, and black‐tailed deer (Odocoileus hemionus columbianus) behavior and performance, with a focus on the influence of maternal nutrition on fawn survival. We hypothesized that black‐tailed deer performance (i.e., fawn birth mass and survival) is influenced by the availability of high‐quality forage during spring and summer and patterns of foodscape use exhibited by individual deer. From 2016–2023 we monitored movement and survival of adult female black‐tailed deer and their offspring. We also conducted intensive vegetation sampling and used generalized additive modeling to map the foodscape available to deer in spring and summer. Suitable forage biomass (i.e., maximum biomass of forage that together exceeded quality thresholds for supporting one fawn) was highly variable across space and time, and our top foodscape model explained 70% of the variation in suitable biomass (adjusted R2 = 0.70). We observed a strong, positive relationship between use of the foodscape by maternal females prior to parturition and fawn birth mass. Although maternal foodscape use after parturition did not influence the probability of fawn survival, survival increased with increasing birth mass. These results suggest that the effects of nutrition on fawn survival in our study system are indirectly mediated by maternal behavior (i.e., use of the foodscape) and the corresponding effects on birth mass of fawns. Our study adds to a growing body of literature supporting a fundamental link between foodscape use and population performance of large herbivores. Wildlife managers can use the dynamic models we developed to assess habitat quality and to make quantitative predictions about how different management actions (e.g., forest thinning) are likely to influence habitat quality and performance of black‐tailed deer.

Climate Change and Herbivores: Forty Years in a Bunchgrass Prairie.

Wild herbivore responses to anthropogenic climate change are often projected to be habitat and geographic range shifts as warmer conditions reduce the quantity and nutritional quality of forage plants, which makes species presence/absence a focus. Since 1978, herbivore abundances at the National Bison Range, MT, USA, were measured for grasshoppers (catch-effort), microtine rodents (runway density), and ungulates (drives and round-ups), along with climate and vegetation quantity (biomass) and quality (nitrogen content and chemical solubility related to digestibility). Counter to expectation with warming and drying, forage biomass increased as grass biomass increased more than dicot biomass decreased, and forage quality (solubility) increased. Consequently, herbivores that consume a grass diet (>25% grass: certain grasshoppers, microtines, bighorn sheep, elk, bison) increased in abundance, while herbivores consuming less grass declined (certain grasshoppers, pronghorn, whitetail, and mule deer). The result is an 18% increase in herbivore abundance and herbivory, counter to climate change expectations. Historically, grasshoppers consumed 46% more vegetation than mammals; now, they consume only 14% more, as grasshoppers did not increase as expected with climate change. Therefore, herbivores respond rapidly to climate-induced vegetation changes, and this is not a simple loss/addition of species, but changing trophic dynamics, which requires more knowledge of ecosystem dynamics.

Estimation of Contact Time Among Animals from Telemetry Data

Continuous processes in most applications are measured discretely with error. This complicates the task of detecting intersections and the number of intersections between two continuous processes (i.e., when the processes have the same value). Intersections of continuous processes are scientifically important, but challenging to estimate from data. For example, in the field of animal ecology, intersections of the paths of moving animals tracked with satellite technologies can be used to understand disease transmission. We illustrate how to quantify contact between animals using telemetry data (i.e., the recorded locations of an animal over time). We introduce our method to quantify contact time with accessible concepts from introductory stochastic process literature, such as Brownian motion. Then, we provide two data examples using white-tailed deer (Odocoileus virginianus) and mule deer (Odocoileus hemionus) telemetry data in a region with high prevalence of chronic wasting disease. Our work provides a needed connection between existing model-based literature for animal movement and rule-based literature for animal interaction. Further, our work illustrates a unique statistical problem receiving minimal attention with broad applicability in human and livestock tracking.

Estimating ungulate migration corridors from sparse movement data

AbstractMany ungulates migrate between distinct summer and winter ranges, and identifying, mapping, and conserving these migration corridors have become a focus of local, regional, and global conservation efforts. Brownian bridge movement models (BBMMs) are commonly used to empirically identify these seasonal migration corridors; however, they require location data sampled at relatively frequent intervals to obtain a robust estimate of an animal's movement path. Fitting BBMMs to sparse location data violates the assumption of conditional random movement between successive locations, overestimating the area (and width) of a migration corridor when creating individual and population‐level occurrence distributions and precluding the use of low‐frequency, or sparse, data in mapping migration corridors. In an effort to expand the utility of BBMMs to include sparse GPS data, we propose an alternative approach to model migration corridors from sparse GPS data. We demonstrate this method using GPS data collected every 2 h from four mule deer (Odocoileus hemionus) and four elk (Cervus canadensis) herds within Wyoming and Idaho. First, we used BBMMs to estimate a baseline corridor for the 2‐h data. We then subsampled the 2‐h data to one location every 12 h (a proxy for sparse data) and fitted BBMMs to the 12‐h data using a fixed motion variance (FMV) value, instead of estimating the Brownian motion variance empirically. A range of FMV values was tested to identify the value that best approximated the baseline migration corridor. FMV values within a species‐specific range (mule deer: 400–1200 m2; elk: 600–1600 m2) successfully delineated migration corridors similar to the 2‐h baseline corridors; overall, lower values delineated narrower corridors and higher values delineated wider corridors. Optimal FMV values of 800 m2 (mule deer) and 1000 m2 (elk) decreased the inflation of the 12‐h corridors relative to the 2‐h corridors from traditional BBMMs. This FMV approach thus enables using sparse movement data to approximate realistic migration corridor dimensions, providing an important alternative when movement data are collected infrequently. This approach greatly expands the number of datasets that can be used for migration corridor mapping—a useful tool for management and conservation across the globe.

Climate change and deer in boreal and temperate regions: From physiology to population dynamics and species distributions.

Climate change causes far-reaching disruption in nature, where tolerance thresholds already have been exceeded for some plants and animals. In the short term, deer may respond to climate through individual physiological and behavioral responses. Over time, individual responses can aggregate to the population level and ultimately lead to evolutionary adaptations. We systematically reviewed the literature (published 2000-2022) to summarize the effect of temperature, rainfall, snow, combined measures (e.g., the North Atlantic Oscillation), and extreme events, on deer species inhabiting boreal and temperate forests in terms of their physiology, spatial use, and population dynamics. We targeted deer species that inhabit relevant biomes in North America, Europe, and Asia: moose, roe deer, wapiti, red deer, sika deer, fallow deer, white-tailed deer, mule deer, caribou, and reindeer. Our review (218 papers) shows that many deer populations will likely benefit in part from warmer winters, but hotter and drier summers may exceed their physiological tolerances. We found support for deer expressing both morphological, physiological, and behavioral plasticity in response to climate variability. For example, some deer species can limit the effects of harsh weather conditions by modifying habitat use and daily activity patterns, while the physiological responses of female deer can lead to long-lasting effects on population dynamics. We identified 20 patterns, among which some illustrate antagonistic pathways, suggesting that detrimental effects will cancel out some of the benefits of climate change. Our findings highlight the influence of local variables (e.g., population density and predation) on how deer will respond to climatic conditions. We identified several knowledge gaps, such as studies regarding the potential impact on these animals of extreme weather events, snow type, and wetter autumns. The patterns we have identified in this literature review should help managers understand how populations of deer may be affected by regionally projected futures regarding temperature, rainfall, and snow.

Unraveling the impact of dog‐friendly spaces on urban–wildland pumas and other wildlife

As the most widespread large carnivore on the planet, domestic dogs Canis lupus familiaris can pose a major threat to wildlife, even within protected areas (PAs). Growing human presence in PAs, coupled with increasing pet dog ownership underscores the urgency to understand the influence of dogs on wildlife activity and health. This knowledge can mitigate the adverse repercussions of recreation, optimizing PA management. Drawing on five years (2017–2021) of data from 101 camera traps in the San Francisco Bay Area, California, United States, we measured the spatiotemporal responses of puma Puma concolor, bobcat Lynx rufus, coyote Canis latrans, and mule deer Odocoileus hemionus towards domestic dogs. Additionally, using six years (2017–2022) of community science data, we explored the impacts of PA dog policies on puma sightings outside park boundaries. Puma responses provide insights into broader ecological impacts, while analyses of bobcat, coyote, and mule deer offer a comprehensive understanding of species responses to dog‐friendly spaces. Because dogs can be perceived as predators or competitors by wildlife, we anticipated shifts in spatial and temporal activity patterns in response to dogs. Wildlife responses included avoidance (bobcat, puma) or spatial overlap (mule deer) for areas with more dogs, and no effect (coyote). Mule deer may benefit from a “human shield” provided by people with dogs, while pumas and bobcats appeared more sensitive, and coyotes more adaptable. Dog policies influenced puma and mule deer temporal activity, with increased nocturnal activity in dog‐friendly PAs. Bobcat temporal activity was less variable in dog‐friendly PAs and coyote activity was similar between treatments. Outside PAs, puma sightings increased with human disturbance. Our study underscores the trade‐offs between recreation and wildlife conservation, emphasizing the need to quantify the ecological impacts of dogs. This understanding is vital for informing conservation strategies and promoting coexistence between dogs, wildlife, and protected environments.

Mule deer selection of fuel reductions is restricted by site fidelity and structured by circadian and seasonal patterns

Forests in the western US have undergone a profound transformation over the last 100 years due to chronic fire suppression and a cycle of extensive timber harvest followed by little silvicultural activity. Forested landscapes in this region are now dominated by intermediate age, denser stands of coniferous trees that reduce transmission of light and precipitation to the understory, with potential consequences for ungulate nutrition. We used a 20-year dataset of mule deer locations (560 animal-years of data) to evaluate long-term patterns of selection of forest stands that had been thinned and burned compared to untreated reference stands. We evaluated within home-range (3rd order) selection at 3 temporal scales (hourly, daily, annually) and landscape-scale (2nd order) use annually. We found that annual selection of treated stands during summer generally increased with two peaks, once immediately after treatments were applied and again 15 years later. Mule deer also showed strong seasonal and temporal patterns in selection of treated forest stands. Deer selected treated stands at night in July and August immediately after treatments. After 4–6 years, mule deer selected treated stands both during the day and at night in May, July, and August, but with stronger selection at night. We hypothesize that preference for treated forest stands were driven by differences in forage quantity and quality among forest stands. Vegetation surveys during years of peak selection showed that treated stands had significantly higher biomass and digestible energy of neutrally selected forage and lower biomass of avoided forage species, although there was no difference in biomass of preferred forage species. A subset of female mule deer with multiple years of data did not shift home ranges to overlap with treated forest stands over time (2nd order use) but did show increasing selection over time for treated forest stands within their home ranges (3rd order). Our results show that thinning and burning of forest stands can benefit mule deer both immediately and for up to 15 years after treatment and that researchers should evaluate temporal and seasonal patterns in studies of habitat selection. Given the diverse habitat needs of mule deer, treatments would be most beneficial if they were scattered across large landscapes and staggered in time to provide a diversity of forage and cover types.

SARS-CoV-2 Seropositivity in Urban Population of Wild Fallow Deer, Dublin, Ireland, 2020-2022.

SARS-CoV-2 can infect wildlife, and SARS-CoV-2 variants of concern might expand into novel animal reservoirs, potentially by reverse zoonosis. White-tailed deer and mule deer of North America are the only deer species in which SARS-CoV-2 has been documented, raising the question of whether other reservoir species exist. We report cases of SARS-CoV-2 seropositivity in a fallow deer population located in Dublin, Ireland. Sampled deer were seronegative in 2020 when the Alpha variant was circulating in humans, 1 deer was seropositive for the Delta variant in 2021, and 12/21 (57%) sampled deer were seropositive for the Omicron variant in 2022, suggesting host tropism expansion as new variants emerged in humans. Omicron BA.1 was capable of infecting fallow deer lung type-2 pneumocytes and type-1-like pneumocytes or endothelial cells ex vivo. Ongoing surveillance to identify novel SARS-CoV-2 reservoirs is needed to prevent public health risks during human-animal interactions in periurban settings.

Movement behavior in a dominant ungulate underlies successful adjustment to a rapidly changing landscape following megafire

BackgroundMovement plays a key role in allowing animal species to adapt to sudden environmental shifts. Anthropogenic climate and land use change have accelerated the frequency of some of these extreme disturbances, including megafire. These megafires dramatically alter ecosystems and challenge the capacity of several species to adjust to a rapidly changing landscape. Ungulates and their movement behaviors play a central role in the ecosystem functions of fire-prone ecosystems around the world. Previous work has shown behavioral plasticity is an important mechanism underlying whether large ungulates are able to adjust to recent changes in their environments effectively. Ungulates may respond to the immediate effects of megafire by adjusting their movement and behavior, but how these responses persist or change over time following disturbance is poorly understood.MethodsWe examined how an ecologically dominant ungulate with strong site fidelity, Columbian black-tailed deer (Odocoileus hemionus columbianus), adjusted its movement and behavior in response to an altered landscape following a megafire. To do so, we collected GPS data from 21 individual female deer over the course of a year to compare changes in home range size over time and used resource selection functions (RSFs) and hidden Markov movement models (HMMs) to assess changes in behavior and habitat selection.ResultsWe found compelling evidence of adaptive capacity across individual deer in response to megafire. Deer avoided exposed and severely burned areas that lack forage and could be riskier for predation immediately following megafire, but they later altered these behaviors to select areas that burned at higher severities, potentially to take advantage of enhanced forage.ConclusionsThese results suggest that despite their high site fidelity, deer can navigate altered landscapes to track rapid shifts in encounter risk with predators and resource availability. This successful adjustment of movement and behavior following extreme disturbance could help facilitate resilience at broader ecological scales.

Comparing camera‐based ungulate density estimates: a case study using island populations of bighorn sheep and mule deer

AbstractCamera‐based abundance estimators are an alternative methodology of growing interest in both research and management applications. The statistical formulations of camera‐based abundance estimators using time‐lapse data should theoretically produce precise and unbiased estimates; however, production of unbiased results also requires meeting several important assumptions, and real‐world case studies evaluating such results remain relatively few. We applied instantaneous sampling (IS) and space‐to‐event (STE) estimators to remote camera data collected in April 2021 via time‐lapse sampling of closed populations of bighorn sheep (Ovis canadensis) and mule deer (Odocoileus hemionus) on Wild Horse Island in western Montana, USA, and compared results for bighorn sheep to aerial and ground‐based counts. Point estimates from camera‐based approaches underestimated bighorn sheep populations by 32–44% (IS estimator) and 62–69% (STE estimator) relative to aerial and ground counts. Patchy spatial distribution and group‐living behavior of sheep resulted in a high degree of noise surrounding the IS estimate. In comparison, a low point estimate with relatively narrow confidence intervals suggested potential sensitivity of the STE estimator to violating assumptions of independence among individual animals and sampling occasions. Estimates of mule deer had improved precision over sheep estimates, as indicated by lower estimated coefficients of variation of the mean (CVmean) derived from the analytic SE estimator. Using 15‐m viewsheds and the IS estimators, mule deer density estimates came with a 26% CVmean compared to 43% CVmean for bighorn sheep. This discrepancy may be a result of differences in distribution, behavior, and relative abundance between the 2 species. Accounting for group size and increasing time between sampling may improve accuracy of density estimates and adhere better to model assumptions when estimating precision. In addition, factors influencing viewshed and resulting density extrapolations must be considered carefully. While camera‐based methods theoretically provide an alternative way to estimate density when traditional methods are impractical, our results suggest that more work is needed to ensure density estimates are accurate and precise enough to inform population management.

A fine-scale examination of parturition timing in temperate ungulates.

Parturition timing has long been a topic of interest in ungulate research. However, few studies have examined parturition timing at fine scale (e.g., <1 day). Predator activity and environmental conditions can vary considerably with diel timing, which may result in selective pressure for parturition to occur during diel times that maximize the likelihood of neonate survival. We monitored parturition events and early-life survival of elk (Cervus canadensis) and mule deer (Odocoileus hemionus) in Utah, USA to better understand diel timing of parturition in temperate ungulates. Diel timing of parturition was moderately synchronous among conspecifics and influenced by environmental variables on the date of parturition. For elk, parturition events were most common during the morning crepuscular period and generally occurred later (i.e., closer to 12:00) when a relatively large proportion of the moon was illuminated. For mule deer, parturition events were most common during the diurnal period and generally occurred later (i.e., closer to 15:00) on cold, wet dates. Diel timing of parturition did not influence neonate survival, but larger datasets may be required to verify the apparent lack of influence. Although additional work could evaluate alternative variables that might affect parturition timing, our data provide an improved and finer scale understanding of reproductive ecology and phenology in ungulates.

Evaluating mountain lion diet before and after a removal of feral horses in a semiarid environment

AbstractNon‐native species can affect ecosystems by influencing native predator‐prey dynamics. Therefore, management interventions designed to remove non‐natives may inadvertently lead to increased predation on native species. Feral horses are widely distributed throughout the arid parts of western North America. A growing body of research indicates that horses can be an important prey species to mountain lions in ecosystems where they overlap. In December 2020, the Bureau of Land Management removed 455 horses from the Delamar Mountains, Nevada, USA. We leveraged this management intervention to implement a before–after–control–impact study to test hypotheses about predation on horses and native ungulates. We predicted (1) that horses would comprise an important part of the diet in this mixed‐prey community, (2) following removal, the proportion of horses in the diet would decrease and native ungulates would increase, and (3) mountain lion home ranges overlapping the treatment areas would increase in response to decreased prey availability. From 2018 to 2022, we investigated 1360 clusters from 29 GPS‐collared lions and identified 1056 prey items. To model the probability of a predation event (a kill), we fit a mixed‐effects logistic regression model for ungulate prey as a function of lion sex, treatment area (in/out), and treatment period (pre‐/post‐removal). We used a log‐linear regression model to evaluate changes in home range size. The most common prey were mule deer (55%), feral horses (32%), and coyotes (4%). Twenty‐two of 29 lions consumed horses, although the rate of horse consumption was highly variable across individuals. Horses of both sexes and all age classes were predated. In contrast to predictions, our models detected no effect of removals on diet composition (βinteraction = 0.30 ± 1.1), nor did the removal influence home range size (βinteraction = 0.02 ± 0.02). Despite a 46% reduction in horse abundance, we found no evidence for prey‐switching following the horse removal treatment. Removal magnitude, rapid horse immigration, and/or behavioral specialization of individual mountain lions may help explain these results. Our findings have important implications for mountain lion and feral horse management in arid environments characterized by high prey diversity, but low prey abundance.

Intelligent identification system of wild animals image based on deep learning in biodiversity conservation law

This study aims to overcome the impact of complex environmental backgrounds on the recognition of wildlife in monitoring images, thereby exploring the role of a deep learning-based intelligent wildlife recognition system in biodiversity conservation. The automatic identification of wildlife images is conducted based on convolutional neural networks (CNNs). Target detection technology, based on regression algorithms, is initially employed to extract Regions of Interest (ROI) containing wildlife from images. The wildlife regions in monitoring images are detected, segmented, and converted into ROI images. A dual-channel network model based on Visual Geometry Group 16 (VGG16) is implemented to extract features from sample images. Finally, these features are input into a classifier to achieve wildlife recognition. The proposed optimized model demonstrates superior recognition performance for five wildlife species, caribou, lynx, mule deer, badger, and antelope, compared to the dual-channel network model based on VGG16. The optimized model achieves a Mean Average Precision (MAP) of 0.714, with a maximum difference of 0.145 compared to the other three network structures, affirming its effectiveness in enhancing the accuracy of automatic wildlife recognition. The model effectively addresses the issue of low recognition accuracy caused by the complexity of background information in monitoring images, achieving high-precision recognition and holding significant implications for the implementation of biodiversity conservation laws.

Detection of Chronic Wasting Disease Prions in Prairie Soils from Endemic Regions.

Chronic wasting disease (CWD) is a contagious prion disease that affects cervids in North America, Northern Europe, and South Korea. CWD is spread through direct and indirect horizontal transmission, with both clinical and preclinical animals shedding CWD prions in saliva, urine, and feces. CWD particles can persist in the environment for years, and soils may pose a risk for transmission to susceptible animals. Our study presents a sensitive method for detecting prions in the environmental samples of prairie soils. Soils were collected from CWD-endemic regions with high (Saskatchewan, Canada) and low (North Dakota, USA) CWD prevalence. Heat extraction with SDS-buffer, a serial protein misfolding cyclic amplification assay coupled with a real-time quaking-induced conversion assay was used to detect the presence of CWD prions in soils. In the prairie area of South Saskatchewan where the CWD prevalence rate in male mule deer is greater than 70%, 75% of the soil samples tested were positive, while in the low-prevalence prairie region of North Dakota (11% prevalence in male mule deer), none of the soils contained prion seeding activity. Soil-bound CWD prion detection has the potential to improve our understanding of the environmental spread of CWD, benefiting both surveillance and mitigation approaches.

Temporal habitat use of mule deer in the Pueblo of Santa Ana, New Mexico

AbstractMule deer (Odocoileus hemionus) are important economically, culturally, and recreationally to the Pueblo of Santa Ana in central New Mexico, USA. Studies of habitat selection improve our understanding of mule deer ecology in central New Mexico and provide the Tribe with valuable information for management of mule deer. We used global positioning system telemetry‐collar data collected on mule deer around the Pueblo of Santa Ana to create resource selection functions from proximity‐based habitat predictors using a generalized linear mixed model. We created separate resource selection functions for females and males during summer and winter at different times of the day. Season generally had a greater effect on mule deer habitat use than the time of day. Female and male mule deer selected for similar habitats but were sexually segregated in their summer distributions. These findings are consistent with results from other locations where mule deer partitioned habitat similarly between seasons and sexes. Supported models reaffirm accepted patterns of habitat selection for mule deer to the Pueblo of Santa Ana where local results were lacking. Our results can help managers identify locations in and around the Pueblo of Santa Ana where future development such as highway expansion are likely to conflict with mule deer activity and locations where habitat enhancement projects such as adding water sources can have the greatest effect for the deer population.

Mule deer mortality in the northern Great Plains in a landscape altered by oil and natural gas extraction

AbstractA worldwide increasing demand for renewable and non‐renewable energy resources has been ongoing since the mid‐1970s and is projected to increase for the next 2 decades. The effects of oil and natural gas development on wildlife mortality risk may play an important role in mule deer (Odocoileus hemionus) population dynamics. We evaluated the potential effects of oil and natural gas development on mortality risk of mule deer in western North Dakota and eastern Montana, USA. We assessed adult and juvenile female mule deer mortality risk with Poisson point process models using 265 deer fitted with global positioning system (GPS) radio‐collars that were deployed from 2013–2016. Mortality covariates included proportion of area disturbed by oil and natural gas development, distance to oil and natural gas development, distance to roads, temperature, snow depth, normalized difference vegetation index (NDVI), and age of deer. During the study there was no effect of oil and natural gas development or roads on mule deer mortality, though &lt;1% of all deer locations were within 500 m of active drilling rigs. Mule deer mortality was greatest in winter and spring, and positively related to temperature during these seasons. Estimated annual adult survival probability was 0.79 (95% CI = 0.71–0.85). Given the strong influence of season and temperature variables on mortality risk, weather had the strongest influence on mule deer mortality during this study. Although we did not detect an effect of energy development on mule deer mortality, effects on space use resulting from development could influence deer dynamics in the region through displacement and could occur over longer time scales than we evaluated. This study can be used in pre‐development planning in a risk assessment framework to minimize effects of development on mule deer.

Facts about Wildlife Diseases: Things You Should Know about Mule Deerpox Virus in Farmed White-Tailed Deer in Florida

Pox viruses are widespread and infect many hosts, including insects, reptiles, birds, and mammals. Some, like chicken pox, are highly adapted to humans, and others, like monkeypox, can be transmitted from species to species. All are highly contagious and usually cause lesions or rashes. Poxvirus infections occur in domestic hoofstock, including cattle, sheep, goats, camels, horses, and swine, and they have been reported in wild ungulates, including mountain sheep, mountain goats, reindeer, mule deer, musk-ox, caribou, moose, and white-tailed deer. In 1983, Mule deerpox virus, a genetically distinct pox virus, was found in free-ranging mule deer in Wyoming. Since the 1990s, several cases of mule deerpox virus have been reported from black-tailed deer from California and Oregon and a white-tailed deer from Mississippi, suggesting that this virus may be a potential emerging pathogen for white-tailed deer. It is unclear whether the virus is more prevalent or whether detection has increased.

Chronic wasting disease alters the movement behavior and habitat use of mule deer during clinical stages of infection.

Integrating host movement and pathogen data is a central issue in wildlife disease ecology that will allow for a better understanding of disease transmission. We examined how adult female mule deer (Odocoileus hemionus) responded behaviorally to infection with chronic wasting disease (CWD). We compared movement and habitat use of CWD-infected deer (n = 18) to those that succumbed to starvation (and were CWD-negative by ELISA and IHC; n = 8) and others in which CWD was not detected (n = 111, including animals that survived the duration of the study) using GPS collar data from two distinct populations collared in central Wyoming, USA during 2018-2022. CWD and predation were the leading causes of mortality during our study (32/91 deaths attributed to CWD and 27/91 deaths attributed to predation). Deer infected with CWD moved slower and used lower elevation areas closer to rivers in the months preceding death compared with uninfected deer that did not succumb to starvation. Although CWD-infected deer and those that died of starvation moved at similar speeds during the final months of life, CWD-infected deer used areas closer to streams with less herbaceous biomass than starved deer. These behavioral differences may allow for the development of predictive models of disease status from movement data, which will be useful to supplement field and laboratory diagnostics or when mortalities cannot be quickly retrieved to assess cause-specific mortality. Furthermore, identifying individuals who are sick before predation events could help to assess the extent to which disease mortality is compensatory with predation. Finally, infected animals began to slow down around 4 months prior to death from CWD. Our approach for detecting the timing of infection-induced shifts in movement behavior may be useful in application to other disease systems to better understand the response of wildlife to infectious disease.

An individual-based movement model for contacts between mule deer (Odocoileus hemionus)

Contacts between individuals are key for the spread of infectious disease. Although essential to understanding disease spread, contact rates are difficult to predict, based simply on population demographics in wildlife populations, because contact rates depend upon environmental features as well as the nature of social interactions within and between groups of individuals. We developed a detailed, behaviorally structured, individual-based model (IBM) in Netlogo to simulate contacts between- and within-groups of individual mule deer (Odocoileus hemionus), a species particularly susceptible to chronic wasting disease. The model tracks contacts (defined as two individuals coming within five meters of one another), recorded as between- or within-group depending on the social group membership of the two individuals (dyad). We parameterized the model with data from mule deer with global positioning systems (GPS) collars in east-central Alberta, Canada. Individuals move according to habitat preferences, home range attraction, and grouping behaviours. Animals were tracked at two-hour time steps and were modelled as selecting locations relative to preferred resources based on sex-specific integrated step-selection functions (iSSFs) with steps biased toward a home range centroid. Total within-group contacts increased with group size and were sensitive to changes in movement cohesion of the group and movement persistence, particularly movement cohesion. Total between-group contacts were sensitive only to the number of groups. We compared model predictions for where the locations of deer contacts occurred against an existing statistical model for the relative contact probabilities (RCP) on the same landscape (Dobbin et al. 2023). Predicted locations of deer contacts generally were consistent with higher predicted RCP values. When disease transmission is a function of contact rate, the model can be used to assess the interaction between model components (e.g., movement rates, grouping rules, home ranges, animal densities) and the spatial distribution of key natural and artificial resources that may attract deer and potentially increase disease spread.