Cause-specific neonatal mortality of white-tailed deer in Wisconsin, USA

Using decoys and camera traps to estimate depredation rates and neonate survival

Ungulate neonates-individuals less than four weeks old-typically experience the greatest predation rates, and variation in their survival can influence ungulate population dynamics. Typical methods to measure neonate survival involve capture and radio-tracking of adults and neonates to discover mortality events. This type of fieldwork is invasive and expensive, can bias results if it leads to neonate abandonment, and may still have high uncertainty about the predator species involved. Here we explore the potential for a non-invasive approach to estimate an index for neonate survival using camera traps paired with decoys that mimic white-tailed deer (Odocoileus virginianus) neonates in the first month of life. We monitored sites with camera traps for two weeks before and after the placement of the neonate decoy and urine scent lure. Predator response to the decoy was classified into three categories: did not approach, approached within 2.5 m but did not touch the decoy, or physically touched the decoy; when conducting survival analyses, we considered these second two categories as dead neonates. The majority (76.3%) of the predators approached the decoy, with 51.1% initiating physical contact. Decoy probability of survival was 0.31 (95% CI = 0.22, 0.35) for a 30-day period. Decoys within the geographic range of American black bear (Ursus americanus) were primarily (75%) attacked by bears. Overall, neonate survival probability decreased as predator abundance increased. The camera-decoy protocol required about ½ the effort and 1/3 the budget of traditional capture-track approaches. We conclude that the camera-decoy approach is a cost-effective method to estimate a neonate survival probability index based on depredation probability and identify which predators are most important.

Demographic effects of road mortality on mammalian populations: a systematic review

In light of rapidly expanding road networks worldwide, there is increasing global awareness of the growing amount of mammalian roadkill. However, the ways in which road mortality affects the population dynamics of different species remains largely unclear. We aimed to categorise the demographic parameters in mammalian populations around the world that are directly or indirectly affected by road mortality, as well as identify the most effective study designs for quantifying population-level consequences of road mortality. We conducted a comprehensive systematic review to synthesise literature published between 2000 and 2021 and out of 11,238 unique studies returned, 83 studies were retained comprising 69 mammalian species and 150 populations. A bias towards research-intensive countries and larger mammals was apparent. Although searches were conducted in five languages, all studies meeting the inclusion criteria were in English. Relatively few studies (13.3%) provided relevant demographic context to roadkill figures, hampering understanding of the impacts on population persistence. We categorised five direct demographic parameters affected by road mortality: sex- and age-biased mortality, the percentage of a population killed on roads per year (values up to 50% were reported), the contribution of roadkill to total mortality rates (up to 80%), and roadkill during inter-patch or long-distance movements. Female-biased mortality may be more prevalent than previously recognised and is likely to be critical to population dynamics. Roadkill was the greatest source of mortality for 28% of studied populations and both additive and compensatory mechanisms to roadkill were found to occur, bringing varied challenges to conservation around roads. In addition, intra-specific population differences in demographic effects of road mortality were common. This highlights that the relative importance of road mortality is likely to be context specific as the road configuration and habitat quality surrounding a population can vary. Road ecology studies that collect data on key life parameters, such as age/stage/sex-specific survival and dispersal success, and that use a combination of methods are critical in understanding long-term impacts. Quantifying the demographic impacts of road mortality is an important yet complex consideration for proactive road management.

Snapshot Wisconsin: networking community scientists and remote sensing to improve ecological monitoring and management

Biological data collection is entering a new era. Community science, satellite remote sensing (SRS), and local forms of remote sensing (e.g., camera traps and acoustic recordings) have enabled biological data to be collected at unprecedented spatial and temporal scales and resolution. There is growing interest in developing observation networks to collect and synthesize data to improve broad-scale ecological monitoring, but no examples of such networks have emerged to inform decision-making by agencies. Here, we present the implementation of one such jurisdictional observation network (JON), Snapshot Wisconsin, which links synoptic environmental data derived from SRS to biodiversity observations collected continuously from a trail camera network to support management decision-making. We use several examples to illustrate that Snapshot Wisconsin improves the spatial, temporal, and biological resolution and extent of information available to support management, filling gaps associated with traditional monitoring and enabling consideration of new management strategies. JONs like Snapshot Wisconsin further strengthen monitoring inference by contributing novel lines of evidence useful for corroboration or integration. SRS provides environmental context that facilitates inference, prediction, and forecasting, and ultimately helps managers formulate, test, and refine conceptual models for the monitored systems. Although these approaches pose challenges, Snapshot Wisconsin demonstrates that expansive observation networks can be tractably managed by agencies to support decision making, providing a powerful new tool for agencies to better achieve their missions and reshape the nature of environmental decision-making.

Understanding environmental patterns of canid predation on white-tailed deer (Odocoileus virginianus)

The outcome of encounters between predators and prey affects predation rates and ultimately population dynamics. Determining how environmental features influence predation rates helps guide conservation and management efforts. We studied where gray wolves (Canis lupus Linnaeus, 1758) and coyotes (Canis latrans Say, 1823) killed white-tailed deer (Odocoileus virginianus (Zimmermann, 1780)) in northern Wisconsin, USA. We monitored 499 white-tailed deer for cause-specific mortality between 2011 and 2014 using VHF radio collars. We investigated the locations of 125 deer mortalities and determined that 63 were canid (wolf or coyote) kill sites. We analyzed spatial patterns of kill sites using resource selection functions in a model selection framework, incorporating environmental variables including vegetative cover, human development, snow depth, and water. We found no evidence that vegetative cover or human development affected predation risk; however, we did find that increasing snow depth resulted in increased relative predation risk. This finding is consistent with existing research on the influence of snow cover on white-tailed deer survival. Our results suggest that understanding the spatial and temporal patterns of white-tailed deer predation requires a better understanding of snow depth variation in space and time. As climate change scenarios predict changes in snowfall throughout the northern hemisphere, understanding the effect on predator–prey spatial dynamics will be important for management and conservation efforts.

Capture method affects survival estimates and subsequent interpretation of ecological covariates for a long-lived cervid

Understanding what variables affect ungulate neonate survival is imperative to successful conservation and management of the species. Predation is commonly cited as a cause-specific source of mortality, and ecological covariates often influence neonate survival. However, variation in survival estimates related to capture methodology has been documented with opportunistically captured neonates generally displaying greater survival than those captured via aid of vaginal implant transmitters (VITs), likely because of increased left truncation observed in the opportunistically captured datasets. Our goal was to assess whether 3- and 6-month survival estimates varied by capture method while simultaneously assessing whether capture method affected model selection and interpretation of ecological covariates for white-tailed deer neonates captured from three study sites from 2014 to 2015 in North Dakota and South Dakota, USA. We found survival varied by capture method for 3-month neonate survival with opportunistically captured neonates displaying up to 26% greater survival than their counterparts captured via VITs; however, this relationship was not present for 6-month survival. We also found model selection and subsequent interpretation of ecological covariates varied when analyzing datasets comprised of neonates captured via VITs, neonates captured opportunistically, and all neonates combined regardless of capture method. When interpreting results from our VIT-only analysis for 3-month survival, we found survival varied by three time intervals and was lowest in the first two weeks of life. Capture method did not affect 6-month survival, which was most influenced by total precipitation occurring during 3 - 8 weeks of a neonate's life and percent canopy cover found at a neonate's capture site. Our results support previous research that capture method must be accounted for when deriving survival estimates for ungulate neonates as it can impact derived estimates and subsequent interpretation of results.

Habitat selection of white-tailed deer fawns and their dams in the Northern Great Plains

Habitat availability can affect important life-history traits such as survival; however, little information exists on how microhabitat characteristics found at parturition sites selected by dams and bed sites selected by their offspring differ from the surrounding area and from each other. Therefore, we assessed how vegetation affected maternal parturition and offspring bed site selection for white-tailed deer (Odocoileus virginianus) in the Northern Great Plains. Dams selected for sites with decreased vegetation height, potentially improving their visibility, which may increase their ability to escape approaching predators. Conversely, there was no variation between vegetative characteristics at neonate bed sites and their associated random sites, indicating grasslands provide adequate concealment for neonates. Dams possess the ability to flee from approaching predators, thus increasing the importance of visibility while giving birth. Conversely, neonates depend on fear bradycardia as their main antipredator defense, so concealment is more important. Our results suggest that vegetation structure is an important characteristic to white-tailed deer as habitat needs vary between adults and neonates.

Survival of white-tailed deer fawns in central Iowa

Understanding demographic parameters such as survival is important for scientifically sound wildlife management. Survival can vary by region, sex, age-class, habitat, and other factors. White-tailed deer fawn survival is highly variable across the species’ range. While recent studies have investigated fawn survival in several Midwestern states, there have been no published estimates from Iowa for 30 years. We radio-collared 48 fawns in central Iowa from 2015–2017 to estimate survival, home range size, and habitat composition and identity causes of mortality. Estimated fawn survival (± SE) was similar to other Midwest studies at 30 (0.78 ± 0.07)) and 60 days (0.69 ± 0.08), but considerably lower at 7 months (0.31 ± 0.02). Survival was positively associated with woodland habitat through 30 and 60 days, but not related to habitat at 7 months. Female fawns avoided agricultural habitat in their home ranges. Fawn 95% kernel density home ranges were smaller than in other studies in the Midwest (21.22 ± 2.74 ha at 30 days, 25.47 ± 2.87 ha at 60 days, and 30.59 ± 2.37 ha at 7 months). The large amount of woodland and grassland (>90%) in our study area meant that fawns did not have to travel far to find suitable cover, which may explain their small home ranges. We recorded 21 mortalities, the leading cause of which was disease (n = 9; 56% epizootic hemorrhagic disease [EHD]) followed by suspected predation (4) and harvest (3). The mortality associated with an outbreak of EHD in 2016, all of which occurred after 60 days post-capture, is the most likely explanation for our low survival estimate at 7 months. While predation, usually early in life, is the leading cause of mortality in most studies, sporadic diseases like EHD can be a major source of mortality in older fawns in some years.

Variation in anti-predator behaviors of white-tailed deer (Odocoileus virginianus) in a multi-predator system

Anti-predator responses to perceived predation risk can influence population demography. Understanding the relative effect of predator exposure and intraspecific interactions across a variety of anti-predator behaviors provides important insight into inter- and intra-specific drivers of species-specific behaviors. We merged classical behavioral observation methods with camera trapping techniques to examine anti-predator behaviors of white-tailed deer (Odocoileus virginianus (Zimmermann, 1780)) relative to variation in predator exposure and interspecific interactions. We coded 772 behavioral observations from >180 000 images spanning 605 trap-nights. Seasonal differences in behavioral responses to diminishing returns on foraging effort indicated that deer are risk-averse foragers and are more likely to exhibit risky behaviors in the presence of a concentrated food resource when the nutritional value of food resources are high. However, deer tended to spend less time at a site as resources diminished, supporting marginal value theories of habitat use. Intraspecific interaction predicted vigilance and the amount of time spent at a site. Similar to many other species, deer tended to be less vigilant and spend more time at a site as group size increased. Our research suggests that white-tailed deer in Wisconsin make foraging decisions based on factors associated with individual fitness, presence of conspecifics, and habitat characteristics.

Modeling reproduction of whitetail deer and its applications

Many environmental factors, such as annual precipitation, temperature variations, and the embedded stochasticity of natural systems, affect resource availability from one region to the next, such that animal survival and reproduction rates differ by region. For species exhibiting phenotypic plasticity, embedding phenotypes in a model of population dynamics becomes important, as region-driven plastic responses play a significant role when estimating parameters values. In this paper, we discuss how to include observable characteristics and climate patterns in estimates of reproduction rates of whitetail deer (Odocoileus virginianus). Using many studies already available in the literature, we establish a strong correlation between reproduction rate and both body weight and USDA plant hardiness zone. We demonstrate the accuracy of the estimated whitetail deer fecundity rates for various geographical regions in North America and show that Bergmann's rule is necessary to maintain similar biological fitness between various spatial distributions of deer populations. We demonstrate that the standard deviation of the weight distribution has almost no effect on reproduction rate estimates for adult deer populations. However, statistical analysis reveals sensitivity of fawn reproduction rates to environmental stochasticity. We incorporate the reproduction function in a stage- and gender-based model and prove the existence of a stable solution. Finally, we demonstrate a possible application of the model using harvested deer weights, without collecting reproduction data directly.