Obtaining unbiased estimates of wildlife distribution and abundance is an important objective in research and management. Occupancy and N‐mixture abundance models, which correct for imperfect detection, are commonly used for this purpose. Fitting these models in a Bayesian framework has advantages but doing so can be challenging and time‐consuming for many researchers. We developed an R package, ubms, which provides an easy‐to‐use, formula‐based interface for fitting occupancy, N‐mixture abundance and other models in a Bayesian framework using Stan. The package also provides tools for visualizing parameter effects, calculating residuals, assessing goodness‐of‐fit and comparing models. We demonstrate the use of ubms by fitting an N‐mixture model to ruffed grouse Bonasa umbellus count data from drumming surveys conducted at roadside points sampled on five occasions annually during 2013–2015. To demonstrate the functionality of ubms, we used survey site as a random effect, and occasion date and per cent aspen cover at each site as covariates of detection and abundance respectively. The top‐ranked model included a positive effect of per cent aspen on grouse abundance. ubms has the potential to greatly increase the range of users who will be able to rigorously assess species distribution and abundance while correcting for imperfect detection in a Bayesian framework.

Predation is the dominant source of mortality for white‐tailed deer (Odocoileus virginianus) <6 months old throughout North America. Yet, few white‐tailed deer fawn survival studies have occurred in areas with 4 predator species or have considered concurrent densities of deer and predator species. We monitored survival and cause‐specific mortality from birth to 6 months for 100 neonatal fawns during 2013–2015 in the Upper Peninsula of Michigan, USA, while simultaneously estimating population densities of deer, American black bear (Ursus americanus), coyote (Canis latrans), bobcat (Lynx rufus), and gray wolf (Canis lupus). We estimated fawn predation risk in response to sex, birth mass, and date of birth. Six‐month fawn survival pooled among years was 36%, and fawn mortality risk was not related to birth mass, date of birth, or sex. Estimated mean annual deer and predator densities were 334 fawns/100 km2, 25.9 black bear/100 km2, 23.8 coyotes/100 km2, 3.8 bobcat/100 km2, and 2.8 wolves/100 km2. Despite lower estimated per‐individual kill rates, coyotes and black bears were the leading sources of fawn mortality because they had greater densities relative to bobcats and wolves. Our results indicate that the presence of more predator species in a system is not entirely additive in its effect on fawn survival. © The Wildlife Society, 2019

With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14‐week period (17 August–24 November of 2019). We sampled wildlife at 1,509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian’s eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the United States. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban–wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot‐usa, as will future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species‐specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.

A relationship between winter weather and survival of northern ungulates has long been established, yet the possible roles of biological (e.g., nutritional status) and environmental (e.g., weather) conditions make it important to determine which potential limiting factors are most influential. Our objective was to examine the potential effects of individual (body mass and age) and extrinsic (winter severity and snowmelt conditions) factors on the magnitude and timing of mortality for adult (>2.5 years old) female white‐tailed deer (Odocoileus virginianus [Zimmerman, 1780]) during February–May in the Upper Peninsula of Michigan, USA. One hundred and fifty deer were captured and monitored during 2009–2015 in two areas with varying snowfall. February–May survival ranged from 0.24 to 0.89 (mean = 0.69) across years. Mortality risk increased 1.9% with each unit increase in cumulative winter severity index, decreased 8.2% with each cumulative snow‐free day, and decreased 4.3% with each kg increase in body mass. Age and weekly snow depth did not influence weekly deer survival. Predation, primarily from coyote (Canis latrans [Say, 1823]) and wolves (Canis lupus [L., 1758]), accounted for 78% of known‐cause mortalities. Our results suggest that cumulative winter severity, and possibly to a lesser degree deer condition entering winter, impacted deer winter survival. However, the timing of spring snowmelt appeared to be the most influential factor determining late‐winter mortality of deer in our study. This supports the hypothesis that nutrition and energetic demands from weather conditions are both important to northern ungulate winter ecology. Under this model, a delay of several weeks in the timing of spring snowmelt could exert a large influence on deer survival, resulting in a survival bottleneck.

No abstract

Interference competition occurs when two species have similar resource requirements and one species is dominant and can suppress or exclude the subordinate species. Wolves (Canis lupus) and coyotes (C. latrans) are sympatric across much of their range in North America where white‐tailed deer (Odocoileus virginianus) can be an important prey species. We assessed the extent of niche overlap between wolves and coyotes using activity, diet, and space use as evidence for interference competition during three periods related to the availability of white‐tailed deer fawns in the Upper Great Lakes region of the USA. We assessed activity overlap (Δ) with data from accelerometers onboard global positioning system (GPS) collars worn by wolves (n = 11) and coyotes (n = 13). We analyzed wolf and coyote scat to estimate dietary breadth (B) and food niche overlap (α). We used resource utilization functions (RUFs) with canid GPS location data, white‐tailed deer RUFs, ruffed grouse (Bonasa umbellus) and snowshoe hare (Lepus americanus) densities, and landscape covariates to compare population‐level space use. Wolves and coyotes exhibited considerable overlap in activity (Δ = 0.86–0.92), diet (B = 3.1–4.9; α = 0.76–1.0), and space use of active and inactive RUFs across time periods. Coyotes relied less on deer as prey compared to wolves and consumed greater amounts of smaller prey items. Coyotes exhibited greater population‐level variation in space use compared to wolves. Additionally, while active and inactive, coyotes exhibited greater selection of some land covers as compared to wolves. Our findings lend support for interference competition between wolves and coyotes with significant overlap across resource attributes examined. The mechanisms through which wolves and coyotes coexist appear to be driven largely by how coyotes, a generalist species, exploit narrow differences in resource availability and display greater population‐level plasticity in resource use.

1. Degree of reproductive synchronization in prey is hypothesized as a predator defense strategy reducing prey risk via predator satiation or predator avoidance. Species with precocial young, especially those exposed to specialist predators, should be highly synchronous to satiate predators (predator satiation hypothesis), | 2537 Functional Ecology MICHEL Et aL.

COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals’ 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.