Diet studies are frequently used to improve understanding of predator ecology, potential effects of carnivores on prey populations, and competition among predators. However, field identification of carnivore scat typically relies on scat morphology, size, and contents resulting in possible subjective predator identification and potentially biased results. Advancements in noninvasive genetic sampling allow for molecular identification of predator scat, eliminating many issues associated with field identification methods. We collected scat samples once per month from June 2011 to May 2012 in western Virginia, USA, using morphological characteristics for field identification of the predator. We then used mitochondrial DNA to identify the predator species of each scat and identified prey remains visually. Using confusion matrices, we found a range of accuracy in field identification for the 3 target species: coyotes (Canis latrans; 54.0%), bobcats (Lynx rufus; 57.1%), and black bears (Ursus americanus; 95.2%), even though we only considered samples with high-confidence field identification. We found a high coyote false-positive rate (52.7%), indicating we often incorrectly identified scats as coyote (98% of misidentified bobcat scats and 75% of misidentified black bear scats were recorded as coyote in the field). This asymmetrical bias in predator identification resulted in inaccurate estimates of dietary niche breadth and overlap between competitors. Our results suggest that caution should be exercised when interpreting results from studies in which carnivore species are identified by scat morphology. Future studies should employ noninvasive genetic sampling for carnivore scat identification, especially in areas with sympatric predator species that have similar scat morphology. Ó 2016 The Wildlife Society.
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.
In the presence of a predator, prey may alter their temporal activity patterns to reduce the risk of an encounter that may induce injury or death. Prey perception of predation risk and antipredator responses may increase in the presence of dependent offspring. We conducted a camera trap study during summer 2015 in North Carolina and Tennessee, USA to evaluate temporal avoidance of a predator (coyote Canis latrans) by white-tailed deer (Odocoileus virginianus). We analyzed activity patterns of bucks, does, and nursery groups (i.e., groups that included fawns) relative to those of coyotes to determine the coefficient of overlap (Δ) using a kernel density estimator. We found that bucks and does had similar Δ with coyotes [Δ 1 = 0.729 (0.629-0.890) and Δ 1 = 0.686 (0.558-0.816, respectively] and exhibited crepuscular activity patterns comparable to those of coyotes. However, nursery groups displayed a dramatically different activity pattern: unimodal activity was concentrated in the middle of the day with little overlap with coyote activity [Δ 1 = 0.362 (0.176-0.491)]. Because adult deer are rarely prey for coyotes, whereas fawns are common prey during summer, the shift in activity patterns of nursery groups demonstrates a behavioral shift likely aimed at avoiding coyote predation on fawns.
Nonconsumptive effects of predators potentially have negative fitness consequences on prey species through changes in prey behavior. Coyotes (Canis latrans) recently expanded into the eastern United States, and raccoons (Procyon lotor) are a common mesocarnivore that potentially serve as competitors and food for coyotes. We used camera traps at baited sites to quantify vigilance behavior of feeding raccoons and used binomial logistic regression to analyze the effects of social and environmental factors. Additionally, we created raccoon and coyote activity patterns from the camera trap data by fitting density functions based on circular statistics and calculating the coefficient of overlap (Δ). Overall, raccoons were vigilant 46% of the time while foraging at baited sites. Raccoons were more vigilant during full moon and diurnal hours but less vigilant as group size increased and when other species were present. Raccoons and coyotes demonstrated nocturnal activity patterns, with coyotes more likely to be active during daylight hours. Overall, raccoons did not appear to exhibit high levels of vigilance. Activity pattern results provided further evidence that raccoons do not appear to fear coyotes, as both species were active at the same time and showed a high degree of overlap (Δ = 0.75) with little evidence of temporal segregation in activity. Thus, our study indicates that nonconsumptive effects of coyotes on raccoons are unlikely, which calls into question the ability of coyotes to initiate strong trophic cascades through some mesocarnivores.
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