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Dry deciduous dipterocarp forests (DDF) cover about 15%–20% of Southeast Asia and are the most threatened forest type in the region. The jungle cat (Felis chaus) is a DDF specialist that occurs only in small isolated populations in Southeast Asia. Despite being one of the rarest felids in the region, almost nothing is known about its ecology. We investigated the ecology of jungle cats and their resource partitioning with the more common leopard cats (Prionailurus bengalensis) in a DDF‐dominated landscape in Srepok Wildlife Sanctuary, Cambodia. We used camera‐trap data collected from 2009 to 2019 and DNA‐confirmed scats to determine the temporal, dietary and spatial overlap between jungle cats and leopard cats. The diet of jungle cats was relatively diverse and consisted of murids (56% biomass consumed), sciurids (15%), hares (Lepus peguensis; 12%), birds (8%), and reptiles (8%), whereas leopard cats had a narrower niche breadth and a diet dominated by smaller prey, primarily murids (73%). Nonetheless, dietary overlap was high because both felid species consumed predominantly small rodents. Both species were primarily nocturnal and had high temporal overlap. Two‐species occupancy modelling suggested jungle cats were restricted to DDF and had low occupancy, whereas leopard cats had higher occupancy and were habitat generalists. Our study confirmed that jungle cats are DDF specialists that likely persist in low numbers due to the harsh conditions of the dry season in this habitat, including annual fires and substantial decreases in small vertebrate prey. The lower occupancy and more diverse diet of jungle cats, together with the broader habitat use of leopard cats, likely facilitated the coexistence of these species. The low occupancy of jungle cats in DDF suggests that protection of large areas of DDF will be required for the long‐term conservation of this rare felid in Southeast Asia. We studied the ecology of jungle cat, one of the rarest felids in Southeast Asia, and its resource partitioning with the more common leopard cat. The diet, activity, and habitat use overlapped considerably between the two felid species, suggesting high‐niche overlap. Overall, we found that jungle cats were habitat specialists for open dry deciduous forests and were rare, suggesting that large areas of this habitat will be required for their long‐term conservation.

Investigating species responses to trophic interactions and abiotic factors is crucial to better understanding their ecology and creating effective management strategies. In carnivore communities, smaller species are often regulated by larger ones via top‐down interference competition. Smaller subordinate carnivores can also be regulated by bottom‐up and abiotic factors, such as the availability of important prey, habitat features, and climatic conditions. However, substantial ambiguity remains regarding the relative roles these complex factors play in shaping subordinate carnivore populations, especially during winter. To investigate this issue, we conducted a large‐scale camera‐trapping study (n = 197 sites distributed across a ~60,000 km2 landscape) using a balanced study design that sampled a gradient of forest disturbance and climatic conditions. We used dynamic occupancy modeling to examine the influences of top‐down (interference competition), bottom‐up (prey and habitat), and abiotic (climate) factors on a widespread, generalist subordinate carnivore, the red fox (Vulpes vulpes), in Maine, USA. Across three winters, we collected 107 red fox and 185 coyote (Canis latrans) daily detections, and 3875 snowshoe hare (Lepus americanus) detections. We found evidence for the top‐down effects of coyotes on red fox detection probability and site colonization. However, contrary to theoretical expectations, the association between coyotes and red foxes was positive rather than negative. Snowshoe hares had a positive association with local extinction by red foxes, which also contrasts with prevailing theory given that snowshoe hares are an important winter prey of red foxes in this ecosystem. The intensity of forest disturbance and the proportion of conifer forest had negative effects on red fox occurrence and detection probability, while snow depth had a strong negative effect on site colonization. Together, these results suggest red foxes are limited more by abiotic and bottom‐up factors related to habitat than by the top‐down interference competition or primary prey availability in winter. Our study supports recent findings that bottom‐up factors may shape carnivore distributions during less productive times of year. Our work also highlights how caution is needed when extrapolating previous results from summer studies to winter, as the role of top‐down and bottom‐up factors may change seasonally.

Barriers to passage of aquatic organisms at stream road crossings are a major cause of habitat fragmentation in stream networks. Accordingly, large investments have been made to restore passage at these crossings, but often without estimation of population-level benefits. Here, we describe a broad-scale approach to quantifying the effectiveness of passage restoration in terms interpretable at population levels, namely numbers of fish and length of stream gained through restoration, by sampling abundance in a study design that accounts for variable biogeographic species pools, variable stream and barrier configurations, and variable probabilities of capture and detectability for multiple species. We modified an existing zero-inflated negative-binomial model to estimate the probability of site access, abundance conditional on access, and capture probability of individual fish. Therein, we modeled probability of access as a function of gradient, stream road-crossing type, and downstream access by fish simultaneously with a predictive model for abundance at sites accessible to fish. Results indicated that replacement of barriers with new crossing designs intended to allow for greater movement was associated with dramatically higher probability of access for all fishes, including migratory Pacific salmon, trout, sculpin, and lamprey. Conversely, existing non-replaced crossings negatively impacted fish distributions. Assuming no downstream constraints on access, we estimated the potential length of stream restored by the program ranged between 7.33 (lamprey) and 15.28 km (small coastal cutthroat and rainbow trout). These contributions represented a fraction of the total length available upstream (187 km) of replaced crossings. When limited ranges of species were considered, the estimated contributions of culvert replacement were reduced (1.65-km range for longnose dace to 12.31 km for small coastal cutthroat and rainbow trout). Numbers of fish contributed ranged from less than 500 (longnose dace) to greater than 100 000 (sculpin). Although our framework can address the question of effectiveness in a broad array of stream and crossing configurations, much stronger inferences would be possible if future restoration efforts were designed to address the limitations we encountered in this study, particularly the lack of available information on crossings and species presence prior to restoration, and nonrandom selection of crossings to be replaced.

Competition is a widespread interaction among carnivores, ultimately manifested through one or more dimensions of the species' ecological niche. One of the most explicit manifestations of competitive interactions regards spatial displacement. Its interpretation under a theoretical context provides an important tool to deepen our understanding of biological systems and communities, but also for wildlife management and conservation. We used Bayesian multispecies occupancy models on camera-trapping data from multiple sites in Southwestern Europe (SWE) to investigate competitive interactions within a carnivore guild, and to evaluate how species' ecological traits are shaping coexistence patterns. Seventeen out of 26 pairwise interactions departed from a hypothesis of independent occurrence, with spatial association being twice as frequent as avoidance. Association behaviors were only detected among mesocarnivores, while avoidance mainly involved mesocarnivores avoiding the apex predator (n = 4) and mesocarnivore-only interactions (n = 2). Body mass ratios, defined as the dominant over the subordinate species body mass, revealed an important negative effect (β̂ = −0.38; CI95 = −0.81 to −0.06) on co-occurrence probability, and support that spatially explicit competitive interactions are mostly expressed by larger species able to dominate over smaller ones, with a threshold in body mass ratios of ∼4, above which local-scale intraguild coexistence is unlikely. We found a weak relationship between pairwise trophic niche overlap and the probability of coexistence (β̂ = −0.19; CI95 = −0.58 to 0.21), suggesting that competition for feeding resources may not be a key driver of competition, at least at the scale of our analysis. Despite local-scale avoidance, regional-scale coexistence appears to be maintained by the spatial structuring of the competitive environment. We provide evidence that SWE ecosystems consist of spatially structured competitive environments, and propose that coexistence among near-sized species is likely achieved through the interplay of “facultative” and “behavioral” character displacements. Factors influencing carnivore coexistence likely include context-dependent density and trait-mediated effects, which should be carefully considered for a sound understanding of the mechanisms regulating these communities.

Over the past half century, migratory birds in North America have shown divergent population trends relative to resident species, with the former declining rapidly and the latter increasing. The role that climate change has played in these observed trends is not well understood, despite significant warming over this period. We used 43 y of monitoring data to fit dynamic species distribution models and quantify the rate of latitudinal range shifts in 32 species of birds native to eastern North America. Since the early 1970s, species that remain in North America throughout the year, including both resident and migratory species, appear to have responded to climate change through both colonization of suitable area at the northern leading edge of their breeding distributions and adaption in place at the southern trailing edges. Neotropical migrants, in contrast, have shown the opposite pattern: contraction at their southern trailing edges and no measurable shifts in their northern leading edges. As a result, the latitudinal distributions of temperate-wintering species have increased while the latitudinal distributions of neotropical migrants have decreased. These results raise important questions about the mechanisms that determine range boundaries of neotropical migrants and suggest that these species may be particularly vulnerable to future climate change. Our results highlight the potential importance of climate change during the nonbreeding season in constraining the response of migratory species to temperature changes at both the trailing and leading edges of their breeding distributions. Future research on the interactions between breeding and nonbreeding climate change is urgently needed.

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.

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap-nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID-19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site-level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.

Advances in species distribution modeling continue to be driven by a need to predict species responses to environmental change coupled with increasing data availability. Recent work has focused on development of methods that integrate multiple streams of data to model species distributions. Combining sources of information increases spatial coverage and can improve accuracy in estimates of species distributions. However, when fusing multiple streams of data, the temporal and spatial resolutions of data sources may be mismatched. This occurs when data sources have fluctuating geographic coverage, varying spatial scales and resolutions, and differing sources of bias and sparsity. It is well documented in the spatial statistics literature that ignoring the misalignment of different data sources will result in bias in both the point estimates and uncertainty. This will ultimately lead to inaccurate predictions of species distributions. Here, we examine the issue of misaligned data as it relates specifically to integrated species distribution models. We then provide a general solution that builds off work in the statistical literature for the change-of-support problem. Specifically, we leverage spatial correlation and repeat observations at multiple scales to make statistically valid predictions at the ecologically relevant scale of inference. An added feature of the approach is that addressing differences in spatial resolution between data sets can allow for the evaluation and calibration of lesser-quality sources in many instances. Using both simulations and data examples, we highlight the utility of this modeling approach and the consequences of not reconciling misaligned spatial data. We conclude with a brief discussion of the upcoming challenges and obstacles for species distribution modeling via data fusion.

Outdoor recreation in natural areas has become an increasingly popular activity globally, yet the long-term effects on wildlife are poorly known. Reconciling human access to nature and wildlife conservation requires sound evaluations of how outdoor activities affect biodiversity in space and time. We aimed to contribute to this topic by asking whether tourism in the world-renown Dolomites, Italy, affected wild mammals in the long term, and if it elicited spatial or temporal avoidance. We detected mammals by systematic camera trapping over seven consecutive summers at 60, consistently sampled, sites, and estimated trends in occurrence at community and species levels through a dynamic community occupancy model, combined with site use intensity and an index of nocturnality. Overall, 70% of the 520 000 images obtained depicted humans, whose presence intensified over the 7-year period. Nonetheless, both community and most species-level occurrences increased. However, human activities caused a strong temporal avoidance in the whole community, especially in most disturbed sites, while spatial avoidance was observed only for bigger-sized species.

The occurrence of false positive detections in presence-absence data, even when they occur infrequently, can lead to severe bias when estimating species occupancy patterns. Building upon previous efforts to account for this source of observational error, we established a general framework to model false positives in occupancy studies and extend existing modeling approaches to encompass a broader range of sampling designs. Specifically, we identified three common sampling designs that are likely to cover most scenarios encountered by researchers. The different designs all included ambiguous detections, as well as some known-truth data, but their modeling differed in the level of the model hierarchy at which the known-truth information was incorporated (site level or observation level). For each model, we provide the likelihood, as well as R and BUGS code needed for implementation. We also establish a clear terminology and provide guidance to help choosing the most appropriate design and modeling approach.