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SNAPSHOT USA is a multicontributor, long‐term camera trap survey designed to survey mammals across the United States. Participants are recruited through community networks and directly through a website application (https://www.snapshot-usa.org/). The growing Snapshot dataset is useful, for example, for tracking wildlife population responses to land use, land cover, and climate changes across spatial and temporal scales. Here we present the SNAPSHOT USA 2021 dataset, the third national camera trap survey across the US. Data were collected across 109 camera trap arrays and included 1711 camera sites. The total effort equaled 71,519 camera trap nights and resulted in 172,507 sequences of animal observations. Sampling effort varied among camera trap arrays, with a minimum of 126 camera trap nights, a maximum of 3355 nights, a median 546 nights, and a mean 656 ± 431 nights. This third dataset comprises 51 camera trap arrays that were surveyed during 2019, 2020, and 2021, along with 71 camera trap arrays that were surveyed in 2020 and 2021. All raw data and accompanying metadata are stored on Wildlife Insights (https://www.wildlifeinsights.org/), and are publicly available upon acceptance of the data papers. SNAPSHOT USA aims to sample multiple ecoregions in the United States with adequate representation of each ecoregion according to its relative size. Currently, the relative density of camera trap arrays varies by an order of magnitude for the various ecoregions (0.22–5.9 arrays per 100,000 km2), emphasizing the need to increase sampling effort by further recruiting and retaining contributors. There are no copyright restrictions on these data. We request that authors cite this paper when using these data, or a subset of these data, for publication. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government. [ABSTRACT FROM AUTHOR]

Camera trapping has revolutionized wildlife ecology and conservation by providing automated data acquisition, leading to the accumulation of massive amounts of camera trap data worldwide. Although management and processing of camera trap‐derived Big Data are becoming increasingly solvable with the help of scalable cyber‐infrastructures, harmonization and exchange of the data remain limited, hindering its full potential. There is currently no widely accepted standard for exchanging camera trap data. The only existing proposal, "Camera Trap Metadata Standard" (CTMS), has several technical shortcomings and limited adoption. We present a new data exchange format, the Camera Trap Data Package (Camtrap DP), designed to allow users to easily exchange, harmonize and archive camera trap data at local to global scales. Camtrap DP structures camera trap data in a simple yet flexible data model consisting of three tables (Deployments, Media and Observations) that supports a wide range of camera deployment designs, classification techniques (e.g., human and AI, media‐based and event‐based) and analytical use cases, from compiling species occurrence data through distribution, occupancy and activity modeling to density estimation. The format further achieves interoperability by building upon existing standards, Frictionless Data Package in particular, which is supported by a suite of open software tools to read and validate data. Camtrap DP is the consensus of a long, in‐depth, consultation and outreach process with standard and software developers, the main existing camera trap data management platforms, major players in the field of camera trapping and the Global Biodiversity Information Facility (GBIF). Under the umbrella of the Biodiversity Information Standards (TDWG), Camtrap DP has been developed openly, collaboratively and with version control from the start. We encourage camera trapping users and developers to join the discussion and contribute to the further development and adoption of this standard. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Interactions between species can influence their distribution and fitness, with potential cascading ecosystem effects. Human disturbance can affect these competitive dynamics but is difficult to measure due to potential simultaneous spatial and temporal responses. We used camera traps with a multispecies occupancy model incorporating a continuous‐time detection process to evaluate spatial and temporal interactions between two competing carnivore species, coyote (Canis latrans) and gray fox (Urocyon cinereoargenteus), along an urbanization gradient. Coyotes were less likely to occupy high housing density sites than gray foxes, but the two species were more likely to co‐occur in suburban forest fragments. Gray foxes were less likely to occupy low housing density sites in the presence of coyotes, shifted their activity patterns to be more nocturnal when coyotes were present and avoided sites recently used by coyotes. These effects were most pronounced where forest cover was low, suggesting these shifts are not necessary where forest cover is high, perhaps due to the gray fox's ability to climb trees. Gray foxes did not spatially or temporally avoid coyotes moving through the suburban matrix nor did precipitation mediate temporal avoidance in suburban habitats (i.e., by washing away scent), possibly because coyotes are less likely to establish territories at high housing densities, and thus less likely to scent mark. As reports of gray fox declines in portions of North America mount and coyotes are implicated, our results suggest that preserving tree cover could be important for gray fox persistence. At least 50% of forest cover in a 1 km radius resulted in lower coyote occupancy with gray fox occupancy rising to ≥0.1, suggesting a good benchmark for management. [ABSTRACT FROM AUTHOR]

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Summary: Wildlife is an essential component of all ecosystems. Most places in the globe do not have local, timely information on which species are present or how their populations are changing. With the arrival of new technologies, camera traps have become a popular way to collect wildlife data. However, data collection has increased at a much faster rate than the development of tools to manage, process and analyse these data. Without these tools, wildlife managers and other stakeholders have little information to effectively manage, understand and monitor wildlife populations. We identify four barriers that are hindering the widespread use of camera trap data for conservation. We propose specific solutions to remove these barriers integrated in a modern technology platform called Wildlife Insights. We present an architecture for this platform and describe its main components. We recognize and discuss the potential risks of publishing shared biodiversity data and a framework to mitigate those risks. Finally, we discuss a strategy to ensure platforms like Wildlife Insights are sustainable and have an enduring impact on the conservation of wildlife. [ABSTRACT FROM AUTHOR]

The rise of the Panamanian Isthmus 3–4 million years ago enabled the first dispersal of mammals between North and South America in what is known as the Great American Biotic Interchange. Modern deforestation threatens the historic forest connectivity and creates new habitat for open-country species, as documented by recent expansions of North American coyotes (Canis latrans) and South American crab-eating foxes (Cerdocyon thous) into Central America. We used camera traps to map the expansions of these species into eastern Panama and found that, by 2015, coyote populations had colonized most agricultural area west of Lago Bayano. Most of our camera arrays east of this point documented crab-eating foxes, and evidence from roadkills showed some foxes had advanced farther west, but we never documented both species at the same camera-trap array, suggesting the possibility of fine-scale spatial avoidance. We used a data fusion approach to build species distribution models combining our camera surveys with records from the literature and roadkill. While the auxiliary data improved the predictive accuracy for both species, few clear habitat patterns emerged, which might reflect the generalist tendencies of these canids, or the fact that both are in the early stages of colonizing the region. Camera-trap photos showed that both species were nocturnal and revealed some dog-like morphology in coyotes, which could indicate their recent hybridization with dogs (Canis familiaris). Our continued monitoring of the Darién documented single coyotes moving through the western edge of the area in 2016 and 2018. This leaves only the great Darién forests between coyotes and South America. If deforestation continues in the region, these two invasive canids could represent the first of a new, Not-So-Great American Biotic Interchange, where generalist species adapted to human disturbance cross continents and threaten native biota. [ABSTRACT FROM AUTHOR]

Interspecific interactions can provoke temporal and spatial avoidance, ultimately affecting population densities and spatial distribution patterns. The ability (or inability) of species to coexist has consequences for diversity and ultimately ecosystem stability. Urbanization is predicted to change species interactions but its relative impact is not well known. Urbanization gradients offer the opportunity to evaluate the effect of humans on species interactions by comparing community dynamics across levels of disturbance.We used camera traps deployed by citizen scientists to survey mammals along urbanization gradients of two cities (Washington, DC and Raleigh, NC, USA). We used a multispecies occupancy model with four competing predator species to test whether forest fragmentation, interspecific interactions, humans or prey had the greatest influence on carnivore distribution.Our study produced 6,413 carnivore detections from 1,260 sites in two cities, sampling both private and public lands. All species used all levels of the urbanization gradient to a similar extent, but co‐occurrence of urban‐adapted foxes with less urban‐adapted bobcats and coyotes was dependent on the availability of green space, especially as urbanization increased. This suggests green space allows less urban‐adapted species to occupy suburban areas, but focuses their movements through remaining forest patches, leading to more species interactions.Synthesis and applications. Species interactions, forest fragmentation and human‐related covariates were important determinants of carnivore occupancy across a gradient of urbanization with the relative importance of forest fragmentation being highest. We found evidence of both positive and negative interactions across the gradient with some dependent on available green space, suggesting that fragmentation leads to higher levels of spatial interaction. Where green space is adequate, there appears to be sufficient opportunity for coexistence between carnivore species in an urban landscape. Species interactions, forest fragmentation and human‐related covariates were important determinants of carnivore occupancy across a gradient of urbanization with the relative importance of forest fragmentation being highest. We found evidence of both positive and negative interactions across the gradient with some dependent on available green space, suggesting that fragmentation leads to higher levels of spatial interaction. Where green space is adequate, there appears to be sufficient opportunity for coexistence between carnivore species in an urban landscape. [ABSTRACT FROM AUTHOR]

Citizen science has been touted as an effective means to collect large-scale data while engaging the public. We demonstrate that children as young as 9 years old can collect valuable mammal monitoring data using camera traps while connecting with nature and learning through their own scientific discoveries. Indian, Kenyan, Mexican, and American students used camera traps near their schools and detected 13–37 species, all of which were verified by professionals. These data describe rich mammal faunas near schools, sometimes surpassing nearby protected areas, and included five endangered species. Ninety-four percent of the camera traps were set in accordance with scientific protocols, and the teachers reported the experience as highly engaging for their students. Furthermore, the generated photos and results had community-wide impacts involving local politicians, community members, and the media. We show that children can run sensors to contribute valid scientific data important for conservation and research. [ABSTRACT FROM AUTHOR]

Citizen science approaches are of great interest for their potential to efficiently and sustainably monitor wildlife populations on both public and private lands. Here we present two studies that worked with volunteers to set camera traps for ecological surveys. The photographs recorded by these citizen scientists were archived and verified using the eMammal software platform, providing a professional grade, vouchered database of biodiversity records. Motivated by managers' concern with perceived high bear activity, our first example enlisted the help of homeowners in a short-term study to compare black bear activity inside a National Historic Site with surrounding private land. We found similar levels of bear activity inside and outside the NHS, and regional comparisons suggest the bear population is typical. Participants benefited from knowing their local bear population was normal and managers refocused bear management given this new information. Our second example is a continuous survey of wildlife using the grounds of a nature education center that actively manages habitat to maintain a grassland prairie. Center staff incorporated the camera traps into educational programs, involving visitors with camera setup and picture review. Over two years and 5,968 camera-nights this survey has collected 41,393 detections of 14 wildlife species. Detection rates and occupancy were higher in open habitats compared to forest, suggesting that the maintenance of prairie habitat is beneficial to some species. Over 500 volunteers of all ages participated in this project over two years. Some of the greatest benefits have been to high school students, exemplified by a student with autism who increased his communication and comfort level with others through field work with the cameras. These examples show how, with the right tools, training and survey design protocols, citizen science can be used to answer a variety of applied management questions while connecting participants with their secretive mammal neighbors. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

1. The distance travelled by animals is an important ecological variable that links behaviour, energetics and demography. It is usually measured by summing straight-line distances between intermittently sampled locations along continuous animal movement paths. The extent to which this approach underestimates travel distance remains a rarely addressed and unsolved problem, largely because true movement paths are rarely, if ever, available for comparison. Here, we use simulated movement paths parameterized with empirical movement data to study how estimates of distance travelled are affected by sampling frequency. 2. We used a novel method to obtain fine-scale characteristics of animal movement from camera trap videos for a set of tropical forest mammals and used these characteristics to generate detailed movement paths. We then sampled these paths at different frequencies, simulating telemetry studies, and quantified the accuracy of sampled travel distance estimation. 3. For our focal species, typical telemetry studies would underestimate distances travelled by 67-93%, and extremely high sampling frequencies (several fixes per minute) would be required to get tolerably accurate estimates. The form of the relationship between tortuosity, sample frequency, and distance travelled was such that absolute distance cannot accurately be estimated by the infrequent samples used in typical tracking studies. 4. We conclude that the underestimation of distance travelled is a serious but underappreciated problem. Currently, there is no reliable, widely applicable method to obtain approximately unbiased estimates of distance travelled by animals. Further research on this problem is needed. [ABSTRACT FROM AUTHOR]

The establishment of protected areas is a key strategy for preserving biodiversity. However, human use of protected areas can cause disturbance to wildlife, especially in areas that allow hunting and if humans are accompanied by dogs ( Canis familiaris ). We used citizen-science run camera traps to investigate how humans, dogs and coyotes ( Canis latrans ) used 33 protected areas and analyzed behavioral responses by three prey species: white-tailed deer ( Odocoileus virginianus ), eastern gray squirrel ( Sciurus carolinensis ) and northern raccoon ( Procyon lotor ). We obtained 52,863 detections of native wildlife, 162,418 detections of humans and 23,332 detections of dogs over 42,874 camera nights. Most dogs (99%) were on the trail, and 89% of off-trail dogs were accompanied by humans. Prey avoided dogs, humans and coyotes temporally, but did not avoid them spatially, or greatly increase vigilance. Our results indicate that humans are perceived as a greater risk than coyotes, and this increases when dogs accompany their owners. The concentration of dogs on the trail with their owners, and relatively minor behavioral impacts on prey, contrasts the strong negative ecological effects found in studies of free-ranging dogs. We found dog management to be effective: prohibiting dogs in protected areas reduced their use of an area by a factor of 10 and leash laws increased leashing rates by 21%. Although millions of dogs use natural areas in North America each year, regulations enacted by protected areas combined with responsible management of dog behavior greatly reduce the ecological impact of man's best friend. [ABSTRACT FROM AUTHOR]