Motivation: SNAPSHOT USA is an annual, multi-contributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables Contained: SNAPSHOT USA 2024 contains 377,427 records of camera trap image sequence data and 3127 records of camera trap deployment metadata. Spatial Location and Grain: Data were collected across the United States of America in 49 states, 12 ecoregions and many ecosystems. Time Period and Grain: Data were collected between 1 August and 19 December in 2024. Major Taxa and Level of Measurement: The dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software Format: SNAPSHOT USA 2024 comprises two.csv files. The original data can be found within the SNAPSHOT USA 2024 project on the Wildlife Insights platform.

ABSTRACTMotivationSNAPSHOT USA is an annual, multicontributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns.Main Types of Variables ContainedSNAPSHOT USA 2019–2023 contains 987,979 records of camera trap image sequence data and 9694 records of camera trap deployment metadata.Spatial Location and GrainData were collected across the United States of America in all 50 states, 12 ecoregions and many ecosystems.Time Period and GrainData were collected between 1st August and 29th December each year from 2019 to 2023.Major Taxa and Level of MeasurementThe dataset includes a wide range of taxa but is primarily focused on medium to large mammals.Software FormatSNAPSHOT USA 2019–2023 comprises two .csv files. The original data can be found within the SNAPSHOT USA Initiative in the Wildlife Insights platform.

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.

Aim: The assembly of species into communities and ecoregions is the result of interacting factors that affect plant and animal distribution and abundance at biogeographic scales. Here, we empirically derive ecoregions for mammals to test whether human disturbance has become more important than climate and habitat resources in structuring communities. Location: Conterminous United States. Time Period: 2010-2021. Major Taxa Studied: Twenty-five species of mammals. Methods: We analysed data from 25 mammal species recorded by camera traps at 6645 locations across the conterminous United States in a joint modelling framework to estimate relative abundance of each species. We then used a clustering analysis to describe 8 broad and 16 narrow mammal communities. Results: Climate was the most important predictor of mammal abundance overall, while human population density and agriculture were less important, with mixed effects across species. Seed production by forests also predicted mammal abundance, especially hard-mast tree species. The mammal community maps are similar to those of plants, with an east-west split driven by different dominant species of deer and squirrels. Communities vary along gradients of temperature in the east and precipitation in the west. Most fine-scale mammal community boundaries aligned with established plant ecoregions and were distinguished by the presence of regional specialists or shifts in relative abundance of widespread species. Maps of potential ecosystem services provided by these communities suggest high herbivory in the Rocky Mountains and eastern forests, high invertebrate predation in the subtropical south and greater predation pressure on large vertebrates in the west. Main Conclusions: Our results highlight the importance of climate to modern mammals and suggest that climate change will have strong impacts on these communities. Our new empirical approach to recognizing ecoregions has potential to be applied to expanded communities of mammals or other taxa.

Introduced ungulates have a profound impact on Hawaiian ecosystems yet are also considered a valuable resource for recreational and subsistence hunting. These conflicting values have led to challenging issues for resource managers. Distribution assessments allow resource managers to simultaneously prioritize areas for targeted removal for conservation benefit while also maintaining or even promoting hunting opportunities in other areas. This study identified distribution trends for three introduced ungulate species, wild pigs (Sus scrofa), black-tailed deer (Odocoileus hemionus columbianus), and feral goats (Capra hircus) on the island of Kaua'i in the Hawaiian Islands. Using species distribution modeling techniques, we aimed to identify patterns in ungulate distributions across ecosystems and time, and potential species interactions. Data were collected using motion activated cameras deployed across the entire island of Kaua'i from July 2020 to July 2021. Wild pigs were the most frequently detected species, observed at 53 out of 59 locations, followed by black-tailed deer at 30 locations, and feral goats at 9 locations. Distribution models indicate some degree of competition between deer and pigs and show considerable overlap between black-tailed deer distribution and much of the last remaining critical habitat for threatened and endangered native species. Our results suggest that pigs prefer mid-elevation areas with moderate rainfall while goats preferred arid areas regardless of slope and elevation. Differences in the distribution and abundance of these species highlight the divergent impacts invasive ungulates have on native ecosystems throughout the Hawaiian Islands and may help identify high priority areas for their management.

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.

Background Non-native wild pigs ( Sus scrofa ) threaten sensitive flora and fauna, cost billions of dollars in economic damage, and pose a significant human–wildlife conflict risk. Despite growing interest in wild pig research, basic life history information is often lacking throughout their introduced range and particularly in tropical environments. Similar to other large terrestrial mammals, pigs possess the ability to shift their range based on local climatic conditions or resource availability, further complicating management decisions. The objectives of this study were to (i) model the distribution and abundance of wild pigs across two seasons within a single calendar year; (ii) determine the most important environmental variables driving changes in pig distribution and abundance; and (iii) highlight key differences between seasonal models and their potential management implications. These study objectives were achieved using zero-inflated models constructed from abundance data obtained from extensive field surveys and remotely sensed environmental variables. Results Our models demonstrate a considerable change in distribution and abundance of wild pigs throughout a single calendar year. Rainfall and vegetation height were among the most influential variables for pig distribution during the spring, and distance to adjacent forest and vegetation density were among the most significant for the fall. Further, our seasonal models show that areas of high conservation value may be more vulnerable to threats from wild pigs at certain times throughout the year, which was not captured by more traditional modeling approaches using aggregated data. Conclusions Our results suggest that (i) wild pigs can considerably shift their range throughout the calendar year, even in tropical environments; (ii) pigs prefer dense forested areas in the presence of either hunting pressure or an abundance of frugivorous plants, but may shift to adjacent areas in the absence of either of these conditions; and (iii) seasonal models provide valuable biological information that would otherwise be missed by common modeling approaches that use aggregated data over many years. These findings highlight the importance of considering biologically relevant time scales that provide key information to better inform management strategies, particularly for species whose ranges include both temperate and tropical environments and thrive in both large continental and small island ecosystems.

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.

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.

Most of Earth's terrestrial carbon is stored in the soil and can be released as carbon dioxide (CO2) when disturbed. Although humans are known to exacerbate soil CO2 emissions through land-use change, we know little about the global carbon footprint of invasive species. We predict the soil area disturbed and resulting CO2 emissions from wild pigs (Sus scrofa), a pervasive human-spread vertebrate that uproots soil. We do this using models of wild pig population density, soil damage, and their effect on soil carbon emissions. Our models suggest that wild pigs are uprooting a median area of 36,214 km(2) (mean of 123,517 km(2)) in their non-native range, with a 95% prediction interval (PI) of 14,208 km(2)-634,238 km(2). This soil disturbance results in median emissions of 4.9 million metric tonnes (MMT) CO2 per year (equivalent to 1.1 million passenger vehicles or 0.4% of annual emissions from land use, land-use change, and forestry; mean of 16.7 MMT) but that it is highly uncertain (95% PI, 0.3-94 MMT CO2) due to variability in wild pig density and soil dynamics. This uncertainty points to an urgent need for more research on the contribution of wild pigs to soil damage, not only for the reduction of anthropogenically related carbon emissions, but also for co-benefits to biodiversity and food security that are crucial for sustainable development.

The International Union for the Conservation of Nature’s (IUCN) Red List of Threatened Species is a comprehensive database of over 120,000 species and is a powerful tool to evaluate the threat of invasive species to global biodiversity. Several problematic species have gained global recognition due to comprehensive threat assessments quantifying the threat these species pose to biodiversity using large datasets like the IUCN Red List of Threatened Species. However, the global threat of wild pigs ( Sus scrofa ) to biodiversity is still poorly understood despite well-documented ecosystem level impacts. In this study, we utilized the IUCN Red List to quantify the impacts of this globally distributed species throughout its native and non-native range. Here we show that wild pigs threaten 672 taxa in 54 different countries across the globe. Most of these taxa are listed as critically endangered or endangered and 14 species have been driven to extinction as a direct result of impacts from wild pigs. Our results show that threats from wild pigs are pervasive across taxonomic groups and that island endemics and taxa throughout the non-native range of wild pigs are particularly vulnerable.

Invasive wild pigs (Sus scrofa) have been spread by humans outside of their native range and are now established on every continent except Antarctica. Through their uprooting of soil, they affect societal and environmental values. Our recent article explored another threat from their soil disturbance: greenhouse gas emissions (O’Bryan et al., Global Change Biology, 2021). In response to our paper, Don (Global Change Biology, 2021) claims there is no threat to global soil carbon stocks by wild pigs. While we did not investigate soil carbon stocks, we examine uncertainties regarding soil carbon emissions from wild pig uprooting and their implications for management and future research.

Species distribution models play a central role in informing wildlife management. For models to be useful, they must be based on data that best represent the presence or abundance of the species. Data used as inputs in the development of these models can be obtained through numerous methods, each subject to different biases and limitations but, to date, few studies have examined whether these biases result in different predictive spatial models, potentially influencing conservation decisions. In this study, we compare distribution model predictions of feral pig (Sus scrofa) relative abundance using the two most common monitoring methods: detections from camera traps and visual surveys of pig sign. These data were collected during the same period using standardised methods at survey sites generated using a random stratified sampling design. We found that although site-level observed sign data were only loosely correlated with observed camera detections (R2=0.32–0.45), predicted sign and camera counts from zero-inflated models were well correlated (R2=0.78–0.88). In this study we show one example in which fitting two different forms of abundance data using environmental covariates explains most of the variance between datasets. We conclude that, as long as outputs are produced through appropriate modelling techniques, these two common methods of obtaining abundance data may be used interchangeably to produce comparable distribution maps for decision-making purposes. However, for monitoring purposes, sign and camera trap data may not be used interchangeably at the site level.