SNAPSHOT USA 2021: A third coordinated national camera trap survey of the United States

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.

AlInAsSb Geiger-mode SWIR and eSWIR SPADs with high avalanche probability

Single-photon avalanche diodes (SPADs) that are sensitive to photons in the Short-wave infrared and extended short-wave infrared (SWIR and eSWIR) spectra are important components for communication, ranging, and low-light level imaging. The high gain, low excess noise factor, and widely tunable bandgap of AlxIn1-xAsySb1-y avalanche photodiodes (APDs) make them a suitable candidate for these applications. In this work, we report single-photon-counting results for a separate absorption, charge, and multiplication (SACM) Geiger-mode SPAD within a gated-quenching circuit. The single-photon avalanche probabilities surpass 80% at 80 K, corresponding with single-photon detection efficiencies of 33% and 12% at 1.55 µm and 2 µm, respectively.

Effect of species-level trait variation on urban exploitation in mammals

Identifying drivers of urban association in wildlife is a central challenge in conservation biology. Traits facilitating access to novel resources and avoiding humans often correspond with urban exploitation in mammal species, but these relationships differ by taxa and trophic guild. Variation among or within traits may be a yet untested explanation for the non-generality of species-trait relationships in cities. Using camera trap data from 1,492 sites throughout the contiguous USA in 2019, we investigated if mammal species with greater intraspecific trait variation have higher degrees of urban occupancy. We hypothesized that intraspecific trait variation would correspond with urban occupancy, but that the strength of these relationships would vary by taxonomic order due to expected phylogenetic constraints. Mean trait values (average home range size, body mass, group size, weaning age, litter size, and diet composition) varied widely across orders. The only traits that affected urban association across all species corresponded with demography (litter size), while responses across orders were more variable and informative. Mean trait values associated with home range and body size had informative relationships with urbanization for Cetartiodactyla, Rodentia, and Carnivora, while intraspecific variation in traits corresponding with diet (Carnivora), demography (Cetartiodactyla, Carnivora, Rodentia), and temporal responses to humans (Carnivora) had informative relationships to urbanization. This is the first study investigating mammalian species-level trait variation and its relationship to urban exploitation across many traits and taxa. Since natural selection requires trait variation, the variation of demographic traits, like litter size, can have significant implications for wildlife management and conservation. Our results also provide further evidence for omnivory as a form of dietary plasticity supporting urban accessibility in higher trophic guilds (e.g., Carnivora). Using this information, we can better manage and understand which species occupy and adapt to cities, thereby promoting human-wildlife coexistence.

Counting the Capital's cats: Estimating drivers of abundance of free-roaming cats with a novel hierarchical model

Free-roaming cats are a conservation concern in many areas but identifying their impacts and developing mitigation strategies requires a robust understanding of their distribution and density patterns. Urban and residential areas may be especially relevant in this process because free-roaming cats are abundant in these anthropogenic landscapes. Here, we estimate the occupancy and density of free-roaming cats in Washington D.C. and relate these metrics to known landscape and social factors. We conducted an extended camera trap survey of public and private spaces across D.C. and analyzed data collected from 1483 camera deployments from 2018 to 2020. We estimated citywide cat distribution by fitting hierarchical occupancy models and further estimated cat abundance using a novel random thinning spatial capture-recapture model that allows for the use of photos that can and cannot be identified to individual. Within this model, we utilized individual covariates that provided identity exclusions between photos of unidentifiable cats with inconsistent coat patterns, thus increasing the precision of abundance estimates. This combined model also allowed for unbiased estimation of density when animals cannot be identified to individual at the same rate as for free-roaming cats whose identifiability depended on their coat characteristics. Cat occupancy and abundance declined with increasing distance from residential areas, an effect that was more pronounced in wealthier neighborhoods. There was noteworthy absence of cats detected in larger public spaces and forests. Realized densities ranged from 0.02 to 1.75 cats/ha in sampled areas, resulting in a district-wide estimate of ~7296 free-roaming cats. Ninety percent of cat detections lacked collars and nearly 35% of known individuals were ear-tipped, indicative of district Trap-Neuter-Return (TNR) programs. These results suggest that we mainly sampled and estimated the unowned cat subpopulation, such that indoor/outdoor housecats were not well represented. The precise estimation of cat population densities is difficult due to the varied behavior of subpopulations within free-roaming cat populations (housecats, stray and feral cats), but our methods provide a first step in establishing citywide baselines to inform data-driven management plans for free-roaming cats in urban environments.

Spatial and temporal overlap of domestic cats (Felis catus) and native urban wildlife

Free-roaming domestic cats (Felis catus) are known to pose threats to ecosystem health via transmission of zoonotic diseases and predation of native wildlife. Likewise, free-roaming cats are also susceptible to predation or disease transmission from native wildlife. Physical interactions are required for many of these risks to be manifested, necessitating spatial and temporal overlap between cats and wildlife species. Therefore, knowledge of the location and extent of shared habitat and activity periods would benefit management programs. We used data from a 3-year camera trap survey to model species-specific occupancy and identify landscape variables that contribute to the distribution of free-roaming domestic cats and eight native mammal species in Washington, DC. (USA). Our analysis includes five species that are common prey items of domestic cats, and three species that are potential disease vectors or are otherwise known to be a risk to cats. We then predicted the probability of occupancy and estimated the probability of spatial overlap between cats and each native wildlife species at multiple scales. We also used kernel density estimations to calculate temporal overlap between cats and each native wildlife species. Across spatial scales, occupancy for potential disease vector species was generally positively correlated with canopy cover and open water. Prey species were also generally positively correlated with canopy cover, but displayed negative associations with human population density and inconsistent associations with average per capita income. Domestic cat occupancy was negatively correlated with natural habitat characteristics and positively correlated with human population density. Predicted spatial overlap between domestic cats and native wildlife was greatest for potential disease vector species. Temporal overlap was high (>0.50) between cats and all but two native wildlife species, indicating that temporal overlap is probable wherever species overlap spatially. Our findings indicate that the risk to and from domestic cats varies across urban landscapes, but primarily arises from human activities. As such, humans are implicated in the negative outcomes that result from cats interacting with wildlife. Data-driven management to reduce such interactions can aid in cat population management, biodiversity conservation, and public health campaigns.

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID-19 pandemic

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.

SNAPSHOT USA 2019: a coordinated national camera trap survey of the United States

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.

Thinking outside the park: recommendations for camera trapping mammal communities in the urban matrix

Urbanization is increasing globally, fragmenting habitats and prompting human–wildlife conflict. Urban wildlife research is concurrently expanding, but sampling methods are often biased towards large and intact habitats in public green spaces, neglecting the far more abundant, but degraded, habitats in the urban matrix. Here, we introduce the Five P’s of Urban Ecology—Partnerships, Planning, Placements, Public participation and Processing—as a path to overcoming the logistical barriers often associated with camera-trapping in the urban matrix. Though the Five P’s can be applied to a variety of urban sampling methods, we showcase the camera-trapping efforts of the DC Cat Count project in Washington, DC, as a case study. We compared occupancy models for eight urban mammal species using broad categorizations of land cover and local land use to determine drivers of mammal occurrence within the urban matrix as compared with urban habitat patches. Many native species maintained a strong association with large, semi-natural green spaces, but occupancy was not limited to these locations, and in some cases, the use of private yards and the built environment were not notably different. Furthermore, some species exhibited higher occupancy probabilities in developed areas over green spaces. Though seemingly intuitive, we offer advice on how to greatly reduce habitat-biased sampling methods in urban wildlife research and illustrate the importance of doing so to ensure accurate results that support the formation of effective urban planning and policy.