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ABSTRACT MotivationSNAPSHOT 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. 

Abstract A tenet of ecology is that temporal variability in ecological structure and processes tends to decrease with increasing spatial scales (from locales to regions) and levels of biological organization (from populations to communities). However, patterns in temporal variability across trophic levels and the mechanisms that produce them remain poorly understood. Here we analyzed the abundance time series of spatially structured communities (i.e., metacommunities) spanning basal resources to top predators from 355 freshwater sites across three continents. Specifically, we used a hierarchical partitioning method to disentangle the propagation of temporal variability in abundance across spatial scales and trophic levels. We then used structural equation modeling to determine if the strength and direction of relationships between temporal variability, synchrony, biodiversity, and environmental and spatial settings depended on trophic level and spatial scale. We found that temporal variability in abundance decreased from producers to tertiary consumers but did so mainly at the local scale. Species population synchrony within sites increased with trophic level, whereas synchrony among communities decreased. At the local scale, temporal variability in precipitation and species diversity were associated with population variability (linear partial coefficient, β = 0.23) and population synchrony (β = −0.39) similarly across trophic levels, respectively. At the regional scale, community synchrony was not related to climatic or spatial predictors, but the strength of relationships between metacommunity variability and community synchrony decreased systematically from top predators (β = 0.73) to secondary consumers (β = 0.54), to primary consumers (β = 0.30) to producers (β = 0). Our results suggest that mobile predators may often stabilize metacommunities by buffering variability that originates at the base of food webs. This finding illustrates that the trophic structure of metacommunities, which integrates variation in organismal body size and its correlates, should be considered when investigating ecological stability in natural systems. More broadly, our work advances the notion that temporal stability is an emergent property of ecosystems that may be threatened in complex ways by biodiversity loss and habitat fragmentation. 

Abstract Spatial synchrony is defined by related fluctuations through time in population abundances measured at different locations. The degree of relatedness typically declines with increasing distance between sampling locations. Standard approaches for assessing synchrony assume isotropy in space and uniformity across timescales of analysis, but it is now known that spatial variability and timescale structure in population dynamics are common features. We tested for spatial and timescale structure in the patterns of synchrony of freshwater plankton in Kentucky Lake, U.S.A. We also evaluated whether different mechanisms may drive synchrony and its spatial structure on different timescales. Using wavelet techniques and matrix regression, we analyzed phytoplankton biomass and abundances of seven zooplankton taxa at 16 locations sampled from 1990 to 2015. We found that zooplankton abundances and phytoplankton biomass exhibited synchrony at multiple timescales. Timescale structure in the potential mechanisms of synchrony was revealed primarily through networks of relationships among zooplankton taxa, which differed by timescale. We found substantial interspecific variability in geographic structures of synchrony and their causes: all mechanisms we considered strongly explained geographic structure in synchrony for at least one species, while Euclidean distance between sampling locations was generally less well supported than more mechanistic explanations. Geographic structure in synchrony and its underlying mechanisms also depended on timescale for a minority of the taxa tested. Overall, our results show substantial and complex but interpretable variation in structures of synchrony across three variables: space, timescale, and taxon. It seems likely these aspects of synchrony are important general features of freshwater systems.