SNAPSHOT USA 2019–2023: The First Five Years of Data From a Coordinated Camera Trap Survey of the United States - Brigit Rooney; Roland Kays; Michael V. Cove; Alex Jensen; Benjamin R. Goldstein; Christopher Pate; Paula Castiblanco; Maggie E. Abell; Jessie Adley; Briana Agenbroad; Adam A. Ahlers; Peter D. Alexander; et al. (Global Ecology and Biogeography, 2025)
Motivation SNAPSHOT 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 Contained SNAPSHOT USA 2019–2023 contains 987,979 records of camera trap image sequence data and 9694 records of camera trap deployment metadata. Spatial Location and Grain Data were collected across the United States of America in all 50 states, 12 ecoregions and many ecosystems. Time Period and Grain Data were collected between 1st August and 29th December each year from 2019 to 2023. 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 2019–2023 comprises two .csv files. The original data can be found within the SNAPSHOT USA Initiative in the Wildlife Insights platform.

SNAPSHOT USA 2021: A third coordinated national camera trap survey of the U nited S tates - Hila Shamon; Roi Maor; Michael V. Cove; Roland Kays; Jessie Adley; Peter D. Alexander; David N. Allen; Maximilian L. Allen; Cara L. Appel; Evan Barr; Erika L. Barthelmess; Carolina Baruzzi; et al. (Ecology, 2024)
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 km 2 ), 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.

Corridor‐based approach with spatial cross‐validation reveals scale‐dependent effects of geographic distance, human footprint and canopy cover on grizzly bear genetic connectivity - Eric C. Palm; Erin L. Landguth; Zachary A. Holden; Casey C. Day; Clayton T. Lamb; Paul F. Frame; Andrea T. Morehouse; Garth Mowat; Michael F. Proctor; Michael A. Sawaya; Gordon Stenhouse; Jesse Whittington; et al. (Molecular Ecology, 2023)
Understanding how human infrastructure and other landscape attributes affect genetic differentiation in animals is an important step for identifying and maintaining dispersal corridors for these species. We built upon recent advances in the field of landscape genetics by using an individual‐based and multiscale approach to predict landscape‐level genetic connectivity for grizzly bears ( Ursus arctos ) across ~100,000 km 2 in Canada's southern Rocky Mountains. We used a genetic dataset with 1156 unique individuals genotyped at nine microsatellite loci to identify landscape characteristics that influence grizzly bear gene flow at multiple spatial scales and map predicted genetic connectivity through a matrix of rugged terrain, large protected areas, highways and a growing human footprint. Our corridor‐based modelling approach used a machine learning algorithm that objectively parameterized landscape resistance, incorporated spatial cross validation and variable selection and explicitly accounted for isolation by distance. This approach avoided overfitting, discarded variables that did not improve model performance across withheld test datasets and spatial predictive capacity compared to random cross‐validation. We found that across all spatial scales, geographic distance explained more variation in genetic differentiation in grizzly bears than landscape variables. Human footprint inhibited connectivity across all spatial scales, while open canopies inhibited connectivity at the broadest spatial scale. Our results highlight the negative effect of human footprint on genetic connectivity, provide strong evidence for using spatial cross‐validation in landscape genetics analyses and show that multiscale analyses provide additional information on how landscape variables affect genetic differentiation.

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID ‐19 pandemic - Roland Kays; Michael V. Cove; Jose Diaz; Kimberly Todd; Claire Bresnan; Matt Snider; Thomas E. Lee; Jonathan G. Jasper; Brianna Douglas; Anthony P. Crupi; Katherine C. B. Weiss; Helen Rowe; et al. (Ecology, 2022)
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.

The North Atlantic Aerosol and Marine Ecosystem Study (NAAMES): Science Motive and Mission Overview - Michael J. Behrenfeld; Richard H. Moore; Chris A. Hostetler; Jason Graff; Peter Gaube; Lynn M. Russell; Gao Chen; Scott C. Doney; Stephen Giovannoni; Hongyu Liu; Christopher Proctor; Luis M. Bolaños; et al. (Frontiers in Marine Science, 2019)

Differential Morphological and Biochemical Recovery from Chemotherapy-Induced Peripheral Neuropathy Following Paclitaxel, Ixabepilone, or Eribulin Treatment in Mouse Sciatic Nerves - B. M. Cook; K. M. Wozniak; D. A. Proctor; R. B. Bromberg; Y. Wu; B. S. Slusher; B. A. Littlefield; M. A. Jordan; L. Wilson; Stuart C. Feinstein (Neurotoxicity Research, 2018)

The 2011–2016 Transdisciplinary Research on Energetics and Cancer (TREC) Initiative: Rationale and Design - Ruth E. Patterson; Graham A. Colditz; Frank B. Hu; Kathryn H. Schmitz; Rexford S. Ahima; Ross C. Brownson; Kenneth R. Carson; Jorge E. Chavarro; Lewis A. Chodosh; Sarah Gehlert; Jeff Gill; Karen Glanz; et al. (Cancer Causes & Control, 2013)

Sea lice, Lepeophtheirus salmonis , transfer between wild sympatric adult and juvenile salmon on the north coast of British Columbia, Canada - A S Gottesfeld; B Proctor; L D Rolston; C Carr‐Harris (Journal of Fish Diseases, 2009)
We examine sea lice, Lepeophtheirus salmonis , on juvenile and adult salmon from the north coast of British Columbia between 2004 and 2006 in an area that does not at present contain salmon farms. There is a pronounced zonation in the abundance of L. salmonis on juvenile pink salmon, Oncorhynchus gorbuscha , in the Skeena and Nass estuaries. Abundances in the proximal and distal zones of these estuaries are 0.01 and 0.05 respectively. The outer zones serve as feeding and staging areas for the pink salmon smolts. Returning Chinook, Oncorhynchus tshawytscha , and coho salmon, Oncorhynchus kisutch , concentrate in these areas. We collected data in 2006 to examine whether L. salmonis on returning adult salmon are an important source of the sea lice that appear on juvenile pink salmon. Nearly all (99%) of the sea lice on returning Chinook and over 80% on coho salmon were L. salmonis. Most of the L. salmonis were motile stages including many ovigerous females. There was a sharp increase in the abundance of sea lice on juvenile pink salmon smolts between May and July 2006 near the sites of adult captures. As there are no salmon farms on the north coast, few sticklebacks, Gasterosteus aculeatus , and very few resident salmonids until later in the summer, it seems that the most important reservoir of L. salmonis under natural conditions is returning adult salmon. This natural source of sea lice results in levels of abundance that are one or two orders of magnitude lower than those observed on juvenile pink salmon in areas with salmon farms such as the Broughton Archipelago.

Integration of Mouse Phenome Data Resources - John M. Hancock; Niels C. Adams; Vassilis Aidinis; Andrew Blake; Judith A. Blake; Molly Bogue; Steve D. M. Brown; Elissa J. Chesler; Duncan Davidson; Christopher Duran; Janan T. Eppig; Valérie Gailus-Durner; et al. (Mammalian Genome, 2008)

A three thousand year record of North Atlantic climate - Proctor C.; Baker A.; Barnes W. (Climate Dynamics, 2002)

A thousand year speleothem proxy record of North Atlantic climate from Scotland - C. J. Proctor; A. Baker; W. L. Barnes; M. A. Gilmour (Climate Dynamics, 2000)

Synergistic Effect of Formulated Plasmid and Needle-Free Injection for Genetic Vaccines - Khursheed Anwer; Keith A. Earle; Mei Shi; Jijun Wang; Russell J. Mumper; Belinda Proctor; Kimberly Jansa; Harry C. Ledebur; Stephen Davis; William Eaglstein; Alain P. Rolland (Pharmaceutical Research, 1999)