Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges. This data release provides summary data for each of the 50 species. Four types of files are included in a ZIP file distributed for each species, including 1) GeoTIFF files that represent species distributions for 2001 and 2075 (including model runs with and without climate or land use), 2) PDF files summarizing MaxENT model runs for 2001, demonstrating sensitivity of the models to climate and land use, 3) lambda values for each model run that contain variables used in that run and constants that can be used to compute values for the fitted model, and 4) a JPG file depicting a summary map of modeled species range in 2001, and panel maps depicting changes in species probability as land use and/or climate change by 2075. A summary Excel spreadsheet summarizes and compares results across the 50 species.

The USGS’s FORE-SCE model was used to produce land-use and land-cover (LULC) projections for the conterminous United States. The projections were originally created as part of the "LandCarbon" project, an effort to understand biological carbon sequestration potential in the United States. However, the projections are being used for a wide variety of purposes, including analyses of the effects of landscape change on biodiversity, water quality, and regional weather and climate. The year 1992 served as the baseline for the landscape modeling. The 1992 to 2005 period was considered the historical baseline, with datasets such as the National Land Cover Database (NLCD), USGS Land Cover Trends, and US Department of Agriculture's Census of Agriculture used to guide the recreation of historical land cover for this period. 2006 to 2100 was considered the future projection time frame. Four scenarios were modeled for 2006 to 2100, corresponding to four major scenario storylines from the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES). The global IPCC SRES (A1B, A2, B1, and B2 scenarios) were downscaled to ecoregions in the conterminous United States, with the USGS Forecasting Scenarios of land use (FORE-SCE) model used to produce landscape projections consistent with the IPCC SRES. The land-use scenarios focused on socioeconomic impacts on anthropogenic land use (demographics, energy use, agricultural economics, and other socioeconomic considerations). The projections provided here are characterized by: 1) 250-meter spatial resolution (250-m pixels) 2) 17 land-cover classes, similar to classes from NLCD 3) Annual land cover maps from 1992 to 2100 4) Spatial coverage for the entire conterminous United States 5) An additional "forest stand age" layer for both the historical period (1992-2005) and the projected period (2006-2100). These data mark age in years since last land-use change or disturbance for forest pixels. Data are provided here for 1) the historical 1992 to 2005 period, and 2) for each of the four scenarios from 2006 to 2100. 10 .zip files are available for download, 5 representing land-use and land-cover maps for both the historical period and the four future scenarios, and 5 representing forest stand age. Each zip file contains GeoTIFF files with annual maps for the given timeframe. The metadata associated with this data release provides a key for identifying file names associated with each of the .zip files, as well as definitions for the 17 land-cover classes.

Renewable energy production can kill birds, but little is known about how it affects avian populations. We assessed vulnerability of populations for 23 priority bird species killed at wind and solar facilities in California, USA.

There is a growing movement within natural resource management to view wildlife health as a cumulative outcome of many different factors, rather than simply the absence of disease. This inclusive understanding of health opens the door to management options that are more creative than traditional techniques to prevent or mitigate pathogens. The public health field uses a determinants of health framework to understand the physical, social, and cultural systems that impact health at the individual and community levels (National Academies of Sciences, Engineering, and Medicine 2016). Applying a similar framework to wildlife can help managers focus on tangible actions to positively impact wildlife health in the absence of disease (Wittrock et al. 2019). In the south-central United States, changes in water availability and quality resulting from changing temperature, precipitation, and land-use patterns can have significant impacts on the health of migratory birds that depend on wildlife refuges as seasonal habitat. These data were collected in partnership with several U.S. Fish and Wildlife Service National Wildlife Refuges across Oklahoma (n=2), New Mexico (n=3), and Louisiana (n=1, 8 individual refuges administratively grouped within the Southeast Louisiana Refuge Complex) to examine how managers define determinants of health for migratory birds and assess how those determinants may be impacted by local changes in water regimes. This data release contains nineteen (19) related datafiles and their associated metadata. For each participating refuge there are three files: an image file of the final conceptual diagram, a .csv file containing information about the elements in the diagram, and a .csv file containing information about the connections in the diagram. The conceptual diagram of migratory bird health was constructed using information collected through interviews with refuge personnel and supplemented (to gain additional context, when necessary) with refuge management documents and information on their public-facing websites. The diagrams are provided as .jpg files exported from the free system mapping and visualization program Kumu, in which they were created. Each diagram consists of nodes (referred to as elements) and relationships (referred to as connections). The elements and connections represent elements of the refuge system that were highlighted by personnel as playing an important role in migratory bird health or water availability. Detailed, narrative descriptions for each system component are provided in their respective .csv files. There is also a .csv file containing data from a pre-interview survey sent to each refuge to gather basic information about the high-priority migratory bird guilds on their refuge, their management objectives in relation to migratory birds, and the water-related threats they consider highest concern.

There is a growing movement within natural resource management to view wildlife health as a cumulative outcome of many different factors, rather than simply the absence of disease. This inclusive understanding of health opens the door to management options that are more creative than traditional techniques to prevent or mitigate pathogens. The public health field uses a determinants of health framework to understand the physical, social, and cultural systems that impact health at the individual and community levels (National Academies of Sciences, Engineering, and Medicine 2016). Applying a similar framework to wildlife can help managers focus on tangible actions to positively impact wildlife health in the absence of disease (Wittrock et al. 2019). In the south-central United States, changes in water availability and quality resulting from changing temperature, precipitation, and land-use patterns can have significant impacts on the health of migratory birds that depend on wildlife refuges as seasonal habitat. These data were collected in partnership with several U.S. Fish and Wildlife Service National Wildlife Refuges across Oklahoma (n=2), New Mexico (n=3), and Louisiana (n=1, 8 individual refuges administratively grouped within the Southeast Louisiana Refuge Complex) to examine how managers define determinants of health for migratory birds and assess how those determinants may be impacted by local changes in water regimes. This data release contains nineteen (19) related datafiles and their associated metadata. For each participating refuge there are three files: an image file of the final conceptual diagram, a .csv file containing information about the elements in the diagram, and a .csv file containing information about the connections in the diagram. The conceptual diagram of migratory bird health was constructed using information collected through interviews with refuge personnel and supplemented (to gain additional context, when necessary) with refuge management documents and information on their public-facing websites. The diagrams are provided as .jpg files exported from the free system mapping and visualization program Kumu, in which they were created. Each diagram consists of nodes (referred to as elements) and relationships (referred to as connections). The elements and connections represent elements of the refuge system that were highlighted by personnel as playing an important role in migratory bird health or water availability. Detailed, narrative descriptions for each system component are provided in their respective .csv files. There is also a .csv file containing data from a pre-interview survey sent to each refuge to gather basic information about the high-priority migratory bird guilds on their refuge, their management objectives in relation to migratory birds, and the water-related threats they consider highest concern.

This data release provides avian data for 11 songbird species (Bewick’s wren [Thryomanes bewickii], black-throated gray warbler [Setophaga nigrescens], Brewer’s sparrow [Spizella breweri], gray flycatcher [Empidonax wrightii], gray vireo [Vireo vicinior], green-tailed towhee [Pipilo chlorurus], juniper titmouse [Baeolophus ridgwayi], loggerhead shrike [Lanius ludovicianus], sagebrush sparrow [Artemisiospiza nevadensis], sage thrasher [Oreoscoptes montanus], and Townsend’s solitaire [Myadestes townsendi]) associated with summertime point count surveys conducted throughout the InterMountain West under the Integrated Monitoring in Bird Conservation Regions (IMBCR) program, 2008 - 2020. Additionally, remotely sensed environmental data used in analyses, summarized at various spatial extents, is included in this data release. Finally, we provide code written in the R programming language to model avian abundance as a function of environmental covariates, evaluate model output for fit and chain convergence, and summarize model results in both table and figure formats.

This data release provides avian data for 11 songbird species (Bewick’s wren [Thryomanes bewickii], black-throated gray warbler [Setophaga nigrescens], Brewer’s sparrow [Spizella breweri], gray flycatcher [Empidonax wrightii], gray vireo [Vireo vicinior], green-tailed towhee [Pipilo chlorurus], juniper titmouse [Baeolophus ridgwayi], loggerhead shrike [Lanius ludovicianus], sagebrush sparrow [Artemisiospiza nevadensis], sage thrasher [Oreoscoptes montanus], and Townsend’s solitaire [Myadestes townsendi]) associated with summertime point count surveys conducted throughout the InterMountain West under the Integrated Monitoring in Bird Conservation Regions (IMBCR) program, 2008 - 2020. Additionally, remotely sensed environmental data used in analyses, summarized at various spatial extents, is included in this data release. Finally, we provide code written in the R programming language to model avian abundance as a function of environmental covariates, evaluate model output for fit and chain convergence, and summarize model results in both table and figure formats.

This data release provides pinyon jay (Gymnorhinus cyanocephalus) counts and local-scale vegetation data associated with summertime point count surveys conducted throughout the InterMountain West under the Integrated Monitoring in Bird Conservation Regions (IMBCR) program, 2008 - 2020. We also provide code written in the R programming language to model pinyon jay abundance as a function of local-scale covariates.