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This spatial model was applied over the entire sagebrush biome for several time periods and was estimated for 5 historical time periods between 1998 and 2020, and for one future time period (2030-2060). For each time period, input data were derived from satellite imagery (e.g. data on sagebrush and perennial grass cover), and the spatial model used those input values to estimate sagebrush ecological integrity. This approach to estimating ecological integrity was developed by consultation with experts from across the biome, allowing for the relationship between integrity and plant cover to vary among regions, as described in Doherty et al (2022). These data can be used to inform and prioritize conservation and restoration efforts across the sagebrush biome. For more information, please see - https://www.sciencebase.gov/catalog/item/62d57e89d34e87fffb2dda62 . 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"name": "Forest Connectivity", "type": "Raster Layer", "description": "This dataset uses human modification ( Theobald 2020 - https://essd.copernicus.org/articles/12/1953/2020/ ) and forest cover data to identify key areas of importance for forest landscape connectivity across North America. This dataset uses a 700-meter search radius to evaluate landscape connectivity. In large, unfragmented areas with intact forest cover, forest dependent species may move freely across the landscape. These areas may provide options for maintaining ecological connections. In highly developed and altered landscapes, where forest cover is largely absent, species movement is impeded and restricted, reflecting the difficulty species may experience in moving through these human-modified landscapes. In areas with adjacent natural and modified lands, where forest cover is limited in distribution, species movement is concentrated in areas (pinch points or bottlenecks) where few alternative movement pathways exist. These concentrated movement areas may be particularly important for maintaining or restoring ecological connectivity for forest-dependent species and processes. Areas with the top 30% of connectivity scores are identified, representing areas where very highly, highly, and concentrated forest connectivity occurs. - (Belote et al. unpublished; Belote et al. 2022 - https://academic.oup.com/bioscience/article/70/2/122/5680447) \n\nMap and Data Disclaimer: The USDA Forest Service makes no warranty, expressed or implied, including the warranties of Merchant ability and fitness for a particular purpose, and assumes no legal liability or responsibility for the accuracy, reliability, completeness, or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. 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It refers to the physical features that provide the environmental setting or \"stage\" for biological activity. Areas with greater diversity in physical features usually correlate with higher levels of biodiversity. The greater number of ecological niches present in a physiographically diverse landscape often support the presence of rare species and high levels of endemism. As a result, geodiversity may be used in some contexts as a proxy for biodiversity and/or endemism when other data are unavailable and/or to augment existing information on species and their habitats. Geodiversity is also recognized as a crucial element of climate refugia.\n\nTo develop this dataset, Theobald et al. generated novel spatial databases for 15 landform and 269 physiographic types across the conterminous United States of America. They examined their potential use by natural resource managers by placing them within a contemporary climate change adaptation framework, and found the physiographic databases could play key roles in four of seven general adaptation strategies. They also calculated correlations with common empirical measures of biodiversity to examine the degree to which the physiographic setting explains various aspects of current biodiversity patterns. Additionally, they evaluated the relationship between landform diversity and measures of climate change to explore how changes may unfold across a geophysical template. \n\n( Theobald et al 2015 - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0143619 ).\n\nMap and Data Disclaimer: The USDA Forest Service makes no warranty, expressed or implied, including the warranties of Merchant ability and fitness for a particular purpose, and assumes no legal liability or responsibility for the accuracy, reliability, completeness, or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. 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