These data were compiled so that annual wildfire could be modelled across the sagebrush region in the western United States. Our goal was to understand how wildfire probability relates to climate and fuel conditions across the entire sagebrush region. To do this we developed a statistical model that represents the relationship between annual wildfire probability and a small number of climate and fuel variables. Specifically, created predictions of wildfire probability using a biologically plausible logistic regression model that related wildfire probability to mean temperature, annual precipitation, the proportion summer precipitation (PSP), and aboveground biomass of annual herbaceous plants and perennial herbaceous plants. The biomass variables were used as proxies for fine fuel availability. These data represent annual fire occurrence in 1 km pixels (i.e. did a given pixel burn that year), predicted wildfire probability, as well as the three year running average (i.e. average across the current and previous two years) of climate and vegetation variables. These data were collected across the sagebrush region (the extent of the study area is provided by the cell_number_ids.tif file). The climate and vegetation data were compiled using a existing gridded dataset (Daymet) of daily precipitation and temperature, and vegetation data were summaries of annual estimates of aboveground biomass of annual and perennial herbaceous plants from the Rangeland Analysis Platform (https://rangelands.app/). These data can be used to understand spatial and temporal variability in wildfire occurrence and modelled wildfire probability between 1988 and 2019 and how that variability relates to spatial and temporal variability in climate and vegetation.

These data were compiled so that annual wildfire could be modelled across the sagebrush region in the western United States. Our goal was to understand how wildfire probability relates to climate and fuel conditions across the entire sagebrush region. To do this we developed a statistical model that represents the relationship between annual wildfire probability and a small number of climate and fuel variables. Specifically, created predictions of wildfire probability using a biologically plausible logistic regression model that related wildfire probability to mean temperature, annual precipitation, the proportion summer precipitation (PSP), and aboveground biomass of annual herbaceous plants and perennial herbaceous plants. The biomass variables were used as proxies for fine fuel availability. These data represent annual fire occurrence in 1 km pixels (i.e. did a given pixel burn that year), predicted wildfire probability, as well as the three year running average (i.e. average across the current and previous two years) of climate and vegetation variables. These data were collected across the sagebrush region (the extent of the study area is provided by the cell_number_ids.tif file). The climate and vegetation data were compiled using a existing gridded dataset (Daymet) of daily precipitation and temperature, and vegetation data were summaries of annual estimates of aboveground biomass of annual and perennial herbaceous plants from the Rangeland Analysis Platform (https://rangelands.app/). These data can be used to understand spatial and temporal variability in wildfire occurrence and modelled wildfire probability between 1988 and 2019 and how that variability relates to spatial and temporal variability in climate and vegetation.

This table summarizes areas of burn severity, sagebrush biophysical types, and soil temperature/moisture regimes within large wildfires from 1984 to 2013 occuring within greater sage-grouse population areas. Methods used to derive these data are detailed in the report [Brooks, M.L., Matchett, J.R., Shinneman, D.J., and Coates, P.S., 2015, Fire patterns in the range of greater sage-grouse, 1984-2013; Implications for conservation and management: U.S. Geological Survey Open-File Report 2015-1167, 66 p., http://dx.doi.org/10.3133/ofr20151167]

This table summarizes areas of burn severity, sagebrush biophysical types, and soil temperature/moisture regimes within large wildfires from 1984 to 2013 occuring within greater sage-grouse population areas. Methods used to derive these data are detailed in the report [Brooks, M.L., Matchett, J.R., Shinneman, D.J., and Coates, P.S., 2015, Fire patterns in the range of greater sage-grouse, 1984-2013; Implications for conservation and management: U.S. Geological Survey Open-File Report 2015-1167, 66 p., http://dx.doi.org/10.3133/ofr20151167]

This three-band, 30-m resolution raster contains sagebrush vegetation types, soil temperature/moisture regime classes, and large fire frequencies across greater sage-grouse population areas within the Wyoming Basin sage-grouse management zone. Sagebrush vegetation types were defined by grouping together similar vegetation types from the LANDFIRE biophysical settings layer. Soil moisture and temperature regimes were from an USDA-NRCS analysis of soil types across the greater sage-grouse range. Fire frequencies were derived from fire severity rasters created by the Monitoring Trends in Burn Severity program. The area of analysis included the greater sage-grouse populations areas within specific management zones. Methods used to derive these data are detailed in the report [Brooks, M.L., Matchett, J.R., Shinneman, D.J., and Coates, P.S., 2015, Fire patterns in the range of greater sage-grouse, 1984-2013; Implications for conservation and management: U.S. Geological Survey Open-File Report 2015-1167, 66 p., http://dx.doi.org/10.3133/ofr20151167]

This three-band, 30-m resolution raster contains sagebrush vegetation types, soil temperature/moisture regime classes, and large fire frequencies across greater sage-grouse population areas within the Colorado Plateau sage-grouse management zone. Sagebrush vegetation types were defined by grouping together similar vegetation types from the LANDFIRE biophysical settings layer. Soil moisture and temperature regimes were from an USDA-NRCS analysis of soil types across the greater sage-grouse range. Fire frequencies were derived from fire severity rasters created by the Monitoring Trends in Burn Severity program. The area of analysis included the greater sage-grouse populations areas within specific management zones. Methods used to derive these data are detailed in the report [Brooks, M.L., Matchett, J.R., Shinneman, D.J., and Coates, P.S., 2015, Fire patterns in the range of greater sage-grouse, 1984-2013; Implications for conservation and management: U.S. Geological Survey Open-File Report 2015-1167, 66 p., http://dx.doi.org/10.3133/ofr20151167]

This three-band, 30-m resolution raster contains sagebrush vegetation types, soil temperature/moisture regime classes, and large fire frequencies across greater sage-grouse population areas within the Wyoming Basin sage-grouse management zone. Sagebrush vegetation types were defined by grouping together similar vegetation types from the LANDFIRE biophysical settings layer. Soil moisture and temperature regimes were from an USDA-NRCS analysis of soil types across the greater sage-grouse range. Fire frequencies were derived from fire severity rasters created by the Monitoring Trends in Burn Severity program. The area of analysis included the greater sage-grouse populations areas within specific management zones. Methods used to derive these data are detailed in the report [Brooks, M.L., Matchett, J.R., Shinneman, D.J., and Coates, P.S., 2015, Fire patterns in the range of greater sage-grouse, 1984-2013; Implications for conservation and management: U.S. Geological Survey Open-File Report 2015-1167, 66 p., http://dx.doi.org/10.3133/ofr20151167]

This three-band, 30-m resolution raster contains sagebrush vegetation types, soil temperature/moisture regime classes, and large fire frequencies across greater sage-grouse population areas within the Colorado Plateau sage-grouse management zone. Sagebrush vegetation types were defined by grouping together similar vegetation types from the LANDFIRE biophysical settings layer. Soil moisture and temperature regimes were from an USDA-NRCS analysis of soil types across the greater sage-grouse range. Fire frequencies were derived from fire severity rasters created by the Monitoring Trends in Burn Severity program. The area of analysis included the greater sage-grouse populations areas within specific management zones. Methods used to derive these data are detailed in the report [Brooks, M.L., Matchett, J.R., Shinneman, D.J., and Coates, P.S., 2015, Fire patterns in the range of greater sage-grouse, 1984-2013; Implications for conservation and management: U.S. Geological Survey Open-File Report 2015-1167, 66 p., http://dx.doi.org/10.3133/ofr20151167]

This three-band, 30-m resolution raster contains sagebrush vegetation types, soil temperature/moisture regime classes, and large fire frequencies across greater sage-grouse population areas within the Colorado Plateau sage-grouse management zone. Sagebrush vegetation types were defined by grouping together similar vegetation types from the LANDFIRE biophysical settings layer. Soil moisture and temperature regimes were from an USDA-NRCS analysis of soil types across the greater sage-grouse range. Fire frequencies were derived from fire severity rasters created by the Monitoring Trends in Burn Severity program. The area of analysis included the greater sage-grouse populations areas within specific management zones. Methods used to derive these data are detailed in the report [Brooks, M.L., Matchett, J.R., Shinneman, D.J., and Coates, P.S., 2015, Fire patterns in the range of greater sage-grouse, 1984-2013; Implications for conservation and management: U.S. Geological Survey Open-File Report 2015-1167, 66 p., http://dx.doi.org/10.3133/ofr20151167]

This three-band, 30-m resolution raster contains sagebrush vegetation types, soil temperature/moisture regime classes, and large fire frequencies across greater sage-grouse population areas within the Great Plains sage-grouse management zone. Sagebrush vegetation types were defined by grouping together similar vegetation types from the LANDFIRE biophysical settings layer. Soil moisture and temperature regimes were from an USDA-NRCS analysis of soil types across the greater sage-grouse range. Fire frequencies were derived from fire severity rasters created by the Monitoring Trends in Burn Severity program. The area of analysis included the greater sage-grouse populations areas within specific management zones. Methods used to derive these data are detailed in the report [Brooks, M.L., Matchett, J.R., Shinneman, D.J., and Coates, P.S., 2015, Fire patterns in the range of greater sage-grouse, 1984-2013; Implications for conservation and management: U.S. Geological Survey Open-File Report 2015-1167, 66 p., http://dx.doi.org/10.3133/ofr20151167]