We evaluated sagebrush on 24 post-fire seeding sites encompassing >50,000 acres on the Snake River Plain in the Northern Great Basin, specifically in Southwest Idaho. Sites were initially identified using the Land Treatment Digital Library (LTDL; http://greatbasin.wr.usgs.gov/ltdl/; and Inciweb fire information (http://inciweb.nwcg.gov/) websites to identify seeding projects located in predominantly Wyoming big sagebrush sites (2,500 to 4,000 feet ASL; 2 sites also had A.t. vaseyana, 2 other sites had only A.t. vaseyana) that 1) had burned and were seeded within the year following fire, from 1987-2010, 2) but had not burned since, and 3) had information on seed sources. Standard USDA species abbreviations are used.

This dataset contains observations used to better understand the initial establishment of sagebrush (Artemisia sp.), in the first 1-2 years post-wildfire. Field data come from 460 sagebrush populations sampled across the Great Basin and many GIS-derived co-variates are included as well.

This dataset contains observations used to better understand the initial establishment of sagebrush (Artemisia sp.), in the first 1-2 years post-wildfire. Field data come from 460 sagebrush populations sampled across the Great Basin and many GIS-derived co-variates are included as well.

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 dataset contains information on seedling survival, physiochemical, morphological, and eco-physiological characteristics of seedlings grown and planted from seed collected from different sagebrush populations as well as the climatic conditions of those seed source sites in relation to the common garden location in which they were planted.

This dataset contains information on seedling survival, physiochemical, morphological, and eco-physiological characteristics of seedlings grown and planted from seed collected from different sagebrush populations as well as the climatic conditions of those seed source sites in relation to the common garden location in which they were planted.

The dataset includes several variables sampled across burned and unburned sagebrush communities located in a ~30 square kilometer portion of the Columbia Plateau Ecoregion in eastern Washington, USA. The study area is characterized by landforms interspersed at fine-scales, representative of the channeled scabland topography of the region (Baker 2009), including: “mounds,” which are dome-like micro-topographic features, typically 1-2 m in height and ~2 m to 25 m in mean diameter, with relatively deep, well-drained loess soils; and surrounding “flats,” with rocky, thin-soils over basaltic bedrock. Unburned mounds are typically dominated by big sagebrush (A. tridentata) and flats by scabland sagebrush (A. rigida) communities. We used a stratified-random sampling design to select potential sites across the study area based on two primary strata: 1) landform-community type (i.e. big sagebrush mounds and scabland sagebrush flats); and 2) recent fire frequency, including unburned, once- (2012), twice- (2003, 2012), and thrice-burned (2003, 2007, 2012) areas. A total of 80 sites (10 sites X two landforms X four burned strata) were sampled in 2016. Vegetation sampling was conducted at each site within a 10 x 10 m plot, a size and shape deemed optimal for the small landforms. Within each plot we measured several vegetation characteristics as outlined in the Data Quality Section.