Data includes cover and presence (within microsites and 13 m radius plots) of three exotic annual grass, Bromus tectorum, Taeniatherum caput-medusae, and Ventenata dubia and presence (within microsites) of four perennial bunchgrass species (Agropyron cristatum, Pseudoroegneria spicata, Poa secunda, Elymus elymoides) within the first five years after the 2015 Soda wildfire. Additional landscape and weather covariates hypothesized to influence landscape resistance to invasion are included.

Data includes functional group cover of exotic annual grasses, deep rooted perennial grasses, and shallow rooted perennial grasses within the first five years after the 2015 Soda wildfire across different post-fire restoration treatments. Additional landscape and weather covariates hypothesized to influence treatment effectiveness are included.

Data includes functional group cover of exotic annual grasses, deep rooted perennial grasses, and shallow rooted perennial grasses within the first five years after the 2015 Soda wildfire across different post-fire restoration treatments. Additional landscape and weather covariates hypothesized to influence treatment effectiveness are included.

The point data file ("Soda Fire Point and Pasture Data (2016).Point Data.csv") includes 2016 vegetative cover values of exotic annual grass and perennial grass measured within three different types of plots for 75 pastures in the Soda Fire, which burned in 2015: 6m² plot using a grid-point intercept photo software, SamplePoint (Booth et al. 2006), 1m² quadrat using an unguided rapid ocular estimate in the field, 531m² circular plot using an unguided rapid ocular estimate in the field. Smaller plots were nested within larger plots. The pasture data file ("Soda Fire Point and Pasture Data (2016).Pasture Data.csv") includes pasture level metrics of area, elevation, precipitation, slope, heatload, soils, and herbicide treatments within the 75 pastures. Booth, D.T., Cox, S.E., and Berryman, R.D., 2006, Point sampling digital imagery with ‘SamplePoint’, Environmental Monitoring and Assessment, 123 (1-3): 97-108, https://doi.org/10.1007/s10661-005-9164-7.

Data includes functional group cover of exotic annual grasses and deep rooted perennial grasses within the first five years after the 2015 Soda wildfire across different post-fire restoration treatments. Additional landscape and restoration treatment covariates hypothesized to influence post-fire invasive annual grass and perennial grass cover are included.

Data includes functional group cover of exotic annual grasses and deep rooted perennial grasses within the first five years after the 2015 Soda wildfire across different post-fire restoration treatments. Additional landscape and restoration treatment covariates hypothesized to influence post-fire invasive annual grass and perennial grass cover are included.

These rasters represent plant cover during each of the first five growing seasons after fire in the area burned in the 2015 Soda wildfire. Specifically included cover layers are annual herbaceous, perennial herbaceous, shrub, exotic annual grass, and bareground. Training data for each year was collected via grid-point intercept monitoring between April and August. Empirical Bayesian Kriging Regression (EBK regression) was then used to interpolate field training data and create continuous maps of cover. Accuracy for rasters was assessed via independent test data sets collected on the same landscape.

These data provide current and future projected post-fire invasion risk by non-native short-lived grasses and forbs based on vegetation cover data from 26,729 plots in the western United States that burned prior to being sampled. Projected post-fire invasion risk was calculated using random forests with gridded climate, soil, and topographic predictor variables following Prevéy et al. (2024). Projections cover the western United States west of -100 longitude over the current time period (1981-2010), mid-century (2041–2070) and the end of the century (2071–2100) under medium (SSP245) and high (SSP585) greenhouse gas emission scenarios for non-native C3 short-lived grasses and non-native short-lived forbs. Each raster file represents the projected post-fire invasion risk for each non-native functional group ('sl_grass' = short-lived C3 grass, 'sl_forb' = short-lived forb), then the time period (current = 1981-2010, mid = 2041-2071, and late = 2071-2100), and lastly, the emissions scenario (none for current, '245' for SSP245, and '585' for SSP585). For example, 'sl_grass_mid_245.tif' is a raster file showing projected post-fire invasion risk for non-native short-lived C3 grasses for mid-century (2041-2070) under the SSP245 emissions scenario.

These data provide current and future projected post-fire invasion risk by non-native short-lived grasses and forbs based on vegetation cover data from 26,729 plots in the western United States that burned prior to being sampled. Projected post-fire invasion risk was calculated using random forests with gridded climate, soil, and topographic predictor variables following Prevéy et al. (2024). Projections cover the western United States west of -100 longitude over the current time period (1981-2010), mid-century (2041–2070) and the end of the century (2071–2100) under medium (SSP245) and high (SSP585) greenhouse gas emission scenarios for non-native C3 short-lived grasses and non-native short-lived forbs. Each raster file represents the projected post-fire invasion risk for each non-native functional group ('sl_grass' = short-lived C3 grass, 'sl_forb' = short-lived forb), then the time period (current = 1981-2010, mid = 2041-2071, and late = 2071-2100), and lastly, the emissions scenario (none for current, '245' for SSP245, and '585' for SSP585). For example, 'sl_grass_mid_245.tif' is a raster file showing projected post-fire invasion risk for non-native short-lived C3 grasses for mid-century (2041-2070) under the SSP245 emissions scenario.

Cheatgrass (Bromus tectorum) and other invasive annual grasses represent one of the single largest threats to the health and resilience of western rangelands. To address this challenge, the Western Governors Association (WGA)-appointed Western Invasive Species Council convened a cheatgrass working group to develop a new regional vision for invasive annual grass management across the West. Foundational to implementing this new vision is the creation of a common spatial map to guide strategic actions. The WGA cheatgrass working group sought to develop a 30-m base map of annual herbaceous cover to support a common spatial strategy for tackling invasive annual grasses across the western U.S. Here, we leverage three large-scale datasets to provide land managers with a product estimating the recent extent (2016-2018) of annuals across western rangelands. Input annual herbaceous datasets include Rangeland Analysis Platform (Jones et al. 2018), US Geological Survey (USGS) Harmonized Landsat and Sentinel (Pastick et al. 2020, Pastick et al. in prep) and USGS National Land Cover Database (NLCD) (Rigge et al. 2020). These three datasets are combined using a weighted mean approach to generate the final annual herbaceous mean cover product across the sagebrush biome (Jeffries and Finn 2019). References: Jeffries, M.I., and Finn, S.P. 2019. The Sagebrush Biome Range Extent, as Derived from Classified Landsat Imagery: U.S. Geological Survey data release, https://doi.org/10.5066/P950H8HS. Jones, M.O., Allred, B.W., Naugle, D.E., Maestas, J.D., Donnelly, P., Metz, L.J., Karl, J., Smith, R., Bestelmeyer, B., Boyd, C., Kerby, J.D., McIver, J.D. 2018. Innovation in rangeland monitoring: annual, 30m, plant functional type percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9, e02430. https://doi.org/10.1002/ecs2.2430. Pastick, N.J., Dahal, D., Wylie, B.K., Parajuli, S., Boyte, S.P., Wu, Z. 2020. Characterizing Land Surface Phenology and Exotic Annual Grasses in Dryland Ecosystems Using Landsat and Sentinel-2 Data in Harmony. Remote Sens. 12, 725. Pastick, N.J., Dahal, D., Wylie, B.K., Rigge, M.B., Jones, M.O, Allred, B.W., Boyte, S.P., Parajuli, S., and Wu, Z. In prep. Rapid monitoring of the occurrence and spread of exotic annual grasses in the western United States using remote sensing and machine learning. Global Change Biology. Reeves, M., and Mitchell, J. 2011. Extent of Coterminous US Rangelands: Quantifying Implications of Differing Agency Perspectives. Rangeland Ecology and Management 64: 585-597. Rigge, M., Shi, H., Homer, C., Danielson, P., Granneman, B. 2019. Long-term trajectories of fractional component change in the Northern Great Basin, USA. Ecosphere: e02762. Rigge, M., Homer, C., Cleeves, L., Meyer, D., Bunde, B., Shi, H., Xian, G., Bobo, M. 2020. Quantifying Western U.S. Rangelands as Fractional Components with Landsat. Remote Sensing. 12: 412.