Proportion of agricultural land cover within 18-km radius developed using a circular focal moving window analysis.

Location of agricultural land cover obtained from the LANDFIRE Existing Vegetation Type dataset

Location of agricultural land cover obtained from the LANDFIRE Existing Vegetation Type dataset

Agricultural land cover for the western United States. This dataset was developed from Sagestitch, the Eastern Washington Shrubsteppe Mapping Project, and several state level GAP products (AZ, CA, NM, OR, and WA).

Agricultural land cover for the western United States. This dataset was developed from Sagestitch, the Eastern Washington Shrubsteppe Mapping Project, and several state level GAP products (AZ, CA, NM, OR, and WA).

This raster data depicts the modeled distribution of three grassland states: Biocrust, Grass-bare, and Annualized-bare. We developed models of bare ground, total vegetation, exotic grasses and biological soil crust using spectral data from three year composites of growing season (March-October) Landsat data in Google Earth Engine and field data that were collected over the same period at monitoring sites. The resulting regression models were used to characterize the spatial distribution of putative grassland ecological states across our 251,430 ha study area in and around Canyonlands National Park, UT. This model illustrates how a remote sensing approach to land-cover change can be implemented to guide dryland ecosystem management actions such as monitoring, livestock management, and restoration.

This raster data depicts the modeled distribution of three grassland states: Biocrust, Grass-bare, and Annualized-bare. We developed models of bare ground, total vegetation, exotic grasses and biological soil crust using spectral data from three year composites of growing season (March-October) Landsat data in Google Earth Engine and field data that were collected over the same period at monitoring sites. The resulting regression models were used to characterize the spatial distribution of putative grassland ecological states across our 251,430 ha study area in and around Canyonlands National Park, UT. This model illustrates how a remote sensing approach to land-cover change can be implemented to guide dryland ecosystem management actions such as monitoring, livestock management, and restoration.

The file 'ssm_data_3.25.csv' contains data necessary for analyzing state-space models for male greater sage-grouse (Centrocercus urophasianus) populations in response to grazing level (relative grazing index), timing, and NDVI (Normalized Difference Vegetation Index) in Wyoming, USA. In this case, all covariates were measured within 3.25 km of lek sites.

The file 'ssm_data_3.25.csv' contains data necessary for analyzing state-space models for male greater sage-grouse (Centrocercus urophasianus) populations in response to grazing level (relative grazing index), timing, and NDVI (Normalized Difference Vegetation Index) in Wyoming, USA. In this case, all covariates were measured within 3.25 km of lek sites.

The importance of monitoring shrublands to detect and understand changes through time is increasingly recognized as critical to management. This dataset focuses on ecological change observation over ten years of field observation at 134 plots within two sites that are located in Southwestern of Wyoming, USA from 2008-2018. At sites 1 and 3, 134 long-term field observation plots were measured annually from 2008 to 2018. General plot locations were selected in 2006 using segments and spectral clusters on QuickBird imagery to identify the best locations for representing the variability of the entire site (one QuickBird image). Ground measurements were conducted using ocular measurements with cover was estimated from an overhead perspective (satellite), with the total cover of all vegetation and bare ground components summing to 100%. Ground measurements were conducted annually on the same approximate dates, and plot measurements were conducted by the same two individuals over the same plots every year to minimize observer bias. Five shrub components were measured that included shrub cover, sage cover, herbaceous, litter, and bare ground.