Data

Genetic networks can characterize complex genetic relationships among groups of individuals, which can be used to rank nodes most important to the overall connectivity of the system. Ranking allows scarce resources to be guided towards nodes integral to connectivity. The greater sage-grouse (Centrocercus urophasianus) is a species of conservation concern that breeds on spatially discrete leks that

These data represent predicted common raven (Corvus corax) density (ravens/square-km) derived from random forest models given field site unit-specific estimates of raven density that were obtained from hierarchical distance sampling models at 43 field site units within the Great Basin region, USA. Fifteen landscape-level predictors summarizing climate, vegetation, topography and anthropogenic foot

Conservation planning efforts for sagebrush ecosystems of western North America increasingly focus on enhancing operational resilience though decision-support tools that link spatially explicit variation in soil and plant processes to outcomes of biotic and abiotic disturbances spanning large spatial extents. However, failure to consider higher trophic-level fauna (e.g. wildlife) in these tools ca

In 'Predicted (1989-2015) and forecasted (2015-2114) estimates for rate of change and recovery of sagebrush (Artemisia spp.) following energy development in southwestern Wyoming, USA', we provide spatially- and temporally-explicit maps of predictions for the rate of change and time to recovery and percent recovery of sagebrush cover after 100 years (Monroe et al. In Review). The rasters beginning

This dataset contains information on the survival of individual sagebrush seedlings, stands of seedlings and the vegetative and topographic conditions in which they were planted.

We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies

This dataset consists of historical estimates and future projections of land use and climate data summarized within the 1:100,000 National Hydrography Dataset Version 2 (NHDPlusV2) framework for catchments and upstream accumulated watersheds. Historical land use data are for the year 2005 and future land use projections are for the years 2030, 2060, and 2090. The projections offer a unique combina

The files in this data release are the raw DNA metagenome sequence files referenced in Chapter 2 of the Bureau of Ocean Energy Management Environmental Studies Program Report entitled "Multidisciplinary Assessment of Deep-Water Coral Ecosystems: Tools to Detect Impacts of Sub-lethal Stress." Chapter 2, written by Christina A. Kellogg, is entitled "Deep-Sea Coral Metagenomes." The files represent a

In 2015, approximately 10 million acres of Federal lands across six western states were proposed for withdrawal from mineral entry by the Bureau of Land Management (BLM) in order to conserve habitat critical for the greater sage-grouse. As a result, the U.S. Geological Survey (USGS) launched the Sagebrush Mineral Resource Assessment (SaMiRA) project in late-2015 to provide BLM with an assessment o

This dataset provides a near-real-time estimate of 2019 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015. Rangelands 38:278-284.) This estimate was based on remotely sensed enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) data g

These data depict reptile species richness within the range of the Greater Sage-grouse. Species boundaries were defined as the total extent of a species geographic limits. This raster largely used species range data from "U.S. Geological Survey - Gap Analysis Project Species Range Maps CONUS_2001", however in order for a more complete picture of species richness, additional sources were used for s

The dataset provides a spatially explicit estimate of 2019 herbaceous annual percent cover predicted on May 1st with an emphasis on annual grasses. The estimate is based on the mean output of two regression-tree models. For one model, we include, as an independent variable amongst other independent variables, a dataset that is the mean of 17-years of annual herbaceous percent cover (https://doi.or