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Emerging applications of ecosystem resilience and resistance concepts in sagebrush ecosystems allow managers to better predict and mitigate impacts of wildfire and invasive annual grasses. Soil temperature and moisture strongly influence the kind and amount of vegetation, and consequently, are closely tied to sagebrush ecosystem resilience and resistance (Chambers et al. 2014, 2016). Soil taxonomic temperature and moisture regimes can be used as indicators of resilience and resistance at landscape scales to depict environmental gradients in sagebrush ecosystems that range from cold/cool-moist sites to warm-dry sites. We aggregated soil survey spatial and tabular data to facilitate broad-scale analyses of resilience...
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We conducted a study to test the factors related to detectability of two invasive aquatic plants (Egeria densa and Myriophyllym spicatum) using environmental DNA (eDNA), over extended periods of time, and specifically examined how plant growth stage and abundance relates to eDNA detection in semi-natural and natural conditions. This dataset is from sampling performed in summer of 2018 in lakes with varying species abundances, and a subset of lakes were re-sampled to test temporal variability in detection.
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Values represent percent of surrounding landscape (5K) are dominated by sagebrush cover. Reclassified LANDFIRE 2013 Existing Vegetation Type by selecting the ecological systems containing sagebrush (Codes: 2080, 2125, 2126, 2220, 2064, 2072, 2079, 2124) to create a binary raster dataset with 1 for the sagebrush land cover types and zero for all others.To incorporate sagebrush lost to fire in fires since the Landsat was flown in 2010 that Landfire was derived from, I used fire perimeters from 2011,2012, & 2013 to reclassify pixels designated as having sagebrush as 0 (not having sagebrush), which assumes a homogenous burn (in reality there may be patches of sagebrush left within a burn perimeter). I then ran focalsum...
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Reclassed areas of just sagebrush (1) and no sagebrush (0, areas with originally no sagebrush or recently burned areas). Landfire codes were: 2080, 2125, 2126, 2220, 2064, 2072, 2079, 2124) This layer is an intermediate layer used to create a sagebrush landscape cover layer using a moving window analysis. See Landfire metadata for an assessment of that data. See WFDSS, GEOMAC and MTBS fire metadata for more information on those data
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This dataset represents the extent of urbanization (for the year indicated) predicted by the model SLEUTH, developed by Dr. Keith C. Clarke, at the University of California, Santa Barbara, Department of Geography and modified by David I. Donato of the United States Geological Survey (USGS) Eastern Geographic Science Center (EGSC). Further model modification and implementation was performed at the Biodiversity and Spatial Information Center at North Carolina State University.Urban growth probability extents throughout the 21st century were projected for the Southeast Regional Assessment Project (SERAP), which encompasses all or parts of the states of Alabama, Arkansas, Florida, Georgia, Illinois, Indiana, Kentucky,...
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Emerging applications of ecosystem resilience and resistance concepts in sagebrush ecosystems allow managers to better predict and mitigate impacts of wildfire and invasive annual grasses. Soil temperature and moisture strongly influence the kind and amount of vegetation, and consequently, are closely tied to sagebrush ecosystem resilience and resistance (Chambers et al. 2014). Soil taxonomic temperature and moisture regimes can be used as indicators of resilience and resistance at landscape scales to depict environmental gradients in sagebrush ecosystems that range from cold/cool-moist sites to warm-dry sites. We aggregated soil survey spatial and tabular data to facilitate broad-scale analyses of resilience and...
Emerging applications of ecosystem resilience and resistance concepts in sagebrush ecosystems allow managers to better predict and mitigate impacts of wildfire and invasive annual grasses. Soil temperature and moisture strongly influence the kind and amount of vegetation, and consequently, are closely tied to sagebrush ecosystem resilience and resistance (Chambers et al. 2014, 2016). Soil taxonomic temperature and moisture regimes can be used as indicators of resilience and resistance at landscape scales to depict environmental gradients in sagebrush ecosystems that range from cold/cool-moist sites to warm-dry sites. We aggregated soil survey spatial and tabular data to facilitate broad-scale analyses of resilience...
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This dataset represents the extent of urbanization (for the year indicated) predicted by the model SLEUTH, developed by Dr. Keith C. Clarke, at the University of California, Santa Barbara, Department of Geography and modified by David I. Donato of the United States Geological Survey (USGS) Eastern Geographic Science Center (EGSC). Further model modification and implementation was performed at the Biodiversity and Spatial Information Center at North Carolina State University.
Emerging applications of ecosystem resilience and resistance concepts in sagebrush ecosystems allow managers to better predict and mitigate impacts of wildfire and invasive annual grasses. Soil temperature and moisture strongly influence the kind and amount of vegetation, and consequently, are closely tied to sagebrush ecosystem resilience and resistance (Chambers et al. 2014). Soil taxonomic temperature and moisture regimes can be used as indicators of resilience and resistance at landscape scales to depict environmental gradients in sagebrush ecosystems that range from cold/cool-moist sites to warm-dry sites. We aggregated soil survey spatial and tabular data to facilitate broad-scale analyses of resilience and...
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Emerging applications of ecosystem resilience and resistance concepts in sagebrush ecosystems allow managers to better predict and mitigate impacts of wildfire and invasive annual grasses. Soil temperature and moisture strongly influence the kind and amount of vegetation, and consequently, are closely tied to sagebrush ecosystem resilience and resistance (Chambers et al. 2014, 2016). Soil taxonomic temperature and moisture regimes can be used as indicators of resilience and resistance at landscape scales to depict environmental gradients in sagebrush ecosystems that range from cold/cool-moist sites to warm-dry sites. We aggregated soil survey spatial and tabular data to facilitate broad-scale analyses of resilience...
Emerging applications of ecosystem resilience and resistance concepts in sagebrush ecosystems allow managers to better predict and mitigate impacts of wildfire and invasive annual grasses. Soil temperature and moisture strongly influence the kind and amount of vegetation, and consequently, are closely tied to sagebrush ecosystem resilience and resistance (Chambers et al. 2014, 2016). Soil taxonomic temperature and moisture regimes can be used as indicators of resilience and resistance at landscape scales to depict environmental gradients in sagebrush ecosystems that range from cold/cool-moist sites to warm-dry sites. We aggregated soil survey spatial and tabular data to facilitate broad-scale analyses of resilience...
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This dataset represents the extent of urbanization (for the year indicated) predicted by the model SLEUTH, developed by Dr. Keith C. Clarke, at the University of California, Santa Barbara, Department of Geography and modified by David I. Donato of the United States Geological Survey (USGS) Eastern Geographic Science Center (EGSC). Further model modification and implementation was performed at the Biodiversity and Spatial Information Center at North Carolina State University.Urban growth probability extents throughout the 21st century were projected for the Southeast Regional Assessment Project (SERAP), which encompasses all or parts of the states of Alabama, Arkansas, Florida, Georgia, Illinois, Indiana, Kentucky,...


    map background search result map search result map Dataset: Sagebrush MW5k Percent SLEUTH Projected Urban Growth Dataset: Index of Relative Ecosystem Resilience and Resistance across Sage-Grouse Management Zones SLEUTH Urbanization 2020-2100 Urban Growth Projection for DSL-SAMBI Sagebrush MW5k Percent Detection of invasive aquatic plants Myriophyllum spicatum and Egeria densa in lakes using eDNA, field and mesocosm data Detection of invasive aquatic plants Myriophyllum spicatum and Egeria densa in lakes using eDNA, field and mesocosm data SLEUTH Urbanization 2020-2100 Urban Growth Projection for DSL-SAMBI Dataset: Index of Relative Ecosystem Resilience and Resistance across Sage-Grouse Management Zones Dataset: Sagebrush MW5k Percent Sagebrush MW5k Percent SLEUTH Projected Urban Growth