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Person

Martin C Holdrege

Student Contractor

Email: mholdrege@usgs.gov

Location
2255 North Gemini Drive
Flagstaff , AZ 86001
US
These data were compiled as a part of a landscape conservation design effort for the sagebrush biome, and are the result of applying a spatially explicit model that assessed geographic patterns in sagebrush ecological integrity and used these results to identify Core Sagebrush Areas (CSAs), Growth Opportunity Areas (GOAs), and Other Rangeland Areas (ORAs). Our overall objective in this study was to characterize geographic patterns in ecological integrity of sagebrush ecosystems. These data represent the estimated integrity of sagebrush ecosystems, estimated from a spatial model that assigns high integrity is areas with abundant big sagebrush and perennial grass/forb cover and with minimal annual grass/forb cover,...
Tags: Arizona, Botany, California, Climatology, Colorado, All tags...
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Understanding how climate change will contribute to ongoing declines in sagebrush ecological integrity is critical for informing natural resource management. We assessed potential future changes in sagebrush ecological integrity under a range of scenarios using an individual plant-based simulation model, integrated with remotely sensed estimates of current sagebrush ecological integrity. The simulation model allowed us to estimate how climate change, wildfire, and invasive annuals interact to alter the potential abundance of key plant functional types that influence sagebrush ecological integrity: sagebrush, perennial grasses, and annual grasses. We provide GeoTIFFs of biome-wide projections of future sagebrush...
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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...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Arizona, Botany, California, Climatology, Colorado, All tags...
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