Folders: ROOT > ScienceBase Catalog > National and Regional Climate Adaptation Science Centers > South Central CASC > FY 2014 Projects > Understanding Future Fire Frequency and Impacts on Species Distribution in the South Central U.S. > Approved DataSets ( Show direct descendants )
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ROOT _ScienceBase Catalog __National and Regional Climate Adaptation Science Centers ___South Central CASC ____FY 2014 Projects _____Understanding Future Fire Frequency and Impacts on Species Distribution in the South Central U.S. ______Approved DataSets Filters
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These data were generated with MAXENT 3.3.3k freeware (Phillips et al. 2011) using climate data and fire probability data for for three time periods: reference (1900-1929), mid-century (2040-2069) and late century (2070-2099), and community occurrence point data extracted from LANDFIRE Environmental Site Potential (ESP). Future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. In MAXENT, we used the logistic output format (generating presence probabilities between 0 and 1), a random test percentage of 30 (using 70 % of the occurrence points to generate the suitability model and 30 % of the occurrence points to validate it), and a jackknife test to measure variable importance....
These data were generated with MAXENT 3.3.3k freeware (Phillips et al. 2011) using climate data and fire probability data for for three time periods: reference (1900-1929), mid-century (2040-2069) and late century (2070-2099), and community occurrence point data extracted from LANDFIRE Environmental Site Potential (ESP). Future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. In MAXENT, we used the logistic output format (generating presence probabilities between 0 and 1), a random test percentage of 30 (using 70 % of the occurrence points to generate the suitability model and 30 % of the occurrence points to validate it), and a jackknife test to measure variable importance....
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Climate Change,
Drought, Fire and Extreme Weather,
Environmental Suitability Models,
Fire,
LANDFIRE,
These data were generated with MAXENT 3.3.3k freeware (Phillips et al. 2011) using climate data and fire probability data for for three time periods: reference (1900-1929), mid-century (2040-2069) and late century (2070-2099), and community occurrence point data extracted from LANDFIRE Environmental Site Potential (ESP). Future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. In MAXENT, we used the logistic output format (generating presence probabilities between 0 and 1), a random test percentage of 30 (using 70 % of the occurrence points to generate the suitability model and 30 % of the occurrence points to validate it), and a jackknife test to measure variable importance....
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Climate Change,
Drought, Fire and Extreme Weather,
Environmental Suitability Models,
Fire,
LANDFIRE,
These data were generated with MAXENT 3.3.3k freeware (Phillips et al. 2011) using climate data and fire probability data for for three time periods: reference (1900-1929), mid-century (2040-2069) and late century (2070-2099), and community occurrence point data extracted from LANDFIRE Environmental Site Potential (ESP). Future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. In MAXENT, we used the logistic output format (generating presence probabilities between 0 and 1), a random test percentage of 30 (using 70 % of the occurrence points to generate the suitability model and 30 % of the occurrence points to validate it), and a jackknife test to measure variable importance....
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Climate Change,
Drought, Fire and Extreme Weather,
Environmental Suitability Models,
Fire,
LANDFIRE,
Three .csv files contain occurrence points (longitude and latitude) for three woody vegetation communities found in Texas, Oklahoma and New Mexico. Points were extracted from publicly available LANDFIRE Environmental Site Potential 30 m raster downgraded to 1 km using a majority classification algorithm. The three communities are an oak type (dominated by Quercus stellata and Q. marilandica), a mesquite type (dominated by Prosopis glandulosa and P. velutina), and a pinyon-juniper type (dominated by Pinus edulis and Juniperus osteosperma). The 21 rasters contain environmental suitability scores for each of the three communities, generated with MAXENT freeware using historic and projected climate and fire probability...
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