Filters: Tags: maxent (X) > partyWithName: U.S. Geological Survey - ScienceBase (X)
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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....
Climatic suitability models and assessments for plant species and communities of the Southwestern US
These data were compiled to assess potential changes in the climatic suitability for 66 species (dominant and associate plant species) and forecast climate exposure for 29 major plant communities within major plant communities in the southwestern United States. An objective of our study was that species within plant communities have unique climate suitability signatures and forecast changes in climatic suitability will not be uniform within the species respective communities or among species within the community. The climate suitability spatial models were developed under a modern baseline (1960-90) and future climate scenario (2041-2060) using Maxent and WorldClim temperature and precipitation variables. Plant...
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,
This raster dataset represents spatially explicit predictions of probability of ignition in the Mojave Desert based on models developed from data on perimeters of fires greater than 405 hectares that burned between 1972 to 2010. Raster resolution equals 30 meters, projection equals UTM Zone 11N.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Grass-fire cycle,
Maxent,
Mojave Desert,
Mojave Desert,
Predictive models,
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...
These data were compiled to forecast climate exposure for 29 major plant communities in the southwestern United States to changing climate under two future climate change scenarios. An objective of our study was that species within plant communities have unique climate suitability signatures and forecast changes in climatic suitability will not be uniform within the species respective communities or among species within the community. We developed these spatial models where climate exposure is represented as a composite score of the climate exposure of characteristic plants for each community. Baseline climate exposure rasters represent a baseline climate change and were developed for current climate conditions...
These point data (lat long coordinates) represent pixel centers for three woody ecosystem types found in Texas, Oklahoma and New Mexico. Points were extracted from the publicly available LANDFIRE Fire Environmental Site Potential (ESP) raster that we downgraded from 30 m to 1 km pixels. The three data sets include: Oak ESP occurrence points.csv; Mesquite ESP occurrence points; and Pinyon-juniper ESP occurrence points
Categories: Data;
Tags: Climate Change,
Environmental Site Potential,
Environmental Suitability Models,
LANDFIRE,
MAXENT,
This dataset comprises high-resolution geotif files representing various aspects of the ʻākohekohe (Palmeria dolei) potential habitat on the Island of Hawaiʻi. It includes a habitat suitability map showing average suitability scores, a map of homogenous forested areas (HFAs) depicting clusters with consistent suitability scores, and a map of pixel-wise standard deviation across habitat suitability models. These maps were generated through a comprehensive analysis using lidar-based metrics, offering detailed insights into the habitat preferences of ʻākohekohe.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Assisted colonization,
Climate Change,
Conservation Introduction,
Endangered Species,
Hawaii,
These data were compiled to assess potential changes in the climatic suitability for 66 species (dominant and associate plant species) within major plant communities in the southwestern United States. An objective of our study was that species within plant communities have unique climate suitability signatures and forecast changes in climatic suitability will not be uniform within the species respective communities or among species within the community. We developed these spatial models of climate suitability under a modern baseline (1960-90) and future climate scenario (2041-2060) using Maxent and WorldClim temperature and precipitation variables. Plant species were chosen that are characteristic species of plant...
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