Filters: Tags: maxent (X) > Types: Map Service (X)
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This layer represents fundamentally suitable and unsuitable habitat for freshwater mussels in the Meramec Basin as modeled by these authors on May 17, 2017 based on spatial data ranging from 1990 to 2014. Identification of habitat characteristics associated with the presence of freshwater mussels is challenging but crucial for the conservation of this declining fauna. Most mussel species are found in multi-species assemblages suggesting that physical factors influence presence similarly across species. In lotic environments, geomorphic and hydraulic characteristics appear to be important factors for predicting mussel presence. We used maximum entropy (MaxEnt) modeling to evaluate hydrogeomorphic variables associated...
Categories: Data,
Data Release - In Progress,
Project;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: MaxEnt,
Meramec,
Missouri,
Ozark,
biota,
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,
The four primary objectives of this project were to: (1) compile a dataset of fish occurrence records for the entirety of the Rio Grande drainage in the US and Mexico; (2) improve that dataset by reformatting dates, synonymizing species names to a modern taxonomy, georeferencing localities, and flagging geographic outliers; (3) for those species with sufficient data for modeling, create species distribution models (SDMs); (4) use the environmental conditions determined via those models to project the species distributions into the future under two climate scenarios. To accomplish those objectives, we compiled 495,101 fish occurrence records mined from 122 original sources into a single database. We then, on the...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Academics & scientific researchers,
Alligator gar,
American eel,
Anguilla rostrata,
Aquatic resource management,
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,
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,
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