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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Habitat modeling is an important tool used to simulate the potential distribution of a species for a variety of basic and applied questions. The desert tortoise (Gopherus agassizii) is a federally listed threatened species in the Mojave Desert and parts of the Sonoran Desert of California, Nevada, Utah, and Arizona. Land managers in this region require reliable information about the potential distribution of desert tortoise habitat to plan conservation efforts, guide monitoring activities, monitor changes in the amount and quality of habitat available, minimize and mitigate disturbances, and ultimately to assess the status of the tortoise and its habitat toward recovery of the species. By applying information from...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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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....
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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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, All tags...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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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....
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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....
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...


map background search result map search result map Final Report: Data provision and projected impact of climate change on fish biodiversity within the Desert LCC Reference period and projected environmental suitability scores-Pinyon-Juniper Reference period and projected environmental suitability scores-Oaks Reference period and projected environmental suitability scores-Mesquite BLM REA SOD 2010 Predicted Habitat of the Desert Tortoise (Gopherus agassizii) BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Branta canadensis BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Alces americanus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Somateria fischeri BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Brachyramphus brevirostris BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Somateria mollissima BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Falco peregrinus BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Ovibos moschatus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Plectrophenax hyperboreus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Limosa lapponica BLM REA SNK 2010 Alaska Gap Analsysis Project: Year Round Distribution Map for Rangifer tarandus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Calidris canutus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Numenius tahitiensis BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Limosa haemastica BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Melanitta nigra BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Ursus americanus BLM REA SOD 2010 Predicted Habitat of the Desert Tortoise (Gopherus agassizii) BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Calidris canutus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Numenius tahitiensis BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Falco peregrinus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Plectrophenax hyperboreus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Limosa haemastica BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Ursus americanus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Branta canadensis BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Alces americanus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Somateria fischeri BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Brachyramphus brevirostris BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Somateria mollissima BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Ovibos moschatus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Limosa lapponica BLM REA SNK 2010 Alaska Gap Analsysis Project: Year Round Distribution Map for Rangifer tarandus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Melanitta nigra Final Report: Data provision and projected impact of climate change on fish biodiversity within the Desert LCC Reference period and projected environmental suitability scores-Pinyon-Juniper Reference period and projected environmental suitability scores-Oaks Reference period and projected environmental suitability scores-Mesquite