AndreaBozzo/ceres-open-data-index huggingface dataset:
Broad-Footed Mole Range - CWHR M018 [ds1814]

<div style='text-align:Left;'><div><div><p style='margin:0 0 14 0;'><span><span>Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for California's wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (</span><a href='https://www.wildlife.ca.gov/Data/CWHR' style='text-decoration:underline;' rel='nofollow ugc'><span>https://www.wildlife.ca.gov/Data/CWHR</span></a><span>). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.</span></span></p></div></div></div>

Tags: Auth_CDFW, Broad-Footed Mole, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1814_20160616_wm, Scapanus latimanus, habitat, mammal, natural resources, species, wildlife
Organization: California Department of Fish and Wildlife
Yellow-billed Magpie Habitat Model for NSNF Connectivity - CDFW [ds1056]

The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al. 2006). Species occurrence points were primarily obtained from CNDDB (California Natural Diversity Database) and other CDFW sources, GBIF (Global Biodiversity Information Facility), PRBO (Point Blue Conservation Science) and Arctos museum databases. Vegetation, distance to water, elevation, and bioclimatic variables (Franklin et al. 2013) were used as predictor variables. The models were run at 270 m spatial resolution with five replications using cross-validation as a method of sample evaluation. Cross-validation involved the partitioning of the sample data into n subsets, fitting the models to n-1subsets, and testing the model on the one subset not used in fitting the model. Initial model runs showed that our models converged around 2,000 iterations and for this reason we ran all models with 2,500 maximum iterations. Maxent was implemented in R using the ‘dismo''package (Hijmans et al. 2011). Model evaluation was carried out using the ‘PresenceAbsence''package in R (Freeman and Moisen 2008). We used AUC as a metric to evaluate model performance. The package also computes threshold values using several accuracy metrics to translate predicted probability maps into binary suitable and unsuitable habitats. We selected the MeanProb, a threshold set based on the mean predicted probability of species occurrences. The output from Maxent are grid datasets in a multiband ‘tif''format with one band for each replication. We averaged the five replicated maps and created a mean grid for each species. The grid was then symbolized to represent low (threshold-50), medium (50-75) and high (75-100) habitat suitability, with pixel values that are below the threshold excluded. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1056_20141006_wm, bird, cn Yellow-billed Magpie, connectivity modeling, habitat modeling, sn Pica nuttalli
Organization: California Department of Fish and Wildlife
Western Pond Turtle Habitat Model for NSNF Connectivity - CDFW [ds1055]

The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al. 2006). Species occurrence points were primarily obtained from CNDDB (California Natural Diversity Database) and other CDFW sources, GBIF (Global Biodiversity Information Facility), PRBO (Point Blue Conservation Science) and Arctos museum databases. Vegetation, distance to water, elevation, and bioclimatic variables (Franklin et al. 2013) were used as predictor variables. The models were run at 270 m spatial resolution with five replications using cross-validation as a method of sample evaluation. Cross-validation involved the partitioning of the sample data into n subsets, fitting the models to n-1subsets, and testing the model on the one subset not used in fitting the model. Initial model runs showed that our models converged around 2,000 iterations and for this reason we ran all models with 2,500 maximum iterations. Maxent was implemented in R using the ‘dismo''package (Hijmans et al. 2011). Model evaluation was carried out using the ‘PresenceAbsence''package in R (Freeman and Moisen 2008). We used AUC as a metric to evaluate model performance. The package also computes threshold values using several accuracy metrics to translate predicted probability maps into binary suitable and unsuitable habitats. We selected the MeanProb, a threshold set based on the mean predicted probability of species occurrences. The output from Maxent are grid datasets in a multiband ‘tif''format with one band for each replication. We averaged the five replicated maps and created a mean grid for each species. The grid was then symbolized to represent low (threshold-50), medium (50-75) and high (75-100) habitat suitability, with pixel values that are below the threshold excluded. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1055_20141006_wm, cn Western Pond Turtle, connectivity modeling, habitat modeling, reptile, sn Actinemys marmorata
Organization: California Department of Fish and Wildlife
Red Sesbania Distribution - lines [ds81]

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This layer conatains line data for the red sesbania (Sesbania punicea) database. The database represents historic and current observations by various individuals of occurrences of red sesbania, a non-native invasive plant that currently is invading riparian ecosystems in California. Most occurrences are in the Central Valley, but a few are in the San Francisco Bay area and in a few watersheds to the north. These data were compiled to aid in the eradication and control of the species where it is invasive, as well as to inform the public of its spread. As of February 1, 2006, there were 25 records of linear occurrences maintained in an Access database titled SesbaniaData. Each record represents a line, or linear scattered occurrence of red sesbania.</SPAN></P></DIV></DIV></DIV>

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS0081_20060706_wm, cn Red sesbiana, distribution, invasive, inventory, management, monitoring, plant, sn Sesbania punicea
Organization: California Department of Fish and Wildlife
Wood Duck Habitat Model for NSNF Connectivity - CDFW [ds1054]

The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al. 2006). Species occurrence points were primarily obtained from CNDDB (California Natural Diversity Database) and other CDFW sources, GBIF (Global Biodiversity Information Facility), PRBO (Point Blue Conservation Science) and Arctos museum databases. Vegetation, distance to water, elevation, and bioclimatic variables (Franklin et al. 2013) were used as predictor variables. The models were run at 270 m spatial resolution with five replications using cross-validation as a method of sample evaluation. Cross-validation involved the partitioning of the sample data into n subsets, fitting the models to n-1subsets, and testing the model on the one subset not used in fitting the model. Initial model runs showed that our models converged around 2,000 iterations and for this reason we ran all models with 2,500 maximum iterations. Maxent was implemented in R using the ‘dismo''package (Hijmans et al. 2011). Model evaluation was carried out using the ‘PresenceAbsence''package in R (Freeman and Moisen 2008). We used AUC as a metric to evaluate model performance. The package also computes threshold values using several accuracy metrics to translate predicted probability maps into binary suitable and unsuitable habitats. We selected the MeanProb, a threshold set based on the mean predicted probability of species occurrences. The output from Maxent are grid datasets in a multiband ‘tif''format with one band for each replication. We averaged the five replicated maps and created a mean grid for each species. The grid was then symbolized to represent low (threshold-50), medium (50-75) and high (75-100) habitat suitability, with pixel values that are below the threshold excluded. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1054_20141006_wm, bird, cn Wood Duck, connectivity modeling, habitat modeling, sn Aix sponsa
Organization: California Department of Fish and Wildlife
Western Gray Squirrel Habitat Model for NSNF Connectivity - CDFW [ds1053]

The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al. 2006). Species occurrence points were primarily obtained from CNDDB (California Natural Diversity Database) and other CDFW sources, GBIF (Global Biodiversity Information Facility), PRBO (Point Blue Conservation Science) and Arctos museum databases. Vegetation, distance to water, elevation, and bioclimatic variables (Franklin et al. 2013) were used as predictor variables. The models were run at 270 m spatial resolution with five replications using cross-validation as a method of sample evaluation. Cross-validation involved the partitioning of the sample data into n subsets, fitting the models to n-1subsets, and testing the model on the one subset not used in fitting the model. Initial model runs showed that our models converged around 2,000 iterations and for this reason we ran all models with 2,500 maximum iterations. Maxent was implemented in R using the ‘dismo''package (Hijmans et al. 2011). Model evaluation was carried out using the ‘PresenceAbsence''package in R (Freeman and Moisen 2008). We used AUC as a metric to evaluate model performance. The package also computes threshold values using several accuracy metrics to translate predicted probability maps into binary suitable and unsuitable habitats. We selected the MeanProb, a threshold set based on the mean predicted probability of species occurrences. The output from Maxent are grid datasets in a multiband ‘tif''format with one band for each replication. We averaged the five replicated maps and created a mean grid for each species. The grid was then symbolized to represent low (threshold-50), medium (50-75) and high (75-100) habitat suitability, with pixel values that are below the threshold excluded. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1053_20141006_wm, cn Western Gray Squirrel, connectivity modeling, habitat modeling, mammal, sn Sciurus griseus
Organization: California Department of Fish and Wildlife
Spotted Towhee Habitat Model for NSNF Connectivity - CDFW [ds1052]

This grid represents habitat suitability based on the California Wildlife Habitat Relationships (CWHR) expert opinion habitat suitability rankings by habitat type. Habitat suitability rankings (ranging 0-100) for each combination of habitat type, size class (dbh) and cover class (density) were applied to the 30 m vegetation grid using CWHRs Bioview. These values were then averaged across grid cells to create a 270 m grid consistent with that used in the Maxent models for the project. The grid was then symbolized to represent low (0-50), medium (50-75) and high (75-100) habitat suitability. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1052_20141006_wm, bird, cn Spotted Towhee, connectivity modeling, habitat modeling, sn Pipilo maculatus
Organization: California Department of Fish and Wildlife
Southern Alligator Lizard Habitat Model for NSNF Connectivity - CDFW [ds1051]

The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al. 2006). Species occurrence points were primarily obtained from CNDDB (California Natural Diversity Database) and other CDFW sources, GBIF (Global Biodiversity Information Facility), PRBO (Point Blue Conservation Science) and Arctos museum databases. Vegetation, distance to water, elevation, and bioclimatic variables (Franklin et al. 2013) were used as predictor variables. The models were run at 270 m spatial resolution with five replications using cross-validation as a method of sample evaluation. Cross-validation involved the partitioning of the sample data into n subsets, fitting the models to n-1subsets, and testing the model on the one subset not used in fitting the model. Initial model runs showed that our models converged around 2,000 iterations and for this reason we ran all models with 2,500 maximum iterations. Maxent was implemented in R using the ‘dismo''package (Hijmans et al. 2011). Model evaluation was carried out using the ‘PresenceAbsence''package in R (Freeman and Moisen 2008). We used AUC as a metric to evaluate model performance. The package also computes threshold values using several accuracy metrics to translate predicted probability maps into binary suitable and unsuitable habitats. We selected the MeanProb, a threshold set based on the mean predicted probability of species occurrences. The output from Maxent are grid datasets in a multiband ‘tif''format with one band for each replication. We averaged the five replicated maps and created a mean grid for each species. The grid was then symbolized to represent low (threshold-50), medium (50-75) and high (75-100) habitat suitability, with pixel values that are below the threshold excluded. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1051_20141006_wm, cn Southern Alligator Lizard, connectivity modeling, habitat modeling, reptile, sn Elgaria multicarinata
Organization: California Department of Fish and Wildlife
Pallid Bat Habitat Model for NSNF Connectivity -  CDFW [ds1049]

This grid represents habitat suitability based on the California Wildlife Habitat Relationships (CWHR) expert opinion habitat suitability rankings by habitat type. Habitat suitability rankings (ranging 0-100) for each combination of habitat type, size class (dbh) and cover class (density) were applied to the 30 m vegetation grid using CWHRs Bioview. These values were then averaged across grid cells to create a 270 m grid consistent with that used in the Maxent models for the project. The grid was then symbolized to represent low (0-50), medium (50-75) and high (75-100) habitat suitability. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1049_20141006_wm, cn Pallid Bat, connectivity modeling, habitat modeling, mammal, sn Antrozous pallidus
Organization: California Department of Fish and Wildlife
Racer Habitat Model for NSNF Connectivity - CDFW [ds1050]

This grid represents habitat suitability based on the California Wildlife Habitat Relationships (CWHR) expert opinion habitat suitability rankings by habitat type. Habitat suitability rankings (ranging 0-100) for each combination of habitat type, size class (dbh) and cover class (density) were applied to the 30 m vegetation grid using CWHRs Bioview. These values were then averaged across grid cells to create a 270 m grid consistent with that used in the Maxent models for the project. The grid was then symbolized to represent low (0-50), medium (50-75) and high (75-100) habitat suitability. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1050_20141006_wm, __, cn Racer, connectivity modeling, habitat modeling
Organization: California Department of Fish and Wildlife
Northern Pygmy Owl Habitat Model for NSNF Connectivity - CDFW [ds1048]

The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al. 2006). Species occurrence points were primarily obtained from CNDDB (California Natural Diversity Database) and other CDFW sources, GBIF (Global Biodiversity Information Facility), PRBO (Point Blue Conservation Science) and Arctos museum databases. Vegetation, distance to water, elevation, and bioclimatic variables (Franklin et al. 2013) were used as predictor variables. The models were run at 270 m spatial resolution with five replications using cross-validation as a method of sample evaluation. Cross-validation involved the partitioning of the sample data into n subsets, fitting the models to n-1subsets, and testing the model on the one subset not used in fitting the model. Initial model runs showed that our models converged around 2,000 iterations and for this reason we ran all models with 2,500 maximum iterations. Maxent was implemented in R using the ‘dismo''package (Hijmans et al. 2011). Model evaluation was carried out using the ‘PresenceAbsence''package in R (Freeman and Moisen 2008). We used AUC as a metric to evaluate model performance. The package also computes threshold values using several accuracy metrics to translate predicted probability maps into binary suitable and unsuitable habitats. We selected the MeanProb, a threshold set based on the mean predicted probability of species occurrences. The output from Maxent are grid datasets in a multiband ‘tif''format with one band for each replication. We averaged the five replicated maps and created a mean grid for each species. The grid was then symbolized to represent low (threshold-50), medium (50-75) and high (75-100) habitat suitability, with pixel values that are below the threshold excluded. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1048_20141006_wm, bird, cn Northern Pygmy Owl, connectivity modeling, habitat modeling, sn Glaucidium californicum
Organization: California Department of Fish and Wildlife
Mule Deer Habitat Model for NSNF Connectivity - CDFW [ds1047]

The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al. 2006). Species occurrence points were primarily obtained from CNDDB (California Natural Diversity Database) and other CDFW sources, GBIF (Global Biodiversity Information Facility), PRBO (Point Blue Conservation Science) and Arctos museum databases. Vegetation, distance to water, elevation, and bioclimatic variables (Franklin et al. 2013) were used as predictor variables. The models were run at 270 m spatial resolution with five replications using cross-validation as a method of sample evaluation. Cross-validation involved the partitioning of the sample data into n subsets, fitting the models to n-1subsets, and testing the model on the one subset not used in fitting the model. Initial model runs showed that our models converged around 2,000 iterations and for this reason we ran all models with 2,500 maximum iterations. Maxent was implemented in R using the ‘dismo''package (Hijmans et al. 2011). Model evaluation was carried out using the ‘PresenceAbsence''package in R (Freeman and Moisen 2008). We used AUC as a metric to evaluate model performance. The package also computes threshold values using several accuracy metrics to translate predicted probability maps into binary suitable and unsuitable habitats. We selected the MeanProb, a threshold set based on the mean predicted probability of species occurrences. The output from Maxent are grid datasets in a multiband ‘tif''format with one band for each replication. We averaged the five replicated maps and created a mean grid for each species. The grid was then symbolized to represent low (threshold-50), medium (50-75) and high (75-100) habitat suitability, with pixel values that are below the threshold excluded. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: Auth_CDFW, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS1047_20141006_wm, cn Mule Deer, connectivity modeling, habitat modeling, mammal, sn Odocoileus hemionus
Organization: California Department of Fish and Wildlife