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Technological advancements in Global Positioning System (GPS) telemetry markers allow almost real-time observation of waterfowl movements and habitat selection. Telemetry data on ducks marked with GPS transmitters can be used to evaluate performance of remote sensing data (for example, dynamic open-water maps produced by Point Blue Conservation Science) for classifying habitats that are flooded and available for waterfowl. Translating dynamic open-water maps to waterfowl-relevant habitat maps provides a major improvement for wildlife researchers and managers to assist in their assessments of the areas and habitats used by waterfowl as hydrologic conditions change, both temporally and spatially. Suitable habitat...
This U.S. Geological Survey (USGS) data release represents geospatial data that are the beach mouse presence outputs from the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The USGS partnered with the U.S. Fish and Wildlife Service (USFWS), the Florida Fish and Wildlife Conservation Commission, and their conservation partners to develop a Bayesian Network model that predicts the annual probability of beach mouse presence at a local (30-m) scale. The model was used to predict the annual probability of presence across a portion of the USFWS's Central Gulf and Florida Panhandle Coast Biological Planning Unit. This spatial extent included critical habitat for three endangered sub-species...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Bayesian network,
Florida,
Gulf of Mexico,
adaptive management,
beach mouse,
This U.S. Geological Survey (USGS) data release represents tabular data that were used to develop the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The USGS partnered with the U.S. Fish and Wildlife Service (USFWS), the Florida Fish and Wildlife Conservation Commission, and their conservation partners to develop a Bayesian Network model that predicts the annual probability of beach mouse presence at a local (30-m) scale. The model was used to predict the annual probability of presence across a portion of the USFWS's Central Gulf and Florida Panhandle Coast Biological Planning Unit. This spatial extent included critical habitat for three endangered subspecies of beach mice...
This U.S. Geological Survey (USGS) data release represents geospatial data that are the beach mouse presence outputs from the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The USGS partnered with the U.S. Fish and Wildlife Service (USFWS), the Florida Fish and Wildlife Conservation Commission, and their conservation partners to develop a Bayesian Network model that predicts the annual probability of beach mouse presence at a local (30-m) scale. The model was used to predict the annual probability of presence across a portion of the USFWS's Central Gulf and Florida Panhandle Coast Biological Planning Unit. This spatial extent included critical habitat for three endangered sub-species...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Bayesian network,
Florida,
Gulf of Mexico,
adaptive management,
beach mouse,
The Gulf Sturgeon is a federally listed, anadromous species, inhabiting Gulf Coast rivers, estuaries, and coastal waters from Louisiana to Florida. The U.S. Geological Survey partnered with the U.S. Fish and Wildlife Service (USFWS), U.S. Army Corps of Engineers, University of Georgia, and their conservation partners to support adaptive management of Gulf Sturgeon (Acipenser oxyrinchus desotoi) by developing a quantitative, spatial model. The model is a Bayesian network that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in estuarine critical habitat. The model predicts habitat availability (days) for 75 alternative physiological and habitat...
This U.S. Geological Survey (USGS) data release represents tabular data that were used to develop the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The USGS partnered with the U.S. Fish and Wildlife Service (USFWS), the Florida Fish and Wildlife Conservation Commission, and their conservation partners to develop a Bayesian Network model that predicts the annual probability of beach mice presence at a local (30-m) scale. The model was used to predict the annual probability of presence across a portion of the USFWS's Central Gulf and Florida Panhandle Coast Biological Planning Unit. This spatial extent included critical habitat for three endangered subspecies of beach mice (Peromyscus...
Categories: Data;
Tags: Bayesian network,
Florida,
Gulf of Mexico,
adaptive management,
beach mouse,
This U.S. Geological Survey (USGS) data release represents tabular and geospatial data for the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The data release was produced in compliance with 'open data' requirements as a way to make the scientific products associated with USGS research efforts and publications available to the public. The release consists of six items: 1. Bayesian network model that predicts the annual probability of beach mouse presence at a 30-m resolution in Florida coastal habitat (Tabular datasets) 2. Bayesian network model beach mice casefile (Tabular dataset) 3. Bayesian network model detection casefile (Tabular dataset) 4. Bayesian network model output...
In this data set, records (rows) represent GPS locations of ducks marked with telemetry in California and whether locations were overlapping (within 300 m of) locations of marked ducks in other consecutive years (2015-16, 2016-17, and 2017-18) during October - March. Years 2015-16, 2016-17, and 2017-18 represented drought, non-drought, and non-drought, respectively. Matchett and company (2020; see Larger Work section for citation) summarized this data set in tables E3 and E4 to compare overlap of duck locations between consecutive years to investigate interannual habitat stability in relationship with drought, habitat management (daytime roosts and night feeding sites), and in two regions (Suisun Marsh and California...
Categories: Data;
Tags: California,
Central Valley,
Global Positioning System (GPS) observations,
Suisun Marsh,
biota,
This U.S. Geological Survey (USGS) data release represents geospatial data that are the beach mouse presence outputs from the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The USGS partnered with the U.S. Fish and Wildlife Service (USFWS), the Florida Fish and Wildlife Conservation Commission, and their conservation partners to develop a Bayesian Network model that predicts the annual probability of beach mouse presence at a local (30-m) scale. The model was used to predict the annual probability of presence across a portion of the USFWS's Central Gulf and Florida Panhandle Coast Biological Planning Unit. This spatial extent included critical habitat for three endangered sub-species...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Bayesian network,
Florida,
Gulf of Mexico,
adaptive management,
beach mouse,
This U.S. Geological Survey (USGS) data release represents tabular data that were used to develop the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The USGS partnered with the U.S. Fish and Wildlife Service (USFWS), the Florida Fish and Wildlife Conservation Commission, and their conservation partners to develop a Bayesian Network model that predicts the annual probability of beach mice presence at a local (30-m) scale. The model was used to predict the annual probability of presence across a portion of the USFWS's Central Gulf and Florida Panhandle Coast Biological Planning Unit. This spatial extent included critical habitat for three endangered subspecies of beach mice (Peromyscus...
Categories: Data;
Tags: Bayesian network,
Florida,
Gulf of Mexico,
adaptive management,
beach mouse,
In this data set, records (rows) represent the distance between primary daytime roosts and night (feeding) locations of ducks marked with telemetry in California in years 2015-16, 2016-17, and 2017-18, during October - March. Years 2015-16, 2016-17, and 2017-18 represented drought, non-drought, and non-drought, respectively. Matchett and company (2020; see Larger Work section for citation) summarized this data set in figures E3 and E4 to compare distances moved among months, years, and for two regions (Suisun Marsh and California except Suisun Marsh). Matchett and company examined the effect of drought on distributions of ducks by evaluating differences in spatial distributions of duck locations within and among...
Categories: Data;
Tags: California,
Central Valley,
Global Positioning System (GPS) observations,
Suisun Marsh,
birds,
This USGS data release represents tabular and geospatial data for the Gulf Sturgeon Bayesian Network Model. The Gulf Sturgeon is a federally listed, anadromous species, inhabiting Gulf Coast rivers, estuaries, and coastal waters from Louisiana to Florida. The data release was produced in compliance with 'open data' requirements as way to make the scientific products associated with USGS research efforts and publications available to the public. The dataset consists of 2 separate items: 1. Bayesian network model that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in Apalachicola Bay, FL (Tabular datasets) 2. Bayesian network model outputs of...
We used Point Blue Conservation Science's dynamic open-water dataset of water distribution and our telemetry data for duck locations to develop frequently updated habitat maps for the Central Valley and Suisun Marsh in California during October-March of 2014-15 through 2017-18. Telemetry data additionally was used to compare performance of each of three series of habitat maps produced. To create this tabular dataset, we intersected telemetry locations for ducks (vector point data) with habitat maps (raster mosaics) in a Geographic Information System (GIS) and attributed duck locations with map pixel values representing habitat, non-habitat, or unclassified (if data were missing). To develop maps of waterfowl habitat,...
Categories: Data;
Tags: California,
Central Valley,
Global Positioning System (GPS) observations,
Suisun Marsh,
biota,
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