Filters: Tags: biota (X) > Extensions: ArcGIS REST Service (X)
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This dataset provides the results of an assessment of estuary habitat condition in the conterminous United States. To analyze estuary condition, a cumulative disturbance index was developed based on habitat stressor variable data available at a national scale for anthropogenic disturbances measured within estuaries and their associated watersheds. Twenty-eight variables were combined within stressor categories to develop four sub-indices of disturbance for land use, alterations of river flows, pollution sources, and estuary eutrophication. These four sub-indices of disturbance were then combined to develop cumulative disturbance index scores for each estuary. This index describes the estimated combined stress on...
The Species Richness Maps included here are based on the Gap Analysis Project (GAP) habitat maps, which are predictions of the spatial distribution of suitable environmental and land cover conditions within the United States for individual species. Individual species habitat distribution models were summed to create the total richness for each vertebrate taxa. The summing process was coded in Python 2.7 and employed the arcpy module for geoprocessing steps. The code is documented in the log file which is included in the Sciencebase item along with the richness data for each taxa (See processing steps for file names and sciencebase urls). Mapped habitat distribution areas represent places where the environment is...
Categories: Data;
Types: ArcGIS REST Map Service,
Map Service;
Tags: United States,
biodiversity,
biota,
conservation,
gap analysis,
This CSV file contains cumulative fish habitat condition index (HCI) scores generated for river reaches of the conterminous United States as well as indices generated specifically for four spatial units including local and network catchments and 90 m local and network buffers of river reaches. Note that the cumulative HCI score is determined from limiting index scores generated for the four spatial units listed above. Detailed methods for calculating cumulative fish habitat condition index scores as well as the indices for each spatial extent can be found on the following website: http://assessment.fishhabitat.org/: The variables used to create indices in catchments vs. buffers differ due to differences in resolution...
Categories: Data;
Types: ArcGIS REST Map Service,
Map Service;
Tags: 2015 National Assessment,
2015 National Assessment,
Alabama,
Anthropogenic factors,
Aquatic habitats,
A combination of citizen science inventories and expert assessments will be used to collect critical baseline information on known spring and seep resources using the Spring Ecosystem Inventory and Assessment Protocols and adapting them as needed for the unique arid Sky Island ecosystems. The assessment will collect information on channel morphology, riparian and wetland vegetation, water quality, aquatic macroinvertebrates, and wildlife. This information will be combined with historic data from cooperating agencies (Pima County, Santa Cruz County, USFS, NPA, USGS, USFWS, BLM, and AGFD) in a regional, on-line database to provide a landscape level context for managing resources, which was previously unavailable due...
Categories: Data,
Project;
Types: ArcGIS REST Map Service,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2011,
AZ-02,
AZ-03,
Arizona,
Arizona,
The Species Richness Maps included here are based on the Gap Analysis Project (GAP) habitat maps, which are predictions of the spatial distribution of suitable environmental and land cover conditions within the United States for individual species. Individual species habitat distribution models were summed to create the total richness for each vertebrate taxa. The summing process was coded in Python 2.7 and employed the arcpy module for geoprocessing steps. The code is documented in the log file which is included in the Sciencebase item along with the richness data for each taxa (See processing steps for file names and sciencebase urls). Mapped habitat distribution areas represent places where the environment is...
Categories: Data;
Types: ArcGIS REST Map Service,
Map Service;
Tags: United States,
biodiversity,
biota,
conservation,
gap analysis,
Data represent presence/absence for cedar decline occurrence. Cedar decline refers to the dying or decline of yellow-cedar (Chamaecyparis nootkatensis) forests in Southeast Alaska and is characterized by red or yellow foliage in trees currently dying, or by white-gray snags of old mortality. Mapped snags can be standing dead as long as eighty years. The data were collected via aerial sketch mapping techniques and recorded on 1:250,000 USGS base maps from 500-3000 foot above ground level(AGL) observations. Survey coverage has been most intense for forests adjacent to shorelines and waterways. Data are collected, refined and updated on an annual basis. This data represent not one year's mortality but the cumulative...
Categories: Data;
Types: ArcGIS REST Map Service,
Map Service;
Tags: Aerial,
Alaska,
Damage,
Disease,
Forest,
Reclassed areas of just sagebrush (1) and no sagebrush (0, areas with originally no sagebrush or recently burned areas). Landfire codes were: 2080, 2125, 2126, 2220, 2064, 2072, 2079, 2124) This layer is an intermediate layer used to create a sagebrush landscape cover layer using a moving window analysis. See Landfire metadata for an assessment of that data. See WFDSS, GEOMAC and MTBS fire metadata for more information on those data
Categories: Data;
Types: ArcGIS REST Map Service,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Downloadable Data,
Landfire,
Landfire,
SageDAT-data,
biota,
The Regional Estuary Assessment for the northern Gulf of Mexico represents an effort to develop, test, and implement a new assessment methodology for marine habitats that improves the analytical basis for identifying impacts to estuary fish habitats. Building from work completed for the National Estuary Assessment, this approach includes: 1) information on fish and shellfish presence/absence from over 70,000 sampling events collected over two decades, to better relate fish habitat condition to natural and anthropogenic variables; 2) data on natural factors, to better incorporate information on the natural susceptibility of individual estuaries; and 3) regional datasets not available on a nationally-consistent basis....
Categories: Data;
Types: ArcGIS REST Map Service,
Map Service;
Tags: 2015 National Assessment,
2015 National Assessment,
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > ALABAMA,
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > FLORIDA,
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > LOUISIANA,
This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was...
Categories: Data;
Types: ArcGIS REST Map Service,
Map Service;
Tags: Alabama,
Alaska,
Aleutian and Berind Sea Islands,
Appalachian,
Arctic, Northwestern Interior Forest,
This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was...
Categories: Data;
Types: ArcGIS REST Map Service,
Map Service;
Tags: Alabama,
Alaska,
Aleutian and Berind Sea Islands,
Appalachian,
Arctic, Northwestern Interior Forest,
The Species Richness Maps included here are based on the Gap Analysis Project (GAP) habitat maps, which are predictions of the spatial distribution of suitable environmental and land cover conditions within the United States for individual species. Individual species habitat distribution models were summed to create the total richness for each vertebrate taxa. The summing process was coded in Python 2.7 and employed the arcpy module for geoprocessing steps. The code is documented in the log file which is included in the Sciencebase item along with the richness data for each taxa (See processing steps for file names and sciencebase urls). Mapped habitat distribution areas represent places where the environment is...
Categories: Data;
Types: ArcGIS REST Map Service,
Map Service;
Tags: United States,
biodiversity,
biota,
conservation,
gap analysis,
The Species Richness Maps included here are based on the Gap Analysis Project (GAP) habitat maps, which are predictions of the spatial distribution of suitable environmental and land cover conditions within the United States for individual species. Individual species habitat distribution models were summed to create the total richness for each vertebrate taxa. The summing process was coded in Python 2.7 and employed the arcpy module for geoprocessing steps. The code is documented in the log file which is included in the Sciencebase item along with the richness data for each taxa (See processing steps for file names and sciencebase urls). Mapped habitat distribution areas represent places where the environment is...
Categories: Data;
Types: ArcGIS REST Map Service,
Map Service;
Tags: United States,
biodiversity,
biota,
conservation,
gap analysis,
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