Filters: Tags: San Luis Valley (X)
797 results (9ms)|
Filters
|
This dataset includes the magnetotelluric (MT) sounding data collected in 2006 in the Southern San Luis Valley, Colorado. The U.S. Geological Survey conducted a series of multidisciplinary studies, including MT surveys, in the San Luis Valley to improve understanding of the hydrogeology of the Santa Fe Group and the nature of the sedimentary deposits comprising the principal groundwater aquifers of the Rio Grande rift. The shallow unconfined and the deeper confined Santa Fe Group aquifers in the San Luis Basin are the main sources of municipal water for the region. The population of the San Luis Valley region is growing rapidly and water shortfalls could have serious consequences. Future growth and land management...
Types: Citation;
Tags: Colorado,
Costilla County,
Electromagnetic surveying,
GPS measurement,
Geophysics,
This dataset includes the magnetotelluric (MT) sounding data collected in 2009 in and near the San Luis Basin, New Mexico. The U.S. Geological Survey conducted a series of multidisciplinary studies, including MT surveys, in the San Luis Basin to improve understanding of the hydrogeology of the Santa Fe Group and the nature of the sedimentary deposits comprising the principal groundwater aquifers of the Rio Grande rift. The shallow unconfined and the deeper confined Santa Fe Group aquifers in the San Luis Basin are the main sources of municipal water for the region. The population of the San Luis Basin region is growing rapidly and water shortfalls could have serious consequences. Future growth and land management...
Mapping of terrestrial vertebrates focuses on linking a spatial representation of species-habitat matrices to geographic distribution. Each model is a combination of distribution from regional and state references in association with contiguous appropriate habitats. Ranges for all species were based on 8-digit HUCs. Habitats were based on a raster SWReGAP 1 acre MMU land cover data set, with hydrology habitats added in from USGS NHD dataset directly or through modeling. Habitat association information was obtained from various state, regional, and national references with updates from scientific literature. This portion of the Southwest Regional Gap Analysis Project produced predicted habitat distribution maps for...
Mapping of terrestrial vertebrates focuses on linking a spatial representation of species-habitat matrices to geographic distribution. Each model is a combination of distribution from regional and state references in association with contiguous appropriate habitats. Ranges for all species were based on 8-digit HUCs. Habitats were based on a raster SWReGAP 1 acre MMU land cover data set, with hydrology habitats added in from USGS NHD dataset directly or through modeling. Habitat association information was obtained from various state, regional, and national references with updates from scientific literature. This portion of the Southwest Regional Gap Analysis Project produced predicted habitat distribution maps for...
This dataset presents current and future change agent models and combined future potential for change (PFC) within the pinyon-juniper woodland system Conservation Element.The pinyon-juniper woodland system extent was determined by querying the LANDFIRE existing vegetation dataset for Pinyon-Juniper Woodland and clipping the data to the ecoregion boundary.This dataset presents current and future change agent models and combined future potential for change (PFC). Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development...
This map shows the classes, vegetation departure, current/future landscape intactness, current/future change agents, and potential for change for the Visual Resource Management (VRM) in the study area. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness, or other characteristics appropriate for applications that potential users of the data may contemplate. The User is encouraged to carefully consider the content of the...
This map shows the distribution, vegetation departure, current/future landscape intactness, current/future change agents, and potential for change of Northern Goshawk Habitat in the study area. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness, or other characteristics appropriate for applications that potential users of the data may contemplate. The User is encouraged to carefully consider the content of the metadata...
This map shows the distribution of ecological systems in the study area. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness, or other characteristics appropriate for applications that potential users of the data may contemplate. The User is encouraged to carefully consider the content of the metadata file associated with these data. The BLM should be cited as the data source in any products derived from these data.
This map shows species richness in the study area. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness, or other characteristics appropriate for applications that potential users of the data may contemplate. The User is encouraged to carefully consider the content of the metadata file associated with these data. The BLM should be cited as the data source in any products derived from these data.
This map shows Class I Prevention of Significant Deterioration (PSD) areas. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness, or other characteristics appropriate for applications that potential users of the data may contemplate. The User is encouraged to carefully consider the content of the metadata file associated with these data. The BLM should be cited as the data source in any products derived from these data.
Mapping of terrestrial vertebrates focuses on linking a spatial representation of species-habitat matrices to geographic distribution. Each model is a combination of distribution from regional and state references in association with contiguous appropriate habitats. Ranges for all species were based on 8-digit HUCs. Habitats were based on a raster SWReGAP 1 acre MMU land cover data set, with hydrology habitats added in from USGS NHD dataset directly or through modeling. Habitat association information was obtained from various state, regional, and national references with updates from scientific literature. This portion of the Southwest Regional Gap Analysis Project produced predicted habitat distribution maps for...
Mapping of terrestrial vertebrates focuses on linking a spatial representation of species-habitat matrices to geographic distribution. Each model is a combination of distribution from regional and state references in association with contiguous appropriate habitats. Ranges for all species were based on 8-digit HUCs. Habitats were based on a raster SWReGAP 1 acre MMU land cover data set, with hydrology habitats added in from USGS NHD dataset directly or through modeling. Habitat association information was obtained from various state, regional, and national references with updates from scientific literature. This portion of the Southwest Regional Gap Analysis Project produced predicted habitat distribution maps for...
Monthly and Annual dataset covering the conterminous U.S., for the years 1905-1919. Contains spatially gridded average mean temperature at 4km grid cell resolution. Distribution of the point measurements to the spatial grid was accomplished using the PRISM model, developed and applied by Dr. Christopher Daly of the PRISM Climate Group at Oregon State University. This dataset is available free-of-charge on the PRISM website.
Mapping of terrestrial vertebrates focuses on linking a spatial representation of species-habitat matrices to geographic distribution. Each model is a combination of distribution from regional and state references in association with contiguous appropriate habitats. Ranges for all species were based on 8-digit HUCs. Habitats were based on a raster SWReGAP 1 acre MMU land cover data set, with hydrology habitats added in from USGS NHD dataset directly or through modeling. Habitat association information was obtained from various state, regional, and national references with updates from scientific literature. This portion of the Southwest Regional Gap Analysis Project produced predicted habitat distribution maps for...
To support the BLM's San Luis Valley-Taos Plateau Landscape Assessment. This dataset presents current and future change agent models and combined future potential for change (PFC) within big game migration corridors.The big game migration corridors extent was determined from CDOW data. Species include bighorn sheep, elk, mule deer, and pronghorn. Migration corridors were clipped to the study area boundary and merged and dissolved across species.This dataset presents current and future change agent models and combined future potential for change (PFC). Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future...
The soils with potential for erosion dataset was created using the USDA Natural Resources Conservation Service’s (NRCS’s) SSURGO soil survey data and supplemented with STATSGO data in areas where SSURGO was not available. The dataset uses, in part, the soil data viewer extension for ArcMap to query various soil attributes. Output datasets were then queried for specific thresholds and combined into a composite soils with potential for erosion dataset. There were ten input parameters for the model based on SSURGO/STATSGO soil properties: Available water capacity (=63), electrical conductivity (> 16 dS/m), Sodium adsorption ration (=13), calcium carbonate (>5%), Depth to any soil restrictive layer ( 0.4), slope (>45%),...
Mapping of terrestrial vertebrates focuses on linking a spatial representation of species-habitat matrices to geographic distribution. Each model is a combination of distribution from regional and state references in association with contiguous appropriate habitats. Ranges for all species were based on 8-digit HUCs. Habitats were based on a raster SWReGAP 1 acre MMU land cover data set, with hydrology habitats added in from USGS NHD dataset directly or through modeling. Habitat association information was obtained from various state, regional, and national references with updates from scientific literature. This portion of the Southwest Regional Gap Analysis Project produced predicted habitat distribution maps for...
This dataset presents current and future change agent models and combined future potential for change (PFC) within native fish assemblage current distribution and potentially suitable habitat.The native fish assemblage current distribution and potentially suitable habitat extent was determined by combining the distribution of Rio Grande cutthroat trout, Rio Grande chub, and Rio Grande sucker (provided by BLM and CDOW) and clipping to the study area for the SLV-TP Landscape Assessment. This dataset presents current and future change agent models and combined future potential for change (PFC). Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each...
This dataset presents current and future change agent models and combined future potential for change (PFC) within big game seasonal ranges.The big game seasonal ranges extent was determined by aggregating datasets on seasonal ranges of several big game species (Elk, Mule Deer, Pronghorn, and Bighorn Sheep). Seasonal ranges include winter, crucial winter, crucial summer, and parturition areas. Data were obtained from state natural resource agencies (Colorado Parks and Wildlife) and the BLM.This dataset presents current and future change agent models and combined future potential for climate change (PFC). Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents...
Types: Downloadable;
Tags: BLM,
Big Game,
Bighorn Sheep,
Bureau of Land Management,
Crucial Summer Range,
To support the BLM's San Luis Valley-Taos Plateau Landscape Assessment. This dataset presents current and future change agent models and combined future potential for change (PFC) within big game migration corridors.The big game migration corridors extent was determined from CDOW data. Species include bighorn sheep, elk, mule deer, and pronghorn. Migration corridors were clipped to the study area boundary and merged and dissolved across species.This dataset presents current and future change agent models and combined future potential for change (PFC). Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future...
|
|
