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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,
This dataset presents current and future change agent models and combined future potential for change (PFC) within the basin grassland and shrubland system Conservation Element.The basin grassland and shrubland system extent was determined by querying the LANDFIRE existing vegetation dataset for basin grassland and shrubland and clipping the data to the ecoregion boundary.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 within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures...
This table contains information about the amount of each threat analysis attribute, indicator and metric quantified for the 6th level Hydrological Unit (HUC12). These attributes were calculated for the entire HUC 12, the streams within the HUC 12, or the riparian corridor within the HUC 12. The attributes were calculated using ArcMap Tools.
The consolidated dataset represents polygonal fire perimeters of known fire occurrences between pre-1950 and 2010 within the state of Wyoming. Where it was included or possible to determine, information about fire types, causes, names, and dates has been retained. The following sources were used to consolidate all known and mapped fire occurrences: the USGS GeoMAC program, the National Park Service (Yellowstone National Park), the Monitoring Trends in Burn Severity (MTBS) program, the US Forest Service, the Bureau of Land Management, the Western Fires US database, and the National Fire and Aviation Management Web Applications (FAMWEB) program.
This dataset shows the combination of high probability areas from two Maxent models that predict human and naturally-caused fire occurrence. This long-term estimate is based on projecting the Maxent model developed on current climate conditions onto downscaled climate projections from RegCM3 based on ECHAM5 boundary conditions. Caution should be exercised in interpreting this dataset, as it is based on an association between landscape factors and the locations of fire occurrences. This dataset does not provide information about the likely outcome of a fire. See the human and naturally-caused fire occurrence datasets for more information and limitations.
This is a StoryMap used to organize a series of web applications related to Alaska wildland fires. Alaska Wildland Fire Information uses a tabbed layout. Each tab as a specific fire-related theme. The five (5) tabs are: Wildland Fires: This tab provides access to a broad suite of information related to wildland fires in Alaska. Lightning: This tab is tailored to show current and recent lightning activity in Alaska and neighboring territories. Fire Spotter: This tab is designed to provided information used on wildland fire detection missions. Reporting and Admin: This tab is designed to provide information commonly incorporated into wildland fire reports. Fire History and Fuels: This tab is tailored to provide information...
The Geospatial Multi-Agency Coordination Group, or GeoMAC, is an internet-based mapping tool originally designed for fire managers to access online maps of current wildland fire locations and perimeters in the continental United States, including Alaska. Perimeters are submitted to GeoMAC by the incidents via posting to FTP and web sites for downloading. This file contains wildland fire perimeters submitted to GeoMAC from the year 2000 to the calendar year preceeding the current one. The projection is geographic and the datum is NAD83. Last updated January 20, 2011, SPW. Additional metadata available at: http://rmgsc.cr.usgs.gov/outgoing/GeoMAC/historic_fire_data/us_hist_fire_perimeters_dd83_METADATA.htm
This dataset contains reclassified Landfire Mean Fire Return Interval (MFRI) data for the middle rockies ecoregion. Categorical values were assigned based on years until mean fire return according to key ecological attributes table.
This dataset presents current and future change agent models and combined future potential for change (PFC) within northern goshawk potentially suitable habitat.The northern goshawk potentially suitable habitat extent was determined using the SWReGAP Vertebrate Habitat Distribution Models for the northern goshawk clipped 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 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of...
The Monitoring Trends in Burn Severity (MTBS) project assesses the frequency, extent, and magnitude (size and severity) of all large fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 through 2011. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer...
The Monitoring Trends in Burn Severity (MTBS) project assesses the frequency, extent, and magnitude (size and severity) of all large fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 through 2011. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer...
The Monitoring Trends in Burn Severity (MTBS) project assesses the frequency, extent, and magnitude (size and severity) of all large fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 through 2011. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer...
The Monitoring Trends in Burn Severity (MTBS) project assesses the frequency, extent, and magnitude (size and severity) of all large fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 through 2011. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer...
This dataset shows areas of increased or decreased potential for human or naturally-caused fires between Maxent projections based on near-term climate and current climate.
This dataset shows areas burned by wildfire between 1999 and 2010 derived from fire perimeter and LANDFIRE disturbance datasets (Prescribed fires were not included in this analysis.). Where available, this dataset shows fire severity information.
The Geospatial Multi-Agency Coordination Group, or GeoMAC, is an internet-based mapping tool originally designed for fire managers to access online maps of current wildland fire locations and perimeters in the continental United States, including Alaska. Perimeters are submitted to GeoMAC by the incidents via posting to FTP and web sites for downloading. This file contains wildland fire perimeters submitted to GeoMAC from the year 2000 to the calendar year preceeding the current one. The projection is geographic and the datum is NAD83. Last updated January 20, 2011, SPW. Additional metadata available at: http://rmgsc.cr.usgs.gov/outgoing/GeoMAC/historic_fire_data/us_hist_fire_perimeters_dd83_METADATA.htm
This dataset presents current and future change agent models and combined future potential for change (PFC) within grassland fauna assemblage potentially suitable habitat.The grassland fauna assemblage potentially suitable habitat extent was determined by combining the SWReGAP Vertebrate Habitat Distribution Models for the burrowing owl, mountain plover, Gunnison's prairie dog, and swift fox 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 1 km reporting unit. Current...
The LANDFIRE existing vegetation layers describe the following elements of existing vegetation for each LANDFIRE mapping zone: existing vegetation type, existing vegetation canopy cover, and existing vegetation height. Vegetation is mapped using predictive landscape models based on extensive field reference data, satellite imagery, biophysical gradient layers, and classification and regression trees. DATA SUMMARY: The existing vegetation height (EVH) data layer is an important input to LANDFIRE modeling efforts. Canopy height is generated separately for tree, shrub and herbaceous cover life forms using training data and a series of geospatial data layers. EVH is determined by the average height weighted by species...
The LANDFIRE existing vegetation layers describe the following elements of existing vegetation for each LANDFIRE mapping zone: existing vegetation type, existing vegetation canopy cover, and existing vegetation height. Vegetation is mapped using predictive landscape models based on extensive field reference data, satellite imagery, biophysical gradient layers, and classification and regression trees.DATA SUMMARY: The existing vegetation type (EVT) data layer represents the current distribution of the terrestrial ecological systems classification developed by NatureServe for the western Hemisphere (http://www.natureserve.org/publications/usEcologicalsystems.jsp). A terrestrial ecological system is defined as a group...
LANDFIRE disturbance data are developed to provide temporal and spatial information related to landscape change for determining vegetation transitions over time and for making subsequent updates to LANDFIRE vegetation, fuel and other data. Disturbance data include attributes associated with disturbance year, type, and severity. These data are developed through use of Landsat satellite imagery, local agency derived disturbance polygons, and other ancillary data. DATA SUMMARY: The disturbance data are developed through a multistep process. Inputs to this process include; Landsat imagery and derived NBR (normalized burn ratio) data; polygon data developed by local agencies for the LANDFIRE Refresh effort; fire data...
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