Filters: Tags: Rangeland (X) > Types: Downloadable (X)
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This dataset contains a raster representing current (2017-2020) core sagebrush, growth opportunity areas, and other rangelands on tribal and federal lands that are estimated to be climate resilient into the future (2030-2060). We determined climate-resiliency by comparing current (2017-2020) core sagebrush, growth opportunity areas, and other rangelands to estimated future (2030-2060) conditions of core and growth opportunity areas under mid-century climate change (Representative Concentration Pathway 8.5) conditions (Doherty et al. 2022). The Department of the Interior (DOI) Sagebrush Keystone Initiative (KI) team worked with partners to identify areas within the sagebrush biome for strategic investments in conservation...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: California,
Colorado,
Conservation,
Idaho,
Montana,
RMU Units - a feature class depicting the boundaries of Rangeland Management Units (allotments, exclosures, general resource areas, and wild horse/burro territories) as managed by National Forests within Region 5 of the USDA Forest Service.
Defining site potential for an area establishes its possible long-term vegetation growth productivity in a relatively undisturbed state, providing a realistic reference point for ecosystem performance. Modeling and mapping site potential helps to measure and identify naturally occurring variations on the landscape as opposed to variations caused by land management activities or disturbances (Rigge et al. 2020). We integrated remotely sensed data (250-m enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) (https://earthexplorer.usgs.gov/)) with land cover, biogeophysical (i.e., soils, topography) and climate data into regression-tree software (Cubist®). We...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arid,
Arizona,
Colorado,
Ecology,
Geography,
This feature class includes monitoring data collected nationally to understand the status, condition, and trend of resources on BLM lands. Data are collected in accordance with the BLM Assessment, Inventory, and Monitoring (AIM) Strategy. The AIM Strategy specifies a probabilistic sampling design, standard core indicators and methods, electronic data capture and management, and integration with remote sensing. Attributes include the BLM terrestrial core indicators: bare ground, vegetation composition, plant species of management concern, non-native invasive species, and percent canopy gaps (see Entity/Attribute Section for exact details on attributes). Data were collected and managed by BLM Field Offices, BLM Districts,...
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