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This dataset was created to monitor the status, condition and trend of national BLM resources in accordance with BLM policies. The methodology used for the collection of these data can be found on landscapetoolbox.org and the Monitoring Manual, 2nd Edition. These data should not be used for statistical or spatial inferences without knowledge of how the sample design was drawn or without calculating spatial weights for the points based on the sample design. These include 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...
This interactive web application viewer shows locations where the BLM collects information about vegetation and soils to help us understand and monitor the health of terrestrial ecosystems such as sagebrush-steppe.
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 Interpreting Indicators for Rangeland Health (IIRH) method. The IIRH method is a qualitative assessment of rangeland health, defined as "the degree to which the integrity of the soil, vegetation, water, and air, as well as the ecological processes of the rangeland ecosystem are balanced and sustained." Attributes include the final rating for IIRH indicators: hydrologic function, biotic integrity, and soil/site stability (see Entity/Attribute Section for exact details on attributes). Data were collected and managed by BLM Field Offices,...
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 indicator summaries (all first hit percentages) needed for remote sensing purposes (see Entity/Attribute Section for exact details on attributes). Data were collected and managed by BLM Field Offices, BLM Districts, and/or affiliated field crews with support from the BLM National Operations...
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,...
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 aquatic core indicators: pH, conductivity, temperature, pool depth, length, frequency, streambed particles sizes, bank stability and cover, floodplain connectivity, large woody debris, macroinvertebrate biological integrity, ocular estimates of vegetative type, cover, and structure...
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