The Hydric Soils section presents the most current information about hydric soils. It updates information that was previously published in Hydric Soils of the United States and coordinates it with information that has been published in the Federal Register. It also includes the most recent set of field indicators of hydric soils. The database selection criteria are selected soil properties that are documented in Soil Taxonomy and were designed primarily to generate a list of potentially hydric soils from soil survey databases. Only criteria 1, 3, and 4 can be used in the field to determine hydric soils; however, proof of anaerobic conditions must also be obtained for criteria 1, 3, and 4 either through data or best professional judgment (from Tech Note 1). The primary purpose of these selection criteria is to generate a list of soil map unit components that are likely to meet the hydric soil definition.
This website is designed to help you calculate the Drainage Index (DI) and Productivity Index (PI) of all soils that are classified within the US system of Soil Taxonomy. These data aid in the identification of areas at risk to various forest insects and diseases because of their ability to identify regions of potential tree stress.
The Soil and Water Assessment Tool (SWAT) is a public domain model jointly developed by USDA Agricultural Research Service (USDA-ARS) and Texas A&M AgriLife Research, part of The Texas A&M University System. SWAT is a small watershed to river basin-scale model to simulate the quality and quantity of surface and ground water and predict the environmental impact of land use, land management practices, and climate change. SWAT is widely used in assessing soil erosion prevention and control, non-point source pollution control and regional management in watersheds.
USDA Forest Service Remote Sensing Applications Center and Geospatial Technology and Applications Center
The Forest Service's Remote Sensing Applications Center (RSAC) is in Salt Lake City, Utah, co-located with the agency's Geospatial Service and Technology Center. Guided by national steering committees and field sponsors, RSAC provides national assistance to agency field units in applying the most advanced geospatial technology toward improved monitoring and mapping of natural resources. RSAC's principal goal is to develop and implement less costly ways for the Forest Service to obtain needed forest resource information.
The Air, Water, and Aquatic Environments (AWAE) research program is one of eight Science Program areas within the Rocky Mountain Research Station (RMRS). Our science develops core knowledge, methods, and technologies that enable effective watershed management in forests and grasslands, sustain biodiversity, and maintain healthy watershed conditions.
SWIFT (Small Watershed Nutrient Forecasting Tool) is a web-based tool that allows the rapid estimation of sediment and nutrient loads from small watersheds for a given ecoregion in the US.
NLET (National Load Estimating Tool) is a web-based tool for estimating pollutant loads in watersheds across the contiguous United States. This tool helps visualize the effects of land use patterns, cultivated crops, and conservation practices through graphical representation.
Longleaf pine forests once encompassed more than 90 million acres of the North American landscape and represented some of the world’s most unique biologically diverse ecosystems. In 2010, approximately three percent, or 3.4 million acres, of longleaf pine forest remained. This dataset includes a printer-friendly CCA map and shapefiles for GIS.
LANDFIRE (LF), Landscape Fire and Resource Management Planning Tools, is a shared program between the wildland fire management programs of the U.S. Department of Agriculture Forest Service and U.S. Department of the Interior, providing landscape scale geo-spatial products to support cross-boundary planning, management, and operations. LANDFIRE is a program that provides over 20 national geo-spatial layers (e.g. vegetation, fuel, disturbance, etc.), databases, and ecological models that are available to the public for the US and insular areas.
Data from: Data from camera surveys identifying co-occurrence and occupancy linkages between fishers (Pekania pennanti), rodent prey, mesocarnivores, and larger predators in mixed-conifer forests
These data provide information on the frequency of fisher detections by camera traps, and single-season occupancy and local persistence of fishers in small patches of Sierra Nevada mixed-conifer forest habitats. The data are used to identify basic patterns of co-occurrence with fishers, and to evaluate the relative importance of presence of competing mesocarnivores, rodent prey, and predators for fisher occupancy of small, 1 km^2^ grid cells of forest habitat.