The Great Plains Landscape Conservation Cooperative (GPLCC, https://www.fws.gov/science/catalog) is a partnership that provides applied science and decision support tools to assist natural resource managers conserve plants, fish and wildlife in the mid- and short-grass prairie of the southern Great Plains. It is part of a national network of public-private partnerships — known as Landscape Conservation Cooperatives (LCCs, http://www.fws.gov/science/shc/lcc.html) — that work collaboratively across jurisdictions and political boundaries to leverage resources and share science capacity. The Great Plains LCC identifies science priorities for the region and helps foster science that addresses these priorities to support wildlife conservation throughout the Great Plains region. It also assists partners in building their own capacity to address scientific challenges associated with our rapidly changing environment.These data were compiled because the information did not previously exist as a single resource for the GPLCC area. They are intended to inform local and regional conservation and management strategies with a complete regional perspective. Abstract provided by original data sources: "This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the Northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the Southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. In areas of the county (central U.S., Northeast) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. In 2009 Landfire data was combined by the Landscope project into one uniform coverage. This compiled data was the data pulled into this project. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-naturalvegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003). Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. Online references Northwest Gap Analysis Project Southwest Gap Analysis Project- Southeast Gap Analysis Project- California Gap land cover project LANDFIRE- Landscope- NatureServe- National Land Cover Dataset- ".Data were the best available at the time of compilation (2011) with current information represented by a combination of national-scale datasets and state or other regional data (e.g. soils) that could be reasonably aggregated.