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Gap Analysis Project

How well are we protecting common plants and animals? Gap Analysis is the science of answering this question. Developing the data and tools to support that science is the mission of the Gap Analysis Project (GAP). Check out our SCIENCE section on the left to begin exploring GAP products: Species, Land Cover, and Protected Areas Database of the United States.

News

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Join upcoming webinars or view recorded webinars to learn more about PAD-US

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Major Update for America’s Inventory of Parks and Other Protected Areas: Protected Areas Database of the United States

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GAP Terrestrial Vertebrate Species Richness Maps Released for the Conterminous U.S.

Publications

Gap Analysis Project (GAP) Terrestrial Vertebrate Species Richness Maps for the Conterminous U.S.

The mission of the Gap Analysis Project (GAP) is to support national and regional assessments of the conservation status of vertebrate species and plant communities. This report explains conterminous United States species richness maps created by the U.S. Geological Survey for four major classes in the phylum Chordata: mammals, birds, reptiles, and amphibians. In this work, we focus on terrestrial

A comparison of NLCD 2011 and LANDFIRE EVT 2010: Regional and national summaries.

In order to provide the land cover user community a summary of the similarity and differences between the 2011 National Land Cover Dataset (NLCD) and the Landscape Fire and Resource Management Planning Tools Program Existing Vegetation 2010 Data (LANDFIRE EVT), the two datasets were compared at a national (conterminous U.S.) and regional (Eastern, Midwestern, and Western) extents (Figure 1). The c

Integrating multiple data sources in species distribution modeling: A framework for data fusion

The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species’ occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the tradeof