Gap Analysis Project

Time 2020-12-26 21:06:55

Web Name: Gap Analysis Project

WebSite: http://gapanalysis.usgs.gov

ID:147109

Keywords:

Gap,Analysis,Project,

Description:

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.Species DataGAP has delineatedspecies range and predicted distribution maps for more than 2,000 species that occur within the continental U.S. as well as Alaska, Hawaii, and Puerto Rico.Download DataLand Cover DataThe GAP/LANDFIRE National Terrestrial Ecosystems data set includes detailed vegetation and land cover patterns for the continental United States. The data set incorporates the Ecological System classification system developed byNatureServe.Download DataProtected Areas DataPAD-US is America s official national inventory of U.S. terrestrial and marine protected areas (List of National Geospatial Data Assets).Download Data  Join upcoming webinars or view recorded webinars to learn more about PAD-US.  A new version of the Protected Areas Database of the U.S. (PAD-US), has major federal, state and easement updates, an easier-to-use data structure, new web services, national-scale printable maps, and more.   USGS Technical Announcement The USGS Gap Analysis Project, part of Core Science System's Science Analytics and Synthesis, has released terrestrial vertebrate species richness maps for the Conterminous U.S. Year Published: 2019 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,... Gergely, Kevin J.; Boykin, Kenneth G.; McKerrow, Alexa J.; Rubino, Matthew J.; Tarr, Nathan M.; Williams, Steven G. Attribution: Science Analytics and Synthesis (SAS), Gap Analysis Project View Citation Gergely, K.J., Boykin, K.G., McKerrow, A.J., Rubino, M.J., Tarr, N.M., and Williams, S.G., 2019, Gap Analysis Project (GAP) terrestrial vertebrate species richness maps for the conterminous U.S.: U.S. Geological Survey Scientific Investigations Report 2019–5034, 99 p., https://doi.org/10.3133/sir20195034. Year Published: 2017 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... Pacifici, Krishna; Reich, Brian J.; Miller, David A.W.; Gardner, Beth; Stauffer, Glenn E.; Singh, Susheela; McKerrow, Alexa J.; Collazo, Jaime A. Attribution: Core Science Systems, Cooperative Research Units, Gap Analysis Project, Science Analytics and Synthesis (SAS) View Citation Pacifici, K., Reich, B. J., Miller, D. A. W., Gardner, B., Stauffer, G., Singh, S., McKerrow, A. and Collazo, J. A. (2017), Integrating multiple data sources in species distribution modeling: a framework for data fusion*. Ecology, 98: 840–850. Year Published: 2017 Long-term fish monitoring in large rivers: Utility of “benchmarking” across basins In business, benchmarking is a widely used practice of comparing your own business processes to those of other comparable companies and incorporating identified best practices to improve performance. Biologists and resource managers designing and conducting monitoring programs for fish in large river systems tend to focus on single river basins or... Ward, David L.; Casper, Andrew F.; Counihan, Timothy D.; Bayer, Jennifer M.; Waite, Ian R.; Kosovich, John J.; Chapman, Colin; Irwin, Elise R.; Sauer, Jennifer S.; Ickes, Brian; McKerrow, Alexa J. Attribution: Southwest Biological Science Center, Western Fisheries Research Center, Core Science Systems, Ecosystems, Fisheries Program, Gap Analysis Project, Science Analytics and Synthesis (SAS) View Citation Ward, D.L., Casper, A.F., Counihan, T.D., Bayer, J.M., Waite, I.R., Kosovich, J.J., Chapman, C.G., Irwin, E.R., Sauer, J.S., Iches, B.S., and McKerrow, A.J., 2017,Long-Term Fish Monitoring in Large Rivers: Utility of “Benchmarking” across Basins: Fisheries, no. 42, v. 2, p

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