Burke, Ingrid C.2007-01-032007-01-031999-2001http://hdl.handle.net/10217/85531http://dx.doi.org/10.25675/10217/85531The Short Grass Steppe site encompasses a large portion of the Colorado Piedmont Section of the western Great Plains. The extent is defined as the boundaries of the Central Plains Experimental Range (CPER). The CPER has a single ownership and landuse (livestock grazing). The PNG is characterized by a mosaic of ownership and land use. Ownership includes federal, state or private and land use consists of livestock grazing or row-crops. There are NGO conservation groups that exert influence over the area, particularly on federal lands.Natural Resource Ecology Laboratory (NREL)Shortgrass Steppe-Long Term Ecological Research (SGS-LTER)This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Repository (http://hdl.handle.net/10217/100254). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Carbon (C) sequestration potential in grasslands is thought to be high due to the large soil organic carbon pools characteristic of these ecosystems. Inputs of C (aboveground net primary productivity) are highly correlated to precipitation across the Great Plains region; however, changes in C pool size at a specific site are governed by the relative input and output rates across time. Our objective was to quantify the ecosystem C response of three grassland community types (shortgrass steppe, mixed grass and tallgrass prairie) to interannual variation in precipitation. At five sites across a precipitation gradient in the Great Plains, we measured net primary production (NPP), soil respiration (SRESP), and litter decomposition rates for three consecutive years. NPP, SRESP, and litter decomposition increased from shortgrass steppe (175, 454, and 47 g C m-2 yr-1) to tallgrass prairie (408, 1221, and 348 g C m-2 yr-1 for NPP, SRESP, and litter decomposition respectively). Increased growing season precipitation between study years resulted in increased NPP, SRESP, and litter decomposition at almost all sites. However, the regional patterns of the interannual NPP, SRESP, and litter decomposition responses differ from each other. This data suggests NPP and SRESP are more sensitive to interannual changes in precipitation than litter decomposition, and that shortgrass steppe sites are more responsive to interannual variability in precipitation than mixed grass and tallgrass prairie.ZIPPDFTXTXMLengData sets were provided by the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Program, a partnership between Colorado State University, United States Department of Agriculture, Agricultural Research Service, and the U.S. Forest Service Pawnee National Grassland. Significant funding for these data was provided by the National Science Foundation Long Term Ecological Research program (NSF Grant Number DEB-1027319). The SGS-LTER project (1980-2014) was established as one of the first sites in the US LTER Network and has produce a rich legacy of digital materials including reports, proposals, images, and data packages. Data, products and other information produced from the SGS-LTER are curated as a collection within the Repository (http://hdl.handle.net/10217/100254). Materials can be accessed from the Institutional Digital Repository of Colorado State University or upon request by emailing ecodata_nrel@colostate.edu. All data are open for dissemination and re-use for any purpose, but you must attribute credit to the owner and cite use appropriately according to the LTER Data Access Policy (http://www.lternet.edu/policies/data-access).precipitationaboveground net primary productivitybiomassprimary productionweatherDataset