Human land use, such as livestock grazing, can have profound yet varied effects on wildlife interacting within common ecosystems, yet our understanding of land-use effects is often generalized from short-term, local studies that may not correspond with trends at broader scales. Here we used public land records to characterize livestock grazing across Wyoming, USA, and we used Greater Sage-grouse (Centrocercus urophasianus) as a model organism to evaluate responses to livestock management. With annual counts of male Sage-grouse from 743 leks (breeding display sites) during 2004–2014, we modeled population trends in response to grazing level (represented by a relative grazing index) and timing across a gradient in vegetation productivity as measured by the Normalized Vegetation Difference Index (NDVI). We found grazing can have both positive and negative effects on Sage-grouse populations depending on the timing and level of grazing. Sage-grouse populations responded positively to higher grazing levels after peak vegetation productivity, but populations declined when similar grazing levels occurred earlier, likely reflecting the sensitivity of cool-season grasses to grazing during peak growth periods. We also found support for the hypothesis that effects of grazing management vary with local vegetation productivity. These results illustrate the importance of broad-scale analyses by revealing patterns in Sage-grouse population trends that may not be inferred from studies at finer scales, and could inform sustainable grazing management in these ecosystems.
|Title||Patterns in Greater Sage-grouse population dynamics correspond with public grazing records at broad scales|
|Authors||Adrian Monroe, Cameron L. Aldridge, Timothy J. Assal, Kari E. Veblen, David A. Pyke, Michael L. Casazza|
|Publication Subtype||Journal Article|
|Series Title||Ecological Applications|
|Record Source||USGS Publications Warehouse|
|USGS Organization||Forest and Rangeland Ecosystem Science Center; Fort Collins Science Center; Advanced Research Computing (ARC)|