Welcome to the Rangeland Resources & Systems Research (RRSR), where our mission is to develop science-based management strategies for the provision of ecosystem goods and services from semiarid rangeland ecosystems. These strategies will be used to enhance decision-making by land managers using monitoring-informed adaptive management to improve resiliency and reduce risk for rangelands in a changing climate. Our research is conducted by 8 scientists (David Augustine, Dana Blumenthal, Justin Derner, David Hoover, Liwang Ma, Dannele Peck, Lauren Porensky and John Tatarko) and 1 post-doc (Hailey Wilmer) in Colorado and Wyoming at 3 primary field locations: 1) the Central Plains Experimental Range (shortgrass steppe, 1of 18 sites in the Long-Term Agroecosystem Research, LTAR, network, and the core site for Domain 10 for the National Ecological Observatory Network, NEON), 2) the High Plains Grasslands Research Station (northern mixed-grass prairie, and 3) the Thunder Basin National Grassland (ecotone of sagebrush grassland – northern mixed-grass prairie). Research projects are highly multi- and transdisciplinary with numerous collaborators including: University of Wyoming, Colorado State University, Texas A&M University, University of California-Davis, Crow Valley Livestock Cooperative, Inc., King Ranch, Thunder Basin Grasslands Prairie Ecosystem Association and many others.
Research objectives include:
- Develop adaptive grazing management strategies for rangelands that balance objectives for improving livestock production and enhancing other ecosystem services under a variety of climatic conditions.
- Develop science-based decision-support tools for rangelands to aid land managers in enhancing livestock production and other ecosystem goods and services at ecological site and landscape levels.
- As part of the LTAR network, use the Central Plains Experimental Range LTAR to improve the observational capabilities and data accessibility of the LTAR network to support research to sustain or enhance agricultural production and environmental quality in agroecosystems characteristic of the Central Great Plains. Expand plant trait data collection and synthesis across the LTAR sites to provide more robust mechanistic explanations of plant responses to management strategies and climate change.
- Validate untested science incorporated into Wind Erosion Prediction System (WEPS) for simulations of dryland crop rotations, tillage/no-tillage, organic soils, and residue cover, including the effects of within-field variability, against experimental data, and adjust algorithms where needed. Provide technology transfer of WEPS via data stewardship, data and algorithm documentation, and continual dialogue with the Natural Resources Conservation Service (NRCS).
- Survey and document grazing land model decision support functions requested by ranchers and public land managers; assess the ability of currently available models to reliably and accurately provide those functions using LTAR data; and outline a strategy to achieve a highly reliable, spatially-explicit, and high temporal resolution grazing land model that will meet the requested decision support needs.
Dr. David Augustine was part of a video on Dryland Agricluture. This film was produced by Rumplefarm in partnership with the Lexicon of Sustainability.