2020 ESA Annual Meeting (August 3 - 6)

OOS 30 Abstract - Partnerships and data to strengthen the usability of Grass-Cast for rangeland management decisions under uncertainty

Dannele Peck1, William Parton2, Justin D. Derner3, Melannie Hartman2, William Smith4, Brian Fuchs5, Emile H. Elias6, Rafael Guerrero7, Michael A. Wilson8 and Matt C. Reeves9, (1)Northern Plains Climate Hub, USDA Agricultural Research Service, Fort Collins, CO, (2)Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, (3)USDA-ARS, Rangeland Resources and Systems Research Unit, Cheyenne, WY, (4)School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, (5)National Drought Mitigation Center, University of Nebraska-Lincoln, Lincoln, NE, (6)Southwest Climate Hub, USDA Agricultural Research Service, Las Cruces, NM, (7)Central National Technology Support Center, USDA Natural Resources Conservation Service, Fort Worth, TX, (8)USDA Natural Resources Conservation Service, Lincoln, NE, (9)USDA Forest Service Rocky Mountain Research Station, Missoula, MT
Background/Question/Methods

A multi-disciplinary team of researchers and outreach specialists across several universities and federal agencies collaborated with grassland managers and practitioners to co-develop and release a new grassland productivity forecast known as “Grass-Cast.” This innovative tool translates historical climate information and weather forecasts into an ecological forecast that relates more directly to the decisions that ranchers and other grassland managers must typically make ahead of an upcoming growing season.

Historically, grassland managers have made stocking decisions under high levels of uncertainty. Grass-Cast reduces this uncertainty by providing a forecast in early May about the expected productivity of grasslands during the upcoming growing season. Grass-Cast is then updated every two weeks throughout the growing season to incorporate newly observed weather data and updated precipitation outlooks.

Through partnerships and co-design processes, involving fellow grassland scientists, managers, and practitioners throughout the study area, the science underlying Grass-Cast has become stronger and its outreach products more useful to decision-makers.

Results/Conclusions

Partnerships with other grassland scientists have been essential to identifying and obtaining long-term ANPP datasets, which underpin the Grass-Cast model and its validation. Scientists at USDA Agricultural Research Service, University Extension, and Agricultural Experiment Stations, among others, have contributed ANPP datasets that enabled Grass-Cast to expand from the Northern Plains (in 2018) to the Southern Plains (2019) and now to the Southwest (2020).

Essential to the outreach success of Grass-Cast has been an on-going co-design process with grassland managers and practitioners—including USDA Natural Resources Conservation Service, Farm Service Agency, and Forest Service, as well as University Extension and private ranchers. Through a series of workshops, these partners made critical design improvements to Grass-Cast. A critical improvement was to replace a 1-map forecast, which users were reluctant to trust, to a more robust 3-map forecast. This made any remaining uncertainties more transparent about precipitation during the upcoming growing season.

The 3-map Grass-Cast now provides grassland managers with three different “what-if” scenarios to use in grazing contingency plans. The three maps indicate how much above-ground net primary productivity (ANPP) is expected to grow in any given 10-km2 location (relative to that location’s long-term average ANPP) depending on whether precipitation over the rest of the growing season is: 1) above-normal, 2) near-normal, or 3) below-normal.

Grassland managers and practitioners also co-designed the Grass-Cast website, where you will find current and archived Grass-Cast maps, along with tutorial videos, science webinar recordings, and links to publications: https://grasscast.unl.edu/.