2018 ESA Annual Meeting (August 5 -- 10)

PS 5-66 - Developing decision support tools for conservation grazing management on Midwestern grasslands

Monday, August 6, 2018
ESA Exhibit Hall, New Orleans Ernest N. Morial Convention Center
Greta Landis, Environment & Resources, University of Wisconsin-Madison, Madison, WI, Chelsea Zegler, University of Wisconsin-Madison, Madison, WI, Mark J. Renz, Agronomy, University of Wisconsin-Madison, Madison, WI and Randall D. Jackson, Department of Agronomy, University of Wisconsin-Madison, Madison, WI
Background/Question/Methods

Rotational grazing for grassland management is gaining support in the Upper Midwest as a conservation strategy to improve grassland habitat while increasing the resilience grassfed beef and dairy. However, even experienced land managers and livestock producers can spend many years struggling with a ‘trial and error’ approach in grazing to meet their management goals. To improve planning and reduce ecological and financial risks for grassland management in Wisconsin, we are collaborating with the Wisconsin Department of Natural Resources (WDNR), grazing specialists, and cattle producers to develop a set of decision support tools (DSTs) for grazing.

Using input and testing from land managers and livestock producers, the preliminary version of this grassland management DST was developed as a set of grazing calculators to assess key ecosystem variables. Through literature review and analysis of Wisconsin-based data collected over a 15-year period, representing approximately 240 plot-years of yield responses (20 experiments with an average of 4 treatments typically running for 3 years), we populated the calculators with vegetation and soils data from cool-season grasslands of varying composition, edaphic, and climatic conditions managed with grazing.

Results/Conclusions

In the initial version of the grazing DST, users were able to manipulate different grazing factors in combination with plant community, forage, and soil data to explore agroecosystem relationships, infrastructure needs and costs, and comparisons with alternative land management approaches. However, the predictive capabilities of the grazing DST varied in accuracy during user testing on grassland forage yield and quality. Further refinement is needed to integrate climate parameters into management calculations. Building on these preliminary results, we will diagnose specific design problems and test modifications with our collaborators to improve the accuracy and utility of the tools, and further assess relationships between management variables.

Comprehensive grazing DSTs will improve planning and negotiation among land managers and producers while providing a teaching resource for livestock management and conservation. This work aims to maintain critical grassland habitat for wildlife and public recreation in a changing global climate, support new public-private partnerships and opportunities, and increase the profitability and accessibility of conservation agriculture.