Grazing in an uncertain environment: Modeling the trade-off between production and robustness

Authors: SABATIER, RODOLPHE - Institut National De La Recherche Agronomique (INRA); OATES, LAWRENCE - University Of Wisconsin; Brink, Geoffrey; Bleier, Jonathan; JACKSON, RANDALL - University Of Wisconsin

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/18/2014
Publication Date: 1/13/2015
Publication URL: http://handle.nal.usda.gov/10113/62455
Citation: Sabatier, R., Oates, L.G., Brink, G.E., Bleier, J.S., Jackson, R.D. 2015. Grazing in an uncertain environment: Modeling the trade-off between production and robustness. Agronomy Journal. 107:257-264.

Interpretive Summary: Relying on cool-season grass forages as the primary component of livestock diets requires not only knowledge of culture and utilization, but also a consideration of the importance of uncertainty in management choices. We developed a simple model of grassland growth to quantify the robustness and production of management strategies. The model was calibrated on data from cool-season grasslands in south central Wisconsin that were grazed continuously or rotationally. Robustness was defined as the probability that a given management strategy did not lead to overgrazing, while production was the number of days a livestock unit could be supported per unit of land area by a particular grazing strategy. Robustness was strongly dependent on timing and intensity of grazing and the highest levels of production were incompatible with a high level of robustness. Beyond a certain threshold of production (500 livestock unit days per hectare), there was a trade-off between robustness and production where robustness decreased until maximum production (800 livestock unit days per hectare) was reached. This trade-off did not significantly differ between continuous grazing and management-intensive rotational grazing. The results illustrate how making grass the core of a livestock feeding strategy not only requires technical knowledge, but also an understanding of how to manage a system in a manner that reduces risk while increasing production.

Technical Abstract: Concern with the environmental, economic, and social impacts of the post-WWII model of agricultural intensification has led to renewed interest in grazing as a feeding strategy for temperate livestock farming systems. Putting the culture and utilization of grass at the core of livestock feeding not only requires technical knowledge, but also reconsidering the importance of uncertainty in management choices. We developed a simple stochastic model of grassland dynamics to quantify both robustness and production of alternative management strategies under continuous grazing and management-intensive rotational grazing. The model was calibrated on data from cool-season grasslands in southcentral Wisconsin (USA). We defined robustness as the probability that a given management strategy did not lead to overgrazing, while the production indicator was number of livestock unit days per hectare enabled by the grazing strategy. Robustness was strongly dependent on timing and intensity of grazing and the highest levels of production were incompatible with a high value of robustness. Beyond a certain threshold of production (500 LU days ha-1), we observed a trade-off between robustness and production where robustness decreases regularly until the maximum possible production (800 LU days ha-1). This trade-off did not significantly differ between continuous grazing and management-intensive rotational grazing. We identified key management practices that led to both high production and high robustness. These results illustrate how making grass the core of a livestock feeding strategy not only requires farmers to acquire new technical knowledge, but also a change of paradigm: from controlling environmental variability with external inputs to maximize production to understanding and managing a stochastic agroecosystem in a way that reduces negative externalities while increasing production efficiencies.