Grazing management-Tools for Improving the Efficiency of Grazing Beef Production

Abstract The beef sector is facing mounting challenges related to its perceived impact on climate change and other negative ecological externalities that can occur from the rearing of beef cattle. This would include greenhouse gas emissions (GHG), soil degradation, eutrophication of water ways and a decrease in biodiversity, to name a few. Within the industry, the largest contributor of GHG comes from the grazing sector, predominantly in the form of enteric methane (CH4) produced during the reticulo-rumen fermentation process. This presents a unique challenge, as the grazing sector is one where animal scientists have low precision with respect to experimental design and data collection, and where producers assert a lower level of dietary control relative to confined operations. While enteric CH4 inhibitors are getting closer to regulatory approval, their ability to reduce emissions in grazing systems is still relatively unknown due to the “pulse” supplementation strategy being unstudied to date. Therefore, management decisions that improve the quality of the forage base are the most practical strategies to reduce enteric CH4 production. This would include strategies such as adaptive grazing management, inclusion of high-quality forages, and improved forage diversity as potential tools to reduce emissions, dependent on geographic location. Furthermore, how the human dimension influences soil-plant-animal interrelationships may lead to beneficial ecological outcomes such as carbon sequestration and soil health. Therefore, potential “win-win” outcomes may be achieved. However, climatic gradients, and more specifically moisture, can influence or limit outcomes and thus interpreting research should be done on a geographical and climatic specific basis. The objective of this presentation is to outline and examine how management decisions can influence the efficiency and environmental impact of U.S. beef production, and to identify potential limitations and knowledge gaps in need of future research.