Book Description

As population and demand for animal products increase, livestock producers are under both social and economic pressure to intensify production to meet demand. Simultaneously, environmental impacts of livestock production, such as greenhouse gas emissions (GHG) and irrigated water usage, are under increased public and regulatory scrutiny for their contributions to climate change and resource scarcity. One GHG under particular scrutiny is methane (CH4), which enters the atmosphere from both manure and enteric emissions by ruminants such as sheep and cattle. For livestock agriculture to continue to meet demand, the processes driving these environmental impacts must be understood and quantified so that impacts may be effectively mitigated. Quantitative models of animal biology can be used by researchers to quantify and analyze environmental impacts of livestock production on both animal-level and system-level scales. Mechanistic models model higher-level processes by explicitly representing the underlying structure of the system being modeled as an integration of lower-level processes. These mechanistic models can be used as both research tools to explore understanding of a current system, or to predict animal performance and environmental impacts. AusBeef is a mechanistic, dynamic model for predicting beef cattle performance, and which predicts enteric CH4 production based on ruminal hydrogen balance. The ability of AusBeef to predict enteric CH4 and gross energy intake was compared to that of the 2016 Beef NRC model, an empirical model of beef cattle production, and the Ruminant Nutrition System (RNS) a dynamic, mechanistic model (Tedeschi & Fox 2016). Overall, AusBeef performed most similarly to the empirical NRC model, and all models required further refinement to improve CH4 prediction on forage diets. Three sensitivity analysis methods, one local and two global, were then used to evaluate AusBeef’s behaviour on forage-based and concentrate-based diets for four methane-relevant outputs of interest. Different patterns of sensitivity were observed between forage-based and concentrate-based diets, but patterns were consistent within diet types. System-level models such as those used in Life Cycle Assessment (LCA) can be mechanistic or empirical in nature, and are useful for evaluating the impacts of a specific production system, as well as to benchmark or evaluate environmental impacts on an industry level. Region-specific analysis of livestock emissions and resource usage helps to understand unique characteristics of a region’s livestock production systems and can be used to develop mitigation methods tailored to these specific circumstances. A cradle-to-farm gate LCA of the California sheep industry was conducted to evaluate the carbon and irrigated water footprints of five different meat sheep production systems. Enteric CH4 was the largest contributor to overall emissions, while irrigated pasture use was a major driver of irrigated water footprint. Sensitivity analysis showed that carbon footprint per kg market lamb was sensitive to ewe replacement rate and lambs produced per ewe, highlighting the importance of flock management strategies to overall sustainability. The present studies show the utility of animal-level and system-level models to evaluate the environmental impacts of different livestock production systems, as well as the usefulness of sensitivity analysis in identifying model drivers. These studies also suggest future directions for data collection and model development to help identify and target mitigation strategies for both beef and sheep production.