Modelling the effect of feeding management on greenhouse gas and nitrogen emissions in cattle farming systems

Highlights: • Feed management decisions affect gaseous emission from cattle production systems • Statistical and empirical models are practical in evaluating diets and inventories • Mechanistic or Process-based models allow capturing variation in on-farm emissions • Integral assessment approaches are preferred over isolating each emission source • Combined use of process-based models for individual farm elements not used yet Feed management decisions are an important element of managing greenhouse gas (GHG) and nitrogen (N) emissions in livestock farming systems. This review aims to a) discuss the impact of feed management practices on emissions in beef and dairy production systems and b) assess different modelling approaches used for quantifying the impact of these abatement measures at different stages of the feed and manure management chain. Statistical and empirical models are well-suited for practical applications when evaluating mitigation strategies, such as GHG calculator tools for farmers and for inventory purposes. Process-based simulation models are more likely to provide insights into the impact of biotic and abiotic drivers on GHG and N emissions. These models are based on equations which mathematically describe processes such as fermentation, aerobic and anaerobic respiration, denitrification, etc. and require a greater number of input parameters. Ultimately, the modelling approach used will be determined by a) the activity input data available, b) the temporal and spatial resolution required and c) the suite of emissions being studied. Simulation models are likely candidates to be able to better explain variation in on-farm GHG and N emissions, and predict with a higher accuracy for a specific mitigation measure under defined farming conditions, due to the fact that they better represent the underlying mechanisms causal for emissions. Integrated farm system models often make use of rather generic values or empirical models to quantify individual emissions sources, whereas combining a whole set of process-based models (or their results) that simulates the variation in GHG and N emissions and the associated whole farm budget has not been used. The latter represents a valuable approach to delineate underlying processes and their drivers within the system and to evaluate the integral effect on GHG emissions with different mitigation options.