Sensitivity of greenhouse gas emissions to extreme differences in forage production of dairy farms

Abstract Dairy farms follow a wide variety of management practices depending on the economic and environmental objectives that farmers target. Management practices are reflected, among other things, by a wide variety of forage-production and animal-feeding strategies, which influence productivity and greenhouse gas (GHG) emissions of dairy farms. Many studies focus on agricultural systems with “average” characteristics to generalize results to a larger percentage of existing systems. This approach, however, ignores systems with uncommon characteristics, whose environmental impacts may be unusually large (e.g. due to inefficiencies) or small (e.g. due to innovations). To address this issue, we used Extreme-Value Theory (EVT) as a statistical tool to identify dairy farms with forage-related characteristics that could be considered “extreme”. Application of EVT to a dataset of 78 dairy farms in Normandy (France) identified 15-20% of dairy farms with extreme minimum amounts of dry matter (DM) of grass from pastures or maize silage and 10-15% of farms with extreme maximum amounts of one or the other. Mean amounts of DM between the minimum sample and maximum sample differed by a factor of ca. 3 for grass and a factor of 1.5 for maize silage. Consequently, the maximum sample for grass or maize silage had mean estimated gross GHG emissions (kg CO2 eq) 13% lower or 25% higher, respectively, than those of the minimum sample. Four strategies were identified for setting DM of grass and maize silage at extreme levels, which influenced milk production and GHG emissions. Extreme changes in the DM of one forage were generally compensated by changes in those of the other forage and concentrated feed fed at non-extreme levels, which influenced enteric methane emissions, manure management or the amount of feeds purchased.