CONTEXTLivestock production contributes to food security and livelihood improvement globally but places a significant burden on the environment. In Ireland, an ongoing transition towards highly profitable dairy production after the phasing out of EU milk quotas has changed the composition of the national cattle herd with more dairy and fewer beef cows. This shift impacts greenhouse gas (GHG) accounting across different cattle cohorts, e.g. increasing the proportion of calves from the dairy herd. Dairy x beef crossbreeds (DxB) increasingly contribute to national beef output, leveraging larger average daily liveweight gain (ADG) traits from beef breeding bulls. OBJECTIVEProspective modelling of climate and land consequences arising from alternative cattle production strategies requires more accurate simulation of cohort-specific ADG and associated feed requirements and GHG emissions. METHODSA new COHORTS model was developed to improve national climate scenario mitigation modelling. COHORTS is capable of simulating 21 genetics-gender-age cohorts calibrated to Irish performance, using just a few basic input parameters (at minimum dairy- and beef-cow numbers). A cohort specific ADG and average standing liveweight is estimated for each genetic (pure dairy calves, DxB and pure beef calves), gender and age combination, enabling more accurate calculation of energy requirements and enteric fermentation emissions based on IPCC Tier 2 calculations. RESULTS AND CONCLUSIONSNational simulation of cattle numbers, enteric fermentation emissions and beef outputs were validated against relevant Irish inventories. For the period between 2006 and 2020, simulations resulted in total cattle numbers, emissions and beef production within 4%, 1.8% and 0.5%, respectively, of officially reported data. Our results indicate that climate projections based on average emission factors for pre-adult cattle cohorts may overestimate emissions in scenarios with projected growing dairy calf numbers and declining beef calf numbers. SIGNIFICANCEValidation using a 15-year data time series provides a high degree of confidence that COHORTS can be used to represent future herd dynamics in a wide range of scenarios, supporting robust policy regarding GHG mitigation, livestock production and land use – distinguishing between different levels of dairy or beef specialisation and across different levels of performance to predict forage (land) requirements and GHG emissions more accurately. COHORTS can be easily adapted for other countries, even when limited data are available.
Read full abstract