Summary
This paper presents a multi-criteria mathematical model for optimising the structure of national livestock production to simultaneously achieve economic, environmental and nutritional objectives. Using nonlinear optimisation, the authors modelled trade-offs between reducing greenhouse gas emissions, maintaining farm income, and meeting dietary adequacy targets. The analysis identifies multiple Pareto-optimal strategies that can reduce carbon intensity without necessarily triggering socio-economic harm, and suggests that technological improvements and feed quality management could offset negative effects of herd size reductions.
Regional applicability
This study was conducted for Russian livestock systems and national-level optimisation. Direct application to United Kingdom conditions would require recalibration with UK-specific livestock populations, feed systems, dietary patterns, and carbon accounting methodologies, though the multi-criteria optimisation framework may offer methodological utility for UK agricultural policy planning.
Key measures
Carbon footprint (tonnes CO₂ equivalent), livestock population by species, sectoral revenue, per capita consumption of meat, milk and eggs relative to medical dietary recommendations
Outcomes reported
The study developed a nonlinear optimisation model to analyse livestock sector structure at national level across three criteria: economic revenue, environmental carbon footprint, and social nutritional adequacy. Model experiments revealed that carbon footprint reduction is primarily driven by reducing dairy and beef cattle, sheep and goat populations, with lesser impact from pork and poultry sectors.
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