Abstract for: UK livestock farmers’ incentives and barriers for change in the transition to Net Zero
| Introduction | Attaining Net Zero within the UK livestock agri-food system demands attention not only to technological mitigation options for greenhouse gas emissions, but also to the socio-economic incentive structures and behavioural dynamics that shape adoption by livestock farmers and meat processors. This study investigates the feedback mechanisms influencing the adoption of greenhouse gas emission reduction practices. |
| Approach | Using Systems Thinking and System Dynamics, the study combined a systemic literature review, participatory group-modelling workshops, and targeted surveys of UK livestock farmers and meat processors. These informed a conceptual system map, a causal loop diagram, and a quantitative stock-and-flow model linking socio-economic and biophysical dynamics, calibrated to reproduce greenhouse gas emission trends from 1990 to 2025. |
| Results | The model reproduced historical greenhouse gas emission reduction trends and identified key balancing loops that hinder adoption, notably climate-change scepticism, implementation costs, and perceptions of environmental impacts on the immediate versus distant environment. Reinforcing loops related to knowledge, skills, advice access, peer-to-peer support, scheme participation, resources, and environmental care promoted adoption. Scenario analysis showed that reducing scepticism and strengthening peer learning substantially accelerate emission reductions. |
| Discussion | These findings suggest that the UK livestock sector’s transition to Net Zero is conditioned as much by feedback-rich socio-economic dynamics as by the technical characteristics of mitigation options. The study shows how interventions targeting feedback structure can shift system behaviour and accelerate emission reductions. It provides a foundation for further model elaboration, including integration with complementary agent-based and statistical approaches, and for policy design informed by system-level leverage points. |