Agent-Based Model Simulates Low-Emission Fertilizer Adoption on Irish Dairy Farms
A recent study introduces an agent-based modeling (ABM) framework designed to simulate nitrogen management and the use of low-emission fertilizers on 295 dairy farms in Ireland over a span of 15 years. The model, grounded in empirical data, illustrates farm interactions via a social network, reflecting the effects of peer influence and group discussions. Factors influencing adoption rates include social contagion, characteristics specific to farm size, and policy measures like subsidies and carbon taxes. By employing Monte Carlo simulation and sensitivity analysis, the framework assesses sector-wide greenhouse gas emissions, cumulative abatement, and trade-offs between private and social costs. The model aligns closely with actual adoption patterns (R² = 0.979, RMS), underscoring the significance of farm diversity and social dynamics in dairy farming system analysis.
Key facts
- Agent-based modeling framework simulates low-emission fertilizer adoption on 295 Irish dairy farms over 15 years.
- Model uses empirical data and social network to represent farm communication and peer influence.
- Adoption probabilities influenced by social contagion, farm-scale characteristics, and policy interventions like subsidies and carbon taxes.
- Framework estimates sectoral greenhouse gas emissions, cumulative abatement, and cost trade-offs.
- Monte Carlo simulation and sensitivity analysis quantify uncertainty.
- Model shows strong agreement with observed adoption trajectories (R² = 0.979, RMS).
- Study published on arXiv with ID 2605.03648.
- Research emphasizes need to capture farm heterogeneity and social interactions in dairy farming system dynamics.
Entities
Institutions
- arXiv
Locations
- Ireland