Abstract
To understand complex system dynamics in dairy farming requires tools that capture farm heterogeneity, social interactions, and cumulative environmental impacts. This study proposes an agent-based modelling (ABM) framework to simulate nitrogen management and low-emission fertiliser adoption across 295 Irish dairy farms over a 15-year period. Using empirical data, the model replicates farm communication through a social network, where adoption probabilities are driven by social contagion, farm-scale factors, and policy interventions such as subsidies and carbon taxes. The framework computes sectoral greenhouse gas emissions, cumulative abatement, and private-social costs, with Monte Carlo and sensitivity analyses quantifying uncertainty. The model achieved high predictive accuracy ((R^2 = 0.979), (textrm{RMSE} = 0.0274)) and was validated against observed adoption data using a Kolmogorov-Smirnov test ((D = 0.2407), (p < 0.001)). Adoption dynamics were fitted to Rogers logistic curves, reproducing a realistic saturation plateau (91%) while acknowledging structural laggard effects. By conceptualizing decarbonization as a socio-technical evolution rather than a purely monetary calculation, this study establishes an exploratory policy framework for evaluating the diffusion of climate strategies prior to implementation.
Acknowledgements
The authors acknowledge financial support from the Department of Agriculture, Food and the Marine (DAFM) 2023 Thematic Research Call (Project Reference: 2023RP956).
Funding
This research was supported by the Department of Agriculture, Food and the Marine (DAFM) 2023 Thematic Research Call (Project Reference: 2023RP956).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Supplementary Information. (download ZIP )
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Reprints and permissions
About this article
Cite this article
Jayakumar, S., Sullivan, K., McLaughlin, J. et al. Agent-based modeling of low-emission fertilizer adoption for dairy farm decarbonisation using empirical farm data.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-63267-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-63267-8
Keywords
- Agent-based modelling
- Technology diffusion
- Fertilizer management
- Greenhouse gas emissions
- Dairy systems
- Monte Carlo simulation
- Carbon farming
Source: Ecology - nature.com
