English

The unrealized potential of agroforestry for an emissions-intensive agricultural commodity

Computer Vision and Pattern Recognition 2025-08-25 v2

Abstract

Reconciling agricultural production with climate-change mitigation is a formidable sustainability problem. Retaining trees in agricultural systems is one proposed solution, but the magnitude of the current and future-potential benefit that trees contribute to climate-change mitigation remains uncertain. Here, we help to resolve these issues across a West African region that produces ~60% of the world's cocoa, a crop contributing one of the highest carbon footprints of all foods. Using machine learning, we mapped shade-tree cover and carbon stocks across the region and found that existing average cover is low (~13%) and poorly aligned with climate threats. Yet, increasing shade-tree cover to a minimum of 30% could sequester an additional 307 million tonnes of CO2e, enough to offset ~167% of contemporary cocoa-related emissions in Ghana and C\^ote d'Ivoire--without reducing production. Our approach is transferable to other shade-grown crops and aligns with emerging carbon market and sustainability reporting frameworks.

Keywords

Cite

@article{arxiv.2410.20882,
  title  = {The unrealized potential of agroforestry for an emissions-intensive agricultural commodity},
  author = {Alexander Becker and Jan D. Wegner and Evans Dawoe and Konrad Schindler and William J. Thompson and Christian Bunn and Rachael D. Garrett and Fabio Castro-Llanos and Simon P. Hart and Wilma J. Blaser-Hart},
  journal= {arXiv preprint arXiv:2410.20882},
  year   = {2025}
}