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

arXiv: https://arxiv.org/abs/2410.20882 · HTML: https://mlsanity.com/paper/2410.20882/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 107 references that are in the map.
- First posted on arXiv 28 Oct 2024.

## Builds on (most cited first, 1 of 1)

- [A high-resolution canopy height model of the Earth](https://mlsanity.com/paper/2204.08322/) (2022)

## Built on by (most cited first, 1 of 1)

- [Is sub-metre resolution necessary for cocoa mapping? A landscape-stratified evaluation of very high resolution imagery, decametric Earth Observation inputs, and operational products in Cote d'Ivoire](https://mlsanity.com/paper/2607.08945/) (2026)

## Abstract (arXiv)

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 Cote d'Ivoire--without reducing production. Our approach is transferable to other shade-grown crops and aligns with emerging carbon market and sustainability reporting frameworks.