提升可可种植区树冠覆盖率，可大幅减排且不影响产量
The unrealized potential of agroforestry for an emissions-intensive agricultural commodity
- 用机器学习绘制西非可可产区树冠分布与碳储量图
- 树冠覆盖率提至30%可多固碳3.07亿吨，抵消加纳科特迪瓦167%排放
- 方法可推广至其他遮荫作物，契合碳市场和可持续报告标准
将农业产出与气候变化减缓相协调是重大的可持续性挑战。在农田中保留树木是一种被提出的解决方案，但树木对气候减缓的当前及未来潜在贡献程度仍不明确。本文以全球约60%可可产量来自的西非地区为研究对象，该作物是所有食品中碳足迹最高的之一。利用机器学习技术，我们绘制了该区域的遮荫树覆盖范围与碳储量分布。结果显示，当前平均树冠覆盖仅为约13%，且与气候威胁不匹配。若将遮荫树覆盖提高至最低30%，可额外固碳3.07亿吨二氧化碳当量（CO2e），相当于抵消加纳与科特迪瓦当前可可相关排放量的167%，且无需降低产量。该方法可应用于其他遮荫作物，并与新兴碳市场及可持续报告框架相契合。
原文摘要 · Abstract (English)
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 Côte d'Ivoire--without reducing production. Our approach is transferable to other shade-grown crops and aligns with emerging carbon market and sustainability reporting frameworks.
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