Conservation agriculture (CA) is being promoted as a set of management practices that can sustain crop production while providing positive environmental benefits. However, its impact on crop productivity is hotly debated, and how this productivity will be affected by climate change remains uncertain. Here we compare the productivity of CA systems and their variants on the basis of no tillage versus conventional tillage systems for eight major crop species under current and future climate conditions using a probabilistic machine-learning approach at the global scale. We reveal large differences in the probability of yield gains with CA across crop types, agricultural management practices, climate zones and geographical regions. For most crops, CA performed better in continental, dry and temperate regions than in tropical ones. Under future climate conditions, the performance of CA is expected to mostly increase for maize over its tropical areas, improving the competitiveness of CA for this staple crop.

保护性农业 (CA) 正在被推广为一套可以维持作物生产同时提供积极环境效益的管理实践。然而，它对作物生产力的影响引起了激烈的争论，而且这种生产力将如何受到气候变化的影响仍然不确定。在这里，我们使用概率机器学习方法在全球范围内比较了在当前和未来气候条件下八种主要作物物种的免耕和传统耕作系统的 CA 系统及其变体的生产力。我们揭示了在作物类型、农业管理实践、气候区和地理区域中，CA 增产概率的巨大差异。对于大多数作物，CA 在大陆、干旱和温带地区的表现优于热带地区。