Résumé
Many countries have made ambitious pledges to increase forest areas to mitigate climate change. However, the availability of land to meet these goals is not well understood. Global studies indicate substantial potential, but do not account for local land-use and regional variation, crucial for policy making. Using India as a case study, we use a machine learning framework to define the bioclimatic envelope of forest cover and map this against current land-uses with varying suitability for restoration. We estimate the additional feasible area for restoration to be only 1.58 Mha, cumulatively sequestering 61.3 TgC, which is substantially less than estimates derived from global studies. However, we also find up to 14.67 Mha of opportunity for agroforestry in current agricultural land, delivering up to 98.1 TgC nationally. In the UN Decade of Restoration, we recommend developing forest restoration strategies that are compatible with existing land-uses, such as agroforestry, especially in countries that have large smallholder agriculture holdings.