Carbon sink conservation: Cost-effective spatial priorities and feasible management policies for China

For effective climate mitigation, land ecosystem conservation should focus on preserving carbon sinks instead of carbon stocks. However, the carbon sink capacity of land ecosystems is dynamic and uncertain, and its conservation is management-intensive and livelihood-impacting. This calls for more reliable evidence on future carbon sink dynamics and feasible policies for their conservation. This study evaluated spatial priorities for future carbon sink conservation in China by predicting carbon sink capacity from 2020 to 2100 using machine-learning models, while also mapping potential costs associated with management and population impacts. We found that intensified climate change may undermine future carbon sink capacity across extensive regions. Prioritised conservation areas were identified primarily in central, southern, and northeastern China, covering 8 %, 21.3 %, and 33.9 % of the country under conservative, moderate, and ambitious conservation targets, respectively. There is a modest synergy between priorities for carbon sink and biodiversity conservation, with a correlation coefficient of 0.515 and a spatial overlap of 9.9 %–42.6 % depending on conservation target levels. For actionable policies, we recommend focusing intensive management on just 12.6 % of China’s land, which aligns well with existing national ecological restoration projects. These findings provide evidence-based and feasible policies for carbon sink conservation in a resource-constrained country, with implications discussed for developing countries worldwide. • Spatial prioritization considering carbon sink dynamics and potential costs. • Intensified climate change threatens land carbon sink capacity and increases costs. • Three-level targets were set at national and provincial scales at 5-km resolution. • Modest synergy exists between carbon sink and biodiversity conservation. • Intensive management is required for only 12.6 % of China for cost-effectiveness.