固碳
中国
树(集合论)
播种
农林复合经营
环境科学
生物
地理
农学
生态学
数学
二氧化碳
数学分析
考古
作者
Ling Yao,Tang Liu,Jun Qin,Hou Jiang,Lin Yang,Pete Smith,Xi Chen,Chenghu Zhou,Shilong Piao
标识
DOI:10.1038/s41467-024-52785-6
摘要
China's large-scale tree planting programs are critical for achieving its carbon neutrality by 2060, but determining where and how to plant trees for maximum carbon sequestration has not been rigorously assessed. Here, we developed a comprehensive machine learning framework that integrates diverse environmental variables to quantify tree growth suitability and its relationship with tree numbers. Then, their correlations with biomass carbon stocks were robustly established. Carbon sink potentials were mapped in distinct tree-planting scenarios. Under one of them aligned with China's ecosystem management policy, 44.7 billion trees could be planted, increasing forest stock by 9.6 ± 0.8 billion m³ and sequestering 5.9 ± 0.5 PgC equivalent to double China's 2020 industrial CO
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