ArticleNature communications2024
Carbon sequestration potential of tree planting in China.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Optimized Land-Water Management Expands Afforestation Potential Under Land and Human Water-Use Constraints.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Afforestation and reforestation support coupled gains in soil life and carbon storage worldwide.Nature ecology & evolution · 2026Article
- Dynamics of Carbon Storage Allocation and Its Drivers in Post-FirePlants (Basel, Switzerland) · 2026Article
- Assessment of water ecosystem service value in the Jianghuai watershed area: a case study of Chuzhou.Scientific reports · 2026Article
- Synthesizing the ecosystem services benefits, synergies and trade-offs of forest restoration in China.npj biodiversity · 2026Review
- Enhanced forest carbon gains from stronger protection in China's protected areas.Nature communications · 2026Article
- Enhancing carbon sinks in China using a spatially-optimized forestation strategy.Nature communications · 2026Article
- Distribution characteristics and influencing factors of carbon storage inFrontiers in plant science · 2026Article
- Differentiated response mechanisms of soil microbial communities to nitrogen deposition driven by tree species variations in subtropical planted forests.Frontiers in microbiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.