Nature Communications||中国植树造林的碳汇潜力

1、文献信息

2、期刊发文量

3、摘要

中国的大规模植树计划对于实现到2060年的碳中和至关重要，但在哪里以及如何种植树木以最大限度地吸收碳还没有经过严格的评估。在这里，我们开发了一个综合的机器学习框架，该框架集成了不同的环境变量，以量化树木的生长适宜性及其与树木数量的关系。然后，稳健地建立了它们与生物量碳储量的相关性。在不同的植树情景下绘制了碳汇潜力图。其中一项与中国生态系统管理政策相一致，可种植447亿棵树，增加森林蓄积量9.6±8亿立方米，封存5.9±0.5 PgC，相当于中国2020年工业二氧化碳排放量的两倍。我们发现，在现有森林中进行树木增密是一种经济上可行且有效的策略，因此在未来的大规模种植计划中应该优先考虑。

4、引言及引用的文献

4.1研究背景(第一段):

植树被认为是一种具有成本效益的策略，也是从大气中捕获碳和减缓气候变化的最实用的基于自然的解决方案之一。自20世纪70年代初以来，中国启动了一系列雄心勃勃的植树造林工程其主要目标是减少水土流失和沙尘暴，改善当地生态环境。然而，与早期相比，近年来森林扩张的速度有所放缓。为了实现在2060年之前实现碳中和的承诺，中国正在加强植树活动以吸收更多的碳，目标是到2035年将森林覆盖率提高到26%，到2050年提高到30%。

Tree planting is regarded as a cost-effective strategy and one of the most practical nature-based solutions for capturing carbon from the atmosphere and mitigating climate change. Since the early 1970s, China has launched a series of ambitious tree-planting programs, such as the Three-North Shelter Forest program, the Natural Forest Protection Program and the Yangtze River Shelter Forest project, whose main goals are to reduce soil erosion and sandstorms and improve local ecological environments. Reflecting the efforts of these programs, China has led the world in terms of planted tree area, significantly increasing the country’s forest cover from less than 13% in 1978 to about 23% in 2019, and substantially enhancing its terrestrial carbon sinks9,10. However, the rate of forest expansion has slowed in recent years compared to earlier periods11. To achieve the pledge of realizing carbon neutrality before 2060, China is stepping up the tree-planting campaign to sequester more carbon, with the aim of raising its overall forest coverage to 26% by 2035 and 30% by 2050 s.

共引用13篇文献，Nature（1篇）、PANS（2）、Science(3) 、 Agricultural and Forest Meteorology(1)、LDD（1）、IPCC和全球报告（2）、中国森林资源报告（1）及国家重大工程规划（2）。

4.2当前存在的问题(第二段-第三段)

共15篇文献，Nature（4）、Science（1）、1区top期刊（Journal of Cleaner Production、Land Use Policy、Global Change Biology等有8篇）、NASA EOSDIS Land Processes Distributed Active Archive Center（1）、中国林业和草原统计年鉴（1）。

4.3研究目标和方法(第四段):

在这里，我们提出了一个评估植树和碳封存潜力的综合方法框架(见“方法”)。其核心思想是根据一个地区的历史树木覆盖率来确定该地区的植树潜力。

Here we present a comprehensive methodological framework for assessing the potential of tree planting and carbon sequestration (see “Methods”). The core idea is to determine the tree planting potential of an area based on its historical tree cover. If an area was once extensively covered by forests, its climatic conditions are suitable for tree growth. Conversely, if an area has long been devoid of tree cover and has not been disturbed by human activities, it is likely unsuitable for tree growth. Areas that fall in between these two extremes will have tree growth-carrying capacities that are crucial for further enhancing forest carbon sequestration. First, we use environmental covariates related to tree growth (such as climate, soil, and topography) along with forest distribution time series data29 to quantify tree growth suitability (TGS) scores in different areas. This score serves as a standard for measuring the environmental carrying capacity for a certain area (Fig. 1b). Based on this, we introduce tree density data30 and analyze its relationship with the TGS score to estimate the potential of increasing tree density for different forest types (Fig. 1c). Considering the resolution of climatic environmental layers and existing tree density dataset, as well as the feasibility of large-scale intensive calculations, this study sets the grid size to 1 km. For grid cells without trees (i.e., tree density is 0), tree planting activities are considered as afforestation; for grid cells with existing trees, it is designated as densification (Fig. 1d). Furthermore, we have constructed a quantitative relationship between the number of trees and their aboveground/belowground forest biomass carbon stocks (AGFBC/BGFBC) to compute the amount of carbon that could be sequestrated, and the economic costs and carbon returns via tree planting (Fig. 1e).

5、文献配图

文献参考：Yao, L., Liu, T., Qin, J. et al. Carbon sequestration potential of tree planting in China. Nat Commun15, 8398 (2024). https://doi.org/10.1038/s41467-024-52785-6