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基于过程的模型的学习集,用于高准确地评估中国森林生态系统的百年碳汇潜力

Zhaosheng Wang¹, Renqaing Li¹, Qingchun Guo²

¹Key Laboratory of Ecosystem Network Observation and Modeling, National Data Center for Ecological Sciences, Institute of Geographic Sciences and Natural Resources Research, CAS, China.

|July 13, 2023

概括

中国的森林显著吸收大气中的二氧化碳 (CO2),减轻气候变化. 一个新的多模型随机森林组合 (MMRFE) 模型准确地估计了森林碳汇潜力,指导了未来的封存工作.

科学领域:

林业科学林业科学
气候变化研究气候变化研究
生态系统的碳循环循环.

背景情况:

中国的森林对全球碳循环至关重要,吸收大气中的二氧化碳以缓解气候变化.
准确评估森林碳吸收潜力 (CSP) 对于有效的气候行动至关重要.
现有的方法需要改进,以精确评估碳捕集能力.

研究的目的:

开发和验证一个先进的模型来评估中国森林生态系统的碳储量和潜力.
引入一种新的碳汇指数,以准确评估碳汇状态和强度区域.
为未来的森林碳捕获战略提供数据驱动的决策支持.

主要方法:

整合规范差异植被指数 (NDVI),现场数据和基于过程的模型输出.
开发一个多模型随机森林组合 (MMRFE) 模型来模拟植被和土壤碳密度.
应用新的碳汇指数来识别和量化碳汇强度区域.

主要成果:

该MMRFE模型在模拟森林碳密度 (r=0.94,P<0.001) 方面表现出高准确度.
从历史上看,中国的森林积累了1.33 Pg C (48.62 Bt CO2),抵消了全国二氧化碳排放的50%以上.
未来的预测显示,每年的二氧化碳吸收量为1.69-1.85亿二氧化碳,中等/强的沉降区域占森林面积的65%.

结论:

中国的森林生态系统拥有巨大的和不断增长的碳汇潜力.
MMRFE模型和碳汇指数为准确的CSP估计提供了强大的工具.
对于有效的自然碳捕获行动,建议优先考虑中等碳汇强度地区.

关键词:

潜在的碳汇可能会沉没.森林生态系统森林生态系统基于过程的模型的学习集.随机森林模型是一个随机森林模型.

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相关概念视频

The Carbon Cycle

The Carbon Cycle

Carbon is the basis of all organic matter on Earth, and is recycled through the ecosystem in two primary processes: one in which carbon is exchanged among living organisms, and one in which carbon is cycled over long periods of time through fossilized organic remains, weathering of rocks, and volcanic activity. Human activities, including increased agricultural practices and the burning of fossil fuels, has greatly affected the balance of the natural carbon cycle.