Advance methodological approaches for carbon stock estimation in forest ecosystems

Environmental monitoring and assessment(2023)

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摘要
The forests are a key player in maintaining ecological balance on the earth. They not only conserve biodiversity, reduce soil erosion, and protect watersheds but also promote the above and below-ground ecosystem services. Forests are known as air cleaners on the planet and play a significant role in mitigating greenhouse gas (GHG) emissions into the atmosphere. As per programs launched in the Conference of Parties (COP) 26, there is a need to promote policies and programs to reduce the atmospheric carbon (C) through the forest ecosystem; it is because forests can capture the atmospheric CO 2 for a long time and help to achieve the goals of net-zero emission CO 2 on the earth. Therefore, there is an urgent need to know the advanced technological approaches for estimating C stock in forest ecosystems. Hence, the present article is aimed at providing a comprehensive protocol for the four C stock estimation approaches. An effort has also been made to compare these methods. This review suggests that tree allometry is the most common method used for the quantification of C stock, but this method has certain limitations. However, the review shows that accurate results can be produced by a combination of two or more methods. We have also analyzed the results of 42 research studies conducted for C stock assessment along with the factors determining the amount of C in different types of forests. The C stock in vegetation is affected by temporal and spatial variation, plantation age, land use, cropping pattern, management practices and elevation, etc. Nevertheless, the available results have a large degree of uncertainty mainly due to the limitations of the methods used. The review supports the conclusion that the uncertainty in C stock measurements can be addressed by the integration of the above-mentioned methods.
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关键词
Carbon stock estimation,Eddy’s covariance technique,Forests,Photosynthesis and leaf respiration,Remote sensing,Tree allometry
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