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Advance methodological approaches for carbon stock estimation in forest ecosystems

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dc.contributor.authorNandal, Abhishek
dc.contributor.authorYadav, Surender Singh
dc.contributor.authorRao, Amrender Singh
dc.contributor.authorMeena, Ram Swaroop
dc.contributor.authorLal, Rattan
dc.date.accessioned2025-01-28T09:55:15Z
dc.date.available2025-01-28T09:55:15Z
dc.date.issued2023
dc.description.abstractThe 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 CO2 for a long time and help to achieve the goals of net-zero emission CO2 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. � 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
dc.identifier.doihttps://doi.org/10.1007/s10661-022-10898-9
dc.identifier.issn1676369
dc.identifier.urihttps://dl.bhu.ac.in/ir/handle/123456789/22851
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.subjectCarbon stock estimation
dc.subjectEddy�s covariance technique
dc.subjectForests
dc.subjectPhotosynthesis and leaf respiration
dc.subjectRemote sensing
dc.subjectTree allometry
dc.titleAdvance methodological approaches for carbon stock estimation in forest ecosystems
dc.typeReview
dspace.entity.typePublication
journal.titleEnvironmental Monitoring and Assessment
journalvolume.identifier.volume195

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2023