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Forests
Special Issues
Carbon Cycle in Forest Ecosystems
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Carbon Cycle in Forest Ecosystems

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Ecology and Management".

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 1939

Special Issue Editor

Prof. Dr. Chih-Hsin Cheng

E-Mail Website
Guest Editor
School of Forestry and Resources Conservation, National Taiwan University, No. 1 Section 4, Roosevelt Road, Taipei 106, Taiwan
Interests: carbon cycle; extreme climatic events; disturbances; forest management

Special Issue Information

Dear Colleagues,

The continuous flow of carbon from land and water through the atmosphere and living organisms makes up the global carbon cycle. It contains reservoirs where carbon is stored and features dynamic flows of carbon between the carbon pools. Forests are some of the largest carbon reservoirs on Earth, and the storage and release of carbon from these have a significant impact on the global carbon cycle. Forests absorb carbon from the atmosphere through carbon sequestration, which describes the uptake of carbon through photosynthesis. This carbon is then used to create new plant biomass and release carbon back to the atmosphere as dead plant matter decays. Forest succession, from young stand to old stand, and natural and anthropogenic disturbances, such as forest fires, landslides, pest outbreaks, and forest management, can affect the carbon cycle in forest ecosystems. Notably, we face extreme climatic events and novel conditions at local and regional scales, which are likely to be translated into new equilibriums of forest ecosystems. The driving mechanisms that are already going on and expected to control future forests need to be better understood. We encourage studies from all fields, including experimental studies, monitoring approaches, and models to contribute to this Special Issue to promote knowledge and adaptation strategies for the preservation, management, and future development of forest ecosystems.

Prof. Dr. Chih-Hsin Cheng
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • carbon cycle
  • natural disturbances
  • carbon sequestration
  • forest succession
  • human activities
  • pest outbreaks
  • forest fires
  • forest management

Published Papers (1 paper)

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Research

18 pages, 5642 KiB  
Article
Improving the Accuracy of Estimating Forest Carbon Density Using the Tree Species Classification Method
by Ziheng Pang, Gui Zhang, Sanqing Tan, Zhigao Yang and Xin Wu
Forests 2022, 13(12), 2004; https://0-doi-org.brum.beds.ac.uk/10.3390/f13122004 - 27 Nov 2022
Cited by 5 | Viewed by 1464
Abstract
The accurate and effective estimation of forest carbon density is an essential basis for effectively responding to climate change and achieving the goal of carbon neutrality. Aiming at the problem of the significant differences in the forest carbon model parameters of different tree [...] Read more.
The accurate and effective estimation of forest carbon density is an essential basis for effectively responding to climate change and achieving the goal of carbon neutrality. Aiming at the problem of the significant differences in the forest carbon model parameters of different tree species, this study used the tree forest in Yueyang City, Hunan Province, China, as the study object and used the random forest classification algorithm through the Google Earth Engine platform to classify the dominant tree species within the forested range of the study area based on the image elements. The overall accuracy in the forest/non-forest classification (primary classification) was 93.79% with a Kappa of 0.9145. The overall accuracy in the dominant species classification (secondary classification) was 87.30% with a Kappa of 0.7747. Based on the classification, a multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) were constructed for different dominant tree species by combining some Forest Resource Inventory data and remote sensing data. The results showed that the RF model had a significantly higher coefficient of determination (R2 = 0.4054–0.7602) than the MLR (R2 = 0.0900–0.4070) and SVM (R2 = 0.1650–0.4450) as well as a substantially lower RMSE and MAE; its spatial distribution of forest carbon density ranged from 3.06 to 62.80 t·hm−2. Compared with the spatial distribution of the forest carbon density (4.64 to 31.96 t·hm−2) without the classification of dominant species, the method eliminated the problems of severe overfitting and significant underestimation of peak values when estimating under unclassified conditions. The method provides a reference for the remote sensing inversion of forest carbon density on a large scale. Full article
(This article belongs to the Special Issue Carbon Cycle in Forest Ecosystems)
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