Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)

Proposed Forest Carbon Sequestration Management Plan Based on Mathematical Modeling Method

Authors
Yitong Sun1, *
1School of Management, Shenyang Jianzhu University, Shenyang, 110168, Liaoning, China
*Corresponding author. Email: syt20010216@126.com
Corresponding Author
Yitong Sun
Available Online 20 December 2022.
DOI
10.2991/978-94-6463-030-5_48How to use a DOI?
Keywords
Carbon Sequestration Model; TOPSIS Evaluation Model; Logistic Model
Abstract

In order to alleviate global warming, reducing carbon emissions has become a common goal for human being. Forests as the largest carbon sequestration site in the ecosystem, they have made a huge contribution to reducing the carbon content in the air. Nowadays, using the carbon sequestration capacity of forests to sequester CO2 has become a trending topic. This study took Yellowstone National Park as an example, using the analytic hierarchy process to extract the forest value with the help of the concept of multivariate elasticity, and the forest stock volume conversion factor method was used to take into account the carbon sequestration capacity and the rotation period to obtain the forest area and structure. Then we got the forest growth rate, biodiversity, he weights of socio-economic factors are 0.35, 0.25, 0.2, 0.1 and 0.1, respectively. Finally, we proposed a forest management plan potential evaluation index model (PCSDPI), and a management plan that is most in line with the forest characteristics of Yellowstone National Park is obtained. In addition, we calculated the balance point of different plans as 3.2 years, 5.1 years, 6.8 years and 9.3 years. This study also applied the model to the whole world, adding two indicators of development degree and climating to the existing management plan evaluation indicators, obtaining the best management plan of four kinds of forests. The results of the pros and cons are 0.6046 and 0.7583. We used a logistic model to predict the annual number of trees planted and felled in the forest. The results showed that the change rates of the felled trees were 2.47%, 2.96%, 2.11%, and 3.14%, The rate of change of the planted were 2.41%, 2.86%, 2.14%, and 3.23%, respectively. Finally, we arrived at a 10-year timeline for forest managers to transition to new decisions. In conclusion, the whole framework of this research will help forest managers to give the most reasonable forest management plan under the premise of ensuring the carbon sequestration capacity of the forest which can fully reflect the forest value.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
20 December 2022
ISBN
978-94-6463-030-5
ISSN
2589-4919
DOI
10.2991/978-94-6463-030-5_48How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Yitong Sun
PY  - 2022
DA  - 2022/12/20
TI  - Proposed Forest Carbon Sequestration Management Plan Based on Mathematical Modeling Method
BT  - Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)
PB  - Atlantis Press
SP  - 466
EP  - 481
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-030-5_48
DO  - 10.2991/978-94-6463-030-5_48
ID  - Sun2022
ER  -