Mulyana, Budi and Polgár, András and Vityi, Andrea (2023) Three Decades of Forest Carbon Dynamics Modeling Using CO2FIX: A Bibliometric Analysis. Evergreen, 10 (4). 2105 – 2119. ISSN 21890420
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Abstract
Forest carbon modeling is essential in climate change mitigation activities. Projection of forest carbon for a certain period can be used to develop other actions to mitigate climate change, such as public policy, forest management scenarios, and other interventions to reduce greenhouse gas emissions. The CO2FIX model estimates carbon content through empirical growth data that is a user-friendly measurement for forest managers. This review article aims to describe the research trends in forest carbon dynamics modeling using CO2FIX. Our findings show that CO2FIX has been applied to a wide range of forest types in 27 countries. The most productive researchers have come from China, India, the Netherlands, and Spain. However, collaboration among researchers across countries has been limited. The number of articles related to CO2FIX indexed by the Scopus or the Web of Science (WoS) database has gradually increased since the first was published in 1995. Furthermore, the top five items used in the CO2FIX publications were carbon sequestration, CO2FIX, carbon, forestry, and forest management. In conclusion, CO2FIX is a user-friendly, forest carbon dynamics model that is used widely by researchers for various types of forests and results in a precise estimation. Furthermore, based on 63 articles indexed by the Scopus database and 50 articles indexed by WoS, collaboration among researchers should increase to solve more complex problems related to climate change mitigation in the forestry sector. © 2023 Novel Carbon Resource Sciences. All rights reserved.
Item Type: | Article |
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Additional Information: | Cited by: 3; All Open Access, Gold Open Access |
Uncontrolled Keywords: | climate change, forest types, research trends, carbon sequestration, VOSviewer |
Subjects: | S Agriculture > SD Forestry |
Divisions: | Faculty of Forestry |
Depositing User: | Sri JUNANDI |
Date Deposited: | 14 Nov 2024 07:52 |
Last Modified: | 14 Nov 2024 07:52 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/11082 |