Files and links (2)
Formulating biomass allometric model for Paraserianthes falcataria (L) Nielsen (Sengon) in smallholder plantations, Central Kalimantan, Indonesia3.13 MB
Published VersionCC BY V4.0, Open Access
Journal article
Formulating biomass allometric model for Paraserianthes falcataria (L) Nielsen (Sengon) in smallholder plantations, Central Kalimantan, Indonesia
Forest Science and Technology, Vol.19(4), pp.268-284
2023
Abstract
The forests in Central Kalimantan, Indonesia have been heavily impacted by logging, mining, fires, and other degradation activities for over 30 years. To address this, the Indonesian government has promoted community-based forest management schemes. One such scheme, called Hutan Kemasyarakatan (HKm), has introduced Sengon (Paraserianthes falcataria) in smallholder plantations in Rungan Barat, Gunung Mas, Central Kalimantan. However, accurate estimation of biomass is crucial for carbon sequestration credits, but there are no specific allometric models for estimating Sengon above-ground biomass (AGB) in this area. To create a site-specific AGB allometric model for Sengon, 23 trees were felled to collect fresh biomass data. Various tree variables, such as diameter at breast height: 1.3 m (DBH), total height, merchantable height, and stem bole volume were measured for each sample tree. The average wood basic density of Sengon at the study site was also calculated. A total of nine alternative candidate regression equations were fitted and tested to select the best-fit AGB allometric model. Also, to assess the adaptedness of the identified AGB allometric model, comparisons with the models from literature, and comparisons between two interchangeable methodologies (i.e. direct biomass allometric model and biomass expansion factor (BEF)-based biomass estimation) were undertaken. This study has developed a regression function, denoted as Y=0.08062×DBH2.36816, to estimate the AGB of Sengon trees in smallholder plantations in Central Kalimantan, Indonesia. The formulated regression function demonstrated better estimation performance compared to common pantropical and regional AGB allometric models. In terms of the BEF-biomass approach, the AGB estimation derived from Smalian’s volume was relatively accurate, close to the mean AGB obtained by the formulated model in this study. In summary, this study proposes using the developed model, based solely on DBH, to accurately estimate AGB and carbon sequestration potential in Sengon trees. The accurate estimation of AGB using this model has additional advantages, including facilitating carbon credit acquisition and informing long-term management decisions.
Details
- Title
- Formulating biomass allometric model for Paraserianthes falcataria (L) Nielsen (Sengon) in smallholder plantations, Central Kalimantan, Indonesia
- Authors
- Md. Sazzad Hossain (Corresponding Author) - Technische Universität DresdenTomiwa Oluwajuwon (Author) - University of the Sunshine Coast, Queensland, Tropical Forests and People Research CentreAfentina N. Ludgen (Author) - University of Palangka RayaDavid P. Hasert (Author) - Fairventures Digital GmbH (Stuttgart, Germany)Marisa Sitanggang (Author) - Fairventures Social Forestry GmbH (Stuttgart, Germany)Chinedu Offiah (Author) - University of Göttingen
- Publication details
- Forest Science and Technology, Vol.19(4), pp.268-284
- Publisher
- Korean Forest Society
- Date published
- 2023
- DOI
- 10.1080/21580103.2023.2256355
- ISSN
- 2158-0715; 2158-0103
- Copyright note
- This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
- Grant note
- Fairventures Digital GmbH
- Organisation Unit
- Tropical Forests and People Research Centre; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99968898302621
- Output Type
- Journal article
Metrics
1 File views/ downloads
82 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Forestry
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites