Carbon Emissions from Selective Logging: Case of FMU 1525 (Southern Cameroon)
選択伐採からの炭素排出：FMU 1525（カメルーン南部）の事例 (AI 翻訳)
Rodine Lontsi, Arsene Abena, E. Ngahane, Charles Sap, M. Ngaba
🤖 gxceed AI 要約
日本語
この研究はカメルーンの選択伐採による炭素排出量を評価し、低影響伐採（LIP）の実践が不十分であることを明らかにしました。インフラ建設が最大の排出源であり、全体の排出係数は1.067 t C/m³でした。排出削減のための作業手順コードが提案されています。
English
This study assesses carbon emissions from selective logging in Cameroon, finding an overall emission factor of 1.067 t C/m³ logged. Infrastructure construction is the largest source. Low-impact logging practices were applied only 35% of the time, and a work procedure code is proposed to reduce emissions.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
カメルーンの事例ですが、森林炭素会計の手法や低影響伐採の知見は、日本の森林管理や温室効果ガスインベントリにも応用可能性があります。
In the global GX context
This paper provides empirical emission factors for selective logging in African forests, contributing to REDD+ carbon accounting and sustainable forest management globally. It highlights the gap between low-impact logging principles and practice.
👥 読者別の含意
🔬研究者:This paper provides empirical emission factors and highlights the need for improved forest management practices to reduce carbon emissions from selective logging.
🏢実務担当者:Forestry companies can use the emission factors and work procedure code to estimate and reduce their carbon footprint.
🏛政策担当者:Policymakers in tropical forest countries can use this data to inform REDD+ strategies and enforce low-impact logging standards.
📄 Abstract（原文）
Logging activities significantly impact climate change by contributing to greenhouse gas emissions. However, scientific data on this subject for African forests is limited. This study assesses carbon emission rates resulting from selective logging in Cameroon and proposes measures to mitigate emissions associated with this activity. The research was conducted in Annual Cutting Area 3-1 of Forest Management Unit 1525, known as the "Municipal Forest of Efoulan and Ebolowa 1st." Field data on damaged and extracted biomass were collected across three 15-ha plots and compiled in Microsoft Excel. GPS-derived spatial data were processed using DNRGPS and visualized with ArcGIS 10.5. Allometric equations were applied to dendrometric measurements to estimate aboveground biomass, which was converted to carbon using a factor of 0.5. Emission factors were calculated per cubic meter of extracted wood, and polynomial regression models were used to extrapolate results to the entire cutting area. Open-ended questionnaires administered to site staff and direct field observations evaluated logging technique compliance. Data analysis revealed a logging intensity of 1.6 stems/ha with an average extracted volume of 16.18 m³/ha. Infrastructure construction was identified as the primary source of carbon emissions at 0.497 t C/m³, followed by residues from extracted wood at 0.412 t C/m³. The overall emission factor was 1.067 t C/m³ logged, totaling approximately 17.072 t C/ha. Evaluation of logging techniques indicated that low-impact logging practices (LIP) were applied only 35% of the time. A work procedure code aligned with the regional LIP code has been proposed to reduce emissions. The findings underscore the urgent need for improved forest management practices that prioritize sustainability and carbon sequestration, with stakeholder engagement enhancing implementation effectiveness.
🔗 Provenance — このレコードを発見したソース
- semanticscholar http://article.sciencepg.com/pdf/j.ijnrem.20261101.16first seen 2026-07-24 06:59:45
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。