温帯林における木材炭素率が樹木および森林生態系スケールの炭素推定に及ぼす影響の定量化
Quantifying the influence of wood carbon fractions on tree- and forest ecosystem-scale carbon estimation in a temperate forest (原題)
Adam R. Martin, Dilene Mugenzi, Sean C. Thomas, Audrey Barker Plotkin, Mahendra Doraisami, Mark Givelas, Adam Gorgolewski, Rachel. O. Mariani, David A. Orwig, Benton N. Taylor, Leeladarshini Sujeeun
🤖 gxceed AI 要約
日本語
カナダの温帯林で39,000本以上の樹木データと公開木材炭素率データベースを組み合わせ、種特異的な炭素率が樹木から森林スケールの炭素貯留量推定に与える影響を定量化。一般的な50%仮定やIPCC値と比較し、種特異的データが重要であることを示した。バイオマス密度の高い針葉樹林では最大23.5 Mg C/haの差が生じ、温帯林全体では2.2–2.5 Pg Cの過大評価につながる。
English
Using data from over 39,000 trees in a Canadian temperate forest, this study quantifies how species-specific wood carbon fractions affect carbon stock estimates from tree to forest scales. Compared to generic assumptions (e.g., 50% CF or IPCC values), species-specific data reduce bias, with differences up to 23.5 Mg C/ha in dense gymnosperm stands. Extrapolated to the temperate biome, the 50% assumption overestimates global carbon stocks by 2.2–2.5 Pg C, highlighting the need for species-specific data in forest carbon accounting.
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
日本の森林炭素計上やJ-クレジット制度においても、木材炭素率の精緻化は排出削減量の信頼性向上に寄与する。本研究成果は、国内の森林インベントリや炭素吸収源評価の精度向上に示唆を与える。
In the global GX context
This study provides empirical evidence that generic wood carbon fraction assumptions can significantly bias forest carbon stock estimates, with implications for global carbon accounting frameworks such as IPCC guidelines and national greenhouse gas inventories. It underscores the importance of species-specific data for accurate reporting under the Paris Agreement and voluntary carbon markets.
👥 読者別の含意
🔬研究者:Provides quantitative evidence on the sensitivity of forest carbon estimates to wood carbon fraction assumptions, informing methodological choices in carbon accounting research.
🏢実務担当者:Highlights the need for species-specific wood carbon fractions in forest carbon projects to ensure accurate carbon credit calculations and inventory reporting.
🏛政策担当者:Suggests that national forest carbon inventories should incorporate species-specific wood carbon fractions to improve accuracy in climate reporting and mitigation strategies.
📄 Abstract(原文)
Abstract. Accurate forest carbon (C) accounting is critical for understanding the role forests play in the global C cycle. Forest C accounting relies on wood carbon fractions (CF) in order to convert estimates of tree biomass into C stock estimates, which are then upscaled to estimate forest C stocks at larger spatial scales. Generic wood CFs are often used in C accounting frameworks, despite evidence suggesting this trait varies widely across species, and that this variability influences our understanding of C stocks in trees and forests. Here, we couple data from over 39,000 trees in a 13.5-ha forest dynamics plot in central Ontario, Canada, with open-access wood CF databases, to quantify how wood CFs influence C stock estimates at individual tree- through to 400 m2 and 1-ha forest ecosystem scales. In comparison to generalized wood CF assumptions (e.g., assuming a 50 % CF or using wood CFs from the Intergovernmental Panel on Climate Change), species-specific wood CFs significantly influence C estimates at multiple scales. In comparison to species-specific wood CF data, tree-level estimates derived from other wood CF assumptions were biased by 0.8–3.9 kg of C per tree on average, with differences ranging up to > 500 kg of C in large trees. While relatively small, these tree-level differences compound at larger spatial scales, with C stocks estimated using generalized wood CFs differing by 1.3–3.2 Mg of C ha−1 on average vs. those generated using species-specific wood CFs. These forest-scale discrepancies in C estimates increase in forest stands with high amounts of aboveground biomass in large trees and greater proportions of gymnosperms, in some instances exceeding 23.5 Mg of C ha−1 in especially biomass-dense gymnosperm-dominated forest stands. When extrapolated to the temperate forest biome, our results indicate that a 50 % wood CF assumption—historically and presently one of the most common methodological assumptions in forest C research—overestimates global C stocks by 2.2–2.5 Pg of C. Our study is among the first to examine how wood CF assumptions influence tree- and forest-scale C accounting. We specifically demonstrate that species-specific wood CF data—especially for species that comprise the largest trees—are critical to ensuring accurate C stock estimates derived from forest and tree inventory data.
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- openalex https://doi.org/10.5194/bg-23-5811-2026first seen 2026-08-27 04:53:42
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