The importance of large trees as carbon sinks in UK woodlands
英国の森林において大径木が炭素吸収源として重要であること (AI 翻訳)
Wilkes P, Castro G, Digby M, Openshaw I, Barber R, Egan G, Moat J, Roberts R, Wilkinson T
🤖 gxceed AI 要約
日本語
英国の森林において、大径木が地上部炭素（AGC）の不均衡な吸収源であることを、地上LiDAR計測により実証。従来のサイズ-重量アロメトリー法（英国のWoodland Carbon Codeを含む）は、特に古木広葉樹林でAGCを最大70%過小評価する。既存手法の適用範囲に注意が必要で、新たなアロメトリーの開発には大型木を対象としたLiDAR手法が有効。
English
Terrestrial LiDAR data from UK woodlands show large trees are disproportionate sinks of aboveground carbon (AGC). Existing allometric methods, including the UK's Woodland Carbon Code, underestimate AGC by up to 70% in ancient broadleaf woodlands. The study urges caution when applying these methods beyond their intended scope and suggests LiDAR-based approaches for developing new allometry for large trees.
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
本論文は英国の森林炭素計算法の問題を指摘するが、日本のJ-クレジット制度における森林炭素吸収量の算定にも示唆を与える。特に、大径木の寄与を過小評価する既存アロメトリー式の適用範囲を再検討する必要がある。
In the global GX context
This paper challenges widely used allometric methods (e.g., UK Woodland Carbon Code) for forest carbon accounting by showing large trees' disproportionate contribution. It offers LiDAR as a scalable alternative, relevant to global carbon reporting under TCFD/ISSB and voluntary carbon markets.
👥 読者別の含意
🔬研究者:Highlights the need for improved allometry for large trees and demonstrates LiDAR as a viable calibration tool.
🏢実務担当者:Forest carbon project developers should reassess their AGC estimation methods, especially in old-growth stands, as underestimation can affect carbon credit revenues.
🏛政策担当者:Carbon code authorities should consider updating methodologies to incorporate large-tree contributions and LiDAR verification.
📄 Abstract（原文）
<title>Abstract</title> <p>Background: Temperate forests are globally important sinks of terrestrial carbon, therefore accurately mapping the distribution of carbon in these forests is an important first step in preserving this sink as well as to meet reporting requirements for country’s progressing towards net-zero. Conventional size-to- mass methods to estimate the aboveground carbon (AGC) pool are not scale invariant and tend to underestimate the contribution of large trees. Here, we use terrestrial LiDAR to estimate AGC density across three forest and woodland types typical of the UK, and compare these to estimates derived from widely applied size-to-mass allometric approaches. <h4>Results:</h4> Analysis of terrestrial LiDAR data captured across Kew Wakehurst, UK, indicate large trees are a disproportionate sink of AGC across both broadleaf woodland and conifer plantation. A suggested reason for this is the allocation of woody material to support the larger, spreading crowns of dominant trees which is not captured in existing allometry. A comparison with existing approaches reveals an underestimation of AGC across all three forest types, for example, the UK’s Woodland Carbon Code (WCC) underestimated AGC by up to 70% in ancient broadleaf woodlands when compared to a terrestrial LiDAR approach. <h4>Conclusion:</h4> Application of allometric methods to out-of-sample woodland types inevitably leads to an underestimation in AGC. We stress that existing methods, such as the WCC, are fit for purpose in the woodland types they are intended for; however, caution must be used when applying these methods more broadly. Owing to the concentration of AGC in a few large trees, we suggest new size- to-mass allometry needs to be developed using appropriately sized trees. As destructive harvest of large trees is rarely feasible, terrestrial LiDAR methods could be used to estimate the “mass” side of a size-to-mass equation.</p>
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.21203/rs.3.rs-10017170/v1first seen 2026-07-17 04:30:50
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