空間的な林齢ベース枠組みを用いたマングローブ定着軌跡と炭素回復ポテンシャルの評価
Evaluating mangrove establishment trajectories and carbon recovery potential using a spatial age-based framework (原題)
Yuxuan Zhao, Tong Li, Bohan Zheng, Xinyu Wang, Yifan Wang, Qiyue Zhang, Zheng Xiao, Nan Xu, Yuxin Chen, Yangfan Li
🤖 gxceed AI 要約
日本語
Landsat時系列とLandTrendr変化検出、林齢別ロジスティック成長モデルを組み合わせ、中国海南島のマングローブ定着状況を30m解像度で2000〜2023年にわたり地図化した研究。2023年時点で337haが定着し、その半数超が林齢7年以下ながら成熟林炭素量の43%を既に蓄積していることを示す。継続保護下での炭素貯留潜在量は約33,668Mg Cと推計され、林齢に応じた差別的管理と国家炭素クレジット市場への基盤提供を訴える。
English
This study maps established mangroves across Hainan Island, China (2000–2023) at 30-m resolution by combining an optimized LandTrendr change-detection algorithm with age-stratified logistic growth models. It finds 337 ha established by 2023, with over half ≤7 years old yet already holding 43% of mature-forest carbon stocks. Under continued protection, these stands could store ~33,668 Mg C, supporting differentiated management and national carbon credit baselines.
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
日本でもブルーカーボン生態系はJ-クレジット制度や自治体の脱炭素先行地域で注目されるが、面積ベース評価の限界は国内でも共通課題。林齢別の炭素回復軌跡を定量化する本枠組みは、国内の藻場・干潟クレジットの品質担保やモニタリング高度化の参考になる。
In the global GX context
As nature-based solutions gain traction in voluntary carbon markets and biodiversity frameworks (TNFD, SBTN), area-based restoration metrics are increasingly criticized. This age-based, spatially explicit framework offers a replicable approach for verifying blue-carbon credit integrity and aligning restoration monitoring with emerging disclosure and offset standards.
👥 読者別の含意
🔬研究者:林齢構造を組み込んだ炭素蓄積モデリングとリモートセンシング変化検出の統合手法として参考になる。
🏢実務担当者:ブルーカーボンクレジット創出や自然資本開示を検討する企業が、面積ではなく回復段階に基づくモニタリング設計に活用できる。
🏛政策担当者:炭素クレジット制度や生態系回復政策において、面積指標から林齢・機能回復指標への移行を検討する際の根拠となる。
📄 Abstract（原文）
Abstract Mangrove restoration is a vital nature-based solution for climate change mitigation and biodiversity conservation. However, large-scale mangrove restoration success is predominantly evaluated using area-based metrics, which fail to capture the complex temporal trajectories of forest structural and functional recovery. Stand age directly determines structural heterogeneity and carbon stocks, making it a key indicator for monitoring recovery trajectories and estimating carbon stocks. We developed a spatial age-based framework to map established mangrove stands and quantify the existing carbon stock and remaining potential. To this end, we combined an optimized LandTrendr change-detection algorithm with age-stratified logistic growth models using Landsat time-series data. We generated a 30-m resolution age map of all established mangroves from 2000 to 2023 across tropical Hainan Island, China. Our results identified 337 ha of established mangroves as of 2023. Notably, >50% (173 ha) of the detected stands are ≤7 years old yet have already attained 43% of mature forest carbon stocks, whereas only 4% of them have reached ≥15 years. Under continued protection, these forests are expected to store an estimated 33,668 Mg C (27,971-38,902 Mg C), with the greatest potential concentrated in the Dongzhaigang area. Conversely, the limited extent of older forests (4% of the established area) already secures significant recovered carbon stocks, warranting urgent protection. This contrast underscores the necessity of differentiated management strategies calibrated to both restoration scale and stand development stage. Ultimately, this spatially explicit framework informs evidence-based management to improve restoration outcomes and provides actionable baselines for national carbon credit markets.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1088/1748-9326/aeb621first seen 2026-10-21 04:45:23
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