気候変動下における草原の生物多様性と炭素の共便益最適化：気候・生態・経済の統合モデリング枠組み
Optimizing grassland biodiversity and carbon co-benefits under climate change: An integrated climate-ecological-economic modelling framework (原題)
Rong‐Gang Cong, Xin Zhang, Wenying Han, Apostolos Kyriazopoulos, Henrik G. Smith
🤖 gxceed AI 要約
日本語
中国内モンゴル典型草原を対象に、気候・生態・経済を統合したモデリング枠組みを構築し、炭素隔離と生物多様性のトレードオフを評価した。蝶を指標とし、SSPシナリオ下でNSGA-IIにより2025〜2050年の刈取り・放牧の最適配置（パレート解）を導出。降水変動が温度より共管理ポテンシャルに大きく影響し、最適解は刈取り優位（77〜94%）となった。機会費用を組み込み、地域経済制約下での移転可能な手法を提示する。
English
An integrated climate-ecological-economic framework evaluates biodiversity-carbon trade-offs in Inner Mongolian steppe grasslands. Using butterflies as biodiversity indicators and NSGA-II optimization under SSP1-2.6 to SSP5-8.5, it derives Pareto-optimal mowing-grazing configurations for 2025-2050. Precipitation shifts mattered more than temperature; optimized solutions were mowing-dominated (77-94%). Opportunity-cost accounting adds a regional economic layer, offering a transferable approach for grassland co-management.
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
日本では草原（採草地・放牧地）の炭素貯留と生物多様性はTNFD・ネイチャーポジティブ文脈で関心が高まるが、本論文は中国事例であり直接の政策接続は弱い。ただし自然資本・生物多様性と炭素の共便益を定量化する統合モデル手法は、日本企業のTNFD対応や農業・土地利用セクターの気候-自然統合評価に方法論的示唆を与える。
In the global GX context
This work sits at the intersection of climate mitigation and biodiversity (nature) agendas increasingly linked in global disclosure frameworks such as TNFD and the ISSB's nature-related work. Its integrated modelling of carbon-biodiversity co-benefits under climate scenarios offers a methodological template for quantifying nature-climate trade-offs, though the empirical case is regionally specific to Inner Mongolia.
👥 読者別の含意
🔬研究者:気候・生態・経済を統合しパレート最適解を導く枠組みは、自然資本と炭素の共便益評価研究の方法論的参照点となる。
🏢実務担当者:TNFDや自然関連開示で炭素と生物多様性のトレードオフを定量化する際の統合的評価アプローチとして参考になる。
🏛政策担当者:草原管理の気候・生物多様性政策を統合設計する際、シナリオ別の最適管理配置と機会費用の考え方が示唆を与える。
📄 Abstract（原文）
Managing grasslands for both carbon sequestration and biodiversity conservation is increasingly challenging under climate change. We develop an integrated climate–ecological–economic modelling framework to evaluate biodiversity–carbon trade-offs in the Inner Mongolian typical steppe, where mowing and grazing are dominant management practices. Using butterflies as biodiversity indicators, carbon-sequestration estimates, regional opportunity-cost parameters, and downscaled climate projections under SSP1–2.6, SSP2–4.5, and SSP5–8.5, we applied the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to identify Pareto-optimal mowing–grazing configurations from 2025 to 2050. The simulations indicated that, within the parameterized water-limited response functions, projected precipitation differences were associated with larger shifts in biodiversity–carbon co-management potential than temperature differences. Under the assumptions of our modelling framework, optimized configurations were generally mowing-dominated, with mowing accounting for 77%–94% of the management-allocation matrix in representative 2030 solutions, although grazing-oriented patches remained important in biodiversity-priority outcomes by maintaining habitat heterogeneity. Opportunity-cost accounting provided a regional economic comparison layer for Pareto-optimal configurations, with temporal cost increases mainly reflecting the assumed annual escalation and cross-scenario differences reflecting the cost ranges of feasible Pareto-optimal solutions. Overall, the framework provides a transferable approach for linking climate scenarios, land-use allocation, ecological outcomes, and economic constraints in grassland biodiversity–carbon co-management, subject to recalibration with local ecological, management, and economic parameters.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.landusepol.2026.108368first seen 2026-10-16 05:09:24
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