Beyond Traditional PES: A Hydrology-Integrated Blockchain System for Forest Carbon, Water Regulation, and Invasive Species Control in the Himalayas
従来のPESを超えて:ヒマラヤにおける森林炭素、水調整、外来種対策のための水文学統合型ブロックチェーンシステム (AI 翻訳)
Ram Ranjan
🤖 gxceed AI 要約
日本語
本研究は、ヒマラヤ地域の森林が提供する炭素吸収・水調整・外来種対策を統合的に評価するブロックチェーン型PESモデルを提案。生態指標に連動したトークン価格が、コミュニティの行動インセンティブを従来型PESより改善することを示す。火災リスク下では、不確実な将来炭素クレジットの先行販売によりリスク移転が可能となり、保全努力が向上する。
English
This study develops a blockchain-enabled bioeconomic model integrating forest growth, water services, invasive species dynamics, and fire risk. Token prices adjust to ecological indicators, creating incentives for communities to balance immediate income vs. long-term ecosystem gains. Under fire risk, blockchain crediting allows risk transfer to buyers, supporting higher conservation than traditional PES.
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
日本の森林炭素クレジット制度(J-クレジット)や水環境保全施策において、生態系サービスを統合したインセンティブ設計は参考になる。特に、ブロックチェーンによる透明性向上とリスク移転機能は、今後の国内制度設計にも示唆を与える。
In the global GX context
This paper advances global understanding of how blockchain can enhance payment for ecosystem services by linking payments to real-time ecological data. It offers a novel approach to integrating carbon, water, and fire risk, relevant for nature-based solutions and climate finance discourse.
👥 読者別の含意
🔬研究者:Researchers in ecological economics and blockchain applications can explore the bioeconomic modeling framework and its implications for incentive design under uncertainty.
🏢実務担当者:Practitioners designing PES programs or carbon credit projects may find the dynamic token pricing and risk-transfer mechanism useful for improving community engagement.
🏛政策担当者:Policymakers in forestry and climate adaptation can consider how blockchain-based systems might complement existing carbon markets and enhance resilience in vulnerable ecosystems.
📄 Abstract(原文)
Water-related ecosystem services, such as infiltration, streamflow regulation, and water quali-ty, are central to the wellbeing of forest-dependent Himalayan communities but are increas-ingly threatened by forest degradation, Lantana camara invasion, and rising fire risk. Con-ventional Payments for Ecosystem Services (PES) and carbon-focused afforestation schemes rarely capture these hydrological co-benefits or the strategic trade-offs communities face un-der ecological uncertainty. This study develops a hydrology-integrated, blockchain-enabled bioeconomic model that links forest growth, water-service valuation, lantana dynamics, and fire risk to a performance-indexed token pricing system. Token values adjust in real time to ecological indicators such as carbon buffer size, water-service gains, cumulative harvesting, invasive-species pressure, and fire hazard, with smart contracts converting these indicators into payments. Results show that blockchain-based pricing creates strategic incentives not present in traditional PES. Communities face a trade-off between early credit sales for imme-diate income and retaining larger carbon buffers that strengthen water services and future to-ken values. When post-fire income is absent, high fire risk encourages precautionary liquida-tion. However, when post-fire income streams such as water PES and fuelwood are available, this effect is moderated, and higher risk can instead reduce token prices and dampen sales. Strong hydrological benefits and rising token-price trends promote long-term accumulation. Lantana removal competes across oak and pine stands, revealing tensions among hydrologi-cal gains, fire reduction, and restoration costs. Policy experiments indicate that subsidies and higher water-PES payments shift outcomes toward greater restoration and improved water-shed resilience. Under explicit fire risk, blockchain-based crediting enables communities to partially transfer wildfire-related financial risk to external buyers by monetizing uncertain future carbon benefits, thereby supporting higher conservation effort than would be possible under traditional PES.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1142/s2382624x26500062first seen 2026-05-15 17:16:04
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