将两种环境服务结合在一个单一的PES项目下是否能产生更好的环境结果和更低的成本?

IF 1.8 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES Natural Resource Modeling Pub Date : 2021-04-16 DOI:10.1111/nrm.12303
R. Ranjan
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引用次数: 0

摘要

本文开发了一个集成框架,用于为提供多种环境服务的生态系统服务(PES)机制建模。具体而言,在社区主导的PES下,促进森林保护以实现碳和溪流的效益。上游社区通过联合国减少森林砍伐和森林退化造成的排放方案(REDD)获得避免薪材采伐的报酬,而向下游社区出售水则产生额外收入。生物经济模型得出了薪柴采伐的最佳水平,这与森林物种组成的变化、河流水文和火灾风险、对PES项目碳和水生成潜力的影响相结合。结果表明,当水和碳服务相结合时,森林保护效果更好,但在基于碳的PES下,该计划的总成本更低。森林物种组成的变化造成了水和碳效益之间的权衡。森林火灾通过减少河流流量和碳固存潜力,进一步挑战PES方案的可行性。
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Can combining two environmental services under a single PES program result in better environmental outcomes and lower costs?
This paper develops an integrated framework for modeling payment for ecosystem services (PES) mechanisms that deliver multiple environmental services. Specifically, under a community‐led PES, forest conservation is promoted to deliver carbon and stream water benefits. The upstream community is paid for avoided fuelwood harvesting through a United Nations programme on reducing emissions from deforestation and forest degradation (REDD) program, whereas additional income is generated from water sales to the downstream communities. A bio‐economic model derives optimal level of fuelwood harvesting, which in conjunction with the changing species composition of forests, streamflow hydrology and fire risks, impacts on the carbon and water generation potential of the PES project. Results indicate that forest conservation outcomes are better when water and carbon services are combined, however overall cost to the program is lower under a carbon‐based PES. Changing species composition of forests creates tradeoffs between water and carbon benefits. Forest fires further challenge the viability of PES schemes through reducing streamflow and carbon sequestration potential.
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来源期刊
Natural Resource Modeling
Natural Resource Modeling 环境科学-环境科学
CiteScore
3.50
自引率
6.20%
发文量
28
审稿时长
>36 weeks
期刊介绍: Natural Resource Modeling is an international journal devoted to mathematical modeling of natural resource systems. It reflects the conceptual and methodological core that is common to model building throughout disciplines including such fields as forestry, fisheries, economics and ecology. This core draws upon the analytical and methodological apparatus of mathematics, statistics, and scientific computing.
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