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李婷,吕一河.生态系统服务建模技术研究进展.生态学报,2018,(15).http://dx.doi.org/10.5846/stxb201708291562  
生态系统服务建模技术研究进展
A review on the progress of modeling techniques in ecosystem services
投稿时间:2017-08-29  修订日期:2018-03-07
DOI: 10.5846/stxb201708291562
关键词生态系统服务  建模技术  模型  决策支持
Key Wordsecosystem services  modeling techniques  models  decision support
基金项目国家重点研发计划重点专项(2016YFC0501601)* 通讯作者 Corresponding author.E-mail: lyh@ rcees.ac.cn
作者单位E-mail
李婷 中国科学院生态环境研究中心 tli_st@rcees.ac.cn 
吕一河 中国科学院生态环境研究中心 lyh@rcees.ac.cn 
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摘要:
在生态系统服务评估模型的数量、类型及应用大量增加的背景下,为将生态系统服务评估有效整合到决策中,系统比较、甄别不同建模工具并筛选出适合决策需求的生态系统服务评估和模拟方法尤为必要。因此,归纳并总结了国内外现有的生态系统服务评估模型的建模技术,包括:相关关系法、生物-物理过程法以及专家知识法;分别对其原理、差异、优缺点以及适用性进行了详尽阐释。大多数相关模型侧重于统计关系,相对容易创建和扩展,适用于生态系统服务的初始评估;生物-物理过程模型难以构建且不易获取,但提供了探索人-地系统相互作用和长期变化的有效机制;专家知识法有效结合了多种类型的知识体系,关注人类社会与自然系统之间反馈和交互动态的系统整合,但当评估地点发生变化时难以验证。在此基础上,本文介绍了基于上述3种建模技术的典型生态系统服务综合评估模型的发展和应用现状。各类建模技术面临着实用性和科学准确性之间的权衡。通过对不同建模技术的梳理与整合分析旨在提升当前生态系统服务研究的决策支撑能力,并为国内相关研究提供参考和借鉴。
Abstract:
The number, diversity and application of ecosystem service models has greatly increased over the past decade. To integrate ecosystem service assessment into decision-making processes, systematically comparing and examining the different tools to identify the corresponding approaches that apply to decision requirements are especially essential and important. In this context, we summarized the existing modeling techniques for ecosystem service assessments nationally and internationally, including correlative models, process-based models, and expert-based models. We analyzed their principles, differences, advantages, and disadvantages in detail. Each of these modeling approaches had strengths and weaknesses that made them a better fit to different decision contexts: (1) the correlative models focused on existing statistical relationships, which were easy to use, to create and to revise making these types of models useful in initial or rapid assessments. However, the weakness was that they could dramatically fail in data-poor situations. (2) Process-based models, which represented a scientific understanding of key dynamics for ecosystem services, were difficult to produce and to access but allowed the exploration of interactions and long-term dynamics in human-earth systems. (3) Expert-based models could facilitate to achieve the incorporation of diverse types of expert knowledge into ecosystem service assessments, which was particularly useful for bridging multiple knowledge systems as well as focusing on the interactions among people and nature systems. However, the expert-based models were often only partial and were difficult to verify from place to place. Furthermore, the applications of typical ecosystem service assessments models based on the three techniques were systematically reviewed and discussed. Our study highlighted that these modeling approaches had to compromise between usability and scientific accuracy, which meant that practitioners need to weigh their requirements for specific projects carefully before deciding on the appropriate tools. The analysis and integration of different modeling techniques would enhance the capabilities of decision support for ecosystem services assessments, and help to provide information and reference for domestically relevant research.
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