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应用生态学报 ›› 2009, Vol. 20 ›› Issue (12): 3084-3092.

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湿地景观生态分类研究进展

曹宇**;莫利江;李艳;章文妹   

  1. 浙江大学土地管理系, 杭州 310029
  • 出版日期:2009-12-18 发布日期:2009-12-18

Wetland landscape ecological classification: Research progress.

CAO Yu;MO Li-jiang|LI Yan|ZHANG Wen-mei   

  1. Department of Land Management, Zhejiang University, Hangzhou 310029, China
  • Online:2009-12-18 Published:2009-12-18

摘要: 湿地景观生态分类是湿地景观生态学研究的前提与基础,直接影响湿地研究结果的精度和有效性.基于国内外湿地景观生态分类在分类理论、分类指标、分类方法等方面的研究历史、现状与最新进展,本文系统介绍并评价了NWI、Ramsar、HGM等湿地分类体系,指出基于HGM分类思想以及综合考量湿地空间结构、生态功能、生态过程、地形、土壤、植被、水文、人类活动干扰强度等多种因素的混合分类方法是该研究领域未来发展的主要方向.集成运用3S技术、数学定量、景观模型、知识工程、人工智能、神经网络等多种方法以提高分类的自动化水平与精度,将是今后湿地景观生态分类研究的重点与难点.

关键词: 景观生态学, 湿地分类, 美国国家湿地清查, Ramsar公约, 水文地貌法, 树木年代学, 树木年轮气候学, 木材解剖, 林线动态

Abstract: Wetland landscape ecological classification, as a basis for the studies of wetland landscape ecology, directly affects the precision and effectiveness of wetland-related research. Based on the history, current status, and latest progress in the studies on the theories, indicators, and methods of wetland landscape classification, some scientific wetland classification systems, e.g., NWI, Ramsar, and HGM, were introduced and discussed in this paper. It was suggested that a comprehensive classification method based on HGM and on the integral consideration of wetlands spatial structure, ecological function, ecological process, topography, soil, vegetation, hydrology, and human disturbance intensity should be the major future direction in this research field. Furthermore, the integration of 3S technologies, quantitative mathematics, landscape modeling, knowledge engineering, and artificial intelligence to enhance the automatization and precision of wetland landscape ecological classification would be the key issues and difficult topics in the studies of wetland landscape ecological classification.

Key words: landscape ecology, wetland classification, NWI, Ramsar Convention, hydrogeomorphic method (HGM), dendrochronology, dendroclimatology, wood anatomy, treeline dynamics.