城市人工构筑物的多尺度生态影响

人工构筑物是城市生态系统的重要组成部分,是人-自然耦合关系的基本作用单元。自然要素中的水、土、气、生通过人工构筑物这一基本单元作用或影响人的生存、健康与发展,而人通过构筑物作用或影响自然中的水、土、气、生,进一步进化成人为主导、构筑物为基础、自然要素为条件的城市生态系统。论文综述了近年来人工构筑物多尺度生态影响的研究进展,评述了人工构筑物对土壤（水）、大气、生物生态影响的前沿动态,提出了各研究分支的关注重点及要解决的关键问题,分析了人工构筑物生态学研究的方法学问题与挑战,展望了未来该领域的基本发展走向。论文认为,构筑物生态影响涉及城乡水、土、气、生及人的健康等不同方面,现有的相关研究分散而局部,且受技术方法局限,分析结果存在很大的不确定性,研究面临巨大的转型挑战。未来构筑物生态学研究需要多学科、多尺度、多层次的系统化方法与技术的推动,城乡生态观测与实验技术的发展、多源数据处理技术以及智能计算方法的创新是该领域取得重大发展的基础与条件。

Multiple-scale Ecological Impacts of Artificial Structures in Urban Ecosystems

Artificial structures (constructions) are important components of urban ecosystems and essential unit of human-nature coupling relations. The water, soil, air and organisms in natural ecosystems exert their functions through artificial structures on human survival, health and development. On the contrary, human activities also influence the water, soil, air and organism in natural ecosystems through artificial structures. This interaction facilitates the development of urban ecosystems. This paper summarizes recent research progresses in multiple-scale ecological impacts of artificial structures on water, soil, atmosphere and organisms in urban ecosystems, and presents the focus points in this research field and key issues to be resolved. The paper analyzes the methodological difficulties and challenges in ecology of artificial structures, and finally proposes some future tendencies in this field. The authors point out that the diversified ecological impacts of artificial structures cover the various aspects of water, soil, atmosphere and organism in urban and rural ecosystems. Current researches on this topic are dispersive and local concerned, the methods and techniques are limit, and the results of analysis have great uncertainty. Future research on key issues of this topic needs powerful multiple-scale or multiple-level approaches by means of integration of multiple-disciplinary methods, and the research will be better promoted through developing advanced techniques of ecological field observation and experiment and innovating the technology and intellectual computing for processing multiple-source or multiple-level data, and intellectual computing.