作 者 ：欧洋,王晓燕*
期 刊 ：生态学报 2010年 30卷 23期 页码：6624~6634
Keywords:landscape, stream ecosystems, watershed hydrology, spatial scale, land use,
摘 要 ：从景观的视角研究河流生态系统，是目前河流生态学中受到广泛关注且发展迅速的内容之一。流域内多尺度景观强烈影响河流的理化及生物特征，已成为共识，但有关量度、整合景观与河流生态系统二者之间联系的理论体系与方法的建立尚处于起步阶段。对景观组成与空间格局影响河流生态系统的机制与途径进行了系统总结，提出了该领域研究中的主要难题，即如何识别景观中人为因素和自然因素的协变现象，如何衡量多空间尺度景观对河流生态系统的交互影响，如何理解景观阈值的不确定性。为克服当前研究面临的困难与挑战，填补已有知识的不足，提出今后研究的重点方向：河流景观分类系统的改进；更具代表性时空数据的采集；新型景观指标的开发与应用；微观尺度数据与宏观尺度数据的整合等。
Abstract:Understanding and measuring the key landscape factors and how they influence the characteristics of river ecosystems has been a central focus of those who study, manage, and use river systems. The development of assessment methods for lotic ecosystems, combined with advances in geographic information systems (GIS) and spatial analysis has resulted in a rapidly expanding literature linking land use to river response. Hundreds of studies provide strong evidence that increases in agricultural and urban land is frequently a predictor of a degraded state of the stream condition. Higher inputs of sediments, nutrients, and pesticides accompany increasing the extent of agricultural land within catchments. Major changes associated with increased urban land area include increases in the amounts and variety of pollutants in runoff, more erratic hydrology, increased water temperature and reduction in channel morphology and habitat. Recent studies in landscape ecology have paid particular attention to the spatial structure of landscapes in examining the relationships between land uses and river systems. From landscape ecological perspectives, the landscape pattern and other landscape information may play an important role in determining natural habitats, hydrological processes, energy flow and nutrient cycles. Although it has been recognized for some time that physicochemical and biological characteristics of rivers are strongly influenced by landscape within the surrounding watershed at multiple scales, the development of conceptual frameworks and tools for measuring and synthesizing such linkages is a relatively recent approach. Understanding the pathways and mechanisms through which land use influences stream conditions is aided by the comparative and empirical approaches that are the focus of this review; yet, such knowledge at present is extremely limited. Empirical associations between land use and stream response only succeed to varying in implicating influence pathways. In synthesizing these studies, three key challenges are identified for studying and managing landscape-river systems, which includes identifying covariation of anthropogenic and natural gradients in landscapes, measuring how various spatial-scale factors interactively influence instream habitat and biota and understanding uncertainties concerning the importance of thresholds. Natural and anthropogenic gradients often are cross-corelated, because human activities are most intensive in certain landscape settings, making it difficult to determine how extensive alterations of land cover by human activities modify natural river characteristics and their associated biological communities and assemblages. There is ample evidence that landscape factors influence river ecosystems across a wide range of spatial scales, but the roles of riparian buffer vs. larger scale factors may be difficult to separate. A non-linear response indicating a threshold is useful for managers, because it suggests a critical region of sensitivity of the ecosystem to a stress, and, therefore, helps to set acceptable limits. However, whether the threshold responses are widespread is uncertain, owing partly to the scatter that is common in empirical relationships between land use and stream response. Future research that focuses on overcoming the challenges and filling the knowledge gaps will substantially improve our understanding of river ecosystems. These include improving river-landscape classification; capturing appropriate spatial and temporal scale data; fueling the development of new landscape indicators for linking the functions and processes operating at various spatial scales and integrating data at molecular scales to landscape scales.
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