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水质和水文因素的空间变化对城市水生态环境中食物网结构的影响。

Impact of spatial variations in water quality and hydrological factors on the food-web structure in urban aquatic environments.

机构信息

College of Water Sciences, Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing Normal University, Beijing, 100875, PR China; ICube, UdS, CNRS (UMR 7357), 300 Bld Sebastien Brant, CS 10413, 67412, Illkirch, France.

College of Water Sciences, Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing Normal University, Beijing, 100875, PR China.

出版信息

Water Res. 2019 Apr 15;153:121-133. doi: 10.1016/j.watres.2019.01.015. Epub 2019 Jan 22.

Abstract

Global aquatic ecosystems are essential to human existence and have deteriorated seriously in recent years. Understanding the influence mechanism of habitat variation on the structure of the food-web allows the effective recovery of the health of degraded ecosystems. Whereas most previous studies focused on the selection of driving habitat factors, the impact of habitat variation on the food-web structure was rarely studied, resulting in the low success rate of ecosystem restoration projects globally. This paper presents a framework for exploring the effects of spatial variations in water quality and hydrological habitat factors on the food-web structure in city waters. Indices for the evaluation of the food-web structure are first determined by integrating model-parameter extraction via literature refinement. The key water quality and hydrological factors are then determined by coupling canonical correspondence analysis with partial least squares regression. Their spatial variation is investigated using spatial autocorrelation. Finally, fuzzy clustering is applied to analyze the influence of the spatial variations in water quality and hydrological factors on the food-web structure. The results obtained in Ji'nan, the pilot city of water ecological civilization in China, show that the Shannon diversity index, connectance index, omnivory index, and the ratio of total primary production to the total respiration are important indicators of food-web structural change. They show that the driving factors affecting the aquatic food-web structure in Ji'nan are hydrological factors (e.g., river width, water depth, and stream flow), physical aspects of water quality (e.g., air temperature, water temperature, electrical conductivity, and transparency), and chemical aspects (e.g., potassium, dissolved oxygen, calcium, and total hardness). They also show that the stability of the food-web is more prone to spatial variations in water quality than in hydrological factors. Higher electrical conductivity, potassium, total hardness, and air temperature lead to deteriorated food-web structures, whereas better transparency improves structure and stability. We found that water and air temperature are the most important factors in the spatial variation of the food-web structure in the study area, followed by total hardness. Transparency is the least important factor. Large disparities and varied spatial distributions exist in the driving effects of water quality and hydrological factors across regions attributable to differences in geographical environments, water salinity (fresh vs. sea water), and environmental factors (e.g., water pollution). The above methods and results serve as a theoretical and scientific basis for a high success rate of aquatic ecosystem restoration projects in the study area and other cities worldwide.

摘要

全球水生生态系统对人类的生存至关重要,但近年来其严重恶化。了解栖息地变化对食物网结构的影响机制,可以有效促进退化生态系统的健康恢复。然而,大多数先前的研究侧重于选择驱动栖息地的因素,很少研究栖息地变化对食物网结构的影响,这导致全球生态系统恢复项目的成功率较低。本文提出了一个框架,用于探索水质和水文生境因素的空间变化对城市水域食物网结构的影响。首先通过文献提炼提取模型参数来确定食物网结构评估指标。然后通过典范对应分析与偏最小二乘回归耦合确定关键水质和水文因素。使用空间自相关研究它们的空间变化。最后,应用模糊聚类分析水质和水文因素的空间变化对食物网结构的影响。以中国水生态文明试点城市济南为例,结果表明香农多样性指数、连接度指数、杂食性指数和总初级生产力与总呼吸之比是食物网结构变化的重要指标。研究表明,影响济南水生生境结构的驱动因素是水文因素(如河宽、水深和水流)、水质的物理方面(如空气温度、水温、电导率和透明度)以及化学方面(如钾、溶解氧、钙和总硬度)。研究还表明,与水文因素相比,食物网的稳定性更容易受到水质空间变化的影响。较高的电导率、钾、总硬度和空气温度会导致食物网结构恶化,而较好的透明度则会改善结构和稳定性。研究发现,水温和空气温度是研究区域食物网结构空间变化的最重要因素,其次是总硬度。透明度是最不重要的因素。由于地理位置、水的盐度(淡水与海水)以及环境因素(如水污染)的差异,水质和水文因素的驱动作用在不同地区存在较大差异和不同的空间分布。上述方法和结果为研究区及全球其他城市的水生生态系统恢复项目提供了高成功率的理论和科学依据。

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