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首页> 外文期刊>The Science of the Total Environment >Agriculture versus wastewater pollution as drivers of macroinvertebrate community structure in streams
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Agriculture versus wastewater pollution as drivers of macroinvertebrate community structure in streams

机译:农业与废水污染是河流中无脊椎动物群落结构的驱动力

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摘要

Water pollution is ubiquitous globally, yet how the effects of pollutants propagate through natural ecosystems remains poorly understood. This is because the interactive effects of multiple stressors are generally hard to predict. Agriculture and municipal wastewater treatment plants (WWTPs) are often major sources of contaminants for streams, but their relative importance and the role of different pollutants (e.g. nutrients or pesticides) are largely unknown. Using a 'real world experiment' with sampling locations up-and downstream ofWWTPs, we studied how effluent discharges affected water quality and macroinvertebrate communities in 23 Swiss streams across a broad land-use gradient.Variation partitioning of community composition revealed that overall water quality explained approximately 30% of community variability, whereby nutrients and pesticides each independently explained 10% and 2%, respectively. Excluding oligochaetes (which were highly abundant downstream of the WWTPs) from the analyses, resulted in a relatively stronger influence (3%) of pesticides on the macroinvertebrate community composition, whereas nutrients had no influence. Generally, the macroinvertebrate community composition downstream of the WWTPs strongly reflected the upstream conditions, likely due to a combination of efficient treatment processes, environmental filtering and organismal dispersal. Wastewater impacts were most prominently by the Saprobic index, whereas the SPEAR index (a trait-based macroinvertebrate metrics reflecting sensitivity to pesticides) revealed a strong impact of arable cropping but only a weak impact of wastewater.Overall, our results indicate that agriculture can have a stronger impact on headwater stream macroinvertebrate communities than discharges fromWWTP. Yet, effects of wastewater-born micropollutants were clearly quantifiable among all other influence factors. Improving our ability to further quantify the impacts of micropollutants requires highly-resolved water quality and taxonomic data with adequate spatial and temporal sampling. These improvements would help to better account for the underlying causal pathways that drive observed biological responses, such as episodic contaminant peaks and dispersal-related processes. (C) 2018 Elsevier B.V. All rights reserved.
机译:水污染在全球范围内无处不在,但是对污染物如何通过自然生态系统传播的了解仍然很少。这是因为通常很难预测多个压力源的交互作用。农业和市政废水处理厂(WWTP)通常是溪流污染物的主要来源,但是它们的相对重要性和不同污染物(例如养分或农药)的作用在很大程度上尚不清楚。通过对污水处理厂上游和下游采样位置的``现实世界实验'',我们研究了污水排放如何在广阔的土地利用梯度上影响了23条瑞士河流中水质和大型无脊椎动物群落。群落组成的变化划分显示,总体水质得到了解释大约30%的社区变异,其中养分和农药分别分别解释了10%和2%。从分析中剔除寡果类(在污水处理厂下游高度丰富)后,农药对大型无脊椎动物群落组成的影响相对较大(3%),而养分则没有影响。通常,污水处理厂下游的大型无脊椎动物群落组成强烈反映了上游条件,这可能是由于有效的处理过程,环境过滤和生物扩散共同作用的结果。腐殖质指数对废水的影响最为显着,而SPEAR指数(基于性状的无脊椎动物指标反映了对农药的敏感性)显示了耕作的强大影响,但废水的影响很小。总体而言,我们的结果表明农业可以对水源地大型无​​脊椎动物群落的影响要大于污水处理厂的排放量。然而,在所有其他影响因素中,废水中微量污染物的影响显然是可以量化的。要提高我们进一步量化微量污染物影响的能力,需要高度解析的水质和分类数据,并要有足够的时空采样。这些改进将有助于更好地解释驱动观察到的生物学响应(例如情景污染物峰和与扩散相关的过程)的潜在因果途径。 (C)2018 Elsevier B.V.保留所有权利。

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