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温带深水湖泊中的水生食物网:关键物种通过其个体生态学的多功能性得以确立。

Aquatic food webs in deep temperate lakes: Key species establish through their autecological versatility.

作者信息

Qu Zhishuai, Forster Dominik, Bruni Estelle P, Frantal Daniela, Kammerlander Barbara, Nachbaur Laura, Pitsch Gianna, Posch Thomas, Pröschold Thomas, Teubner Katrin, Sonntag Bettina, Stoeck Thorsten

机构信息

Ecology Group, Technische Universität Kaiserslautern, Kaiserslautern, Germany.

Limnological Station, Department of Plant and Microbial Biology, University of Zurich, Kilchberg, Switzerland.

出版信息

Mol Ecol. 2021 Feb;30(4):1053-1071. doi: 10.1111/mec.15776. Epub 2020 Dec 21.

DOI:10.1111/mec.15776
PMID:33306859
Abstract

Microbial planktonic communities are the basis of food webs in aquatic ecosystems since they contribute substantially to primary production and nutrient recycling. Network analyses of DNA metabarcoding data sets emerged as a powerful tool to untangle the complex ecological relationships among the key players in food webs. In this study, we evaluated co-occurrence networks constructed from time-series metabarcoding data sets (12 months, biweekly sampling) of protistan plankton communities in surface layers (epilimnion) and bottom waters (hypolimnion) of two temperate deep lakes, Lake Mondsee (Austria) and Lake Zurich (Switzerland). Lake Zurich plankton communities were less tightly connected, more fragmented and had a higher susceptibility to a species extinction scenario compared to Lake Mondsee communities. We interpret these results as a lower robustness of Lake Zurich protistan plankton to environmental stressors, especially stressors resulting from climate change. In all networks, the phylum Ciliophora contributed the highest number of nodes, among them several in key positions of the networks. Associations in ciliate-specific subnetworks resembled autecological species-specific traits that indicate adaptions to specific environmental conditions. We demonstrate the strength of co-occurrence network analyses to deepen our understanding of plankton community dynamics in lakes and indicate biotic relationships, which resulted in new hypotheses that may guide future research in climate-stressed ecosystems.

摘要

微生物浮游群落是水生生态系统食物网的基础,因为它们对初级生产和营养物质循环做出了重大贡献。DNA宏条形码数据集的网络分析已成为一种强大的工具,用于理清食物网中关键参与者之间复杂的生态关系。在本研究中,我们评估了根据两个温带深水湖泊(奥地利蒙德湖和瑞士苏黎世湖)表层(湖面温水层)和底层水(湖下层)原生生物浮游群落的时间序列宏条形码数据集(12个月,每两周采样一次)构建的共现网络。与蒙德湖群落相比,苏黎世湖浮游群落的连接性较差,更加分散,并且对物种灭绝情况的敏感性更高。我们将这些结果解释为苏黎世湖原生生物浮游生物对环境压力源(尤其是气候变化导致的压力源)的稳健性较低。在所有网络中,纤毛门贡献的节点数量最多,其中有几个位于网络的关键位置。纤毛虫特定子网络中的关联类似于指示对特定环境条件适应的个体生态物种特异性特征。我们证明了共现网络分析在加深我们对湖泊浮游群落动态的理解以及指示生物关系方面的优势,这产生了可能指导未来在气候压力生态系统中研究的新假设。

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