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

  • 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.

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Author:Zishuai QuORCiD, Dominik ForsterORCiD, Estelle P. Bruni, Daniela Frantal, Barbara Kammerlander, Laura Nachbaur, Gianna Pitsch, Thomas Posch, Thomas Pröschold, Katrin Teubner, Bettina Sonntag, Thorsten StoeckORCiD
URN:urn:nbn:de:hbz:386-kluedo-79786
DOI:https://doi.org/10.1111/mec.15776
ISSN:1365-294X
Parent Title (English):Molecular Ecology
Publisher:Wiley
Document Type:Article
Language of publication:English
Date of Publication (online):2024/04/10
Year of first Publication:2021
Publishing Institution:Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau
Date of the Publication (Server):2024/04/10
Issue:30/4
Page Number:19
First Page:1053
Last Page:1071
Source:https://onlinelibrary.wiley.com/doi/10.1111/mec.15776
Faculties / Organisational entities:Kaiserslautern - Fachbereich Biologie
DDC-Cassification:5 Naturwissenschaften und Mathematik / 570 Biowissenschaften, Biologie
Collections:Open-Access-Publikationsfonds
Licence (German):Zweitveröffentlichung