Aquatic food webs in deep temperate lakes: Key species establish through their autecological versatility. Issue 4 (21st December 2020)

• Record Type: Journal Article
• Authors: 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
• Is Part Of: Molecular ecology. Volume 30:Issue 4(2021)
• Page Start: 1053
• Page End: 1071
• Publication Date: 2020-12-21
• Subjects: climate stress -- ecosystem robustness -- functional diversity -- network analyses -- protistan plankton; Molecular ecology -- Periodicals; Molecular population biology -- Periodicals; 576
• DOI: 10.1111/mec.15776
• Languages: English
• ISSNs: 0962-1083

Abstract

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.