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bioRxiv · 10.1101/2024.01.12.575328

Seasonal dynamics and drivers of microbial communities in a temperate dimictic lake: insights from metabarcoding and machine learning

Abstract

Microbial communities, consisting of prokaryotes and protists, play a central role in ecological processes in aquatic environments. To understand these communities, metabarcoding provides a powerful tool to assess their taxonomic composition and to track spatio-temporal dynamics in both marine and freshwater environments. While previous research has primarily focused on marine ecosystems, it is important to study microbial communities in freshwater environments, which are characterised by high diversity and susceptibility to rapid environmental change. In temperate lakes, despite extensive research on temporal changes in physico-chemical factors and microscopic studies of plankton, there is a notable research gap regarding their eukaryotic microbial communities. Our study fills this gap by investigating the diversity and seasonal changes of prokaryotic and eukaryotic communities in Lake Ro[s] (Poland), a representative temperate lake characterised by two mixing episodes in spring and autumn and pronounced stratification in summer. Our metabarcoding analysis revealed that both the bacterial and protist communities exhibit distinct seasonal patterns that are not necessarily shaped by dominant taxa. To decipher the drivers of the seasonal communities, we used machine learning and statistical methods and identified crucial amplicon sequence variants (ASVs) specific to each season. In addition, we identified a distinct community in the anoxic hypolimnion. We have also shown that the key factors shaping the community composition in Lake Ro[s] are temperature, oxygen and silicon concentration. Understanding these community structures and the underlying factors is crucial in the context of climate change, which might affect mixing patterns and lead to prolonged stratification. Given the pronounced seasonal shifts observed in these communities, we can anticipate that climate change will profoundly impact the functioning of temperate dimictic lakes.

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BibTeXRIS

Karlicki, M., Bednarska, A., Halakuc, P., Maciszewski, K., Karnkowska, A.. 2024-01-12. Seasonal dynamics and drivers of microbial communities in a temperate dimictic lake: insights from metabarcoding and machine learning. https://doi.org/10.1101/2024.01.12.575328

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