Anthropogenic eutrophication has caused widespread environmental problems in freshwater lakes, reducing biodiversity and disrupting the classic pelagic food chain. Increasing our understanding of the exact role of nutrients and physicochemical variables on microbial dynamics, and subsequent microalgal and cyanobacterial blooms, has involved numerous studies ranging from replicate microcosm-based studies through to temporal studies of real lake data. In a previous experimental microcosm study, we utilised metaproteomics to investigate the functional changes of a microalgal-bacterial community under oligotrophic and eutrophic nutrient levels. Here, we analyse the time series data from this experiment with a combination of typically used univariate analyses and a more modern multivariate approach, structural equation modelling. Our aim was to test, using these modern methods, whether physicochemical variables and nutrient dynamics acted additively, synergistically, or antagonistically on the specific biotic community used in the microcosms. We found that nutrients (nitrogen and phosphorus) and temperature acted additively on the interactions between the microalgae and bacteria present, with the temperature effects elevated in the eutrophic conditions we applied. The data suggests that there may be no synergistic interaction between nutrients and temperature in the tested microcosms. Our approach demonstrates how the application of multivariate methods to existing datasets, in our case from nutrient-enriched freshwater microcosms, enables new information to be extracted, enhancing interpretations as well as allowing more reliable comparisons to similar published studies.
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