Time after time: detecting annual patterns in stream bacterial biofilm communities

To quantify the major environmental drivers of stream bacterial population dynamics, we modelled temporal differences in stream bacterial communities to quantify community shifts, including those relating to cyclical seasonal variation and more sporadic bloom events. We applied Illumina MiSeq 16S rRNA bacterial gene sequencing of 892 stream biofilm samples, collected monthly for 36-months from six streams. The streams were located a maximum of 118 km apart and drained three different catchment types (forest, urban and rural land uses). We identified repeatable seasonal patterns among bacterial taxa, allowing their separation into three ecological groupings, those following linear, bloom/trough and repeated, seasonal trends. Various physicochemical parameters (light, water and air temperature, pH, dissolved oxygen, nutrients) were linked to temporal community changes. Our models indicate that bloom events and seasonal episodes modify biofilm bacterial populations, suggesting that distinct microbial taxa thrive during these events including non-cyanobacterial community members. These models could aid in determining how temporal environmental changes affect community assembly and guide the selection of appropriate statistical models to capture future community responses to environmental change.

Automated summary

By modeling temporal differences in stream bacterial communities, we were able to quantify the major environmental drivers of stream bacterial population dynamics, including cyclical seasonal variation and sporadic bloom events. Our models showed that bloom events and seasonal episodes significantly modify biofilm bacterial populations, indicating the thriving of distinct microbial taxa during these periods. These findings provide insights into how temporal environmental changes affect community assembly and can guide the selection of appropriate statistical models for predicting future community responses to environmental change.