Interactions with phytoplankton influence bacterial community composition and temporal patterns. Environmental conditions, including temperature and light, can alter interactions between phytoplankton and bacteria while also affecting each community directly. Our objective was to determine how phytoplankton, temperature, and light interact to affect bacterial community composition. Bacteria from two humic lakes, South Sparkling Bog (SSB) and Trout Bog (TB), were combined with phytoplankton assemblages from each lake (“home” or “away” treatments) or a no-phytoplankton control and incubated for 5 days under all combinations of light (surface, ~25% surface irradiance) and temperature (5 levels from 10ºC to 25ºC) (n=3). Tag-pyrosequencing of 16S and plastid-specific 23S rRNA genes was used to characterize bacterial and phytoplankton communities, respectively.
Results/Conclusions
As temperature increased, similarity of bacterial communities to their initial composition decreased when they were incubated with phytoplankton. Bacteria incubated without phytoplankton did not respond consistently to temperature. Composition of the phytoplankton assemblage changed over the incubation in response to high-light treatments, while low-light treatments showed little change in phytoplankton composition. Phytoplankton treatment (SSB vs. TB, rho > 0.63) was more strongly correlated to patterns in bacterial community response than phytoplankton community composition (summarized by ordination axes, rho > 0.58).
Lack of significant bacterial community composition response to temperature treatments when incubated without phytoplankton indicates that phytoplankton mediate temperature effects, likely through exudate release. In contrast, light effects on bacterial communities were primarily direct, though small, possibly due to the stimulation of bacterial phototrophs. These results demonstrate the importance of interactions among ecological drivers for structuring bacterial communities and highlight the necessity of studying multiple potential drivers simultaneously to account for context-dependence. Predicting responses of aquatic bacteria to environmental change will require consideration of interactions with phytoplankton.