Stamm, C. | Search bioRxiv

bioRxiv2022

Wastewater microorganisms impact microbial diversity and important ecological functions of stream periphyton

Wastewater treatment plant effluents can impact microbial communities in receiving streams. However, little is known about the role of microorganisms in wastewater as opposed to other wastewater constituents, such as nutrients and micropollutants. We aimed therefore at determining the impact of wastewater microorganisms on the microbial diversity and function of periphyton, key microbial communities in streams. Periphyton was grown in flow-through channels that were continuously alimented with a mixture of stream water and unfiltered or ultra-filtered wastewater. Impacts were assessed on periphyton biomass, activities and tolerance to micropollutants, as well as on microbial diversity. Our results showed that wastewater microorganisms colonized periphyton and modified its community composition, resulting for instance in an increased abundance of Chloroflexi and a decreased abundance of diatoms and green algae. This led to shifts towards heterotrophy, as suggested by the changes in nutrient stoichiometry and the increased mineralization potential of carbon substrates. An increased tolerance towards micropollutants was only found for periphyton exposed to unfiltered wastewater but not to ultra-filtered wastewater, suggesting that wastewater microorganisms were responsible for this increased tolerance. Overall, our results highlight the need to consider the role of wastewater microorganisms when studying potential impacts of wastewater on the receiving water body. Environmental implicationThe present study investigates the impact of wastewater microorganisms on periphyton, i.e. communities forming the microbial skin of streambeds. We were able to disentangle specific effects of wastewater microorganisms in the context of the complex wastewater matrix. Indeed, wastewater microorganisms induced strong changes in periphyton community composition and function, suggesting the need to consider wastewater microbial communities as a stressor per se, similarly to, e.g., nutrients and micropollutants. Moreover, since periphyton is at the basis of the food web in streams, these changes may have consequences for higher trophic levels.

ecology↗

bioRxiv2022

A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess aquatic macroinvertebrate biodiversity

Monitoring freshwater biodiversity is essential to understand the impacts of human activities and for effective management of ecosystems. Thereby, biodiversity can be assessed through direct collection of targeted organisms, through indirect evidence of their presence (e.g. signs, environmental DNA, camera trap, etc.), or through extrapolations from species distribution models (SDM). Differences in approaches used in biodiversity assessment, however, may come with individual challenges and hinder cross-study comparability. In the context of rapidly developing techniques, we compared a triad of approaches in order to understand assessment of aquatic macroinvertebrate biodiversity. Specifically, we compared the community composition and species richness of three orders of aquatic macroinvertebrates (mayflies, stoneflies, and caddisflies, hereafter EPT) obtained via eDNA metabarcoding and via traditional in situ kicknet sampling to catchment-level based predictions of a species distribution model. We used kicknet data from 24 sites in Switzerland and compared taxonomic lists to those obtained using eDNA amplified with two different primer sets. Richness detected by these methods was compared to the independent predictions made by a statistical species distribution model using landscape-level features to estimate EPT diversity. Despite the ability of eDNA to consistently detect some EPT species found by traditional sampling, we found important discrepancies in community composition between the two approaches, particularly at local scale. Overall, the more specific set of primers, namely fwhF2/EPTDr2n, was most efficient for the detection of target species and for characterizing the diversity of EPT. Moreover, we found that the species richness measured by eDNA was poorly correlated to the richness measured by kicknet sampling and that the richness estimated by eDNA and kicknet were poorly correlated with the prediction of the statistical model. Overall, however, neither eDNA nor the traditional approach had strong links to the predictive models, indicating inherent limitations in upscaling species richness estimates. Future challenges include improving the accuracy and sensitivity of each approach individually yet also acknowledge their respective limitations, in order to best meet stakeholder demands addressing the biodiversity crisis we are facing.

ecology↗