Approaching the Impact of Multiple Stressors on River Biofilms

2017 edition

Ferran Romero Blanch

Freshwater ecosystems are threatened by multiple natural and man-made stressors (i.e. physical, chemical and biological stressors). Most of the studies performed so far evaluate the impact of stressors as individual entities acting on model species and originate estimates of “tolerable” concentrations such as the lowest observed effect concentration (LOEC) or the predicted no-effect concentration (PNEC). These studies neglect the fact that potential interactions between co-occurring stressors may take place. Thus, these approaches are unlikely to reveal real impacts of co-occurring stressors in freshwater ecosystems such as rivers and streams. Among the studies addressing multiple stressor impacts, most of them deal with two-stressor combinations, and few actually provide quantitative evidence on multi-stress effects. Given this background, we here propose an experimental design where the effect of five stressors and their combinations will be evaluated following a full-factorial 5-factor experimental design. The present project aims to find potential interactions between co-occurring stressors on river biofilm communities. Biofilms are complex microbial communities growing on river and stream surfaces. Biofilm community is composed of a complex assemblage of short life-cycle organisms (bacteria, algae) permanently exposed to the biotic and abiotic factors within the river. Thus, they may respond to rapid changes in the surrounding environment such as fluctuations in water temperature or the presence of chemicals. The impact of the stressors and their combinations on biofilm community composition and functioning will be evaluated, as well as its recovery capacity after stressors are removed. The impact of the stressors on biofilm community composition will be evaluated with marker gene surveys targeting both prokaryotic and eukaryotic communities (i.e. high-throughput sequencing of 16S/18S rDNA genes). Biofilm functioning will be evaluated through photosynthetic activity measurements and major function-related genes expression. Photosynthetic activity will be evaluated with a pulse amplitude modulator (PAM) fluorometer, whereas real-time reverse transcriptase (RT) PCR (qRT-PCR) will be used to determine the expression level of several major function-related genes.