Warming-induced changes in denitrifier community structure modulate the ability of phototrophic river biofilms to denitrify.

Microbial denitrification is the main nitrogen removing process in freshwater ecosystems. The aim of this study was to show whether and how water warming (+2.5 °C) drives bacterial diversity and structuring and how bacterial diversity affects denitrification enzymatic activity in phototrophic river biofilms (PRB). We used water warming associated to the immediate thermal release of a nuclear power plant cooling circuit to produce natural PRB assemblages on glass slides while testing 2 temperatures (mean temperature of 17 °C versus 19.5 °C). PRB were sampled at 2 sampling times during PRB accretion (6 and 21days) in both temperatures. Bacterial community composition was assessed using ARISA. Denitrifier community abundance and denitrification gene mRNA levels were estimated by q-PCR and qRT-PCR, respectively, of 5 genes encoding catalytic subunits of the denitrification key enzymes. Denitrification enzyme activity (DEA) was measured by the acetylene-block assay at 20 °C. A mean water warming of 2.5 °C was sufficient to produce contrasted total bacterial and denitrifier communities and, therefore, to affect DEA. Indirect temperature effect on DEA may have varied between sampling time, increasing by up to 10 the denitrification rate of 6-day-old PRB and decreasing by up to 5 the denitrification rate of 21-day-old PRB. The present results suggest that indirect effects of warming through changes in bacterial community composition, coupled to the strong direct effect of temperature on DEA already demonstrated in PRB, could modulate dissolved nitrogen removal by denitrification in rivers and streams.

Rotating disk electrodes to assess river biofilm thickness and elasticity.

The present study examined the relevance of an electrochemical method based on a rotating disk electrode (RDE) to assess river biofilm thickness and elasticity. An in situ colonisation experiment in the River Garonne (France) in August 2009 sought to obtain natural river biofilms exhibiting differentiated architecture. A constricted pipe providing two contrasted flow conditions (about 0.1 and 0.45 m s(-1) in inflow and constricted sections respectively) and containing 24 RDE was immersed in the river for 21 days. Biofilm thickness and elasticity were quantified using an electrochemical assay on 7 and 21 days old RDE-grown biofilms (t(7) and t(21), respectively). Biofilm thickness was affected by colonisation length and flow conditions and ranged from 36 ± 15 µm (mean ± standard deviation, n = 6) in the fast flow section at t(7) to 340 ± 140 µm (n = 3) in the slow flow section at t(21). Comparing the electrochemical signal to stereomicroscopic estimates of biofilms thickness indicated that the method consistently allowed (i) to detect early biofilm colonisation in the river and (ii) to measure biofilm thickness of up to a few hundred µm. Biofilm elasticity, i.e. biofilm squeeze by hydrodynamic constraint, was significantly higher in the slow (1300 ± 480 µm rpm(1/2), n = 8) than in the fast flow sections (790 ± 350 µm rpm(1/2), n = 11). Diatom and bacterial density, and biofilm-covered RDE surface analyses (i) confirmed that microbial accrual resulted in biofilm formation on the RDE surface, and (ii) indicated that thickness and elasticity represent useful integrative parameters of biofilm architecture that could be measured on natural river assemblages using the proposed electrochemical method.

Co-occurrence patterns of some small-bodied freshwater fishes in southwestern France: implications for fish conservation and environmental management.

We assessed the influence of environmental variables (elevation, stream order, distance from source, catchment area, slope, stream width, and fish species richness) on the co-occurrence patterns of the minnow, the stone loach, and the gudgeon at the stream system scale. A total of 474 sites were classified according to the seven variables using the Self-Organizing Map (neural network), and three clusters were detected (k-means algorithm). The frequency of the various fish co-occurrence patterns was calculated for each cluster, and general linear modeling was used to specify the conditions that predict the occurrence of each species. Piedmont streams were more likely to support coexisting gudgeon and minnow populations because of higher probabilities of occurrence for both species. The higher co-occurrence frequency for the three species together in headwater streams resulted from lower occurrence frequencies in gudgeon and minnow. Focusing on areas that favor the co-occurrence of species may enhance the effectiveness of conservation projects.