Benthic algae, especially diatoms, are commonly used to assess water quality in rivers. However, algal-based assessments are challenging at the river system scale because longitudinal variation in physical habitat conditions may obscure algal responses to changes in water quality. In the present study, we surveyed benthic diatoms and environmental variables from a mountainous Chinese river system. Hierarchical clustering, discrimination analysis, and indicator species analysis were used together to explore associations between distribution patterns of diatom assemblages and water quality variables. Study sites were clustered into five groups based on their diatom community composition, with sites grouped by the sampling months. Chemical oxygen demand (COD), elevation, and total nitrogen (TN) were the most important predictors for site classification. Site groups with higher elevations had higher TN concentrations; however, COD concentrations were higher in lower elevation groups. Moreover, COD concentrations significantly differed between temporally separated groups. In total, 49 indicator species were identified for individual groups, with most taxa indicating the eutrophic condition. Additionally, we found that European diatom indices are not closely associated with water quality variables. We conclude that the identification of algal patterns and their driving forces can provide valuable information to aid bioassessment at the river system scale.

Although most lotic ecosystems are groundwater dependent, our knowledge on the relatively long-term ecological effects of groundwater discharge on downstream reaches remains limited. We surveyed four connected reaches of a Chinese karst stream network for 72 consecutive months, with one reach, named Hong Shi Zi (HSZ), evidently affected by groundwater. We tested whether, compared with other reaches, HSZ had (1) milder water temperature and flow regimes, and (2) weaker influences of water temperature and flow on benthic algal biomass represented by chlorophyll a (Chl. a) concentrations. We found that the maximum monthly mean water temperature in HSZ was 0.6 °C lower than of the adjacent upstream reach, and the minimum monthly mean water temperature was 1.0 °C higher than of the adjacent downstream reach. HSZ had the smallest coefficient of variation (CV) for water temperature but the largest CV for discharge. Water temperature and discharge displayed a significant 12-month periodicity in all reaches not directly groundwater influenced. Only water temperature displayed such periodicity in HSZ. Water temperature was an important predictor of temporal variation in Chl. a in all reaches, but its influence was weakest in HSZ. Our findings demonstrate that longer survey data can provide insight into groundwater–surface water interactions.

Understanding temporal dynamics of community may provide insights on biological responses under environmental changes. However, our knowledge on temporal dynamics of river organisms is still limited. In the present study, we employed a multivariate time-series modeling approach with a long-term dataset (i.e. 72 consecutive months) to investigate temporal dynamics of benthic diatom communities in four sites located in a Chinese mountainous river network. We hypothesized that: (1) there are multi-scale temporal dynamics within the diatom community; (2) intra-annual fluctuations dominate the community dynamics; (3) diatom species composing the community respond distinctly to environmental changes. We found that intra-annual fluctuations with periodicities <12 months explained 8.1–16.1% of community variation. In contrast, fluctuations with periodicities of 13–36 months and 37–72 months only accounted for 1.1–5.9% and 2.8–9.7% of variance in diatom community dynamics, respectively. Taxa correlating significantly to each significant RDA axis (namely, RDA taxa group) displayed distinct temporal dynamics. Conductivity, total nitrogen, and pH were important to most RDA taxa groups across the four sites while their effects were group-specific. We concluded that intra-annual dynamics dominated temporal variation in diatom communities due to community responses to local environmental fluctuations. We suggest that long-term monitoring data are valuable for identifying multiple-scale temporal dynamics within biological communities.