Modeling cyanobacteria biomass by surface sediment diatoms in lakes: problems and suggestions

Improving biological condition assessment accuracy by multimetric index approach with microalgae in streams and lakes

Multimetric index (MMI) approach is a broadly used in ecological assessment because it can integrate information of various kinds of ecologically related metrics of freshwater ecosystems and provide an easily understandable score for purpose of further evaluation and managements. Accounting for natural variation and disentangling covariation between natural environmental factors and human disturbance factors are imperative for an accurate assessment. Lots of progress has been made recently on the aforementioned two aspects. Three approaches, a priori classification of sites by regions or typologies, site-specific modeling of expected reference condition and varying metrics in site groups, have been tested in lakes and streams to improve assessment accuracy. All existed studies support that site-specific modeling can efficiently account for natural variation and generate a MMI with good performance. However, until now, no strong evidence has shown that diatom/blue-algae typologies are better than regionalization frameworks on accounting for natural variation either in lakes or in streams. To separate the natural variation explained by site specific modeling from that of varying metrics is necessary for a thorough and accurate evaluation on the valuableness of site-grouping by typologies. Different performance of varying metrics among site groups of streams and lakes was most probably caused by the lack of representativeness of diatom metrics on biological condition rather than the complex multi-stressor gradients in streams and rivers. A recent study showed that blue-green algae enhanced performance of diatom-based MMI on defining lake condition under high level of human disturbance. On the other hand, with more and more extensive and intensive use of statistics techniques in developing MMI, we also discussed some statistical challenges faced by scientists in field of ecological assessment, especially on setting significance level of a statistical test and multiple comparison issue in MMI performance comparison.

Ecological impacts of freshwater algal blooms on water quality, plankton biodiversity, structure, and ecosystem functioning

Harmful algal blooms are among the emerging threats to freshwater biodiversity that need to be studied further in the Anthropocene. Here, we studied freshwater plankton communities in ten tropical reservoirs to record the impact of algal blooms, comprising different phytoplankton taxa, on water quality, plankton biodiversity, and ecosystem functioning. We compared water quality parameters (water transparency, mixing depth, pH, electrical conductivity, dissolved inorganic nitrogen, total dissolved phosphorus, total phosphorus, chlorophyll-a, and trophic state), plankton structure (composition and biomass), biodiversity (species richness, diversity, and evenness), and ecosystem functioning (phytoplankton:phosphorus and zooplankton:phytoplankton ratios as a metric of resource use efficiency) through univariate and multivariate analysis of variance, and generalized additive mixed models in five different bloom categories. Most of the bloom events were composed of Cyanobacteria, followed by Dinophyta and Chlorophyta. Mixed blooms were composed of Cyanobacteria plus Bacillariophyta, Chlorophyta, and/or Dinophyta, while non-bloom communities presented phytoplankton biomass below the threshold for bloom development (10 mg L^-1, WHO alert level 2). Higher phytoplankton biomasses were recorded during Cyanobacteria blooms (15.87-273.82 mg L^-1) followed by Dinophyta blooms (18.86-196.41 mg L^-1). An intense deterioration of water quality, including higher pH, eutrophication, stratification, and lower water transparency, was verified during Cyanobacteria and mixed blooms, while Chlorophyta and Dinophyta blooms presented lower pH, eutrophication, stratification, and higher water transparency. All bloom categories significantly impacted phytoplankton and zooplankton structure, changing the composition and dominance patterns. Bloom intensity positively influenced phytoplankton resource use efficiency (R² = 0.25; p < 0.001), while decreased zooplankton resource acquisition (R² = 0.51; p < 0.001). Moreover, Cyanobacteria and Chlorophyta blooms negatively impacted zooplankton species richness, while Dinophyta blooms decreased phytoplankton richness. In general, Cyanobacteria blooms presented low water quality and major threats to plankton biodiversity, and ecosystem functioning. Moreover, we demonstrated that biodiversity losses decrease ecosystem functioning, with cascading effects on plankton dynamics.