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• The IPHYGE is a multimetric index of the ecological quality of French large rivers. • It is based on phytoplankton. • It includes one biomass-based metric and three trophic ones. • Values of the index were correlated with total phosphorus concentrations (R2 > 0.3). • It is compliant with the criteria of the Water Framework Directive. Large rivers around the world are impacted by human activities. Such activities can lead to the eutrophication of these water bodies, and consequently to potentially harmful algal blooms. In this study, we describe the development of a phytoplankton-based multimetric index used for the biomonitoring of the ecological quality of large rivers located in metropolitan France, as advocated by the European Water Framework Directive. Using a dataset containing phytoplanktonic surveys sampled over the 2010–2021 period for a total of 963 station-years, we calculated biomass-based and trophic metrics. We then selected the best biomass-based metric and several trophic metrics based on their ability to highlight situations impaired by eutrophication and/or algal blooms and well correlated to pressure gradients (i.e. using coefficients of determination). The best biomass-based metric was calculated from both the seasonal average and maximal concentrations of chlorophyll-a. Three trophic metrics, created using the Weighted Average – Partial Least-Squares method, were included in the multimetric index. Each metric is correlated with one parameter of interest, namely with total phosphorus, Kjeldahl nitrogen and nitrates. The values of the biomass metric and the three trophic metrics were aggregated to calculate the final value of the IPHYGE index ("Indice Phytoplancton pour les Grands cours d'Eau"; phytoplankton index for large rivers) in order to obtain the best relationship with the eutrophication pressure. Ecological quality classes derived from the index values were well related to gradients of parameters linked to eutrophication, for example total phosphorus and nitrogen compounds. [ABSTRACT FROM AUTHOR]

[Display omitted] • Our database, called BactoTraits, provides 19 traits for 19,455 bacterial strains. • Functional groups of bacterial strains were defined based on similar suite of traits. • Bacterial communities functional traits differed according to soil pollution level. • The trait-based approach is a promising way to understand bacteria assemblage rules. In the environment, abiotic (climatic conditions, physico-chemical parameters), biotic (interactions between microorganisms, vegetation and fauna), and anthropogenic (stress, pollution) filters are driving the microbial diversity observed locally. A key question in microbial ecology is to understand the impact of these filters on bacterial diversity and ecosystem functioning. To highlight the responses of bacterial assemblages to these ecological filters, a new approach based on bacterial functional traits has been developed. This approach provides a functional picture of bacterial assemblages using morphological, physiological, and genomic traits as proxies of functions, and leads to a generalizable approach over a larger range of ecosystems with different bacterial diversities. We have created a user-friendly database of bacterial functional traits, thanks to the properties of 19,455 bacterial strains. This database has been called BactoTraits. For example, oxygen preference, size and shape of bacteria, motility, optimum and range of pH and temperature, genome GC percent and trophic type are among the 19 traits included in BactoTraits. Based on the best-informed strains in the database, we identified five functional groups (i.e. mesophiles, competitors, colonizers, stress-sensitives and stress-tolerants) exhibiting a wide strain taxonomic diversity but with quite similar trait profile combinations. As an example of application, BactoTraits was used to characterize the traits and functional diversity of bacterial assemblages in soil samples from 10 sites with different physico-chemical properties and various levels of metal and polycyclic aromatic hydrocarbon (PAH) contaminations. Inference of functional traits was based on taxonomic diversity information obtained by high-throughput sequencing of 16S rDNA. This trait-based approach has allowed to discriminate soils according to their physico-chemical properties and levels of contamination and to go further into the description of the bacterial assemblages. Several bacterial traits were identified as indicators of specific contaminants such as metals (e.g. filament shape, microaerophile and temperature optimum/range higher than 40 °C) or PAHs (e.g. spherical shape, facultative anaerobe/aerobe, no spore production, pH optimum ≥ 8, low temperature optimum but high temperature variation tolerance). Inferring trait values from a taxonomy-based approach can be extended readily to other microbial systems and contexts such as (i) studies on soils and aquatic ecosystems, (ii) microbial ecology along various environmental gradients, (iii) human, plant and animal microbiotes, as well as (iv) trophic interactions between bacterial communities and their predators. [ABSTRACT FROM AUTHOR]