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Predictive studies of chemical mixtures are typically based on experiments with single species. To study the applicability of the concepts of independent action (IA) and concentration addition (CA) on a multispecies level, the carbon fixation of natural algal communities under toxicant exposure was studied. The presented study focused on a mixture of six dissimilarly acting substances. Conceptual reasoning as well as empirical evidence from single-species tests suggest that IA is more appropriate for this type of mixture. Nonetheless, the potential of CA was also investigated, to assess whether this concept may be applicable as a reasonable worst case prediction of mixture toxicities also on a community level. IA predicted the experimental EC50 precisely. CA underestimated the EC50 by a factor of only 1.4, although the shape of the predicted concentration-response curve was clearly different from experimental data. Hence, it can be concluded that the applicability of the concepts is not restricted to the level of single species. However, some limitations of both concepts became apparent, when stimulating (hormesis-like) effects were observed fo rtwo of the mixture components. These effects were also seen in the experimental mixture toxicity data but cannot be adequately modeled by either concept.

Selection pressure generated by antibiotics released into the environment could enrich for antibiotic resistance genes and antibiotic resistant bacteria, thereby increasing the risk for transmission to humans and animals. Tetracyclines comprise an antibiotic class of great importance to both human and animal health. Accordingly, residues of tetracycline are commonly detected in aquatic environments. To assess if tetracycline pollution in aquatic environments promotes development of resistance, we determined minimal selective concentrations (MSCs) in biofilms of complex aquatic bacterial communities using both phenotypic and genotypic assays. Tetracycline significantly increased the relative abundance of resistant bacteria at 10 μg/L, while specific tet genes (tetA and tetG) increased significantly at the lowest concentration tested (1 μg/L). Taxonomic composition of the biofilm communities was altered with increasing tetracycline concentrations. Metagenomic analysis revealed a concurrent increase of several tet genes and a range of other genes providing resistance to different classes of antibiotics (e.g. cmlA, floR, sul1, and mphA), indicating potential for co-selection. Consequently, MSCs for the tet genes of ≤ 1 μg/L suggests that current exposure levels in e.g. sewage treatment plants could be sufficient to promote resistance. The methodology used here to assess MSCs could be applied in risk assessment of other antibiotics as well.

The authors hypothesize that pollution-induced community tolerance (PICT) is direct evidence that a community is disturbed by a pollutant and, furthermore, that the agent or agents causing the effects can be identified, because induced tolerance will be observed only for those compounds that have exerted selection pressure on the community. A similar concept has been formulated for population tolerance, but we suggest that the concept is more useful when applied at the community level. Our examination of some crucial points behind PICT, using arsenate and periphyton communities, demonstrates that (1) the tolerance increase can be determined in short-term photosynthesis experiments, (2) PICT correctly indicates changes in species composition and net production, and (3) the selection pressure of arsenate is specific—that is, a tolerance increase for one compound is not followed by co-tolerance to other compounds unless they are closely related chemically or in their mode of action. These results support the idea of using PICT as an ecotoxicological tool. If further corroborated, PICT can be applied in both laboratory and field studies. PICT might be used retrospecitively in the field to detect minor disturbances and to identify the causing agent. In a laboratory test system, PICT can be used to estimate the no-effect concentration for the community under study. The authors argue that test systems based on PICT will be sensitive and yield ecologically relevant information.

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