Toxicants have both sub-lethal and lethal effects on aquatic biota, influencing organism fitness and community composition. However, toxicant effects within ecosystems may be altered by interactions with abiotic and biotic ecosystem components, including biological interactions. Collectively, this generates the potential for toxicant sensitivity to be highly context dependent, with significantly different outcomes in ecosystems than laboratory toxicity tests predict. We experimentally manipulated stream macroinvertebrate communities in 32 mesocosms to examine how communities from a low-salinity site were influenced by interactions with those from a high-salinity site along a gradient of salinity. Relative to those from the low-salinity site, organisms from the high-salinity site were expected to have greater tolerance and fitness at higher salinities. This created the potential for both salinity and tolerant-sensitive organism interactions to influence communities. We found that community composition was influenced by both direct toxicity and tolerant-sensitive organism interactions. Taxon and context-dependent responses included: (i) direct toxicity effects, irrespective of biotic interactions; (ii) effects that were owing to the addition of tolerant taxa, irrespective of salinity; (iii) toxicity dependent on sensitive-tolerant taxa interactions; and (iv) toxic effects that were increased by interactions. Our results reinforce that ecological processes require consideration when examining toxicant effects within ecosystems. This article is part of the theme issue ‘Salt in freshwaters: causes, ecological consequences and future prospects’.

Discharges from historic and current coal mines frequently generate waters low in pH (<3), high in heavy metals (e.g. Fe, Al) and cover streambeds in metal precipitates. The present study investigated periphyton communities at 52 stream sites on the West Coast, South Island, New Zealand, representing a range of impacts from acid mine drainage (AMD). Taxonomic richness was negatively related to acidity and metal oxides and biomass was negatively correlated with metal oxides, but positively related to acidity. Streams with low pH (<3.5) had low periphyton richness (14 taxa across all sites) and were dominated by Klebsormidium acidophilum, Navicula cincta and Euglena mutabilis. As pH increased, so did taxonomic richness while community dominance decreased and community composition became more variable. Canonical correspondence analyses of algal assemblages revealed patterns influenced by pH. These findings indicate that streams affected by AMD possess a predictable assemblage composition of algal species that can tolerate the extreme water chemistry and substrate conditions. The predictability of algal communities declines with decreasing stress, as other abiotic and biotic factors become increasingly more important.

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Macroinvertebrates are commonly sampled for bioassessment of freshwater ecosystems. However, current bioassessment protocols involve laborious sorting of the animals from the debris (sample matrix) and morphological identification, where species level identifications are often difficult. DNA metabarcoding has the potential to improve bioassessment by reducing the time taken to process samples and improve the accuracy and speed of macroinvertebrate species identification. In this study, we evaluated DNA metabarcoding of macroinvertebrate samples, which include macroinvertebrates and the debris collected in the sample nets, to test if bulk, unsorted samples can be used to assess macroinvertebrate diversity. First, we tested if the sample matrix prevented the detection of six target macroinvertebrate taxa when DNA metabarcoding. Second, we tested if sample storage influenced the detection of the same six target macroinvertebrates. We also explored different levels of replication at the sample, sub‐sample, and polymerase chain reaction levels and compared the overall macroinvertebrate families detected using DNA metabarcoding to those identified morphologically. We found that the presence of the sample matrix did not interfere with or inhibit the detection of the six target macroinvertebrate taxa. Furthermore, we found that the various sample storage methods did not affect target macroinvertebrate detection. The reliability of detection of the target macroinvertebrates improved as hierarchical levels of replication were combined. We found strong overlap between the detection of overall macroinvertebrate family diversity when comparing DNA metabarcoding to morphological identification. Extracting DNA from the bulk macroinvertebrate samples that included the sample matrix and using this for DNA metabarcoding could improve bioassessment by removing the need for laborious sorting of samples. Furthermore, DNA metabarcoding detection of the six target taxa was not dependent on sample storage of up to 1 year in 95% ethanol, at room temperature or after heating. DNA metabarcoding had the advantage of identifying macroinvertebrate species, but good DNA barcode libraries are needed for widespread species identifications. Further investigation should focus on including multiple samples with different macroinvertebrate composition and densities to refine and standardise bulk sample processing protocols, and on building comprehensive DNA barcode libraries for aquatic macroinvertebrates.

Salinity is increasing in many naturally fresh waters because of human activities, and there are concerns about the ecological effects of these increases. Salinity, as with any stressor, can affect organisms both directly and indirectly. In a previous study (Bray et al. 2019), we evaluated the relative importance of direct and indirect effects of increased salinity on stream invertebrates. Chessman (2021) criticised that study, claiming that the biotic treatments were confounded and did not directly test the hypotheses. Chessman (2021) also conducted a reanalysis of the data. We show through the analysis of new data that our biotic treatments were not confounded and that the conclusions made by Chessman (2021) were probably a consequence of the low statistical power of his analysis. Consequently, we argue that Chessman’s (2021) comments do not substantively alter the conclusions of our study, and we provide more evidence to support the conclusions of our previous publication. The study of biota–stressor interactions is increasingly relevant to a wide range of global ecosystems. There is a need to develop tractable experimental and survey designs that address these problems, and we identify further avenues for study of these complex issues.