DNA metabarcoding is increasingly used for the assessment of aquatic communities, and numerous studies have investigated the consistency of this technique with traditional morpho‐taxonomic approaches. These individual studies have used DNA metabarcoding to assess diversity and community structure of aquatic organisms both in marine and freshwater systems globally over the last decade. However, a systematic analysis of the comparability and effectiveness of DNA‐based community assessment across all of these studies has hitherto been lacking. Here, we performed the first meta‐analysis of available studies comparing traditional methods and DNA metabarcoding to measure and assess biological diversity of key aquatic groups, including plankton, microphytobentos, macroinvertebrates, and fish. Across 215 data sets, we found that DNA metabarcoding provides richness estimates that are globally consistent to those obtained using traditional methods, both at local and regional scale. DNA metabarcoding also generates species inventories that are highly congruent with traditional methods for fish. Contrastingly, species inventories of plankton, microphytobenthos and macroinvertebrates obtained by DNA metabarcoding showed pronounced differences to traditional methods, missing some taxa but at the same time detecting otherwise overseen diversity. The method is generally sufficiently advanced to study the composition of fish communities and replace more invasive traditional methods. For smaller organisms, like macroinvertebrates, plankton and microphytobenthos, DNA metabarcoding may continue to give complementary rather than identical estimates compared to traditional approaches. Systematic and comparable data collection will increase the understanding of different aspects of this complementarity, and increase the effectiveness of the method and adequate interpretation of the results.

Anthropogenic activities are changing the state of ecosystems worldwide, affecting community composition and often resulting in loss of biodiversity. Rivers are among the most impacted ecosystems. Recording their current state with regular biomonitoring is important to assess the future trajectory of biodiversity. Traditional monitoring methods for ecological assessments are costly and time-intensive. Here, we compared monitoring of macroinvertebrates based on environmental DNA (eDNA) sampling with monitoring based on traditional kick-net sampling to assess biodiversity patterns at 92 river sites covering all major Swiss river catchments. From the kick-net community data, a biotic index (IBCH) based on 145 indicator taxa had been established. The index was matched by the taxonomically annotated eDNA data by using a machine learning approach. Our comparison of diversity patterns only uses the zero-radius Operational Taxonomic Units assigned to the indicator taxa. Overall, we found a strong congruence between both methods for the assessment of the total indicator community composition (gamma diversity). However, when assessing biodiversity at the site level (alpha diversity), the methods were less consistent and gave complementary data on composition. Specifically, environmental DNA retrieved significantly fewer indicator taxa per site than the kick-net approach. Importantly, however, the subsequent ecological classification of rivers based on the detected indicators resulted in similar biotic index scores for the kick-net and the eDNA data that was classified using a random forest approach. The majority of the predictions (72%) from the random forest classification resulted in the same river status categories as the kick-net approach. Thus, environmental DNA validly detected indicator communities and, combined with machine learning, provided reliable classifications of the ecological state of rivers. Overall, while environmental DNA gives complementary data on the macroinvertebrate community composition compared to the kick-net approach, the subsequently calculated indices for the ecological classification of river sites are nevertheless directly comparable and consistent.

Large tropical and subtropical rivers are among the most biodiverse ecosystems worldwide, but also suffer from high anthropogenic pressures. These rivers are hitherto subject to little or no routine biomonitoring, which would be essential for identification of conservation areas of high importance. Here, we use a single environmental DNA multi-site sampling campaign across the 200,000 km2 Chao Phraya river basin, Thailand, to provide key information on fish diversity. We found a total of 108 fish taxa and identified key biodiversity patterns within the river network. By using hierarchical clustering, we grouped the fish communities of all sites across the catchment into distinct clusters. The clusters not only accurately matched the topology of the river network, but also revealed distinct groups of sites enabling informed conservation measures. Our study reveals novel opportunities of large-scale monitoring via eDNA to identify relevant areas within whole river catchments for conservation and habitat protection.

Regular monitoring of ecosystems can be used for the early detection of invasive alien species (IAS), and provide information for management and preventing them from becoming established or advancing into new areas. Current methods of monitoring freshwater systems for IAS can be both financially costly and time‐consuming, with routine monitoring often carried out at low intensity and at only a small number of sites. In this study, we evaluate how environmental DNA (eDNA) metabarcoding for monitoring freshwater macroinvertebrate IAS compares to traditional kick‐net sampling as part of a national (Switzerland) and a catchment monitoring programme. Kick‐net sampling was more fruitful for the detection of several well‐known target macroinvertebrate IAS. However, eDNA samples proved complementary for the detection of IAS that belong to species often being unnoticed by traditional sampling due to methodological or taxonomic reasons. Specifically, the invasive jellyfish Craspedacusta sowerbii, hardly detectable using classic kick‐net sampling, was found to be widespread in both the national and the catchment‐scale monitoring with the eDNA method only. Our study shows that IAS detection using eDNA is easily implemented in both national‐ and catchment‐scale monitoring campaigns. However, successful detection of target IAS is still highly dependent on primer choice, species' biology, and availability of adequate markers. Specifically, multiple markers should be considered for detecting IAS from several different taxonomic groups, such as those under the ‘freshwater macroinvertebrate’ umbrella term. While eDNA is still developing in terms of these fundamental methodological requirements, surveillance for both target and non‐target IAS using eDNA is likely to increase efficiency in early detection of IAS in freshwater systems.

Macroinvertebrates serve as key indicators in ecological assessments of aquatic ecosystems, where the composition and richness of their communities are indicative of environmental and anthropogenic change. Established monitoring of macroinvertebrates is expensive and time-consuming, and relies on expert taxonomic knowledge.In contrast, biomonitoring based on molecular tools can support faster characterization of aquatic communities but needs validation for the target taxonomic groups and the study region. Here, we used data from a biomonitoring program covering a large biogeographic gradient to compare the routine kick-net method with eDNA metabarcoding. We used two primer pairs targeting COI, one targeting a broad metazoan spectrum (mICOIintF/jgHCO2198) and another more recently developed primer pair optimized for the detection of freshwater invertebrates (fwhF2/EPTDr2n). We used the data of the macroinvertebrate monitoring with a focus on the orders of Ephemeroptera, Plecoptera, and Trichoptera across 92 rivers in Switzerland, covering four continental drainage basins and an elevational range from 198 to 1650 m a.s.l. Across all sample sites, the kick-net detected more distinct taxa than either of the metabarcoding approaches. At a site level, however, both primer pairs detected on average more species. Comparing both primer pairs, the fwhF2/EPTDr2n primer pair captured more species assigned to the indicator groups Ephemeroptera, Plecoptera, and Trichoptera, and showed a significantly larger overlap with the kick-net method.However, the community composition still varied significantly among the different metabarcoding approaches. Fewer Trichoptera species were recovered by eDNA, whereas the fwhF2/EPTDr2n primer pair detected more Plecopterans than the other two approaches. This study highlights the importance of the optimization and validation of novel molecular approaches under consideration of the target organismal group and the study area.

Assessment of the diversity and composition of biological communities is central to studies in ecology as well as for ecological monitoring. Historically, individual taxonomic groups have been assessed separately, while for an understanding of the state and change of biodiversity under ongoing global change an integrated assessment would be necessary. DNA metabarcoding has been proposed to be a highly promising approach especially for the assessment of aquatic communities, and numerous studies have investigated the consistency of this new technique with traditional morpho-taxonomic approaches. These individual studies have used DNA metabarcoding to assess diversity and community structure of aquatic organisms both in marine and freshwater systems globally over the last decade. However, a systematic analysis of the comparability and effectiveness of DNA-based community assessment across all of these studies has hitherto been lacking. Here we performed the first meta-analysis of all available studies comparing traditional methods and DNA metabarcoding to measure and assess biological diversity of key aquatic groups, including microorganisms, macroinvertebrates, and fish. Across 215 datasets, we found that DNA metabarcoding provides diversity estimates (richness) that are globally consistent to those obtained using traditional methods. DNA metabarcoding also generates species inventories that are highly congruent with traditional methods for fish. Contrastingly, however, species inventories of microorganisms and macroinvertebrates obtained by DNA metabarcoding showed pronounced differences to traditional methods, missing some taxa but at the same time detecting otherwise overseen diversity. Our results indicate that DNA metabarcoding is efficient to estimate local and regional richness. The method is generally sufficiently advanced to study the composition of fish communities and replace more invasive traditional methods. For smaller organisms, like macroinvertebrates and microorganisms, DNA metabarcoding may continue to give complementary rather than identical estimates compared to traditional approaches. Systematic and comparable data collection will increase the understanding of different aspects of this complementarity, and increase the effectiveness of the method and adequate interpretation of the results.

Metabarcoding of environmental DNA (eDNA) is a powerful tool for describing biodiversity, such as finding keystone species or detecting invasive species in environmental samples. Continuous improvements in the method and the advances in sequencing platforms over the last decade have meant this approach is now widely used in biodiversity sciences and biomonitoring. For its general use, the method hinges on a correct identification of taxa. However, past studies have shown how this crucially depends on important decisions during sampling, sample processing, and subsequent handling of sequencing data. With no clear consensus as to the best practice, particularly the latter has led to varied bioinformatic approaches and recommendations for data preparation and taxonomic identification. In this study, using a large freshwater fish eDNA sequence dataset, we compared the frequently used zero-radius Operational Taxonomic Unit (zOTU) approach of our raw reads and assigned it taxonomically (i) in combination with publicly available reference sequences (open databases) or (ii) with an OSU (Operational Sequence Units) database approach, using a curated database of reference sequences generated from specimen barcoding (closed database). We show both approaches gave comparable results for common species. However, the commonalities between the approaches decreased with read abundance and were thus less reliable and not comparable for rare species. The success of the zOTU approach depended on the suitability, rather than the size, of a reference database.Contrastingly, the OSU approach used reliable DNA sequences and thus often enabled species-level identifications, yet this resolution decreased with the recent phylogenetic age of the species. We show the need to include target group coverage, outgroups and full taxonomic annotation in reference databases to avoid misleading annotations that can occur when using short amplicon sizes as commonly used in eDNA metabarcoding studies. Finally, we make general suggestions to improve the construction and use of reference databases for metabarcoding studies in the future.

Mercury (Hg) is one of the most toxic heavy metals and is known for its persistence in the environment and potential to accumulate along the food chain. In many terrestrial polluted sites, earthworms are in direct contact with Hg contamination by ingesting large quantities of soil. However, little is known about the impact of Hg soil pollution on earthworms’ gut microbiome. In this study, two incubation experiments involving earthworms in soils from a long-term Hg-polluted site were conducted to assess: (1) the effect of soil Hg contamination on the diversity and structure of microbial communities in earthworm, cast and soil samples; and (2) how the gut microbiome of different digestive track parts of the earthworm responds to soil Hg contamination. The large accumulation of total Hg and methyl-Hg within the earthworm tissues clearly impacted the bacterial and fungal gut community structures, drastically decreasing the relative abundance of the dominating gut bacterial class Mollicutes. Hg-tolerant taxa were found to be taxonomically widespread but consistent along the different parts of the earthworm digestive tract. This study revealed that although Hg might not directly affect the health of macro-organisms in the food-web such as earthworms, their metabolism and legacy in the soil might be impacted through changes in their gut microbiome.