Measuring the state of aquatic environments using eDNA-upscaling spatial resolution of biotic indices.

Aquatic macroinvertebrates, including many aquatic insect orders, are a diverse and ecologically relevant organismal group yet they are strongly affected by anthropogenic activities. As many of these taxa are highly sensitive to environmental change, they offer a particularly good early warning system for human-induced change, thus leading to their intense monitoring. In aquatic ecosystems there is a plethora of biotic monitoring or biomonitoring approaches, with more than 300 assessment methods reported for freshwater taxa alone. Ultimately, monitoring of aquatic macroinvertebrates is used to calculate ecological indices describing the state of aquatic systems. Many of the methods and indices used are not only hard to compare, but especially difficult to scale in time and space. Novel DNA-based approaches to measure the state and change of aquatic environments now offer unprecedented opportunities, also for possible integration towards commonly applicable indices. Here, we first give a perspective on DNA-based approaches in the monitoring of aquatic organisms, with a focus on aquatic insects, and how to move beyond traditional point-based biotic indices. Second, we demonstrate a proof-of-concept for spatially upscaling ecological indices based on environmental DNA, demonstrating how integration of these novel molecular approaches with hydrological models allows an accurate evaluation at the catchment scale. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Modelling environmental DNA transport in rivers reveals highly resolved spatio-temporal biodiversity patterns.

The ever-increasing threats to riverine ecosystems call for novel approaches for highly resolved biodiversity assessments across taxonomic groups and spatio-temporal scales. Recent advances in the joint use of environmental DNA (eDNA) data and eDNA transport models in rivers (e.g., eDITH) allow uncovering the full structure of riverine biodiversity, hence elucidating ecosystem processes and supporting conservation measures. We applied eDITH to a metabarcoding dataset covering three taxonomic groups (fish, invertebrates, bacteria) and three seasons for a catchment sampled for eDNA at 73 sites. We upscaled eDNA-based biodiversity predictions to approximately 1900 reaches, and assessed α- and ß-diversity patterns across seasons and taxonomic groups over the whole network. Genus richness predicted by eDITH was generally higher than values from direct eDNA analysis. Both predicted α- and ß-diversity varied depending on season and taxonomic group. Predicted fish α-diversity increased downstream in all seasons, while invertebrate and bacteria α-diversity either decreased downstream or were unrelated to network position. Spatial ß-diversity mostly decreased downstream, especially for bacteria. The eDITH model yielded a more refined assessment of freshwater biodiversity as compared to raw eDNA data, both in terms of spatial coverage, diversity patterns and effect of covariates, thus providing a more complete picture of freshwater biodiversity.

Spatio-temporal patterns of multi-trophic biodiversity and food-web characteristics uncovered across a river catchment using environmental DNA.

Accurate characterisation of ecological communities with respect to their biodiversity and food-web structure is essential for conservation. However, combined empirical study of biodiversity and multi-trophic food webs at a large spatial and temporal resolution has been prohibited by the lack of appropriate access to such data from natural systems. Here, we assessed biodiversity and food-web characteristics across a 700 km2 riverine network over seasons using environmental DNA. We found contrasting biodiversity patterns between major taxonomic groups. Local richness showed statistically significant, season-dependent increases and decreases towards downstream location within the catchment for fish and bacteria, respectively. Meanwhile, invertebrate richness remained spatially unchanged but varied across seasons. The structure of local food webs, such as link density and nestedness, also varied across space and time. However, these patterns did not necessarily mirror those observed for biodiversity and functional feeding characteristics. Our results suggest that biodiversity patterns and food-web dynamics are not directly scalable to each other even at the same spatial and temporal scales. In order to conserve species diversity as well as the functional trophic integrity of communities, patterns of biodiversity and food-web characteristics must thus be jointly studied.

Meta-analysis shows both congruence and complementarity of DNA and eDNA metabarcoding to traditional methods for biological community assessment.

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.

Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment.

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.

Mapping biodiversity hotspots of fish communities in subtropical streams through environmental DNA.

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.

Assessing the impact of the threatened crucian carp (Carassius carassius) on pond invertebrate diversity: A comparison of conventional and molecular tools.

Fishes stocked for recreation and angling can damage freshwater habitats and negatively impact biodiversity. The pond-associated crucian carp (Carassius carassius) is rare across Europe and is stocked for conservation management in England, but its impacts on pond biota are understudied. Freshwater invertebrates contribute substantially to aquatic biodiversity, encompassing many rare and endemic species, but their small size and high abundance complicate their assessment. Practitioners have employed sweep-netting and kick-sampling with microscopy (morphotaxonomy), but specimen size/quality and experience can bias identification. DNA and environmental DNA (eDNA) metabarcoding offer alternative means of invertebrate assessment. We compared invertebrate diversity in ponds (N = 18) with and without crucian carp using morphotaxonomic identification, DNA metabarcoding and eDNA metabarcoding. Five 2 L water samples and 3 min sweep-net samples were collected at each pond. Inventories produced by morphotaxonomic identification of netted samples, DNA metabarcoding of bulk tissue samples and eDNA metabarcoding of water samples were compared. Alpha diversity was greatest with DNA or eDNA metabarcoding, depending on whether standard or unbiased methods were considered. DNA metabarcoding reflected morphotaxonomic identification, whereas eDNA metabarcoding produced markedly different communities. These complementary tools should be combined for comprehensive invertebrate assessment. Crucian carp presence minimally reduced alpha diversity in ponds, but positively influenced beta diversity through taxon turnover (i.e., ponds with crucian carp contained different invertebrates to fishless ponds). Crucian carp presence contributes to landscape-scale invertebrate diversity, supporting continued conservation management in England. Our results show that molecular tools can enhance freshwater invertebrate assessment and facilitate development of more accurate and ecologically effective pond management strategies.

Targeted and passive environmental DNA approaches outperform established methods for detection of quagga mussels, Dreissena rostriformis bugensis in flowing water.

The early detection of invasive non-native species (INNS) is important for informing management actions. Established monitoring methods require the collection or observation of specimens, which is unlikely at the beginning of an invasion when densities are likely to be low. Environmental DNA (eDNA) analysis is a highly promising technique for the detection of INNS-particularly during the early stages of an invasion.Here, we compared the use of traditional kick-net sampling with two eDNA approaches (targeted detection using both conventional and quantitative PCR and passive detection via metabarcoding with conserved primers) for detection of quagga mussel, Dreissena rostriformis bugensis, a high priority INNS, along a density gradient on the River Wraysbury, UK.All three molecular tools outperformed traditional sampling in terms of detection. Conventional PCR and qPCR both had 100% detection rate in all samples and outperformed metabarcoding when the target species was at low densities. Additionally, quagga mussel DNA copy number (qPCR) and relative read count (metabarcoding) were significantly influenced by both mussel density and distance from source population, with distance being the most significant predictor. Synthesis and application. All three molecular approaches were more sensitive than traditional kick-net sampling for the detection of the quagga mussel in flowing water, and both qPCR and metabarcoding enabled estimates of relative abundance. Targeted approaches were more sensitive than metabarcoding, but metabarcoding has the advantage of providing information on the wider community and consequently the impacts of INNS.

Environmental DNA metabarcoding of lake fish communities reflects long-term data from established survey methods.

Organisms continuously release DNA into their environments via shed cells, excreta, gametes and decaying material. Analysis of this 'environmental DNA' (eDNA) is revolutionizing biodiversity monitoring. eDNA outperforms many established survey methods for targeted detection of single species, but few studies have investigated how well eDNA reflects whole communities of organisms in natural environments. We investigated whether eDNA can recover accurate qualitative and quantitative information about fish communities in large lakes, by comparison to the most comprehensive long-term gill-net data set available in the UK. Seventy-eight 2L water samples were collected along depth profile transects, gill-net sites and from the shoreline in three large, deep lakes (Windermere, Bassenthwaite Lake and Derwent Water) in the English Lake District. Water samples were assayed by eDNA metabarcoding of the mitochondrial 12S and cytochrome b regions. Fourteen of the 16 species historically recorded in Windermere were detected using eDNA, compared to four species in the most recent gill-net survey, demonstrating eDNA is extremely sensitive for detecting species. A key question for biodiversity monitoring is whether eDNA can accurately estimate abundance. To test this, we used the number of sequence reads per species and the proportion of sampling sites in which a species was detected with eDNA (i.e. site occupancy) as proxies for abundance. eDNA abundance data consistently correlated with rank abundance estimates from established surveys. These results demonstrate that eDNA metabarcoding can describe fish communities in large lakes, both qualitatively and quantitatively, and has great potential as a complementary tool to established monitoring methods.