Fit for purpose? Evaluating benthic invertebrate DNA metabarcoding for ecological status class assessment in streams under the Water Framework Directive

The ecological state of aquatic ecosystems is systematically monitored using various bioindicators in many countries worldwide. In the European Union, freshwater biomonitoring is the central component of the EU Water Framework Directive (WFD, 2000/60/EC) and currently based on morpho-taxonomic methods. DNA metabarcoding is a novel approach to assess the ecological state fast and efficiently based on organismal DNA signatures and thereby support and upscale biomonitoring. However, compliance of metabarcoding with existing morpho-taxonomic methods must be ensured prior to official implementation. Thus, this study, co-designed by research institutions and environmental agencies, explored necessary key parameters and performed method intercalibration for the implementation of metabarcoding into WFD assessments of running waters. We focussed on benthic invertebrates as the most commonly used bioindicators. We analysed 170 invertebrate samples collected as part of the German federal state WFD routine stream biomonitoring, first via microscopic determination and then using metabarcoding. Our goals were to quantify overlap in i) taxonomic composition and ii) ecological status derived with both methods. For this purpose, we established data harmonisation measures to integrate invertebrate metabarcoding data into the official national WFD classification modules considering abundance and presence/absence data. Our results revealed a high (ca. 70 %) overlap of bioindicator taxa found with both methods. Metabarcoding identified significantly more small invertebrate taxa and detected similar proportions of the important bioindicator 'EPT' taxa (mayflies, stoneflies, caddisflies). Despite deviations in some detected bioindicator taxa, the derived ecological status classes were highly correlated between methods, particularly after intercalibration (R2 = 0.74, Spearman rho = 0.86). Regardless of whether we used abundance or presence/absence data, the resulting stream type classifications showed strong agreement. Thus, our study not only demonstrates the consistency of the methods for the stream types analysed but is also the first to operationalise a path to integration of metabarcoding data into the WFD assessment modules based on formal intercalibration guidelines.

Insights into the representativeness of biodiversity assessment in large reservoir through eDNA metabarcoding

Monitoring biodiversity on a large scale, such as in hydropower reservoirs, poses scientific challenges. Conventional methods such as passive fishing gear are prone to various biases, while the utilization of environmental DNA (eDNA) metabarcoding has been restricted. Most eDNA studies have primarily focused on replicating results from traditional methods, which themselves have limitations regarding representativeness and bias. In our study, we employed eDNA metabarcoding with three markers (12SrRNA, COI, and 16SrRNA) to evaluate the biodiversity of an 800 km2 reservoir. We utilized hydrodynamic modeling to determine water flow velocity and the water renewal ratio throughout the study area. Additionally, we conducted statistical comparisons-rarefaction curves and multivariate methods-among samples as an alternative approach to assess biodiversity representation. The eDNA identified taxa previously documented in the reservoir by traditional monitoring methods, as well as revealed 29 -nine fishes and 20 non-fish-previously unreported species. These results highlight the robustness of eDNA as a biodiversity monitoring technique. Our findings also indicated that by randomly sampling 30% of the original number of samples, we could effectively capture the same biodiversity. This approach enabled us to comprehend the reservoir's biodiversity profile and propose a straightforward, cost-effective monitoring protocol for the future based on eDNA.

Cobalt effects on prokaryotic communities of river biofilms: Impact on their colonization kinetics, structure and functions

Although cobalt (Co) plays a significant role in the transition to low-carbon technologies, its environmental impact remains largely unknown. This study examines Co impacts on the prokaryotic communities within river biofilms to evaluate their potential use as bioindicators of Co contamination. To this end, biofilms were cultivated in artificial streams enriched with different environmental Co concentrations (0.1, 0.5, and 1 μM Co) over 28 days and examined for prokaryotic abundance and diversity via quantitative PCR and DNA-metabarcoding every 7 days. The prokaryotic community's resilience was further investigated after an additional 35 days without Co contamination. The prokaryotic communities were affected by 0.5 and 1 μM Co from the onset of biofilm colonization. The biofilm biomass was comparable between treatments, but the community composition differed. Control biofilms were dominated by Cyanobacteria and Planctomycetes, whereas Bacteroidetes dominated the Co-contaminated biofilms. Potential functional redundancy was observed through the implementation of carbon fixation alternatives by non-photosynthetic prokaryotes in biofilms exposed to high Co concentrations. No structural resilience was observed in the biofilms after 35 days without Co contamination. Measuring the prokaryotic community structural response using molecular approaches appears to be a promising method for assessing shifts in water quality owing to Co contamination.

Automated identification of aquatic insects: A case study using deep learning and computer vision techniques

Deep learning techniques have recently found application in biodiversity research. Mayflies (Ephemeroptera), stoneflies (Plecoptera) and caddisflies (Trichoptera), often abbreviated as EPT, are frequently used for freshwater biomonitoring due to their large numbers and sensitivity to environmental changes. However, the morphological identification of EPT species is a challenging but fundamental task. Morphological identification of these freshwater insects is therefore not only extremely time-consuming and costly, but also often leads to misjudgments or generates datasets with low taxonomic resolution. Here, we investigated the application of deep learning to increase the efficiency and taxonomic resolution of biomonitoring programs. Our database contains 90 EPT taxa (genus or species level), with the number of images per category ranging from 21 to 300 (16,650 in total). Upon completion of training, a CNN (Convolutional Neural Network) model was created, capable of automatically classifying these taxa into their appropriate taxonomic categories with an accuracy of 98.7 %. Our model achieved a perfect classification rate of 100 % for 68 of the taxa in our dataset. We achieved noteworthy classification accuracy with morphologically closely related taxa within the training data (e.g., species of the genus Baetis, Hydropsyche, Perla). Gradient-weighted Class Activation Mapping (Grad-CAM) visualized the morphological features responsible for the classification of the treated species in the CNN models. Within Ephemeroptera, the head was the most important feature, while the thorax and abdomen were equally important for the classification of Plecoptera taxa. For the order Trichoptera, the head and thorax were almost equally important. Our database is recognized as the most extensive aquatic insect database, notably distinguished by its wealth of included categories (taxa). Our approach can help solve long-standing challenges in biodiversity research and address pressing issues in monitoring programs by saving time in sample identification.

Hidden diversity: DNA metabarcoding reveals hyper-diverse benthic invertebrate communities

BACKGROUND

Freshwater ecosystems, such as streams, are facing increasing pressures from agricultural land use and recent literature stresses the importance of robust biomonitoring to detect trends in insect decline globally. Aquatic insects and other macroinvertebrates are often used as indicators of ecological condition in freshwater biomonitoring programs; however, these diverse groups can present challenges to morphological identification and coarse-level taxonomic resolution can mask patterns in community composition. Here, we incorporate molecular identification (DNA metabarcoding) into a stream biomonitoring sampling design to explore the diversity and variability of aquatic macroinvertebrate communities at small spatial scales. While individual stream reaches can be very heterogenous, most community ecology studies focus on larger, landscape-level patterns of community composition. A high degree of community variability at the local scale has important implications for both biomonitoring and ecological research, and the incorporation of DNA metabarcoding into local biodiversity assessments will inform future sampling protocols.

RESULTS

We sampled twenty streams in southern Ontario, Canada, for aquatic macroinvertebrates across multiple time points and assessed local community variability by comparing field replicates taken ten meters apart within the same stream. Using bulk-tissue DNA metabarcoding, we revealed that aquatic macroinvertebrate communities are highly diverse at small spatial scales with unprecedented levels of local taxonomic turnover. We detected over 1600 Operational Taxonomic Units (OTUs) from 149 families, and a single insect family, the Chironomidae, contained over one third of the total number of OTUs detected in our study. Benthic communities were largely comprised of rare taxa detected only once per stream despite multiple biological replicates (24-94% rare taxa per site). In addition to numerous rare taxa, our species pool estimates indicated that there was a large proportion of taxa that remained undetected by our sampling regime (14-94% per site). Our sites were located across a gradient of agricultural activity, and while we predicted that increased land use would homogenize benthic communities, this was not supported as within-stream dissimilarity was unrelated to land use. Within-stream dissimilarity estimates were consistently high for all levels of taxonomic resolution (invertebrate families, invertebrate OTUs, chironomid OTUs), indicating stream communities are very dissimilar at small spatial scales.

Evaluation and comparison of the benthic and microbial indices of biotic integrity for urban lakes based on environmental DNA and its management implications

With the intensification of human disturbance in urban lakes, the loss of eukaryotic biodiversity (macroinvertebrates, etc.) reduces the accuracy of the index of biotic integrity (IBI) assessment. Therefore, how to accurately evaluate the ecological status of urban lakes based on IBI has become an important issue. In this study, 17 sampling sites from four lakes in Wuhan City, China were selected to analyze the composition and diversity characteristics of benthic and microbial communities and their relationship with environmental factors based on eDNA high-throughput sequencing, and compare the application effects of the benthic index of biotic integrity (B-IBI) and the microbial index of biotic integrity (M-IBI). Canonical correspondence analysis showed that the key environmental factors affecting benthic family/genus composition were temperature, conductivity, total phosphorus (TP), and total nitrogen (TN). Redundancy analysis showed that pH, TP, conductivity, and ammonia nitrogen had the greatest impact on microbial phyla/genera. After screening, four and six core metrics were determined from candidate parameters to establish B-IBI and M-IBI. The B-IBI evaluation results showed that healthy, sub-heathy, and poor accounted for 58.8%, 35.3%, and 5.9%, respectively, in the sites. The results of the M-IBI evaluation showed that 29.4% of the sites were healthy, 47.1% were sub-healthy, and 23.5% were common. M-IBI was positively correlated with water quality (r = 0.74, P < 0.001), whereas B-IBI was not. Further results showed that M-IBI was negatively correlated with the relative abundance of bloom-forming cyanobacteria Planktothrix (r = -0.54, P < 0.05). Therefore, M-IBI is more sensitive than B-IBI and can better reflect the actual water pollution status. This study can provide a new perspective for ecological assessment and management of urban lakes strongly disturbed by human activities.

MetaWorks: A flexible, scalable bioinformatic pipeline for high-throughput multi-marker biodiversity assessments

Multi-marker metabarcoding is increasingly being used to generate biodiversity information across different domains of life from microbes to fungi to animals such as for molecular ecology and biomonitoring applications in different sectors from academic research to regulatory agencies and industry. Current popular bioinformatic pipelines support microbial and fungal marker analysis, while ad hoc methods are often used to process animal metabarcode markers from the same study. MetaWorks provides a harmonized processing environment, pipeline, and taxonomic assignment approach for demultiplexed Illumina reads for all biota using a wide range of metabarcoding markers such as 16S, ITS, and COI. A Conda environment is provided to quickly gather most of the programs and dependencies for the pipeline. Several workflows are provided such as: taxonomically assigning exact sequence variants, provides an option to generate operational taxonomic units, and facilitates single-read processing. Pipelines are automated using Snakemake to minimize user intervention and facilitate scalability. All pipelines use the RDP classifier to provide taxonomic assignments with confidence measures. We extend the functionality of the RDP classifier for taxonomically assigning 16S (bacteria), ITS (fungi), and 28S (fungi), to also support COI (eukaryotes), rbcL (eukaryotes, land plants, diatoms), 12S (fish, vertebrates), 18S (eukaryotes, diatoms) and ITS (fungi, plants). MetaWorks properly handles ITS by trimming flanking conserved rRNA gene regions as well as protein coding genes by providing two options for removing obvious pseudogenes. MetaWorks can be downloaded from https://github.com/terrimporter/MetaWorks and quickstart instructions, pipeline details, and a tutorial for new users can be found at https://terrimporter.github.io/MetaWorksSite.

A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess richness of mayflies, stoneflies and caddisflies in rivers

Monitoring biodiversity is essential to understand the impacts of human activities and for effective management of ecosystems. Thereby, biodiversity can be assessed through direct collection of targeted organisms, through indirect evidence of their presence (e.g. signs, environmental DNA, camera trap, etc.), or through extrapolations from species distribution and species richness models. Differences in approaches used in biodiversity assessment, however, may come with individual challenges and hinder cross-study comparability. In the context of rapidly developing techniques, we compared three different approaches in order to better understand assessments of aquatic macroinvertebrate diversity. Specifically, we compared the community composition and species richness of three orders of aquatic macroinvertebrates (mayflies, stoneflies, and caddisflies, hereafter EPT) obtained via eDNA metabarcoding and via traditional in situ kicknet sampling to catchment-level based predictions of a species richness model. We used kicknet data from 24 sites in Switzerland and compared taxonomic lists to those obtained using eDNA amplified with two different primer sets. Richness detected by these methods was compared to the independent predictions made by a statistical species richness model, that is, a generalized linear model using landscape-level features to estimate EPT diversity. Despite the ability of eDNA to consistently detect some EPT species found by traditional sampling, we found important discrepancies in community composition between the kicknet and eDNA approaches, particularly at a local scale. We found the EPT-specific primer set fwhF2/EPTDr2n, detected a greater number of targeted EPT species compared to the more general primer set mlCOIintF/HCO2198. Moreover, we found that the species richness measured by eDNA from either primer set was poorly correlated to the richness measured by kicknet sampling (Pearson correlation = 0.27) and that the richness estimated by eDNA and kicknet were poorly correlated with the prediction of the species richness model (Pearson correlation = 0.30 and 0.44, respectively). The weak relationships between the traditional kicknet sampling and eDNA with this model indicates inherent limitations in upscaling species richness estimates, and possibly a limited ability of the model to meet real world expectations. It is also possible that the number of replicates was not sufficient to detect ambiguous correlations. Future challenges include improving the accuracy and sensitivity of each approach individually, yet also acknowledging their respective limitations, in order to best meet stakeholder demands and address the biodiversity crisis we are facing.

Environmental DNA metabarcoding for benthic monitoring: A review of sediment sampling and DNA extraction methods

Environmental DNA (eDNA) metabarcoding (parallel sequencing of DNA/RNA for identification of whole communities within a targeted group) is revolutionizing the field of aquatic biomonitoring. To date, most metabarcoding studies aiming to assess the ecological status of aquatic ecosystems have focused on water eDNA and macroinvertebrate bulk samples. However, the eDNA metabarcoding has also been applied to soft sediment samples, mainly for assessing microbial or meiofaunal biota. Compared to classical methodologies based on manual sorting and morphological identification of benthic taxa, eDNA metabarcoding offers potentially important advantages for assessing the environmental quality of sediments. The methods and protocols utilized for sediment eDNA metabarcoding can vary considerably among studies, and standardization efforts are needed to improve their robustness, comparability and use within regulatory frameworks. Here, we review the available information on eDNA metabarcoding applied to sediment samples, with a focus on sampling, preservation, and DNA extraction steps. We discuss challenges specific to sediment eDNA analysis, including the variety of different sources and states of eDNA and its persistence in the sediment. This paper aims to identify good-practice strategies and facilitate method harmonization for routine use of sediment eDNA in future benthic monitoring.

Long-term abundance trends of insect taxa are only weakly correlated

Changes in the abundances of animals, such as with the ongoing concern about insect declines, are often assumed to be general across taxa. However, this assumption is largely untested. Here, we used a database of assemblage-wide long-term insect and arachnid monitoring to compare abundance trends among co-occurring pairs of taxa. We show that 60% of co-occurring taxa qualitatively showed long-term trends in the same direction-either both increasing or both decreasing. However, in terms of magnitude, temporal trends were only weakly correlated (mean freshwater r = 0.05 (±0.03), mean terrestrial r = 0.12 (±0.09)). The strongest correlation was between trends of beetles and those of moths/butterflies (r = 0.26). Overall, even though there is some support for directional similarity in temporal trends, we find that changes in the abundance of one taxon provide little information on the changes of other taxa. No clear candidate for umbrella or indicator taxa emerged from our analysis. We conclude that obtaining a better picture of changes in insect abundances will require monitoring of multiple taxa, which remains uncommon, especially in the terrestrial realm.

The power of metabarcoding: Can we improve bioassessment and biodiversity surveys of stream macroinvertebrate communities?

Most stream bioassessment and biodiversity surveys are currently based on morphological identification of communities. However, DNA metabarcoding is emerging as a fast and cost-effective alternative for species identification. We compared both methods in a survey of benthic macroinvertebrate communities across 36 stream sites in northern Finland. We identified 291 taxa of which 62% were identified only by DNA metabarcoding. DNA metabarcoding produced extensive species level inventories for groups (Oligochaeta, Chironomidae, Simuliidae, Limoniidae and Limnephilidae), for which morphological identification was not feasible due to the high level of expertise needed. Metabarcoding also provided more insightful taxonomic information on the occurrence of three red-listed vulnerable or data deficient species, the discovery of two likely cryptic and potentially new species to Finland and species information of insect genera at an early larval stage that could not be separated morphologically. However, it systematically failed to reliably detect the occurrence of gastropods that were easily identified morphologically. The impact of mining on community structure could only be shown using DNA metabarcoding data which suggests that the finer taxonomic detail can improve detection of subtle impacts. Both methods generally exhibited similar strength of community-environment relationships, but DNA metabarcoding showed better performance with presence/absence data than with relative DNA sequence abundances. Our results suggest that DNA metabarcoding holds a promise for future anthropogenic impact assessments, although, in our case, the performance did not improve much from the morphological species identification. The key advantage of DNA metabarcoding lies in efficient biodiversity surveys, taxonomical studies and applications in conservation biology.

Linking environmental with biological data: Low sampling frequencies of chemical pollutants and nutrients in rivers reduce the reliability of model results

Linking environmental and biological data using ecological models can provide crucial knowledge about the effects of water quality parameters on freshwater ecosystems. However, a model can only be as reliable as its input data. Here, the influence of sampling frequency of temporal variable environmental input data on the reliability of model results when linked to biological data was investigated using Threshold Indicator Taxa Analysis (TITAN) and species sensitivity distributions (SSDs). Large-scale biological data from benthic macroinvertebrates and matching water quality data including four metals and four nutrients of up to 559 site-year combinations formed the initial data sets. To compare different sampling frequencies, the initial water quality data sets (n = 12 samples per year, set as reference) were subsampled (n = 10, 8, 6, 4, 2 and 1), annual mean values calculated and used as input data in the models. As expected, subsampling significantly reduced the reliability of the environmental input data across all eight substances. For TITAN, the use of environmental input data with a reduced reliability led to a considerable (1) loss of information because valid taxa were no longer identified, (2) gain of unreliable taxon-specific change points due to false positive taxa, and (3) bias in the change point estimation. In contrast, the reliability of the SSD results appeared to be much less reduced. However, closer examination of the SSD input data indicated that existing effects were masked by poor model performance. The results confirm that the sampling frequency of water quality data significantly influences the reliability of model results when linked with biological data. For studies limited to low sampling frequencies, the discussion provides recommendations on how to deal with low sampling frequencies of temporally variable water quality data when using them in TITAN, in SSDs, and in other ecological models.

Environmental DNA provides higher resolution assessment of riverine biodiversity and ecosystem function via spatio-temporal nestedness and turnover partitioning

Rapidly assessing biodiversity is essential for environmental monitoring; however, traditional approaches are limited in the scope needed for most ecological systems. Environmental DNA (eDNA) based assessment offers enhanced scope for assessing biodiversity, while also increasing sampling efficiency and reducing processing time, compared to traditional methods. Here we investigated the effects of landuse and seasonality on headwater community richness and functional diversity, via spatio-temporal dynamics, using both eDNA and traditional sampling. We found that eDNA provided greater resolution in assessing biodiversity dynamics in time and space, compared to traditional sampling. Community richness was seasonally linked, peaking in spring and summer, with temporal turnover having a greater effect on community composition compared to localized nestedness. Overall, our assessment of ecosystem function shows that community formation is driven by regional resource availability, implying regional management requirements should be considered. Our findings show that eDNA based ecological assessment is a powerful, rapid and effective assessment strategy that enables complex spatio-temporal studies of community diversity and ecosystem function, previously infeasible using traditional methods.

Mathew Seymour et al. compare eDNA with traditional biodiversity metrics to assess the functional diversity of a river basin in Wales over space and time and variable land use. Their results show that eDNA can generate greater biodiversity resolution and reliably detect spatio-temporal changes in community and functional diversity.

Adding DNA barcoding to stream monitoring protocols - What's the additional value and congruence between morphological and molecular identification approaches?

Although aquatic macroinvertebrates and freshwater fishes are important indicators for freshwater quality assessments, the morphological identification to species-level is often impossible and thus especially in many invertebrate taxa not mandatory during Water Framework Directive monitoring, a pragmatism that potentially leads to information loss. Here, we focus on the freshwater fauna of the River Sieg (Germany) to test congruence and additional value in taxa detection and taxonomic resolution of DNA barcoding vs. morphology-based identification in monitoring routines. Prior generated morphological identifications of juvenile fishes and aquatic macroinvertebrates were directly compared to species assignments using the identification engine of the Barcode of Life Data System. In 18% of the invertebrates morphology allowed only assignments to higher systematic entities, but DNA barcoding lead to species-level assignment. Dissimilarities between the two approaches occurred in 7% of the invertebrates and in 1% of the fishes. The 18 fish species were assigned to 20 molecular barcode index numbers, the 104 aquatic invertebrate taxa to 113 molecular entities. Although the cost-benefit analysis of both methods showed that DNA barcoding is still more expensive (5.30–8.60€ per sample) and time consuming (12.5h), the results emphasize the potential to increase taxonomic resolution and gain a more complete profile of biodiversity, especially in invertebrates. The provided reference DNA barcodes help building the foundation for metabarcoding approaches, which provide faster sample processing and more cost-efficient ecological status determination.

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.

Executing multi-taxa eDNA ecological assessment via traditional metrics and interactive networks

Current approaches to ecological assessment are limited by the traditional morpho-taxonomic methods presently employed and the inability to meet increasing demands for rapid assessments. Advancements in high throughput sequencing now enable rapid high-resolution ecological assessment using environmental DNA (eDNA). Here we test the ability of using eDNA-based ecological assessment methods against traditional assessment of two key indicator groups (diatoms and macroinvertebrates) and show how eDNA across multiple gene regions (COI, rbcL, 12S and 18S) can be used to infer interactive networks that link to ecological assessment criteria. We compared results between taxonomic and eDNA based assessments and found significant positive associations between macroinvertebrate (p < 0.001 R² = 0.645) and diatom (p = 0.015, R² = 0.222) assessment metrics. We further assessed the ability of eDNA based assessment to identify environmentally sensitive genera and found an order of magnitude greater potential for 18S, versus COI or rbcL, to determine environmental filtering of ecologically assessed communities. Lastly, we compared the ability of traditional metrics against co-occurrence network properties of our combined 18S, COI and rbcL indicator genera to infer habitat quality measures currently used by managers. We found that transitivity (network connectivity), linkage density and cohesion were significantly associated with habitat modification scores (HMS), whereas network properties were inconsistent with linking to the habitat quality score (HQS) metric. The incorporation of multi-marker eDNA network assessment opens up a means for finer scale ecological assessment, currently limited using traditional methods. While utilization of eDNA-based assessment is recommended, direct comparisons with traditional approaches are difficult as the methods are intrinsically different and should be treated as such with regards to future research. Overall, our findings show that eDNA can be used for effective ecological assessment while offering a wider range of scope and application compared to traditional assessment methods.

How to learn to stop worrying and love environmental DNA monitoring

Environmental DNA is one of the most promising new tools in the aquatic biodiversity monitoring toolkit, with particular appeal for applications requiring assessment of target taxa at very low population densities. And yet there persists considerable anxiety within the management community regarding the appropriateness of environmental DNA monitoring for certain tasks and the degree to which environmental DNA methods can deliver information relevant to management needs. This brief perspective piece is an attempt to address that anxiety by offering some advice on how end-users might best approach these new technologies. I do not here review recent developments in environmental DNA science, but rather I explore ways in which managers and decision-makers might become more comfortable adopting environmental DNA tools-or choosing not to adopt them, should circumstances so dictate. I attempt to contextualize the central challenges associated with acceptance of environmental DNA detection by contrasting them with traditional "catch-and-look" approaches to biodiversity monitoring. These considerations lead me to recommend the cultivation of four "virtues," attitudes that can be brought into engagement with environmental DNA surveillance technologies that I hope will increase the likelihood that those engagements will be positive and that the future development and application of environmental DNA tools will further the cause of wise management.

Minimizing human error in macroinvertebrate samples analyses for ensuring quality precision in freshwater monitoring programs

Benthic macroinvertebrates are often used in ecological quality monitoring. However, due to the large number of samples and specimens, sample processing (sorting/identification) is a labor-intensive task that is susceptible to errors. These errors can consequently lead to biased assessment results. We conducted the first audit of the Greek National Water Monitoring program. Totally, 444 samples were sorted at the laboratory by primary sorters and macroinvertebrate identification was conducted mainly at family level by primary taxonomists, having different taxonomic expertise. The Percentage Sorting Efficiency (PSE), Percentage of Taxonomic Disagreement (PTD), and the Relative Percentage Difference (RPD) were calculated to determine differences between auditing stages. Control charts were used to determine the process changes of the personnel (sorting: PSE index and identification: PTD index) as a calibration check. Additionally, national ecological indices/metrics were calculated to identify how they are affected by errors. All samples except from one had PSE values higher than 90%. The most common overlooked families were Chironomidae, followed by Baetidae and Gammaridae due to their high abundances. Average values of the PTD index for the total number of samples was 5.75% and 1.86% in each phase, respectively. The PTD values decreased between the two phases due to the gained experience of primary taxonomists during the 1st phase. The average action control limit was 95% for the PSE values and 14% for the PTD values. Overall, our ecological quality results indicated that the sorting error was less important than the identification one as the latter may lead to different ecological quality classifications. Our results show that our auditing procedure is effective and increases the quality and accuracy of the sample analysis procedure. It also highlights that human error should not be neglected since it may affect the ecological quality results and especially the good/moderate boundary which leads to rehabilitation measures.

Analysis of 13,312 benthic invertebrate samples from German streams reveals minor deviations in ecological status class between abundance and presence/absence data

Benthic invertebrates are the most commonly used organisms used to assess ecological status as required by the EU Water Framework Directive (WFD). For WFD-compliant assessments, benthic invertebrate communities are sampled, identified and counted. Taxa × abundance matrices are used to calculate indices and the resulting scores are compared to reference values to determine the ecological status class. DNA-based tools, such as DNA metabarcoding, provide a new and precise method for species identification but cannot deliver robust abundance data. To evaluate the applicability of DNA-based tools to ecological status assessment, we evaluated whether the results derived from presence/absence data are comparable to those derived from abundance data. We analysed benthic invertebrate community data obtained from 13,312 WFD assessments of German streams. Broken down to 30 official stream types, we compared assessment results based on abundance and presence/absence data for the assessment modules “organic pollution” (i.e., the saprobic index) and “general degradation” (a multimetric index) as well as their underlying metrics.

In 76.6% of cases, the ecological status class did not change after transforming abundance data to presence/absence data. In 12% of cases, the status class was reduced by one (e.g., from good to moderate), and in 11.2% of cases, the class increased by one. In only 0.2% of cases, the status shifted by two classes. Systematic stream type-specific deviations were found and differences between abundance and presence/absence data were most prominent for stream types where abundance information contributed directly to one or several metrics of the general degradation module. For a single stream type, these deviations led to a systematic shift in status from ‘good’ to ‘moderate’ (n = 201; with only n = 3 increasing). The systematic decrease in scores was observed, even when considering simulated confidence intervals for abundance data. Our analysis suggests that presence/absence data can yield similar assessment results to those for abundance-based data, despite type-specific deviations. For most metrics, it should be possible to intercalibrate the two data types without substantial efforts. Thus, benthic invertebrate taxon lists generated by standardised DNA-based methods should be further considered as a complementary approach.

Increased performance of DNA metabarcoding of macroinvertebrates by taxonomic sorting

DNA-based identification through the use of metabarcoding has been proposed as the next step in the monitoring of biological communities, such as those assessed under the Water Framework Directive (WFD). Advances have been made in the field of metabarcoding, but challenges remain when using complex samples. Uneven biomass distributions, preferential amplification and reference database deficiencies can all lead to discrepancies between morphological and DNA-based taxa lists. The effects of different taxonomic groups on these issues remain understudied. By metabarcoding WFD monitoring samples, we analyzed six different taxonomic groups of freshwater organisms, both separately and combined. Identifications based on metabarcoding data were compared directly to morphological assessments performed under the WFD. The diversity of taxa for both morphological and DNA-based assessments was similar, although large differences were observed in some samples. The overlap between the two taxon lists was 56.8% on average across all taxa, and was highest for Crustacea, Heteroptera, and Coleoptera, and lowest for Annelida and Mollusca. Taxonomic sorting in six basic groups before DNA extraction and amplification improved taxon recovery by 46.5%. The impact on ecological quality ratio (EQR) scoring was considerable when replacing morphology with DNA-based identifications, but there was a high correlation when only replacing a single taxonomic group with molecular data. Different taxonomic groups provide their own challenges and benefits. Some groups might benefit from a more consistent and robust method of identification. Others present difficulties in molecular processing, due to uneven biomass distributions, large genetic diversity or shortcomings of the reference database. Sorting samples into basic taxonomic groups that require little taxonomic knowledge greatly improves the recovery of taxa with metabarcoding. Current standards for EQR monitoring may not be easily replaced completely with molecular strategies, but the effectiveness of molecular methods opens up the way for a paradigm shift in biomonitoring.

Combining ddPCR and environmental DNA to improve detection capabilities of a critically endangered freshwater invertebrate

Isogenus nubecula is a critically endangered Plecoptera species. Considered extinct in the UK, I. nubecula was recently rediscovered (in one location of the River Dee, Wales), after 22 years of absence. In a similar way to many other species of Perlodidae, I. nubecula could be utilised as a bio-indicator, for assessing water quality and health status of a given freshwater system. However, conventional monitoring of invertebrates via kick-sampling, is invasive and expensive (time consuming). Further, such methods require a high level of taxonomic expertise. Here, we compared the traditional kick-sampling method with the use of eDNA detection using qPCR and ddPCR-analyses. In spring 2018, we sampled eDNA from twelve locations on the River Dee. I. nubecula was detected using kick-sampling in five of these locations, three locations using both eDNA detection and kick-sampling and one location using eDNA detection alone – resulting in a total of six known and distinct populations of this critically endangered species. Interestingly, despite the eDNA assay being validated in vitro and in silico, and results indicating high sensitivity, qPCR analysis of the eDNA samples proved to be ineffective. In contrast, ddPCR analyses resulted in a clear detection of I. nubecula at four locations suggesting that inhibition most likely explains the large discrepancy between the obtained qPCR and ddPCR results. It is therefore important to explore inhibition effects on any new eDNA assay. We also highlight that ddPCR may well be the best option for the detection of aquatic organisms which are either rare or likely to shed low levels of eDNA into their environment.

DNA barcode reference libraries for the monitoring of aquatic biota in Europe: Gap-analysis and recommendations for future work

Effective identification of species using short DNA fragments (DNA barcoding and DNA metabarcoding) requires reliable sequence reference libraries of known taxa. Both taxonomically comprehensive coverage and content quality are important for sufficient accuracy. For aquatic ecosystems in Europe, reliable barcode reference libraries are particularly important if molecular identification tools are to be implemented in biomonitoring and reports in the context of the EU Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD). We analysed gaps in the two most important reference databases, Barcode of Life Data Systems (BOLD) and NCBI GenBank, with a focus on the taxa most frequently used in WFD and MSFD. Our analyses show that coverage varies strongly among taxonomic groups, and among geographic regions. In general, groups that were actively targeted in barcode projects (e.g. fish, true bugs, caddisflies and vascular plants) are well represented in the barcode libraries, while others have fewer records (e.g. marine molluscs, ascidians, and freshwater diatoms). We also found that species monitored in several countries often are represented by barcodes in reference libraries, while species monitored in a single country frequently lack sequence records. A large proportion of species (up to 50%) in several taxonomic groups are only represented by private data in BOLD. Our results have implications for the future strategy to fill existing gaps in barcode libraries, especially if DNA metabarcoding is to be used in the monitoring of European aquatic biota under the WFD and MSFD. For example, missing species relevant to monitoring in multiple countries should be prioritized for future collaborative programs. We also discuss why a strategy for quality control and quality assurance of barcode reference libraries is needed and recommend future steps to ensure full utilisation of metabarcoding in aquatic biomonitoring.

DNA metabarcoding from sample fixative as a quick and voucher-preserving biodiversity assessment method

Metabarcoding is a powerful, increasingly popular tool for biodiversity assessment, but it still suffers from some drawbacks (specimen destruction, separation, and size sorting). In the present study, we tested a non-destructive protocol that excludes any sample sorting, where the ethanol used for sample preserving is filtered and DNA is extracted from the filter for subsequent DNA metabarcoding. When tested on macroinvertebrate mock communities, the method was widely successful but was unable to reliably detect mollusc taxa. Three different protocols (no treatment, shaking, and freezing) were successfully applied to increase DNA release to the fixative. The protocols resulted in similar success in taxa detection (6.8–7 taxa) but differences in read numbers assigned to taxa of interest (33.8%–93.7%). In comparison to conventional bulk sample metabarcoding of environmental samples, taxa with pronounced exoskeleton and small-bodied taxa were especially underrepresented in ethanol samples. For EPT (Ephemeroptera, Plecoptera, Trichoptera) taxa, which are important for determining stream ecological status, the methods detected 46 OTUs in common, with only 4 unique to the ethanol samples and 10 to the bulk samples. These results indicate that fixative-based metabarcoding is a non-destructive, time-saving alternative for biodiversity assessments focussing on taxa used for ecological status determination. However, for a comprehensive assessment on total invertebrate biodiversity, the method may not be sufficient, and conventional bulk sample metabarcoding should be applied.

High-throughput environmental DNA analysis informs a biological assessment of an urban stream

There is growing interest in the use of DNA barcoding and metabarcoding approaches to aid biological assessments and monitoring of waterbodies. While biodiversity measured by morphology and by DNA often has been found correlated, few studies have compared DNA data to established measures of impairment such as multimetric pollution tolerance indices used by many bioassessment programs. We incorporated environmental DNA (eDNA) metabarcoding of seston into a rigorous watershed-scale biological assessment of an urban stream to examine the extent to which eDNA richness and diversity patterns were correlated with multimetric indices and ecological impairment status designations. We also evaluated different filtering approaches and taxonomic classifications to identify best practices for environmental assessments. Seston eDNA revealed a wide diversity of eukaryotic taxa but was dominated by diatoms (36%). Differentiation among sites in alpha and beta diversity was greater when operational taxonomic units (OTUs) were classified taxonomically, but coarse resolution taxonomy (kingdom) was more informative than finer resolution taxonomy (family, genus). Correlations of DNA richness and diversity with multimetric indices for fish and macroinvertebrates were generally weak, possibly because Metazoa were not highly represented in our DNA dataset. Nonetheless, sites could be differentiated based on ecological impairment status, with more impaired sites having lower eDNA diversity as measured by the Shannon index, but higher taxonomic richness. Significant environmental drivers of community structure, as inferred from constrained ordination analyses, differed among kingdoms within the eDNA dataset, as well as from fish and macrobenthos, suggesting that eDNA provides novel environmental information. These results suggest that even a simple seston eDNA filtering protocol can provide biodiversity information of value to stream bioassessment programs. The approach bears further investigation as a potentially useful rapid assessment protocol to supplement more intensive field sampling efforts.

The influence of macroinvertebrate abundance on the assessment of freshwater quality in The Netherlands

The use of molecular tools for the detection and identification of invertebrate species enables the development of more easily standardisable inventories of biological elements for water quality assessments, as it circumvents human-based bias and errors in species identifications. Current Ecological Quality Ratio (EQR) assessments methods, however, often rely on abundance data. Translating metabarcoding sequence data into biomass or specimen abundances has proven difficult, as PCR amplification bias due to primer mismatching often provides skewed proportions of read abundances. While some potential solutions have been proposed in previous research, we instead looked at the necessity of abundance data in EQR assessments. In this study, we used historical monitoring data from natural (lakes, rivers and streams) and artificial (ditches and canals) water bodies to assess the impact of species abundances on the EQR scores for macroinvertebrates in the Water Framework Directive (WFD) monitoring programme of The Netherlands. By removing all the abundance data from the taxon observations, we simulated presence/absence-based monitoring, for which EQRs were calculated according to traditional methods. Our results showed a strong correlation between abundance-based and presence/absence-based EQRs. EQR scores were generally higher without abundances (75.8% of all samples), which resulted in 9.1% of samples being assigned to a higher quality class. The majority of the samples (89.7%) were assigned to the same quality class in both cases. These results are valuable for the incorporation of presence/absence metabarcoding data into water quality assessment methodology, potentially eliminating the need to translate metabarcoding data into biomass or absolute specimen counts for EQR assessments.

Choice of DNA extraction method affects DNA metabarcoding of unsorted invertebrate bulk samples

Characterisation of freshwater benthic biodiversity using DNA metabarcoding may allow more cost-effective environmental assessments than the current morphological-based assessment methods. DNA metabarcoding methods where sorting or pre-sorting of samples are avoided altogether are especially interesting, since the time between sampling and taxonomic identification is reduced. Due to the presence of non-target material like plants and sediments in crude samples, DNA extraction protocols become important for maximising DNA recovery and sample replicability. We sampled freshwater invertebrates from six river and lake sites and extracted DNA from homogenised bulk samples in quadruplicate subsamples, using a published method and two commercially available kits: HotSHOT approach, Qiagen DNeasy Blood &amp; Tissue Kit and Qiagen DNeasy PowerPlant Pro Kit. The performance of the selected extraction methods was evaluated by measuring DNA yield and applying DNA metabarcoding to see if the choice of DNA extraction method affects DNA yield and metazoan diversity results. The PowerPlant Kit extractions resulted in the highest DNA yield and a strong significant correlation between sample weight and DNA yield, while the DNA yields of the Blood &amp; Tissue Kit and HotSHOT method did not correlate with the sample weights. Metazoan diversity measures were more repeatable in samples extracted with the PowerPlant Kit compared to those extracted with the HotSHOT method or the Blood &amp; Tissue Kit. Subsampling using Blood &amp; Tissue Kit and HotSHOT extraction failed to describe the same community in the lake samples. Our study exemplifies that the choice of DNA extraction protocol influences the DNA yield as well as the subsequent community analysis. Based on our results, low specimen abundance samples will likely provide more stable results if specimens are sorted prior to DNA extraction and DNA metabarcoding, but the repeatability of the DNA extraction and DNA metabarcoding results was close to ideal in high specimen abundance samples.

A DNA metabarcoding protocol for hyporheic freshwater meiofauna: Evaluating highly degenerate COI primers and replication strategy

The hyporheic zone, i.e. the ecotone between surface water and the groundwater, is a rarely studied freshwater ecosystem. Hyporheic taxa are often meiofaunal (&lt;1 mm) in size and difficult to identify based on morphology. Metabarcoding approaches are promising for the study of these environments and taxa, but it is yet unclear if commonly applied metabarcoding primers and replication strategies can be used. In this study, we took sediment cores from two near natural upstream (NNU) and two ecologically improved downstream (EID) sites in the Boye catchment (Emscher River, Germany), metabarcoding their meiofaunal communities. We evaluated the usability of a commonly used, highly degenerate COI primer pair (BF2/BR2) and tested how sequencing three PCR replicates per sample and removing MOTUs present in only one out of three replicates impacts the inferred community composition. A total of 22,514 MOTUs were detected, of which only 263 were identified as Metazoa. Our results highlight the gaps in reference databases for meiofaunal taxa and the potential problems of using highly degenerate primers for studying samples containing a high number of non-metazoan taxa. Alpha diversity was higher in EID sites and showed higher community similarity when compared to NNU sites. Beta diversity analyses showed that removing MOTUs detected in only one out of three replicates per site greatly increased community similarity in samples. Sequencing three sample replicates and removing rare MOTUs is seen as a good compromise between retaining too many false-positives and introducing too many false-negatives. We conclude that metabarcoding hyporheic communities using highly degenerate COI primers can provide valuable first insights into the diversity of these ecosystems and highlight some potential application scenarios.

Environmental DNA filtration techniques affect recovered biodiversity

Freshwater metazoan biodiversity assessment using environmental DNA (eDNA) captured on filters offers new opportunities for water quality management. Filtering of water in the field is a logistical advantage compared to transport of water to the nearest lab, and thus, appropriate filter preservation becomes crucial for maximum DNA recovery. Here, the effect of four different filter preservation strategies, two filter types, and pre-filtration were evaluated by measuring metazoan diversity and community composition, using eDNA collected from a river and a lake ecosystem. The filters were preserved cold on ice, in ethanol, in lysis buffer and dry in silica gel. Our results show that filters preserved either dry or in lysis buffer give the most consistent community composition. In addition, mixed cellulose ester filters yield more consistent community composition than polyethersulfone filters, while the effect of pre-filtration remained ambiguous. Our study facilitates development of guidelines for aquatic community-level eDNA biomonitoring, and we advocate filtering in the field, using mixed cellulose ester filters and preserving the filters either dry or in lysis buffer.

River doctors: Learning from medicine to improve ecosystem management

Effective ecosystem management requires a robust methodology to analyse, remedy and avoid ecosystem damage. Here we propose that the overall conceptual framework and approaches developed over millennia in medical science and practice to diagnose, cure and prevent disease can provide an excellent template. Key principles to adopt include combining well-established assessment methods with new analytical techniques and restricting both diagnosis and treatment to qualified personnel at various levels of specialization, in addition to striving for a better mechanistic understanding of ecosystem structure and functioning, as well as identifying the proximate and ultimate causes of ecosystem impairment. In addition to applying these principles, ecosystem management would much benefit from systematically embracing how medical doctors approach and interview patients, diagnose health condition, select treatments, take follow-up measures, and prevent illness. Here we translate the overall conceptual framework from medicine into environmental terms and illustrate with examples from rivers how the systematic adoption of the individual steps proven and tested in medical practice can improve ecosystem management.

Sensitivity and accuracy of high-throughput metabarcoding methods for early detection of invasive fish species

High-throughput DNA metabarcoding has gained recognition as a potentially powerful tool for biomonitoring, including early detection of aquatic invasive species (AIS). DNA based techniques are advancing, but our understanding of the limits to detection for metabarcoding complex samples is inadequate. For detecting AIS at an early stage of invasion when the species is rare, accuracy at low detection limits is key. To evaluate the utility of metabarcoding in future fish community monitoring programs, we conducted several experiments to determine the sensitivity and accuracy of routine metabarcoding methods. Experimental mixes used larval fish tissue from multiple “common” species spiked with varying proportions of tissue from an additional “rare” species. Pyrosequencing of genetic marker, COI (cytochrome c oxidase subunit I) and subsequent sequence data analysis provided experimental evidence of low-level detection of the target “rare” species at biomass percentages as low as 0.02% of total sample biomass. Limits to detection varied interspecifically and were susceptible to amplification bias. Moreover, results showed some data processing methods can skew sequence-based biodiversity measurements from corresponding relative biomass abundances and increase false absences. We suggest caution in interpreting presence/absence and relative abundance in larval fish assemblages until metabarcoding methods are optimized for accuracy and precision.

The importance of molecular markers and primer design when characterizing biodiversity from environmental DNA

Environmental DNA (eDNA) comprises DNA fragments that have been shed into the environment by organisms, and which can be extracted from environmental samples such as water or soil. Characterization of eDNA can allow researchers to infer the presence or absence of species from a particular site without the need to locate and identify individuals, and therefore may provide an extremely valuable tool for quantifying biodiversity. However, as is often the case with relatively new protocols, methodological challenges remain. A number of earlier reviews have discussed these challenges, but none have provided extensive treatment of the critical decisions surrounding molecular markers and primer development for use in eDNA assays. This review discusses a number of options and approaches that can be used when determining which primers and gene regions are most appropriate for either targeted species detection or metabarcoding macro-organisms from eDNA. The latter represents a new field that is growing rapidly, and which has the potential to revolutionize future assessments of community and ecosystem diversity.

Environmental DNA reveals that rivers are conveyer belts of biodiversity information

DNA sampled from the environment (eDNA) is a useful way to uncover biodiversity patterns. By combining a conceptual model and empirical data, we test whether eDNA transported in river networks can be used as an integrative way to assess eukaryotic biodiversity for broad spatial scales and across the land-water interface. Using an eDNA metabarcode approach, we detect 296 families of eukaryotes, spanning 19 phyla across the catchment of a river. We show for a subset of these families that eDNA samples overcome spatial autocorrelation biases associated with the classical community assessments by integrating biodiversity information over space. In addition, we demonstrate that many terrestrial species are detected; thus suggesting eDNA in river water also incorporates biodiversity information across terrestrial and aquatic biomes. Environmental DNA transported in river networks offers a novel and spatially integrated way to assess the total biodiversity for whole landscapes and will transform biodiversity data acquisition in ecology.

Evaluating the Utility of Single-Locus DNA Barcoding for the Identification of Ribbon Worms (Phylum Nemertea)

Whereas many nemerteans (ribbon worms; phylum Nemertea) can be identified from external characters if observed alive, many are still problematic. When it comes to preserved specimens (as in e.g. marine inventories), there is a particular need for specimen identifier alternatives. Here, we evaluate the utility of COI (cytochrome c oxidase subunit I) as a single-locus barcoding gene. We sequenced, data mined, and compared gene fragments of COI for 915 individuals representing 161 unique taxonomic labels for 71 genera, and subjected different constellations of these to both distance-based and character-based DNA barcoding approaches, as well as species delimitation analyses. We searched for the presence or absence of a barcoding gap at different taxonomic levels (phylum, subclass, family and genus) in an attempt to understand at what level a putative barcoding gap presents itself. This was performed both using the taxonomic labels as species predictors and using objectively inferred species boundaries recovered from our species delimitation analyses. Our data suggest that COI works as a species identifier for most groups within the phylum, but also that COI data are obscured by misidentifications in sequence databases. Further, our results suggest that the number of predicted species within the dataset is (in some cases substantially) higher than the number of unique taxonomic labels-this highlights the presence of several cryptic lineages within well-established taxa and underscores the urgency of an updated taxonomic backbone for the phylum.

Can DNA-Based Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass--Sequence Relationships with an Innovative Metabarcoding Protocol

Metabarcoding is an emerging genetic tool to rapidly assess biodiversity in ecosystems. It involves high-throughput sequencing of a standard gene from an environmental sample and comparison to a reference database. However, no consensus has emerged regarding laboratory pipelines to screen species diversity and infer species abundances from environmental samples. In particular, the effect of primer bias and the detection limit for specimens with a low biomass has not been systematically examined, when processing samples in bulk. We developed and tested a DNA metabarcoding protocol that utilises the standard cytochrome c oxidase subunit I (COI) barcoding fragment to detect freshwater macroinvertebrate taxa. DNA was extracted in bulk, amplified in a single PCR step, and purified, and the libraries were directly sequenced in two independent MiSeq runs (300-bp paired-end reads). Specifically, we assessed the influence of specimen biomass on sequence read abundance by sequencing 31 specimens of a stonefly species with known haplotypes spanning three orders of magnitude in biomass (experiment I). Then, we tested the recovery of 52 different freshwater invertebrate taxa of similar biomass using the same standard barcoding primers (experiment II). Each experiment was replicated ten times to maximise statistical power. The results of both experiments were consistent across replicates. We found a distinct positive correlation between species biomass and resulting numbers of MiSeq reads. Furthermore, we reliably recovered 83% of the 52 taxa used to test primer bias. However, sequence abundance varied by four orders of magnitudes between taxa despite the use of similar amounts of biomass. Our metabarcoding approach yielded reliable results for high-throughput assessments. However, the results indicated that primer efficiency is highly species-specific, which would prevent straightforward assessments of species abundance and biomass in a sample. Thus, PCR-based metabarcoding assessments of biodiversity should rely on presence-absence metrics.