No abstract

100Effective identification of species using short DNA fragments (DNA barcoding and DNA 101 metabarcoding) requires reliable sequence reference libraries of known taxa. Both 102 taxonomically comprehensive coverage and content quality are important for sufficient 103 accuracy. For aquatic ecosystems in Europe, reliable barcode reference libraries are 104 particularly important if molecular identification tools are to be implemented in biomonitoring 105 and reports in the context of the EU Water Framework Directive (WFD) and the Marine 106Strategy Framework Directive (MSFD). We analysed gaps in the two most important 107 reference databases, Barcode of Life Data Systems (BOLD) and NCBI GenBank, with a 108 focus on the taxa most frequently used in WFD and MSFD. Our analyses show that 109 coverage varies strongly among taxonomic groups, and among geographic regions. In 110 general, groups that were actively targeted in barcode projects (e.g. fish, true bugs, 111 caddisflies and vascular plants) are well represented in the barcode libraries, while others 112 have fewer records (e.g. marine molluscs, ascidians, and freshwater diatoms). We also 113 found that species monitored in several countries often are represented by barcodes in 114 reference libraries, while species monitored in a single country frequently lack sequence 115 records. A large proportion of species (up to 50%) in several taxonomic groups are only 116represented by private data in BOLD. Our results have implications for the future strategy to 117 fill existing gaps in barcode libraries, especially if DNA metabarcoding is to be used in the 118 monitoring of European aquatic biota under the WFD and MSFD. For example, missing 119 species relevant to monitoring in multiple countries should be prioritized. We also discuss 120 why a strategy for quality control and quality assurance of barcode reference libraries is 121 needed and recommend future steps to ensure full utilization of metabarcoding in aquatic 122 biomonitoring. 123 124

Background The heterogeneous nature of environmental DNA (eDNA) and its effects on species detection and community composition estimates has been highlighted in several studies in the past decades. Mostly in the context of spatial distribution over large areas, in fewer occasions looking at spatial distribution within a single body of water. Temporal variation of eDNA, similarly, has mostly been studied as seasonality, observing changes over large periods of time, and often only for small groups of organisms such as fish and amphibians. Methods We analyzed and compared small-scale spatial and temporal variation by sampling eDNA from two small, isolated dune lakes for 20 consecutive weeks. Metabarcoding was performed on the samples using generic COI primers. Molecular operational taxonomic unit (MOTUs) were used to assess dissimilarities between spatial and temporal replicates. Results Our results show large differences between samples taken within one lake at one point in time, but also expose the large differences between temporal replicates, even those taken only 1 week apart. Furthermore, between-site dissimilarities showed a linear correlation with time frame, indicating that between-site differences will be inflated when samples are taken over a period of time. We also assessed the effects of PCR replicates and processing strategies on general patterns of dissimilarity between samples. While more inclusive PCR replicate strategies lead to higher richness estimations, dissimilarity patterns between samples did not significantly change. Conclusions We conclude that the dissimilarity of temporal replicates at a 1 week interval is comparable to that of spatial replicate samples. It increases, however, for larger time intervals, which suggests that population turnover effects can be stronger than community heterogeneity. Spatial replicates alone may not be enough for optimal recovery of taxonomic diversity, and cross-comparisons of different locations are susceptible to inflated dissimilarities when performed over larger time intervals. Many of the observed MOTUs could be classified as either phyto- or zooplankton, two groups that have gained traction in recent years as potential novel bio-indicator species. Our results, however, indicate that these groups might be susceptible to large community shifts in relatively short periods of time, highlighting the need to take temporal variations into consideration when assessing their usability as water quality indicators.

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.

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/absencebased 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.