Abstract
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.
Highlights
Quality monitoring of freshwater ecosystems is prescribed under the European Union Water Framework Directive of 2000 (EU WFD; Directive 2000/60/EC) and focuses on monitoring of biological quality elements (BQEs)
Removal of abundance data had a stronger effect on samples from the lowest quality class (“bad”), where the mean ΔEQR was significantly higher than all other quality classes (Dunn’s test, p
In the artificial systems, this only amounts to one third of the final score, so one would expect the impact to be smaller, especially considering that the quality classes most impacted by the removal of abundance (“bad” and “poor”, Figure 2B) only account for 35.8% of the artificial water samples in the data presented in this paper, whereas those classes account for 49.4% and 81.1% of lakes and streams, respectively
Summary
Quality monitoring of freshwater ecosystems is prescribed under the European Union Water Framework Directive of 2000 (EU WFD; Directive 2000/60/EC) and focuses on monitoring of biological quality elements (BQEs). In Europe, benthic invertebrates are one of the most prevalently monitored BQE (Birk et al 2012). Traditional monitoring of freshwater macroinvertebrates, is labour-intensive and heavily dependent on expert knowledge of the assessors, making it slow, expensive and prone to human-induced bias and errors at all stages of collecting, sorting and identifying (Clarke and Hering 2006, Haase et al 2010). The incorporation of DNA barcodes (Hebert et al 2003) into the identification process seems to have alleviated some of the human-induced issues.
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