Department Aquatic Ecology

Advancements have been made in the use of DNA-based methods for the detection of single species. However, the routine application of DNA-based methods to monitor whole communities using a metabarcoding approach and derive ecosystem status continues to be limited. We undertook a structured experiment to assess factors influencing the precision and accuracy of molecular methods for freshwater macroinvertebrate community assessment. Macroinvertebrates were sorted, identified and counted from kick-net samples using standard morphometric protocols, then reconstituted. These bulk specimen samples were then homogenised. From each bulk sample, aliquots of the homogenate were distributed among seven laboratories across Europe for DNA extraction, PCR amplification, library preparation and sequencing. Additionally, each laboratory was provided with a DNA extract from the bulk homogenate to allow for amplification through to sequencing, in order to assess the influence of DNA extraction. Hierarchical nested analyses were used to identify sources of uncertainty in the data and explore factors influencing the returned community and metrics of ecosystem quality. Furthermore, comparison with morphological analysis enabled us to benchmark molecular to traditional processing approaches. Metrics derived by morphological and DNA-based methods differed substantially. The strongest methodological influences on variance in metrics derived from DNA-based methods were attributed to sequencing (read count per sample) and laboratory (strong variation within samples). Furthermore, the performance of the DNA-based method varied among samples, most likely due to differences in the composition of the invertebrate community. Logistic regression indicated that detectability did not vary among taxa, but that taxa occurring in low abundance (less than five individuals in our samples) were more likely to be missed via metabarcoding. Our findings highlight sources of uncertainty influencing DNA-based methods and, particularly, the variability of results generated from individual laboratories. Our findings underline the need for clear guidelines, standardisation and quality assurance schemes.