Adapting metabarcoding-based benthic biomonitoring into routine marine ecological status assessment networks

Abstract

The use of genomic approaches to assist with biodiversity estimations is an alternative to traditional biomonitoring, which is very time-consuming and costly. In response to the high demand for quick community descriptions, DNA metabarcoding can simultaneously assign taxonomy to hundreds of samples rapidly and at low cost. However, the technique has not routinely been incorporated into biomonitoring network programs yet. Here, we applied DNA metabarcoding methodologies at stations within the monitoring network of the Basque Water Agency, the competent authority for the application of the European Water Framework Directive in this region. We characterized the benthic macroinvertebrate communities from 18 estuarine and coastal sediment samples using morphology and metabarcoding-based taxonomic identification and evaluated the performance of several versions of the AZTI's Marine Biotic Index (AMBI). Although metabarcoding detected 112 taxa against the 206 taxa identified through morphology, we showed that metabarcoding leads to similar biomonitoring conclusions compared with traditional techniques. Using the abundance and biomass of those taxa detected from morphological methodologies, we found a significant positive correlation with the number of reads obtained with metabarcoding approaches. The metabarcoding-based index derived from read counts, gAMBI, and the morphology-based index derived from individuals' biomass, (B)AMBI, showed the best correlation and revealed excellent agreement at determining the ecological status of the stations analyzed. We calculated that, for the analysis of the 51 stations included in the Basque monitoring network, metabarcoding was 55\% less costly and 72\% less time consuming. The results of our study are relevant to policy makers and researchers in the field of ecological assessment and will contribute to the quick implementation of DNA metabarcoding to intensive monitoring programs.