Multi-marker DNA barcoding for zooplankton community inference
We present an analytical pipeline for time-efficient DNA-metabarcoding species identification and diversity inference in zooplankton communities, based on total DNA extracted from water samples. These bulk tissue samples were either taken directly from the open water of ponds or resulted from hatching experiments on resting stages from sediment. We used a two-fragment DNA metabarcoding approach (COI and 18S) which significantly improved species recognition by offsetting some of the errors that may have occurred due to incompleteness of reference databases, but potentially also due to primer bias, i.e., biased amplification successes among different taxonomic groups (Cicala et al., 2021; Clarke et al., 2017; Leite et al., 2021; Stefanni et al., 2018; Zhang et al., 2018). Indeed, without the use of two markers, a fair proportion of species (41.5 %) in our kettle holes would have remained undetected, potentially reducing the power of our biodiversity assessment. It should be noted that utilization of public uncurated sequence databases may have an influence on species detection, in two ways: (1) taxonomic misassignments of sequences will go undetected and lead to erroneous species assignment; (2) public databases may be incomplete regarding species potentially encountered in a DNA metabarcoding study. While the former could only be mitigated by carefully curated data bases not available to date and beyond the scope of individual barcoding studies, taxonomic misassignment because of data base incompleteness is minimized by applying stringent established thresholds of sequence identity (here, ≥ 97 %). This approach is conservative in the sense of avoiding false positives, at the expense of potentially underestimating species diversity (as OTUs not assigned with certainty to a species were excluded). Indeed, field studies in the area (albeit not in the same years and kettle holes) have revealed a total of 89 zooplankton species (Colangeli, 2018) by microscopic identification. Our study revealing 65 species in total may hence have underestimated the true diversity.