Scales of variation in zooplankton communities and monitoring for species of concern in southcentral Alaska

Abstract DNA metabarcoding of plankton samples is a cost-effective approach to analyze the richness and composition of zooplankton in coastal waters. Plankton surveys using metabarcoding can also be used to monitor species of concern, both for planktonic species and benthic species with planktonic larvae. We used DNA metabarcoding with the mitochondrial cytochrome oxidase I gene to: (1) evaluate time of sampling (year, month, week), tidal cycle, time of day, and sampling location as potential sources of variation for zooplankton community richness and composition, and (2) as an early detection tool for species of concern in Prince William Sound. We found that seasonality of sampling had the strongest impact on species richness and community composition. Differences in community composition were mostly driven by differences among meroplankton groups, with the peak in meroplankton abundance occurring in April and May, depending on the location. We detected eight potentially introduced species, three holoplanktonic (Limnoithona tetraspina, Oithona davisae, Pseudodiaptomus marinus), one benthic (Monocorophium acherusicum), and four meroplanktonic species (Amphibalanus improvisus, Philine auriformis, Alitta succinea, Marenzelleria neglecta). Most of these potentially introduced species detections occurred in a single sample with low read counts; but Oithona davisae was detected in three locations over two years. We discuss confidence in the genetic ID and invasion history for each of the species of concern. We showed that (1) plankton surveys can be a broad monitoring tool for species of concern, (2) timing of sampling can be critical depending on the organisms’ life histories, and (3) sampling during the meroplankton peak concentration can increase the chance of detecting larval stages of introduced benthic species. Finally, we provide some bioinformatic recommendations to improve species detection and validate identifications.