Species Composition and Diversity Patterns across the Salish Sea: Multiple Targeted Metabarcode Analyses of Zooplankton and eDNA in Relation to Chemical Conditions

Ecological sampling depends on accurate taxon identification, delineation, and abundances, yet traditional analyses are time consuming, expensive, involve considerable taxonomic expertise, and often are thwarted by lack of diagnostic morphological characters. The latter is especially true for early life stages, rare, invasive, and/or cryptic taxa. Targeted multi-gene metabarcode high-throughput sequencing (HTS) analyses entailing field sampling and bioinformatics offers means to rapidly and accurately simultaneously characterize the species identities, diversity, and compositions of entire communities, including rare and cryptic taxa, along with their relative representation. We present results of multiple diagnostic Illumina MiSeq HTS assays and our custom bioinformatics pipeline developed to analyze communities of invertebrates and fishes from zooplankton net tows, and environmental (e)DNA water samples, from the Washington Ocean Acidification Center’s cruises in the Salish Sea. We compare and contrast results among sites, seasons, and years, for seven locations from samples taken in April, July, and September 2018 and 2019. Biological community compositions, diversity levels, and species patterns are compared to water chemistry, including temperature, pH, salinity, and dissolved oxygen to elucidate possible effects of hypoxia, acidification, and other environmental fluctuations. We statistically compare our sequence read results to conventional morphological identifications from microscopy, revealing positive relationships to species identities, counts of individuals, and their respective biomasses, with better fit to biomass than counts. Findings show considerable divergence in species composition and diversity among sites and in relation to seasonality, which reflect salinity and pH and proximity to the ocean and nearby populations. This approach appears especially useful for assessing species diversity of marine communities in conjunction with changing conditions, including ocean acidification, temperature, and hypoxia. Results from these multiple metabarcode analyses demonstrate considerable application across marine ecosystems at a scale, accuracy, complexity, and capacity for automation not otherwise feasible.