Leveraging ichthyoplankton metabarcoding to identify non-target invertebrate diversity and ecological patterns

Abstract

DNA metabarcoding has emerged as a powerful tool for biodiversity assessment in aquatic ecosystems; however, most studies focus solely on target taxa. This study leveraged surplus COI metabarcoding data originally generated from ichthyoplankton bulk samples to characterize mesozooplanktonic marine invertebrate communities across coastal and estuarine environments in southern Portugal. By reanalyzing the previously generated high-throughput sequencing (HTS) amplicon libraries of two COI primer sets, a total of 424 mesozooplankton taxa (403 species) belonging to 10 metazoan phyla were identified, revealing diverse non-target groups. Arthropoda, Mollusca, and Cnidaria were the most represented phyla, accounting for 84.12% of the total species-level diversity, while the estuarine records overlapped with 62.5% of the historically documented species represented in the COI reference database. Additionally, significant seasonal variability in mesozooplankton composition was detected during the estuarine sampling period, and higher species richness was observed at nearshore sites in the separately analyzed marine dataset. The low diversity observed during summer (n = 105) in estuarine samples, compared to the unexpectedly higher richness in winter (n = 126), appears to reflect the atypical climatic conditions recorded during the sampling year. These findings suggest that metabarcoding, even when applied to non-target taxa, can potentially detect shifts in community composition that, in this case, may be associated with particular hydrological and climatic conditions. Furthermore, 28 taxa classified as non-indigenous species (NIS) in the Bay of Biscay and Iberian Coast region were identified, highlighting the capacity of this molecular approach to support early NIS screening in regular assessments. Overall, this study demonstrates that ichthyoplankton metabarcoding datasets can be repurposed to provide insights into broader planktonic communities, maximizing the ecological value of routine monitoring efforts.