DNA metabarcoding as a tool for characterising the spatio-temporal distribution of planktonic larvae in the phylum Echinodermata

Abstract

AbstractMetabarcoding is revolutionising the analysis of biodiversity in marine ecosystems, especially as it provides a means of detecting and identifying cryptic life stages in field samples. The planktonic larval stage of many species underpins the abundance and distribution of adult populations but is challenging to characterise given the small size of larvae and diffuse distributions in pelagic waters. Yet, planktonic larval dynamics are key to understanding phenomena observed in adult populations, such as the boom-and-bust dynamics exhibited by some echinoderms. Rapid changes in echinoderm population density can have significant effects on local benthic ecosystems. For example, outbreaks of the crown-of-thorns sea star (CoTS) on the Great Barrier Reef (GBR) have led to considerable declines in coral cover. Here, we used a DNA metabarcoding approach to investigate the spatio-temporal distribution and diversity of echinoderm larvae on the GBR, including CoTS. Generalised linear mixed models revealed that echinoderm larval richness, was significantly correlated with temporal variables (i.e. season and year) which is consistent with expected fluctuations in larval output based on adult spawning periodicity. However, neither site-specific differences in echinoderm larval richness, nor correlations between larval composition and environmental, temporal, or spatial variables were found. This study validates the utility of metabarcoding approaches for detecting and characterising echinoderm larvae, including CoTS, which could prove useful to future monitoring efforts. Our findings suggest that metabarcoding can be used to better understand the life history of planktonic larvae, and analyses combining environmental (e.g., temperature, nutrients) and oceanographic (e.g., currents) data could deliver valuable information on the factors influencing their spatio-temporal distributions.