Quantitative assessment of fish larvae community composition in spawning areas using metabarcoding of bulk samples.

Accurate assessment of larval community composition in spawning areas is essential for fisheries management and conservation but is often hampered by the cryptic nature of many larvae, which renders them difficult to identify morphologically. Metabarcoding is a rapid and cost-effective method to monitor early life stages for management and environmental impact assessment purposes but its quantitative capability is under discussion. We compared metabarcoding with traditional morphological identification to evaluate taxonomic precision and reliability of abundance estimates, using 332 fish larvae from multinet hauls (0-50 m depth) collected at 14 offshore sampling sites in the Irish and Celtic seas. To improve quantification accuracy (relative abundance estimates), the amount of tissue for each specimen was standardized and mitochondrial primers (12S gene) with conserved binding sites were used. Relative family abundance estimated from metabarcoding reads and morphological assessment were positively correlated, as well as taxon richness (R  = 0.81, P = 0.007) and diversity (R  = 0.90, P = 0.002). Spatial patterns of community composition did not differ significantly between metabarcoding and morphological assessments. Our results show that DNA metabarcoding of bulk tissue samples can be used to monitor changes in fish larvae abundance and community composition. This represents a feasible, efficient, and faster alternative to morphological methods that can be applied to terrestrial and aquatic habitats.