Rapid quantitative assessment of fish larvae community composition using metabarcoding

Abstract

Climate change stressors greatly impact the early life-stages of many organisms but their cryptic morphology often renders them difficult to monitor using morphological identification. High-throughput sequencing of DNA amplicons (metabarcoding) is potentially a rapid and cost-effective method to monitor early life-stages for management and environmental impact assessment purposes. Yet, there is conflicting information about the quantitative capability of metabarcoding. We compared metabarcoding with traditional morphological identification to evaluate taxonomic precision and reliability of abundance estimates, using 332 fish larvae from multinet hauls (0-50m depth) collected at 14 offshore sampling sites in the Irish and Celtic seas. To improve relative abundance estimates, the amount of tissue for each specimen was standardised and mitochondrial primers with conserved binding sites were used. Family level correction factors for amplification bias and back-calculations were applied to estimate numbers of individuals of a given taxon in a sample. Estimates from metabarcoding reads and morphological assessment were positively correlated for relative family abundances as well as taxon richness (Rs=0.81, P=0.007) and diversity (Rs=0.88, P=0.003). After applying family level correction, back-estimates of the number of individuals per family within a sample were accurate to {+/-} 2 individuals. 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 identification that can be applied to terrestrial and aquatic habitats.