From egg to adult: comprehensive (e)DNA metabarcoding monitoring of fish diversity in a temperate estuary

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This study compared fish diversity detection via eDNA and ichthyoplankton metabarcoding, finding metabarcoding identified significantly more species, captured seasonal variations, and revealed spawning periods in the Guadiana Estuary.

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Abstract

Monitoring fish species through ichthyoplankton surveys provides important information for fish stock assessment and management. To test the effectiveness of DNA metabarcoding to identify fish species and to capture seasonal variations in local ichthyofauna, monthly ichthyoplankton and 2 L water samples were collected over 13 months in the lower section of the Guadiana River Estuary in southeast Portugal. Both sample types underwent high-throughput sequencing for three genetic markers (COI, 12S, 16S), with morphological identification also performed for ichthyoplankton. Bulk and water samples identified a total of 131 fish species throughout the year. DNA metabarcoding demonstrated higher taxonomic resolution and diversity detection, with 115 species recovered, while morphology identified only 23 species. Ichthyoplankton metabarcoding also detected 40% more fish than water eDNA, recovering almost the double of species despite the fact that both approaches used the same metabarcoding primers. The integration of multiple molecular markers was crucial to maximize diversity detection in both DNA-based methods. In addition, DNA metabarcoding was able to identify ichthyofaunal spawning periods and captured significant seasonal variations in fish community, with higher diversity observed during the warmer months. With this strategy, around 66% of the historically recorded ichthyoplankton taxa in the region were identified, along with several new records. The findings demonstrated the capability of (e)DNA metabarcoding to uncover seasonal variations in the regional fish community, provided new insights on the ichthyofauna of the Guadiana Estuary, and revealed the need for more in-depth studies to improve the efficiency of multiple sampling methods for fish species identification.

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last seen: 2026-05-20T01:45:00.602351+00:00