Publicação
DNA-based monitoring of ichthyoplankton for application to fish biodiversity conservation and fisheries management
| Resumo: | Monitoring ichthyoplankton communities is essential for assessing fish biodiversity, stock dynamics, and ecosystem health. Traditional morphological identification methods, while valuable, present limitations in terms of taxonomic resolution. DNA metabarcoding has emerged as a powerful alternative, offering high-throughput, cost-effective, and precise species identification. This thesis aimed to apply DNA metabarcoding to ichthyoplankton samples collected along the Portuguese coast to enhance species detection and provide comprehensive insights into fish biodiversity. To achieve this goal, we: i) optimized the DNA metabarcoding workflow, including DNA extraction, primer selection, and bioinformatic pipelines, to maximize species recovery and detection efficiency; ii) conducted a proof-of-concept study to benchmark a multi-marker approach, employing short mitochondrial sequences from cytochrome c oxidase subunit I (COI), 12S rRNA, and 16S rRNA genes, against morphological methods; iii) assessed monthly variations in the Guadiana estuary ichthyoplankton over a 1 year period, comparing species records using morphological identification and bulk metabarcoding, with ichthyofauna detections using environmental DNA (eDNA) from water; and iv) explored the potential of COI-based ichthyoplankton metabarcoding to identify co-occurring mesozooplankton communities. The metabarcoding multi-marker approach enhanced species detection by 20% to 36%, capturing a broader taxonomic range than single-marker strategies and reaching nearly 7 times more species detections (n=75) than morphology (n= 11). Metabarcoding-based monthly monitoring of the ichthyoplankton in the Guadiana estuary was highly effective in revealing the richness of that nursery ground and the diversity of seasonal reproduction patterns of the local ichthyofauna. The eDNA from water detected 40% fewer fish species than ichthyoplankton metabarcoding, identifying only around 50% of the species recovered by the latter despite using the same metabarcoding primers. This result likely reflects the biological material's different nature and mode of collection (bulk net collection versus filtered water), highlighting key aspects that must be considered for effective fish DNA-based monitoring. Furthermore, surplus COI metabarcoding data identified of 429 mesozooplanktonic species, demonstrating the value of this approach in providing a more holistic perspective of the ecosystem’s communities. This study confirms the potential of DNA metabarcoding as a powerful tool to support ichthyoplankton monitoring and fisheries management, emphasizing its essential implementation in future surveys to guide conservation efforts in coastal and estuarine ecosystems. |
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| Autores principais: | Ferreira, André Luís Oliveira |
| Assunto: | DNA metabarcoding Ichthyoplankton High-throughput sequencing Biomonitoring Fisheries management DNA Metabarcoding Ictioplâncton Sequenciação de alto rendimento Biomonitorização Gestão das pescas |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | tese de doutoramento |
| Tipo de acesso: | acesso embargado |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | Monitoring ichthyoplankton communities is essential for assessing fish biodiversity, stock dynamics, and ecosystem health. Traditional morphological identification methods, while valuable, present limitations in terms of taxonomic resolution. DNA metabarcoding has emerged as a powerful alternative, offering high-throughput, cost-effective, and precise species identification. This thesis aimed to apply DNA metabarcoding to ichthyoplankton samples collected along the Portuguese coast to enhance species detection and provide comprehensive insights into fish biodiversity. To achieve this goal, we: i) optimized the DNA metabarcoding workflow, including DNA extraction, primer selection, and bioinformatic pipelines, to maximize species recovery and detection efficiency; ii) conducted a proof-of-concept study to benchmark a multi-marker approach, employing short mitochondrial sequences from cytochrome c oxidase subunit I (COI), 12S rRNA, and 16S rRNA genes, against morphological methods; iii) assessed monthly variations in the Guadiana estuary ichthyoplankton over a 1 year period, comparing species records using morphological identification and bulk metabarcoding, with ichthyofauna detections using environmental DNA (eDNA) from water; and iv) explored the potential of COI-based ichthyoplankton metabarcoding to identify co-occurring mesozooplankton communities. The metabarcoding multi-marker approach enhanced species detection by 20% to 36%, capturing a broader taxonomic range than single-marker strategies and reaching nearly 7 times more species detections (n=75) than morphology (n= 11). Metabarcoding-based monthly monitoring of the ichthyoplankton in the Guadiana estuary was highly effective in revealing the richness of that nursery ground and the diversity of seasonal reproduction patterns of the local ichthyofauna. The eDNA from water detected 40% fewer fish species than ichthyoplankton metabarcoding, identifying only around 50% of the species recovered by the latter despite using the same metabarcoding primers. This result likely reflects the biological material's different nature and mode of collection (bulk net collection versus filtered water), highlighting key aspects that must be considered for effective fish DNA-based monitoring. Furthermore, surplus COI metabarcoding data identified of 429 mesozooplanktonic species, demonstrating the value of this approach in providing a more holistic perspective of the ecosystem’s communities. This study confirms the potential of DNA metabarcoding as a powerful tool to support ichthyoplankton monitoring and fisheries management, emphasizing its essential implementation in future surveys to guide conservation efforts in coastal and estuarine ecosystems. |
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