{"id":{"repo_id":"minho-thes","oai_identifier":"oai:repositorium.uminho.pt:1822/98570"},"canonical_url":"https://search.dev.ndltd.org/etd/minho-thes/oai:repositorium.uminho.pt:1822/98570","repository":{"repo_id":"minho-thes","name":"Universidade do Minho","base_url":"http://repositorium.sdum.uminho.pt/oai/request"},"display":{"title":"DNA-based monitoring of ichthyoplankton for application to fish biodiversity conservation and fisheries management","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Ferreira, André Luís Oliveira"],"institution":"Universidade do Minho","degree_name":"Programa doutoral em Molecular and Environmental Biology (especialização em Evolution, Biodiversity and Ecology)","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Costa, Filipe O.","Santos, António Miguel Piecho de Almeida"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-05-19","date_published":"2025-05-19","updated_at":"2026-08-21T16:46:39Z","subjects":["DNA metabarcoding","Ichthyoplankton","High-throughput sequencing","Biomonitoring","Fisheries management","Ictioplâncton","Sequenciação de alto rendimento","Biomonitorização","Gestão das pescas"],"languages":["eng"],"rights":["embargoedAccess (2 Years)"],"rights_urls":["http://creativecommons.org/licenses/by-nc-nd/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1822/98570","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"source_record":{"url":"http://repositorium.sdum.uminho.pt/oai/request?verb=GetRecord&metadataPrefix=dim&identifier=oai%3Arepositorium.uminho.pt%3A1822%2F98570","prefix":"dim"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Costa, Filipe O.","Santos, António Miguel Piecho de Almeida"]},{"key":"dc:creator","label":"Author","values":["Ferreira, André Luís Oliveira"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-12-15T14:37:44Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-05-19"]},{"key":"dc:relation","label":"Dc Relation","values":["Centre of Molecular and Environmental Biology [UIDB/04050/2020]","CIRCNA/BRB/0156/2019","LA/P/0069/2020","DFA/BD/6653/2020"]},{"key":"dc:type","label":"Dc Type","values":["doctoralThesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Programa doutoral em Molecular and Environmental Biology (especialização em Evolution, Biodiversity and Ecology)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Universidade do Minho"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["DNA metabarcoding","Ichthyoplankton","High-throughput sequencing","Biomonitoring","Fisheries management","Ictioplâncton","Sequenciação de alto rendimento","Biomonitorização","Gestão das pescas"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["embargoedAccess (2 Years)"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by-nc-nd/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1822/98570"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.","A monitorização das comunidades de ictioplâncton é essencial para avaliar a biodiversidade de peixes, a dinâmica das populações e a saúde dos ecossistemas. A tradicional identificação morfológica, embora valiosa, apresenta limitações em termos de resolução taxonómica. O DNA metabarcoding surgiu como uma forte alternativa, possibilitando identificações ao nível da espécie com alta precisão, eficiência de custo e elevado rendimento. Esta tese teve como objetivo aplicar o DNA metabarcoding a amostras de ictioplâncton recolhidas ao longo da costa portuguesa, com o intuito de melhorar a capacidade de deteção de espécies. Para tal, foram realizadas as seguintes etapas: i) otimização do protocolo de DNA metabarcoding, incluindo a extração de DNA, seleção de primers e pipelines bioinformáticos, com o intuito de maximizar a eficiência na deteção de espécies; ii) realização de um estudo de prova de conceito para testar uma abordagem multi-marcador, utilizando os genes citocromo c oxidase subunidade I (COI), 12S rRNA e 16S rRNA, comparando os resultados com os métodos morfológicos; iii) avaliação das variações mensais no ictioplâncton do estuário do Guadiana ao longo de cerca de um ano, comparando os registos de espécies obtidos através da identificação do ictioplâncton com as deteções da ictiofauna usando DNA ambiental (eDNA) proveniente da água; e iv) exploração do potencial do COI metabarcoding de ictioplâncton para identificar comunidades de mesozooplâncton. A abordagem de multi-marcador aumentou a deteção de espécies entre 20% e 36%, capturando uma gama taxonómica mais ampla do que o uso de um único marcador e identificando quase 7 vezes mais espécies (n=75) do que a morfologia (n=11). A monitorização mensal baseada em metabarcoding revelou-se altamente eficaz na identificação da riqueza e dos padrões sazonais de reprodução da ictiofauna local. O eDNA proveniente da água detetou 40% menos espécies em comparação com o metabarcoding do ictioplâncton, identificando apenas cerca de 50% das espécies recuperadas por este último, apesar da utilização dos mesmos primers. Este resultado reflete a diferença na natureza e no modo de recolha do material biológico (recolha em massa por rede versus filtração de água), destacando aspetos a considerar para uma monitorização eficaz de peixes baseada em DNA. Além disso, a análise dos dados adicionais do COI metabarcoding permitiu a identificação de 429 espécies de mesozooplâncton, demonstrando o valor desta abordagem na obtenção de uma perspetiva mais holística das comunidades do ecossistema. Este estudo confirma o potencial do DNA metabarcoding como uma ferramenta poderosa para apoiar a monitorização do ictioplâncton e a gestão das pescas, enfatizando o seu valor em futuros programas de monitorização para orientar estratégias de conservação em ecossistemas costeiros e estuarinos."]},{"key":"dc:title","label":"Title","values":["DNA-based monitoring of ichthyoplankton for application to fish biodiversity conservation and fisheries management"]}]}],"canonical_facts":{"dc:contributor.advisor":["Costa, Filipe O.","Santos, António Miguel Piecho de Almeida"],"dc:creator":["Ferreira, André Luís Oliveira"],"dc:date.accessioned":["2025-12-15T14:37:44Z"],"dc:date.issued":["2025-05-19"],"dc:description.abstract":["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.","A monitorização das comunidades de ictioplâncton é essencial para avaliar a biodiversidade de peixes, a dinâmica das populações e a saúde dos ecossistemas. A tradicional identificação morfológica, embora valiosa, apresenta limitações em termos de resolução taxonómica. O DNA metabarcoding surgiu como uma forte alternativa, possibilitando identificações ao nível da espécie com alta precisão, eficiência de custo e elevado rendimento. Esta tese teve como objetivo aplicar o DNA metabarcoding a amostras de ictioplâncton recolhidas ao longo da costa portuguesa, com o intuito de melhorar a capacidade de deteção de espécies. Para tal, foram realizadas as seguintes etapas: i) otimização do protocolo de DNA metabarcoding, incluindo a extração de DNA, seleção de primers e pipelines bioinformáticos, com o intuito de maximizar a eficiência na deteção de espécies; ii) realização de um estudo de prova de conceito para testar uma abordagem multi-marcador, utilizando os genes citocromo c oxidase subunidade I (COI), 12S rRNA e 16S rRNA, comparando os resultados com os métodos morfológicos; iii) avaliação das variações mensais no ictioplâncton do estuário do Guadiana ao longo de cerca de um ano, comparando os registos de espécies obtidos através da identificação do ictioplâncton com as deteções da ictiofauna usando DNA ambiental (eDNA) proveniente da água; e iv) exploração do potencial do COI metabarcoding de ictioplâncton para identificar comunidades de mesozooplâncton. A abordagem de multi-marcador aumentou a deteção de espécies entre 20% e 36%, capturando uma gama taxonómica mais ampla do que o uso de um único marcador e identificando quase 7 vezes mais espécies (n=75) do que a morfologia (n=11). A monitorização mensal baseada em metabarcoding revelou-se altamente eficaz na identificação da riqueza e dos padrões sazonais de reprodução da ictiofauna local. O eDNA proveniente da água detetou 40% menos espécies em comparação com o metabarcoding do ictioplâncton, identificando apenas cerca de 50% das espécies recuperadas por este último, apesar da utilização dos mesmos primers. Este resultado reflete a diferença na natureza e no modo de recolha do material biológico (recolha em massa por rede versus filtração de água), destacando aspetos a considerar para uma monitorização eficaz de peixes baseada em DNA. Além disso, a análise dos dados adicionais do COI metabarcoding permitiu a identificação de 429 espécies de mesozooplâncton, demonstrando o valor desta abordagem na obtenção de uma perspetiva mais holística das comunidades do ecossistema. Este estudo confirma o potencial do DNA metabarcoding como uma ferramenta poderosa para apoiar a monitorização do ictioplâncton e a gestão das pescas, enfatizando o seu valor em futuros programas de monitorização para orientar estratégias de conservação em ecossistemas costeiros e estuarinos."],"dc:identifier.uri":["https://hdl.handle.net/1822/98570"],"dc:language.iso":["eng"],"dc:relation":["Centre of Molecular and Environmental Biology [UIDB/04050/2020]","CIRCNA/BRB/0156/2019","LA/P/0069/2020","DFA/BD/6653/2020"],"dc:rights":["embargoedAccess (2 Years)"],"dc:rights.uri":["http://creativecommons.org/licenses/by-nc-nd/4.0/"],"dc:subject":["DNA metabarcoding","Ichthyoplankton","High-throughput sequencing","Biomonitoring","Fisheries management","Ictioplâncton","Sequenciação de alto rendimento","Biomonitorização","Gestão das pescas"],"dc:title":["DNA-based monitoring of ichthyoplankton for application to fish biodiversity conservation and fisheries management"],"dc:type":["doctoralThesis"],"thesis:degree_name":["Programa doutoral em Molecular and Environmental Biology (especialização em Evolution, Biodiversity and Ecology)"],"thesis:institution_name":["Universidade do Minho"]},"updated_at":"2026-08-21T16:46:39Z"}