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Towards a unified eco-evolutionary framework for fisheries management: Coupling advances in next-generation sequencing with species distribution modelling

2023Journal article Open access
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dc.contributor.authorBaltazar-Soares, Miguel
dc.contributor.authorLima, André R.A.
dc.contributor.authorSilva, Gonçalo
dc.contributor.authorGaget, Elie
dc.date.accessioned2023-02-27T20:17:10Z
dc.date.available2023-02-27T20:17:10Z
dc.date.issued2023
dc.description.abstractThe establishment of high-throughput sequencing technologies and subsequent large-scale genomic datasets has flourished across fields of fundamental biological sciences. The introduction of genomic resources in fisheries management has been proposed from multiple angles, ranging from an accurate re-definition of geographical limitations of stocks and connectivity, identification of fine-scale stock structure linked to locally adapted subpopulations, or even the integration with individual-based biophysical models to explore life history strategies. While those clearly enhance our perception of patterns at the light of a spatial scale, temporal depth and consequently forecasting ability might be compromised as an analytical trade-off. Here, we present a framework to reinforce our understanding of stock dynamics by adding also a temporal point of view. We propose to integrate genomic information on temporal projections of species distributions computed by Species Distribution Models (SDMs). SDMs have the potential to project the current and future distribution ranges of a given species from relevant environmental predictors. These projections serve as tools to inform about range expansions and contractions of fish stocks and suggest either suitable locations or local extirpations that may arise in the future. However, SDMs assume that the whole population respond homogenously to the range of environmental conditions. Here, we conceptualize a framework that leverages a conventional Bayesian joint-SDM approach with the incorporation of genomic data. We propose that introducing genomic information at the basis of a joint-SDM will explore the range of suitable habitats where stocks could thrive in the future as a function of their current evolutionary potential.pt_PT
dc.description.sponsorshipFundação para a Ciência e Tecnollogia - FCT; ARNETpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBaltazar-Soares, M., Lima, A. R. A., Silva, G., & Gaget, E. (2023). Towards a unified eco-evolutionary framework for fisheries management: Coupling advances in next-generation sequencing with species distribution modelling. Frontiers in Marine Science, 9 https://doi.org/10.3389/fmars.2022.1014361opt_PT
dc.identifier.doi10.3389/fmars.2022.1014361pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.12/9054
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherFrontiers Media S.A.pt_PT
dc.relationLA/ P/0069/2020pt_PT
dc.relationMarine and Environmental Sciences Centre
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectHigh-throughput sequencingpt_PT
dc.subjectgenomicspt_PT
dc.subjectSpecies distribution model (SDMs)pt_PT
dc.subjectFisheries applicationspt_PT
dc.subjectEvolutionary ecologypt_PT
dc.titleTowards a unified eco-evolutionary framework for fisheries management: Coupling advances in next-generation sequencing with species distribution modellingpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleMarine and Environmental Sciences Centre
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04292%2F2020/PT
oaire.citation.conferencePlaceSwizerlandpt_PT
oaire.citation.endPage9pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleFrontiers in Marine Sciencept_PT
oaire.citation.volume9pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameBaltazar-Soares
person.familyNameAraújo Lima
person.familyNameFranco Silva
person.familyNameGaget
person.givenNameMiguel
person.givenNameAndré Ricardo
person.givenNameGonçalo Jorge
person.givenNameElie
person.identifierU4X7rRYAAAAJ&hl
person.identifier283148
person.identifier.ciencia-id3D1D-4AB0-7388
person.identifier.ciencia-idDD16-FC8C-D1D0
person.identifier.ciencia-idDA15-EB7F-6483
person.identifier.orcid0000-0002-9698-8302
person.identifier.orcid0000-0001-6700-6720
person.identifier.orcid0000-0003-3462-9686
person.identifier.ridC-4931-2019
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication320235b1-4a95-4412-bdd5-c2f544e192c4
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relation.isAuthorOfPublication.latestForDiscovery327ea96b-a59e-4c95-b0c5-54f8ee6a0084
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