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Enregistrement W7042949060

Report of the Working Group on the Application of Genetics in Fisheries and Mariculture (WGAGFM). 7–9 May 2014 Olhãu, Portugal

2015· article· en· W7042949060 sur OpenAlexaboutno aff

Notice bibliographique

RevueInstitutional Archive of Ifremer (French Research Institute for Exploitation of the Sea) · 2015
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueFusion and Plasma Physics Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMaricultureFisheries managementPopulationScale (ratio)Diversity (politics)Working groupWork (physics)Fish <Actinopterygii>
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The Working Group on the Application of Genetics in Fisheries and Mariculture (WGAGFM) convened in Olhãu, Portugal 7–9 May 2014. Members met to discuss and consider the five Terms of Reference (ToR) decided by the ICES Science Committee. The report contains the main issues discussed and the management recommendations for each of these ToRs. Dorte Bekkevold (Denmark) chaired the meeting, which opened at 09:00 on the 7 May and closed at 13.30 on 9 May. The meeting had 23 participants representing the European Joint Research Centre in Italy and 12 other member nations (Belgium, Canada, Denmark, France, Germany, Iceland, Norway, Portugal, Russian Federation, Spain, Sweden and UK). WGAGFM have established a three-year term for the chair, and it was the final year for the current chair’s term. The members present at the meeting unanimously supported that WG member Professor Gary R. Carvalho be-come the next Chair for WGAGFM. \nMembers discussed the current status and way forward in integrating genomic meth-ods with marine fisheries management. Fisheries biologists and managers have long acknowledged the importance of intraspecific diversity, as described for most ex-ploited species, though management remains mostly based at the scale of large sea basins with fixed administrative boundaries and rectangular management areas. The latter geographically defined framework typically fails to match the biological struc-ture of populations. It follows that in order to move towards sustainable fisheries, a central challenge is to incorporate spatial biological diversity into contemporary man-agement schemes Moreover, population connectivity and dynamics must be reliably monitored to support management strategy implementation. Genomic methods pro-vide one important tool to achieve this goal and members discussed cases incorporat-ing such approaches with other relevant data in diverse fisheries management scenarios, showing that evolutionary thinking can add valuable information to the suc-cessful implementation of strategies to promote profitable and sustainable fisheries within an ecosystem context .Members found that the examples demonstrate the meth-ods’ relevance for a suite of management questions and recommend that ICES SCICOM and ACOM push for more standardized use of the methods as well as initiate that application of genetic methods are included in its training courses.\nWGAGFM received an advice request from OSPAR (4/2014) on “Interactions be-tween wild and captive fish stocks”. WGAGFM contributed information on genetic effects and potential management solutions to mitigate adverse impact. Several studies have demonstrated that the gene pools of wild populations change when hatchery produced farm fish escape (or are released) at large-scales. Several studies also report that intro-gression by escaped farm fish can incur a fitness cost to wild populations, causing in-creasing concern for the continuing health and viability of wild populations and awareness about conserving native fish gene pools. Knowledge is mainly based on salmonids fish but should be transferrable to fully marine organisms, making aquacul-ture escapees a general concern. Molecular quantification has proved valuable for demonstrating introgression by farm fish. However, WGAGFM reviewed studies and found that in many cases, the introgression process is complex, e.g. with respect to escape rates and genetic make-up of escapees, and impacts can therefore be difficult to assess and predict. Members concluded that in order to develop and implement relia-ble management strategies and advice, locally and internationally, it is of importance to consider on a case-by-case basis the different options for the analysis of genetic data to quantify level of introgression.\nFollowing on from work initiated in 2013, members discussed the application of ge-netic methods in shellfish. Invertebrates such as shellfish of interest in an aquaculture context have very different life histories compared to finfish and these characteristics mean that the transfer of technology and selection approaches from the finfish industry to the shellfish one is not always simple or even possible. However, this emphatically does not mean that the general principle of identifying adaptive markers and utilizing them in the scenarios outlined above cannot result in benefits to both industry and wild populations. Recent developments in genetic screening techniques (e.g. Next-Genera-tion Sequencing and genome sequencing) promise even greater power to identify markers linked to traits of interest and the incorporation of such techniques should be encouraged in the shellfish aquaculture context.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,010
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,073
Score d'incertitude au seuil0,244

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0100,007
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0020,001
Communication savante0,0050,002
Science ouverte0,0020,005
Intégrité de la recherche0,0030,003
Charge utile insuffisante (le modèle a refusé de juger)0,0730,036

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,093
Tête enseignante GPT0,317
Écart entre enseignants0,224 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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