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Enregistrement W6948545094 · doi:10.5281/zenodo.10851994

Overview And Progress Of Consortium Research Related To The Biology, Ecology And Aquaculture Of Rabbitfish

2022· article· en· W6948545094 sur OpenAlexaff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueGrowth Hormone and Insulin-like Growth Factors
Établissements canadiensDalhousie University
Organismes subventionnairesnon disponible
Mots-clésFishingSeagrassHabitatCoral reefMarine habitatsContext (archaeology)Marine conservationPopulation

Résumé

récupéré en direct d'OpenAlex

BackgroundCoastal habitats support global fisheries by ensuring the survival of juvenile fishes.These habitats constitute one of the fishing areas targeted by small-scale fishermenin the least developed countries, including Madagascar. The accessibility of thesehabitats at low tides makes it an ideal fishing area for mosquito seine nets asobserved for instance in SW Madagascar and beach seining in Kenya. However, thispractice negatively impacts fisheries production due to catches of high numbers ofjuveniles, in Madagascar and Kenya mostly composed of shoemaker spinefootrabbitfish (Siganus sutor). Despite Malagasy laws that forbid the deployment ofmosquito seine nets, fishermen continue with their use. In Kenya, the beach seineshave been outlawed but enforcement remains a challenge. This context highlightsthe need for management measures and alternative sources of income for asustainable use of marine resources and for improving the fishermen livelihood. Theongoing consortium research entitled “Fish juvenile recruitment in coastal habitats ofwestern Indian Ocean” was funded by MASMA program administered by WIOMSA.It is an interdisciplinary research program intending to understand recruitmentpatterns of shoemaker spinefoot rabbitfish (Siganus sutor) in coastal habitats ofKenya and Madagascar. It explores evidence-based solutions for improving thewelfare of coastal communities and sustainable use of marine resources.MethodResearch activities were divided into four work packages. In WP1, Siganus sutorrecruitment patterns in coastal habitats were targeted to identify the nursery groundand recruitment periods. It is based on juvenile fish sampling at four coastal habitats(mangroves, seagrass meadows, intermediate areas and seagrass associated withthe coral reef) in Madagascar during twelve months. In WP2, sampling for theanalysis of the population connectivity of S. sutor for detecting the sources ofjuveniles in the coastal habitats at five sites along the western coast of Madagascarwas completed. In WP3, ecological models for predicting the arrival of newly settledS. sutor will be based on historical and newly collected data (WP1) using the randomforests algorithm. Predictors are composed of remotely sensed oceanic conditionsand a post-larval supply index calculated from post-larval sampling in the coastalhabitats using light-traps. Like juvenile sampling, post-larval sampling was performedthree nights per month which will cover all the juvenile sampling periods. In WP4,fish feeding behavior is studied and experiments on capture-based juvenile fishgrow-out are ongoing at the Belaza aquaculture facilities (Toliara, Madagascar).Eight fish grow-out treatments focusing on three stocking densities, three fish diets,and pond dimensions are being tested.ResultsIn WP1, about 5,720 juvenile individuals were obtained from 120 juvenile fishsamples. The standard length of each of these individuals were measured foranalyzing the spatial distribution of S. sutor. The nursery ground and recruitmentseasons for S. sutor emerged from our research. The findings will be presentedorally by PhD student Helga Berjulie Ravelohasina during the symposium. Inaddition, about 360 epifaunal community samples were obtained between July 2021and April 2022. The spatial distribution of abundance, diversity and richness ofepifauna associated with seagrass will be presented in a poster by MSc studentMory Justino. In WP2, at each location, 45 individuals were sampled, for a total of225 adults for Madagascar and 180 from Kenya. Genotyping is in progress. In WP3,monitoring of the newly settled fish, in parallel with post-larval sampling, is inprogress and should be completed by June 2022. In meantime, the extraction ofremotely sensed oceanic conditions covering the sampling periods is beingprocessed with R programming for the period. In WP4, preliminary results on fishgrow-out identified the best fish diet and the most optimal stocking density at thesmallest size (about 2 cm of standard length). More details related to these findingswill be presented in a poster by master student Nandrianina Maminantenaina. Inaddition, the gut content and stage isotopes of three ontogenetic stages (i.e. post-larvae, juvenile, and adult) of S. sutor were analysed the natural trophodynamics.The findings are based on 1160 gut contents and muscle tissue samples collectedduring the warm (October 2021 to February 2022) and cool season (May to August2022).ConclusionThe potential nursery areas and the main recruitment seasons of Siganus sutor wereidentified. The oral presentation entitled “The potential nursery areas and recruitmentseason of S. sutor in Madagascar” by Helga Berjulie Ravelohasina will providefurther details of our findings. The variability of food availability related to epifaunaconcentration will be known in the poster on Mory Justino. The most optimal fish dietas well as the optimal stocking density will be presented in a separate poster entitled“Density and fish diet effect on rabbitfish growth in controlled systems” presented byNandrianina Maminantenaina.

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)0,021
score de la tête « metaresearch » (Gemma)0,018
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,021
Score d'incertitude au seuil0,113

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0210,018
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0130,017
Études des sciences et des technologies0,0010,002
Communication savante0,0050,005
Science ouverte0,0020,005
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0120,003

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 Opus0,049
Tête enseignante GPT0,307
Écart entre enseignants0,258 · 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'étudeRevue systématique
Domainenon disponible
GenreSynthèse

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
Publié2022
Routes d'admission1
Résumé présentoui

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