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Enregistrement W7029065567

Investigating the role of Vibrio aestuarianus in summer mortality of farmed Crassostrea gigas in Baynes Sound, British Columbia

2021· dissertation· en· W7029065567 sur OpenAlexaboutno aff

Notice bibliographique

RevueUVic’s Research and Learning Repository (University of Victoria) · 2021
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueMarine Bivalve and Aquaculture Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCrassostreaPacific oysterAquacultureOysterShellfishAbundance (ecology)Vibrio
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Marine aquaculture is already vital to global food security and will continue to become more important in the coming years. Crassostrea gigas (Pacific oysters) is the primary oyster species cultivated worldwide. The FAO and IPCC predict that climate change will create uncertainty and challenges for marine aquaculture. Baynes Sound, British Columbia, is a productive region for aquaculture, producing >50% of British Columbia’s total annual bivalve production by live weight and value. Major summer mortality events have been documented in farmed Crassostrea gigas globally since the 1950’s. These events are believed to be caused by a multiplicity of factors including changes induced by anthropogenic climate change. One of the major contributors to summer mortality is the proliferation of Vibrio bacteria, specifically Vibrio aestuarianus, which has been shown to increase in abundance and virulence when seawater temperatures rise. Despite this connection and the economic importance of oyster farming in the region, little is known about the presence of V. aestuarianus in Baynes Sound. Our 17-month study sampled 7 sites in Baynes Sound on 33 occasions from May 2019 to September 2020. We found a positive correlation between seawater temperature and total Vibrio detected in water samples in Baynes Sound, an association that was stronger when the overall temperature regime was warmer. We found no significant correlation between any of the bacterial assays tested and salinity, pH, or Ωarag saturation. We also did not identify a geographic pattern to bacterial abundance or virulence amongst test C. gigas in the field. Understanding that flagellates are the predominant type of microalgae present in Baynes Sound when summer mortality events occur, in lab trials, we found that incorporating V. aestuarianus into marine aggregates with flagellate microalgae caused higher mortality than aggregates with diatoms or planktonic V. aestuarianus. These results were not statistically significant but led us to look at how exposure to husbandry stress pre and post inoculation with V. aestuarianus incorporated into marine aggregates affects mortality. We found that stress was a significant driver of mortality, particularly when administered 24h post inoculation, suggesting that farmers should avoid sorting or tumbling their oysters in the summer, and particularly immediately after a marine heatwave. Oysters lack adaptive immune systems and are grown in an open ocean environment where it is not possible to eliminate their exposure to pathogens. These factors make it impossible to use vaccines or antibacterial disinfectants to combat diseases. Therefore, breeding genetic resistance to V. aestuarianus may be the most effective way to fight summer mortality. Creating a repeatable and accurate protocol for inoculating oysters with marine bacteria is key to accurate heritability measurements and the estimation of breeding values of different families. Key factors include controlling for dose per animal, laboratory efficiency, and inoculation via a mechanism that mimics real-world infection and does not bypass the animal’s immune defenses. We designed a protocol which controls for these factors, separating each animal into individual containers and adding a controlled dose of planktonic bacteria to each. Previously used methods of injection or using an infected “donor” animal in a group tank do not control for dose or bypass parts of the oysters’ natural immune system, potentially creating inaccuracies in survival data generated with these methods. After designing this protocol, we tested 32 full-sib families and estimated the heritability of survival to V. aestuarianus on the observed and underlying liability scales to be 0.095 (SE = 0.043), and 0.15 (SE = 0.068) respectively. We also found a strong negative correlation between oyster size and survival, with a gram of additional weight creating a 73% increase in the risk of death. Fast growth and large size are two traits which have been explicitly bred into C. gigas stock. Our work suggests that breeding a slower-growing, smaller animal may reduce summer mortality.

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)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,092
Score d'incertitude au seuil0,186

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,019
Tête enseignante GPT0,261
Écart entre enseignants0,242 · 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'étudeObservationnel
Domainenon disponible
GenreEmpirique

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
Publié2021
Routes d'admission1
Résumé présentoui

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