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Enregistrement W6959583916 · doi:10.7939/r3-3g6r-3m87

Understanding Yellowmouth: Reeling in the Root of Antimicrobial Use in British Columbia Salmonid Production

2024· dissertation· en· W6959583916 sur OpenAlexaboutno aff

Notice bibliographique

RevueUniversity of Alberta Library · 2024
Typedissertation
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueBotanical Research and Chemistry
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAquacultureSustainabilityBiosecurityAgricultureStockingPopulationOutbreakFish farmingProduction (economics)

Résumé

récupéré en direct d'OpenAlex

Food insecurity is a pressing global issue that has been further exacerbated by challenges such as a burgeoning global population and unforeseen crises like the COVID-19 pandemic. Salmonid aquaculture could mitigate these challenges by contributing to sustainable food systems. In British Columbia, Canada, the salmonid aquaculture industry is facing critical sustainability and economic challenges due to bacterial diseases, with yellowmouth disease caused by Tenacibaculum maritimum posing substantial concerns. This disease necessitates antimicrobial use (AMU), thereby increasing the risk of antimicrobial resistance (AMR), a problem that spans the One Health sectors of environmental, human, and animal health. The current research delves into understanding and managing yellowmouth disease in salmonid farming operations to reduce AMU and mitigate AMR risks. By synthesizing existing research through a comprehensive scoping review and analyzing extensive data from an Atlantic salmon producer in British Columbia, this thesis aims to identify the management, production, and environmental factors that contribute to the incidence of yellowmouth disease. Understanding these factors is crucial for developing targeted interventions that can reduce disease. Chapter 2 of the thesis is a scoping review aimed at synthesizing the available literature on factors associated with T. maritimum infection in both farmed and wild salmonids. The review highlighted the multifactorial nature of the disease, emphasizing the interplay of host biology, environmental factors, and pathogen characteristics. Key findings included the importance of considering fish age and size at sea entry, stocking density, minimizing physical abrasions, and reducing stress-inducing conditions to manage and prevent outbreaks effectively. The chapter also identified an important gap in previous research regarding multivariable analyses of T. maritimum infections, underscoring a need for comprehensive studies that incorporate multiple interacting factors. Chapter 3 examined data from a British Columbia Atlantic salmon producer (2015-2021) using random forest models and multivariable linear regression to identify factors associated with antimicrobial use (AMU), a proxy for yellowmouth disease incidence. Key findings included a significant protective effect of higher salinity levels, reducing AMU by 0.09 mg/kg biomass (p < 0.05). Temperature also acted as a confounding variable. The findings further underscored the importance of broodstock and days between weights of 100-500 grams (DBW) after placement at sea on AMU. Specific interactions between broodstock types and DBW showed differential impacts on AMU, indicating that genetic factors and growth rates are critical in disease management. There were seasonal and year-to-year trends that differed in magnitude and shape depending on the area of placement. Antimicrobial use was generally the greatest when fish were placed in the middle of the year (week 20), falling when fish were placed towards the end of the year, but these trends depended on the area of production. Additionally, site-level clustering was significant, with an intraclass correlation coefficient (ICC) of 0.30 (p < 0.001), emphasizing the need for site-specific management. The study also highlighted interactions between area and temporal variables, indicating the importance of regional and seasonal considerations in disease management strategies. The findings of this thesis provide valuable insights into the factors influencing antimicrobial use (AMU) in the Atlantic salmon aquaculture industry in BC. As the industry faces increasing public pressure to adopt sustainable practices, understanding the specific roles of environmental conditions, broodstock genetics, growth rates (DBW), and site-specific management is essential. Continued research is necessary, and the complexity of our findings highlight the necessity for targeted approaches to meet public demand for responsible aquaculture practices. Integrating the findings in this thesis and future research will support the health of both aquaculture systems and the broader environmental context in which they operate. Preserving and improving aquatic health through informed management practices in BC finfish farms is crucial for reducing antimicrobial use (AMU) and slowing the development of antimicrobial resistance (AMR). This study embodies the One Health approach by exploring how management practices and environmental factors affect AMU in aquaculture. This highlights the idea that the management of Tenacibaculum maritimum impacts not only salmon health but also the broader marine ecosystem and human health by potentially contributing to the development of AMR, emphasizing the interconnected impact on animal, human, and environmental health.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,750
Score d'incertitude au seuil0,919

Scores Codex et Gemma par catégorie

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

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 Opus0,033
Tête enseignante GPT0,195
Écart entre enseignants0,163 · 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 tête enseignante, 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
Publié2024
Routes d'admission1
Résumé présentoui

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