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Enregistrement W7030088126

Microplastics in coastal marine habitats and food webs

2021· dissertation· en· W7030088126 sur OpenAlexaboutno aff

Notice bibliographique

RevueUVic’s Research and Learning Repository (University of Victoria) · 2021
Typedissertation
Langueen
DomaineEngineering
ThématiqueRailway Engineering and Dynamics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMicroplasticsMarine habitatsSampling (signal processing)Marine debrisHabitatSeawaterEcotoxicologyShellfishMarine speciesFood chain
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Microplastic particles (MPs) are widely distributed in aquatic environments and present a potential risk to marine life. This thesis considers several issues relating to methodologies for sampling and analyzing MPs and the sources and fate of these particles in the marine environment, wild and farmed shellfish, and food webs of southern coastal British Columbia, Canada. 
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\nChapter 1 introduces MPs as a contaminant, methodologies for studying them, and reviews what is known about their source, fates, and ecotoxicology in marine environments. Chapter 1 also outlines the goals of this thesis.
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\nChapter 2 compares the potential MP concentration estimates provided by two different seawater sampling methods. Jar samples filtered to 8-µm yielded MP concentrations averaging approximately 8.5 times higher than bucket samples filtered to 63 µm, per L of water (at the site level), driven largely by differences in the number of microfibres. An analysis of MP concentrations and mesh sizes reported in the literature suggests that using a 300–350-µm mesh may underestimate total MP concentrations by one to four orders of magnitude compared with samples filtered through much smaller mesh sizes (e.g., less than 100 µm), and despite the effect of sample volume. Particles less than 300 µm in diameter make up a large component of MPs commonly found in fish and invertebrates. As such, common sampling practices fail to adequately measure a biologically relevant class of MPs, thereby undermining the ability to quantify ecological risk. 
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\nChapter 3 determines the influence of shellfish aquaculture activity, and its use of plastic equipment, on MPs in bivalves and their environment by comparing MP concentrations in Manila clams (Venerupis philippinarum) and Pacific oysters (Crassostrea gigas) grown on commercial shellfish beaches with those grown on non-aquaculture beaches from six areas. MP concentrations in water and sediment were also determined in four of the areas. MP concentrations did not differ between shellfish aquaculture and non-aquaculture sites for either bivalve species or for sediment and water samples. Beach sediment type had a minor effect, with more gravelly or sandier beaches associated with higher MP concentrations in oysters or clams, respectively. Oysters on sites using many synthetic anti-predator nets had more MPs than those on sites without any plastic, but analysis of particles using Fourier-transform infrared spectroscopy suggested a predominance of textile fibres including nylon and polyester, which are not typically used in shellfish aquaculture. 
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\nChapter 4 uses stable isotope food web analysis and hierarchical Bayesian generalized linear mixed models to explore whether bioaccumulation and biomagnification are occurring in coastal marine food webs at three locations. Bioaccumulation was higher for smaller-bodied suspension feeding animals such as bivalves. However, biomagnification was not occurring in animal digestive tracts, and trophic dilution was demonstrated in fish livers. Trophic transfer was shown to occur between prey and predator for rockfish, but higher concentrations in full stomachs compared with empty ones suggested rapid excretion of ingested MPs.
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\nChapter 5 supplies some general conclusions on the status of MPs in the British Columbian environment, as well as risks to seafood consumers. It also explores future work that will be needed to understand the complex ecotoxicology of MPs.

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 candidatesMéta-épidémiologie (sens strict)
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 enseignants0,196
Score d'incertitude au seuil1,000

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 recherche0,0000,001
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 Opus0,009
Tête enseignante GPT0,218
Écart entre enseignants0,209 · 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.

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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