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Enregistrement W2994823244

Effects of Bioavailability and Accumulation of Single Metal and Mixture Metal on Toxicity to the Mite, Oppia nitens

2019· dissertation· en· W2994823244 sur OpenAlexaboutno aff
Olukayode Jegede

Notice bibliographique

RevueUniversity Library (University of Saskatchewan) · 2019
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueEnvironmental Toxicology and Ecotoxicology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBioavailabilityToxicityMiteMetalEnvironmental chemistryChemistryToxicologyBiologyPharmacologyEcologyOrganic chemistry
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Canada has some of the largest metal deposits in the world and the Canadian mining industry is one the largest employers of labour in Canada. Consequently, mining and smelting operations in Canada are one of the sources of metal level increase in the environment. Metals pollute the terrestrial environment because of fall-out from the mining industry. Soils are major sinks for metals in the terrestrial environment. It is therefore important that metal risk assessment should clearly reflect the metal contamination in the soils. \nThe main objectives of this thesis were to generate more realistic metal toxicity data using a native Canadian invertebrate species that will help improve metal risk assessment in Canada. Firstly, toxicity of common metals (Cu, Pb, Zn, Co, Ni) found in contaminated sites in Canada was assessed on an oribatid mite, Oppia nitens which is abundant in Canadian soils. The metal toxicities were assessed as singles and as mixtures in five different soils. The metal mixture ratios were fixed such that it reflected ratios of metals found in contaminated sites. The patterns of sensitivity of the mite to metals by soils differed between single metals and metal mixtures. Nickel, which had not been tested with Oppia nitens before, was found to be the most toxic metal to the mite and zinc was less toxic. Concentration addition was protective of 53% of metal mixture toxicity due to antagonistic and concentration addition. Bioavailable metals existed as metals bound to fulvic acid.\nAfter determining the toxicity of the metals in the five soils, the multigenerational effect of one of the metals on soil mites was investigated in the most sensitive soil to single metal contamination. Continuous and pulse zinc exposure effect on O. nitens populations was assessed in three generations of the mites. Using critical-effect levels (EC50s), pulse exposed mites seemed to be tolerant and the continuous exposed mites were sensitive. However, the instantaneous population growth rate showed that both pulse and continuous exposures were more sensitive than their parents. The major finding from this study was that persistence of metals in soils can cause multigenerational adverse effects on continuously exposed mites in the soil. \nThe last chapter of this thesis investigated the direct effect of soil habitat quality as a site-specific feature on organisms and how it influenced their response to metal contamination. For this test, forty-seven (47) soils were ranked according to their habitat qualities from one to three (high to low), using standard soil invertebrate species (Folsomia candida, Enchytraeus crypticus) fitness and plant (Elymus lanceolatus) productivity as metrics to choose habitat qualities. From the ranked 47 soils, eighteen (18) soils comprising six soils making each habitat quality was chosen in a duplicated experiment. The soils were spiked with increasing concentrations of Zn and the Zn toxicokinetics, toxicodynamics, survival and reproduction of mites were assessed. The mites in the soils of high habitat quality were less stressed than mites in the low habitat quality soils despite being exposed to the same amount of bioavailable metals. The key findings from this study were that soil habitat quality has a direct influence on how its inhabitants cope with metal stress. Therefore, habitat qualities of soils can be considered as a site-specific feature in remediation of contaminated sites.

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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,573
Score d'incertitude au seuil0,941

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 technologies0,0000,001
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,008
Tête enseignante GPT0,184
Écart entre enseignants0,176 · 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
Publié2019
Routes d'admission1
Résumé présentoui

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