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Testing technosols over an ultramafic gradient for rehabilitation of diamond mine wastes in a subarctic region

2017· dissertation· en· W2735912252 sur OpenAlexfundno aff
Andrea Hanson

Notice bibliographique

RevueLu Zone Ul (Laurentian University) · 2017
Typedissertation
Langueen
DomaineEngineering
ThématiqueMineral Processing and Grinding
Établissements canadiensnon disponible
Organismes subventionnairesNatural Sciences and Engineering Research Council of Canada
Mots-clésSubarctic climateDiamondUltramafic rockMining engineeringGeologyGeochemistryEarth scienceEnvironmental scienceMetallurgyMaterials scienceOceanography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Subarctic regions are recognized as one of the largest remaining pristine landscapes on earth, but are currently experiencing progressive degradation due to human activity. Mining and site rehabilitation in northern regions can be challenging largely due to the remote location of these developments. Rehabilitation is often restricted to using local mine waste materials to construct technosols. This study focused on how mines in northern regions, specifically the isolated De Beers Victor Diamond Mine, can use local mineral mine waste material to manufacture successful soil covers. Specifically, our research focused on examining the performance and success of technosols across a gradient increasing in serpentine characteristics. The objectives of the study were to, (1) determine how technosols increasing in serpentine characteristics influence vegetation establishment and microbial activity, (2) determine how the quantity of peat influences vegetation establishment and microbial activity, and (3) determine how early physical and chemical characteristics, and early plant colonization on our technosols compare to a local natural environment undergoing primary succession. We constructed a factorial experiment on two areas of mine waste at the Victor Mine, the waste rock dumpsite, and a processed kimberlite storage facility. Three test blocks were constructed on each site comprising a total of 48 5 m x 5 m experimental plots with four mineral substrate mixtures, and two levels of peat application. Mixtures consisted of various combinations of coarse and fine processed kimberlite, a silty loam marine overburden, and 20% or 40% peat, creating a gradient with ultramafic, serpentine characteristics. Each plot was fertilized at a rate of 12.5 g m-2 (NPK 8-32-16), inoculated with a microbial inoculation ‘tea’ mixture, and seeded with a variety of native vegetation. Various early physical,
\niv
\nchemical and biological characteristics were examined, including early plant colonization and microbial activity. To measure microbial activity, a 7-day aerobic soil incubation experiment was preformed in growth chambers, with and without the addition of glucose, where CO2 respiration rate was the only parameter examined. The results indicated that mixtures increasing in serpentine characteristics resulted in decreased vegetation establishment and microbial activity in the short-term, while the mixtures that were non-serpentine (100% overburden-peat) were the most successful for vegetation establishment and potentially short-term microbial activity. However, most differences between our mixtures were minor. Differences in quantity of peat were minor between our experimental mixtures, causing them to have no influence on the vegetation establishment between our mixtures, and only minor differences in microbial activity between our mixtures. Our technosols shared similar physical and chemical aspects with the early successional Attawapiskat River floodplain environment, and also shared similarities with a peat-overburden mixture currently being used to rehabilitate a stockpile at the Victor Mine. These early similarities could show their potential for success during mine rehabilitation. Our research provides insight into challenges associated with rehabilitation of subarctic environments and, in general, mine waste substrates. This research will provide the De Beers Victor Mine with suggestions for rehabilitation upon closure, and will provide them with information on challenges they may face if incorporating processed kimberlite into technosols.

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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,275
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
Bibliométrie0,0010,000
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 Opus0,013
Tête enseignante GPT0,220
Écart entre enseignants0,207 · 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

Citations1
Publié2017
Routes d'admission1
Résumé présentoui

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