Development of soils for revegetation in northern diamond mines
Notice bibliographique
Résumé
Mining in the Canadian north has increased since diamonds were discovered in the 1990s. The large physical disturbances and large amounts of waste from diamond mining, coupled with inherent challenges in northern environments due to the harsh climate, make land reclamation particularly challenging. Building suitable anthroposols, human made or altered soils, is the first step for reclamation and ecosystem development as finding a source of soil in remote northern sites is not possible. Small scale field experiments at a diamond mine in northern Canada and greenhouse experiments using diamond mine materials assessed effectiveness of substrate and amendment combinations to build anthroposols, the role of micro topographic variability and use of short term erosion control methods to develop reclamation strategies. Amendment and substrate combinations under water limited and non-limited conditions using various amendment rates were assessed in greenhouse experiments to determine effects on vegetation and water retention. Substrates were collected from Diavik Diamond Mine (crushed rock, lakebed sediment, processed kimberlite, combinations). Amendments were collected at Diavik or purchased in Edmonton (biochar, Black Earth, fertilizer, hydrogel, peat, sewage, soil, combinations). Experiments ran from 8 to 12 weeks. Two field experiments explored vegetation response on three mine wastes (crushed rock, lakebed sediment, processed kimberlite) with organic amendments (soil, sewage), micro topography (mounds, boulders, depressions, furrows, flats) and erosion control methods (Soil Lynx, erosion control blankets, treated jute, jute with Soil Lynx) over four years. In all experiments, material properties were assessed and vegetation establishment and growth were monitored. In greenhouse experiments with non-limited water availability, vegetation response was greatest in crushed rock and lowest in processed kimberlite. Under water limited conditions, crushed rock and processed kimberlite were more effective than lakebed sediment. Processed kimberlite had the greatest water retention relative to other substrates. Organic amendments had limited effect on water retention; hydrogel increased water retention in crushed rock and processed kimberlite. In all experiments, sewage at any rate resulted in the greatest above ground biomass and plant height. Soil and peat were more effective at high rates, although plant density increased under water available conditions relative to sewage. Competition of large plants in sewage likely reduced density. Biochar, Black Earth and hydrogel did not improve vegetation establishment or growth due to lack of nutrients or substrate improvement. Fertilizer had a limited effect, only improving plant growth with specific amendment and substrate combinations where nutrients were lacking. In field experiments, crushed rock was the most successful substrate and processed kimberlite the least. Crushed rock’s success was due to its rough surface creating suitable micro sites for seed germination and plant establishment and growth relative to smoother, sandy processed kimberlite. Sewage resulted in greater cover and species richness with taller plants, as its high nutrient content provided resources limiting in unamended or soil amended treatments. Micro topography had a limited effect in crushed rock due to its natural rough surface. In processed kimberlite, and to a lesser extent lakebed sediment, cover, height and number of plants and species were greater when micro topography included low areas which facilitated seed collection and safe micro site creation. Erosion control materials had a limited effect; jute and erosion control blankets provided some benefit in lakebed sediment and processed kimberlite. This research has contributed significantly to the knowledge base for building anthroposols, with a focus on northern diamond mines, assisting in developing strategies to select substrates, amendments, micro topography and erosion control methods. Results can be expanded to similar disturbances in the north and other environments due to the large number of comparisons assessed and the focus on properties of materials. Major next steps include approaching reclamation strategies at an industrial scale.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».