Impact of land use activities on sediment-associated contaminants; Quesnel River Basin, British Columbia.
Notice bibliographique
Résumé
The impact of various land use activities (forestry, mining, and agriculture) on the quality of fine-grained sediment (<63 μm) was investigated in the Quesnel River Basin (QRB) (approx. 12,000 km²) in British Columbia, Canada. Samples of fine-grained sediment were collected monthly during the snow-free season in 2008 using time-integrated samplers at sites representative of forestry, mining, and agricultural activities in the basin. Samples were also collected from replicate control sites that had undergone limited or no disturbance in recent years, and also from the main stem of the Quesnel River. Generally, metal and nutrient concentrations for 'impacted' sites were greater than for control sites. Concentrations of As (mining sites), Cu (forestry sites) and Zn (forestry sites) were close to or exceeded upper Sediment Quality Guideline (SQG) thresholds, while Se concentrations for mining sites were elevated and within the range cited for contaminated environments. Phosphorus values were generally <1000 μm g⁻¹ for all land use activities and below available SQGs. Values for individual samples were, however, greater than upper SQG levels, such as 22.7 μm g⁻¹ (As for mining), 5.0 μm g⁻¹ (Se for forestry) and 2192 μm g⁻¹ (P for forestry). Results suggest that metal mining and forest harvesting are having a greater influence on the concentration of sediment-associated metals and nutrients in the Quesnel basin, than agricultural activities. Temporal and spatial differences in the metal and P content of fine suspended sediment within the QRB during the 2008 field season were analyzed using rank sum tests in comparison to discharge (Q) and precipitation (PPT) values. Temporal results suggest the overall mining signature was often a function of changes in activity from point sources, while the diffuse sources, forestry and agriculture, were influenced by variations in transport conditions (e.g. PPT and Q). Spatial variation was greatest between mining and control geochemical concentrations. Forestry and agriculture differed for select elements, but played a lesser role than mining. To further characterize the roles of land uses a sediment fingerprinting method was used, involving stepwise discriminant function analysis (DFA). This resulted in a composite signature capable of differentiating correctly 100% of the source geochemical contributions from each land use type. The composite signature was used to determine the basin-scale geochemical signature using a multivariate mixing model. This determined that agriculture was the highest overall contributor of the sediment signature at the outlet in Quesnel. Additionally, the control influence was strongest earlier in the sampling campaign while mining contributed most in the latter sampling periods. This project contributes to the broader science, and future research in the basin, through a study of multiple land uses in a large basin; a different application of the sediment fingerprinting approach; and a contemporary flume-based sampler evaluation.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».