Natural patterns and land use impacts on lacustrine sedimentation in Northwestern British Columbia
Notice bibliographique
Résumé
It has long been established that land use disturbances can induce elevated sediment yields in affected drainage basins. This effect is well documented with respect to forestry activities in the Pacific Northwest. A major problem encountered in studying disturbed sediment yields in the Pacific Northwest is putting the forestry impacts in context with the high degree of spatial and temporal variability in the sedimentary system. The analysis of lake sediments is an attractive method for assessing land use impacts on sediment yield at the basin scale, since a long term sedimentary record can be established that reflects all of the integrated upstream watershed effects. In this study, lake sediment records have been utilized to investigate historical sedimentation patterns in Northwestern British Columbia. Core chronologies and sedimentation rates were derived from ²¹³Pb dating techniques. Study catchments have been selected that span a range of spatial scales, physiographic regions, and land use histories, in order to permit a comprehensive regional assessment of lake catchment sediment yield. Study objectives include the assessment of the natural patterns of lake sedimentation, determining the relative impact of forestry on lake sedimentation in context with the naturally observed variability, and the confirmation of lake coring and associated analysis techniques as appropriate methods of assessing land use disturbances. Specific sediment yield, or sediment yield per unit of contributing basin area, is used as an index of primary subareal denudation of the lake catchments. Specific yield in Northwestern British Columbia spans two orders of magnitude, from 0.0015 Mg/km²/day in the Interior Plateau to 0.1434 Mg/km²/day in the North Coast. The higher rates of sediment yield in the North Coast reflects the higher erosion rates, greater transport capacity, and lower storage potential in that region. Specific sediment yield also increases with increasing drainage area in the North Coast. This trend is likely associated with the dominance 6f secondary remobilization of Quaternary sediments from stream banks and valley bottom areas. In the flat-lying plateau and major valley areas specific sediment yield decreases with increasing drainage area, thus fitting the conventional model of sediment delivery where storage efficiency increases downstream. In the Hazelton and Skeena Mountains there is no significant relation between specific yield and drainage area. There is a clear trend towards increasing lacustrine sedimentation rates irrespective of land use change in the lake catchments. This natural trend is a major confounding factor in disentangling land use impacts on sedimentation patterns. This trend may be related to precipitation increases undergone in the whole study area over the last few decades. Natural disturbances, such as mass wasting and other geomorphic events, are important processes of sediment transfer in headwater lake catchments, although specific processes influencing lacustrine sediment yield were undetermined. Superimposed on. all of the observed natural variability are some qualitative and semi-quantitative land use effects on sediment yield. Land use impacts could only be partially separated from natural fluctuations, however, a clear land use signature, in the form of increased sedimentation rates, was observed in some of the study lakes. Most significant recent increases in sedimentation rates have occurred in the Nechako Plateau, Nass Basin and Major Valleys lakes which have been exposed to extensive forestry activities. Lake catchments which have been subject to multiple land use activities also showed a clear land use impact in the sedimentary signatures. Results indicate that lake sediment-based research can be an effective and useful approach to assess the long term impacts of forest harvesting and other land use disturbances on lake catchment yield. Inherent limitations of the lake sediment-based methodology and recommendations for future work are reviewed.
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 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 | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 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) | 0,002 | 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 ».