Landscape analysis & boundary detection of bog peatlands’ transition to mineral land: The laggs of the eastern New Brunswick Lowlands, Canada
Notice bibliographique
Résumé
The wet zone – the lagg – that tends to form at the edge of ombrotrophic peatlands is believed to play an important role in promoting and maintaining the health of bog systems. The lagg is well-recognized by peatland scientists, yet empirical knowledge is surprisingly limited, and most of the characteristics associated with this ecotone come from qualitative observations. Understanding the role played by the lagg, and the potential impact its disturbance might have on the integrity of a raised bog system, is valuable for sustainable land management and peatland restoration science alike. This thesis explores and documents the basic ecohydrological characteristics of the lagg in the context of the neighbouring natural landscapes, and discusses the spatial properties of various types of laggs by exploring airborne LiDAR datasets to detect and position the ecotone. The specific objectives are 1) to describe the form and abiotic controls of the laggs and margins of bog peatlands, 2) to propose a conceptual model in cross-section of the “bog-lagg-mineral land” transition, 3) to explore the potential of data derived from aerial LiDAR (Light Detection And Ranging) to detect and locate laggs and lagg boundaries, and 4) to consider the spatial distribution of laggs around raised bog peatlands. Data were collected along 10 transects located within 6 relatively undisturbed bogs of the New Brunswick eastern lowlands, Canada. Each transect consisted of 4-6 wells, straddling the ombrotrophic bog and the adjacent mineral land, and of 3 nested piezometers in the center of each lagg. These instruments were used to monitor the position of the water table, to measure hydraulic gradient, hydraulic conductivity, and for water sampling. Dissimilarity analysis (edge-detection, split moving window) and similarity analysis (cluster, k-means) were used to test the delineation capacity of five variables derived from the LiDAR dataset; ground elevation (topography), vegetation height, topographic wetness index, and spatial frequency of both vegetation and ground LiDAR returns. The major abiotic control of the lagg appears to be topography. Two geomorphological categories were identified; confined and unconfined. The importance of topography is through the affect it has on water flow rates and direction, which in turn affect water chemistry, and most likely nutrient transport and availability, hence vegetation characteristics. Dissimilarity analysis of the five variables derived from LiDAR data revealed that some indicators were better at predicting the bog-lagg boundary (e.g. vegetation height), and others at finding the lagg-mineral land boundary (e.g. topography). In contrast, the similarity analysis gave more decisive influence to the topographic wetness index. When the lagg was confined between the bog and the adjacent upland, it took a linear form, parallel to the peatland’s edge. However, when the adjacent mineral land was flat or even sloping away, the lagg spatial distribution was discontinuous and intermittent around the bog. Our results confirms that laggs can take many forms, while suggesting two broad geomorphological categories from which they can more easily be studied and understood and highlight the potential offered by LiDAR technology in predicting their likely location around a raised bog. The results and conclusion from this research further our understanding of the goals to be achieved for ecological restoration, and favor sustainable management inclusive of the margins or bog peatlands.
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 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 ».