Notice bibliographique
Résumé
Predicting how gradual changes in abiotic conditions affect ecosystem functioning is a key challenge in ecology and environmental science. For many ecosystems, the response to gradual changes may not be smooth, but rapid and almost irreversible shifts in ecosystem states may occur. Early warning signals for such catastrophic shifts are difficult to obtain. Recent research suggests that so-called self-organized patchiness (regular spatial vegetation patterning) can serve as an indicator for such sudden changes. Self-organized patchiness has been observed in a variety of ecosystems, including peatlands. Most research has focused on linear patterns along the contours of peatland slopes. More recently, aerial photographs from relatively flat ground in Siberia revealed peatlands with so-called maze-patterning, because this type of patchiness somewhat resembles the corridors of a maze. The striking self-organized patchiness has amazed many peatland scientists and has lead to considerable attention for peatland patterning in the literature. Until now, however, the driving mechanisms of peatland patchiness still remain elusive, despite more than a century of research on this phenomenon. This thesis investigates underlying mechanisms that explain self-organized patchiness in peatlands, and whether this patchiness could serve as an indicator for proximity to catastrophic shifts in peatland ecosystem states. A combination of theoretical and empirical approaches is used. We conclude that the potential importance of different driving mechanisms for peatland patterning depends on climatic conditions. Increased evapotranspiration in vegetation patches with high density may be particularly important in peatlands where most water leaves the system through evapotranspiration. Alternatively, in peatlands where water is lost via drainage or overland flow, a positive feedback between the thickness of the upper aerobic peat layer and the rate of peat formation the peat accumulation mechanism may be more important. Global climate models project for most peatland regions an increasing importance of evapotranspiration during the coming century, with the strongest increases being projected for Siberia and Canada. Based on the results in this thesis, we speculate that evapotranspiration may become the main driver of pattern formation in parts of these regions. We also conclude that a shift from an unpatterned state without hummocks and hollows toward a patterned state with hummocks and hollows already comprises a catastrophic shift in ecosystem functioning that is difficult to reverse. This means that a pattern cannot be used as an indicator of proximity to a catastrophic shift, but rather indicates that the shift has already happened. Moreover, the very slow development of peatlands calls for caution when applying equilibrium concepts, which are used in most mathematical models of pattern formation, to peatland dynamics. Investigation of the mechanisms that drive self-organized patchiness in ecosystems is a promising approach to increase our understanding of ecosystem functioning, and the response of ecosystems to changing abiotic conditions. This thesis exemplifies that studies on pattern formation need to include both theoretical and empirical approaches, because the driving mechanisms of self-organized patchiness may change with climatic regions and may therefore be site-specific.
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 | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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 ».