Notice bibliographique
Résumé
Fire is the dominant disturbance that drives ecosystem structure and function in the boreal forest of North America (Weber and Flannigan, 1997). Fire frequency varies widely across different regions of the boreal forest, but the interval between fires is generally long enough for trees to re-establish and recover to mature stands before the stand burns again (Heinselman, 1981; Payette, 1992). In the western boreal forest of North America, historic fire-return intervals have been estimated as typically 80–120 years between fires (Johnson, 1992). Tree establishment occurs most rapidly in the first years following fire, when the availability of viable seed and nutrients is at its highest (Johnson and Fryer, 1989; Johnstone et al., 2004). In a typical fire cycle of one to two centuries, the individuals that germinate in the first few years following a fire are the same individuals that reach reproductive maturity and are burned in the next fire, continuing the cycle of post-fire self-replacement. Boreal tree species demonstrate a variety of adaptations to fire, including serotinous cones (that require heat for seed release) maintained in aerial seed banks (Pinus spp., Picea mariana) and vegetative re-sprouting from roots and stumps following fire (Betula spp., Populus spp.; Li, 2000). In the latitudinal tree line (or forest-tundra ecotone) of the boreal forest, the growing conditions for trees are suboptimal. Because of the underlying permafrost, the soils of this region are relatively cold and wet and thus have slow nutrient turnover rates. Black spruce (Picea mariana), a dominant boreal conifer, exhibits slow growth under these conditions, taking several decades to reach reproductive maturity. However, historical fire cycles allow for black spruce to accumulate enough viable seed for self-replacement after fire. Many regions of the circumpolar North have undergone an increase in temperature, particularly in the past four decades (Chapin et al., 2005). The northern regions of Yukon and Alaska have experienced a 2 C increase in summer temperatures since the 1960s (Chapin et al., 2005). In the boreal forest, fires are expected to occur more often as the climate warms (Stocks et al., 1998; Flannigan et al., 2005; Soja et al., 2007), and increased fire activity is already being noted in some parts of the region (Gillett et al., 2004; Kasischke and Turetsky, 2006). Because of the long period black spruce require to become reproductively mature, an increase in fire activity may interrupt the cycle of post-fire self-replacement for this dominant boreal conifer. This interruption could initiate a change in the structure and function of these northern ecosystems that will have important implications for the global carbon cycle because it alters patterns of carbon accumulation and storage (Grace et al., 2002; Bond-Lamberty et al., 2004). The long-term, landscape-level consequences of altering the fire return interval in the tree-line forest are unknown. On the decadal scale, shifts from coniferous to deciduous dominance after high-severity or frequent fire have been documented in tree-line and interior northern boreal forests (Landhausser and Wein, 1993; Johnstone and Chapin, 2006). The failure of coniferous species following fire is thought to occur because of reduced availability of viable seed (Landhausser and Wein, 1993; Lloyd et al., 2002; Johnstone and Chapin, 2006). Tree-line forests, by definition, occupy areas on the extremes of species tolerance limits, and thus are likely to be sensitive to direct climate effects. With increased temperatures in northern ecosystems, it is assumed that typically southern species will shift their distributions northwards. In the northwestern boreal forest, however, the bottleneck to forest establishment is recruitment, which is strongly mediated by reproductive output and disturbance effects. Through my PhD research, I am specifically focusing on the indirect pathway of disturbance-mediated recruitment by investigating whether an altered fire return interval will initiate ecosystem change in the tree-line forest of northern Yukon.
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 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) | 0,007 | 0,001 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».