Drivers of contrasting boreal understory vegetation in coniferous and broadleaf deciduous alternative states
Notice bibliographique
Résumé
Abstract Alternative states defined by tree‐canopy dominance result in different ecosystem functioning and shape habitat conditions for the understory vegetation. One example in the boreal forest is the alternation between broadleaf deciduous and coniferous forests. Disturbances related to natural fires and human land uses have produced changes in tree‐canopy dominance in the boreal region where coniferous forests change to broadleaved forests, affecting understory community dynamics and their related ecosystem processes and functions. To analyze the factors driving changes in understory vegetation and the resistance of its vegetation to shifts between alternative states, we compared the effects of changes in the system between two contrasting boreal forest types (black spruce vs. trembling aspen) in adjacent stands with similar topoedaphic conditions. We performed a 5‐year in situ experiment using alternative states as a theoretical framework including two approaches: (1) the ecosystem approach, manipulating environmental conditions of light, litter, and nutrients in each forest type to determine the main mechanisms associated with tree‐canopy dominance that affect the diversity and composition of understory communities; and (2) the community approach, physically exchanging understory communities between alternative states, to determine their resistance under a new tree‐canopy dominance through time, as well as the resilience of the forest understory after a small‐scale disturbance. Results indicate that the understory vegetation of trembling aspen forests were resistant through time both after changes in local conditions in the ecosystem approach and in the new black spruce‐dominated alternative state in the community approach. In contrast, mosses and ericaceous plants that typically dominate the forest floor of black spruce forests were negatively affected by the physical effect of broadleaf litter addition in our ecosystem approach and they were not resistant when transplanted to trembling aspen forests in the community approach, as they decreased in abundance and were invaded by aspen understory community species over time. The understory vegetation is a key forest ecosystem driver that can contribute to maintain the resilience of the boreal system and help to preserve their ecosystem services, which is a key aspect to consider in forest management faced with the effects of climate change.
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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 | 0,001 |
| 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) | 0,000 | 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 tête enseignante, 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 ».