Impact of climate change and extreme events on tree architecture: implications for forest decline and die-back
Notice bibliographique
Résumé
Global climate models agree in predicting a warmer climate on most continental areas, with more frequent extreme events such as heat waves and repeated or exceptional droughts. By increasing drought stress, global warming is a direct threat to forest health and survival in all types of forest ecosystems around the world. Two physiological mechanisms can be involved, separately or simultaneously, in tree decline or mortality during these stressing events: hydraulic failure and carbon starvation. \nStudy goals: We present a study performed as an international effort to understand the influence of climate change and extreme events on the architectural development of forest trees, mainly conifers, in several countries. We discuss its potential contribution to forest decline and die-back. Fourteen conifers and one broadleaved species from Europe, USA and Canada were studied with the same protocol. In 47 sites as a whole, nearly 11000 twigs, from 2300 branches of 470 trees were sampled between 2005 and 2014, some of them repeatedly every year or few years. Branch and trunk length growth, architectural development (branching and polycyclism rates) and reproduction were retrospectively measured from morphological markers over a period of 10 to 45 years according to species. Needle or leaf number per growth unit, size and life span were measured on a subsample of twigs. Study sites include four experimental designs with climate manipulation in controlled conditions: rain exclusion, irrigation or heating and combinations of heat and drought on one of them. A phenological survey was performed on three of them to monitor monthly tree architectural development. Study sites cover conditions going from the limit of the desert to the tree line in mountains. We developed a generic architectural model for conifer trunks or branches, based on the relationships between climate and all measured parameters of tree architecture and needles. It aims at simulating the immediate consequences and after-effects of climate stresses on tree architecture and leaf area, for 10-year periods. \nIn both Europe and Northern America, repeated or extreme droughts, heat waves and other stresses considerably reduced tree and branch vigour for all species at all sites, leading to reduced branch length and tree height growth, low polycyclism and branching rates, shorter and narrower than normal needles or leaves, and small number of needles or leaves per growth unit. A strong reduction of the life span of leaves and needles for evergreen species was also measured. \nThus a significant leaf area deficit was observed and modelled during or just after but also several years after severe stresses. Two mechanisms explained the long lasting legacies of these stresses: (i) the slow recovery of the number of active twigs, due to the twig deficit induced by a low branching rate during and after the stress, limiting the number of leaves and needles, and (ii) the persistence, for many years on some species, of the cohorts of small leaves and needles formed in the bad years. The long lasting reduction of tree leaf area may contribute to carbon shortage and, in extreme cases, to delayed die-off by carbon starvation.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 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 ».