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Enregistrement W4385255181 · doi:10.3389/ffgc.2023.1256577

Editorial: Natural tree seedling establishment and forest regeneration under climate change

2023· editorial· en· W4385255181 sur OpenAlexaboutno aff
Renée M. Marchin, Zuoqiang Yuan

Notice bibliographique

RevueFrontiers in Forests and Global Change · 2023
Typeeditorial
Langueen
DomaineEnvironmental Science
ThématiqueForest Management and Policy
Établissements canadiensnon disponible
Organismes subventionnairesNational Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesNational Science Foundation
Mots-clésSeedlingRegeneration (biology)Natural regenerationClimate changeNatural (archaeology)Tree (set theory)Natural forestAgroforestryForest regenerationForestryEnvironmental scienceGeographyEcologyBiologyBotanyMathematicsArchaeology

Résumé

récupéré en direct d'OpenAlex

Forests provide valuable ecosystem services including carbon storage, water capture and supply, and local climate regulation (Miura et al., 2015) but are increasingly threatened by climatic changes and associated disturbances such as forest fires, drought, and storms. Largescale mortality events have occurred in all forest biomes and are associated with hotter droughts (Hammond et al., 2022). The hotter, drier edge of species' ranges are becoming unsuitable in some landscapes, initiating conversion of forests to non-forested states (Davis et al., 2019).Natural regeneration is required for long-term forest survival and relies on successful seedling establishment. Many variables influence forest regeneration, including soil temperature, soil fertility, and the existence of favorable microsites. Newly emerged seedlings are vulnerable before their root system develops, whereas established seedlings and mature trees have carbon and water stores and are more resilient to episodic climatic events. A better understanding of the processes influencing seedling survival is needed for predicting changes in forest extent. This Research Topic of six articles explores the factors influencing seedling establishment and survival, from seedling to sapling to tree. The collection outlines critical knowledge gaps and advances our understanding of how forest regeneration may change in the future. These studies span boreal forests in Canada and Sweden, conifer forests in the western USA, and temperate and subtropical forests in Asia.In their review, Brodersen et al. outline a gap in forestry research -understanding the mechanisms by which climate, and other factors, inhibit seedling establishment at mountain forest boundaries. The upward elevational movement of timberlines depends on recruitment in favorable microsites facilitated by microtopography, existing vegetation, or inanimate objects (e.g., rocks, fallen logs). To enable cross-study comparisons, the authors proposed terminology to differentiate 'emergent seedlings' -the initial 1-2 years of growth when cotyledons are present -from 'established seedlings' that have developed their first set of leaves. They advocated for further research aimed at long-term monitoring of first-year seedling abundance and mortality at both upper and lower forest boundaries, identification of the nature and frequency of favorable microsites, and a better understanding of seedling ecophysiology.To help predict future forest distribution in fire-prone landscapes across the western USA, Rank et al. assessed soil surface temperature as a predictor of conifer seedling survival and forest regeneration potential. First, the authors extracted survival data from past laboratory experiments that exposed seedlings to elevated soil surface temperatures for varying durations. Next, they developed logistic models to predict survival of individual seedlings for different species, including species with very few observations. They found that the concept of a lethal temperature strongly depends on the duration of exposure, particularly from 45-60 °C. Their findings suggest soil surface temperature is a promising climate metric for characterizing the environmental boundaries suitable for seedling survival.index can be used for real-time monitoring of gross primary productivity (GPP) in subtropical and temperate monsoon regions of southwest China. They used satellite observations from 2000-2015 to assess the potential for large-scale monitoring of drought and GPP. At a monthly scale, SIF was more strongly correlated with GPP than traditional vegetation indices such as the normalized difference vegetation index (NDVI). In forests with complex canopy structure, monthly NDVI was relatively stable and failed to fully capture the effects of a winter drought event. In hot, wet regions that lack seasonal water limitations, SIF was a useful real-time monitoring tool for predicting GPP and monitoring drought effects over large spatial scales.Using an experimental approach, Marty et al. investigated the effects of soil warming and increased nitrogen deposition on soil organic N mineralization and tree growth in two eastern Canada boreal forests. In response to 9 years of soil warming (+2-4 °C) and canopy N addition (+0.30-0.35 kg N ha -1 yr -1 ), the soil was remarkably stable. Net soil N mineralization, soil chemistry and fertility, and soil organic matter quality were barely impacted, despite evidence that some of the added N reached the forest floor. Minor changes in seedling growth and foliar chemistry may have been driven by mycorrhizal fungi. The main effect of soil warming was to accelerate bud development and budburst, suggesting boreal seedlings may be more vulnerable to late spring frosts in the future.In boreal forests in Sweden, Jessen et al. investigated the effects of warming, both directly and indirectly through changes in understory vegetation, on growth and survival of seedlings. They planted 6400 seedlings and removed competing understory plants (feather moss and/or ericaceous shrubs), then installed passive open-top chambers to increase air temperature (+0.4 °C) at sites with varying successional status. Seedling growth and survival was affected by understory vegetation and successional status, but not warming. Seedling survival increased with feather moss removal, with the greatest benefit in old, late-successional forests with thick moss layers. For birch seedlings, this effect was canceled by shrub removal, possibly because shrubs protected young seedlings from herbivores. For pine species, growth of seedlings was promoted by both shrub and moss removal, suggesting facilitation among understory functional groups is highly species-specific. Ugawa et al. investigated the effects of elevated CO2 and/or O3 on the growth and composition of organic constituents of stems in planted two-year-old seedlings of Japanese oak. Elevated CO2 (550 ppm) increased leaf and stem growth, plus structural stem components such as holocellulose, while decreasing the extractive content of stems by 21%. Extractive compounds such as tannins, flavonoids, and terpenoids are non-structural but have an antimicrobial function that inhibits biodegradation. Seedling growth and organic constituents were not sensitive to elevated O3 (twice ambient), but O3 reduced the influence of elevated CO2. Their findings suggest elevated CO2 and O3 may lead to faster decomposition of Japanese oak and altered C cycling of temperate forests in East Asia. This collection identified potential approaches for monitoring forest productivity and better understanding and predicting forest distribution. Other studies highlighted that many interacting environmental factors, such as warming, nitrogen deposition, and changing atmospheric gas concentrations, affect seedling survival. Filling the remaining research gaps will help to better understand forest regeneration and safeguard forest ecosystems.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,030
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,015
Tête enseignante GPT0,254
Écart entre enseignants0,239 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2023
Routes d'admission1
Résumé présentoui

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