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Enregistrement W2164426298 · doi:10.1093/treephys/tpt069

Will rising CO2 and temperatures exacerbate the vulnerability of trees to drought?

2013· letter· en· W2164426298 sur OpenAlexafffund
Danielle A. Way

Notice bibliographique

RevueTree Physiology · 2013
Typeletter
Langueen
DomaineEnvironmental Science
ThématiquePlant Water Relations and Carbon Dynamics
Établissements canadiensWestern University
Organismes subventionnairesNatural Sciences and Engineering Research Council of CanadaU.S. Department of AgricultureU.S. Department of EnergyNational Science Foundation
Mots-clésClimate changeEnvironmental scienceVulnerability (computing)Global warmingVapour Pressure DeficitHeat waveDrought stressAtmospheric sciencesClimatologyHeat stressGeographyEcologyTranspirationBiologyAgronomyBotanyPhotosynthesisGeology

Résumé

récupéré en direct d'OpenAlex

Large-scale tree dieback events are increasing in frequency around the world, with many of them attributed to the effects of climate change-related droughts (i.e., droughts that co-occur with heat stress) (Adams et al. 2010, Allen et al. 2010). As mean global temperatures are expected to rise by 2–4 °C in the next 85 years (Christensen et al. 2007) and elevated temperatures are correlated with higher vapor pressure deficits and evaporative driving forces (Oishi et al. 2010), we may expect a rise in tree mortality due to drought in a warmer future. However, climate warming is mainly driven by rising atmospheric CO2 concentration, a factor that can increase plant drought tolerance (Drake et al. 1997). The degree to which these two global change factors will alter the vulnerability of trees to drought is unclear, and combinatorial experiments studying the effects of both warming and elevated CO2 on tree drought tolerance are rare (but see Wertin et al. 2010, 2012, Zeppel et al. 2012, Lewis et al. 2013). Research on what causes tree mortality during climate-change drought events tends to focus on two hypotheses: direct hydraulic failure or carbon starvation (McDowell et al. 2008). The first hypothesis acknowledges that if stomata remain open during drought to maintain carbon fixation for metabolism, then the associated water losses from transpiration will eventually cause catastrophic cavitation (Anderegg et al. 2012). The second hypothesis focuses on the role of stomata in maintaining the integrity of the hydraulic pathway of trees. As stomata close during drought, respiration continues to burn carbohydrates without new photosynthetic carbon fixation and the plant's carbohydrate stores are depleted until they cannot maintain metabolic needs (Adams et al. 2009). The role of carbon starvation in limiting tree survival and responses to climate is clearest during glacial periods with low CO2 concentrations (∼200 ppm) (Gerhart et al. 2012), but low stomatal conductance during drought may generate analogously low intercellular CO2 concentrations under future high CO2 conditions. Lastly, the interdependence of water transport and carbohydrate status in trees has also received increasing recognition (McDowell et al. 2011, Sala et al. 2012): phloem transport of sugars to sink tissues requires adequate water transport, and there is recent evidence that embolism repair may depend on carbohydrate availability (Secchi and Zwieniecki 2011). In this issue of Tree Physiology, Duan et al. (2013) add to our growing knowledge of how climate change may alter this second aspect of drought tolerance, plant carbon dynamics. They looked at the combined impact of elevated CO2 concentrations and warming on leaf-level carbon fluxes, growth and non-structural carbohydrate (NSC) status in droughted Eucalyptus seedlings. While elevated CO2 increased plant carbon status and growth, and high temperatures reduced leaf carbon balance during moderate drought, these treatment effects were not evident as the drought became severe. When high CO2 and growth temperatures were applied concurrently, they increased growth during the early, moderate stage of the drought, but this response also disappeared as water stress progressed. The data also indicate the difficulty in predicting whole-tree NSC status or growth from leaf-level carbon fluxes. In Eucalyptus experiencing a sustained drought, elevated temperatures suppressed photosynthesis and stimulated respiration, which might be expected to reduce growth and NSC content. But instead, seedling mass and NSC tended to be higher in warm-grown plants than in ambient-climate seedlings. The effects of climate change factors on the other side of tree drought tolerance, hydraulic vulnerability, also deserve more study. High CO2 reduces leaf-level stomatal conductance, which is the basis for predicting that plants will use less water and be less sensitive to drought in the future (Ainsworth and Rogers 2007). While overall allocation between roots and shoots is unaffected by elevated CO2 (Poorter et al. 2012), some trees and younger stands that develop at elevated CO2 have larger canopy areas, offsetting some of the leaf-level water savings at the whole tree and forest plot levels (Bobich et al. 2010, Warren et al 2011a, Medeiros and Ward 2013). CO2 concentration can also alter xylem anatomy, with an overall tendency for larger conduit sizes at high CO2 in ring-porous species and some conifers, but little difference in xylem vessel diameter in diffuse-porous tree species (e.g., Conroy et al. 1988, Atkinson and Taylor 1996, Saxe et al. 1998, Ceulemans et al. 2002, Kaakinen et al. 2004, Watanabe et al. 2008, Domec et al. 2010, Phillips et al. 2011). Where elevated CO2 increases the conduit size, this translates into lower stem cavitation resistance (Domec et al. 2010) that may make trees more vulnerable to moderate drought stresses. As well, lower stomatal conductance at high CO2 reduces transpirational cooling of leaves and raises leaf temperatures (Bernacchi et al. 2007), which can actually increase the vulnerability of trees to drought during hot, dry spells (Bobich et al. 2010, Warren et al. 2011b). With respect to warming, higher growth temperatures tend to increase the canopy leaf area and generally lead to smaller root-to-shoot ratios in trees, both of which may make future trees less capable of withstanding drought (Way and Oren 2010, Poorter et al. 2012). Growth at high temperatures can alter xylem anatomy, hydraulic conductivity and cavitation vulnerability (Maherali and DeLucia 2000a, 2000b, Thomas et al. 2004, Phillips et al. 2011) and these anatomical and physiological changes can make warm-grown trees more susceptible to drought (Way et al. 2013). Higher growth temperatures also influence carbon dynamics parameters that may influence the ability to survive a drought. Warming tends to stimulate respiration rates and may accelerate the depletion of carbon stores (Adams et al. 2009), although acclimation can offset this significantly in tree species (Way and Oren 2010). While photosynthetic acclimation to elevated temperatures can maintain carbon gain in woody species, not all species show significant thermal acclimation of photosynthesis, especially if the warming is substantial (Way and Oren 2010, Way and Yamori in press). Duan et al. (2013) add to the growing literature on how tree carbon dynamics under drought respond to combined high CO2 and elevated temperatures, a topic where we need more data to make strong predictions about future forest behavior. There are, however, only two studies to my knowledge that examine any aspect of how tree hydraulic characteristics respond to these two combined growth conditions (Maherali and DeLucia 2000b, Phillips et al. 2011). So, how do we move forward with the data we have? While we cannot rely heavily on the results of single-factor studies in predicting how future vegetation will be affected by drought, we can look for commonalities in the responses of tree hydraulic and carbon balance traits to either global change factor alone (Table 1). This analysis suggests that hydraulic traits (such as the water potential at which 50% of hydraulic conductivity is lost, or the P50) may predispose trees to being more vulnerable to drought under future conditions, while carbon dynamic parameters may be more resilient to combined changes in temperature and CO2. In summary, we clearly need more information on how trees will respond to drought when they develop under both elevated CO2 and growth temperatures, if we are to attempt to mitigate and adapt to the effects of climate change in forests. Physiological and anatomical traits in trees that may affect drought tolerance, their generalized responses to either elevated growth temperatures or elevated CO2 concentrations and postulated responses to combined elevated temperatures and growth CO2 where responses to the single factors overlap. Trends are taken from literature cited in the text. gs, stomatal conductance; P50, water potential at which half of the hydraulic conductivity of a tissue is lost; VPD, vapor pressure deficit. Physiological and anatomical traits in trees that may affect drought tolerance, their generalized responses to either elevated growth temperatures or elevated CO2 concentrations and postulated responses to combined elevated temperatures and growth CO2 where responses to the single factors overlap. Trends are taken from literature cited in the text. gs, stomatal conductance; P50, water potential at which half of the hydraulic conductivity of a tissue is lost; VPD, vapor pressure deficit. This work was supported by grants to D.A.W. from NSERC, the US Department of Agriculture, Agriculture and Food Research Initiative (#2011-67003-30222), the US Department of Energy, Terrestrial Ecosystem Sciences (#11-DE-SC-0006967), and the US-Israeli Bi-national Science Foundation (#2010320).

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,024
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,029
Score d'incertitude au seuil0,023

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,024
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0030,002
Communication savante0,0020,002
Science ouverte0,0010,001
Intégrité de la recherche0,0290,023
Charge utile insuffisante (le modèle a refusé de juger)0,0070,005

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 Opus0,008
Tête enseignante GPT0,213
Écart entre enseignants0,205 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

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

En bref

Citations16
Publié2013
Routes d'admission2
Résumé présentoui

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