Corrigendum to “Seasonal variations of Quercus pubescens isoprene emissions from an in natura forest under drought stress and sensitivity to futureclimate change in the Mediterranean area”

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Water stress impact on isoprene emission from Quercus pubescens Willd.

Les Composés Organiques Volatils biogènes (COVB) sont des molécules issues du métabolisme secondaire des végétaux, dont l'émission peut être modulée par les conditions environnementales. Parmi ces composés, l'isoprène a été très étudié du fait des flux d'émission important et de son implication dans la photochimie troposphérique. Cependant, les mécanismes d'action des facteurs environnementaux sont encore mal connus, et notamment celui de l'impact du stress hydrique. Dans le contexte de changements climatiques, ce type de stress va particulièrement impacter la région méditerranéenne.Nous avons étudié l'impact du stress hydrique sur les émissions d'isoprène de Quercus pubescens Willd. Cette espèce, très présente dans cette région, serait la seconde source d'isoprène en Europe.Deux étude ont été menées.La première, effectuée en pépinière, a consisté à appliquer un stress hydrique modéré et sévère d'avril à octobre. Une augmentation des émissions d'isoprène des arbres modérément stressés a été observée alors qu'il n'y a eu aucune modification des émissions pour les arbres très stressés.La seconde a consisté à faire un suivi saisonnier du stress hydrique au sein d'une chênaie pubescente. Un stress hydrique amplifié a été appliqué par un système d'exclusion de pluie, permettant de diminuer la quantité de pluie de 30%. Nous avons observé que le stress hydrique amplifié augmentait les facteurs d'émission d'isoprène des arbres.Cette base de données a permis le développement, par Réseau de Neurones Artificiels (RNA), d'un algorithme d'émission d'isoprène. Nous avons ainsi mis en évidence l'impact prédominant du contenu en eau du sol sur les émissions d'isoprène.Biogenic Volatile Organic Compounds (BVOC) are plants secondary-metabolism-molecules. Their emissions are modulated by environmental conditions. Among these compounds, isoprene has been particularly studied due to its intense emission fluxes as well as its major contribution to tropospheric photochemistry. However, the impacts of environmental constraints on isoprene emission are still not yet well known. In particular, water stress impact is still a contradictory issue. In a world facing multiple climatic changes, models expect this kind of stress to hit Mediterranean area.This work focused on the impact of water stress on Quercus pubescens Willd. isoprene emissions. This species, widely spread in this area, is the second isoprene emitter in Europe.Two types of study were used.First, during an experimental carried out in a nursery, Q. pubescens saplings were grown under a moderate and severe water stress from April to October. This experimentation highlighted an increase of isoprene emissions for mid-stressed trees, while no emission changes were observed for the highly stressed trees.Secondly, an experimentation was conducted on a pubescent oak forest with trees acclimated to long lasting stress periods. We followed, during a whole season, the impact, on isoprene emissions, of a water stress created by artificially reducing 30% of the rains by means of a specific deploying roof. Isoprene emission factors were observed to increase under water stress.The database thus obtained was used in an Artificial Neural Network (ANN) to develop an appropriate isoprene emission algorithm. We underlined the predominant impact of soil water content on isoprene emissions

Isoprene emissions from downy oak under water limitation during an entire growing season: what cost for growth?

Increases in the production of terpene- and phenolic-like compounds in plant species under abiotic stress conditions have been interpreted in physiological studies as a supplementary defense system due to their capacity to limit cell oxidation. From an ecological perspective however, these increases are only expected to confer competitive advantages if they do not imply a significant cost for the plant, that is, growth reduction. We investigated shifts of isoprene emissions, and to a lesser extent phenolic compound concentration, of Quercus pubescens Willd. from early leaf development to leaf senescence under optimal watering (control: C), mild and severe water stress (MS, SS). The impact of water stress was concomitantly assessed on plant physiological (chlorophyll fluorescence, stomatal conductance, net photosynthesis, water potential) functional (relative leaf water content, leaf mass per area ratio) and growth (aerial and root biomass) traits. Growth changes allowed to estimate the eventual costs related to the production of isoprene and phenolics. The total phenolic content was not modified under water stress whereas isoprene emissions were promoted under MS over the entire growing cycle despite the decline of Pn by 35%. Under SS, isoprene emissions remained similar to C all over the study despite the decline of Pn by 47% and were thereby clearly uncoupled to Pn leading to an overestimation of the isoprene emission factor by 44%. Under SS, maintenance of isoprene emissions and phenolic compound concentration resulted in very significant costs for the plants as growth rates were very significantly reduced. Under MS, increases of isoprene emission and maintenance of phenolic compound concentration resulted in moderate growth reduction. Hence, it is likely that investment in isoprene emissions confers Q. pubescens an important competitive advantage during moderate but not severe periods of water scarcity. Consequences of this response for air quality in North Mediterranean areas are also discussed

Indicators of water stress degree.

<p>T: mean temperature recorded inside the greenhouses every month; ⁽²⁾ RH: air relative humidity recorded inside the greenhouses every month.</p><p>Soil relative water content (SRWC), leaf relative water content (LRWC) and midday water potential (ψ_mid) under control, mild and severe water stress (C, MS and SS) all over the growing season. Climatic conditions under the greenhouse are also shown. Variability of these parameters due to water stress, month and their interaction are tested using two-way ANOVA (F) followed by Tukey test. Lower case letters (a>b) represent differences between treatments month by month. Capital letters (A>B) represent differences between treatments all months averaged (Annual mean column). Values are mean ± SE of n = 5; N.S.: not significant. Lower case or capital letters under brackets denote Tukey test differences at 90% confidence level; df: degrees of freedom.</p><p>Indicators of water stress degree.</p

Gas exchanges (photosynthesis, stomatal conductance and isoprene).

<p>Seasonal course of the net photosynthesis (P_n, graph a), stomatal conductance to water vapor (G_w, graph b) and isoprene emissions (graph c) under control (–⧫–), mild () and severe (···⋄···) water stressed. Note that 70% of isoprene emissions were mostly measured under standard conditions (refer to materials and method for details). Differences are tested using a two-way ANOVA repeated measures (F) followed by Tukey tests. Since interaction between seasonality and treatment is not significant according to the two-way ANOVA, results of water stress impact are shown in the small graph where data of all months are pooled together and differences between treatments are denoted by capital letters (A>B) while seasonality impact is shown in the main graph (in lower case letters: a>b>c). Values are mean ± SE of n = 5.</p

Mapping control, mild stress and severe stress.

<p>Two-dimensional mapping of the Principal Component Analysis (PCA) performed for all plant traits measured at the end of the experiment (plant growth, emission or concentration of secondary metabolites, gas exchange and water status). This analysis was performed on n = 5 trees per treatment. Traits shown at the end of some arrows correspond to the most explanatory traits.</p

Experimental and calculated isoprene emission factors.

<p>Comparison between the isoprene emission factor calculated with Guenther et al. (1993) algorithm () and the experimental isoprene emission factor (▪) obtained under standard conditions (30±1°C and 1000±50 µmol m⁻²s⁻¹ of PPFD) for control, mild and severely water stressed sapling. t: value of the paired sample comparison tests. N.S.: not significant, *0.01<<i>P</i><0.05. Values are mean ± SE of n = 6–7 saplings.</p

Leaf total phenolic concentration.

<p>Seasonal course of leaf total phenolic concentration under control (–⧫–), mild () and severe (···⋄···) water stress. Differences are tested using a two-way ANOVA (F) followed by Tukey tests. Since interaction between seasonality and treatment was not significant, the impact of water stress is shown in the small embedded graph where data of all months are pooled together and differences between treatments are denoted by capital letters (similar capital letters indicate the absence of water stress influence) while seasonality impact is shown in the main graph (in lower case letters: a>b>c). Values are mean ± SE of n = 5.</p

Biomass growth.

<p>Shoot, foliar and root biomass (g_DM ind⁻¹) during leaf senescence (in November) for control, mild and severe water stress. Differences are tested with one-way ANOVA (F). Capital black lower case black and white lower case letters denote statistical differences for shoot, foliar and root biomasses respectively with a>b or A>B given by Tukey tests. Values are mean ± SE. n = 5.</p

Isoprene emission rate as percentage of carbon re-emitted.

<p>Seasonal course of the percentage of photosynthetically assimilated carbon re-emitted as isoprene under control (–⧫–), mild () and severe (···⋄···) water stress. Differences are tested using a two-way ANOVA (F) repeated measurements followed by Tukey tests. Since interaction between seasonality and treatment is not significant according to the two-way ANOVA, results of water stress impact are shown in the small embedded graph where data of all months are pooled together and differences between treatments are denoted by capital letters (A>B) while seasonality impact is shown in the main graph (in lower case letters: a>b). Values are mean ± SE of n = 5 saplings.</p