Morpho-anatomical and physiological traits in saplings of drought-tolerant Mediterranean woody species

Savi, Tadeja; Love, Veronica Lee; Borgo, Anna Dal; Martellos, Stefano; Nardini, Andrea

doi:10.1007/s00468-017-1533-7

Cited by 24 publications

(23 citation statements)

References 57 publications

(115 reference statements)

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“…Rosner et al (2019) defined an additional capacitance parameter, the RWL at P 50 , i.e., the RWL that results from 50% conductivity loss. RWL at P 50 varies widely across angiosperm and conifer species and is negatively related to wood density, as found for other capacitance traits as well (Pratt et al 2007;Scholz et al 2007;McCulloh et al 2014;Trifilò et al 2015;Savi et al 2017;Pratt and Jacobsen 2017).…”

Section: Introductionsupporting

confidence: 54%

The conifer-curve: fast prediction of hydraulic conductivity loss and vulnerability to cavitation

Rosner

Johnson

Voggeneder

et al. 2019

Annals of Forest Science

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& Key message The relationship between relative water loss (RWL) and hydraulic conductivity loss (PLC) in sapwood is robust across conifer species. We provide an empirical model (conifer-curve) for predicting PLC from simple RWL measurements. The approach is regarded as a new relevant phenotyping tool for drought sensitivity and offers reliable and fast prediction of diurnal, seasonal, or drought-induced changes in PLC. & Context For conifer species drought is one of the main climate risks related to loss of hydraulic capacity in sapwood inducing dieback or mortality. More frequently occurring drought waves call for fast and easily applicable methods to predict drought sensitivity. & Aims We aimed at developing a fast and reliable method for determination of the percent loss of hydraulic conductivity (PLC) and eventually the drought sensitivity trait P 50 , i.e., the water potential that causes 50% conductivity loss. & Methods We measured the loss of water transport capacity, defined as the relative water loss (RWL) together with PLC in trunk wood, branches, and saplings of eight different conifer species. Air injection was used to induce specific water potentials. & Results The relationship between RWL and PLC was robust across species, organs, and age classes. The equation established allows fast prediction of PLC from simple gravimetrical measurements and thus post hoc calculation of P 50 (r 2 = 0.94). & Conclusion The approach is regarded as a relevant new phenotyping tool. Future potential applications are screening conifers for drought sensitivity and a fast interpretation of diurnal, seasonal, or drought-induced changes in xylem water content upon their impact on conductivity loss.

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Section: Introductionsupporting

confidence: 54%

The conifer-curve: fast prediction of hydraulic conductivity loss and vulnerability to cavitation

Rosner

Johnson

Voggeneder

et al. 2019

Annals of Forest Science

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“…Differences in hydraulic vulnerability within a stem (age‐specific) and between plant organs (roots, trunk, branches) have been reported for conifers (Domec and Gartner , Domec et al , Rosner et al ) and for angiosperms (Charrier et al ). Interspecies‐ (Hacke et al , Hacke and Jansen , Lachenbruch and McCulloh ) or age‐specific variability of P 50 in conifer stem axes is strongly related to wood density (Domec et al , Rosner ), but such relationships may be rather weak or do not necessarily exist for conifer branches (Martínez‐Vilalta et al , Corcuera et al , Lamy et al ) or across angiosperm and conifer species (Gleason et al , Savi et al ). Accordingly, we found no relationship between P 50 and wood density across species.…”

Section: Discussionmentioning

confidence: 99%

“…High‐wood density can be associated with low capacitance (Pratt et al , Scholz et al , McCulloh et al , Trifilò et al , Pratt and Jacobsen , Savi et al ), as it was the case in F. sylvatica saplings and S. torminalis branches (Table ). We found a trend for decreasing capacitance (expressed as lower relative water loss resulting in 50% of conductivity loss) with increasing wood density across species in accordance with the studies mentioned above.…”

Section: Discussionmentioning

confidence: 99%

“…Continuously drought stressed sapwood faces three phases: (1) water release from open conduits, damaged and non‐functional conduits (fatigued conduits) and intercellular spaces, (2) cavitation and release from elastic storage, and (3) the loss of tightly bound water after the wood has lost all of its hydraulic conductivity (Pratt and Jacobsen ). Capacitance of sapwood has been mainly calculated from experiments where small samples, often derived from coring, are allowed to dehydrate and where the Ψ is subsequently measured at decreasing water content by hygrometers (Trifilò et al , Savi et al ) or thermocouple psychrometry (Meinzer et al , McCulloh et al , Jupa et al ). Such curves obtained for sapwood have an exponential shape with extremely high‐water release at high Ψ.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of hydraulic conductivity loss from relative water loss: new insights into water storage of tree stems and branches

Rosner

Heinze

Savi

et al. 2018

Physiologia Plantarum

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More frequently occurring, drought waves call for a deeper understanding of tree hydraulics and fast and easily applicable methods to measure drought stress. The aim of this study was to establish empirical relationships between the percent loss of hydraulic conductivity (PLC) and the relative water loss (RWL) in woody stem axes with different P , i.e. the water potential (Ψ) that causes 50% conductivity loss. Branches and saplings of temperate conifer (Picea abies, Larix decidua) and angiosperm species (Acer campestre, Fagus sylvatica, Populus x canescens, Populus tremula, Sorbus torminalis) and trunk wood of mature P. abies trees were analyzed. P was calculated from hydraulic measurements following bench top dehydration or air injection. RWL and PLC were fitted by linear, quadratic or cubic equations. Species- or age-specific RWLs at P varied between 10 and 25% and P , the Ψ that causes 88% conductivity loss, between 18 and 44%. P was predicted from the relationship between Ψ and the RWL. The predictive quality for P across species was almost 1:1 (r = 0.99). The approach presented allows thus reliable and fast prediction of PLC from RWL. Branches and saplings with high hydraulic vulnerability tended to have lower RWLs at P and at P . The results are discussed with regard to the different water storage capacities in sapwood and survival strategies under drought stress. Potential applications are screening trees for drought sensitivity and a fast interpretation of diurnal, seasonal or drought induced changes in xylem water content upon their impact on conductivity loss.

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“…; Savi et al . ), and there is a less understanding of how this trait can be used as an indicator of drought tolerance. Only a few studies have investigated π O for (i) its use as a proxy for drought tolerance and the degree of iso‐ versus anisohydry, (ii) its correlation with the ability to withstand low leaf water potentials, or (iii) tested the relationship between π O with water availability, and with morpho‐anatomical traits, such as WC sat , and physiological traits, such as g S , Ψ w , π tlp , leaf and stem vulnerability to cavitation, and leaf hydraulic conductance (Brown et al .…”

Section: Introductionmentioning

confidence: 99%

Correlation of drought traits and the predictability of osmotic potential at full leaf turgor in vegetation from New Zealand

et al. 2018

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Scientists do not know precisely how severe will be the impact of climate change on species. Evidence suggests that for some species, their future distributions might be jeopardized by local extinctions and drought-induced tree mortality. Thus, we require models capable of estimating drought tolerance across many species. We can approach this goal by assessing functional traits. The trait osmotic potential at full turgor, p O , is potentially a good drought indicator; however, few studies address its importance as a drought-tolerance predictor and it is difficult to measure in the field with accuracy. In this work, we aim to answer the questions: which drought traits correlate with p O ?; do morpho-anatomical traits correlate with p O ?; and which trees and shrubs are more (or less) vulnerable to drought? To achieve this aim, we assessed physiological and morpho-anatomical traits for 14 native species from New Zealand forests. We included leaf-and wood-related traits, p O , water potential and stomatal conductance. We examined how these traits correlate with p O and sought to generate models to predict p O as a function of other traits. We tested 33 different models and evaluated them using Akaike's information criterion. Unfortunately, none of the morpho-anatomical traits correlated well with p O . Instead, water potential correlated most strongly with p O . None of the models using only morpho-anatomical traits produced plausible results. The model with the best predictive performance incorporated the effects of both morpho-anatomical and physiological traits: water potential and wood saturated water content. Of the species analysed, and based on their p O response, Lophozonia menziesii was considered the most vulnerable to drought stress, whereas Plagianthus regius was the least vulnerable. Our findings imply that it is potentially valuable to keep exploring the use of p O as a drought indicator and that the effort required to measure some physiological traits, such as water potential, may be essential to consider plant drought responses and to predict p O .We measured four physiological and six morpho-anatomical traits. Morpho-anatomical traits included individual-leaf area (LA), leaf relative water content (LRWC), leaf

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Morpho-anatomical and physiological traits in saplings of drought-tolerant Mediterranean woody species

Cited by 24 publications

References 57 publications

The conifer-curve: fast prediction of hydraulic conductivity loss and vulnerability to cavitation

The conifer-curve: fast prediction of hydraulic conductivity loss and vulnerability to cavitation

Prediction of hydraulic conductivity loss from relative water loss: new insights into water storage of tree stems and branches

Correlation of drought traits and the predictability of osmotic potential at full leaf turgor in vegetation from New Zealand

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