TY - JOUR
AU - Petit,, Giai
AB - Abstract Understanding which structural and functional traits are linked to species’ vulnerability to embolism formation (P50) may provide fundamental knowledge on plant strategies to maintain an efficient water transport. We measured P50, wood density (WD), mean conduit area, conduit density, percentage areas occupied by vessels, parenchyma cells (PATOT) and fibers (FA) on branches of angiosperm and gymnosperm species. Moreover, we compiled a dataset of published hydraulic and anatomical data to be compared with our results. Species more vulnerable to embolism had lower WD. In angiosperms, the variability in WD was better explained by PATOT and FA, which were highly correlated. Angiosperms with a higher P50 (less negative) had a higher amount of PATOT and total amount of nonstructural carbohydrates. Instead, in gymnosperms, P50 vs PATOT was not significant. The correlation between PATOT and P50 might have a biological meaning and also suggests that the causality of the commonly observed relationship of WD vs P50 is indirect and dependent on the parenchyma fraction. Our study suggests that angiosperms have a potential active embolism reversal capacity in which parenchyma has an important role, while in gymnosperms this might not be the case. Introduction In plants, water is transported over long distances through elongated dead xylem conduits while under negative pressure, and is hence maintained in the liquid phase while below its vapor pressure (Tyree 1997). This mechanism exposes plants to the risk of embolism formation at critical xylem tension, when gas bubbles from surrounding compartments are aspirated into the water-filled xylem conduits and expand, occupying the whole conduit volume (Nardini et al. 2011, Vilagrosa et al. 2012). Embolism can spread between adjacent conduits, thus decreasing the xylem hydraulic conductance (K) (Jacobsen et al. 2005, Domec et al. 2006), with negative effects on sap flow rate and thus plant performance (growth, reproduction and survival). In fact, carbon assimilation with photosynthesis ultimately depends on the functional balance between the water absorbed from the soil and transported across the xylem to the leaves (sap flow rate, F), and the water lost via leaf transpiration (T) (i.e., F = T). F depends on the difference of water potential between the leaves and the soil and on the xylem hydraulic conductance (i.e., F = ΔΨ*K). Therefore, any decrease in K due to embolism can alter this balance, potentially leading to turgor loss and stomatal closure due to progressive leaf dehydration. Plants frequently operate at leaf water potentials close to critical thresholds of conductivity loss by embolism formation (Nardini and Salleo 2000, Choat et al. 2012), suggesting that this latter phenomenon is not a rare occurrence in every day plant life. Hence, plants have evolved strategies to avoid emboli spread or to tolerate embolism until the production of new xylem conduits (Pratt et al. 2005), or they have developed mechanisms to recover the hydraulic functionality after embolism formation (Salleo et al. 2004). Species’ vulnerability to xylem embolism can be quantified by means of ‘vulnerability curves’ and derived values of xylem pressure causing 50% loss of hydraulic conductance of xylem (P50). In earlier studies, P50 was linked to several physiological/anatomical traits in an effort to understand which factors are linked to vulnerability to embolism formation. Among the several structural–functional relationships emerging from these studies focused on different species’ assemblages, the one reported most commonly is the negative relationship between wood density (WD) and P50 (Hacke et al. 2001, Lachenbruch and McCulloh 2014, Rosner 2017), with denser wood being more resistant to embolism formation. Nevertheless, the mechanistic basis for this relationship and the identification of which wood traits are mostly driving it are still uncertain. Higher resistance to embolism has been also commonly found in species with narrower conduits, often characterized by smaller pit areas (Becker et al. 2003, Lazzarin et al. 2016), which would make conduits safer against air seeding (Hacke et al. 2006, Martínez-Cabrera et al. 2009). In addition, according to the rules of xylem spatial distribution (xylem packing) the conduit area (CA) is inversely related to the conduit density (CD: number of conduits per unit xylem area) (Martinez-Vilalta et al. 2012), so that narrower and denser conduits are commonly reported to be more resistant to embolism formation (Hacke et al. 2017). According to Johnson et al. (2012) plants operate at different distances from their hydraulic safety margins, resulting in the formation of different degrees of embolism. Hydraulic safety margin is defined as the difference between the leaf water potential at stomata closure (i.e., the daily/seasonal minimum xylem pressure, Pmin) and P50. Gymnosperms were found to have larger safety margins than angiosperms (Choat et al. 2012), suggesting that tight stomatal control in this group of species may help to safeguard the xylem from embolism formation better than angiosperms. The low safety margins of angiosperms would suggest that most of them regularly experience a certain degree of xylem embolism, exposing their hydraulic system to a risk of high loss of hydraulic conductance (Choat et al. 2012), with negative consequences on transpiration and carbon assimilation. While nonlethal loss of xylem hydraulic conductance can be recovered by the production of new xylem potentially characterized by adaptive changes in hydraulic properties (Petit et al. 2016, Secchi et al. 2017), it is conceivable that the ability to repair embolism and recover full gas exchange rates might confer an adaptive advantage to some woody species, especially angiosperms (Klein et al. 2018). Some species have been reported to refill embolized conduits with water upon drought relief (Nardini et al. 2017). However, the occurrence of this phenomenon has been questioned by some studies due to methodological uncertainties (Cochard and Delzon 2013, Klein et al. 2018), while other studies showed the inability of species to recover embolized conduits (Choat et al. 2018, Creek et al. 2018, Johnson et al. 2018); thus, the phenomenon remains at present controversial. Xylem embolism reversal has been reported in both angiosperms and gymnosperms (Brodersen and McElrone 2013, Mayr et al. 2014), although gymnosperms have been found to have a long recovery process (Secchi et al. 2017). Short-term embolism reversal has been hypothesized to depend on active metabolic processes that require a source of energy and a source of water. According to the current paradigm, soluble carbohydrates released in xylem conduits by surrounding living cells would accumulate and reclaim water from surrounding tissues via an osmotic mechanism (Salleo et al. 2004, Zwieniecki and Holbrook 2009). Therefore, wood parenchyma cells are expected to play a fundamental role in the process of embolism reversal (Brodersen and McElrone 2013, Trifilò et al. 2019), as the main sources of nonstructural carbohydrates (NSC) (Plavcova et al. 2016) and stored water to be diverted into the refilling conduits (Rosner et al. 2018). In this context, starch degradation is hypothesized to provide sugars (Tomasella et al. 2017). In parallel, parenchyma cells may be necessary to sustain physiological processes while the recovery mechanism is active (Secchi et al. 2017). In this scheme, it can be expected that the plant’s capacity to recover the water transport system from emboli formed in the conduits correlates with the volume of parenchyma cells in the xylem (Secchi et al. 2017). Hence, a higher abundance of parenchyma cells in the xylem (i.e., a higher amount of stored starch and water) is hypothesized to be required in species more vulnerable to embolism formation with low safety margins, in which the refilling mechanism would be of higher importance for their survival, especially under prolonged drought (Ogasa et al. 2013, Trifilò et al. 2015). In this study, we performed anatomical analyses and measured the P50 and WD of branches in different angiosperm and gymnosperm species, examining correlations between key structural and functional traits related to embolism vulnerability. We also gathered available data from previous studies to perform a global analysis and compare our experimental results. We aimed to understand which of the wood characteristics explain better the variability of P50. We addressed the following hypotheses: (i) there are differences in the traits related to embolism vulnerability between angiosperms and gymnosperms; (ii) the wood composition (i.e., the percentages of wood tissues) and the xylem anatomical traits correlate to species’ embolism vulnerability; and (iii) there is a relationship between embolism vulnerability and the fraction of the living tissues, at least in angiosperms. Materials and methods We performed measurements on branch segments of angiosperm (N = 75) and gymnosperm species (N = 14) (Table 1) growing at the Botanical garden of the University of Padova (45.3996° N; 11.8805° E), in the Karst region (Trieste) (45.6495° N; 13.7768° E) and in Messina (Sicily) (38.1938° N; 15.5540° E), in Italy. We measured the WD; the percentage areas occupied by parenchyma cells, fibers and conduits; and the conduit anatomical characteristics (see below). For some of the species we measured the P50 value, while for others the same parameter was derived from previously published studies (see below). We also compiled a global dataset summarizing P50, amount of total NSC (including starch) stored in the wood, WD and xylem parenchyma amount (PATOT), as reported from previous published studies focused on very diverse species’ assemblages. Table 1 The 15 angiosperm species for which we performed hydraulic experiments, their maximum vessel length (VLmax) (cm), their water potential of 50% loss of hydraulic conductivity (P50) (MPa) and the number of segments used for the estimation of P50 (n). Standard error (SE) is shown in brackets next to the mean values. VLmax for Fraxinus ornus is non-applicable due to data loss. Spp. VLmax (cm) (SE) P50 (MPa) (SE) n Acer monspessulanum L. 13.7 (0.9) −4.99 (0.38) 4 Carpinus orientalis Mill. 5 (1.7) −3.81 (0.53) 4 Corylus avellana L. 19.6 (3.5) −2.86 (0.20) 3 Ficus carica L. 25 (15) −1.74 (0.36) 3 Fraxinus ornus L. na −3.48 (0.37) 3 Hedera helix L. 4.8 (0.2) −2.84 (0.81) 2 Morus alba L. 77.2 (13.5) −0.9 (0.05) 2 Ostrya carpinifolia Scop. 5 (1.7) −4.31 (0.27) 5 Pistacia terebinthus L. 63.8 (8.9) −2.71 (0.38) 4 Prunus mahaleb L. 25.5 (3.5) −5.54 (0.37) 4 Quercus ilex L. 57.0 (7) −3.56 (0.85) 4 Quercus pubescens Willd. 67.7 (2.8) −2.37 (0.80) 3 Robinia pseudoacacia L. 79.8 (14.3) −2.59 (0.24) 3 Tilia cordata Mill. 15.4 (4.4) −1.64 (0.10) 3 Whisteria sinensis (Sims) Sweet 84.6 (5.9) −1.19 (1.17) 3 Spp. VLmax (cm) (SE) P50 (MPa) (SE) n Acer monspessulanum L. 13.7 (0.9) −4.99 (0.38) 4 Carpinus orientalis Mill. 5 (1.7) −3.81 (0.53) 4 Corylus avellana L. 19.6 (3.5) −2.86 (0.20) 3 Ficus carica L. 25 (15) −1.74 (0.36) 3 Fraxinus ornus L. na −3.48 (0.37) 3 Hedera helix L. 4.8 (0.2) −2.84 (0.81) 2 Morus alba L. 77.2 (13.5) −0.9 (0.05) 2 Ostrya carpinifolia Scop. 5 (1.7) −4.31 (0.27) 5 Pistacia terebinthus L. 63.8 (8.9) −2.71 (0.38) 4 Prunus mahaleb L. 25.5 (3.5) −5.54 (0.37) 4 Quercus ilex L. 57.0 (7) −3.56 (0.85) 4 Quercus pubescens Willd. 67.7 (2.8) −2.37 (0.80) 3 Robinia pseudoacacia L. 79.8 (14.3) −2.59 (0.24) 3 Tilia cordata Mill. 15.4 (4.4) −1.64 (0.10) 3 Whisteria sinensis (Sims) Sweet 84.6 (5.9) −1.19 (1.17) 3 Open in new tab Table 1 The 15 angiosperm species for which we performed hydraulic experiments, their maximum vessel length (VLmax) (cm), their water potential of 50% loss of hydraulic conductivity (P50) (MPa) and the number of segments used for the estimation of P50 (n). Standard error (SE) is shown in brackets next to the mean values. VLmax for Fraxinus ornus is non-applicable due to data loss. Spp. VLmax (cm) (SE) P50 (MPa) (SE) n Acer monspessulanum L. 13.7 (0.9) −4.99 (0.38) 4 Carpinus orientalis Mill. 5 (1.7) −3.81 (0.53) 4 Corylus avellana L. 19.6 (3.5) −2.86 (0.20) 3 Ficus carica L. 25 (15) −1.74 (0.36) 3 Fraxinus ornus L. na −3.48 (0.37) 3 Hedera helix L. 4.8 (0.2) −2.84 (0.81) 2 Morus alba L. 77.2 (13.5) −0.9 (0.05) 2 Ostrya carpinifolia Scop. 5 (1.7) −4.31 (0.27) 5 Pistacia terebinthus L. 63.8 (8.9) −2.71 (0.38) 4 Prunus mahaleb L. 25.5 (3.5) −5.54 (0.37) 4 Quercus ilex L. 57.0 (7) −3.56 (0.85) 4 Quercus pubescens Willd. 67.7 (2.8) −2.37 (0.80) 3 Robinia pseudoacacia L. 79.8 (14.3) −2.59 (0.24) 3 Tilia cordata Mill. 15.4 (4.4) −1.64 (0.10) 3 Whisteria sinensis (Sims) Sweet 84.6 (5.9) −1.19 (1.17) 3 Spp. VLmax (cm) (SE) P50 (MPa) (SE) n Acer monspessulanum L. 13.7 (0.9) −4.99 (0.38) 4 Carpinus orientalis Mill. 5 (1.7) −3.81 (0.53) 4 Corylus avellana L. 19.6 (3.5) −2.86 (0.20) 3 Ficus carica L. 25 (15) −1.74 (0.36) 3 Fraxinus ornus L. na −3.48 (0.37) 3 Hedera helix L. 4.8 (0.2) −2.84 (0.81) 2 Morus alba L. 77.2 (13.5) −0.9 (0.05) 2 Ostrya carpinifolia Scop. 5 (1.7) −4.31 (0.27) 5 Pistacia terebinthus L. 63.8 (8.9) −2.71 (0.38) 4 Prunus mahaleb L. 25.5 (3.5) −5.54 (0.37) 4 Quercus ilex L. 57.0 (7) −3.56 (0.85) 4 Quercus pubescens Willd. 67.7 (2.8) −2.37 (0.80) 3 Robinia pseudoacacia L. 79.8 (14.3) −2.59 (0.24) 3 Tilia cordata Mill. 15.4 (4.4) −1.64 (0.10) 3 Whisteria sinensis (Sims) Sweet 84.6 (5.9) −1.19 (1.17) 3 Open in new tab Parenchyma amount and wood anatomy One to three branch segments from different individuals were sampled. We used the replicates to ensure that there is a low intraspecific variability between individuals growing under similar environmental conditions. For each segment, we cut transverse and tangential microsections at 25 μm with a rotary microtome LEICA RM 2245 (Leica Biosystems, Nussloch, Germany), stained them with a solution of safranin and Astra Blue (1% and 0.5% in distilled water, respectively) and permanently fixed them on glass slides with Eukitt (BiOptica, Milano, Italy). Images from the transverse microsections were acquired at 100× and for the tangential at 40× magnification, using a D-sight slide scanner (Menarini Group, Florence, Italy). The images of transverse and tangential sections were analyzed with ImageJ 2.0.0 (Schneider et al. 2012) for the estimation of the percentages of the areas occupied by parenchyma cells. For each image, we selected an area of ~1 mm2 (AIMAGE) with intact tissues (i.e., not affected by artificial cracks caused by cutting), and manually outlined the areas occupied by parenchyma cells. For the transverse sections, we outlined and measured only the total area of axial parenchyma cells (PAA), including both apotracheal and paratracheal cells, whereas in the tangential sections, the total area of radial parenchyma cells (PAR) was measured. Both PAA and PAR were then converted into percentage amounts (%PAA and %PAR, respectively) by dividing by AIMAGE. Since the PAA and PAR orientate perpendicularly to our transverse and tangential sections, respectively, the percentage area occupied by parenchyma cells was estimated as: PATOT = (%PAA + %PAR)*(%XA/100) + %Apith, where %Apith is the percentage of pith area (Apith) and %XA is the percentage of xylem area (XA) estimated by ROXAS (see below) on the complete transverse section. Images from the transverse sections were further used for the automatic anatomical measurements in ROXAS v3.0.139 (von Arx and Dietz 2005, von Arx and Carrer 2014). The analysis was performed on a wedge of known angle (α) centered at the pith for each image. A first manual editing of the images to outline the contour of the pith and of each ring was carried out. For each outlined sector in the wedge (i.e., pith or rings), ROXAS automatically measured the area (RA), the conduit number (CNo), the mean CA (MCA) and the conduit hydraulic diameter. Then, traits’ data (Y′) of Apith, total XA and total CNo were upscaled to the whole cross-section as Y = Y′/α * 360. Conduit density was calculated from the upscaled total CNo and total XA. The percentage of Apith was calculated as %Apith = (Apith/(Apith + XA)) * 100 and of XA as %XA = 100 − %Apith. We furthermore estimated the total area occupied by vessels (VA) as a percentage over the total XA (VA = CNo * MCA * 100/XA) and the percentage area occupied by FA as the total area (100%) minus the percentage area occupied by parenchyma cells, the percentage VA and the Apith (FA = 100 − PATOT − VA − %Apith). Wood density The WD of one to three branch segments (~2–8 mm in diameter)—the same that were used in the anatomical analysis—of 51 angiosperms and 13 gymnosperms was measured using the water displacement method according to the Archimedes’ principle. The branch segments were boiled in a container filled with water until they sank upon rehydration and then debarked. Another container was filled with water, placed on a digital balance calibrated to the nearest 0.01 g (Acculab ALC-1100.2 Acculab, USA, Arvada Colorado) and re-zeroed. Each segment was connected from the pith to a needle attached to a thread and carefully immersed in water. The weight of water displaced was equal to the segment wet volume of xylem + pith and 1 g of displacement was equivalent to 1 cm3. After measuring their volume, the segments were put in the oven at 60 oC for 72 h. The dry weight was measured with the same digital balance (Acculab ALC-1100.2 Acculab, USA, Arvada Colorado) immediately when the samples were taken out of the oven and cooled. Wood density was then calculated as dry weight (g)/volume (cm3). Measurements of P50 Hydraulic measurements were performed on 15 species of angiosperms (Table 1) during summer 2018 (June–August). Before the estimation of P50, we assessed the maximum vessel length (VLmax) for each species (Table 1) to avoid experimental artifacts (Ennajeh et al. 2011). For each species, we cut at least three branches (1–2 m long) originating from different individuals. Both the basal and apical parts (~15 cm from the apex) of the branch were then trimmed three times underwater with a razor blade and connected from the apical part to a tubing system. Air was perfused from the apical end of the branch at a pressure of 10 kPa, while the basal end was immersed in a water tank and observed with a magnifying lens for the presence of air bubbles. The basal end of the branch was cut progressively by 1 cm until air bubbles were observed. The VLmax for each branch was equal to the length of the branch when at least two evident streams of air bubbles were observed indicating that at least two vessels were open at both ends. The species VLmax was estimated as the average value of VLmax of the three replicates. For the estimation of P50, vulnerability curves were determined with the air-injection method (Ennajeh et al. 2011). At least three branches 1–2 m long depending on the species VLmax were collected early in the morning from at least three individuals per species. Three branches per species were used when the variability in P50 was low (except from Hedera helix and Morus alba, for which only two branches were used), while for higher variability the number of replicates was increased (same as in Savi et al. 2018). The branches were immediately placed with the distal end in a bucket filled with water and covered with a plastic bag for at least 2 h before the measurements to relax the tension and avoid the artifact of inducing embolism (Wheeler et al. 2013). Before the measurement, each branch was recut underwater (final length > VLmax), debarked at both ends for 2 cm and connected to a hydraulic apparatus (Xyl’EM xylem embolism meter, Bronkhorst, Montigny-Les-Cormeilles, France). All the leaves were removed cutting the stalk underwater. Branches were flushed with a filtered poly-ionic solution enriched with a 10-mmolL−1 KCl solution at a pressure of 0.18 MPa for 30 min. Then the branch was submerged in water, and the bark was removed from a central portion that was later connected to a double-ended pressure chamber (Ennajeh et al. 2011). The cut ends were slightly trimmed again, and the basal area of the segment was connected to a 1-m long tube, which was wide enough to allow the escape of air bubbles. Maximum conductance (Kmax) was then measured at low pressure (4.8 kPa). After measuring the Kmax, increasing pressures at steps of 0.2–1 MPa were applied to the branches and the branch conductance at each step (Kp) was measured. The percentage loss of conductance (PLC) at each pressure was calculated as: PLC = 100 *(Kmax − Kp)/Kmax. Figure 1. Open in new tabDownload slide (a) Vulnerability to embolism (P50) against the WD for angiosperms in light cyan and gymnosperms in dark purple. The data are from our measurements and from literature. (b) P50 against the MCA for angiosperm species. (c) P50 against the CD for angiosperm species. Figure 1. Open in new tabDownload slide (a) Vulnerability to embolism (P50) against the WD for angiosperms in light cyan and gymnosperms in dark purple. The data are from our measurements and from literature. (b) P50 against the MCA for angiosperm species. (c) P50 against the CD for angiosperm species. The measurements were repeated for each branch until reaching a PLC of at least 70–80%. Vulnerability curves, consisting of 7–12 points each, were assessed using the packages Rcmdr version 2.4–4 (Fox 2005, 2017; Fox and Bouchet-Valat 2018) and fitplc version 1.1–7 (Duursma and Choat 2017) in R Studio version 1.1.423 (RStudio Team 2015) and the water potential at which the PLC equals 50% (P50) was estimated accordingly. Only sigmoidal shaped curves were taken into consideration (example shown in Figure S1 available as Supplementary Data at Tree Physiology Online). For a few branches the resulting curves were nonsigmoidal (r-shaped); these curves were discarded and another replicate was repeated for the species. This was done not only to have a uniform analysis as most curves were sigmoidal, but also and most importantly because non-sigmoidal (r-shaped) curves possibly result from open vessels artifacts and lead to an overestimation of P50 (Cochard et al. 2013; Wang et al. 2014; Savi et al. 2018). Some studies have suggested that nonsigmoidal curves may accurately describe species’ vulnerability to embolism formation (Jacobsen and Pratt 2012; Sperry et al. 2012; Hacke et al. 2015), other than different from the air-injection were used by them to evaluate the P50. Sigmoidal and nonsigmoidal curves were recognized by eye based on Figure 1 of Cochard et al. (2013). Values of P50 for all the other species were obtained from Choat et al. (2012). Global dataset We compiled a global dataset (Table S1 available as Supplementary Data at Tree Physiology Online) including species-specific data of branches (and when not available we used stem data) for 107 species (68 angiosperms and 39 gymnosperms). In this dataset, we included PATOT data collected from Morris et al. (2016), P50 collected from Choat et al. (2012), WD data that were taken from the Global Wood Density Database (Chave et al. 2009; Zanne et al. 2009) and total NSC contents (sugars and starch) that were obtained from several published studies (listed in Table S1 available as Supplementary Data at Tree Physiology Online). Statistical analysis We assessed the relationship between P50 and WD in angiosperms and gymnosperms. We then tested the relationships P50 vs MCA and P50 vs CD. Moreover, we tried to understand if FA, VA and PATOT explain the variation in the distribution of WD and of P50 in angiosperms. We assessed these relationships with linear regressions and tested the normality and homoscedasticity of the residuals. In case of nonparametric data, we applied a log10 transformation. We used the absolute values of P50 for its log10 transformation. For angiosperms, we tested for differences in the slopes (b) and the y-intercepts between our measurements and the compiled global dataset in the relationships P50 vs PATOT and P50 vs WD, and we assessed the relationship of P50 vs NSC in the compiled dataset. We applied the Bonferroni adjustment in these models and quantile plots to test for statistically significant outliers (i.e., outside the 95% confidence envelope) (Figures S2–S4 available as Supplementary Data at Tree Physiology Online). In gymnosperms the total sample number was too low to allow for valid results. All the statistical analyses were performed in R version 3.4.2 (R Development Core Team 2017). Results P50 and WD We found a significant negative relationship between P50 and WD, with species being less vulnerable to embolism formation (i.e., lower P50) producing denser wood (Figure 1a). The relationship was significant for both angiosperm (R2 = 0.17; P < 0.001) and gymnosperm (R2 = 0.18; P < 0.01) species. The comparison between the different sources of data (global dataset vs our own measurements) revealed that the relationship is significant in angiosperms in both datasets, although we observed a marginally significant offset in the y-intercept (Figure S5a and Table S2 available as Supplementary Data at Tree Physiology Online). In gymnosperms, the relationship was not significant when testing the two datasets separately (Table S2 available as Supplementary Data at Tree Physiology Online). P50 and xylem anatomy We assessed the effects of MCA and CD on the vulnerability to embolism formation (P50). In angiosperms, we found a significant positive relationship between P50 and MCA (Figure 1b; R2 = 0.27; P < 0.001), suggesting that angiosperms with wider vessels are more vulnerable to embolism formation. In addition, we also found a negative relationship between P50 and CD (Figure 1c; R2 = 0.19; P < 0.001), indicating that species with denser vessels are less vulnerable to embolism formation. However, MCA was negatively related to CD according to a highly significant power scaling with b~ −1 (Figure S6c available as Supplementary Data at Tree Physiology Online; R2 = 0.72; P < 0.001). In contrast, in gymnosperms, we did not find any significant relationship. However, the sample size was likely too low to obtain robust results (N = 14). We furthermore explored correlations between other wood structural properties (i.e., percentage areas occupied by vessels, VA; parenchyma cells, PATOT; and fibers, FA) and P50. We found that PATOT was significantly related with P50 in angiosperms (Figure 2a; R2 = 0.16; P < 0.001), with more vulnerable species having larger amounts of parenchyma. The assessed relationship comprised data from literature and our own measurements, as we found no significant difference in the parameters of the fitting equation between the different groups of source data (Figure S5b and Supplementary Table S2 available as Supplementary Data at Tree Physiology Online). However, this relationship was not significant in gymnosperms (P > 0.05) (Figure 2a; Table S2 available as Supplementary Data at Tree Physiology Online). Figure 2. Open in new tabDownload slide (a) PATOT against the vulnerability to embolism (P50) for angiosperms in light cyan and gymnosperms in dark purple. The data are from our measurements and from literature. (b) Total amount of structural carbohydrates in the stem (stem NSC) against the vulnerability to embolism (P50) for angiosperm species. The data are collected from literature. Figure 2. Open in new tabDownload slide (a) PATOT against the vulnerability to embolism (P50) for angiosperms in light cyan and gymnosperms in dark purple. The data are from our measurements and from literature. (b) Total amount of structural carbohydrates in the stem (stem NSC) against the vulnerability to embolism (P50) for angiosperm species. The data are collected from literature. For the angiosperms only, the percentage VA did not vary much across species (13.27 ± 5.85; N = 74) (mean ± SD) (Figure 3a, triangles) whereas PATOT and FA showed a highly significant negative relationship (R2 = 0.80; P < 0.001; Figure 3a, circles). Accordingly, we also found a highly significant negative relationship between P50 and FA (Figure 3b; R2 = 0.22; P < 0.001), whereas VA was not related to P50 (P > 0.05). Figure 3. Open in new tabDownload slide (a) FA (light cyan solid circles) and VA (dark cyan triangles) against the PATOT. (b) FA against the vulnerability to embolism (P50). Figure 3. Open in new tabDownload slide (a) FA (light cyan solid circles) and VA (dark cyan triangles) against the PATOT. (b) FA against the vulnerability to embolism (P50). Wood density and % of wood tissues We analyzed the variation in wood structure as a function of WD for the different angiosperm species. We found that FA significantly increased (Figure 4, triangles; R2 = 0.33; P < 0.001) and PATOT significantly decreased with increasing WD (Figure 4, circles; R2 = 0.25; P < 0.001). However, VA was not significantly related to WD (P > 0.05). Figure 4. Open in new tabDownload slide FA (dark cyan triangles) and PATOT (light cyan solid circles) against the WD. Figure 4. Open in new tabDownload slide FA (dark cyan triangles) and PATOT (light cyan solid circles) against the WD. P50 and NSC We assessed the relationship between P50 and total amount of NSC in the stem using data available from literature and found a significant positive relationship (Figure 2b; R2 = 0.09; P < 0.05), which suggests that species more vulnerable to embolism formation have on average a higher amount of NSC stored in wood compartments. Discussion Our results show that xylem vulnerability to embolism formation is significantly related to different wood structural traits, although they singularly explain a minor proportion of the total P50 variability and often are mutually correlated. We found clear differences between the wood compositions in angiosperm vs gymnosperm species. Species in the first functional group present a xylem composed of a rather constant amount of conductive vascular elements, i.e., 10–20% of the total volume. The remaining 80% of xylem volume can largely vary in the relative amount of parenchyma cells and fiber elements, according to a tight negative relationship (Figure 3a), which was found to be the main driver for the variation in WD (Figure 4). Instead, gymnosperms had a relatively fixed and low amount of parenchyma cells (PATOT ~ 5–10% of the total volume). This would suggest that the variation in WD in conifer wood substantially depends on the frequency distribution of tracheid diameters and their cell wall thickness (CWT). Although the number of gymnosperm species was too low to support any significant relationship between WD and CD or CWT, other more detailed analyses are clearly in agreement with this hypothesis (Rosner 2017). In general, species with higher WD were less vulnerable to embolism (more negative P50) (Figure 1a), consistent with earlier studies (e.g., Hacke and Sperry 2001; Jacobsen et al. 2005; Lens et al. 2013; Rosner 2017). However, our anatomical analyses would suggest that the relationship between P50 and WD is functionally different between angiosperms and gymnosperms, where in the former it was driven by the variation in the amount of parenchyma vs fibers, whereas in the latter P50 would seem to be more likely related to the scaling of tracheid number vs diameter. Tracheid diameter was found to scale isometrically with pit aperture (Becker et al. 2003; Lazzarin et al. 2016), an ultrastructural feature of the cell wall supposedly proportional to the susceptibility of torus displacement under tension and thus to the vulnerability to air seeding (Martínez-Cabrera et al. 2009). Moreover, larger conduits with thinner cell walls are less resistant against tension-induced implosion (Hacke et al. 2001). Therefore, conifer species with lower WD usually have larger tracheids and are more vulnerable to embolism formation (less negative P50) (Hacke and Sperry 2001; Larter et al. 2017). Also, for angiosperm vessels a relationship between diameter and P50 has been often found at both interspecific (Hacke et al. 2006) and intraspecific (Nardini et al. 2017) levels, but also among different–sized vessels within the xylem (Jacobsen et al. 2019), consistent with our results and potentially underlining a relationship between pit traits and vessel size, as for gymnosperms. Indeed, previous studies reported that narrower vessels with smaller pit areas are less vulnerable to air seeding (Sperry and Tyree 1988; Tyree and Sperry 1989; Cochard and Tyree 1990; Hacke et al. 2006; Martínez-Cabrera et al. 2009; Christman et al. 2012). In addition, denser (and therefore smaller) cells (Sperry et al. 2008) (cf. Figure S6c available as Supplementary Data at Tree Physiology Online) are thought to be hydraulically safer against losses of xylem conductance because water can more easily bypass embolized conduits (Venturas et al. 2017). Accordingly, angiosperm species with narrower and denser vessels were also those with a lower (i.e., more negative) P50 (Figure 1b and c). We found that gymnosperm species did not vary much in their amount of parenchyma tissue (i.e., PATOT~ 5–10% of a given volume of wood). On the contrary, a significant proportion of the higher %PATOT variability in stem and branches of angiosperms was explained by the species’ vulnerability to embolism formation (P50) (Figure 2a), meaning that more vulnerable angiosperms have a higher amount of parenchyma in the wood. This tissue not only provides a storage compartment for sugars and water to be used upon requirement (Scholz et al. 2011; Spicer 2014; Jupa et al. 2016), but also represents a cost for the plant carbon balance due to its metabolic activity as it is a living tissue. Hence, since vulnerable angiosperm species would frequently operate at conditions favoring embolism formation (Choat et al. 2012), it is intriguing that these species, potentially limited in gas exchange due to periodical reductions in xylem conductance, have developed a large and carbon–expensive wood parenchyma. It is worth mentioning here that in the study of Pratt et al. (2007), roots of angiosperms had more parenchyma and fewer fibers than stems, but even with a higher amount of parenchyma they were more vulnerable to embolism formation. This fact might be explained by the axial increase of vessels’ size and connectivity (Lechthaler et al. 2018), with wider vessels in the roots being more vulnerable to embolism, since embolism vulnerability is related to conduit size (e.g., Brodersen and McElrone 2013). At the same instant, roots are in less need of mechanical stability (i.e., fewer fibers) and this might be the reason that plants invested in the production of more parenchyma cells, and thus a higher storage of sugars, in roots. A first possible explanation for our result is that large NSC reserves stored in the abundant parenchyma during favorable periods help these species to avoid carbon starvation due to stomatal closure during periods of prolonged water shortage. Also, the relationship between PATOT and P50 would be consistent with the hypothesis that parenchyma has a fundamental role in xylem embolism reversal by actively translocating into the embolized conduits the necessary amount of sugars needed to osmotically attract water molecules from the surrounding compartments (Zwieniecki and Holbrook 2009). In this view, abundant parenchyma cells would provide the necessary sugars and energy to trigger the whole refilling process (Secchi and Zwieniecki 2011; Trifilò et al. 2019) in species frequently exposed to conditions favoring embolism formation. Since PATOT was tightly related to the amount of fibers in the wood (Figure 3a), FA and WD were also related to P50. While FA and WD do not really provide a functional explanation for the variation in P50 (Lachenbruch and McCulloh 2014), these results would strongly suggest that these parameters are indirectly related to P50, as more vulnerable species would require a higher amount of parenchyma for carbon storage and/or for efficient embolism reversal. Consistent with this hypothesis, we found that angiosperms more vulnerable to embolism not only had a higher percentage of parenchyma cells in the wood, but also had a higher storage of NSC (Figure 2b). These results agree with a recent study by Plavcova et al. (2016), who found that the amount of parenchyma tissues is a strong determinant of the amount of stored NSC. In conclusion, we found global patterns in the differences in wood structure between angiosperm and gymnosperm species that correlate with their vulnerability to embolism formation (P50). In particular, in gymnosperms the relationship between P50 and WD is likely driven by the scaling between CNo and diameter, and thus CWT. In contrast, in angiosperms, the relative amounts of parenchyma cells and fibers were significantly related to embolism formation. The amount of parenchyma volume in the xylem, which may be involved in the maintenance/repair of plant hydraulic systems, was significantly related to P50. Angiosperm species that were more vulnerable to embolism formation not only had wider and less dense vessels, but also had a higher amount of parenchyma, consistent with hypothesis around embolism reversal mechanisms, where parenchyma and the amount of NSC would play a central role. Acknowledgments We are grateful to Matteo Baiocco for help during literature data collection. Conflict of interest None declared. Authors’ contributions L.D.S. collected and prepared the samples and carried out the measurements. F.P. created the dataset from the literature. 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TI - Vulnerability to xylem embolism correlates to wood parenchyma fraction in angiosperms but not in gymnosperms
JF - Tree Physiology
DO - 10.1093/treephys/tpz068
DA - 2019-10-01
UR - https://www.deepdyve.com/lp/oxford-university-press/vulnerability-to-xylem-embolism-correlates-to-wood-parenchyma-fraction-5aMLRwdLmn
SP - 1675
VL - 39
IS - 10
DP - DeepDyve
ER -