the trade-off between safety and efficiency in hydraulic

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Tree Physiology 31, 865–877doi:10.1093/treephys/tpr076

The trade-off between safety and efficiency in hydraulic architecture in 31 woody species in a karst area

Da-Yong Fan1, Sheng-Lin Jie1,2, Chang-Cheng Liu1,2, Xiang-Ying Zhang1,2, Xin-Wu Xu1, Shou-Ren Zhang1 and Zong-Qiang Xie1,3

1State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, the Chinese Academy of Sciences, Beijing 100093, China; 2Graduate School of the Chinese Academy of Sciences, Beijing 100049, China; 3Corresponding author ([email protected])

Received February 15, 2011; accepted June 15, 2011; published online August 24, 2011; handling Editor Guillermo Goldstein

Karst topography is a special landscape shaped by the dissolution of one or more layers of soluble bedrock, usually carbon-ate rock such as limestone or dolomite. Due to subterranean drainage, overland flow, extraction of water by plants and evapotranspiration, there may be very limited surface water. The hydraulic architecture that plants use to adapt to karst topography is very interesting, but few systematic reports exist. The karst area in southwestern China is unique when com-pared with other karst areas at similar latitudes, because of its abundant precipitation, with rainfall concentrated in the grow-ing season. In theory, resistance to water-stress-induced cavitation via air seeding should be accompanied by decreased pore hydraulic conductivity and stem hydraulic conductivity. However, evidence for such trade-offs across species is ambigu-ous. We measured the hydraulic structure and foliar stable carbon isotope ratios of 31 karst woody plants at three locations in Guizhou Province, China, to evaluate the functional coordination between resistance to cavitation and specific conductivity. We also applied phylogenetically independent contrast (PIC) analysis in situations where the inter-species correlations of functional traits may be biased on the potential similarity of closely related species. The average xylem tension measurement, at which 50% of hydraulic conductivity of the plants was lost (Ψ50), was only −1.27 MPa. Stem Ψ50 was positively associated with specific conductance (Ks) (P < 0.05) and leaf specific conductance (Kl) (P < 0.05). However, the PIC correlation for both relationships was not statistically significant. δ13C was positively related to Kl in both the traditional cross-species correlation analysis and the corresponding PIC correlations (P < 0.05). The Huber value (sapwood area:leaf area ratio) was negatively correlated with Ks in both the traditional cross-species correlation and the corresponding PIC correlations (P < 0.01). The characteristics of hydraulic architecture measured in this study showed that karst plants in China are not highly cavitation-resistant species. This study also supports the idea that there may not be an evolutionary trade-off between resistance to cavitation and specific conductivity in woody plants. Whole-plant hydraulic adjustment may decouple the trade-off relation-ship between safety and efficiency at the branch level.

Keywords: correlated evolution, foliar stable carbon isotope ratio, hydraulic architecture, karst plants, karst topography.

Introduction

‘Hydraulic failure’ and associated other downstream physiologi-cal processes have been regarded as critical for woody plants unable to cope with the challenge of supplying enough water to their leaves under restrictions they experience at different time scales (Maseda and Fernández 2006, McDowell et al. 2008).

Negative tension as a result of low water potentials of the intact water column could make the entire water transport pathway susceptible to cavitation, due to the seeding of air bubbles through pit membranes and into the water column under stress conditions. Embolized xylem cells subsequently reduced hydraulic conductivity and greatly retarded photosynthesis and

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growth. A more severe catastrophic hydraulic failure will lead to the death of plants in extreme cases in the absence of feedback of limiting transpiration.

Although many reports have shown a functional coordination between hydraulic structure and other functional traits among and within species (Brodribb et al. 2002, Meinzer 2002, Maherali et al. 2006), our knowledge of the association between variation in cavitation resistance (safety) and water transport capacity (efficiency) among plants is ambiguous. Some studies showed a trade-off of varying degrees of signifi-cance and others showed no relationship at all (Sperry and Saliendra 1994, Tyree et al. 1994, Wagner et al. 1998, Pockman and Sperry 2000, Martínez-Vilalta et al. 2002, Maherali et al. 2006, Sperry et al. 2008, Meinzer et al. 2010). Furthermore, if data were collected on a larger scale across many vegetation types (Maherali et al. 2004), or if phylogenetically independent contrast (PIC) analysis was applied (Maherali et al. 2006), there might be a weak or even insignificant evolutionary trade-off between resistance to cavitation and specific conductivity in woody plants.

Comprehensive investigation of such trade-offs across a broad range of taxonomic groups can be problematical, pri-marily due to both a lack of control of data gathered across seasons and years (Jacobsen et al. 2007) and the utilization of different methods (van Ieperen 2007). Phylogenetically inde-pendent contrast analysis within a few woody species (<10) may also suffer from statistical ‘funnel effects’ described previ-ously (Wright et al. 2005). Furthermore, according to the Ohm’s law analogy, the xylem tension range determined the relationship between flow resistance and flow rate (Tyree and Ewers 1991). Therefore, only under a similar xylem tension range there may be functional coordination between safety and efficiency. Hence, although Maherali et al. (2004) previ-ously studied the adaptive significance of variation in cavitation resistance and water transport capacity across a broad range of taxonomic groups, we believe it is necessary to investigate this issue in other specialized vegetation with a similar xylem tension range in different climate zones across the world for a more comprehensive understanding of the role of such trade-offs in the adaptation of woody plants to the local environment (Sperry et al. 2008).

Karst topography is a special landscape shaped by the dis-solution of one or more layers of soluble bedrock, usually car-bonate rock such as limestone or dolomite. Subterranean drainage, overland flow, plant extraction and evapotranspira-tion lead to low levels of water available to plants in the shallow soils in many karst landscapes. The hydraulic architecture that plants use to adapt to karst topography is very interesting, but few systematic reports exist. The few existing studies focusing on hydraulic structure, which looked at several woody species in karst topography in the Mediterranean area and the Edwards Plateau of central Texas, have shown that most of the species

studied are highly cavitation-resistant (Tognetti et al. 1998, Martínez-Vilalta et al. 2002, Maherali et al. 2004, McElrone et al. 2004). However, this may not be conclusive, because a diversity of karst environments and vegetation are distributed worldwide, such as Madagascar’s dry deciduous forest (Fowler et al. 1989), Vietnam’s tropical forest (Tuyet 2001) and Slovakia’s spruce forest (Oszlanyi 1997).

The karst area in southwestern China is unique when com-pared with other karst areas at similar latitudes, because of its abundant precipitation, with rainfall concentrated in the growing season (Wu et al. 2003), mainly due to the rise in elevation of the Qinghai-Tibet Plateau. Meteorological data show that two consecutive rainfall events normally occur 7–10 days apart dur-ing the growing season (Li et al. 2008). Eco-physiological field investigations report that woody plants in this area experienced similar midday leaf water potentials during the growing season (Yu et al. 2002) (C.C. Liu, unpublished data), suggesting a simi-lar terminal xylem tension control across a variety of taxa. All these characteristics make karst areas in China an ideal plat-form on which to investigate the issues mentioned above. Furthermore, investigation of hydraulic acclimation in this area is of practical importance in assessing the hydrological imbal-ance, as well as associated land degradation issues due to cur-rent over-exploitation by intensive agro-economic activities.

In this study, first we measured the hydraulic architecture of 31 karst woody species at three locations in Guizhou Province, China, and conducted a comparison based on the global data-base of hydraulic architecture of woody plants (Maherali et al. 2004). Second, by using information on phylogenetic relation-ships among seed plants, we calculated PICs to evaluate the strength of the relationship between vulnerability to xylem cav-itation and xylem transport capacity in woody species of karst habitats in China. We focus on two specific questions: (i) what are the characteristics of hydraulic architecture of woody spe-cies of karst habitats in China? (ii) is there a significant coordi-nation between the evolutionary aspects of vulnerability to xylem cavitation and xylem transport capacity among woody species in karst habitats?

Materials and methods

Study site and plant materials

The study was conducted at three sites in Guizhou Province, southwest China. These sites, the Huajiang site (HJ, 25°42′N, 105°35′E), the Puding site (PD, 26°15′N, 105°44′E) and the Libo site (LB, 25°26′N, 108°05′E), are located in the south-western, western and southern parts of Guizhou Province, at altitudes of ~900, 1200 and 800 m, respectively.

The HJ site has a warm temperate climate, a mean annual temperature of 18.4 °C (Wu et al. 2003) and a mean annual precipitation (MAP) of 1100 mm, of which 83% falls during the

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growing season (May–October). This site is characterized by a secondary deciduous forest on barren soils with predominantly precipitous slopes.

The PD site has a humid monsoon climate, a mean annual temperature of 15.1 °C (Wu et al. 2003) and an MAP of 1398 mm, most of which falls during the growing season, simi-lar to the HJ site. This site has evergreen and deciduous broad-leaved species growing on lime yellow soil.

The Libo region has a warm temperate climate, a mean annual temperature of 18.3 °C and an MAP of 1320 mm. The site is characterized by its large area of well-conserved primary evergreen and deciduous mixed forest. The soil, mainly com-posed of black lime soil, has a thin soil layer and exposed car-bonate rocks at the floor surface. This region is the least disturbed by human activities of the three study sites, as it has been well protected as a national nature reserve since 1987.

Hydraulic conductance and vulnerability to xylem cavitation

We sampled 31 common canopy and sub-canopy woody angiosperm species in 20 plant families (Table 1). We sampled saplings or young trees 2–4 m tall that occurred either in can-opy gaps created by natural disturbance or near clearings associated with forest roads to ensure that all samples experi-enced similar light environments. We collected four to nine sun-exposed shoots 0.4–0.7 m long from each species in late July and early August 2007. Stem samples were typically 2–4 years old, based on cross-sectional growth ring counts. Samples were collected in the early morning, immediately wrapped in moist paper towels and sealed in plastic bags to minimize dehydration. In the laboratory, all stem samples were re-cut to 17–19 cm length under water and the cut ends were trimmed with a razor blade. Information on vessel lengths for

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Table 1. Species characteristics of the 31 tree species included in this study.

Species (abbreviation) Family Wood type1 Leaf phenology

Location

Sapium sebiferum (L.) Roxb. (Ss) Euphorbiaceae DP (400–980) D HJMelia azedarach L. (Ma) Meliaceae RP (223–462) D HJMallotus philippensis (Lam.) Muell. Arg. Euphorbiaceae DP (320–700) E HJ, LBVernicia fordii (Hemsl.) Airy Shaw Euphorbiaceae RP (454–964) D HJ, LBFicus benguetensis Merrill (Fb) Moraceae DP (240–520) D HJAlchornea davidii Pampanini (Ad) Euphorbiaceae — D HJMallotus barbatus (Wall.) Muell. Arg. Euphorbiaceae DP (280–430) D HJFlemingia philippinensis Merr. & Rolfe (Fp) Papilionoideae — D HJSolanum verbascifolium L. (Sv) Solanaceae DP D HJBrucea javanica (L.) Merrill (Bj) Simaroubaceae — D HJRhamnella franguloides (Max.) Web. (Rf) Rhamnaceae DP (260) D HJMallotus japonicus (L. f.) Müll. var. floccosus (Mj) Euphorbiaceae — D HJBroussonetia papyifera (Linn.) L’Hert. ex Vent. Moraceae sRP (140–350) D HJPicrasma quassioides (D. Don) Bennett (Pq) Simaroubaceae RP (150–250) D HJAlangium chinense (Lour.) Harms Alangiaceae RP (254–733) D HJ, LBPteroceltis tatarinowii Max. (Pt) Ulmaceae DP (610–1770) D LBLiquidambar formosana Hance (Lf) Hamamelidaceae DP (669–1752) D LBPlatycarya longipes Wu Juglandaceae RP (159–541) D LB, PDLindera communis Hemsl. Lauraceae DP (470) E LB, PDMacaranga tanarius (L.) Muell. (Mt) Euphorbiaceae DP (500–1240) E LBPittosporum xylocarpum Hu & F. T. Wang (Px) Pittosporaceae DP (310–700) E LBMaackia hupehensis Takeda in Sargent (Mh) Papilionoideae RP (120–280) D LBItea chinensis Hook. & Arn. (Ic) Saxifragaceae — E PDCarpinus pubescens Burkill (Cp) Betulaceae DP (600–1250) D PDStachyurus obovatus (Rehder) Handel-Mazzetti, (So) Stachyuraceae — E PDDaphniphyllum oldhami (Hemsl.) Rosenth. (Do) Daphniphyllaceae DP (650–2000) E PDQuercus aliena Blume var. acutiserrata spp. (Qa) Fagaceae RP (440–660) D PDLigustrum lucidum W. T. Aiton (Ll) Oleaceae sRP (400–1520) E PDCeltis sinensis Persoon (Cs) Ulmaceae RP (107–320) D PDIlex chinensis Sims Aquifoliaceae DP (600–1200) E PDLithocarpus glaber (Thunb.) Nakai (Lg) Fagaceae DP (290–630) E PD

The polygenetic relationship among studied species is shown in Figure 1. D, winter deciduous; E, evergreen; HJ, Huajiang site; PD, Puding site; LB, Libo site. DP, diffuse-porous; RP, ring-porous; sRP, semi-ring-porous; number in parentheses: range of vessel length variation in micrometers.1Data were compiled from Cheng, J.Q., Yang, J.J. and Liu, P. (eds.) 1992. Woods in China. Chinese Forestry Publishing House, ISBN 7-5038-0392-4, P820. – indicates no data available.


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our species was incomplete (Table 1), so some vessels of investigated species may have been open.

Hydraulic conductance (Kh) was measured as described by Sperry and Saliendra (1994) in an air-conditioned laboratory (26 °C). Segments were cleared of air emboli by perfusing them at high pressure with filtered (0.2 µm) distilled water for 30 min at 110 kPa. Water conducted through the seg-ments at ~8 kPa of hydrostatic pressure was collected in a vial on a 0.0001 g balance (Satorius, Germany) connected to a computer to record efflux weight changes every 30 s. Measurements were not initiated until after ~2 min, when the flow rates stabilized. Hydraulic conductivity (Kh; kg m MPa−1 s−1) was expressed as the flow rate divided by the pressure gradient. Specific conductivity (Ks; kg m−1 MPa−1 s−1) was cal-culated by dividing Kh by the segment’s sapwood cross- sectional area. Stem sapwood cross-sectional area was determined by measuring the maximum and minimum diameter of the acropetal end of each branch segment using a digital micrometer. Pith area was subtracted from gross cross- sectional area after measuring its dimension under a dissect-ing microscope equipped with a stage micrometer. Leaf specific conductivity (Kl; kg m−1 MPa−1 s−1) was calculated by dividing Kh by the leaf area distal to the measured sample. Sampled leaves were first scanned with a scanner (Epson, Japan), and then each leaf sample’s area was calculated using WinFOLIA software (Regent, Canada). The Huber value was calculated as the ratio of wood cross section per unit leaf area attached.

The vulnerability of xylem to cavitation was characterized using a vulnerability curve constructed by the method described by Sperry and Saliendra (1994). After measuring the maximum hydraulic conductivity (Kh), stems were inserted and sealed into a collar with both ends protruding. Air was then injected into the collar to the desired air injection pressure, which was maintained for 15 min. Two shallow (0.5 mm deep) notches were cut into opposite sides of the xylem ~0.05 m apart at the midpoint of the segment. These cuts ensured entry of air into the xylem inside the pressure chamber. The air injection pres-sure used is equivalent to the negative value of water potential in the xylem (Cochard et al. 1992, Sperry and Saliendra 1994). The pressure in the collar was then slowly released down to 0.1 MPa and hydraulic conductivity was re-measured. This pro-cedure was repeated to progressively higher pressures in steps of 0.5 MPa until >90% loss in conductivity was reached. The percentage loss of conductivity (PLC) following each pressur-ization of the chamber was calculated as PLC = 100 × ((Kh–Khi)/Kh), where Khi is the hydraulic conductivity of the sample mea-sured after each chamber pressurization. Vulnerability curves were fitted with an exponential sigmoidal equation (Pammenter and Vander 1998):

= + × ΨPLC 100 / (1 exp( ( – ))a b (1)

where Ψ is the negative of the injection pressure, a is a measure of the steepness of the response of conductivity to injection pressure or tension (curve slope) and b represents the Ψ at which a 50% loss in conductivity occurs (Ψ50 or curve displacement along the x-axis). Coefficients a and b were estimated using the non-linear regression procedure in SPSS 10.0 (SPSS, Evanston, IL, USA).

Foliar carbon isotope discrimination

After measurement of leaf area, leaves distal to the measured samples were oven-dried at 70 °C for 48 h and finely ground. Specific leaf area (SLA) was calculated by dividing leaf size by leaf mass. A sub-sample of 1 mg of powdered leaf material was combusted and analyzed for 13C composition using an iso-tope ratio mass spectrometer (Finnigan MAT Delta V advan-tage, ThermoFinnigan, USA). Leaf carbon isotope composition (δ13C) was calculated as

sa st13

stC 1000

R RR−δ = × (2)

where Rsa and Rst are the 13C/12C ratios in the sample and in the conventional Pee Dee Belemnite standard, respectively.

Since only sunlit leaves were sampled, atmospheric CO2 concentration (Ca) and carbon isotope composition (δ13Ca) at close sites can be considered as constant (Buchmann et al. 1997). In fact, we sampled atmospheric CO2 at these three sites and found no significant difference. We corrected the δ13C for elevation by a method based on Hultine and Marshall (2000) and Marshall and Zhang (1994) to obtain rigorous data. All δ13C data were normalized to the elevation of 800 m.

Phylogenetically independent contrasts and statistical analyses

As the cross-species correlations may be biased by a lack of statistical independence between data points of closely related species with shared evolutionary history, PICs were applied in this study. We first constructed the phylogenies for our spe-cies with the program Phylomatic (Webb et al. 2008), using a maximally resolved seed plant tree (Phylomatic tree version: R20040402) based on the Angiosperm Phylogeny Group supertree (Hilu et al. 2003). The Phylomatic program, how-ever, was unable to fully resolve the trees to the species level, resulting in four species-level polytomies within the phylogeny, which could theoretically create >2000 fully resolved trees.

As a fully bifurcated tree is the premise for the calculation of independent contrasts, we found several papers (Chase et al. 1993, Wurdack et al. 2005, Tokuoka 2007) to resolve these polytomies to reduce the number of resolved trees. We were unable to find support for resolution below the level of genus Mallotus, resulting in one polytomy within the phylogeny. Resolving it to create fully bifurcated trees resulted in three possible trees. Because we combined several trees to create

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our final trees, our phylogenies lacked branch length informa-tion; therefore, all analyses were run assuming equal branch lengths. This is a conservative approach that minimizes the Type I error rate (Ackerly 2000).

Phylogenetically independent contrasts were calculated to test for patterns of correlated evolutionary change between traits (Felsentein 1985) using COMPARE, version 4.6b (Martins 2004). Contrasts were calculated for all three fully resolved trees. For the five species co-occurring at two sites, mean values were used in the analyses. Phylogenetically independent contrast Pearson correlation analyses between traits were con-ducted through the point of coordinates (0, 0), because of the arbitrary sign of an independent contrast. Because the PIC correlations calculated over the three alternate phylogenies were similar, only the PIC results for phylogeny in Figure 1 are presented in this study.

Analysis of variance was applied to test the difference among sites and between leaf phenologies separately. Pearson corre-lation analysis was conducted among investigated traits. For the cross-species correlation analysis, all data were log10-transformed prior to analysis, because previously described non-linear relationships exist between some trait sets (Pockman and Sperry 2000, Martínez-Vilalta et al. 2002, McElrone et al. 2004). To facilitate log transformation and analysis, Ψ50 and δ13C data were converted from negative to positive values.

Results

There were wide variations in hydraulic architecture across investigated species (Table 2; Figure 2). Stachyurus obovatus, an evergreen species at the PD site, was the most resistant species to xylem cavitation with a Ψ50 of −4.31 MPa. This was about eightfold more negative than the species most vulnera-ble to xylem cavitation, Broussonetia papyrifera (L.) L’Hér. ex Vent., a deciduous-leaved species at HJ site (Figure 2). The mean value of resistance to xylem cavitation of the 31 studied woody species was only −1.27 MPa (Table 2). Similarly, Ks and Kl also showed wide inter-specific variations. For example, Ks ranged from 0.29 of Ilex chinensis Sims, an evergreen species at the PD site, to 7.52 kg m−1 MPa−1 s−1 of Alangium chinense (Loureiro) Harms, a deciduous species at HJ site. In addition, species with low stem Ψ50 also had low hydraulic conductance, and vice versa (Table 2).

In the three sites, hydraulic architecture and foliar carbon iso-tope discrimination were significantly different between the two types of leaf phenology (Table 3). Deciduous woody species displayed higher Ks, Kl and Ψ50, a less negative δ13C, higher SLA and lower Huber value than evergreen woody species. There was no significant difference in hydraulic architecture and leaf carbon isotope discrimination between the HJ and LB sites. However, both sites contrasted significantly with the PD site. This might be due to the different leaf phenology of the investi-gated species, as the species studied at the HJ site included 14 deciduous (D) and one evergreen (E) species (Table 1). The three sites had D and E species as follows: HJ (14D/1E), LB (6D/4E) and PD (4D/7E). No significant difference in Ks, Kl, SLA and Huber value was found among the three sites for the decid-uous species. Within the evergreen species, there was no sig-nificant difference in hydraulic structure and δ13C between the PD and LB sites (data not shown). The HJ site was excluded, as it had only one evergreen species.

Three species co-occurred at the LB and HJ sites and two species co-occurred at the LB and PD sites. Alangium chinense, Mallotus philippensis (Lam.) Müll. and Vernicia fordii (Hemsley) Airy Shaw at the HJ site had significantly higher δ13C than that at the LB site; meanwhile, the former two species had higher Ks ( P < 0.05) and the latter one had lower Ψ50 (P < 0.05) at the HJ site (Figure 3). There were no significant differences in hydraulic structure and δ13C of Platycarya longipes Wu and Lindera communis Hemsley between the LB and PD sites, except that Platycarya longipes had higher Ks ( P < 0.001) at the LB site (Figure 3).

In the cross-species analysis, our results show that resistance to water-stress-induced xylem cavitation (Ψ50) increased sig-nificantly with decreasing Ks (Figure 4, P = 0.042) and Kl (Figure 4, P = 0.039). However, these relationships were not supported by the PIC correlation (Figure 4). Only Kl increased with increasing δ13C in the cross-species comparison and PICs (Figure 5). Nevertheless, there was no association between


Figure 1. One of three alternative phylogenetic trees showing the rela-tionships among the species used in this study. It was first constructed using the program Phylomatic, and then modified manually based on the literature, and re-drawn using TreeViewX (version 5.0). The unre-solved polytomy is shown in the inset.


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other hydraulic traits and δ13C across all taxa in PICs (Figure 5). The cross-species relationship between Ψ50 and δ13C was also insignificant in PIC analysis.

Specific leaf area had a strong positive correlation with hydraulic conductance (Ks and Kl) and a negative association with the Huber value in both the raw values and PIC co-rela-tionship analyses (Figure 5, Table 4), suggesting adaptive association among these functional traits. In contrast, SLA was not associated with Ψ50 in the PIC co-relationship analysis (Figure 5, Table 4). The Huber value was negatively correlated with hydraulic conductance (Ks and Kl), but only showed a significant positive correlation with Ks in the PIC co-relationship analysis.

Discussion

Karst plants in China are not highly cavitation-resistant species

The average value of Ψ50 of 31 karst woody species in Guizhou Province, China, was only −1.27 MPa. This value can be com-pared with Ψ50 values of other ecosystem types. Our species Ψ50 values fall between those of tropical rain forest (≈− 0.77 MPa) and tropical dry forest (≈− 2.42 MPa), and show that the 31 species in this study are much more vulnerable to xylem cavitation than Mediterranean (≈− 5.31 MPa) or desert vegetation (≈− 4.48 MPa) (Maherali et al. 2004). Since high cavitation resistance is a key component of drought tolerance

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Table 2. Summary of stem Ks (specific conductivity, kg m−1 MPa−1 s−1), Kl (leaf specific conductivity, kg m−1 MPa−1 s−1), Ψ50 (MPa), SLA (g cm−2) and leaf isotope discrimination δ13C (‰) for each species at the three sites in the study.

Species1 Ks Kl (×10−4) SLA Ψ50 δ13C2 (‰) Location

Ss 4.58 ± 0.62 4.52 ± 0.82 209.35 ± 56.41 −0.65 ± 0.08 −27.72 ± 0.24 HJMa 6.08 ± 1.51 8.09 ± 3.49 219.49 ± 16.06 −1.11 ± 0.23 −26.92 ± 0.45 HJMp 3.32 ± 0.76 2.86 ± 0.73 118.63 ± 8.96 −0.68 ± 0.10 −27.62 ± 0.44 HJMp 1.22 ± 0.37 2.00 ± 0.71 103.10 ± 5.75 −0.64 ± 0.12 −29.14 ± 0.07 LBVf 3.30 ± 0.79 4.10 ± 1.03 116.79 ± 13.70 −1.23 ± 0.22 −25.07 ± 0.02 HJVf 4.82 ± 0.66 5.37 ± 0.74 113.02 ± 1.95 −0.73 ± 0.12 −26.76 ± 0.16 LBFb 1.64 ± 0.85 2.17 ± 1.27 123.30 ± 5.84 −0.66 ± 0.09 −26.57 ± 0.52 HJAd 3.25 ± .54 2.51 ± 1.18 135.03 ± 3.37 −0.55 ± 0.13 −27.34 ± 0.12 HJMb 7.06 ± .50 5.70 ± 2.10 188.74 ± 7.92 −1.67 ± 0.40 −26.83 ± 0.26 HJFp 2.52 ± 0.21 4.35 ± 0.24 182.56 ± 10.12 −0.91 ± 0.13 −27.55 ± 0.15 HJSv 3.12 ± 0.38 4.68 ± 0.27 147.37 ± 8.85 −0.70 ± 0.04 −28.66 ± 0.93 HJBj 2.67 ± 0.35 2.14 ± 0.31 186.43 ± 11.90 −1.21 ± 0.16 −28.29 ± 0.28 HJRf 4.93 ± 1.70 6.32 ± 1.08 90.98 ± 4.44 −1.64 ± 0.56 −25.89 ± 1.18 HJMj 2.52 ± 0.22 3.53 ± 0.63 113.17 ± 4.27 −1.12 ± 0.12 −27.21 ± 0.15 HJBp 3.36 ± 0.94 7.85 ± 3.72 141.83 ± 8.36 −0.51 ± 0.15 −27.89 ± 0.56 HJPq 3.42 ± 0.09 5.60 ± 0.49 108.00 ± 7.56 −0.93 ± 0.13 −25.71 ± 0.71 HJAc 7.52 ± 1.20 6.06 ± 1.13 122.35 ± 2.64 −1.08 ± 0.23 −27.12 ± 0.41 HJAc 4.58 ± 0.49 5.02 ± 0.66 122.61 ± 7.72 −0.81 ± 0.20 −28.52 ± 0.26 LBPt 3.60 ± 0.21 5.03 ± 0.80 123.54 ± 7.55 −0.96 ± 0.05 −26.98 ± 0.26 LBLf 0.31 ± 0.12 0.56 ± 0.17 106.75 ± 12.56 −1.26 ± 0.29 −28.12 ± 0.45 LBPl 5.68 ± 1.66 4.04 ± 1.32 150.14 ± 25.22 −1.06 ± 0.33 −29.50 ± 0.75 LBPl 2.73 ± 0.33 2.46 ± 0.55 155.90 ± 27.00 −1.50 ± 0.04 −28.39 ± 0.33 PDLc 0.53 ± 0.11 0.77 ± 0.23 107.19 ± 6.82 −0.92 ± 0.14 −29.97 ± 0.46 LBLc 0.31 ± 0.06 0.51 ± 0.21 130.65 ± 6.32 −0.85 ± 0.12 −30.23 ± 0.33 PDMt 2.83 ± 0.50 2.43 ± 0.47 136.42 ± 6.47 −0.63 ± 0.09 −28.51 ± 0.17 LBPx 1.78 ± 0.17 1.72 ± 0.34 98.99 ± 2.44 −1.58 ± 0.15 −29.63 ± 0.07 LBMh 4.62 ± 0.58 6.30 ± 3.12 145.69 ± 2.95 −1.40 ± 0.17 −29.81 ± 0.28 LBIc 0.45 ± 0.03 1.40 ± 0.49 85.03 ± 4.99 −2.54 ± 0.26 −27.26 ± 0.13 PDCp 2.70 ± 0.77 2.68 ± 0.88 129.24 ± 26.98 −1.39 ± 0.15 −27.38 ± 0.44 PDSo 0.55 ± 0.10 0.86 ± 0.19 100.45 ± 5.45 −4.31 ± 0.39 −28.68 ± 0.65 PDDo 0.46 ± 0.17 0.91 ± 0.32 82.62 ± 10.66 −0.62 ± 0.08 −27.92 ± 1.00 PDQa 6.30 ± 2.44 6.26 ± 1.91 155.44 ± 30.82 −2.09 ± 1.03 −28.41 ± 0.16 PDLl 1.39 ± 0.25 1.44 ± 0.19 119.05 ± 12.51 −3.67 ± 0.60 −29.79 ± 0.19 PDCs 6.89 ± 1.48 8.77 ± 1.50 165.54 ± 15.42 −0.81 ± 0.16 −28.39 ± 0.90 PDIch 0.29 ± 0.11 0.55 ± 0.15 79.84 ± 7.43 −2.84 ± 0.45 −28.22 ± 0.66 PDLg 1.51 ± 0.79 1.70 ± 0.53 95.39 ± 19.23 −1.57 ± 0.32 −27.41 ± 0.67 PDMean 3.21 ± 0.45 3.52 ± 0.24 135.77 ± 5.56 −1.27 ± 0.09 −27.92 ± 0.20

1Abbreviations indicate genus and species, as listed in Table 1.2Data were normalized to the elevation of 800 m, according to the method of Hultine and Marshall (2000) and Marshall and Zhang (1994).


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(Maherali et al. 2004, but see Jacobsen et al. 2008), the pres-ent study does not support the idea that karst plants are long-term drought-tolerant species. In fact, in 2010 we observed widespread mortality of woody species in study areas, due to a lack of rainfall for 6 weeks in the 2009 growing season (C.C. Liu, field observation).

Meteorological data showed that the annual rainfall in Guizhou Province ranged between 1100 and 1500 mm, close to that reported for rain forest in Xishuangbanna in southern China (Qu et al. 2001, Tan et al. 2008). Critically, >80% of annual rainfall occurred in the growing season, from April to October (Wu et al. 2003), suggesting the lack of a high water deficit for local vegetation during the growing season. Since MAP is the main environmental stimulus that determines Ψ50 (Maherali et al. 2004), we hypothesized that the unique abundant rainfall in summer in this karst area of China, combined with other biologi-cal characteristics, such as the deep root system of woody karst plants (Jackson et al. 1999, Bleby et al. 2010), will alleviate the

plant’s water deficit caused by the very limited surface soil water capacity of this karst topography. This may be one reason why well-developed primary and secondary evergreen and deciduous forests occur in this region, compared with arid veg-etation in other karst areas at similar latitudes globally.

A site’s effect on the hydraulic architecture of the investi-gated species was partially attributed to the different leaf phe-nology composition of these species. Evergreen-leaved species had developed more resistance to xylem cavitation and lower hydraulic conductance when compared with co-occurring deciduous species (Table 3), in agreement with previous reports (Choat et al. 2004, Chen et al. 2009). Higher hydraulic conductance and lower water transport safety of deciduous species might guarantee sufficient acquisition of water when water is abundant during the growing season, and reflected the balance between carbon gain and water transport capacity through stomatal regulation in favor of fast growth closely associated with a higher photosynthetic rate (Santiago et al.


Figure 2. Percentage loss in hydraulic conductivity as a function of pressure for stems of 31 karst woody species in this study. Curves were fitted using all data; only means (±1 SE) are presented.


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872 Fan et al.

Figure 3. Specific conductivity (Ks), xylem tension at 50% cavitation (Ψ50) and leaf isotope discrimination (δ13C) for five co-occurring woody species at different sites in this study. Means followed by the same letter were not statistically different at P < 0.05.

Table 3. Analysis of variance performed to test the site and leaf phenology effect on hydraulic architecture and leaf isotope discrimination.

Source of variance

Ks Kl (×10−4) SLA Ψ50 δ13C Huber value (×10−4)

Site P = 0.003 P = 0.003 P = 0.003 P < 0.001 P < 0.001 P = 0.009HJ 3.94 ± 0.30a 4.36 ± 0.35a 155.68 ± 10.5a −0.95 ± 0.06a −27.23 ± 0.16a 1.10 ± 0.06a

LB 3.06 ± 0.38a 3.10 ± 0.36a 120.50 ± 4.06a −0.97 ± 0.08a −28.14 ± 0.22b 1.18 ± 0.08a

PD 2.12 ± 0.48b 2.50 ± 0.51b 116.94 ± 6.63b −2.11 ± 0.24b −28.63 ± 0.24b 1.52 ± 0.16b

Leaf phenology P < 0.001 P < 0.001 P = 0.013 P < 0.001 P = 0.005 P < 0.001D 4.18 ± 0.26 4.53 ± 0.29 150.60 ± 7.68 −1.05 ± 0.06 −27.60 ± 0.18 1.13 ± 0.05E 1.25 ± 0.18 1.48 ± 0.17 106.48 ± 3.51 −1.70 ± 0.22 −28.35 ± 0.25 1.45 ± 0.08

D, winter deciduous; E, evergreen. Ks, stem specific conductivity (kg m−1 MPa−1 s−1); Kl (leaf specific conductivity, kg m−1 MPa−1 s−1); Ψ50, xylem tension at 50% cavitation (MPa); SLA (g cm−2); δ13C, leaf isotope discrimination (‰); Huber value, the ratio of wood cross-section invested per unit leaf area attached. Means followed by the same letter were not statistically different at P < 0.05.


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2004, Chen et al. 2009). During droughts or winter, deciduous species could avoid excessive transpiration by shedding leaves, and so might experience weaker selection pressure for increased resistance to water-stress-induced cavitation (Prior and Eamus 2000, Maherali et al. 2004).

Looking more closely at the differences in hydraulic struc-ture of co-occurring species at the three sites, species at the HJ site tended to have more resistance to xylem cavitation, lower water use efficiency (indicated by higher δ13C) and higher hydraulic conductance than the LB site (Figure 3). The HJ site has the most historic human disturbance of the three sites studied (Li et al. 2008). At any site, serious human distur-bance will increase soil erosion and correspondingly decrease soil water retention capacity, thus increasing the water trans-port safety of local plants. It remains to be explained why HJ species inherited a higher δ13C and a higher hydraulic conduc-tance than LB species, although a subsequent instantaneous water use efficiency measurement confirmed the tendency (S.R. Zhang, unpublished data).

The trade-off between vulnerability to xylem cavitation and xylem transport capacity

Previous studies and our investigation of the daily leaf minimum water potential (Ψmin) have shown that woody species had Ψmin values of −1.51 ± 0.04 MPa at the PD site (C.C. Liu, unpublished data) and −1.43 ± 0.12 MPa at the LB site (Yu et al. 2002), sug-gesting that a relatively similar daily xylem tension range was experienced by the species investigated in this study. Based on this, and while taking phylogeny into account, we investigated the trade-off between hydraulic safety and efficiency among 31 karst woody species in China, with the same method and simi-lar xylem tension range during the same growing season.

On the surface, the traditional cross-species correlation r was significant for the trade-off between hydraulic safety and effi-ciency in the present study, confirming previous reports (Pockman and Sperry 2000, Martínez-Vilalta et al. 2002) in other ecosystems, and the investigation of the trade-off rela-tionship between efficiency and vulnerability to cavitation across stem, shallow roots and deep roots of two woody karst species in the Edwards Plateau of central Texas (McElrone et al. 2004). However, when phylogenetic information was included using PICs, the correlation was weakened to an insignificant level, fur-ther supporting the idea that there may not be an evolutionary trade-off between resistance to cavitation and specific conduc-tivity in woody plants (Maherali et al. 2004, 2006).

The absence of an evolutionary correlation between stem Ψ50 and Ks among woody angiosperm species in karst ecosystems may be attributable to differences in other xylem traits across sampled taxonomic species, such as vessel conductivity com-pensation by length (Sperry and Hacke 2004), the embolus refilling process (Bucci et al. 2003) and mitigation of tension fluctuation by xylem capacitance (Sperry et al. 2007, Meinzer et al. 2009). Plants can develop alternative functional designs with different hydraulic trait combinations, leading to approxi-mately equivalent fitness in a specific habitat (Jacobsen et al. 2008, Meinzer et al. 2010). For example, in the present study, the sapwood area to leaf area ratio (As:Al, Huber value) was negatively associated with Ks if PICs were applied (Table 4), sug-gesting adaptive significance between the stem water transport capacity and the plant’s architectural adjustment (Maherali and DeLucia 2001). Given that the canopy conductivity is propor-tional to the product of As:Al, the water potential gradient, Ks, and the inverse of tree height (Schäfer et al. 2000), an increase of As:Al and a decrease of Ks under a similar xylem tension range and tree height may result in similar canopy conductivities across the studied species. On the other hand, adjustments of As:Al did not correspond to changes in vulnerability to cavitation in stems (Table 4, PIC coefficient). The most likely explanation for this observation is that mean conduit diameter (proportional to )SA (Martínez-Vilalta et al. 2002) and the size of the largest pit pore (inversely proportional to Ψ50) in a conduit did not hold a con-stant relationship across species (Martínez-Vilalta et al. 2002,


Figure 4. Specific conductivity (Ks) and leaf specific conductivity (Kl) as a function of xylem tension at 50% cavitation (Ψ50) for 31 woody species in the karst area in this study. Phylogenetically independent contrast (PIC) plots and correlation coefficients are shown in the inset in each subfigure. Note that Ψ50 was converted to positive values for log10 transformation. Therefore, positive correlations were represented by negative correlation coefficients. *P < 0.05, ns is non-significant (P > 0.05).


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Table 4. Magnitude and statistical significance of Pearson correlations and PIC data sets comprising 31 woody species in this study.

Traits of contrast Ks Kl (×10−4) SLA Ψ50 δ13C Huber (×10−4)

Ks 1Kl 0.939**

0.907** (PICs)

1

SLA 0.665**0.522**

0.597**0.403*

1

Ψ50 −0.315*0.175

−0.322*−0.191

−0.310*−0.150

1

δ13C −0.2780.080

−0.373*−0.368*

0.0490.155

0.175−0.062

1

Huber −0.617** −0.403* −0.592** 0.147 −0.165 1−0.450** −0.099 −0.501** −0.003 −0.091

Value in the lower row in each cell: Pearson correlation coefficient based on PICs. Ψ50 and δ13C were converted to positive values for log10 transformation. Therefore, positive correlations were represented by negative correlation coefficients.*P < 0.05, **P < 0.01.

Figure 5. Specific conductivity (Ks), leaf specific conductivity (Kl) and xylem tension at 50% cavitation (Ψ50) as a function of leaf isotope discrimi-nation (δ13C) and specific leaf area (SLA) for 31 woody species in this study. Phylogenetically independent contrast (PIC) plots and correlation coefficients are shown in the inset in each subfigure. Note that Ψ50 was converted to positive values for log10 transformation. Therefore, positive correlations were represented by negative correlation coefficients. **P < 0.01, *P < 0.05, ns is non-significant (P > 0.05).


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Jacobsen et al. 2007). Therefore, whole-plant hydraulic adjust-ment may obscure the trade-off relationship between safety and efficiency at the organismal level, as discussed by Sperry et al. (2008) and Meinzer et al. (2010).

The maximum stomatal conductance measured at one point in time has been seen as one of the critical components of xylem tension control, and has been shown to have close physi-ological coordination with xylem structure (Sobrado 1993, Choat et al. 2004). However, xylem architecture is almost entirely determined by integrative long-term structural acclima-tion to environmental stimuli over time (Mencuccini 2003). As a consequence, the association between the average stomatal conductance over time and xylem structure will be more physi-ologically relevant than maximum stomatal conductance. The integrated stomatal conductance could be represented by aver-age intercellular partial pressures of CO2 (Ci), and consequently indicated by the carbon isotope discrimination (δ13C) (Farquhar et al. 1989, Huc et al. 1994, Bonal et al. 2001).

In this study, δ13C was positively correlated with Kl but not Ks (Table 4, PIC coefficient; Figure 5), suggesting that loose sto-matal control (higher δ13C) was associated with higher leaf hydraulic conductivity, consistent with previous reports (Sobrado 1993, Choat et al. 2004). A close association between stomatal control and leaf hydraulic conductivity may guarantee similar xylem tension ranges among studied species (Yu et al. 2002), as the leaf water potential gradient was largely determined by the product of stomatal conductance and the inverse of Kl (Tyree and Ewers 1991). On the other hand, the absence of an evolutionary correlation between δ13C and Ks may be attributable to other factors, such as the buffering effect of stem xylem capacitance (Meinzer et al. 2009).

Specific leaf area, one of the leading dimensions of leaf trait variations related to plant carbon economy, was functionally associated with Ks and Kl (Table 4, Figure 5), which agrees with some previous reports (Mitchell et al. 2008, O’Grady et al. 2009) but does not agree with the findings of others (Tyree et al. 1999, Taylor and Eamus 2008). Such inconsistency could be explained by the idea that the relationships between SLA and other leaf traits would diverge from global patterns under low light environments (Santiago and Wright 2007). If samples expe-rienced similar light environments at exposed sites, as in the present study, SLA would show a positive relationship with photo synthetic capacity and stomatal conductance (Santiago and Wright 2007), and be closely associated with hydraulic con-ductance via stomatal regulation, which was well-documented in previous reports (Santiago et al. 2004, Chen et al. 2009).

Our study, like other investigations of the hydraulic architec-ture of several species, has limitations. First, we could not guarantee we randomly sampled taxa in the study area, which may limit both traditional cross-species analysis and indepen-dent contrasts (Ackerly 2000). As a consequence, non-random sampling will lead to an underestimation of the true PIC corre-

lation coefficients, and so only the significant PICs in our study should be regarded as robust. Nevertheless, this limitation must be balanced against inflated Type I error rates of non-phylogenetically corrected cross-species correlations (Ackerly 2000). Second, woody species with other growth forms were not included in this study. For example, there may be a weak evolutionary trade-off between hydraulic conductance and Ψ50 in gymnosperm species (Maherali et al. 2004). Finally, intra- and inter-specific trait variations caused by different microhabi-tats should be taken into account both in traditional cross-species co-relationship studies and in independent con-trast analysis (Santiago and Wright 2007).

Despite all this, to the best of our knowledge, data on the hydraulic architecture of woody karst species in China have not been reported in the literature previously. Therefore, our study provides a fundamental framework for the further investigation of hydraulic architecture of plants on karst topography in China. Comparative community physiology (Jacobsen et al. 2008) in water relations among karst plant communities, and between communities at karst and no-karst sites in similar climates, will be very helpful for understanding the characteristics of the hydraulic architecture of karst plants.

Conclusion

In conclusion, we provide the first available systematically col-lected data on the hydraulic architecture of woody karst spe-cies in China. We found that karst plants in China were not highly cavitation-resistant species. Our findings support the idea that there might not be an evolutionary trade-off between resistance to cavitation and specific conductivity in woody plants. The interactions between stomatal behavior, hydraulic capacity and other functional traits controlling xylem tension for maintenance of homeostatic water balance in whole plants, particularly under the highly variable daily moisture conditions in karst areas, are worthy of further study. Furthermore, such a study may also prove useful in understanding vegetation changes in karst ecosystems in response to local, regional and global changes in environmental conditions.

Acknowledgments

We thank H. Maherali, F.C. Meinzer and two anonymous review-ers for providing valuable critiques of the manuscript.

Funding

This study was financially supported by National Natural Science Foundation of China (31070356), major state basic research development programs in China (2010CB951301-6), and the special S&T project on treatment and control of water pollution (2009ZX07104-003-05).



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