The relationships between leaf economics and ...

Science of the Total Environment 621 (2018) 245–252

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

The relationships between leaf economics and hydraulic traits of woody plants depend on water availability Qiulong Yin, Lei Wang, Maolin Lei, Han Dang, Jiaxin Quan, Tingting Tian, Yongfu Chai, Ming Yue ⁎ Key Laboratory of Resource Biology and Biotechnology in Western China, Northwest University, Xi' an City, Shaanxi Province, China

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Leaf economics and hydraulic traits were coupled on the Loess Plateau. • The relationships between these two sets of traits depend on the changing conditions. • Stomatal guard cell length may play a more important role than stomatal density in flexibility of plants.

a r t i c l e

i n f o

Article history: Received 26 October 2017 Received in revised form 15 November 2017 Accepted 15 November 2017 Available online xxxx Editor: Elena PAOLETTI Keywords: Vein density Stomatal density Stomatal guard cell length Leaf nitrogen concentrations Leaf dry mass per area Palisade tissue thickness

a b s t r a c t Leaf economics and hydraulic traits are simultaneously involved in the process of trading water for CO2, but the relationships between these two suites of traits remain ambiguous. Recently, Li et al. (2015) reported that leaf economics and hydraulic traits were decoupled in five tropical-subtropical forests in China. We tested the hypothesis that the relationships between economics and hydraulic traits may depend on water availability. We analysed five leaf economics traits, four hydraulic traits and anatomical structures of 47 woody species on the Loess Plateau with poor water availability and compared those data with Li et al. (2015) obtained in tropical-subtropical regions with adequate water. The results showed that plants on the Loess Plateau tend to have higher leaf tissue density (TD), leaf nitrogen concentrations and venation density (VD) and lower stomatal guard cell length (SL) and maximum stomatal conductance to water vapour (gwmax). VD showed positive correlations with leaf nitrogen concentrations, palisade tissue thickness (PT) and ratio of palisade tissue thickness to spongy tissue thickness (PT/ST). Principal component analysis (PCA) showed a result opposite from those of tropical-subtropical regions: leaf economics and hydraulic traits were coupled on the Loess Plateau. A stable correlation between these two suites of traits may be more cost-effective on the Loess Plateau, where water availability is poor. The correlation of leaf economics and hydraulic traits may be a type of adaptation mechanism in arid conditions. © 2017 Elsevier B.V. All rights reserved.

1. Introduction ⁎ Corresponding author at: College of Life Science, Northwest University, Xi' an, Shaanxi Province 710069, China. E-mail address: [email protected] (M. Yue).

https://doi.org/10.1016/j.scitotenv.2017.11.171 0048-9697/© 2017 Elsevier B.V. All rights reserved.

Leaves play an especially important role in carbon assimilation, water relations and energy balance (Ackerly et al., 2002). Studies of

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Q. Yin et al. / Science of the Total Environment 621 (2018) 245–252

functional traits in leaves have greatly advanced our understanding of leaf function and plant performance (Sack et al., 2003; Reich, 2014; Blackman et al., 2016; Chai et al., 2015b). Among various leaf traits, those related to light capture and water and CO2 exchange have received more attention, reflecting the crucial importance of these processes in the functioning of biosphere (Li et al., 2015). Leaf traits related to carbon economy are strongly correlated across and within biomes, such as leaf maximum photosynthetic capacity (Amax), leaf dry mass per area (LMA) and leaf nitrogen concentrations, which form the leaf economics traits (Wright et al., 2004; Wright et al., 2005). Certain other groups of traits, such as venation traits and stomatal traits, are often found to be correlated across species, suggesting a balance between water demand and supply, and they form the hydraulic traits (Franks and Beerling, 2009; Zhang et al., 2012; Sack and Scoffoni, 2013; Li et al., 2015). For land plants, the greatest biophysical barrier to carbon gain and ultimately survival is the ability of leaves to maintain high photosynthetic rate while avoiding desiccation (Simonin et al., 2012; Mitchell et al., 2013; Zwieniecki and Boyce, 2014). Water transport and CO2 diffusion are two important processes that determine the CO2 assimilation efficiency in leaves (Flexas et al., 2013). In fact, CO2 uptake through stomata is inevitably coupled to water loss from photosynthetic tissue to the atmosphere (Hanson and Weltzin, 2000; Nardini and Luglio, 2014). Some studies have found coordinated relationships between leaf hydraulic and economics traits (e.g., Brodribb et al., 2005; Brodribb et al., 2007; Nardini et al., 2012; Villagra et al., 2013; Jin et al., 2016; Scoffoni et al., 2016; John et al., 2017). However, Li et al. (2015) reported that leaf economics and hydraulic traits were decoupled in five tropical-subtropical forests in China recently. To date, most of the studies about the relationships between leaf economics and hydraulic traits have been conducted in tropical and subtropical regions with adequate water. The relationship between these two sets of traits in arid regions remains unclear. Since water is an important determinant in photosynthesis and hydraulic processes, the relationships between leaf economics and hydraulic traits might be stronger with poor water availability. We tested the hypothesis that relationships between economics and hydraulic traits depend on water availability. To test this hypothesis, we selected 47 woody angiosperms representing 38 genera and 18 families on the Loess Plateau, which is characterized by poor water availability. We then compared our results to Li et al. (2015) to detect the differences between tropical-subtropical regions and the Loess Plateau. To make a better comparison, all of the leaf economics and hydraulic traits conducted in this study were consistent with previous study in wet regions (Li et al., 2015), except for leaf stable carbon concentration. We analysed five common economics traits which suggest the carbon investments, including leaf dry mass per area (LMA), leaf thickness (LT), leaf tissue density (TD), leaf area-based N concentration (Narea) as well as leaf mass-based N concentration (Nmass). And we analysed four hydraulic traits which suggest the balance between water supply and demand, including venation density (VD), stomatal density (SD), stomatal guard cell length (SL), calculated maximum stomatal conductance to water vapour (gwmax). All of the nine traits were measured according to Li et al. (2015), except that leaf stable carbon concentration was not measured in the present study. Since Li et al. (2015) guessed that the decouple of these two sets of traits may be a result of the physical separation of leaf structures but related analyses were lacking, we analysed the anatomical structures of leaves, including of palisade tissue thickness (PT), spongy tissue thickness (ST) and the ratio of PT to ST (PT/ST), through paraffin section method.

Province, China. The climate is semiarid, temperate, continental monsoon, with a mean annual temperature of 9–11 °C (Chai et al., 2016a). The mean annual precipitation is approximately 560 mm (1539– 2651 mm in Li et al., 2015) and mostly occurs in July, August and September. The soil type is cinnamon soil, which is rich in calcium (Liang et al., 2010). Further, the denuded lands have been abandoned to forest succession (Chai et al., 2016b). Quercus wutaishanica forest is the natural climax vegetation in this region (Wang et al., 2013). Leaves were collected from 47 woody species belonging to 38 genera and 18 families. The species selected are common in the study area. For each species, at least 3–4 individuals were sampled and leaves were collected from the sun-exposed branches of each individual. After harvesting, 30–50 leaves of each species were preserved in plastic bags for analyses of economics traits and 8–10 leaves were preserved in a formalin-acetic-alcohol (FAA) solution for analyses of venation traits, stomatal traits and anatomical structures. 2.2. Economics traits A picture of each fresh leaf surface was taken with a digital camera, and leaf surface area (LA, cm2) was measured with Motic Images Plus 2.0 (Motic China, Xiamen) software. All leaves were then placed in a drying oven for 72 h at 70 °C to determine the dry mass. Leaf dry mass per area (LMA, g m−2) was calculated as the ratio of dry mass to LA. Leaf thickness (LT, mm) was measured through transverse sections using Image-Pro Plus 6.0, avoiding the influence of major veins. For each section, 10–20 measurements were made. Leaf tissue density (TD, g cm−3) was calculated as the ratio of LMA to LT. Leaf nitrogen content were determined on a subsample of dried leaf material from each species. Leaves were ground into a fine power, stored under desiccation, and leaf nitrogen concentrations per unit leaf mass (Nmass, mg g− 1) were determined using an elemental analyser (Euro Vector EA3000, Milan, Italy). Nitrogen per unit leaf area (Narea, g m−2) was obtained by a product of Nmass and LMA. 2.3. Hydraulic traits

2. Materials and methods

The nail-polish imprint method was used to examine stomatal traits (Zhao et al., 2016). Clear nail polish was applied onto the middle of the abaxial leaf surface, allowed to dry, and then pulled off the leaf by using Sellotape and mounted onto a glass slide. We photographed the stomatal prints under a Classica SK200 Digital light microscope (Motic China Group Co., Ltd., China) at 200–400× magnification. SL (μm) was measured using Image-Pro Plus 6.0 (Media Cybernetics, USA) software. SD (mm−2) was calculated as the number of stomata per unit epidermal area by dividing leaves into grids of 100 × 100 μm. SL and SD were averaged from more than 20 randomly selected fields of view. gwmax (mol m−2 s−1) was calculated according to the following equation: gwmax = dαLD / (v(0.5 + 0.627√α)); d is the diffusivity of water in air (m2 s−1), L is the stomatal guard cell length (μm), D is stomata density (mm−2), and v is the molarvolume of air (m3 mol−1). A mid-range value of 0.12 for α was used for the demonstrations here (Franks et al., 2009). After removing the nail-polish, a sample of approximately 1 cm2 was excised from the leaf and then placed in 10% sodium hydroxide aqueous solution for several hours to several days, until the minor veins were exposed. Each sample was then soaked in distilled water and then stained in 1% toluidine blue for 30–60 s. The samples were then mounted onto glass slides and photographed. VD (m mm−2) was calculated as the total length of leaf veins per leaf area using Image-Pro Plus 6.0 by manually dividing leaves into grids of 100 × 100 μm by drawing. VD was averaged from more than 20 randomly selected fields of view.

2.1. Sites and sampling

2.4. Anatomical structures

The leaf specimens were collected from the Ziwuling Forest Region (35°09′N, 108°45′E) in the middle of the Loess Plateau, Shaanxi

The middle portions of leaves were excised, dehydrated in an ethanol series and then embedded in paraffin for sectioning. The transverse


sections were made on a Leica RM2135 rotary microtome (Leica Inc., Bensheim, Germany), and then mounted on glass slides. The transverse sections were examined and photographed. Thickness of the palisade tissue (PT, μm) and spongy tissue (ST, μm) were measured using Image-Pro Plus 6.0, avoiding the influence of major veins (Zhang et al., 2012). For each section, 10–20 measurements of palisade tissue thickness and spongy tissue thickness were made respectively. We then calculated the ratio of the thickness of palisade tissue to spongy tissue (PT/ ST). 2.5. Statistical analysis Differences in leaf traits between the Loess Plateau and tropicalsubtropical regions were tested with one-way ANOVA by using the PASW Statistics 13.0 software package (SPSS, Chicago, IL, USA). Relationships between pairwise leaf traits were analysed with Pearson's correlation, using log10-transformed values of the means of traits to meet the normality assumption. Linear regression analyses were used to examine the correlations of traits (SigmaPlot, SPSS Inc., Chicago, IL, USA). Multivariate associations of leaf traits were analysed with a principal component analysis (PCA) in CANOCO software for Windows 4.5 (Microcomputer Power, Ithaca, NY, USA), using zero-mean transformed values of the means of traits to meet the normality assumption. Multivariate associations of leaf traits were also calculated with phylogenetically independent contrasts (PICs) to evaluate whether the observed

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traits associations were the result of repeated evolutionary divergences, by using the “analysis of traits” (AOT) module in Phylocom version 4.1 (Webb and Donoghue, 2005; Zhu et al., 2013). 3. Results Seven of nine traits differed significantly between the Loess Plateau and tropical-subtropical regions (Fig. 1, the abbreviations and units of leaf traits are shown in Table 1). Plants on the Loess Plateau had significantly higher Nmass, TD, Narea and VD compared to those from tropicalsubtropical regions (Fig. 1b, d, e, h). Plants from tropical-subtropical regions had significantly higher LT, SL and gwmax than those of the Loess Plateau (Fig. 1a, c, i). LMA and SD showed no significant differences between the Loess Plateau and tropical-subtropical regions (Fig. 1f, g). Among the economics traits, LMA showed positive correlations with LT, TD and Narea, and TD showed a negative correlation with LT (Table 2). Pearson correlation analysis using PICs showed consistent results with the analysis using original data, except that the correlation between LMA and LT was not significant according to PICs (Table 2). Among the hydraulic traits, VD was positively correlated to gwmax according to PICs, and SL was negatively correlated to SD both using original data and PICs (Table 2). Between the economics and hydraulic traits, SD had no significant correlations with the five economics traits. SL was positively correlated to LT and LMA, but the correlation between SL and LT was not significant according to PICs (Table 2). VD was

Fig. 1. Differences in 9 leaf traits between the Loess Plateau (white columns) and tropical-subtropical regions (grey columns, data from Li et al., 2015 Data S1). Error bars represent 1 SE and significance is denoted by asterisks: **, P b 0.01; ***, P b 0.001; ns, not significant. Trait abbreviations: LT (leaf thickness), TD (leaf tissue density), LMA (leaf dry mass per area), Nmass (leaf nitrogen concentration per mass), Narea (leaf nitrogen concentration per area), VD (vein density), SL (stomatal guard cell length), SD (stomatal density), and gwmax (maximum stomatal conductance to water vapour).

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Table 1 Variation in 12 leaf traits of 47 wood species. Leaf traits

Abbrev

Unit

Min

Max

Mean

Coefficient of variance

Leaf thickness Leaf tissue density Leaf dry mass per area Leaf nitrogen concentration per mass Leaf nitrogen concentration per area Vein density Stomatal guard cell length Stomatal density Maximum stomatal conductance to water vapour Palisade tissue thickness Spongy tissue thickness Ratio of PT to ST

LT TD LMA Nmass Narea VD SL SD gwmax PT ST PT/ST

mm g cm−3 g cm−2 mg g−1 g m−2 mm mm−2 μm mm−2 mol m−2 s−1 μm μm –

0.07 0.29 35.65 11.91 0.77 4.72 7.70 104.17 0.24 25.36 21.62 0.59

0.22 0.90 116.00 42.96 3.41 15.51 26.91 1069.45 1.85 103.32 118.76 2.54

0.15 0.54 77.72 22.50 1.74 10.92 16.64 351.01 0.90 65.71 53.55 1.31

25.71% 25.76% 23.10% 32.05% 39.21% 21.63% 32.07% 65.52% 44.18% 30.98% 35.83% 35.73%

positively correlated to Nmass and Narea using original data, and positively correlated to LT according to PICs (Table 2). In addition, we found strong coordination of VD with PT and PT/ST, but no significant correlation with ST (Fig. 2). PCA was employed to evaluate how economics and hydraulic traits were associated. PCA axis 1, accounting for 27.99% of the total variation, showed strong loadings on LT, LMA, Nmass, Narea and SL. PCA axis 2, accounting for 25.24% of the total variation, showed strong loadings on VD, SD and gwmax (Table 3). The results indicated a covariation between leaf economics traits and hydraulic traits (Fig. 3a), which was opposite to the results of Li et al. (2015) that these two sets of traits were orthogonal. On the whole, PCA analysis according to PICs showed a pattern similar to that of the analysis using original data (Fig. 3b). 4. Discussion 4.1. Differences in leaf traits between the Loess Plateau and tropicalsubtropical regions Plants often exhibit considerable variations of functional traits to adapt to changing environments and maintain normal physiological activities (Franks and Beerling, 2009; Zhang et al., 2012). Stomatal control of water loss allows plants to occupy habitats with fluctuating environmental conditions (Hetherington and Woodward, 2003). Although we detected significantly smaller stomata on the Loess Plateau than those in tropical-subtropical regions, SD was not significantly different between these two regions (Fig. 1c, f). Previous studies stated that SL plays a substantial role in adaptation to drought (Xu and Zhou, 2008). Small stomata can react more quickly to environmental stimuli (Franks et al., 2009), and accordingly, plants with small stomata can attain rapid diffusive conductance under favourable conditions and exhibit higher water-use efficiency (Franks et al., 2009; Zhang et al., 2012). Spence et al. (1986) reported that small stomata could remain open under drought, demonstrating a balance between the prevention of excessive water loss and carbon gain though photosynthesis in adapted to dry conditions. Carins Murphy et al. (2014) found that Toona ciliata M. Roem maintained water homeostasis mainly by dynamic closure of

stomata rather than by a reduction in density. Our findings indicate that SL might play a more important role than SD in flexibility of plants on the Loess Plateau. On the other hand, since plants need constant supplementation to replenish the water lost from open stomata, an efficient water supply through the xylem is crucial to plant growth and survival (Brodribb and Jordan, 2011; Sack and Scoffoni, 2013). VD is vital in determining the efficiency of water transport (Brodribb and Jordan, 2011; Xiong et al., 2017) due to its effects on hydraulic pathlength and bundle sheath surface area (Sack and Frole, 2006; Thomas et al., 2015). In the present study, plants on the Loess Plateau showed a higher VD than those of plants from tropical-subtropical regions; as a result, they possess more efficient water transport (Fig. 1h). Higher VD means a shorter distance through which water must flow in the mesophyll before evapourating, considering that the resistance to water flow through living leaf mesophyll is much higher than the hydraulic resistance of vein xylem (Brodribb et al., 2007; North et al., 2013; Xiong et al., 2014; Zwieniecki and Boyce, 2014). In addition, by providing alternative water transport pathways to bypass embolized veins, high density of major veins is important in determining the drought resistance of plants (Sack et al., 2008; Scoffoni et al., 2011). Moreover, previous studies stated that increased vapour pressure between leaf and atmosphere (VPD) would induce an increase in VD (Carins Murphy et al., 2014). Hence, high VD might be a type of adaptation of plants on the Loess Plateau to the arid environment. In addition, higher VD generally increases the carbon investment of plants (Brodribb et al., 2010). Hence, to satisfy the greater carbon cost, leaves on the Loess Plateau need more nitrogen to maintain a higher photosynthetic rate (Chai et al., 2015a). In the present study, leaves of plants on the Loess Plateau retained higher N concentrations than those of tropical and subtropical forest plants (Fig. 1b, e). In general, leaf N concentration tends to increase with decreasing average annual temperature (Han et al., 2005; Reich, 2005). In this study, the mean annual temperature is 9–11 °C, and it is approximately 20 °C in the study of Li et al. (2015). This is another reason why leaves of plants on the Loess Plateau retained higher N concentrations than those of tropical and subtropical forest plants.

Table 2 Pearson correlation coefficients (lower diagonal) and phylogenetically independent contrasts (upper diagonal) among 9 leaf traits. Leaf traits LT TD LMA Nmass Narea VD SL SD gwmax

LT −0.52** 0.50** 0.08 0.40** 0.07 0.43** −0.10 0.20

TD

LMA

Nmass

Narea

VD

SL

SD

gwmax

−0.34*

0.32 0.75**

−0.07 −0.19 −0.29

0.14 0.41* 0.49** 0.66**

0.42* 0.03 0.27 0.17 0.34*

0.21 0.17 0.36* −0.15 0.14 0.03

−0.03 −0.03 −0.10 0.25 0.11 0.30 −0.59**

0.20 −0.03 0.06 0.28 0.26 0.48** −0.11 0.80**

0.48** −0.16 0.20 0.15 −0.06 −0.03 −0.08

−0.07 0.61** 0.22 0.38** −0.13 0.12

0.75** 0.36* −0.02 0.11 0.11

0.43** 0.24 −0.01 0.17

−0.07 0.27 0.28

−0.58** 0.03

0.80**

All traits were log-transformed to meet the normality assumption. Significant correlations are denoted by asterisks: *, P b 0.05; **, P b 0.01. Trait abbreviations are provided in Table 1.


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Fig. 2. Relationships of venation density (VD) with palisade tissue thickness (PT), spongy tissue thickness (ST) and ratio of PT to ST (PT/ST). Linear regressions were fitted to the data. All traits were log-transformed to meet the normality assumption.

On the other hand, higher VD and more carbon investment increase TD (Blonder et al., 2011; Blonder et al., 2013), and TD is negatively correlated to precipitation (Niinemets, 2001). Hence, leaves on the Loess Plateau have higher TD (Fig. 1d). In addition, LT increased with increasing mean temperature (Niinemets, 2001). In consequence, we detected a smaller LT on the Loess Plateau than tropical-subtropical regions (Fig. 1a). Furthermore, LMA is a comprehensive reflection of LT and TD (Niinemets, 2001; Onoda et al., 2011; John et al., 2017). We found LMA was positively related to LT and TD, and therefore, decreased LT and increased TD could lead to the lack of a significant difference in LMA between the Loess Plateau and tropical-subtropical regions (Fig. 1g).

Table 3 Loading scores of 9 leaf traits in the PCA among 47 woody species. Variable

PC 1

PC 2

PC 3

LT TD LMA Nmass Narea VD SL SD gwmax % of variance Cumulative %

−0.6841 0.0293 −0.7022 −0.5513 −0.8554 −0.3827 −0.553 0.2605 −0.041 27.99% 27.99%

−0.1041 −0.0628 −0.1934 0.4717 0.2927 0.5017 −0.5315 0.8994 0.754 25.24% 53.23%

−0.5356 0.9807 0.4514 −0.1361 0.1370 0.2648 −0.1278 −0.0321 −0.0726 17.58% 70.81%

Trait abbreviations are provided in Table 1.

Fig. 3. Principal component analysis (PCA) on leaf economics traits (red lines) and leaf hydraulic traits (yellow lines) by using original data (a) and using PICs (b), respectively. Values in parentheses in the axis labels are percentages explained by the first two components. Trait abbreviations: LT (leaf thickness), TD (leaf tissue density), LMA (leaf dry mass per area), Nmass (leaf nitrogen concentration per mass), Narea (leaf nitrogen concentration per area), VD (vein density), SL (stomatal guard cell length), SD (stomatal density), gwmax (maximum stomatal conductance to water vapour). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

4.2. The coupled relationship on the Loess Plateau versus the decoupled relationship in tropical-subtropical regions Relationships between leaf economics and hydraulic traits have been discussed in several studies. Blonder et al. (2011) proposed a venation model to assess leaf economics traits and believed that leaf economic trade-offs were venation-mediated (“vein origin” hypothesis). High photosynthetic rates need efficient water supply and thus higher VD, which is coupled with high construction costs (Brodribb et al., 2007; Boccalandro et al., 2009). In contrast, Sack et al. (2004) reported that LMA was independent of water flux traits, and Sack et al. (2014) considered that “vein origin” hypothesis was supported only by a mathematical model with predestined outcomes.

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Recently, Li et al. (2015) found that leaf economics and hydraulic traits were decoupled in five tropical-subtropical forests in China. However, the present study revealed an opposite result on the Loess Plateau. We inferred that the differences between our studies and that of Li et al. (2015) were due to the different environments, especially the differences in water availability. The main reasons are as follows. First, Li et al. (2015) argued that leaf economics and hydraulic traits were features of different structural modules and represent two functional subsystems, given that leaf economics traits were located in upper subsystems (palisade mesophyll tissues) and leaf hydraulic traits were located in lower subsystems (spongy mesophyll tissues). However, we found strong coordination of VD with PT and PT/ST, but no significant correlation with ST, considering that VD is an important hydraulic trait. Sack and Frole (2006) revealed that PT/ST was correlated negatively with leaf hydraulic resistance. Moreover, plants tend to have higher PT/ST in arid areas (Zhao and Huang, 1981). Thus, there seems to be a trade-off between palisade tissues and spongy tissues to acclimate to drought, consequently leading to a correlation between leaf economics and hydraulic traits. In our view, though most of the leaves of dicotyledons were partitioned between palisade and spongy tissues, they were not absolutely separated. Material transportation is ubiquitous between palisade and spongy tissues (see Fig. 2 of Li et al., 2015). CO2 diffuses through spongy tissues to palisade tissues for photosynthesis, while palisade tissues produce carbon for the construction of veins. Furthermore, leaf veins form the transport network not only for water but also for nutrients and carbon (Brodribb et al., 2007). Second, Li et al. (2015) mainly discussed the independence between VD and LMA. In general, the independence between VD and LMA was found across different biomes, different plant functional types and in the entire global dataset (Li et al., 2015). We also found the independence between VD and LMA. In general, plants that adapted to arid conditions tend to have higher LMA (Poorter et al., 2009). In the present study, plants of the Loess Plateau showed significantly higher VD than those of the tropical-subtropical regions, whereas LMA is almost the same (Fig. 1g, h). This might induce the independence between VD and LMA on the Loess Plateau. However, it is obviously not convincing to only considering the relationship between VD and LMA. In this study, VD was positively correlated to Nmass and Narea using original data, and positively correlated to LT according to PICs (Table 2). It illustrates that VD was correlated with other economics traits than LMA. In addition, we found a decoupling between SD and leaf economics traits (Table 2). This may due to the high coefficient of variance (65.52%) in SD. It showed that some specific hydraulic traits were decoupled with economic traits to some degree, but on the whole these two sets of traits were coupled. Last but not the least, Li et al. (2015) argued that decoupled relationships between leaf economics and hydraulic traits brought about greater freedom for more combinations of leaf traits in adaption to multifarious environmental gradients. This might be a rule in speciesrich biomes where species differences are gradual and environmental gradients are divided finely (Li et al., 2015). However, in arid regions, species diversity is low, and water availability is the main limiting factor. A steady and stable correlation between these two suites of traits may be preponderant under such arid conditions. Plants tend to a persistent combination of economics and hydraulic traits to acclimate to the arid conditions. In other words, in an uncomplicated environment, plants do not need multiple combinations of traits, which are costly.

petiole though xylem and across bundle sheath to evapouration sites) (Tyree and Zimmermann, 2002; Flexas et al., 2012; Flexas et al., 2013). Decreases in Kleaf usually cause leaves to be less hydrated, and ultimately to close stomata and reduce CO2 assimilation (Johnson et al., 2009; Sperry, 2000). Flexas et al. (2008) have reviewed the idea that gm is a significant limitation on photosynthetic rate. Furthermore, LMA and LT have great effects on gm (Muir et al., 2014), and Kleaf is strongly influenced by VD (Sack and Scoffoni, 2013) and leaf N concentration (Xiong et al., 2014). Thus, there may be a broad physiological basis for the relationships between leaf economics and hydraulic traits, but multiple relationships among numerous physiological traits are lacking. We should create the physiological foundation of the relationships between these two sets of traits, and combine with anatomical structures of leaves. Furthermore, relationships of leaf economics and hydraulic traits may vary among different scales of traits. Zhao et al. (2016) found a weak correlation between SD and VD of 105 angiosperm species in Southwest China, and SD and VD were not correlated with leaf area, but stomatal number per leaf and vein length per leaf were strongly correlated. As the leaf is an integrated functional unit, more attention should be paid to the relationships of traits at the whole-leaf scale. To the best of our knowledge, few studies have focused on the relationships between leaf economics and hydraulic traits under controlled environments. Blackman et al. (2016) found that leaf economics and hydraulic traits were decoupled among genotypes of eucalypt grown under ambient and elevated CO2 conditions. Moreover, Villagra et al. (2013) found that these two sets of traits were correlated in response to nutrient addition. However, relationships of these two sets of traits under different environmental states (e.g., water availability, temperature and light intensity) are still indistinct. To deeper understand the mechanism of plants acclimate to environment, more studies on numerous species at different environment gradients are needed.

4.3. Future prospects

5. Conclusion

Relationships of paired traits have been discussed in physiology (Fig. 4). A strong correlation has been found between mesophyll conductance to CO2 (gm: the conductance of the gaseous CO2 diffusional pathway from the substomatal cavity through mesophyll tissue into cells and chloroplasts, where photosynthesis occurs) and leaf hydraulic conductance (Kleaf: the conductance of liquid water flow pathway from

Leaf economics and hydraulic traits are coupled on the Loess Plateau, in contrast to the results obtained in tropical-subtropical regions. Resources (especially water) are insufficient in arid areas, where plants suffer stronger selection pressure compared to tropical and subtropical forest areas. As hydraulic traits mainly function in water transport, the correlation of leaf economics and hydraulic traits may be a type of

Fig. 4. The relationships between leaf economics traits and hydraulic traits, based on the present study and a synthesis of previous studies (Sperry, 2000; Flexas et al., 2008; Johnson et al., 2009; Flexas et al., 2013; Sack and Scoffoni, 2013; Muir et al., 2014; Xiong et al., 2014). Grey-shaded variables were tested in the present study. White-shaded variables were not tested in the present study. Solid arrows indicate positive correlations; dotted arrows indicate negative correlations. Trait abbreviations: LT (leaf thickness), TD (leaf tissue density), LMA (leaf dry mass per area), Nmass (leaf nitrogen concentration per mass), Narea (leaf nitrogen concentration per area), VD (vein density), SL (stomatal guard cell length), SD (stomatal density), gwmax (maximum stomatal conductance to water vapour), gm (mesophyll conductance to CO2), Pn (net photosynthetic rate) and Kleaf (leaf hydraulic conductance).


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