Trade-offs between water loss and carbon gain in a subtropical 1 primary forest on Karst soils in China

Abstract. Little attention has been given to plants's trade-off between carbon gain and water loss in Karst Critical Zone in southwestern China with low soil nutrient and water availability. An advanced understanding of the impact of CO 2 diffusion and maximum carboxylase activity of Rubisco ( V cmax ) on the light-saturated net photosynthesis ( A ) and intrinsic water use efficiency (iWUE) in Karst plants can provide insight into physiological strategies used in adaptation to harsh environments. We selected six plant life forms (63 species) in a subtropical Karst primary forest in southwestern China, and measured CO 2 response curves, and calculated corresponding stomatal conductance to CO 2 ( g s ), mesophyll conductance to CO 2 ( g m ), and V cmax . The results showed that g s varied from 0.05 to 0.38 mol CO 2 m −2 s −1 , g m varied from 0.02 to 0.69 mol CO 2 m −2 s −1 , and g m was positively related to g s ; foliar A was co-limited by g s , g m , and V cmax in trees, tree/shrubs, and shrubs with relatively high leaf mass per area (LMA), and mainly constrained by g m in grasses, vines, and ferns with relatively low LMA; and iWUE varied from 29.52 to 88.92 μmol CO 2 mol −1 H 2 O across all species, and was significantly correlated with g s , g m / g s , and V cmax / g s . These results indicated that Karst plants maintained relatively high A and low iWUE through the co-variation of g s , g m , and V cmax as adaptation to Karst environment.


Introduction
The Karst Critical Zone (Karst CZ) in southwestern China accounts for over 12% of the total global land area (more than 54×10 4 km 2 ) (Zhang et al., 2011).Compared with other CZs developed on other lithologies, Karst CZ was developed on limestone bedrock, and characterized by inhomogeneous and shallow soil due to the greater hydraulic erosion and complex underground drainage network (Nie et al., 2014;Chen et al., 2015).In such conditions, the soil cannot retain enough nutrients and water for plant growth even though precipitation is high (1000-2000 mm) (Liu et al., 2011;Fu et al., 2012;Chen et al., 2015).To adapt to the harsh environment, Karst plants develop distinct patterns of light-saturated net photosynthesis (A) and trade-off between carbon gain and water loss to adapt to the harsh environment (Sullivan et al., 2017).The intrinsic water use efficiency (iWUE=A/g sw , the ratio of A to stomatal conductance to H 2 O (g sw )), is an effective indicator of the trade-off between carbon gain and water loss (Moreno-Gutierrez et al., 2012).Until now, variability in A and iWUE has been reported only in 13 co-occurring trees and 12 vines (Chen et al., 2015), and 12 co-occurring tree species (Fu et al., 2012) in two tropical Karst forests in southwestern China.
Based on Fick's first law, A has been shown to be limited only by leaf stomatal conductance to CO 2 (g s = g sw /1.6) and V cmax (Flexas et al., 2012;Buckley and Warren, 2014); originally, mesophyll conductance to CO 2 (g m ) was proposed to be infinite, i.e.CO 2 concentration in chloroplast (C c ) was equal to the CO 2 concentration in intercellular air space (C i ).Indeed, g m varies greatly among species (Warren and Adams, 2006;Flexas et al., 2013).Recent studies have confirmed that A was constrained jointly by g s , g m , and V cmax , and their relative contribution to A was species-dependent and site-specific (Carriqui et al., 2015;Tosens et al., 2016;Galmes et al., 2017;Peguero-Pina et al., 2017a;Peguero-Pina et al., 2017b;Veromann-Jurgenson et al., 2017).
Variation in iWUE (=A/g sw ) depends on the relative changes in A (g s , g m , V cmax ) and g sw (g sw =1.6g s ) (Flexas et al., 2013;Gago et al., 2014).Theoretical relationships between iWUE and g s , g m , and V cmax have been deduced using two approaches.Based on Fick's first law of CO 2 diffusion, Flexas et al. (2013) deduced that iWUE was a function of g m /g s and CO 2 gradients (C a -C c ) within leaf.On the other hand, combining Fick's first law of CO 2 diffusion and Farquhar biochemical model (Farquhar and Sharkey, 1982), Flexas et al. (2016) deduced that iWUE was a function of V cmax /g s , C c , CO 2 compensation point of photosynthesis (Γ * ), and the effective Michaelis-Menten constant of Rubisco for CO 2 (K m ).Until now, most previous studies focused on the role of CO 2 diffusion in limiting iWUE, and suggested that iWUE was negatively related to g s , and positively related to g m /g s (Flexas et al., 2013).Gago et al. (2014) used a meta-analysis with 239 species, and were the first to confirm that iWUE was positively related to V cmax /g s .Although both g m /g s and V cmax /g s were positively correlated with iWUE, there was only a weak correlation between g m /g s and V cmax /g s , which indicates that iWUE can be improved by increasing V cmax or g m (proportionally higher than g s ), not both (Gago et al., 2014).
It is noteworthy that Flexas et al. (2016) and Gago et al. (2014) found that most of the previous work on constraints of g s , g m , and V cmax on A were conducted in crops or saplings, and only a few studies were in natural ecosystems.For example, g m was the main factor limiting A in two Antarctic vascular grasses (Saez et al., 2017), and in 35 Australian sclerophylls (Niinemets et al., 2009b) in different habitats.The A of two closely-related Mediterranean Abies species growing in two different habitats was mainly constrained by g m in one, and by g s in the other habitat (Peguero-Pina et al., 2012).Beyond that, it still remains unknown how g s , g m , and V cmax regulate A and iWUE across species in natural ecosystems.
In this study, we selected 63 dominant plant species, including six life forms (29 trees, 11 trees/shrubs, 11 shrubs, 4 grasses, 5 vines, and 3 ferns), from a subtropical primary forest in the Karst CZ of southwestern China, and measured their A and CO 2 response curves.The g m was calculated using the curve-fitting method (Ethier and Livingston, 2004).The obtained g m was used to transform the A-C i into A-C c response curves, and then to calculate the A and V cmax .Our objective was to determine and distinguish the limitations of CO 2 diffusion (g s and g m ) and V cmax on A and iWUE in different life forms in this Karst primary forest.

Site information
This study was conducted in a subtropical primary forest (26°14′48″N, 105°45′51″E; elevation, 1460 m), located in the Karst CZ of southwestern China.This region has a typical subtropical monsoon climate, with a mean annual precipitation of 1255 mm, and mean annual air temperature of 15.1°C (Zeng et al., 2016).The soils are characterized by a high ratio of exposed rock, shallow and nonhomogeneous soil cover, and complex underground drainage networks, e.g.grooves, channels and depressions (Chen et al., 2010;Zhang et al., 2011;Wen et al., 2016).Soils and soil water are easily leached into underground drainage networks.Soil texture was silt-clay loam, and soil PH was 6.80±0.16(Chang et al., 2018).The total nitrogen and phosphorus content in soil was 7.30±0.66and 1.18±0.35g Kg -1 , respectively, which was similar with that of non-Karst CZs (Wang et al., in review).However, the soil quantities (16.04~61.89Kg m -2 ) and nitrogen and phosphorus storage (12.04 and 1.68 t hm -2 ) was much lower than that of non-Karst CZs, due to the thin and heterogeneous soil layer (He et al., 2008;Jobbagy et al., 2000;Lu et al., 2010;Li et al., 2008).The typical vegetation type is mixed evergreen and broadleaf deciduous primary forest, dominated by Itea yunnanensis Franch, Carpinus pubescens Burk., and Lithocarpus confinis Huang, etc. (Wang et al., in review).

Leaf gas-exchange measurements
In July and August 2016, 63 dominant species of six life forms (Table S1), including 29 trees, 11 trees/shrubs, 4 shrubs, 4 grasses, 5 vines, and 3 ferns, were selected for Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-44Manuscript under review for journal Biogeosciences Discussion started: 20 February 2018 c Author(s) 2018.CC BY 4.0 License.measurements of the A and CO 2 response curves.Details of leaf sampling and measurements of CO 2 response-curves were described in Wang et al. (in review).
Briefly, a total of 189 fully sun-exposed, mature leaves were collected from adult individuals of 63 species to measure CO 2 response curves following procedural guidelines (Longand Bernacchi, 2003) using a portable photosynthesis system USA).
A and the corresponding g sw (g s =g sw /1.6), C a , and C i were extracted from the CO 2 response curve under saturating light (1500 μmol m -2 s -1 ) conditions, with CO 2 concentration inside the cuvette set to 400 μmol mol -1 (Domingues et al., 2010;Domingues et al., 2010).V cmax was estimated by fitting A-C c curves (Ethier and Livingston, 2004).The obtained values of g m were used to transform the A-C i into The g m was calculated using a curve-fitting method (Ethier and Livingston, 2004).In this study, calculated C c and the initial slope of A-C c curves were above zero, indicating that g m estimated by the curve fitting method was valid (Warren and Adams, 2006).Further details on the method to calculate g m are given in Section 4.1.

Theory of trade-off between carbon and water at leaf scale
The exchange of H 2 O and CO 2 between the leaf and the atmosphere is regulated by stomata (Gago et al., 2014).According to Fick's first law of diffusion, A and stomatal conductance to CO 2 (g s ) are related as: (1) where A is the photosynthetic rate (μmol CO 2 m -2 s -1 ); C a is the ambient CO 2 concentration (μmol mol -1 ); C i is the intercellular CO 2 concentration (μmol mol -1 ).
Besides stomata, mesophyll is another barrier for CO 2 inside the leaf.A and mesophyll conductance to CO 2 (g m ) are related as: (2) where C c is the CO 2 concentration at the sites of carboxylation (μmol mol -1 ).C c not only depends on CO 2 supply by g m , but also on CO 2 demand (the maximum carboxylase activity of Rubisco, V cmax ).
(1) The relationship between iWUE and g m /g s iWUE is a function of CO 2 diffusion conductances (e.g.g s and g m ) and leaf CO 2 concentration gradients.We can express A as the product of the total CO 2 diffusion conductance (g t ) from ambient air to chloroplasts, and the corresponding CO 2 concentration gradients by combining Eq. ( 1) and ( 2) (Flexas et al., 2013): (3) where g t = 1/(1/g s +1/g m ).This equation demonstrates that CO 2 concentration gradients in leaves are constrained by stomatal and mesophyll resistance to CO 2 .Therefore, iWUE can be expressed as： (4) Eq. ( 4) means that iWUE is positively related to g m /g s , but not to g m itself (Warren and Adams, 2006;Flexas et al., 2013;Buckley and Warren, 2014;Cano et al., 2014).
(2) The relationship between iWUE and V cmax /g s When Fick's first law and the Farquhar biochemical model (Farquhar and Sharkey, 1982) are combined, iWUE is also a function of V cmax .Based on the Farquhar biochemical model (Farquhar and Sharkey, 1982), when A is limited by Rubisco, it can be expressed by the following equation (Sharkey et al., 2007): (5) where Γ * is the CO 2 compensation point of photosynthesis in the absence of non-photorespiratory respiration in light (R d ), and K m is the effective Michaelis-Menten constant of Rubisco for CO 2 .Combining Eq. ( 1) and ( 5) (Flexas et al., 2016), we obtain: Because R d is much smaller than A in actively photosynthesizing leaves, V cmax /g s can be approximated as: Consequently, iWUE can be expressed as: (8)

Quantitative analysis of limitations on A
The relative contribution of g s (l s ), g m (l m ) and V cmax (l b ) to A can be separated by a quantitative limitation model introduced by Jones (Jones, 1985) and further developed by Grassi & Magnani (2005).The sum of l s , l m , and l b is 1. l s , l m and l b can be calculated as: where ∂A/ ∂C c was calculated as the slope of A-C c response curves over a C c range of 50-100 μmol mol -1 .l s , l m and l b have no units.A is co-limited by the three factors when l s ≈0.3, l m ≈0.3 and l b ≈0.4 (Galmes, J. et al., 2017).

Statistical analysis
The correlation analysis was performed using the least square method, and all of the data were log e -transformed.The probability of significance was defined at p< 0.05.

Results
3.1 Interrelation among g s , g m , g t , and V cmax CO 2 concentration gradients in leaf were controlled by CO 2 diffusion conductance and V cmax .Fig. 1 shows the relationship between CO 2 gradients (C a -C i , C i -C c and C a -C c ) in leaf and the corresponding CO 2 diffusion conductance (g s , g m and g t ) (Fig. 1a-c), and between C a -C c and V cmax (Fig. 1d).CO 2 concentration gradients (C a -C i , C i -C c and C a -C c ) were significantly negatively associated with the corresponding CO 2 diffusion conductance (g s , g m and g t ) (P<0.001).V cmax was positively associated with The g s , g m , and g t were significantly positively related to each other (P<0.001)(Fig. S1).The contribution of g m to leaf CO 2 gradient was similar to that of g s (Fig. S3).
No relationship was found between the CO 2 diffusion conductance (g s , g m , and g t ) and V cmax (Fig. S2).However, after normalization of g s , g m , g t , and V cmax for A (normalized parameters are hereafter called G S =g S /A, G m =g m /A, G t =g t /A, and V=V cmax /A), V was significantly positively correlated with G m and G t (P<0.001) (Fig. 2b and c), and was slightly positively correlated with G s (P<0.05) (Fig. 2a), which represented the trade-off between CO 2 supply and demand.

Contribution of g s , g m and V cmax to A
The variation in A was attributed to variation in both of g s , g m , g t , and V cmax .A was positively correlated with g s (Fig. 3a), g m (Fig. 3b), and V cmax (Fig. 3c).We used the quantitative limitation model (Eqs.( 13), ( 14) and ( 15)) to separate contributions by g s (l s ), g m (l m ), and V cmax (l b ) to limiting A. The l s , l m , and l b were negatively associated with, respectively, g s , g m , and V cmax (Fig. 4).The contributions by g s , g m , and V cmax to limiting A were different for each species (Fig. S3).l s varied from 0.17 to 0.45 (2.6-fold), l m varied from 0.05 to 0.55 (10.5-fold), and l b varied from 0.11 to 0.68 (6.2-fold) across species.Overall, g m contribution to limiting A was the largest (l m =0.38±0.12),followed by V cmax (l b =0.34±0.11),and g s (l s =0.28±0.07).
To further understand how A was limited by g s , g m , and V cmax , we grouped the 63 species into 6 life forms: tree, tree/shrub, shrub, grass, vine, and fern.The results showed that tree, tree/shrub, and shrub with relatively high LMA were co-limited by g s , g m , and V cmax , while g m was the main constrain factor for the other three life forms with relatively low LMA (Fig. 5).The l s showed a decreasing trend from tree to fern.The largest average value of l s was observed for tree and tree/shrub, followed by shrub, grass, and vine and fern.The l m first declined, and then increased.
Grass had the largest averaged value of l m .In contrast, l b first increased and then decreased.Grass had the smallest averaged value of l b .

Effect of g s , g m and V cmax on iWUE
The iWUE varied from 29.52 to 88.92 μmol CO 2 mol -1 H 2 O.In theory, iWUE is regulated by g s (g sw =1.6g s ), g m , and V cmax .However, a simple correlation analysis showed that iWUE was negatively related to g s (Fig. 6b), and not related to A (Fig. 6a), g m (Fig. 6c), and V cmax (Fig. 6d).
A correlation analysis was used to test how g m /g s and V cmax /g s affected iWUE.The results showed that iWUE was positively correlated with g m /g s (Fig. 7a) and V cmax /g s (Fig. 7b).However, there was no significant relationship between g m /g s and V cmax /g s .Three methods are most commonly used for g m estimation.Those methods have been reviewed by Warren (2006) and Pons et al. (2009).Briefly, g m can be calculated by the stable isotope method (Evans, 1983;Sharkey et al., 1991;Loreto et al., 1992), J method (Bongi and Loreto, 1989;Dimarco et al., 1990;Harley et al., 1992;Epron et al., 1995;Laisk et al., 2005), and 'curve-fitting' method (Ethier and Livingston, 2004;Sharkey et al., 2007).All of these methods are based on gas exchange measurements (Pons et al., 2009), and some common assumptions (Warren, 2006).Thus, the accuracy of each method is largely unknown (Warren, 2006).

Biogeosciences
The g m was estimated by the 'curve-fitting' method in this study.Although the 'curve-fitting' method is less precise than the stable isotope method, the 'curve-fitting' method is much more readily available and has been used for several decades (Warren, 2006;Sharkey, 2012).Accurate measurements of A and C i is a prerequisite for estimating g m using the 'curve-fitting' method (Pons et al., 2009).Warren (2006) pointed out that highly-accurate measurements need small leaf area and low flow rates.We confirmed that the calculated C c and the initial slope of A-C c curves were positive, suggesting that the measured g m was reliable (Warren, 2006).
Large variability in g m has been shown both between and within species with different leaf forms and habits (Gago et al., 2014;Flexas et al., 2016).Variability in g m in this study is similar to that in global datasets (Gago et al., 2014;Flexas et al., 2016).The order of averaged g m from different life forms was as follows: tree > tree/shrub > grass > shrub > vine > fern.Previous studies have confirmed that the liquid phase of Large uncertainties can be introduced by ignoring g m .On one hand, g m plays a similar or somewhat lesser role than g s in CO 2 diffusion in leaf (Warren, 2006).In the present study, g m was positively related to g s (Fig. S1), variability range of g m was larger than that of g s , and the contribution of g m to C a -C c was similar to that of g s .Hence, ignoring g m would overestimate the carbon isotope discrimination in photosynthesis (△ 13 C) (von-Caemmerer, 1996;Warren, 2006).Consistent with previous studies (von-Caemmerer, 1996;Warren, 2006), there was a significantly positive relationship between △ 13 C_g m and △ 13 C_g s (△ 13 C_g m =2.38*△ 13 C_g s -35.54,R 2 =0.22,P<0.001).
△ 13 C_g m represented the carbon isotope discrimination when g m was finite, and △ 13 C_g s represented the carbon isotope discrimination when g m was infinite.
On the other hand, ignoring g m would underestimate V cmax up to 75% (Sun et al., 2014).In this study, the relationship between V cmax_Ci and V cmax_Cc can be expressed as: V cmax_Cc =2.6*V cmax_Cc -22.12 (R 2 =0.25, P<0.001).V cmax_Ci represented V cmax calculated based on the A-C i curve, and V cmax_Cc represented V cmax calculated based on the A-C c curve.Furthermore, the leaf barrier to CO 2 caused by g m has not been represented in the global carbon cycles, leading to an overestimation of CO 2 supply for carboxylation and an underestimation of the response of photosynthesis to atmospheric CO 2 (Sun et al., 2014).

Co-variation in g s , g m and V cmax in regulating A
The A was constrained by g s , g m , and V cmax acting together, however, variability in the relative contribution of these three factors depended on species and habitats (Tosens et al., 2016;Galmes et al., 2017;Peguero-Pina et al., 2017a al., 2017).Compared with the global dataset, the A in the study site was high at a given leaf phosphorus (P) level (Wang et al., in review).Under well-watered conditions, A was co-limited by the three factors in angiosperm species (Galmes et al., 2017), and mainly limited by g m in ferns (Carriqui et al., 2015).Similarly in the present study, A of tree, tree/shrub, and shrub was co-limited by g s , g m , and V cmax , and A of fern was mainly limited by g m .However, A of both grass and vine was mainly limited by g m (average l m >0.4, with the largest value of 0.55 and 0.54 for grass and fern, respectively).In addition, 20 of the 63 species were mainly limited by V cmax (l b >0.4, with the largest value of 0.68).
The importance of g s and g m in constraining A was variable, and depended on leaf and mesophyll structural traits, i.e.LMA (Tomas et al., 2013), and thickness of leaf, cell wall (Peguero-Pina et al., 2017b), and mesophyll itself (Giuliani et al., 2013).The negative correlation of g m with LMA has been reported in previous studies (Niinemets et al., 2009a;Tomas et al., 2013).The lack of correlation between g m and LMA, and a positive relationship between g m /LMA and LMA in this study were similar to those shown for gymnosperms (Veromann-Jurgenson et al., 2017).The reason for the similarities may be a strong investment in supportive structures (Veromann-Jurgenson et al., 2017).
A of species with low LMA was co-limited by g s , g m , and V cmax , while A of species with high LMA was mainly limited by CO 2 diffusion (Tomas et al., 2013).In this study, trees, tree/shrub, and shrubs with relatively high LMA were co-limited by g s , g m , and V cmax , and life forms with low LMA were mainly limited by g m .Furthermore, we found that g m was positively related to A (R 2 =0.54,P<0.001, Fig. 3b), however, there was no close relationship between g m and LMA.The reason for this may be that species with high LMA may have thin cell walls in mesophyll (Terashima et al., 2011), andchloroplast (Tosens et al., 2016) Furthermore, the co-variation of g s and g m can also regulate A. Both g s and g m are important physical determinants of CO 2 supply from the atmosphere to the chloroplasts (Giuliani et al., 2013).The restricted CO 2 diffusion from the ambient air to chloroplast is the main reason for a decreased A under water stress conditions due to both the stomatal and mesophyll limitations (Olsovska et al., 2016).The relationship between g s and g m may reflect a co-variation between A and g m , or a tendency for g m to compensate for reductions in g s (Buckley and Warren, 2014).
The relative contribution of V cmax to A not only depends on C a -C c , but also on leaf nutrient levels.Leaf nitrogen (N) and P were closely related to V cmax .Leaf N:P ratio in the same plants in a related study was 24.55±7.7 (Wang et al., in review), indicating a P limitation to photosynthesis (Gusewell 2004).Although there was no significant relationship between l m and leaf N:P, there was a trend of increasing l m with increasing leaf N:P.
The trade-off between CO 2 supply (g s and g m ) and demand (carboxylation capacity of Rubisco) can help maintain high photosynthetic efficiency with low CO 2 diffusion conductance (Galmes et al., 2017;Saez et al., 2017).In this study, we used V cmax as a proxy for the carboxylation capacity of Rubisco, and the normalized V cmax by A (V=V cmax /A) was significantly negatively correlated with the normalized g s by A (G t =g s /A) (P<0.001) (Fig. 2c), indicating that the trade-off between CO 2 supply and demand also existed among different species in the same ecosystems.For genus Limonium (flowering plants) (Galmes et al., 2017), g t was significantly positively related to Rubisco carboxylase specific activity, and significantly negatively related to Rubisco specificity factor to CO 2 .In case of Antarctic vascular (Saez et al., 2017) and Mediterranean plants (Flexas et al., 2014), A was mainly limited by low g m , but it could be partially counterbalanced by a highly-efficient Rubisco through high specificity for CO 2. This highlights the importance of the trade-off between CO 2 supply and demand in plant adaptation to Karst environment.However, it is still unknown how leaf anatomical traits affect g m and A, and this should be further explored.(2014) studied the carbon gain and water loss of woody species in contrasting climates, and found that species in hot and wet regions tend to loss more water in order to fix more carbon (high g s /A, low V cmax_Ci /A), and vice versa.These results

Co-variation of
indicates that plants tend to loss more water in order to fix more carbon.However, the variability of iWUE in this study was larger than in the Karst tropical primary forest (Fu et al., 2012;Chen et al., 2015).The average iWUE of 12 vines and 13 trees in the Karst tropical primary forest was 41.23±13.21μmol CO 2 mol -1 H 2 O (Chen et al., 2015), while that of 6 evergreen and 6 deciduous trees was 66.7±4.9 and 49.7±2.0μmol CO 2 mol -1 H 2 O, respectively (Fu et al., 2012) The iWUE was regulated by the co-variation of g s , g m , and V cmax .In theory, water loss was regulated by g s only, while A was regulated by g s , g m , and V cmax (Fig. 3) (Lawson and and Blatt, 2014).However, iWUE in this study was negatively related to g s , and not related to A, g m , or V cmax (Fig. 6).The reason for these relationships maybe that A, g m , and V cmax co-varied.First, g s was positively correlated to g m .Second, an increase in V cmax would inevitably reduce C c at a given g s and g m (Flexas et al., 2016).While no significant relationship was found between V cmax and CO 2 diffusion conductance (g s , g m , and g t ), V was negatively correlated with G s , G m , and G t .CO 2 diffusion and Farquhar biochemical model indicated that iWUE was affected by g m /g s and V cmax /g s (Gago et al., 2014;Flexas et al., 2016).There was a hyperbolic dependency of iWUE on g m /g s due to the roles of g s and g m in C i and C c , and of C c in A (Flexas et al., 2016).In meta-analyses, both Gago et al. (2014) and Flexas et al. (2016) found that iWUE was significantly positively related to g m /g s and V cmax /g s .The results of this study are consistent with the meta-analyses (Fig. 7), demonstrating that plant types with relatively high g m /g s or V cmax /g s had relatively high iWUE.
However, plants cannot simultaneously have high g m /g s and high V cmax /g s .Similarly to the study of Gago et al. (2014), we found no relationship between g m /g s and V cmax /g s .Gago et al. (2014) thought that the poor relationship between g m /g s and V cmax /g s indicated that the iWUE may be improved by g m /g s or V cmax /g s separately; if both of them were simultaneously improved, the enhanced effect on iWUE could be anticipated.In addition, Flexas et al. (2016) showed in a simulation that the increase in iWUE caused by overinvestment in photosynthetic capacity would progressively lead to inefficiency in trade-off between carbon gain and water use, causing an imbalance between CO 2 supply and demand.
Water use strategies are critical to the survival and distribution of species, especially in harsh environments, e.g. in low-nutrient availability and water stress (Nie et al., 2014).Species with high g s , and low iWUE were defined to have 'profligate/opportunistic' water use strategy, and species with low g s and high iWUE were defined to exhibit 'conservative' water use strategy (Moreno-Gutierrez et al., 2012).Species in Karst environment tended to lose more water to gain more carbon, i.e.Karst plants using 'profligate/opportunistic' water use strategy to adapt to the harsh enviroment,.).
Discuss., https://doi.org/10.5194/bg-2018-44Manuscript under review for journal Biogeosciences Discussion started: 20 February 2018 c Author(s) 2018.CC BY 4.0 License.role of g m in CO 2 diffusion and V cmax mesophyll(Veromann-Jurgenson et al., 2017), cell wall thickness of mesophyll(Terashima et al., 2011)  or chloroplast(Tosens et al., 2016), and surface area of Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-44Manuscript under review for journal Biogeosciences Discussion started: 20 February 2018 c Author(s) 2018.CC BY 4.0 License.mesophyll and chloroplast exposed to intercellular space (Veromann-Jurgenson et al., 2017) were the main limitations for g m .The LMA varied from 22.98 g m -2 to 154.61 g m -2 , the averaged value was 69.32±32.70g m -2(Wang et al., in review).Hence, the wide variability of g m between different species and life forms in the same ecosystem seems to be related to the diversity in leaf anatomical traits.

Figure 2 .
Figure 2. Relationships between (a) V and G s ; (b) V and G m ; and (c) V and G t .V is the ratio of photosynthetic capacity (V cmax ) to light-saturated

V cmax in regulating iWUE
(Flexas et al., 2016)d with the global dataset under well-watered conditions (19.27-171.88μmolCO 2 mol -1 H 2 O)(Flexas et al., 2016), the iWUE (29.52-88.92μmol CO 2 mol -1 H 2 O) in this study was somewhat lower in this study.Although Karst soils cannot contain enough water for plant growth, the water use strategies (high g s /A and low V cmax_Ci /A) were similar to the shown for plants growing in hot and wet regions.Prentice et al.

5 Conclusions
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-44Manuscriptunderreview for journal Biogeosciences Discussion started: 20 February 2018 c Author(s) 2018.CC BY 4.0 License.Our results studied the impact factors (g s , g m , and V cmax ) on A and iWUE in plants with different life forms in field.The different contributions of g s , g m , and V cmax to A indicated that plants used diverse trade-off between CO 2 supply and demand to maintain relatively high A. iWUE was relatively low, but ranged widely, indicating that plants used 'profligate/opportunistic' water use strategy to maintain the survival, growth, and structure of the community.Those findings highlight the importance of co-variation of g s , g m , and V cmax for the adaptation of plants to the harsh environment.However, the effects of leaf anatomical traits on g s , g m , and the trade-off between leaf anatomical traits and V cmax should be further explored.