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Keywords:

  • carbon gain;
  • leaf hydraulic conductance;
  • leaf lifespan;
  • leaf size;
  • photosynthesis;
  • water transport

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Description
  5. Materials and Methods
  6. Results
  7. Discussion
  8. Conclusions
  9. Acknowledgements
  10. References
  11. Supporting Information
  • Previous research suggests that the lifetime carbon gain of a leaf is constrained by a tradeoff between metabolism and longevity. The biophysical reasons underlying this tradeoff are not fully understood.
  • We used a photosynthesis–leaf water balance model to evaluate biophysical constraints on carbon gain. Leaf hydraulic conductance (KLeaf), carbon isotope discrimination (Δ13C), leaf mass per unit area (LMA) and the driving force for water transport from stem to leaf (ΔΨStem–Leaf) were characterized for leaves spanning three orders of magnitude in surface area and two orders of magnitude in lifespan.
  • We observed positive isometric scaling between KLeaf and leaf area but no relationship between Δ13C and leaf area. Leaf lifespan and LMA had minimal effect on KLeaf per unit leaf area, but a negative correlation exists among LMA, lifespan, and KLeaf per unit dry mass. During periods of leaf water loss, ΔΨStem–Leaf was relatively constant.
  • We show for the first time that KLeaf, mass, an index of the carbon cost associated with water use, is negatively correlated with lifespan. This highlights the importance of characterizing KLeaf, mass and suggests a tradeoff between resource investment in liquid phase processes and structural rigidity.

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Description
  5. Materials and Methods
  6. Results
  7. Discussion
  8. Conclusions
  9. Acknowledgements
  10. References
  11. Supporting Information

For land plants, the greatest biophysical barrier to carbon gain, and ultimately survival, is the ability of leaves to maintain high surface conductance to CO2 while avoiding desiccation. This is because CO2 and water vapor exchange between leaves and the atmosphere share a common pathway through the stomatal pores on leaf surfaces. As such, any change in the architecture and distribution of stomatal pores that result in greater surface conductance to CO2 assimilation will also result in greater surface conductance to water vapor and ultimately leaf water loss for a given leaf to air vapor pressure difference (Cowan, 1977; Franks & Farquhar, 2001). This coupling between stomatal conductance (gs) to CO2 and water vapor, and the need to maintain a favorable leaf water balance, has led to a strong positive scaling between gs and the liquid phase transport capacity of leaves, that is, leaf hydraulic conductance per unit area; KLeaf, area (Sack et al., 2003; Sack & Frole, 2006; Brodribb et al., 2005. Further, owing to the tight coupling between gs and Aarea within and across C3 species (Wong et al., 1979), positive scaling between gs and KLeaf, area leads to positive scaling between KLeaf, area and Aarea (Brodribb et al., 2005, 2007; Franks, 2006).

In addition to having biophysical ties to carbon gain, the structure and function of the liquid-phase transport pathway in leaves directly influences leaf rigidity and ultimately longevity. This is because physical investment in leaf plumbing and strength are closely related. Specifically, the transpiration stream of a leaf occurs through a highly branched hydraulic network. Water moves from the petiole through a hierarchy of xylem conduits that form a network of veins, increasing in density from lower- to higher-order veins (McKown et al., 2010). The xylem conduits that form the leaf venation network contribute directly to leaf rigidity by increasing the leaf’s elastic modulus (an index of the stress to strain ratio of a material), at the same time providing water to other leaf tissues to create a hydrostatic skeleton via turgor maintenance (Niklas, 1999; Roth-Nebelsick et al., 2001). Further, leaf venation architecture directly influences leaf physiological tolerance to damages conferred by mechanical abrasions or insect attack (Sack et al., 2008). But it is also important to note that leaf veins only represent one pathway in the liquid phase of the transpiration stream. After passing through the xylem vascular network, water is transported through extra-xylem tissues via apoplastic, symplastic, and/or transcellular pathways to the sites of evaporation in the cell walls’ adjacent intercellular air spaces (Aasamaa et al., 2005; Sack & Holbrook, 2006; Zwieniecki et al., 2007; McKown et al., 2010). On average this extra-xylem pathway is considered to account for c. 50% of the total leaf hydraulic resistance (Sack & Holbrook, 2006). Although the exact sites of evaporation in the leaf are still debated (Meidner, 1975; Sheriff, 1977; Sack & Holbrook, 2006; Pieruschka et al., 2010), the vast majority of leaf tissues (e.g. palisade, spongy mesophyll, bundle sheath cells and epidermis) are considered to participate in the transpiration stream (Zwieniecki et al., 2007; Ye et al., 2008; Pieruschka et al., 2010). Structural modifications to these extra-xylem water transport pathways can enhance leaf longevity in response to mechanical and/or water stress, such as increased cell wall thickness, cell wall lignification and decreased internal air space, all of which result in greater leaf density and rigidity (Niklas, 1999; Wright & Westoby, 2002; Kitajima & Poorter, 2010). Because of this coupling between strength and plumbing in leaves, structural modifications that enhance leaf longevity are expected to increase the cost of the liquid-phase transport pathways that supply water used in the transpiration stream. Yet, how these costs impact on the efficiency of liquid-phase transport per unit leaf dry mass (i.e. KLeaf, mass) is not well understood.

In this paper we examine the coordination between variation in leaf lifespan (LL) and KLeaf on both an area and mass basis (i.e. KLeaf, area and KLeaf, mass) and explore how this coordination influences variation in lifetime leaf carbon gain. Specifically, our aim is to investigate the degree of coordination among leaf area, KLeaf, Leaf mass per unit area (LMA), and LL, and then explore how these leaf traits contribute to variation in the lifetime carbon gained by leaves using a coupled photosynthesis–leaf water balance model. Based on the coupling between strength and plumbing in leaves, the coupling between gs and KLeaf, area, and the strong dependence of carbon gain on gs, we predict that the cost of transpiration increases with leaf longevity such that KLeaf, mass decreases as LL increases (negative scaling); and that lifetime leaf water use is optimized for carbon gain.

Description

  1. Top of page
  2. Summary
  3. Introduction
  4. Description
  5. Materials and Methods
  6. Results
  7. Discussion
  8. Conclusions
  9. Acknowledgements
  10. References
  11. Supporting Information

Theory – biophysical linkages between leaf water balance and carbon gain

Whole-leaf net photosynthesis relates to leaf water loss and leaf hydraulic efficiency as follows using Fick’s and Darcy’s physical transport laws. Water vapor and CO2 diffusion across leaf surfaces can be described from first principles using Fick’s law. The rate of water loss from leaf to atmosphere is (Cowan, 1977; Farquhar & Sharkey, 1982):

  • image(Eqn 1)

where E is the rate of leaf water loss (mmol m−2 s−1), gs is whole-leaf conductance (mmol m−2 s−1) to water vapor, and (wiwa) is the difference between the mole fractions of water vapor (mmol mol−1) in the intercellular spaces and the air. Similarly, net photosynthesis (Aarea; μmol m−2 s−1) is described by Fick’s law as:

  • image(Eqn 2)

where ca is the molar concentration of CO2 in the air immediately outside the leaf (μmol mol−1), ci is the molar concentration of CO2 in the intercellular spaces (μmol mol−1) and 1.6 is the diffusivity correction between water vapor and CO2. Combining Eqns l and 2, the relationship between E and Aarea can be described as (Katul et al., 2003):

  • image(Eqn 3)

Since C3 angiosperms generally function across a narrow range of ci (Wong et al., 1979; Yoshie, 1986), increased resource allocation to leaf tissues that maintain high rates of E are required in order to increase Aarea for a given difference in the leaf to air mole fraction of water vapor (wiwa).

Biophysical constraints on maintaining high rates of E can be described using Darcy’s law:

  • image(Eqn 4)

where ΔΨStem–Leaf is the driving force for water transport from stem to leaf (MPa) and KLeaf, area is the rate of water transport per unit ΔΨStem–Leaf (mmol m−2 s−1 MPa−1). Leaves often operate within a relatively narrow range of ΨLeaf because KLeaf, area and turgor are sensitive to large ΔΨLeaf (Sack & Holbrook, 2006). As such, leaf hydraulic conductance must increase in order to maintain high rates of E while avoiding turgor loss and increased risk of air embolism.

By combining Eqns 3 and 4, the functional relationship between maximum KLeaf, area and Aarea, is described as:

  • image(Eqn 5)

and thus

  • image(Eqn 6)

Therefore, according to biophysical transport laws, increases in KLeaf, area should enhance photosynthetic carbon gain for a given ΔΨStem–Leaf, (wiwa), and ci/ca. Based on the coordination between KLeaf, area and Aarea the influence of KLeaf on lifetime carbon gain can be modeled as:

  • image(Eqn 7)

where inline image is lifetime carbon gain (mol C g−1). Whereas lifetime leaf water use is a function of:

  • image(Eqn 8)

where inline image is lifetime leaf water use per unit leaf dry mass (mol H2O g−1). Using Eqns 7 and 8, and log–log scaling slope analysis, we can evaluate how the covariation among LL, LMA and KLeaf influences lifetime carbon gain and water use via the simple linear model: log(Y ) = β + αlog(X ); where X and Y represent two continuous traits, such as KLeaf, mass and LL, β is a constant, and α describes the slope of the log-transformed relationship between X and Y. According to log-log scaling slope analysis, if α = −l or +l (known as isometric scaling between X and Y ), then a change in KLeaf, mass (i.e. X in this example) is associated with an equal proportional change in LL (i.e. Y). Deviations from an α = −l or +l means that a change in KLeaf, mass is associated with a disproportionate change in LL.

Materials and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Description
  5. Materials and Methods
  6. Results
  7. Discussion
  8. Conclusions
  9. Acknowledgements
  10. References
  11. Supporting Information

Leaf hydraulic conductance and leaf size data sets

The whole-leaf hydraulic conductance (KLeaf; mmol s−1 MPa−1) and leaf area (cm2) data used in this study come both from previously published data (Nardini & Salleo, 2000; Sack et al., 2002; Lo Gullo et al., 2005; Nardini et al., 2005; Sack & Frole, 2006; Scoffoni et al., 2008) and from a new set of measurements made on leaves collected in the University of California, Berkeley Botanical Garden (UCBG; Supporting Information Table S1). We used the evaporative flux method described in detail by Sack et al. (2002) to measure KLeaf for the species collected at the UCBG. The KLeaf and leaf area data collected from previously published data sets were gathered from data tables when available and from figures if data were not presented in tabular form (Graph Click version 3.0, Arizona Software, Tucson, AZ, USA). If multiple methods were used in a single study, we included only the data obtained using the evaporative flux method when available. The combined data set provided KLeaf values for 54 species spanning three orders of magnitude in leaf area. The data set used to test for the covariation among KLeaf per unit leaf area (KLeaf, area), KLeaf per unit leaf mass (KLeaf, mass), and LMA (Brodribb et al., 2005; Nardini et al., 2005; Sack et al., 2005; Scoffoni et al., 2008) consisted of 58 species (Table S2).

Leaf and stem water potential

In an effort to capture a wide range of variation in leaf and stem water potential, measurements were made on leaves and stems collected from plant species growing in the UCBG and plant species occurring in their native range (Table S3). We measured the driving force for water transport from stem to leaf (i.e. ΔΨStem–Leaf) using a Scholander-type pressure chamber (SAPS II, Soil Moisture Equipment Corp., Santa Barbara, CA, USA). This technique for measuring ΔΨStem–Leaf requires sampling two adjacent leaves: one is used to measure stem water potential (ΨStem) while the adjacent leaf is sampled for leaf water potential (ΨLeaf). Leaves used as an assay for ΨStem were covered in plastic film and aluminum foil the evening before the measurement period to allow for equilibration between stem xylem water potential and the covered leaf water potential. Immediately following excision, the uncovered leaf was wrapped in plastic and placed in a Scholander-type pressure chamber for determination of ΨLeaf (SAPS II). After measuring ΨLeaf, the paired covered leaf was placed in the pressure chamber for determination of ΨStem. Balancing pressure was recorded when xylem exudates reached the cut stem surface as verified by a dissecting scope at ×25 magnification. We used this technique to evaluate ΔΨStem–Leaf during periods of leaf water loss and carbon assimilation for a wide range of distantly related temperate and tropical plant species (Table S3).

Stable carbon isotope data

We estimated variation in flux weighted ci/ca by measuring carbon isotope discrimination (Δ13C). For C3 species, Δ13C varies linearly with variation in ci/ca as described by (Farquhar & Richards, 1984):

  • image(Eqn 9)

where a is the fractionation resulting from diffusion in air (4.4‰), and b is the net fractionation as a result of carboxylation (RuBP carboxylase, 27‰) and d is a composite variable that includes fractionation during photorespiration, dark respiration and the transport of CO2 to the chloroplasts. Bulk leaf material was sampled from 40 species spanning three orders of magnitude in leaf surface area (LA). Leaves for the 40 species were gathered from the UCBG collection (Table S4). The Δ13C of bulk leaf material was measured as (Brugnoli & Farquhar, 2004):

  • image(Eqn 10)

where δa is the δ13C of source CO2 (measured as −11‰ for the glasshouse plants and −9‰ for plants grown outdoors) and δp is the δ13C of bulk leaf material. For C3 species Δ13C typically varies between 13 and 25‰ (Farquhar et al., 1989; Dawson et al., 2002).

Leaf lifespan data

The LL data were collected from previously published studies (Wright et al., 2004; Brodribb & Holbrook, 2005) along with measurements made on species at the UCBG. For species at the UCBG, LL was calculated by monitoring the time between first bud break and leaf senescence on marked branches over 2 yr (2007–2008). Estimates of LL for species with LL > 2 yr (i.e. Pinus ponderosa, Sequoia sempervirens and Umbellaria californica) were based on the number of successive cohorts maintained on a branch during the period of study. Our estimates of LL for P. ponderosa, Arbutus menziesii, Populus fremontii, and S. sempervirens were consistent with previous evaluations (Espinosa-Garcia & Langenheim, 1990; Reich et al., 1998; Ackerly, 2004). In addition, we surveyed the literature to find studies where KLeaf and LMA were measured simultaneously. If KLeaf was measured and expressed per unit leaf area (i.e. KLeaf, area) then leaf hydraulic conductance per unit leaf mass was calculated as KLeaf, area × 1/LMA. Leaf trait data were collected from data tables first, and figures second if data were not presented in tabulated form (Graph Click version 3.0, Arizona Software). Studies that only reported KLeaf and LMA were used if LL data for individuals grown in a similar climate were available from the GLOPNET database (Wright et al., 2004). Only one study reported all three leaf traits (Brodribb & Holbrook, 2005). Leaf lifespan data for three of the species found in Brodribb & Holbrook (2005) and the UCBG also occurred in the GLOPNET database; these measurements of LL varied by < 2 months from the GLOPNET data. The total number of species available for the KLeaf vs LL comparison was 24. The GLOPNET database was used as an estimate of LL for 13 of the 24 KLeaf–LL pairs. We calculated the slope and intercept for linear models describing the functional relationship between leaf traits using SMATR version 2.0 (Falster et al., 2006).

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Description
  5. Materials and Methods
  6. Results
  7. Discussion
  8. Conclusions
  9. Acknowledgements
  10. References
  11. Supporting Information

As reported previously (Tyree et al., 1999; Salleo & Nardini, 2000; Sack et al., 2003), we observed no correlation between LMA and KLeaf, area for the eight species we studied at the UCBG or when the common garden species were combined with previously published data (Fig. 1a; Table 1). We observed a weak correlation between LL and KLeaf, area (r2 = 0.32) for the eight species we studied at the UCBG (Fig. 1b; Table 1). When the common garden species were combined with previously published data, a significant yet weak correlation was observed between LL and KLeaf, area (r2 = 0.22; Fig. 1b; Table 1).

image

Figure 1. Covariation between leaf form and function. (a) The independence of leaf hydraulic conductance per unit area (KLeaf, area) and leaf mass per unit area (LMA); (b) the covariation between KLeaf, area and leaf lifespan (LL); (c), the covariation between leaf hydraulic conductance per unit lamina mass (KLeaf, mass) and LMA; (d) the covariation between KLeaf, mass and LL. Ac, Acer macrophyllum; Ar, Arbutus menziesii; Me, Metasequoia glyptostroboides; Pi, Pinus ponderosa; Po, Populus fremontii; Qu, Quercus kelloggii; Se, Sequoia sempervirens; Um, Umbellularia californica; circles, species from the common garden; squares, previously published values for deciduous and evergreen woody species and herbaceous species (Wright et al., 2004; Brodribb & Holbrook, 2005; Brodribb et al., 2005; Nardini et al., 2005; Sack et al., 2005; Scoffoni et al., 2008). Only one study reported KLeaf, area, LMA, and estimates of LL (Brodribb & Holbrook, 2005). The remainder of the studies reported both KLeaf, area and LMA with estimates of LL obtained from species mean values reported in the GLOPNET database (Wright et al., 2004). The solid regression lines were fitted to the species used in this study; the bold dotted line was fitted to the entire dataset. The regression slopes for the entire dataset are presented in Table 1.

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Table 1.   Standardized major axis (SMA) regression slopes (α) for log–log linear relationships among leaf hydraulic conductance (KLeaf) per unit area (KLeaf, area) and mass (KLeaf, mass), leaf surface area (LA), leaf mass per unit area (LMA) and leaf lifespan (LL) measured at the University of California, Berkeley Botanical Garden and from previously published data
 α95% CIr2ModelH  = 1
  1. Also shown are results from a test comparing the observed SMA slopes to 1 (H = 1).

Log KLeaf vs log LA1.070.97, 1.180.85< 0.0001= 0.16
Log KLeaf, area vs log LMA−0.91−1.17, −0.710.02= 0.31= 0.48
Log KLeaf, area vs log LL−0.80−1.15, −0.540.22= 0.018= 0.22
Log KLeaf, mass vs log LMA−1.48−1.69, −1.300.66< 0.0001< 0.001
Log KLeaf, mass vs log LL−1.09−1.39, −0.860.69< 0.0001= 0.46

In contrast to the area-based measures, a strong correlation was observed between KLeaf, mass, LMA and LL. For the eight species we studied at the UCBG, as LMA increased, KLeaf, mass decreased (r= 0.58; Fig. 1c; Table 1). This same trend was observed when the common garden species were combined with previously published data (r2 = 0.66; Fig. 1c; Table 1). Similarly, an increase in LL was associated with a decrease in KLeaf, mass for both the common garden species (r2 = 0.82; Fig. 1d; Table 1) and the combined data set (r2 = 0.69; Fig. 1d; Table 1). The slope describing the covariation between KLeaf, mass and LL was not significantly different from 1 (Table 1). Overall, the coordination among KLeaf, mass, LMA and LL was much stronger and more consistent than the coordination among KLeaf, area, LMA and LL (Fig. 1; Table 1).

We observed a strong positive relationship between KLeaf and LA (r2 = 0.86; Fig. 2a; Table 1) for the 54 species we compared. The slope describing the covariation between KLeaf and LA was not significantly different from 1 (Table 1). Therefore, on average, an increase in LA is accompanied by a proportionally equal increase in KLeaf and thus variation in KLeaf, area is independent of variation in LA as suggested by previous model simulataions (McKown et al., 2010). We observed a relatively small amount of variation in Δ13C for species grown in a common environment (Table S1), and no relationship between Δ13C and LA (Fig. 2b). This finding is consistent with previous research (Wong et al., 1979; Yoshie, 1986). The lack of a correlation between Δ13C and LA suggests that small variations in ci/ca can occur for any given E and therefore gs (Eqns l–6). Additionally, variation in leaf and stem water potential during periods of leaf water loss and carbon gain were tightly coordinated, resulting in a relatively constant ΔΨStem–Leaf of −0.32 MPa (r2 = 0.97; ΨLeaf = 1.01(ΨStem) – 0.32; Fig. 2c).

image

Figure 2. Log–log bivariate relationship between leaf hydraulic conductance (KLeaf) and leaf surface area (LA) (a); stable isotope discrimination (Δ13C) and LA (b); covariation between stem water potential (ΨStem) and leaf water potential (ΨLeaf) during periods of leaf water loss (c). The standardized major axis regression curve is shown as a solid line. The slope of the linear model describing the covariation between KLeaf and LA is presented in Table 1.

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Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Description
  5. Materials and Methods
  6. Results
  7. Discussion
  8. Conclusions
  9. Acknowledgements
  10. References
  11. Supporting Information

Our study provides strong support for the hypothesis that variation in LL is tightly coupled to variation in the cost of water transport as measured by KLeaf, mass. Across two orders of magnitude in LMA, we observed a strong negative relationship between KLeaf, mass and LMA and no correlation between LMA and KLeaf, area. Similarly, across two orders of magnitude in LL we observed a strong negative relationship between KLeaf, mass and LL and a relatively weak correlation between KLeaf, area and LL. This lack of a consistent correlation between LMA and KLeaf, area has led previous investigators to conclude that KLeaf, a pivotal plant water-relations trait, is orthogonal (i.e. statistically independent) to traits influencing LL and, by extension, lifetime carbon gain (Sack et al., 2003; Sack & Frole, 2006). However, standardizing leaf traits by leaf surface area obscures existing variation in the carbon cost of light interception, gas exchange, and water transport that are, in fact, present if the traits are standardized by dry mass. For example, A. menziesii, P. ponderosa, and U. californica all possess dense, long-lived leaves and showed higher maximum KLeaf, area than Metasequoia glyptostroboides, a species with short-lived leaves (Fig. 1a). Yet, when KLeaf was standardized by leaf dry mass, M. glyptostroboides had greater KLeaf, mass than both P. ponderosa and U. californica, and was equivalent to A. menziesii because of a lower LMA (Fig. 1c,d). Similarly, Reich et al. (1997) and Wright et al. (2004) found that variations in LL and LMA were weakly correlated with variation in photosynthetic capacity when expressed on an area basis (Aarea). Although previous research has shown that the cost of water transport, as measured by the fractional investment of lamina biomass in the midrib, is tied to variation in LL (Niinemets et al., 2007), the present study shows for first time that the cost of leaf water transport, as measured by KLeaf, mass, is tightly coupled to variation in LL.

Functional basis for the coordination between leaf lifespan, LMA and KLeaf on a mass vs area basis

Variation in LMA occurs via changes in leaf density (LD; g mm−3) and/or leaf thickness (T; mm) where inline image. Across genera, LD is relatively independent of variation in leaf thickness (Niinemets, 1999) and a recent meta-analysis by Poorter et al. (2009) showed that variation in LMA is more closely related to changes in LD than to changes in thickness. Further, previous research has shown that LL is positively correlated with LD and often independent of variation in thickness (Kitajima & Poorter, 2010; Wright & Westoby, 2002; although see Wright & Cannon, 2001). Taken together, the positive correlation between LD and LMA (Poorter et al., 2009) and LD and LL (Wright & Westoby, 2002; Kitajima & Poorter, 2010) provides firm evidence that LD strongly influences the coordination between LMA and LL.

Variation in LD, both within and between species, occurs through changes in the relative contribution of different leaf tissues toward whole leaf dry mass. Although leaves are composed of a wide variety of cell and tissue types, the total volume of a leaf (VL) can be divided into three broad component volumes that directly influence the overall structure and function of leaves: the volume occupied by air spaces (Va), the volume occupied by cell walls and the cuticle, that is, the structural volume (Vw), and the volume bound by the plasma membrane (Vc; Shipley et al., 2006; Roderick et al., 1999a,b). In general, Vw represents the vast majority of leaf dry mass such that variation in leaf dry mass is approximately equal to the product of Vw and the specific gravity of cell walls (d ), which is relatively constant at c. 1.5 across species (Desch, 1973; Siau, 1984). As such, LD can be approximated by:

  • image

Thus, increases in LD, and by extension LMA, can occur through decreases in the ratio of Vc/Vw and/or Va/Vw. Changes in Vc/Vw are driven largely by changes in the average leaf cell wall thickness relative to the average size of leaf cells, whereas changes in Va/Vw are dictated by variation in the packing of mesophyll cells, that is, changes in the fractional airspace, Va/VL. These changes in leaf architecture are expected to directly influence liquid- and/or vapor-phase transport within and between the leaf tissues that define the leaf transpiration stream (Boyer, 1974; Cruziat et al., 1980; Tyree et al., 1981; Fricke, 2000; Sack et al., 2004; Aasamaa et al., 2005; Zwieniecki et al., 2007; Ye et al., 2008; Pieruschka et al., 2010).

Although the effect of changes in Vc/Vw and/or Va/Vw on leaf water transport has not been evaluated, previous research suggests the hydraulic linkages between the xylem and extra-xylem transport pathways and the relative contribution of different leaf tissues to the transpiration stream are influenced by changes in Vc /Vw and/or Va /Vw and therefore LMA. For example, if we assume that the rehydration kinetics of leaves are symmetrical with the transpiration stream, then data from Zwieniecki et al. (2007) suggest that for leaves with relatively large bundle sheath extensions and a dense mesophyll (i.e. mesophyll with low Va/Vw), the vast majority of extra-xylem tissues are likely to participate in the fast phase of the transpiration stream; whereas for leaves with a relatively diffuse mesophyll, the epidermis appears to be the major extra-xylary tissue involved in the transpiration stream, with much less water originating from the palisade and spongy mesophyll tissues. Therefore, according to the interpretations by Zwieniecki et al. (2007), as mesophyll density increases so does the volume of liquid-phase transport pathways involved in the fast phase of the transpiration stream. Since the hydraulic architecture of a leaf approximates a hierarchical network of parallel resistors (Sack & Holbrook, 2006; McKown et al., 2010) and resistors in parallel add in reciprocal, then, all else being equal, an increase in the number of parallel resistors (e.g. space filling through greater packing of conduits) should result in lower resistance to liquid-phase transport. However, if this were true, as LMA and the number of extra-xylem pathways increase, leaf hydraulic conductance should also increase, resulting in a positive correlation between KLeaf, area and LMA. Yet, across genera no consistent relationship is observed between KLeaf, area and LMA (Fig. 1a) or LD (see appendix D from Sack & Frole, 2006). Instead a negative correlation is seen between KLeaf, mass and LMA, and KLeaf, mass and LL (Fig. 1c,d). This lack of an area-based correlation suggests that the extra-xylem pathways for water transport in leaves with a high LD and LMA are, on a pathway-by-pathway basis, more resistant than the extra-xylem pathways for water transport in leaves with a low LD and LMA, such that summing the resistances in parallel has little to no effect on KLeaf, area. Therefore, the lack of correlation between KLeaf, area and LMA, and the negative correlation among KLeaf, mass, LMA and LL provides strong evidence for a biophysical tradeoff between resource allocation to extra-xylem tissues specialized for liquid-phase processes (i.e. high KLeaf, mass) vs structural rigidity and longevity (i.e. low KLeaf, mass).

Implications for lifetime leaf water loss and carbon gain

The data presented here suggest that lifetime leaf water use is optimized to maximize leaf carbon gain. Across two orders of magnitude of variation in LA, we observed strong positive isometric scaling between KLeaf and LA. Isometric scaling between KLeaf and LA means that, on average, any increase in LA is accompanied by a proportionally equal increase in KLeaf, and thus KLeaf, area is independent of variation in LA, as seen in previous evaluations and modeling simulations (Sack & Frole, 2006; McKown et al., 2010). Additionally, during periods of leaf water loss and CO2 assimilation, we observed a relatively constant driving gradient for water transport from stem to leaf (i.e. ΔΨStem–Leaf). Furthermore, for the species grown in a common environment, Δ13C was uncorrelated with variation in LA. According to the coupled photosynthesis–leaf water balance model shown in Eqn 6, a relatively constant ΔΨStem–Leaf along with relatively small variations in Δ13C, and by extension time-integrated ci/ca (Eqn 9), suggests KLeaf, area is directly proportional to Aarea. However, despite relatively constant Δ13C and ΔΨStem–Leaf, the actual amount of carbon gain per unit leaf water loss (i.e. inline image) is tightly coupled to variation in the water vapor concentration difference from leaf to air (i.e. (wiwa); see Eqns 5, 6). It is widely recognized that (wiwa) is tightly coupled to variation in leaf form, in particular variation in leaf area. This is because, larger leaves heat up faster in sunlight than smaller leaves, as a result of increased resistance to sensible heat loss, resulting in greater wi (Gates, 1980). Thus in order to minimize (wiwa) and optimize leaf water loss for carbon gain, leaves should decrease in size in response to increasing radiation interception and atmospheric demand for water (i.e. lower wa). If LA varies in a way that minimizes (wiwa) then the maximum potential lifetime carbon gain of a leaf is dependent on the covariation between KLeaf, mass and LL as shown by Eqn 7.

We observed negative isometeric scaling between KLeaf, mass and LL across the 24 species evaluated here (Fig. 1d). Negative isometric scaling between KLeaf, mass and LL means that, on average, any increase in LL is associated with an equally proportional decrease in KLeaf, mass. Therefore, according to the lifetime leaf water use model described in Eqn 8, since variation in LL results in an equally proportional change in KLeaf, mass, but in the opposite direction (i.e. negative isometric scaling), and ΔΨStem–Leaf is relatively constant, lifetime leaf water use per unit leaf dry mass (inline image) is relatively constant and independent of variation in LL. Similarly according to the lifetime leaf carbon gain model described in Eqn 7, since Δ13C and ΔΨStem–Leaf are relatively constant and KLeaf, mass scales negatively and isometrically with variation in LL, lifetime leaf carbon gain per unit dry mass (inline image) is relatively constant and independent of variation in LL. Therefore, according to Eqns 7 and 8 the data reported here suggests lifetime leaf water loss has been optimized for carbon gain such that inline image is independent of variation in LL.

Although negative isometric scaling between KLeaf, mass and LL suggests that lifetime leaf water loss has been optimized for carbon gain (i.e. inline imageis relatively constant) it is important to note that Eqns 7 and 8 are estimates of the maximum potential carbon gain and water use, yet the actual lifetime carbon gain and water use of a leaf is much more complex (Mediavilla & Escuders, 2003; Kikuzawa et al., 2004; Kikuzawa & Lechowicz, 2006; Blonder et al., 2010). For example, LL often overestimates the physiologically active LL. This is especially true for species that inhabit a seasonal climate, when temperature and water availability regularly fall below the minimum requirement for photosynthetic metabolism on an annual basis (Kikuzawa et al., 2004). Further, changes in water availability and subsequently ΨLeaf can have negative consequences for KLeaf via water stress-induced hydraulic failure (Sack & Holbrook, 2006), although, to date, there is no evidence of a tradeoff between KLeaf and the susceptibility to water stress-induced hydraulic failure on either an area basis (KLeaf, area; Blackman et al., 2010; Sack & Holbrook, 2006; Sack et al., 2003) or a mass basis (based on data from table 1 of Blackman et al., 2010; KLeaf, mass = KLeaf, area × 1/LMA). However, a weak positive relationship has been observed between LMA and the water potential at which 50% hydraulic failure occurs. Therefore, the data presented here suggest that further research into the susceptibility of KLeaf, mass to hydraulic failure, when exposed to variation in water availability, is needed to better understand the biophysical limitations on LL and the lifetime carbon gain of leaves.

Conclusions

  1. Top of page
  2. Summary
  3. Introduction
  4. Description
  5. Materials and Methods
  6. Results
  7. Discussion
  8. Conclusions
  9. Acknowledgements
  10. References
  11. Supporting Information

The results of this study support the hypothesis that the cost of leaf water use as measured by KLeaf, mass is negatively correlated with LL and provides strong evidence for a tradeoff between dry-mass allocation to leaf tissues specialized for structural rigidity and longevity and those specialized for efficient KLeaf, mass. Further research is required to better understand how the extra-xylem water transport pathway varies with changes in LMA and how variation in leaf architecture influences KLeaf, mass and the susceptibility of leaves to hydraulic failure.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Description
  5. Materials and Methods
  6. Results
  7. Discussion
  8. Conclusions
  9. Acknowledgements
  10. References
  11. Supporting Information

The authors would like to thank Greg Goldsmith, Adam Roddy, Michal Shuldman, Margaret Barbour and Peter Franks for valuable comments on an earlier draft and Jarmila Pittermann for valuable discussions and assistance with setting up equipment for use with the evaporative flux method. We also thank the anonymous reviewers for comments that greatly improved the manuscript.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Description
  5. Materials and Methods
  6. Results
  7. Discussion
  8. Conclusions
  9. Acknowledgements
  10. References
  11. Supporting Information

Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Description
  5. Materials and Methods
  6. Results
  7. Discussion
  8. Conclusions
  9. Acknowledgements
  10. References
  11. Supporting Information

Table S1 Mean leaf surface area (LA), leaf hydraulic conductance (KLeaf) for species used in the analysis

Table S2 Mean leaf mass per unit area (LMA) and leaf hydraulic conductance per unit leaf area (KLeaf, area) for species used in the analysis

Table S3 Species used to evaluate the driving force for water movement from stem to leaf (ΔΨStem–Leaf) during periods of leaf water loss

Table S4 Mean leaf surface area (LA) and carbon isotope discrimination (Δ13C) for species used in the analysis

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