Abstract

The response of whole-plant water-use efficiency, termed transpiration efficiency (TE), to variation in soil fertility was assessed in a tropical pioneer tree, Ficus insipida Willd. Measurements of stable isotope ratios (δ13C, δ18O, δ15N), elemental concentrations (C, N, P), plant growth, instantaneous leaf gas exchange, and whole-plant water use were used to analyse the mechanisms controlling TE. Plants were grown individually in 19 l pots with non-limiting soil moisture. Soil fertility was altered by mixing soil with varying proportions of rice husks, and applying a slow release fertilizer. A large variation was observed in leaf photosynthetic rate, mean relative growth rate (RGR), and TE in response to experimental treatments; these traits were well correlated with variation in leaf N concentration. Variation in TE showed a strong dependence on the ratio of intercellular to ambient CO2 mole fractions (ci/ca); both for instantaneous measurements of ci/ca (R2=0.69, P <0.0001, n=30), and integrated estimates based on C isotope discrimination (R2=0.88, P <0.0001, n=30). On the other hand, variations in the leaf-to-air humidity gradient, unproductive water loss, and respiratory C use probably played only minor roles in modulating TE in the face of variable soil fertility. The pronounced variation in TE resulted from a combination of the strong response of ci/ca to leaf N, and inherently high values of ci/ca for this tropical tree species; these two factors conspired to cause a 4-fold variation among treatments in (1–ci/ca), the term that actually modifies TE. Results suggest that variation in plant N status could have important implications for the coupling between C and water exchange in tropical forest trees.

Introduction

Water-use efficiency at the whole-plant level, often referred to as transpiration efficiency (TE), is defined as the rate of biomass production of a plant relative to the rate of transpiration (Bacon, 2004). Although ecophysiologists frequently assess water-use efficiency at the leaf level, relatively few measurements of TE have been reported, largely due to the logistical challenges involved in obtaining such data. Nonetheless, the whole plant is clearly a meaningful organizational level at which to analyse controls over growth, CO2 exchange, and water use (McCree, 1986; Meinzer and Goldstein, 1996). The TE effectively describes the coupling between whole-plant C and water exchange in terrestrial vegetation. Thus, a mechanistic understanding of the controls over TE is relevant to studies of plant competition, ecosystem function, and plant responses to climate change. In tropical forests, it was recently reported that seasonal drought significantly impacts tree community dynamics (Engelbrecht et al., 2007), suggesting that TE could play an important role in determining the performance and distribution of tropical tree species.

Leaf-level water-use efficiency generally increases in response to increasing leaf N concentration in C3 plants (Wong, 1979; Toft et al., 1989; Duursma and Marshall, 2006). This is because more leaf N is usually associated with more photosynthetic capacity, which allows for a greater photosynthetic rate at a given rate of water loss. At the whole-plant scale, the TE of trees has also generally been observed to increase with increasing N availability (Guehl et al., 1995; Syvertsen et al., 1997; Livingston et al., 1999; Ripullone et al., 2004), although not always (Guehl et al., 1995; Hobbie and Colpaert, 2004). This trend also appears to apply for tropical trees: TE of Ficus insipida Willd., a fast-growing tropical pioneer tree capable of high rates of photosynthesis (Zotz et al., 1995), increased in response to fertilizer application (Winter et al., 2001); and a linear relationship was observed between TE and leaf N concentration in an experiment involving seven tropical tree species (Cernusak et al., 2007). Although there appears to be general agreement among experiments regarding the direction of response of tree TE to variation in soil fertility (Raven et al., 2004), the physiological mechanisms modulating the response are less well understood. For example, it was suggested that variation in respiratory C use (Guehl et al., 1995), or in the amount of unproductive water loss (Hobbie and Colpaert, 2004), could play important roles in determining the response of TE to soil fertility, in addition to the effects associated with leaf-level photosynthesis.

Since the revelation that C isotope fractionation correlates positively with the ratio of intercellular to ambient CO2 mole fractions in C3 plant leaves (Farquhar et al., 1982), analysis of 13C/12C in plant organic material has played an important role in water-use efficiency research (Bacon, 2004). It was later suggested that analysis of 18O/16O in plant organic material could also aid investigations of water-use efficiency by providing complementary information to that obtained from C isotope analyses (Farquhar et al., 1989; Sternberg et al., 1989). In this study, measurements of C and O isotope ratios were combined with measurements of plant elemental composition, growth, instantaneous leaf gas exchange, and whole-plant water use to analyse the mechanisms controlling the response of TE of the tropical pioneer tree Ficus insipida to variation in soil fertility.

Theory

At the leaf level, photosynthetic water-use efficiency can be expressed as the quotient of the diffusive fluxes of CO2 and water vapour into and out of the leaf, respectively, during photosynthesis (Farquhar and Richards, 1984): 

(1)
graphic
where A is net photosynthesis (μmol CO2 m−2 s−1), E is leaf transpiration (mmol H2O m−2 s−1), ca and ci are atmospheric and intercellular CO2 mole fractions (μmol mol−1), 1.6 is the ratio of diffusivities for water vapour and CO2 in air, and v is the leaf-to-air water vapour mole fraction difference (mmol mol−1). A list of symbols used in the text is given in Table 1. Equation (1) can be scaled to the whole-plant level by taking into account respiratory C use and water loss not associated with photosynthesis (Farquhar and Richards, 1984; Hubick and Farquhar, 1989). Thus, whole-plant transpiration efficiency (TE) can be defined as 
(2)
graphic
where TE is mmol C fixed in plant biomass mol−1 H2O transpired by the plant; ϕc is the proportion of C fixed during photosynthesis that is subsequently lost by respiration from roots and stems during the day, and from roots, stems, and leaves during the night; and ϕw is the proportion of unproductive water loss relative to that associated with C uptake, i.e. nocturnal transpiration through partially open stomata and cuticular water loss by leaves and stems during the day and night.

Table 1.

Symbols used in the text

A Net photosynthetic rate (μmol CO2 m−2 s−1
a 13C/12C discrimination during diffusion through the stomatal pore 
ab 13C/12C discrimination during diffusion through the leaf boundary layer 
al 13C/12C discrimination during liquid phase diffusion 
b 13C/12C discrimination by carboxylating enzymes during C3 photosynthesis 
C Molar concentration of water (mol m−3
ca Ambient CO2 mole fraction (μmol mol−1
ci Intercellular CO2 mole fraction (μmol mol−1
D Diffusivity of H218O in water (m2 s−1
d 13C/12C discrimination caused by processes other than a and b during C3 photosynthesis 
E Transpiration rate (mmol H2O m−2 s−1
Egrav Plant transpiration determined gravimetrically (mmol H2O m−2 s−1
Etot Cumulative transpiration over the course of an experiment (mol H2O) 
e 13C/12C discrimination during dark respiration 
es 13C/12C discrimination during dissolution of CO2 into water 
f 13C/12C discrimination during photorespiration 
gb Boundary layer conductance to CO2 (mol m−2 s−1
gc Total conductance to CO2 of stomata plus boundary layer (mol m−2 s−1
gi Mesophyll conductance to CO2 (mol m−2 s−1
I Intercept of the linear relationship between TE and Δ13
k Carboxylation efficiency during C3 photosynthesis (mol CO2 m−2 s−1
L Scaled effective path length in relation to 18O advection/diffusion (m) 
LA Leaf area (m2
MTR Mean transpiration rate (mol H2O m−2 d−1
m Slope of the linear relationship between TE and Δ13
Narea Leaf N concentration expressed on an area basis (mmol N m−2
N/P Mass ratio of N to P in leaf dry matter 
PFD Photosynthetic photon flux density (μmol m−2 s−1
Parea Leaf P concentration expressed on an area basis (mmol P m−2
pex Proportion of O atoms exchanging with local water during cellulose synthesis 
px Proportion of unenriched source water in developing plant tissues 
Rd Leaf dark respiration rate (μmol CO2 m−2 s−1
RGR Mean relative growth rate (mg g−1 d−1
rb Boundary layer resistance (m2 s mol−1
rs Stomatal resistance (m2 s mol−1
T Leaf temperature in K 
TE Transpiration efficiency (mmol C mol−1 H2O) 
TEN Transpiration efficiency of N acquisition (μmol N mol−1 H2O) 
TL Leaf temperature in C 
t Number of days in experiment 
v Leaf-to-air water vapour mole fraction difference (mmol mol−1
wa Water vapour mole fraction of ambient air (mmol mol−1
wi Water vapour mole fraction in the intercellular air spaces (mmol mol−1
Δ13Photosynthetic 13C/12C discrimination 
Δ13CL 13C/12C discrimination in leaf dry matter 
Δ13CS 13C/12C discrimination in stem dry matter 
Δ13CR 13C/12C discrimination in root dry matter 
Δ13Cwp 13C/12C discrimination in whole plant dry matter 
Δ1818O/16O enrichment relative to source water 
Δ18Oc 18O/16O enrichment of plant cellulose relative to source water 
Δ18Oe 18O/16O enrichment at the evaporative sites in leaves relative to source water 
Δ18OL 18O/16O enrichment of leaf mesophyll water relative to source water 
Δ18Op 18O/16O enrichment of plant dry matter relative to source water 
Δ18Ov 18O/16O enrichment of atmospheric water vapour relative to source water 
δ1313C/12C of a sample expressed relative to the Pee Dee Belemnite standard 
δ13Ca 13C/12C of atmospheric CO2 expressed relative to the Pee Dee Belemnite standard 
δ13Cp 13C/12C of plant material expressed relative to the Pee Dee Belemnite standard 
δ1515N/14N of a sample expressed relative to that of air 
δ1818O/16O of a sample expressed relative to that of Vienna Standard Mean Ocean Water 
δ18Op δ18O of leaf dry matter 
δ18Os δ18O of source water 
εcp δ18O difference between plant cellulose and plant dry matter 
εk 18O/16O fractionation during water vapour diffusion through stomata and boundary layer 
εwc Equilibrium 18O/16O fractionation between organic O and medium water 
ε+ Equilibrium 18O/16O fractionation between liquid water and vapour 
ϕc Proportion of fixed C respired to the atmosphere 
ϕw Ratio of unproductive to productive water loss 
Γ* CO2 compensation point of C3 photosynthesis in the absence of Rd 
℘ Péclet number 
A Net photosynthetic rate (μmol CO2 m−2 s−1
a 13C/12C discrimination during diffusion through the stomatal pore 
ab 13C/12C discrimination during diffusion through the leaf boundary layer 
al 13C/12C discrimination during liquid phase diffusion 
b 13C/12C discrimination by carboxylating enzymes during C3 photosynthesis 
C Molar concentration of water (mol m−3
ca Ambient CO2 mole fraction (μmol mol−1
ci Intercellular CO2 mole fraction (μmol mol−1
D Diffusivity of H218O in water (m2 s−1
d 13C/12C discrimination caused by processes other than a and b during C3 photosynthesis 
E Transpiration rate (mmol H2O m−2 s−1
Egrav Plant transpiration determined gravimetrically (mmol H2O m−2 s−1
Etot Cumulative transpiration over the course of an experiment (mol H2O) 
e 13C/12C discrimination during dark respiration 
es 13C/12C discrimination during dissolution of CO2 into water 
f 13C/12C discrimination during photorespiration 
gb Boundary layer conductance to CO2 (mol m−2 s−1
gc Total conductance to CO2 of stomata plus boundary layer (mol m−2 s−1
gi Mesophyll conductance to CO2 (mol m−2 s−1
I Intercept of the linear relationship between TE and Δ13
k Carboxylation efficiency during C3 photosynthesis (mol CO2 m−2 s−1
L Scaled effective path length in relation to 18O advection/diffusion (m) 
LA Leaf area (m2
MTR Mean transpiration rate (mol H2O m−2 d−1
m Slope of the linear relationship between TE and Δ13
Narea Leaf N concentration expressed on an area basis (mmol N m−2
N/P Mass ratio of N to P in leaf dry matter 
PFD Photosynthetic photon flux density (μmol m−2 s−1
Parea Leaf P concentration expressed on an area basis (mmol P m−2
pex Proportion of O atoms exchanging with local water during cellulose synthesis 
px Proportion of unenriched source water in developing plant tissues 
Rd Leaf dark respiration rate (μmol CO2 m−2 s−1
RGR Mean relative growth rate (mg g−1 d−1
rb Boundary layer resistance (m2 s mol−1
rs Stomatal resistance (m2 s mol−1
T Leaf temperature in K 
TE Transpiration efficiency (mmol C mol−1 H2O) 
TEN Transpiration efficiency of N acquisition (μmol N mol−1 H2O) 
TL Leaf temperature in C 
t Number of days in experiment 
v Leaf-to-air water vapour mole fraction difference (mmol mol−1
wa Water vapour mole fraction of ambient air (mmol mol−1
wi Water vapour mole fraction in the intercellular air spaces (mmol mol−1
Δ13Photosynthetic 13C/12C discrimination 
Δ13CL 13C/12C discrimination in leaf dry matter 
Δ13CS 13C/12C discrimination in stem dry matter 
Δ13CR 13C/12C discrimination in root dry matter 
Δ13Cwp 13C/12C discrimination in whole plant dry matter 
Δ1818O/16O enrichment relative to source water 
Δ18Oc 18O/16O enrichment of plant cellulose relative to source water 
Δ18Oe 18O/16O enrichment at the evaporative sites in leaves relative to source water 
Δ18OL 18O/16O enrichment of leaf mesophyll water relative to source water 
Δ18Op 18O/16O enrichment of plant dry matter relative to source water 
Δ18Ov 18O/16O enrichment of atmospheric water vapour relative to source water 
δ1313C/12C of a sample expressed relative to the Pee Dee Belemnite standard 
δ13Ca 13C/12C of atmospheric CO2 expressed relative to the Pee Dee Belemnite standard 
δ13Cp 13C/12C of plant material expressed relative to the Pee Dee Belemnite standard 
δ1515N/14N of a sample expressed relative to that of air 
δ1818O/16O of a sample expressed relative to that of Vienna Standard Mean Ocean Water 
δ18Op δ18O of leaf dry matter 
δ18Os δ18O of source water 
εcp δ18O difference between plant cellulose and plant dry matter 
εk 18O/16O fractionation during water vapour diffusion through stomata and boundary layer 
εwc Equilibrium 18O/16O fractionation between organic O and medium water 
ε+ Equilibrium 18O/16O fractionation between liquid water and vapour 
ϕc Proportion of fixed C respired to the atmosphere 
ϕw Ratio of unproductive to productive water loss 
Γ* CO2 compensation point of C3 photosynthesis in the absence of Rd 
℘ Péclet number 

The ratio of intercellular to ambient CO2 mole fractions (ci/ca), shown in equation (2), also relates independently to C isotope discrimination (Δ13C). The Δ13C for C3 photosynthesis can be defined as (Farquhar et al., 1982; Farquhar and Richards, 1984; Hubick et al., 1986) 

(3)
graphic
where a is the 13C/12C fractionation caused by gaseous diffusion through stomata (4.4‰), and b is the fractionation caused by Rubisco, the primary carboxylating enzyme in C3 plants (29‰). The term d summarizes collectively the fractionations caused by dissolution of CO2 and liquid phase diffusion, photorespiration, and dark respiration (Farquhar et al., 1989). The effects of fractionations associated with these processes on the overall Δ13C are small compared with that caused by Rubisco, but nonetheless significant (Brugnoli and Farquhar, 2000; Ghashghaie et al., 2003). The d in equation (3) substitutes for the following terms in the full model of Δ13C for C3 plants (Farquhar et al., 1989) 
(4)
graphic
where gb and gi are conductances to CO2 (mol m−2 s−1) of the leaf boundary layer and between the intercellular air spaces and sites of carboxylation, respectively. The ab is the discrimination against 13CO2 during diffusion through the leaf boundary layer (2.8‰), es is that during dissolution into water (1.1‰), and al is that during liquid phase diffusion (0.7‰). The Rd is day respiration (μmol CO2 m−2 s−1), e is the 13C discrimination associated with day respiration, k is the carboxylation efficiency (mol CO2 m−2 s−1), f is the discrimination against 13C associated with photorespiration, and Γ* is the CO2 compensation point in the absence of Rd (μmol mol−1). The Δ13C in equation (3) is defined with respect to atmospheric CO2 as Δ13C=Ra/Rp–1, where Ra is 13C/12C of atmospheric CO2 and Rp is 13C/12C of plant material (Farquhar and Richards, 1984). In practice, Δ13C is calculated from measured δ13C values as 
(5)
graphic
where δ13Ca is δ13C of CO2 in air, and δ13Cp is that of plant material. For convenience, Δ13C and δ13C values are typically expressed as per mil (‰), meaning that they have been multiplied by the scaling factor 1000.

Equations (2) and (3) suggest that TE and Δ13C share a mutual dependence on ci/ca. Combining the two equations yields (Hubick and Farquhar, 1989) 

(6)
graphic
which, in turn, can be rearranged as 
(7)
graphic

Equation (7) presents a linear relationship between TE and Δ13C with slope –m and intercept m(bd): 

(8)
graphic
where m=ca(1–ϕc)/[1.6v(1+ϕw)(ba)]. Thus, as demonstrated previously (Hubick et al., 1986), the coefficients of a linear regression equation between TE and Δ13C can be used to make inferences about parameters in equation (7) that are difficult to determine experimentally. Namely, the term d can be calculated as d=b–(I/m), where I is the intercept and m is the negative slope of the relationship between TE and Δ13C, and ϕc can be calculated as ϕc=1–1.6vm(1+ϕw)(b–a)/ca. Note that these calculations assume that the terms for which m and I substitute in equation (7) are invariant over the range of Δ13C for which the regression equation is fitted.

It was previously suggested that measurements of 18O/16O of plant organic material could prove useful in water-use efficiency studies by providing a means for making integrated estimates of v (Farquhar et al., 1989; Sternberg et al., 1989). The v is defined as wiwa, where wi is the water vapour mole fraction in the leaf intercellular air spaces and wa is that in the surrounding atmosphere. The suggestion was that the following set of equations, describing the processes contributing to the 18O/16O of plant organic material, could be inverted to solve for wi.

The terms wa and wi relate to steady-state leaf water 18O enrichment at the sites of evaporation in leaves (Δ18Oe) in the following way (Craig and Gordon, 1965; Dongmann et al., 1974; Farquhar and Lloyd, 1993) 

(9)
graphic
where ε+ is the equilibrium fractionation that occurs during the phase change from liquid water to vapour, εk is the kinetic fractionation that occurs during water vapour diffusion through stomatal pores and the leaf boundary layer, and Δ18Ov is the 18O enrichment of atmospheric water vapour with respect to water taken up by the roots (source water). The 18O enrichment (Δ18O) is defined with respect to source water as Δ18O=R/Rs–1, where R is 18O/16O of the sample of interest and Rs is that of source water. The equilibrium fractionation, ε+, can be calculated as follows (Bottinga and Craig, 1969): 
(10)
graphic
where T is leaf temperature in K. The kinetic fractionation, εk, can be calculated as (Farquhar et al., 1989b) 
(11)
graphic
where rs and rb are stomatal and boundary layer resistances to water vapour diffusion (m2 s mol−1), and 32 and 21 are associated fractionation factors scaled to per mil (Cappa et al., 2003).

The Δ18O of leaf mesophyll water (Δ18OL), the signature most relevant to production of plant organic material (Cernusak et al., 2003), can be related to Δ18Oe as (Farquhar and Lloyd, 1993; Farquhar and Gan, 2003) 

(12)
graphic
The ℘ is a Péclet number, defined as EL/(CD), where E is transpiration rate (mol m−2 s−1), L is a scaled effective path length (m), C is the molar concentration of water (mol m−3), and D is the diffusivity of H218O in water (m2 s−1). The D can be calculated as (Cuntz et al., 2007) 
(13)
graphic
where T is leaf temperature in K. The Δ18OL can in turn be related to the 18O enrichment of plant cellulose (Δ18Oc) according to the following equation (Barbour and Farquhar, 2000): 
(14)
graphic
where pex is the proportion of O atoms that exchange with local water in the developing plant tissue during cellulose synthesis, px is the proportion of unenriched source water in the developing tissue, and εwc is the equilibrium fractionation between organic O and medium water. Finally, the 18O enrichment of plant dry matter (Δ18Op) can be related to that of plant cellulose by adding an additional fractionation factor (εcp) to account for the δ18O difference between the two (Barbour and Farquhar, 2000); 
(15)
graphic

Materials and methods

Plant material and experimental treatments

The experiment took place at the Smithsonian Tropical Research Institute, Santa Cruz Experimental Field Facility, Gamboa, Republic of Panama. The site is located at 9°07’ N latitude, 79°42’ W longitude, at an altitude of 28 m above sea level. Seeds of Ficus insipida Willd. (Moraceae) were collected from mature trees growing in the Panama Canal watershed. Seeds were germinated in trays containing a commercial potting soil in July 2005. Following germination, three seedlings each were transplanted into 40 pots, each of volume 19 l. Upon transplanting, a handful of soil was added to each pot together with roots taken from the base of the palm tree Attalea butyracea (Mutis ex L.f.) Wess. Boer. as a source of mycorrhizal inoculant. The pots were placed under a translucent rain shelter on plastic tables; they were elevated approximately 0.8 m above the concrete surface below the shelter. The shelter reduced incoming photon flux density (PFD) by approximately 20%. After an adjustment period of about 1 month, two seedlings were removed from each pot, leaving a uniform population of seedlings, with one seedling per pot. Among the 40 pots, five treatments were deployed, yielding eight pots per treatment. For each treatment, two pots were selected to serve as controls without plants; seedlings were removed from these pots. The discarded seedlings were used to measure seedling dry mass at the beginning of the experiment, estimated as 0.27 g.

The five soil fertility treatments consisted of varying mixtures of homogenous, dark topsoil and rice husks, with the high fertility treatment additionally receiving a one-time application of slow-release fertilizer. It was expected that the addition of rice husks to the soil mixture would reduce the soil fertility in two ways; both by diluting the nutrient content of the pot, and by adding a high C/N substrate that would tend to immobilize N and other nutrients, leading to greater deficiencies as the proportion of rice husks increased. The treatments were as follows, given as the volumetric percentage of air-dried topsoil in the topsoil/rice-husk mixture: 20, 40, 60, 80, 80+N. For the 80+N treatment, approximately 13 g of Osmocote-Plus controlled-release fertilizer (Scotts-Sierra, Maryville, OH, USA) was added to each pot. Due to the difference in density between the topsoil and rice husks, the dry mass of the topsoil/rice-husk mixture required to fill each 19 l pot varied by treatment: 5.4, 8.9, 12.4, 15.4, and 15.4 kg were placed in each pot for treatments 20, 40, 60, 80, and 80+N, respectively. The amount of water required to bring the pots to field capacity also varied slightly: 4.0, 4.5, 5.0, 5.0, and 5.0 kg of water were added to treatments 20, 40, 60, 80, and 80+N, respectively. 1.5 kg of gravel was added to the soil surface of each pot to reduce soil evaporation.

Plant water use

The pots were weighed at regular intervals from 23 August 2005 until plant harvest on 4 November 2005, a period of approximately 10 weeks. Pot weights were determined with a 64 kg capacity balance (Sartorius QS64B, Thomas, Swedesboro, NJ, USA). The pots were initially weighed once per week, but the frequency was increased to as much as three times per week when plant stature and water use increased toward the end of the experiment. Pot water loss in the interval between weight measurements did not exceed 2.5 kg; this value was only approached near the very end of the experiment and only for the largest plants. Woody tree seedlings typically do not show a reduction in daily transpiration rate until soil water content falls to approximately one-third the value at field capacity (Sinclair et al., 2005), so it is assumed that transpiration was not limited by soil water content at any time during the experiment. After weighing each pot, water was added until the initial weight at field capacity was restored. Plant transpiration over the course of the experiment was calculated as the difference between cumulative pot water loss and the mean water loss of the control pots for each treatment. Leaves, stems, and roots were oven-dried at 70 °C after harvest and weighed separately for each plant. Abscised leaves were collected during the experiment and their dry weight added to the plant dry weight for TE calculations. Leaf area at plant harvest was determined with an LI-3100 Leaf-Area Meter (Li-Cor Inc., Lincoln, NE, USA).

Meteorological conditions during the experiment were recorded every 15 min using an automated weather station (Campbell Scientific, Logan, UT, USA), as described previously (Winter et al., 2001, 2005). The mean daytime temperature, calculated between the h of sunrise and sunset, was 27.3 °C; mean daytime relative humidity was 81.5%; mean PFD was 670 μmol m−2 s−1; and mean daytime wind speed was 0.4 m s−1.

For three days prior to plant harvest, daily and nightly water use of each plant was measured. Pots were weighed prior to sunrise (05.30 h) and again following sunset (18.00 h).

Control pots were also weighed and control water loss subtracted from that of pots with plants to calculate plant water loss. Mean daily and nightly transpiration rates were expressed on a leaf area basis by dividing by the leaf area determined at plant harvest, which followed the third cycle of day/night measurements. The term ϕw for each plant was calculated as night-time plant water use divided by daytime plant water use.

Leaf gas exchange measurements

Gas exchange of the youngest, fully-expanded leaf of each plant was measured under light-saturating conditions (PFD >800 μmol m−2 s−1) at both morning and midday on 20 October 2005 with an Li-6400 portable photosynthesis system (Li-Cor Inc., Lincoln, NE, USA). Leaves were illuminated during measurements by natural sunlight. The mean PFD at the leaf surface during morning measurements was 1094±225 μmol m−2 s−1 (mean ±1 SD), whereas that during midday measurements was 1333±121 μmol m−2 s−1. The mean v during morning measurements was 12.8±1.6 mmol mol−1, and that during midday measurements was 17.2±1.4 mmol mol−1. Mean leaf temperatures (TL) during morning and midday measurements were 33.0±1.0 °C, and 36.0±0.5 °C, respectively. Dark respiration was measured on the youngest, fully-expanded leaf of each plant on 3 November 2005 between 19.30 h and 22.00 h. Mean leaf temperature during measurements was 25.9±0.2 °C.

Isotopic and elemental analyses

Leaf, stem, and root dry matter were ground to a fine powder for elemental and isotopic analyses. The 13C/12C and 15N/14N isotope ratios of leaf, stem, and root dry matter were measured at the Idaho Stable Isotopes Laboratory at the University of Idaho, Moscow, ID, USA; the 18O/16O of leaf dry matter was measured at the Stable Isotope Core Laboratory, Washington State University, Pullman, WA, USA. For 13C/12C and 15N/14N analyses, samples of approximately 3 mg were combusted in an NC2500 elemental analyser (CE Instruments, Milan, Italy), then swept by a helium carrier gas, via a continuous flow interface, into a Delta Plus isotope ratio mass spectrometer (Finnigan MAT, Bremen, Germany). In addition to 13C/12C and 15N/14N, the C and N elemental concentrations of the sample material were determined from peak areas obtained from mass spectrometric measurements. The 18O/16O of leaf dry matter was measured on samples of approximately 1 mg on a Delta XP isotope ratio mass spectrometer (Finnigan MAT, Bremen, Germany), following pyrolysis in a high-temperature furnace (Thermoquest TC/EA, Finnigan MAT, Bremen, Germany). The C, N, and O stable isotope ratios were obtained in delta notation relative to standards of Pee Dee Belemnite, air, and Vienna Standard Mean Ocean Water, respectively.

Whole-plant δ13C and δ15N compositions were calculated by mass balance using the dry mass of each plant organ (leaves, stems, and roots), the C or N mass fraction, and the δ13C or δ15N composition. The Δ13C was calculated from δ13C values according to equation (5). The δ13Ca was assumed to be –8‰, consistent with observed daytime δ13Ca near Panama City, Panama (Winter and Holtum, 2002). The leaf Δ18Op was expressed with respect to the δ18O of irrigation water (–4.0‰) according to the equation Δ18Op=(δ18Op–δ18Os)/(1+δ18Os), where δ18Op is the δ18O of leaf dry matter, and δ18Os is that of irrigation (source) water (Barbour et al., 2004).

In addition, elemental concentrations of P, K, Ca, Mg, Mn, and Zn were quantified in leaf dry matter. Approximately 200 mg of finely ground, oven-dried leaf material were digested at 380 °C in sulphuric acid and lithium sulphate with a selenium catalyst and hydrogen peroxide. Elemental concentrations were then determined on an inductively-coupled plasma optical-emission spectrometer (Perkin Elmer Inc., Wellesley, MA, USA).

Leaf temperature and leaf-to-air humidity gradient

Three different methods were used to estimate average values for TL and v over the course of the experiment for the five soil fertility treatments. In the first method, a leaf energy balance model was used, details of which have been recently described (Barbour et al., 2000; Cernusak et al., 2003a). In the model, mean daytime air temperature, relative humidity, irradiance, and wind speed were used over the course of the experiment along with the transpiration rates measured gravimetrically just prior to plant harvest. The transpiration rates used in the analysis were those measured on 2 November 2005, when the mean daily PFD and mean daily air water vapour mole fraction deficit matched very closely the average values recorded over the course of the experiment (684 μmol m−2 s−1 and 6.6 mmol mol−1 versus 670 μmol m−2 s−1 and 6.6 mmol mol−1, respectively). It was assumed that the incoming PFD was reduced by 20% by the translucent rain shelter covering the plants, and that the mean intercepted PFD for each plant was further reduced by 25% by self shading and non-horizontal leaf orientation. Thus, the PFD used in the leaf energy balance analysis was 400 μmol m−2 s−1. The mean surface area of individual leaves for each treatment was used to calculate boundary layer conductance. The leaf energy balance model was used to predict mean TL for each treatment, and v was calculated as the difference between the saturation vapour mole fraction at TL and the average daytime air vapour mole fraction.

In the second method for estimating TL and v, equation (2) was used, along with measured values of TE, ci/ca (based on measurements of Δ13C), and ϕw. It was assumed that ca was constant at 375 μmol mol−1, and that ϕc was constant at 0.4. Equation (2) for v was then solved. Average wa was used to calculated wi, and TL was calculated as the dew point temperature at wi.

The third method for estimating TL and v was based on measurements of Δ18Op for leaf dry matter. Equations (9) to (15) were inverted to solve for wi starting with values of Δ18Op. The εcp was assumed to be –6.8‰ (Cernusak et al., 2004); εwc was assumed to be 27‰ (Sternberg and DeNiro, 1983); the term pexpx was assumed to be 0.38 (Cernusak et al., 2005); the L was assumed to be 0.015 m (Cernusak et al., 2002, 2005); the D was calculated to be 2.46×10−9 m2 s−1; the rs values were taken from leaf gas exchange measurements; the rb was calculated from mean leaf surface area and mean wind speed, as for the leaf energy balance analysis; the ε+ was calculated to be 8.9‰; and the Δ18Ov was assumed equal to –ε+ (Farquhar et al., 2007). Although the parameters D and ε+ are dependent on leaf temperature, estimates of v are relatively insensitive to small changes in these parameters. For example, calculating these parameters with a TL of 25 °C versus 30 °C would shift our mean estimate of v from 8.1 to 8.0 mmol mol−1 in the case of D, and from 7.9 to 8.0 mmol mol−1 in the case of ε+. Therefore, D and ε+ were calculated assuming an approximate TL of 28 °C. Final TL was calculated from wi as described above.

Statistical analysis

Ordinary least squares regression was used to evaluate the relationships between leaf isotopic characteristics, gas exchange characteristics, and leaf elemental concentrations. These analyses were used to determine the ability of an explanatory variable to predict variation in a response variable. However, to determine the regression coefficients for the relationship between TE and Δ13C for estimations of d and ϕc, geometric mean regression was used. In this case, we were interested in the functional relationship between TE and Δ13C rather than a causal, predictive relationship, the values of the regression coefficients were the primary focus of the analysis, and both parameters were measured with error, thereby indicating the use of geometric mean regression (Sokal and Rohlf, 1995). Analysis of variance was used to test for variation among treatments in physiological and morphological parameters. Tukey's method for pair-wise comparisons was used to test for significant differences between individual treatments.

Results

Plant growth and morphology

Plant growth and morphology differed among the soil fertility treatments (Table 2). Mean plant dry mass at the time of harvest ranged from 2.6 to 80.4 g from the lowest to the highest soil fertility treatment. Corresponding mean relative growth rates (RGR) ranged from 30.4 to 78.0 mg g−1 d−1, respectively (Table 2). Differences in RGR among treatments were statistically significant for all pairs of treatments, except 40% and 60% soil. There was significant variation in root:shoot ratio, leaf area ratio, and specific leaf area among treatments, but this variation did not appear to be systematically related to the soil fertility treatments (Table 2).

Table 2.

Morphological and physiological parameters for Ficus insipida plants according to soil fertility treatment

 Soil/rice-husk mixture (v/v) 
 20% Soil 40% Soil 60% Soil 80% Soil 80% Soil plus fertilizer 
Plant dry mass at harvest (g) 2.6±1.0 a 11.8±3.3 a 7.8±2.0 a 27.4±5.2 b 80.4±12.3 c 
Leaf area at harvest (cm2247±92 a 1086±248 b 826±224 a,b 1885±285 c 7449±750 d 
Root/shoot ratio (g g−10.68±0.28 a 0.45±0.06 a,b 0.43±0.05 b 0.58±0.07 a,b 0.46±0.07 a,b 
Leaf area ratio (m2 kg−19.5±2.3 a 9.4±1.4 a 10.6±1.0 a 6.9±0.3 b 9.4±0.9 a 
Specific leaf area (m2 kg−122.5±1.6 a 20.2±1.3 b,c 22.2±1.3 a,c 19.1±1.4 b 21.4±1.0 a,c 
Mean relative growth rate (mg g−1 d−130.4±5.5 a 51.4±4.2 b 45.8±3.5 b 63.3±2.7 c 78.0±2.2 d 
Gravimetric daytime transpiration (mmol m−2 s−11.92±0.18 a 1.58±0.09 b 1.70±0.09 b 1.32±0.08 c 1.14±0.13 c 
Gravimetric night-time transpiration (mmol m−2 s−10.30±0.10 a 0.18±0.03 b,c 0.23±0.03 a,c 0.14±0.02 b 0.13±0.01 b 
Ratio night-time/daytime transpiration (ϕw0.15±0.05 a 0.11±0.02 a,b 0.13±0.02 a,b 0.11±0.01 b 0.11±0.01 a,b 
Net photosynthesis (μmol CO2 m−2 s−111.0±2.2 a 15.1±1.5 b 16.4±1.7 b 15.4±1.3 b 22.4±1.7 c 
Stomatal conductance to H2O (mol m−2 s−10.59±0.06 a 0.72±0.08 a,b 0.76±0.10 b 0.75±0.08 b 0.81±0.09 b 
Instantaneous transpiration (mmol m−2 s−18.4±0.5 a 9.1±0.4 a,b 8.6±1.0 a 9.0±0.8 a,b 9.9±0.5 b 
Dark respiration rate (μmol CO2 m−2 s−10.71±0.15 a 1.07±0.29 a,b 1.08±0.25 a,b 0.98±0.15 a,b 1.34±0.33 b 
Ratio dark respiration/net photosynthesis 0.07±0.02 a 0.07±0.02 a 0.07±0.01 a 0.06±0.01 a 0.06±0.01 a 
Whole-plant N isotope ratio (δ15N, ‰) 2.7±0.8 a 3.2±0.5 a 2.4±0.4 a 3.4±0.7 a 2.8±0.6 a 
Transpiration efficiency: N (μmol N mol−1 H2O) 17.8±4.3 a 35.8±3.9 b 39.5±4.0 b 41.8±4.6 b 107.0±18.5 c 
Whole-plant C isotope discrimination (Δ13Cwp; ‰) 24.1±0.6 a 23.1±0.3 b 23.1±0.3 b 22.4±0.4 c 21.5±0.3 d 
Leaf C isotope discrimination (Δ13CL; ‰) 24.4±0.7 a 23.3±0.3 b 23.5±0.3 b 23.0±0.4 b 22.1±0.3 c 
Stem C isotope discrimination (Δ13CS; ‰) 24.5±0.6 a 23.1±0.3 b 23.0±0.3 b,c 22.4±0.5 c 21.5±0.5 d 
Root C isotope discrimination (Δ13CR; ‰) 23.7±0.5 a 22.9±0.3 a,b 22.7±0.6 b 21.8±0.3 c 20.4±0.5 d 
Integrated ci/ca calculated from whole-plant Δ130.96±0.02 a 0.92±0.01 b 0.92±0.01 b 0.89±0.01 c 0.86±0.01 d 
Instantaneous ci/ca from gas exchange 0.88±0.02 a 0.86±0.01 a 0.86±0.01 a 0.86±0.01 a 0.82±0.01 b 
Transpiration efficiency: C (mmol C mol−1 H2O) 0.74±0.13 a 1.25±0.15 b 1.20±0.07 b 1.81±0.16 c 2.69±0.11 d 
Leaf dry matter O isotope enrichment (Δ18Op; ‰) 24.9±0.3 a 24.8±0.6 a 24.3±0.2 a 24.4±0.3 a 23.6±0.4 b 
 Soil/rice-husk mixture (v/v) 
 20% Soil 40% Soil 60% Soil 80% Soil 80% Soil plus fertilizer 
Plant dry mass at harvest (g) 2.6±1.0 a 11.8±3.3 a 7.8±2.0 a 27.4±5.2 b 80.4±12.3 c 
Leaf area at harvest (cm2247±92 a 1086±248 b 826±224 a,b 1885±285 c 7449±750 d 
Root/shoot ratio (g g−10.68±0.28 a 0.45±0.06 a,b 0.43±0.05 b 0.58±0.07 a,b 0.46±0.07 a,b 
Leaf area ratio (m2 kg−19.5±2.3 a 9.4±1.4 a 10.6±1.0 a 6.9±0.3 b 9.4±0.9 a 
Specific leaf area (m2 kg−122.5±1.6 a 20.2±1.3 b,c 22.2±1.3 a,c 19.1±1.4 b 21.4±1.0 a,c 
Mean relative growth rate (mg g−1 d−130.4±5.5 a 51.4±4.2 b 45.8±3.5 b 63.3±2.7 c 78.0±2.2 d 
Gravimetric daytime transpiration (mmol m−2 s−11.92±0.18 a 1.58±0.09 b 1.70±0.09 b 1.32±0.08 c 1.14±0.13 c 
Gravimetric night-time transpiration (mmol m−2 s−10.30±0.10 a 0.18±0.03 b,c 0.23±0.03 a,c 0.14±0.02 b 0.13±0.01 b 
Ratio night-time/daytime transpiration (ϕw0.15±0.05 a 0.11±0.02 a,b 0.13±0.02 a,b 0.11±0.01 b 0.11±0.01 a,b 
Net photosynthesis (μmol CO2 m−2 s−111.0±2.2 a 15.1±1.5 b 16.4±1.7 b 15.4±1.3 b 22.4±1.7 c 
Stomatal conductance to H2O (mol m−2 s−10.59±0.06 a 0.72±0.08 a,b 0.76±0.10 b 0.75±0.08 b 0.81±0.09 b 
Instantaneous transpiration (mmol m−2 s−18.4±0.5 a 9.1±0.4 a,b 8.6±1.0 a 9.0±0.8 a,b 9.9±0.5 b 
Dark respiration rate (μmol CO2 m−2 s−10.71±0.15 a 1.07±0.29 a,b 1.08±0.25 a,b 0.98±0.15 a,b 1.34±0.33 b 
Ratio dark respiration/net photosynthesis 0.07±0.02 a 0.07±0.02 a 0.07±0.01 a 0.06±0.01 a 0.06±0.01 a 
Whole-plant N isotope ratio (δ15N, ‰) 2.7±0.8 a 3.2±0.5 a 2.4±0.4 a 3.4±0.7 a 2.8±0.6 a 
Transpiration efficiency: N (μmol N mol−1 H2O) 17.8±4.3 a 35.8±3.9 b 39.5±4.0 b 41.8±4.6 b 107.0±18.5 c 
Whole-plant C isotope discrimination (Δ13Cwp; ‰) 24.1±0.6 a 23.1±0.3 b 23.1±0.3 b 22.4±0.4 c 21.5±0.3 d 
Leaf C isotope discrimination (Δ13CL; ‰) 24.4±0.7 a 23.3±0.3 b 23.5±0.3 b 23.0±0.4 b 22.1±0.3 c 
Stem C isotope discrimination (Δ13CS; ‰) 24.5±0.6 a 23.1±0.3 b 23.0±0.3 b,c 22.4±0.5 c 21.5±0.5 d 
Root C isotope discrimination (Δ13CR; ‰) 23.7±0.5 a 22.9±0.3 a,b 22.7±0.6 b 21.8±0.3 c 20.4±0.5 d 
Integrated ci/ca calculated from whole-plant Δ130.96±0.02 a 0.92±0.01 b 0.92±0.01 b 0.89±0.01 c 0.86±0.01 d 
Instantaneous ci/ca from gas exchange 0.88±0.02 a 0.86±0.01 a 0.86±0.01 a 0.86±0.01 a 0.82±0.01 b 
Transpiration efficiency: C (mmol C mol−1 H2O) 0.74±0.13 a 1.25±0.15 b 1.20±0.07 b 1.81±0.16 c 2.69±0.11 d 
Leaf dry matter O isotope enrichment (Δ18Op; ‰) 24.9±0.3 a 24.8±0.6 a 24.3±0.2 a 24.4±0.3 a 23.6±0.4 b 

Values are given as mean ±1 standard deviation. For each treatment, n=6. Values within a row followed by different letters are significantly different at P <0.05.

Elemental composition

Whole-plant C concentration varied among treatments, but over a rather narrow range of 0.40–0.42 g g−1 (Table 3). Whole-plant N concentration, on the other hand, showed more pronounced variation among treatments, ranging from 11.6 to 19.7 mg g−1 (Table 3). Leaf N concentration per unit leaf area (Narea) increased from 53.9 mmol m−2 to 90.4 mmol m−2 from the lowest to the highest soil fertility treatment (Table 3). Leaf P concentration showed an opposite trend to leaf N concentration, decreasing from the lowest to the highest soil fertility treatment (Table 3). Leaf Mg, Mn, and Zn concentrations followed similar trends to leaf P, decreasing from the lowest to the highest soil fertility (Table 3). Leaf K and Ca concentrations were less variable among treatments, although they showed weak tendencies to decrease (K) or increase (Ca) from the lowest to the highest soil fertility (Table 3).

Table 3.

Elemental composition of the dry matter of Ficus insipida plants according to soil fertility treatment

 Soil/rice-husk mixture (v/v) 
 20% Soil 40% Soil 60% Soil 80% Soil 80% Soil plus fertilizer 
Whole-plant C concentration (g g−10.40±0.01 a 0.42±0.01 b,c 0.41±0.01 a,c 0.42±0.01 b,c 0.42±0.01 b,c 
Whole-plant N concentration (mg g−111.9±2.0 a 14.2±1.6 a,b 16.0±1.6 b 11.6±1.0 a 19.7±3.7 c 
Whole-plant C/N ratio (g g−134.3±5.5 a,b 29.7±3.7 b,c 26.0±2.4 c,d 36.7±2.7 a 21.9±3.0 d 
Leaf N/P ratio (g g−14.7±0.9 a 6.0±0.8 a 5.9±1.0 a 7.9±0.7 b 16.4±1.1 c 
Leaf N per unit area (mmol m−253.9±6.6 a 68.9±6.4 b 67.7±6.9 b 62.0±4.4 a,b 90.4±10.8 c 
Leaf P per unit area (mmol m−25.34±1.07 a 5.22±0.44 a 5.22±0.49 a 3.55±0.38 b 2.49±0.20 c 
Leaf N concentration (mg g−116.9±2.1 a 19.4±2.0 a,b 21.0±2.3 b 16.5±1.2 a 27.1±3.7 c 
Leaf P concentration (mg g−13.75±0.90 a 3.27±0.47 a 3.58±0.31 a 2.09±0.20 b 1.65±0.14 b 
Leaf K concentration (mg g−127.4±2.1 a,b 26.2±1.9 a,b 29.1±1.8 b 25.1±3.1 a 24.5±2.6 a 
Leaf Ca concentration (mg g−114.4±1.4 a,b 13.6±0.6 b 14.7±2.0 a,b 16.8±1.7 a 15.4±2.0 a,b 
Leaf Mg concentration (mg g−12.89±0.37 a 2.18±0.28 b,c 2.64±0.44 a,b 2.25±0.27 b,c 2.04±0.18 c 
Leaf Mn concentration (μg g−1154±7 a 134±14 a,b 133±16 a,b 132±28 a,b 118±15 b 
Leaf Zn concentration (μg g−128.4±3.2 a 21.9±2.9 b 23.1±4.5 a,b 16.6±4.6 b,c 15.1±3.5 c 
 Soil/rice-husk mixture (v/v) 
 20% Soil 40% Soil 60% Soil 80% Soil 80% Soil plus fertilizer 
Whole-plant C concentration (g g−10.40±0.01 a 0.42±0.01 b,c 0.41±0.01 a,c 0.42±0.01 b,c 0.42±0.01 b,c 
Whole-plant N concentration (mg g−111.9±2.0 a 14.2±1.6 a,b 16.0±1.6 b 11.6±1.0 a 19.7±3.7 c 
Whole-plant C/N ratio (g g−134.3±5.5 a,b 29.7±3.7 b,c 26.0±2.4 c,d 36.7±2.7 a 21.9±3.0 d 
Leaf N/P ratio (g g−14.7±0.9 a 6.0±0.8 a 5.9±1.0 a 7.9±0.7 b 16.4±1.1 c 
Leaf N per unit area (mmol m−253.9±6.6 a 68.9±6.4 b 67.7±6.9 b 62.0±4.4 a,b 90.4±10.8 c 
Leaf P per unit area (mmol m−25.34±1.07 a 5.22±0.44 a 5.22±0.49 a 3.55±0.38 b 2.49±0.20 c 
Leaf N concentration (mg g−116.9±2.1 a 19.4±2.0 a,b 21.0±2.3 b 16.5±1.2 a 27.1±3.7 c 
Leaf P concentration (mg g−13.75±0.90 a 3.27±0.47 a 3.58±0.31 a 2.09±0.20 b 1.65±0.14 b 
Leaf K concentration (mg g−127.4±2.1 a,b 26.2±1.9 a,b 29.1±1.8 b 25.1±3.1 a 24.5±2.6 a 
Leaf Ca concentration (mg g−114.4±1.4 a,b 13.6±0.6 b 14.7±2.0 a,b 16.8±1.7 a 15.4±2.0 a,b 
Leaf Mg concentration (mg g−12.89±0.37 a 2.18±0.28 b,c 2.64±0.44 a,b 2.25±0.27 b,c 2.04±0.18 c 
Leaf Mn concentration (μg g−1154±7 a 134±14 a,b 133±16 a,b 132±28 a,b 118±15 b 
Leaf Zn concentration (μg g−128.4±3.2 a 21.9±2.9 b 23.1±4.5 a,b 16.6±4.6 b,c 15.1±3.5 c 

Values are given as the mean ±1 standard deviation. For each treatment, n=6. Values within a row followed by different letters are significantly different at P <0.05.

The mass ratio of leaf N to P (N/P) increased across treatments from a mean of 4.7 for the lowest soil fertility to 16.4 for the highest soil fertility (Table 3). Variation in TE was closely correlated with variation in N/P (Fig. 1A). The relationship between the two parameters was slightly non-linear, such that the natural logarithm of N/P explained 90% of variation in TE, whereas N/P explained 87%. The relationship between Ln(N/P) and TE was TE=1.42Ln(N/P)–1.28 (R2=0.90, P <0.0001, n=30). The RGR showed a non-linear response to variation in N/P; it increased up to N/P of about 15, then decreased slightly over the small range of values above 15 (Fig. 1B). Variation in RGR and TE was closely correlated (Fig. 1C). Again the relationship was slightly non-linear, such that the relationship between RGR and Ln(TE) was slightly stronger (R2=0.95, P <0.0001, n=30) than that between RGR and TE (R2=0.92, P <0.0001, n=30).

Fig. 1.

Transpiration efficiency (A) and mean relative growth rate (B) plotted against leaf N/P mass ratio, and mean relative growth rate plotted against transpiration efficiency (C) for Ficus insipida plants subject to varying soil fertility.

Fig. 1.

Transpiration efficiency (A) and mean relative growth rate (B) plotted against leaf N/P mass ratio, and mean relative growth rate plotted against transpiration efficiency (C) for Ficus insipida plants subject to varying soil fertility.

Leaf Parea showed a strong positive, linear dependence on mean daytime transpiration rate, also expressed on a leaf area basis, with Egrav explaining 74% of variation in leaf Parea (Fig. 2A). Similar positive, linear dependencies on Egrav were also observed for leaf Zn per unit area (R2=0.45, P <0.0001, n=29) and leaf Mg per unit area (R2=0.23, P <0.005, n=29).

Fig. 2.

Leaf P per unit area (A) and leaf dry matter 18O enrichment (B) plotted against mean daytime transpiration rate for Ficus insipida plants. Transpiration was determined gravimetrically for whole plants on 1–3 November 2005; plant leaf area was determined after harvest on 4 November 2005.

Fig. 2.

Leaf P per unit area (A) and leaf dry matter 18O enrichment (B) plotted against mean daytime transpiration rate for Ficus insipida plants. Transpiration was determined gravimetrically for whole plants on 1–3 November 2005; plant leaf area was determined after harvest on 4 November 2005.

Leaf gas exchange

Photosynthesis of the youngest, fully-expanded leaf of each plant at saturating irradiance increased with increasing soil fertility; mean treatment values ranged from 11.0 to 22.4 μmol CO2 m−2 s−1 from the lowest to the highest soil fertility treatment (Table 2). These values represent averages of measurements made during morning and midday. Leaf dark respiration also increased from low to high soil fertility, with treatment means ranging from 0.71 to 1.34 μmol CO2 m−2 s−1 (Table 2). The ratio of leaf dark respiration to leaf net photosynthesis, on the other hand, was invariant among treatments (Table 2). Leaf net photosynthesis, leaf dark respiration, and whole-plant relative growth rate were linearly related to leaf Narea (Fig. 3). The ratio of leaf dark respiration to leaf net photosynthesis, in contrast, showed no correlation with Narea (P=0.67, n=30).

Fig. 3.

Light-saturated photosynthesis (A), leaf dark respiration (B), and mean relative growth rate (C) plotted against leaf N per unit area for plants of Ficus insipida subject to varying soil fertility. Leaf photosynthesis was measured during morning and midday on 20 October 2005; mean photon flux density was ∼1200 μmol m−2 s−1. Leaf dark respiration was measured on 3 November 2005; mean leaf temperature was ∼26 °C. Gas-exchange measurements were made on the youngest fully-expanded leaf for each plant.

Fig. 3.

Light-saturated photosynthesis (A), leaf dark respiration (B), and mean relative growth rate (C) plotted against leaf N per unit area for plants of Ficus insipida subject to varying soil fertility. Leaf photosynthesis was measured during morning and midday on 20 October 2005; mean photon flux density was ∼1200 μmol m−2 s−1. Leaf dark respiration was measured on 3 November 2005; mean leaf temperature was ∼26 °C. Gas-exchange measurements were made on the youngest fully-expanded leaf for each plant.

Gravimetric transpiration

Mean daytime transpiration rates, determined gravimetrically, varied among soil fertility treatments. Mean treatment daytime Egrav ranged from 1.92 to 1.14 mmol m−2 s−1, and generally decreased from the lowest soil fertility treatment to the highest (Table 2). Mean night-time Egrav followed a similar pattern (Table 2). The term ϕw, describing night-time transpiration as a proportion of daytime transpiration, ranged from 0.15 to 0.11 from low to high soil fertility treatments, respectively (Table 2). Mean daytime Egrav showed a negative, linear dependence on Narea. The equation describing the relationship was Egrav= –0.01Narea+2.3 (R2=0.29, P=0.001, n=29).

Stable isotope composition

Mean values of Δ13CL, Δ13CS, Δ13CR, and Δ13Cwp for the five soil fertility treatments are shown in Table 2. All Δ13C values decreased from lowest to highest soil fertility (Table 2). The general pattern among the different plant tissues was Δ13CL13CS13CR (Table 2). Average whole-plant δ15N values spanned a relatively narrow range from 2.4‰ to 3.4‰, and did not differ significantly among treatments (Table 2). Leaf Δ18Op was significantly lower for the highest soil fertility treatment than for the other treatments, and tended to decrease with increasing soil fertility (Table 2). The Δ18Op was negatively correlated with mean daytime Egrav across all treatments (Fig. 2B).

Leaf temperature and leaf-to-air humidity gradient

Estimates of TL and v generated by the three different methods are summarized in Table 4. The leaf energy balance model estimated a variation of 1.5 °C in TL across the soil fertility treatments. Values ranged from 27.1 °C to 28.6 °C from the lowest to the highest soil fertility treatment; corresponding values for v ranged from 6.2 mmol mol−1 to 9.5 mmol mol−1 (Table 4). The second method that was used to estimate TL and v, which assumed a constant value of 0.4 for ϕc, predicted less variation among treatments; values ranged from 26.9 °C to 27.8 °C and 5.8 mmol mol−1 to 7.8 mmol mol−1, respectively. The third method, based on measurements of Δ18Op, predicted a similar range of values to the leaf energy balance model, but with values trending in the opposite direction across treatments; i.e., decreasing from the lowest to the highest soil fertility. For the Δ18Op method, values ranged from 28.4 °C to 27.0 °C for TL and from 9.0 mmol mol−1 to 6.0 mmol mol−1 for v (Table 4).

Table 4.

Estimates for average leaf temperature (TL) and average leaf to air water vapour mole fraction difference (v) over the course of the experiment for the five soil fertility treatments

Method of estimation Parameter Soil/rice-husk mixture (v/v) 
  20% Soil 40% Soil 60% Soil 80% Soil 80% Soil plus fertilizer 
Leaf energy balance TL (°C) 27.1 27.7 27.5 28.4 28.6 
 v (mmol mol−16.2 7.5 7.1 9.0 9.5 
Constant ϕc TL (°C) 26.9 27.7 27.8 27.7 27.3 
 v (mmol mol−15.8 7.6 7.8 7.4 6.7 
Leaf 18O enrichment TL (°C) 28.4 28.4 27.9 27.9 27.0 
 v (mmol mol−19.0 9.1 7.9 8.0 6.0 
Method of estimation Parameter Soil/rice-husk mixture (v/v) 
  20% Soil 40% Soil 60% Soil 80% Soil 80% Soil plus fertilizer 
Leaf energy balance TL (°C) 27.1 27.7 27.5 28.4 28.6 
 v (mmol mol−16.2 7.5 7.1 9.0 9.5 
Constant ϕc TL (°C) 26.9 27.7 27.8 27.7 27.3 
 v (mmol mol−15.8 7.6 7.8 7.4 6.7 
Leaf 18O enrichment TL (°C) 28.4 28.4 27.9 27.9 27.0 
 v (mmol mol−19.0 9.1 7.9 8.0 6.0 

Three different methods were used to estimate TL and v. The first method employed a leaf energy balance model. The second method relied on an assumption of constant ϕc across treatments. The third method was based on leaf dry matter Δ18Op.

Transpiration efficiency

The TE varied strongly among soil fertility treatments (Table 2). Variation in TE was closely correlated with variation in Δ13Cwp (Fig. 4). The equation relating TE to Δ13Cwp, determined by geometric mean regression, was TE= –0.72Δ13Cwp+18.0. These coefficients were similar to those determined by ordinary least-squares regression (–0.68 and 17.0 for m and I, respectively). The d calculated from m and I values of –0.72 and 18.0 was 4.0‰. Long-term, integrated ci/ca estimated from Δ13Cwp, using d=4.0‰, varied strongly among treatments (Table 2). Treatment means ranged from 0.96 to 0.86 from low to high soil fertility. The Δ13Cwp was well correlated with ci/ca determined from instantaneous gas exchange measurements (Fig. 5), as was TE (R2=0.69, P <0.0001, n=30). Instantaneous ci/ca was lower than Δ13Cwp-based ci/ca for all treatments (Table 2). Instantaneous ci/ca, Δ13Cwp, and TE each correlated well with leaf Narea (Fig. 6A, B, C). These parameters also correlated strongly with the light-saturated photosynthetic rate of the youngest, fully-expanded leaf of each plant (Fig. 6D, E, F). There were weaker correlations between stomatal conductance and ci/ca, Δ13Cwp, and TE; however, these correlations were opposite in sign to what would be expected if variation in stomatal conductance were controlling variation in these parameters (Table 2).

Fig. 4.

Transpiration efficiency (TE) plotted as a function of whole-plant C isotope discrimination (Δ13Cwp) for Ficus insipida plants subject to varying soil fertility. The Δ13Cwp was calculated from measurements of δ13C and C mass in leaves, stems, and roots. The δ13C of ambient air was assumed to be –8‰.

Fig. 4.

Transpiration efficiency (TE) plotted as a function of whole-plant C isotope discrimination (Δ13Cwp) for Ficus insipida plants subject to varying soil fertility. The Δ13Cwp was calculated from measurements of δ13C and C mass in leaves, stems, and roots. The δ13C of ambient air was assumed to be –8‰.

Fig. 5.

Whole-plant C isotope discrimination (Δ13Cwp) plotted as a function of the ratio of intercellular to ambient CO2 mole fractions (ci/ca) for plants of Ficus insipida subject to varying soil fertility. The ci/ca was calculated from instantaneous leaf gas exchange measurements made during the morning and at midday on 20 October 2005. The Δ13Cwp was calculated from measurements of δ13C and C mass in leaves, stems, and roots. The δ13C of ambient air was assumed to be –8‰.

Fig. 5.

Whole-plant C isotope discrimination (Δ13Cwp) plotted as a function of the ratio of intercellular to ambient CO2 mole fractions (ci/ca) for plants of Ficus insipida subject to varying soil fertility. The ci/ca was calculated from instantaneous leaf gas exchange measurements made during the morning and at midday on 20 October 2005. The Δ13Cwp was calculated from measurements of δ13C and C mass in leaves, stems, and roots. The δ13C of ambient air was assumed to be –8‰.

Fig. 6.

Ratio of intercellular to ambient CO2 mole fractions, ci/ca, determined from instantaneous gas-exchange measurements (A), whole-plant C isotope discrimination, Δ13Cwp (B), and transpiration efficiency, TE (C) plotted against leaf N per unit area. Similarly, ci/ca (D), Δ13Cwp (E), and TE (F) plotted against light-saturated net photosynthetic rate of the youngest fully-expanded leaf.

Fig. 6.

Ratio of intercellular to ambient CO2 mole fractions, ci/ca, determined from instantaneous gas-exchange measurements (A), whole-plant C isotope discrimination, Δ13Cwp (B), and transpiration efficiency, TE (C) plotted against leaf N per unit area. Similarly, ci/ca (D), Δ13Cwp (E), and TE (F) plotted against light-saturated net photosynthetic rate of the youngest fully-expanded leaf.

The transpiration efficiency of N acquisition (TEN), calculated as whole-plant N increment divided by cumulative plant water loss, increased from 17.8 μmol N mol−1 H2O for the lowest soil fertility treatment to 107.0 μmol N mol−1 H2O for the highest soil fertility treatment (Table 2). The TE increased linearly as a function of TEN according to the equation TE=0.020TEN+0.58 (R2=0.84, P <0.0001, n=30).

A sensitivity analysis is shown in Table 5 illustrating the predicted effect of changing the input parameters in equation (2) on TE. The ranges of input values used in the analysis were based on observations for the five soil fertility treatments for the parameters ci/ca, v, and ϕw; for the parameters ϕc and ca, the selected ranges represent best guesses at likely limits of their variation. Table 5 suggests that the variation that was observed in TE was largely driven by variation in ci/ca.

Table 5.

A sensitivity analysis of the dependence of transpiration efficiency (TE) on ca, ϕc, ci/ca, v, and ϕw

Parameter Range of values Change in TE (mmol C mol−1 H2O) 
ca (μmol mol−1370 380 –0.04 
ϕc 0.35 0.45 0.25 
ci/ca 0.86 0.96 1.66 
v (mmol mol−16.0 9.0 0.62 
ϕw 0.11 0.15 0.05 
Parameter Range of values Change in TE (mmol C mol−1 H2O) 
ca (μmol mol−1370 380 –0.04 
ϕc 0.35 0.45 0.25 
ci/ca 0.86 0.96 1.66 
v (mmol mol−16.0 9.0 0.62 
ϕw 0.11 0.15 0.05 

Symbols are defined as follows: ca, ambient CO2 mole fraction; ϕc, the proportion of net photosynthesis used for respiration; ci/ca, the ratio of intercellular to ambient CO2 mole fractions; v, the leaf-to-air water vapour mole fraction difference; and ϕw, unproductive water loss as a proportion of productive water loss. Values of the input parameters were varied over their ranges one at a time, and the change in TE calculated according to equation (2). Parameters that were not being varied during each calculation were fixed at the median value in the given range.

Discussion

Large variation in growth and whole-plant water-use efficiency of a tropical pioneer tree in response to variation in soil fertility was observed under non-limiting soil moisture conditions. Analyses of elemental concentrations in dry matter of the experimental plants indicated that treatment differences in RGR and TE resulted largely from variation in N availability. Leaf photosynthesis and dark respiration rates were well correlated with leaf Narea, as was RGR (Fig. 3). Variation in TE was linearly correlated with variation in ci/ca, both for instantaneous measurements of ci/ca, and for integrated estimates based on Δ13Cwp (Figs 4, 5). The ci/ca, Δ13Cwp, and TE, in turn, were well correlated with variation in leaf Narea and leaf photosynthesis (Fig. 6). The response of TE to soil fertility was largely caused by variation in ci/ca; on the other hand, variations in v, ϕc and ϕw probably played only minor roles in modulating TE in response to soil fertility (Table 5). The variation in ci/ca resulted from variation in photosynthetic capacity caused by variation in leaf Narea, rather than from variation in stomatal conductance (Table 2; Fig. 6).

Elemental composition

Of the mineral elements quantified in the leaves of the experimental plants, leaf N showed the strongest positive relationship with RGR. The only other element to be positively correlated with RGR was Ca. However, leaf Ca per unit area explained only 13% of variation in RGR, whereas leaf N per unit area explained 46%. Thus, it is concluded that plant growth was primarily constrained by N availability. Of the other measured elements, P, Mg, and Zn showed positive linear correlations with Egrav, suggesting that these elements were absorbed in relatively constant proportion to the water flux into the roots. The relationship with leaf P was particularly striking, with variation in Egrav explaining 74% of variation in leaf Parea (Fig. 2A). This relationship was surprising, given that P is generally thought to be relatively insoluble in soils. Supply of a source of mycorrhizal inoculant at planting and the high organic matter content of the soil due to the addition of rice husks may have played some role in enabling the relationship between leaf Parea and Egrav in our experiment. In contrast to the relationship between leaf Parea and Egrav, there was a negative correlation between leaf Narea and Egrav across the soil fertility treatments. Variation in leaf Narea explained 29% of variation in Egrav. Increases in transpiration in response to low N availability have also been observed in other tree species (Guehl et al., 1995; Livingston et al., 1999), and transpirational control of N accumulation was previously demonstrated in a mistletoe/tree complex (Marshall et al., 1994).

A non-linear response of RGR to leaf N/P was observed (Fig. 1B). The maximum RGR occurred near N/P of 15, which agrees well with the prediction that N and P should be in balanced supply at N/P between 14 and 16 (Koerselman and Meuleman, 1996). Koerselman and Meuleman (1996) suggested that at N/P <14, growth would be N limited, whereas at N/P >16, growth would be P limited. This further reinforces the notion that variation in RGR and TE in our experiment was primarily caused by differential N availability.

It was found that N/P was an excellent predictor of variation in TE (Fig. 1A); the natural logarithm of N/P explained 90% of variation in TE. For comparison, Δ13Cwp explained 88% of variation in TE. The close correlation between N/P and TE stemmed from the relationships between leaf N and photosynthetic rate (Fig. 3A) and leaf P and transpiration rate (Fig. 2A). Whether such a relationship will hold up more generally outside our experimental conditions is unknown.

C isotope discrimination and ci/ca

Estimating ci/ca from Δ13C according to equation (3) requires an estimate of d. The method described in the theory section for estimating d, based on the coefficients of a regression analysis between TE to Δ13C, assumes that the terms for which the slope and intercept coefficients substitute are invariant over the range of the analysis. This assumption was not strictly met in our experiment; for example, there were probably subtle variations in v and ϕw among treatments (Tables 2, 4). However, if the assumption were strongly violated, one would expect either to see curvature in the relationship between TE and Δ13Cwp, or a large degree of scatter. In fact, the relationship that was observed appeared linear with little scatter: variation in Δ13Cwp explained 88% of variation in TE in a least-squares linear regression (Fig. 4). There were, however, two data points that appeared to depart slightly from the linear trend; these two points had the highest Δ13Cwp values in the dataset (Fig. 4). Repeating the analysis with these two data points excluded would result in an estimate for d of 4.4‰, whereas the estimate for the full data set was 4.0‰. Although this difference is not large, it nonetheless highlights the sensitivity of our method for estimating d to variations in the values of the regression coefficients.

Few direct estimates of d exist in the literature, although assessment of d is implicit in the determination of mesophyll conductance from instantaneous measurements of Δ13C and ci/ca (Evans et al., 1986). Hubick et al. (1986) estimated d to be approximately 3‰, based on the simultaneous measurements in wheat of Δ13C and ci/ca (Evans et al., 1986). The d was later estimated to be near zero for barley (Hubick and Farquhar, 1989), and approximately 1‰ for peanut (Hubick, 1990). Thus, our estimate of 4.0‰ for d in Ficus insipida is slightly higher than values previously reported for crop plants. In the method used here to calculate d [i.e., d=bI/m from equation (8)], the value of d clearly depends on the assumed value of b. Fortunately, any change in the assumed value of b has only a minor effect on Δ13C-based estimates of ci/ca. This is because any change in the assumed value of b will be offset by a similar change in the calculated value of d. Thus, changing the assumed value of b from 29‰ to 27‰ in our analysis would only change the mean Δ13C-based estimate of ci/ca from 0.913 to 0.906.

It is clear from equation (4) that d is a complex parameter, and the general trend in the literature has been to drop it from equation (3) when making long-term, integrated estimates of ci/ca from measurements of Δ13C in plant tissues. However, based on our analysis, it is suggested that it may not be prudent to omit d from equation (3). Assuming b=29‰, excluding d from the calculations would shift the mean Δ13Cwp-based estimate of ci/ca in our experiment from 0.91 to 0.75. Whereas if we assumed b=27‰, the mean Δ-based estimate of ci/ca would shift from 0.91 to 0.82 if d were omitted. If these ci/ca estimates were then used to predict TE from equation (2), the shift caused by omitting d would equate to an approximately 3-fold increase in predicted TE at b=29‰, and a doubling of predicted TE at b=27‰.

It was observed that instantaneous measurements of ci/ca were consistently lower than Δ13Cwp-based estimates across treatments (Table 2). The mean instantaneous estimate for all treatments combined was 0.85, whereas the mean Δ13Cwp-based estimate was 0.91. This discrepancy may have partly resulted from differences between v and PFD averaged over the course of the experiment, as compared with values in the cuvette during instantaneous measurements (8 mmol mol−1 versus 15 mmol mol−1 for v, respectively; and 400 μmol m−2 s−1 versus 1200 μmol m−2 s−1 for PFD, respectively). However, at least part of the discrepancy between instantaneous ci/ca and Δ13Cwp-based ci/ca relates to the fact that ci/ca is calculated differently from instantaneous gas exchange measurements than from isotopic measurements, as described by GD Farquhar (unpublished presentation, BASIN meeting, Marshall, USA, 2004). The equations used to calculate ci from instantaneous measurements are based on a ternary system of gases: CO2, water vapour, and air (Jarman, 1974). The ci is calculated as ci=[(gcE/2)caA]/(gc+E/2), where gc is the total conductance to CO2 of stomata plus boundary layer (Caemmerer and Farquhar, 1981). This calculation takes into account not only collisions between CO2 and air, but also collisions between CO2 and water vapour. By contrast, the equations presented in the theory section of this paper describing the relationship between ci/ca and Δ13C do not take into account collisions between CO2 and water vapour. Instead, ci is simply defined as ci=caA/gc. If the data from the instantaneous measurements are recalculated using this latter definition of ci, a mean value for ci/ca of 0.88 is obtained, which cuts in half the observed difference between instantaneous and Δ13Cwp-based estimates of ci/ca.

In our analysis of the relationship between TE and Δ13C, the whole-plant Δ13C was used rather than that of a single tissue, such as leaves. Using Δ13CL in place of Δ13Cwp has only a small effect on our results. It would shift our estimate of d from 4.0‰ to 3.8‰, and would shift the mean Δ13C-based estimate of ci/ca from 0.91 to 0.92.

Unproductive water loss

The unproductive water loss described by the term ϕw in equation (2) comprises non-stomatal water loss during the day and night, and stomatal water loss at night. Of the two, the expectation was that transpiration at night through partially open stomata would dominate. Conductances of leaf cuticles are on the order of 1–2 mmol m−2 s−1 (Kerstiens, 1996), as are surface conductances of branches and stems (Cernusak and Marshall, 2000; Cernusak et al., 2001). In contrast, it is not uncommon to observe nocturnal stomatal conductances ranging from 20 to more than 100 mmol m−2 s−1 (Donovan et al., 1999; Snyder et al., 2003; Bucci et al., 2004; Barbour et al., 2005; Seibt et al., 2007). The mean nocturnal stomatal conductance that was observed during the dark respiration measurements was 124±43 mmol m−2 s−1 (mean ±1 SD). However, because nocturnal v is typically low (mean value of 1.3 mmol mol−1 in our experiment), as are nocturnal wind speeds, nocturnal transpiration is still likely to be small in comparison to daytime transpiration. A mean ϕw of 0.12 was observed in our experiment, indicating that nocturnal transpiration was equal to 0.12 times daytime transpiration. Expressed as a percentage of total transpiration, nocturnal transpiration was 11% on average. This can be compared to observations of nocturnal transpiration as a percentage of total transpiration of 5% for Eucalyptus grandis (Benyon, 1999), 10% for Betula papyrifera (Daley and Phillips, 2006), and 13–28% for woody species in Brazilian savanna (Bucci et al., 2004, 2005). The mean ϕw of 0.12 that was observed is similar to the value of 0.18 cited by Hubick and Farquhar (1989).

Data reviewed above suggest maximum likely values for ϕw of about 0.4. By contrast, values for ϕw ranging from 3.3 to 5.6 were reported for an experiment with seedlings of Pinus sylvestris (Hobbie and Colpaert, 2004). This would suggest that nocturnal transpiration was 3.3–5.6 times greater than daytime transpiration. The possibility is suggested that these surprisingly high estimates of ϕw may have resulted from omitting d from equation (3), which was used to calculate ci/ca from measurements of Δ13C. Mean ci/ca for the Pinus sylvestris seedlings was estimated to be 0.65. This value can be compared to the mean Δ13C-based ci/ca estimate of 0.91 for our experiment with Ficus insipida. The Pinus sylvestris seedlings were grown under similar conditions to those in our experiment: low irradiance (300 μmol photons m−2 s−1), low v (7.3 mmol mol−1), and low N availability. The relative insensitivity of equation (2) to variations in ϕw, as shown in Table 5, means that if the equation is inverted to solve for ϕw, as was done in the experiment with Pinus sylvestris, the predicted values of ϕw can be highly sensitive to any bias in terms such as ci/ca.

Although significant variation in ϕw was observed among treatments in our experiment, the range of variation was small, with treatment means ranging from 0.11 to 0.15 (Table 1). This narrow range of values occurred over a large gradient in soil fertility, as evidenced by the large variation among treatments in RGR (Table 2). Compared with other terms in equation (2), such as ci/ca and v, the ϕw played a very minor role in our experiment in modulating TE (Table 5).

Leaf-to-air humidity gradient

Three different methods were employed to estimate v for the experimental treatments. Whereas the three methods yielded a similar range of results, there were some differences in the direction of variation proceeding from low soil fertility to high soil fertility (Table 4). In using the leaf energy balance model to estimate v, it was necessary to assume a relationship between the mean intercepted irradiance at the leaf level and the irradiance measured outside the canopy. It was assumed that the former would be 0.75 times the latter for all treatments. This assumption is probably not realistic because the increasing plant size and leaf area going from low to high soil fertility (Table 2) would have been accompanied by increased self shading, and increasingly non-horizontal leaf orientation. Therefore, the mean intercepted irradiance at the leaf surface was likely less at high soil fertility than at low soil fertility. Thus, the leaf energy balance model may have overestimated v, especially for the highest soil fertility treatment, where the leaf area per plant was substantially greater than in the other treatments (Table 2).

The Δ18Op method, based on equations (9) to (15), provides a means for estimating v that could have considerable advantages over the other two. Namely, it provides an integrated measurement over the life of the plant, based on a single isotopic analysis of plant organic material. The disadvantage of this method is that it requires assumed values for a large number of parameters. Some of these parameters, such as L and εcp, have been measured only for a small number of species, so the extent to which they can be generalized is largely unknown (Barbour, 2007). Nonetheless, it is encouraging that it was possible to obtain estimates of v that agreed rather well with the other two methods of estimation (Table 4).

The final method that was used to estimate v was one that involved assuming a constant value for ϕc. It has been suggested that the term ϕc should be a relatively conservative parameter in terrestrial plants (McCree and Troughton, 1966; Gifford, 1994, 2003; Dewar et al., 1999; Thornley and Cannell, 2000). Estimates of ϕc for individual plants are typically in the range of about 0.35 to 0.45 (McCree, 1986; Gifford, 2003). The slope of the regression between TE and Δ suggests a mean ϕc for our experiment near the midrange value of 0.4. Using the slope coefficient and the relationship with ϕc described in the theory section, a mean ϕc of 0.4 would correspond to a mean v across treatments of 7.0 mmol mol−1, close to the mean values for v estimated by the leaf energy balance model and the Δ18Op method (Table 4). Although using the slope coefficient in this way does not allow us to test for variation among treatments in ϕc, no significant variation was observed among treatments at the leaf level in the ratio of dark respiration/net photosynthesis, and systematic variation across treatments in leaf area ratio was not observed (Table 2). Thus, it is suggested that it is possible that there was relatively little variation in ϕc in our experiment.

Farquhar et al. (1989) noted that v in equation (2) should actually be weighted by conductance, because a particular v results in greater water loss when conductance is large than when it is small. This consideration suggests an added complexity to v that may not be well represented in the leaf energy balance or Δ18Op models. Solving equation (2) for v, using measured data, and assuming ca of 375 μmol mol−1 and ϕc of 0.40, resulted in a smaller range of values across treatments than the other two methods (Table 4). Although this method of estimating v requires assuming values for ca and ϕc, the possible ranges of these two parameters are reasonably well constrained. Therefore, we suggest that v predictions based on this method probably provided the most reliable estimates under our experimental conditions.

O isotope enrichment

A positive correlation was observed between Δ18Op and mean daytime Egrav (Fig. 2B). Sheshshayee et al. (2005) recently observed similar positive correlations for different genotypes of groundnut and rice. In their experiments, plant transpiration was measured gravimetrically and expressed as mean transpiration rate (MTR), where MTR=Etot/[(LA1+LA2)0.5t], where Etot is cumulative transpiration over the course of the experiment, LA1 and LA2 are leaf area at the beginning and end of the experiment, and t is number of days in the experiment. If our transpiration data are expressed as MTR and Δ18Op plotted against it, a positive linear relationship is also observed, in which Δ18Op=0.017MTR+23.2 (R2=0.45, P <0.0001, n=30).

Farquhar et al. (2007) recently reviewed theory underlying steady-state leaf water enrichment, and posed the following question: as E increases, Δ18O should also increase, true or false? Equations (9) through (13) suggest the following response: when the source of variation in E is evaporative demand, Δ18O should increase with increasing E; conversely, when the source of variation in E is stomatal, Δ18O should decrease with increasing E (Farquhar et al., 2007). At first glance, data presented in Fig. 2B appear to be in disagreement with this generalized response. This is because the plants were grown side by side during the same time period, so that the evaporative demand of the bulk atmosphere was the same for all plants. However, closer examination of the data in Table 2 reveals that the source of variation in Egrav among treatments was not stomatal. By contrast, increasing stomatal conductance across soil fertility treatments was actually associated with decreasing Egrav. The decreasing Egrav was probably associated with decreasing v and increasing canopy boundary layer resistance at high soil fertility as compared to low soil fertility. The increased leaf area per plant with increasing soil fertility would have caused both of these factors, through increased self-shading, and therefore lower canopy-averaged TL, and increased canopy boundary layer development. As seen in equations (9) and (11), these processes would also result in decreasing Δ18Oe, due to greater wa/wi and lower εk. The decrease in Δ18Oe accompanying lower E would be countered by a relative increase in Δ18OL, as seen in equation (12); however, in our data set, this relatively subtle shift caused by the Péclet effect was apparently not sufficient to overcome the effect of lower Δ18Oe, such that the net result was a decrease in Δ18Op with decreasing Egrav.

Uncoupling is commonly observed between cuvette-based measurements of stomatal conductance and transpiration measured at the whole plant level for tropical trees (Meinzer et al., 1996). In our experiment, cuvette-based measurements of E were 5-fold higher than corresponding values for Egrav (Table 2). The discrepancy can be partly accounted for by variation in v, which was 2-fold greater in the cuvette than the average value in ambient air during Egrav measurments. The remaining variation relates to differences in leaf boundary layer resistance between the cuvette and the ambient environment, and possibly to variation in stomatal conductance between the youngest, fully-expanded leaf, on which gas exchange measurements were made, and the integrated average over the whole canopy. This uncoupling, in addition to the surprising result of the positive correlation between Δ18Op and Egrav, demonstrates the importance of measuring physiological processes at the whole-plant scale, in addition to the leaf scale.

Conclusions

It was observed that ci/ca was the primary control over variation in TE in response to soil fertility in a pioneer tree grown under tropical field conditions (Table 5). It is suggested that ci/ca may be a particularly important control over whole-plant water-use efficiency in fast-growing tropical trees, where ci/ca may generally be high, as evidenced by low δ13C (Guehl et al., 1998; Martinelli et al., 1998; Bonal et al., 2000a, b; Holtum and Winter, 2005). When ci/ca is high, the impact of any change in ci/ca on TE is amplified. This is because the relevant term in equation (2) is not actually ci/ca, but rather (1–ci/ca). For example, a change in ci/ca from 0.95 to 0.90, while seemingly trivial, will cause a doubling of TE, all else being equal.

The strong response of ci/ca and TE to leaf Narea in tropical trees, as observed here and previously (Cernusak et al., 2007), could have important implications for the management of tropical forest plantations, particularly where managers aim to maximize biomass production relative to stand water use; in addition, it could have important implications for the coupling of C and water cycles of tropical vegetation subject to anthropogenic alterations in N availability.

We thank Milton Garcia, Rodrigo Nuñez, Tania Romero, and Aurelio Virgo for technical assistance, and Bob Brander, Ben Miller, and Ben Harlow for assistance with isotopic analyses. We thank two anonymous reviewers for helpful comments on the manuscript. This research was funded by the AW Mellon Foundation and the Smithsonian Tropical Research Institute. LAC was supported by a Smithsonian Institution Postdoctoral Fellowship.

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