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Keywords:

  • canopy stomatal conductance;
  • δ13C;
  • δ18O;
  • δ2H;
  • evaporative enrichment;
  • phloem;
  • transpiration;
  • water availability

ABSTRACT

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. ACKNOWLEDGMENT
  9. REFERENCES

This study investigated the influence of meteorological, pedospheric and physiological factors on the water relations of Scots pine, as characterized by the origin of water taken up, by xylem transport as well as by carbon isotope discrimination (Δ13C) and oxygen isotope enrichment (Δ18O) of newly assimilated organic matter. For more than 1 year, we quantified δ2H and δ18O of potential water sources and xylem water as well as Δ13C and Δ18O in twig and trunk phloem organic matter biweekly, and related these values to continuously measured or modelled meteorological parameters, soil water content, stand transpiration (ST) and canopy stomatal conductance (Gs). During the growing season, δ18O and δ2H of xylem water were generally in a range comparable to soil water from a depth of 2–20 cm. Long residence time of water in the tracheids uncoupled the isotopic signals of xylem and soil water in winter. Δ18O but not Δ13C in phloem organic matter was directly indicative of recent environmental conditions during the whole year. Δ18O could be described applying a model that included 18O fractionation associated with water exchange between leaf and atmosphere, and with the production of organic matter as well as the influence of transpiration. Phloem Δ13C was assumed to be concertedly influenced by Gs and photosynthetically active radiation (PAR) (as a proxy for photosynthetic capacity). We conclude that isotope signatures can be used as effective tools (1) to characterize the seasonal dynamics in source and xylem water, and (2) to assess environmental effects on transpiration and Gs of Scots pine, thus helping to understand and predict potential impacts of climate change on trees and forest ecosystems.


INTRODUCTION

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. ACKNOWLEDGMENT
  9. REFERENCES

Owing to global warming as predicted by climate models (IPCC 2001), near-surface air temperature is assumed to increase in Europe within the next several decades. Model predictions are supported by trend analyses of precipitation and air temperature measurements in southwestern Germany (Mayer et al. 2005), and suggest an increase in mean air temperature of about 1 °C by 2050 along with a propensity for greater rainfall in winter and more frequent drought periods in summer. Such changes will have significant effects on water balance and, therefore, on forest growth and vitality of trees. A first step towards the development of climate-adapted forest management strategies is to gain a better understanding into how key parameters of the water balance of trees are affected by changes in environmental conditions.

Stand transpiration (ST) rates are a direct measure of water consumption by trees. Transpiration rate is a function of stomatal aperture and the water vapour gradient between the leaf internal air space and the atmosphere. Stomatal conductance is determined by numerous environmental and physiological factors such as photosynthetically active radiation (PAR), internal CO2 pressure and water vapour pressure deficit (VPD) (Gao et al. 2002; Tuzet, Perrier & Leuning 2003). When soil water is limited, both transpiration and stomatal conductance become closely coupled with soil water potential via chemical signal transfer such as abscisic acid (Comstock 2002), thus providing information on drought reactions of trees. There is, however, a lack of information on how the interaction of different environmental factors potentially controlsstomatal conductance during the seasonal course (Matsumoto, Ohta & Tanaka 2005). It is also not clear if there are threshold values for particular factors that define if they exert control over stomatal conductance or not (Irvine et al. 1998).

Owing to its relationship to ci/ca (ratio of partial pressures of CO2 in the substomatal cavity and the ambient air) as described by Farquhar, O’Leary & Berry (1982) and – on the other hand – the dependency of ci on Gs (Keitel et al. 2003), δ13C in organic matter can be used to characterize the effects of environmental parameters such as atmospheric and soil water deficit (e.g. Livingston & Spittlehouse 1996; Williams & Ehleringer 1996; Korol et al. 1999) on stomatal reactions.

δ13C of plant organic matter is depleted compared to source carbon (CO2) because of fractionation during diffusion through the leaves and carboxylation (Farquhar, Ehleringer & Hubick 1989a). The relationship between carbon isotope discrimination and leaf internal CO2 concentration is explained by a two-stage model developed by Farquhar et al. (1982):

  • image(1)

where the discrimination of 13C is controlled by factors a (fractionation during diffusion through stomata and leaf intercellular space), b[discrimination during carboxylation by ribulose 1·5-bisphosphate carboxylase/oxygenase (Rubisco)] and ci/ca. In addition to stomatal conductance, the CO2 fixing activity of Rubisco can have an influence on ci/ca. As a consequence, the variation in carbon isotope fractionation cannot be directly attributed to variations in stomatal conductance. The oxygen isotope composition (δ18O) or the oxygen isotopic enrichment above source water (Δ18O) of plant organic matter has been shown to provide additional information to separate effects of stomatal conductance from the influence of changes in photosynthetic capacity (Farquhar, Barbour & Henry 1998) when stomatal conductance is assumed to be controlled by relative humidity (rH) (Scheidegger et al. 2000).

Analysing carbon and oxygen isotope composition or isotopic depletion/enrichment compared to a source in rapid turnover organic matter pools like phloem sugars provides information on environmental signals within the preceding hours to days (Cernusak et al. 2003a; Keitel et al. 2003; Gessler, Rennenberg & Keitel 2004; Cernusak, Farquhar & Pate 2005). Only recently, Keitel et al. (2006) showed that Δ18O of phloem organic matter of European beech could be accurately predicted over a wide range of climatic conditions by applying a steady-state evaporative enrichment model that takes into account the isotopic gradients of leaf water caused by a Péclet effect. However, until now, an assessment of Δ18O or Δ13C in phloem organic matter has been done only for two different tree species (Eucalyptus globulus and Fagus sylvatica), and there have been no verified attempts at applying this model to coniferous species. In addition, evaporative enrichment models have only been applied in short-term studies, and we lack information about whether we can predict Δ18O of a fast turnover organic matter pool throughout the whole growing season.

In addition to stomatal reaction, the availability of water resources in the soil affects the water balance of trees. Comparing stable isotope composition (δ2H, δ18O) of xylem water with that of potential water sources has recently been accepted as a method to examine water utilization by trees (e.g. Farrington, Turner & Gailitis 1996). This is feasible as no isotope fractionation steps occur during uptake and transport of water through the xylem (Zimmermann, Ehhalt & Munnich 1967; Ehleringer & Dawson 1992;Thorburn, Walker & Brunel 1993). The main aim of previous studies assessing δ2H and δ18O of water resources (e.g. Adar et al. 1995; Rose, Graham & Parker 2003) was, however, the partitioning of soil water versus groundwater as main water sources. When highly different δ2H and δ18O signatures are exhibited in the water along the soil profile in combination with relatively slow variations with time, it may be possible to estimate the depth from which soil water is absorbed by trees. Still, when using such an approach, it is crucial to consider potential time lags in the isotopic signature between source water in the soil and water in the capillaries of the tree in different heights (Waring, Whitehead & Jarvis 1979).

In the present study, we aimed to asses the water balance of Pinus sylvestris growing in a dry environment where trees cannot reach the groundwater directly as it is located about 7 m below ground level (Reif 1996). We combined isotopic approaches with xylem flow measurements and modelling of canopy stomatal conductance (Gs) over more than 1 year. In addition to our attempt to characterize the origin of water taken up by the trees, we related Δ13C and Δ18O in phloem organic matter obtained from twigs and trunks to environmental and physiological parameters. We sought to assess if this combined analysis of carbon and oxygen isotopes can be used as a tool to characterize water relations of the conifer P. sylvestris during the growing season.

We aimed to test the following main working hypotheses: Δ13C of the phloem organic matter can be used as an indicator for Gs with a time lag of a few days for the conifers species examined in a way as previously shown for a deciduous species (Keitel et al. 2003). If Gs is not a direct proxy for ci/ca, (i.e. if additional factors related to Rubisco activity and carboxylation influence ci) this can be revealed by the relation between Δ13C and the oxygen isotope enrichment (Scheidegger et al. 2000) – provided that Gs is mainly controlled by rH or VPD.

In addition, we hypothesized that Δ18O of phloem organic matter can be described not only for short periods but also during the whole year by applying the model of Farquhar & Lloyd (1993) that takes into account isotopic fractionations associated with H218O diffusion, with phase transition from liquid water to vapour, and with exchange between carbonyl oxygen and water as well as the isotopic gradients in leaf water caused by the Péclet effect.

In addition, we aimed to test if we could decipher the soil depth from which water is absorbed throughout the year by comparing the oxygen and hydrogen isotopic composition in precipitation, soil water at different depths and xylem water.

MATERIAL AND METHODS

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. ACKNOWLEDGMENT
  9. REFERENCES

Site description

Field experiments were carried out in an approximately 40-year-old Scots pine plantation (Pinus sylvestris L.) at the Hartheim forest meteorological experimental site (201 m a.s.l.; 47°56′N and 7°37′E) operated by the Meteorological Institute of the University of Freiburg. The pine stand is located in the southern upper Rhine plain near the village of Hartheim in Germany close to the river Rhine and the French border. Annual precipitation amounts to 667 mm and mean annual temperature to 9.8 °C according to the nearby weather station Bremgarten for the period 1951–1980 (Mayer et al. 2002). During the growing season (April–September), potential evaporation frequently exceeds precipitation (Tajchman 1972). Mean temperature during the growing season is 15.4 °C. Soil profiles are characterized as a calcaric Fluvisol (Hädrich & Stahr 1997) according to the Food and Agriculture Organization (FAO) classification, with a mean depth of the topsoil of 40 cm. Soil textural class is sandy silt, and soil density amounts to 1.0–1.4 g cm−3. The pH of the mineral soil varies between 7.2 and 8.1 (Hädrich & Stahr 1997).

Because of different measures of river regulation (between 1817 and 1959), the groundwater table has receded and is at present 7 m below the surface in this former flood plain forest area.

The historical vegetation was an alluvial forest that was replaced by drought-resistant Scots pine forests in the middle of the last century (Mayer et al. 2002).

Mean height of the trees was 14.3 m; stand density was 800 trees ha−1. Basal sap wood area amounted to 22.12 cm2 m−2, and projected LAIwas 2.07 after a thinning in autumn 1993 (Mayer et al. 2002). Further thinning in 2003 decreased basal sap wood area and LAI to 17.69 cm2 m−2 and 1.47, respectively, at the time of the studies. Understorey vegetation consists mainly of Brachypodium pinnatum, Carex alba and Carex flacca (Wedler et al. 1996).

Meteorological parameters

Dry and wet bulb temperatures were measured at a height of c. 15 m on a meteorological tower. Down- and upwelling short-wave radiation (pyranometers, type CM21; Kipp & Zonen, Delft, the Netherlands) as well as down- and upwelling long-wave radiation (pyrgeometers, type CG1, Kipp & Zonen) were measured immediately above the Scots pine forest canopy at 16 m above-ground level. Photosynthetic photon flux density (LI-190SA; Li-Cor, Lincoln, NE, USA) was recorded above the canopy. Precipitation was monitored at the top of the 30 m tower. All sensors were sampled every 30 s. A data acquisition system (CR23X; Campbell, Logan, UT, USA), which calculates 10 min average values and for precipitation, 10 min totals, was stationed at the experimental site. VPD was calculated from dry and wet bulb temperature.

Potential evapotranspiration rates (Epot) were obtained using the hydrological model BROOK90 (Federer, Vorosmarty & Fekete 1996), which is based on the approach by Shuttleworth & Wallace (1985).

Transpiration and canopy stomatal conductance

Prevailing conditions of water availability were analysed by measuring xylem water flow as a measure for tree water use applying Granier-style probes and by scaling up flow densities from a single tree to the stand level (Granier et al. 1996). Xylem sap flow was measured on 12 trees with thermocouple probes as described by Granier (1985, 1987).

Sap flow densities (SFDs) (L m−2 sapwood area s−1) were determined every 5 min and were calculated as means of 30 min. Daily sums of ST based on the stand ground area were upscaled using the following equation:

  • image(2)

where SA is the stand sapwood area (m2 m−2) and ΣSFD is the SFD summed up over 24 h (L m−2 d−1). Studying radial sap flow patterns of P. sylvestris, Nadezhdina, Cermak & Ceulemans (2002) found that active sapwood is restricted to the outer 60% of the stem radius. By analysing the sapwood area using the displacement method with a basic fuchsin/periodic acid dye for trees of different radii, a correlation was found between stem disc area at 1.3 m height and sapwood area (data not shown). From this relation, we calculated a mean sapwood area of 17.69 cm2 m−2, which was used for the ST calculation. Values of single trees were multiplied with a correction factor of 0.86 to incorporate the reduction of SFD at a depth of 20 to 40 mm (relative to the cambium) (Köstner et al. 1996).

Based on sap flux densities, mean daily canopy stomatal conductance (Gs, mmol m−2 s−1) was calculated using a simplified Penman–Monteith equation according to Pataki, Oren & Phillips (1998) & Keitel et al. (2003):

  • image(3)

where Gc is canopy conductance; γ is the psychrometric constant (kPa K−1); λ is the latent heat of vapourization (J kg−1); ρ is the density of moist air (kg m−3); cp is the heat capacity of moist air (J kg−1 K−1); P is the atmospheric pressure (Pa); R is the ideal gas constant (8.31 J mol−1 K−1]; Ta is air temperature (K); Js is mean daily sap flux density given in kg m−2 s−1, and LAI is the leaf area per ground area given in m2 m−2. VPD is given in kPa.

These calculations assume that (1) stem capacitance can be neglected, and that (2) canopy aerodynamic conductance is much larger than Gs as reported by Whitehead & Jarvis (1981), which means that aerodynamic resistance can be neglected in comparison with stomatal resistance. In short-term experiments lasting 9 d, Brandes et al. (2006) showed that canopy stomatal conductance (Gs) was comparable to mean leaf level stomatal conductance (gs) as determined with a portable gas exchange measurement device.

Plant material

Samples were collected biweekly at approximately 1100 h Central European Time (CET). Twigs of the lower, yet fully sun-exposed crown were collected from eight dominant or co-dominant trees. Trees were chosen randomly, but alternately, to avoid repetitive sampling that could produce artefacts because of wounding responses.

Phloem exudate collection was performed according to the method described in detail by Gessler et al. (2004). Active phloem tissue was cut from the twigs using a scalpel and from the trunks at 1.3 m height using a punch, and was subsequently separated from older bark tissue. From 24 February 2004 to 6 October 2004, additional phloem samples were collected from eight trees at each sampling date. Tissues were rinsed with water in order to remove cellular constituents that might have been released from destroyed cells at the site of cutting, and resin from resin reservoirs destroyed during sampling. Bark pieces were incubated in 2 mL H2O for 5 h at room temperature. Thereafter, the exudates were centrifuged. Previous studies (Schneider et al. 1996) with different species showed that contamination of phloem exudates with cellular constituents using the exudation technique are negligible under the experimental conditions applied.

Xylem sap was collected from sampled twigs and small branches. At the cut basal (or proximal when related to the main trunk) end of the twig, bark tissue was removed to avoid contamination with phloem sap. We applied a gentle vacuum with a hand pump to the cut end of the sampled branch that was sealed with silicon putty in 2 mL glass vials. Vacuum was maintained, and xylem sap was collected while small segments of branch wood were repeatedly cut from the apical end of the shoot.

Xylem water from twigs of trees is often extracted applying the cryogenic distillation technique (Ehleringer, Roden & Dawson 2000). In order to test if the mild vacuum extraction method we used was comparable to distillation, we harvested larger branches from the crown of seven pine trees and then sampled two twigs of a comparable order of ramification (with a diameter of approximately 1 cm) from each larger branch. A section of one twig (after removing the bark) was subjected to cryogenic distillation as described by Ehleringer et al. (2000). The other twig was used for mild vacuum extraction. Our assessment revealed that δ18O of xylem water did not differ significantly between the two methods (vacuum extraction, −4.13 ± 0.19‰; cryogenic distillation, −4.32 ± 0.42‰; P < 0.05).

Collection of precipitation and soil water

Precipitation and soil water samples were collected biweekly at the same time when plant material was collected. Precipitation was sampled above the canopy, using collection vessels designed after specification of the IAEA (2002) to avoid isotopic fractionation by evaporation of rainwater stored in the rain gauge. The special construction of these vessels prevents moisture exchange with the atmosphere. Soil samples were taken at depths of 0–2, 2–20 and 20–40 cm, packed in air-tight plastic bags and stored in a refrigerator until further treatment.

Soil samples were analysed gravimetrically for water content, and soil water was extracted using the toluene distillation method (Revesz & Woods 1990).

Carbon, oxygen and hydrogen isotope composition

From phloem exudates, 200 µL aliquots were transferred into silver (δ18O analysis) or tin (δ13C analysis) capsules and oven dried at 70 °C. Chromosorb (10 mg) was added into the tin capsules to improve combustion for δ13C analysis.

Samples were combusted in an elemental analyser (NA 2500; CE Instruments, Milan, Italy) for δ13C analysis and in a high temperature conversion/elemental analyser (TC/EA; Finnigan MAT GmbH, Bremen, Germany) for δ18O analysis, both coupled to an isotope ratio mass spectrometer (Deltaplus, Finnigan MAT GmbH) by a Conflo II interface (Finningan MAT GmbH). SDs were ±0.1 and ±0.4‰ for measurements of δ13C and δ18O, respectively.

Cernusak et al. (2003a) reported that δ18O of phloem organic matter from E. globulus varies depending on whether the sample cups were sealed under argon immediately upon removal from the drying oven, or whether they were folded so as to not form a gas-tight seal. The authors presume that the difference is caused by adsorption of water vapour from the atmosphere onto the surface of the dried sugars when the sample is not enclosed in a gas-tight cup. We tested this presumption on a separate set of 24 samples by sealing the dried phloem samples under argon immediately after removing them from the drying oven. We indeed found that the δ18O in phloem organic matter was lower if the samples were not sealed under argon, both sealed and unsealed data sets being well linearly correlated (r = 0.980, P < 0.0001, n = 24). We applied the following correction to our (unsealed) phloem samples: δ18Ocorrected = 1.14 × δ18Ounsealed − 2.88.

For the δ18O measurement of xylem sap samples, 0.3 µL of sap was injected by a GCPal autosampler (CTC, Zwingen, Switzerland) into a high TC/EA modified according to Gehre et al. (2004), coupled online to an isotope ratio mass spectrometer (Delta plus XP) via a ConFlo III interface (both Finnigan MAT GmbH). SDs for measurements were ±0.2‰.

Analyses of δ2H and δ18O of precipitation and soil water, as well as δ2H of xylem water were conducted using a Finnigan MAT Delta S dual inlet isotope ratio mass spectrometer (IRMS). For δ2H analysis, 1 µL of the sample was injected into an H-device using a chrome reduction method at 900 °C that subsequently produces hydrogen gas. δ18O measurements were performed by equilibrating 5 mL of the sample with CO2 for 11 h at 20 °C within an equilibration unit. Analytical precision was better than ±0.2 and ±1‰ for δ18O and δ2H, respectively.

The isotopic values are expressed in delta notation (in ‰ units), relative to Vienna Pee Dee Belemnite (VPDB) for carbon and Vienna Standard Mean Ocean Water (VSMOW) for oxygen and hydrogen.

Isotopic calculations for organic matter and oxygen isotope theory

To eliminate the influence of source water on δ18O and of atmospheric CO2 on δ13C, respectively, in phloem organic compounds, Δ18O and Δ13C were calculated. Δ18O defines the enrichment of phloem organic compounds compared to xylem sap signature and was calculated using the following equation:

  • image(4)

where Δ18Oorg is the enrichment of phloem organic compounds in 18O above source (i.e. xylem) water; δ18Oorg is the oxygen isotope composition of phloem organic compounds, and δ18Os is the oxygen isotope composition of xylem water. The discrimination of 13C during assimilation (Δ13C) was calculated using the equation:

  • image(5)

where Δ13Corg is the depletion of 13C in phloem organic compounds compared to the source C isotope composition, which is that of atmospheric CO2(δ13CCO2). δ13Corg is the carbon isotope composition of phloem organic compounds. δ13C values of atmospheric CO2 were derived from measurements recorded at the nearby Schauinsland measurement station of the Umweltbundesamt between 1977 and 1992 (Levin, Graul & Trivett 1995). This station is approximately 20 km from the field site examined here. Mean annual peak-to-peak amplitude was 0.8‰ during that period. A slight annual decrease of 0.02‰ was recorded in the first 10 years, but no long-term trend was observed thereafter. We thus used averaged monthly values (range: −7.7 to −8.5‰) of the last 5 years for calculating Δ13C.

The enrichment of water at the sites of evaporation can be calculated with the following model (Craig & Gordon 1965; Farquhar & Lloyd 1993):

  • image(6)

where ε+ is the equilibrium fractionation between liquid water and vapour at the air–water interfaces; εk is the kinetic fractionation during diffusion of water vapour from the leaf intercellular gaseous space to the atmosphere (calculated according to Farquhar et al. 1989b), taking into account new determinations of the isotopic effect for diffusion of H218O in air (Cappa et al. 2003); Δ18Ov is the difference in δ18O between source water and atmospheric water, and ea/ei is the ratio of external to internal water vapour pressure. Average lamina mesophyll water is, however, supposed to be less enriched than the water at the evaporative sites because of the influx of unenriched xylem water into the leaf. Steady-state enrichment of mean lamina leaf water (Δ18OL) depends on the steady-state enrichment at the evaporative site of the leaf (Δ18Oe) and on the lamina radial Péclet number inline image (Farquhar et al. 1993; Farquhar & Gan 2003):

  • image(7)

where the Péclet number is defined as EL/CD, where E and L are transpiration rates (mol m−2 s−1) and scaled effective path length (m), respectively; C is the molar concentration of water (mol m−3), and D is the diffusivity of H218O in water (m2 s−1). Oxygen isotope signatures in organic plant material record the 18O signature of the water in which they were formed (Epstein, Thompson & Yapp 1977; Yakir & Deniro 1990). Enrichment of 18O above source water in the newly produced organic matter (Δ18Op) depends on Δ18O of average lamina mesophyll water (Δ18OL, Eqn 7) and on the equilibrium fractionation between organic carbonyl oxygen and water (εwc; +27‰; Cernusak, Wong & Farquhar 2003b). We, thus, applied Eqn 7, taking into account εwc for predicting Δ18O of phloem organic matter (Δ18Ocalc).

For this calculation, we made the following assumptions according to Keitel et al. (2006): water vapour was in isotopic equilibrium with source water, as often assumed to be valid during the growing season in Europe (Förstel & Hützen 1983; Saurer, Borella & Leuenberger 1997). In that case, Δ18Ov in Eqn 6 equals −ε+. Keitel et al. (2006) revealed that making this assumption is justified when calculating 18O enrichment of phloem organic matter in Central Europe. Different from Keitel et al. (2006) working with a broadleaf species, we assumed here that leaf temperature equals air temperature according to Barbour, Walcroft & Farquhar (2002). These authors showed that needles of Pinus radiata were strongly coupled to the environment, making leaf temperature, ei and ε+ scale directly to air temperature.

ε+ was calculated from air temperature according to Bottinga & Craig (1969). εk was calculated according to Farquhar et al. (1989b), taking into account new determinations of the isotopic effect for diffusion of H218O in air (Cappa et al. 2003). The range for εk was 31.2–32.0‰. We assumed aerodynamic resistance << stomatal resistance when calculating εk. Values for the effective length L generally vary between 0.004 and 0.17 m (Wang, Yakir & Avishai 1998; Barbour & Farquhar 2004). Thus, we tested values for L of 0.005, 0.015, 0.025, 0.04, 0.055 and 0.07 m. In addition, we calculated Δ18Ocalc ignoring a potential Péclet effect.

Δ18Ocalc was modelled with the mean day-time values of Gs, air temperature, ea, ei and transpiration rate from different times (1–5 d) preceding phloem sampling.

Statistical analyses

Statistical analyses were conducted using SPSS 10.05 (SPSS Inc., Chicago, IL, USA) Correlations were calculated using the bivariate correlation procedure. Significance of correlation was calculated according to Sachs (1984). Regression lines between δ13C and δ18O were determined by linear regression analysis. Differences between mean values were estimated applying Student's t-test.

RESULTS

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. ACKNOWLEDGMENT
  9. REFERENCES

Meteorological and hydrological conditions

Total precipitation (P) during the study period amounted to 1008 mm (Fig. 1a). Almost 400 mm of precipitation fell during the growing season (April–September). The highest monthly precipitation value was recorded in October 2004 (170 mm), the lowest in April 2004 (12 mm). Daily values of P were variable with a maximum of 50.4 mm on 26 October 2004.

image

Figure 1. Meteorological and hydrological parameters at the experimental site of Hartheim from July 2003 to December 2004. (a) Daily sum (mm d−1) and cumulative precipitation, (b) daily mean air temperature (°C) (dashed line) and potential evapotranspiration (Epot) (mm d−1) (solid line), (c) relative humidity (rH) (%) and (d) soil water content (mm) in the soil layer 0–40 cm.

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Maximum air temperature (Ta) was 27.5 °C in August 2003, and minimum values of −4.5 °C were detected in January 2004 (Fig. 1b). Epot followed the same trend as air temperature with a total sum of 1239 mm during the investigation period and 697 mm during the growing season.

Relative humidity showed minimum values at the beginning of August 2003 and July 2004, and there was a longer period of low rH < 65% between mid April and early May 2004.

Soil water contents in the upper soil horizon (0–40 cm; Fig. 1d) were close to the permanent wilting point (PWP = 46.8 mm) in summer and autumn 2003. In October 2003, soil water content increased to values above 100 mm and remained close to saturation (field capacity = 125.6 mm) until April 2004. Soil water content varied between 20 and 105 mm in summer 2004, and reached field capacity again in November 2004.

Transpiration and canopy stomatal conductance

Highest daily ST values in 2003 were between 1.2 and 1.3 mm d−1 during several days in September and October. ST decreased in the middle of October and remained at approximately 0.24 mm d−1 between November 2003 and mid-March 2004 (Fig. 2). Highest ST during the growing season was slightly above 2 mm d−1, and average transpiration was 1.29 mm d−1. Transpiration was coupled to atmospheric evaporative demand because daily sums of transpiration showed dependency (R2 = 0.51, P < 0.0001) on mean daily VPD with a regression line characterized by the following linear equation: ST(mm d−1) = 0.0012(mm d−1 Pa−1) × VPD(Pa) + 0.2338(mm d−1). Gs calculated from the simplified Penman–Monteith equation was not realistic between 17 October 2003 and 14 March 2004, and from 8 November to 31 December 2004 because of Ta approaching 0 and rH close to 100% (Keitel et al. 2003). Throughout the measurement period, Gs values were eliminated at times when rH exceeded 90% and Ta was below 0 °C. During the periods when calculations were possible, mean daily Gs values were on average 87 mmol m−2 s−1 and varied between 10 and 214 mmol m−2 s−1. Whereas soil water content was not related significantly to Gs (P = 0.272), an increase in VPD decreased maximum Gs (Fig. 3). Value pairs (Gs/VPD) were grouped by the VPD value in a way that each step of 100 Pa was categorized as one VPD range group. The maximum Gs value from each group was used to complete a regression analysis. The linear equation for the regression line was Gs(mmol m−2 s−1) = −0.102(mmol m−2 s−1 Pa−1) × VPD(Pa) + 206(mmol m−2 s−1) with R2 = 0.91 and P < 0.0001.

image

Figure 2. Daily sums of stand transpiration (ST) (grey bars) and mean daily canopy stomatal conductance (Gs) (black line) from August 2003 to December 2004. Data gaps for ST in September and October 2003 are due to a data logger malfunction. Using the Penman–Monteith equation canopy stomatal conductance could not be calculated during winter.

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image

Figure 3. Daily averaged Gs versus daily averaged VPD of all days on which Gs could be calculated. The whole range of VPD values during the investigation period was divided into VPD groups with a range of 100 Pa each. Closed symbols show maximum Gs values for each of the 17 VPD groups. Open symbols show all other measured data points.

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Isotopic signatures of precipitation, soil water and xylem water

Figure 4a reveals the hydrogen and oxygen isotopic composition of precipitation above the canopy and the monthly mean values weighted for the amount of precipitation. The mean value of the entire measurement period was c. −53‰ (range: −7 to −144‰) for δ2H and −7.8‰ (range: −1.6 to −19.2‰) for δ18O. A clear annual pattern with isotopically enriched precipitation from April to October and relatively depleted precipitation during winter (November–March) was evident. The weighted monthly means of δ18O and δ2H were significantly correlated with mean monthly air temperatures [δ18O(‰) = 0.373(‰ °C−1) × T(°C) − 11.895(‰), R2 = 0.6, P < 0.01; δ2H(‰) = 2.9278(‰ °C−1) × T(°C) − 84.505(‰), R2 = 0.58, P < 0.01].

image

Figure 4. Hydrogen and oxygen isotope composition of precipitation, soil water and xylem water at the experimental site of Hartheim from July 2003 to December 2004. (a) δ18O and δ2H of precipitation, (b) δ18O and (c) δ2H values of soil water at different depths and xylem water. Xylem water values are means ± SD of eight trees.

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The annual patterns of δ18O and δ2H in precipitation could be found again in the isotopic composition of soil water (Fig. 4b,c). However, soil water δ18O and δ2H were damped in their annual variation compared to precipitation. The scattering of the values around the annual mean value, described by the variance (σ2), was reduced, for example, for δ18O from 13.5‰ for precipitation to 11.6‰ (soil water 0–2 cm), 8.0‰ (soil water 2–20 cm) and finally to 2.7‰ for soil water in 20–40 cm depth. Xylem δ18O and δ2H were generally comparable to signatures of middle and lower parts of the soil profile (2–20 cm and 20–40 cm) from March to October. Differing from soil and rain water, there was only a slight decline in δ18O and δ2H of xylem water during winter. As a consequence, xylem water δ18O and δ2H signatures were greater when compared with potential source water from November to February.

Δ13C of organic matter

Δ13C of organic matter in trunk and twig phloem varied between 16.5 and 19.3‰, and between 17.3 and 20.2‰, respectively (Fig. 5a). Δ13C of twig phloem was positivelyrelated to Δ13C of trunk phloem (R2 = 0.41, P < 0.0001), and the regression line was below the 1 : 1 line [Δ13Ctrunk(‰) = 0.5859 × Δ13Ctwig(‰) + 6.8137(‰)]. Applying Student's t-test, a significant (P < 0.001) difference between average values of trunk phloem Δ13C and twig phloem Δ13C was revealed. Twig phloem organic carbon was depleted in 13C on average by 1.1‰ compared to trunk phloem.

image

Figure 5. Δ13C (a) and Δ18O (b) of organic matter from trunk phloem (closed circles) and twig phloem (open circles). Data shown are mean values + or − SD from eight trees sampled for twig and trunk phloem except for the period from 10 February 2004 to 6 October 2004 where 16 trees were sampled for trunk phloem.

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Correlation analysis between Δ13C and meteorological and physiological parameters did not reveal significant relations. Not even moderate correlations could be found between Δ13C and P, ST, Ta, rH, VPD, global radiation (GR), PAR and Gs, respectively. Even if time lags of 1–7 d between environmental/physiological traits and a potentially detectable influence on phloem Δ13C were assumed (Keitel et al. 2003), correlation coefficients were always < 0.5 (data not shown).

Δ18O of organic matter

Δ18O in trunk and twig phloem varied throughout the year with amplitudes of 13.5 and 13.3‰ (Fig. 5b), respectively, which were about 4.5 times as high as those of Δ13C. Trunk phloem Δ18O was strongly related to twig phloem Δ18O [Δ18Otrunk(‰) = 0.8447 × Δ18Otwig(‰) + 5.8442(‰) R2 = 0.81, P < 0.0001). Student's t-test showed a significant (P < 0.001) difference between average values of trunk phloem Δ18O and twig phloem Δ18O. Trunk phloem signatures were on average 0.8‰ higher throughout the measurement period. From September 2003 to March 2004, Δ18O values exhibited a steady increase of c. 4‰. In April 2004, Δ18O of twig and trunk phloem increased dramatically until they reached values of up to 42‰ in mid May, then they decreased until July 2004. In November and December 2004, values were c. 2‰ lower than in the year before.

Table 1 shows Pearson's correlation coefficients between Δ18O in the twig phloem (Table 1a) or trunk phloem (Table 1b) and various climatic and physiological parameters. Time lags between recorded parameters and corresponding Δ18O were between 0 (parameters recorded on the day of phloem sampling) and 5 d. At a significance level of P < 0.01, weak or moderate correlations were found between Δ18O in the twig phloem and ST, rH, VPD, PAR and GR; the highest correlations with rH, VPD, PAR and GR arose with a time lag of 1 d. Correlations of Δ18O from trunk phloem organic matter with the same parameters (Table 1b) depicted similar results: for rH and VPD, the highest correlations were obtained with a time lag of 1 d, and there were no clear differences when different time lags were applied for PAR and GR. With both, Δ18O of twig and trunk phloem, Ta and P were only weakly correlated. Gs and ST showed moderate correlation at time lags > 2 d.

Table 1.  Correlation between Δ18O in organic compounds of the twig (a) or trunk phloem sap (b) and daily means/sums of physiological and meteorological parameters and Δ18Ocalc of the day of sampling and 1 to 5 d prior to sampling
(a)Time lag (d)
Δ18O twig versus012345
Gs0.320.270.310.600.450.71
ST0.370.490.560.560.530.51
Ta0.120.280.330.340.270.21
rH−0.33−0.63−0.50−0.28−0.44−0.43
VPD0.280.520.380.230.370.28
P0.12−0.29−0.09−0.23−0.08−0.25
PAR0.320.530.460.420.520.36
GR0.310.520.450.400.510.35
Δ18Ocalc0.620.720.800.490.320.25
(b)Time lag (d)
  1. Values in italics and bold are significant at the 0.05 and 0.01 level, respectively.

  2. Gs, canopy stomatal conductance; ST, stand transpiration; Ta, air temperature; rH, relative humidity; VPD, water vapour pressure deficit; P, precipitation; PAR, photosynthetic active radiation; GR, global radiation; Δ18Ocalc, calculated enrichment of phloem organic matter.

Δ18O trunk versus012345
Gs0.320.210.290.610.330.69
ST0.400.420.550.590.570.67
Ta0.190.320.370.350.300.23
rH−0.36−0.58−0.52−0.28−0.40−0.49
VPD0.290.460.380.210.340.38
P0.22−0.06−0.06−0.150.14−0.25
PAR0.330.500.480.480.540.50
GR0.330.500.460.460.540.50
Δ18Ocalc0.710.760.810.540.420.33

In addition, Δ18Ocalc modelled with a scaled effective path length of 0.055 m was related to measured Δ18O in the twig and trunk phloem. The highest correlation coefficients (0.80, twig phloem; 0.81, stem phloem) were obtained when a time lag of 2 d was taken into account.

Figure 6 shows the quantification of the relationship between measured Δ18O in the twig and trunk phloem organic matter and Δ18Ocalc by means of regression analysis. Δ18Ocalc was computed for different L or by not taking into account the Péclet effect for a time lag of 2 d. The highest R2 values were obtained for twig (R2 = 0.64) and trunk phloem (R2 = 0.66) organic matter, assuming L to be 0.055 m, whereas higher and lower values for L decreased R2. The linear equations for the regression (L = 0.055 m) lines were Δ18Ocalc(‰) = 0.993 × Δ18O twig phloem (‰) + 1.506(‰) and Δ18Ocalc(‰) = 0.973 × Δ18O trunk phloem (‰) + 1.326(‰).

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Figure 6. Modelled Δ18O of phloem organic matter (Δ18Ocalc) plotted against measured Δ18O in the twig (a) in trunk phloem (b) organic matter assuming a time lag of 2 d. Regression relations were calculated with Δ18Ocalc computed for different values of L (thin dotted line, 0.005 m; thin dashed line, 0.015 m; thin dash-dotted line, 0.025 m; bold dotted line, 0.04; bold dashed line, 0.055; bold dash-dotted line, 0.07; thin solid line, Péclet effect not taken into account). The bold solid line denotes the 1:1 line. The circles displayed are the data points for L = 0.055.

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The slope of the regression line between Δ18O and Δ13C is required for analysis of the conceptual model proposed by Scheidegger et al. (2000). Plotting Δ13C of phloem organic matter versus Δ18O produced a horizontal scatter cloud with a regression slope not significantly differing from 0 [Δ13C(‰) = −0.0814 × Δ18O(‰) + 21.333(‰); R2 = 0.08, P = 0.25].

DISCUSSION

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. ACKNOWLEDGMENT
  9. REFERENCES

The aim of the present study was to assess the influence of meteorological, pedospheric and physiological factors on the water relations of Scots pine, as characterized by the carbon isotope discrimination (Δ13C) and oxygen isotope enrichment (Δ18O) of newly assimilated organic matter during the entire year. In addition, we aimed to describe the origin of water absorbed by these conifers via a comparison between δ18O and δ2H of xylem water with potential source water.

The meteorological conditions at the experimental site during the investigation period were characterized by a very warm and dry summer 2003 and a dry spring period in 2004 followed by a relatively wet summer and autumn in 2004. We were thus able to characterize water relations of Scots pine within a wide range of meteorological conditions.

Transpiration and canopy stomatal conductance

Daily sums of ST in Hartheim were comparable with those of 70-year-old P. sylvestris trees in a mixed forest stand with similar stand density (Meiresonne et al. 2003). Irvine et al. (1998) reported a decline in transpiration in Scots pines when volumetric soil water content decreased below 12%. However, the trees investigated in our study did not show reactions of Gs towards decreased soil water contents with values approaching the PWP (PWP = 46.8 mm equals 11.7 volume%). This difference might be explained by the fact that the Hartheim trees were experiencing ‘normal’ conditions within the period of our measurements because they are adapted to comparable soil water depletion during their individual development. As Gs appears not to be influenced by soil/root-borne signals, transpiration rates should change according to the atmospheric water demand. This is in agreement with the correlation found between VPD and ST, and the connection between VPD and Gs. Whereas transpiration is closely coupled to atmospheric water demand, stomatal conductance is more likely to be controlled physiologically and probably triggered on different control levels. Figure 3 shows that only the maximum of Gs for a given VPD range is strongly controlled and limited by atmospheric water demand, whereas no general correlation between Gs and VPD can be established. We therefore have to assume that additional factors (which might be, e.g. connected to photosynthetic activity and CO2 demand) influence Gs.

Isotopic signatures of precipitation, soil water and xylem water

The isotopic composition of precipitation is influenced by different fractionation effects (Moser & Rauert 1980; Kendall & McDonnell 1998). The most important effect at the plot scale is the seasonal effect due to temperature differences with isotopically lighter precipitation in winter months and heavier in summer as shown for the present study in Fig. 4a.

The calculated relationship between weighted monthly mean values of δ18O in precipitation and air temperature are in line with the worldwide relationship reported by Clark & Fritz (1997) [δ18O(‰) = 0.338(‰ °C−1) × T(°C) − 11.99(‰); R2 = 0.815]. It must, however, be mentioned here that on a larger (or even worldwide) scale, elevation effects also influence δ18O of precipitation (Barbour, Andrews & Farquhar 2001).

In spring, summer and autumn 2004, both δ18O and δ2H of xylem water were in a range comparable to soil water of 2–20 cm depth. In August 2003 when soil water availability was very low and superficial desiccation of soil has to be assumed, xylem water isotopic composition equalled thatof soil water from deeper soil layers, thus confirming our working hypothesis. In contrast to the main growing season, oxygen and deuterium signatures in twig xylem water were higher compared with soil water at all three depths during late autumn and winter of both 2003 and 2004 (Fig. 4b,c).

Two main possible factors can explain this observation. Firstly, if isotopically enriched phloem water (Cernusak et al. 2005) is transferred to the xylem, where it mixes with xylem water, this could result in 18O and 2H enrichment during periods of low xylem-flow rates. Evaporative influences would be indicated by a change in the slope of the regression line between δ18O and δ2H of xylem samples compared to the local meteoric water line (LMWL) (Gonfiantini 1986).

Figure 7 shows the δ2H and δ18O values of the soil water samples at different depths, and the xylem samples from winter and summer. Soil water samples collected in summer from the uppermost soil layer exhibited a lower slope (4.2‰/‰) for the relationship between δ2H and δ18O compared with the LMWL as a result of evaporative enrichment. In contrast, xylem samples are well represented by the LMWL. We can therefore exclude any influence of evaporation on the isotopic composition of xylem water.

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Figure 7. δ18O versus δ2H values of soil water at different depths (filled diamonds, 0–2 cm; semi-filled diamonds, 2–20 cm; and open diamonds, 20–40 cm) and xylem water (open circles, summer period July–October 2003 and May–October 2004; grey filled circles, winter period November 2003–April 2004 and November and December 2004). The black dashed line is the regression line between summer values (July–October) of δ18O and δ2H in soil water (0–2 cm); GMWL (global meteoric water line): δ2H(‰) = 8(‰/‰) × 18O(‰) + 10(‰); LMWL (local meteoric water line): δ2H(‰) = 7.85(‰/‰) × 18O(‰) + 6.2(‰).

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The second explanation can be related to the time it takes for water to be taken up from the soil and transported to the canopy in winter, when temperature and transpiration rates are low (Figs 1 & 2). In an experiment initiated in June 2004 in which trees of the same stand were irrigated with deuterium-labelled water, a transport time of 5 d from the soil to the twigs was detected when average daily sums of transpiration were 1.18 mm (Wenninger & Brandes, unpublished results). This result is well within the range of water transit times during the growing season for different conifers (Meinzer et al. 2006). As daily transpiration sums were 0.2 mm from mid-October 2003 to February 2004 and 0.17 mm from November to December 2004, transport times of 30 and 33 d, respectively, can be assumed. In addition, tree stems can function as water-storage pools with residence times for water of up to 44 d in some conifers (Meinzer et al. 2006). During winter, recharge of sapwood water storage over a period of several months has been observed (Waring et al. 1979). Thus, it is most likely that the deviation of the isotopic composition of xylem water from soil water in winter is due to slow water transport within the xylem and a mixing of newly absorbed water with isotopically heavier stored water. Water storage in stems may also attenuate the variations in δ18O and δ2H in xylem water as compared to soil water during the growing season.

Δ13C and Δ18O of organic matter

In general, it is assumed that Δ13C and Δ18O of short-turn over carbon pools in leaves or phloem are strongly dependent on ci/ca (or on proxies for this value) (for Δ13C) and on Gs (for Δ18O), respectively (Brugnoli et al. 1988; Barbour & Farquhar 2000; Barbour et al. 2000; Cernusak et al. 2003a; Keitel et al. 2003; Scartazza et al. 2004). Keitel et al. (2003) and Gessler et al. (2004) showed that Gs could be used as a proxy for ci/ca in beech and, consequently, they found a relation between carbon isotope signature of trunk phloem organic matter and Gs, taking into account that transport of newly produced assimilates from the canopy to the stem base took approximately 2 d. In contrast to previous observations, no such correlation was observed for Scots pine trees in this study.

Because of the lack of a direct linear dependency between Δ13C and environmental or physiological parameters, we may conclude that there is a combined influence resulting from several parameters. In short-term assessments during 9 d within the same stand, Brandes et al. (2006) showed that the combined influence of stomatal diffusion and carboxylation determined internal CO2 concentration and, consequently, photosynthetic carbon isotope discrimination of pine trees. The authors applied a multiple regression model including Gs and assimilation rate as determinants that explained 55% of the variation in ci/ca.

According to the conceptual model of Scheidegger et al. (2000), this interaction should also be reflected by the relation between Δ18O and Δ13C. Δ18O of recently synthesized organic matter should share – according to that model – the dependence on stomatal conductance with Δ13C but should not be dependent on Rubisco activity (Barbour et al. 2004). When a combined influence of stomatal conductance and carboxylation efficiency on carbon isotope discrimination is assumed, plotting Δ13C (y-axis) versus Δ18O (x-axis) should result in a regression line with a slope close to 0 as also observed for our data. However, a prerequisite for Scheidegger's model is that stomatal conductance is strongly guided by rH or VPD because ea/ei is in fact mainly controlling Δ18O (Eqn 6). As shown in Fig. 3, only maximum Gs but not Gs in general is controlled by VPD in this study. Consequently, we have to assume that the Scheidegger model is not applicable in our case and have to reject the working hypothesis that the relation between Δ18O and Δ13C can be used as a tool to differentiate between influences of stomatal diffusion and carboxylation efficiency on Δ13C.

To overcome this constraint, we applied a multiple regression model with Gs and PAR (as a proxy for assimilation rate) as independent variables to explain the variability of Δ13C during the entire year in a manner comparable to the regression analysis Brandes et al. (2006) used for determining ci/ca in their short-term experiment. However, such an approach applied on the whole year data set did not reveal any significant results (P = 0.56). Keitel et al. (2006) hypothesized that the relative influence of Gs and carboxylation on the carbon isotope composition of phloem organic matter from beech varied during the growing season, resulting in stronger dependency of δ13C on Gs in July compared with September. We can assume that a comparable variable influence of the two determinants on Δ13C during the year prevents single or multiple regression models from being significant in our study.

Δ18O in both trunk and twig phloem organic matter was significantly correlated with rH with a time lag of 1 or 2 d, whereas no significant relation was found with Gs. After 3–5 d, a significant correlation with Gs was found, however, (1) without a concomitant correlation with rH and (2) with a positive correlation coefficient. Therefore, and because time lags between atmospheric or physiological conditions during assimilation and the isotopic signal in phloem organic matter collected at different positions including the stem base from beech and pine are reported to lie between 1 and 2 d (Keitel et al. 2003; Gessler et al. 2004; Brandes et al. 2006) we have to assume these relations not to be causal.

On the other hand, the model we applied to predict evaporative 18O enrichment, which takes into account the 18O fractionation associated with the exchange of water between leaves and the atmosphere and with production of organic matter, is able to explain up to 66% of the variation of phloem organic matter during the year with a realistic time lag. In addition, the model shows that besides ea/ei, a Péclet effect, mainly driven by transpiration, has to be taken into account when estimating Δ18O of organic matter. The highest regression coefficient was obtained when a scaled effective path length of 0.055 m was assumed. This value is well within the range observed for other tree species including conifers (Wang et al. 1998; Cernusak et al. 2005; Farquhar & Cernusak 2005; Pendall, Williams & Leavitt 2005). When comparing modelled Δ18O to 18O enrichment in both twig and trunk phloem organic matter, a slight offset from the 1:1 line was observed.

This offset and the fact that 34–36% of the variation of Δ18O cannot be explained by the regression line shown in Fig. 6 may be due to the simplified assumptions made when applying the steady-state model for calculating evaporative enrichment.

For our model application, we assumed atmospheric water vapour to be in isotopic equilibrium with source (xylem) water. In regions not located close to the coast, air moisture is in fact often near equilibrium with local precipitation water (e.g. Dansgaard 1964; Gat 1998). However, at the local scale, significant short-term variation can occur in δ18O of water vapour mainly associated with changes in wind direction and not related to evapotranspiration (Yakir 1998) and may, thus, temporarily prevent equilibrium conditions. In addition, for our model, we assume isotopic steady-state conditions for leaves. However, stronger changes in rH during the diurnal cycle combined with slow leaf water turnover are known to result in deviations from this steady state (Wang & Yakir 1995) and can potentially lead to an overestimation of Δ18O. Furthermore, it is likely that the term L does not remain constant with environmental conditions, leaf age and time (Pendall et al. 2005). Plants can quickly react with reduced tissue hydraulic conductance to drought stress, a reaction that is supposed to be mainly mediated by reduced expression and/or activity of aquaporins (for a recent review, see Tyerman, Niemietz & Bramley 2002).

Moreover, we have to assume that – especially during spring – remobilization of starch from the previous year needles might affect Δ18O in phloem organic matter. The 18O enrichment of sucrose remobilized from starch is partially uncoupled from current leaf water enrichment. When we assume that part of the oxygen atoms in sucrose generated from starch to be exchangeable with the reaction water via carbonyl hydration (Farquhar et al. 1998), we must consider a mixed influence of leaf water conditions during the time of starch storage and current conditions.

Organic matter from twig phloem was consistently depleted in 13C and in 18O compared to that from stem phloem throughout the year. Other studies conducted on Scots pine have hypothesized that the smooth bark surfaces of twigs are capable of photosynthetic CO2 refixation (Linder & Troeng 1980), whereas this does not occur in trunks that have thick, rough barks. Carbon refixed from respired CO2 by photosynthetic bark is strongly depleted in 13C compared with the carbon fixed by leaves (Cernusak et al. 2001). Additionally, organic matter refixed in the bark where reaction water is not or only slightly enriched and should have a Δ18O of approximately 27‰ (Cernusak et al. 2005), well below the enrichment for sugars fixed in leaves. If the bark phloem exudates from twigs included some sugars formed by refixation, whereas those from the trunks did not (or – when we assume that part of the refixed sugars is transported in basipetal direction – contained a lower amount), this would explain the variation between the two in isotopic composition.

CONCLUSIONS

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. ACKNOWLEDGMENT
  9. REFERENCES

Comparing the natural isotopic composition of soil and xylem water gives insight into the potential for trees to acquire water from different soil layers depending on water availability during summer, when transpiration rates are high.

Whereas Δ13C in phloem was not a direct predictor for recent stomatal reaction, the measurement and modelling of Δ18O in organic matter combined with the assessment of ST and canopy stomatal conductance proved to be effective tools in assessing the water balance of pine trees at that dry site, thus helping to understand and predict potential impacts of climate change on trees and forest ecosystems.

ACKNOWLEDGMENT

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. ACKNOWLEDGMENT
  9. REFERENCES

The study was financially supported by the state of Baden-Württemberg (Landesforschungsschwerpunkt-Programm). AG acknowledges personal financial support by a research fellowship from the Deutsche Forschungsgemeinschaft (GE 1090/4-1). The authors thank R.A. Werner and N. Buchmann for supporting part of the oxygen isotope analyses. We would also like to thank D. Onorato for critical reading and three anonymous referees for their helpful and constructive comments.

REFERENCES

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  2. ABSTRACT
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSIONS
  8. ACKNOWLEDGMENT
  9. REFERENCES
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