text:
The present work was supported by the European Community's Human Potential Programunder contract HPRN-CT-1999-00059, NETCARB, coordinated by Jaleh Ghashghaie.
On the 13C/12C isotopic signal of day and night respiration at the mesocosm level
Article first published online: 15 JAN 2010
DOI: 10.1111/j.1365-3040.2010.02115.x
© 2010 Blackwell Publishing Ltd
Plant, Cell & Environment
Volume 33, Issue 6, pages 900–913, June 2010
Additional Information
How to Cite
TCHERKEZ, G., SCHÄUFELE, R., NOGUÉS, S., PIEL, C., BOOM, A., LANIGAN, G., BARBAROUX, C., MATA, C., ELHANI, S., HEMMING, D., MAGUAS, C., YAKIR, D., BADECK, F. W., GRIFFITHS, H., SCHNYDER, H. and GHASHGHAIE, J. (2010), On the 13C/12C isotopic signal of day and night respiration at the mesocosm level. Plant, Cell & Environment, 33: 900–913. doi: 10.1111/j.1365-3040.2010.02115.x
Publication History
- Issue published online: 13 MAY 2010
- Article first published online: 15 JAN 2010
- Received 12 September 2009; received in revised form 20 December 2009; accepted for publication 2 January 2010
- Day respiration;
- isotope;
- fractionation;
- mesocosm;
- sunflower
- Top of page
- Supporting Information
While there is currently intense effort to examine the 13C signal of CO2 evolved in the dark, less is known on the isotope composition of day-respired CO2. This lack of knowledge stems from technical difficulties to measure the pure respiratory isotopic signal: day respiration is mixed up with photorespiration, and there is no obvious way to separate photosynthetic fractionation (pure ci/ca effect) from respiratory effect (production of CO2 with a different δ13C value from that of net-fixed CO2) at the ecosystem level. Here, we took advantage of new simple equations, and applied them to sunflower canopies grown under low and high [CO2]. We show that whole mesocosm-respired CO2 is slightly 13C depleted in the light at the mesocosm level (by 0.2–0.8‰), while it is slightly 13C enriched in darkness (by 1.5–3.2‰). The turnover of the respiratory carbon pool after labelling appears similar in the light and in the dark, and accordingly, a hierarchical clustering analysis shows a close correlation between the 13C abundance in day- and night-evolved CO2. We conclude that the carbon source for respiration is similar in the dark and in the light, but the metabolic pathways associated with CO2 production may change, thereby explaining the different 12C/13C respiratory fractionations in the light and in the dark.
- Top of page
- Supporting Information
Isotopic fractionation against 13CO2 during photosynthesis (denoted as Δ) drives the isotopic signal of ecosystems, in which the carbon isotope composition of fixed CO2 follows the well-accepted relationship involving internal CO2 mole fraction and fractionations associated with diffusion and carboxylation (Farquhar, O'Leary & Berry 1982; Lloyd & Farquhar 1994). Nevertheless, at the ecosystem level, CO2 evolved by plant respiration is believed to account for 30–70% of the ecosystem CO2 exchange (Amthor 2000) so that the isotopic signal of respired CO2 has a major influence on the 12C/13C ecosystem mass balance (Lavigne et al. 1997). Therefore, current efforts are devoted to elucidating the isotopic signal of CO2 evolved by several ecosystem compartments such as trunks (Brandes et al. 2006; Gessler et al. 2007; Maunoury et al. 2007) and soil (Ekblad & Hogberg 2001; Bostrom, Comstedt & Ekblad 2007). At the leaf level, there is now compelling evidence that photorespiration fractionates against 13C, thereby liberating 13C-depleted CO2 as compared to photosynthates (Lanigan et al. 2008).
In contrast, little is known on the isotopic composition of day-respired CO2, although several authors have suggested that day respiration produces 13C-depleted CO2 (von Caemmerer 2000; Ghashghaie et al. 2003; Tcherkez et al. 2004; Lanigan et al. 2008). In the dark, leaf-respired CO2 has been shown to be 13C enriched, with some variations that depend on the respiratory rate, which is in turn influenced by leaf temperature or leaf respiratory substrates (Duranceau et al. 1999; Ghashghaie et al. 2001; Tcherkez et al. 2003). In fact, leaf-respired CO2 is considerably 13C enriched just after darkening (Mortazavi et al. 2005; Barbour et al. 2007; Werner et al. 2007; Gessler et al. 2009), and then reaches a steady value up to 6‰ enriched as compared to sucrose (Duranceau et al. 1999). The isotope composition of CO2 evolved by other organs is less well documented: while roots have been repeatedly shown to produce 13C-depleted CO2 (Badeck et al. 2005; Klumpp et al. 2005; Bathellier et al. 2009), twigs and trunks have a more variable pattern that depends upon environmental parameters (Damesin & Lelarge 2003). However, the respiratory contribution of all non-photosynthetizing organs when integrated as isotopic fractionations at the plant level is not well defined (for a recent review, see Bowling, Pataki & Randerson 2008).
In consequence, it has often been assumed that the respiratory isotopic signal of plants, mesocosm and ecosystems is similar in the light and in the dark (e.g. Schnyder et al. 2003, but see Kodama et al. 2008 and references therein). For isotope partitioning studies, the value of ecosystem-respired CO2 is typically measured at night, and then used to partition respiratory processes of the light period (for a specific discussion on this topic, see Zobitz et al. 2008). However, such an assumption does not seem consistent with published data of isotopic biochemistry of plants (see also Cernusak et al. 2009 for a review). Firstly, a positive relationship has been observed between the carbohydrate content and the respiration rate in many plant organs (see, e.g. Azcon Bieto & Osmond 1983; Tjoelker et al. 2008). In leaves, the availability of respiratory substrates has a clear impact on the δ13C value of dark-evolved CO2 (Tcherkez et al. 2003; Hymus et al. 2005; Gessler et al. 2009). For organs other than leaves, where circadian rhythms occur in sucrose content, there may be different δ13C values in respiratory CO2 in the light and in the dark. Secondly, sucrose molecules produced in the dark (from 13C-enriched, transitory starch) and in the light (from 13C-depleted, cytoplasmic triose phosphates) do not have the same isotope composition (Tcherkez et al. 2004; Gessler et al. 2008). This may drive a light/dark cycle of the δ13C value of CO2 evolved by source or sink organs depending on whether respiration is dominated by autotrophic or heterotrophic processes in those tissues. Thirdly, while some organs such as roots do not have any apparent growth circadian rhythm, others have (leaves and secondary meristems in stems) (Zweifel, Item & Hasler 2001; Walter & Schurr 2005; Deslauriers et al. 2007). Owing to the tight relationship between respiration and plant growth (for a review, see Amthor 2000), light/dark growth variations may have an effect on the δ13C of evolved CO2.
In the present paper, the isotopic signal of day-respired CO2 was determined (13C enrichment or depletion compared to net fixed CO2) as compared to dark-evolved CO2. We carried out mesocosm-level experiments with sunflower (Helianthus annuus) canopies, in which both the day and dark isotopic signals associated with respiration were investigated and compared with CO2 evolved by individual organs. For this purpose, we propose two techniques to measure the isotopic impact of CO2 evolved in the light. Furthermore, a 12C/13C labelling was conducted in order to see metabolic correlations between day-respired CO2, dark-respired CO2 and different plant components.
- Top of page
- Supporting Information
Plant material and growth conditions
Sunflower (H. annuus L. cv. Sanluca) plants were sown individually in plastic pots (5 cm diameter – 35 depth) filled with washed quartz sand. The pots were distributed at a density of 118 plants m−2 in two growth chambers (E15, Conviron, Winnipeg, Canada). Modified Hoagland nutrient solution (7.5 mol N m−3) was supplied by an automatic irrigation system throughout the experiment. Irradiance during the 16 h photoperiod was supplied by cool white fluorescent tubes (16 × 160 W; Sylvania Germany GmbH, Erlangen, Germany) and incandescent lamps (12 × 100 W; General Electric Germany, München, Germany), and was maintained at 520 µmol m−2 s−1 photosynthetic photon flux density (PPFD) at the top of the canopy by adjusting the height of the lamps following plant development. Air temperature was controlled at 20/16 °C and relative humidity at 75/80% during the photo and dark periods, respectively. The CO2 mole fraction of the air in the chamber was 200 and 1000 µmol mol−1 (chambers 1 and 2, respectively; for details on gas mixing and controlling, see next paragraph).
Gas exchange measurements and isotope analysis
Mesocosm level. The two growth chambers formed part of the mesocosm 13CO2/12CO2 open gas exchange system described in detail by Schnyder et al. (2003). A screw compressor (S40, Boge, Bielefeld, Germany) and adsorption dryer (KEN3100, Zander, Essen, Germany) generated CO2-free, dry air. Each chamber had an individual gas-mixing system comprising two computer-operated mass flow controllers (FC-2925V for air and FC-2900 4S for CO2, Tylan General, San Diego, CA, USA) mixing dry air with CO2 of known isotopic composition (δ13C). The CO2 concentrations were held constant at the chamber outlets by adjusting the rate and CO2 concentration of the air supplied to the increasing rates of photosynthesis. For each CO2 concentration, the chambers were first supplied with CO2 coming from a mineral source (13C enriched, δ13C −3.5‰) (pre-labelling period) and then originating from a fossil organic source (13C depleted, δ13C −44.5‰; both CO2 from Linde AG, Munich, Germany) (labelling).
For measurements of CO2 fluxes and associated on-line 12C/13C discrimination of the canopies, sample air was collected at the inlet and outlet (vent) of each growth chamber, and continuously pumped to a computer-controlled sample air selector (SAS) at a rate of approx. 2 L min−1. During simultaneous operation of all chambers, the SAS sequentially sampled each sample air line (n = 8) at 2 min intervals. Sample air was split to serve the infrared gas analyser (IRGA; Li-6262; Li-Cor Inc., Lincoln, NE, USA) and isotope ratio mass spectrometer (IRMS; Delta Plus, Finnigan MAT, Bremen, Germany) in parallel. Gas lines between the SAS, IRMS and IRGA were flushed with sample air for 2 min before taking IRGA readings of absolute CO2 and H2O concentration and measurement of δ13C of CO2 by IRMS. The IRMS was interfaced with the SAS via a steel capillary tube (i.d. 0.1 mm), a six-port, two-position valve (Valco Instruments Co. Inc., Houston, TX, USA), dryer (Nafion), gas chromatograph (25 m × 0.32 mm Poraplot Q; Chrompack, Middelburg, the Netherlands) and open split. These components all formed part of a custom-made interface (GC–GP Interface; Finnigan MAT). Sample air was pumped continuously through the steel capillary feeding the Valco valve and a 300 µL sample loop attached to it. After a 2 min flushing period, shortly before the SAS switched to the next sample air line, the content of the sample loop was swept with helium carrier gas through the interface, where water vapour was removed by the Nafion membrane, and CO2 was separated from all other gaseous components of the air sample in the GC column. Finally, the CO2 was introduced directly into the ion source of the IRMS via the open split. Samples were compared with a V-PDB-gauged, working standard reference CO2 injected once at the start and once at the end of a measurement cycle. The overall precision of the measurement at the chamber inlets over a 24 h period was typically better than 0.15‰. A full measurement cycle, including one set of measurements (concentrations of CO2 and H2O, and δ13C of CO2) on the inlet and outlet of each growth chamber, was completed within 24 min.
The net CO2 exchange flux of the canopies (N, µmol CO2 m−2 s−1) was obtained as the balance of CO2 entering and leaving the chamber divided by the chamber ground area (s, m2):
with E and O the fluxes of CO2 (µmol s−1) entering and leaving the chamber. The difference E – O is denoted as P below ('Calculations' in Materials and methods). In the light, N is the net assimilation value at the mesocosm level, and as such, it is denoted as A (net assimilation) in the following. In the dark, N is the negative of the mesocosm-level respiration rate.
Mesocosm-scale 'on-line'12C/13C discrimination (denoted as Δ) during photosynthesis (i.e. gas exchange in light) was obtained as given by Evans et al. (1986):
where ξ = ce/(ce − co), and ce and co are the CO2 mole fractions (µmol mol−1) of the air entering and leaving the chamber after correcting to standard humidity.
While N could be measured continuously from the first day of the experiment, the associated isotope analyses could be done with reasonable precision only after day 12, when rates of photosynthesis were high enough to yield significant differences in the C-isotopic composition of the CO2 entering and leaving the chambers. The δ13C of dark-respired CO2 was measured at days 30–34, that is, when canopies were closed (plants at the three fully expanded leaves stage) and CO2 exchange rates had reached a steady state on a day-to-day basis. At days 35 and 36, CO2 response curves of canopies were carried out by changing the CO2 concentration at the chamber inlet gradually from 100 to 1500 µmol mol−1 within 2 h. Again, measurements of net CO2 exchange fluxes were accompanied by the simultaneous determination of Δ. The corresponding results of the A/ca curve are shown in the Supporting Information Fig. S1. At day 37 after the start of the experiment, canopies were isotopically labelled by switching the source CO2 from mineral (−3.5‰) to fossil organic (−44.5‰) CO2. Gas exchange analyses continued for 5 more days with labelling CO2 and otherwise unchanged growth conditions.
Organ level. One plant was removed from the growth chambers described above, and the attached organs were placed in a closed system for the on-line measurement of the δ13C of the respired CO2. The closed system which was described previously by Tcherkez et al. (2003) was directly coupled to the IRMS (Finnigan) as specified above. The procedure for accumulating respired CO2 in the dark and measure the isotope composition was identical. All experiments were carried out on the top expanding (EL) and mature (ML) leaves, and in the adjacent stem (ST). The contribution to the mesocosm exchange of the two cotyledons was considered negligible as they had died at the time the measurements were done. The photosynthetic fractionation at the leaf level was measured following the procedure of Nogués et al. (2004) and Tcherkez et al. (2005), that is, by coupling the portable gas exchange system (TPS-2, PP systems) to the IRMS through a three-way valve.
Metabolite extraction and quantification. Plants were harvested and the different organs were frozen in liquid nitrogen, lyophilized and analysed as follows. The extraction–purification procedure for starch, sucrose, glucose and fructose was that described previously (Tcherkez et al. 2003). Purified metabolites were lyophilized, resuspended in 100 µL of distilled water and then transferred to tin capsules (Courtage Analyze Service, Mont-Saint-Aignan, France) and dried for isotope analysis. The isotope analysis of metabolites and total organic matter was carried out with the EA-IRMS (EA1500; Carlo-Erba, Milan, Italy, coupled to the Optima, GV Instruments (Villeurbanne, France) on the isotopic facility structure Plateforme Métabolisme-Métabolome, as already described (Tcherkez et al. 2003; Nogués et al. 2004).
In the following, simple relationships are used to derive the isotopic signature of respired CO2 in the light. Firstly, the mesocosm system was considered as a big assimilation cuvette, and equations derived from gas exchange are used to calculate an estimate of the contribution (thereafter denoted as d*/ca) of day mesocosm-respired CO2 to net photosynthetic fractionation of the mesocosm. Secondly, the contribution of non-photosynthetic organs to the net photosynthetic fractionation of the mesocosm was estimated by taking advantage of the net photosynthetic fractionation of leaves that was measured separately. That is, the respiratory isotopic signal of non-photosynthetic organs (thereafter denoted as , see the definition of symbols in Table 1 and just below) was determined by 'substracting' the effect of leaf net photosynthesis from the mesocosm-level photosynthetic fractionation. Thirdly, the respiratory isotopic signal of non-photosynthetic organs was followed after isotopic CO2 labelling to calculate the proportion (denoted as xday) of old, pre-labelling carbon to CO2 production in the light.
|Expression or symbol used (units)
|Isotope fractionation associated with net photosynthesis (CO2 exchange) of the mesocosm
|Average isotope fractionation associated with net photosynthesis (CO2 exchange) of leaves
|Isotope fractionation associated with mesocosm-level net photosynthetic assimilation, when net photosynthesis tends to zero
|e (‰)
|Isotope fractionation associated with leaf day respiration
|f (‰)
|Isotope fractionation associated with CO2 evolution by photorespiration at the leaf level
|enp (‰)
|Isotope fractionation associated with respiration of non-photosynthetic organs in the light at the mesocosm level
|eapp (‰)
|Apparent isotope fractionation associated with respiration of non-photosynthetic organs in the light after isotopic labelling at the mesocosm level
|N (µmol m−2 s−1)
|Net mesocosm CO2 exchange
|P (µmol s−1)
|Net mesocosm CO2 exchange (not scaled to surface area)
|xday (dl.)
|Proportion of recent carbon in CO2 respired by non-photosynthetic organs in the light at the mesocosm level
|xnight (dl.)
|Proportion of recent carbon in CO2 respired by the mesocosm in darkness at the mesocosm level
|d*/ca (‰)
|(Photo)respiratory isotopic contribution to the photosynthetic fractionation at the mesocosm level (Eqn 2)
|Respiratory isotopic contribution of non-photosynthetic organs to the photosynthetic fractionation at the mesocosm level (Eqn 3)
|en (‰)
|Isotope fractionation of night respiration by the mesocosm (Eqn 7)
The main parameters used throughout the present paper and explained below are summarized in Table 1. The expression '(photo)respiratory' CO2 used in the following stands for the sum of photorespiratory and day respiratory evolved CO2.
The isotopic (photo)respiratory component of Δ at the mesocosm level
The (photo)respiratory component of the net photosynthetic carbon isotope discrimination Δ (i.e. the (photo)respiratory term in Farquhar's expression giving Δ; see Eqn 1) was calculated using equations derived from Evans et al. (1986) as explained below. The present methods were developed to avoid the need of ci, the internal CO2 mole fraction, because this parameter could not be reached at the mesocosm level in the present study. The (photo)respiratory component is denoted here as d* as follows (Farquhar et al. 1982):
- (1)
where Δ is the net photosynthetic (observed) carbon isotope discrimination, and a, ai and b are the fractionations associated with diffusion in air, dissolution and diffusion in water, and carboxylation, respectively. ca, ci and cc are the CO2 mole fractions in the atmosphere, in the intercellular spaces and at the carboxylation sites, respectively. d* is equal to where e and f are the carbon isotope fractionation associated with day respiration (the rate of which is Rd) and photorespiration. Γ* is the CO2 compensation point in the absence of day respiration, and k is the carboxylation efficiency.
In both methods used below, it is assumed that d* is constant with respect to ca. This hypothesis may not be verified when ca varies because k depends upon CO2 mole fraction. Here, we used the region of low assimilation values in which the relative change of k is rather small, so that the assumption of a constant d* is valid.
We also recognize that the value of d* obtained here includes both leaf day respiration and heterotrophic respiration (from roots and stems), and so is not strictly equal to that used in the equation of Farquhar et al. (1982) (Eqn 1). That is, the day respiratory component eRd/kca applies at the level of cc (i.e. day-respired CO2 is released into the intracellular CO2 pool), while CO2 evolved by heterotrophic organs is not released at cc but rather into surrouding air (at ca). Nevertheless, Eqn 1 is not altered. Let us denote as δh the carbon isotope composition of CO2 evolved by non-photosynthetic organs, and ε the CO2 amount (in µmol mol−1) produced by respiration of non-photosynthetic organs. ΔA is the net photosynthetic fractionation of photosynthetic organs (leaves). By mass balance, we have:
This re-arranges to:
where Δobs is the observed discrimination at the mesocosm level (including both leaves and heterotrophic organs), using the equation of Evans et al. (1986), as indicated above. Within the numerator, the term δhΔA may be neglected, giving δo − ΔA − δh, which is very close to the isotope fractionation associated with respiration of heterotrophic organs, with respect to carbon fixed by leaves. Let us denote this fractionation as eh. The denominator is very close to ce − co, and the ratio ε/(ce − co) is equal to Rh/A, where Rh denotes respiration by heterotrophic organs, and A is net mesocosm photosynthesis. This gives:
In other words, the apparent value of d* obtained from Δobs (as explained below) here includes an additional term that represents heterotrophic respiration. That is,
The heterotrophic term ehRhca/A, and the leaf term eRd/k are very similar because the carboxylation efficiency k is defined as vc/cc, where vc is the carboxylation rate and cc is internal CO2 mole fraction. Therefore, the input of heterotrophic respiration to mesocosm CO2 at the level of ca does not modify the general equations described here, and the d* value computed below simply includes heteretrophic respiration in the light. It should be noted that similarly, there would also be a contribution of heterotrophic respiration to the apparent d* value at the leaf level because of the contribution of non-photosynthetic leaf cells such as phloem tissue, epidermis, etc. In other words, the present equations may also apply to leaf-level gas exchange experiments, even though the heterotrophic term ehRhca/A is quantitatively modest in most leaves.
First method. We used the following relationships: A = gs (ca − ci) = gm (ci − cc), where A is CO2 net assimilation, and gs and gm are the stomatal and internal conductance for CO2, respectively. Subtracting b from each side of Eqn 1, and re-arranging gives:
- (2)
In the following, we denote the left-hand side of Eqn 2 by 〈Δ〉. In the present study, experiments involved A/ca curves, that is, variation of the CO2 level (Supporting Information Fig. S1). Importantly, the use of Eqn 2 does not require ca to be constant as d* is assumed ca independent, and we used the intercept (and not the slope). When plotted against A, 〈Δ〉 shows a non-linear relationship, simply because both conductances vary with A. Stomatal conductance typically decreases at high CO2, and so the slope of the 〈Δ〉-versus-A relationship increases with A. Similarly, it has been recently shown that internal conductance responds to changes in ca (Flexas et al. 2007). Nevertheless, when A converges to zero, 〈Δ〉 converges to d*. In other words, with a set of Δ, ca and A values, extrapolating 〈Δ〉 at A = 0 gives a value of d*. This graphical method is depicted in Fig. 1, in which the linear regression used data with A less than 17 µmol m−2 s−1 (linear region of the plot).
Second method. Equation 2 is still valid at the CO2 compensation point, Γ, at which A = 0. This simply gives:
- (3)
where Δ0 is the net photosynthetic carbon isotope discrimination for A = 0. Clearly, such a value cannot be measured (no net CO2 exchange) and should be extrapolated with a plot representing Δ against A. This method is depicted in the inset of Fig. 1.
The respiratory contribution of non-photosynthetic organs to mesocosm-level isotopic gas exchange in the light
The respiratory component of isotopic exchange between the mesocosm and the atmosphere was calculated using classical mass balance equations and taking advantage of the photosynthetic carbon isotope fractionation measured at the leaf level and applied to the photosynthetizing leaves of the mesocosm. We used the following iso-flux conservation equation at the level of the mesocosm:
- (4)
where qA and qr are the total mass of leaves and non-photosynthetic organs (roots and stems), respectively; u is the air flow rate through the mesocosm chamber (in mol s−1); co and ce are the outlet and inlet CO2 mole fractions (in µmol mol−1) corrected to standard humidity, with the associated δ13C values δo and δe, respectively. is the average net photosynthetic rate (in µmol g−1 s−1) of leaves. and are the mass average respiratory rate and the respiration average isotopic composition of CO2 respired by non-photosynthetic organs, respectively. is the isotope composition of net fixed carbon in leaves.
If we denote as P the net CO2 exchange by the mesocosm (in µmol s−1) in the light, we have: . Equation 4 may then be rewritten using P, which is the parameter measured by the mesocosm system. This gives:
With the proxies where is the average leaf net photosynthetic fractionation, and where enp is the respiratory fractionation by non-photosynthetic organs, we have:
- (5)
It is not possible to separate the three variables in the left term of Eqn 5; it represents the non-photosynthetic respiratory contribution to the mesocosm-level fractionation. However, such a value is in ‰µmol s−1, which is not consistent with d*/ca value (see above), that is, the (photo)respiratory contribution to the mesocosm-level fractionation (in ‰). At the mesocosm level, we used here , which is a scaled contribution of respiratory isotopic signal, and is in ‰. This may be calculated by dividing all the terms of Eqn 5 by P. It should be emphasized that the use of Eqn 5 does not require any assumption on the carbon isotope composition of CO2 evolved by respiration in the light. Other authors suppose a similar value in the light and in the dark. Nevertheless, this assumption is unlikely, simply because of the contribution of photosynthetizing organs to night respiration, and such organs have proven to be isotopically different (lighter) than other organs. It should be noted that the value computed with Eqn 5 is relative because it depends upon the leaf photosynthetic fractionation : any slight variation of this parameter at the mesocosm scale as compared to the leaf-level measurement causes variations in . In practice, we used the average of pre-labelling values (mature leaves). Any error in only induces an offset in and does not impact on the percentage of new carbon (see below Eqn 6) and the covariation analysis (Fig. 4).
The contribution of recent photosynthates to respiration of non-photosynthetic organs in the light
The term of Eqn 5 is expected to vary after CO2 labelling. For example, if the labelling CO2 is 13C depleted, the CO2 produced by respiration is expected to be strongly 13C enriched relative to fixed CO2 because of the lag phase needed to renew respiratory pools. In other words, the use of 'old', 13C-enriched carbon by respiration will artificially lead to a large negative term (this is illustrated in Fig. 3). That is, enp is artificially decreased by the decarboxylation of old, 13C-enriched carbon. In the following, we then denote it as eapp and use enp for the intrinsic respiratory fractionation (which is independent of the 13C abundance of the C source).
We may use the apparent value to calculate the proportion of 'old' and recent carbon in CO2 evolved by non-photosynthetic organs in the light. The proportion of recent carbon in CO2 is denoted as xday in the following. The isotope composition of respired CO2 coming from 'old' carbon is approx. where, again, enp is here the 'intrinsic', δ13C-independent, respiratory fractionation, while that of new carbon is approx. where δo′ is the new (labelled) isotope composition of outlet air. The resulting isotope composition of respiratory CO2 is then:
that simply re-arranges to: , that is,
in the light cannot be calculated nor measured. We take advantage here of the definitions (see the above section):
where the symbol 'prime' indicates values obtained after labelling. As and is assumed constant before and after labeling, we have:
In order to get an estimate of xday, we may multiply its numerator and denominator by , giving:
- (6)
xday is then calculated using the value calculated with Eqn 5 before and after (symbol 'prime') labelling, and the value of measured at night, when only respiration occurs (it is equal to –P measured at night). Such a value of is somewhat overestimated because photosynthetic organs respire at night; hence, the xday value obtained with Eqn 6 is slightly overestimated.
The contribution of recent photosynthates to mesocosm respiration in darkness
The carbon isotope composition of CO2 respired by the whole mesocosm (photosynthetic and non-photosynthetic organs) in darkness is denoted as δn. The isotope fractionation associated with night respiration of the mesocosm, with respect to CO2 fixed in the previous light period is then:
- (7)
where is the isotope composition of mesocosm-level net fixed carbon, and Δ is the mesocosm-level net photosynthetic fractionation. The subscript 'n' is used here to distinguish the respiratory isotope fractionation in darkness from that in the light (denoted as e; see above).
After labelling, the proportion of recent carbon in evolved CO2 in darkness may be calculated. Such a proportion is denoted as xnight below, and is given by (Schnyder 1992; Schnyder et al. 2003; Nogués et al. 2004):
- (8)
where the superscripts 'after' and 'before' refer to after and before labelling, respectively.
Covariation analyses
The covariation analysis was done following the isotopomic array representation of Tcherkez, Ghashghaie & Griffiths (2007). In the present study, the isotope composition of the different plant fractions (starch, sucrose, etc.) and respired CO2 was recalculated to isotope ratios times 100. The intensity of the red or green colour represents the strength of the natural 13C enrichment or depletion, respectively. Both the drawing of the array and the clustering analysis were done with the MeV 4.1 software (Saeed et al. 2003). The clustering of Fig. 4 is based on the cosine correlation method. The results are similar to other correlation methods, such as the Euclidean distance. To introduce mesocosm day-respired CO2 into the correlation analysis, the estimated isotope composition (δ13C) of day-respired CO2 was calculated with the values of obtained with Eqn 5, as follows: , where δo is the isotope composition of mesocosm outlet air, and Δ is the mesocosm-level net photosynthetic fractionation (measured on-line). It should be noted that in Fig. 2, eapp is negative (favours 13C) because of the breakdown of 'old', 13C-enriched photosynthates. In other words, after the start of labelling, day-respired CO2 is enriched compared to fixed CO2.
- Top of page
- Supporting Information
Day-respired CO2
The isotopic contribution of (photo)respiration to the net photosynthetic carbon isotope fractionation, usually written as , is here abbreviated as d*/ca. At the mesocosm level, this term correponds to both leaf (photo) respired CO2 and CO2 evolved by other non-photosynthetic organs. It may be calculated using the intercept of the response curve of 〈Δ〉 = ca(b − Δ) to net assimilation A (Eqn 2). Such response curves are shown in Fig. 1. Both chambers showed a linear relationship for low values of A. For chamber 2 (high CO2 growth conditions), the 〈Δ〉 value did not increase linearly at higher A values, and the slope increased at lower stomatal conductances (Eqn 2). Accordingly, the plot of Δ versus A shows indeed that the carbon isotope discrimination decreased slightly at high A values, indicating a lower ci/ca (Fig. 1, inset). Otherwise, stomatal aperture increased slowly with A as evidenced by the general positive trend between Δ and A (Fig. 1, inset).
The isotopic contribution of (photo)respiration at both the leaf and mesocosm scale was then calculated with the data of Fig. 1; the results are shown in Table 2. Equations 2 and 3 gave very similar results. When expressed on the same scale (at near-ambient CO2 mole fraction, i.e. 400 µmol mol−1 as ca), the isotopic contribution was larger under high than low CO2, while both being in the range 1–3‰. The relative effect was higher when growth CO2 mole fraction was used to compute d*/ca (2–3‰ versus 1‰ at 200 and 1000 µmol mol−1, respectively). However, the d*/ca value included the photorespiration effect that was different at 200 and 1000 µmol mol−1 CO2. With typical values of fΓ* (f = 11‰, Tcherkez 2006; Lanigan et al. 2008; Γ* ∼ 40 µmol mol−1, Brooks & Farquhar 1985), the contribution of respiration (Eqn 1) was very similar in both chambers, roughly around 0.5 ± 0.3‰ regardless of growth CO2 mole fraction (Table 2).
|With b = 29‰
|Chamber 1 (ca = 200 µmol mol−1)
|Eqn 2 and Fig. 1
|0.82 (−0.06, −0.2)
|Eqn 3 and Fig. 1, inset
|0.81 (−0.06, −0.2)
|Chamber 2 (ca = 1000 µmol mol−1)
|Eqn 2 and Fig. 1
|0.76 (−0.01, −0.04)
|Eqn 3 and Fig. 1, inset
|0.63 (−0.01, −0.04)
|With b = 27‰
|Chamber 1 (ca = 200 µmol mol−1)
|Eqn 2 and Fig. 1
|0.68 (−0.06, −0.2)
|Eqn 3 and Fig. 1, inset
|0.21 (−0.06, −0.2)
|Chamber 2 (ca = 1000 µmol mol−1)
|Eqn 2 and Fig. 1
|0.75 (−0.01, −0.04)
|Eqn 3 and Fig. 1, inset
|0.47 (−0.01, −0.04)
Because ca was larger in chamber 2, the similar value probably came from a higher Rday value. In fact, respiration rates in the dark were more than 80% higher at 1000 µmol mol−1 CO2 (6.3 µmol m−2 s−1 compared to 3.4 µmol m−2 s−1 at 200 µmol mol−1 CO2). This arose from both a higher specific respiration rate (6.8 versus 5.4 nmol g−1 DW s−1) and higher plant biomass (5.6 versus 3.9 g DW per plant) at 1000 compared to 200 µmol mol−1 CO2. Still, both d* values were (slightly) positive, showing that evolved CO2 was 13C depleted in the light (e > 0) with an average value within the 0.6–0.8‰ range (Table 2, right column). These results are clearly sensitive to the 12C/13C fractionation associated with carboxylation (b value: see Eqns 2 & 3). While it is currently believed that b = 29‰, we also calculated the d* with b = 27‰ (Table 2, lower): the value was then lower, but fractionation against 13C remained positive, within the 0.2–0.7‰ range.
Night-respired CO2
The night respiration rate at the mesocosm level (Nvalue in the dark, see Materials and methods) was 3.4 and 6.3 µmol m−2 s−1 in chambers 1 (200 µmol mol−1 CO2) and 2 (1000 µmol mol−1 CO2), respectively. The carbon isotope composition of CO2 within the mesocosm or evolved by individual organs in darkness was measured, and the results are shown in Table 3, where the δ13C values are also expressed as apparent fractionations with respect to net fixed CO2 (between parentheses). At the mesocosm level, night-respired CO2 was slightly 13C enriched, so was leaf-respired CO2, while roots produced 13C-depleted CO2, and stem respiration did not seem associated with an apparent fractionation. Such a pattern was very similar in both chambers. While there are not enough data to close the isotopic mass balance in our study, it is likely that 13C-enriched, dark-respired CO2 of the mesocosm was dominated by leaf respiration, which was the only 13C-enriched signal (Table 3).
|δ13C of respired CO2 in darkness (‰)
|Mature leaves
|Young leaves
|Chamber 1 (ca = 200 µmol mol−1):
|−19.6 ± 2.1
|−26.6 ± 2.0
|−23.0 ± 0.2
|−13.8 ± 1.0
|−15.7 ± 1.0
|Chamber 2 (ca = 1000 µmol mol−1):
|−24.4 ± 2.1
|−28.5 ± 1.0
|−26.1 ± 0.6
|−19.0 ± 1.2
|−20.5 ± 1.0
Day-respired CO2 after labelling
The isotopic gas exchange of the mesocosm was followed during a labelling experiment that used 13C-depleted CO2 (−44.5‰) while maintaining the CO2 mole fraction (200 and 1000 µmol mol−1). The isotopic contribution of respiration of non-photosynthetic organs to the isotopic CO2 exchange in the light (denoted as , Table 1) was calculated using the 'deviation' from the expected Δ (Eqn 5). The results are shown in Fig. 2 in which, for convenience, (positive value) was represented. All the values are associated with a large standard error, simply because very slight variations in P (the net mesocosm gas exchange, in µmol s−1) or propagate into large uncertainties in . In other words, it is not possible to compare directly the initial value at day 0 and the isotopic contribution d*/ca computed above (see also Materials and methods).
That said, it is apparent that CO2 evolved in the light was 13C enriched, that is, respiration used carbon atoms that were fixed before labelling. The minimal proportion of 'new' carbon in day-respired CO2 was calculated (Eqn 6; Fig. 2, inset). Both chambers behaved similarly with a progressive turnover of day-respired CO2 which reached a maximum near 40% (chamber 2, at 1000 µmol mol−1) and 60% (chamber 1, at 200 µmol mol−1). That is, mesocosm respiration was fed by: (1) current photosynthates via a pool that had a half-life time of several hours (accounting for 40–60% of total respiration); and (2) stored carbon with a half-life time in the order of several days (accounting, respectively, for the remaining 40–60% of total respiration).
The comparison of day- and night-respired CO2 by the mesocosm
The δ13C value of CO2 evolved by the mesocosm in the dark was also measured after labelling. As night-respired CO2 is intrinsically 13C enriched (see above and Table 3) while day-respired CO2 was intrinsically 13C depleted (see above and Table 2), it is more convenient to compare the proportions of 'new' carbon in respired CO2 (Eqns 6 & 8) instead of δ13C values. Such a representation is shown in Fig. 3. While being somewhat noisy, day- and night-respired CO2 followed similar carbon sources (close to the 1:1 line). This agrees with the covariation analysis carried out with the whole set of δ13C values in CO2 and metabolites, as shown in Fig. 4. When represented as an isotopomic array, it appears that the closest relative of day-respired CO2 (for the mesocosm) was night-respired CO2 of both the mesocosm and individual organs (Fig. 4, bottom). Within the same cluster (Fig. 4, left), the second-order relative of respired CO2 was stem and leaf sucrose, suggesting that, unsurprisingly, sucrose was a major source of carbon for respiration. Fructose, glucose, starch and organic matter belong to a different cluster.
- Top of page
- Supporting Information
While there is currently a growing literature on the carbon isotope composition of CO2 evolved in the dark by either leaves, roots or ecosystems, less is known on the isotope composition of day-respired CO2 (Ghashghaie et al. 2003; Bowling et al. 2008). This lack of knowledge stems from the technical difficulties associated with the measurement of the pure, respiratory isotopic signal. Such difficulties are independent of the scale of interest (leaf to ecosystem). Disentangling the (photo)respiratory contribution to the net isotopic fractionation usually requires assumptions on either its magnitude or associated fractionation. Here, we manipulated both the atmospheric CO2 mole fraction (two growth conditions) and the isotope composition of inlet CO2 (labelling), and took advantage of the mesocosm gas exchange facility (Schnyder et al. 2003). We used new simple equations (Materials and methods; Table 1) and Δ versus A curves to gain information of the carbon isotope composition of respiratory CO2 evolved in the light, without prerequisite assumptions.
Is day-respired CO213C depleted or 13C enriched?
When plotted against A, the ca(b − Δ) intercept directly gave the d* value. Scaled to atmospheric CO2 mole fraction of interest (d*/ca), this gave the (photo)respiratory component of mesocosm photosynthetic fractionation (Eqn 2; Fig. 1). Our results show that day-(photo)respired CO2 was 13C depleted as compared to net fixed CO2, and this difference depended on growth CO2 conditions (Table 2). However, the contribution of photorespiration was dissimilar under different CO2 conditions, and the estimated pure respiratory signal was close to +0.7‰ in both chambers (Table 2, with b = 29‰), that is, day-respired CO2 was slightly 13C depleted. We, nevertheless, recognize that such a value depended upon the chosen values of f (photorespiratory fractionation) and Γ*, that is, they were assumed to be independent of growth CO2 mole fraction. Both assumption are nevertheless reasonable (Thomas et al. 1993; Lanigan et al. 2008), and our sensitivity analysis shows that variations in Γ* and f variations have little effect on the pure respiratory signal (Table 2). It may be argued that day-respired CO2 is 13C enriched at the leaf level, as shown by isotopic analyses of CO2 evolved from darkened leaves during the light period (see, e.g. Hymus et al. 2005). It is believed that such a 13C enrichment comes from the metabolism associated with light-enhanced dark respiration (Barbour et al. 2007; Gessler et al. 2009). In addition, our value (depletion by 0.7‰) agrees with the data from previous investigations: in Senecio, Ghashghaie et al. (2003) found an intercept (Δ versus A/ca curve) of around 1.5‰, which corresponds to a pure respiratory component of +0.31‰, with their values of f = 11‰ and Γ* = 39 µmol mol−1. This is also in agreement with the theoretical study of Tcherkez et al. (2004), in which the commitment of 13C-depleted triose phosphates to mitochondrial respiration in the light led to 13C-depleted CO2. That said, measurements under 2% O2 (non-photorespiratory conditions) gave an intercept of about 1‰, and such a value indicates a much larger respiratory component (Ghashghaie et al. 2003) than the value of 0.31‰ quoted above. In fact, there is now a body of evidence that day respiratory metabolism is affected by the photorespiration rate (Tcherkez et al. 2008 and for a review see Noguchi and Yoshida 2007) and likely therefore, so is the isotopic contribution of evolved CO2 to net photosynthetic fractionation.
The similar values of 0.3–0.8‰ associated with the respiratory contribution to photosynthetic fractionation at both the leaf and mesocosm level show that presumably, CO2 evolved by leaves and non-photosynthetic organs was isotopically similar. With typical mesocosm values of Rday = 3 µmol m−2 s−1 and k = 0.1 mol m−2 s−1, the respiratory fractionation (usually denoted as e) is then about 5 ± 1‰ at the leaf level under a CO2 mole fraction of 400 µmol mol−1. This value agrees with the theoretical estimation of Tcherkez et al. (2004) (see also the discussion below).
Such a pattern is in clear contrast with night-respired CO2 which is 13C enriched by several per mil in leaves (Ghashghaie et al. 2003 and references therein, and Table 3) and ca. 0.6‰ (Schnyder et al. 2003) to 3‰ (Table 3) in the mesocosm. At the forest level, night-time respired CO2 appears slightly 13C enriched compared to photosynthates with, however, considerable variations (Bowling, Baldocchi & Monson 1999; Cai et al. 2008). Under our conditions, the 13C enrichment of mesocosm dark-evolved CO2 came from leaves that were indeed the sole organs to produce 13C-enriched CO2. As such, leaves probably dominated the CO2 production in the night in the present study. This scenario agrees with another study on sunflower (Klumpp et al. 2005) in which night-time-respired CO2 was 13C enriched in shoots and 13C depleted in roots, suggesting that the slight 13C enrichment of night-respired CO2 at the stand scale originated from shoots.
The day/night oscillation of the isotopic composition of CO2 respired by the mesocosm may come from: (1) the decrease of the contribution of leaves because of the inhibition of leaf respiration by light (Atkin et al. 2000); (2) the decarboxylation of 13C-enriched malate in the dark in leaves (Gessler et al. 2009); (3) the change of respiratory carbon source (13C-enriched starch at night and 13C-depleted sucrose in the light) (Gessler et al. 2008); and (4) a change of metabolic pathways or commitments so that 12C/13C fractionations of respiratory enzymes vary. While assumptions (1) and (2) are likely and supported by experimental results, assumptions (3) and (4) are not demonstrated yet and are addressed below.
Are day- and night-respired CO2 correlated?
We used here isotopic labelling to make the respiratory isotopic signal to vary: the inlet CO2 source to the mesocosm was changed from −3.5‰ to −44.5‰. The day respiratory contribution to the photosynthetic fractionation was then calculated with Eqn 3. It should be emphasized that such a value included the production of respired CO2 by non-photosynthetic organs, as we use the net photosynthetic fractionation of leaves in Eqn 3. Unsurprisingly, the respiratory component was associated with 13C-enriched CO2 (Fig. 2), clearly showing the contribution of 13C-enriched, old carbon sources to day respiration. The calculated proportion of 'new' carbon was indeed 40–60% (Fig. 2, inset). Similar values have already been obtained at both the leaf (Nogués et al. 2004), plant (Lehmeier et al. 2008), mesocosm (Schnyder et al. 2003) and ecosystem scale (Gamnitzer, Schäufele & Schnyder 2009) in the dark. Our data show that: (1) day- and night-respired CO2 had a very similar turnover pattern (Fig. 3); and (2) the covariation analysis indicated that the closest relative of day-respired CO2 was night-respired CO2 (Fig. 4). We therefore conclude that both day and night respiratory substrate pools were likely to be fed by the same carbon source. The latter may comprise several components: the kinetics of CO2 turnover indeed suggest that at least two carbon sources provide substrates to respiratory metabolism. It has been argued that one of them arises from carbohydrates because of the respiratory quotient of 1 (Nogués et al. 2004). Our data support this assumption, because the closest relative to evolved CO2 was stem (i.e. mainly phloem) and leaf sucrose (Fig. 4).
While both day- and dark-respired CO2 comprised always a lower proportion of 'new' carbon under high CO2 (chamber 2) than under low CO2 (chamber 1) (Fig. 3), the absolute decarboxylation rate of 'new'carbon was similar under both conditions: it was 60% × 3.4 µmol m−2 s−1 = 2.04 µmol m−2 s−1 at low CO2, and 40% × 6.3 µmol m−2 s−1 = 2.52 µmol m−2 s−1 at high CO2. Therefore, the rate at which recently fixed carbon fed respiration did not vary with CO2 conditions, while the rate of remobilization increased as CO2 (and carbon availability) increased. Consistent with this are observations that when pools of respiratory intermediates (such as citrate) and storage molecules (such as starch) increase under high CO2 conditions at fixed N supply, the specific N content (Bernacchi et al. 2007) and amino acid pools were identical or even smaller (Geiger et al. 1999; Li et al. 2008). Such a metabolic effect tends to impede the turnover of respiratory metabolites, as evidenced here (Fig. 2).
Why is day-respired CO213C depleted?
While assumption (2) above (decarboxylation of 13C-enriched material in the dark) has received strong support in the literature, it is likely that both day- and night-evolved CO2 originate from similar substrates (see just above). In fact, the involvement of the decarboxylation of 13C-enriched malate in leaves has been shown to last less than half an hour (Barbour et al. 2007). Therefore, different metabolic processes probably explain why the natural 13CO2 abundance is dissimilar in the light and in the dark. One of them is the inhibition of leaf respiration that is accompanied by the decrease of both the pyruvate dehydrogenase and TCA cycle activity (Randall et al. 1990; Hanning and Heldt 1993; Tcherkez et al. 2005, 2008, and for a review, see Hurry et al. 2005). These two metabolic steps fractionate against 13C (Melzer and Schmidt 1987; Tcherkez & Farquhar 2005), and the associated isotope effects are expected to increase as the metabolic commitment decreases (O'Leary 1980), thereby depleting evolved CO2 in 13C. By contrast, the δ13C value of CO2 evolved by roots under continuous darkness has been shown to be independent of the carbon source availability (Bathellier et al. 2009). This suggests that the day/night transition does not induce major changes in the root-respired isotopic signal, unless the δ13C of root-imported sucrose (carbon input) varies. Because leaf respiration seemed to be a major component of mesocosm respiration in our study, it is therefore likely that the inhibition of leaf respiration by light contributed to the 13C depletion of mesocosm CO2.
We nevertheless recognize that day/night cycles are accompanied by circadian variations of the 13C abundance in sucrose (Tcherkez et al. 2004; Gessler et al. 2008), with 13C-enriched values at night and 13C-depleted values in the light. Such variations are caused by the 12C/13C isotope effect of aldolases (Gleixner & Schmidt 1997), that catalyse the production of fructose-1,6-bisphosphate from triose phosphates, thereby depleting day sucrose and enriching transitory starch (and night sucrose). Such a circadian variation in sucrose that feeds non-photosynthetic organs is likely to contribute to further deplete mesocosm day-respired CO2 in 13C, because non-photosynthetic organs were taken into account in our estimate of day respiratory fractionation.
Our results indicate that the respiratory isotopic signal is very dynamic and follows day/night variations, which correlate predominantly with leaf-level 13C signals, and this appears to be unaffected by growth CO2 conditions. In that sense, the mesocosm can be considered as a big leaf under our experimental conditions. We, nevertheless, gave little attention to other parameters that may change this pattern (such as temperature, nitrogen availability, etc.) through an effect on the root/shoot ratio, the growth rate and the δ13C value of evolved CO2. In fact, the isotope composition of night-time-respired CO2 is sensitive to temperature, vapour pressure deficit or light level (Cai et al. 2008). In addition, the results can certainly not be extrapolated to natural forest ecosystems because trees comprise woody organs (branches and trunks) that have particular isotopic signals. In natural conditions, CO2 respired by heterotrophic organs of trees is ordinarily 13C enriched (Brandes et al. 2006; Gessler et al. 2007; Maunoury et al. 2007) with noticeable diel variations (Kodama et al. 2008). Such a pattern is in clear contrast to herbaceous plants in which heterotrophic organs produce 13C-depleted CO2 (see references above and the present study). Therefore, further studies are needed to determine whether day-respired CO2 is similarly 13C depleted in natural ecosystems.
On-line carbon isotope discrimination measured at the leaf level is often used to gain information on, for example, mesophyll conductance, and quite frequently, the respiratory contribution to the net photosynthetic carbon isotope fractionation is thought to be negligible (Warren 2006; Flexas et al. 2007). Our results suggest that this very contribution may not be negligible at the mesocosm level (Table 2) particularly when the δ13C value of CO2 used for isotopic measurements strongly differs from that of growth CO2.
- Top of page
- Supporting Information
S.N., C.P., A.B., G.L., C.B. and C.M. acknowledge the financial support of the European Community's Human Potential Program NETCARB through postdoctoral grants. The authors thank Max Hill for high-performance liquid chromatography purification of sugars.
The present work was supported by the European Community's Human Potential Program under contract HPRN-CT-1999-00059, NETCARB, coordinated by Jaleh Ghashghaie.
- Top of page
- Supporting Information
- 2000) The McCree–de Wet-Penning de Vries–Thornley respiration paradigms: 30 years later. Annals of Botany 86, 1–20. (
- 2000) Photosynthesis, carbohydrate metabolism and respiration in leaves of higher plants. In Photosynthesis, Physiology and Metabolism (eds R.C.Leegood, T.D.Sharkey & S.Von Caemmerer) Kluwer Academic Publisher, London, UK. , , & (
- 1983) Relationship between photosynthesis and respiration. Plant Physiology 71, 574–581. & (
- 2005) Post-photosynthetic fractionation of carbon stable isotopes between plant organs – a widespread phenomenon. Rapid Communications in Mass Spectrometry: RCM 19, 1381–1391. , , , & (
- 2007) A new measurement technique reveals rapid post-illumination changes in the carbon isotope composition of leaf-respired CO2. Plant, Cell & Environment 30, 469–482. , , , & (
- 2009) Metabolic origin of the δ13C of respired CO2 in roots of Phaseolus vulgaris. The New Phytologist 181, 387–399. , , , , & (
- 2007) Allometric analysis reveals relatively little variation in nitorgen versus biomass accrual in four plant species exposed to varying light, nutrients, water and CO2. Plant, Cell & Environment 30, 1216–1222. , , & (
- 2007) Isotope fractionation and C-13 enrichment in soil profiles during the decomposition of soil organic matter. Oecologia 153, 89–98. , & (
- 1999) Dynamics of isotopic exchange of carbon dioxide in a Tennessee deciduous forest. Global Biogeochemical Cycles 13, 903–922. , & (
- 2008) Carbon isotopes in terrestrial ecosystem pools and CO2 fluxes. The New Phytologist 178, 24–40. , & (
- 2006) Short-term variation in the isotopic composition of organic matter allocated from the leaves to the stem of Pinus sylvestris: effects of photosynthetic and post-photosynthetic carbon isotope fractionation. Global Change Biology 12, 1922–1939. , , , , , , & (
- 1985) Effect of temperature on the CO2/O2 specificity of ribulose-1,5-bisphosphate carboxylase/oxygenase and the rate of respiration in the light. Planta 165, 397–406. & (
- 2000) Biochemical Models of Leaf Photosynthesis. CSIRO Publishing, Victoria, Australia. (
- 2008) Modelling environmental controls on ecosystem photosynthesis and the carbon isotope composition of ecosystem-respired CO2 in a coastal Douglas-fir forest. Plant, Cell & Environment 31, 435–453. , , & (
- 2009)Why are non-photosynthetic tissues generally 13C-enriched compared to leaves in C3 plants? Review and synthesis of current hypotheses. Functional Plant Biology 36, 199–213. , , , et al. (
- 2003) Carbon isotope composition of current-year shoots from Fagus sylvatica in relation to growth, respiration and use of reserves. Plant, Cell & Environment 26, 207–219. & (
- 2007) Using simple causal modeling to understand how water and temperature affect daily stem radial variation in trees. Tree Physiology 27, 1125–1136. , , & (
- 1999) δ13C of CO2 respired in the dark in relation to δ13C of leaf carbohydrates in Phaseolus vulgaris L. under progressive drought. Plant, Cell & Environment 22, 515–523. , , , & (
- 2001) Natural abundance of C-13 in CO2 respired from forest soils reveals speed of link between tree photosynthesis and root respiration. Oecologia 127, 305–308. & (
- 1986) Carbon isotope discrimination measured concurrently with gas exchange to investigate CO2 diffusion in leaves of higher plants. Australian Journal of Plant Physiology 13, 281–292. , , & (
- 1982) On the relationship between carbon isotope discrimination and the intercellular carbon dioxide concentration in leaves. Australian Journal of Plant Physiology 9, 121–137. , & (
- 2007) Rapid variations of mesophyll conductance in response to changes in CO2 concentration around leaves. Plant, Cell & Environment 30, 1284–1298. , , , , & (
- 2009) Observing 13C labelling kinetics in CO2 respired by a temperate grassland ecosystem. The New Phytologist 184, 376–386. , & (
- 1999) The nitrate and ammonium nitrate supply have a major influence on the response of photosynthesis, carbon metabolism, nitrogen metabolism and growth to elevated carbon dioxide in tobacco. Plant, Cell & Environment 22, 1177–1199. , , , & (
- 2007) δ13C of organic matter transported from the leaves to the roots in Eucalyptus delegatensis: short term variations and relation to respired CO2. Functional Plant Biology 34, 692–706. , , , , , , , & (
- 2008) Diel variations of the carbon isotope composition in leaf, stem and phloem sap organic matter in Ricinus communis. Plant, Cell & Environment 31, 941–953. , , , & (
- 2009) On the metabolic origin of the carbon isotope composition of CO2 evolved from darkened light-acclimated leaves in Ricinus communis. The New Phytologist 181, 385–398. , , , , , & (
- 2001) δ13C of CO2 respired in the dark in relation to leaf metabolites: comparisons between Nicotiana sylvestris and Helianthus annuus under drought. Plant, Cell & Environment 24, 505–515. , , , , & (
- 2003) Carbon isotope fractionation during dark respiration and photorespiration in C3 plants. Phytochemical Reviews 2, 145–161. , , , , , , & (
- 1997) Carbon isotope effects on the fructose-1,6-bisphosphate aldolase reaction, origin for non-statistical 13C distribution in carbohydrates. Journal of Biological Chemisty 272, 5382–5387. & (
- 1993) On the function of mitochondrial metabolism during photosynthesis in spinach (Spinacia oleracea L.) leaves. Plant Physiology 103, 1147–1154. & (
- 2005) Respiration in photosynthetic cells: gas exchange components, interactions with photorespiration and the operation of mitochondria in the light. In Advances in Photosynthesis and Respiration: Respiration and the Environment (eds H.Lambers & M.Ribas-Carbó) Kluwer Academic Publishers, Dordrecht, the Netherlands. , , , , , & (
- 2005) Large daily variation in 13C enrichment of leaf-respired CO2 in two Quercus forest canopies. The New Phytologist 167, 377–384. , , & (
- 2005) C-isotope composition of CO2 respired by shoots and roots: fractionation during dark respiration? Plant, Cell & Environment 28, 241–250. , , , , & (
- 2008)Temporal dynamics of the carbon isotope composition in a Pinus sylvestris stand: from newly assimilated organic carbon to respired carbon dioxide. Oecologia 156, 737–750. , , , et al. (
- 2008) Carbon isotope fractionation during photorespiration and carboxylation in Senecio. Plant Physiology 148, 2013–2020. , , & (
- 1997) Comparing nocturnal eddy covariance measurements to estimates of ecosystem respiration made by scaling chamber measurements at six coniferous boreal sites. Journal of Geophysical Research – Atmospheres 102, 28977–28985. , , , et al. (
- 2008) Root and shoot respiration of perennial ryegrass are supplied by the same substrate pools – assessment by dynamic 13C labeling and compartmental analysis of tracer kinetics. Plant Physiology 148, 1148–1158. , , , & (
- 2008) Arabidopsis transcript and metabolite profiles: ecotype-specific responses to open-air elevated [CO2]. Plant Cell & Environment 31, 1673–1687. , , , , , & (
- 1994) C-13 discrimination during CO2 assimilation by the terrestrial biosphere. Oecologia 99, 201–215. & (
- 2007) Seasonal, daily and diurnal variations in the stable carbon isotope composition of carbon dioxide respired by tree trunks in a deciduous oak forest. Oecologia 151, 268–279. , , , , & (
- 1987) Carbon isotope effects on the pyruvate dehydrogenase reaction and their importance for relative carbon-13 depletion in lipids. The Journal of Biological Chemistry 262, 8159–8164. & (
- 2005) Temporal variability in C-13 of respired CO2 in a pine and a hardwood forest subject to similar climatic conditions. Oecologia 142, 57–69. , , , , & (
- 2007) Interaction between photosynthesis and respiration in illuminated leaves. Mitochondrion 8, 87–99. & (
- 2004) Respiratory carbon metabolism following illumination in intact French bean leaves using 12C/13C labeling. Plant Physiology 136, 3245–3254. , , & (
- 1980) Determination of heavy atom isotope effects on enzyme-catalyzed reactions. Methods in Enzymology 64, 83–104. (
- 1990) Phosphorylation of the leaf mitochondrial pyruvate dehydrogenase complex and inactivation of the complex in the light. Current Topics in Plant Biochemistry and Physiology 9, 313–328. , , , , , & (
- 2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34, 374–378. , , , et al. (
- 1992) Long-term steady-state labelling of wheat plants by use of natural 13CO2/12CO2 mixtures in an open, rapidly turned-over system. Planta 187, 128–135. (
- 2003) Disentangling CO2 fluxes: direct measurements of mesocosm-scale natural abundance 13CO2/12CO2 gas exchange, 13C discrimination, and labelling of CO2 exchange flux components in controlled environments. Plant, Cell & Environment 26, 1863–1874. , , & (
- 2006) How large is the carbon isotope fractionation of the photorespiratory enzyme glycine decarboxylase? Functional Plant Biology 33, 911–920. (
- 2005) Carbon isotope effect predictions on enzymes involved in the primary carbon metabolism of plant leaves. Functional Plant Biology 32, 277–291. & (
- 2003) Metabolic origin of carbon isotope composition of leaf dark-respired CO2 in French bean. Plant Physiology 131, 237–244. , , , , & (
- 2004) Theoretical considerations about carbon isotope distribution in glucose of C3 plants. Functional Plant Biology 31, 857–877. , , & (
- 2005) In vivo respiratory metabolism of illuminated leaves. Plant Physiology 138, 1596–1606. , , , & (
- 2007) Methods for improving the visualization and deconvolution of isotopic signals. Plant, Cell & Environment 30, 887–891. , & (
- 2008) Respiratory metabolism of illuminated leaves depends on CO2 and O2 conditions. Proceedings of the National Academy of Sciences of the United States of America 105, 797–802. , , , , & (
- 1993) Growth and maintenance components of leaf respiration of cotton grown in elevated carbon-dioxide partial pressure. Plant, Cell & Environment 16, 539–546. , , & (
- 2008) Coupling of respiration, nitrogen, and sugars underlies convergent temperature acclimation in Pinus banksiana across wide-ranging sites and populations. Global Change Biology 14, 782–797. , , & (
- 2005) Dynamics of leaf and root growth: endogenous control versus environmental impact. Annals of Botany 95, 891–900. & (
- 2006) Estimating the internal conductance to CO2 movement. Functional Plant Biology 33, 431–442. (
- 2007) Evaluating high time-resolved changes in carbon isotope ratio of respired CO2 by a rapid in-tube incubation technique. Rapid Communications in Mass Spectrometry 21, 1352–1360. , , , & (
- 2008) Partitioning net ecosystem carbon exchange and the carbon isotopic disequilibrium in asubalpine forest. Global Change Biology 14, 1785–1800. , , & (
- 2001) Link between diurnal stem radius changes and tree water relations. Tree Physiology 21, 869–877. , & (
Supporting Information
- Top of page
- Supporting Information
Figure S1. Typical A/ca curves at the mesocosm level. The growth CO2 conditions were 200 μmol mol−1 (chamber 1, closed symbols) or 1000 μmol mol−1 (chamber 2, open symbols).
Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.
|Supporting info item
Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.


text:
Museum of Intolerance might well be an interesting concept to pursue. The local Arab population as well as most Muslim states have had a tough time showing any tolerance toward the thought of a Jewish entity, even though the entire world agreed, through the democratic processes of the UN, to have them establish a state there. But the narrower issue here is what to do with unused cemeteries in urban areas. This same story is repeated throughout the world, as the population grows, we are running out of room. Makes for gripping headlines, but not much in the way of sense.
If selected for publication, it will appear as soon as possible on Haaretz.com.

subset: commoncrawl


text:
Latest: Fast Liquid Transfer Down to Picoliter Levels with Tecan's D300e
Latest: Crown Bioscience Announces a Key Expansion of its Partnership with The National Resource ...
Latest: Corning Inc. Agrees to Purchase Gerresheimer's Pharmaceutical Glass Tubing Business
Latest: Bosch Packaging Technology Introduces New Remote Service Portal
Latest: Huber Kältemaschinenbau Presents New E-grade "Explore" for Process Development at ACHEMA ...
Latest: Advances in Eikonix SCAN Range of Automated Colony Counters
Latest: Successful Exhibition for HUBER CHINA at CPhI in Shanghai
Webinar Highlights: Analytical Methods for Semi-Targeted Screening of Pharmaceuticals and Illicit D...
EKF Diagnostics: In Profile
Fast Liquid Transfer Down to Picoliter Levels with Tecan's D300e
Bosch Packaging Technology Introduces New Remote Service Portal
The Latest Food and Beverage News
10 Top Tips for Life Science Laboratory Efficiency
Analysis of High-Alloyed Steel by HR ICP-OES on PlasmaQuant® PQ 9000
Screening HDAC Inhibitors – A Workflow Comprising High Throughput and High Content Screen...
Multi-Technique Spectral Searching in the KnowItAll® Spectroscopy Software
BigDye® Terminator Cleanup using Agencourt CleanSEQ® on the MICROLAB® STAR
Genomic STARlet: Increasing Process Stability For Automated Genomic DNA Isolation From Wh...
Controlled Cultivation of Stem Cells – Factors to Consider When Thinking of Scale-Up
Clinical Chemistry Analyzers
Next Generation Sequencing
Hematology Analyzers
Microplate Readers
Water Purification
PCR Technology
Allergies 2015
08 Jul 2015-09 Jul 2015
AACC (American Association fo...
26 Jul 2015-30 Jul 2015
Neuroscience 2015
17 Oct 2015-21 Oct 2015
12 Dec 2015-16 Dec 2015
This application note by Life Technologies (Invitrogen) analyses the performance of a protein detection technology designed to eliminate the common bottlenecks of detection of protein expression and cellular location. The system is based on Lumio™ technology; a small, six-amino acid recognition sequence. The unique sequence rarely appears in endogenous proteins—providing precise detection of proteins with this fusion tag.
Download this Article


text:
Engineering Seminar
Transportation Systems Program Speaker
- Presenter:
- Hanghang Tong
- Presenter Affiliation:
- Assistant Professor, Computer Science Department, City College, City University of New York.
- Location:
- 338A Davis hall
- Campus:
- North Campus
- Date:
- 5/16/2014
- Time:
- 1:00 p.m. - 2:00 p.m.
- Cost:
- Free
- Sponsor:
- Department of Civil, Structural and Environmental Engineering, Institute For Sustainable Transportation And Logistics, Transportation Informatics university Center
Featured Events.
Enjoy summertime tea at International Tea Time
Let's Go Fly a Kite!
Professional development seminar on utilizing LinkedIn
Paint at the Point on this Warm Weather Wednesday


text:
PokerStars parent company wants to buy NJ casino
The proposed deal will be scrutinized closely. State lawmakers have passed a bill that would authorize Internet gambling, but Republican Gov. Chris Christie hasn't acted on it.
Last year, PokerStars paid $547 million to settle money laundering charges from a U.S. government crackdown on illegal Internet gambling. It admitted no wrongdoing and is allowed to operate in states where online gambling is legal.
Rational is seeking from the New Jersey Division of Gaming Enforcement interim casino authorization, which is preliminary approval to move forward with the purchase. It would then need approval from the New Jersey Casino Control Commission to complete the purchase.
On its website, Rational describes PokerStars as the world's largest online poker site, with more than 50 million registered members. Since December 2001, the company says, more than 85 billion hands have been played on its site.
Wayne Parry can be reached at http://twitter.com/WayneParryAC


text:
Queen Anne's County asks residents to evacuateUPDATED 6:30 PM EDT Oct 28, 2012
Queen Anne's County Emergency Services Director J. Kevin Aftung explains what they're doing to protect residents during Hurricane Sandy.
More Video
CommentsThe views expressed are not those of this site, this station or its affiliated companies. By posting your comments you agree to accept our terms of use.blog comments powered by Disqus


text:
Grade: 2
Turns out that when I fell over in the river in the night during TWALK I cracked a bone in my finger...brilliant.
Strap the finger and try not to use it too much.
Jul 4, 2015 |
processing time:0.005s | © 2000–2015
Attackpoint LLC
| about orienteering
| privacy policy
| copyright policy
| donate


text:
Book your room at Holiday Inn Columbus-Hilliard
Standard Two Queens Non SmokingMax Occupancy: 4 guests (up to 3 children, 3 infants)
Standard Room Non SmokingMax Occupancy: 2 guests (up to 1 child, 1 infant)
Leisure King Non SmokingMax Occupancy: 2 guests (up to 1 child, 1 infant)
Accessible King Non SmokingMax Occupancy: 2 guests (up to 1 child, 1 infant)
Feature King Non SmokingMax Occupancy: 2 guests (up to 1 child, 1 infant)
Get an overview of this hotel3-star hotel with restaurant and indoor pool
Situated in Columbus, this hotel is 2.4 mi (3.9 km) from Anthony Thomas Chocolates and within 6 mi (10 km) of Ten Pin Alley and Early Television Museum. Hollywood Casino and Ohio Craft Museum are also within 6 mi (10 km).
Hotel Features
A restaurant, an indoor pool, and a fitness center are available at this smoke-free hotel. Free wired Internet in public areas and free self parking are also provided. Other amenities include a bar/lounge, a meeting room, and dry cleaning.
Room Amenities
Rooms offer conveniences like refrigerators and microwaves, plus free WiFi, free wired Internet, and cable TV. Room service, coffee makers, and free weekday newspapers are among the other amenities available to guests.Information missing or incorrect? Tell us!
Hotel Amenities
Hotel Amenities
Holiday Inn Columbus-Hilliard features an indoor pool and a fitness center. The hotel offers a restaurant. A bar/lounge is on site where guests can unwind with a drink. Wired high-speed Internet access is complimentary.
Event facilities measuring 1350 square feet (122 square meters) include a meeting room. This Columbus hotel also offers complimentary newspapers in the lobby, laundry facilities, and dry cleaning/laundry services. Complimentary self parking is available on site.
Holiday Inn Columbus-Hilliard is a smoke-free property.
- Free self parking
- Free wired high-speed Internet
- Restaurant
- Indoor pool
- Bar/lounge
- Fitness facilities
- Conference space size (feet) - 1350
- Conference space size (meters) - 122
- One meeting room
- Dry cleaning/laundry service
- Laundry facilities
- Free newspapers in lobby
- Safe-deposit box at front desk
- Elevator/lift
- Smoke-free property
Family Friendly Amenities
- Free Wi-Fi
- Indoor pool
- Refrigerator
- Microwave
- Cribs/infant beds (complimentary)
- Rollaway/extra beds available
- Laundry facilities
Available in all rooms: Free WiFi , Free wired high-speed Internet
Available in some public areas: Free wired high-speed Internet
Free self parking
Room Amenities
- Free WiFi
- Free wired high-speed Internet
- Room service
- Cable TV service
- Refrigerator
- Microwave
- Shower/tub combination
- Coffee/tea maker
- Free cribs/infant beds
- Rollaway/extra beds available
- Daily housekeeping
- Free weekday newspaper
- Free local calls
- Hair dryer
- Phone
- Iron/ironing board
- Climate control
- Private bathroom
- Connecting/adjoining rooms available
Where to Eat
Holiday Inn Columbus-Hilliard has a restaurant on site.
Room service is available.
Nearby Things to Do
Recreational amenities at the hotel include an indoor pool and a fitness center.
To make requests for specific accessibility needs, complete the "Special or Accessibility Requests" section of "Trip Preferences" when you book your hotel.
- Accessible path of travel
- Accessible bathroom
- Roll-in shower
- Accessible parking
- In-room accessibility
- Accessibility equipment for the deaf
- Braille or raised signage
Hotel Policies
Check-in time starts at 3 PM
Check-out time is 11 AM
Payment types
Children and extra beds
- Children are welcome.
- Rollaway/extra beds are available.
- Free cribs (infant beds)!
You need to know
Extra-person charges may apply and vary depending on hotel policy.
Government-issued photo identification and a credit card or cash deposit are required at check-in for incidental charges.
Special requests are subject to availability upon check-in and may incur additional charges. Special requests cannot be guaranteed.
We should mention
The property has connecting/adjoining rooms, which are subject to availability and can be requested by contacting the property using the number on the booking confirmation. Construction is underway at a neighboring building and there may be noise disturbance from the construction work.


text:
Bacterial contamination of tile drainage water and shallow groundwater under different application methods of liquid swine manure.
ABSTRACT A 2 year field experiment evaluated liquid manure application methods on the movement of manure-borne pathogens (Salmonella sp.) and indicator bacteria (Escherichia coli and Clostridium perfringens) to subsurface water. A combination of application methods including surface application, pre-application tillage, and post-application incorporation were applied in a randomized complete block design on an instrumented field site in spring 2007 and 2008. Tile and shallow groundwater were sampled immediately after manure application and after rainfall events. Bacterial enumeration from water samples showed that the surface-applied manure resulted in the highest concentration of E. coli in tile drainage water. Pre-tillage significantly (p < 0.05) reduced the movement of manure-based E. coli and C. perfringens to tile water and to shallow groundwater within 3 days after manure application (DAM) in 2008 and within 10 DAM in 2007. Pre-tillage also decreased the occurrence of Salmonella sp. in tile water samples. Indicator bacteria and pathogens reached nondetectable levels within 50 DAM. The results suggest that tillage before application of liquid swine manure can minimize the movement of bacteria to tile and groundwater, but is effective only for the drainage events immediately after manure application or initial rainfall-associated drainage flows. Furthermore, the study highlights the strong association between bacterial concentrations in subsurface waters and rainfall timing and volume after manure application.
Article: Tile Drainage Management Influences on Surface-Water and Groundwater Quality following Liquid Manure Application[Show abstract] [Hide abstract]
ABSTRACT: This study investigated the potential for controlled tile drainage (CD) to reduce bacteria and nutrient loading to surface water and groundwater from fall-season liquid manure application (LMA) on four macroporous clay loam plots, of which two had CD and two had free-draining (FD) tiles. Rhodamine WT (RWT) was mixed into the manure and monitored in the tile water and groundwater following LMA. Tile water and groundwater quality were influenced by drainage management. Following LMA on the FD plots, RWT, nutrients, and bacteria moved rapidly via tiles to surface water; at the CD plots, tiles did not flow until the first post-LMA rainfall, so the immediate risk of LMA-induced contamination of surface water was abated. During the 36-d monitoring period, flow-weighted average specific conductance, redox potential, and turbidity, as well as total Kjeldahl N (TKN), total P (TP), NH-N, reactive P, and RWT concentrations, were higher in the CD tile effluent; however, because of lower tile discharge from the CD plots, there was no significant ( ≤ 0.05) difference in surface water nutrient and RWT loading between the CD and FD plots when all tiles were flowing. The TKN, TP, and RWT concentrations in groundwater also tended to be higher at the CD plots. Bacteria behaved differently than nutrients and RWT, with no significant difference in total coliform, , fecal coliform, fecal streptococcus, and concentrations between the CD and FD tile effluent; however, for all but , hourly loading was higher from the FD plots. Results indicate that CD has potential for mitigating bacteria movement to surface water.Journal of Environmental Quality 05/2013; 42(3):881-892. DOI:10.2134/jeq2012.0261 · 2.35 Impact Factor


text:
$25 Shipping When You Purchase 12 Bottles - Click For Details
Mobile Site
Your cart:
Advanced search
Search again:
Advanced search
Jermann Vinnaioli Riesling Afix Venezie Igt 2010
Jermann Vinnaioli - Friuli-Venezia Giulia - Italy - Venezia Giulia
Professional Wine Reviews for Jermann Vinnaioli Riesling Afix Venezie Igt 2010
Rated 90 by Decanter
Dried fruits with apples and licorice with hints of violets. Full and fruity. Minerally finish. Made from Riesling. (Suckling)
Additional information »
12 Bottle
(case price $398.88)
Check availability
This item is available for
online ordering only
. It can be
picked up or shipped from our location within 4-6
business days.
Add 12x
more to get fixed rate shipping
Add 12 more to get fixed rate shipping
Allow substitute vintage?
Ask First
More wines available from Jermann Vinnaioli
Jermann Vinnaioli Chardonnay Venezia Giulia Igt 2012 750ml
Jermann Vinnaioli Chardonnay Were Dreams, Now It Is Just...
Jermann Vinnaioli Pinot Nero Red Angel On The Moonlight...
Jermann Vinnaioli Sauvignon Blanc Venezia Giulia Igt 2012...
Jermann Vinnaioli Vintage Tunina 2011 750ml
Jermann Vinnaioli Riesling Afix Venezie Igt 2010 Customer Reviews
There have been no reviews for this product. Be first to
write review
Customer also bought
Canyon Road Moscato 750ml
Canyon Road White Zinfandel 750ml
William Wycliff Vineyards Brut Champagne NV 750ml
Luc Belaire Rare Rose Sparkling Wine 750ml
Veuve Clicquot Ponsardin Champagne Yellow Label NV 375ml
Canyon Road Merlot 750ml
Canyon Road Pinot Noir 750ml
Mumm Napa Brut Prestige NV 750ml
Canyon Road Cabernet Sauvignon 750ml
Antinori Castello Della Sala Chardonnay Bramito Del Cervo...
Duche Longueville French Sparkling Cider Non-Alc NV 750ml
Salmon Creek Chardonnay 750ml
Salmon Creek Merlot 750ml
Gerstacker Weinkellerei Nurnberger Markt Gluhwein 1.0Ltr
Canyon Road Pinot Grigio 750ml
Vinos Sin-Ley Monastrell 2011 750ml
Gold Seal Catawba Pink 750ml
Skyfall Vineyard Pinot Gris 750ml
Additional Information on Jermann Vinnaioli Riesling Afix Venezie Igt 2010
Jermann Vinnaioli
Vintage: 2010
2010 saw extremely high quality viticulture in many parts of the world, with an exceptionally long and hot summer providing huge benefits for wineries across many countries, especially in the southern hemisphere. The northern hemisphere and Europe saw something of a cooler summer and flowering period, but this was by no means as disastrous as it could have been. France, especially, had a fantastic year in 2010, with the world renowned Burgundy region proclaiming that their white wines of this year are ones to look out for, and despite yields being relatively small across much of the country, the quality was exceptionally high. Spain, too, received some cooler weather, but Rioja and the rest of central Spain are hailing 2010 as a very good year indeed, again as a result of smaller, finer yields. California also received similar climatic conditions, but again, wineries are highly positive about the overall effect this had on their produce, as the slightly challenging conditions resulted in smaller yields of much elegance and distinction. 2010 was really Australia's year, and in South Australia and across the Mornington Peninsula, Chardonnay vines produced good yields with a lower sugar level than in previous years. As such, the majority of South Australian white wines from 2010 are superb, and packed full of character. Shiraz also had a great year, and most Australian wineries have been proclaiming 2010 one of the great vintages. Both the Argentinian and Chilean wine industries benefited from some ideal climatic conditions this year, and are reportedly ecstatically pleased with the fact that their 2010 wines ended up with lower alcohol levels, and were beautifully balanced wines packed full of flavor.
Varietal: Riesling
Riesling grapes have been grown in and around central Europe for centuries, and over time, they became the lasting symbol of south Germany's ancient and proud wine culture. Whilst the reputation of German wines abroad has in the past been mixed, the Germans themselves take an enormous amount of pride in their wineries, and Riesling grapes have now spread around the globe, growing anywhere with the correct climate in which they can thrive. Riesling grape varietals generally require much cooler climatic conditions than many other white grapes, and they are generally considered to be a very 'terroir expressive' varietal, meaning that the features and characteristics of the terroir they are grown on comes across in the flavors and aromas in the bottle. It is this important feature which has allowed Riesling wines to be elevated into the category of 'fine' white wines, as the features of the top quality bottles are generally considered to be highly unique and offer much to interest wine enthusiasts.
Region: Friuli-Venezia Giulia
Situated in the north of Italy, between the Alps and the Adriatic Sea, Friuli-Venezia Giulia is a fascinating and ancient wine region which is only just being discovered by the international wine audiences, keen to uncover more lesser known gems of Italy. Because Friuli-Venezia Giulia is so close to the Austrian and Slovenian borders, the wines there display a distinctly Germanic character, and typically Germanic grape varietals such as Riesling grow extremely well there, and capture much of their stunning alpine terroir. As such, alpine freshness, crystal clear mountain water and beautifully dry and crisp notes are what Friuli-Venezia Giulia's wines are most renowned for, and the Riesling, Pinot Bianco and Pinot Grigio wines of Friuli-Venezia Giulia, made by small, dedicated and traditional wineries, are considered amongst the finest in the world.
Country: Italy
Italy is recognised as being one of the finest wine producing countries in the world, and it isn't difficult to see why. With a vast amount of land across the country used primarily for vineyard cultivation and wine production, each region of Italy manages to produce a wide range of excellent quality wines, each representative of the region it is produced in. Any lover of Italian wines will be able to tell you of the variety the country produces, from the deliciously astringent and alpine-fresh wines of the northern borders, to the deliciously jammy and fruit-forward wines of the south and the Italian islands. Regions such as Barolo are frequently compared with Bordeaux and Burgundy in France, as their oak aged red wines have all the complexity and earthy, spicy excellence of some of the finest wines in the world, and the sparkling wines of Asti and elsewhere in Italy can easily challenge and often exceed the high standards put forward by Champagne. Thanks to excellent terrain and climatic conditions, Italy has long since proven itself a major player in the world of wines, and long may this dedication to quality and excellence continue.
Questions? Feedback?
powered by
Olark live chat software


text:
1000 Burton Ave
Northfield, NJ 08225-0609
Northfield, NJ 08225-0609
Tel: (609)677-9960
Yale School's mission is to provide a structured, enriched, and safe environment that meets each student¡¯s educational needs, and helps each student develop the knowledge and skills to become an independent and responsible citizen.
At The Yale School, we believe every student deserves high quality, evidence based instructional strategies designed to promote meaningful progress.
School Overview
|School Type
|Special Education School
|School Membership(s)School Assoc.
|Other associations(s) for exceptional children
|Religious Affiliation
|Grades Offered
|Grades 4 - 12
Student Body
|Total Students
|49 students
|Student Body Type
|% Students of Color
State avg.: 31%
|Students by Grade
Academics and Faculty
|Total Classroom Teachers
|9 teachers
|Student : Teacher Ratio
National avg.: 13:1
Nearby Schools:
All Schools | High Schools | Elementary Schools | Preschools | Public Schools
Show me:
- School Location Miles Students Grades
Egg Harbor TownshipTrocki Hebrew Academy Of Atlantic County
6814 Black Horse Pike
Egg Harbor Township, NJ 08234
(609)383-8484(Jewish)1.3 mi | 69 students | Gr. K-9
Egg Harbor TownshipKids' Choice Academy
6701 Black Horse Pike Ste A13
Egg Harbor Township, NJ 08234
(609)272-1181Daycare / Preschool1.9 mi | 17 students | Gr. PK-KG
LinwoodCreative Learning Pre School
515 Hamilton Avenue
Linwood, NJ 08221
(609)927-4715Daycare / Preschool3 mi | 92 students | Gr. NS-K
AbseconHoly Spirit High School
500 S New Rd
Absecon, NJ 08201
(609)646-3000(Roman Catholic)3.6 mi | 609 students | Gr. 9-12
LinwoodGospel Of Grace Christian School
2115 New Rd
Linwood, NJ 08221
(609)927-7578(Christian)3.7 mi | 53 students | Gr. PK-6
School Reviews
Area Statistics
Rental Market Monitor
Recent Articles
Updated June 28, 2015
When it comes to choosing a private school, there are so many choices to consider that the project can be a huge challenge to most of us. We offer some help and advice to help you get started.
Sending your child to a foreign language school makes good sense when you have been posted to this country from abroad and in other circumstances as well.
Do you need financial aid? Not sure? Confused by how financial aid works? Here are some answers.


text:
Trailer Bulletin: Jeff Bridges in "The Amateurs"
Written and directed by Michael Traeger (he wrote "Big Man on Campus" many moons ago), "The Amateurs" stars (get this) Jeff Bridges, Tim Blake Nelson, Joe Pantoliano, Ted Danson, William Fichtner, Patrick Fugit, Glenne Headly, Jeanne Tripplehorn, and Lauren Graham.
Check out the trailer right here.
"The Amateurs" opens in limited release on September 15th.


text:
VIEWS: 3 PAGES: 5 POSTED ON: 6/23/2012 Public Domain
LEVIN FAMILY FOUNDATION GRANT APPLICATION ALL SPACES ON THIS PAGE MUST BE FILLED AND ALL SIGNATURES ARE REQUIRED Section One Organization Data Applicant Organization (Legal Name): Doing Business As: Previous Name, if changed: Street Address: City: State: ___________ Zip: ________________ County: E-mail: Web site: Phone: ( ) Fax: ( ) IRS Name, as listed on 501(c)(3) letter: IRS letter date: / / Tax Exempt ID number (EIN): Executive Director: Direct Phone: ( ) Organization's Budget: $ Endowment Size: $ Organization's Major Funding Sources: Organization's Affiliation and/or accreditation body (check all that apply) United Way _____ Fine Arts Fund _____ Better Business Bureau _____ Chapter of national or regional organization __________________________________ Other (Specify) Request Data Program/Project Title: Amount of this request: $ Total Budget for this Program/Project: $ Proposal contact person information: Name Title Phone ( ) Fax ( ) E-mail Community/Counties served by this Program/Project: Projected number of people to be served by Program/Project_____________________________________ ___________________________________________________________________________________________ Brief demographic description of population served by this Program/Project: Type of request (check all that apply) Capital _______ Program/Project _______ Endowment ______ Operating _____ Technical Assistance ______ Start-up ______ Signature of Executive Director: / Printed Name ___________________________________________________________ (date) Signature of Board President: / Version 01/05 Page 1 Printed Name____________________________________________________________ (date) Version 01/05 Page 2 EXECUTIVE SUMMARY – 1 Page Only Version 01/05 Page 3 The narratives for Sections Two through Six should not exceed five pages. Responses must be typed, single- spaced, single-sided and use a minimum of 12-point type. Section Two – Profile of Organization 1) Brief summary of organization's history* 2) Brief statement of organization's vision/mission* 3) Brief description of current programs/projects and activities 4) Description of organization's constituency and geographic region (if different than the project's as described above) *You may omit if 1 & 2 have been submitted with another project during the last 2 years Section Three –-Statement of Need 1) Statement of need project is attempting to meet and evidence of that need. Section Four –- Program/Project Description & Methodology 1) Description of program/project, including: a) Activities to accomplish programs/project (Is this a new or ongoing activity?) b) Goals/objectives c) Timetable for implementation d) Duration of program/project e) Measurable outcomes f) Evidence of use of best practices 2) Will the organization collaborate with other organizations (if so, with whom and how?) 3) Why is your organization qualified and appropriate to address this need or benefit? Section Five –- Evaluation 1) How will success be defined and measured, for example what are the short term, intermediate and/or long term outcomes? 2) How will the evaluation be conducted? 3) How will the people served be involved in the program/project evaluation? 4) How will the results be used and disseminated? Version 01/05 Page 4 Section Six –- Program/Project Funding Plans 1) List of other funders to which the proposal has been and will be submitted. For each funder, indicate amount requested and status of request, i.e., request will be submitted, is pending, was funded or was declined. If funded, specify amount of grant. 2) Other anticipated funding including: a) Earned revenue b) In-kind support c) Special events d) Fundraisers, etc. 3) Anticipated future/long-term funding strategies and sources, if appropriate Section Seven -– Required Financial Attachments 1) Statement of Revenue/Support and Expenses for your organization's most recently completed fiscal/calendar year. (Sample forms are available upon request) 2) Balance Sheet for most recently completed fiscal year. 3) Most recent, complete audit including auditor's notes. If the organization does not have an audit done, then send the most recent 990. 4) Budget for the current fiscal/calendar year including a column showing the organization's year-to-date status. (Sample forms are available upon request) 5) Project Budget for your entire project. (Sample forms are available upon request) 6) Provide pro forma project budgets for the next three years, if there are ongoing expenses associated with your project which increase the organization's operating budget by 20% or more, or if this is a new organization. The purpose of the pro forma is to show how the organization plans to sustain the project. Section Eight –- Required Non-Financial Attachments 1) IRS letter of determination 501(c)(3)* 2) Names, affiliations and demographics of board members 3) List of key staff members and qualifications, or an organizational chart 4) One or more examples of the following a) Annual reports b) Organizational brochure c) Sample newsletter d) Program 5) Letters of commitment from collaborating organizations, if appropriate. *If you have submitted an application before, you do not need to send this again. Version 01/05 Page 5
Pages to are hidden for
"Applicant Organization (Legal Name)"Please download to view full document