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First published online December 23, 2004; 10.1104/pp.104.051375 Plant Physiology 137:383-395 (2005) © 2005 American Society of Plant Biologists The Sources of Carbon and Nitrogen Supplying Leaf Growth. Assessment of the Role of Stores with Compartmental Models1Lehrstuhl für Grünlandlehre, Technische Universität München, D–85350 Freising-Weihenstephan, Germany (F.A.L., H.S.); and Soil Plant Microbial Interactions Group, The Macaulay Institute, Craigiebuckler, Aberdeen AB15 8QH, United Kingdom (B.T.)
Patterns of synthesis and breakdown of carbon (C) and nitrogen (N) stores are relatively well known. But the role of mobilized stores as substrates for growth remains less clear. In this article, a novel approach to estimate C and N import into leaf growth zones was coupled with steady-state labeling of photosynthesis (13CO2/12CO2) and N uptake (15NO3–/14NO3–) and compartmental modeling of tracer fluxes. The contributions of current C assimilation/N uptake and mobilization from stores to the substrate pool supplying leaf growth were then quantified in plants of a C3 (Lolium perenne) and C4 grass (Paspalum dilatatum Poir.) manipulated thus to have contrasting C assimilation and N uptake rates. In all cases, leaf growth relied largely on photoassimilates delivered either directly after fixation or short-term storage (turnover rate = 1.6–3.3 d–1). Long-term C stores (turnover rate < 0.09 d–1) were generally of limited relevance. Hence, no link was found between the role of stores and C acquisition rate. Short-term (turnover rate = 0.29–0.90 d–1) and long-term (turnover rate < 0.04 d–1) stores supplied most N used in leaf growth. Compared to dominant (well-lit) plants, subordinate (shaded) plants relied more on mobilization from long-term N stores to support leaf growth. These differences correlated well with the C-to-N ratio of growth substrates and were associated with responses in N uptake. Based on this, we argue that internal regulation of N uptake acts as a main determinant of the importance of mobilized long-term stores as a source of N for leaf growth.
Most plants store carbon (C) and nitrogen (N) either by accumulation of assimilation/uptake overflows, or by deposition of specific reserve or recyclable compounds (Chapin et al., 1990  ). Stores are continuously built up or mobilized, hence interacting directly with the provision and utilization of plant resources. Allocation of C and N toward, and mobilization from, storage pools has been described in many species, and the effects of changes in growth conditions on such patterns are relatively well known (Millard, 1988; Chatterton et al., 1989; Chapin et al., 1990; Volenec et al., 1996). Conversely, the role of mobilized stores in supplying plant C and N growth demand is less clear, particularly regarding vegetative growth of perennial species.
One reason is simply lack of information. Studies of the role of stores require accurate identification of substrates derived from distinct sources, which poses methodological problems. Steady-state labeling techniques proved particularly useful in discriminating the use of newly acquired versus already available resources in response to specific stimuli, such as defoliation (de Visser et al., 1997
Another reason hindering the understanding of the role of stores is the absence of knowledge about its ecophysiological determinants. Often, the relative importance of stores as a source of substrates for growth tends to be associated with changes in mobilization intensity. However, it may depend as much on these as on responses of actual acquisition and demand rates (Bausenwein et al., 2001
The aims of this study were to (1) develop a method able to distinguish and quantify the sources of C and N supplying leaf growth in grasses, and then (2) use it to analyze the influence of plant status on the relative importance of those sources with the hypothesis that mobilization from stores is of greater importance for leaf growth when acquisition of C or N is more limited. In order to do this, a previously described method for estimating import of C and N substrates into leaf growth zones (Fig. 1; Lattanzi et al., 2004
The relative contribution of these sources was evaluated in plants of a C3 (Lolium perenne) and C4 (Paspalum dilatatum Poir.) grass growing undisturbed in mixed stands. Contrasting C3/C4 balances of the stands were brought about by moderately high (23°C) and low (15°C) temperature regimes. This exploited the differential growth response of C3 and C4 species to temperature to place L. perenne and P. dilatatum plants in contrasting hierarchical positions within the stands, and thus produce dominant and subordinate individuals with different rates of C assimilation and N uptake (Table I; see also Lattanzi et al., 2004 ).
Import of C and N into the Growth Zone and Tracer Import in Briefly Labeled Plants
Sequential analysis of leaf elongation rate (LER) and of lineal density of C and N along the immature part of leaves showed that import of C and N into the leaf growth zone (
Besides their stability, a remarkable feature of the results was the contrasting behavior of C and N substrates. Between 48% and 64% of the C imported over a day (i.e. 24 h) derived from C assimilated during the previous 12-h light period. Conversely, N taken up over the same period contributed only 3% to 17% to total daily N import.
Continuous steady-state labeling was applied to follow the saturation kinetics of label in the different C and N pools that served as sources for leaf growth. Continuous labeling thus meant that C and N tracers entered the plants over the whole 15-d (23°C) or 18-d (15°C) experimental period. In this case, the proportion of tracer in imported C and N substrates (
Models described well the time course of  and  as indicated by the close agreement of values estimated by Equation 3b and model predictions (Fig. 5). The SE of predicted values (Fig. 3), as well as of derived parameters (Table III), was within reasonable limits, with coefficients of variation below 20% for Q1 and close to 35% for Q2C. However, k21N had comparatively large SE, which clearly reflected on the SE of its derived parameter, Q2N (Table III).
Model Validation Formally analogous models able to identify Q1 and Q2 with biochemically and spatially defined metabolites have been evaluated by comparing predicted and estimated values (e.g. Suc in leaves; Rocher and Prioul, 1987 ). In this study, the system was too complex to expect such direct correspondences, for there are several intermediaries with unknown spatial compartmentalization between CO2 assimilation/NO3– uptake and subsequent import of C and N into the leaf growth zone, mainly as Suc and amino acids (Schnyder and Nelson, 1988; Gastal and Nelson, 1994). As an alternative, sizes of Q1 and Q2 were compared to tiller average C and N mass. This revealed Q1C represented between 1.1% and 1.8% of tiller C mass. Since IC was underestimated due to unaccounted respiration, Q1C values should have been approximately 30% higher (Volenec and Nelson, 1984). Conversely, Q1N represented 10% to 30% of tiller N mass (Table III).
Smaller relative size of Q1C than Q1N was a common feature in all plants. But the magnitude of this difference varied greatly. Dominant plants had relatively larger Q1C than subordinate plants. The opposite was true for Q1N. As a result, the ratio of Q1C to Q1N (Q1C:N) discriminated well subordinate from dominant plants (1.0 versus 2.9 in L. perenne; 0.5 versus 1.9 in P. dilatatum). Strictly comparable data are scarce. Farrar (1990)
Q2 values were reasonable for C, although somewhat high in subordinate L. perenne plants. But Q2N values were 2 to 3 times greater than the average N mass of tillers (Table III). Clearly, despite the models' good statistical behavior, Q2N values were unrealistic. Knowledge of N cycling within grasses indicates that a delay might occur between tracer incorporation (e.g. into growing tissue) and its subsequent mobilization (e.g. from senescing tissue; Robson and Deacon, 1978
Taken together, these results indicate Q1 size and half-time, and
Models were used to determine the time elapsed between C and N tracers entering the plant and their arrival at the growth zone. This yielded an age profile of imported substrates, where import of nonlabeled C or N at the end of the experimental period was described as older than 15 (23°C) or 18 (15°C) d. Additionally, in the two-pool model, the total amount of C and N tracer derived from each day's assimilation/uptake was further separated into the fraction derived from mobilization from Q2 and that only cycling through Q1 (Fig. 6).
In all treatments, imported C derived mostly from very recent photosynthesis. A high proportion, 50% to 65%, corresponded to the C reaching the growth zone within 12 h of entering the plant (day 1). The remaining C was chiefly imported during the following dark and light periods (day 2). Virtually all this C cycled only through Q1C. Thus, Q1C effectively acted as a short-term store buffering day/night cycles. Opposite to C results, the importance of very recent N uptake was small: N derived from same-day uptake (day 1) represented less than one-sixth of the total imported N. Imported N derived in more or less similar proportions from last 3-d (23°C) to 5-d (15°C) uptake. Again, most of this recent N cycled only through Q1 (compare with Fig. 6). With half-times >0.8 d, stores within Q1N would have been involved in moderating day-to-day variations in supply. Mobilization from Q2 supplied <10% of imported C. Q2C half-times, approximately 10 d, were close to leaf expansion duration (Table I). The exceptions were subordinate L. perenne plants, where Q2 provided 27% of imported C and had a half-time twice as long and more similar to that of Q2N (Table III). Conversely, the contribution of mobilized N was variable but relevant in all plants. In subordinate plants, N mobilized from Q2 was the preponderant source, supplying three-fourths of imported N. In dominant plants, it was more important in the C4 (41%) than in the C3 (24%) grass. Half-times of Q2N were relatively long, but these must be interpreted with caution because they implied unrealistically large pool sizes. Consideration of a lag time, which could have caused such behavior, reduced half-times to 8 (subordinate L. perenne), 10 (subordinate P. dilatatum), and 19 (dominant P. dilatatum) d (compare with Table III). When added to the 14- to 16-d lag times, these values become closer to leaf lifespans (Table I).
On the Approach
This article presents a novel approach for analyzing the contribution of distinct sources in supplying C and N substrates for growth. It involves three steps: (1) estimating C and N import into growth zones; (2) determining their labeled fraction under steady-state labeling of C assimilation and N uptake; and (3) analyzing the time course of these fractions with compartmental models. The first is an extension of a previously presented method, based on well-established knowledge of C and N fluxes within growth zones (Lattanzi et al., 2004
Compared to prior labeling studies, this approach imports several advancements. First, deposition of C and N in the growth zone is solely driven by the demand of dividing, expanding, and maturing cells (Schnyder and Nelson, 1988 The second advantage derives from explicitly addressing tracer mixing. In doing so, the assumptions customary to compartmental analysis are made. Some of these are a major restriction in applying this approach, such as that of a system in steady state; some are of difficult validation, such as that of homogeneous, well-mixed pools. Indeed, aggregating C and N metabolism into one or two pools is a simplification that is almost certainly invalid. Still, we think the approach renders a more meaningful interpretation of tracer fluxes than assuming close correspondences between labeled and nonlabeled substrates and the sources supplying them. For instance, in six out of eight modeled situations, the fraction of imported tracer deriving from current assimilation/uptake varied from virtually 1.0, for tracer imported within 1 d of its assimilation/uptake, to <0.5, for tracer imported 3 d (C) or 5 to 10 d (N) after its assimilation/uptake (Fig. 6). In these cases, assuming invariant relationships would have been misleading, revealing the importance of analyzing time courses. Finally, use of a modeling approach allowed the realization that the substrate pool (Q1) acted as a short-term store and that the ratio of C-to-N substrates indicated plant C/N status (see below). Such insights would have otherwise been difficult to gain.
As the pool directly supplying the growth zone, Q1 is analogous to a growth substrate, i.e. compounds readily available for tissue synthesis. A distinct feature of Q1 was its contrasting kinetics for C and N substrates. In all cases, Q1C had a shorter half-time than Q1N (Table III).
At first glance, such a difference might be thought to be related to a greater proximity, either physical or metabolic, of CO2 fixation to subsequent import of Suc into the growth zone than that of NO3– uptake from amino acid import. Short-term labeling studies do show that photoassimilates can reach the leaf growth zone within 10 to 20 min, whereas it would take at least 1 h for newly absorbed N to do the same (compare with Cooper and Clarkson, 1989
We are not aware of any other comparative study of C and N growth substrate kinetics with which these results could be compared. Compartmental analyses of source photosynthetic leaves have consistently indicated a cytoplasmic/apoplastic (Suc) transport pool, and a vacuolar (Suc)/chloroplastic (starch) storage pool with half-times <2 h and 12 to 25 h, respectively (Rocher and Prioul, 1987
Contrasting these values with Q1 half-times (Table III) leads to three conclusions. First, it corroborates that Q1C and Q1N included storage components; neither Q1C nor Q1N labeling kinetics were as fast as expected if accounted for solely by transport pools. Second, differences of 0.5 to 2 d between Q1C and Q1N half-times can be explained only by differences in the kinetics of C and N storage (not transport) pools. Thus, Q1C half-times <0.5 d resemble a flux-weighted average of transport and storage pools in source leaves. But Q1N half-times
Stores were an integral part of the supply of C and N substrates for leaf growth in all plants, providing about one-half of C and >80% of N imported into the leaf growth zone (Fig. 6). We hypothesized the importance of mobilized stores in supplying leaf growth increases whenever resource acquisition becomes limited. This was not the case for C. Subordinate plants had low C assimilation rates, closely related to their reduced light capture (Table I). But C older than 2 to 3 d contributed little to C import, corroborating the notion that leaf growth relies on recent assimilates (Anderson and Dale, 1983
In exception to this general pattern, mobilization from Q2C provided 27% of imported C in subordinate L. perenne plants (Table III). In vegetative grasses, there are two potential sources of old C: carbohydrate stores in sheath bases and stems (Chatterton et al., 1989
Notably, this flux of old C was absent in subordinate P. dilatatum plants, even though long-term N stores supplied an equally significant part of imported N. In fact, calculations in the C4 grass indicated more Q2-derived amino-C than the total amount of Q2-derived C, and thus an unrealistic, higher than 100%, contribution of amino-C (Table IV). The reason for this difference between L. perenne and P. dilatatum is not clear. Varying the assumed C-to-N ratio affected estimated values only slightly. Hence, the fault probably resides in assuming a strict relationship between unlabeled C and unlabeled N within organic N compounds.
Stores provided most of imported N in all treatments. However, this similarity hid contrasting responses. In dominant plants, stores within Q2N were important, particularly in L. perenne (Fig. 6; Table III). The comparatively low importance of mobilization from Q2N plus the short half-time of Q1N determine that, in fact, N import in these plants depended strongly on continuous uptake. Conversely, leaf growth in subordinate plants of both species became largely independent of external N, as 75% of imported N derived from Q2N. However, there is no indication that dominant and subordinate plants would have used qualitatively different N sources. In all plants, the lag time between incorporation and mobilization of N tracer in Q2N, and the close relation between the half-time of this pool and leaf lifespan, suggest that mobilization of long-term N stores was associated with leaf turnover. This agrees with long-term N stores in grasses being largely accounted for by export of amino acids from senescing leaves (Millard, 1988
Interestingly, Q1C:N was closely and negatively correlated with the fractional contribution of Q2N to IN, accommodating differences between plants growing in contrasting hierarchical positions, and also between L. perenne and P. dilatatum dominant plants (Fig. 7). This indicates that the importance of long-term stores in supplying N for leaf growth was related to the relative abundance/scarcity of C and N substrates. There is now convincing evidence for nitrate uptake being controlled by plant N demand through the regulatory activity of C and N metabolites, indicators of plant C/N status (Touraine et al., 1994
In suggesting a causal link between the importance of long-term stores and the internal capacity for N acquisition, this explanation is consistent with our working hypothesis. A corollary of plant C/N status controlling both N acquisition and the importance of long-term stores is that, whenever possible, a plant will acquire and use new N rather than stores (and increase its growth rate). This might not be so in all grasses. Farrar (1990) suggested the inherent difference between slow- and fast-growing species is their use of C stores. A differential use of nutrient stores seems a plausible possibility worthy of experimental testing.
A novel approach to study the sources of C and N supplying leaf growth is presented. Compared to previous analyses, it imports a more mechanistic definition of the process studied, an increased accuracy with which it is measured, and a more meaningful interpretation of tracer fluxes. By using such an approach, we were able to show that stores were a critical part of the supply of C and N substrates for leaf growth in both L. perenne (C3) and P. dilatatum (C4). Long-term carbohydrate stores were of little relevance for leaf growth in these undisturbed plants, and short-term C stores had an important role in buffering light/dark cycles in all plants. Hence, no evidence was found of a causal link between C acquisition and the importance of C stores in supplying leaf growth. Long-term N stores were important in supplying leaf growth in all situations, but particularly in plants where growth was more C than N limited and N uptake capacity was lower. It is proposed that a common mechanism regulates N acquisition and use of N stores.
In the following, we will first describe the labeling facility employed, along with the plant material and growth conditions used to generate stands with contrasting C3/C4 balances. Next, we will detail the two labeling strategies (and associated sampling schemes) used, and formulas to calculate import of total and labeled C and N into the growth zone. Last, we will present the models used to describe tracer kinetics, the assumptions made in solving them, and their (partial) verification.
The equipment and principles involved have been detailed elsewhere (Schnyder et al., 2003
Plant material and growth conditions have also been detailed previously (Lattanzi et al., 2004 Plants grew under a 12-h photoperiod, with a PPFD of 550 µmol photons m–2 s–1 at canopy height, provided by cool-white fluorescent lamps. Vapor pressure deficit was controlled at 0.5/0.3 kPa (light/dark) in all growth cabinets. An automated irrigation system watered the stands four times a day, flooding the boxes for 30 min with modified one-half-strength Hoagland solution (105 mg N L–1 supplied only as nitrate). Stands were periodically flushed with distilled water to prevent salt accumulation. Canopy air temperature was set at 25°C/23°C (light/dark) in two growth cabinets (cabinets II and III), and at 15°C/14°C (light/dark) in the other two cabinets (cabinets I and IV). These temperature regimes resulted in daily average sand temperatures (15 mm below surface) of 23°C and 15°C, respectively. After 8 weeks of growth at 23°C, P. dilatatum individuals were larger and taller than their L. perenne neighbors. The opposite occurred in mixed stands at 15°C (Table I). Within each mixture, larger individuals will be referred to as dominant plants and the others as subordinate plants.
On day 0, after either eight (23°C) or 10 (15°C) weeks of uninterrupted growth, PPFD and plant leaf areas were recorded at 15-cm increments from top to the bottom of the stands. Intercepted PPFD was then partitioned between the C3 and C4 grass by weighting the fraction of PPFD intercepted at each canopy stratum by the proportional contribution of each species to the leaf area present in that stratum.
Leaf expansion duration and leaf lifespan were estimated from biweekly measurements of leaf appearance rate, number of growing leaves, and number of green leaves in a set of 12 tillers per treatment (Davies, 1993
Plants were sampled in a series of six harvests at day 0, 1, 2, 4, 8, and 15 (23°C), or at day 0, 1, 2, 5, 12, and 18 (15°C). There were two labeling strategies associated with these harvests: Assimilated C and absorbed N were labeled either briefly (last 12 h, i.e. the entire photoperiod prior to sampling) or continuously (since day 0) before sampling (Fig. 8). In both strategies, C labeling was performed by swapping individual plants between growth cabinets, which resulted in the exposure of plants grown under 13C-enriched CO2 (
In the case of briefly labeled plants, four plants per species and temperature regime were swapped during the dark period preceding the labeling photoperiod. Previously, plants were flushed with 0.5 L of distilled water. Importantly, labeling commenced only once lights went on. For C, the reason is obvious. For N, this was so because the first irrigation event after the plant transfer was scheduled immediately before the start of the light period. In the case of continuously labeled plants, 16 plants per species and temperature regime, different from briefly labeled ones, were swapped during the dark period after the first harvest: eight plants per species transferred from cabinet II to cabinet III, plus eight from cabinet III to cabinet II (23°C treatment), and the same for cabinets I and IV (15°C treatment; Fig. 8). Previously, stands were flooded with distilled water three successive times.
At each harvest, 10 plants per treatment (five per growth cabinet) were sampled from the central part of the stands: Four were continuously labeled plants, two were briefly labeled plants, and four were nonlabeled (control) plants. In each plant, the growth zone and an immediately adjacent piece of recently produced tissue (RPT) were dissected out of two to three growing leaves whose length was approximately one-half that of the youngest fully expanded leaf present in the tiller (Fig. 1; for details, see Lattanzi et al., 2004
The proportion of C or N (X) tracer in a sample is directly proportional to the content of 13C or 15N in it. Therefore, the amount of 13C or 15N in each sample (Aspl X) was expressed as a lineal function of the fractions of labeled and unlabeled C or N (flab X and funlab X), and the 13C or 15N content of analogous samples from control plants (Alab X and Aunlab X),
For example, for a plant swapped from cabinet II to cabinet III, Aunlab C and Alab C correspond to the amount of 13C of samples taken from control plants continuously grown under CO2 with
Since funlab X = 1 – flab X, Equation 1a can be solved for flab X:
The amount of labeled C or N was then calculated as the C or N mass of the sample times the corresponding flab C or flab N value.
C assimilation and N uptake were estimated as the total amount of C and N tracer found in whole briefly labeled plants. For C, this is a measure related to daytime C gain, although respiration of nonlabeled C is unaccounted for. In the case of N, this measure is close to a net balance between N influx and efflux over the 12-h light period.
Briefly Labeled Plants
Continuously Labeled Plants
Tissue-bound C and N export out of the growth zone (EX) was estimated over 1-d intervals (ti–1 – ti) as the product of leaf elongation rate (
This method was further developed to estimate the labeled and nonlabeled components of C and N fluxes. The amount of labeled C or N imported into the growth zone (Ilab X) was assessed for 1-d intervals as the export of labeled C or N (Elab X) plus the variation in mass of labeled C or N within the growth zone (Glab X) over the same time interval:
The fraction of labeled C or N in import
Since IC and IN, as well as GC and GN, were constant in time (at a 1-d timescale; Lattanzi et al., 2004
Equation 3b explicitly shows that estimation of
The five specific 1-d intervals over which
Modeling of Time Course of C and N Tracer Imported into the Growth Zone
We propose a two-pool model to describe the time course of the incorporation of tracer into the growth zone, which is formally similar to that used in compartmental analyses of C export from source leaves (e.g. Moorby and Jarman, 1975
Assuming the system is in steady state, that is, dQ1/dt = dQ2/dt = 0, pool sizes are given by
In some cases, a simpler one-pool model was proposed in which labeled and nonlabeled C and N enter Q1 and from there are imported into the growth zone (Fig. 4b). Hence, the one-pool model is the special case of the former, where Q2 becomes infinitely large and k21 infinitely small.
Assuming first-order kinetics,
 are fitted parameters. Note that equals k12/(k10 + k12) in the two-pool model.
Models were implemented in MODELMAKER (version 4.0; Cherwell Scientific, Oxford, UK). Differential equations were solved using the fourth-order Runge-Kutta numerical method, with a step size of 0.01 d. Predicted
Verification of Assumptions
Regarding Assumption 1, previously presented data from this same experiment (Lattanzi et al., 2004 Eventual effects of noncontinuous incorporation of tracer, arising from diurnal cycles in C assimilation/N uptake, were assessed assuming that import of C and N into the growth zone (IX) was constant over the day, but tracer import (TX) occurred only over the 12-h light periods. Optimized solutions indicated consistent reductions of about 25% in size and half-time of Q1C in all modeled situations. However, these were unstable, probably due to a limited data set. Including a similar diel cycle in N uptake had no effect upon Q1N parameters. Since general responses were unchanged and because of a lack of quantitative support for eventual day/night changes in C and N import rates, we chose to retain the previous optimized values, observing that Q1C size and half-time would be overestimated.
Assumption 2 is, in a strict sense, probably false. However, support for its practical validity has been found repeatedly (Prosser and Farrar, 1981 Assumption 3 is perhaps the model's most drastic simplification. Probably, neither Q1 nor Q2 are homogeneous and well-mixed pools, but comprise a set of biochemically and/or spatially distinct compartments. Further compartmentalization, however, did not improve goodness of fit of the model, although this may reflect a limited number of data points or the short time span of the experiment. Assumption 4 was most likely true because fractionation during C and N transport and conversion are small compared to the 13C and 15N enrichments used.
The SE associated with the determination of the total and proportional amount of labeled and nonlabeled C or N in the flux imported into the growth zone was estimated by Gaussian error propagation. Models were assessed by, and selection of alternative models based on, ANOVA. Ideally, partitioning the residual mean square into lack of fit and pure error terms would provide an objective basis for choosing between alternative models. In this case, however, lack of true time replicated
In nonlinear regression, the SE of a fitted parameter is of very limited value in assessing its significance. This is because the usually non-normal distribution of errors renders strongly asymmetric confidence intervals. Thus, SE of fitted parameters in the one- and two-pool models (i.e. rate constants and
We thank Dr. Warren Williams (AgResearch, Palmerston North, New Zealand) for providing seeds of Paspalum dilatatum. The staff at the Lehrstuhl für Grünlandlehre (Technische Universität, Munich) provided invaluable assistance, particularly Rudi Schäufele and Wolfgang Feneis. Received August 9, 2004; returned for revision October 13, 2004; accepted October 26, 2004.
1 This work was supported by the Deutsche Forschungsgemeinschaft (SFB 607) and the Scottish Executive Environment and Rural Affairs Department. F.A.L. was partially supported by an award from the British Council and Fundación Antorchas (Argentina).  Article, publication date, and citation information can be found at www.plantphysiol.org/cgi/doi/10.1104/pp.104.051375. * Corresponding author; e-mail schnyder{at}wzw.tum.de; fax 49–8161–71–3242.
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ABSTRACT
RESULTS
) increases until it equals the LER when cell elongation ceases. Lineal density of C and N (
LC and 
IC
and 
, 
) and briefly labeled (
, 
) C (
) was not stable, as in briefly labeled plants, but characterized by rapid increases followed by either slower increases or complete stabilization (
, 
) and N (
, 
) into the growth zone for continuously labeled L. perenne (
0.9 d suggest N tracer entered storage pools more than once before reaching the growth zone. Third, the more straightforward metabolism of C, compared to that of N, makes a more important storage component within N than C growth substrates highly probable, independent of species or growth conditions. Inherently different kinetics of C and N growth substrates may be a consequence of contrasting buffering requirements. Whereas C acquisition has an abrupt diurnal cycle, N uptake is likely to experience more drastic changes at timescales of days due to the pulsed and patchy nature of external N availability (Chapin et al., 1990
(the deviation of the 13C-to-12C ratio in CO2 from that of the international standard, Vienna Pee Dee Belemnite [VPDB]). Periodic adjustments of airflow and CO2 concentration in the inlet maintained a constant CO2 concentration of 300 µL L–1 within the growth cabinet. Two growth cabinets received 13C-enriched CO2 (Messer Griesheim, Frankfurt; 
, cabinets I and II), and two 13C-depleted CO2 (Messer Griesheim; 
Respiration was ignored, thus underestimating actual C import by the amount lost through respiration. This measure of import is analogous to a net deposition rate (Allard and Nelson, 1991
thus results:
Hence, 
can be directly estimated as:
over the same time interval; (2) 
at the lower (ti–1) and upper (ti) ends of the time interval; and (3) GX/
). Similarly, nonlinear functions fitted to the time course of the 
was estimated were defined by the six harvest dates as follows: days 0 to 1, 1 to 2, 3 to 4, 7 to 8, and 14 to 15, and days 0 to 1, 1 to 2, 4 to 5, 11 to 12, and 17 to 18 for the 23°C and 15°C temperature regimes, respectively. To test the accuracy of the method, 
and 
were integrated over 1-d intervals, thus producing data comparable to measured values (i.e. 
