Assessing and avoiding C isotopic contamination artefacts in mesocosm-scale 13CO2/12CO2 labelling systems: from biomass components to purified carbohydrates and dark respiration

Assessing and avoiding C isotopic contamination artefacts in mesocosm-scale 13CO2/12CO2 labelling systems: from biomass components to purified carbohydrates and dark respiration | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Method Article Assessing and avoiding C isotopic contamination artefacts in mesocosm-scale 13 CO 2 / 12 CO 2 labelling systems: from biomass components to purified carbohydrates and dark respiration Jianjun Zhu, Regina T. Hirl, Juan C. Baca Cabrera, Rudi Schäufele, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6759212/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Aug, 2025 Read the published version in Plant Methods → Version 1 posted 10 You are reading this latest preprint version Abstract Background Quantitative understanding of plant carbon (C) metabolism by 13 CO 2 / 12 CO 2 -labelling studies requires absence (or knowledge) of C-isotopic contamination artefacts during tracer application and sample processing. This concern has not been studied explicitly but is especially crucial in experiments at different atmospheric CO 2 concentrations ([CO 2 ]), when experimental protocols require frequent access to the labelling chambers. Here, we used a plant growth chamber-based 13 CO 2 / 12 CO 2 gas exchange facility to address this topic. The facility comprised four independent units, with two chambers routinely operated in parallel under identical conditions except for the isotopic composition of the CO 2 supplied to them (δ 13 C CO2 –43.5‰ versus –5.6‰). In this setup, dδ 13 C X (the measurements-based δ 13 C-difference between matching samples X collected from the parallel chambers) is expected to equal dδ 13 C Ref (the predictable, non-contaminated δ 13 C-difference ), if sample-C is completely derived from the contrasting CO 2 sources. Accordingly, contamination ( f contam ) was determined as f contam = 1 – dδ 13 C X /dδ 13 C Ref in this experimental setup. Determinations were made for biomass fractions, water-soluble carbohydrate (WSC) components and dark respiration of Lolium perenne (perennial ryegrass) stands following growth for ~9 weeks at 200, 400 or 800 mmol mol -1 CO 2 , with a terminal two weeks-long period of extensive experimental disturbance of the chambers. Results Contamination was small and similar (average 3.3% ±0.9% SD, n = 18) for shoot and root biomass and WSC fractions (fructan, sucrose, glucose, fructose) at every [CO 2 ] level. [CO 2 ] had no significant effect on contamination of these samples . There was no evidence for any contamination of WSC components during extraction, separation and analysis. At 200 and 400 mmol mol -1 CO 2 , contamination of respiratory CO 2 was close to that of biomass- and WSC-C, suggesting it originated primarily from in vivo -contaminated respiratory substrate. Surprisingly, however, we found no evidence of contamination of respiratory CO 2 at 800 mmol mol -1 CO 2 . Overall, contamination likely resulted overwhelmingly from photosynthetic fixation of extraneous (contaminating) CO 2 which entered chambers primarily during (daytime) experimental activities. Conclusions The labelling facility enables months-long, quantitative 13 CO 2 / 12 CO 2 -labelling of large numbers of plants with accuracy and precision across contrasts of [CO 2 ], empowering eco-physiological study of climate change scenarios. Effective protocols for contamination avoidance are discussed. Atmospheric CO2 concentration bulk carbon 13C isotopic labelling C tracer CO2 gas exchange contamination experimental artifact water-soluble carbohydrates (fructan sucrose glucose fructose) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 BACKGROUND Isotopic labelling of the carbon (C) in CO 2 supplied to photosynthesizing organisms is a unique and powerful method for investigating C fluxes in central metabolism, transport, allocation and partitioning of photosynthetic products from the organelle (chloroplast) to the ecosystem scale [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. Multiple different techniques, including pulse-chase and dynamic labelling ( sensu Ratcliffe & Shachar-Hill [ 18 ]; or synonymous ‘steady-state’ or ‘continuous’ labelling [ 7 ]) with different C isotopes ( 11 C, 13 C or 14 C) have been designed and applied to different aspects of the analysis of C fluxes in plants [ 6 , 7 , 19 , 20 , 21 , 22 ]. One such method is especially useful for long-term (hours- to months-long) labelling at large scales, with large numbers of plants in controlled environments, and uses inexpensive and harmless near-natural abundance 13 CO 2 / 12 CO 2 mixtures [ 21 , 23 , 24 , 25 ]. These are derived from 13 C-depleted fossil-organic or (relatively) 13 C-enriched mineral sources and thus termed ‘fossil-organic’ or ‘mineral CO 2 ’. This technique has proven useful for the determination of functional components of CO 2 fluxes, such as dark respiration in light [ 25 , 26 ], distinction of autotrophic and heterotrophic ecosystem respiration [ 21 ] and quantification of the labelling kinetics of metabolic and storage substrate pools supplying sink tissue [ 27 , 28 ] or dark respiration of shoots and roots [ 29 , 30 ]. Further, such tracer studies have enabled analysis of C fluxes in central carbohydrate metabolism of source leaves and of the function and importance of assimilate stores (or reserves) in supplying substrate to growth or respiration by compartmental models at organ, plant and ecosystem scale [ 27 , 31 , 32 , 33 ]. A special variant of this labelling strategy – particularly useful for exploring contamination artefacts (as we show here) – uses two parallel identical growth chambers with the same plant material grown in the same conditions except for the C isotopic composition (δ 13 C, Table 1 ) of the CO 2 (δ 13 C CO2 ) supplied to the chambers. In our laboratory, such a system is directly connected with a continuous-flow stable isotope ratio mass spectrometer (CF-IRMS) which permits quasi-continuous monitoring of δ 13 C CO2 at the chamber inlet and outlet of the air stream passing through the chambers (Fig. 1 ). As air is ventilated strongly inside the chambers, the δ 13 C CO2 at the chamber outlet reflects that inside the chamber [ 25 ] as in leaf cuvettes [ 34 ]. In nature, as well as in the labelling system, the δ 13 C of plant biomass is generally 13 C-depleted relative to CO 2 because of 13 C discrimination (Δ 13 C) in photosynthesis [ 35 , 36 ], possibly modified further to a smaller degree by post-photosynthetic fractionation effects [ 29 , 37 , 38 , 39 , 40 ]. According to Farquhar et al. [ 35 , 36 ], δ 13 C of a given plant sample X (tissue or compound) is related to δ 13 C CO2 as δ 13 C X = (δ 13 C CO2 – Δ 13 C X ) / (1 + Δ 13 C X ), (1) with Δ 13 C X representing the sample-specific Δ 13 C (which integrates both photosynthetic and eventual post-photosynthetic effects). Although Δ 13 C X can vary as a function of environmental conditions [ 41 , 42 ], it is theoretically independent of the isotopic composition of CO 2 [ 36 ] and, hence, must be the same when plants are grown in identical conditions with different δ 13 C CO2 [ 24 , 25 ]. Table 1 Definition of symbols, and specifications Symbol Definition Specification δ 13 C Defined as δ 13 C = ( R P / R S – 1) × 1000, with R the molar abundance ratio 13 C/ 12 C, and P referring to the sample and S to the international Vienna-Pee Dee Belemnite (V-PDB) standard (‰) Farquhar et al. [ 36 ] δ 13 C CO2 δ 13 C of CO 2 (‰) Here we used CO 2 of mineral (δ 13 C CO2 ~–5.6‰) and fossil-organic origin (δ 13 C CO2 ~–43.5‰) to supply parallel growth chambers δ 13 C inlet δ 13 C of CO 2 at the inlet of a growth chamber (‰) Measured δ 13 C outlet δ 13 C of CO 2 at the outlet of a growth chamber (‰) Measured δ 13 C outlet pure δ 13 C of uncontaminated CO 2 at the outlet of a growth chamber (‰) Calculated as: δ 13 C outlet pure = (Δ 13 C + ξ δ 13 C inlet Δ 13 C/1000 + ξ δ 13 C inlet )/( Δ 13 C/1000 ( ξ – 1) + ξ), with Δ 13 C fixed at 21‰ δ 13 C X δ 13 C of sample X (‰), with X referring to net photosynthesis, dark respiration, biomass, or WSC in the form of fructan, sucrose, glucose or fructose Measured δ 13 C WSC δ 13 C of water-soluble carbohydrates (WSC) (‰) Measured δ 13 C WSC−free biomass δ 13 C of WSC-free biomass (‰) Calculated as δ 13 C WSC−free biomass = (δ 13 C biomass × W biomass – δ 13 C WSC × W WSC )/( W biomass – W WSC ) dδ 13 C X δ 13 C-difference between samples of the same kind (net photosynthesis, dark respiration, biomass, or WSC, in the form of fructan, sucrose, glucose or fructose) collected simultaneously from parallel chambers supplied with CO 2 of contrasting δ 13 C CO2 (‰) Based on measurements δ 13 C Ref δ 13 C of uncontaminated (pure) reference (‰) Calculated as δ 13 C Ref = (δ 13 C inlet × F inlet – δ 13 C outlet pure × F outlet ) / ( F inlet – F outlet ) dδ 13 C Ref δ 13 C-difference between uncontaminated (pure) references from parallel chambers supplied with CO 2 of contrasting δ 13 C CO2 (‰) Based on calculations of δ 13 C Ref for ‘samples’ collected simultaneously from parallel chambers supplied with contrasting δ 13 C CO2 f contam X Fraction of contaminating C in sample X Calculated as 1 – dδ 13 C X /dδ 13 C Ref Δ 13 C Carbon isotope discrimination (‰) Farquhar et al. [ 36 ], here set to 21‰ in estimations of δ 13 C Ref Δ 13 C X Carbon isotope discrimination as expressed in sample X (‰) Based on measurements, and calculated as Δ 13 C X = (δ 13 C outlet – δ 13 C X )/(1 + δ 13 C X /1000) ξ Ratio of the rate of CO 2 entry into a growth chamber relative to the net rate of CO 2 uptake (net photosynthesis) After Evans et al. [ 34 ] Calculated as ξ = C inlet / ( C inlet – C outlet ) [CO 2 ] CO 2 concentration in air (µmol mol − 1 ) C inlet CO 2 concentration in air at the inlet of the growth chamber (µmol mol − 1 ) Measured C outlet CO 2 concentration in air at the outlet of the growth chamber (µmol mol − 1 ) Measured F inlet Flux of CO 2 entering a growth chamber (µmol s − 1 ) Based on measurements F outlet Flux of CO 2 leaving a growth chamber (µmol s − 1 ) Based on measurements A Ground area of a growth chamber (m 2 ) N Net CO 2 exchange rate in light, i.e. whole-stand net photosynthesis rate (µmol m − 2 s − 1 ) N = ( F inlet – F outlet ) / A , during daytime R n Whole-stand respiration rate in the dark (µmol m − 2 s − 1 ) R n = ( F inlet – F outlet ) / A , during nighttime W biomass C mass of a certain biomass sample (g) Measured W WSC C mass of WSC in a certain sample (g) Based on measurements and the mass fraction of C in different forms of water-soluble carbohydrates (fructan ~ 0.44, sucrose 0.42, glucose and fructose 0.40) X Designation of samples of a given kind collected simultaneously from parallel chambers supplied with contrasting CO 2 ; may refer to dark respiration, biomass, or WSC (fructan, sucrose, glucose, fructose) Here, CO 2 of mineral (δ 13 C CO2 ~ − 5.6‰) or fossil-organic (δ 13 C CO2 ~–43.5‰) origin Therefore, when established in the above two-chamber system, the δ 13 C of an uncontaminated (pure) plant C sample (termed δ 13 C Ref ) which is synthesized completely from photosynthetic CO 2 uptake of a certain CO 2 source is expected to accord with Eq. 1 independently of the δ 13 C CO2 of the source CO 2 . Accordingly – and again in artefact-free conditions and steady-state – the δ 13 C-difference (dδ 13 C Ref ) between chambers supplied with 13 C-enriched (mineral) and 13 C-depleted (fossil) CO 2 should be identical to that predicted using Eq. 1. Any C contamination of an actual sample X would cause a (contamination-weighted) decrease of dδ 13 C X actual relative to dδ 13 C Ref (i.e. dδ 13 C X actual < dδ 13 C Ref ). In the extreme, where dδ 13 C X =0, the sample X is fully independent of the different δ 13 C CO2 used, i.e. is completely contaminated. Accordingly, the fraction of contaminating C in a certain sample X ( f contam X ) can be defined as: f contam X = 1 – dδ 13 C X actual / dδ 13 C Ref . (2) Ceteris paribus , a given contaminating C source has the same δ 13 C and adds the same quantity of C to a certain sample X collected from the parallel chambers which are fed with different δ 13 C CO2 . This is true especially, if the parallel chambers are operated simultaneously, are housed in the same room, and sample collection and processing uses identical protocols (as was the case in this work). Putative contaminating C sources are many, and include (1) free atmospheric CO 2 (which has a δ 13 C of approx. − 9‰ at present [ 43 ]), (2) CO 2 exhaled by people (e.g. experimenters; − 17 and − 25‰ [ 44 , 45 ]), and (3) cross-contamination with the different labelling CO 2 s [ 24 , 25 ]. Further, (4) contamination with organic C compounds might occur during sample collection or processing [ 46 , 47 ]. In the context, also (5) seed biomass-C (or biomass of any type of experimental starting material, e.g. vegetative cuttings or seedlings) ‘qualifies’ as a contaminant, as it shares the same δ 13 C in the different labelling chambers. Perhaps most importantly, in climate change experiments, the likelihood and extent of contamination could perhaps depend on the atmospheric CO 2 concentration, [CO 2 ], which is used in the experiments. This would cause a [CO 2 ]-dependent experimental artefact and bias conclusions, if unnoted or uncorrected. As far as we know, there have been no systematic, comprehensive analyses of contamination artefacts in large- or stand-scale, long-term C labelling studies (but see Gong et al. [ 26 ]). Particularly, we know of no such methodological study under sub-ambient or elevated [CO 2 ] conditions. In this work, we ask: How does [CO 2 ] affect C contamination ( f contam ) of a range of parameters that are of interest in labelling studies, including biomass fractions (shoot and root), non-structural carbohydrate components (water-soluble carbohydrates (WSC): fructan, sucrose, glucose, fructose) and dark respiration? In addition, we perform a sensitivity analysis of C isotope discrimination (Δ 13 C) assumptions on the estimates of contamination. At the outset, we provide a description of the custom-made labelling facility used here. The work was performed with stands of Lolium perenne (perennial ryegrass, C 3 ) established from 12 days-old seedlings grown in parallel growth chambers under identical conditions with contrasting δ 13 C CO2 (i.e. δ 13 C CO2 of − 43.5‰ or − 5.6‰) at 200, 400 or 800 µmol mol − 1 CO 2 , approximating Last Glacial Maximum, current ambient, or predicted end-of-the 21st century [CO 2 ] levels [ 48 ]. Biomass samples for contamination analysis were collected immediately after the terminal, two weeks-long experimental period in which the labelling vessels (growth chambers) had to be accessed frequently for plant sampling or non-destructive measurements [ 48 , 49 , 50 ]. These perturbations provided a special opportunity for contaminations of the chamber atmospheres with extraneous CO 2 . MATERIALS AND METHODS Mesocosm-scale 13 CO 2 / 12 CO 2 gas exchange and labelling system The 13 CO 2 / 12 CO 2 gas exchange and labelling facility corresponded to a modernized and upgraded version of the system originally described by Schnyder et al. [ 25 ]. The facility was composed of four main modules (Figs. 1 , S1 and S2): (1) a screw compressor and adsorption dryer which generated CO 2 -free air, (2) a gas mixing system which controlled the addition of CO 2 to CO 2 -free air and supplied air with known δ 13 C CO2 and [CO 2 ] at an individually set rate for both air flow and [CO 2 ] to each labelling vessel, (3) four plant growth chambers, which served as the labelling vessels, and (4) a gas analysis unit, comprising a sample air selector, an infrared CO 2 gas analyzer (IRGA) and a continuous flow 13 CO 2 / 12 CO 2 IRMS, which analyzed in sequence the [CO 2 ] and δ 13 C CO2 of sample gas collected at the inlet and outlet of each chamber. Specifically, the four growth chambers served as open-system, mesocosm-scale gas exchange cuvettes, each having a 1.5 m 2 plant growth area and equipped with a microprocessor controller and environmental data acquisition system. All air supply to a growth chamber was provided by a dedicated gas mixing station which consisted of two computer-controlled mass flow controllers (Fig. 1 ) which regulated the mixing of CO 2 with known δ 13 C (0–1 standard liter per minute, SLPM) and CO 2 -free air (0–1000 SLPM). Dry CO 2 -free air was obtained with a self-regenerating adsorption dryer at up to 180 m 3 h − 1 at ambient atmospheric pressure. The dryer was fed with compressed air (approx. 7 MPa) by a screw compressor via an oil and water condensate drain and filters as shown in Fig. 1 . Commercially available CO 2 of known δ 13 C was supplied from cylinders (Fig. 1 ). Typically, rates of air supply to individual chambers ranged between 250 and 750 SLPM. Thus, with an internal chamber volume of approx. 3000 L, air flow through a chamber was equal to 5–15 times the chamber volume per hour. Accordingly, the mean residence time of CO 2 in the chamber was 4–12 min. Sample air was collected at the inlet and outlet of each growth chamber and continuously pumped to the 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; Fig. 1 ) at approx. 3 minutes-intervals. Sample air was split to serve the IRGA and CF-IRMS in parallel. Gas lines between the SAS and CF-IRMS and IRGA were flushed with sample air for 3 min before taking IRGA readings of CO 2 and H 2 O concentration and measurement of δ 13 C by the CF-IRMS. The CF-IRMS was interfaced with the sample air selector via a steel capillary tube (1 mm i.d.), a eight-port, two-position valve (Valco Instruments Co. Inc., Houston, TX, USA), dryer (Nafion®), gas chromatograph (25 m × 0.32 mm Poraplot Q; Chrompack, Middelburg, Netherlands) and open split. These components all formed part of a custom-made interface (Gasbench II; ThermoFinnigan, Bremen, Germany). Sample air for the CF-IRMS was pumped continuously through the steel capillary feeding the Valco valve and a 0.25 mL sample loop attached to it. After a 90 sec flushing period, the content of the sample loop was swept with helium carrier gas through the interface, where water vapor was removed by the Nafion trap and CO 2 was separated from other sample air gases in a GC column. Finally, the CO 2 was introduced directly into the ion source of the IRMS via a glass capillary (0.1 mm i.d.) connected to the interface by an open split. After another 90 sec, shortly before the sample air selector switched to the next sample air line, a second sample of the same air was taken. Thus, within 3 min, each inlet/outlet was measured in duplicate. After every second sample, a VPDB-gauged CO 2 reference gas was injected into the CF-RMS via the open split. A full measurement cycle, including one set of measurements (concentrations of CO 2 and H 2 O, and δ 13 C of CO 2 ) on the inlet and outlet of each growth chamber, was completed within less than 30 min. The long-term precision (SD) for repeated measurements at the chamber inlet was < 0.20‰. Empty chamber tests performed before every experiment confirmed that gas lines throughout the air supply systems of the chambers were virtually leak-free based on measurements with CO 2 free air generated by the adsorption dryer and CF-IRMS based measurement of the peak size (observed peak area corresponded to a CO 2 concentration of < 250 SLPM, as was routinely the case in experiments. Individual CO 2 cylinders contained approx. 30 kg of CO 2 , and more than one cylinder had to be used in experiments of long duration (> 4 weeks). For this reason, we examined batches of CO 2 cylinders for uniformity of their δ 13 C CO2 . Typically, the δ 13 C CO2 was quite similar (< 0.27‰ SD) between cylinders of the same type (mineral or fossil-organic CO 2 ) within a batch. Plant material and growth conditions The details for the plant material and growth conditions used in this study have been presented before [ 48 , 49 , 50 ]. In short, plants of Lolium perenne were established and grown singly in individual plastic pots (350 mm height, 50 mm diameter) filled with 800 g of washed quartz sand (0.3–0.8 mm grain size). Pots were arranged at a density of 383 plants m − 2 in plastic containers (770 × 560 × 300 mm), and two of such containers placed in each growth chamber. Plants were supplied four times a day with a Hoagland-type nutrient solution with reduced nitrate-N content [ 48 ]. Light was supplied by cool-white, fluorescent tubes and warm-white, light-emitting diode (LED) bulbs with a constant photosynthetic photon flux density (PPFD) of 800 µmol m − 2 s − 1 at plant height during the 16 h-long light period [ 48 ]. Temperature was controlled at 20°C/16°C and relative humidity (RH) at 50%/75% during the light/dark periods. Importantly, we observed no chamber effects on any measured parameter in the studies of Baca Cabrera et al. [ 48 , 49 , 50 ]. [CO] treatments and sequence of experimental activities and sampling [CO 2 ] treatments were installed when seedlings were 12 days old following seed imbibition. In each of two experimental runs chamber air was controlled near the target CO 2 concentration ([CO 2 ] of 200, 400 or 800 µmol mol − 1 ) [ 48 ] with two chambers per [CO 2 ] treatment. In that, one chamber was supplied with 13 C-enriched (mineral) CO 2 and the other with 13 C-depleted (fossil-organic) CO 2 . Maintenance of [CO 2 ] near target values throughout the experiment – from 12 days-old seedlings to closed stands and beyond – required periodic adjustments of airflow and [CO 2 ] at the chamber inlet. This was done in such a way that the (photosynthetic) drawdown of [CO 2 ] inside the chambers did not exceed 14%. Quasi-continuous 13 CO 2 / 12 CO 2 measurements at the inlet and outlet of chambers were performed from day 20 to at least day 65. Disturbance of the [CO 2 ] and δ 13 C CO2 in the chambers was minimized by maintaining a small overpressure in the chambers relative to the outside atmosphere (Figure S2D) and by restricting daytime experimental activities inside the chambers between days 49 and 63 as much as possible within the limitations of the experimental plan [ 48 , 49 , 50 ]. Also, air locks (Figure S3A) were installed in chamber doors throughout the 14 days-long period of active experimentation. For the latter chambers had to be routinely accessed daily before the end of the light period for (non-destructive) measurements of leaf elongation on eight plants per chamber[ 48 ]. In parallel, leaf level gas exchange measurements (not reported here) were made on individual plants [ 48 ]. These measurements were performed in a different, dedicated growth chamber which was controlled at the same [CO 2 ] with the same δ 13 C CO2 as the chamber of origin of a given plant. Thus, individual plants were removed from their chambers for leaf level gas exchange measurements and later returned to their chamber of origin [ 48 ]. In addition, intensive sampling activities over two consecutive days occurred before the end of the light and dark periods on days 49 and 50, and days 63 and 64 (data not reported here, but partly presently in Baca Cabrera et al.[ 49 , 50 ]). The above activities intrinsically meant a disturbance which generated opportunities for contamination of the chamber atmospheres with extraneous CO 2 (Fig. 2 ). Here, we quantify the cumulative effect of all putative sources of contamination (see Background) on the δ 13 C of plant biomass and WSC components. For this, we sampled plants shortly after the end of the intensive experimental period (day 65) at the beginning of the dark period. Two replicate samples from each growth chamber were collected, with one replicate consisting of three randomly selected plants. Plants were removed from their pots, their roots washed to free them of sand and dissected into their shoot and root parts. The plant parts were weighed to determine their fresh weight, then frozen in liquid nitrogen and stored at − 18°C before freeze-drying for 72 h. Dry weights were subsequently determined. After that, plant material was ground to a fine powder in a ball mill (Mixer mill MM 400, Retsch, Haan, Germany) in 2-mL stainless steel grinding jars with 0.5-mm stainless steel beads, and thereafter stored again at − 18°C until further use. WSC extraction and separation WSC were extracted from shoot samples and fractions (fructan, sucrose, glucose, and fructose) separated using the procedures described by Gebbing & Schnyder [ 51 ]. Briefly, aliquots of 200 mg of milled sample material were weighed into 2-mL capped Eppendorf tubes and topped off with 1.8 mL of deionized water. Tubes were briefly vortexed (Vortex-Genie 2, Scientific Industries, New York, USA), held in a water bath at 93°C for 10 min, shaken for 45 min (Shaker, Heidolph Instruments, Schwabach, Germany) at room temperature, and then centrifuged at 9500 g for 15 min (Universal 320, Merck, Tuttlingen, Germany). The supernatant, which contained the dissolved WSC, was passed through nylon-membrane filters with a pore size of 0.45 µm and then stored in clean 2-mL capped Eppendorf tubes at − 18°C. WSC fractions (fructan, sucrose, glucose and fructose) were separated, quantified and collected using a high-performance liquid chromatography (HPLC) system similar to that of Gebbing & Schnyder [ 51 ]. Thus, 0.2 mL aliquots of the filtered supernatant were passed through a guard column (Shodex KS-LG, Showa Denko, Tokyo, Japan) and a preparative column (Shodex Sugar KS2002, 300×20 mm, Showa Denko, Tokyo, Japan) held at 50°C, with HPLC-grade water (Carl Roth, Karlsruhe, Germany) as the eluent, at a flow rate of 0.75 mL min − 1 and a system pressure of approximately 2.1 bar. The WSC were detected by refractive index measurement (Shodex RI-101, Showa Denko, Tokyo, Japan) and concentrations quantified by comparing sample peak areas against reference calibration curves of pure and mixed standards of analytical grade inulin, sucrose, glucose and fructose (all from Merck, Darmstadt, Germany). Knowing when the individual carbohydrates eluted from the preparative column (Fig. 2 ), fractions of fructan, sucrose, glucose, and fructose were individually collected in test tubes. 13 C analysis of biomass and water-soluble carbohydrate components The δ 13 C of biomass samples was determined for all shoot and root replicates, as in Lattanzi et al. [ 27 ]. The stored samples were thawed, re-dried at 40°C for 24 h and stored in desiccator vessels. Aliquots of 0.70 ± 0.05 mg of the shoot and root materials were weighed and packed into tin cups (3.3 x 5 mm, IVA Analysentechnik, Meerbusch, Germany). These were then combusted in an elemental analyzer (NA 1110, Carlo Erba Instruments, Milan, Italy) interfaced (Conflo III, Finnigan MAT, Bremen, Germany) to a continuous-flow isotope-ratio mass spectrometer (CF-IRMS, Delta Plus, Finnigan MAT, Bremen, Germany) which measured δ 13 C. A solid internal laboratory standard (SILS, fine ground wheat flour) was measured as a reference after every tenth sample to correct for possible instrument drift. All samples and SILS were measured against a laboratory working standard CO 2 gas, which was previously calibrated against a secondary isotope standard (IAEA-CH6; calibration accuracy ± 0.06‰ SD). The long-term precision given as the SD of repeated measurements of the SILS was < 0.2‰. Aliquots of approximately 0.70 mg of the different WSC fractions were transferred to tin cups, dried at 60°C for 24 h, and then analyzed for their δ 13 C using the same CF-IRMS system as above. δC of WSC-free biomass The δ 13 C of WSC free biomass (δ 13 C WSC−free biomass ) was determined from isotopic mass balance for a given biomass sample X , thus δ 13 C WSC−free biomass = (δ 13 C biomass × W biomass – δ 13 C WSC × W WSC ) / ( W biomass – W WSC ), (5) with W biomass and W WSC the C mass in biomass and in total WSC of a give sample, and δ 13 C biomass and δ 13 C WSC the of δ 13 C of the biomass and WSC extracted from that biomass sample. δ 13 C of respired CO 2 The δ 13 C of respired CO 2 (δ 13 C Rn ) was obtained as [ 25 ]: δ 13 C Rn = (δ 13 C inlet × F inlet – δ 13 C outlet × F outlet ) / ( F inlet – F outlet ), (4) with δ 13 C inlet and δ 13 C outlet the (measured) δ 13 C of CO 2 entering and leaving the growth chamber, respectively, and F inlet and F outlet the fluxes of CO 2 (µmol s − 1 ) entering and leaving the chamber during dark period. Estimation of C contamination The fraction contamination of the C ( f contam ) contained in any one type X of sample (with X standing for biomass or WSC fraction (fructan, sucrose, glucose or fructose) or respired CO 2 was determined as f contam X = 1 – dδ 13 C X actual /dδ 13 C Ref (Eq. 2) as explained in the Background section. In this, dδ 13 C X corresponds to the measurements-based δ 13 C-difference between samples of the same type collected simultaneously from parallel chambers, where one was supplied with 13 C-depleted CO 2 and the other with 13 C-enriched CO 2 . Meanwhile, dδ 13 C Ref refers to an estimation of the contamination-free δ 13 C-difference between the 13 C-depleted and 13 C-enriched CO 2 supplied to the chambers for the reference sample (see below and Table 1 ). For calculation of δ 13 C Ref for each chamber, we first estimated the uncontaminated δ 13 C of CO 2 at the outlet of the chamber (δ 13 C outlet pure ), by solving for δ 13 C outlet the Eq. 10 as[ 34 ] δ 13 C outlet pure = (Δ 13 C + ξ δ 13 C inlet (Δ 13 C/1000) + ξ δ 13 C inlet ) / (( Δ 13 C/1000)( ξ – 1) + ξ), (6) with Δ 13 C given in per mil (‰). In Eq. 6, δ 13 C inlet corresponds to the δ 13 C of CO 2 as measured at the inlet of the growth chamber. Δ 13 C was set to 21‰, a value close to that estimated for shoot biomass of perennial ryegrass or temperate (C 3 ) grassland in the absence of drought stress in many works [ 52 , 53 , 54 , 55 ]. ξ was obtained as [ 34 ]: ξ = C inlet / ( C inlet – C outlet ), (7) with C inlet and C outlet the CO 2 concentration in air as measured at the inlet and outlet of the growth chamber, respectively. Next, we estimated δ 13 C Ref , the contamination-free δ 13 C representative for all functional parameters (biomass fractions, WSC components or dark respiration; see below) as, δ 13 C Ref = (δ 13 C inlet × F inlet – δ 13 C outlet pure × F outlet ) / ( F inlet – F outlet ). (8) Then, dδ 13 C Ref , the uncontaminated δ 13 C-difference between δ 13 C ref estimates for the parallel chambers, was obtained as the numerical difference between the two δ 13 C Ref values. In the process, we used dδ 13 C Ref in all calculations of f contam for all types of samples and treatments, thus – for the time being – positing that Δ 13 C did not differ between treatments and that eventual post-photosynthetic discrimination was constant. In a second step, however, we explored the sensitivity of contamination estimates to variation of Δ 13 C during daytime gas exchange measurements, as observed in the different [CO 2 ] treatments. Statistical analysis One-way analysis of variance (ANOVA) with Tukey’s HSD post hoc tests for pairwise comparisons was conducted to explore the effect of CO 2 treatments on the contamination ( f contam ) of biomass ( n = 2–4) and WSC components ( n = 2–4). For f contam of dark respiration ( n = 17–39), a linear mixed-effects model (LMM) was fitted using the lme4 package [ 56 ]. The model included [CO 2 ] treatment as a fixed effect and sampling day as a random effect to account for temporal pseudo-replication. The significance of fixed effects was evaluated using sequential (Type I) likelihood ratio tests, and post hoc pairwise comparisons performed with Tukey’s HSD using the emmeans package [ 57 ]. All statistical analyses were performed in R v.4.0.2 [ 58 ]. The R-package ggplot2 [ 59 ] was used for data visualization. RESULTS Variation of [CO 2 ] and δ 13 C CO2 during the experiment The daytime mean CO 2 concentration at the chamber outlet varied little (coefficient of variation < 2%) between 20 and 65 days, and on average was 4.0 (±4.3 SD), 7.2 (±6.2 SD) and 13.9 (±8.3 SD) µmol mol − 1 higher than the target [CO 2 ] of 200, 400 and 800 µmol mol − 1 , respectively (Fig. 4 ). These differences corresponded to mean relative deviations from target [CO 2 ] of ≤2% in every treatment. These deviations did not differ ( P > 0.05) between chambers receiving 13 C-depleted and 13 C-enriched CO 2 (Fig. 4 ). Meanwhile, the δ 13 C of CO 2 at the chamber outlet (δ 13 C CO2 outlet ) relative to the chamber inlet (δ 13 C CO2 inlet ) increased by several ‰ during daytime until day 30 to 35 (Fig. 5 ) when canopies became closed. Thereafter, the increase of δ 13 C at the chamber outlet relative to that at the inlet was relatively stable until the end of the experiments (Fig. 5 ). Contamination ANOVA provided no evidence for a significant effect of [CO 2 ] treatments on the fraction of contaminating C ( f contam ) in any parameter of the study, except for respired CO 2 (Table 2 ). Biomass components (shoot and root), including WSC-free shoot biomass, and the different WSC fractions shared a very similar contamination of (on average) 3.3% (±0.9% SD), which was – moreover – close to that of respired CO 2 at both 200 and 400 µmol mol − 1 CO 2 (compare in Table 3 ), and did not differ significantly ( P = 0.84) between the latter. Conversely f contam of respired CO 2 was slightly negative at 800µmol mol − 1 CO 2 , but not significantly different from zero, and significantly smaller than at 200 and 400 µmol mol − 1 CO 2 ( P < 0.05 for both comparisons). Significantly, the uncertainty for the individual estimates of contamination (represented by the SD) was not much smaller than the contamination estimate for most biomass and WSC parameters (average SD 2.3%) and corresponded to an average coefficient of variation CV = SD/mean of 67%. Table 2 Significance ( P -value) of [CO 2 ] treatment effects on contamination ( f contam ) parameters. CO 2 effect significance ( P -value) Biomass components Shoot 0.787 Root 0.219 Water-soluble carbohydrates Fructan 0.374 Sucrose 0.972 Glucose 0.816 Fructose 0.759 WSC-free shoot biomass 0.358 Dark respiration < 0.001 CO 2 treatment effects were tested with one-way ANOVA for biomass and WSC components (n = 2–4) and a linear mixed model for dark respiration (n = 17–39). Table 3 The fraction of contaminating C ( f contam , %) in diverse sample types. Parameter CO 2 concentration (µmol mol − 1 ) 200 400 800 f contam , % Biomass components Shoot 3.9 (0.2) 4.1 (2.3) 2.7 (2.8) Root 4.0 (0.7) 4.6 (1.6) 2.0 (1.4) Water-soluble carbohydrates Fructan 3.7 (0.7) 2.2 (1.8) 4.8 (2.9) Sucrose 3.4 (4.4) 2.7 (3.0) 3.4 (5.1) Glucose 3.1 (4.2) 4.8 (2.3) 3.3 (5.1) Fructose 3.7 (3.3) 4.5 (1.4) 1.9 (7.6) WSC-free shoot biomass 3.6 (0.3) 4.3 (1.8) 2.1 (1.1) Dark respiration 3.5 (2.7) a 3.5 (4.5) a -2.4 (5.2) b f contam was determined for canopy-scale dark respiration for days 38 to 65, and bulk shoot and root C, and fructan, sucrose, glucose and fructose extracted and purified from shoot biomass sampled at the beginning of the light period on day 65. In all experiments, growth chambers were maintained near target [CO 2 ] of 200, 400 or 800 µmol mol − 1 using one of two CO 2 sources, a relatively 13 C-depleted (δ 13 C -43.5‰) or 13 C-enriched source (δ 13 C -5.6‰). f contam for dark respiration was determined during periods of steady-state gas exchange of chambers. That is, measurements in the first 45 min of a dark period or following the opening of the chamber were removed, and values over 1.5 × IQR (Interquartile Range) away from the mean were removed as outliers. Except for [CO 2 ] and δ 13 C CO2 , all conditions were kept the same in all chambers (see Materials and Methods). The means and standard deviations (SD) are presented for each treatment and were calculated based on daily replicates ( n = 17–39) for dark respiration measurements or chamber-level replicates ( n = 2–4) for all other parameters. Different superscript letters in the same row indicate a significant ( P < 0.05) effect of [CO 2 ] treatments. The effect of varying discrimination on estimates of contamination As illustrated by the methodology, assumptions of Δ 13 C impact estimations of contamination (i.e. f contam ) via the determination of the dδ 13 C Ref -values (see Eqs. 2, 6 and 8). Significantly, we observed [CO 2 ] dependent variation of Δ 13 C during daytime net CO 2 exchange (Δ 13 C N ) counter to expectations: thus, Δ 13 C N increased from approx. 19 to 23‰ between 200 and 800 µmol mol − 1 of CO 2 (Table S1 ). Thus, our literature-based assumption of constant Δ 13 C (= 21‰) must have biased estimations of f contam to some degree. The numerical effect of this Δ 13 C-dependent variation on estimates of f contam is explored in Fig. 6 . This analysis demonstrated a negative relationship between estimates of f contam and assumed Δ 13 C, with a 0.44% decrease of the estimated f contam for a 6‰ decrease of Δ 13 C from 18 to 24‰. The maximum error on estimates of f contam which resulted from neglecting the [CO 2 ] treatment effect on Δ 13 C as observed here was 0.3%, but did not change conclusions with respect to the non-significance (or significance) of the [CO 2 ] treatment effect on f contam (Table S2). DISCUSSION Contamination was small and similar for all parameters To the best of our knowledge, this work presents the first explicit, comprehensive and quantitative assessment of isotopic contamination artifacts in a long-term labelling experiment. This analysis determined a very small contamination of samples, which was – moreover – closely similar for a range of functional parameters (biomass fractions, WSC components and respired CO 2 ) and not significantly different for the different [CO 2 ] treatments (Tables 2 and 3 ), except for respiration at high CO 2 which was insignificant. Lack of statistical significance for the [CO 2 ] effect on contamination was not intuitive based on the expectation that incursion of a defined volume of extraneous CO 2 into labelling vessels would cause a (proportionally) greater mixing with a low than a high set CO 2 concentration, under ceteris paribus conditions. Indeed, there was a non-significant tendency for a lower contamination at 800 µmol mol − 1 [CO 2 ] than at 200 and 400 µmol mol − 1 , especially for the biomass components. Also, there was a significant (negative) [CO 2 ] treatment-effect on f contam for respired CO 2 , which accorded with the expected (relatively) smaller extraneous CO 2 incursion at 800 µmol mol − 1 [CO 2 ]. Yet, these effects were very small, and not even considering the [CO 2 ] treatment-effect on Δ 13 C (Table S1 ) did change conclusions with respect to the (non-)significance of [CO 2 ] treatment-effect on f contam (Table S2). The fact that contamination was generally very small certainly contributed to the absence of statistical significance via a small signal to error ratio (which is – basically – the inverse of the CV) in the data. In that, the experimental error was not large at all (see also Materials and Methods). This may be recognized by translating a given contamination-% into the δ 13 C-difference (between 13 C-enriched and 13 C-depleted chambers), which is required to return a certain contamination-%. For instance, a 3% contamination corresponded to an approx. 1.1‰ smaller δ 13 C-difference between the measurements (dδ 13 C X ) than the predicted uncontaminated reference estimates (dδ 13 C Ref ). By comparison, with a very good average, whole-system SD of (say) 0.4‰ for the δ 13 C X data – which integrates all errors from CO 2 administration over an extended period of time, labelling chamber operation (including adjustments in flow rates, changes of CO 2 flasks, variation of δ 13 C CO2 in the chambers, and sample collection and preparation) – error propagation yields a (whole system) SD of 0.57‰ on average for the dδ 13 C X data. Given the average 1.1‰-signal associated with a 3% contamination (see above), this SD of 0.57‰ translates to a CV of 52% for the contamination estimate which is not far from that observed here for the biomass and WSC components (67%). Clearly, increasing the isotopic spread between the two CO 2 sources used in experiments would help to increase the signal-to-error ratio of contamination estimation. In our laboratory we have used commercial sources of CO 2 with δ 13 C as high as − 2‰ and as low as − 50‰, which yields an isotopic spread which is somewhat larger than that found here (-48‰ vs 38‰). Of course, using artificially 13 C-enriched CO 2 sources [ 31 ] could further reduce the relative experimental error, including that of contamination estimations, and therefore increase to some degree the sensitivity of 13 CO 2 / 12 CO 2 tracer studies, albeit at much greater financial cost for the labelling CO 2 . Importantly, in the present work contamination of the different WSC components was very similar to whole shoot biomass (from which they were extracted) and WSC-free shoot biomass. Based on this close similarity, we find no indication for any additional contamination which might have occurred during WSC extraction, separation and analysis. Given absence of evidence for additional contamination of WSC, it is futile to discuss any such eventual sources, except for acknowledging the effectiveness of the protocols and the cleanliness of the laboratory work. Strikingly, contamination of respiratory CO 2 at 200 and 400 µmol mol − 1 CO 2 was also close to that of biomass and – specifically – WSC components. This observation agrees with the expectation that contamination of the respiratory substrate (specifically WSC) was the dominant factor explaining contamination of respired CO 2 at least in these treatments. It is well accepted that non-structural carbohydrates are the dominant source of substrate for dark respiration[ 32 , 60 ]. At the same time, this would also suggest that no additional contamination with extraneous CO 2 occurred during respiration measurements. This is also unsurprising given the fact that dark respiration measurements occurred during (undisturbed) isotopic steady-state for gas exchange during periods when chambers had not been opened for at least 45 min previously. Meanwhile, we cannot explain the observation that respired CO 2 was apparently uncontaminated at 800 µmol mol − 1 CO 2 , albeit this estimate was associated with relatively large uncertainty. Particularly, we have not found any chamber effects on any morpho-physiological parameters studied in the work of Baca Cabrera et al. [ 48 , 49 , 50 ], which occurred just prior to the tests which are presented here. One question not directly explored by the present analysis is whether the δ 13 C CO2 of the contaminating source was more similar to the 13 C-enriched or the 13 C-depleted CO 2 source used in this work. This question is also of interest for the accuracy of the Δ 13 C X data which can be obtained from the present data. We opine that the actual δ 13 C CO2 of the extraneous (contaminating) CO 2 was likely close to a 50:50 mix of of the 13 C-enriched and 13 C-depleted CO 2 sources: (δ 13 C CO2 − 43.5 and − 5.6‰ at the chamber inlet) both slightly 13 C-enriched 3‰ at the outlet of chambers (see Fig. 5 ): δ 13 C CO2 of contaminating CO 2 ≈ (0.5 × − 43.5‰ + 0.5 × − 5.6‰) + 3‰ = 27.6‰. This δ 13 C-value is also close to the δ 13 C of human-exhaled CO 2 (e.g. the experimenters) when based on a typical Central European, mainly C 3 -based diet [ 61 ]. Mixing of the CO 2 inside the room housing the labelling facility (in the basement of ‘Alte Akademie 12’ in Freising-Weihenstephan) with free atmospheric CO 2 (δ 13 C CO2 approx. − 9‰) was likely a very minor factor, as the volume of air in this room was continuously flushed with air from the growth chambers at a high rate. In consequence, we argue that reasonable Δ 13 C X -values can be obtained by averaging the Δ 13 C X -values from the 13 C-enriched and 13 C-depleted chambers. Although not comparable in terms of experimental purpose, system design and level of 13 C enrichment, the degree of isotopic contamination observed in the present work is comparable to that of commercial systems which are used to manufacture highly isotopically enriched compounds. Thus, for instance, closed systems [ 62 ] specially designed to produce highly isotopically enriched plant compounds with pure 13 CO 2 gas, achieved a degree of labelling of 96–98 atom-%. This would (also) correspond to an isotopic contamination (with 12 C) of approx. 2–4%. In the present work, contamination was likely dominated by extraneous CO 2 entering the growth chambers during light periods when these had to be accessed for experimental or maintenance purposes (e.g. changes of defective light sources). Unfortunately, we did not sample the 12 days-old seedlings when we started the δ 13 C CO2 treatments, so we cannot quantify the possible contribution of the experimental starting material (see Background) to the integral contamination estimate. However, if we make assumptions extrapolated from our first chamber-scale gas exchange measurements, we estimate an experimental starting material-associated contamination of not more than ~ 1% (compare also plant sizes in Figure S4). How to deal with contamination in tracer data evaluation? Of course, the best way to avoid complications with contamination is to avoid contamination altogether. As we emphasize, using air locks in chamber doors and minimizing experimental and maintenance operations inside the chambers during daytime are important contamination avoidance principles in addition to precautions already mentioned in the Discussion sections above. Concerning air locks, there may be a trade-off between their effectiveness in reducing CO 2 incursion when doors are open and the ease of access to the chamber interior that they permit (compare Figures S3A and B). While we failed to compare the effectiveness of these two versions of air locks directly, the measurements by Lehmeier et al. [ 32 ] do suggest that their airlocks provide excellent proof for their effectiveness (Figure S3B). The fact that we observed only small contamination, despite of the fact that the study was performed with a highly experimentally-perturbed system, supports our assessment that previous works which were performed with less experimentally disturbed studies in a very similar system [ 25 , 32 ] should have been affected even less by contamination. This view is supported by the absence of a CO 2 source ( 13 C enriched vs 13 C-depleted CO 2 ) effect on measurements of Δ 13 C during net CO 2 exchange in light [ 25 ]. Nevertheless, for instance, Lehmeier et al. [ 32 ] did allow for some contamination in their evaluation of the tracer kinetics of respired CO 2 when using a very similar, two-chamber system with two distinct δ 13 C CO2 . In that, they used measurements from plants which had grown continuously in the presence of 13 C enriched or 13 C-depleted CO 2 as the endmembers (δ 13 C new and δ 13 C old ) of the isotopic mixing model which they applied to the tracer data. This procedure did correct for an eventual contamination, although it used the assumption that contamination was a constant. CONCLUSIONS The aim of this work was to quantify the isotopic contamination artifact which occurred in a > 9 weeks-long experiment with continuous exposure of L. perenne plants to one of two C-isotopically distinct natural CO 2 sources, one a 13 C-depleted fossil-organic source and the other a (relatively) 13 C enriched mineral source, at one of three [CO 2 ]-levels: 200, 400 or 800 µmol mol − 1 CO 2 in plant growth chambers. The experiments provided an elevated opportunity for contamination due to extensive experimental activities in all chambers during the last two weeks just prior to determination of contamination. Nevertheless, the findings indicated only a low level of contamination (3.3% on average) for biomass and WSC fractions, with no significant effect of [CO 2 ] on contamination. Thus, our work supports the use of the present 13 CO 2 / 12 CO 2 system for quantitative C tracer experiments of plant metabolism across contrasts of [CO 2 ]. Contamination avoidance principles used (and discussed) here should also be adopted in simpler tracer systems (e.g. one-chamber systems with or without inclusion of CF-IRMS or other online gas isotope analysers) in controlled or field environments [ 21 , 31 ]. Declarations Ethics approval and consent to participate Not applicable (the study involved no animals and no human participants, human data or human tissue) Consent for publication Not applicable Availability of data and materials All data supporting the findings are original and included in the manuscript. The datasets used and/or analysed during the current study are available from the corresponding authors on reasonable request. Competing interests The authors declare that they have no competing interests. Funding Deutsche Forschungsgemeinschaft (DFG SCHN 557/9‐1) Authors‘ contributions HS and RTH acquired funding of the project. JZ, RS and HS conceived the idea of the study. JZ, RS, JCBC and RTH performed the work. 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Supplementary Files ZhuetalSupplementalInformation20250527.pdf Cite Share Download PDF Status: Published Journal Publication published 11 Aug, 2025 Read the published version in Plant Methods → Version 1 posted Editorial decision: Revision requested 21 Jul, 2025 Reviews received at journal 19 Jul, 2025 Reviews received at journal 12 Jul, 2025 Reviewers agreed at journal 12 Jul, 2025 Reviewers agreed at journal 26 Jun, 2025 Reviewers agreed at journal 08 Jun, 2025 Reviewers invited by journal 02 Jun, 2025 Editor assigned by journal 30 May, 2025 Submission checks completed at journal 30 May, 2025 First submitted to journal 27 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6759212","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Method Article","associatedPublications":[],"authors":[{"id":465503496,"identity":"dd5bb5c1-add3-4313-ba6b-60a42e5a8b01","order_by":0,"name":"Jianjun Zhu","email":"","orcid":"","institution":"Technische Universität München","correspondingAuthor":false,"prefix":"","firstName":"Jianjun","middleName":"","lastName":"Zhu","suffix":""},{"id":465503497,"identity":"1c2b689b-6b16-4e5a-967f-ab1745252ee1","order_by":1,"name":"Regina T. Hirl","email":"","orcid":"","institution":"Technische Universität München","correspondingAuthor":false,"prefix":"","firstName":"Regina","middleName":"T.","lastName":"Hirl","suffix":""},{"id":465503498,"identity":"076ce2b3-90da-4c65-99e4-fa864cf96b94","order_by":2,"name":"Juan C. Baca Cabrera","email":"","orcid":"","institution":"Forschungszentrum Jülich GmbH","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"C. Baca","lastName":"Cabrera","suffix":""},{"id":465503499,"identity":"a4aab67e-26d4-4a16-8a1e-1b36ba3c268b","order_by":3,"name":"Rudi Schäufele","email":"","orcid":"","institution":"Technische Universität München","correspondingAuthor":false,"prefix":"","firstName":"Rudi","middleName":"","lastName":"Schäufele","suffix":""},{"id":465503502,"identity":"1852cf19-8859-49ab-b0e7-5200b35b751e","order_by":4,"name":"Hans Schnyder","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtklEQVRIiWNgGAWjYFACHiBmY2DgB3PYSNEi2UayFoNjxGqRbz977DFPmU2+8f0e0w0MZTaEtRicyUs35jmXZrntGI/ZDYZzaURokeAxk+ZtO2xgBtLC2HaYCIfNAGv5b2DcBtbyn7AWhhtgLQcMDNjAWg4Q4bAzOWaSc84lG0gcSyu7kXAumQiHtZ8xk3hTZmfA33x4240PZXZEOAwImHhgrATiNDAwMP4gVuUoGAWjYBSMTAAAMgAzENinj3QAAAAASUVORK5CYII=","orcid":"","institution":"Technische Universität München","correspondingAuthor":true,"prefix":"","firstName":"Hans","middleName":"","lastName":"Schnyder","suffix":""}],"badges":[],"createdAt":"2025-05-27 12:08:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6759212/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6759212/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13007-025-01431-3","type":"published","date":"2025-08-11T15:57:54+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83942874,"identity":"5f78b3f8-6959-4cd3-b226-1fd5db5c3c7b","added_by":"auto","created_at":"2025-06-04 19:14:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82395,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic diagram of the \u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eCO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e/\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eCO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2 \u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003elabelling and gas exchange system.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCOMP, screw compressor (S40, Boge, Bielefeld, Germany); F1, oil and water condensate drain (CSP005; Hiross, Mönchengladbach, Germany); F2, oil, water and particle filter (≥0.01 µm; G12XD, with filter element 2030X, Zander); AD, adsorption dryer (KEN 3100 TE; Zander, Essen, Germany) and molecular sieve: activated aluminium oxide F200; Alcoa,\u003c/p\u003e\n\u003cp\u003eHouston, TX, USA); F3, universal filter (≥1 µm; G12ZHD and filter element: 2030Z, Zander); AR, air receiver (1 m\u003csup\u003e3\u003c/sup\u003e) (Magnet Kft, Magocs, Hungary); E and D, cylinders with \u003csup\u003e13\u003c/sup\u003eC-depleted (fossil) and -enriched (mineral)\u0026nbsp; CO\u003csub\u003e2\u003c/sub\u003e\u0026nbsp; from Linde AG (Unterschleissheim, Germany) and CARBO Kohlensäurewerke (Bad Hönningen, Germany); S, CO\u003csub\u003e2\u003c/sub\u003e source unit for mineral and fossil-organic CO\u003csub\u003e2\u003c/sub\u003e (DMP Ltd, Fehraltdorf, Switzerland); MFC CO\u003csub\u003e2\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e mass flow controller (Red-y, Vögtlin, Muttenz, Switzerland, max 1 SLPM); MFC air, mass flow controller for CO\u003csub\u003e2\u003c/sub\u003e free air (EL-FLOW, Bronkhorst, Veenendaal, Netherlands; 1000 SLPM); GC 1-4, growth chambers (PGR15; Conviron, Winnipeg, Canada); SAS, sample air selector (DMP Ltd, Fehraltdorf, Switzerland); IRGA, CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO infrared gas analyser (Li-840, Li-Cor Inc., Lincoln, NE, USA); CF-IRMS, continuous-flow \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e isotope ratio mass spectrometer (Delta plus; Finnigan MAT, Bremen, Germany). For simplicity, a number of auxillary components of the facility are not included in the figure (but see text).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6759212/v1/cbf2a6227bc1520b33a5950b.png"},{"id":83942867,"identity":"2bbe1f1f-6510-4aad-93ab-24f420e9a083","added_by":"auto","created_at":"2025-06-04 19:14:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":255042,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConcentration (a - f) and δ\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eC (g - l) of CO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e inside growth chambers during one light period.\u003c/strong\u003e Growth chambers were supplied with target [CO\u003csub\u003e2\u003c/sub\u003e] of 200 (a, d, g and j), 400 (b, e, h and k), or 800 (c, f, i and l) mmol\u0026nbsp;mol\u003csup\u003e-1\u003c/sup\u003e with either \u003csup\u003e13\u003c/sup\u003eC-depleted CO\u003csub\u003e2\u003c/sub\u003e (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e -43.5‰) ( a, b, c, g, h, and i) or \u003csup\u003e13\u003c/sup\u003eC-enriched CO\u003csub\u003e2\u003c/sub\u003e (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e -5.6‰; right) ( d, e, f, j, k, and l). Open circles denote measurements at the chamber outlet, and closed circles at the chamber inlet. Vertical arrows indicate chamber door openings during sampling activities on day 49. Data points represent individual measurements.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6759212/v1/f51163a61d96b1f1ff7934e9.png"},{"id":83942866,"identity":"bd8db01b-65c3-4e35-a620-e6018466d6e0","added_by":"auto","created_at":"2025-06-04 19:14:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":72791,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTypical HLPC elution diagram for water-soluble carbohydrates (WSC) extracted from whole shoot biomass of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eLolium perenne\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e The fractions corresponding to fructan, sucrose, glucose and fructose are indicated in the panel. Note the two small peaks on the lefthand side of the sucrose peak, which likely corresponded (from right to left) to fructan tri-saccharides and tetra-saccharides. The thin grey line represents the baseline. The total elution time was about 90 minutes following sample injection. The sample was taken from plants grown in 800 μmol mol\u003csup\u003e-1\u003c/sup\u003e [CO\u003csub\u003e2\u003c/sub\u003e].\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6759212/v1/b4c1e43c712af44bdd4688f5.png"},{"id":83943315,"identity":"85b7e3dc-0b63-4826-90bc-f9a8045d0bb9","added_by":"auto","created_at":"2025-06-04 19:30:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":171247,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e concentration difference between chamber outlet ([CO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e]\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eoutlet\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e) and the set target [CO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e] ([CO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e]\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003etarget\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e)\u003c/strong\u003e between day 20 and 65 in experimental runs with target [CO\u003csub\u003e2\u003c/sub\u003e] of: (a, b) 200, (c, d) 400 and (e, f) 800 mmol\u0026nbsp;mol\u003csup\u003e-1\u003c/sup\u003e. Growth chambers were supplied with either \u003csup\u003e13\u003c/sup\u003eC-depleted CO\u003csub\u003e2\u003c/sub\u003e (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e -43.5‰) (panels a, c and e) or \u003csup\u003e13\u003c/sup\u003eC-enriched CO\u003csub\u003e2\u003c/sub\u003e (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e -5.6‰; right) (panels b, d, f). Measurements taken during the first 45 min of the light period, or following the opening of the chamber, or exceeding 1.5 times the interquartile range (outliers) were eliminated from the data set. Data points and error bars represent daily means ±SD (\u003cem\u003en \u003c/em\u003e= 9-23).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6759212/v1/b2e07cb22a651355526fa1ac.png"},{"id":83942929,"identity":"0778d5a3-b95e-47ad-b18e-f83909b293df","added_by":"auto","created_at":"2025-06-04 19:22:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":127436,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe δ\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eC-difference between CO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e measured at the chamber outlet (δ\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eCO2 outlet\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e) and inlet (δ\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eCO2 inlet\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e) over time (δ\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eCO2 outlet \u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e- δ\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eCO2 inlet\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e). \u003c/strong\u003eCO\u003csub\u003e2\u003c/sub\u003e concentration at chamber outlet ([CO\u003csub\u003e2\u003c/sub\u003e]\u003csub\u003eoutlet\u003c/sub\u003e) was maintained near target [CO\u003csub\u003e2\u003c/sub\u003e]: 200 (a, b), 400 (c, d) and 800 (e, f) mmol\u0026nbsp;mol\u003csup\u003e-1\u003c/sup\u003e (see Figure 4). Growth chambers were supplied with either \u003csup\u003e13\u003c/sup\u003eC-depleted (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e -43.5‰; panels a, c and e) or \u003csup\u003e13\u003c/sup\u003eC-enriched CO\u003csub\u003e2\u003c/sub\u003e (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e -5.6‰; b, d and f). Measurements taken during the first 45 min of the light period, or following the opening of the chamber, or exceeding 1.5 times the interquartile range (outliers) were eliminated from the data set. Data points and error bars represent daily means ± SD (\u003cem\u003en \u003c/em\u003e= 9-23).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6759212/v1/0e4bb460c7795914ca7773a1.png"},{"id":83942869,"identity":"a072ac6d-8b1f-4e69-acbd-a07533036b09","added_by":"auto","created_at":"2025-06-04 19:14:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":39289,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSensitivity of contamination-% (\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ef\u003c/strong\u003e\u003c/em\u003e\u003csub\u003e\u003cstrong\u003econtam\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, %) estimates to assumptions of D\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eC\u003c/strong\u003e in the range of 18 to 24‰. The analysis was based on an arbitrary sample with an estimated \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam \u003c/sub\u003eof 4.05% at D\u003csup\u003e13\u003c/sup\u003eC = 21‰ (see Materials and Methods).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6759212/v1/df054de770e58bb631650078.png"},{"id":89310690,"identity":"389b3169-ea65-4f86-b411-b93ddde19103","added_by":"auto","created_at":"2025-08-18 16:09:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2444061,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6759212/v1/b6f5f880-2bdf-487f-b5ef-0d3aa76c11e7.pdf"},{"id":83942875,"identity":"bd566c35-d5d3-476a-9f3a-e0f40c5dc86e","added_by":"auto","created_at":"2025-06-04 19:14:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":5752730,"visible":true,"origin":"","legend":"","description":"","filename":"ZhuetalSupplementalInformation20250527.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6759212/v1/0d8e44cefa7a0ef64a55ffdf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAssessing and avoiding C isotopic contamination artefacts in mesocosm-scale \u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eCO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e/\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eCO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e labelling systems:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003efrom biomass components to purified carbohydrates and dark respiration\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eIsotopic labelling of the carbon (C) in CO\u003csub\u003e2\u003c/sub\u003e supplied to photosynthesizing organisms is a unique and powerful method for investigating C fluxes in central metabolism, transport, allocation and partitioning of photosynthetic products from the organelle (chloroplast) to the ecosystem scale [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Multiple different techniques, including pulse-chase and dynamic labelling (\u003cem\u003esensu\u003c/em\u003e Ratcliffe \u0026amp; Shachar-Hill [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]; or synonymous \u0026lsquo;steady-state\u0026rsquo; or \u0026lsquo;continuous\u0026rsquo; labelling [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]) with different C isotopes (\u003csup\u003e11\u003c/sup\u003eC, \u003csup\u003e13\u003c/sup\u003eC or \u003csup\u003e14\u003c/sup\u003eC) have been designed and applied to different aspects of the analysis of C fluxes in plants [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. One such method is especially useful for long-term (hours- to months-long) labelling at large scales, with large numbers of plants in controlled environments, and uses inexpensive and harmless near-natural abundance \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e mixtures [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These are derived from \u003csup\u003e13\u003c/sup\u003eC-depleted fossil-organic or (relatively) \u003csup\u003e13\u003c/sup\u003eC-enriched mineral sources and thus termed \u0026lsquo;fossil-organic\u0026rsquo; or \u0026lsquo;mineral CO\u003csub\u003e2\u003c/sub\u003e\u0026rsquo;. This technique has proven useful for the determination of functional components of CO\u003csub\u003e2\u003c/sub\u003e fluxes, such as dark respiration in light [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], distinction of autotrophic and heterotrophic ecosystem respiration [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and quantification of the labelling kinetics of metabolic and storage substrate pools supplying sink tissue [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] or dark respiration of shoots and roots [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Further, such tracer studies have enabled analysis of C fluxes in central carbohydrate metabolism of source leaves and of the function and importance of assimilate stores (or reserves) in supplying substrate to growth or respiration by compartmental models at organ, plant and ecosystem scale [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA special variant of this labelling strategy \u0026ndash; particularly useful for exploring contamination artefacts (as we show here) \u0026ndash; uses two parallel identical growth chambers with the same plant material grown in the same conditions except for the C isotopic composition (δ\u003csup\u003e13\u003c/sup\u003eC, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) of the CO\u003csub\u003e2\u003c/sub\u003e (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e) supplied to the chambers. In our laboratory, such a system is directly connected with a continuous-flow stable isotope ratio mass spectrometer (CF-IRMS) which permits quasi-continuous monitoring of δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e at the chamber inlet and outlet of the air stream passing through the chambers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As air is ventilated strongly inside the chambers, the δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e at the chamber outlet reflects that inside the chamber [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] as in leaf cuvettes [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn nature, as well as in the labelling system, the δ\u003csup\u003e13\u003c/sup\u003eC of plant biomass is generally \u003csup\u003e13\u003c/sup\u003eC-depleted relative to CO\u003csub\u003e2\u003c/sub\u003e because of \u003csup\u003e13\u003c/sup\u003eC discrimination (Δ\u003csup\u003e13\u003c/sup\u003eC) in photosynthesis [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], possibly modified further to a smaller degree by post-photosynthetic fractionation effects [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. According to Farquhar et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], δ\u003csup\u003e13\u003c/sup\u003eC of a given plant sample \u003cem\u003eX\u003c/em\u003e (tissue or compound) is related to δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e as\u003c/p\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e = (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e \u0026ndash; Δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e) / (1\u0026thinsp;+\u0026thinsp;Δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e), (1)\u003c/p\u003e \u003cp\u003ewith Δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e representing the sample-specific Δ\u003csup\u003e13\u003c/sup\u003eC (which integrates both photosynthetic and eventual post-photosynthetic effects). Although Δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e can vary as a function of environmental conditions [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], it is theoretically independent of the isotopic composition of CO\u003csub\u003e2\u003c/sub\u003e [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and, hence, must be the same when plants are grown in identical conditions with different δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDefinition of symbols, and specifications\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymbol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecification\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefined as δ\u003csup\u003e13\u003c/sup\u003eC = (\u003cem\u003eR\u003c/em\u003e\u003csub\u003eP\u003c/sub\u003e/\u003cem\u003eR\u003c/em\u003e\u003csub\u003eS\u003c/sub\u003e \u0026ndash; 1) \u0026times; 1000, with \u003cem\u003eR\u003c/em\u003e the molar abundance ratio \u003csup\u003e13\u003c/sup\u003eC/\u003csup\u003e12\u003c/sup\u003eC, and \u003cem\u003eP\u003c/em\u003e referring to the sample and \u003cem\u003eS\u003c/em\u003e to the international Vienna-Pee Dee Belemnite (V-PDB) standard (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarquhar et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC of CO\u003csub\u003e2\u003c/sub\u003e (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHere we used CO\u003csub\u003e2\u003c/sub\u003e of mineral\u003c/p\u003e \u003cp\u003e(δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e ~\u0026ndash;5.6\u0026permil;) and fossil-organic origin (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e ~\u0026ndash;43.5\u0026permil;) to supply parallel growth chambers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003einlet\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC of CO\u003csub\u003e2\u003c/sub\u003e at the inlet of a growth chamber (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeasured\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC of CO\u003csub\u003e2\u003c/sub\u003e at the outlet of a growth chamber (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeasured\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet pure\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC of uncontaminated CO\u003csub\u003e2\u003c/sub\u003e at the outlet of a growth chamber (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalculated as:\u003c/p\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet pure\u003c/sub\u003e = (Δ\u003csup\u003e13\u003c/sup\u003eC\u0026thinsp;+\u0026thinsp;ξ δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003einlet\u003c/sub\u003e Δ\u003csup\u003e13\u003c/sup\u003eC/1000\u0026thinsp;+\u0026thinsp;ξ δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003einlet\u003c/sub\u003e)/( Δ\u003csup\u003e13\u003c/sup\u003eC/1000 ( ξ \u0026ndash; 1) + ξ),\u003c/p\u003e \u003cp\u003ewith Δ\u003csup\u003e13\u003c/sup\u003eC fixed at 21\u0026permil;\u003c/p\u003e\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC of sample \u003cem\u003eX\u003c/em\u003e (\u0026permil;), with X referring to net photosynthesis, dark respiration, biomass, or WSC in the form of fructan, sucrose, glucose or fructose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeasured\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eWSC\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC of water-soluble carbohydrates (WSC) (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeasured\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eWSC\u0026minus;free biomass\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC of WSC-free biomass (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalculated as\u003c/p\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eWSC\u0026minus;free biomass\u003c/sub\u003e = (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003ebiomass\u003c/sub\u003e \u0026times; \u003cem\u003eW\u003c/em\u003e\u003csub\u003ebiomass\u003c/sub\u003e \u0026ndash; δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eWSC\u003c/sub\u003e \u0026times; \u003cem\u003eW\u003c/em\u003e\u003csub\u003eWSC\u003c/sub\u003e)/(\u003cem\u003eW\u003c/em\u003e\u003csub\u003ebiomass\u003c/sub\u003e \u0026ndash; \u003cem\u003eW\u003c/em\u003e\u003csub\u003eWSC\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC-difference between samples of the same kind (net photosynthesis, dark respiration, biomass, or WSC, in the form of fructan, sucrose, glucose or fructose) collected simultaneously from parallel chambers supplied with CO\u003csub\u003e2\u003c/sub\u003e of contrasting δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBased on measurements\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC of uncontaminated (pure) reference (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalculated as\u003c/p\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e = (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003einlet\u003c/sub\u003e \u0026times; \u003cem\u003eF\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u0026ndash; δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet pure\u003c/sub\u003e \u0026times; \u003cem\u003eF\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e) / (\u003cem\u003eF\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u0026ndash; \u003cem\u003eF\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eδ\u003csup\u003e13\u003c/sup\u003eC-difference between uncontaminated (pure) references from parallel chambers supplied with CO\u003csub\u003e2\u003c/sub\u003e of contrasting δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBased on calculations of δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e for \u0026lsquo;samples\u0026rsquo; collected simultaneously from parallel chambers supplied with contrasting δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam X\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFraction of contaminating C in sample \u003cem\u003eX\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalculated as\u003c/p\u003e \u003cp\u003e1 \u0026ndash; dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e /dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔ\u003csup\u003e13\u003c/sup\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbon isotope discrimination (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarquhar et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e],\u003c/p\u003e \u003cp\u003ehere set to 21\u0026permil; in estimations of δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbon isotope discrimination as expressed in sample \u003cem\u003eX\u003c/em\u003e (\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBased on measurements, and calculated as\u003c/p\u003e \u003cp\u003eΔ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e = (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet\u003c/sub\u003e \u0026ndash; δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e)/(1\u0026thinsp;+\u0026thinsp;δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e/1000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eξ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRatio of the rate of CO\u003csub\u003e2\u003c/sub\u003e entry into a growth chamber relative to the net rate of CO\u003csub\u003e2\u003c/sub\u003e uptake (net photosynthesis)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAfter Evans et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eCalculated as\u003c/p\u003e \u003cp\u003eξ\u0026thinsp;=\u0026thinsp;\u003cem\u003eC\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u003cem\u003e/\u003c/em\u003e (\u003cem\u003eC\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u0026ndash; \u003cem\u003eC\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e[CO\u003csub\u003e2\u003c/sub\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e concentration in air (\u0026micro;mol\u0026nbsp;mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e concentration in air at the inlet of the growth chamber (\u0026micro;mol\u0026nbsp;mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeasured\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e concentration in air at the outlet of the growth chamber (\u0026micro;mol\u0026nbsp;mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeasured\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFlux of CO\u003csub\u003e2\u003c/sub\u003e entering a growth chamber (\u0026micro;mol\u0026nbsp;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBased on measurements\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFlux of CO\u003csub\u003e2\u003c/sub\u003e leaving a growth chamber (\u0026micro;mol\u0026nbsp;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBased on measurements\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGround area of a growth chamber (m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNet CO\u003csub\u003e2\u003c/sub\u003e exchange rate in light, i.e. whole-stand net photosynthesis rate (\u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e = (\u003cem\u003eF\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u0026ndash; \u003cem\u003eF\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e) / \u003cem\u003eA\u003c/em\u003e, during daytime\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csub\u003en\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhole-stand respiration rate in the dark (\u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csub\u003en\u003c/sub\u003e = (\u003cem\u003eF\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u0026ndash; \u003cem\u003eF\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e) / \u003cem\u003eA\u003c/em\u003e, during nighttime\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eW\u003c/em\u003e\u003csub\u003ebiomass\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC mass of a certain biomass sample (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeasured\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eW\u003c/em\u003e\u003csub\u003eWSC\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC mass of WSC in a certain sample (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBased on measurements and the mass fraction of C in different forms of water-soluble carbohydrates (fructan\u0026thinsp;~\u0026thinsp;0.44, sucrose 0.42, glucose and fructose 0.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDesignation of samples of a given kind collected simultaneously from parallel chambers supplied with contrasting CO\u003csub\u003e2\u003c/sub\u003e; may refer to dark respiration, biomass, or WSC (fructan, sucrose, glucose, fructose)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHere, CO\u003csub\u003e2\u003c/sub\u003e of mineral (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e ~ \u0026minus;\u0026thinsp;5.6\u0026permil;) or fossil-organic (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e ~\u0026ndash;43.5\u0026permil;) origin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTherefore, when established in the above two-chamber system, the δ\u003csup\u003e13\u003c/sup\u003eC of an uncontaminated (pure) plant C sample (termed δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e) which is synthesized completely from photosynthetic CO\u003csub\u003e2\u003c/sub\u003e uptake of a certain CO\u003csub\u003e2\u003c/sub\u003e source is expected to accord with Eq.\u0026nbsp;1 independently of the δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e of the source CO\u003csub\u003e2\u003c/sub\u003e. Accordingly \u0026ndash; and again in artefact-free conditions and steady-state \u0026ndash; the δ\u003csup\u003e13\u003c/sup\u003eC-difference (dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e) between chambers supplied with \u003csup\u003e13\u003c/sup\u003eC-enriched (mineral) and \u003csup\u003e13\u003c/sup\u003eC-depleted (fossil) CO\u003csub\u003e2\u003c/sub\u003e should be identical to that predicted using Eq.\u0026nbsp;1. Any C contamination of an actual sample \u003cem\u003eX\u003c/em\u003e would cause a (contamination-weighted) decrease of dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX actual\u003c/sub\u003e relative to dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e (i.e. dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX actual\u003c/sub\u003e \u0026lt; dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e). In the extreme, where dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e=0, the sample \u003cem\u003eX\u003c/em\u003e is fully independent of the different δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e used, i.e. is completely contaminated. Accordingly, the fraction of contaminating C in a certain sample \u003cem\u003eX\u003c/em\u003e (\u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam X\u003c/sub\u003e) can be defined as:\u003c/p\u003e \u003cp\u003e \u003cem\u003ef\u003c/em\u003e \u003csub\u003econtam X\u003c/sub\u003e = 1 \u0026ndash; dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX actual\u003c/sub\u003e / dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e. (2)\u003c/p\u003e \u003cp\u003e \u003cem\u003eCeteris paribus\u003c/em\u003e, a given contaminating C source has the same δ\u003csup\u003e13\u003c/sup\u003eC and adds the same quantity of C to a certain sample \u003cem\u003eX\u003c/em\u003e collected from the parallel chambers which are fed with different δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e. This is true especially, if the parallel chambers are operated simultaneously, are housed in the same room, and sample collection and processing uses identical protocols (as was the case in this work). Putative contaminating C sources are many, and include (1) free atmospheric CO\u003csub\u003e2\u003c/sub\u003e (which has a δ\u003csup\u003e13\u003c/sup\u003eC of approx. \u0026minus;\u0026thinsp;9\u0026permil; at present [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]), (2) CO\u003csub\u003e2\u003c/sub\u003e exhaled by people (e.g. experimenters; \u0026minus;\u0026thinsp;17 and \u0026minus;\u0026thinsp;25\u0026permil; [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]), and (3) cross-contamination with the different labelling CO\u003csub\u003e2\u003c/sub\u003es [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Further, (4) contamination with organic C compounds might occur during sample collection or processing [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. In the context, also (5) seed biomass-C (or biomass of any type of experimental starting material, e.g. vegetative cuttings or seedlings) \u0026lsquo;qualifies\u0026rsquo; as a contaminant, as it shares the same δ\u003csup\u003e13\u003c/sup\u003eC in the different labelling chambers. Perhaps most importantly, in climate change experiments, the likelihood and extent of contamination could perhaps depend on the atmospheric CO\u003csub\u003e2\u003c/sub\u003e concentration, [CO\u003csub\u003e2\u003c/sub\u003e], which is used in the experiments. This would cause a [CO\u003csub\u003e2\u003c/sub\u003e]-dependent experimental artefact and bias conclusions, if unnoted or uncorrected. As far as we know, there have been no systematic, comprehensive analyses of contamination artefacts in large- or stand-scale, long-term C labelling studies (but see Gong et al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]). Particularly, we know of no such methodological study under sub-ambient or elevated [CO\u003csub\u003e2\u003c/sub\u003e] conditions.\u003c/p\u003e \u003cp\u003eIn this work, we ask: How does [CO\u003csub\u003e2\u003c/sub\u003e] affect C contamination (\u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e) of a range of parameters that are of interest in labelling studies, including biomass fractions (shoot and root), non-structural carbohydrate components (water-soluble carbohydrates (WSC): fructan, sucrose, glucose, fructose) and dark respiration? In addition, we perform a sensitivity analysis of C isotope discrimination (Δ\u003csup\u003e13\u003c/sup\u003eC) assumptions on the estimates of contamination. At the outset, we provide a description of the custom-made labelling facility used here. The work was performed with stands of \u003cem\u003eLolium perenne\u003c/em\u003e (perennial ryegrass, C\u003csub\u003e3\u003c/sub\u003e) established from 12 days-old seedlings grown in parallel growth chambers under identical conditions with contrasting δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e (i.e. δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e of \u0026minus;\u0026thinsp;43.5\u0026permil; or \u0026minus;\u0026thinsp;5.6\u0026permil;) at 200, 400 or 800 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e, approximating Last Glacial Maximum, current ambient, or predicted end-of-the 21st century [CO\u003csub\u003e2\u003c/sub\u003e] levels [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Biomass samples for contamination analysis were collected immediately after the terminal, two weeks-long experimental period in which the labelling vessels (growth chambers) had to be accessed frequently for plant sampling or non-destructive measurements [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These perturbations provided a special opportunity for contaminations of the chamber atmospheres with extraneous CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eMesocosm-scale \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e gas exchange and labelling system\u003c/h2\u003e\n \u003cp\u003eThe \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e gas exchange and labelling facility corresponded to a modernized and upgraded version of the system originally described by Schnyder et al. [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. The facility was composed of four main modules (Figs. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, S1 and S2): (1) a screw compressor and adsorption dryer which generated CO\u003csub\u003e2\u003c/sub\u003e-free air, (2) a gas mixing system which controlled the addition of CO\u003csub\u003e2\u003c/sub\u003e to CO\u003csub\u003e2\u003c/sub\u003e-free air and supplied air with known \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e and [CO\u003csub\u003e2\u003c/sub\u003e] at an individually set rate for both air flow and [CO\u003csub\u003e2\u003c/sub\u003e] to each labelling vessel, (3) four plant growth chambers, which served as the labelling vessels, and (4) a gas analysis unit, comprising a sample air selector, an infrared CO\u003csub\u003e2\u003c/sub\u003e gas analyzer (IRGA) and a continuous flow \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e IRMS, which analyzed in sequence the [CO\u003csub\u003e2\u003c/sub\u003e] and \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e of sample gas collected at the inlet and outlet of each chamber.\u003c/p\u003e\n \u003cp\u003eSpecifically, the four growth chambers served as open-system, mesocosm-scale gas exchange cuvettes, each having a 1.5 m\u003csup\u003e2\u003c/sup\u003e plant growth area and equipped with a microprocessor controller and environmental data acquisition system. All air supply to a growth chamber was provided by a dedicated gas mixing station which consisted of two computer-controlled mass flow controllers (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) which regulated the mixing of CO\u003csub\u003e2\u003c/sub\u003e with known \u0026delta;\u003csup\u003e13\u003c/sup\u003eC (0\u0026ndash;1 standard liter per minute, SLPM) and CO\u003csub\u003e2\u003c/sub\u003e-free air (0\u0026ndash;1000 SLPM). Dry CO\u003csub\u003e2\u003c/sub\u003e-free air was obtained with a self-regenerating adsorption dryer at up to 180 m\u003csup\u003e3\u003c/sup\u003e h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at ambient atmospheric pressure. The dryer was fed with compressed air (approx. 7 MPa) by a screw compressor \u003cem\u003evia\u003c/em\u003e an oil and water condensate drain and filters as shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Commercially available CO\u003csub\u003e2\u003c/sub\u003e of known \u0026delta;\u003csup\u003e13\u003c/sup\u003eC was supplied from cylinders (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Typically, rates of air supply to individual chambers ranged between 250 and 750 SLPM. Thus, with an internal chamber volume of approx. 3000 L, air flow through a chamber was equal to 5\u0026ndash;15 times the chamber volume per hour. Accordingly, the mean residence time of CO\u003csub\u003e2\u003c/sub\u003e in the chamber was 4\u0026ndash;12 min. Sample air was collected at the inlet and outlet of each growth chamber and continuously pumped to the computer-controlled sample air selector (SAS) at a rate of approx. 2 L min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. During simultaneous operation of all chambers the SAS sequentially sampled each sample air line (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8; Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) at approx. 3 minutes-intervals. Sample air was split to serve the IRGA and CF-IRMS in parallel. Gas lines between the SAS and CF-IRMS and IRGA were flushed with sample air for 3 min before taking IRGA readings of CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO concentration and measurement of \u0026delta;\u003csup\u003e13\u003c/sup\u003eC by the CF-IRMS. The CF-IRMS was interfaced with the sample air selector \u003cem\u003evia\u003c/em\u003e a steel capillary tube (1 mm i.d.), a eight-port, two-position valve (Valco Instruments Co. Inc., Houston, TX, USA), dryer (Nafion\u0026reg;), gas chromatograph (25 m \u0026times; 0.32 mm Poraplot Q; Chrompack, Middelburg, Netherlands) and open split. These components all formed part of a custom-made interface (Gasbench II; ThermoFinnigan, Bremen, Germany). Sample air for the CF-IRMS was pumped continuously through the steel capillary feeding the Valco valve and a 0.25 mL sample loop attached to it. After a 90 sec flushing period, the content of the sample loop was swept with helium carrier gas through the interface, where water vapor was removed by the Nafion trap and CO\u003csub\u003e2\u003c/sub\u003e was separated from other sample air gases in a GC column. Finally, the CO\u003csub\u003e2\u003c/sub\u003e was introduced directly into the ion source of the IRMS via a glass capillary (0.1 mm i.d.) connected to the interface by an open split. After another 90 sec, shortly before the sample air selector switched to the next sample air line, a second sample of the same air was taken. Thus, within 3 min, each inlet/outlet was measured in duplicate. After every second sample, a VPDB-gauged CO\u003csub\u003e2\u003c/sub\u003e reference gas was injected into the CF-RMS \u003cem\u003evia\u003c/em\u003e the open split. A full measurement cycle, including one set of measurements (concentrations of CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO, and \u0026delta;\u003csup\u003e13\u003c/sup\u003eC of CO\u003csub\u003e2\u003c/sub\u003e) on the inlet and outlet of each growth chamber, was completed within less than 30 min. The long-term precision (SD) for repeated measurements at the chamber inlet was \u0026lt;\u0026thinsp;0.20\u0026permil;.\u003c/p\u003e\n \u003cp\u003eEmpty chamber tests performed before every experiment confirmed that gas lines throughout the air supply systems of the chambers were virtually leak-free based on measurements with CO\u003csub\u003e2\u003c/sub\u003e free air generated by the adsorption dryer and CF-IRMS based measurement of the peak size (observed peak area corresponded to a CO\u003csub\u003e2\u003c/sub\u003e concentration of \u0026lt;\u0026thinsp;\u0026lt;\u0026thinsp;0.5 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) of mass 44, i.e. \u003csup\u003e12\u003c/sup\u003eC\u003csup\u003e16\u003c/sup\u003eO\u003csub\u003e2,\u003c/sub\u003e at the chamber inlet. The same was true for measurements at the chamber outlet, when the flow rate of CO\u003csub\u003e2\u003c/sub\u003e-free air was maintained at \u0026gt;\u0026thinsp;250 SLPM, as was routinely the case in experiments.\u003c/p\u003e\n \u003cp\u003eIndividual CO\u003csub\u003e2\u003c/sub\u003e cylinders contained approx. 30 kg of CO\u003csub\u003e2\u003c/sub\u003e, and more than one cylinder had to be used in experiments of long duration (\u0026gt;\u0026thinsp;4 weeks). For this reason, we examined batches of CO\u003csub\u003e2\u003c/sub\u003e cylinders for uniformity of their \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e. Typically, the \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e was quite similar (\u0026lt;\u0026thinsp;0.27\u0026permil; SD) between cylinders of the same type (mineral or fossil-organic CO\u003csub\u003e2\u003c/sub\u003e) within a batch.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003ePlant material and growth conditions\u003c/h3\u003e\n\u003cp\u003eThe details for the plant material and growth conditions used in this study have been presented before [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e]. In short, plants of \u003cem\u003eLolium perenne\u003c/em\u003e were established and grown singly in individual plastic pots (350 mm height, 50 mm diameter) filled with 800 g of washed quartz sand (0.3\u0026ndash;0.8 mm grain size). Pots were arranged at a density of 383 plants m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e in plastic containers (770 \u0026times; 560 \u0026times; 300 mm), and two of such containers placed in each growth chamber. Plants were supplied four times a day with a Hoagland-type nutrient solution with reduced nitrate-N content [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]. Light was supplied by cool-white, fluorescent tubes and warm-white, light-emitting diode (LED) bulbs with a constant photosynthetic photon flux density (PPFD) of 800 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at plant height during the 16 h-long light period [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]. Temperature was controlled at 20\u0026deg;C/16\u0026deg;C and relative humidity (RH) at 50%/75% during the light/dark periods. Importantly, we observed no chamber effects on any measured parameter in the studies of Baca Cabrera et al. [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003e[CO] treatments and sequence of experimental activities and sampling\u003c/h3\u003e\n\u003cp\u003e[CO\u003csub\u003e2\u003c/sub\u003e] treatments were installed when seedlings were 12 days old following seed imbibition. In each of two experimental runs chamber air was controlled near the target CO\u003csub\u003e2\u003c/sub\u003e concentration ([CO\u003csub\u003e2\u003c/sub\u003e] of 200, 400 or 800 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e] with two chambers per [CO\u003csub\u003e2\u003c/sub\u003e] treatment. In that, one chamber was supplied with \u003csup\u003e13\u003c/sup\u003eC-enriched (mineral) CO\u003csub\u003e2\u003c/sub\u003e and the other with \u003csup\u003e13\u003c/sup\u003eC-depleted (fossil-organic) CO\u003csub\u003e2\u003c/sub\u003e. Maintenance of [CO\u003csub\u003e2\u003c/sub\u003e] near target values throughout the experiment \u0026ndash; from 12 days-old seedlings to closed stands and beyond \u0026ndash; required periodic adjustments of airflow and [CO\u003csub\u003e2\u003c/sub\u003e] at the chamber inlet. This was done in such a way that the (photosynthetic) drawdown of [CO\u003csub\u003e2\u003c/sub\u003e] inside the chambers did not exceed 14%. Quasi-continuous \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e measurements at the inlet and outlet of chambers were performed from day 20 to at least day 65.\u003c/p\u003e\n\u003cp\u003eDisturbance of the [CO\u003csub\u003e2\u003c/sub\u003e] and \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e in the chambers was minimized by maintaining a small overpressure in the chambers relative to the outside atmosphere (Figure S2D) and by restricting daytime experimental activities inside the chambers between days 49 and 63 as much as possible within the limitations of the experimental plan [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e]. Also, air locks (Figure S3A) were installed in chamber doors throughout the 14 days-long period of active experimentation. For the latter chambers had to be routinely accessed daily before the end of the light period for (non-destructive) measurements of leaf elongation on eight plants per chamber[\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]. In parallel, leaf level gas exchange measurements (not reported here) were made on individual plants [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]. These measurements were performed in a different, dedicated growth chamber which was controlled at the same [CO\u003csub\u003e2\u003c/sub\u003e] with the same \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e as the chamber of origin of a given plant. Thus, individual plants were removed from their chambers for leaf level gas exchange measurements and later returned to their chamber of origin [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]. In addition, intensive sampling activities over two consecutive days occurred before the end of the light and dark periods on days 49 and 50, and days 63 and 64 (data not reported here, but partly presently in Baca Cabrera et al.[\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e]).\u003c/p\u003e\n\u003cp\u003eThe above activities intrinsically meant a disturbance which generated opportunities for contamination of the chamber atmospheres with extraneous CO\u003csub\u003e2\u003c/sub\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Here, we quantify the cumulative effect of all putative sources of contamination (see Background) on the \u0026delta;\u003csup\u003e13\u003c/sup\u003eC of plant biomass and WSC components. For this, we sampled plants shortly after the end of the intensive experimental period (day 65) at the beginning of the dark period. Two replicate samples from each growth chamber were collected, with one replicate consisting of three randomly selected plants. Plants were removed from their pots, their roots washed to free them of sand and dissected into their shoot and root parts. The plant parts were weighed to determine their fresh weight, then frozen in liquid nitrogen and stored at \u0026minus;\u0026thinsp;18\u0026deg;C before freeze-drying for 72 h. Dry weights were subsequently determined. After that, plant material was ground to a fine powder in a ball mill (Mixer mill MM 400, Retsch, Haan, Germany) in 2-mL stainless steel grinding jars with 0.5-mm stainless steel beads, and thereafter stored again at \u0026minus;\u0026thinsp;18\u0026deg;C until further use.\u003c/p\u003e\n\u003ch3\u003eWSC extraction and separation\u003c/h3\u003e\n\u003cp\u003eWSC were extracted from shoot samples and fractions (fructan, sucrose, glucose, and fructose) separated using the procedures described by Gebbing \u0026amp; Schnyder [\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e]. Briefly, aliquots of 200 mg of milled sample material were weighed into 2-mL capped Eppendorf tubes and topped off with 1.8 mL of deionized water. Tubes were briefly vortexed (Vortex-Genie 2, Scientific Industries, New York, USA), held in a water bath at 93\u0026deg;C for 10 min, shaken for 45 min (Shaker, Heidolph Instruments, Schwabach, Germany) at room temperature, and then centrifuged at 9500 \u003cem\u003eg\u003c/em\u003e for 15 min (Universal 320, Merck, Tuttlingen, Germany). The supernatant, which contained the dissolved WSC, was passed through nylon-membrane filters with a pore size of 0.45 \u0026micro;m and then stored in clean 2-mL capped Eppendorf tubes at \u0026minus;\u0026thinsp;18\u0026deg;C.\u003c/p\u003e\n\u003cp\u003eWSC fractions (fructan, sucrose, glucose and fructose) were separated, quantified and collected using a high-performance liquid chromatography (HPLC) system similar to that of Gebbing \u0026amp; Schnyder [\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e]. Thus, 0.2 mL aliquots of the filtered supernatant were passed through a guard column (Shodex KS-LG, Showa Denko, Tokyo, Japan) and a preparative column (Shodex Sugar KS2002, 300\u0026times;20 mm, Showa Denko, Tokyo, Japan) held at 50\u0026deg;C, with HPLC-grade water (Carl Roth, Karlsruhe, Germany) as the eluent, at a flow rate of 0.75 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and a system pressure of approximately 2.1 bar. The WSC were detected by refractive index measurement (Shodex RI-101, Showa Denko, Tokyo, Japan) and concentrations quantified by comparing sample peak areas against reference calibration curves of pure and mixed standards of analytical grade inulin, sucrose, glucose and fructose (all from Merck, Darmstadt, Germany). Knowing when the individual carbohydrates eluted from the preparative column (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), fractions of fructan, sucrose, glucose, and fructose were individually collected in test tubes.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026nbsp;\u003cstrong\u003e13\u003c/strong\u003e\u0026nbsp;\u003c/sup\u003e \u003cstrong\u003eC analysis of biomass and water-soluble carbohydrate components\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u0026delta;\u003csup\u003e13\u003c/sup\u003eC of biomass samples was determined for all shoot and root replicates, as in Lattanzi et al. [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]. The stored samples were thawed, re-dried at 40\u0026deg;C for 24 h and stored in desiccator vessels. Aliquots of 0.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 mg of the shoot and root materials were weighed and packed into tin cups (3.3 x 5 mm, IVA Analysentechnik, Meerbusch, Germany). These were then combusted in an elemental analyzer (NA 1110, Carlo Erba Instruments, Milan, Italy) interfaced (Conflo III, Finnigan MAT, Bremen, Germany) to a continuous-flow isotope-ratio mass spectrometer (CF-IRMS, Delta Plus, Finnigan MAT, Bremen, Germany) which measured \u0026delta;\u003csup\u003e13\u003c/sup\u003eC. A solid internal laboratory standard (SILS, fine ground wheat flour) was measured as a reference after every tenth sample to correct for possible instrument drift. All samples and SILS were measured against a laboratory working standard CO\u003csub\u003e2\u003c/sub\u003e gas, which was previously calibrated against a secondary isotope standard (IAEA-CH6; calibration accuracy\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u0026permil; SD). The long-term precision given as the SD of repeated measurements of the SILS was \u0026lt;\u0026thinsp;0.2\u0026permil;.\u003c/p\u003e\n\u003cp\u003eAliquots of approximately 0.70 mg of the different WSC fractions were transferred to tin cups, dried at 60\u0026deg;C for 24 h, and then analyzed for their \u0026delta;\u003csup\u003e13\u003c/sup\u003eC using the same CF-IRMS system as above.\u003c/p\u003e\n\u003ch3\u003e\u0026delta;C of WSC-free biomass\u003c/h3\u003e\n\u003cp\u003eThe \u0026delta;\u003csup\u003e13\u003c/sup\u003eC of WSC free biomass (\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eWSC\u0026minus;free biomass\u003c/sub\u003e) was determined from isotopic mass balance for a given biomass sample \u003cem\u003eX\u003c/em\u003e, thus\u003c/p\u003e\n\u003cp\u003e\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eWSC\u0026minus;free biomass\u003c/sub\u003e = (\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003ebiomass\u003c/sub\u003e \u0026times; \u003cem\u003eW\u003c/em\u003e\u003csub\u003ebiomass\u003c/sub\u003e \u0026ndash; \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eWSC\u003c/sub\u003e \u0026times; \u003cem\u003eW\u003c/em\u003e\u003csub\u003eWSC\u003c/sub\u003e) / (\u003cem\u003eW\u003c/em\u003e\u003csub\u003ebiomass\u003c/sub\u003e \u0026ndash; \u003cem\u003eW\u003c/em\u003e\u003csub\u003eWSC\u003c/sub\u003e), (5)\u003c/p\u003e\n\u003cp\u003ewith \u003cem\u003eW\u003c/em\u003e\u003csub\u003ebiomass\u003c/sub\u003e and \u003cem\u003eW\u003c/em\u003e\u003csub\u003eWSC\u003c/sub\u003e the C mass in biomass and in total WSC of a give sample, and \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003ebiomass\u003c/sub\u003e and \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eWSC\u003c/sub\u003e the of \u0026delta;\u003csup\u003e13\u003c/sup\u003eC of the biomass and WSC extracted from that biomass sample.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e\u0026delta;\u003csup\u003e13\u003c/sup\u003eC of respired CO\u003csub\u003e2\u003c/sub\u003e\u003c/h2\u003e\n \u003cp\u003eThe \u0026delta;\u003csup\u003e13\u003c/sup\u003eC of respired CO\u003csub\u003e2\u003c/sub\u003e (\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRn\u003c/sub\u003e) was obtained as [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]:\u003c/p\u003e\n \u003cp\u003e\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRn\u003c/sub\u003e = (\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003einlet\u003c/sub\u003e \u0026times; \u003cem\u003eF\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u0026ndash; \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet\u003c/sub\u003e \u0026times; \u003cem\u003eF\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e) / (\u003cem\u003eF\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u0026ndash; \u003cem\u003eF\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e), (4)\u003c/p\u003e\n \u003cp\u003ewith \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003einlet\u003c/sub\u003e and \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet\u003c/sub\u003e the (measured) \u0026delta;\u003csup\u003e13\u003c/sup\u003eC of CO\u003csub\u003e2\u003c/sub\u003e entering and leaving the growth chamber, respectively, and \u003cem\u003eF\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e and \u003cem\u003eF\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e the fluxes of CO\u003csub\u003e2\u003c/sub\u003e (\u0026micro;mol s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) entering and leaving the chamber during dark period.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eEstimation of C contamination\u003c/h3\u003e\n\u003cp\u003eThe fraction contamination of the C (\u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e) contained in any one type \u003cem\u003eX\u003c/em\u003e of sample (with \u003cem\u003eX\u003c/em\u003e standing for biomass or WSC fraction (fructan, sucrose, glucose or fructose) or respired CO\u003csub\u003e2\u003c/sub\u003e was determined as \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam X\u003c/sub\u003e = 1 \u0026ndash; d\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX actual\u003c/sub\u003e/d\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e (Eq. 2) as explained in the Background section. In this, d\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e corresponds to the measurements-based \u0026delta;\u003csup\u003e13\u003c/sup\u003eC-difference between samples of the same type collected simultaneously from parallel chambers, where one was supplied with \u003csup\u003e13\u003c/sup\u003eC-depleted CO\u003csub\u003e2\u003c/sub\u003e and the other with \u003csup\u003e13\u003c/sup\u003eC-enriched CO\u003csub\u003e2\u003c/sub\u003e. Meanwhile, d\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e refers to an estimation of the contamination-free \u0026delta;\u003csup\u003e13\u003c/sup\u003eC-difference between the \u003csup\u003e13\u003c/sup\u003eC-depleted and \u003csup\u003e13\u003c/sup\u003eC-enriched CO\u003csub\u003e2\u003c/sub\u003e supplied to the chambers for the reference sample (see below and Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). For calculation of \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e for each chamber, we first estimated the uncontaminated \u0026delta;\u003csup\u003e13\u003c/sup\u003eC of CO\u003csub\u003e2\u003c/sub\u003e at the outlet of the chamber (\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet pure\u003c/sub\u003e), by solving for \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet\u003c/sub\u003e the Eq. 10 as[\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e\n\u003cp\u003e\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet pure\u003c/sub\u003e = (\u0026Delta;\u003csup\u003e13\u003c/sup\u003eC\u0026thinsp;+\u0026thinsp;\u0026xi; \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003einlet\u003c/sub\u003e (\u0026Delta;\u003csup\u003e13\u003c/sup\u003eC/1000) + \u0026xi; \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003einlet\u003c/sub\u003e) / (( \u0026Delta;\u003csup\u003e13\u003c/sup\u003eC/1000)( \u0026xi; \u0026ndash; 1) + \u0026xi;), (6)\u003c/p\u003e\n\u003cp\u003ewith \u0026Delta;\u003csup\u003e13\u003c/sup\u003eC given in per mil (\u0026permil;). In Eq.\u0026nbsp;6, \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003einlet\u003c/sub\u003e corresponds to the \u0026delta;\u003csup\u003e13\u003c/sup\u003eC of CO\u003csub\u003e2\u003c/sub\u003e as measured at the inlet of the growth chamber. \u0026Delta;\u003csup\u003e13\u003c/sup\u003eC was set to 21\u0026permil;, a value close to that estimated for shoot biomass of perennial ryegrass or temperate (C\u003csub\u003e3\u003c/sub\u003e) grassland in the absence of drought stress in many works [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e]. \u0026xi; was obtained as [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]:\u003c/p\u003e\n\u003cp\u003e\u0026xi;\u0026thinsp;=\u0026thinsp;\u003cem\u003eC\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e / (\u003cem\u003eC\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u0026ndash; \u003cem\u003eC\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e), (7)\u003c/p\u003e\n\u003cp\u003ewith \u003cem\u003eC\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e and \u003cem\u003eC\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e the CO\u003csub\u003e2\u003c/sub\u003e concentration in air as measured at the inlet and outlet of the growth chamber, respectively.\u003c/p\u003e\n\u003cp\u003eNext, we estimated \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e, the contamination-free \u0026delta;\u003csup\u003e13\u003c/sup\u003eC representative for all functional parameters (biomass fractions, WSC components or dark respiration; see below) as,\u003c/p\u003e\n\u003cp\u003e\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e = (\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003einlet\u003c/sub\u003e \u0026times; \u003cem\u003eF\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u0026ndash; \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eoutlet pure\u003c/sub\u003e \u0026times; \u003cem\u003eF\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e) / (\u003cem\u003eF\u003c/em\u003e\u003csub\u003einlet\u003c/sub\u003e \u0026ndash; \u003cem\u003eF\u003c/em\u003e\u003csub\u003eoutlet\u003c/sub\u003e). (8)\u003c/p\u003e\n\u003cp\u003eThen, d\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e, the uncontaminated \u0026delta;\u003csup\u003e13\u003c/sup\u003eC-difference between \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eref\u003c/sub\u003e estimates for the parallel chambers, was obtained as the numerical difference between the two \u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e values. In the process, we used d\u0026delta;\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e in all calculations of \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e for all types of samples and treatments, thus \u0026ndash; for the time being \u0026ndash; positing that \u0026Delta;\u003csup\u003e13\u003c/sup\u003eC did not differ between treatments and that eventual post-photosynthetic discrimination was constant. In a second step, however, we explored the sensitivity of contamination estimates to variation of \u0026Delta;\u003csup\u003e13\u003c/sup\u003eC during daytime gas exchange measurements, as observed in the different [CO\u003csub\u003e2\u003c/sub\u003e] treatments.\u003c/p\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eOne-way analysis of variance (ANOVA) with Tukey\u0026rsquo;s HSD post hoc tests for pairwise comparisons was conducted to explore the effect of CO\u003csub\u003e2\u003c/sub\u003e treatments on the contamination (\u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e) of biomass (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2\u0026ndash;4) and WSC components (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2\u0026ndash;4). For \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e of dark respiration (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;17\u0026ndash;39), a linear mixed-effects model (LMM) was fitted using the lme4 package [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]. The model included [CO\u003csub\u003e2\u003c/sub\u003e] treatment as a fixed effect and sampling day as a random effect to account for temporal pseudo-replication. The significance of fixed effects was evaluated using sequential (Type I) likelihood ratio tests, and post hoc pairwise comparisons performed with Tukey\u0026rsquo;s HSD using the emmeans package [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e]. All statistical analyses were performed in R v.4.0.2 [\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e]. The R-package ggplot2 [\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e] was used for data visualization.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eVariation of [CO\u003csub\u003e2\u003c/sub\u003e] and δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e during the experiment\u003c/h2\u003e \u003cp\u003eThe daytime mean CO\u003csub\u003e2\u003c/sub\u003e concentration at the chamber outlet varied little (coefficient of variation\u0026thinsp;\u0026lt;\u0026thinsp;2%) between 20 and 65 days, and on average was 4.0 (\u0026plusmn;4.3 SD), 7.2 (\u0026plusmn;6.2 SD) and 13.9 (\u0026plusmn;8.3 SD) \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e higher than the target [CO\u003csub\u003e2\u003c/sub\u003e] of 200, 400 and 800 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These differences corresponded to mean relative deviations from target [CO\u003csub\u003e2\u003c/sub\u003e] of \u0026le;2% in every treatment. These deviations did not differ (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05) between chambers receiving \u003csup\u003e13\u003c/sup\u003eC-depleted and \u003csup\u003e13\u003c/sup\u003eC-enriched CO\u003csub\u003e2\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMeanwhile, the δ\u003csup\u003e13\u003c/sup\u003eC of CO\u003csub\u003e2\u003c/sub\u003e at the chamber outlet (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2 outlet\u003c/sub\u003e) relative to the chamber inlet (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2 inlet\u003c/sub\u003e) increased by several \u0026permil; during daytime until day 30 to 35 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) when canopies became closed. Thereafter, the increase of δ\u003csup\u003e13\u003c/sup\u003eC at the chamber outlet relative to that at the inlet was relatively stable until the end of the experiments (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eContamination\u003c/h2\u003e \u003cp\u003eANOVA provided no evidence for a significant effect of [CO\u003csub\u003e2\u003c/sub\u003e] treatments on the fraction of contaminating C (\u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e) in any parameter of the study, except for respired CO\u003csub\u003e2\u003c/sub\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBiomass components (shoot and root), including WSC-free shoot biomass, and the different WSC fractions shared a very similar contamination of (on average) 3.3% (\u0026plusmn;0.9% SD), which was \u0026ndash; moreover \u0026ndash; close to that of respired CO\u003csub\u003e2\u003c/sub\u003e at both 200 and 400 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e (compare in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), and did not differ significantly (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.84) between the latter. Conversely \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e of respired CO\u003csub\u003e2\u003c/sub\u003e was slightly negative at 800\u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e, but not significantly different from zero, and significantly smaller than at 200 and 400 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for both comparisons). Significantly, the uncertainty for the individual estimates of contamination (represented by the SD) was not much smaller than the contamination estimate for most biomass and WSC parameters (average SD 2.3%) and corresponded to an average coefficient of variation CV\u0026thinsp;=\u0026thinsp;SD/mean of 67%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSignificance (\u003cem\u003eP\u003c/em\u003e-value) of [CO\u003csub\u003e2\u003c/sub\u003e] treatment effects on contamination (\u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e) parameters.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e effect significance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(\u003cem\u003eP\u003c/em\u003e-value)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiomass components\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShoot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater-soluble carbohydrates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFructan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFructose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.759\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWSC-free shoot biomass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDark respiration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e treatment effects were tested with one-way ANOVA for biomass and WSC components (n\u0026thinsp;=\u0026thinsp;2\u0026ndash;4) and a linear mixed model for dark respiration (n\u0026thinsp;=\u0026thinsp;17\u0026ndash;39).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe fraction of contaminating C (\u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e, %) in diverse sample types.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e concentration (\u0026micro;mol\u0026nbsp;mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e800\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e, %\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiomass components\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShoot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.9 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7 (2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.0 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater-soluble carbohydrates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFructan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8 (2.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.4 (5.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.8 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3 (5.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFructose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9 (7.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWSC-free shoot biomass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.6 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1 (1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDark respiration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5 (2.7)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 (4.5)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.4 (5.2)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ef\u003c/em\u003e \u003csub\u003econtam\u003c/sub\u003e was determined for canopy-scale dark respiration for days 38 to 65, and bulk shoot and root C, and fructan, sucrose, glucose and fructose extracted and purified from shoot biomass sampled at the beginning of the light period on day 65. In all experiments, growth chambers were maintained near target [CO\u003csub\u003e2\u003c/sub\u003e] of 200, 400 or 800 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e using one of two CO\u003csub\u003e2\u003c/sub\u003e sources, a relatively \u003csup\u003e13\u003c/sup\u003eC-depleted (δ\u003csup\u003e13\u003c/sup\u003eC -43.5\u0026permil;) or \u003csup\u003e13\u003c/sup\u003eC-enriched source (δ\u003csup\u003e13\u003c/sup\u003eC -5.6\u0026permil;). \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e for dark respiration was determined during periods of steady-state gas exchange of chambers. That is, measurements in the first 45 min of a dark period or following the opening of the chamber were removed, and values over 1.5 \u0026times; IQR (Interquartile Range) away from the mean were removed as outliers. Except for [CO\u003csub\u003e2\u003c/sub\u003e] and δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e, all conditions were kept the same in all chambers (see Materials and Methods). The means and standard deviations (SD) are presented for each treatment and were calculated based on daily replicates (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;17\u0026ndash;39) for dark respiration measurements or chamber-level replicates (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2\u0026ndash;4) for all other parameters. Different superscript letters in the same row indicate a significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) effect of [CO\u003csub\u003e2\u003c/sub\u003e] treatments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eThe effect of varying discrimination on estimates of contamination\u003c/h2\u003e \u003cp\u003eAs illustrated by the methodology, assumptions of Δ\u003csup\u003e13\u003c/sup\u003eC impact estimations of contamination (i.e. \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e) \u003cem\u003evia\u003c/em\u003e the determination of the dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e-values (see Eqs.\u0026nbsp;2, 6 and 8). Significantly, we observed [CO\u003csub\u003e2\u003c/sub\u003e] dependent variation of Δ\u003csup\u003e13\u003c/sup\u003eC during daytime net CO\u003csub\u003e2\u003c/sub\u003e exchange (Δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eN\u003c/sub\u003e) counter to expectations: thus, Δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eN\u003c/sub\u003e increased from approx. 19 to 23\u0026permil; between 200 and 800 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of CO\u003csub\u003e2\u003c/sub\u003e (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Thus, our literature-based assumption of constant Δ\u003csup\u003e13\u003c/sup\u003eC (=\u0026thinsp;21\u0026permil;) must have biased estimations of \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e to some degree. The numerical effect of this Δ\u003csup\u003e13\u003c/sup\u003eC-dependent variation on estimates of \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e is explored in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis analysis demonstrated a negative relationship between estimates of \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e and assumed Δ\u003csup\u003e13\u003c/sup\u003eC, with a 0.44% decrease of the estimated \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e for a 6\u0026permil; decrease of Δ\u003csup\u003e13\u003c/sup\u003eC from 18 to 24\u0026permil;. The maximum error on estimates of \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e which resulted from neglecting the [CO\u003csub\u003e2\u003c/sub\u003e] treatment effect on Δ\u003csup\u003e13\u003c/sup\u003eC as observed here was 0.3%, but did not change conclusions with respect to the non-significance (or significance) of the [CO\u003csub\u003e2\u003c/sub\u003e] treatment effect on \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e (Table S2).\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eContamination was small and similar for all parameters\u003c/h2\u003e \u003cp\u003eTo the best of our knowledge, this work presents the first explicit, comprehensive and quantitative assessment of isotopic contamination artifacts in a long-term labelling experiment. This analysis determined a very small contamination of samples, which was \u0026ndash; moreover \u0026ndash; closely similar for a range of functional parameters (biomass fractions, WSC components and respired CO\u003csub\u003e2\u003c/sub\u003e) and not significantly different for the different [CO\u003csub\u003e2\u003c/sub\u003e] treatments (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), except for respiration at high CO\u003csub\u003e2\u003c/sub\u003e which was insignificant. Lack of statistical significance for the [CO\u003csub\u003e2\u003c/sub\u003e] effect on contamination was not intuitive based on the expectation that incursion of a defined volume of extraneous CO\u003csub\u003e2\u003c/sub\u003e into labelling vessels would cause a (proportionally) greater mixing with a low than a high set CO\u003csub\u003e2\u003c/sub\u003e concentration, under \u003cem\u003eceteris paribus\u003c/em\u003e conditions. Indeed, there was a non-significant tendency for a lower contamination at 800 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e [CO\u003csub\u003e2\u003c/sub\u003e] than at 200 and 400 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, especially for the biomass components. Also, there was a significant (negative) [CO\u003csub\u003e2\u003c/sub\u003e] treatment-effect on \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e for respired CO\u003csub\u003e2\u003c/sub\u003e, which accorded with the expected (relatively) smaller extraneous CO\u003csub\u003e2\u003c/sub\u003e incursion at 800 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e [CO\u003csub\u003e2\u003c/sub\u003e]. Yet, these effects were very small, and not even considering the [CO\u003csub\u003e2\u003c/sub\u003e] treatment-effect on Δ\u003csup\u003e13\u003c/sup\u003eC (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) did change conclusions with respect to the (non-)significance of [CO\u003csub\u003e2\u003c/sub\u003e] treatment-effect on \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e (Table S2). The fact that contamination was generally very small certainly contributed to the absence of statistical significance \u003cem\u003evia\u003c/em\u003e a small signal to error ratio (which is \u0026ndash; basically \u0026ndash; the inverse of the CV) in the data. In that, the experimental error was not large at all (see also Materials and Methods). This may be recognized by translating a given contamination-% into the δ\u003csup\u003e13\u003c/sup\u003eC-difference (between \u003csup\u003e13\u003c/sup\u003eC-enriched and \u003csup\u003e13\u003c/sup\u003eC-depleted chambers), which is required to return a certain contamination-%. For instance, a 3% contamination corresponded to an approx. 1.1\u0026permil; smaller δ\u003csup\u003e13\u003c/sup\u003eC-difference between the measurements (dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e) than the predicted uncontaminated reference estimates (dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e). By comparison, with a very good average, whole-system SD of (say) 0.4\u0026permil; for the δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e data \u0026ndash; which integrates all errors from CO\u003csub\u003e2\u003c/sub\u003e administration over an extended period of time, labelling chamber operation (including adjustments in flow rates, changes of CO\u003csub\u003e2\u003c/sub\u003e flasks, variation of δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e in the chambers, and sample collection and preparation) \u0026ndash; error propagation yields a (whole system) SD of 0.57\u0026permil; on average for the dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e data. Given the average 1.1\u0026permil;-signal associated with a 3% contamination (see above), this SD of 0.57\u0026permil; translates to a CV of 52% for the contamination estimate which is not far from that observed here for the biomass and WSC components (67%).\u003c/p\u003e \u003cp\u003eClearly, increasing the isotopic spread between the two CO\u003csub\u003e2\u003c/sub\u003e sources used in experiments would help to increase the signal-to-error ratio of contamination estimation. In our laboratory we have used commercial sources of CO\u003csub\u003e2\u003c/sub\u003e with δ\u003csup\u003e13\u003c/sup\u003eC as high as \u0026minus;\u0026thinsp;2\u0026permil; and as low as \u0026minus;\u0026thinsp;50\u0026permil;, which yields an isotopic spread which is somewhat larger than that found here (-48\u0026permil; vs 38\u0026permil;). Of course, using artificially \u003csup\u003e13\u003c/sup\u003eC-enriched CO\u003csub\u003e2\u003c/sub\u003e sources [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] could further reduce the relative experimental error, including that of contamination estimations, and therefore increase to some degree the sensitivity of \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e tracer studies, albeit at much greater financial cost for the labelling CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eImportantly, in the present work contamination of the different WSC components was very similar to whole shoot biomass (from which they were extracted) and WSC-free shoot biomass. Based on this close similarity, we find no indication for any additional contamination which might have occurred during WSC extraction, separation and analysis. Given absence of evidence for additional contamination of WSC, it is futile to discuss any such eventual sources, except for acknowledging the effectiveness of the protocols and the cleanliness of the laboratory work.\u003c/p\u003e \u003cp\u003eStrikingly, contamination of respiratory CO\u003csub\u003e2\u003c/sub\u003e at 200 and 400 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e was also close to that of biomass and \u0026ndash; specifically \u0026ndash; WSC components. This observation agrees with the expectation that contamination of the respiratory substrate (specifically WSC) was the dominant factor explaining contamination of respired CO\u003csub\u003e2\u003c/sub\u003e at least in these treatments. It is well accepted that non-structural carbohydrates are the dominant source of substrate for dark respiration[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. At the same time, this would also suggest that no additional contamination with extraneous CO\u003csub\u003e2\u003c/sub\u003e occurred during respiration measurements. This is also unsurprising given the fact that dark respiration measurements occurred during (undisturbed) isotopic steady-state for gas exchange during periods when chambers had not been opened for at least 45 min previously. Meanwhile, we cannot explain the observation that respired CO\u003csub\u003e2\u003c/sub\u003e was apparently uncontaminated at 800 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e, albeit this estimate was associated with relatively large uncertainty. Particularly, we have not found any chamber effects on any morpho-physiological parameters studied in the work of Baca Cabrera et al. [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], which occurred just prior to the tests which are presented here.\u003c/p\u003e \u003cp\u003eOne question not directly explored by the present analysis is whether the δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e of the contaminating source was more similar to the \u003csup\u003e13\u003c/sup\u003eC-enriched or the \u003csup\u003e13\u003c/sup\u003eC-depleted CO\u003csub\u003e2\u003c/sub\u003e source used in this work. This question is also of interest for the accuracy of the Δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e data which can be obtained from the present data. We opine that the actual δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e of the extraneous (contaminating) CO\u003csub\u003e2\u003c/sub\u003e was likely close to a 50:50 mix of of the \u003csup\u003e13\u003c/sup\u003eC-enriched and \u003csup\u003e13\u003c/sup\u003eC-depleted CO\u003csub\u003e2\u003c/sub\u003e sources: (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e \u0026minus;\u0026thinsp;43.5 and \u0026minus;\u0026thinsp;5.6\u0026permil; at the chamber inlet) both slightly \u003csup\u003e13\u003c/sup\u003eC-enriched 3\u0026permil; at the outlet of chambers (see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e): δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e of contaminating CO\u003csub\u003e2\u003c/sub\u003e \u0026asymp; (0.5 \u0026times; \u0026minus;\u0026thinsp;43.5\u0026permil; + 0.5 \u0026times; \u0026minus;\u0026thinsp;5.6\u0026permil;)\u0026thinsp;+\u0026thinsp;3\u0026permil; = 27.6\u0026permil;. This δ\u003csup\u003e13\u003c/sup\u003eC-value is also close to the δ\u003csup\u003e13\u003c/sup\u003eC of human-exhaled CO\u003csub\u003e2\u003c/sub\u003e (e.g. the experimenters) when based on a typical Central European, mainly C\u003csub\u003e3\u003c/sub\u003e-based diet [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Mixing of the CO\u003csub\u003e2\u003c/sub\u003e inside the room housing the labelling facility (in the basement of \u0026lsquo;Alte Akademie 12\u0026rsquo; in Freising-Weihenstephan) with free atmospheric CO\u003csub\u003e2\u003c/sub\u003e (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e approx. \u0026minus;\u0026thinsp;9\u0026permil;) was likely a very minor factor, as the volume of air in this room was continuously flushed with air from the growth chambers at a high rate. In consequence, we argue that reasonable Δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e-values can be obtained by averaging the Δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e-values from the \u003csup\u003e13\u003c/sup\u003eC-enriched and \u003csup\u003e13\u003c/sup\u003eC-depleted chambers.\u003c/p\u003e \u003cp\u003eAlthough not comparable in terms of experimental purpose, system design and level of \u003csup\u003e13\u003c/sup\u003eC enrichment, the degree of isotopic contamination observed in the present work is comparable to that of commercial systems which are used to manufacture highly isotopically enriched compounds. Thus, for instance, closed systems [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e] specially designed to produce highly isotopically enriched plant compounds with pure \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e gas, achieved a degree of labelling of 96\u0026ndash;98 atom-%. This would (also) correspond to an isotopic contamination (with \u003csup\u003e12\u003c/sup\u003eC) of approx. 2\u0026ndash;4%.\u003c/p\u003e \u003cp\u003eIn the present work, contamination was likely dominated by extraneous CO\u003csub\u003e2\u003c/sub\u003e entering the growth chambers during light periods when these had to be accessed for experimental or maintenance purposes (e.g. changes of defective light sources). Unfortunately, we did not sample the 12 days-old seedlings when we started the δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e treatments, so we cannot quantify the possible contribution of the experimental starting material (see Background) to the integral contamination estimate. However, if we make assumptions extrapolated from our first chamber-scale gas exchange measurements, we estimate an experimental starting material-associated contamination of not more than ~\u0026thinsp;1% (compare also plant sizes in Figure S4).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eHow to deal with contamination in tracer data evaluation?\u003c/h2\u003e \u003cp\u003eOf course, the best way to avoid complications with contamination is to avoid contamination altogether. As we emphasize, using air locks in chamber doors and minimizing experimental and maintenance operations inside the chambers during daytime are important contamination avoidance principles in addition to precautions already mentioned in the Discussion sections above. Concerning air locks, there may be a trade-off between their effectiveness in reducing CO\u003csub\u003e2\u003c/sub\u003e incursion when doors are open and the ease of access to the chamber interior that they permit (compare Figures S3A and B). While we failed to compare the effectiveness of these two versions of air locks directly, the measurements by Lehmeier et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] do suggest that their airlocks provide excellent proof for their effectiveness (Figure S3B).\u003c/p\u003e \u003cp\u003eThe fact that we observed only small contamination, despite of the fact that the study was performed with a highly experimentally-perturbed system, supports our assessment that previous works which were performed with less experimentally disturbed studies in a very similar system [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] should have been affected even less by contamination. This view is supported by the absence of a CO\u003csub\u003e2\u003c/sub\u003e source (\u003csup\u003e13\u003c/sup\u003eC enriched vs \u003csup\u003e13\u003c/sup\u003eC-depleted CO\u003csub\u003e2\u003c/sub\u003e) effect on measurements of Δ\u003csup\u003e13\u003c/sup\u003eC during net CO\u003csub\u003e2\u003c/sub\u003e exchange in light [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Nevertheless, for instance, Lehmeier et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] did allow for some contamination in their evaluation of the tracer kinetics of respired CO\u003csub\u003e2\u003c/sub\u003e when using a very similar, two-chamber system with two distinct δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e. In that, they used measurements from plants which had grown continuously in the presence of \u003csup\u003e13\u003c/sup\u003eC enriched or \u003csup\u003e13\u003c/sup\u003eC-depleted CO\u003csub\u003e2\u003c/sub\u003e as the endmembers (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003enew\u003c/sub\u003e and δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eold\u003c/sub\u003e) of the isotopic mixing model which they applied to the tracer data. This procedure did correct for an eventual contamination, although it used the assumption that contamination was a constant.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eThe aim of this work was to quantify the isotopic contamination artifact which occurred in a\u0026thinsp;\u0026gt;\u0026thinsp;9 weeks-long experiment with continuous exposure of \u003cem\u003eL. perenne\u003c/em\u003e plants to one of two C-isotopically distinct natural CO\u003csub\u003e2\u003c/sub\u003e sources, one a \u003csup\u003e13\u003c/sup\u003eC-depleted fossil-organic source and the other a (relatively) \u003csup\u003e13\u003c/sup\u003eC enriched mineral source, at one of three [CO\u003csub\u003e2\u003c/sub\u003e]-levels: 200, 400 or 800 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e in plant growth chambers. The experiments provided an elevated opportunity for contamination due to extensive experimental activities in all chambers during the last two weeks just prior to determination of contamination. Nevertheless, the findings indicated only a low level of contamination (3.3% on average) for biomass and WSC fractions, with no significant effect of [CO\u003csub\u003e2\u003c/sub\u003e] on contamination. Thus, our work supports the use of the present \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e system for quantitative C tracer experiments of plant metabolism across contrasts of [CO\u003csub\u003e2\u003c/sub\u003e]. Contamination avoidance principles used (and discussed) here should also be adopted in simpler tracer systems (e.g. one-chamber systems with or without inclusion of CF-IRMS or other online gas isotope analysers) in controlled or field environments [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable (the study involved no animals and no human participants, human data or human tissue)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data supporting the findings are original and included in the manuscript. The \u0026nbsp;datasets used and/or analysed during the current study are available from the corresponding authors on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDeutsche Forschungsgemeinschaft (DFG SCHN 557/9‐1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors‘ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHS and RTH acquired funding of the project. JZ, RS and HS conceived the idea of the study. JZ, RS, JCBC and RTH performed the work. JZ, HS and RS wrote the paper. JZ, RTH, JCBC, RS and HS revised the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe project was funded by the Deutsche Forschungsgemeinschaft (DFG SCHN 557/9-1). JZ was supported by the China Scholarship Council (CSC). Anja Schmidt, Monika Michler, Angela Ernst-Schwärzli, Laura Dorn, Wolfgang Feneis and Richard Wenzel are thanked for expert assistance with maintenance of the gas exchange facility (WF, RW), sample collection and processing (AS, MM, AES) and carbohydrate analyses (AS, LD).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllen DK, Libourel IGL, Shachar‐Hill Y. Metabolic flux analysis in plants: coping with complexity. Plant Cell Environ. 2009;32:1241\u0026ndash;57.\u003c/li\u003e\n\u003cli\u003eAllen DK, Young JD. Tracing metabolic flux through time and space with isotope labeling experiments. Curr Opin Biotechnol. 2020;64:100\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eBassham JA, Benson AA, Kay LD, Harris AZ, Wilson AT, Calvin M. The path of carbon in photosynthesis. XXI. The cyclic regeneration of carbon dioxide acceptor. 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Why are non-photosynthetic tissues generally \u003csup\u003e13\u003c/sup\u003eC enriched compared with leaves in C\u003csub\u003e3\u003c/sub\u003e plants? Review and synthesis of current hypotheses. Funct Plant Biol. 2009;36:199\u0026ndash;213.\u003c/li\u003e\n\u003cli\u003eDiefendorf AF, Mueller KE, Wing SL, Koch PL, Freeman KH. Global patterns in leaf \u003csup\u003e13\u003c/sup\u003eC discrimination and implications for studies of past and future climate. Proc Natl Acad Sci USA. 2010;107:5738\u0026ndash;43.\u003c/li\u003e\n\u003cli\u003eBaca Cabrera JC, Hirl RT, Sch\u0026auml;ufele R, Zhu J, Liu H, Og\u0026eacute;e J. et al. \u003csup\u003e18\u003c/sup\u003eO enrichment of leaf cellulose correlated with \u003csup\u003e18\u003c/sup\u003eO enrichment of leaf sucrose but not bulk leaf water in a C\u003csub\u003e3\u003c/sub\u003e grass across contrasts of atmospheric CO\u003csub\u003e2\u003c/sub\u003e concentration and air humidity. https://doi.org/10.21203/rs.3.rs-596094/v1\u003c/li\u003e\n\u003cli\u003eGraven H, Keeling RF, Rogelj J. Changes to carbon isotopes in atmospheric CO\u003csub\u003e2\u003c/sub\u003e over the industrial era and into the future. Glob Biogeochem Cycles. 2020;34:e2019GB006170.\u003c/li\u003e\n\u003cli\u003eEpstein S, Zeiri L. Oxygen and carbon isotopic compositions of gases respired by humans. Proc Natl Acad Sci USA. 1988;85:1727\u0026ndash;31.\u003c/li\u003e\n\u003cli\u003eYanes Y, Yapp CJ. 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Atmospheric CO\u003csub\u003e2\u003c/sub\u003e and VPD alter the diel oscillation of leaf elongation in perennial ryegrass: compensation of hydraulic limitation by stored‐growth. New Phytol. 2020;227:1776\u0026ndash;89.\u003c/li\u003e\n\u003cli\u003eBaca Cabrera JC, Hirl RT, Zhu J, Sch\u0026auml;ufele R, Og\u0026eacute;e J, Schnyder H. \u003csup\u003e18\u003c/sup\u003eO enrichment of sucrose and photosynthetic and nonphotosynthetic leaf water in a C\u003csub\u003e3\u003c/sub\u003e grass \u0026ndash; atmospheric drivers and physiological relations. Plant Cell Environ. 2023;46:2628\u0026ndash;48.\u003c/li\u003e\n\u003cli\u003eBaca Cabrera JC, Hirl RT, Zhu J, Sch\u0026auml;ufele R, Og\u0026eacute;e J, Schnyder H. Half of the \u003csup\u003e18\u003c/sup\u003eO enrichment of leaf sucrose is conserved in leaf cellulose of C\u003csub\u003e3\u003c/sub\u003e grass across atmospheric humidity and CO\u003csub\u003e2\u003c/sub\u003e levels. Plant Cell Environ. 2024;47:2274\u0026ndash;87.\u003c/li\u003e\n\u003cli\u003eGebbing T, Schnyder H. \u003csup\u003e13\u003c/sup\u003eC labelling kinetics of sucrose in glumes indicates significant refixation of respiratory CO\u003csub\u003e2\u003c/sub\u003e in the wheat ear. Funct Plant Biol. 2001;28:1047\u0026ndash;53.\u003c/li\u003e\n\u003cli\u003eSchnyder H, Schwertl M, Auerswald K, Sch\u0026auml;ufele R. Hair of grazing cattle provides an integrated measure of the effects of site conditions and interannual weather variability on d\u003csup\u003e13\u003c/sup\u003eC of temperate humid grassland. Glob Change Biol. 2006;12:1315\u0026ndash;29.\u003c/li\u003e\n\u003cli\u003eK\u0026ouml;hler IH, Poulton PR, Auerswald K, Schnyder H. Intrinsic water-use efficiency of temperate seminatural grassland has increased since 1857: an analysis of carbon isotope discrimination of herbage from the Park Grass Experiment. Glob Chang Biol. 2010;16:1531\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eK\u0026ouml;hler IH, Macdonald A, Schnyder H. Nutrient supply enhanced the increase in intrinsic water-use efficiency of a temperate seminatural grassland in the last century. Glob Chang Biol. 2012;18:3367\u0026ndash;76.\u003c/li\u003e\n\u003cli\u003eBarbosa ICR, K\u0026ouml;hler IH, Auerswald K, L\u0026uuml;ps P, Schnyder H. Last-century changes of alpine grassland water use efficiency: a reconstruction through carbon isotope analysis of a time-series of Capra ibex horns. Glob Change Biol. 2010;16:1171\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003eBates D, M\u0026auml;chler M, Bolker B, Walker S, Christensen RH, Singmann H, et al. lme4: linear mixed-effects models using Eigen and S4. R package version1.1\u0026ndash;10. https://cran.r-project.org/web/packages/lme4/index.html. Accessed 2 May 2025.\u003c/li\u003e\n\u003cli\u003eLenth RV. emmeans: estimated marginal means, aka least-squares means. R package version 1.8.7. https://CRAN.R-project.org/package=emmeans.Accessed 10 Jun 2022.\u003c/li\u003e\n\u003cli\u003eR Core Team. R: A language and environment for statistical computing. Vienna, Austria2020. https://www.r-project.org/.Accessed 8 Jun 2020.\u003c/li\u003e\n\u003cli\u003eWickham H. ggplot2: elegant graphics for data analysis. New York: Springer; 2016. \u003c/li\u003e\n\u003cli\u003eDusenge ME, Duarte AG, Way DA. Plant carbon metabolism and climate change: elevated CO\u003csub\u003e2\u003c/sub\u003e and temperature impacts on photosynthesis, photorespiration and respiration. New Phytol. 2019;221:32\u0026ndash;49.\u003c/li\u003e\n\u003cli\u003eMcCue MD, Passement CA, Rodriguez M. The magnitude of the naturally occurring isotopic enrichment of 13C in exhaled CO2 is directly proportional to exercise intensity in humans. Comp Biochem Physiol A Mol Integr Physiol. 2015;179:164\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eCeranic A, Doppler M, B\u0026uuml;schl C, Parich A, Xu K, Koutnik A, et al. Preparation of uniformly labelled 13C- and 15N-plants using customized growth chambers. Plant Methods. 2020;16:47. doi:10.1186/s13007-020-00589-2.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-methods","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plme","sideBox":"Learn more about [Plant Methods](http://plantmethods.biomedcentral.com/)","snPcode":"13007","submissionUrl":"https://submission.nature.com/new-submission/13007/3","title":"Plant Methods","twitterHandle":"@PlantMethods","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Atmospheric CO2 concentration, bulk carbon, 13C isotopic labelling, C tracer, CO2 gas exchange, contamination, experimental artifact, water-soluble carbohydrates (fructan, sucrose, glucose, fructose) ","lastPublishedDoi":"10.21203/rs.3.rs-6759212/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6759212/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative understanding of plant carbon (C) metabolism by \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e-labelling studies requires absence (or knowledge) of C-isotopic contamination artefacts during tracer application and sample processing. This concern has not been studied explicitly but is especially crucial in experiments at different atmospheric CO\u003csub\u003e2\u003c/sub\u003e concentrations ([CO\u003csub\u003e2\u003c/sub\u003e]), when experimental protocols require frequent access to the labelling chambers. Here, we used a plant growth chamber-based \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2 \u003c/sub\u003egas exchange facility to address this topic. The facility comprised four independent units, with two chambers routinely operated in parallel under identical conditions except for the isotopic composition of the CO\u003csub\u003e2\u003c/sub\u003e supplied to them (δ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eCO2\u003c/sub\u003e –43.5‰ \u003cem\u003eversus\u003c/em\u003e –5.6‰). In this setup, dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e (the measurements-based δ\u003csup\u003e13\u003c/sup\u003eC-difference between matching samples \u003cem\u003eX\u003c/em\u003e collected from the parallel chambers) is expected to equal dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e (the predictable, non-contaminated δ\u003csup\u003e13\u003c/sup\u003eC-difference ), if sample-C is completely derived from the contrasting CO\u003csub\u003e2\u003c/sub\u003e sources. Accordingly, contamination (\u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam\u003c/sub\u003e) was determined as \u003cem\u003ef\u003c/em\u003e\u003csub\u003econtam \u003c/sub\u003e= 1 – dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eX\u003c/sub\u003e/dδ\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eRef\u003c/sub\u003e in this experimental setup. Determinations were made for biomass fractions, water-soluble carbohydrate (WSC) components and dark respiration of \u003cem\u003eLolium perenne\u003c/em\u003e (perennial ryegrass) stands following growth for ~9 weeks at 200, 400 or 800 mmol mol\u003csup\u003e-1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e, with a terminal two weeks-long period of extensive experimental disturbance of the chambers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContamination was small and similar (average 3.3% ±0.9% SD, \u003cem\u003en \u003c/em\u003e= 18) for shoot and root biomass and WSC fractions (fructan, sucrose, glucose, fructose) at every [CO\u003csub\u003e2\u003c/sub\u003e] level. [CO\u003csub\u003e2\u003c/sub\u003e] had no significant effect on contamination of these samples\u003cem\u003e.\u003c/em\u003e There was no evidence for any contamination of WSC components during extraction, separation and analysis. At 200 and 400 mmol mol\u003csup\u003e-1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e,\u003csub\u003e \u003c/sub\u003econtamination of respiratory CO\u003csub\u003e2\u003c/sub\u003e was close to that of biomass- and WSC-C, suggesting it originated primarily from \u003cem\u003ein vivo\u003c/em\u003e-contaminated respiratory substrate. Surprisingly, however, we found no evidence of contamination of respiratory CO\u003csub\u003e2\u003c/sub\u003e at 800 mmol mol\u003csup\u003e-1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e. Overall, contamination likely resulted overwhelmingly from photosynthetic fixation of extraneous (contaminating) CO\u003csub\u003e2\u003c/sub\u003e which entered chambers primarily during (daytime) experimental activities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe labelling facility enables months-long, quantitative \u003csup\u003e13\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e/\u003csup\u003e12\u003c/sup\u003eCO\u003csub\u003e2\u003c/sub\u003e-labelling of large numbers of plants with accuracy and precision across contrasts of [CO\u003csub\u003e2\u003c/sub\u003e], empowering eco-physiological study of climate change scenarios. Effective protocols for contamination avoidance are discussed.\u003c/p\u003e","manuscriptTitle":"Assessing and avoiding C isotopic contamination artefacts in mesocosm-scale 13CO2/12CO2 labelling systems:\nfrom biomass components to purified carbohydrates and dark respiration","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-04 19:14:27","doi":"10.21203/rs.3.rs-6759212/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-21T04:51:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-19T16:39:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-12T09:56:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"22271109853448693243874884327063986980","date":"2025-07-12T05:50:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"40939829617665801056278351095192843526","date":"2025-06-26T06:13:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"189681007453181788249945042020130820566","date":"2025-06-08T22:08:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-02T22:59:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-30T13:53:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-30T13:52:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant Methods","date":"2025-05-27T11:52:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-methods","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plme","sideBox":"Learn more about [Plant Methods](http://plantmethods.biomedcentral.com/)","snPcode":"13007","submissionUrl":"https://submission.nature.com/new-submission/13007/3","title":"Plant Methods","twitterHandle":"@PlantMethods","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8912e03a-a567-4572-bec9-24438604ec21","owner":[],"postedDate":"June 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-18T16:06:16+00:00","versionOfRecord":{"articleIdentity":"rs-6759212","link":"https://doi.org/10.1186/s13007-025-01431-3","journal":{"identity":"plant-methods","isVorOnly":false,"title":"Plant Methods"},"publishedOn":"2025-08-11 15:57:54","publishedOnDateReadable":"August 11th, 2025"},"versionCreatedAt":"2025-06-04 19:14:27","video":"","vorDoi":"10.1186/s13007-025-01431-3","vorDoiUrl":"https://doi.org/10.1186/s13007-025-01431-3","workflowStages":[]},"version":"v1","identity":"rs-6759212","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6759212","identity":"rs-6759212","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}