Carbon Isotope Composition of Nighttime Leaf-Respired CO₂ in the Agricultural-Pastoral Zone of the Songnen Plain, Northeast China

Abstract

Variations in the carbon isotope signature of leaf dark-respired CO₂ (δ¹³C_R) within a single night is a widely observed phenomenon. However, it is unclear whether there are plant functional type differences with regard to the amplitude of the nighttime variation in δ¹³C_R. These differences, if present, would be important for interpreting the short-term variations in the stable carbon signature of ecosystem respiration and the partitioning of carbon fluxes. To assess the plant functional type differences relating to the magnitude of the nighttime variation in δ¹³C_R and the respiratory apparent fractionation, we measured the δ¹³C_R, the leaf gas exchange, and the δ¹³C of the respiratory substrates of 22 species present in the agricultural-pastoral zone of the Songnen Plain, northeast China. The species studied were grouped into C₃ and C₄ plants, trees, grasses, and herbs. A significant nocturnal shift in δ¹³C_R was detected in 20 of the studied species, with the magnitude of the shift ranging from 1‰ to 5.8‰. The magnitude of the nighttime variation in δ¹³C_R was strongly correlated with the daytime cumulative carbon assimilation, which suggests that variation in δ¹³C_R were influenced, to some extent, by changes in the contribution of malate decarboxylation to total respiratory CO₂ flux. There were no differences in the magnitude of the nighttime variation in δ¹³C_R between the C₃ and C₄ plants, as well as among the woody plants, herbs and graminoids. Leaf respired CO₂ was enriched in ¹³C compared to biomass, soluble carbohydrates and lipids; however the magnitude of enrichment differed between 8 pm and 4 am, which were mainly caused by the changes in δ¹³C_R. We also detected the plant functional type differences in respiratory apparent fractionation relative to biomass at 4 am, which suggests that caution should be exercised when using the δ¹³C of bulk leaf material as a proxy for the δ¹³C of leaf-respired CO₂.

Introduction

The stable C isotope composition (δ¹³C) has been widely used to trace the carbon flow within ecosystem components or between the ecosystem and the atmosphere [1–7]. The applications of stable carbon isotope technique require a mechanistic understanding of the temporal and spatial variation in the δ¹³C signature of component fluxes [8–10]. As an important component of ecosystem carbon fluxes, leaf respired CO₂ has been reported to vary substantially in its carbon isotope composition at diurnal timescale [11–15]. Unfortunately, we still lack a comprehensive understanding of the processes controlling the dynamics in the δ¹³C signature of leaf respired CO₂ [9, 16].

It has been extensively reported that δ¹³C_R varied substantially, up to 14.8‰, on a diurnal timescale [12, 13, 17, 18]. Several mechanisms have been developed to explain short-term variation in δ¹³C_R. Firstly, intramolecular ¹³C distribution is not homogeneous in hexose molecules, which combined with changes in the relative contribution of the metabolic pathways to the respiration could lead to variation in δ¹³C_R [14, 19–22]. Secondly, shifts in δ¹³C_R can be attributed to the changes in the contribution of malate (¹³C-enriched) decarboxylation to the overall respiratory flux [8, 23]. Thirdly, changes in the use of the respiratory substrates having different δ¹³C may subsequently affect δ¹³C_R [16, 18]. Finally, short variation in carbohydrate pool size may also influence δ¹³C_R through affecting the allocation of respiratory intermediates [24]. The results of previous study showed substantial intraspecific and interspecific differences in the amplitude of the short-term variation in δ¹³C_R [14, 18, 25]. Intraspecific differences in the range of the diurnal variation in δ¹³C_l are caused mainly by the availability of resources associated changes in the substrate availability and the allocation of the respiratory intermediates [25]. The findings of previous studies by Werner et al. (2007) and Priault et al. (2009) indicated large diurnal variations in the δ¹³C_R of slow-growing aromatic plants, whereas no apparent diurnal shift was found in the δ¹³C_R in temperate trees and fast-growing herbs. These results highlight the potential plant functional type differences relating to the extent of the variation in δ¹³C_R on a diurnal timescale [11, 14, 22]. However, plant functional type differences in the magnitude of short-term variation in δ¹³C_R need to be further explored, especially for C₃ and C₄ species which differed substantially in the magnitude of heterogeneous ¹³C distribution within hexose molecules [21, 26].

Leaf dark-respired CO₂ is often enriched in ¹³C compared with leaf bulk tissue or other potential respiratory substrates, such as starch, soluble carbohydrates, and others [27–29]. This phenomenon is attributed mainly to non-homogeneous ¹³C distribution among the carbon atoms within the hexose molecules and the incomplete oxidation of hexoses. However, the phenomenon is also attributed partially to the utilization of isotopically different respiratory substrates [21, 24, 30]. Because of the intramolecular ¹³C/¹²C differences, CO₂ that evolved from pyruvate decarboxylation contains more ¹³C relative to that derived from acetyl-CoA oxidation [31, 32]. Depending on substrate availability, ¹³C-depleted acetyl-CoA could be used for the biosynthesis of lipids and secondary compounds, or decarboxylation in the TCA cycle to generate adenosine triphosphate (ATP). Therefore, the incomplete oxidation of acetyl-CoA could lead to ¹³C enrichment in leaf dark-respired CO₂ relative to respiratory substrates. The plant functional types differed substantially with regard to the allocation of ¹³C-depleted compounds. Trees, for instance, allocated proportionally more acetyl-CoA to the synthesis of lipids and lignin than did grasses [14, 26]. This could lead to the leaf-respired CO₂ in trees being more enriched in ¹³C in comparison with the putative respiratory substrates or the bulk leaf material. Indeed, plant functional type differences in respiratory apparent fractionation have been reported between C₃ and C₄ species, but not between woody plants and C₃ herbs [15, 16]. However, these findings were derived from meta-analysis of results obtained under various growing habitats and using different methods, which makes the conclusions unreliable. Therefore, the existence of plant functional type differences with regard to respiratory apparent fractionation needs to be further verified and, if they do exist, we need to incorporate these into the flux partitioning.

The vegetation of the agricultural-pastoral zone of the Songnen Plain is characterized as mosaics of grassland and cultivated land, dominated mainly by C₃ species and C₄ species, respectively. We measured the δ¹³C_R and δ¹³C of the putative primary respiratory substrates of 22 species at 8 pm and 4 am. The leaf gas-exchange parameters, including net assimilation rate, stomatal conductance, and nighttime respiration rate were also measured. The plant species were grouped into C₃ and C₄ species, trees, graminoids, and herbs. The objectives of the present study were to assess the plant functional type differences in the range of nighttime variation in δ¹³C_R and the respiratory apparent fractionation relative to the bulk leaf material and the putative respiratory substrates.

Materials and Methods

Ethics Statement

No specific permissions were required for the field studies described, because the Songnen Grassland Ecological Research Station is a department of the Northeast Normal University. No specific permissions were required for the study either, as it was conducted in accordance with the guidelines set by the Northeast Normal University. No specific permissions were required for the locations or the activities. No location was privately owned or protected in any way, and the field studies did not involve endangered or protected species.

Study site

The study was conducted in the agricultural-pastoral zone of the Songnen Plain (44°40′–44°44′N, 123°44′–123°47′E, elevation 138–144 m) in northeast China. The study area has a semiarid continental climate, with a mean annual temperature of 6.4°C. The mean annual rainfall is 471 mm, with over 70% of the precipitation occurs from June to August (Fig 1A). Drought, especially spring drought, occurs frequently in the studied area during the growing season; however there is no fixed drought period. The duration of the frost-free season is approximately 150 days. Detailed information on daily precipitation and daily temperature in 2012 is provided in Fig 1B. The main soil type of the study area is chernozem, with a soil organic carbon content of 2.0% and a soil total nitrogen content of 0.15% [33]. The vegetation in the study area is characterized as mosaics of grassland and cultivated land. The grassland is dominated by Leymus chinensis, while Phragmites australis and Chloris virgata are present in abundance[34]. The major crops on the cultivated land are Zea mays, Setaria italica, Helianthus annuus, and Sorghum bicolor. We studied 22 plant species, representative of the major species present on the grassland and the cultivated land. The details of the species studied are provided in Table 1. The field studies were conducted from July 25^th to August 5^th in 2012, which is the peak biomass season for the study area. None of the studied species showed signs of senescence. Information on the development stage of the studied species is provided in Table 1.

Fig 1. Growing season average monthly precipitation (mm) from 1963 to 2012 (a), and daily precipitation (mm) and daily mean air temperature (°C) from April 1^th to October 31^th in 2012 (b).

The shaded area in panel b denotes the field sampling period.

Table 1. Information on species studied.

List of plant species studied, and their photosynthetic pathway, classification and phenological phase.

Species	Photosynthetic pathway	Functional type	Class	Phenological phase
Leymus chinensis	C3	Graminoids	Monocotyledoneae	Fructescence
Phragmites australis	C3	Graminoids	Monocotyledoneae	Florescence
Lespedeza bicolor	C3	Trees	Dicotyledoneae	Florescence
Malus asiatica	C3	Trees	Dicotyledoneae	Fructescence
Populus simonii	C3	Trees	Dicotyledoneae	Post-fruiting vegetative stage
Prunus salicina	C3	Trees	Dicotyledoneae	Fructescence
Chenopodium glaucum	C3	Herbs	Dicotyledoneae	Florescence
Glycine max	C3	Herbs	Dicotyledoneae	Flowering and pod formation stage
Helianthus annuus	C3	Herbs	Dicotyledoneae	Florescence
Saussurea amara	C3	Herbs	Dicotyledoneae	Florescence
Vigna radiata	C3	Herbs	Dicotyledoneae	Flowering and pod formation stage
Vigna unguiculata	C3	Herbs	Dicotyledoneae	Flowering and pod formation stage
Xanthium sibiricum	C3	Herbs	Dicotyledoneae	Florescence
Chloris virgata	C4	Graminoids	Monocotyledoneae	Florescence
Echinochloa crusgalli	C4	Graminoids	Monocotyledoneae	Florescence
Hemarthria altissima	C4	Graminoids	Monocotyledoneae	Heading stage
Panicum miliaceum	C4	Graminoids	Monocotyledoneae	Florescence
Setaria italica	C4	Graminoids	Monocotyledoneae	Florescence
Setaria viridis	C4	Graminoids	Monocotyledoneae	Florescence
Sorghum bicolor	C4	Graminoids	Monocotyledoneae	Elongation stage
Zea mays	C4	Graminoids	Monocotyledoneae	Tasseling stage
Amaranthus retroflexus	C4	Herbs	Dicotyledoneae	Florescence

Leaf gas-exchange measurement

Leaf photosynthesis was measured every three hours, from 6 am to 6 pm, using a LI-6400 infrared gas-exchange analyzer (LI-COR Biosciences Inc., Lincoln, NE, USA). We selected fully expanded leaves from the sunny side for leaf photosynthetic rate measurements. Before each measurement, the leaf chamber conditions were set to match the environmental conditions, including the photosynthetically active radiation, air temperature, and relative humidity. Leaf respiration rates at 8 pm and 4 am were measured under zero light intensity. The leaf photosynthesis and respiration measurements for each species were conducted on five randomly selected plants.

Collection of leaf-respired CO₂

Leaf-respired CO₂ was collected in the field using the gas-tight syringe incubation method [11]. In brief, young and fully expanded leaves (comparable to those used to measure the photosynthesis and the respiration rates), were detached and placed inside a gas-tight syringe barrel. The syringe barrel was subsequently flushed with CO₂-free air to remove the background CO₂. The syringe barrel was then sealed and incubated for 15 min to allow for the buildup of leaf-respired CO₂. After the incubation, 5 ml of air, containing leaf-respired CO₂, was injected into a 12 ml vial. The vial was filled with helium and fitted with septum caps. For each studied species, the leaf-respired CO₂ was collected twice (8 pm and 4 am) during a single night. For the period of field sampling, sunset time ranged from 7:17 pm to 7:04 pm, therefore the collection of leaf-respired CO₂ at 8 pm was conducted at least 40 min after sunset and in the darkness. The leaf-respired CO₂ was sampled each time on five randomly selected plants or populations.

Lipids, soluble carbohydrates, and starch extractions

Simultaneously with the leaf-respired CO₂ sampling, we collected leaves for measuring the carbon isotope composition of leaf bulk materials and potential respiratory substrates. The collected leaves were comparable (age and canopy position, etc.) with those used for the leaf photosynthesis measurements. The collected leaves were immersed in liquid nitrogen to stop the metabolic activities. They were subsequently stored at -80°C in a deep freezer before being freeze-dried with a Labconco freeze drier (Labconco Kansas City, MO, USA). A ball mill (MM 400 Retsch, Haan, Germany) was used to grind the freeze-dried leaves into fine powder.

We used the protocols described by Wanek et al. (2001) and Göttlicher et al. (2006) [35, 36] for the extraction of lipids, soluble carbohydrates, and starch. In brief, the powdered leaf material was extracted with methanol/chloroform/water (MCW; 12:5:3, v/v/v). After centrifugation, the chloroform and the deionized water were added to the supernatant for phase separation. The chloroform phase (containing lipids) was dried in a ventilation device and subsequently analyzed for the carbon isotope composition.

The upper water phase (containing soluble carbohydrates) was transferred into a reaction vial and oven dried for carbohydrate extraction. The residue was re-dissolved in deionized water. After centrifugation, the phase containing the soluble carbohydrates was purified by an ion-exchange column, including both anion- and cation-exchange resin. The eluent was collected and oven dried, and the carbon isotope composition was subsequently analyzed, using an isotope ratio mass spectrometer.

The plant materials were re-extracted with MCW to remove the residual lipids and the soluble carbohydrates. After the starch in the plant materials had been gelatinized and hydrolyzed, the aqueous phase was separated from the pellet by centrifugation. The upper aqueous phase was subsequently purified by a centrifugal filter unit (Microcon YM-10; Millipore, Billerica, MA, USA). The filtrate containing glucose originated from starch was oven dried in a tin capsule and then analyzed for the carbon isotope composition.

Carbon isotope ratio analysis

All carbon isotope ratio analyses were performed using an isotope ratio mass spectrometer (Isoprime 100, Isoprime Ltd., Manchester, UK). The precision of repeated δ¹³C measurements on solid and gaseous working standards was < 0.1‰. The C isotope ratios are reported in parts per thousand relative to Vienna Pee Dee Belemnite (VPDB) as

$${\mathrm{\delta }}^{13}\mathrm{C}\left(‰\right)=（R_{\text{sample}}/R_{\text{standard}}-1）\times \mathrm{1,000}$$

Respiratory apparent ¹³C/¹²C fractionation

Respiratory apparent ¹³C/¹²C fractionation, relative to potential respiratory substrates, was calculated as:

$${\mathrm{\Delta }}_{R,X}=\frac{{\mathrm{\delta }}^{13}{\text{C}}_X-{\mathrm{\delta }}^{13}{\text{C}}_R}{1+{\mathrm{\delta }}^{13}{\text{C}}_R}$$ (1)

where Δ_R,X represents the respiratory apparent ¹³C/¹²C fractionation, relative to substrate X, and δ¹³C_X represents the carbon isotope composition of substrate X. X represents the leaf bulk materials, lipids, starch, or soluble carbohydrates, while δ¹³C_R represents δ¹³C of the leaf-respired CO₂.

Statistical analysis

We used one-way analysis of variance (ANOVA) to assess the differences between the photosynthetic pathways in the range of the nighttime variation of δ¹³C_R, the leaf net CO₂ assimilation rate (A), stomatal conductance (g _s), C _i/C _a, and the respiratory rate (R). Linear regression analysis was employed to assess the dependence of the magnitude of the nighttime variation in δ¹³C_R on the cumulative carbon assimilation. One-way analysis of variance was conducted to assess the plant functional type differences with regard to the leaf gas-exchange parameters, the magnitude of the nocturnal shifts in δ¹³C_R, and the nighttime respiratory apparent fractionation. The Statistical Package for the Social Science (SPSS) (version 13.0, IBM, Armonk, NY, USA) was used for all statistical analyses. Data are reported as mean ± 1 standard error.

Results

Leaf gas exchange

For the species studied, the maximum leaf net CO₂ assimilation rate (Amax) in the C₃ species varied from 15.1±1.2 to 38.4±5.8 μmol m^-2 s^-1; whereas it ranged from 22.3±1.7 to 33.7±1.6 μmol m^-2 s^-1 in the C₄ plants (Table 2). The average Amax value in the C₄ plants (28.1 μmol m^-2 s^-1) was greater than it was in the C₃ plants (22.4 μmol m^-2 s^-1) (Table 3). The mean leaf net CO₂ assimilation rate (Mean A) varied substantially between 9.6±0.4 and 24.0±0.5 μmol m^-2 s^-1 (Table 2). There were no statistically significant differences in Mean A between the C₃ and C₄ species (Table 3). Moreover, no apparent differences in Amax and Mean A were detected among the different plant functional types (Table 3).

Table 2. Leaf gas-exchange data.

Maximum leaf net CO₂ assimilation rate ( Amax, μmol m^-2 s^-1 ), mean leaf net CO₂ assimilation rate (Mean A, μmol m^-2 s^-1 ), maximum stomatal conductance (g _smax, mol m^-2 s^-1), mean ratio of intercellular air space to ambient CO₂ concentration (Mean C _i/C _a), and nighttime mean respiratory rate (Mean R, μmol m^-2 s^-1) of the species studied. Data are reported as mean ± 1 SE.

Species	Amax	Mean A	g smax	Mean C i/C a	Mean R
L. chinensis	19.9±3.99	11.8±0.82	0.295±0.022	0.75±0.01	1.32±0.16
P. australis	17.2±0.35	11.8±0.35	0.268±0.011	0.71 ±0.01	0.71 ±0.08
L. bicolor	22.6±1.87	12.2±0.67	0.586±0.047	0.78±0.01	2.07 ±0.26
M. asiatica	22.3±0.90	17.0±0.63	0.446±0.017	0.69±0.01	0.74 ±0.09
P. simonii	23.2±0.32	17.1±0.52	0.511±0.041	0.73±0.03	1.22 ±0.11
P. salicina	15.3±1.65	11.2±0.75	0.531±0.057	0.65±0.01	0.51 ±0.06
C. glaucum	28.8±1.04	21.1±0.43	0.943±0.051	0.80 ±0.01	1.28 ±0.13
G. max	17.0±0.54	10.8±0.49	0.098±0.005	0.20±0.03	1.45±0.11
H. annuus	21.1±0.13	13.1±0.28	0.128±0.002	0.44 ±0.01	1.10 ±0.10
S. amara	15.1±1.20	9.6 ±0.36	0.443±0.022	0.82 ±0.01	0.73 ±0.17
V. radiata	26.3±2.98	14.8±1.64	0.247±0.009	0.81 ±0.01	2.22±0.17
V. unguiculata	23.9±4.90	15.2±2.66	0.712±0.072	0.59 ±0.14	1.54 ±0.17
X. sibiricum	38.4±5.80	21.2±1.20	0.814±0.083	0.79 ±0.02	2.12 ±0.13
C. virgata	28.1±1.71	15.5±1.14	0.179±0.005	0.42 ±0.03	0.91 ±0.13
E. crusgalli	22.6±1.34	13.1±0.20	0.212±0.017	0.49 ±0.03	0.87 ±0.08
H. altissima	22.3±1.68	13.8±1.57	0.146±0.015	0.49 ±0.03	1.36 ±0.24
P. miliaceum	27.9±0.31	18.1±0.28	0.204±0.019	0.41 ±0.03	1.54 ±0.07
S. italica	30.8±2.27	18.0±0.63	0.247±0.013	0.41 ±0.03	0.82 ±0.40
S. viridis	27.6±1.88	15.3±0.57	0.199±0.007	0.49 ±0.01	1.15 ±0.11
S. bicolor	26.2±1.34	17.0±0.47	0.183±0.034	0.27 ±0.02	1.45 ±0.16
Z. mays	33.7±1.62	23.6 ±0.93	0.367±0.051	0.54 ±0.06	0.82 ±0.05
A. retroflexus	33.3±0.53	24.0±0.49	0.520±0.040	0.59 ±0.03	1.80 ±0.10

Table 3. Statistical data.

The df and P values from the photosynthetic pathway and the plant functional type differences in the maximum leaf net CO₂ assimilation rate ( Amax, μmol m^-2 s^-1 ), the mean leaf net CO₂ assimilation rate (Mean A, μmol m^-2 s^-1 ), maximum stomatal conductance (g _smax, mol m^-2 s^-1), mean ratio of leaf internal to ambient CO₂ concentration (Mean C_i/C_a), nighttime mean respiration rate (Mean R, μmol m^-2 s^-1), magnitude of nocturnal shift in δ¹³C_R (Variation in δ¹³C_R), and respiratory apparent ¹³C/¹²C fractionation (‰) comparative to biomass (Δ_{R, biomass}), soluble carbohydrates (Δ_{R, sugar}), starch (Δ_{R, starch}) and lipids (Δ_{R, lipid}) at 8 pm and 4 am, respectively.

	Photosynthetic pathway		Functional type
	df	P	df	P
Amax	1	0.03	2	0.40
Mean A	1	0.39	2	0.77
g s max	1	0.02	2	0.02
Mean Ci/Ca	1	<0.01	2	0.09
Mean R	1	0.59	2	0.14
Variation in δ13CR	1	0.07	2	0.29
ΔR, biomass-8pm	1	0.90	2	0.78
Δ R, biomass-4am	1	0.02	2	0.52
ΔR, sugar-8pm	1	<0.01	2	0.09
Δ R, sugar-4am	1	0.22	2	0.27
Δ R, starch-8pm	1	0.89	2	0.60
Δ R, starch-4am	1	0.11	2	0.33
Δ R, lipid-8pm	1	<0.01	2	<0.01
Δ R, lipid-4am	1	<0.01	2	<0.01

The maximum daily stomatal conductance (g _smax) varied from 0.10±0.01 to 0.94±0.05 mol m^-2 s^-1. Moreover, the apparent differences in g _smax were detected between the C₃ and the C₄ species (Tables 2 & 3). In addition, we detected significant differences in g _smax among the woody plants, forbs, and graminoids (Table 3). The mean respiration rate (Mean R) varied from 0.51±0.06 to 2.22±0.17 μmol m^-2 s^-1 (Table 2). There was no significant difference in the mean R among the functional groups, and it did not differ between the C₃ and the C₄ species either (Table 3). The mean ratio of the leaf intercellular air space to the ambient CO₂ concentration (Mean C _i/C _a) varied from 0.20±0.03 to 0.81±0.01 and 0.27±0.02 to 0.59±0.03 for the C₃ and C₄ species, respectively. The mean C _i/C _a in the C₃ plants was significantly greater than it was in the C₄ plants (Tables 2 & 3). Furthermore, no apparent differences in the Mean C _i/C _a were detected among the different functional types (Table 3).

δ¹³C of nighttime leaf-respired CO₂

We observed a significant nocturnal shift of the δ¹³C of leaf-respired CO₂ (δ¹³C_R) in 20 of the 22 species studied, the exceptions being Chenopodium glaucum and Saussurea amara (Table 4). The leaf-respired CO₂ at 8 pm was enriched in ¹³C compared with that at 4 am. However, the C₃ and C₄ plants showed no statistical significant difference in the amplitude of the nighttime variation in δ¹³C_R (Table 3). Moreover, no significant differences in the nocturnal shift in δ¹³C_R were detected among the plant functional types (Table 3).

Table 4. Carbon isotope composition.

The C isotope composition (‰) of leaf-respired CO₂ (δ¹³C_R), leaf soluble carbohydrates (δ¹³C_sugar), leaf starch (δ¹³C_starch) and leaf lipids (δ¹³C_lipid) at 8 pm and 4 am, respectively. The carbon isotope composition of leaf bulk tissue (δ¹³C_biomass) was measured once at 8 pm. The amplitude of the nighttime variation in δ¹³C_R (Variation in δ¹³C_R) was estimated as δ¹³C_R-8pm—δ¹³C_R-4am. Differences in the δ¹³C_R between the samples collected at 8 pm and 4 am were assessed by One-way analysis of variance (ANOVA) and the P values are presented.

Species	δ13CR-8pm (‰)	δ13CR-4am (‰)	Variation in δ13CR	P	δ13Cbiomass (‰)	δ13Csugar-8pm (‰)	δ13Csugar-4am (‰)	δ13Cstarch-8pm (‰)	δ13Cstarch-4am (‰)	δ13Cipid-8pm (‰)	δ13Cipid-4am (‰)
L. chinensis	-22.7±0.17	-24.5±0.16	1.8±0.15	<0.01	-26.6±0.21	-27.4±0.55	-27.9±0.23	-24.7±0.17	-25.3±0.38	-29.9±0.36	-29.3±0.47
P. australis	-21.7±0.09	-23.5±0.10	1.8±0.12	<0.01	-25.8±0.13	-29.0±0.17	-29.5±0.10	-22.9±0.32	-24.2±0.10	-30.2±0.31	-29.5±0.32
L. bicolor	-24.9±0.13	-26.6±0.16	1.7±0.26	<0.01	-28.5±0.09	-30.1±0.20	-30.9±0.30	-29.6±0.06	-30.0±0.10	-30.0±0.22	-30.5±0.25
M. asiatica	-21.2±0.17	-24.7±0.16	3.5±0.32	<0.01	-26.8±0.16	-25.5±0.37	-25.6±0.30	-24.0±0.08	-24.5±0.14	-31.3±0.12	-30.6±0.15
P. simonii	-22.9±0.24	-25.6±0.17	2.7±0.26	<0.01	-27.8±0.15	-27.4±0.17	-28.5±0.04	-26.1±0.25	-28.5±0.10	-30.6±0.32	-31.8±0.33
P. salicina	-22.6±0.15	-25.5±0.22	3.0±0.31	<0.01	-26.9±0.18	-25.9±0.26	-25.6±0.08	-25.9±0.21	-25.6±0.16	-30.5±0.13	-29.9±0.17
C. glaucum	-26.0±0.32	-26.1±0.28	0.2±0.47	0.72	-28.5±0.18	-32.6±0.36	-33.3±0.26	-26.6±0.39	-25.4±0.36	-30.9±0.25	-30.3±0.15
G. max	-22.6±0.16	-24.7±0.10	2.2±0.25	<0.01	-27.8±0.07	-28.6±0.35	-28.5±0.35	-26.8±0.12	-27.7±0.10	-32.4±0.24	-32.2±0.25
H. annuus	-26.3±0.31	-28.1±0.26	1.9±0.73	<0.01	-28.2±0.36	-27.7±0.26	-26.8±0.18	-27.0±0.25	-27.6±0.11	-32.3±0.42	-32.1±0.16
S. amara	-25.5±0.16	-25.0±0.30	0.5±0.32	0.17	-28.4±0.12	-29.1±0.05	-29.4±0.06	-27.0±0.12	-26.8±0.23	-31.4±0.09	-31.8±0.23
V. radiata	-19.9±0.19	-23.4±0.07	3.5±0.24	<0.01	-26.5±0.09	-27.5±0.04	-27.6±0.15	-26.4±0.07	-26.7±0.11	-33.0±0.32	-30.6±1.06
V. unguiculata	-23.5±0.32	-27.0±0.41	3.5±0.41	<0.01	-29.3±0.22	-29.3±0.60	-28.1±0.23	-27.4±0.18	-28.8±0.21	-31.1±0.16	-30.8±0.24
X. sibiricum	-23.7±0.22	-24.6±0.26	1.0±0.41	0.02	-26.2±0.27	-25.5±0.14	-25.3±0.29	-24.9±0.29	-24.4±0.26	-29.5±0.20	-29.1±0.20
C. virgata	-8.3±0.17	-10.2±0.10	2.0±0.16	<0.01	-12.8±0.26	-15.5±0.24	-15.6±0.32	-11.8±0.07	-12.1±0.38	-21.7±0.28	-21.9±0.36
E. crusgalli	-9.6±0.12	-11.3±0.08	1.8±0.18	<0.01	-13.2±0.35	-15.7±0.28	-14.1±0.36	-11.6±0.41	-11.2±0.13	-20.1±0.34	-17.9±0.70
H. altissima	-9.4±0.10	-11.4±0.14	2.0±0.21	<0.01	-12.8±0.31	-15.3±0.27	-15.0±0.21	-11.7±0.16	-12.2±0.13	-21.3±0.18	-21.3±0.28
P. miliaceum	-8.9±0.33	-13.1±0.14	4.1±0.33	<0.01	-13.3±0.13	-16.0±0.46	-18.1±0.58	-11.4±0.12	-11.9±0.13	-21.3±0.16	-21.1±0.61
S. italica	-8.6±0.19	-11.9±0.30	3.2±0.39	<0.01	-12.1±0.14	-17.7±0.16	-16.9±0.46	-11.2±0.21	-11.1±0.13	-22.2±0.51	-20.8±0.39
S. viridis	-7.3±0.14	-9.5±0.17	2.2±0.27	<0.01	-12.2±0.07	-13.5±0.19	-19.4±0.24	-11.4±0.04	-11.8±0.29	-21.1±0.52	-20.5±0.64
S. bicolor	-9.5±0.13	-12.2±0.20	2.7±0.18	<0.01	-12.3±0.19	-13.2±0.20	-12.9±0.32	-10.8±0.19	-11.5±0.59	-22.0±0.24	-21.2±0.40
Z. mays	-5.3±0.22	-11.1±0.28	5.8±0.24	<0.01	-12.4±0.19	-14.9±0.71	-13.6±0.28	-10.3±0.09	-11.0±0.44	-22.0±0.68	-21.9±0.35
A. retroflexus	-7.6±0.26	-12.3±0.31	4.7±0.36	<0.01	-12.2±0.13	-16.6±0.74	-16.5±0.58	-10.8±0.45	-12.4±0.39	-21.0±0.50	-20.9±0.45

Data are reported as the mean ±1 SE (n = 5)

Correlations between the nocturnal shift in δ¹³C_R and cumulative carbon assimilation

We calculated the daytime cumulative carbon assimilation, using gas-exchange data to explore the potential effects of the pool size of the daytime cumulative photosynthates on the magnitude of the nighttime variation in δ¹³C_R. A strong positive correlation was found between the amplitude of the nighttime variation in δ¹³C_R and the cumulative carbon assimilation (Fig 2).

Fig 2. Dependence of the amplitude of the variations in δ¹³C of leaf-respired CO₂ (δ¹³C_R, ‰) on the amount of cumulative carbon assimilation (mol CO₂ m^-2 d^-1).

The data contains 19 of the 22 studied species, the exceptions being Chenopodium glaucum, Saussurea amara and Xanthium sibiricum. The r ² and P values are provided. The data are reported as mean ±1 standard error (n = 5).

Respiratory apparent ¹³C/¹²C fractionation

We calculated respiratory apparent ¹³C/¹²C fractionation (Δ_R) relative to the δ¹³C values of the bulk leaf material, soluble carbohydrates (Δ_{R, sugar}), starch (Δ_{R, starch}), and lipids (Δ_{R, lipid}) at 8 pm and 4 am, respectively (Table 5). Differences in Δ_{R, biomass} between the C₃ and the C₄ species were detected at 4 am, but not at 8 pm (Table 3; Fig 3A and 3B). There were no nighttime Δ_{R, biomass} differences among the trees, graminoids and herbs at either 8 pm or 4 am (Table 3; Fig 3A and 3B). Significant differences were found in the Δ_{R, sugar} between the C₃ and the C₄ species at 8 pm (Table 3). Neither photosynthetic pathway nor plant functional type differences in Δ_{R, starch} were detected (Table 3). The C₃ and C₄ plants differed significantly in the Δ_{R, lipid} at both 8 pm and 4 am (Table 3; Fig 3G and 3H). We also detected plant functional type differences in the Δ_{R, lipid} (Table 3), with the Δ_{R, lipid} values in the graminoids being more negative than they were in the trees or herbs (Fig 3G and 3H).

Table 5. Respiratory apparent fractionation.

Respiratory apparent ¹³C/¹²C fractionation (‰) of the nighttime leaf-respired CO₂, comparative to biomass (Δ_{R, biomass}), soluble carbohydrates (Δ_{R, sugar}), starch (Δ_{R, starch}) and lipids (Δ_{R, lipid}) at 8 pm and 4 am, respectively.

Species	ΔR, biomass-8pm (‰)	ΔR, biomass-4am (‰)	ΔR, sugar-8pm (‰)	ΔR,sugar-4am (‰)	ΔR, starch-8pm (‰)	ΔR,starch-4am (‰)	ΔR, lipid-8pm (‰)	ΔR,lipid-4am (‰)
L. chinensis	-4.00±0.28	-2.12±0.27	-4.80±0.69	-3.52±0.28	-2.07±0.48	-0.77±0.52	-7.36±0.51	-4.93±0.60
P. australis	-4.23±0.63	-2.35±0.23	-7.49±0.20	-6.10±0.12	-1.31±0.33	-0.68±0.16	-8.72±0.34	-6.19±0.31
L. bicolor	-3.67±0.31	-1.91±0.26	-5.49±0.21	-4.40±0.43	-4.81±0.15	-3.37±0.21	-5.22±0.27	-4.00±0.34
M. asiatica	-5.72±0.33	-2.19±0.29	-4.42±0.32	-0.97±0.22	-2.90±0.16	0.19±0.23	-10.35±0.20	-6.13±0.13
P. simonii	-5.02±0.43	-2.67±0.33	-4.62±0.39	-3.05±0.18	-3.27±0.40	-3.02±0.25	-7.90±0.55	-6.41±0.29
P. salicina	-4.41±0.41	-1.38±0.33	-3.40±0.40	-0.07±0.20	-3.46±0.34	-0.05±0.27	-8.15±0.27	-4.51±0.12
C. glaucum	-2.60±0.83	-2.44±0.44	-6.86±0.61	-7.41±0.45	-0.70±0.43	0.70±0.37	-5.11±0.45	-4.33±0.40
G. max	-5.35±0.57	-3.16±0.33	-6.14±0.34	-3.85±0.36	-4.28±0.11	-3.08±0.15	-10.06±0.24	-7.65±0.30
H. annuus	-1.99±0.57	-0.08±0.48	-1.49±-0.86	-1.35±0.27	-0.77±0.41	0.55±0.35	-6.21±0.59	-4.06±0.11
S. amara	-3.03±0.52	-3.56±0.96	-3.71±0.14	-4.50±0.32	-1.54±0.23	-1.86±0.10	-6.05±0.20	-7.03±0.41
V. radiata	-6.73±1.03	-3.22±0.52	-7.76±0.20	-4.31±0.11	-6.75±0.29	-3.36±0.13	-13.3±0.51	-7.39±1.08
V. unguiculata	-5.90±0.23	-2.34±0.45	-5.93±0.70	-1.09±0.56	-3.99±0.26	-1.84±0.59	-7.74±0.26	-3.92±0.55
X. sibiricum	-2.60±0.36	-1.62±0.45	-1.92±0.28	-0.73±0.44	-1.25±0.98	0.24±0.37	-5.98±0.39	-4.65±0.36
C. virgata	-4.42±0.26	-2.47±0.29	-7.21±0.19	-5.32±0.35	-3.49±0.11	-1.78±0.38	-13.49±0.20	-11.70±0.35
E. crusgalli	-3.68±0.38	-1.89±0.50	-6.21±0.28	-2.78±0.34	-2.02±0.38	0.12±0.06	-10.6±0.33	-6.68±0.68
H. altissima	-3.44±0.32	-1.39±0.35	-5.94±0.30	-3.58±0.31	-2.31±0.20	-0.72±0.16	-11.97±0.18	-9.93±0.23
P. miliaceum	-4.37±0.49	-0.22±0.30	-7.13±0.41	-5.12±0.65	-2.46±0.34	1.19±0.21	-12.48±0.26	-8.20±0.74
S. italica	-3.49±0.87	-0.24±0.39	-8.92±0.49	-5.09±0.64	-2.59±0.23	0.74±0.34	-13.64±0.38	-9.02±0.45
S. viridis	-4.91±0.20	-2.68±0.19	-10.46±0.21	-9.99±0.19	-4.14±0.12	-2.30±0.18	-13.91±0.50	-11.09±0.59
S. bicolor	-2.81±0.55	-0.04±0.67	-4.00±0.25	-0.71±0.34	-1.30±0.29	0.74±0.43	-12.6±0.22	-9.11±0.38
Z. mays	-7.07±0.61	-1.28±0.38	-9.58±0.75	-2.56±0.40	-4.97±0.14	0.11±0.66	-16.8±0.80	-10.88±0.34
A. retroflexus	-4.72±0.40	-0.04±0.54	-9.07±0.95	-4.31±0.40	-3.24±0.58	-0.08±0.51	-13.53±0.65	-8.69±0.56

Fig 3. Plant functional type differences in respiratory apparent fractionation comparative to leaf bulk materials (Δ_{R, biomass}), soluble carbohydrates (Δ_{R, sugar}), starch (Δ_{R, starch}) and lipids (Δ_{R, lipid}) at 8 pm and 4 am, respectively.

Data are reported as mean ± 1 standard error (n = 5). The different letters within each panel indicate the significant differences (P <0.05) among the plant functional types.

Discussion

Variation in δ¹³C of leaf-respired CO₂

For most of the species studied, leaf-respired CO₂ collected at 8 pm and 4 am differed significant in its carbon isotope composition, with the leaf-respired CO₂ at 8 pm was enriched in ¹³C compared with the evolved CO₂ at 4 am (Table 4). This result is consistent with the findings of previous studies [12, 18, 30]. No significant variation in δ¹³C_R were detected in two C₃ herbs (Chenopodium glaucum and Saussurea amara), which is in agreement with the finding of Priault et al. (2009). However, we observed a significant variation in δ¹³C_R in the other three herbs (Table 4) with the magnitude of the nighttime shift was up to 4.7±0.4‰ in a C₄ herb Amaranthus retroflexus. In contrast with the results of Priault et al. (2009), the three tree species we studied showed significant nocturnal shifts in δ¹³C_R. Large nocturnal shifts in δ¹³C_R have also been reported in other tree species, such as Prosopis velutina and Celtis reticulata [25]. To assess potential plant functional type differences in the magnitude of variation in δ¹³C_R, we grouped the studied species with significant variation in δ¹³C_R according to their differences in photosynthetic pathway and growth form. However, there were no differences in the magnitude of variation in δ¹³C_R between the C₃ and C₄ plants, as well as among the woody plants, herbs and graminoids (Table 3).

The amplitude of the nighttime variation in δ¹³C_R was strongly correlated with the daytime cumulative carbon assimilation (Fig 2). Similar phenomenon has also been reported previously and was mainly attributed to changes in the contribution of light-enhanced dark respiration (LEDR) associated malate decarboxylation to the total respiratory CO₂ flux [8, 14]. In the light, malate, fixed by phosphoenolpyruvate carboxylase (PEPc), accumulates because of the inhibition of the key respiratory enzymes, such as the mitochondrial isocitrate dehydrogenase, the succinate dehydrogenase, and the 2-oxoglutarate dehydrogenase [16, 37]. In darkness, the mitochondrial malic enzyme and the mitochondrial malate dehydrogenase catalyzed decarboxylation of the ¹³C-enriched malate pool caused the respired CO₂ to be ¹³C enriched [38]. In a study by Barbour et al. (2011), they reported the effects of LEDR associated malate decarboxylation on ¹³C-enrichment in leaf-respired CO₂ can last up to 100 min after sunset. For the present study, ¹³C enrichment in leaf-respired CO₂ at 8 pm (40–50 min after sunset) may partially be attributed to the decarboxylation of malate.

Large diel variation in photosynthetic discrimination (Δ_P) has also been hypothesized to affect δ¹³C_R by changing the δ¹³C of the primary respiratory substrates [18, 28]. We observed no significant differences in the primary respiratory sources (soluble carbohydrates, starch, and lipids) between 8 pm and 4 am. A previous report [24] has also found no apparent variation in the δ¹³C of the leaf primary respiratory substrates. However, we could not discount the effects of the changes in the use of respiratory substrates having different δ¹³C, because we, along with most other studies, measured the δ¹³C of the entire leaf respiratory substrate pools. It is difficult to identify the pool size and the isotopic signature of the fast- and the slow-turnover pools.

Other mechanisms, such as heterogeneous ¹³C distribution within hexose molecules and nighttime variation in the utilization of respiratory intermediates [14, 21], short term variation in carbohydrate pool size and respiration rate, have also been employed to explain nighttime variation in δ¹³C_R [15, 16]. However, with the current data set we are unable to test these hypotheses.

Respiratory apparent ¹³C/¹²C fractionation

Leaf-respired CO₂ was enriched in ¹³C compared with the biomass, starch, soluble carbohydrates, and lipids (Table 5). This finding is in agreement with the results of previous studies [16, 19, 27, 28, 39, 40]. ¹³C enrichment in leaf-respired CO₂, relative to the potential respiratory substrates, could be caused by the incomplete oxidation of hexose molecules, which cause a greater ratio of C-3 and C-4 atoms (¹³C enriched compared with other C atoms) being converted to CO₂ [30, 37]. However, there were some differences in the magnitude of the respiratory apparent fractionation between the C₃ and C₄ species, and among the different plant functional types (Fig 3, Table 3). Differences in Δ_{R, biomass} were detected between C₃ and C₄ species at 4 am, but not at 8 pm, which were caused primarily by different magnitude of variation in δ¹³C_R between the two photosynthetic types. In a recent review paper, Ghashghaie & Badeck (2014) reported that C₃ and C₄ species differed in Δ_{R, biomass}. There were no differences in the Δ_{R, biomass} among the trees, the herbs, and the graminoids (Fig 3A), which is in line with the results of Ghashghaie & Badeck (2014). The detected differences in Δ_{R, biomass} between C₃ and C₄ species needs to be incorporated into the partitioning of the CO₂ exchange between the ecosystem and the atmosphere when leaf bulk materials are used as a proxy for δ¹³C_R [25].

Δ_{R, lipid} significantly differed between the C₃ and the C₄ plants, as well as among the plant functional types (Table 3), which could have resulted primarily from the carbon allocation differences associated with the plant functional group types. Compared with the woody plants or the herbs, the grasses allocated a smaller proportion of acetyl CoA to the synthesis of lipids. This leads to grass lipids being generally more depleted compared with the bulk tissue [26, 41].

Soluble carbohydrates are often found to be ¹³C-enriched compared to bulk leaf material [9, 15, 28]. However, we observed that soluble carbohydrates in 16 of the 22 studied species were depleted in ¹³C relative to the leaf biomass (Table 4). Similar results with up to 4‰ depletion in soluble carbohydrates compared to bulk materials have also been reported previously in various C₃ and C₄ species [3535, 36, 42]. This discrepancy may be attributed to both differences in the extraction method and timing of leaf sample collection.

Conclusions

For both the C₃ and the C₄ species (except Chenopodium glaucum and Saussurea amara), the δ¹³C of leaf-respired CO₂ (δ¹³C_R) showed a significant nocturnal shift. The leaf-respired CO₂ at 8 pm was enriched in ¹³C, relative to what it was at 4 am. The amplitude of the nighttime variation in δ¹³C_R was strongly correlated with the daytime cumulative carbon assimilation, which suggests that variation in δ¹³C_R were influenced, to some extent, by changes in the contribution of malate decarboxylation to total respiratory CO₂ flux. There were no differences in the magnitude of the nocturnal shift in δ¹³C_R between the C₃ and C₄ plants, as well as among the woody plants, herbs and graminoids. The plant functional group differences in respiratory apparent fractionation relative to biomass indicate that caution should be exercised when the δ¹³C of bulk leaf material is used as a proxy for the δ¹³C of leaf-respired CO₂.

Data Availability

All relevant data are within the paper.

Funding Statement

This research was supported by National Natural Science Foundation of China (31270445), the State Key Laboratory of Vegetation and Environmental Change (LVEC2012kf01), and Program for New Century Excellent Talents in University (NCET-12-0814). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.