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. 2019 Nov 8;11(6):plz073. doi: 10.1093/aobpla/plz073

Effect of simulated warming on the functional traits of Leymus chinensis plant in Songnen grassland

Rui Guo 1,✉, Ji Zhou 2, Xiuli Zhong 1, Fengxue Gu 1, Qi Liu 1, Haoru Li 1
Editor: Jeff Atkins
PMCID: PMC6986685  PMID: 32010438

Abstract

Leymus chinensis grassland in Northeast China provides a natural laboratory for the investigation of climate change. The response of L. chinensis to experimental warming can provide insight into its regeneration behaviour and the likely composition of future communities under warmer climate. We used MSR-2420 infrared radiators to elevate temperature and examined soil organic carbon and nitrogen and soil total phosphorus and determined the growth and physiology of L. chinensis in response to manipulations of ambient condition and warming. Results showed that compared with the control, L. chinensis subjected to warming treatment showed increased soil organic carbon and soil total nitrogen, but no significant difference was observed in soil total phosphorus. Climate warming increased shoot biomass, ecosystem respiration, and ecosystem water-use efficiency and reduced net ecosystem CO2 exchange and evapotranspiration. This result implies that warming could rapidly alter carbon fluxes. The effect of warming treatment significantly increased the contents of glucose and fructose and significantly inhibited sucrose synthesis. However, the TCA cycle was enhanced when citric and malic acid contents further accumulated. The results implied that L. chinensis probably enhanced its warming adaption mechanism mainly through increasing glycolysis consumption when it was exposed to elevated temperature. These results provide an understanding of the fundamental evidence explaining the primary metabolism of L. chinensis in response to warming and suggest the future impact of the terrestrial carbon-cycle feedback on global climate change.

Keywords: Carbon, growth, L. chinensis, nitrogen, physiology, warming

Understanding how grasses are affected by a long-term increase in temperature is crucial to understanding the future impact of global climate change. Measurements of soil properties, ecosystem gas exchange and physiological characteristics were made in Leymus chinensis grassland under elevated temperatures. The result showed that warming increased the soil organic carbon, soil total nitrogen, shoot biomass, ecosystem respiration and ecosystem water-use efficiency, but reduced net ecosystem CO2 exchange and evapotranspiration. This result implies that warming could rapidly alter carbon fluxes, and L. chinensis probably enhanced its warming adaptation mechanism mainly through increasing glycolysis consumption.

Introduction

Climate change increased production of greenhouse gasses, such as CO2, CH4 and N2O; globally elevated temperatures; and changed precipitation distributions that lead to frequent and intense extreme weather events; these conditions causes deficits in soil water availability, reducing plant yields and degrading natural ecosystems (Florides and Paul 2009; Cheng et al. 2010). According to the United Nations Intergovernmental Panel on Climate Change, the mean global temperature has risen by ~0.76 °C since 1850 and may further rise by 1.88–4.08 °C by the end of the century without policies to reduce greenhouse gas emission (IPCC 2007).

Temperature changes can affect carbon pools and fluxes within these ecosystems and therefore considerably affect the global carbon cycle. A warmer climate can differentially affect gross ecosystem production and ecosystem respiration. Disproportionate increases in carbon uptake can limit the build-up of atmospheric CO2, whereas corresponding increases in carbon release will accelerate this process. The warming also causes a substantial global cycle of nitrogen, generally increasing both the availability and mobility of nitrogen over large regions of land (Vitousek et al. 1997). Therefore, unprecedented global warming will have profound long-term impacts on terrestrial plants and ecosystems. Responses of terrestrial plants and ecosystems to global warming may feed back to climate change via ecosystem and global carbon cycling (Beier et al. 2004).

Grasslands cover ~3.5 billion ha in 2000, and store 20 % of the world’s soil carbon (Ramankutty et al. 2008). Therefore, people significantly rely upon grassland for food and forage (FAO 2009). Global climate change significantly affects grass composition, structure and function through changes in water-use efficiency (WUE), temperature and length of the growing season or by altering the disturbance regimes (Roerink et al. 2003; Mu et al. 2013; Sun et al. 2013). Increased temperatures significantly enhanced the net photosynthetic rate, nutrient availability and lengthening of the growing season; these mechanisms may lead to significant shifts in community structure in a warmer world (Llorens et al. 2004; Verlinden et al. 2014). Global warming seriously affects the circulation of soil nutrients and the relationships among nutrients, including carbon, nitrogen phosphorus (Zhang et al. 2013; Gong et al. 2015). Therefore, it is essential to know the distinctive distribution of soil C, N, P and their responses to global warming. The results will contribute to the understanding of soil nutrient status and may have potential significant implications for the management of grassland restoration. Leymus chinensis is a perennial rhizome grass widely distributed in the Eastern Eurasian Steppe from North Korea westward to Mongolia and Northern China and north-westward to Siberia (Yang and Li 2003). Leymus chinensis accounts for more than two-thirds of the total grassland area in the Songnen Plain in China (Li and Zheng 1997). The use of L. chinensis to investigate responses to climate change in the Songnen region will help the development of effective climate change management strategies.

Warming could alter the plant phonological periods, plant community structure, soil physical and chemical properties as well as ecosystem carbon exchange. However, the some results were not consistent because of the time of warming, warming facilities and different environment conditions. As one of the major methodology in global change research, ecosystem warming studies can facilitate model projections on potential changes in terrestrial biomes in terms of parameterization and validation. In this study, we simulated elevated temperatures in the Songnen grassland under otherwise natural conditions, investigated changes in the L. chinensis physiology responses to warm climate and analysed L. chinensis productivity and conservation of natural grassland ecosystems in response to warm climate change. The results will help ecologists assess and predict the effect of global climate change on major grassland species, such as L. chinensis, and provide a basis for grassland management.

Materials and Methods

Study site and materials

This research was carried out in Chang Ling County, Jilin Province, China (44°30′–44°45′N, 123°31′–123°56′E). This area has a typical mesothermal monsoon climate with dry, windy spring, hot and arid summers and a mean annual rainfall of 400–500 mm predominantly between June and August. The mean annual temperature in the study area was 5.5 °C, and the accumulated temperatures are 2545.6–3374.2 °C. Evaporation in this area greatly exceeds the mean annual rainfall (Shi and Guo 2006). The soil in Songnen grassland is a soda-saline type, the main cation is Na+, and the main anion is HCO3− (Qu and Guo 2003). The Songnen grassland is dominated by L. chinensis, Chloris virgata, Kalimeris integrifolia, Carex duriuscula and Rhizoma phragmitis. The average grass layer height is 80 cm and vegetation coverage is nearly 95 % in the experimental site (Zhang et al. 2014).

Experimental design

The experiment was carried out from April in 2016 to October in 2018 in grassland of the Songnen Plain, and the sites were single dominant L. chinensis communities. We set up eight of 3 m × 4 m plots, four warmed plots, and four control plots with 3 m between each plot. The plots shared similar climatic conditions and soil types. The warmed plots were heated continuously with 165 cm × 15 cm MSR-2420 infrared radiators (Kalglo Electronics, Bethlehem, PA, USA) suspended 2.25 m above the ground (Fig. 1) (Wan et al. 2002). In experiment plots, the mean month temperature is 24.86 ± 0.36 °C and the month precipitation is 88.1 ± 0.88 mm from June to September in 2018. Each plot represented one replicate in all experiments.

Figure 1.

Figure 1.

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The infrared radiator used to simulate the effects of global warming on the community structures in Songnen grassland in northern China.

Measurement of soil properties

Soil temperature and moisture at the depth of 10 cm were measured using an ECH2O dielectric aquameter (Em50, USA), which automatically determined the soil temperature and water content in mid-June, mid-July, early August and mid-September. The electrical conductivity (EC) of the soil was measured using a conductivity meter (DDG-2080-S, Anhui, China). The pH was measured using a PSH-3C pH meter (China).

Soil samples were collected in each plot at depths of 0–10, 10–20, 20–30 and 30–40 cm in middle June, July, August and September in 2018. Afterward, the obtained samples were mixed together to obtain a uniform sample and passed through a 0.25-mm soil sieve after natural drying. The soil organic carbon was measured by potassium dichromate heating (Li et al. 2014). The content of soil total nitrogen was assayed through Kjeldahl determination (De Borba et al. 2014). The content of soil total phosphorus was determined via the sulfuric–perchloric acid method (Bao 2000).

Measurements of ecosystem gas exchange

Ecosystem gas exchange (CO2 and water flux) was measured in a transparent chamber (0.5 m× 0.5 m × 0.9 m) attached to an infrared gas analyser (IRGA; LI-6400, Li-Cor, Lincoln, NE, USA) on one of the two frames in each subplot between 09:00 and 11:00 in the morning. The base of the chamber was sealed while measurements were being carried out, and four small fans ran continuously to mix the air inside the chamber. Nine consecutive readings of CO2 and water vapour concentration were recorded on each base at 10-s intervals during a 90-s period. CO2 and H2O flux rates were determined from the time course of the concentrations and were used to calculate net ecosystem exchange (NEE) and evapotranspiration (ET) rates (Steduto et al. 2002). After measurements, the chamber was vented, replaced on the base and covered with an opaque cloth. CO2 concentration in the chamber then increased steadily and usually replenished ~30 s after the chamber was covered, at which point the CO2 exchange measurements were repeated. Given that the second set of measurements eliminated light (and hence photosynthesis), the values obtained represented ecosystem respiration (ER). Gross ecosystem productivity (GEP) was then calculated as the difference between NEE and ER. Ecosystem WUE was calculated as NEE/ET. Positive NEE values reflect net carbon uptake by the ecosystem, whereas negative values reflect net carbon release.

Measurement of physiological variables

Leymus chinensis was collected carefully from each experimental plot in June, July, August and September in 2018 and then washed with distilled water. The shoots and roots were separated and frozen immediately in liquid nitrogen. The shoots of L. chinensis were oven-dried separately at 80 °C and then ground to powder, which was used for physiological index measurements.

Sugar contents were determined by high-performance liquid chromatography (Shimadu, Kyoto, Japan) with Sugar-Pak I columns (Waters Company, Tokyo, Japan). The mobile phase comprised 0.1 mmol L−1 EDTA·Na2Ca, and the separation was carried out at 70 °C at a flow rate of 0.3 mL min−1. The retention times of sucrose, glucose and fructose were 13.545, 16.740 and 20.349 min, respectively. The sucrose, glucose and fructose contents were calculated according to the chromatographic peak area (Rovio et al. 2008). The contents of citric acid, malic acid and succinic acid were determined by ion chromatography (DX-300 ion chromatographic system) with ICE-AS6 ion-exclusion column.

The concentrations of ions (Na+, K+, Ca2+ and Mg2+) were determined using an atomic absorption spectrophotometer (TAS-990, Purkinje General, Beijing). The concentrations of anions (NO3−, Cl−, SO42− and H2PO4−) were determined using ion-exchange chromatography (DX-300 ion chromatographic system, AS4A-SC ion-exchange column and CD M-II electrical conductivity detector; DIONEX, Sunnyvale, CA, USA) with a mobile phase comprising 1.7 mM Na2CO3 and 1.8 mM NaHCO3 (Yang et al. 2007).

Statistical analysis

Statistical analysis was conducted by repeated measures ANOVA to examine warming effects on soil microclimate, ecosystem C, water fluxes, physiological variables and ions over the growing season in 2018. Between-subject effects were evaluated as warming treatments; within-subject effects were time-of-season. One‐way ANOVA was used to examine the statistical difference in averages for measuring variables among the four months (June, July, August and September). All statistical analyses were conducted with SPSS software (SPSS 19.0 for WINDOWS, Chicago, IL, USA) and standard errors of four replicates.

Results

Measurement of soil properties

Trends in the changes in soil properties under the two treatment conditions were similar, but the change under warming condition was greater than that under ambient condition (Table 1). Experimental warming manipulated with infrared radiators significantly elevated soil temperature (Table 1). Across the whole experimental period, under warming mean soil temperature at 10 cm depth was 1.76 °C higher than ambient condition (Table 1). However, warming decreased seasonal mean soil moisture content significantly as compare with ambient condition (Table 1. There was no significant difference in the EC and pH between treatments (Table 1). Compared with ambient condition, warming showed almost no effect on the contents of soil total P, but soil organic C and soil total N content was increased dramatically (Table 1).

Table 1.

Effects of experimental warming on the growing season mean soil properties of soil temper true (ST), soil moisture (SM), electrical conductivity (EC), pH, soil organic C (SOC), soil total N (STN) and soil total P content (STP). Significant differences between CK and W plots were determined by ANOVA and marked as ‘*’ (P < 0.05). CK, ambient plots; W, warming plots.

Plots/parameters Growing season mean soil properties
ST (°C) SM (v/v %) EC (dS m−1) pH SOC (g kg−1) STN (g kg−1) STP (g kg−1)
CK 0.94 ± 0.32 22.56 ± 4.77* 1.12 ± 0.44 8.42 ± 1.62 10.78 ± 0.69 0.21 ± 0.02 0.38 ± 0.03
W 1.76 ± 0.58* 20.85 ± 5.13 1.26 ± 0.38 8.34 ± 2.21 12.25 ± 0.72* 0.27 ± 0.02* 0.38 ± 0.03
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The flux of carbon, nitrogen and WUE

The shoot biomass showed a peak reflecting seasonal dynamics in all plots, but the mean shoot biomass in the warmed plots (322.76 g m−2) was higher than that in the ambient plots (272.93 g m−2) throughout the growing season (Fig. 2A; Table 2). The season patterns of NEE, ER, GEP and ET were similar and could be expressed a single peak curve. The maximum values appeared in July (Fig. 2B–E). In the control plots, the seasonal mean NEE (8.13 µmol m−2 s−1) and ET (3.86 µmol m−2 s−1) values were 14.35 and 17.10 % higher than those in the warmed plots, whereas ER (−6.72 µmol m−2 s−1) was 27.38 % lower (Fig. 2; Table 2). Gross ecosystem productivity was not significantly different between the two experiment plots (Fig. 2; Table 2). The temporal dynamics of WUE was not obvious, and the low value appeared in September and June in ambient and warmed plots, respectively (Fig. 2F). The seasonal mean WUE (2.06 µmol m−2 s−1) in the control plots was 32.04 % lower than that in the warmed plots (2.72 µmol m−2 s−1; Table 2).

Figure 2.

Figure 2.

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Seasonal dynamics and means (mean ± SE) of (A) shoot biomass, (B) net ecosystem CO2 exchange (NEE), (C) ecosystem respiration (ER), (D) gross ecosystem productivity (GEP), (E) ecosystem evapotranspiration (ET) and (F) ecosystem water-use efficiency (WUE) in experiments plots. CK, ambient plots; W, warming plots. One-way ANOVA was used to examine the statistical difference in averages for measuring variables among the four months (June, July, August and September). Different letters in figures indicate significant difference (P < 0. 05) in seasonal averages for measuring variables among the four months.

Table 2.

Effect of warming on the seasonal averages of shoot biomass (SB), net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), gross ecosystem productivity (GEP), ecosystem evapotranspiration (ET) and ecosystem water-use efficiency (WUE) values. Significant differences between CK and W plots were determined by ANOVA and marked as ‘*’ (P < 0.05). CK, ambient plots; W, warming plots.

Plots/parameters Growing seasonal means of biomass and ecosystem gas exchange parameters
SB (g m−2) NEE (µmol m−2 s−1) ER (µmol m−2 s−1) GEP (µmol m−2 s−1) ET (µmol m−2s−1) WUE (µmol m−2 s−1)
CK 272.93 ± 34.00 8.13 ± 0.55* −6.72 ± −0.59 15.50 ± 1.40 3.86 ± 0.03* 2.06 ± 0.25
W 322.76 ± 41.25* 7.11 ± 0.48 −8.56 ± −0.93* 15.65 ± 1.57 3.20 ± 0.40 2.72 ± 0.34*
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Measurement of sugar and organic acid contents

We have identified sucrose as the major sugar in L. chinensis shoots (Table 3). Compared with ambient plots, the warmed plots showed significantly decreased sucrose contents but dramatically increased glucose and fructose contents (Table 3). In seasonal dynamics, the change trends of sucrose, glucose and fructose were similar, and their maximum value appeared in June and then decreased (Fig. 3A–C). Citric and malic acid contents increased under warming condition, but elevated temperature appeared to not affect succinic acid contents of shoot (Table 3). Citric and malic acid contents increased in July and then decreased during the rest of the season, whereas the contents of succinic acid fell over the same period (Fig. 3D–F).

Table 3.

Effect of warming on the seasonal averages of sucrose, glucose, fructose, citric acid, malic acid and succinic acid. Significant differences between CK and W plots are determined by ANOVA and marked as ‘*’ (P < 0.05). CK, ambient plots; W, warming plots.

Plots/parameters Sugars (µmol g−1 DW) Organic acids (µmol g−1 DW)
Sucrose Glucose Fructose Citric acid Malic acid Succinic acid
CK 241.60 ± 20.93* 42.05 ± 8.60 46.30 ± 8.82 4.65 ± 0.39 28.96 ± 3.11 1.36 ± 0.22
W 186.39 ± 15.07 125.43 ± 13.03* 120.35 ± 14.42* 8.10 ± 0.88* 34.27 ± 4.26* 1.59 ± 0.15
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Figure 3.

Figure 3.

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Seasonal dynamics and means (mean ± SE) of sucrose (A), glucose (B), fructose (C), citric acid (D), malic acid (E) and succinic acid (F) in shoots in experiment plots. CK, ambient plots; W, warming plots. One‐way ANOVA was used to examine the statistical difference in averages for measuring variables among the four months (June, July, August and September). Different letters in figures indicate significant difference (P < 0. 05) in seasonal averages for measuring variables among the four months.

Measurement of cation and anion concentrations

In response to warming, the percentages of K+, Ca2+ and Mg2+ in the shoots increased, whereas Na+ content decreased significantly. However, warming had no significant effect on the levels of the anions Cu2+, Fe2+, Zn2+ and Mn2+ and the cations Cl−, NO3−, H2PO4− and SO42− (Table 4).

Table 4.

Percentage of the contribution of various free ions to total charge on the seasonal averages of L. chinensis shoots tissue in ambient and warmed plots. Significant differences between CK and W plots were determined by ANOVA and marked as ‘*’ (P < 0.05). CK, ambient plots; W, warming plots.

Plots/parameters Anion (%) Cation (%)
K+ Na+ Ca2+ Mg2+ Cu2+ Fe2+ Zn2+ Mn2+ Cl− NO3− H2PO4− SO42−
CK 4.87 20.56* 7.64 7.57 0.87 0.77 0.06 0.06 40.57 0.83 9.59 6.62
W 6.32* 15.41 8.98* 8.83* 0.96 0.91 0.08 0.06 41.23 0.88 9.55 6.79
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Discussion

Soil organic carbon, N and P in response to manipulations of ambient and warm conditions

The unprecedented global warming will have profound long-term impacts on terrestrial plants and ecosystems (Trumbore 1997). Responses of terrestrial plants and ecosystems to global warming may feed back to climate change via ecosystem and global carbon cycling. Soil organic carbon is the active part in soil and is a crucial component of the earth’s carbon; its storage and fluxes play a major role in the global budget of carbon (Mohan et al. 1999). Our results showed that the maximum value of soil organic C appeared in July, and the mean value in growing seasonal under warming treatment was higher by 12.02 % than in ambient condition (Table 1). Combined shoot biomass results in Table 2, implying elevated temperature could stimulate plant activities, meanwhile, soil organic C will increase for more carbon input from plant litter (Zhou et al. 2007). Our results also showed that compared with ambient condition, warming condition increased the content of soil total N, mainly because warming is associated with vigorous seasonal vegetation growth that increases the shoot biomass and the absorption of the nutrients is enhanced. Therefore, large accumulations of available N in soil after mineralization when warming enhanced the rate of microbial activity; a similar result was also reported by Piatek and Allen (1999) and Knoepp and Swank (2002). In the current study, we found that during the growing season, mean soil total P was not affected by warming treatment, though shoot biomass increased need more available P. This phenomenon was probably due to the increase in soil microbial activity that are related to decomposed the litter. A large amount of P is returned to the soil, and the amount of total P is not much changed (Chen et al. 2003).

Effects of elevated temperature on carbon and water fluxes

Warming is an important indicator of global climate change and strongly influences the physiological and ecological characteristics of plants (Billings et al. 1982; Zhou et al. 2007). Our results have shown that elevated temperature increased biomass accumulation in L. chinensis, resulting in increased length and thickness of stems; this condition may also induce the phonological process, stimulating root and microbial respiration (Billings et al. 1982; Knoepp and Swank 2002; Zhou et al. 2007). Therefore, warming induced a significant increase in species richness in the studied meadow steppe community, which is in accordance with the results observed in temperate grasslands and annual grassland (Zavaleta et al. 2010; Yang et al. 2011). In the midsummer months, when the rate of vegetation growth was greatest, the NEE, GEP and ER rates reached their maximum values. Later in the growing season, GEP and ER tended to decrease as senescence occurred and air temperature declined (Fig. 2). Transpiration and soil evaporation also increased with air and soil temperature in spring and early summer, leading to an increase in ET (Fig. 2E). The senescence of plant tissue and falling soil temperature in late autumn generally caused ET decline. Our data concerning seasonal carbon and water flux in the Songnen grassland in Northeastern China were comparable with those reported in other temperate grasslands (Niu et al. 2008). Moreover, our NEE values were similar to those reported for other grassland ecosystems (Flanagan et al. 2002). In this experimental, warming increased ER more than GEP, leading to a decrease in NEE. It implied that warming effect on NEE could be largely attributable to ER, and consequently lower soil moisture. In the other way, warming increased WUE could stimulate root and microbial activities and respiration and the direct positive temperature effect, leading to insignificant changes in GEP. The results also suggested that plant transpiration accounted for the majority of ecosystem ET in the Songnen grassland. A similar result was reported for semiarid grassland in North America and temperate steppes in China (Niu et al. 2008).

Effects of elevated temperature on sugars and organic acids

The L. chinensis stems were long and thick in warming plots, and their formation depends on the accumulative properties of cellulose during fibre thickening development. The accumulation of cellulose is a process related to the decomposition and recycling of sucrose, glucose and fructose sugars; the process is affected by related substances and enzymes (Winter and Huber 2000; Babb and Haigler 2001). Figure 3 shows that sugar contents in L. chinensis declined throughout the growing season, particularly in July. Sucrose is the main storage sugar in L. chinensis. Sucrose contents were lower in plants subjected to warming than that in ambient plots. However, glucose and fructose contents were markedly higher in warming than ambient conditions. Our results indicated that warming might have prompted the sustained increased activities of sucrose synthase and sucrose phosphate synthase, whereas the activity of acid invertase and alkaline invertase decreased, and the sucrose transformed thoroughly (Candace et al. 2001; Saxena and Brown 2000). Thus, glucose and fructose content was increased, and cellulose accumulated sustainably and steadily, resulting in long and thick stems. The results showed that the elevated temperature induced increases of tricarboxylic acid cycle (TCA cycle) intermediates citric acid, malic acid and succinic acid, supporting the notion that TCA cycle processes promotion, probably through warming effects. Organic acids are known to play important roles in osmotic adjustment. Organic acids accumulated in the cytoplasm of L. chinensis cells in warm conditions, helping to balance the osmotic pressure in the vacuoles. This feature may represent a key adaptive mechanism by which L. chinensis maintains homeostasis at elevated temperatures. The results suggest that elevated temperatures caused mass dissipation of energy and enhanced sugar synthesis.

Effects of elevated temperature on ionic balance

The cytoplasm of plant cells usually has low Na+ content and high K+ level to maintain essential enzymatic processes (Munns and Tester 2008). Our results confirmed that competitive relationships exist between K+ and Na+ during their uptake under the conditions of warming. The percentage of Na+ increased, whereas the K+ percentage decreased in shoots of L. chinensis. Ca2+ and Mg2+ are necessary to maintain membrane stability and are important components of cell walls and chlorophyll (Philip and Martin 2003; Parida and Das 2005). The responses of Ca2+ and Mg2+ to elevated temperatures were similar, and their percentages were enhanced in shoots, implying that warming enhanced chlorophyll synthesis and photosynthesis. Thus, warming has a certain adaptation and protection mechanism. The percentages of Cu2+, Fe2+, Zn2+ and Mn2+ to the total ions present were very low. Cl−, NO3−, H2PO4− and SO42− contents increased in L. chinensis plants subjected to warming to balance Na+ influx. This finding suggests that warming may enhance the uptake of anions from the environment.

Conclusion

Simulated global warming increased the content of soil organic C and soil total N but did not influence soil total P in the growing season. We found that the effect of the warming treatment significantly increased the levels of biomass stem fresh weight and stem quality of L. chinensis, whereas experimental warming increased ER, leading to a decrease in NEE and ET. We supposed that the measured C fluxes reduced might be attributed to offsetting of the direct and positive effects of elevated temperature by the indirect and negative effects via exacerbating osmotic stress. On the other hand, warming induced metabolic changes in sugar synthesis. The enhanced formation of sugars was established probably as a reaction to attenuate the osmotic stress caused by warming. The active synthesis of organic acids in leaves was essential to adaption of high temperature. To adapt to elevated temperature, L. chinensis accumulated K+ and reduced Na+ to maintain the intracellular ion balance and a number of enzymatic processes.

Sources of Funding

This work was supported by the Project of the National Natural Science Foundation of China (grant no. 31570328).

Contributions by the Authors

R.G. designed the research. J.Z. and R.G. performed the research. X.L.Z., F.X.G. and R.G. analysed the data, and R.G., J.Z., X.L.Z., F.X.G., Q.L. and H.R.L. wrote the paper. All authors reviewed the manuscript.

Conflict of interest

None declared.

Acknowledgements

We thank International Science Editing for language editing. We are also grateful to Mr Junliang Deng (Biotree Biotechnology Co., Ltd, Shanghai, China) for providing helps in data measure and analyses.

Literature Cited

  1. Babb VM, Haigler CH. 2001. Sucrose phosphate synthase activity rises in correlation with high-rate cellulose synthesis in three heterotrophic systems. Plant Physiology 127:1234–1242. [PMC free article] [PubMed] [Google Scholar]
  2. Bao SD. 2000. Soil assay on properties of agro-chemistry, 3rd edn. Beijing: Nanjiang Agriculture University: China Agriculture Press. [Google Scholar]
  3. Beier C, Emmett B, Gundersen P, Tietema A, Penuelas J, Estiarte M, Gordon C, Gorissen A, Llorens L, Roda F, Williams D. 2004. Novel approaches to study climate change effects on terrestrial ecosystems in the field: drought and passive nighttime warming. Ecosystems 6:583–597. [Google Scholar]
  4. Billings WD, Luken JO, Mortensen DA, Peterson KM. 1982. Increasing atmospheric carbon dioxide: possible effects on arctic tundra. Oecologia 58:286–289. [DOI] [PubMed] [Google Scholar]
  5. Candace HH, Milka ID, Patrick SH, Vadim VS, Sangjoon H, Kirt M, Deborah PD. 2001. Carbon partitioning to cellulose synthesis. Plant Molecular Biology 47:29–51. [PubMed] [Google Scholar]
  6. Chen CR, Condron LM, Davis MR, Sherlock RR. 2003. Seasonal changes in soil phosphorus and associated microbial properties under adjacent grassland and forest in New Zealand. Forest Ecology and Management 177:539–557. [Google Scholar]
  7. Cheng WG, Sakai H, Yagi K, Hasegawa T. 2010. Combined effects of elevated [CO2] and high night temperature on carbon assimilation, nitrogen absorption, and the allocations of C and N by rice (Oryza sativa L.). Agricultural and Forest Meteorology 150:1174–1181. [Google Scholar]
  8. De Borba BM, Jack RF, Rohrer JS, Wirt J, Wang D. 2014. Simultaneous determination of total nitrogen and total phosphorus in environmental waters using alkaline persulfate digestion and ion chromatography. Journal of Chromatography. A 1369:131–137. [DOI] [PubMed] [Google Scholar]
  9. FAO 2009. Agriculture and environmental challenges of the twenty-first century: a strategic approach for FAO. Rome: Food and Agriculture Organization of the United Nations. [Google Scholar]
  10. Flanagan LB, Wever LA, Carlson PJ. 2002. Seasonal and interannual variation in carbon dioxide exchange and carbon balance in a northern temperate grassland. Global Change Biology 8:599–615. [Google Scholar]
  11. Florides GA, Christodoulides P. 2009. Global warming and carbon dioxide through sciences. Environment International 35:390–401. [DOI] [PubMed] [Google Scholar]
  12. Gong SW, Guo R, Zhang T, Guo JX. 2015. Warming and nitrogen addition increase litter decomposition in a temperate meadow ecosystem. PLoS One 10:e0116013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. IPCC 2007. IPCC WGI fourth assessment report. Climatic change: the physical science basis. Geneva: Intergovernmental Panel on Climate Change. [Google Scholar]
  14. Knoepp JD, Swank WT. 2002. Using soil temperature and moisture to predict forest soil nitrogen mineralization. Biology and Fertility Soils 36:177–182. [Google Scholar]
  15. Li JD, Zheng HY. 1997. The control of alkalinized-salinized grasslands in the Songnen Plain and their mechanisms. Beijing: Science Press. [Google Scholar]
  16. Li YJ, Zhu Y, Zhao JN, Li G., Wang H, Lai X, Yang DL. 2014. Effects of rest grazing on organic carbon storage in Stipa grandis steppe in Inner Mongolia, China. Journal of Integrative Agriculture 3:624–634. [Google Scholar]
  17. Llorens L, Peñuelas J, Estiarte M, Bruna P. 2004. Contrasting growth changes in two dominant species of a Mediterranean shrubland submitted to experimental drought and warming. Annals of Botany 94:843–853. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Mohan KW, Fatih E, Tristram O. 1999. Assessing terrestrial ecosystem sustainability: usefulness of regional carbon and nitrogen models. Nature and Resources 35:21–33. [Google Scholar]
  19. Mu SJ, Yang HF, Li JL, Chen YZ, Gang CC, Zhou W, Ju WM. 2013. Spatio-temporal dynamics of vegetation coverage and its relationship with climate factors in Inner Mongolia, China. Journal of Geographical Sciences 23:231–246. [Google Scholar]
  20. Munns R, Tester M. 2008. Mechanisms of salinity tolerance. Annual Review of Plant Biology 59:651–681. [DOI] [PubMed] [Google Scholar]
  21. Niu SL, Wu MY, Han Y, Xia JY, Li LH, Wang SQ. 2008. Water-mediated responses of ecosystem carbon fluxes to climatic change in a temperate steppe. New Phytologist 17:209–219. [DOI] [PubMed] [Google Scholar]
  22. Parida AK, Das AB. 2005. Salt tolerance and salinity effects on plants: a review. Ecotoxicology and Environmental Safety 60:324–349. [DOI] [PubMed] [Google Scholar]
  23. Philip JW, Martin RB. 2003. Calcium in plants. Annals of Botany 92:487–511. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Piatek KB, Allen HL. 1999. Nitrogen mineralization in a pine plantation 15 years after harvesting and site preparation. Soil Science Society of America Journal 63:990–998. [Google Scholar]
  25. Qu G, Guo J. 2003. The relationship between different plant communities and soil characteristics in Songnen grassland. Acta Prataculturae Sinica 12:18–22. [Google Scholar]
  26. Ramankutty N, Evan AT, Monfreda C, Foley JA. 2008. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochemical Cycles 22:GB1003. [Google Scholar]
  27. Roerink GJ, Menenti M, Soepboer W, Su Z. 2003. Assessment of climate impact on vegetation dynamics by using remote sensing. Physics and Chemistry of the Earth, Parts A/B/C 28:103–109. [Google Scholar]
  28. Rovio S, Simolin H, Koljonen K, Sirén H. 2008. Determination of monosaccharide composition in plant fiber materials by capillary zone electrophoresis. Journal of Chromatography. A 1185:139–144. [DOI] [PubMed] [Google Scholar]
  29. Saxena IM, Brown RM Jr. 2000. Cellulose synthases and related enzymes. Current Opinion in Plant Biology 3:523–531. [DOI] [PubMed] [Google Scholar]
  30. Shi LX, Guo JX. 2006. Changes in photosynthetic and growth characteristics of Leymus chinensis community along the retrogression on the Songnen grassland in northeastern China. Photosynthrtica 44:542–547. [Google Scholar]
  31. Steduto P, Çetinkökü Ö, Albrizio R, Kanber R. 2002. Automated closed-system canopy-chamber for continuous field-crop monitoring of CO2 and H2O fluxes. Agricultural and Forest Meteorology 111:171–186. [Google Scholar]
  32. Sun J, Cheng GW, Li WP, Sha YK, Yang YC. 2013. On the variation of NDVI with the principal climatic elements in the Tibetan Plateau. Remote Sensing-Basel 5:1894–1911. [Google Scholar]
  33. Trumbore SE. 1997. Potential responses of soil organic carbon to global environmental change. Proceedings of the National Academy of Sciences of the United States of America 94:8284–8291. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Verlinden M, De Boeck HJ, Nijs I. 2014. Climate warming alters competition between two highly invasive alien plant species and dominant native competitors. Weed Research 54:234–244. [Google Scholar]
  35. Vitousek PM, Aber JD, Howarth RW. 1997. Human alteration of the global nitrogen cycle: causes and consequences. Ecological Applications 7:737–750. [Google Scholar]
  36. Wan SQ, Lou Y, Wallace LL. 2002. Changes in microclimate induced by experimental warming and clipping in tall grass prairie. Global Change Biology 8:754–768. [Google Scholar]
  37. Winter H, Huber SC. 2000. Regulation of sucrose metabolism in higher plants: localization and regulation of activity of key enzymes. Critical Reviews in Biochemistry and Molecular Biology 35:253–289. [DOI] [PubMed] [Google Scholar]
  38. Yang C, Chong J, Kim C, Li C, Shi D, Wang D. 2007. Osmotic adjustment and ion balance traits of an alkaline resistant halophyte Kochia sieversiana during adaptation to saline and alkaline conditions. Plant and Soil 294:263–276. [Google Scholar]
  39. Yang YF, Li JD. 2003. Convergent growth patterns of leaf populations of Leymus chinensis and Hordeum brevisubulatum of cultivated pasture on the Songnen Plains of China. Acta Prataculturae Sinica 12:38–47. [Google Scholar]
  40. Yang H, Wu M, Liu W, Zhang Z, Zhang N, Wan S. 2011. Community structure and composition in response to climate change in a temperate steppe. Global Change Biology 17:452–465. [Google Scholar]
  41. Zavaleta ES, Pasari JR, Hulvey KB, Tilman GD. 2010. Sustaining multiple ecosystem functions in grassland communities requires higher biodiversity. Proceedings of the National Academy of Sciences of the United States of America 107:1443–1446. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Zhang T, Guo R, Gao S, Guo JX, Sun W. 2014. Response of plant community composition and productivity to warming and nitrogen deposition in a temperate meadow ecosystem. Biogeosciences 11:1–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Zhang NY, Guo R, Song P, Guo JX, Gao YZ. 2013. Effects of warming and nitrogen deposition on the coupling mechanism between soil nitrogen and phosphorus in Songnen meadow steppe, northeastern China. Soil Biology & Biochemistry 65:96–104. [Google Scholar]
  44. Zhou XH, Wan SQ, Luo YQ. 2007. Source components and interannual variability of soil CO2 efflux under experimental warming and clipping in a grassland ecosystem. Global Change Biology 13:761–775. [Google Scholar]

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