Variation of Q₁₀ values in a fenced and a grazed grassland on the loess plateau, northwestern China

Abstract

Soil respiration (SR) and microbial respiration (MR), which were primarily regulated by soil temperature, can act as a feedback to climate change. Although many studies suggest that global warming will accelerate carbon dioxide (CO₂) emissions from soil, the magnitude of this feedback is unknown, mostly due to uncertainty in the temperature sensitivity (Q₁₀, increaing ratio of SR and MR after a 10°C increase of temperature) of SR and MR. To investigate the seasonal variation of short-term Q₁₀ and estimate how grazing impacts temperature sensitivity of SR and MR, we measured SR and MR in a fenced and a grazed grassland on the loess plateau, northwestern China, during 2008–2010. In this semiarid grassland ecosystem, soil temperature was the dominant factor controlling SR and MR during the experimental period. Short-term apparent Q₁₀ of SR and MR had a clearly seasonal variation, and was significantly and negatively related to soil temperature at 2-cm depth. However, no relationship was found between soil moisture (0–10 cm soil layer) and apparent Q₁₀. By decreasing soil organic carbon and root biomass, grazing reduced the long-term Q₁₀ of SR and MR. In both the short term and the long term, Q₁₀ of MR was lower than that of SR, suggesting that autotrophic respiration is more sensitive than heterotrophic respiration to temperature. We emphasize the importance of using Q₁₀ when modeling trajectories of soil carbon stocks under climate change scenarios, and the seasonal variation of Q₁₀ should also be regarded as a parameter in the global carbon models.

Key words:

• soil respiration
• microbial respiration
• apparent Q₁₀
• grazing
• soil temperature

1. INTRODUCTION

Because soil respiration (SR) is an essential process of the global carbon cycle, SR has attracted considerable research interest in recent years. Even subtle changes in climate (e.g., atmospheric temperature, nitrogen deposition) could trigger significant changes in SR, which would markedly alter ecosystem carbon budgets. Aside from its large quantity, SR is exponentially related to soil temperature which has dramatically increased during the last three decades, and will continue to increase in this century (IPCC 2007) in most ecosystems (e.g., Xu and Qi 2001b; Sampson et al. 2007). Other factors can also profoundly influence SR, such as soil quality (soil organic carbon), nitrogen deposition, climate conditions and human disturbance (Qi et al. 2002; Davidson and Janssens 2006; Davidson et al. 2006; Mo et al. 2007). Among all factors, Jones et al. (2003) suggested that climate change, particularly rising temperature, was the major cause of increasing SR. Q₁₀ of SR under temperature T defined as SR_T+10/SR_T, where SR_T was soil respiration under soil temperature of T°C (Pang et al. 2013), was used to describe the sensitivity of SR to temperature, and was usually estimated based on empirical functions (e.g., exponential equation) between soil temperature and SR (Lloyd and Taylor 1994). An increase in this apparent Q₁₀ in response to rising temperature is expected to have a positive feedback to global warming (Jenkinson et al. 1991; Raich and Schlesinger 1992). Nonetheless, the magnitude of this feedback is uncertain.

SR can be partitioned into two dominant fluxes (controlled by distinct processes): plant root respiration (autotrophic respiration; RR) and soil organic carbon (SOC) decomposition by soil fauna and soil microbes (heterotrophic respiration or microbial respiration; MR) (Hanson et al. 2000). Accordingly, the response of SR to temperature is determined by the effects of temperature on RR, MR and their interactions, which are also impacted by soil moisture, nutrient cycling, substrate availability and plant species traits (Cornwell et al. 2008). The apparent Q₁₀ value of MR is one of the most important uncertainties in predicting future climate and terrestrial ecosystem function (Holland et al. 2000; Jones et al. 2003; Lenton and Huntingford 2003). If global warming from anthropogenic carbon dioxide (CO₂) stimulates the decomposition of SOC, the extra CO₂ efflux may accelerate the warming trend, forming a positive feedback (Jenkinson et al. 1991). The strength of this feedback largely depends on the realized temperature sensitivity of MR (Q₁₀). Therefore, the SOC decomposition response to temperature has been extensively studied in recent years. Despite numerous studies, the temperature sensitivity of MR remains controversial (Davidson and Janssens 2006; Kirschbaum 2006; Hakkenberg et al. 2008). For example, Suseela et al. (2012) found the temperature sensitivity of heterotrophic respiration was unresponsive to warming treatments; however, a reduction of the temperature sensitivity of soil organic matter decomposition with sustained temperature increasing was reported by Craine et al. (2013). The causes of this controversy may stem from confounding controlling factors such as soil moisture and substrate availability (Davidson and Janssens 2006; Kirschbaum 2006).

Confounding factors such as plant phenological processes (Curiel Yuste et al. 2004) and soil water status (Gaumont-Guay et al. 2006) can cause a discrepancy between long-term (e.g., annual) and short-term (e.g., diel) temperature response parameters (Q₁₀). The apparent annual Q₁₀ value of SR and MR may not reflect the true biotic temperature sensitivity if obscured by seasonally varying factors other than soil temperature (Curiel Yuste et al. 2004). This is consistent with the ongoing debate on the use of a fixed (universal) vs. variable (environmentally controlled) Q₁₀ in carbon cycle prediction (Mahecha et al. 2010). Single-site studies have reported large seasonal variation and temperature dependence of short-term unconfounded Q₁₀ estimates for SR in forest ecosystems cycle modeling (Janssens and Pilegaard 2003; Curiel Yuste et al. 2004; Gaumont-Guay et al. 2006). Because a small deviation of the Q₁₀ of SR may cause a significant bias in the estimate of SR (Xu and Qi 2001a), the use of a constant, seasonal Q₁₀ in models may result in significant errors in predictions of future soil carbon losses. Therefore, estimating both long-term and short-term apparent Q₁₀ of SR and MR may provide insights into the mechanisms driving soil and microbial respiration in a grassland, and aid in model parameterization.

Many studies have shown that warming accelerates MR, but most of these studies have examined soil in controlled laboratory conditions without considering many environmental constraints that could affect temperature sensitivity of organic matter decomposition. By using a root-exclusion method to partition SR, most of the ecosystem-scale experiments to date have focused on the contribution of RR and MR to total SR (Gaumont-Guay et al. 2008; Li et al. 2010; Ruehr and Buchmann 2010; Subke et al. 2011), rather than the effects of climate change on the components of SR and the Q₁₀ values of each component. In this study, we compared the apparent Q₁₀ of SR and MR by using a trenching method in a fenced grassland and a grazed grassland on the loess plateau, China. Specifically, our objectives were: (1) to investigate the variation of short-term Q₁₀ of SR and MR in both fenced and grazed grassland; (2) to determine how soil temperature and moisture influence the short-term Q₁₀ of SR and MR. In addition, as reported, grazing could influence the soil CO₂ efflux (Wayne et al. 2008) and thereby SR sensitivity to temperature in grasslands (Paz-Ferreiro et al. 2012); one of our goals was to examine grazing effects on the long-term Q₁₀ of SR and MR.

2. MATERIALS AND METHODS

2.1 Study sites

The experiment was conducted at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL), located at 35°57′N, 104°09′E (Gansu province, China), with a continental semiarid climate. A grazed grassland (G+) with a grazing rate of ~2 sheep per hectare and a fenced grassland (G–; about 500 m away, and fenced in 2005 to protect from grazing since then) were selected as the experimental site. The elevation of the site is 1966 m above sea level, the mean annual air temperature is 6.7°C and the mean annual precipitation is 382 mm. The soil is classified as a Sierozem, a calcareous soil which is characteristic of the loess plateau. The experimental site was a cultivated cropland before 1986, and had been restored from long-term farming since then. We divided the fenced and grazed grasslands into three subplots (50 m × 50 m) as replicates. The dominant plant species at the site were Stipa bungeana, Tripolium vulgare Ness. and Artemisia frigida.

2.2 Partitioning SR

We partitioned SR into MR and RR using the trench method described by Li et al. (2010). In each subplot of both fenced and grazed grassland, 12 plots (0.5 m × 0.5 m in scale; plots were arranged in two lines, six plots in one line; and plots were separated by walkways of about 5 m) were selected as root-free plots, and close to (about 0.5 m from) each root-free plot, one control plot was selected (same size with root-free plots, and 12 control plots in total). In early May 2007, trenches (0.1 m wide and 0.5 m deep, based on the root status in the local grassland) were excavated around each root-free plot. After lining the trench with nylon mesh (0.038-mm mesh size), soil was refilled into the trench. This mesh prevents root growth into the plots but allows the movement of water, bacteria, organic matter and minerals (Moyano et al. 2007). The root-free plots were then kept free of vegetation by manual cutting (per fortnight) throughout the study, while extra care was taken to minimize disturbance to the soil. According to Li et al. (2010), the CO₂ efflux measured in the root-free plots represents MR, while CO₂ efflux measured in the control plots represents SR. To minimize the error caused by the trench method, another 12 root-free plots in each subplot were rebuilt in May of each year during the experimental period (2008–2010), and each root-free plot was only used 1 year for the measurement of microbial respiration. All root-free plots were put to use for at least 8 months after the trenches had been built, in order to make sure the initial roots in the root-free plots were decomposed completely.

2.3 Measuring protocols

2.3.1 Soil respiration (SR) and microbial respiration (MR)

Soil CO₂ efflux was measured on a clear day of each month in the growing season during 2008–2010 (for fenced grassland, 2008–2010; and for grazed grassland, 2009–2010). Before each sampling day, one polyvinyl chloride (PVC) collar (11 cm in diameter and 5 cm in height) was inserted into the soil to a 3-cm depth in each root-free plot and control plot in order to reduce CO₂ efflux caused by disturbance. In the control plots, the plants in the collar were removed before the measurement in each sampling day. SR and MR were measured using a LI-6400 portable photosynthesis system attached to a soil CO₂ flux chamber (991 cm³ in total volume; LI-COR 6400-09TC, LI-COR Inc., Lincoln, NE, USA). To avoid any pulse effect of precipitation on soil CO₂ efflux, measurements were taken on the third or fourth day after a rain event. SR in each control plot and MR in each root-free plot were measured once a measuring day at 8:00 am and 11:00 am (local time). Each measurement usually took 1–2 minutes.

2.3.2 Soil temperature and moisture

Soil temperature and volumetric soil moisture were determined simultaneously with each measurement of soil CO₂ flux. Soil temperature was measured using a thermocouple probe connected to the LI-6400 at a depth of 2 cm adjacent to each PVC collar, and volumetric soil moisture was determined at a depth of 0–10 cm using a TRIME TDR probe (IMKO, Ettlingen, Germany) adjacent to the sites where PVC collars were located.

2.3.3 Root biomass

Six quadrats were built in each subplot for measurements of root biomass in September of each year in both fenced and grazed grassland. Underground soil samples were recovered with an auger (9.3 cm inner diameter). In each quadrat, three soil cores to a depth of 50 cm were taken and divided into five 10-cm soil columns. Roots were collected by washing over a 0.5-mm sieve. No attempt was made to separate live and dead roots. To determine dry weight, all the samples were oven-dried at 85°C until a constant weight was reached.

2.3.4 Soil organic carbon (SOC)

In order to identify grazing effect on soil organic carbon, soil samples were collected in May of every year using an auger (5.5 cm inner diameter). In each control plot, one soil core to a depth of 10 cm was taken, then sieved through a 2-mm sieve. Soil organic carbon was determined with the oil bath–potassium dichromate (K₂CrO₇) titration method (oxidization with dichromate in presence of sulfuric acid (H₂SO₄), heated at 180°C for 5 minutes).

2.4 Data analyses and statistics

An exponential equation (Eq. 1) was selected to determine the relationships between CO₂ flux and soil temperature (Suseela et al. 2012):

(1)

where CO₂ flux stands for SR and MR, T is measured soil temperature at a depth of 2 cm, and α and β are regression coefficients.

The apparent Q₁₀ values used in this study were calculated according to the following equation (Eq. 2) which was derived from Eq. 1 (Lloyd and Taylor 1994):

(2)

where β is the coefficient from Eq. 1. The short-term apparent Q₁₀ values (exempt from seasonally confounding effects) were attained by the regression based on one day measurement (one measuring day timescale), while the long-term apparent Q₁₀ was based on the entire experimental data (entire experimental timescale). For increasing the accuracy, all data in both fenced and grazed grassland (from three subplots) were parameterized into one regression equation. Then, in each sampling day, we only got one Q₁₀ value for both fenced and grazed grassland, and the standard error (SE) of apparent Q₁₀ values were computed by the method of Tu et al. (2011).

We averaged SR and MR from the 12 collars in each subplot, and the means were used to represent each subplot for analysis. Data analyses were performed with SPSS 17.0 for Windows (USA). The independent T-test was employed to estimate the effect of grazing on SR and MR. One-way analysis of variance (ANOVA) was used to test the seasonal variations of SR and MR in both lands. An exponental equation was fitted for the relationships between short-term apparent Q₁₀ values and soil temperature. There was no significant correlation between short-term apparent Q₁₀ and soil moisture during the entire experiment. Statistical significance was defined at the 95% confidence level. The values in the text are means ± SE.

3. RESULTS

3.1 Soil microclimate, SR, MR and their relationships

The seasonal variation of soil temperature, soil moisture, and SR and MR from 2008 to 2010 are presented in Fig. 1. The soil temperature and moisture were not affected by trenching and grazing, and both variables exhibited clear seasonal patterns in all plots (P < 0.001, Fig. 1a–b). SR and MR also showed similar seasonal variations (P < 0.001), and SR in both fenced and grazed grassland was significantly higher than MR (Fig. 1c). Additionally, SR and MR in fenced grassland were higher than that in grazed grassland (Fig. 1c). SR and MR peaked in the growing season and bottomed out in winter during the whole experimental period. It appeared that SR and MR co-varied with soil temperature (Fig. 1a and c). During the entire study period, SR and MR were strongly correlated with soil temperature (r from 0.91 to 0.97, Table 1; Fig. 2a), but not with soil moisture (Fig. 2b).

Table 1 Regression equation of soil and microbial respiration and soil temperature (2008–2010).

	SR	R^2	MR	R^2
Fenced grassland	SR = 0.49e^0.0558T	0.94	MR = 0.34e^0.0505T	0.89
Grazed grassland	SR = 0.36e^0.0519T	0.82	MR = 0.22e^0.0438T	0.91

Note: SR, soil respiration; MR, microbial respiration; T, soil temperature at 2 cm.

Figure 1 Seasonal variations in soil temperature (a: 2 cm), soil volumetric moisture (b: 0–10 cm) and soil and microbial respiration (c) measured in fenced (G–, 2008–2010) and grazed grassland (G+, 2009–2010). The bars in (b) represent precipitation. CO₂: carbon dioxide.

Figure 2 The relationship between soil respiration (SR) and microbial respiration (MR), and (a) soil temperature, and (b) soil moisture during the entire experiment. The open and black triangles indicate the data of SR and MR in the grazed grassland (G+); and open and black circles are data of SR and MR in the fenced grassland (G–). The solid line indicates the relationship between SR and soil temperature in G–; the medium dashed line shows the relationship between MR and soil temperature in G–; the long dashed line shows the relationship between SR and soil temperature in G+; and the short dashed line shows the relationship between MR and soil temperature in G+. CO₂: carbon dioxide.

3.2 Seasonal variation of short-term apparent Q₁₀ values of SR and MR

Regardless of treatments, the short-term apparent Q₁₀ values of SR and MR showed clear seasonal variation (Fig. 3). The Q₁₀ values of MR ranged from 1.19 to 10.36 and 1.42 to 8.06 in the fenced grassland and grazed grassland respectively, while Q₁₀ values of SR ranged from 1.27 to 5.76 and 1.53 to 7.34 in the fenced grassland and grazed grassland respectively (Fig. 3). Q₁₀ values of SR and MR in the growing season were lower than in the dormant season in the whole study period, and SR and MR exhibited no significant difference on short-term Q₁₀ values in the growing season. Additionally, grazing did not affect the short-term apparent Q₁₀ values of SR and MR significantly. In April and May of 2009 and October of 2010, Q₁₀ values of MR were significantly higher than those of SR in fenced grassland (Fig. 3b–c).

Figure 3 Seasonal variations of short-term Q₁₀ (temperature sensitivity) values of soil respiration (SR) and microbial respiration (MR) in the fenced grassland (G–, 2008–2010) and grazed grassland (G+, 2009–2010).

3.3 Controlling factors of apparent Q₁₀ values

An exponential regression was used to fit the relationship between short-term apparent Q₁₀ of SR and MR and soil temperature, and we found a negative correlation (P < 0.05) between short-term apparent Q₁₀ of SR and MR and soil temperature in both fenced and grazed grassland (Fig. 4). However, short-term apparent Q₁₀ values of SR and MR in both grasslands were not correlated to soil moisture (P > 0.05, Fig. 5).

Figure 4 Relationships between short-term Q₁₀ values and soil temperature (at 2 cm depth). (a) Q₁₀ of microbial respiration (MR) in the fenced grassland (G–); (b) Q₁₀ of soil respiration (SR) in G–; (c) Q₁₀ of MR in the grazed grassland (G+); (d) Q10 of SR in G+.

Figure 5 Relationships between short-term Q₁₀ values and soil moisture (0–10 cm). Black circles: Q₁₀ of microbial respiration (MR) in the fenced grassland (G–); open circles: Q₁₀ of soil respiration (SR) in the fenced grassland (G–); black triangles: Q₁₀ of microbial respiration in the grazed grassland (G+); open triangles: Q₁₀ of soil respiration in the grazed grassland (G+).

By analyzing the long-term apparent Q₁₀ values, we found that fenced grassland had larger long-term apparent Q₁₀ values of SR and MR when compared to grazed grassland (Table 2). In addition, long-term apparent Q₁₀ values of MR in both grasslands were lower than those of SR (Table 2). Mean SR in fenced grassland was significantly higher than in grazed grassland, and so was mean MR (P < 0.001, Table 2). In addition, mean MR values were lower than mean SR values. Means of root biomass (0–50 cm) and soil organic carbon (0–10 cm) in fenced grassland were significantly higher than in grazed grassland (P < 0.001, Table 2).

Table 2 Long-term apparent Q₁₀ (temperature sensitivity) values and means of soil and microbial respiration, root biomass and soil organic carbon in the fenced and grazed grassland during the entire experimental period.

	SR (μmol CO2 m^−2 s^−1)	Q10 of SR	MR (μmol CO2 m^−2 s^−1)	Q10 of MR	Root biomass (g m^−2)	SOC (g kg^−1)
Fenced grassland	1.47 ± 0.16 a	1.75	1.06 ± 0.09 a	1.66	327.21 ± 20.28 a	8.71 ± 0.18 a
Grazed grassland	0.93 ± 0.06 b	1.68	0.66 ± 0.07 b	1.55	271.94 ± 6.21 b	7.67 ± 0.21 b

Note: CO₂, carbon dioxide; SR, soil respiration; MR, microbial respiration; SOC, soil organic carbon. Different letters in the same column indicate a signficant difference between fenced and grazed grassland.

4. DISCUSSION

4.1 The seasonal variation of short-term apparent Q₁₀ of SR and MR

Our study indicated that short-term apparent Q₁₀ of SR and MR had a clear seasonality, which is consistent with the recent results of Jia et al. (2013) and Suseela et al. (2012). Jia et al. (2013) found that short-term Q₁₀ was higher in the beginning of the growing season in a Chinese pine (Pinus tabulaeformis) plantation. Similarly, Suseela et al. (2012) indicated that Q₁₀ values in summer were lower than in fall and spring.

Short-term Q₁₀ of SR and MR decreased with increasing soil temperature (Fig. 4), which was consistent with many previous studies (Kirschbaum 1995; Janssens and Pilegaard 2003; Curiel Yuste et al. 2004; Chen and Tian 2005; Gaumont-Guay et al. 2006; Peng et al. 2009; Wang et al. 2010). The reduction in Q₁₀ with increasing soil temperature may be explained by the changes of limitation for SR and MR, from acclimation of enzymatic activity at low temperatures to limitation by substrate supply at high temperatures (Reichstein et al. 2005a; Gaumont-Guay et al. 2006). In addition, because Q₁₀ is increasing in rate, it must be largely affected by the initial value. The same increment would be evaluated higher when the original value is smaller, and vice versa. For example, when the original respiration is very low (e.g., MR in October 2010, Fig. 1c), it would be easy to increase. However, if the initial respiration is high enough (e.g., SR in May 2008, Fig. 1c), it would hardly increase. This is one of the major reasons why Q₁₀ takes a lower value under high soil temperature where respiration is already high enough. Soil moisture has been reported to regulate the seasonal temperature response of SR: e.g., Q₁₀ decreases during drought (Xu and Qi 2001a; Craine and Gelderman 2011; Suseela et al. 2012). However, as reported by Luan et al. (2013) and Jia et al. (2013), the short-term apparent Q₁₀ values of SR and MR had no significant relationship with soil moisture (Fig. 5) in this study. Therefore, we suggest that SR and MR were mainly controlled by soil temperature, and less affected by soil moisture (Fig. 2) in this semiarid ecosystem. The lack of regulation of SR by soil moisture has also been reported for temperate and boreal coniferous forests (Gaumont-Guay et al. 2008; Vargas et al. 2010; Jia et al. 2013) and an alpine meadow on the Tibetan Plateau (Suh et al. 2009). The relatively low soil moisture values (Fig. 1) may help explain the absence of a soil moisture effect on SR and MR (Jia et al. 2013). This implies that there is a complex relationship between Q₁₀ and soil moisture, which may result in contradictory results. Further research is needed to examine the effect of soil moisture on temperature sensitivity of SR and MR.

The short-term temperature responses of SR and MR deviated significantly from the long-term apparent Q₁₀ values in both fenced and grazed grassland (Table 2 and Fig. 3), because seasonally varying biophysical drives (e.g., root dynamics, plant photosynthesis and phenology) confound the relationship between SR and temperature (Curiel Yuste et al. 2004; Gaumont-Guay et al. 2006; Sampson et al. 2007). The variability of long-term apparent Q₁₀ of SR was larger than that of MR, which may be due to the fact that Q₁₀ values of SR are more closely related to seasonal changes in autotrophic respiration (Högberg 2010). And some studies have demonstrated that autotrophic respiration is more sensitive to temperature than heterotrophic respiration (Boone et al. 1998; Singh et al. 2003; Gaumont-Guay et al. 2008). The reason for this phenomenon may be that autotrophic respiration is not only controlled by soil temperature but also affected by plant photosynthetic activity or root growth dynamics, or both (which have larger variation on diurnal and seasonal scales). In the present study, the average short-term Q₁₀ of MR and SR in both grasslands were higher than those obtained from the seasonal relationship (Table 2 and Fig. 3). Apparent Q₁₀ values calculated from the short-term (or high-frequency) temperature response are exempt from seasonally confounding effects, and thus are better able to reflect the biological sensitivity of respiration to temperature (Janssens and Pilegaard 2003; Curiel Yuste et al. 2004; Mahecha et al. 2010). However, terrestrial carbon models such as Roth-C, CENTURY and TEM generally assume a constant temperature sensitivity of SR regardless of the characteristics of the ecosystems (Jenkinson et al. 1991; Tian et al. 1999), although a study by Raich and Schlesinger (1992) suggested that Q₁₀ is likely to vary across different ecosystems and climatic conditions. Our study also demonstrated that the temperature sensitivity of soil organic matter decomposition is governed not only by substrate traits but also by the environmental constraints that are undergoing constant changes (Fig. 4); this is consistent with many other reports (Davidson and Janssens 2006; Conant et al. 2011; Suseela et al. 2012). We suggest that the short-term and long-term Q₁₀ should both be used in predicting the future carbon cycle.

4.2 Effect of grazing on long-term Q₁₀

Grazing decreased SR and MR and their long-term apparent Q₁₀ values, which might be caused by the decrease in plant productivity and SOC (Table 2). Grazing animals affect soil organic matter quantity and quality in several ways, such as through trampling and defecation. Grazing especially plays a key role in governing the amount of plant residue and root exudates in soil by causing the plant productivity to differ and changing plant species composition, thereby possibly having profound effects on the activity and composition of soil microbial communities (Bardgett and Wardle 2003). These changes, in turn, affect rates of nutrient cycling, creating feedbacks to plant productivity that affect the amount of organic matter entering soil (Bardgett and Wardle 2003).

Luan et al. (2013) found a positive relationship between apparent Q₁₀ and fine root biomass, and an association between the fine root biomass and the fast-turnover carbon pool. The importance of plant activity in controlling the apparent temperature response of SR has been well documented (Reichstein et al. 2003; Curiel Yuste et al. 2004; Hogberg and Read 2006; Sampson et al. 2007). Several studies have also found a strong positive correlation between the basal rate of SR (SR at 10°C) and plant productivity across different forest sites (Sampson et al. 2007; Irvine et al. 2008). In general, the seasonal Q₁₀ of SR can be stimulated by plant activity through several (at least two) mechanisms. First, plant activity has a direct effect on SR via root and rhizosphere respiration (Wang et al. 2010). Second, plant activity indirectly affects microbial decomposition of SOC via the so-called rhizosphere priming effect, in which interactions between roots and soil may accelerate microbial decomposition of native SOC (Dijkstra and Cheng 2007). The increased plant productivity and SOC in the fenced grassland is probably most responsible for the higher SR and MR and their apparent Q₁₀ values (Table 2).

Many studies have examined the responses of the temperature sensitivities of labile and recalcitrant pools of SOC to warming (Giardina and Ryan 2000; Fang et al. 2006; Conant et al. 2008) as well as the mechanisms underlying those responses, such as the degree of acclimation of microbes (Bradford et al. 2008; Allison et al. 2010) or depletion of substrates (Kirschbaum 2004; Eliasson et al. 2005; Hartley and Ineson 2008). It has been suggested that different SOC pools should have different intrinsic temperature sensitivities (Knorr et al. 2005; Davidson and Janssens 2006; Feng and Simpson 2008; Hartley et al. 2008) so that changes in the relative abundance of different soil carbon substrates across sites may lead to differences in the temperature sensitivity of overall SOC decomposition (Knorr et al. 2005; Fierer et al. 2006). This may help explain the higher Q₁₀ of MR in fenced grassland than in grazed grassland (fenced grassland had a higher SOC, Table 2). According to the kinetic theory of Arrhenius, the temperature sensitivity increases with increasing activation energy. If the differences in decomposition rate are entirely due to the activation energy (the energy required for decomposers to access the material), the temperature sensitivity should increase with the recalcitrance (which is consistent with SOC) of the organic material (Davidson and Janssens 2006; Hartley and Ineson 2008). Additionally, the carbon quality temperature (CQT) hypothesis (Bosatta and Ågren 1999; Fierer et al. 2005; Davidson and Janssens 2006) predicts that the temperature sensitivity of organic matter decomposition increases with biochemical recalcitrance, which has been detected on a variety of substrates and spatial scales (Fierer et al. 2005, 2006; Conant et al. 2008; Craine et al. 2010). However, the evidence for the temperature sensitivity of organic matter decomposition correlated with biochemical recalcitrance is organic matter specific. For example, some studies were able to detect different Q₁₀s for different substrates (Knorr et al. 2005; Leifeld and Fuhrer 2005; Fierer et al. 2006), whereas others were not able to do so or obtained inconsistent results (Fang et al. 2005; Reichstein et al. 2005b; Conen et al. 2006). Conant et al. (2011) recently suggested that the physico-chemical protection from decomposition of organic matter (OM) would affect the temperature response of SOM. Further research is needed to quantify the effects of the different relative abundance of various soil carbon substrates on the different SR sensitivities to temperature observed at different sites.

5. CONCLUSIONS

While multiple factors can influence short-term apparent Q₁₀ of both SR and MR, our findings show that, for this semiarid ecosystem, soil temperature is the primary reason why apparent Q₁₀ has a clearly seasonal variation. The seasonal patterns are similar in both fenced and grazed grassland, with lower Q₁₀s in growing season and larger Q₁₀s in the beginning and end of growing season. No relationship was found between soil moisture and short-term apparent Q₁₀ of SR and MR. Given the plant phenological dynamic, long-term apparent Q₁₀ is different from short-term Q₁₀. Thus, we conclude that climate change (e.g., rising temperature and nitrogen deposition) in this semiarid grassland ecosystem, as predicted by the Intergovernmental Panel on Climate Change (IPCC 2007), will result in a complex impact on temperature sensitivity of SR and especially MR. The information on long- and short-term apparent Q₁₀ changes should be carefully incorporated into carbon cycle modelling processes, especially under global change scenarios.

Additionally, grazing has a negative effect on the long-term apparent Q₁₀ of SR and MR. This result can be explained by the decrease of root biomass and soil organic carbon caused by livestock grazing. Furthermore, in general, the Q₁₀ of MR is found to be lower than that of SR, which implies that autotrophic respiration is more sensitive to temperature than heterotrophic respiration is. We speculate that temperature sensitivity of respiration is influenced not only by abiotic factors but also by substrate availability.

ACKNOWLEDGMENTS

This study was supported by the National Basic Research Program of China (2014CB138703), the “Strategic Priority Research Program – Climate Change: Carbon Budget and Related Issues” of the Chinese Academy of Sciences (XDA05050406-8), the Natural Science Foundation of China (31070412 and 31201837), the Fundamental Research Funds for Central Universities (lzujbky-2014-78), and the Program for Changjiang Scholars and Innovative Research Team in University (IRT13019). The authors are grateful to the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) for supporting the field work.