0Wetlands Ecol Manage (2015) 23:977-987
DOI 10.1007/s11273-015-9434-2 CrossMark
ORIGINAL PAPER
Responses of SOM decomposition to changing temperature in Zoige alpine wetland, China
Jingyue Xue . Hongxuan Zhang .
Nianpeng He . Youmin Gan . Xuefa Wen . Jie Li .
Xuelian Zhang . Peibin Fu
Received: 29 August 2014/Accepted: 4 June 2015/Published online: 23 August 2015 © Springer Science+Business Media Dordrecht 2015
Abstract Alpine wetlands are considered to be very sensitive to future climate warming. Understanding changes in decomposition rates (Rs) of soil organic matter (SOM) and temperature sensitivity (Q10) in alpine wetlands, under the scenarios of a warming climate and decreasing soil moisture, is important for predicting their carbon (C) budget. Here, we established three sampling transects from wetland edge to meadow in the Zoige alpine wetlands in China, which represented the gradients of decreasing soil moisture. We conducted an incubation experiment (5-25 °C) to explore changes in Q10 with the degradation process from alpine wetland to alpine meadow. The results showed that temperature significantly influenced Rs in all locations. Rs first increased from site I to site IV and then decreased from site IV to site V. However, Q10 and activation energy (Ea) showed no apparent trends
with soil coming from sites along a moisture gradient. Overall, the Q10 values in the wetland (sites 1.50) were significantly lower than that of the meadow (1.83); similar trends were observed for Ea. In addition, Ea exhibited a negative logarithmic relationship with C quality indices in all locations, which suggested that the C quality-temperature hypothesis is applicable to both alpine wetlands and meadows. These findings provide a theoretical foundation for predicting the potential influences of warming climate on soil C turnover and storage in alpine wetlands.
Keywords Activation energy • Alpine wetland • Carbon quality-temperature hypothesis • Soil organic carbon • Temperature sensitivity • Soil moisture
Introduction
J. Xue • H. Zhang (&) Sichuan Academy of Grassland Science, Chengdu 611731, China e-mail: zhanghx@189.cn
J. Xue • Y. Gan (&) • X. Zhang • P. Fu College of Animal Science and Technology, Sichuan Agricultural University, Yaan 625014, China e-mail: ganyoumin1954@163.com
N. He (&) • X. Wen • J. Li
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China e-mail: henp@igsnrr.ac.cn
It is estimated that wetlands store approximately 20-30 % of terrestrial soil organic carbon (SOC), although they occupy only 5-8 % of the land surface (Mitsch and Gosselink 2007). Wetland degradation, especially decreasing area and soil water content, has been widely observed in association with warming climate (Froend 1999; Jin et al. 2007), which is accompanied by the reduction of productivity, biodiversity (Hart and Lovvorn 2000), and soil nutrients (Gilbert et al. 2004). Gillespie et al. (2014) pointed out that under warming climate, higher decomposition of soil organic matter (SOM) and a lower water table
would occur in subarctic wetlands and result in increased CO2 release in this region. Therefore, the degradation of wetlands has an immediate impact on their C budget, and it is necessary to take effective measures to restore them (Limpens et al. 2008).
Few studies have investigated the effect of and lowered water table on SOM decomposition in alpine wetlands. Theoretically, changes in soil moisture play important roles in regulating SOM decomposition. Soil water films may promote diffusion of extracellular enzymes and soluble organic carbon (C) substrates and may increase substrate availability in micro-sites when water content is moderate (Davidson and Janssens 2006; Toberman et al. 2008). Gao et al. (2008) demonstrated that soil moisture strongly influences microbial activity and SOM decomposition in wetlands. Numerous researchers have found that the content and quality of SOM may influence SOM decomposition to large extent in alpine wetlands where temperature and moisture are not limiting (de Bruijn and Butterbach-Bahl 2010; Huo et al. 2013; Kirschbaum 2006).
Temperature is a key factor influencing the decomposition rates (Rs) of SOM decomposition (Jones et al. 2003; Lenton and Huntingford 2003). The temperature sensitivity (Q10) has been widely used to depict the response of SOM decomposition to changing temperature (Bauer et al. 2008; He et al. 2013; Kirschbaum 2000). Some studies have demonstrated that Q10 is important for predicting the C budget in terrestrial ecosystems under warming scenarios, and some experimental studies have explored the spatiotemporal patterns of the Q10 values in terrestrial ecosystems (Davidson and Janssens 2006; Fang et al. 2005; Fierer et al. 2006; Gillabel et al. 2010). However, the response of Q10 values to the degradation in alpine wetlands have not been investigated to date. Furthermore, on basis of the principles of thermodynamics and enzyme kinetics, the C quality-temperature hypothesis (CQT) has been proposed to explain the mechanisms of SOM decomposition and substrate quality (Conant et al. 2008; Davidson and Janssens 2006; Xiang and Freeman 2009). This hypothesis assumes that molecular complexity of the substrate is associated with the quality of organic matter, and lower-quality substrates have recalcitrant molecular structure and higher activation energy (Ea) and thus a greater Q10 value. As the temperature increases, more molecules reach or exceed their Ea; however, there is a
decline in the relative increase in the fraction of molecules with sufficient energy to react, indicating that Q10 decreases with increasing temperature (Davidson and Janssens 2006). The CQT hypothesis has been validated by some studies using different approaches (Bosatta and Agren 1999; Craine et al. 2010a, b; Mikan et al. 2002; Xu et al. 2012). However, whether or not the CQT hypothesis could be applicable to alpine wetlands has not been verified.
The Zoige alpine wetland is located at the eastern edge of the Qinghai-Tibet Plateau and is the largest alpine wetland in China (Fei et al. 2006). SOM decomposition in alpine wetlands is expected to increase to some extent under climatic warming scenarios accompanied by decreasing wetland area and water table. In this study, we established three transects from wetland edge to meadow along the gradients of decreasing soil moisture, and conducted an incubation experiment to explore the changes in Rs and Q10. Our main objectives were to (1) investigate the changing trends of Rs with the degradation of the alpine wetland, (2) explore the changes in Q10 and Ea with the alpine wetland degradation, and (3) verify the applicability of the CQT hypothesis in the alpine wetland and meadow.
Materials and methods
Study area
The Zoige Wetlands (32°56'-34°19'N, 102°08'-103°39'E) is located at the eastern edge of the Qinghai-Tibet Plateau in China and is the largest alpine wetland in China. The altitude of the study area is approximately 3,400-3,800 m a.s.l. This region has a typical humid and semi-humid continental monsoon climate of plateau cold temperate zone. The mean annual temperature is approximately 0.7 °C, and the mean annual precipitation is 600-800 mm (Bai et al. 2013). The coldest month is January (-10.6 °C) and the warmest month is July (10.8 °C). The major vegetation types are marsh-meadow and meadow. The marsh-meadow is dominated by Carex muliensis, C. lasiocarpa, and C. meyeriana, whereas the meadow is dominated by Poaceae grasses such as Elymus dahuricus, and Poa pratensis (Huo et al. 2013).
Soil samples were collected in July 2013 in Huahu Lake, Zoige, Sichuan Province. Huahu Lake is the
highest alpine lake in Zoige and has typical water-table gradients from alpine wetland to alpine meadow (Chen et al. 2011). A decline in wetland area and water table has been observed in past decades in this region (Tan et al. 2012; Tang et al. 2012; Zhang et al. 2011).
Sampling and pretreatment
We first established three transects from the edge of Huahu Lake to the alpine meadow, with five sampling locations (I, II, III, IV, and V) in each transect to represent the gradients of decreasing soil moisture. Sampling sites I-IV were in the alpine wetland region, and site V was in the alpine meadow region (Fig. 1). All sampling sites had been subjected to long-term free grazing by yak, according to local grazing tradition. Plant community composition and above-ground productivity, and coverage showed that vegetation was in good condition in locations I-IV, whereas V was slightly degraded as a result of higher grazing intensity (Table 1).
We measured soil water content, plant species composition, and aboveground biomass in six quadrats (50 x 50 cm) at random locations in each sampling site. We recorded plant coverage, density, height, and frequency in three quadrats per sampling
location; aboveground biomass was clipped at ground level in all quadrats. Three soil samples were taken at each sampling location in the 0-10 and 10-30 cm soil layers using an auger (7 cm diameter). Soil samples were sieved (<2 mm), and visible roots and organic debris were removed by hand. Approximately 100 g of soil for each sample was air-dried for analysis of soil properties (C, nitrogen (N), and pH). The remaining soil samples were stored at 4 °C.
Chemical analysis and incubation experiment
Soil water holding capacity (WHC, %) and gravimetric water content (%) were measured in the laboratory. The concentrations of soil total C and total N were measured using a Vario Max CN elemental analyzer (Vario Max CN, Elementar Company, Germany). Soil pH was measured in a soil-water slurry (1:2.5, w/w) with an Ultrameter-2 pH meter (Myron L. Company, California, USA).
To prevent the thermal adaptation of soil microorganisms (Sierra et al. 2010), the 56-d laboratory incubation was conducted at five temperatures (8, 13, 18, 23, and 28 °C in the daytime; 5, 10, 15, 20, and 25 °C at night). A total of 225 soil samples (3 transects x 5 sampling sites x 3 temperatures x 3
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replicates) were used in the incubation experiment. In brief, 40 g of fresh soil, adjusted to 55 % WHC, was placed into incubation bottles (5 cm diameter, 10 cm tall) and mixed with 10 g quartz sand. The samples were pre-incubated at 20 °C and constant humidity (80 %) for 1 week followed by the incubation temperature for 8 weeks to measure Rs. During the 56-d experiment, Rs were measured 10 times, on days 0, 1, 3, 5, 7, 14, 21, 28, 42, and 56. Soil moisture was adjusted at 3-4 day intervals on a weight basis.
An automatic system has been developed to measure Rs (He et al. 2013). In practice, Rs (ig C g-1 h-1) was calculated from the slope of CO2 concentration and conversion factors as follows:
where C is the slope of the change in CO2 concentration, V is the volume of the incubation bottle and gas tube, m is the soil weight (g), a is the conversion coefficient for CO2 mass, and b is a conversion coefficient of time.
Calculation of Ea and Q
The Q10 values were calculated using the following exponential equations (Fierer et al. 2003):
Rs = Q Q10
(2) (3)
where T is temperature (°C); Q is C quality index of SOM (the exponential constant or activity at 0 °C); and b is the exponential fit parameter for the slope of the line describing the temperature-respiration relationship. The Ea values were calculated using the Arrhenius equations as follows (Hamdi et al. 2013):
Rs = A x eRT
Ea = R x(ln Qw)/(±1_
V T1 T2
where A is a pre-exponential parameter; R is the gas constant (8.314 J mol-1); and T1 and T2 indicate temperature (K) and indicate the 10 °C temperature range for the corresponding Qi0 (i.e., T + 10 = T2). In calculating Ea, Q10 represented the range T-5 to T?5, where T was the average incubation temperature.
Statistical analysis
One-way analysis of variance (ANOVA) was used to compare soil water content, total C and N, pH, and conductivity among different locations. Univariate analysis was used to examine the effects of sampling location, temperature, incubation duration, and their interactions on Rs. Differences in Q10 between alpine wetland and meadow were examined using independent-sample t-tests. Regression analyses were used to evaluate the relationships between C quality index and Ea. Significant differences were defined as P = 0.05. All statistical analyses were conducted using SPSS 13.0 (SPSS Inc., Chicago, IL, USA).
these variables significantly affected Rs, and there was a significant interactive effect for sample position and temperature (P < 0.001; Table 2). Rs increased significantly with increasing incubation temperature at all sampling locations (F = 80.880, P < 0.001, Table 2), which can be well depicted by exponential equations (Fig. 2). As expected, Rs increased gradually from location I to IV and then decreased drastically at location V, regardless of incubation duration (Fig. 3). Furthermore, Rs differed significantly in relation to soil moisture (F = 139.305, P < 0.001; Fig. 3, Table 2), and showed a general trend of IV > III > II > I > V.
Changes in Q10 and Ea with soil moisture gradient
Results
Changes in soil and vegetation
Soil water content decreased gradually and significantly (84-29 %) from locations I to V (Fig. 1; F = 196.233, P < 0.001). Soil C and N content increased initially and then decreased from locations I to V, and they were lowest in the alpine meadow (V). Soil C content was significantly higher in wetlands than in meadow sites (F = 10.194, P = 0.004), but no significant differences were observed among different wetland locations (Table 1).
The Q10 values ranged from 1.49 to 1.83 from locations I to V, and were highest in the alpine meadow. Unexpectedly, Q10 did not differ significantly from location I to IV, which represented a degradation gradient (R2 = 0.316, P = 0.352; Fig. 4c). However, the Q10 values were significantly higher in the alpine meadow than in the wetland (F = 7.657, P < 0.001; Fig. 4d).
Ea increased to some extent with decreasing soil moisture (R2 = 0.394, P = 0.256; Fig. 4a) and Ea was highest in the alpine meadow. The average Ea value in the wetland was significantly lower than that of the alpine meadow (F = 5.713, P = 0.010; Fig. 4b).
Effects of temperature and sampling location on Rs
Ea related to substrate quality
Sampling location, incubation temperature, and incubation duration significantly influenced the accumulation of SOM decomposition, and there was a significant interactive effect (P < 0.001; Table 2). Similarly,
The Ea values decreased significantly with increasing substrate quality index (Q) for all locations. The logarithmic equations fit the negative relationships
well (R2 = 0.254, P < 0.001; Fig. 5a), and the
Table 2 Effects of sampling location, incubation temperature, and duration on SOM decomposition rates and accumulation
Decomposition rate of SOM Accumulation of SOM decomposition
F P F P
Sampling position (P) 139.305 <0.001 175.216 <0.001
Incubation temperature (T) 80.880 <0.001 111.805 <0.001
Incubation duration (D) 6.927 <0.001 152.974 <0.001
P x T 4.298 <0.001 5.800 <0.001
P x D 0.413 0.990 7.393 <0.001
T x D 0.652 0.875 4.829 <0.001
P x T x D 0.226 1.000 0.264 1.000
Fig. 2 Effect of incubation temperature on SOM decomposition rate in alpine wetland and meadow. I, II, III, IV, and V represent different sampling locations (Fig. 1). The data are mean ± SE (n = 9)
Fig. 3 Changes in SOM decomposition rates among different sampling positions. I, II, III, IV, and V indicate different sampling locations (Fig. 1). Data are mean ± SE (n = 9)
relationship was stronger in the alpine meadow (site V, Fig. 5f). Except for location III, Ea deceased significantly with increasing Q in the wetland sites (R2 = 0.147, P = 0.006 for I; R2 = 0.093, P = 0.034 for II; R2 = 0.173, P = 0.002 for IV) (Fig. 5b-e).
Discussion
Rising temperature accelerates SOM decomposition in the alpine wetland
It has become clear that Rs is positively correlated with temperature (Du et al. 2014; Hartley and Ineson
2008; Jenkinson et al. 1991; Knorr et al. 2005; Mitsch and Gosselink 2007). Our findings demonstrated that Rs increased exponentially with increasing temperature in the Zoige alpine wetland and meadow. Similarly, Wang et al. (2010) reported that temperature played an important role in Rs in permafrost wetlands in the Great Hing'an Mountains of China. A study of Mediterranean forest soils in Italy showed that Rs increased exponentially with increasing temperature when soil moisture or other factors were not limiting (Rey et al. 2005). Higher temperatures are conducive to microbial activity and enzymatic activity increase with temperature; thus, increased temperatures in the future would improve substrate utilization and result in higher Rs (Craine et al. 2010b;
Fig. 4 Changes in activation energy (Ea) and temperature sensitivity (Q10) with soil moisture gradient (sampling location). Data in scatter panels (a, c) represent Ea and Q10 of I, II, III, IV, and V. Data in inset column panels (b, d) are derived from wetlands (I, II, III, and IV) and meadow (V)
Gershenson et al. 2009; von Lutzow and Kogel-Knabner 2009).
Changes in substrate and microbial communtiy lead different SOM decomposition
The gradual increases in Rs with decreasing soil moisture in different wetlands indicate that changes in soil substrate and aerobic microbial communtiy lead the difference in SOM decomposition. The findings support our assumption that Rs may first increase and then decrease during the process of degradation of wetland to meadow. When moisture content is moderate, aerobic conditions promote soil enzyme activity, which accelerates SOM decomposition (Carrera et al. 2011; Toberman et al. 2008). Moreover, lower oxygen concentrations in saturated and inundated soils inhibit phenol oxidase activity; which results in the accumulation of phenolic compounds that inhibit the activity of hydrolase enzymes and reduce Rs (Freeman et al. 2001). However, this inhibition is quickly reversible when wetland soils become aerobic (Davidson and Janssens 2006), and can result in higher Rs and larger C loss with the degradation process of alpine wetlands (Shang and Yang 2012; Tian et al. 2004).
The lower Rs observed in the alpine meadow may be linked to C constraints. Furthermore, some studies have demonstrated that changes in soil enzyme activity are important determinants resulting from lower C quality (Shackle et al. 2000) and different C content of different vegetation types (Neff and Hooper 2002).
The alpine wetland has lower temperature sensitivity than the alpine meadow
The significant differences in Q10 between alpine wetlands and meadows provide new evidence that models involving specific Q10 value can better predict the influences of warming climate on the C budget in alpine ecosystems. However, we did not observe a significant trend of Q10 along the wetland degradation gradient. In a study of peatlands in northern Manitoba, Canada, Ise et al. (2008) found that a falling water table increased the sensitivity of peat decomposition to temperature. Soil water content in the alpine wetlands was high, which depressed air diffusion, enzyme activity, and substrate availability (Rey et al. 2005; Tang et al. 2012; Wang et al. 2010); this may have obscured the influences of increasing temperature and resulted in a lack of significant differences in Q10 among different alpine wetlands. Moreover, the alpine wetlands were rich in high-quality SOM, therefore Q10 values should not increase significantly until better-quality SOM is progressively depleted (Hartley and Ineson 2008). According to the CQT hypothesis, similar substrate quality is associated with similar Q10 (Bosatta and Agren 1999; Craine et al. 2010b; Gershenson et al. 2009), which should explain the differences in temperature sensitivity between alpine wetland and alpine meadow to some extent.
C quality-temperature hypothesis is applicable to the alpine wetland and meadow
Ea decreased logarithmically with increasing substrate quality in both alpine wetland and meadow, which supported the CQT hypothesis that the temperature sensitivity (Q10) of soil organic matter (SOM) decomposition is inversely related to organic carbon (C) quality or Ea (Bosatta and Agren 1999; Xu et al. 2012). Substrate quality is particularly important (Giardina and Ryan 2000; Hartley et al. 2009; Mikan et al. 2002). Bosatta and Agren (1999) developed the
Fig. 5 Relationships between activation energy (Ea) and substrate quality index (Q) in alpine wetlands and meadows. The Q values were calculated by exponential models (SR = Q x ebT). The grey points represent the relationship
between Ea and Q of all locations. The black points in b, c, d, e, and f represent the relationship between Ea and Q in the locations I, II, III, IV, and V
CQT hypothesis based on principles of enzyme kinetics, wherein the energy required for SOM decomposition is correlated with substrate quality. In other words, the higher activation energy associated with the breakdown of recalcitrant substrates should result in greater Q10 (Conen et al. 2008). In accordance with previous studies (Fierer et al. 2005; Koch et al. 2007; Wetterstedt et al. 2010), we used a C quality index calculated from exponential equations, and found that the observed Qi0 and Ea were inversely related to substrate quality indices in both alpine
wetland and meadow. Xu et al. (2012) also used the C quality index to represent the overall C quality of SOM being utilized by microbes at a special time point. Using different approaches, Hartley and Ineson (2008) found that Q10 values increased significantly with incubation duration, suggesting that substrate recalcitrance increases as the labile SOC pool is depleted, and that incubation time could reflect substrate quality.
SOM decomposition rates in the Zoige alpine wetlands increased significantly with rising temperature. Lower Q10 values in alpine wetlands could be
explained by changes in soil moisture, enzyme activity, and substrate availability during the degradation process. The activation energy of SOM decomposition decreased logarithmically with increasing substrate quality in both alpine wetland and meadow, indicating that the CQT hypothesis is applicable to these types of sites. The influence of wetland degradation on the Q10 of SOM decomposition provides new insights to improve the prediction of C budget in alpine wetlands under warming scenarios.
Acknowledgments This work was partially supported by Natural Science Foundation of China (31470506 and 31270519), and the Program for Kezhen Distinguished Talents in Institute of Geographic Sciences and Natural Resources Research, CAS (2013RC102).
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