Soil organic carbon contents of two natural inland saline-alkalined wetlands in northeastern China.
Carbon cycles in wetland ecosystems are regulated by a series of interacting processes between soil, hydrology and vegetation (Zhang et al. 2002), of which hydrology is probably the single most important determinant of ecological processes (Gosselink and Turner 1978). A wetland's ability to retain carbon is determined in large part by its ability to remain wet, as SOM decomposition is inhibited by partial or complete waterlogging, from a combination of topographic position and local groundwater hydrology (Post 1993). Billings et al. (1982) found that lowering the water table in these typically waterlogged soils decreased ecosystem C storage more than increased temperature, primarily by stimulating soil decomposition (Peterson et al. 1984). More recently, Moore and Dalva (1997) reported that the high water table and its fluctuation are the primary factors driving SOC decomposition in wetland soils. When a soil is shifting from saturated to unsaturated conditions, the oxidative reactions will be enhanced, resulting in increased soil C[O.sub.2] emission and decreased [N.sub.2]O or C[H.sub.4] emissions (Li et al. 2004). Therefore, a shift in seasonal hydrology may have measurable impacts on the accumulation or loss of organic carbon from wetland soils (Clair et al. 2002), thus influencing the C balance of wetlands. However, the differences of SOC contents in saline-alkalined wetlands with different hydrological conditions are poorly known.
The objectives of this study are (1) to study and compare SOC contents of two types of saline-alkalined wetlands with different hydrological conditions; (2) to study vertical distribution of SOC contents in those wetlands; and (3) to determine the relationship between SOC contents and soil properties of wetlands.
Materials and Methods
Site Description. Xianghai wetland is one of "wetlands of international importance" (China State Forestry Administration 2001) and is a typical inland riverine wetland with the area of about 236 [km.sup.2] (91.1 [mi.sup.2]), located downstream of the Houlin River catchment of Jilin Province, in Northeast China (122[degrees]05' and 122[degrees]31' E; 44[degrees]55' and 45[degrees]09' N; figure 1). Xianghai wetland was listed as the National Nature Reserve in 1986. It lies in the semi-arid grassland zone of the north temperate region and belongs to the continental monsoon climate, with a mean annual temperature of 5.1[degrees]C (41.18[degrees]F). This region is arid with an annual water deficit of 1,536.8 mm [yr.sup.-1] (60.55 in [yr.sup.-1]) due to evaporation (1,945 mm [yr.sup.-1]) (76.63 in [yr.sup.-1]) exceeding precipitation (408.2 mm [yr.sup.-1])(16.08 in [yr.sup.-1])(Zhao 1999). The dry season occurs from November to April while wet season is from June to September. During 1999 to 2001, the climate was drier than normal: mean annual air temperature increased by 2[degrees]C (35.6[degrees]F); mean annual precipitation decreased by 138 mm (5.44 in); and mean annual evaporation increased by 580 mm (22.85 in). The dominant species of marsh vegetation is Phragmites australis, and the companion species include Potentilla anse-rina, Salix brachypoda, Alisma plantago-aquatica, Isoetes acustris, and Plantago asiatica.
Erbaifangzi (EBFZ) and Fulaowenpao (FLWP) were chosen as two typical sites in Xianghai wetland. EBFZ, the open wetland (open to hydrologic fluxes with other systems) with soil salt content of 0.38%, is located in the downstream floodplain. FLWP, located in the backwater area, with soil salt content of 0.51%, is a closed wetland (isolated from hydrologic fluxes with other systems). Water tables in the two sites often fluctuate with dry and wet seasons, ranging from -40 to 20 cm (-15.76 to 7.88 in) and -10 to 30 cm (-3.94 to 11.81 in) in FLWP and EBFZ, respectively. Drying and wetting cycles are more obvious in FLWP, because water supply depends on floods at the site. However, EBFZ often remains waterlogged or overwet because of close hydraulic connections with river water.
Sampling and Analysis Methods. Each site was subdivided into six sampling plots. In each plot, five soil cores were randomly collected in a depth from 0 to 100 cm (0 to 39.38 in), with 10-cm (3.938 in) intervals in 2001, for a grand total of 600 soil samples. All soil samples were taken to the lab and air-dried for three weeks. Recognizable plant litters, coarse root materials, and stones were removed from the air-dried soils. Each soil sample was mixed completely and then equally divided into three parts, where one part was used for the analysis of soil texture, another part was ground to fine power using a muller and was sieved through 2-mm (0.079 in) sieve for determining SOC contents, and the third part was ground and sieved through an 0.18-mm (0.007 in) sieve for determining TP, total nitrogen (TN) and pH.
Soil organic matter was determined by the Walkley and Black (1934) method and TN was measured with the Kjeldahl method (Honda 1962; Lu 1999). Total phosphorous was extracted from soils with 1N HCl after ignition at 550[degrees]C (1,022[degrees]F)(Asplia et al. 1976). Soil pH was measured with electrical conduction method (soil:water = 1:5), and soil particle size analysis was carried out on a particle size analyzer RS-1000 (made in Japan). Bulk density was calculated for the soil intervals on a dry weight basis.
Calculation of Soil Organic Carbon Content. The most appropriate way to study the organic carbon content of soil was on a unit area basis for a specified depth interval (Batjes and Dijkshoorn 1999). Commonly, reference depth intervals of 0 to 0.3 m (0 to 11.82 in) and 0 to 1 m (0 to 1.094 yd) were used in studies of soil organic C pools (Eswaran et al. 1993; Batjes 1996). The soil organic C density (SOCD), the mass of C per unit of surface area (g [m.sup.-2]) in a given soil layer, was calculated by multiplying the C concentration in the unit volume of soil by the thickness of the layer. The total SOCD of the sampled 30-cm (11.81 in) deep and 100-cm (39.38 in) deep soil layer was then calculated by summing all C densities of the sublayers (Turunen et al. 1999).
For an individual profile with n layers, the total SOC content by volume (SOCD) was calculated as the modified Wu's method (Wu et al. 2003):
TC = [n.summation over (i=1)] 0.58 x [D.sub.i] x [B.sub.i] x O[M.sub.i],
where n is the number of soil layers, 0.58 is the Bemmelen index that converts organic matter concentration to organic carbon, TC is SOCD (in Kg [m.sup.-2]) over depth, [D.sub.i] is the thickness of layer i, [B.sub.i] is the bulk density (g [m.sup.-3]) of layer i, and O[M.sub.i] is the content of organic matter.
Statistical Analysis. Analysis of variance (ANOVA) was used to test the differences in soil characteristics and soil carbon densities among the two sites and soil depths. Soil characterization data from six sampling plots in each site were utilized to calculate the mean and standard deviation for bulk density, SOM, TN and TP, C/N, sand, silt and clay. Pearson correlation coefficients were computed to determine relationships between soil characterization data and SOCD. Analyses were conducted using SPSS 10.0 statistical package and Origin 6.0 software package. Differences were considered significant if p < 0.05.
Results and Discussion
Soil Characterization. The selected physicochemical properties of the soils from study sites are listed in table 1. The soils from two saline-alkalined wetlands were characterized by high pH values (8.78 to 9.85), and high variability of dry bulk densities between soil layers (ranging from 1.2 to 1.77 g [cm.sup.-3] and from 1.1 to 1.50 g [cm.sup.-3], respectively) (table 1). Higher soil pH values appeared in deeper soil layers in both sites, while soil pH values in FLWP were significantly higher (p < 0.01) than those in EBFZ. Similarly, bulk densities were significantly higher (p< 0.01) in FLWP than those in EBFZ, with significantly higher values in the underlying soil depths of top soils (p < 0.01). Sand contents in top soils of EBFZ were much lower by about 76.8% than those of FLWP, but silt and clay contents were greatly higher (p < 0.01). Soil particle size did not greatly differ from underlying soil depths between the two wetlands (p < 0.05). Soil organic matter percentages and TN concentrations generally decreased with depth in soil profiles and were higher in 0-to 10-cm (0- to 3.938-in) and 10- to 20-cm (3.938- to 7.88-in) soil depths in FLWP than those in EBFZ, but lower for the underlying soil depths. TP was significantly negatively correlated with depth in both sites (p < 0.01). However, there was no significant difference for SOM, TN or TP contents between both sites (p < 0.05) (table 2).
Soil Organic Carbon Density. SOCDs of both wetland sites were much lower by 43% to 92% than those of other wetlands in China, only accounting for 6% to 8% of the mean SOCD of wetlands in Northeast China (table 3). Moreover, the global mean SOCD of salt marshes (39 [+ or -] 3 kg [m.sup.-2]) (Chmura et al. 2003) was also higher by 78% than the values of this study, thus suggesting inland saline-alkalined wetlands had lower C storage compared with other types of wetlands.
Mean SOCD was 8.23 [+ or -] 1.40 kg C [m.sup.-2] in the upper 100 cm (39.38 in) of EBFZ, higher by about 41% than that of FLWP (table 3), which means that the open wetland had larger C storage than the closed wetland. This was likely related to water table fluctuations in FLWP because drying and wetting cycles favored SOM decomposition and the liberation of C from leaf litter (Baldwin and Mitchell 2000; Bai et al. 2005a). Chen and Li (2003) also found that rapid leaf decomposition in moist areas, especially in wetlands with variable water tables, led to the greatest loss of soil C, which could be attributed to changes in some biological and physical processes in the soils (Bouwman 1990). In addition, because floodwater was the only water source supplying FLWP, flood inputs were identified as one of the key factors regulating organic matter accumulation. Flood pulses can deposit large amounts of organic matter (Jacobson 1997) and trigger the activity of soil microorganisms, directly influencing decomposition and carbon mineralization rates (Jacobson et al. 2000).
Vertical Changes of Soil Organic Carbon Density. SOCD generally decreased with depth in soil profiles in both FLWP and EBFZ, with the highest values 2.64 kg C [m.sup.-2] and 2.14 kg C [m.sup.-2] in top soils, respectively (figure 2). More than 50% of SOC was stored in the upper 30 cm (11.81 in) in both sites. Plant litter inputs, below-ground biomass, and flood deposits could explain higher soil carbon contents of the upper soils. In both sites, plant litter inputs (302.56 g [m.sup.-2] [yr.sup.-1], FLWP; 309.72 g [m.sup.-2] [yr.sup.-1], EBFZ) were one major source of SOM, which accumulated on surface soils, and organic carbon could be incorporated to top soils with the decomposition of plant litter. Battle and Mihuc (2000) also reported that there was significant positive correlation between plant litter inputs and soil carbon contents. Belowground biomass was another important source, since 70% of below-ground biomass was distributed in the upper 40 cm (15.76 in) in both sites (Bai 2003), and root systems could fix a great deal of carbon (Chen and Li 2003). In addition, flood pulses could result in C accumulation in those upper soil layers by depositing large amounts of organic matter to the surface soils (Jacobson 1997).
Although SOC contents in deeper soil layers were generally lower, they could not be ignored since the contribution rates of soil layers below a depth of 50 cm (19.69 in) in FLWP and EBFZ were 22% and 32%, respectively.
Relationship between Soil Organic Carbon Density and Soil Properties. Many studies have shown that the soil C pool is affected by climate, landscape age, soil properties, and human activities (Post et al. 1982; Amundson and Jenny 1997). Soil properties were also found to greatly influence SOC contents in this study (table 2). Soil organic carbon density was significantly correlated with SOM, TN, C/N and TP for all the soils (p < 0.001). The initial composition of soil nutrients would affect their decomposition rates (Lisanework and Michelsen 1994; Couteaux et al. 1995). Soils were abundant in N in both sites as indicated by C:N generally <25 (Yang 1997). Low C:N ratios favor decomposition of SOM (Kadono et al. 2002), which might also be an important factor for lowering SOC contents. In addition, there was also a significantly negative correlation between SOCD and soil pH, which supported the conclusion that the closed wetland had lower C storage, since there was higher alkalinity in the closed wetland than in the open wetland due to drought in recent years (Bai et al. 2005b).
Soil texture greatly impacted SOC contents. The presence of larger SOC stocks in fine-textured compared to coarse-textured soils under the same climate had been widely noted previously (Parton et al. 1987). In this study, we found that SOC contents were negatively significantly correlated with sand contents (p < 0.001), but positively significantly correlated with silt (p < 0.01) and clay contents (p < 0.001). This was in good agreement with the conclusion reported by Oades (1988) and Jacobson et al. (2000). The reason SOC contents were higher in top soils in this study was because the fine texture of clay soils in surface soils was more likely to allow organic matter particles to remain (Bird et al. 2000).
Summary and Conclusions
The two inland saline-alkalined wetlands have much lower SOC contents than those in other wetlands in China, even lower than the global average SOC content in salt marshes, which is closely linked to dry climate and water deficit in this region. SOC contents decrease with depth in soil profiles in the two sites, which is significantly influenced by plant litter, root distribution, rhizodeposits and flood deposition. Although SOC is mainly stored in the upper 30 cm in both sites, SOC stored below the 30-cm depth can't be ignored since it accounts for more than 40% of C storage. Soil nutrients, soil texture and soil pH are important factors influencing SOC storage. SOCD were positively significantly correlated with SOM, TN, TP and clay contents (p < 0.001) and negatively significantly correlated with sand contents (p < 0.001). There was also a significant correlation between SOCD and soil pH, C/N or silt content at the level of p < 0.01. Higher SOC contents appeared in the open wetland due to waterlogged or wetter hydrological conditions compared with the drier closed wetland. Besides the dry climate, the regional plan to build the Baiyunhua reservoir upstream of the Huolin river will also be a potential threat, causing the downstream wetlands to face serious water shortages. Ecological water supplement, that is, water supplement based on ecological water requirement to maintain ecosystem health, may be necessary to mitigate water shortages and increase carbon storage of wetlands in semi-arid and arid regions. Although more studies still need carried out to further confirm the above conclusions, this study provides basic data for carbon stocks in wetland soils at the regional or global scale.
This study was financially supported by the National Basic Research Program (No. 2006CB403301) and the National Natural Science Foundation of China (No. 40701003). We express our thanks to the reviewers and Dr. Kenneth N. Potter for helpful and thoughtful comments and suggestions to improve this paper. We also thank the analysis center of Northeast Institute of Geography and Agricultural Ecology, Chinese Academy of Sciences.
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Junhong Bai is an associate professor and Baoshan Cui is a professor at the State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China. Wei Deng is a researcher/professor at the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China. Zhifeng Yang is a professor at the State key laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China. Qinggai Wang is a senior engineer at the Appraisal Center for Environment and Engineering, State Environmental Protection Administration, Beijing, China. Qiuyi Ding is a master's student at the State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China.
Table 1 Physico-chemical properties of soils in Fulaowenpao (FLWP) and Erbaifangzi (EBFZ). Soil layers SOM In-C TN (cm) pH (%) (%) (mg [kg.sup.-1]) Fulaowenpao 0 to 10 9.39 (0.46) 4.13 (2.40) 2.30 (0.44) 2,591.80 (781.05) 10 to 20 9.65 (0.30) 1.76 (0.89) 2.04 (0.55) 1,005.46 (695.61) 20 to 30 9.74 (0.25) 0.74 (0.34) 2.17 (0.57) 429.24 (187.93) 30 to 40 9.81 (0.24) 0.48 (0.23) 2.17 (0.59) 532.58 (266.64) 40 to 50 9.85 (0.21) 0.59 (0.26) 2.05 (0.62) 330.61 (235.65) 50 to 60 9.84 (0.20) 0.45 (0.29) 1.90 (0.66) 181.67 (45.65) 60 to 70 9.73 (0.13) 0.26 (0.15) 2.01 (0.63) 226.33 (76.32) 70 to 80 9.70 (0.14) 0.24 (0.12) 1.95 (0.61) 257.24 (135.80) 80 to 90 9.67 (0.15) 0.22 (0.12) 1.86 (0.53) 244.41 (180.63) 90 to 100 9.69 (0.18) 0.31 (0.15) 1.79 (0.52) 204.37 (70.02) Erbaifangzi 0 to 10 8.78 (0.59) 4.32 (1.67) 1.16 (0.25) 2,046.46 (672.34) 10 to 20 8.81 (0.53) 1.92 (0.95) 0.80 (0.27) 924.18 (467.62) 20 to 30 8.87 (0.32) 0.90 (0.43) 1.18 (0.33) 775.84 (285.65) 30 to 40 8.81 (0.32) 0.97 (0.47) 1.71 (0.43) 536.68 (176.83) 40 to 50 8.82 (0.31) 0.45 (0.26) 1.92 (0.52) 412.57 (151.45) 50 to 60 8.88 (0.21) 0.47 (0.28) 2.18 (0.54) 386.40 (206.88) 60 to 70 8.83 (0.27) 0.50 (0.24) 2.47 (0.56) 319.78 (108.42) 70 to 80 8.83 (0.31) 0.52 (0.27) 2.49 (0.56) 288.89 (88.74) 80 to 90 8.86 (0.32) 0.57 (0.31) 2.12 (0.51) 406.18 (133.45) 90 to 100 9.02 (0.19) 0.41 (0.21) 2.42 (0.53) 256.48 (92.06) Soil Silt (%) layers TP Sand (%) 0.05 to (cm) (mg [kg.sup.-1]) C/N ratio >0.05 mm 0.005 mm Fulaowenpao 0 to 10 276.48 (70.36) 14.80 (13.03) 77.44 (2.13) 10.50 (0.65) 10 to 20 149.37 (49.78) 11.46 (3.37) 77.73 (1.71) 15.69 (1.33) 20 to 30 104.16 (39.03) 10.87 (5.70) 76.20 (1.23) 19.92 (1.42) 30 to 40 83.17 (29.93) 5.98 (4.93) 82.85 (1.87) 15.25 (1.29) 40 to 50 84.49 (37.12) 9.94 (2.73) 83.75 (1.89) 14.45 (1.21) 50 to 60 74.70 (29.00) 15.54 (10.27) 82.23 (1.73) 16.76 (1.19) 60 to 70 87.02 (30.05) 8.15 (5.70) 80.82 (1.07) 17.61 (1.05) 70 to 80 89.37 (38.86) 5.34 (3.30) 82.99 (1.09) 17.01 (1.02) 80 to 90 81.80 (32.29) 5.37 (2.51) 77.98 (1.03) 19.42 (1.02) 90 to 100 83.31 (35.23) 7.95 (6.72) 74.34 (1.02) 21.78 (1.12) Erbaifangzi 0 to 10 279.04 (177.96) 11.17 (1.33) 17.98 (2.10) 45.19 (1.68) 10 to 20 116.29 (60.58) 9.72 (3.23) 79.39 (1.69) 14.76 (1.12) 20 to 30 113.80 (53.35) 6.64 (2.35) 88.36 (1.34) 9.77 (1.23) 30 to 40 107.66 (51.32) 10.77 (5.83) 85.18 (1.33) 12.91 (1.06) 40 to 50 94.85 (33.55) 6.26 (2.70) 78.95 (1.24) 19.12 (1.13) 50 to 60 96.77 (38.28) 8.03 (5.49) 79.01 (1.09) 18.26 (1.05) 60 to 70 102.41 (41.50) 9.07 (2.59) 76.54 (1.11) 24.46 (1.01) 70 to 80 96.25 (44.13) 9.65 (5.06) 69.81 (1.02) 23.55 (0.96) 80 to 90 93.27 (45.31) 10.0 (6.64) 74.21 (1.03) 19.08 (1.12) 90 to 100 88.20 (47.00) 8.29 (4.72) 72.36 (1.02) 23.82 (0.98) Soil Bulk layers Clay (%) density (cm) <0.005 mm (g [cm.sup.-3]) Fulaowenpao 0 to 10 12.06 (1.21) 1.20 (0.23) 10 to 20 6.59 (1.04) 1.46 (0.27) 20 to 30 3.88 (0.76) 1.58 (0.17) 30 to 40 1.89 (0.34) 1.63 (0.19) 40 to 50 1.80 (0.23) 1.67 (0.13) 50 to 60 1.01 (0.06) 1.71 (0.13) 60 to 70 1.57 (0.11) 1.73 (0.11) 70 to 80 0.00 (0.00) 1.72 (0.12) 80 to 90 2.60 (0.45) 1.77 (0.14) 90 to 100 3.89 (0.42) 1.74 (0.15) Erbaifangzi 0 to 10 27.63 (1.34) 1.10 (0.19) 10 to 20 5.85 (1.15) 1.39 (0.15) 20 to 30 1.85 (0.95) 1.41 (0.14) 30 to 40 1.92 (0.78) 1.44 (0.11) 40 to 50 1.93 (0.92) 1.42 (0.13) 50 to 60 2.73 (0.98) 1.45 (0.13) 60 to 70 1.99 (0.75) 1.50 (0.15) 70 to 80 6.64 (1.13) 1.47 (0.11) 80 to 90 6.70 (0.89) 1.47 (0.97) 90 to 100 3.81 (1.04) 1.46 (0.89) Note: Data are mean values from 30 soil profiles with one standard deviation in parentheses. Table 2 Relationship between soil carbon density with soil properties. Percent SOCD SOM TP SOCD 1.000 Percent SOM 0.987* 1.000 TP 0.722* 0.768* 1.000 TN 0.804* 0.840* 0.719* pH -0.323[dagger] -0.319[dagger] -0.223[double dagger] Percent sand -0.515* -0.580* -0.475* Percent silt 0.266[dagger] 0.323* 0.282[dagger] Percent clay 0.701* 0.765* 0.612* C:N ratio 0.357* 0.286[dagger] 0.086 Percent Percent TN pH sand silt SOCD Percent SOM TP TN 1.000 pH -0.298[dagger] 1.000 Percent sand -0.386* 0.263[dagger] 1.000 Percent silt 0.112 -0.229[double dagger] -0.925* 1.000 Percent clay 0.616* -0.266* -0.919* 0.710* C:N ratio -0.083 0.037 -0.086 0.020 Percent clay C:N ratio SOCD Percent SOM TP TN pH Percent sand Percent silt Percent clay 1.000 C:N ratio 0.152 1.000 Notes: n = 120 from two wetlands (average data in each sampling plot). SOCD = soil organic carbon density; SOM = soil organic matter; TP = total phosphorus; TN = total nitrogen. * Significantly correlated at the level of p < 0.001. [dagger] Significantly correlated at the level of p < 0.01. [double dagger] Significantly correlated at the level of p < 0.05. Table 3 SOC contents of different wetlands in China. SOC SOCD Location (%) (kg C [m.sup.-2]) Reference Erbaifangzi, Jilin 0.80 8.23 [+ or -] 1.40* This study Province (marsh) Fulaowenpao, Jilin 0.53 5.82 [+ or -] 1.15* This study Province (marsh) Guangdong Province 2.18 21.15 Gan et al. 2003 (swamp) Circum Bohai region 1.83 22.90 Liu et al. 2003 (swamp) Inner Mongolia (marsh) 1.21 14.48 Chen et al. 2003 Inner Mongolia (fen) 3.62 30.42 Chen et al. 2003 Northeast China (fen) -- 92.55 Wang et al. 2002 North, west, and central -- 11.6-13 Ni 2002 China (swamps) China (marsh) 7.13 79.42 Wang et al. 1999 China (fen) -- 47.96 Wang et al. 1999 China (wet grassland -- 101.11 Wang et al. 1999 marsh) Notes: SOC = soil organic carbon; SOCD = soil organic carbon density. *Mean SOCD of 30 soil profiles [+ or -] standard deviation.
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|Author:||Bai, J.; Cui, B.; Deng, W.; Yang, Z.; Wang, Q.; Ding, Q.|
|Publication:||Journal of Soil and Water Conservation|
|Date:||Nov 1, 2007|
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