Wetlands (2016) 36 (Suppl 1):S145–S152 DOI 10.1007/s13157-015-0647-1
ORIGINAL RESEARCH
Spatial and Seasonal Variations of Soil Carbon and Nitrogen Content and Stock in a Tidal Salt Marsh with Tamarix chinensis, China Qingqing Zhao & Junhong Bai & Qiang Liu & Qiongqiong Lu & Zhaoqin Gao & Junjing Wang
Received: 23 April 2014 / Accepted: 4 March 2015 / Published online: 13 March 2015 # Society of Wetland Scientists 2015
Abstract To investigate the spatial and seasonal variations of soil organic carbon (SOC) and total nitrogen (TN) contents and stocks in tidal salt marsh soils, 15 cores to a depth of 40 cm were collected in five sampling sites along a sampling belt during three seasons. Our results showed that higher SOC and TN contents occurred in the surface soils in three sampling seasons. Spatial distributions of SOC and TN showed moderate variability. The C/N ratios were higher in the summer and autumn than in spring. The soil organic carbon density (SOCD) and soil total nitrogen density (TND) ranked in the following order: autumn > spring > summer. And the SOCD values positively correlated with the distances from the tidal creek in summer, while this correlation was negative in autumn and spring. The soil properties, such as the soil moisture, salinity, C/N ratio and C/P ratio, significantly correlated with the SOC and TN contents and stocks. The water and salinity regulation and the alternation of ratios of ecological stoichiometry should be considered to strengthen carbon and nitrogen sequestration in coastal wetlands. Keywords Carbon . Nitrogen . C/N ratio . Spatial and temporal variation . Tidal salt marsh
Introduction Wetlands are highly productive ecosystems and serve as an important part of global carbon and nitrogen cycling. Although Q. Zhao : J. Bai (*) : Q. Liu : Q. Lu : Z. Gao : J. Wang State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China e-mail:
[email protected]
wetlands cover 4–6 % of the earth, the stored carbon in wetlands almost accounts for one third of the terrestrial carbon storage (Mitsch and Gosselink 2007; Lawrence and Zedler 2013) and is nearly three times that contained in the aboveground biomass (Eswaran et al. 1993; Matzner and Borken 2008). Reddy and DeLaune (2008) state that wetland soils serve as an important source, sink and transfer of carbon and nitrogen. Approximately, 450 Pg (1 Pg= 1015 g) of carbon is estimated to be stored in wetland soils, which accounts for almost a third of the global carbon stock (approximately 1550 Pg) (Whiting and Chanton 2001; Mitsch and Gosselink 2007; Lal 2008). Therefore, carbon stock of wetland soils plays an important role in the carbon cycle. To understand the carbon cycle better, more information about the dynamic changes of soil organic carbon stocks in wetlands is needed. The balance between the inputs and outputs of organic matter determine the carbon accumulation in wetland soils (Bernal and Mitsch 2008; Kayranli et al. 2010). High primary productivity and low decomposition rate caused by waterlogged conditions could increase the carbon storage in wetland soils (Ceballos et al. 2013). Plant species that can form tussocks tend to allocate more carbon to their roots and thus enhance carbon accumulation in wetland soils (Lawrence and Zedler 2013). Moreover, soil organic carbon stock is also influenced by landscape settings, climate and wetland types as these environmental factors could substantially control wetland productivity and microbial communities (Chmura et al. 2003; Trettin and Jurgensen 2003; Bernal and Mitsch 2008). Hydrological fluctuations (water level changes) create highly productive environments for wetlands by altering the aerobic and anaerobic conditions in wetlands (Odum et al. 1995; Stepanauskas et al. 1996; Trettin and Jurgensen 2003). The anoxic environment in a wetland ecosystem is unfavorable for
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the decomposition of organic matter, which could result in a net retention of organic matter and plant debris (Collins and Kuehl 2001; Holden 2005; Mitsch and Gosselink 2007). In addition, the temperature, nutrient supply and quality of organic matter also affect the breakdown of soil organic matter (Bernal and Mitsch 2008; Noe et al. 2013). Recently, Ceballos et al. (2013) demonstrated that soil volume changes could generate large fluctuations in the carbon storage of wetland ecosystems. Nitrogen is often considered a limiting nutrient in wetlands, especially in coastal wetlands, which highlights the importance of nitrogen dynamics in coastal wetlands (Mitsch and Gosselink 2007). Nitrogen retention and loss in wetlands could be controlled by such biogeochemical processes as nitrogen fixation, mineralization, nitrification, and denitrification and so on, which can be affected by the hydrologic connectivity, soil characteristics, and vegetative inputs (Noe et al. 2013). Additionally, Post et al.(1985) have demonstrated that the soil nitrogen storage can be closely related to the climate, biotic activity, and organic matter decomposition. Although the potential ability to retain carbon and nitrogen in coastal wetlands has been addressed (Ceballos et al. 2013; Ardón et al. 2013), the spatial and temporal variability of soil organic carbon and nitrogen storage in tidal salt marshes still need to be investigated on a field scale. The Yellow River Estuary (YRE) wetland is the youngest coastal wetland and newly formed, playing a great role in biodiversity conservation and carbon and nitrogen stocks (Zhang et al. 2010). However, the YRE has been suffering from wetland degradation due to intensive reclamation projects and oil exploration in response to the demand for local economic development. The tidal Tamarix chinensis wetland in the YRE was restored and protected to improve the wetland biodiversity as Tamarix chinensis is one of the dominant plant species and plays an important role in vegetation succession in this region. Most studies have focused on the relationship of Tamarix chinensis with the soil environment and carbon fixation in coastal regions (Cui et al. 2010; Feng et al. 2013). However, little information on the dynamic change in soil carbon and nitrogen stocks in tidal salt marshes with Tamarix chinensis is available. Therefore, the primary objectives of this study were to investigate the spatial and seasonal variations in carbon and nitrogen content and storage in tidal salt marshes with Tamarix chinensis and to discuss the relationship of the carbon and nitrogen contents and stocks with the selected soil properties.
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of the largest estuaries in China. It features a typical temperate monsoon climate with four distinct seasons. The annual mean temperature is 12.4 °C, and the annual mean precipitation and evaporation are 551.6 and 1962 mm, respectively. The dominant species in the study area is Tamarix chinensis, and the main accompanying species are Phragmites australis and Suaeda salsa. The unique hydrology and salinity conditions allow Tamarix chinensis to distribute densely in this area (Cui et al. 2010). Tidal seawater floods affect the study area twice per day due to the existence of adjacent tidal creek. Soil Collection and Analysis Soil samples were collected from each of the five sampling sites along a 200 m sampling belt perpendicular to a tidal creek in a Tamarix chinensis coastal wetland during three seasons (i.e., summer (August, 2007), fall (November 2007) and spring (April, 2008). These five sampling sites were 10 m (S1), 60 m (S2), 80 m (S3), 120 m (S4) and 200 m (S5) away from the tidal creek (Fig. 1). The micro-elevation of S4 was higher than that of other sites. S1 is a mudflat without plants, and the other sites are mainly covered by Tamarix chinensis, Suaeda salsa and Phragmites australis. Three soil cores were collected along soil profiles at depths varying from 0 to 40 cm. We stratified these cores into three increments (i.e., 0–10, 10– 20 and 20–40 cm). The samples for the same soil increment of each sampling site were mixed and placed in polyethylene bags and then brought to the laboratory. All soil samples were air-dried at room temperature for 1 month and sieved through a 2-mm nylon sieve to remover coarse debris. One part of the sieved soils was determined for physical properties (i.e., pH and EC). The remainder was ground with a pestle and mortar until the sample passed through a 0.125 mm nylon sieve to
Materials and Methods Site Description The study area is located in the YRE, near the south coast of Bohai Bay and the west coast of Laizhou Bay. The YRE is one
Fig. 1 Sampling Sites
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determine soil chemical properties. A given amount (i.e., 5, 1 or 0.1 g) soils were taken to determine the detailed chemical or physical properties according to a standard analytical method. Another soil core (5.046 cm diameter, 5 cm height) was collected from each soil layer of each sampling site, and all soil samples were then oven-dried at 105 °C for 24 h to determine the bulk density and soil moisture content (Bai et al. 2013). The total carbon and nitrogen content were measured using an Elemental Analyzer (CHNOS Elemental Analyzer, Vario EL, Germany). The soil organic carbon (SOC) content was measured with the dichromate oxidation method (Nelson and Sommers 1982). The total phosphorus (TP) content was determined using Inductively Coupled Plasma-Atomic Emission Spectrometry (ICP-AES). The soil pH and salinity were measured in the supernatants of 1:5 soil-water mixtures using a Hach pH meter (Hach Company, Loveland, CO, USA) and a salinity meter (VWR Scientific, West Chester, Pennsylvania, USA), respectively.
SOC and TN Densities The SOC density(SOCD)and TN density (TND) of each increment at each sampling site were calculated as follows (Bai et al. 2013; Li et al. 2014): SOCD ¼
TND ¼
X
X
Bi SOCi Ti
Bi TNi Ti
ð1Þ
ð2Þ
where SOCD and TND are the SOC density and TN density, respectively, and denote the SOC or TN content per unit area (kg C/m2). Bi is the bulk density (g/cm3) of soil, and Ti is the soil layer i (cm). SOCi is the SOC content of soil increment i. TNi is TN content of soil increment i (i=1, 2 and 3). Statistical Analysis and Graphing A one-way analysis of variance (ANOVA) was conducted to identify the differences in the carbon, nitrogen and selected soil properties among different seasons. The normality was tested prior to the ANOVA analysis. A logarithmic transformation was necessary to meet the statistical requirement because the data were not normally distributed. A correlation analysis was performed to reveal the relationships between the SOCD, TND and selected soil properties. The statistical analysis was carried out using the SPSS 19.0 software package (SPSS Inc.). Contour maps were generated using the Surfer 10.0 software package (Golden Software, America).
Results Soil Characterization in the Top 20 cm Table 1 shows the soil properties in the top 20 cm for the three sampling seasons. The bulk density was significantly higher in the summer and autumn than in the spring (P 0.05). The soil pH was higher in autumn than in summer and spring, whereas the salinity was higher in spring than in autumn (P < 0.05). Although the SOC and TN contents did not significantly differ (P>0.05), an increasing tendency was observed from summer to spring. SOC and TN Contents As shown in Fig. 2, the SOC contents substantially fluctuated among the three sampling seasons, with the coefficients of variation ranging from 43 to 54 %. In summer, the surface soils generally contained higher SOC levels than deeper soil fractions. Compared to other sampling sites, the patches containing more SOC appeared in the surface soils at S2 and S5, and the zones containing less SOC were observed at S1 and S4. In autumn, the SOC contents were much higher in large patches of the 10–20 cm soil increments than those in the other soil increments at S1 and S2. The SOC content was lowest in patches of the surface soils of S4. However, higher SOC levels were observed in the surface soils at all sampling sites in spring. Moreover, a patch containing more SOC in the 10– 20 cm soil increment was observed at S1 and the patches containing less SOC appeared in the 10–20 cm soil increments of S2, S4 and S5. The spatial distribution of TN contents in the three sampling seasons is illustrated in Fig. 3. The coefficients of variation of TN ranged from 38 to 59 %. With the exception of S2 in spring, the spatial distribution pattern of TN was similar to that of SOC. Patches containing more TN were observed in the surface soils at S2 and S5 in summer and in the 10–20 cm soil increment of S1 in autumn. Lower TN levels were observed in the 20–40 cm soil increments in both summer and autumn and the 10–20 cm soil increments of S4 and S5 in spring. However, the 20–40 cm soil increment contained more TN in the spring, and the TN accumulation was higher in deeper soils at S4, whereas a patch containing less TN was observed in the surface soils at S2. Dynamic Changes of C/N Ratios Figure 4 shows the dynamic changes in the C/N ratios along the soil profiles in three sampling seasons. The C/N ratios in spring were lower than those in summer and autumn (P80) and 20–40 cm
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Summer Autumn Spring ab
Wetlands (2016) 36 (Suppl 1):S145–S152 Physical-chemical properties of the top 20 cm soils Moisture (%)
BD (g/cm3)
pH
Salinity (‰)
SOC (g/kg)
TN (g/kg)
23.22±1.18a 25.01±2.52a 23.47±2.34a
1.88±0.05a 1.83±0.04a 1.48±0.06b
8.13±0.20a 8.64±0.13b 8.26±0.29a
2.37 ± 1.23ab 1.97 ± 0.57a 3.42 ± 1.80b
2.85 ± 1.54a 3.26 ± 1.42a 4.08 ± 2.16a
0.13±0.05a 0.16±0.09a 0.17±0.10a
Different letters represent significant differences between sampling seasons
(>150) soil increments were highest at S3 in spring and autumn, whereas the C/N ratio (>80) of the 10–20 cm soil increment was highest at S1 in summer. The C/N ratios of the 10–20 cm soil increments were significantly higher in the summer than in autumn and spring (P < 0.05). Moreover, the C/N ratios displayed an opposite relationship along the sampling belt in the summer and spring. However, the C/N ratios did not significantly differ in autumn and spring (P>0.05). The C/ N ratios in the 20–40 cm soil increments did not significantly differ among the three sampling seasons. Generally, the C/ N ratios of these wetland soils were higher in summer and autumn than in spring. SOC and TN Densities Figure 5 demonstrates the SOCD at five sampling sites in three sampling seasons. The SOCD in the top 40 cm generally increased along the sampling belt from S1 to S5 in summer, whereas a decreasing tendency was observed in the autumn and spring. With the exception of S4, the top 20 cm soils in this region exhibited higher SOCD than deeper soils below a 20 cm soil depth in each of the three sampling seasons (P summer (1.64 kg/m2). As shown in Fig. 6, the TND generally changed similarly to the SOCD from S1 to S5 except for the higher TND level observed at S4 in spring. The TND levels were higher in the top 20 cm soils than in deeper soils at most of the sampling sites during the three sampling seasons. The surface soils contained higher TND levels than soils deeper than 10 cm soil depth in the summer, whereas the TND levels were higher in the 10–20 cm soil increment in autumn and the 20–40 cm soil increment in spring. The soil increments deeper than 10– 20 cm contributed more to the total TND of the entire soil profile in spring. The average TND level in three seasons was ranked in the following order: spring (0.095 kg/m2) > autumn (0.073 kg/m2) > summer (0.069 kg/m2). Relationships Between SOC, TN and Selected Soil Properties The relationships of the SOC and TN contents and stocks with the selected soil properties are listed in Table 2. The SOC, TN,
10 20
Summer
30 40 10 20
Autumn
30 40 10 20
Spring
30 40
S1
S2
S3
S4
S5
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Fig. 3 Spatial distribution of TN contents (g/kg) in three sampling season
SOCD and TND significantly positively correlated with each other (P