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Different responses of denitrification rates and denitrifying bacterial communities to hydrologic pulsing in created wetlands
Soil Biology & Biochemistry 42 (2010) 1721e1727
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Different responses of denitrification rates and denitrifying bacterial communities to hydrologic pulsing in created wetlands Keunyea Song a, b, c, Seung-Hoon Lee a, William J. Mitsch b, Hojeong Kang a, * a
School of Civil and Environmental Engineering, Yonsei University, Shinchon 134, Seodaemun-gu, Seoul 120-749, Republic of Korea Wilma H. Schiermeier Olentangy River Wetland Research Park, The Ohio State University, 352 W. Dodridge Street, Columbus, OH 43202, USA c Department of Environmental Engineering, Ewha Womans University, Deahyundong 11-1, Seodaemun-gu, Seoul 120-750, Republic of Korea b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 8 February 2010 Received in revised form 10 June 2010 Accepted 10 June 2010 Available online 2 July 2010
Hydrologic pulsing, including water level drawdown and subsequent flooding, may have a considerable impact on both biogeochemical processes and microbial communities in wetlands. Since denitrifying bacteria play a key role in water quality improvement in wetlands, changes in their activities and communities with hydrologic pulsing are an important issue. We investigated the responses of in situ denitrification rates, denitrifying bacterial community structure and their quantities using nitrite reductase (nir) S gene under different hydrological pulsing conditions in created wetlands in central Ohio USA. Average denitrification rates, measured from 4 different sampling locations, were 302, 133, 71 and 271 mg N2OeN m2 h1 during inundated, saturated, drying and reflooding periods, respectively. In particular, the denitrification rates in shallow water level marsh areas (SM) followed by deepwater level marsh areas (DM) showed more sensitivity and magnitude of changes to hydrologic pulsing events than did non-vegetated deepwater areas. This may have been due to the high aerobic decomposition during the drying period and nutrient flushing in shallower marsh areas after the reflooding event. In contrast, the community structure and diversity of denitrifiers based on terminal-restricted fragment length polymorphism (T-RFLP) analysis showed no significant change due to hydrologic pulsing. Instead, the presence and absence of vegetation altered denitrifying bacterial community structure. The nirS gene copy number remained relatively constant with only minor increases during water level drawdown followed by a significant decrease when a sudden reflooding event occurred. These results indicate that environmental disturbances, such as hydrologic pulsing, have a major impact on the denitrification process, but less impact on the community structures of the denitrifying bacteria. In addition, there was no relationship among the denitrification rate, the community structure, and the quantity of denitrifiers, suggesting that changes in denitrification rates during hydrologic pulsing events were not caused by the changes in microbial community structure but more by physicochemical factors, such as substrate availability and hydrology. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: Hydrologic pulsing Created wetlands Denitrification Denitrifying bacterial community structure Olentangy River Wetland Research Park
1. Introduction Hydrologic changes, such as summer and autumn drought followed by flooding, are now expected to be more severe in rivers and their adjacent riparian ecosystems due to changes in the precipitation patterns as well as riparian buffer zone (IPCC, 2001; Mitsch and Jørgensen, 2004). In particular, since hydrology is considered to be the single most influential factor determining wetland characteristics (Mitsch and Gosselink, 2007), altered
* Corresponding author. Tel.: þ82 2 2123 5803; fax: þ82 2 364 5300. E-mail address: [email protected] (H. Kang). 0038-0717/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.soilbio.2010.06.007
hydrologic regime could be responsible for drastic changes in structures and functions of wetlands. Several studies have reported the effect of hydrologic changes on wetlands in terms of their structure and ecological function. In general, enhanced mineralization rates and substantial nutrient leaching are well known consequences of successive drying and flooding (Baldwin and Mitchell, 2000; Turner and Haygarth, 2001; Venterink et al., 2002). These altered process rates under hydrologic changes could be associated with the responses of microbial communities (Schimel and Gulledge, 1998). It has been also suggested that changes in microbial communities and their biomass caused changes in biogeochemical processes such as methane emissions and soil respiration in wetlands (Freeman et al., 2002; Davidson et al., 2004; Knorr et al., 2008). Likewise, Kim et al.
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(2008) reported that different types of wetlands may exhibit diverse responses to drought in terms of denitrifiers and methanogens. However, the question of whether the microbial community structure affects processes at the ecosystem scale has provoked much debate with conflicting results (e.g. Cavigelli and Robertson, 2000; Loreau et al., 2001; Rich et al., 2003; Dandie et al., 2008; Ma et al., 2008). The effects of pulsing hydrology on water quality, denitrification, nitrous oxide and methane emissions, sedimentation, and aquatic productivity were investigated in a comprehensive pulsing study at the created wetlands in 2004e2005 used in this current study sitedThe Olentangy River Wetland Research Park in central Ohio USA (Mitsch et al., 2005, 2008; Hernandez and Mitsch, 2006, 2007; Altor and Mitsch, 2006, 2008; Nahlik and Mitsch, 2008; Tuttle et al., 2008). Our current study on denitrification and microbial communities in the same wetlands is a follow-up to those investigations of the importance of river pulsing on wetland ecosystem function. One of the important processes occurring in wetlands is denitrification, which transfers nitrate to gas type nitrogen (Paul and Clark, 1996; Zumft, 1997). The denitrification process has been studied as a means of natural water quality improvement and a source/sink of nitrous oxide (e.g. Lashof and Ahuja, 1990; Hernandez and Mitsch, 2006, 2007), and denitrifying bacterial communities have been investigated in natural environments (e.g. Braker et al., 2001; Castro-González et al., 2005: Cao et al., 2008). Wallenstein et al. (2006) suggested that denitrifying bacterial communities in soils are controlled by environmental conditions such as temperature and moisture conditions as proximal control factors and by environmental disturbances as distal factors. Although several researchers have already studied denitrifying bacterial community structure in wetlands, how those communities respond to environmental disturbances such as the drying and reflooding of hydrologic pulses, and their relationship with denitrification rates in wetlands remains poorly understood. Denitrification is mediated by denitrifying bacteria communities under anaerobic conditions (Zumft, 1997; Philippot and Hallin, 2005), hence, it is expected that hydrologic pulsing could affect both denitrifying bacterial community structure and the denitrification process, subsequently. In addition, hydrologic pulsing can act as a physiological stress and disturbance for microorganisms (Baldwin and Mitchell, 2000; Schimel et al., 2007; Gordon et al., 2008) possibly resulting in a decrease in quantity of denitrifying bacteria. Therefore, we investigated how the denitrification process and denitrifying bacterial community structure and quantity responded to hydrologic pulsing events in created wetlands. We also tested the relationships among denitrifying bacterial community structure, their quantity, and denitrification rates to better understand the role of microbial community structure at the ecosystem scale. Since denitrification is catalyzed by nitrite reductase (nir), which is widespread among taxonomically diverse microorganisms (Philippot, 2002), we targeted nitrite reductase (nir) S gene as a marker indicating the presence of denitrifying bacteria. We used the terminal-restricted fragment length polymorphism (T-RFLP) technique and real-time PCR (RT-PCR) to analyze the denitrifying bacterial community structure and denitrifying bacterial quantity, respectively.
were created in 1993e1994 and have had river water pumped through them continuously since then (Mitsch et al., 1998, 2005, 2008). The sampling sites in both wetlands were selected based on both a longitudinal gradient from inflow to outflow and a transverse gradient from deepwater in the middle to shallow water on the edges (Fig. 1). The sampling sites included the inflow and outflow deepwater areas along the longitudinal gradient and the deepwater (DM) and shallow water (SM) marsh sites along the transverse gradient. DM and SM sites were selected near inflow and outflow areas. The two wetlands were used as replicates and each sampling site had 2 pseudo-replicates. To investigate hydrologic pulses, we sampled denitrification rates and microbial communities during 4 different hydrologic phases of a drying and rewetting cycle in each of the two wetlands: inundated, saturated, drying and reflooding. The inundated phase in July 2008 occurred before water level drawdown commenced and was considered a control treatment. In early August 2008, surface water level decreased naturally due to low precipitation for 2 weeks; this was considered to be the saturated phase. Then, pumped water inflow from the river to the wetlands was purposefully discontinued for 7 days from August 23 to 29, 2008, and both wetland dried-up; this is the drying phase. After the week of drying, water was pumped again into the wetlands for the reflooding phase. It took only a day to flood the wetland areas to their initial water depths. The water depths for each phase are presented in Table 1. 2.2. Water and soil sampling and measurements Water temperature, pH, and DO were measured in situ using a YSI-meter. Duplicated soil and water samples from each site were collected and stored at 4 C before subsequent analysis. Soil samples for molecular analysis were preserved at 20 C. Extracted water from soil samples with double distilled water were filtered through 0.45 mm filter and used to determine dissolved organic
2. Materials and methods 2.1. Site description and experimental designs This study was conducted at the Wilma H. Schiermeier Olentangy River Wetland Research Park (ORWRP) placed at The Ohio State University in Columbus, USA (Fig. 1). Two 1-ha wetland areas
Fig. 1. Two 1-ha experimental wetland basins used in this study at the Olentangy River Wetland Research Park at the Ohio State University, Columbus, USA. Open circle, triangle, rectangle and diamond represent inflow deepwater (IN), deepwater marsh (DM), shallow water marsh (SM) and outflow deepwater (OUT), respectively. IN and OUT sampling site had four replicates while DM and SM had eight replicates in two created wetlands.
K. Song et al. / Soil Biology & Biochemistry 42 (2010) 1721e1727 Table 1 Water level (mean SE) in each hydrologic phase in the simulated pulse in the created experimental wetlands at the Olentangy River Wetland Research Park.a Surface water level (cm)
IN
Inundated Saturated Drying Reflooding
6.7 1.3 3.0 5.6
DM
0.0 0.5 0.7 0.0
5.6 0.8 8.0 5.8
SM
0.0 0.8 0.4 0.1
0.6 0.5 7.0 3.1
OUT
0.4 0.5 0.4 0.5
7.4 5.5 0.3 6.1
0.4 2.1 0.1 0.1
a IN, DM, SM and OUT represent different sampling sites: inflow area, deepwater marsh, shallow water marsh and outflow area of the two wetlands, respectively.
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The 20 ml reaction mixture contained template DNA, 2 SYBR green Supermix (Bio-Rad) and primer pair (each final conc. 12.5 mM) nirS832F (TAC CAC CCC GAG CCG CGC GT) e nirS3R (GCC GCC GTC RTG VAG GAA). The thermal cycling conditions of the RT-PCR included denaturation at 95 C for 2 min, 40 cycles of amplification at 95 C for 25 s, 65 C for 30 s and 72 C for 25 s. The PCR was performed using an I-CyclerÔ Version 3.0 a (Bio-Rad) RT-PCR assay was performed two times for each duplicated sample. 2.5. Statistical analysis
2.3. Denitrifying bacterial community structure DNA from soil sample was extracted using an UltraClean soil DNA kit (MoBio) and kept at 20 C prior to analysis. A fingerprinting analysis using terminal-restriction fragment length polymorphism (T-RFLP) was conducted to determine denitrifying bacterial community structure. The 40 ml reaction mixture contained template DNA (approximately 100 ng), PCR buffer, dNTPs (final conc. 200 mM), bovine serum albumin (8 mg), Taq polymerase (2.5 unit) (Promega, USA) and primer pair (each final conc. 12.5 mM). The florescence-labeled primer pair nirS832F (GTN AAY GTN AAR GAR CAN GG) e nirS1606R-FAM (ACR TTR AAY TTN CCN GTN GG) was used as described by Liu et al. (2003). The PCR was performed using a PTC-100 thermal cycler (MJ Research, USA). A denaturation step was at 94 C for 2 min, followed by 35 cycles at 95 C for 30 s, primer annealing at 65 C for 60 s, and extension at 72 C for 1 min and the final extension was performed at 72 C for 10 min. The PCR product was separated by electrophoresis and purified using a DNA purification kit (MoBio). Purified PCR products were then digested using the restriction enzyme HhaI (Promega) at 37 C for 6 h, followed by heat inactivation of the restriction enzyme at 65 C for 15 min. The analysis of T-RFs was performed using an ABI 3730 XL automatic sequencer (Applied Biosystems). 2.4. Quantification of denitrifying bacteria In order to quantify denitrifying bacteria in our soil samples, we used quantitative real-time PCR (RT-PCR) targeting the nirS gene.
Statistical analyses were performed using SPSS ver. 15.0. Significant differences (P < 0.05) in obtained data within treatments and sites were determined according to two-way ANOVA, followed by Tukey’s test. Stepwise linear regression was applied to determine the relationship between denitrification and chemical properties in wetlands. The denitrifying bacterial community structure and diversity were evaluated based on the number and area of terminalrestriction fragments (T-RFs) in each phase. Lengths with less than a 0.5 bp difference were considered to be the same peak. The peak area for each fragment was converted to a proportion of the total area in each community composition and represented as abundances of T-RFs. The bacteria diversity was calculated using the Shannon diversity index (Shannon, 1948). The differences in community structure between treatments were analyzed using multi-response permutation procedures (MRPP) and non-metric multidimensional scaling (NMS) in PC-ORD ver. 5.0 (McCune and Mefford, 1999). 3. Results 3.1. Responses of denitrification to hydrologic pulsing The water level drawdown and drying followed by the reflooding event in the wetlands resulted in significant changes in denitrification (Fig. 2). During the saturated period, denitrification rates decreased dramatically, except at the inflow site. In contrast, denitrification rates increased during reflooding to similar or slightly higher values than the original rates prior to the hydrologic pulsing. Interestingly, denitrification in the SM increased
800
Denitrification (µg N2O-N m-2 hr-1)
carbon (DOC) concentrations (mg g soil1) using TOC-meter (TOCV, Shimadzu). Specific UV absorbance (SUVA) was calculated using the same filtered water samples by UV absorbance at 254 nm (USEPA, 2005). Extractable nitrate contents (mg g soil1) in the sediment were analyzed by the colorimetric method (Anderson and Ingram, 1989). In situ denitrification rates in the presence of hydrologic pulsing events were measured using the acetylene blocking technique (Tiedje, 1982; Tiedje et al., 1989). PVC chambers, 4 cm in diameter and 80 cm in height (Hernandez and Mitsch, 2007), were inserted 10 cm deep into the sediment at each sampling site. Acetylene gas was injected into the chambers until 10% (v/v) of the headspace of the chamber was occupied by the gas. Then, headspace gas samples were collected every 20 min for 2 h. Accumulated nitrous oxide concentrations in the gas samples were analyzed using an electron capture detector (ECD) equipped gas chromatograph (GC-14A, Shimadzu) with a porapak-Q column. For calculating the denitrification flux, only the slope which showed a linear increase in nitrous oxide concentrations with time was selected. Two samples at the most were excluded in a 6 sample set when it was necessary to satisfy the significance of linearity in the slopes. One data point from SM in September was eliminated from subsequent data analysis when it showed an extremely high denitrification rate, which was considered as an outlier.
Site: P=0.547 Hydrology: P=0.001 Interaction: P=0.046
Inundateda Saturatedb Dryingb Refloodinga
600
400
200
0 IN
DM
SM
OUT
Fig. 2. Denitrification rates (mean SE) by hydrologic pulsing treatment in the experimental wetlands. IN, DM, SM and OUT stand for inflow area, deepwater marsh, shallow water depth marsh and outflow areas, respectively. Different letter next to the legend represents significant differences among each period at P < 0.05 based on Tukey analysis in two-way ANOVA. Also, significances of two-way ANOVA for denitrification rates in relation to different site, hydrologic pulsing, and their interaction are shown.
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significantly after reflooding, resulting in 175% higher rates than during the original inundated period (Fig. 2). The magnitude of effect on denitrification rate due to hydrologic pulsing was in the order of SM > DM > OUT > IN based on the slope of each regression (Fig. 3). A significant correlation was found between denitrification rates and water level changes (R2 ¼ 0.31, P < 104) although the individual regressions from the outflow and inflow sites were not statistically significant. Denitrification, soil DOC, SUVA, and NO 3 concentration and the nirS gene copy number for each hydrologic phase are presented in Table 2. SUVA exhibited lower values during drying and reflooding periods. Nitrate concentrations in the soil were 4.74 and 4.22 mg g soil1 in drying and reflooding periods, respectively, higher concentrations than those in the inundated and saturated periods. However, these chemical properties did not exhibit significant differences among hydrologic pulsing phases (Table 3). Although DOC also did not show significant differences among hydrologic pulsing periods, stepwise linear regression showed that denitrification rates could be explained by DOC concentration (R2 ¼ 0.15, P ¼ 0.03, Fig. 4).
3.2. Responses of denitrifying bacterial community structure and quantity to hydrologic pulsing
Table 2 Denitrification rates and chemical characteristics (mean SE) in response to hydrologic pulsing in created experimental wetlands at Olentangy River Wetland Research Park.a SUVA NO No. of gene Denitrification DOC 3 (mg N2OeN (mg g soil1) (L mg-M1) (mg g soil1) copy (1012) m2 h1) Inundated 301 32a Saturated 133 29b Drying 71 21b Reflooding 271 42a
0.49 0.29 0.40 0.35
0.05 0.03 0.02 0.05
1.50 1.46 0.93 1.01
0.14 0.21 0.11 0.11
4.16 4.02 4.61 4.28
0.28 0.25 0.41 0.21
1.49 1.60 1.67 1.02
0.11a 0.13a 0.16a 0.09b
a Different letters next to the values indicate the significant differences (P < 0.05) among different hydrologic periods by Tukey analysis in two-way ANOVA. SUVA represents specific UV absorbance of organic carbon.
NMS ordination confirmed a distinct difference of community composition depending on the presence/absence of marsh vegetation rather than the effect of hydrologic pulsing treatments (Fig. 6). The first 2 axes accounted for 54.7% and 39.3% of community differences. In addition, MRPP statistical A-values for T-RFs confirmed the significance of differences between open water and vegetated marsh areas with an A-value of above 0.21 (P < 0.05, Table 3). 4. Discussion
Denitrification (µg N2O-N m-2 hr-1)
The gene copy number exhibited significant differences among hydrologic phases as well as sites (Fig. 5). Water level drawdown and the drying period led to a slight increase in the nirS gene copy number in all sampling sites except the inflow area. Furthermore, sudden reflooding led to a decrease in nirS gene copy number in every site. Shannon diversity index was also not affected by hydrologic pulsing (Table 2). However, the diversity indices between vegetated marsh and non-vegetated areas were significantly different according to one-way ANOVA (P ¼ 0.048). The diversity indices of the marsh areas (2.42 0.07 for DM and 2.52 0.08 for SM) were higher than those of the non-vegetated areas (2.31 0.11 for IN and 2.26 0.12 for OUT). The community structure of denitrifying bacteria exhibited significant differences among sampling sites while hydrologic pulsing did not induce any significant differences of community structure among the inundated, saturated, drying and reflooding periods (Table 3).
600
IN (a= 8.4) DM* (a= 18.8) SM* (a= 33.3) OUT (a=15.2) Total* (a= 16.4)
400
Hydrologic pulses such as the one described here are expected to occur more often and with higher intensity due to climate change. A decrease of denitrification with water level drawdown has been commonly expected and reported (e.g. Groffman and Tiedje, 1988; Baldwin and Mitchell, 2000). However, increased denitrification in lowered water level in peatland was also reported (Bandibas et al., 1994; Dowrick et al., 1999) and they suggested that denitrification peaked in saturated, not water logged conditions. Previous studies about effects of hydrologic pulsing on microbial communities have been generally focused on eubacteria and fungi (Fierer et al., 2003; Gordon et al., 2008; Fenner et al., 2005). For denitrifiers, only drought effects (Kim et al., 2008) and the effects of different hydrologic regime in different locations (Bougon et al., 2009) have been assessed. Therefore, the response of denitrifiers under hydrologic pulsing is still not known. In addition, the relationship among denitrifying bacterial community, quantity and their process rates have not been considered in most previous studies, even though the altered denitrification rate could be a result of physiological response to hydrologic pulsing of denitrifying bacterial communities (Schimel and Gulldege, 1998; Schimel et al., 2007; Bougon et al., 2009). In this study, we had hypothesized that the responses of denitrification rates in wetlands to hydrologic pulsing would be induced by a shifted denitrifying bacterial community. However, we found that the denitrification process and denitrifying bacterial community responded differently to hydrologic pulsing events in wetlands, which did not match with our hypothesis.
200
Table 3 MRPP A-values of denitrifying bacterial community structure for different hydrologic and site effects in the wetlands (*P < 0.05, **P < 0.01). 0 -0.10
Hydrology -0.05
0.00
0.05
0.10
0.15
Water table level (m) Fig. 3. The responses of denitrification rates depending on surface water level changes by hydrologic pulsing in each sampling site using linear regression. Slope a (102) of each regression line is shown in the legend. An asterisk shows the significance of regression at P < 103. Averaged denitrification rates and water levels from each sampling site in the wetlands were used.
A-value
Site
Inundated
Saturated Drying Reflooding
0.001 0.042 0.013
IN
DR SR OUT
0.25* 0.31** 0.00
A-value
Saturated
Drying Reflooding
0.006 0.014
DR
SR OUT
0.00 0.21**
Drying
Reflooding
0.008
SR
OUT
0.25**
K. Song et al. / Soil Biology & Biochemistry 42 (2010) 1721e1727
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Denitrification (µg N2O-N m-2 hr-1)
500 DeN=346.7 DOC+61.2 (R2=0.147, P=0.03, n=44) 400
300
200
100
0 0.0
0.2
0.4
0.6
0.8
1.0
DOC (mg g soil-1) Fig. 4. Denitrification rates in relation to DOC concentration in the wetlands by stepwise linear regression model. Fig. 6. Non-metric multidimensional scaling (NMS) ordination of denitrifying bacterial community determined by nirS T-RFLP profile. Points with different shapes represent different hydrologic treatment samples with an averaged proportional abundance of T-RFs.
4.1. Responses of denitrification to hydrologic pulsing Denitrification decreased with drying and increased during the reflooding period. This result is consistent with previous results, which showed a major influence of hydrologic changes on denitrification rates (e.g. Groffman and Tiedje, 1988; Freeman et al., 1997; Goldberg and Gebauer, 2009). Freeman et al. (1997) also observed a nitrate release from peatland soils with a decline of N2O emission due to lowered denitrification rate over a drying period and the reversible responses when the inflow was re-initiated. In addition, the extent of the changes in denitrification rates under hydrologic pulsing was spatially different within sampling locations. For example, the highest denitrification rate during the reflooding period was exhibited in the shallow marsh site (SM) although SM sites exhibited the lowest rates during the inundated period. This result could be explained by the magnitude of water level change as well as higher microbial activity in the vegetated marshes. SM sites maintained a relatively longer drying period due to low water level; this could have led to inorganic nutrient release by aerobic decomposition. Release of nitrate in dried peatlands
Inundated
Number of Gene Copy (1011)
30
ab
Site: P=0.043 Hydrology: P=0.001 Interaction: P=0.095
Saturated a Drying a Reflooding
b
20
10
0 IN
DM
SM
OUT
Fig. 5. The patterns of nirS gene copy number (mean SE) with hydrologic pulsing events from different sampling sites in the experimental wetlands. Different letter next to the legend represents significant differences among each period at P < 0.05 based on Tukey analysis in two-way ANOVA. Also, significances of two-way ANOVA for denitrification rates in relation to different site, hydrologic pulsing, and their interaction are shown.
(Freeman et al., 1993), enhanced extracellular enzyme activities and the following large flush of inorganic nutrients after drying period in wetlands (Song et al., 2007) have been reported. Therefore, released inorganic nutrients during a long drying period could result in the drastic increase in denitrification by increasing substrate availability in the SM site. DOC also exhibited a positive correlation with denitrification, indicating that high denitrification is associated with high carbon availability. Therefore, our result suggests that denitrification is regulated by physicochemical characteristics such as substrate availability and water level in wetlands.
4.2. Responses of denitrifying bacterial community structure and quantity to hydrologic pulsing Different from the response of denitrification rate, hydrologic pulsing had no distinct influence on the community structure of denitrifying bacteria in the wetlands. One possible explanation involves the physiological characteristics of denitrifiers. Most denitrifiers are facultative, which prefer oxygen instead of nitrate as an electron acceptor (Zumft, 1997). Therefore, the changes in redox condition resulting from hydrologic pulsing might not have a significant influence on denitrifiers. Another possibility is that microbial communities, that experience repeated mild stresses, tend to be more resistant to stress than other communities that have not experienced stress (Fierer and Schimel, 2002; Griffiths et al., 2005; Schimel et al., 2007; Philippot et al., 2008). Reduced microbial mortality rate by repeated drying-reflooding events (Fierer and Schimel, 2002) and no significant changes in denitrifying bacterial community structure under drought in natural riparian ecosystems (Kim et al., 2008) have been observed. Therefore, we speculate that water stress-tolerating denitrifiers could be selected by natural succession and competition as the created wetlands have undergone natural drying and reflooding events. While hydrologic pulsing did not affect denitrifying bacterial communities, we observed large differences in denitrifying bacterial community structure in the presence/absence of vegetation. The changes in denitrifying community structures in response to their habitat conditions like temperature, DO gradient, vegetation or land use type have been reported (Avarahami et al., 2002; Rich et al., 2003; Castro-González et al., 2005). Nutrients or soil type
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appeared to have greater impacts on microbial communities (Lundquist et al., 1999; McLean and Huhta, 2000; Fierer et al., 2003; Bossio et al., 2006). Bossio et al. (2006) reported that the differences of microbial community structure between sampling sites was greater than seasonal variability within each site. Different vegetation types can also influence the denitrifying bacteria communities (Bremer et al., 2007). However, since two wetlands in this study have relatively similar vegetation communities, dominated by Typha spp. and taxonomically similar species, we could not find the effect of different vegetation type on microbial community structure. Therefore, our results, along with previous studies, support the hypothesis that microbial community structure is influenced by long-term physicochemical characteristics rather than by episodic hydrologic disturbances. We originally expected that reduction in denitrifying bacterial quantity by physiological stress under hydrological pulsing would restrict denitrification rate. In this study, nirS gene copy number slightly increased or remained constant during the drying period, and it dropped as reflooding occurred. We suggest that while facultative denitrifiers can survive in aerobic condition, reflooding caused serious osmotic stress (Schimel et al., 2007), resulting in a decline of gene copy number. This change in quantity of denitrifiers did not correspond with the response of denitrification rates under hydrologic pulsing. For example, the denitrification rate increased while denitrifying bacterial quantity decreased during reflooding period. This result was possibly because the nirS gene copy number does not represent the number of active denitrifying bacteria (Philippot and Hallin, 2005). This kind of discrepancy between microbial biomass and process rates has been reported (Pesaro et al., 2004; Gordon et al., 2008). Gordon et al. (2008) showed the decrease of microbial biomass C and N with an increase of basal respiration as a result of drying and reflooding events. Pesaro et al. (2004) also reported that while respiration rates were recovered, soil microbial biomass was not after drought. Some studies have suggested that different denitrifying bacterial community composition or their quantity would contribute to denitrification rates or N2O emissions due to their physiological differences in communities (Cavigelli and Robertson, 2000, 2001; Rich et al., 2003). However, the different responses of denitrification and denitrifying bacterial communities to hydrological pulsing events in this study imply that the community structure was not a determinant of the denitrification rates. This result supports the insurance hypothesis, suggesting a functional redundancy of biodiversity (Yachi and Loreau, 1999; Loreau et al., 2001).
4.3. Conclusions This study showed that short-term hydrologic pulsing has a major influence on denitrification rates in wetlands. This change in denitrification was not induced by the response of denitrifying bacterial community to hydrologic pulsing. Instead, DOC and water level could initially drive the changes in denitrification rates in the short-term hydrologic disturbance. While hydrologic pulsing did not induce any significant differences in denitrifying bacterial community structure, the presence and absence of vegetation did influence denitrifying bacterial community structure. Our results suggest the prevailing importance of physicochemical properties affecting denitrification rate over community composition or quantity of denitrifying bacteria. However, the abundance of denitrifying bacteria was reduced by hydrologic pulsing, particularly by the reflooding event. Therefore, repeated and severe drying-reflooding events with climate change over the long term could induce large decreases of denitrifying bacteria which could result in poorer water quality in the wetlands and adjacent rivers.
Acknowledgements H. Kang is grateful to AEBRC, EcoSTAR, EcoRiver and NRF (20090079549) for financial support. This research is also partially supported by the Olentangy River Wetland Research Park and by the U.S. Environmental Protection Agency grant (EM83329801-0 and MX95413108-0). References Altor, A.E., Mitsch, W.J., 2006. Methane flux from created wetlands: relationship to intermittent versus continuous inundation and emergent macrophytes. Ecological Engineering 28, 224e234. Altor, A.E., Mitsch, W.J., 2008. Pulsing hydrology, methane emissions, and carbon dioxide fluxes in created marshes: a 2-year ecosystem study. Wetlands 28, 423e438. Anderson, J.M., Ingram, J.S.I., 1989. Tropical Soil Biology and Fertility: a Handbook of Methods. CAB International, Wallingford. Avarahami, S., Conrad, R., Braker, G., 2002. Effect of soil ammonium concentration on N2O release and on the community structure of ammonia oxidizers and denitrifiers. 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Nitrous oxide emissions from a gully mire in mid-Wales, UK, under simulated summer drought. Biogeochemistry 44, 151e162. Fenner, N., Freeman, C., Reynolds, B., 2005. Hydrological effects on the diversity of phenolic degrading bacteria in a peatland: implications for carbon cycling. Soil Biology & Biochemistry 37, 1277e1287. Fierer, N., Schimel, J.P., 2002. Effects of drying-rewetting frequency on soil carbon and nitrogen transformations. Soil Biology & Biochemistry 34, 777e787. Fierer, N., Schimel, J.P., Holden, P.A., 2003. Influence of drying-rewetting frequency on soil bacterial community structure. Microbial Ecology 45, 63e71. Freeman, C., Nevison, G.B., Kang, H., Hughes, S., Reynolds, B., Hudson, J.A., 2002. Contrasted effects of simulated drought on the production and oxidation of methane in a mid-Wales wetland. Soil Biology & Biochemistry 34, 61e67. Freeman, C., Lock, M.A., Reynolds, B., 1993. 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Mitsch, W.J., Zhang, L., Fink, D.F., Hernandez, M.E., Altor, A.E., Tuttle, C.L., Nahlik, A.M., 2008. Ecological engineering of floodplains. Ecohydrology & Hydrobiology 8, 139e147. Nahlik, A.M., Mitsch, W.J., 2008. The effect of river pulsing on sedimentation and nutrients in created riparian wetlands. Journal of Environmental Quality 37, 1634e1643. Paul, E.A., Clark, F.E., 1996. Soil Microbiology and Biochemistry. Academic Press, San Diego, California. Pesaro, M., Widmer, F., Nicollier, G., Zeyer, J., 2004. Impact of soil drying-rewetting stress microbial communities and activities and on degradation of two crop protection products. Applied and Environmental Microbiology 70, 2577e2587. Philippot, L., 2002. Denitrifying genes in bacterial and archaeal genomes. Biochimica et Biophysica Acta 1577, 355e376. Philippot, L., Cregut, M., Chéneby, D., Bressan, M., Dequiet, S., Martin-Laurent, F., Ranjard, L., Lemanceau, P., 2008. Effect of primary mild stresses on resilience and resistance of the nitrate reducer community to a subsequent severe stress. FEMS Microbiology Letters 285, 51e57. Philippot, L., Hallin, S., 2005. Finding the missing link between diversity and activity using denitrifying bacteria as a model functional community. Current Opinion in Microbiology 8, 234e239. Rich, J.J., Heichen, R.S., Bottomley, P.J., Cromack, K., Myrold, D.D., 2003. Community composition and functioning of denitrifying bacteria from adjacent meadow and forest soils. Applied and Environmental Microbiology 69, 5974e5982. Schimel, J., Balser, T., Wallenstein, M., 2007. Microbial stress-response physiology and its implications for ecosystem function. Ecology 88, 1386e1394. Schimel, J.P., Gulledge, J., 1998. Microbial community structure and global trace gases. Global Change Biology 4, 745e758. Shannon, C.E., 1948. A mathematical theory of communication. Bell System Technical Journal 27, 623e656. Song, K.Y., Zoh, K.D., Kang, H., 2007. Release of phosphate in a wetland by changes in hydrological regime. Science of Total Environment 380, 13e18. Tiedje, J.M., 1982. Denitrification. In: Page, A.L., Miller, R.H., Keeney, D.R. (Eds.), Methods of Soil Analysis. Part 2. Chemical and Microbiological Properties. Agronomy No. 9. American Society of Agronomy, Madison, pp. 1011e1026. Tiedje, J.M., Simkins, S., Groffman, P.M., 1989. Perspectives on measurement of denitrification in the field including recommended protocols for acetylene based methods. Plant and Soil 115, 261e284. Turner, B.L., Haygarth, P.M., 2001. Phosphorus solubilization in rewetted soils. Nature 411, 258. Tuttle, C.L., Zhang, L., Mitsch, W.J., 2008. Aquatic metabolism as an indicator of the ecological effects of hydrologic pulsing in flow-through wetlands. Ecological Indicators 8, 795e806. USEPA, 2005. Determination of Total Organic Carbon and Specific UV Absorbance at 254 nm in Source Water and Drinking Water. Method 415.3, EPA/600/R-05/055. Venterink, H.O., Davidsson, T.E., Kiehl, K., Leonardson, L., 2002. Impact of drying and rewetting on N, P, K dynamics in a wetland soil. Plant and Soil 243, 119e130. Wallenstein, M.D., Myrold, D.D., Firestone, M., Voytek, M., 2006. Environmental controls on denitrifying communities and denitrification rates: insights from molecular methods. Ecological Applications 16, 2143e2152. Yachi, S., Loreau, M., 1999. Biodiversity and ecosystem productivity in a fluctuating environment: the insurance hypothesis. Proceedings of the National Academy of Sciences of the United States of America 96, 1463e1468. Zumft, W.G., 1997. Cell biology and molecular basis of denitrification. Microbiology and Molecular Biology Reviews 61, 533e616.
Contents lists available at ScienceDirect
Soil Biology & Biochemistry journal homepage: www.elsevier.com/locate/soilbio
Different responses of denitrification rates and denitrifying bacterial communities to hydrologic pulsing in created wetlands Keunyea Song a, b, c, Seung-Hoon Lee a, William J. Mitsch b, Hojeong Kang a, * a
School of Civil and Environmental Engineering, Yonsei University, Shinchon 134, Seodaemun-gu, Seoul 120-749, Republic of Korea Wilma H. Schiermeier Olentangy River Wetland Research Park, The Ohio State University, 352 W. Dodridge Street, Columbus, OH 43202, USA c Department of Environmental Engineering, Ewha Womans University, Deahyundong 11-1, Seodaemun-gu, Seoul 120-750, Republic of Korea b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 8 February 2010 Received in revised form 10 June 2010 Accepted 10 June 2010 Available online 2 July 2010
Hydrologic pulsing, including water level drawdown and subsequent flooding, may have a considerable impact on both biogeochemical processes and microbial communities in wetlands. Since denitrifying bacteria play a key role in water quality improvement in wetlands, changes in their activities and communities with hydrologic pulsing are an important issue. We investigated the responses of in situ denitrification rates, denitrifying bacterial community structure and their quantities using nitrite reductase (nir) S gene under different hydrological pulsing conditions in created wetlands in central Ohio USA. Average denitrification rates, measured from 4 different sampling locations, were 302, 133, 71 and 271 mg N2OeN m2 h1 during inundated, saturated, drying and reflooding periods, respectively. In particular, the denitrification rates in shallow water level marsh areas (SM) followed by deepwater level marsh areas (DM) showed more sensitivity and magnitude of changes to hydrologic pulsing events than did non-vegetated deepwater areas. This may have been due to the high aerobic decomposition during the drying period and nutrient flushing in shallower marsh areas after the reflooding event. In contrast, the community structure and diversity of denitrifiers based on terminal-restricted fragment length polymorphism (T-RFLP) analysis showed no significant change due to hydrologic pulsing. Instead, the presence and absence of vegetation altered denitrifying bacterial community structure. The nirS gene copy number remained relatively constant with only minor increases during water level drawdown followed by a significant decrease when a sudden reflooding event occurred. These results indicate that environmental disturbances, such as hydrologic pulsing, have a major impact on the denitrification process, but less impact on the community structures of the denitrifying bacteria. In addition, there was no relationship among the denitrification rate, the community structure, and the quantity of denitrifiers, suggesting that changes in denitrification rates during hydrologic pulsing events were not caused by the changes in microbial community structure but more by physicochemical factors, such as substrate availability and hydrology. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: Hydrologic pulsing Created wetlands Denitrification Denitrifying bacterial community structure Olentangy River Wetland Research Park
1. Introduction Hydrologic changes, such as summer and autumn drought followed by flooding, are now expected to be more severe in rivers and their adjacent riparian ecosystems due to changes in the precipitation patterns as well as riparian buffer zone (IPCC, 2001; Mitsch and Jørgensen, 2004). In particular, since hydrology is considered to be the single most influential factor determining wetland characteristics (Mitsch and Gosselink, 2007), altered
* Corresponding author. Tel.: þ82 2 2123 5803; fax: þ82 2 364 5300. E-mail address: [email protected] (H. Kang). 0038-0717/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.soilbio.2010.06.007
hydrologic regime could be responsible for drastic changes in structures and functions of wetlands. Several studies have reported the effect of hydrologic changes on wetlands in terms of their structure and ecological function. In general, enhanced mineralization rates and substantial nutrient leaching are well known consequences of successive drying and flooding (Baldwin and Mitchell, 2000; Turner and Haygarth, 2001; Venterink et al., 2002). These altered process rates under hydrologic changes could be associated with the responses of microbial communities (Schimel and Gulledge, 1998). It has been also suggested that changes in microbial communities and their biomass caused changes in biogeochemical processes such as methane emissions and soil respiration in wetlands (Freeman et al., 2002; Davidson et al., 2004; Knorr et al., 2008). Likewise, Kim et al.
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(2008) reported that different types of wetlands may exhibit diverse responses to drought in terms of denitrifiers and methanogens. However, the question of whether the microbial community structure affects processes at the ecosystem scale has provoked much debate with conflicting results (e.g. Cavigelli and Robertson, 2000; Loreau et al., 2001; Rich et al., 2003; Dandie et al., 2008; Ma et al., 2008). The effects of pulsing hydrology on water quality, denitrification, nitrous oxide and methane emissions, sedimentation, and aquatic productivity were investigated in a comprehensive pulsing study at the created wetlands in 2004e2005 used in this current study sitedThe Olentangy River Wetland Research Park in central Ohio USA (Mitsch et al., 2005, 2008; Hernandez and Mitsch, 2006, 2007; Altor and Mitsch, 2006, 2008; Nahlik and Mitsch, 2008; Tuttle et al., 2008). Our current study on denitrification and microbial communities in the same wetlands is a follow-up to those investigations of the importance of river pulsing on wetland ecosystem function. One of the important processes occurring in wetlands is denitrification, which transfers nitrate to gas type nitrogen (Paul and Clark, 1996; Zumft, 1997). The denitrification process has been studied as a means of natural water quality improvement and a source/sink of nitrous oxide (e.g. Lashof and Ahuja, 1990; Hernandez and Mitsch, 2006, 2007), and denitrifying bacterial communities have been investigated in natural environments (e.g. Braker et al., 2001; Castro-González et al., 2005: Cao et al., 2008). Wallenstein et al. (2006) suggested that denitrifying bacterial communities in soils are controlled by environmental conditions such as temperature and moisture conditions as proximal control factors and by environmental disturbances as distal factors. Although several researchers have already studied denitrifying bacterial community structure in wetlands, how those communities respond to environmental disturbances such as the drying and reflooding of hydrologic pulses, and their relationship with denitrification rates in wetlands remains poorly understood. Denitrification is mediated by denitrifying bacteria communities under anaerobic conditions (Zumft, 1997; Philippot and Hallin, 2005), hence, it is expected that hydrologic pulsing could affect both denitrifying bacterial community structure and the denitrification process, subsequently. In addition, hydrologic pulsing can act as a physiological stress and disturbance for microorganisms (Baldwin and Mitchell, 2000; Schimel et al., 2007; Gordon et al., 2008) possibly resulting in a decrease in quantity of denitrifying bacteria. Therefore, we investigated how the denitrification process and denitrifying bacterial community structure and quantity responded to hydrologic pulsing events in created wetlands. We also tested the relationships among denitrifying bacterial community structure, their quantity, and denitrification rates to better understand the role of microbial community structure at the ecosystem scale. Since denitrification is catalyzed by nitrite reductase (nir), which is widespread among taxonomically diverse microorganisms (Philippot, 2002), we targeted nitrite reductase (nir) S gene as a marker indicating the presence of denitrifying bacteria. We used the terminal-restricted fragment length polymorphism (T-RFLP) technique and real-time PCR (RT-PCR) to analyze the denitrifying bacterial community structure and denitrifying bacterial quantity, respectively.
were created in 1993e1994 and have had river water pumped through them continuously since then (Mitsch et al., 1998, 2005, 2008). The sampling sites in both wetlands were selected based on both a longitudinal gradient from inflow to outflow and a transverse gradient from deepwater in the middle to shallow water on the edges (Fig. 1). The sampling sites included the inflow and outflow deepwater areas along the longitudinal gradient and the deepwater (DM) and shallow water (SM) marsh sites along the transverse gradient. DM and SM sites were selected near inflow and outflow areas. The two wetlands were used as replicates and each sampling site had 2 pseudo-replicates. To investigate hydrologic pulses, we sampled denitrification rates and microbial communities during 4 different hydrologic phases of a drying and rewetting cycle in each of the two wetlands: inundated, saturated, drying and reflooding. The inundated phase in July 2008 occurred before water level drawdown commenced and was considered a control treatment. In early August 2008, surface water level decreased naturally due to low precipitation for 2 weeks; this was considered to be the saturated phase. Then, pumped water inflow from the river to the wetlands was purposefully discontinued for 7 days from August 23 to 29, 2008, and both wetland dried-up; this is the drying phase. After the week of drying, water was pumped again into the wetlands for the reflooding phase. It took only a day to flood the wetland areas to their initial water depths. The water depths for each phase are presented in Table 1. 2.2. Water and soil sampling and measurements Water temperature, pH, and DO were measured in situ using a YSI-meter. Duplicated soil and water samples from each site were collected and stored at 4 C before subsequent analysis. Soil samples for molecular analysis were preserved at 20 C. Extracted water from soil samples with double distilled water were filtered through 0.45 mm filter and used to determine dissolved organic
2. Materials and methods 2.1. Site description and experimental designs This study was conducted at the Wilma H. Schiermeier Olentangy River Wetland Research Park (ORWRP) placed at The Ohio State University in Columbus, USA (Fig. 1). Two 1-ha wetland areas
Fig. 1. Two 1-ha experimental wetland basins used in this study at the Olentangy River Wetland Research Park at the Ohio State University, Columbus, USA. Open circle, triangle, rectangle and diamond represent inflow deepwater (IN), deepwater marsh (DM), shallow water marsh (SM) and outflow deepwater (OUT), respectively. IN and OUT sampling site had four replicates while DM and SM had eight replicates in two created wetlands.
K. Song et al. / Soil Biology & Biochemistry 42 (2010) 1721e1727 Table 1 Water level (mean SE) in each hydrologic phase in the simulated pulse in the created experimental wetlands at the Olentangy River Wetland Research Park.a Surface water level (cm)
IN
Inundated Saturated Drying Reflooding
6.7 1.3 3.0 5.6
DM
0.0 0.5 0.7 0.0
5.6 0.8 8.0 5.8
SM
0.0 0.8 0.4 0.1
0.6 0.5 7.0 3.1
OUT
0.4 0.5 0.4 0.5
7.4 5.5 0.3 6.1
0.4 2.1 0.1 0.1
a IN, DM, SM and OUT represent different sampling sites: inflow area, deepwater marsh, shallow water marsh and outflow area of the two wetlands, respectively.
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The 20 ml reaction mixture contained template DNA, 2 SYBR green Supermix (Bio-Rad) and primer pair (each final conc. 12.5 mM) nirS832F (TAC CAC CCC GAG CCG CGC GT) e nirS3R (GCC GCC GTC RTG VAG GAA). The thermal cycling conditions of the RT-PCR included denaturation at 95 C for 2 min, 40 cycles of amplification at 95 C for 25 s, 65 C for 30 s and 72 C for 25 s. The PCR was performed using an I-CyclerÔ Version 3.0 a (Bio-Rad) RT-PCR assay was performed two times for each duplicated sample. 2.5. Statistical analysis
2.3. Denitrifying bacterial community structure DNA from soil sample was extracted using an UltraClean soil DNA kit (MoBio) and kept at 20 C prior to analysis. A fingerprinting analysis using terminal-restriction fragment length polymorphism (T-RFLP) was conducted to determine denitrifying bacterial community structure. The 40 ml reaction mixture contained template DNA (approximately 100 ng), PCR buffer, dNTPs (final conc. 200 mM), bovine serum albumin (8 mg), Taq polymerase (2.5 unit) (Promega, USA) and primer pair (each final conc. 12.5 mM). The florescence-labeled primer pair nirS832F (GTN AAY GTN AAR GAR CAN GG) e nirS1606R-FAM (ACR TTR AAY TTN CCN GTN GG) was used as described by Liu et al. (2003). The PCR was performed using a PTC-100 thermal cycler (MJ Research, USA). A denaturation step was at 94 C for 2 min, followed by 35 cycles at 95 C for 30 s, primer annealing at 65 C for 60 s, and extension at 72 C for 1 min and the final extension was performed at 72 C for 10 min. The PCR product was separated by electrophoresis and purified using a DNA purification kit (MoBio). Purified PCR products were then digested using the restriction enzyme HhaI (Promega) at 37 C for 6 h, followed by heat inactivation of the restriction enzyme at 65 C for 15 min. The analysis of T-RFs was performed using an ABI 3730 XL automatic sequencer (Applied Biosystems). 2.4. Quantification of denitrifying bacteria In order to quantify denitrifying bacteria in our soil samples, we used quantitative real-time PCR (RT-PCR) targeting the nirS gene.
Statistical analyses were performed using SPSS ver. 15.0. Significant differences (P < 0.05) in obtained data within treatments and sites were determined according to two-way ANOVA, followed by Tukey’s test. Stepwise linear regression was applied to determine the relationship between denitrification and chemical properties in wetlands. The denitrifying bacterial community structure and diversity were evaluated based on the number and area of terminalrestriction fragments (T-RFs) in each phase. Lengths with less than a 0.5 bp difference were considered to be the same peak. The peak area for each fragment was converted to a proportion of the total area in each community composition and represented as abundances of T-RFs. The bacteria diversity was calculated using the Shannon diversity index (Shannon, 1948). The differences in community structure between treatments were analyzed using multi-response permutation procedures (MRPP) and non-metric multidimensional scaling (NMS) in PC-ORD ver. 5.0 (McCune and Mefford, 1999). 3. Results 3.1. Responses of denitrification to hydrologic pulsing The water level drawdown and drying followed by the reflooding event in the wetlands resulted in significant changes in denitrification (Fig. 2). During the saturated period, denitrification rates decreased dramatically, except at the inflow site. In contrast, denitrification rates increased during reflooding to similar or slightly higher values than the original rates prior to the hydrologic pulsing. Interestingly, denitrification in the SM increased
800
Denitrification (µg N2O-N m-2 hr-1)
carbon (DOC) concentrations (mg g soil1) using TOC-meter (TOCV, Shimadzu). Specific UV absorbance (SUVA) was calculated using the same filtered water samples by UV absorbance at 254 nm (USEPA, 2005). Extractable nitrate contents (mg g soil1) in the sediment were analyzed by the colorimetric method (Anderson and Ingram, 1989). In situ denitrification rates in the presence of hydrologic pulsing events were measured using the acetylene blocking technique (Tiedje, 1982; Tiedje et al., 1989). PVC chambers, 4 cm in diameter and 80 cm in height (Hernandez and Mitsch, 2007), were inserted 10 cm deep into the sediment at each sampling site. Acetylene gas was injected into the chambers until 10% (v/v) of the headspace of the chamber was occupied by the gas. Then, headspace gas samples were collected every 20 min for 2 h. Accumulated nitrous oxide concentrations in the gas samples were analyzed using an electron capture detector (ECD) equipped gas chromatograph (GC-14A, Shimadzu) with a porapak-Q column. For calculating the denitrification flux, only the slope which showed a linear increase in nitrous oxide concentrations with time was selected. Two samples at the most were excluded in a 6 sample set when it was necessary to satisfy the significance of linearity in the slopes. One data point from SM in September was eliminated from subsequent data analysis when it showed an extremely high denitrification rate, which was considered as an outlier.
Site: P=0.547 Hydrology: P=0.001 Interaction: P=0.046
Inundateda Saturatedb Dryingb Refloodinga
600
400
200
0 IN
DM
SM
OUT
Fig. 2. Denitrification rates (mean SE) by hydrologic pulsing treatment in the experimental wetlands. IN, DM, SM and OUT stand for inflow area, deepwater marsh, shallow water depth marsh and outflow areas, respectively. Different letter next to the legend represents significant differences among each period at P < 0.05 based on Tukey analysis in two-way ANOVA. Also, significances of two-way ANOVA for denitrification rates in relation to different site, hydrologic pulsing, and their interaction are shown.
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significantly after reflooding, resulting in 175% higher rates than during the original inundated period (Fig. 2). The magnitude of effect on denitrification rate due to hydrologic pulsing was in the order of SM > DM > OUT > IN based on the slope of each regression (Fig. 3). A significant correlation was found between denitrification rates and water level changes (R2 ¼ 0.31, P < 104) although the individual regressions from the outflow and inflow sites were not statistically significant. Denitrification, soil DOC, SUVA, and NO 3 concentration and the nirS gene copy number for each hydrologic phase are presented in Table 2. SUVA exhibited lower values during drying and reflooding periods. Nitrate concentrations in the soil were 4.74 and 4.22 mg g soil1 in drying and reflooding periods, respectively, higher concentrations than those in the inundated and saturated periods. However, these chemical properties did not exhibit significant differences among hydrologic pulsing phases (Table 3). Although DOC also did not show significant differences among hydrologic pulsing periods, stepwise linear regression showed that denitrification rates could be explained by DOC concentration (R2 ¼ 0.15, P ¼ 0.03, Fig. 4).
3.2. Responses of denitrifying bacterial community structure and quantity to hydrologic pulsing
Table 2 Denitrification rates and chemical characteristics (mean SE) in response to hydrologic pulsing in created experimental wetlands at Olentangy River Wetland Research Park.a SUVA NO No. of gene Denitrification DOC 3 (mg N2OeN (mg g soil1) (L mg-M1) (mg g soil1) copy (1012) m2 h1) Inundated 301 32a Saturated 133 29b Drying 71 21b Reflooding 271 42a
0.49 0.29 0.40 0.35
0.05 0.03 0.02 0.05
1.50 1.46 0.93 1.01
0.14 0.21 0.11 0.11
4.16 4.02 4.61 4.28
0.28 0.25 0.41 0.21
1.49 1.60 1.67 1.02
0.11a 0.13a 0.16a 0.09b
a Different letters next to the values indicate the significant differences (P < 0.05) among different hydrologic periods by Tukey analysis in two-way ANOVA. SUVA represents specific UV absorbance of organic carbon.
NMS ordination confirmed a distinct difference of community composition depending on the presence/absence of marsh vegetation rather than the effect of hydrologic pulsing treatments (Fig. 6). The first 2 axes accounted for 54.7% and 39.3% of community differences. In addition, MRPP statistical A-values for T-RFs confirmed the significance of differences between open water and vegetated marsh areas with an A-value of above 0.21 (P < 0.05, Table 3). 4. Discussion
Denitrification (µg N2O-N m-2 hr-1)
The gene copy number exhibited significant differences among hydrologic phases as well as sites (Fig. 5). Water level drawdown and the drying period led to a slight increase in the nirS gene copy number in all sampling sites except the inflow area. Furthermore, sudden reflooding led to a decrease in nirS gene copy number in every site. Shannon diversity index was also not affected by hydrologic pulsing (Table 2). However, the diversity indices between vegetated marsh and non-vegetated areas were significantly different according to one-way ANOVA (P ¼ 0.048). The diversity indices of the marsh areas (2.42 0.07 for DM and 2.52 0.08 for SM) were higher than those of the non-vegetated areas (2.31 0.11 for IN and 2.26 0.12 for OUT). The community structure of denitrifying bacteria exhibited significant differences among sampling sites while hydrologic pulsing did not induce any significant differences of community structure among the inundated, saturated, drying and reflooding periods (Table 3).
600
IN (a= 8.4) DM* (a= 18.8) SM* (a= 33.3) OUT (a=15.2) Total* (a= 16.4)
400
Hydrologic pulses such as the one described here are expected to occur more often and with higher intensity due to climate change. A decrease of denitrification with water level drawdown has been commonly expected and reported (e.g. Groffman and Tiedje, 1988; Baldwin and Mitchell, 2000). However, increased denitrification in lowered water level in peatland was also reported (Bandibas et al., 1994; Dowrick et al., 1999) and they suggested that denitrification peaked in saturated, not water logged conditions. Previous studies about effects of hydrologic pulsing on microbial communities have been generally focused on eubacteria and fungi (Fierer et al., 2003; Gordon et al., 2008; Fenner et al., 2005). For denitrifiers, only drought effects (Kim et al., 2008) and the effects of different hydrologic regime in different locations (Bougon et al., 2009) have been assessed. Therefore, the response of denitrifiers under hydrologic pulsing is still not known. In addition, the relationship among denitrifying bacterial community, quantity and their process rates have not been considered in most previous studies, even though the altered denitrification rate could be a result of physiological response to hydrologic pulsing of denitrifying bacterial communities (Schimel and Gulldege, 1998; Schimel et al., 2007; Bougon et al., 2009). In this study, we had hypothesized that the responses of denitrification rates in wetlands to hydrologic pulsing would be induced by a shifted denitrifying bacterial community. However, we found that the denitrification process and denitrifying bacterial community responded differently to hydrologic pulsing events in wetlands, which did not match with our hypothesis.
200
Table 3 MRPP A-values of denitrifying bacterial community structure for different hydrologic and site effects in the wetlands (*P < 0.05, **P < 0.01). 0 -0.10
Hydrology -0.05
0.00
0.05
0.10
0.15
Water table level (m) Fig. 3. The responses of denitrification rates depending on surface water level changes by hydrologic pulsing in each sampling site using linear regression. Slope a (102) of each regression line is shown in the legend. An asterisk shows the significance of regression at P < 103. Averaged denitrification rates and water levels from each sampling site in the wetlands were used.
A-value
Site
Inundated
Saturated Drying Reflooding
0.001 0.042 0.013
IN
DR SR OUT
0.25* 0.31** 0.00
A-value
Saturated
Drying Reflooding
0.006 0.014
DR
SR OUT
0.00 0.21**
Drying
Reflooding
0.008
SR
OUT
0.25**
K. Song et al. / Soil Biology & Biochemistry 42 (2010) 1721e1727
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Denitrification (µg N2O-N m-2 hr-1)
500 DeN=346.7 DOC+61.2 (R2=0.147, P=0.03, n=44) 400
300
200
100
0 0.0
0.2
0.4
0.6
0.8
1.0
DOC (mg g soil-1) Fig. 4. Denitrification rates in relation to DOC concentration in the wetlands by stepwise linear regression model. Fig. 6. Non-metric multidimensional scaling (NMS) ordination of denitrifying bacterial community determined by nirS T-RFLP profile. Points with different shapes represent different hydrologic treatment samples with an averaged proportional abundance of T-RFs.
4.1. Responses of denitrification to hydrologic pulsing Denitrification decreased with drying and increased during the reflooding period. This result is consistent with previous results, which showed a major influence of hydrologic changes on denitrification rates (e.g. Groffman and Tiedje, 1988; Freeman et al., 1997; Goldberg and Gebauer, 2009). Freeman et al. (1997) also observed a nitrate release from peatland soils with a decline of N2O emission due to lowered denitrification rate over a drying period and the reversible responses when the inflow was re-initiated. In addition, the extent of the changes in denitrification rates under hydrologic pulsing was spatially different within sampling locations. For example, the highest denitrification rate during the reflooding period was exhibited in the shallow marsh site (SM) although SM sites exhibited the lowest rates during the inundated period. This result could be explained by the magnitude of water level change as well as higher microbial activity in the vegetated marshes. SM sites maintained a relatively longer drying period due to low water level; this could have led to inorganic nutrient release by aerobic decomposition. Release of nitrate in dried peatlands
Inundated
Number of Gene Copy (1011)
30
ab
Site: P=0.043 Hydrology: P=0.001 Interaction: P=0.095
Saturated a Drying a Reflooding
b
20
10
0 IN
DM
SM
OUT
Fig. 5. The patterns of nirS gene copy number (mean SE) with hydrologic pulsing events from different sampling sites in the experimental wetlands. Different letter next to the legend represents significant differences among each period at P < 0.05 based on Tukey analysis in two-way ANOVA. Also, significances of two-way ANOVA for denitrification rates in relation to different site, hydrologic pulsing, and their interaction are shown.
(Freeman et al., 1993), enhanced extracellular enzyme activities and the following large flush of inorganic nutrients after drying period in wetlands (Song et al., 2007) have been reported. Therefore, released inorganic nutrients during a long drying period could result in the drastic increase in denitrification by increasing substrate availability in the SM site. DOC also exhibited a positive correlation with denitrification, indicating that high denitrification is associated with high carbon availability. Therefore, our result suggests that denitrification is regulated by physicochemical characteristics such as substrate availability and water level in wetlands.
4.2. Responses of denitrifying bacterial community structure and quantity to hydrologic pulsing Different from the response of denitrification rate, hydrologic pulsing had no distinct influence on the community structure of denitrifying bacteria in the wetlands. One possible explanation involves the physiological characteristics of denitrifiers. Most denitrifiers are facultative, which prefer oxygen instead of nitrate as an electron acceptor (Zumft, 1997). Therefore, the changes in redox condition resulting from hydrologic pulsing might not have a significant influence on denitrifiers. Another possibility is that microbial communities, that experience repeated mild stresses, tend to be more resistant to stress than other communities that have not experienced stress (Fierer and Schimel, 2002; Griffiths et al., 2005; Schimel et al., 2007; Philippot et al., 2008). Reduced microbial mortality rate by repeated drying-reflooding events (Fierer and Schimel, 2002) and no significant changes in denitrifying bacterial community structure under drought in natural riparian ecosystems (Kim et al., 2008) have been observed. Therefore, we speculate that water stress-tolerating denitrifiers could be selected by natural succession and competition as the created wetlands have undergone natural drying and reflooding events. While hydrologic pulsing did not affect denitrifying bacterial communities, we observed large differences in denitrifying bacterial community structure in the presence/absence of vegetation. The changes in denitrifying community structures in response to their habitat conditions like temperature, DO gradient, vegetation or land use type have been reported (Avarahami et al., 2002; Rich et al., 2003; Castro-González et al., 2005). Nutrients or soil type
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appeared to have greater impacts on microbial communities (Lundquist et al., 1999; McLean and Huhta, 2000; Fierer et al., 2003; Bossio et al., 2006). Bossio et al. (2006) reported that the differences of microbial community structure between sampling sites was greater than seasonal variability within each site. Different vegetation types can also influence the denitrifying bacteria communities (Bremer et al., 2007). However, since two wetlands in this study have relatively similar vegetation communities, dominated by Typha spp. and taxonomically similar species, we could not find the effect of different vegetation type on microbial community structure. Therefore, our results, along with previous studies, support the hypothesis that microbial community structure is influenced by long-term physicochemical characteristics rather than by episodic hydrologic disturbances. We originally expected that reduction in denitrifying bacterial quantity by physiological stress under hydrological pulsing would restrict denitrification rate. In this study, nirS gene copy number slightly increased or remained constant during the drying period, and it dropped as reflooding occurred. We suggest that while facultative denitrifiers can survive in aerobic condition, reflooding caused serious osmotic stress (Schimel et al., 2007), resulting in a decline of gene copy number. This change in quantity of denitrifiers did not correspond with the response of denitrification rates under hydrologic pulsing. For example, the denitrification rate increased while denitrifying bacterial quantity decreased during reflooding period. This result was possibly because the nirS gene copy number does not represent the number of active denitrifying bacteria (Philippot and Hallin, 2005). This kind of discrepancy between microbial biomass and process rates has been reported (Pesaro et al., 2004; Gordon et al., 2008). Gordon et al. (2008) showed the decrease of microbial biomass C and N with an increase of basal respiration as a result of drying and reflooding events. Pesaro et al. (2004) also reported that while respiration rates were recovered, soil microbial biomass was not after drought. Some studies have suggested that different denitrifying bacterial community composition or their quantity would contribute to denitrification rates or N2O emissions due to their physiological differences in communities (Cavigelli and Robertson, 2000, 2001; Rich et al., 2003). However, the different responses of denitrification and denitrifying bacterial communities to hydrological pulsing events in this study imply that the community structure was not a determinant of the denitrification rates. This result supports the insurance hypothesis, suggesting a functional redundancy of biodiversity (Yachi and Loreau, 1999; Loreau et al., 2001).
4.3. Conclusions This study showed that short-term hydrologic pulsing has a major influence on denitrification rates in wetlands. This change in denitrification was not induced by the response of denitrifying bacterial community to hydrologic pulsing. Instead, DOC and water level could initially drive the changes in denitrification rates in the short-term hydrologic disturbance. While hydrologic pulsing did not induce any significant differences in denitrifying bacterial community structure, the presence and absence of vegetation did influence denitrifying bacterial community structure. Our results suggest the prevailing importance of physicochemical properties affecting denitrification rate over community composition or quantity of denitrifying bacteria. However, the abundance of denitrifying bacteria was reduced by hydrologic pulsing, particularly by the reflooding event. Therefore, repeated and severe drying-reflooding events with climate change over the long term could induce large decreases of denitrifying bacteria which could result in poorer water quality in the wetlands and adjacent rivers.
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