Limnology (2010) 11:273–279 DOI 10.1007/s10201-010-0311-7

NOTE

Response of microbial community structure to natural and accelerated hydrarch successions in the boreal wetlands in northern Hokkaido, Japan Masaru Akiyama • Satoru Shimizu Yoji Ishijima • Takeshi Naganuma

•

Received: 12 October 2009 / Accepted: 20 January 2010 / Published online: 27 February 2010 Ó The Japanese Society of Limnology 2010

Abstract We estimated the effect of invading Sasa vegetation and accelerated terrestrialization on the microbial community structure in Sarobetsu-genya wetland (SGW) and Nakanominedaira wetland (NW) (original vegetation, Sphagnum). All examined peat-pore water samples were acidic. Electrical conductivity significantly differed between SGW and NW. Nonmetric multidimensional scaling (NMDS) and analysis of similarity based on denaturing gradient gel electrophoresis (DGGE) band patterns revealed differences in the bacterial community structure between the Sasa and Sphagnum vegetations at a depth of 10 cm in NW. In contrast, the bacterial NMDS profiles at all depths differed between the 2 wetlands rather than between the 2 vegetations. The archaeal community structure significantly differed between the wetlands at depths of 30 and 50 cm. The bacterial diversity index derived from the DGGE profiles significantly differed between the wetlands at all depths. The archaeal diversity index significantly differed between the wetlands at a depth of 50 cm. Sasa invasion affected the microbial community structure in the rhizosphere, up to a depth of 10 cm; this effect differed with the terrestrialization speed. These results suggest that in peat bogs subjected to artificially M. Akiyama  S. Shimizu  Y. Ishijima Horonobe Research Institute for the Subsurface Environment, Northern Advancement Center for Science and Technology, 5-3 Sakaemachi, Horonobe-cho, Hokkaido 098-3221, Japan T. Naganuma Graduate School of Biosphere Science, Hiroshima University, 1-4-4 Kagamiyama, Higashi-Hiroshima 739-8528, Japan M. Akiyama (&) Geoscience Research Laboratory Co., Ltd., 1794 Kamiwada, Yamato, Kanagawa 242-0014, Japan e-mail: [email protected]

accelerated terrestrialization, the microbial community changes before the occurrence of the natural hydrarch ecological succession involving ground vegetation. Keywords Microbial community structure  Boreal wetland  Hydrarch succession  Terrestrialization  Denaturing gradient gel electrophoresis

Introduction Many wetlands are saturated with rainwater and groundwater inflow, and the ecological succession process observed in wetlands involves terrestrialization with the assimilation of peat and soil. On a human time scale, the terrestrialization seen in wetlands is slow. However, artificial drainage, for example, that is used for agricultural development, has accelerated the terrestrialization of wetlands worldwide (Mitsch and Gosselink 2007). In the case of both natural and accelerated terrestrialization, invading vegetation, including large plants, rather than the original vegetation introduces oxygen and organic matter into the peat layer by extending the rhizosphere (Bardgett and Shine 1999; Brune et al. 2000). Variations in the covering vegetation may greatly impact microbial activity and material cycling in peat layers beneath the vegetation. Extension of the unsaturated zone because of a decrease in the water table level directly affects microbial activity (Sundh et al. 1997; Mentzer et al. 2006). This suggests that accelerated terrestrialization has a greater impact than ecological succession from the original vegetation to the invading vegetation. However, few reports have been published on the effect of the difference in terrestrialization speeds on the interaction between the vegetation and microbial community in peat layers in wetlands.

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The study sites Sarobetsu-genya wetland (SGW) and Nakanominedaira wetland (NW) are located at 141°430 E, 45°000 N and 142°70 E, 44°590 N, respectively, in northern Hokkaido, Japan. Both wetlands are composed of peat bogs, with Sphagnum moss as the original vegetation. Acute terrestrialization of SGW has occurred because of the introduction of artificial drainage for agricultural development and has resulted in the extension of invading vegetation, especially Sasa bamboo (Fujita 1997). In contrast, extension of the Sasa bamboo community has occurred as a part of natural ecological succession in NW, which is not directly affected by artificial drainage (Tachibana et al. 1997). We compared SGW and NW, which exhibit the same vegetation succession process, in order to determine the relationship between terrestrialization speeds and microbial community. Many authors have analyzed the microbial communities in wetlands but limited their analysis to identifying specific microbial groups: methanogens (Utsumi et al. 2003; Zhang et al. 2008), sulfate-reducing prokaryotes (Loy et al. 2004; Schmalenberger et al. 2007), and denitrifiers (Cao et al. 2008). With regard to the effect of vegetation on microbial community structure, it has been found that dsrA (encoding the alpha-subunit of dissimilatory sulphite reductase) of sulfate-reducing bacteria has a site-specific distribution (Loy et al. 2004), and mcrA (encoding the alpha-subunit of methyl-coenzyme M reductase) of methanogens are more diverse in fens than in bogs (Juottonen et al. 2005). The above-mentioned studies compared microbial community structures according to the process of ecological succession of the covering vegetation and found that the succession process partly determines the functional microbial community structure. To understand the effect of terrestrialization speed, it is important to assess the entire microbial community structure. We conducted denaturing gradient gel electrophoresis (DGGE) analysis based on the prokaryote 16S rRNA gene in order to determine differences in the microbial community structure in the wetlands. DGGE analysis has been used to simultaneously assess the community structure of multiple samples of microbes, including uncultured organisms (Muyzer et al. 1993; Heuer and Smalla 1997). In this study, we estimated the similarity and diversity of the microbial community structure in the wetlands by statistically analyzing DGGE profiles (van Hannen et al. 1999; Koizumi et al. 2003). We selected this analytic method because biases in the sequence retrieval from gradient gels have recently been reported (Nikolausz et al. 2005; Zhang et al. 2005). The purpose of this study was to elucidate the effects of the vegetation succession process and accelerated terrestrialization induced by artificial drainage on the microbial community structure in peat layers of boreal wetlands.

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Limnology (2010) 11:273–279

46°N

140°E

146°E

Sarobetsu River Toikanbetsu River

A

A′

42°N

Hokkaido Island

NW

SGW 0

Japan Sea

masl 500 400 300 200 100 0

A

2

4 km

Teshio River

NW

SGW A′

Fig. 1 Location of the study sites in Sarobetsu-genya wetland (SGW) and Nakanominedaira wetland (NW) (masl meters above sea level)

Materials and methods Peat-core samples were collected from SGW and NW in northern Hokkaido, Japan (Fig. 1). SGW is a freshwater wetland that originated from the estuary of the Sarobetsu River approximately 4,000–7,000 years ago. It has an area of 27.7 km2, and a peat layer that is 200- to 500-cm thick (Ohira 1995). Annual mean temperature, annual precipitation, and maximum snow depth in SGW were 6.6°C, 851 mm, and 74 cm, respectively, according to the climate database Web site of the Japan Meteorological Agency (http://www.jma.go.jp/jma/index.html). Vegetation in the SGW sampling site consisted of the Sphagnum, Moliniopsis, and Sasa communities (Fujita 1997). In 2007, the annual water table level in SGW was ground level (GL) -11.3 cm (maximum GL ?7.2 cm, minimum GL -44.5 cm). NW covers an area of approximately 0.05 km2 and has a 60-cm-thick peat layer. This wetland is located on top of the Teshio Mountains, which are about 40 km inland from the SGW sampling site (Igarashi and Fujiwara 1984). NW experiences an annual temperature of 2.5°C, an annual precipitation of 1,483 mm, and a maximum snow depth of 297 cm (Tachibana et al. 1997). The original vegetation in NW consists of a central Sphagnum community and a peripheral Sasa community (Tachibana et al. 1997). The water table level at the NW sampling site was GL ?0.6 cm (maximum GL ?8.3 cm, minimum GL -17.0 cm) during 2001–2005. In August 2008, we obtained 50-cm-long peat-core samples from SGW and NW by using a peat sampler (Daiki Rika Kogyo Co. Ltd., Konosu, Japan). Three peat cores were collected from 2 sites each of Sasa vegetation and Sphagnum vegetation; thus, 12 peat cores were collected. Peat-pore water was collected from 5 different depths (10, 20, 30, 40, and 50 cm) and centrifuged at 15,0009g for 15 min at 4°C. This supernatant was filtered through membrane filters (pore size 0.45 lm). The pH and

Limnology (2010) 11:273–279

H 0 ¼ Rðni =N Þlnðni =N Þ D ¼ Rðni =N Þ

2

where ni is the band intensity for each band and N is the sum of intensities of bands in a lane. All recognized bands were used to calculate diversity indices.

Results and discussion In this study, we estimated the effects of invading Sasa vegetation and accelerated terrestrialization on the microbial community structure in 2 boreal wetlands located in northern Hokkaido, Japan. All examined peat-pore-water samples were acidic (Fig. 2). Their EC ranged from 4.0 to 18 mS m-1 and significantly differed between SGW and NW at all depths (Fig. 2; Table 1). At the Sasa sampling

EC (mS m-1)

pH 4.4

5.3

6.2

4.0

10

10

20

20

Depth (cm)

Depth (cm)

electrical conductivity (EC) of filtrates were measured using a pH/EC meter (DKK-TOA Corporation, Tokyo, Japan). Bulk DNA was extracted from peat-core samples (wet weight 0.15 g) collected at 3 different depths (10, 30, and 50 cm) using an UltraClean Soil DNA Isolation Kit (MO BIO Laboratories Inc., Carlsbad, CA, USA), according to the manufacturer’s protocol. The DNA was then purified using CHROMA SPINTM Columns (BD, Franklin Lakes, NJ, USA). The 16S rRNA genes of the bacterial and archaeal communities associated with the 2 types of vegetations were amplified using the primer pairs 341f-GC and 534r (Muyzer et al. 1993) and ARC344f-GC (Casamayor et al. 2000) and 519r (Øvrea˚s et al. 1997), respectively. The touchdown protocol described by Muyzer et al. (1993) was used. Polymerase chain reaction (PCR) products were analyzed using DGGE (Dcode Universal Mutation Detection System; Bio-Rad Laboratories, Hercules, CA, USA) as described by Muyzer et al. (1993). Approximately 50– 70 ng of PCR product was applied to individual lanes in the gel. The DGGE patterns were converted to a binary (01) matrix, which was subjected to nonmetric multidimensional scaling analysis (NMDS) (SPSS ver. 17, SPSS Inc., Chicago, IL, USA) to identify changes in the microbial community structure (van Hannen et al. 1999). NMDS representations were assessed using the analysis of similarities (ANOSIM; Clarke and Green 1988) function within the Primer 6 (PRIMER-E Ltd., Plymouth, UK) software package. The positions and relative signal intensities of the detected bands in each gel track were determined using the NIH image software (National Institutes of Health, Bethesda, MD, USA). The Shannon index (H0 ) and Simpson index (1/D) were used as an estimate of microbial diversity. H0 and D were calculated using the following equations:

275

30

13.0

22.0

30

40

40

50

50

Sarobetsu-genya wetland-Sasa Sarobetsu-genya wetland-Sphagnum Nakanominedaira wetland-Sasa Nakanominedaira wetland-Sphagnum

Fig. 2 Vertical profile of pH and electrical conductivity (EC) in peatpore water. Error bars indicate standard deviation

Table 1 P values obtained using two-way analysis of variance (ANOVA) and data pertaining to pH, electrical conductivity (EC), and microbial diversity Depth Factors

pH

EC

10 cm Vegetation (V) ns

ns

Microbial diversity Bacteria

Archaea

H0

1/D

H0

1/D

ns

ns

ns

ns

Wetland (W)

\0.05 \0.05

\0.01 \0.01 ns

ns

V9W

\0.05 ns

ns

ns

ns

ns

20 cm V

ns

ns

–

–

–

–

W

ns

\0.001 –

–

–

–

V9W

ns

ns

–

–

–

–

ns

ns

30 cm V

ns

ns

ns

ns

W

ns

\0.001 \0.05 \0.05 ns

ns

ns

ns

V9W 40 cm V

\0.05 \0.05

ns

ns

ns

ns

–

–

–

–

W

ns

\0.001 –

–

–

–

V9W

ns

ns

–

–

–

–

ns

ns

ns

ns

50 cm V

ns

ns

W

ns

\0.001 \0.01 \0.01 \0.01 \0.01

V9W

ns

ns

ns

ns

ns

ns

0

ns not significant, – no data, H Shannon index, 1/D Simpson index

sites, the rhizosphere for Sasa sp. was mainly observed up to a depth of 20 cm in the peat layers. At the Sphagnum sites, peat assimilation beneath the Sphagnum vegetation was observed without the rhizosphere of the Sasa sp. On the basis of this observation, we assumed that Sasa invasion directly and greatly influences the microbial community structure up to a depth of 20 cm at least. Among the 3 depths (10, 30, and 50 cm) examined in this study, the covering vegetation affected only the top 10 cm of the peat layer, i.e., up to the depth to which the rhizosphere extends (Figs. 3, 4, and 5). Further, differences between the

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Limnology (2010) 11:273–279 S-Sa

S-Sp

N-Sa

S-Sa

N-Sp

B

A

S-Sp

N-Sa

N-Sp

A

B

2

2

1

1

N-Sp

S-Sa

S-Sa

N-Sp

0

S-Sp

0

S-Sp

N-Sa

-1

-2

S-Sp

N-Sa

-1

0

1

S-Sa

S-Sp

N-Sa

D

2 N-Sa

1

N-Sp S-Sp

S-Sa

-2 -1

0

1

-2

S-Sa

E

F

Stress = 0.082; RSQ = 0.965 -2

2

N-Sp

S-Sp

N-Sa

1

0

1

2

N-Sp

F 1

N-Sp

S-Sa

N-Sp

0

0 S-Sp

N-Sa

S-Sa

N-Sa

-1

S-Sp

-2

-2

Stress = 0.129; RSQ = 0.908

Stress = 0.117; RSQ = 0.941 -2

-1

0

1

2

Fig. 3 a, c, e Denaturing gradient gel electrophoresis profiles and b, d, f nonmetric multidimensional scaling diagrams showing changes in the bacterial community structure associated with the covering vegetation at 3 peat depths. a, b 10 cm, c, d 30 cm, e, f 50 cm. S-Sa (closed circles), S-Sp (open circles), N-Sa (closed squares), and N-Sp (open squares) represent the combination of wetland (S Sarobetsugenya wetland, N Nakanominedaira wetland) and vegetation sampled (Sa Sasa sp., Sp Sphagnum sp.). RSQ square of correlation coefficient

2 wetlands in terms of microbial community structure and microbial diversity were emphasized at deeper layers (Tables 1, 2). In NW, at a depth of 10 cm, we observed obvious differences in the bacterial community structure associated with the 2 types of vegetations (Fig. 3; Table 2); the bacterial diversity pertaining to the Sasa vegetation was significantly greater than that pertaining to the Sphagnum vegetation (t test, P \ 0.05). In contrast, the bacterial community structure and diversity in SGW did not significantly differ between the 2 types of vegetations (Figs. 3, 5; Tables 1, 2). The archaeal community structure and diversity at a depth of 10 cm did not significantly differ between the 2 types of vegetations or the 2 wetlands (Tables 1 and 2). These results indicate that at a depth of 10 cm, the effect of invasion by Sasa vegetation reflects differences in the wetlands, such as terrestrialization speed and water-table fluctuation. At depths of 30 and 50 cm, the

123

-1

2

2

-1

S-Sa

N-Sa

-1

Stress = 0.101; RSQ = 0.956 -2

N-Sa

2

0

-1

S-Sp

1

S-Sp

0

S-Sa

0

2

1

N-Sp

E

-1

N-Sp

C

D

Stress = 0.153; RSQ = 0.871 -2

2

N-Sp

C

N-Sa

-2

Stress = 0.095; RSQ = 0.960 -2

S-Sa

-1

-2

-1

0

1

2

Fig. 4 a, c, e Denaturing gradient gel electrophoresis profiles and b, d, f nonmetric multidimensional scaling diagrams showing changes in the archaeal community structure associated with the covering vegetation at 3 peat depths. a, b 10 cm, c, d 30 cm, e, f 50 cm. S-Sa (closed circles), S-Sp (open circles), N-Sa (closed squares), and N-Sp (open squares) represent the combination of wetland (S Sarobetsugenya wetland, N Nakanominedaira wetland) and vegetation sampled (Sa Sasa sp., Sp Sphagnum sp.). RSQ square of correlation coefficient

NMDS profiles of the wetlands clearly differed, and the effect of vegetation was not observed (Figs. 3, 4; Table 2). Bacterial diversity also significantly differed between the wetlands at depths of 30 and 50 cm and archaeal diversity at 50 cm (Fig. 5; Table 1). The reason for the differences in the effects of Sasa invasion on the bacterial community structure between SGW and NW remains to be elucidated. Change in the vegetation, especially from Sphagnum mosses to larger and taller plants, increases the supply of oxygen and organic matter to the soil (Brune et al. 2000). Immediately after the oxygen and organic matter in the peat layers are consumed, reduction reactions mediated by anaerobic microbes ensue (Reddy and DeLaune 2008). Further, the quantity and quality of the substances involved in these reactions may determine the speed of microbial decomposition and the microbial community structure (Gutknecht et al. 2006; Kulichevskaya et al. 2007). Zak et al. (2003) proposed that

Limnology (2010) 11:273–279

A

277

Bacterial diversities

Shannon (H′) 2.0

3.5

Simpson (1/D) 5.0

0

Depth (cm)

Depth (cm)

30

30

30

50

50

Archaeal diversities

Shannon (H′) 2.0

3.5

Simpson (1/D) 5.0

0

10

20

30

10

Depth (cm)

10

Depth (cm)

20

10

10

B

10

30

50

30

50 Sarobetsu-genya wetland-Sasa Sarobetsu-genya wetland-Sphagnum Nakanominedaira wetland-Sasa Nakanominedaira wetland-Sphagnum

Fig. 5 Vertical profiles of a bacterial and b archaeal diversity in peat layers. Diversities are represented by Shannon index (H0 ) and Simpson index (1/D). Error bars standard deviation Table 2 Results of one-way analysis of similarities (ANOSIM) and pairwise tests between sites of bacterial and archaeal communities associated with wetland and vegetation for each of the 3 depths investigated

Depths

10 cm

30 cm

All possible 462 permutations were run for each vegetation and each wetland. As only 10 permutations were possible for the pairwise tests between sites, the test has a minimum probability of P = 0.100 S Sarobetsu-genya wetland, N Nakanominedaira wetland, Sa Sasa sp., Sp Sphagnum sp.

50 cm

Factors and sites

Vegetations (V) Wetlands (W) S-Sa versus S-Sp S-Sa versus N-Sa S-Sa versus N-Sp S-Sp versus N-Sa S-Sp versus N-Sp N-Sa versus N-Sp V W S-Sa versus S-Sp S-Sa versus N-Sa S-Sa versus N-Sp S-Sp versus N-Sa S-Sp versus N-Sp N-Sa versus N-Sp V W S-Sa versus S-Sp S-Sa versus N-Sa S-Sa versus N-Sp S-Sp versus N-Sa S-Sp versus N-Sp N-Sa versus N-Sp

a feedback process exists between vegetation and microbial community: vegetation diversity results in microbial diversity, which in turn increases the inorganic nitrogen content of the soil. Some studies have reported that changes in vegetation affect the microbial community structure of the soil because of the associated changes in the amount of carbon substrates and soil properties (Balasooriya et al. 2007; Nu¨sslein and Tiedje 1999). The changes observed in the bacterial community structure and diversity at a depth of 10 cm imply that natural ecological succession, such as that observed in NW, is very sensitive to the vegetation process. Similar changes were not observed in the bacterial community structure and diversity at a depth of 10 cm in SGW. Vegetation diversity does not affect microbial diversity under specific soil conditions, e.g., high total organic carbon content in the soil (Felske et al. 2000; Wardle et al. 1999) and artificial wetlands containing sewage (Baptista et al. 2008). These findings indicate that the effect of the vegetation process can be nullified by the introduction of large amounts of organic matter and increase in the efficiency of nitrogen utilization. Although the EC data obtained cannot explain the oligotrophic characteristics of the wetlands, the fact that the EC in SGW was significantly higher than that in NW (Table 1) and that the EC in the top 10-cm peat layer was significantly higher Bacteria

Archaea

Global R

Significance (P)

Global R

Significance (P)

0.053 0.781 0.130 0.667 1.000 0.648 1.000 0.667 -0.177 0.823 -0.074 0.593 1.000 0.519 1.000 -0.037 -0.031 0.851 -0.259 1.000 0.704 1.000 0.704 0.370

0.225 0.002 0.400 0.100 0.100 0.100 0.100 0.100 0.989 0.002 0.600 0.100 0.100 0.200 0.100 0.600 0.539 0.002 0.900 0.100 0.100 0.100 0.100 0.200

0.006 0.273 0.148 0.056 0.389 0.333 0.463 0.241 -0.016 0.967 0.407 1.000 0.926 1.000 0.963 0.148 -0.106 0.955 0.481 1.000 1.000 1.000 1.000 0.278

0.422 0.006 0.200 0.600 0.100 0.100 0.100 0.100 0.448 0.002 0.200 0.100 0.100 0.100 0.100 0.400 0.799 0.002 0.100 0.100 0.100 0.100 0.100 0.200

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than that in the deeper layers (t test, P \ 0.05) suggests that nutrients in the former layer were soluble. Fluctuations in the water table level could trigger and accelerate the feedback process described by Zak et al. (2003) because the hydrarch ecological succession process includes terrestrialization and because the oxidation– reduction potential is an important factor influencing the microbial community in peat layers. The water-table fluctuations in SGW were larger than those in NW, which may also alter the microbial community structure (Boon et al. 1996; Mentzer et al. 2006; Sundh et al. 1997). Further, this difference, which reflects the characteristics of each wetland, such as terrestrialization speed and water-table fluctuation, may not have been related to the NMDS profiles of the vegetation at depths below the rhizosphere (Figs. 3, 4; Table 2). In addition, it might indicate that the microbial community structure of SGW is at a more advanced stage of the succession process than the microbial community structure of NW, rather than the lack of any effect of Sasa invasion.

Conclusion In this study, we estimated the effect of Sasa invasion, as secondary vegetation, and accelerated terrestrialization on the bacterial and archaeal community structure in 2 boreal wetlands in northern Hokkaido, Japan. The impact of Sasa invasion on the microbial community structure was observed in the rhizosphere in NW, in which natural ecological succession has been noted. The microbial community structure in the soil below the rhizosphere exhibited the original characteristics observed before Sasa invasion rather than those after Sasa invasion. These results suggest that artificially accelerated terrestrialization affects the microbial community structure in peat layers before it affects the natural hydrarch ecological succession process involving the ground vegetation. Acknowledgments We are grateful to Mutsumi Nomura, Kentaro Takagi, and Hajime Hojo of the Teshio Experimental Forest of Hokkaido University for their cooperation during fieldwork and for providing useful information regarding the study sites. This work was supported by the Ministry of Economy, Trade and Industry (METI) of Japan.

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