Soil bacterial communities in native and regenerated perhumid montane forests

Soil bacterial communities in native and regenerated perhumid montane forests

Applied Soil Ecology 47 (2011) 111–118 Contents lists available at ScienceDirect Applied Soil Ecology journal homepage: www.elsevier.com/locate/apso...

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Applied Soil Ecology 47 (2011) 111–118

Contents lists available at ScienceDirect

Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil

Soil bacterial communities in native and regenerated perhumid montane forests Yu-Te Lin a , Kamlesh Jangid b , William B. Whitman b , David C. Coleman c , Chih-Yu Chiu a,∗ a

Biodiversity Research Center, Academia Sinica, Nankang, Taipei 11529, Taiwan Department of Microbiology, University of Georgia, Athens, GA 30602-2605, USA c Odum School of Ecology, University of Georgia, Athens, GA 30602-2602, USA b

a r t i c l e

i n f o

Article history: Received 23 June 2010 Received in revised form 9 November 2010 Accepted 10 November 2010 Keywords: Bacterial community Forest management Forest soil 16S rRNA genes

a b s t r a c t Forest management often results in changes in soil properties and microbial communities. In the present study, we characterized differences in soil bacterial communities caused by forest management practices using 16S ribosomal RNA (rRNA) gene clone libraries. The communities were from a disturbed Chamaecyparis (DCP) forest subjected to harvesting of snags and downed logs, a secondary Chamaecyparis (SCP) plantation subjected to harvesting of old-growth trees, and a secondary cedar plantation (SCD). These forests were compared to a nearby native Chamaecyparis (NCP) forest in a perhumid montane ecosystem. At this locality, the elevation is from 1500 to 2100 m a.s.l., the mean annual precipitation >4000 mm, the mean annual temperature about 12 ◦ C, and the soil pH <4. The phyla Acidobacteria and Proteobacteria predominated among the three disturbed forest soil communities. Several diversity indices and rarefaction curves revealed that the diversity of the SCD community was higher than that of the DCP soils. The diversity of the SCP community was intermediate. The bacterial diversity of the NCP community was lower than communities in the three disturbed forest soils. Analysis of molecular variance revealed that the bacterial community in SCD soils significantly differed from those in the three Chamaecyparis forest soils. Some of the abundant operational taxonomic units (OTUs) significantly differed among the four forest soils. Compared to the three disturbed forest soil communities, the NCP community was dominated by Proteobacteria, which accounted for more than half of the community. These results suggest that the disturbance of forest harvesting and tree species conversion influence the composition of bacterial communities in natural and disturbed forests and increase the diversity of the disturbed forest soil community. © 2010 Elsevier B.V. All rights reserved.

1. Introduction Tree harvesting and planting result in forest soil disturbance. Such disturbances could alter several characteristics of soil quality, including soil organic matter content, and result in quantitative and qualitative changes in soil carbon and nitrogen pools, as well as soil biological properties (Chen et al., 2004; Burton et al., 2007; Chatterjee et al., 2008). The effects of such disturbance on soil microbial community structure, diversity, and biomass have received some attention (Hannam et al., 2006; Curlevski et al., 2010). However, most of the investigations were conducted in temperate forest ecosystems; little information exists regarding the effects of forest conversion and harvesting on microbial communities in tropical and subtropical soils. Here, we investigated soil bacterial communities from forests subjected to harvesting and adjacent conifer plantations in a perhumid montane, subtropical ecosystem.

∗ Corresponding author. Tel.: +886 2 2787 1068. E-mail address: [email protected] (C.-Y. Chiu). 0929-1393/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.apsoil.2010.11.008

We examined the diversity and composition of the indigenous soil bacterial communities in disturbed forests located near the Yuanyang Lake (YYL) forest ecosystem in Taiwan. YYL is located in the northeastern region of Taiwan. The site is a subtropical mountainous cloud forest and experiences heavy cloud and frequent fog. This locality is temperate, very wet, and has high soil acidity. It is an uncommon ecosystem for a monsoonal part of Southeast Asia and consists of forest dominated by Chamaecyparis tree species. Because of their valuable wood, these trees have long been a major harvested timber species. Our previous study conducted in the native reserve region indicated that the diversity of the soil bacterial community was lower than that in other temperate and tropical forests. Proteobacteria, Acidobacteria and Actinobacteria predominate in the community (Lin et al., 2010). However, the microbial community in the disturbed forest soils adjacent to the YYL natural forest is still unknown. Considering the disturbances inherent in establishing and harvesting plantations, we assumed that the composition and diversity of the soil bacterial communities in these forests would differ even though they are in the same climate and soil type. From analysis of 16S ribosomal RNA (rRNA) clone libraries, we elucidated the effects of timbering on the soil bacterial commu-

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Table 1 Soil chemical and physical properties of study sites. Study site

Elevation (m)

pH

Organic C (g kg−1 )

Total N (g kg−1 )

C:N

SCDa SCPb DCP NCP

1600 1600 1500 1950

3.7 3.6 3.7 3.5

145 475 432 483

8.5 18.9 22.7 22.5

17.0 25.1 19.0 21.5

a Data of SCD and NCP were from Imberger and Chiu (2002). Values of the NCP site were the average of the data of summit and foot slope sites. b Data of SCP and DCP were from Kang (2008).

nities among two disturbed Chamaecyparis forests and a conifer plantation. In the present study, we re-analyzed data from a previous study (Lin et al., 2010), including sequences from foot slope (YYFS) and summit (YYSM) soils in natural Chamaecyparis forests at YYL, in conjunction with new data. This study helps unravel the impact of forest harvesting and conversion on the soil bacterial communities in this ecosystem. 2. Materials and methods 2.1. Study sites and soil sampling This study was conducted in three disturbed forests located near a natural Chamaecyparis (NCP) forest dominated by Taiwan false cypress (Chamaecyparis formosensis) in the YYL ecosystem (24◦ 35 N, 121◦ 24 E). The elevation was 1500–1600 m a.s.l., the mean annual precipitation >4000 mm, and the average annual temperature approximately 12 ◦ C. Two disturbed Chamaecyparis forests included a secondary Chamaecyparis (SCP) forest subjected to harvesting of old-growth trees about 50 years ago and a disturbed, old growth Chamaecyparis (DCP) forest, which had undergone harvesting of dead and fallen trees about 15 years ago. Timber of Chamaecyparis is rich with essence oil, which enables the wood to resist decay for decades even after the trees have fallen by occasional strong typhoons. Large numbers of fallen trees remained intact on the floor of the native Chamaecyparis forest. Collecting fallen trees is considered an alternative way to harvest these valuable trees and minimize disturbance to the forest. The third forest was replanted about 30 years ago with a pure stand of Japanese cedar (Cryptomeria japonica) (SCD). Considering the impact of human activities in these forests, SCD was subjected to the heaviest disturbance, then the SCP and DCP forests. The soils in the three sampling sites were Inceptisol (Drystrochrept) (Imberger and Chiu, 2002). The soils were strongly acidic, with pH values of the surface soils ranging from 3.6 to 3.7. Other characteristics of soil sites are in Table 1. Soil samples were collected in SCD, SCP and DCP forests. For each of the three sites, four replicates were collected from four 50 m × 50 m plots. Soil samples 8 cm in diameter and 10 cm deep were collected with use of a soil auger. Four subsamples collected in each plot were combined. Visible detrital material, such as roots and litter, were manually removed before material was passed through a 2-mm sieve. Soils were then stored at −20 ◦ C for a few days before DNA extraction. 2.2. 16S rRNA gene clone library construction The construction of 16S rRNA clone libraries was as described previously (Lin et al., 2010). In brief, soil community DNA was extracted by use of the PowerSoilTM DNA Isolation kit (MoBio Industries) in accordance with the manufacturer’s instructions. The bacterial 16S rRNA genes were amplified by PCR with the primer set 27F and 1492R (Lane, 1991). The PCR products were cloned by

use of the TOPO TA cloning kit (Invitrogen) and the pCR2.1 vector. White colonies on selective Luria-Bertani (LB) agar plates were placed into 96-well blocks containing 1 ml LB broth plus kanamycin (50 ␮g ml−1 ) and grown overnight. Sterile glycerol was added to a final concentration of 10%, and an aliquot of this was transferred to a 96-well sequencing block. Both the sequencing and original culture blocks were stored at −80 ◦ C. 2.3. DNA sequencing and taxonomic assessment Bacterial clones were partially sequenced with the primer 27F. Sequence analysis involved use of an ABI PRISM Big Dye Terminator cycle sequencing ready reaction kit (Applied Biosystems) and an ABI 3730 Genetic Analyzer (Applied Biosystems) following the manufacturer’s instructions. Sequences were analyzed by use of the Mallard (Ashelford et al., 2006) and Pintail programs (Ashelford et al., 2005) to test for chimeras. The sequences were taxonomically identified by use of the naive Bayesian rRNA classifier (Wang et al., 2007) in the Ribosomal Database Project (http://rdp.cme.msu.edu/index.jsp). Sequences were named as follows. For instance, the sequence SCD101 comprised a six-character code that signified the source of forest soils (SCD, SCP or DCP), the sample replicate in the first number (1 in this case), and a two-digit unique indicator of the sequence (01 in this case). 2.4. Phylogenetic dendrogram construction The obtained clone sequences were submitted to the GenBank database under the accession numbers HQ264404–HQ265229. The NCP bacterial community was described previously (Lin et al., 2010) and was included for comparison purposes. The sequences were screened against those in the NCBI GenBank database by use of the BLAST program. Phylogenetic relationships were analyzed as described (Lin et al., 2010). Phylogenetic trees were constructed by the neighbor-joining method (Saitou and Nei, 1987) with PHYLIP v3.6 (Felsenstein, 2005). Bootstrap values (Felsenstein, 1985) were created with 100 replicates. 2.5. Diversity estimates and library comparison Distance matrices calculated by use of DNADIST in PHYLIP were used as the input file for the program DOTUR (Schloss and Handelsman, 2005). Rarefaction analyses, richness, evenness, Shannon diversity index (H) and Chao1 estimates were calculated for operational taxonomic units (OTUs) with an evolutionary distance (D) of 0.03 (or about 97% 16S rRNA gene sequence similarity). To analyze the distribution of abundant taxa within libraries, groups were constructed by use of DOTUR at a distance of ≤0.03. These groups were then analyzed by the Fisher exact test (Agresti, 1992). UniFrac (Lozupone et al., 2006) analysis was used to compare the clone libraries based on the phylogenetic information. The UniFrac Significance test option with 100 permutations was used to test the significant difference of each pair of samples. The Jackknife Environment Clusters were used with the weighted algorithm (which considers relative abundance of OTUs) and the normalization step. A hierarchy of log-linear models was used to examine differences in the taxonomic composition among rRNA gene libraries (Jangid et al., 2008). The models sought to explain phylotype occurrence as a function of treatment and were run separately with use of the GENMOD procedure in SAS (SAS Inst., Cary, NC). The response variable (i.e., separate counts for each phylotype from replicate libraries) was assumed to approximate a Poisson distribution. The null model assumed that the distribution of all phylotypes across all experimental conditions was the same, subject to sta-

Y.-T. Lin et al. / Applied Soil Ecology 47 (2011) 111–118 Table 2 Phylotypes of clones in 16S rRNA gene libraries. Phylogenetic group

Clone library (% of clones)a SCD

Acidobacteria Actinobacteria Bacteroidetes Chloroflexi Firmicutes Gemmatimonadetes Nitrospira Planctomycetes Proteobacteria ␣-Proteobacteria ␤-Proteobacteria ␥-Proteobacteria ␦-Proteobacteria Unclassified Proteobacteria Verrucomicrobia Unclassified bacteria Total clone numbers

SCP

47.5 35.8 3.5a 8.4b 3.5 4.0 1.2 4.7 2.7 0.7 2.3 0.7 0.4 0.0 3.9 6.0 29.0 31.4 17.4 14.6 3.9a 4.7a 3.9 6.6 3.5ab 5.5a 0.4 0.0 0.4 2.2 5.8 5.8 259 274

Total b

DCP

NCP

36.9 8.2b 0.7 4.4 0.7 0.3 0.0 3.4 36.2 18.8 4.8a 6.5 6.1a 0.0 2.4 6.8 293

19.1 15.5b 0.6 0.0 0.3 0.3 0.0 4.9 55.0 11.2 35.9b 7.3 0.6b 0.0 1.5 2.7 329

33.9 9.3 2.1 2.5 1.0 0.9 0.1 4.6 38.8 15.3 13.4 6.1 3.8 0.1 1.6 5.2 1155

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in SCP and DCP soils was similar to that in SCD soils, it was not significantly different from that in NCP soils at p = 0.01. The mean abundance of Acidobacteria and ␣-Proteobacteria varied two-fold within the soils, but these differences were not significantly different because of the high variation among the replicate samples (Table 2). Thus, despite the similar abundance of phylotypes in all soils, most differences were observed between the native NCP and the most heavily disturbed soil. In the Acidobacteria, clones were further classified into subdivisions 1, 2, 3, 4, 5, 6, 13 and 14 (Fig. 1) according to previous studies (Hugenholtz et al., 1998; Barns et al., 2007). Most of the sequences (82%) were in subdivisions 1 and 2. Within the ␣-Proteobacteria, an abundant OTU with 22 sequences was related to Bradyrhizobium spp. (Fig. 2). Other bacterial taxa closely related to the soil clones included Acetobacteraceae, Caulobacteraceae and Rhodospirillales spp. (Fig. 2). About 10% of clones were affiliated with an unclassified ␣-proteobacterial group. 3.2. Diversity of soil bacterial communities

a

Phylotypes with the same letter in each row indicates no significant difference in abundance according to the GENMOD procedure at p < 0.01. b Data from Lin et al. (2010).

tistical variability. Model selection and calculation and correction for overdispersion were described previously (Jangid et al., 2008). Because the number of replicates for the NCP site was larger than that for the other sites, six versus four, the analysis was repeated three times with random selections of four of the six NCP replicates. All analyses yielded similar conclusions. 3. Results 3.1. Phylogenetic groups represented in the clone libraries About 40–130 clones of 16S rRNA genes were sequenced from each replicate sample collected from the three disturbed forest soils. Each site was represented by four replicate samples, and the sequences from replicates of each site were then combined for further analyses. We obtained 259 clones for the SCD site, 274 for SCP and 293 for DCP (Table 2). No chimeric sequences were detected, and all the resulting sequences were used for further analysis. All clones were classified into 12 phylogenetic groups (Table 2). In three study sites, the most abundant groups were Acidobacteria and Proteobacteria, comprising about 70% of all clones. Actinobacteria was the third most abundant group. The remaining phyla present within the libraries, such as Planctomycetes and Chloroflexi, all comprised less than 5% of the clones. In addition, about 6% of clones from three disturbed forest soils were only distantly related to cultured bacteria and were designated as the unclassified bacterial group. These clones included a representative of the deeply branching but so far uncultured groups, Genera incertae sedis OP10. In the library from NCP soils, the most abundant groups were Proteobacteria, Acidobacteria and Actinobacteria, which accounted for about 90% of total clones (Table 2). Despite the similarity of the relative abundance of clones affiliated with various bacterial groups in all the soils, some phylotypes showed differences detected by the hierarchy of log-linear models. The abundance of ␤-Proteobacteria was significantly higher in the NCP than other soils (Table 2). In contrast, the abundance of the unclassified group was significantly lower in the NCP than in other soils. The abundance of ␦-Proteobacteria was also significantly lower in the NCP than SCP and DCP soils. Although the abundance of this phylotype in SCD soils was similar to that in SCP and DCP soils, it was not significantly different from that in NCP soils at p = 0.01. Similarly, the abundance of Actinobacteria was significantly lower in SCD than NCP soils. Although the abundance of Actinobacteria

For calculation of diversity indices, OTUs were formed at D ≤ 0.03 (about 97% sequence similarity). From the richness and Chao1 estimator, the diversity of the bacterial community was higher in SCD soils than in SCP and DCP soils (Table 3). This conclusion was supported by rarefaction curve analysis. The failure of the rarefaction curves to plateau indicated that these communities were incompletely sampled (Fig. 3). Nevertheless, the slopes of curves for SCP and DCP soil communities were less steep than that for SCD soils, which suggests that the diversity was higher in SCD soils (Fig. 3). The curves also revealed that the community was more diverse in SCP than DCP soils, which is similar to the richness and Chao1 estimator results. To gain further insight into the relative diversity of these communities, the Chao1 estimator was calculated at different sample sizes (Kemp and Aller, 2004). Because the estimators approached a stable plateau with increasing sample size (data not shown), they appeared to be reliable indicators of diversity. Analysis of the sizes of abundant OTUs provided a rationale for the high diversity of the SCD soil community. In the SCP and DCP soils, 28% and 19% of the clones, respectively, were in single-member OTUs or singletons. For the SCD soils, 38% of the clones were in singletons. In SCP and DCP soils, 22% and 25% of the clones were members of abundant OTUs (see below). In SCD soils, the abundant OTUs accounted for 20% (Table 4). In addition, from the richness, Chao1 estimator and rarefaction curve analysis, the three disturbed forest soil communities were all more diverse than the NCP community (Table 3; Fig. 3). 3.3. Abundant OTUs in soil bacterial communities Analyses of composition differences of communities also revealed the distinctness of the SCD and Chamaecyparis forest soils. UniFrac Significance analyses were used to compare the bacterial communities on the basis of the phylogenetic information. The p-values revealed that the SCD community was significantly different from the Chamaecyparis forest soil communities (Table 5). After removing the most abundant ␤-proteobacterial OTUs, the four soil communities were not significantly different (data not shown). Thus, the differences among the ocommunities might result largely from the abundance of ␤-Proteobacteria. In the cluster analyses of the clone libraries, the SCD community was well separated from the cluster formed by the SCP, DCP and NCP communities (Fig. 4). Some of the differences in composition were identified by examination of the abundant OTUs or those with sizes larger than 10, which represented about 31% of all clones (Table 4). Because representatives of each OTU were obtained from independent replicates in multiple sampling locations and the representation was similar

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Fig. 1. Phylogeny of representative Acidobacteria clones for each OTU. OTUs were formed at evolutionary distances ≤0.03. Clones derived in this study are given in boldface. Subdivisions are indicated by brackets. The number of sequences for each OTU is in parentheses following the clone name and GenBank accession number. The names of the sequences comprise a six- to seven-character code that signifies the source from three disturbed forests (two Chamaecyparis forests, SCP and DCP, and one cedar plantation, SCD), and other numbers as described in the Methods. Numbers at nodes denote bootstrap confidence values obtained with 100 resamplings; values ≤70 are not shown. The scale bar indicates 0.1 substitutions per nucleotide position.

Y.-T. Lin et al. / Applied Soil Ecology 47 (2011) 111–118

115

Fig. 2. Phylogeny of representative ␣-Proteobacteria clones. Notation is as described for Fig. 1.

in the different sample replicates (data not shown), their abundance was not due to PCR or cloning artifacts or to a single unusual sample. The most abundant OTU was from the Proteobacteria and related to the genus Burkholderia. It was mainly present in the

NCP community. The distribution of the abundant acidobacterial OTUs, such as DCP110, SCP119 and SCD164, was significantly different among the four soil communities by the Fisher exact test (Table 4). As compared with disturbed forest soil communities, in

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Table 3 Diversity indices for the soil bacterial communities as represented in the 16S rRNA gene librariesa . Index

SCD

SCP

NCPb

DCP

SCD

c

S 148 147 125 95 259 274 293 329 Nd 0.98 0.98 0.98 0.97 Evennesse 0.38 0.28 0.18 0.14 Richnessf 0.98 0.98 0.98 0.97 Shannong Chao 1 338 (257, 480)h 215 (185, 268) 166 (146, 205) 165 (128, 244) a

Calculations were based on OTUs formed at an evolutionary distance of <0.03 (or about 97% similarity). b Values were calculated from Lin et al. (2010). c S defined as the number of OTUs observed. d N defined as the number of sequences. e Evenness defined as H/log S. The observed/maximum possible value is reported. f Richness = (number of singleton OTUs − 1)/log N. The maximum value is (N − 1)/log N. The observed/maximum possible value is reported. g Shannon diversity index (H). The observed/maximum possible value is reported. h Confidence intervals (95%) for the Chao1 estimator are shown in parenthesis.

Number of OTUs Observed

180

120

60

0

0

70

140

210

280

350

Number of Sequences Sampled Fig. 3. Rarefaction curve analysis for secondary cedar plantation (), secondary Chamaecyparis (), disturbed Chamaecyparis (), and native Chamaecyparis () forest soil libraries. OTUs were defined as sequences sharing 97% nucleotide sequence similarity. Values of NCP were calculated from data in Lin et al. (2010). Table 4 Distribution of the most abundant OTUs in 16S rRNA gene clone libraries.a Clone nameb

YYSM113* DCP110* SCD160 SCP431 SCD306 SCD136* SCP135 SCP117 YYSM560* SCP243 SCP275 SCD164* DCP138 DCP340* SCD253* SCP127* DCP118 SCD368*

Taxonomic affiliation

Burkholderia (AJ292637) Acidobacteria (FJ466150) Acidobacterium (FJ625367) Bradyrhizobium (FJ418920) Acidobacteria (FJ624909) Rhodoplanes (FJ475449) Acidobacteria (EU680446) Acidobacterium (FJ466282) Burkholderia (GU472987) Steroidobacter (AY963328) Acidobacteria (EU680344) Acidobacteria (EU445202) Actinomadura (EF220691) Mycobacterium (EU138967) Acidobacterium (FJ625317) Caulobacter (FJ936950) Actinomadura (FJ669088) Acidobacteria (FJ466178)

Table 5 Statistical significance (p-values) of differences among the forest soil bacterial communities.

Nc

Clone library d

SCD

SCP

DCP

NCP

3b 5c 10 3 7 5ab 5 2 0b 1 1 5a 0 0b 2ab 0b 0 4a

4b 4c 3 7 7 1b 6 6 0b 6 5 2ab 2 1b 0b 2ab 1 3ab

0b 16a 5 7 2 5ab 6 5 0b 5 4 5a 5 2ab 0b 0b 4 3ab

90a 0b 4 5 5 8a 1 5 16a 3 2 0b 5 9a 9a 9a 5 0b

97 25 22 22 21 19 18 18 16 15 12 12 12 12 11 11 10 10

OTUs formed at an evolutionary distance ≤0.03 (or about >97% similarity). Data with the same letter in each row indicates no significant difference according to LSD-test at p < 0.05. b Representative clone for each OTU. OTUs with nonrandom distribution are marked by an asterisk. c Total number of clones in an OTU. d Data were calculated from Lin et al. (2010).

SCD SCP DCP NCP



SCP b

<0.001 –

DCP

NCPa

<0.001 0.43 –

<0.001 0.21 0.04 –

a

Values were calculated from Lin et al. (2010). p-Values of UniFrac significance test were based on 100 permutations. Bold values indicate significant difference at p < 0.05. b

NCP soils, some abundant OTUs, such as ␤-, ␣-proteobacterial and actinobacterial-affiliated OTUs, were absent or in low proportions in the three disturbed forest soils (Table 4). 4. Discussion Our results reveal that the bacterial diversity varied with different degrees of disturbance in three forest ecosystems in the YYL region in Taiwan. The community in SCD soils with the heaviest disturbance was the most diverse, then those in SCP and DCP soils. Moreover, the community composition of disturbed forest soils differed greatly from that in natural forest soils in this region. Proteobacteria accounted for more than half of the total clones, and ␤-Proteobacteria was the most dominant group in NCP soils; in contrast, ␣-Proteobacteria was the most abundant group in the three disturbed forest soils. Differences in soil bacterial communities have been detected when comparing undisturbed forests and pastures established from cleared forest land (Nüsslein and Tiedje, 1999). Proportional differences in ␥-Proteobacterialaffiliated clones were also found between forests with whole-tree harvesting without soil compaction and those with harvesting plus complete surface organic matter removal with heavy soil compaction (Axelrood et al., 2002). The harvesting and replantation in these three disturbed forests caused the loss of shading overstory, and the exposure to sunlight might lead to soil temperature fluctuation and water loss. Increased availability in NH4 + has been reported for clear-cut treatments (Smith et al., 2008). Differences in nitrogen input could affect organic matter decomposition and thus result in microbial community and/or decomposing-enzyme shifts (Janssens et al., 2010). Soil C-to-N ratio and the response of trees to this ratio all influence soil microbial community composition (Högberg et al., 2007). Forest management could also influence several environmental factors simultaneously. Thus, discriminating the effects of an individual factor on the community is difficult. In this study, the soil bacterial communities in the three disturbed forests were all more diverse than that in natural forest soils. The disturbed forests experienced more management than the NCP forest, which is a natural reserve with limited anthropogenic disturbance. Previous studies conducted in Georgia, USA, also showed that bacterial communities in frequently tilled cultural soils were

SCD NCP 100

DCP 100

a

SCP 0.1

Fig. 4. A dendrogram from UniFrac Jackknife Environment Clusters analysis of 16S rRNA gene clone libraries. Analysis involved weighted data. Numbers at nodes indicate the frequency with which nodes were supported by jackknife analysis.

Y.-T. Lin et al. / Applied Soil Ecology 47 (2011) 111–118

more diverse than in less disturbed forest soils (Jangid et al., 2008; Upchurch et al., 2008). The higher diversity in these more disturbed soil bacterial communities also supported this conclusion. Besides the effect on diversity, the disturbance of tree conversion (Lauber et al., 2008; Curlevski et al., 2010) in SCD soils could have influenced the soil bacterial community. Molecular surveys have found Acidobacteria in a wide variety of environments (Barns et al., 1999; Zimmermann et al., 2005; Janssen, 2006). In this study, Acidobacteria was also the dominant phylum in the community. However, these clones are not closely related to known species of this phylum, Acidobacterium capsulatum (Kishimoto et al., 1991), Geothrix fermentans (Coates et al., 1999) and Holophaga foetida (Liesack et al., 1994). Hence, predicting function from their properties is not possible. The Acidobacteria might also be metabolically active as well as numerically dominant in soils (Lee et al., 2008). The functional diversity of Acidobacteria is important to examine further to elucidate their ecological roles. In addition, Acidobacteria are considered oligotrophs, so they can maintain viability in nutrient-limited environments (Fierer et al., 2007). Hence, the abundance of Acidobacteria might indicate the limited availability of nutrients or oligotrophic nature of the three disturbed forest soils. By contrast, more than half of the clones were Proteobacteria in the NCP soil community. The ␤-proteobacterial clones were the most abundant group in the Proteobacteria. In contrast to oligotrophic Acidobacteria, the ␤-Proteobacteria are copiotrophic. Their relative abundance was highest in soils with high C availability (Fierer et al., 2007). Axelrood et al. (2002) showed that Acidobacteria are generally less abundant and ␤-Proteobacteria more abundant in soils with high concentrations of organic carbon. In NCP, the relative richness in soil organic carbon may create a more favorable habitat for the growth of ␤-Proteobacteria. Among the three disturbed forest soil communities, ␣Proteobacteria was the most abundant group of the Proteobacteria. One abundant ␣-proteobacterial OTU, represented by clone SCP431, which was equally distributed throughout the study sites, is related to Bradyrhizobium spp. (Table 4). It was highly related to the OTU NT21 H01, which was observed in agricultural and forest soils in Georgia (Upchurch et al., 2008). The genus Bradyrhizobium includes slow-growing bacteria capable of nitrogen fixation and nodule formation on leguminous plants (Jordan, 1982). Symbiotic Bradyrhizobium strains have been isolated from nodules of highly divergent legume tribes, including herbaceous and woody species of tropical and temperate origin (Menna et al., 2009). The physiological properties of the genus Bradyrhizobium indicate the potential roles of this abundant OTU for symbiotic nitrogen fixation in natural and disturbed forest ecosystems. Because of the limited size of our clone libraries, only a portion of the soil diversity was sampled. For instance, more extensive sequencing efforts with pyrosequencing methodologies typically identify thousands of OTUs in soil (Roesch et al., 2007; AcostaMartínez et al., 2008). Nevertheless, the approach we describe has been widely used to study the compositional and structural differences between soil microbial communities. The strategy of replicates for each treatment, community DNA extraction, PCR amplification, clone library construction and sequencing has been used to successfully examine the effects of forest management in other soil microbial communities (He et al., 2006). However, more extensive sampling of the soil microbial community, such as by pyrosequencing or other next-generation sequencing methodologies, will be necessary to fully elucidate the changes in the bacterial communities in these soils. 5. Conclusions Forest management practices, including harvesting and tree conversion, clearly influence the soil microbial community compo-

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sition in natural and disturbed forests. The higher the disturbance of forest management, the higher the diversity of the soil microbial community. The highly diverse and different composition of communities in disturbed forests indicates that the bacterial communities are not fully restored even after 50 years of management. These findings significantly improve on our understanding of variation in soil bacterial community in disturbed forests. Further investigation of the functional diversity of soil bacterial communities in disturbed forest ecosystems is needed to address the impact of forest managements on ecosystem function.

Acknowledgement This work was supported by the Taiwan National Science Council, Taiwan (NSC 97-2621-B-001-001-MY3).

References Acosta-Martínez, V., Dowd, S., Sun, Y., Allen, V., 2008. Tag-encoded pyrosequencing analysis of bacterial diversity in a single soil type as affected by management and land use. Soil Biol. Biochem. 40, 2762–2770. Agresti, A., 1992. A survey of exact inference for contingency tables. Stat. Sci. 7, 131–153. Ashelford, K.E., Chuzhanova, N.A., Fry, J.C., Jones, A.J., Weightman, A.J., 2005. At least 1 in 20 16S rRNA sequence records currently held in public repositories is estimated to contain substantial anomalies. Appl. Environ. Microbiol. 71, 7724–7736. Ashelford, K.E., Chuzhanova, N.A., Fry, J.C., Jones, A.J., Weightman, A.J., 2006. New screening software shows that most recent large 16S rRNA gene clone libraries contain chimeras. Appl. Environ. Microbiol. 72, 5734–5741. Axelrood, P.E., Chow, M.L., Radomski, C.C., McDermott, J.M., Davies, J., 2002. Molecular characterization of bacterial diversity from British Columbia forest soils subjected to disturbance. Can. J. Microbiol. 48, 655–674. Barns, S.M., Takala, S.L., Kuske, C.R., 1999. Wide distribution and diversity of members of the bacterial kingdom Acidobacterium in the environment. Appl. Environ. Microbiol. 65, 1731–1737. Barns, S.M., Cain, E.C., Sommerville, L., Kuske, C.R., 2007. Acidobacteria phylum sequences in uranium-contaminated subsurface sediments greatly expand the known diversity within the phylum. Appl. Environ. Microbiol. 73, 3113–3116. Burton, J., Chen, C., Xu, Z., Ghadiri, H., 2007. Gross nitrogen transformations in adjacent native and plantation forests of subtropical Australia. Soil Biol. Biochem. 39, 426–433. Chatterjee, A., Vance, G.F., Pendall, E., Stahl, P.D., 2008. Timber harvesting alters soil carbon mineralization and microbial community structure in coniferous forests. Soil Biol. Biochem. 40, 1901–1907. Chen, C.R., Xu, Z.H., Mathers, N.J., 2004. Soil carbon pools in adjacent natural and plantation forests of subtropical Australia. Soil Sci. Soc. Am. J. 68, 282–291. Coates, J.D., Ellis, D.J., Gaw, C.V., Lovley, D.R., 1999. Geothrix fermentans gen. nov., sp. nov., a novel Fe(III)-reducing bacterium from a hydrocarbon-contaminated aquifer. Int. J. Syst. Bacteriol. 49, 1615–1622. Curlevski, N.J.A., Xu, Z., Anderson, I.C., Cairney, J.W.G., 2010. Converting Australian tropical rainforest to native Araucariaceae plantations alters soil fungal communities. Soil Biol. Biochem. 42, 14–20. Felsenstein, J., 1985. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 35, 22–33. Felsenstein, J., 2005. PHYLIP (Phylogeny Inference Package) Version 3.6. Department of Genome Sciences, University of Washington, Seattle, Distributed by the author. Fierer, N., Bradford, M.A., Jackson, R.B., 2007. Toward an ecological classification of soil bacteria. Ecology 88, 1354–1364. Hannam, K.D., Quideau, S.A., Kishchuk, B.E., 2006. Forest floor microbial communities in relation to stand composition and timber harvesting in northern Alberta. Soil Biol. Biochem. 38, 2565–2575. He, J.Z., Xu, Z.H., Hughes, J., 2006. Molecular bacterial diversity of a forest soil under residue management regimes in subtropical Australia. FEMS Microbiol. Ecol. 55, 38–47. Högberg, M., Högberg, P., Myrold, D., 2007. Is microbial community composition in boreal forest soils determined by pH, C-to-N ratio, the trees, or all three? Oecologia 150, 590–601. Hugenholtz, P., Goebel, B.M., Pace, N.R., 1998. Impact of culture-independent studies on the emerging phylogenetic view of bacterial diversity. J. Bacteriol. 180, 4765–4774. Imberger, K.T., Chiu, C.Y., 2002. Topographical and seasonal effects on soil fungal and bacterial activity in subtropical, perhumid, primary and regenerated montane forests. Soil Biol. Biochem. 34, 711–720. Jangid, K., Williams, M.A., Franzluebbers, A.J., Sanderlin, J.S., Reeves, J.H., Jenkins, M.B., Endale, D.M., Coleman, D.C., Whitman, W.B., 2008. Relative impacts of landuse, management intensity and fertilization upon soil microbial community structure in agricultural systems. Soil Biol. Biochem. 40, 2843–2853.

118

Y.-T. Lin et al. / Applied Soil Ecology 47 (2011) 111–118

Janssen, P.H., 2006. Identifying the dominant soil bacterial taxa in libraries of 16S rRNA and 16S rRNA genes. Appl. Environ. Microbiol. 72, 1719–1728. Janssens, I.A., Dieleman, W., Luyssaert, S., Subke, J.A., Reichstein, M., Ceulemans, R., Cilas, P., Dolman, A.J., Grace, J., Matteucci, G., Papale, D., Piao, S.L., Schulze, E.D., Tang, J., Law, B.E., 2010. Reduction of forest soil respiration in response to nitrogen deposition. Nat. Geosci. 3, 315–322. Jordan, D.C., 1982. Transfer of Rhizobium japonicum Buchanan 1980 to Bradyrhizobium gen. nov., a genus of slow-growing, root nodule bacteria from leguminous plants. Int. J. Syst. Bacteriol. 32, 136–139. Kang, C.S., 2008. Canopy nutrient dynamics of Chamaecyparis obtuse var. formosana in a subtropical montane cloud forest in Chilanshan area, Taiwan. MSc Thesis, National Taiwan University, Taipei, Taiwan. Kemp, P.F., Aller, J.Y., 2004. Bacterial diversity in aquatic and other environments: what 16S rDNA libraries can tell us. FEMS Microbiol. Ecol. 47, 161–177. Kishimoto, N., Kosako, Y., Tano, T., 1991. Acidobacterium capsulatum gen. nov., sp. nov.: an acidophilic chemoorganotrophic bacterium containing menaquinone from acidic mineral environment. Curr. Opin. Microbiol. 22, 1–7. Lane, D.J., 1991. 16S/23S rRNA sequencing. In: Stackebrandt, E., Goodfellow, M. (Eds.), Nucleic Acid Techniques in Bacterial Systematics. Wiley, New York, pp. 115–175. Lauber, C.L., Strickland, M.S., Bradford, M.A., Fierer, N., 2008. The influence of soil properties on the structure of bacterial and fungal communities across land-use types. Soil Biol. Biochem. 40, 2407–2415. Lee, S.H., Ka, J.O., Cho, J.C., 2008. Members of the phylum Acidobacteria are dominant and metabolically active in rhizosphere soil. FEMS Microbiol. Lett. 285, 263–269. Liesack, W., Bak, F., Kreft, J.U., Stackebrandt, E., 1994. Holophaga foetida gen. nov., sp. nov., a new, homoacetogenic bacterium degrading methoxylated aromatic compounds. Arch. Microbiol. 162, 85–90. Lin, Y.T., Huang, Y.J., Tang, S.L., Whitman, W.B., Coleman, D.C., Chiu, C.Y., 2010. Bacterial community diversity in undisturbed perhumid montane forest soils in Taiwan. Microb. Ecol. 59, 369–378.

Lozupone, C., Hamady, M., Knight, R., 2006. UniFrac – an online tool for comparing microbial community diversity in a phylogenetic context. BMC Bioinformatics 7, 371. Menna, P., Barcellos, F.G., Hungria, M., 2009. Phylogeny and taxonomy of a diverse collection of Bradyrhizobium strains based on multilocus sequence analysis of the 16S rRNA gene, ITS region and glnII, recA, atpD and dnaK genes. Int. J. Syst. Evol. Microbiol. 59, 2934–2950. Nüsslein, K., Tiedje, J.M., 1999. Soil bacterial community shift correlated with change from forest to pasture vegetation in a tropical soil. Appl. Environ. Microbiol. 65, 3622–3626. Roesch, L.F.W., Fulthorpe, R.R., Riva, A., Casella, G., Hadwin, A.K.M., Kent, A.D., Daroub, S.H., Camargo, F.A.O., Farmerie, W.G., Triplett, E.W., 2007. Pyrosequencing enumerates and contrasts soil microbial diversity. ISME J. 4, 283–290. Saitou, N., Nei, M., 1987. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4, 406–425. Schloss, P.D., Handelsman, J., 2005. Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness. Appl. Environ. Microbiol. 71, 1501–1506. Smith, N.R., Kishchuk, B.E., Mohn, W.W., 2008. Effects of wildfire and harvest disturbances on forest soil bacterial communities. Appl. Environ. Microbiol. 74, 216–224. Upchurch, R., Chiu, C.Y., Everett, K., Dyszynski, G., Coleman, D.C., Whitman, W.B., 2008. Differences in the composition and diversity of bacterial communities from agricultural and forest soils. Soil Biol. Biochem. 40, 1294–1305. Wang, Q., Garrity, G.M., Tiedje, J.M., Cole, J.R., 2007. Naïve Bayesian Classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267. Zimmermann, J., Gonzalez, J.M., Saiz-Jimenez, C., Ludwig, W., 2005. Detection and phylogenetic relationships of highly diverse uncultured acidobacterial communities in Altamira Cave using 23S rRNA sequence. Geomicrobiol. J. 22, 379– 388.