Composition and distribution of microbial communities in natural river wetlands and corresponding constructed wetlands

Composition and distribution of microbial communities in natural river wetlands and corresponding constructed wetlands

Ecological Engineering 98 (2017) 40–48 Contents lists available at ScienceDirect Ecological Engineering journal homepage:

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Ecological Engineering 98 (2017) 40–48

Contents lists available at ScienceDirect

Ecological Engineering journal homepage:

Composition and distribution of microbial communities in natural river wetlands and corresponding constructed wetlands Qingqing Cao a , Hui Wang a , Xiaocui Chen a , Renqing Wang a,b,c , Jian Liu a,∗ a b c

Institute of Environmental Research, Shandong University, Jinan 250100, China School of Life Sciences, Shandong University, Jinan 250100, China Shandong Provincial Engineering and Technology Research Center for Vegetation Ecology, Shandong University, Jinan 250100, China

a r t i c l e

i n f o

Article history: Received 26 January 2016 Received in revised form 6 September 2016 Accepted 11 October 2016 Keywords: Constructed wetland River wetland Proteobacteria Nitrification Denitrification

a b s t r a c t Microbial community plays an important role in wetland ecosystem. To explore the composition and distribution of microbial communities in different wetland types, sediments from different sites of Xinxue River (XR) and Zhaoniu River (ZR), and the corresponding Xinxue River Constructed Wetland (XRCW) and Zhaoniu River Constructed Wetland (ZRCW) were sampled and analyzed using high throughput sequencing. The constructed wetlands were found to have more taxa of microbes in sediments than their corresponding river wetlands. The community richness index suggests that microbial richness in XR and XRCW is higher than that in ZR and ZRCW. High potential of sulfur cycle in XRCW is suggested by the superior distribution of Desulfobacterales, Syntrophobacterales orders, and Thiobacillus genus of Proteobacteria. Moreover, ZRCW has relatively lower nitrification ability than other three wetlands according to the distribution of Nitrospirae, Planctomycetes, and Acidobacteria phyla. XR and XRCW show high potential of methanogenesis as the distribution of Methanomicrobia order in Archaea. ZRCW is suggested in a state that organic carbon mineralization exceeds aggregation, denitrification exceeds nitrification based on different distributions of the functional bacteria (such as Nitrospirae, Acidobacteria, and Planctomycetes). Furthermore, it indicates that ammonia removal process in ZRCW sediments is mostly limited to nitrification. This study demonstrated that wetland functions can be detected by the composition and distribution of microbial communities and influenced by the pollution status and surroundings probably. Our results are essential for understanding the interrelationship between microbial distribution and the pollution status of wetlands for the evaluation of constructed wetland. © 2016 Elsevier B.V. All rights reserved.

1. Introduction Due to their specific superiorities, different types of wetlands play various functions in ecosystems (Kansiime et al., 2007; Robertson, 2004; Zhang et al., 2009). River wetlands, as one kind of natural wetlands, can purify river waters in the process of water diversion into lakes or seas (Robertson, 2004). With the discharge of domestic sewage and industrial wastewater, purification of river wetlands can hardly meet the safety standards of water quality in some regions. Based on the water purification principle of river wetlands and the aspiration to raise the purification efficiency of pollutants (Tota-Maharaj et al., 2012), many wetlands are designed and widely constructed around rivers in China, as well as worldwide (Vymazal, 2010; Zhang et al., 2009). At relatively low cost,

∗ Corresponding author. E-mail addresses: [email protected], [email protected] (J. Liu). 0925-8574/© 2016 Elsevier B.V. All rights reserved.

constructed wetlands were used to purify heavy metals, pathogenic bacteria, nitrogen and phosphorus, and other harmful organic pollutants from river waters and sediments effectively (Kadlec and Wallace, 2008; Puigagut et al., 2008). The processes of purification, such as sedimentation, decomposition, adsorption and plant uptake, mostly cannot be separated from the internal activities of microorganisms (Saeed and Sun, 2012; Samsó and García, 2013; Zhou et al., 2015). Microorganisms, including bacteria, fungi, and viruses (Schaechter, 2009), are widely in living organisms and their surroundings (Garcia et al., 2015). Microbial richness and evenness differ from their compatible environment, as microbes have their habit and features (Dheilly et al., 2015). Based on the differences of their surroundings and daily demands, microbes play different functions with daily activities (Sims et al., 2012a,b). In wetland ecosystems, plants, river waters and sediments are filled with many kinds of microbes (Tota-Maharaj et al., 2012). For example, Proteobacteria and Bacteroidetes are easily dominated

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Fig. 1. National, regional, and local maps of the study area. Maps showing the (a) national, (b) regional, and (c and d) local geographical setting of the study area. Map (c) shows the location of the Zhaoniu River (ZR) and Zhaoniu River Constructed Wetland (ZRCW) and map (d) shows the location of the Xinxue River (XR) and Xinxue River Constructed Wetland (XRCW).

Fig. 2. Composition of different communities at phylum level in the two couples of wetlands. (Sequences that could not be classified into any known group are sorted as unassigned phylum; phyla that own few sequences are assigned as other phyla).

in wetland sediments (Ligi et al., 2014; Adrados et al., 2014). As the decomposer of the ecosystem, including the biosphere, microbial composition and function are easily interrelated with the surrounding environment (Merkley et al., 2004). Microbes in natural wetlands have a naturally evolving relationships with their local environments (Yuan et al., 2009), whereas constructed wetlands are built and managed in order to simulate natural wetlands (Tiner, 1999; Zhang et al., 2009) for purposes that include water purification and pollution abatement (Sakadevan and Bavor, 1998). Thus, the microbial varieties and quantities, distribution and composition in natural wetland and their corresponding constructed wetland may have many differences. However, the research on microorganism by comparing constructed wetlands with the relevant river wetlands in China is sparse, or focused only on contrasting wetland types, which are not relevant (Jia et al., 2014; Rai et al., 2015). Thus, in order to explore the differences in microbial community between relevant wetlands, two couples of natural river wetlands and corresponding constructed wetlands (Zhaoniu River (ZR) and

Zhaoniu River Constructed Wetland (ZRCW), Xinxue River (XR) and Xinxue River Constructed Wetland (XRCW)) of Shandong Province, China, were selected and sampled from upstream to downstream. This research is essential for understanding the processing of wetland ecosystem and for the evaluation of constructed wetland.

2. Materials and methods 2.1. Site selection and field sampling This study was conducted at Zhaoniu River Constructed Wetland (ZRCW) and Zhaoniu River (ZR), Xinxue River Constructed Wetland (XRCW) and Xinxue River (XR), Shandong Province, China (Fig. 1a). ZR is a tributary of Tuhai River, which is one important river of Haihe River Basin (Fig. 1b). ZRCW was constructed in 2012 to purify the domestic sewage and industrial wastewater from cities nearby (Fig. 1c). XR is one of the principal rivers feeding Nansi Lake (Fig. 1d), one of the biggest lakes in the South-to-North Water Diversion Project. XRCW was constructed in 2007 in order to purify waters


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Table 1 The numbers of species that are classified to phylum, class, order, family, and genus in the wetlands.

Quality sequences ACE index Chao index Phylum Class Order Family Genus











14091a 3337.55a 2986.92a 30a 90a 132a 161ab 145ab

16760ab 3696.84ab 3451.91ab 35ab 102ab 151ab 175abc 162bc

16380ab 4574.55bc 4136.02bc 47de 117cd 174bcd 176abc 150ab

19174ab 3380.60a 3278.62ab 42bcd 110bc 166bcd 187bcd 175bc

30314b 3912.06abc 3721.11abc 44cde 115bcd 175cd 204d 197c

13764a 4436.45bc 3771.19abc 46cde 109bc 165bcd 177abc 157ab

13293a 3743.43ab 3503.73ab 38bc 104bc 153abc 163ab 146ab

12089a 4167.18abc 3291.85ab 41bcd 107bc 158bc 157a 124a

14928ab 4394.9bc 3792.24abc 51ef 117cd 177cd 171abc 142ab

21008ab 4675.94c 4555.83c 57f 127d 188d 195cd 170bc

Numbers sharing the same letters have no significant difference in each line.

Table 2 Proportions of the important categories in the four wetlands. Name



ZR (%)

ZRCW (%)

XR (%)

XRCW (%)

Thiobacillus Burkholderiales Rhodocyclales Desulfuromonadales Desulfobacterales Syntrophobacterales Myxococcales Saprospirales Bacteroidales Cytophagales Flavobacteriales Sphingobacteriales Phycisphaerales Gemmatales Pirellulales Planctomycetales Acidobacteria-6 Acidimicrobiales Actinomycetales Lactobacillales Clostridiales Thermodesulfovibrionaceae


Proteobacteria Proteobacteria Proteobacteria Proteobacteria Proteobacteria Proteobacteria Proteobacteria Bacteroidetes Bacteroidetes Bacteroidetes Bacteroidetes Bacteroidetes Planctomycetes Planctomycetes Planctomycetes Planctomycetes Acidobacteria Actinobacteria Actinobacteria Firmicutes Firmicutes Nitrospirae

1.62 1.63 0.41 0.77 0.97 1.93 1.67 7.09 3.36 5.92 3.17 1.35 1.11 2.14 4.25 1.03 7.24 1.16 0.80 0.34 0.53 0.79

0.32 3.81 2.16 0.66 1.99 0.72 1.40 5.95 14.01 6.22 7.33 2.05 0.74 0.31 1.54 0.55 0.96 0.54 3.61 4.75 0.96 0.53

2.00 1.82 0.78 0.38 0.73 1.32 1.60 8.05 2.83 6.87 4.32 1.92 1.10 1.11 3.12 0.72 3.27 0.42 0.85 0.86 0.34 5.03

1.21 1.86 0.98 1.16 3.00 2.77 1.71 2.48 6.31 2.28 1.38 0.29 0.88 0.77 3.45 0.46 3.16 0.38 0.94 0.87 0.89 5.91

C: class; O: order; G: genera; F: family.

from XR before it flows into Nansi Lake or the XR estuary. With an area of ∼1000 m2 , XRCW is located on the southern bank of the XR (Zhang et al., 2008). Totally, ten sampling stations (Up/Mid/Down-ZR, Up/DownZRCW, Up/Mid/Down-XR, Up/Down-XRCW) were selected and each station had four sampling sites, at the intervals of 250 m. Thus, a total of 40 sediment samples, across two wetland couples were collected. The global position system recorded the sampling sites of the ZR (36◦ 54 12.10 –37◦ 00 17.82 N and 116◦ 39 51.55 –116◦ 45 36.66 E), XR (34◦ 48 32.44 –34◦ 46 57.30 N and 117◦ 09 23.94 –117◦ 15 27.71 E), (36◦ 56 25.00 –36◦ 56 56.78 N and ZRCW 116◦ 47 41.08 –116◦ 47 54.88 E), and XRCW (34◦ 43 55.39 –34◦ 47 02.07 N and 117◦ 09 17.99 –117◦ 09 41.85 E), respectively. (Fig. 1c).

sequences by sequence similarity of 97%, acquire the taxonomic information of every OTU by comparing to the sequence library, and construct the phylogenetic tree (DeSantis et al., 2006). After that, OTU was accurately processed by removing the OTUs where richness was less than 0.001% of the total sequences (Bokulich et al., 2013). Rarefaction curves, Rank abundance curve, Community richness index (Chao index and ACE index), which reflect the OTU numbers in samples and microbial communities, and positively indicate the richness of microbial community (Pitta et al., 2014, 2010), respectively, were calculated by Mothur analysis. Certain volumes of sediment samples were dried to 105 ◦ C to ˇ ´ 2012). y, measure the moisture and bulk density (Jerman and Cern The pH of sediment samples was measured with a 1:5 sedimentswater ratio by pH meter.

2.2. DNA extraction and lab analyses 2.3. Statistical analyses Sediment samples from ZR, ZRCW, XR, and XRCW were stored in icebox (4 ◦ C) before being transferred into freezer of −20 ◦ C. Samples were freeze-dried and sifted to remove the residues of animals and plants. The processes of DNA extraction and Illumina MiSeq sequencing of the amplified DNA were carried out at Shanghai Paisennuo Biological Technology Co. Ltd (Shanghai, China). The raw data was served in the form of R1.fastq and R2.fastq, which corresponds to Read 1 and Read 2. Qiime (version 1.9.0) and Mothur (version 1.31.2) were used to process the raw sequences. The methods of uclust (Edgar et al., 2011), BLAST (Altschul et al., 1990), and FastTree (Price et al., 2009) were used to cluster the high quality

Data analyses were performed using the SPSS (version 21.0) software. A one-way analysis of variance (ANOVA) was used to determine the differences between the two couples of wetlands (XR and XRCW; ZR and ZRCW), between wetland types (the river and constructed wetlands), and between upstream to downstream of each wetland. Where significant differences were observed, we used Duncan test for post hoc multiple comparisons. Microsoft Excel and Adobe Illustrator (version 16.0.0) were used to draw graphs. Pearson correlation analysis was implemented among phyla of microbial community in sediment samples.

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1 0.294


−0.052 −.104

0.449** 0.136



0.059 0.047






0.666** 0.535** 0.528**



−0.020 0.567**

0.204 0.424**

1 0.939** 0.029


1 0.061



Cyanobacteria Chlorobi Chloroflexi Firmicutes Actinobacteria Verrucomicrobia

Microbes of Down-ZRCW showed the maximum number of quality sequences (30,314). In the four wetlands, ZRCW and XRCW have more microbes at levels of phylum, class, order, family, and genus than the corresponding ZR and XR, respectively (Table 1). Down-ZR also has more microbes than Up-ZR and Mid-ZR at all levels. Microbial richness index (Chao index and ACE index) also suggest that microbial richness of XRCW and XR are higher than that of ZR and ZRCW, and that of XRCW is also higher than XR, while there is no significant difference between ZR and ZRCW (Table 1). In the four wetlands, richness of bacteria (over 95% of all microbes) is significantly higher than archaea in all sampling stations. Moreover, among all the phyla, Proteobacteria and Bacteroidetes dominate in the four wetlands and account for 39.4-61.5% in our study (Fig. 2). Planctomycetes, Acidobacteria, Nitrospirae, Verrucomicrobia, Actinobacteria, Gemmatimonadetes, and Firmicutes as important phyla of bacteria are also largely found in the studied wetlands. Crenarchaeota, Euryarchaeota are two main phyla of archaea in the four wetlands (Fig. 2). Among the four wetlands, the distribution of Proteobacteria has no significant difference. ZRCW owns the most Bacteroidetes, Actinobacteria, and Firmicutes but the least Planctomycetes and Acidobacteria as compared to other wetlands, whereas Planctomycetes and Acidobacteria are significantly higher in ZR, as opposite to ZRCW.




p < 0.05. p < 0.01.

−0.054 −0.586** 0.684**






0.119 −0.155 0.043 Crenarchaeota






0.081 0.048 0.286 −0.018 0.021 −0.052 Cyanobacteria



0.189 0.482**


−0.202 −0.358*






−0.116 −0.400* 0.014 Firmicutes



−0.033 −0.057 Actinobacteria





−0.115 0.416** −0.118 −0.114


−0.170 0.361* Verrucomicrobia



−0.026 0.161 0.075

0.354* 0.369*

0.214 −0.120 0.166 Nitrospirae


1 0.287

0.333* 0.231

0.365* 0.513**

1 1

0.442** 0.496**

−0.185 0.424**



0.023 0.078 −0.008 Acidobacteria



0.490** 0.313* 0.276 0.187 −0.103



−0.286 0.139 −0.117 Bacteroidetes


1 −0.026 0.454** −0.156 −0.429** 0.183 pH Proteobacteria


Acidobacteria Planctomycetes Bacteroidetes Proteobacteria 1



3.2. The distribution and composition of the main phyla in the studied wetlands

Moisture −0.888**

Bulk density

3.1. Composition differences in different wetlands



3. Results

Bulk density


Table 3 Pearson correlation analysis among main phyla and environmental factors in the four wetlands.


The distribution and composition of several important phyla were analyzed to explain their differences among the wetlands. In our study, beta-Proteobacteria, delta-Proteobacteria, gamma-Proteobacteria, alpha-Proteobacteria are the main classes of Proteobacteria, especially beta-Proteobacteria, delta-Proteobacteria (Fig. 3). Thiobacillus is one dominated genus, and Burkholderiales and Rhodocyclales are the main orders of beta-Proteobacteria. Desulfuromonadales, Desulfobacterales, Syntrophobacterales, and Myxococcales are main orders of delta-Proteobacteria. The significantly higher proportion of delta-Proteobacteria in XRCW than in other stations is mainly caused by its abundant Desulfobacterales (3% in XRCW and 1.2% in others), and Syntrophobacterales (2.77% in XRCW and 1.5% in others). ZRCW also has more Desulfobacterales than other stations, but fewer Syntrophobacterales (Figs. 4 and 5; Table 2). There is no significant difference of beta-Proteobacteria in the studied wetlands, which may show their stability in wetlands. For example, ZRCW has the advantage of Burkholderiales (3.8% in ZRCW and 1.8%, equally in others and Rhodocyclales (3.8% in ZRCW and 0.9%, equally in others) but disadvantage of Thiobacillus (Fig. 5). Saprospirales, Bacteroidales, Cytophagales, Flavobacteriales, Sphingobacteriales are the main orders of Bacteroidetes in our study (Fig. 3). The significantly higher Bacteroidetes in ZRCW than other stations is mainly caused by the significantly higher Bacteroidales (14.01%, 6.31%, 3.36%, 2.83% in ZRCW, XRCW, ZR and XR, respectively) and Flavobacteriales (7.33% in ZRCW) than other stations. The significantly lower Bacteroidales in XRCW than in other stations may be resulted from the low Saprospirales, Cytophagales, Sphingobacteriales, and especially Flavobacteriales (1.38% in XRCW). The composition analysis shows that Phycisphaerales, Gemmatales, Pirellulales, and Planctomycetales are the main orders of Planctomycetes in the wetlands. Acidobacteria-6 is the main order of Acidobacteria. Gemm-1 and Gemmatimonadetes are the main classes of Gemmatimonadetes. Acidimicrobiales and Actinomycetales are two main orders of Actinobacteria. Lactobacillales and Clostridiales are two important orders of Firmicutes, and Thermodesulfovibrionaceae


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Fig. 3. The composition of Proteobacteria phylum at class level and of Bacteroidetes phylum at order level in the two couples of wetlands. The different letters between the same class or the same order show significant differences.

Fig. 4. The distribution of five phyla that have significant difference, among the four wetlands. The different letters among the four wetlands show the significant differences.

is the main order of Nitrospirae (Figs. 4 and 5; Table 2). Planctomycetes and Acidobacteria are significantly higher in ZR and lower in ZRCW than other stations and this may be related to the presence Gemmatales (2.2% in ZR and 0.4% in ZRCW), Pirellulales (4.3% in ZR and 1.5% in ZRCW), Acidobacteria-6 (7.2% in ZR and 0.9% in ZRCW). The significantly higher Actinobacteria and Firmicutes in ZRCW are mainly caused by the abundant Lactobacillales (4.8% in ZRCW and 0.7% in other stations equally) and Actinomycetales (3.6% in ZRCW and 0.9% in other stations equally) in ZRCW. Thermodesulfovibrionaceae (main order of Nitrospirae) has the same distribution pattern as Nitrospirae, they are significantly higher in XRCW (5.9%), and lower in ZRCW (0.5%) (Fig. 5). The main order of Euryarchaeota phylum in archaea is Methanomicrobia, which is significantly higher in XR and XRCW (equally 0.84%) than that in ZR and ZRCW (equally 0.1%; p < 0.05).

3.3. Principal component analysis (PCA) of different phyla in the two couples of wetlands The distribution of 20 sampling sites and 20 main phyla from ZR and ZRCW are displayed in Fig. 6A. The variance of 70.8% is attributed to p1, whereas p2 captured 20.9% of the variance. The distribution of sampling sites is mostly around the original point except the sites 13, 19, and 20. The closed gather of most sampling sites suggests that microbial community in the two wetlands has no significant difference. As for XR and XRCW (Fig. 6B), 52.7% and 33.1% of the variances are contributed to p1 and p2, respectively. In contrast with ZR and ZRCW, sampling sites in XR and XRCW scatter much further beyond the origin. This suggests the complicated distribution of microbes between the two wetlands.

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Fig. 5. The distribution of several important taxa in the four wetlands. The same letter shows the same genus or order.

Fig. 6. Principal component analysis (PCA) of different phyla. A: in ZR and ZRCW. B: in XR and XRCW.

The correlations in phylum level show that Proteobacteria and Bacteroidetes are significantly related to most other main phyla, and only Verrucomicrobia, Chloroflexi, and Chlorobi are significantly affected by the moisture. While pH is only notably associated with Verrucomicrobia (p < 0.01; Table 3). The correlations in further taxa (class, order, family and genus) show that moisture is positively connected with Desulfobacterales, Syntrophobacterales and Methanomicrobiales, while pH is negatively correlated with Verrucomicrobiaceae and Verrucomicrobiaceae. Many taxa of beta-Proteobacteria (Burkholderiales, Rhodocyclales) are positively related to most other taxa, and the taxa of delta-Proteobacteria (Desulfuromonadales, Desulfobacterales, etc.) and Bacteroidetes (Bacteroidales, Flavobacteriales, etc.) are mostly associated with each other in their own phyla. Planctomycetes is significantly related with Nitrospirae and Acidobacteria (p < 0.01), and Lactobacillales is significantly related with Actinomycetales (p < 0.01). Syntrophobacterales is positively related with Pirellulales and Acidobacteria-6 while Burkholderiales, Rhodocyclales are significantly related with Lactobacillales and Actinomycetales (Table 4).

4. Discussion Our results show that the constructed wetlands (XRCW and ZRCW) have higher categories of microbes than those of the corresponding river wetlands (XR and ZR), which may suggest that the varieties of microbes are more abundant in constructed wetlands than the corresponding river wetlands. This finding is similar to the report of Fernandes et al. (2015), in which microbe community of constructed wetland is particularly abundant. In terms of the quantities of different phyla, Proteobacteria and Bacteroidetes dominate the four wetlands and they also dominate many other wetlands and even widespread in the world (Ligi et al., 2014; Adrados et al., 2014). Although Myxococcales, mainly in charge of dissimilatory nitrate reduction and N2 O consumption (Manucharova et al., 2000; Zhou et al., 2014), shows similar distribution among the various sampling stations, the significantly higher delta-Proteobacteria (mainly including Desulfobacterales, Syntrophobacterales orders) in XRCW, and the high Thiobacillus genus of beta-Proteobacteria in XR and XRCW may suggest the higher potential of sulfur reduction in


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Table 4 Pearson correlation analysis among main specific categories and environmental factors in the four wetlands.

XRCW, as these orders and genera can mainly reduce sulfur materials (Yousefi et al., 2014; Girguis et al., 2005). The preponderant distribution of Burkholderiales and Rhodocyclales in ZRCW, which take part in denitrifying activity (Eloe, 2011; Zheng et al., 2015), suggests the better denitrification ability of ZRCW than other studied wetlands. Similarly, ZRCW has significantly more Bacteroidetes (mainly include Flavobacteriales, Bacteroidales orders), Actinobacteria (mainly include Actinomycetales), and Firmicutes (include Lactobacillales) phyla and significantly less Planctomycetes (include Pirellulales), Acidobacteria (include Acidobacteria-6), and Nitrospirae (include Thermodesulfovibrionaceae) phyla. These findings suggest that ZRCW may be in a state that organic carbon mineralization exceeds aggregation, denitrification largely exceeds nitrification, and pollutant bearing capacity there may exceed other stations. Since Flavobacteriales, another important heterotrophic denitrifier (Dorador et al., 2009; Gabarró et al., 2013), is also significantly higher in ZRCW than other stations. Actinomycetales and Lactobacillales, which are associated with the decomposition of organic matter and use organic carbon as the main substrate (Freitas et al., 2012; De Vrieze et al., 2015), are significantly higher in ZRCW. Pirellulales and Acidobacteria-6, associated with the organic carbon deposition and aerobic ammonia oxidation (Elshahed et al., 2007), are significantly higher in ZR but lower in ZRCW. Bacteroidales, which is used to assess the sources of fecal pollution (Harwood et al., 2014; Wilkes et al., 2013), is the highest in ZRXW (13% and 2.0%) and XRCW (5.4%), this distribution may suggests the pollution pushed in constructed wetland is higher than that in river wetlands, especially in the ZRCW. And Verrucomicrobiaceae, which is partially lived in excrement of animals and humans (Freitas et al., 2012), is also the highest in ZRCW (2.0%), so it partially indicates the pollution status of ZRCW. Nitrospirae, one important component of ammonia oxidizing bacteria and playing an important role in nitrification (Truu et al., 2009), is significantly higher in XRCW and XR than in ZR and ZRCW. This suggesting the higher ability of nitrification in XRCW and XR.

Pollution may lead to the low dissolved oxygen (DO) in sediment (Sánchez et al., 2007; DOZRCW is 0.18 mg l−1 ). Thus, the more denitrifying bacteria than nitrifying bacteria in ZRCW and in other stations may result from the low dissolved oxygen, as denitrifying bacteria are anaerobic and nitrifying bacteria are aerobic (Robertson and Kuenen, 1990). This may simultaneously suggest that the ammonia removal process (nitrification-denitrification cycle) from ZRCW sediments is mainly limited by the nitrification. Moreover, the higher carbon mineralization in ZRCW than in other stations may also be caused by the high denitrification, as carbon mineralization concurs with denitrification and offers energy for it (Lu et al., 2009). Thus, the functions and internal activities are closely linked to the pollution status of wetlands, especially that of the constructed wetlands. The significantly higher Planctomycetes and Acidobacteria in ZR than other stations, as explained above, also indicate that ZR has the advantage of organic carbon deposition and nitrification. Wetland is an important site of methane emission, which reflects the internal activities of microorganisms (Yan et al., 2012). Moisture is one important factor that influencing Euryarchaeota and Methanomicrobia for their significant relations. And the emission of methane in XRCW as well as other constructed wetlands of China show that methane emission in XRCW is relatively high (Yan et al., 2012; Wang et al., 2013; Xu et al., 2015). This result may be related to the rare methane-oxidizing bacteria and high methanogen in XRCW, which is mainly depend on the Methanomicrobia order of archaea. The report of Sun et al. (2015) indicated that methanogens is negatively associated with nitrate, sulfate, and iron reducers, while this trend is not significant in our study. XR and XRCW show more methanogen and nitrification drivers than other stations. The correlation of different phyla in the studied wetlands may suggest the interaction of the microbes. Moreover, from the closed gather of sampling sites in ZR and ZRCW and the decentralized distribution in XR and XRCW, it may inferred that XR and XRCW are

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more complicated than ZR and ZRCW. In addition, the Chao index and ACE index, which are significantly higher in Up/Mid/Down-XR and XRCW than in the corresponding Up/Mid/Down-ZR and ZRCW, may suggest that XR and XRCW have high microbial richness and very complicated microbial activities. The significant correlation between Proteobacteria, Bacteroidetes and most other main phyla indicate the stability and the interrelationship of the two phyla in the wetland sediments. The relation between the desulfuration bacteria (Desulfobacterales, Syntrophobacterales) (Divya et al., 2011; Zeng et al., 2006) and moisture may suggest that higher moisture is beneficial to sulfur cycle. Two bacteria (Burkholderiales, Rhodocyclales) those involved in denitrification (Eloe, 2011; Zheng et al., 2015), are associated with most other taxa in our study, this finding can prove that denitrification is well-suited in the studied wetlands. Delta-Proteobacteria and Bacteroidetes, the taxa of which are mostly associated with each other in their own phyla, are full of bacteria associated with nitrogen and sulfur cycling (Ligi et al., 2014; Elshahed et al., 2007). It may suggest that most bacteria in Bacteroidetes or in delta-Proteobacteria have significant mutual influence and combined actions. The significantly positive correlations among the S-reductive Syntrophobacterales (Sun et al., 2015), the C-formative Acidobacteria-6 (Kielak et al., 2010) and the S-cycled and C-mineralized Pirellulales (Jiang et al., 2015) show that processes of carbon cycle and sulfur cycle are also interactional. And this finding is further confirmed by the significant relationship between Acidobacteria and Proteobacteria (Ballav et al., 2012; Elshahed et al., 2007). Two main orders (Burkholderiales, Rhodocyclales) for denitrification (Eloe, 2011; Zheng et al., 2015), and Lactobacillales and Actinomycetales for carbon decomposition (Table 3; Ballav et al., 2012) validate that CO2 emissions with denitrification process is mainly operated by Lactobacillales and Actinomycetales. And whether this CO2 emissions is the source in wetland sediments or not still need further research. The studied constructed wetlands have more microbes than the corresponding river wetlands at most classification (Table 1). Moreover, Chao index, and ACE index in XR and XRCW are higher than those in ZR and ZRCW, and so is the microbial complexity. Proteobacteria and Bacteroidetes are two dominated phyla, and there are lots of internal links among different functions of microbes. Distribution differences of microbes among the four wetlands suggest their different functions, correspondingly. XRCW has high efficiency of methanogenesis and sulfur cycle, as it is relatively abundant in these bacteria and archaea, while ZR, XR, and XRCW have high ability of nitrification, as they are abundant in nitrifying bacteria. The abundance of denitrifying bacteria and bacteria which feed on organic matter in ZRCW indicate the high denitrification and carbon mineralization there. Constructed wetlands, especially ZRCW, bear more pollution than corresponding river wetlands based on Bacteroidales and Verrucomicrobia; the functional differences of wetlands probably resulted from the pollution status and surroundings. Our results are conducive to understand the interrelationship between microbial distribution and the pollution status of wetlands, as well as the microbial mechanism of water purification in constructed wetland. Acknowledgements This study was financially supported by “National Natural Science Foundation of China” (No. 31200426), “National Water Special Project” (No. 2012ZX07203-004) and “The Fundamental Research Funds of Shandong University” (No. 2015JC023). References Adrados, B., Sánchez, O., Arias, C.A., Becares, E., Garrido, L., Mas, J., Brix, H., Morató, J., 2014. Microbial communities from different types of natural wastewater


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