Science of the Total Environment 506–507 (2015) 380–390

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Influence of environmental variables on the structure and composition of soil bacterial communities in natural and constructed wetlands Paula Arroyo a,⁎, Luis E. Sáenz de Miera b,1, Gemma Ansola c,2 a b c

Instituto de Medio Ambiente, Recursos Naturales y Biodiversidad, Universidad de León, Calle La Serna, no. 56, CP 24071, León, Spain Departamento de Biología Molecular, Universidad de León, Campus de Vegazana s/n, CP 24071, León, Spain Departamento de Biodiversidad y Gestión Ambiental, Universidad de León, Campus de Vegazana s/n, CP 24071, León, Spain

H I G H L I G H T S • Bacterial communities in natural and constructed wetland soils were analyzed. • Structure was linked with physicochemical parameters and wetland factors. • The wetland receiving the highest nutrient concentration showed the lowest diversity.

a r t i c l e

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Article history: Received 31 July 2014 Received in revised form 24 October 2014 Accepted 11 November 2014 Available online 25 November 2014 Editor: C.E.W. Steinberg Keywords: Soil wetland bacterial community 16S rRNA pyrosequencing Diversity Bacterial community composition Soil and water physicochemistry

a b s t r a c t Bacteria are key players in wetland ecosystems, however many essential aspects regarding the ecology of wetland bacterial communities remain unknown. The present study characterizes soil bacterial communities from natural and constructed wetlands through the pyrosequencing of 16S rDNA genes in order to evaluate the influence of wetland variables on bacterial community composition and structure. The results show that the composition of soil bacterial communities was significantly associated with the wetland type (natural or constructed wetland), the type of environment (lagoon, Typha or Salix) and three continuous parameters (SOM, COD and TKN). However, no clear associations were observed with soil pH. Bacterial diversity values were significantly lower in the constructed wetland with the highest inlet nutrient concentrations. The abundances of particular metabolic groups were also related to wetland characteristics. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Wetlands are the transitional link between aquatic and terrestrial ecosystems. They serve as important carbon sinks and pollution buffers. Moreover, they improve water quality, flood control, and provide valuable wildlife habitats. The capacity of wetlands to transform and store organic matter, nutrients or metals has resulted in a widespread use of wetlands for wastewater treatment worldwide. Constructed wetlands are man-made copies of natural wetlands that optimally exploit the biogeochemical cycles that normally occur in these systems for the purpose of wastewater treatment (Rousseau et al., 2008).

⁎ Corresponding author. Tel.: +34 987 293135. E-mail addresses: [email protected] (P. Arroyo), [email protected] (L.E. Sáenz de Miera), [email protected] (G. Ansola). 1 Tel.: +34 987 293195. 2 Tel.: +34 987 291568; fax: +34 987 291563.

http://dx.doi.org/10.1016/j.scitotenv.2014.11.039 0048-9697/© 2014 Elsevier B.V. All rights reserved.

Bacterial communities are involved in the biogeochemical cycles of wetland soils, and their activities are crucial for the functions of natural wetlands because they play a critical role in energy flows and nutrient transformation (Peralta et al., 2013). Moreover, pollutant removal and bacterial activity in constructed wetlands are closely tied to the cycling of carbon, nitrogen and sulfur (Faulwetter et al., 2009). The application of molecular techniques has made it possible to broaden insights into the vast diversity and interactions that bacteria present in complex environments. Recent use of these molecular tools has provided increasing knowledge about specific soil bacterial groups in natural (Sims et al., 2012a) and constructed wetlands (Ruiz-Rueda et al., 2007; Sims et al., 2012b), as well as characterization of soil bacterial community composition in natural (Yu et al., 2012; Peralta et al., 2013) and constructed wetlands (Li et al., 2010; Arroyo et al., 2013). Moreover, information about bacterial community shifts in relation to environmental factors such as soil and water properties has been recently published (Hartman et al., 2008; Peralta et al., 2013; Ansola

P. Arroyo et al. / Science of the Total Environment 506–507 (2015) 380–390

et al., 2014). Among these properties, soil pH represents the strongest known predictor of bacterial community composition and diversity in surface soils (Bartram et al., 2014). Despite the importance of increasing information about soil bacterial communities, there are still uncertainties concerning the relationship between bacterial diversity and wetland ecosystem functions. Bacterial diversity can be described not only in terms of numbers of entities (taxa or OTUs) and the evenness of their distribution, but in relation with functional types defined as a set of taxa that have similar effects on a specific ecosystem process or similar responses to environmental conditions (Hooper et al., 2005). In this context, some studies about bacterial functional diversity in wetlands have been performed, mainly through the sole-carbon-source utilization profiles using the community-level physiological profiling method (Osem et al., 2007; Deng et al., 2011), assessment of extracellular enzyme activities (Wobus et al., 2003), and potential respiration (Truu et al., 2005). Nevertheless, the assignment of potential metabolic groups from 16S rRNA taxonomic classification has not been reported yet. In a previous survey (Ansola et al., 2014) a pyrosequencing-based approach was used to characterize soil bacterial community structure and composition, comparing a natural and a constructed wetland. The current study doubles the number of wetlands, and defines the following objectives (i) to test the observed influence of wetland type in the structure and composition of bacterial communities, (ii) to evaluate the previous results regarding differences in bacterial community diversity between natural and constructed wetlands, and (iii) to explore the relationships between bacterial communities, water and soil wetland properties.

381

with S. atrocinerea (362.5 m2) (BCX). Further details of the Bustillo de Cea site are available in Ansola et al. (2014).

2.2. Soil sampling and physicochemical analyses Samples were collected as a continuation of a previous study (Ansola et al., 2014). Wetland soil was sampled three times in summer and winter for soil characterization, and once in summer and winter for bacterial community characterization. Samples were collected using a push core sampler (Ø 5.3 cm, 100 cm length). At each wetland, soil was sampled from the top layer (0–5 cm) of three different environments: the lagoon zone, the area with T. latifolia and the area with S. atrocinerea. Root zones were selected in vegetated environments. Three replicates were taken for each sample. The redox potential was measured in situ in each soil using a multiparameter probe (PCE-228-R Redox meter). Each measurement was repeated three times for each sampling point to ensure reliability. At the laboratory, all three replicates were manually mixed and homogenized for each sample. Any visible root or plant material was removed prior to homogenization. Once mixed, a subsample was transferred to a 10 mL tube for bacterial community analysis, and the remainder was used for soil characterization. Soils were air-dried and homogenized, and large constituents (e.g., plant material and rocks) removed prior to soil organic matter (SOM) and pH measurement. SOM (%) was measured using the weight-loss-on-ignition method (Wilson and Sander, 1996). For pH determination, 5 g of each air-dried soil sample was manually mixed with 25 mL of deionized water, mixed manually and allowed to settle for 10 min prior to measurement (Thomas, 1986).

2. Materials and methods 2.1. Site descriptions Four wetlands with similar plant species and morphological characteristics were selected to represent a range of wetland types including natural, disturbed and artificial (man-made) conditions. The wetlands were located in two sites (Cubillas de los Oteros and Bustillo de Cea) 50 km away from each other in northern Leon, NW Spain. A natural and a constructed wetland were selected at the Cubillas de los Oteros site, an intensive agricultural area exposed to widespread anthropogenic impacts. The morphology of the natural wetland includes a lagoon zone (2600 m2) (ANL) partially surrounded by an area dominated by Typha latifolia (1200 m2) (ANT) and another dominated by Salix atrocinerea (1000 m2) (ANX). The constructed wetland treats the municipal wastewater from Cubillas de los Oteros (150 inhabitants), was designed as a Hierarchical Mosaic of Artificial Ecosystems (HMAE®), and is located 1 km away from the natural wetland. The system is composed of a lagoon 1.6 m depth (1073 m2) (ACL), followed by a free water flow constructed wetland unit planted with T. latifolia (195 m2) (ACT), and a horizontal subsurface flow constructed wetland unit planted with S. atrocinerea (585 m2) (ACX). A natural endorheic wetland and a constructed wetland were chosen at the Bustillo de Cea site. The natural wetland includes a lagoon zone (12,000 m2) (BNL) partially surrounded by an area dominated by T. latifolia (680 m2) (BNT), and another area dominated by S. atrocinerea (530 m2) (BNX). The constructed wetland treats the municipal wastewater from Bustillo de Cea (200 inhabitants) and is located 6 km away from the natural wetland. The system is composed of three units; a lagoon of up to 2 m depth at the inlet and 1.5 m depth at the outlet (230 m2) (BCL), a free water flow constructed wetland planted with T. latifolia (210 m2) (BCT), and a last unit divided into two areas: the first one operated with free water flow and planted with Iris pseudacorus (87.5 m2), and the second one operated with horizontal subsurface flow and planted

2.3. Water sampling and physicochemical analyses Water samples were collected using a swing sampler with a replaceable bottle (1000 mL) at the same time and locations as constructed wetland soil samples. Water samples were stored in sterile plastic bottles. In situ measurements of pH, conductivity, redox potential, temperature and dissolved oxygen (DO) were conducted using a field multiparameter instrument (YSI 556 MPS). Measurements were repeated three times at each site to ensure reliability. All water samples were transferred immediately to the lab and stored at 4 °C before analysis. Water samples were tested for nutrients as total Kjeldahl nitrogen (TKN), ammonium nitrogen (NH+ 4 -N), and total phosphorus (TP); for organic matter as biological and chemical oxygen demand (BOD5 and COD, respectively), and for solids as total suspended solids (TSS). All the analyses were performed according to the protocols included in the standard methods for water and wastewater (APHA, 2005). 2.4. DNA extraction, PCR and pyrosequencing Total bacterial community DNA was isolated from 0.25 g of soil per sample using a Power Soil DNA isolation kit (MoBio Laboratories, Inc., Carlsbad, CA, USA) and following the manufacturer's protocols. Bacterial 16S ribosomal DNA fragments, V4 region, were amplified by PCR. Twelve different barcoded forward primers were composed of sequencing adaptor A of Roche 454 pyrosequencing. Details of primers used and 30 μL PCR reaction parameters are further described by Ansola et al. (2014). Three PCR products per sample were pooled and purified with the Agencourt AMPure XP System (Beckman Coulter, Inc., Brea, CA, USA) according to the manufacturer's instructions. Quantification of purified PCR product was performed using PicoGreen (Invitrogen, Carlsbad, CA, USA). Amplicons were subjected to pyrosequencing with a Roche GS Flx system using vendor-specified chemicals.

382 Table 1 Winter and summer averaged water quality monitoring data (mean ± SD) of the studied wetlands. Sampling and analyses were performed according to standard methods (APHA, 2005). Number of samplings: 3. Letters indicate: Geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; wetland type: C = constructed wetland, N = natural wetland; environment: L = lagoon zone, T = zone with T. latifolia, X = zone with S. atrocinerea; Season: S = summer, W = winter. Cubillas de los Oteros (A) Typha latifolia (T)

ANLS

ANLW

ACLS

Temperature (°C) Conductivity (μS cm−1) pH DO (mg L−1) Redox (mV) BOD5 (mg O2 L−1) COD (mg O2 L−1) TKN (mg N L−1) −1 NH+ ) 4 (mg N L TP (mg P L−1) −1 TSS (mg L )

22.2 ± 2.1 596.0 ± 89.1 7.6 ± 0.5 2.5 ± 1.9 −24 ± 93 b1.0 7.0 ± 6.0 b1.00 0.07 ± 0.04 0.55 ± 0.64 8.5 ± 4.9

7.3 ± 4.5 740.0 ± 7.1 7.8 ± 0.2 1.5 ± 0.1 −60 ± 20 b1.0 13.0 ± 2.5 b1.00 0.05 ± 0.05 0.91 ± 0.17 16.0 ± 8.5

22.2 606.0 6.9 1.4 −111 33.0 90.1 15.27 9.05 2.58 46.5

ACLW ± ± ± ± ± ± ± ± ± ± ±

0.6 56.6 1.4 0.9 21 9.9 7.7 2.16 1.32 0.23 9.2

17.2 644.5 6.8 1.4 −104 12.5 31.5 12.76 8.42 1.87 20.5

± ± ± ± ± ± ± ± ± ± ±

2.0 72.8 0.1 0.7 3 3.5 8.6 5.64 4.70 0.34 0.7

S. atrocinerea (X)

ANTS

ANTW

ACTS

18.2 ± 5.2 768.5 ± 95.5 7.7 ± 0.4 0.4 ± 0.3 −190 ± 27 b1.0 9.9 ± 7.0 b1.00 0.05 ± 0.05 0.65 ± 0.41 9.5 ± 12.0

7.6 ± 4.7 764.5 ± 9.2 7.5 ± 0.1 1.4 ± 0.7 −52 ± 56 b1.0 14.1 ± 6.4 b1.00 0.09 ± 0.02 0.96 ± 0.18 35.0 ± 21.2

18.5 620.0 6.5 1.0 −217 27.5 71.5 13.10 6.91 2.51 39.0

ACTW ± ± ± ± ± ± ± ± ± ± ±

1.3 28.3 1.3 0.3 20 10.6 14.5 2.42 2.26 0.11 15.6

14.5 636.0 6.8 1.2 −212 7.5 12.8 9.13 6.22 1.59 31.5

ACXS ± ± ± ± ± ± ± ± ± ± ±

3.5 5.7 0.9 0.1 28 3.5 0.7 5.29 4.54 0.39 26.2

18.4 614.0 6.6 1.2 −31 13.5 44.1 7.90 5.01 1.83 7.0

ACXW ± ± ± ± ± ± ± ± ± ± ±

0.6 19.8 1.3 0.4 69 2.1 2.9 2.29 1.01 0.54 4.2

14.8 626.0 6.8 0.8 −74 5.0 7.3 5.11 3.55 1.12 8.0

± ± ± ± ± ± ± ± ± ± ±

4.2 35.4 1.1 0.1 8 0.1 2.8 1.56 0.81 0.13 2.8

Bustillo de Cea (B) Lagoon (L)

Typha latifolia (T)

Parameter

BNLS

BNLW

Temperature (°C) Conductivity (μS cm−1) pH DO (mg L−1) Redox (mV) BOD5 (mg O2 L−1) COD (mg O2 L−1) TKN (mg N L−1) −1 NH+ ) 4 (mg N L TP (mg P L−1) TSS (mg L−1)

22.3 ± 1.2 158.0 ± 25.5 8.2 ± 0.4 6.8 ± 0.5 144 ± 12 b1.0 5.2 ± 1.0 b1.00 0.05 ± 0.01 0.02 ± 0.02 5.0 ± 1.4

10.1 ± 4.2 252.5 ± 9.2 8.4 ± 0.1 7.2 ± 0.6 176 ± 107 b1.0 4.1 ± 0.2 b1.00 0.04 ± 0.02 b0.01 8.5 ± 4.9

BCLS 16.2 810.5 6.8 2.9 −70 58.0 138.8 23.14 18.20 2.86 148.5

BCLW ± ± ± ± ± ± ± ± ± ± ±

4.8 72.8 0.5 0.7 25 2.8 21.4 0.04 1.01 0.17 44.5

14.5 732.0 7.7 1.5 −100 64.0 144.3 25.48 16.31 2.32 130.0

± ± ± ± ± ± ± ± ± ± ±

8.6 192.3 0.2 0.3 32 31.1 95.7 22.90 19.45 1.18 14.1

S. atrocinerea (X)

BNTS

BNTW

22.7 ± 2.1 165.0 ± 28.3 8.0 ± 0.8 6.7 ± 1.1 101 ± 69 b1.0 3.4 ± 1.3 b1.00 b0.04 b0.01 7.5 ± 2.1

9.6 ± 3.7 256.0 ± 21.2 8.2 ± 0.1 6.3 ± 0.1 37 ± 44 b1.0 4.7 ± 2.2 b1.00 0.07 ± 0.01 b0.01 8.5 ± 10.6

BCTS 14.4 865.0 7.3 2.9 −140 40.0 139.8 22.26 18.08 2.43 61.0

± ± ± ± ± ± ± ± ± ± ±

BCTW 1.1 168.3 1.1 3.1 63 2.8 30.0 0.11 4.16 0.13 5.7

12.5 768.0 7.2 1.5 −167 33.0 135.7 25.30 18.41 1.91 100.0

BCXS ± ± ± ± ± ± ± ± ± ± ±

5.5 332.3 0.2 1.4 36 9.9 52.5 25.51 24.20 0.12 14.1

10.5 603.5 6.3 3.9 73 10.5 82.3 12.27 6.89 0.67 12.5

BCXW ± ± ± ± ± ± ± ± ± ± ±

3.0 2.1 0.3 2.5 64 13.4 39.4 2.03 1.59 0.20 7.8

11.1 462.5 7.6 4.1 76 8.0 22.2 10.60 4.47 1.34 30.0

± ± ± ± ± ± ± ± ± ± ±

4.0 259.5 0.2 0.3 150 2.7 6.1 7.74 0.67 0.89 28.3

P. Arroyo et al. / Science of the Total Environment 506–507 (2015) 380–390

Lagoon (L) Parameter

6.7 ± 0.1 14.8 ± 1.4 −176 ± 22

BCXW BCXS

6.5 ± 0.4 12.2 ± 0.8 −129 ± 25 5.9 ± 0.1 7.8 ± 0.4 −91 ± 29

BNXW BNXS

6.1 ± 1.1 5.0 ± 0.1 −121 ± 2 6.3 ± 0.2 30.6 ± 1.6 −212 ± 47

BCTW BCTS

6.4 ± 0.2 28.9 ± 0.8 − 4±8 6.0 ± 0.2 25.7 ± 3.0 −102 ± 7

BNTW BNTS

5.9 ± 0.4 22.8 ± 4.3 −104 ± 8 6.3 ± 0.4 24.3 ± 1.4 −181 ± 15

BCLW BCLS BNLS

6.8 ± 0.8 1.2 ± 0.4 −131 ± 30 pH SOM (%) Redox (mV)

BNLW

6.2 ± 0.5 27.7 ± 1.8 −170. ± 29

Salix atrocinerea (X) Typha latifolia (T) Lagoon (L)

Bustillo de Cea (B)

6.7 ± 0.5 1.2 ± 0.3 −138 ± 11

7.1 ± 0.1 5.1 ± 0.3 −79 ± 27 7.0 ± 0.1 7.9 ± 0.5 −127 ± 72 7.2 ± 0.2 6.1 ± 4.2 −27 ± 16 7.3 ± 0.2 4.3 ± 0.3 −99 ± 112 6.9 ± 0.6 21.3 ± 3.4 −81 ± 31 6.0 ± 0.1 21.6 ± 3.0 −135 ± 64 6.7 ± 0.7 20.2 ± 1.2 −22 ± 8 6.8 ± 0.8 18.4 ± 3.6 −168 ± 23 7.5 ± 0.2 22.6 ± 3.2 −112 ± 36

ACXW ACXS ANXW ANXS

Salix atrocinerea (X)

ACTW ACTS ANTW ANTS

Typha latifolia (T)

ACLW ACLS

8.3 ± 0.1 20.4 ± 1.4 −85 ± 52 7.1 ± 0.9 8.4 ± 9.2 −65 ± 33 7.8 ± 0.6 10.3 ± 1.6 −68 ± 76

Parameter

A total of 214,805 bacterial sequences were obtained from the analysis of the 24 samples. The number of reads per sample ranged from 7108 to 12,677.

pH SOM (%) Redox (mV)

3.2. Phylum-level taxonomic distribution

ANLW

The water quality parameters for each wetland, environment and season are summarized in Table 1. COD, BOD5, TSS, TKN, NH+ 4 -N, and TP showed an increasing pollution gradient from natural to constructed wetlands, with the differences between the wetlands being statistically significant (p b 0.05). The natural wetland in Bustillo de Cea (BN) presented the lowest organic matter, solid, and nutrient concentration values, followed by the natural (AN) and constructed wetlands (AC) located in Cubillas de los Oteros. The highest organic matter, nutrient and suspended solid concentrations were measured in the constructed wetland in Bustillo de Cea (BC). In both constructed wetlands, a decrease in OM, TSS and nutrient concentrations was observed through the stages of the treatment systems. Regarding the seasonal factor (summer or winter), no significant differences (p N 0.05) were observed among the environments. Soil parameters are shown in Table 2. Overall, soil samples taken in natural wetlands presented lower SOM than those from constructed wetlands, although statistical significance was only observed between natural wetlands and the constructed wetland in Bustillo de Cea (BC) (p b 0.05). The reducing conditions were higher in the constructed wetlands when compared to the natural wetland soils with significant differences distinguishing the constructed wetland in Bustillo de Cea (BC) from a group formed by the other wetlands (p b 0.05). Soils sampled in the natural and constructed wetlands in Bustillo de Cea (BN and BC) presented a significantly lower pH than those sampled in Cubillas de los Oteros (AN and AC) (p b 0.05).

ANLS

3.1. Water and soil physicochemistry

Lagoon (L)

3. Results and discussion

383

Parameter

Short and low-quality sequence reads derived from 454 Flx sequencing were screened and removed using Mothur 1.29 software (Schloss et al., 2009). Taxonomic assignment of sequence reads was obtained using the Naïve Bayesian rRNA classifier tool (Wang et al., 2007) of the Ribosomal Database Project (RDP). Unique sequences were determined with Mothur 1.29 and aligned using the fast, secondarystructure aware Infernal aligner (Nawrocki et al., 2009) from the RDP web site (http://rdp.cme.msu.edu/index.jsp). A hierarchical cluster analysis was performed with the complete linkage clustering tool from RDP. Groups of related DNA sequences were assigned to operational taxonomic units (OTUs) defined at a genetic distance of 5%. α-Diversity (Chao 1 and Shannon index), β-diversity (qualitative Chao dissimilarity and quantitative Morisita-Horn index), and multivariate analyses of community structure and diversity patterns (correspondence analyses, CA; canonical correspondence analyses, CCA; Mantel test; and selection of variables in regression models through the Akaike Information Criterion) were conducted using Mothur 1.29 and the Vegan package (Oksanen et al., 2010) in R software (R Development Core Team, 2011). The Unifrac metric (Lozupone et al., 2006) was estimated using Qiime software (Caporaso et al., 2010). Other basic statistical tests (one-factor Anova; Pearson correlation; and Euclidean distances) were also performed with R software. Significance differences were defined at p b 0.05. Through an extensive taxonomy bibliographic research (references not included), each OTU has been assigned to a specific metabolic function of wetland soils (nitrogen, sulfur and carbon cycles).

Cubillas de los Oteros (A)

2.5. Soil bacterial community analysis

Table 2 Soil physicochemistry (mean ± SD) in natural (i.e., BN and AN) and constructed wetlands (i.e., AC and BC). Number of samplings: 3. Letters indicate: geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; wetland type: C = constructed wetland, N = natural wetland; environment: L = lagoon zone, T = zone with T. latifolia, X = zone with S. atrocinerea; Season: S = summer, W = winter.

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Table 3 Normalized read abundance of the most frequent bacterial phyla within the different bacterial communities. Cubillas de los Oteros (A) Lagoon (L)

Typha latifolia (T)

Salix atrocinerea (X)

Phyla

ANLS

ANLW

ACLS

ACLW

ANTS

ANTW

ACTS

ACTW

ANXS

ANXW

ACXS

ACXW

Proteobacteria Alphaproteobacteria Betaproteobacteria Gammaproteobacteria Deltaproteobacteria Epsilonproteobacteria Verrucomicrobia Chloroflexi Acidobacteria Firmicutes Bacteroidetes Planctomycetes

2596 296 679 750 642 53 1022 892 235 170 257 26

2754 526 649 720 646 25 545 1104 220 254 154 72

2284 145 540 433 641 192 713 557 276 662 89 5

2038 203 468 293 726 6 555 846 297 657 94 5

3076 414 537 684 567 756 1166 843 350 224 70 28

3412 426 768 965 855 178 708 661 289 319 71 50

3131 318 956 875 555 291 1221 728 353 244 69 30

2788 482 633 759 547 194 1218 520 674 350 64 58

2736 677 456 821 532 5 669 718 918 163 102 106

3100 686 509 874 618 150 675 588 631 277 123 139

2259 901 352 588 300 0 591 144 711 265 288 651

2143 602 376 841 168 2 668 145 558 279 638 689

Bustillo de Cea (B) Lagoon (L)

Typha latifolia (T)

Salix atrocinerea (X)

Phyla

BNLS

BNLW

BCLS

BCLW

BNTS

BNTW

BCTS

BCTW

BNXS

BNXW

BCXS

BCXW

Proteobacteria Alphaproteobacteria Betaproteobacteria Gammaproteobacteria Deltaproteobacteria Epsilonproteobacteria Verrucomicrobia Chloroflexi Acidobacteria Firmicutes Bacteroidetes Planctomycetes

1832 114 265 404 802 0 991 1302 463 326 102 37

2039 109 283 487 801 1 853 1448 276 251 132 27

2285 92 511 235 728 461 317 346 208 1130 116 7

2168 141 364 526 698 163 426 472 282 829 353 6

2837 552 674 968 433 40 1791 390 478 104 57 24

2744 221 474 693 849 272 1178 998 554 220 28 21

3478 185 465 696 608 1301 542 506 289 378 368 23

4235 627 1006 1549 223 741 756 84 111 126 1008 32

2177 502 266 308 532 439 531 1530 701 229 51 18

2732 862 498 793 406 48 1234 852 551 161 97 84

4082 480 689 1225 474 1091 549 380 313 335 37 28

3916 1082 610 2009 111 2 1248 27 719 66 63 102

Letters indicate: geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; wetland type: C = constructed wetland, N = natural wetland; environment: L = lagoon zone, T = zone with T. latifolia, X = zone with S. atrocinerea; Season: S = summer, W = winter.

The different communities showed a number of changes in phyla but were generally dominated by Proteobacteria, Verrucomicrobia, Chloroflexi, and Acidobacteria, comprising 68% of all the sampled sequences. The wide distribution of these phyla in natural (Wang et al., 2012; Shange et al., 2013; Peralta et al., 2013; Ligi et al., 2013) and constructed wetlands (Gorra et al., 2007; Ahn et al., 2007) has been well documented. Less abundant bacteria (1–5%) were Firmicutes, Bacteroidetes and Planctomycetes, followed by rare bacteria (b 0.75%) including Cyanobacteria, OD1, Chlorobi, Gemmatimonadetes, Actinobacteria, WS3, Spirochaetes, Armatimonadetes, BRC1, Chlamydiae, TM7, Synergistetes, SR1 Nitrospira, Fusobacteria, Deinococcus, Tenericutes, OP11, Fibrobacteres, Lentisphaerae, Elusimicrobia, and Deferribacteres. Proteobacteria dominated the community composition of all soils (Table 3). The abundance of this phylum was particularly high in the vegetated environments of the constructed wetland in Bustillo de Cea (BC), from 50% to 61% in the area with T. latifolia in summer and winter (BCTS and BCTW, respectively) and from 56% to 58% in the area with S. atrocinerea (BCXW and BCXS, respectively). Within the phyla, the analysis revealed that Deltaproteobacteria were mainly present in the lagoon, Gammaproteobacteria in the T. latifolia and Alphaproteobacteria in S. atrocinerea environments. Earlier studies have described the dominance of Beta- and Deltaproteobacteria (Röske et al., 2012), and Deltaand Gammaproteobacteria (Wang et al., 2012) in freshwater sediments, while a study by Peralta et al. (2013) showed the dominance of Alphaproteobacteria, followed by Delta- and Betaproteobacteria in created and natural wetland soils. In constructed wetlands, Adrados et al. (2014) have reported the dominance of Gammaproteobacteria and Bacteroidetes in two different constructed wetlands operating in Denmark, whereas Arroyo et al. (2013) showed differences among Proteobacteria class abundances linked to the design of the constructed wetland and plant species.

3.3. Linking wetland properties and bacterial community profiles To study the association between wetland properties and bacterial community composition, the number of phylotypes in each soil sample has been defined as the number of operational taxonomic units (OTUs) at a genetic distance of 5%.

3.3.1. Multi-factorial approach Multivariate analyses of bacterial OTUs were used to evaluate the relationships between wetland characteristics and bacterial community composition in order to determine whether patterns in bacterial OTUs distribution could show shifts in community composition as a function of four factors: geographic origin (Cubillas de los Oteros, A; Bustillo de Cea, B); environment (lagoon, L; Typha, T; Salix, X), season (summer, S; winter, W), and wetland type (constructed, C; natural, N). Results obtained through a unimodal method of unconstrained correspondence analysis ordination (CA) are displayed in spider plots (Fig. 1). The first two axes accounted for 30% of the total variation observed in the bacterial community structure. Each bacterial community in the multivariate space is connected to the group centroid with segments to visualize the relationship between community ordination and factors. From this ordination, a detailed analysis indicated that bacterial communities were separated along the first axis with a high level of significance (p b 0.0001, one-way Anova) according to the environment factor (lagoon, Typha and Salix) (Fig. 2A). The second axis discriminated significantly different (p b 0.0001) bacterial communities according to the wetland type (constructed or natural). It also separated the bacterial communities with respect to the geographic origin (Bustillo de Cea or Cubillas de los Oteros), although no significant differences were observed. It is also remarkable

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Fig. 1. Unconstrained correspondence analysis ordination (CA) of bacterial communities. The spider plots present the centroids of the different qualitative study factors and segments of each bacterial community in the multivariate space of the correspondence analysis. Letters indicate: Geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; wetland type: C = constructed wetland, N = natural wetland; environment: L = lagoon zone, T = zone with T. latifolia, X = zone with S. atrocinerea; Season: S = summer, W = winter.

c

c

1.0

bc

B

0.0

CA 2

0.5

-1.0

-1.0

-0.5

-0.5

0.0

CA 1

1.0

0.5

1.5

A

Lagoon

Unvegetated Environment

Typha

Salix

Vegetated Environment

Bustillo Cea (BC)

Cubillas Oteros (AC)

Constructed Wetland (C)

Cubillas Oteros (AN)

Bustillo Cea (BN)

Natural Wetland (N)

Fig. 2. A. Bacterial communities ordination against the axis CA 1 (correspondence analysis) across the environment type factor (lagoon, Typha, Salix) (box whisker plots). B. Bacterial communities ordination against the axis CA 2 (correspondence analysis) across the studied wetlands (box whisker plots). Boxes show the upper (75%) and the lower (25%) percentiles of the data. Whiskers indicate the highest and the lowest values. Letters indicate: Geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; Wetland type: C = constructed wetland, N = natural wetland.

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that neither the first nor the second axis distinguished bacterial communities by sampling season. However, previous surveys on seasonal dynamics in alpine and agricultural soils reported composition shifts at the phylum level in the course of the year (Lipson, 2007; Kuffner et al., 2012). Since water quality parameters showed significant differences among wetlands, it has been considered a combined factor composed by the geographic origin and the wetland type. A one-way Anova with a post hoc analysis (HSD Tukey) defined three significantly different groups of wetlands (p b 0.001) (Fig. 2B). The first group was formed by bacterial communities sampled in the Bustillo de Cea constructed wetland. The second group was formed by the wetlands located in Cubillas de los Oteros. Finally, communities sampled in both natural wetlands formed a third group. As explained previously, the area of Cubillas de los Oteros is impacted by an intensive agriculture activity and water quality in this natural wetland presented higher nutrient and organic matter concentration values than expected. Moreover, Cubillas de los Oteros is a small locality (150 inhabitants) which constructed wetland treats a wastewater characterized by low organic and nutrient concentration values. To find the “best possible” relationship between OTU composition and environment, a permutation test for CCA under reduced model was performed. The obtained model showed that the geographic origin (AB factor), the wetland (CN), and the environment type (LTX) contributed to explain the OTU composition and distribution among bacterial communities (p b 0.01), although no contribution of the seasonal factor (SW) was identified. As a result, this multifactorial model (OTUs ~ LTX + CN + AB) is a significant representation of the response data (OTU composition and distribution) (p b 0.005), in accordance with the multivariate analysis results presented above. The influence of plant species on bacterial communities in

constructed wetlands has been reported by other studies (Calheiros et al., 2009; Arroyo et al., 2013). As far as we know, this is the first study comparing bacterial communities of closely located natural and constructed wetlands with similar morphological characteristics and plant species. 3.3.2. Quantitative approach Since qualitative results showed significant differences among wetlands, a quantitative analysis has been performed in order to link bacterial community composition with water and soil wetland parameters. Significant associations between soil bacterial community structures and wetland physicochemical properties were obtained. The robustness of the results was confirmed by three different tests (Table 4): (i) Mantel test between OTU dissimilarity matrix and Euclidean distances of environmental variables, (ii) a multivariate analysis of variance performed through Adonis function in R; and (iii) a permutation test for a constrained ordination analysis (CCA). The results obtained through the different tests were quite similar, with SOM, TKN, NH+ 4 -N, and COD showing the highest correlations with all β-diversity indexes. Nevertheless, the Unifrac metric, which provides a phylogenetic distance between communities, detected the lowest number of correlations with physicochemical parameters, whereas the permutation test and the multivariate analysis of variance (based on the Morisita–Horn index) showed a higher number of relationships between bacterial communities and parameters. In the present study, bacterial structure was clearly linked to nitrogen concentrations and SOM, similar to the results obtained by Ahn and Peralta (2009) who reported effects of soil carbon to nitrogen ratio on bacterial community structure in four created mitigation wetland sites. However, the obtained results differed from previous studies where soil pH was associated with changes in bacterial community

Table 4 Multivariate analysis of bacterial community structure. The three statistics: r, Pearson product–moment correlation coefficient, Mantel test; F model of Adonis (Vegan) function and F statistic of permutation test; and its probabilities are presented. Mantel test, r coefficient (p)

Multivariate analysis of variance, F model (p)

Environmental variables Soil

Redox pH SOM

Water

Tª Cond Redox DO pH TSS TP TKN NH+ 4 -N COD BOD5

⁎ P b 0.05; ⁎⁎ P b 0.01; ⁎⁎⁎ P b 0.001;

Permutation test, F (p)

UniFrac

Morisita–Horn

Chao

Morisita–Horn

Chao

CCA

0.0712 (0.270) −0.0538 (0.630) 0.2513 (0.004)⁎⁎ −0.1781 (0.978) −0.0116 (0.499) −0.0617 (0.676) −0.0133 (0.480) 0.0449 (0.317) 0.2104 (0.115) 0.0321 (0.374) 0.2548 (0.045))⁎

0.0689 (0.233) 0.0412 (0.340) 0.2362 (0.002)⁎⁎ −0.1172 (0.927) 0.1050 (0.177) 0.0086 (0.452) 0.0361 (0.339) 0.0770 (0.196) 0.2877 (0.013)⁎

2.7837 (0.028)⁎

1.2013 (0.360) 0.6477(0.680)

1.5842 (0.182) 1.2392 (0.28) 2.3159 (0.052) 4.0407 (0.009)⁎⁎

0.9714 (0.443) 1.1699 (0.332) 7.0543 (0.007)⁎⁎ 0.2756 (0.734) 3.3975 (0.063) 1.6848 (0.210) 2.3737 (0.140) 3.4664 (0.061) 5.8260 (0.009)⁎⁎

0.1376 (0.053) 0.3545 (0.002)⁎⁎

−0.0346 (0.620) −0.0131 (0.496) 0.2548 (0.004)⁎⁎ −0.1794 (0.977) 0.0888 (0.213) 0.0514 (0.319) 0.0914 (0.202) 0.1492 (0.072) 0.2583 (0.056) 0.1616 (0.035)⁎ 0.2461 (0.032)⁎

3.1212 (0.016)⁎ 5.1228 (0.003)⁎⁎

3.0268 (0.074) 5.3492 (0.009)⁎⁎

3.1688 (0.015)⁎ 2.3706 (0.028)⁎ 3.3756 (0.013)⁎

0.2436 (0.025))⁎ 0.2387 (0.040))⁎ 0.1588 (0.133)

0.3526 (0.002)⁎⁎ 0.3679 (0.002)⁎⁎ 0.3203 (0.009)⁎⁎

0.2493 (0.018)⁎ 0.2622 (0.020)⁎ 0.2656 (0.036)⁎

5.1635 (0.001)⁎⁎⁎ 5.6942 (0.002)⁎⁎ 4.5925 (0.002)⁎⁎

4.9824 (0.026)⁎ 6.5001 (0.006)⁎⁎ 6.0903 (0.016)⁎

3.2063 (0.010)⁎⁎ 3.1957 (0.01)⁎⁎ 2.4195 (0.015)⁎

2.1099 (0.082) 4.5284 (0.004)⁎⁎ 0.7099 (0.609) 2.7571 (0.029)⁎

2.9007 (0.005)⁎⁎ 0.5417 (0.770) 2.2149 (0.040)⁎ 0.8173 (0.400) 1.5685 (0.120) 2.0971 (0.049)⁎

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composition in a range of soils (Hartman et al., 2008; Ahn and Peralta, 2009; Lauber et al., 2009; Peralta et al., 2013). In this study, only the permutation test detected a significant “weak” association (p = 0.049) between soil bacterial community structures and pH. Ligi et al. (Ligi et al., 2013) also observed a “weak” association with pH and a strong association with other parameters mainly related to nitrogen concentrations. Nevertheless, due to the fact that a constrained CCA using all environmental variables explained 82.5% of the variance, other parameters should also be considered. In this context, parameters such as food web interactions are also likely to have an impact on bacterial community composition (Kent et al., 2004). In addition, stochastic effects should be taken into consideration when analyzing wetlands (Kadlec, 1997), since there is increasing evidence that dispersal limitations may have a more important role in structuring microbial communities than previously thought (Ferrenberg et al., 2013).

3.4. Analysis of metabolic groups defined from the taxonomic classification Reads were assigned to metabolic groups according to the RDP taxonomic classification and the bibliographic taxa description. Four metabolic groups were selected: sulfate-reducing, methanotrophic, denitrifying and nitrifying bacteria groups. The relationships between the wetland characteristics and these specific metabolic groups have been assessed. Sulfate-reducing bacteria are anaerobic bacteria that participate in both the sulfur and carbon cycles. They form a large polyphyletic guild, with species belonging to at least five bacterial phyla and two archaeal phyla (Stahl et al., 2007). Among them, Deltaproteobacteria members of the families Desulfobacteraceae and Syntrophobacteraceae, and bacteria related to Desulfobacca acetoxidans (Syntrophaceae) have been regularly detected in wetland ecosystems (Pester et al., 2012). In this study, sulfate-reducing bacteria in lagoon environments were

a

a

b

0

100 200 300 400 500

Number of sequences sulphate-reducing bacteria

387

10

B

0

200

400

Number of sequences (Type II)

20

A

0

Number of sequences (Type I)

Fig. 3. Number of sequences affiliated with sulfate-reducing bacteria. Lower case letters indicate significant differences among groups. Capital letters indicate: Geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; Wetland type: C = constructed wetland, N = natural wetland; environment: L = lagoon zone, T = zone with T. latifolia, X = zone with S. atrocinerea; Season: S = summer, W = winter.

AC

AN

BC

AC

BN

AN

BC

BN

80 60 40 20 0

Number of sequences nitrifying bacteria

Fig. 4. Number of sequences affiliated with methanotrophic bacteria: type I and type II. Capital letters indicate: Geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; wetland type: C = constructed wetland, N = natural wetland.

A

B

C

N

L

T

X

S

W

Fig. 5. Number of sequences affiliated with nitrifying bacteria. Lower case letters indicate significant differences among groups. Capital letters indicate: Geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; wetland type: C = constructed wetland, N = natural wetland; environment: L = lagoon zone, T = zone with T. latifolia, X = zone with S. atrocinerea; Season: S = summer, W = winter.

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a

b

C

N

400 300 200 100

Number of sequences denitrifying bacteria

500

388

A

B

L

T

X

S

W

Fig. 6. Number of sequences affiliated with denitrifying bacteria. Lower case letters indicate significant differences among groups. Capital letters indicate: Geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; wetland type: C = constructed wetland, N = natural wetland; environment: L = lagoon zone, T = zone with T. latifolia, X = zone with S. atrocinerea; Season: S = summer, W = winter.

significantly more abundant than in Salix environments (p = 0.03, HSD Tukey test) (Fig. 3). When considering other factors, no significant differences were observed. Desulfobacteraceae bacteria were mainly found in lagoon environments (with relative abundances ranging between 2.6 in the Bustillo de Cea and 0.8% in the Cubillas de los Oteros constructed wetlands). Syntrophobacteraceae bacteria were particularly less abundant than Desulfobacteraceae, and were largely detected in vegetated environments ranging between 0.8% (BNXS) and 0.2% (ANTS). Methanotrophs can be taxonomically divided into Proteobacteria and Verrucomicrobia phyla. Within aerobic Proteobacteria methanotrophs, Methylococcaceae (Gammaproteobacteria class) is often referred to as type I while Methylocystaceae (Alphaproteobacteria class) is referred to as type II methanotrophs. In the present study, differences in methanotroph abundance among bacterial communities were significantly higher in wetlands located in Bustillo de Cea (B) in comparison to those in Cubillas de los Oteros (A) (F = 5.68, p = 0.02), and higher in the winter compared to the summer season (F = 7.01, p = 0.01). The methanotroph community was dominated by Type I species in all wetlands and environments (Figs. 4A and 4B). Type I species tolerance to fluctuations in

environmental conditions (Steenbergh et al., 2010) could explain these results. Moreover, it has been also reported that Type I methanotrophs proliferate under high oxygen and low methane conditions (Hanson and Hanson, 1996) as is the case in the Bustillo de Cea (B) compared to the Cubillas de los Oteros (A) wetlands where greater dissolved oxygen measurements have been registered. Fig. 5 presents the abundance of nitrifying bacteria considering the different factors. Nitrifying bacteria have been reported to have a strong correlation with nitrification activity in natural wetlands (Sims et al., 2012a). Bacteria included in the nitrifying group were more abundant in vegetated than in lagoon environments, which could be explained by the higher oxygen concentration in the plant rhizosphere (Jespersen et al., 1998; Armstrong and Armstrong, 2001). Within the bacteria domain, the ability to oxidize ammonia is restricted to chemolithotrophic ammoniaoxidizing bacteria, commonly belonging to the Beta and Gamma proteobacterial classes. In this context, Nitrosomonas (Beta), Nitrospira (Beta) and Nitrosococcus (Gamma) have been identified in different natural and artificial wetlands (Gorra et al., 2007; Dorador et al., 2008; Ahn and Peralta, 2009; Moin et al., 2009). These genera were mainly present in vegetated environments of constructed wetlands.

Table 5 Shannon diversity measures of bacterial communities estimated using phylum and OTU level identification of multi-tag pyrosequencing fragments. Observed and estimated (Chao 1) richness at a genetic distance of 5%. Cubillas de los Oteros (A) Lagoon (L) Bacterial community Shannon index Phylum level OTU-level Observed richness OTU-level Estimated richness Chao 1 index Low confidence High confidence

ANLS 1.72 6.22

Typha latifolia (T) ANLW 1.76 6.39

ACLS 1.76 6.23

ACLW 1.89 6.23

ANTS 1.56 5.94

ANTW 1.49 6.12

Salix atrocinerea (X) ACTS 1.56 5.91

ACTW 1.71 6.26

ANXS 1.77 6.09

ANXW 1.74 6.35

ACXS 1.84 6.06

ACXW 1.88 6.27

1494

1565

1540

1779

1378

1374

1309

1638

1300

1538

1206

1353

2229.2 2092.9 2396.7

2408.5 2255.1 2596.0

2275.8 2139.1 2443.8

2605.4 2455.9 2787.7

2090.6 1951.7 2263.1

1853.7 1757.6 1974.0

1960.3 1826.5 2128.6

2443.2 2300.3 2617.0

1927.8 1800.1 2088.0

2264.2 2129.2 2430.0

1710.0 1597.5 1854.8

1801.7 1707.5 1921.0

BCXS

BCXW

Bustillo de Cea (B) Lagoon (L) Bacterial community Shannon index Phylum level OTU-level Observed richness OTU-level Estimated richness Chao 1 index Low confidence High confidence

BNLS 1.80 6.26

Typha latifolia (T) BNLW 1.71 6.23

BCLS 1.60 5.84

BCLW 1.83 6.18

BNTS 1.49 6.11

BNTW 1.60 6.16

Salix atrocinerea (X) BCTS 1.54 5.49

BCTW 1.23 5.3

BNXS 1.69 6.03

BNXW 1.63 6.10

1.24 5.33

1.28 5.56

1573

1567

1371

1652

1637

1672

1349

1079

1449

1484

1241

1299

2413.6 2258.8 2603.4

2386.6 2237.4 2569.1

1938.7 1823.9 2082.7

2330.1 2202.1 2487.8

2463.5 2314.8 2644.9

2587.2 2426.3 2782.4

1972.0 1847.9 2126.9

1549.2 1445.1 1682.9

2128.8 1996.7 2292.8

2262.8 2114.8 2445.5

1800.2 1682.9 1948.7

1916.2 1790.7 2073.6

Letters indicate: geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; wetland type: C = constructed wetland, N = natural wetland; environment: L = lagoon zone, T = zone with T. latifolia, X = zone with S. atrocinerea; Season: S = summer, W.

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b

b

6.2

6.4

a

b ANLW ANXW

ACXW ACTW ACLS ACLW

BNLS BNLW

ANLS

BCLW

BNTW BNTS BNXW BNXS

ANTW ANXS

6.0

ACXS

5.8

ACTS

5.6

Shannon index

389

ANTS

BCLS

BCXW

5.4

BCTS

BCXS BCTW

Bustillo de Cea (BC)

Cubillas de los Oteros (AC)

Constructed Wetland (C)

Cubillas de los Oteros (AN)

Bustillo de Cea (BN)

Natural Wetland (N)

Fig. 7. Box plots showing variation among Shannon index diversity values in bacterial communities. Boxes show the upper (75%) and the lower (25%) percentiles of the data. Whiskers indicate the highest and the lowest values. Letters indicate: Geographic origin: A = Cubillas de los Oteros, B = Bustillo de Cea; wetland type: C = constructed wetland, N = natural wetland; environment: L = lagoon zone, T = zone with T. latifolia, X = zone with S. atrocinerea; Season: S = summer, W = winter.

The denitrifying bacteria group was significantly more abundant in constructed than in natural wetlands (F = 13.78, p = 0.001) (Fig. 6). No significant differences were observed among environments. Nevertheless, denitrifying bacteria abundances were higher in the lagoon and Typha environments compared to the Salix environments. The denitrification potential of the bacterial community has been related to bacterial community structure by Ligi et al. (2013), who have also suggested that the abundance of those bacteria possessing denitrification genes responds to the conditions created by the water regime at the site. The most abundant sequences classified as denitrifying bacteria, Rhodanobacter (Gamma) and Steroidobacter (Gamma), were mainly present in both constructed wetlands. In a study conducted as a metaanalysis based on publicly available 16S rRNA gene sequences recovered from wetland soils worldwide, Rhodanobacter was the largest genus in the Gammaproteobacteria class, while Steroidobacter genus represented more than 1.0% of proteobacteria sequences (Lv et al., 2014). 3.5. Diversity analysis When considering the OTU-level diversity, the analysis showed that richness (Chao 1, number of estimated OTUs) ranged from 1549 (BCTW) to 2605 (ACLW) (Table 5). Overall, the bacterial communities in Cubillas de los Oteros wetland soils presented higher α-diversity values (Shannon index), ranging from 6.39 (ANLW) to 5.91 (ACTS), whereas those communities sampled in the constructed wetland located in Bustillo de Cea (BC) showed the lowest diversity values (Table 5). The richness and diversity levels obtained in this study were similar to values reported by Fierer et al. (2012) in soils from two experimental nitrogen gradients, and Will et al. (2010) in grassland soils. However, Peralta et al. (2013) obtained lower values in created and natural wetlands, probably related to acidic soil properties. In a previous study performed in both natural and constructed wetlands in Bustillo de Cea (Ansola et al., 2014), natural wetland communities showed greater diversity compared to that of a constructed weland. However, the phyla-level analysis revealed a different trend in the present study. Overall, the most diverse communities were those sampled in the Cubillas de los Oteros constructed wetland (AC), while bacterial

communities sampled in the Bustillo de Cea constructed wetland (BC) presented the lowest diversity values. The analysis of variance (one-factor Anova) revealed significant differences in OTU diversity between constructed and natural wetlands (p = 0.02); and communities sampled in Bustillo de Cea and Cubillas de los Oteros (p = 0.02). However, there were no significant effects observed due to seasonal and environmental factors. A detailed analysis showed that these differences were mainly due to the relative low diversity measures of bacterial communities in the constructed wetland in Bustillo de Cea (BC) (Fig. 7). Since this wetland (BC) presents higher organic and nutrient concentrations, these results could be related to the water quality characteristics. 3.6. Conclusions In conclusion, significant differences were observed in bacterial community composition and structure (richness and diversity values) in relation to the wetland type (constructed and natural), as well as to the environment (lagoon, Typha and Salix) and geographic locality factors. The seasonal factor was not relevant neither the composition nor the diversity. The lowest diversity values corresponded to the constructed wetland which receives the highest nutrient concentrations. Structure and composition of bacterial communities were significantly associated with three wetland physicochemical parameters (SOM, COD and TKN); nevertheless, other aspects should be also considered to explain variation in community composition. Moreover, the abundances of particular metabolic groups were also related with wetland characteristics. This extensive characterization of soil wetland communities introduces new survey data about wetland parameters and its relationships with diversity and composition of bacterial communities. This knowledge will be useful to better understand the wetland functions and improve constructed wetland operation. Acknowledgments We wish to thank Diputación Provincial de León for the financial support offered during the course of this study. We sincerely want to express

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