Capping material type affects rhizosphere bacteria ... - Springer Link

J Soils Sediments (2017) 17:2516–2523 DOI 10.1007/s11368-017-1696-2

SOILS, SEC 5 • SOIL AND LANDSCAPE ECOLOGY • RESEARCH ARTICLE

Capping material type affects rhizosphere bacteria community structure in the cover soil in oil sands reclamation Bin Ma 1,2 & Xiaopeng Li 1 & Scott X. Chang 1,2

Received: 30 November 2016 / Accepted: 15 March 2017 / Published online: 29 March 2017 # Springer-Verlag Berlin Heidelberg 2017

Abstract Purpose Rhizosphere bacteria play critical roles in soil nutrient cycling and plant growth during land reclamation. However, the impact of the type of capping material, used to provide functions such as preventing salt migration from saline groundwater to the cover soil, on rhizosphere bacterial community is unknown. Materials and methods We examined the influence of two capping materials: overburden (OB), a material excavated from below the top soil from oil sand mines, and tailings sand (TS), in comparison to the no capping layer (NC) control, on the composition, structure, and function of bacterial communities in the Pinus banksiana rhizosphere and bulk soil in the peat-mineral mix (PMM, the cover soil) in a 2-year column study simulating soil reconstruction in land reclamation in the oil sands. The bacterial community was determined through high-throughput sequencing the 16S ribosomal RNA (rRNA) gene amplicons, and the potential functional profiles were predicted from the 16S rRNA gene using PICRUSt. Results and discussion Difference in the relative abundance of operational taxonomic units (OTUs) between the rhizosphere and the bulk soil was lower in the NC and OB than in the TS treatment. Rhizosphere bacterial community structure in the cover soil was different among the NC, OB, and TS treatments. Difference in bacterial community structure Responsible editor: Jizheng He * Scott X. Chang [email protected] 1

Department of Renewable Resources, University of Alberta, Edmonton, AB T6G 2E3, Canada

2

Land Reclamation International Graduate School, University of Alberta, Edmonton, AB T6G 2E3, Canada

between the rhizosphere and bulk soil was driven by soil pH and electric conductivity changes in the OB treatment and by water-soluble organic carbon in the TS treatment. The relative abundance of functional genes for nutrient metabolism in the rhizosphere increased in the TS treatment, but those for environmental adaption increased in the NC and OB treatments. Conclusions We conclude that the type of capping material used affects the structure, composition, and function of rhizosphere bacterial communities in cover soils used in land reclamation, and this has implications for ecosystem reestablishment in the disturbed landscape in the oil sands. Keywords Capping layer . Column experiment . Cover soil . Overburden . Pinus banksiana . Tailings sand

1 Introduction Oil sand mining has impacted approximately 896 km2 of boreal forest in the Athabasca oil sand region in northern Alberta, and government policy and regulation require the reclamation of the disturbed mining area to equivalent land capability or better to that existed before surface mining operations (Jamro et al. 2015). Soil salinity is one of the major issues that can substantially impact the success of oil sand reclamation (Davis et al. 2014). The capping layer, which is a layer of clean material placed between contaminated oil sands and the cover soil, is a barrier between the cover soil and the saline groundwater. The capping strategy used in land reclamation in terms of how the different types of capping material would be placed in vertical configuration in layers and the thickness of each layer usually influences soil salinization (Olatuyi and Leskiw 2014). If not properly managed, salts from a variety of oil sand miningrelated sources can migrate into the rooting zone and influence plant growth in reclaimed soils. The design of capping covers

J Soils Sediments (2017) 17:2516–2523

varies across mine sites, from monolayer covers of peat-mineral soil mix (PMM) to complex multiple-layer designs in which a PMM cover soil is placed over an overburden (OB) or tailings sand (TS) layer. The texture and configuration of the capping layers may affect soil hydraulic properties and salt migration (Li et al. 2013). Adopting an appropriate capping strategy that provides an adequate barrier between salt-affected materials and the rooting zone is one of the approaches that could be used to manage potential soil salinity risks in land reclamation in the oil sands. Rhizosphere processes are critical for salinity tolerance of plants established during oil sand reclamation. Many boreal forest species cannot tolerate salinity, and the growth of roots can be susceptible to salts migrated into the rooting zone. Root growth is an important indicator of the success of land reclamation. Our ability to build suitable soil substrates for root growth will largely determine reclamation success. Roots are highly sensitive to changes in their surrounding environment, and root system responses to stresses such as salinity and drought can be very dynamic and complex in nature (Duan et al. 2015). These responses can be manifested differentially at the cellular, tissue, or organ level (Oburger et al. 2013). Rhizosphere bacteria play important roles in salinity amelioration in rhizosphere processes during oil sand reclamation (Ahad and Pakdel 2013). They are intensely involved in the development of new soils on reclamation sites, e.g., by mobilizing nitrogen via ammonification and nitrification or by the fixation of N2 from the atmosphere (Brunner et al. 2015). The structure and the function of the rhizosphere bacteria community are influenced by root activities, such as root exudates, oxygen release, and nutrient uptake (Reinhold-Hurek et al. 2015). The interactions between plants and soil bacteria influence the building of soil structure and restoration of disturbed ecosystems (Philippot et al. 2013). Accordingly, studying the rhizosphere bacterial community is critical for understanding the response of plants to different types of capping materials used in land reclamation. However, the influence of capping material type on the rhizosphere bacterial communities in oil sand reclamation is poorly understood. This study investigated the impact of two types of capping materials, a fine textured overburden (OB) and a coarse textured tailings sand (TS), under a PMM cover soil on the structure, composition, and function of rhizosphere bacterial communities in the cover soil (PMM) by sequencing 16S ribosomal RNA (rRNA) genes in both rhizosphere and bulk soils and predicting functional profiles. More salt can migrate into the rooting zone when OB than when TS is used as the capping material (Li et al. 2013) and can result in different salinity in the PMM layer. High salinity would inhibit plant root activities and consequently affect the rhizosphere bacterial community (Davis et al. 2014). Given that soil bacterial communities change with salinity in soils (Elmajdoub et al. 2014), the rhizosphere bacterial community would respond to changes in

2517

soil salinity in the rhizosphere in association with different types of capping material used. We hypothesize that the structure, composition, and function of the rhizosphere bacterial community will be different among capping treatments due to the influence of capping material type on hydraulic properties and salt migration.

2 Materials and methods 2.1 Column experiment setup A completely randomized block design with a 2 × 2 × 4 factorial treatment structure was set up to examine capping material type at two levels (coarse material TS vs. fine material OB), water balance at two levels (20% more water vs. 20% less water than the actual evapotranspiration in the greenhouse), and capping thickness at four levels: 0 as no capping treatment (NC) and 20, 50, and 100 cm. With three replications for each of the treatments, a total of 48 columns (0.45 m in diameter and 1.8 m in height) were set up. The depth of the PMM cover soil was 0.5 m in all columns. Clean TS was used as the bottom bedding material. Its thickness is the differential between the total height (180 cm) and the thickness of the other layers (cover soil and capping layers). Saline water level for the salinity treatment in the columns was set at the surface between the capping layer and the bottom bedding layer using an external water bottle. The TS and OB capping materials and the PMM were all sourced from the Canadian Natural Resource Ltd. (CNRL) Horizon mine north of Fort McMurray. In each column, four jack pine (Pinus banksiana) seedlings were planted. Tap water was used to irrigate from the top of the column to mimic precipitation, and saline water was supplied from the bottom of each column to mimic the presence of saline groundwater. Saline water was connected to a saline groundwater in columns using a water bottle external to the column to control the saline water level within the column. The simulated saline groundwater for all the treatments was a 3 g/L NaCl solution (electrical conductivity (EC) = 5.7 dS/m), which has similar EC and sodium adsorption ratio (SAR) to that of a typical oil sands process-affected water (OSPW) from the oil sands. The environment in the greenhouse was maintained at 22 °C for 16 h of day and at 16 °C for 8 h of night to simulate the summer condition in the oil sand region. At the end of the third growing season, the columns were destructively sampled. The roots that were retrieved from the columns were shaken vigorously to separate the bulk soil from the rhizosphere soil that tightly adhered to roots. Soil from three replicates was combined to form a composite sample for DNA extraction. Soil pH and EC (soil/water ratio = 1:5, v/v) was determined using a pH meter (Orion, Thermo Fisher Scientific Inc., Beverly, MA) and an AP75 portable waterproof conductivity/TDS meter (Thermo Fisher Scientific

2518

Inc., Waltham, MA), respectively. The water-soluble organic carbon (WSOC) and N (WSON) in the supernatants (soil/water = 1:5, v/v) were analyzed with a Shimadzu 5000A TOC analyzer (Shimadzu Corporation, Kyoto, Japan) after filtering with a 0.45-μm nylon syringe filter. The total carbon (TC) and nitrogen (TN) were determined with a CE440 Elemental Analyzer (Exeter Analytical, Chelmsford, MA, USA).

2.2 DNA extraction and 16S rRNA gene amplicon sequencing Metagenomic DNA was isolated and purified with the FastDNA SPIN Kit for soil (MP Biomedicals, Solon, OH, USA) following the manufacturer’s instructions. After isolation, the purified DNA was eluted in 100 μL of elution buffer. Quality and purity of the isolated metagenomic DNA were confirmed by agarose gel electrophoresis. Once the DNA was extracted, library construction was performed using a two-way PCR method. The PCR1 (locusspecific amplification) amplified a region of the 16S rRNA gene using the tagged primers Glenn (CAGTCGGGCGTCAT CA)-F515 (5′-GTGCCAGCMGCCGCGGTAA-3′) and trp1 (CCTCTCTATGGGCAGTCGGTGATG)-R806 (5′-GACT ACVSGGGTATCTAA T-3′) where Glenn was a universal tag (Glenn 2011), trP1 was the Ion Torrent truncated P1 adaptor (Life Technologies), and F515 and R806 were previously published locus-specific primers (Barberán et al. 2012). PCR2 (barcode and Ion Torrent specific adaptor attachment) used diluted PCR1 product as template. Here, the forward primer was, from the 5′ end, Ion Torrent A adapter sequence including the 4 bp key (Life Technologies), barcode (Life Technologies), and Glenn tag. The reverse primer was trP1 which was the Ion Torrent truncated P1 adaptor sequence (Life Technologies). This amplification, which was verified using agarose gel electrophoresis, resulted in amplicons which contain Ion Torrent specific adaptors, barcode, and the targeted region of the 16S rRNA gene. Amplified samples that were all individually barcoded were then pooled in equal amounts, and this pooled library was then gel purified using QIAquick Gel Extraction Kit (Qiagen) following the manufacturer’s instructions. Purified pooled library was then purified a second time using QIAquick Gel Extraction Kit (Qiagen) following the manufacturer’s instructions. Quantitation of the second purified pooled library performed using the Qubit dsDNA HS Assay Kit (Life Technologies) and the library was diluted to 20 pM. Template preparation of the diluted pooled library was performed with an IonOneTouch2 Instrument using the Ion PGM Template OT2 400 Kit (Life Technologies). Sequencing of templated spheres was conducted using Ion PGM400 Sequencing Kit and an Ion316 Chip on an Ion Torrent Personal Genome Machine (PGM) System


(Life Technologies), following the manufacturer ’s instructions. After sequencing, the individual sequence reads were filtered within the PGM software to remove low-quality and polyclonal sequences. Sequences matching the PGM 3′ adaptor were also automatically trimmed. All PGM quality-filtered data were exported as fastq files (NCBI SRA accession number SRP076502) and subsequently analyzed using open reference operational taxonomic unit (OTU) pickup strategy in the QIIME pipeline (Caporaso et al. 2010). Sequence counts were adjusted based on 16S copy numbers in rrnDB (Stoddard et al. 2015) and were normalized with the negative nominal model (McMurdie and Holmes 2014), which minimized bias associated with sequencing coverage and allowed for comparison of results for all samples. The functional profiles were predicted with the PICRUSt software package (Langille et al. 2013). 2.3 Statistical analyses The odds ratio values were calculated as the following: Rr odds ratio ¼ lg Rb

ð1Þ

where Rr represents the relative abundances of OTUs in rhizosphere and Rb represents the relative abundances of OTUs in bulk soils. The positive odds ratio values of OTUs indicate accumulation of microbial populations in the rhizosphere, and negative odds ratio values indicate depletion of microbial populations in the rhizosphere, relative to the bulk soil. Nonmetric multidimensional scaling (NMDS) analyses were used for ordination based on both the Bray-Curtis and UniFrac phylogenetic distance matrix for bacterial community structure (OTUs). The PERANOVA was employed for testing differences between bacterial community groups from columns with different capping materials and from rhizosphere and bulk soils. The canonical correspondence analysis (CCA) was used for determining the influence of the soil properties on the bacterial community structure. The contributions of soil properties were identified through variation partitioning. All statistical analyses and graphics were done using the R program (http://www.r-project.org).

3 Results 3.1 Capping material type effects on properties of rhizosphere and bulk soils Soil pH and WSOC in the rhizosphere soil were significantly higher than that in the bulk soil in the NC and OB treatments but were significantly lower than in the bulk soil in TS treatment (Fig. 1a, c). The EC values in the bulk soils were not


2519

Fig. 1 The difference of soil properties between rhizosphere and bulk soils in no capping (NC), overburden (OB), and tailings sand (TS) treatments. pH soil pH, EC electrical conductivity, WSOC water-soluble organic carbon, WSON water-soluble organic nitrogen, TC total carbon, TN total nitrogen. The dots are outliers. The asterisks indicate significant difference between the corresponding soil characteristics in the rhizosphere and the bulk soils (P < 0.05)

significantly different between columns with OB and TS capping layers in this study. However, the EC values in rhizosphere soils varied with the capping material type. Soil EC in the rhizosphere was significantly higher than that in the bulk soil in the NC and TS treatments but was not different between the rhizosphere and bulk soils in the OB treatment (Fig. 1b). The WSON in the rhizosphere was significantly higher than that in the bulk soil in the OB treatment (Fig. 1d). Both TC and TN were non-significantly different between the rhizosphere and the bulk soils of the three treatments.

3.2 Capping material type effects on rhizosphere bacterial taxonomic composition Bacterial 16S rRNA genes profiled with high-throughput sequencing show that a total of 421,810 reads were generated after quality control. At 97% sequence identified, a total of 29,532 OTUs were detected. Overall, the bacterial communities were dominated by Alphaproteobacteria (18.8%) and Thermoleophilia (10.0%), followed by Actinobacteria (9.3%), Acidobacteria (6.5%), Betaproteobacteria (6.3%), Ellin6526 (5.4%), and Deltaproteobacteria (5.1%) at the class level (Table 1). The relative abundances of the other 123 classes were less than 5%.

The range of the odds ratio, which measured the differentiation of 423 dominant OTUs (relative abundance >0.01%) between the bacterial communities in the rhizosphere and the bulk soil, was wider for OTUs present in the NC than in the OB and TS treatments (Fig. 2a). Less OTUs were enriched (odds ratio > 0) in the rhizosphere relative to the bulk soil in the NC and OB treatments. The number of OTUs depleted in the rhizosphere (169) was greater than that enriched in the rhizosphere (26) in all three treatments (Fig. 2b). However, the number of OTUs that was only depleted in the rhizosphere of either the TS (17) or NC (17) treatments was less than that enriched in the rhizosphere (53 for NC and 83 for TS). 3.3 Capping material type effects on rhizosphere bacterial community structure Taxonomy-based Bray-Curtis distance matrix and phylogenetic-based UniFrac distance matrix were used for evaluating the similarity between bacterial communities (Fig. 3). The higher turnover rates for the bacterial community in the rhizosphere suggest that variation in community composition was higher in the rhizosphere than in the bulk soil. The structural variation of the bacterial communities in the bulk soil was not different between the OB and TS treatments (PERANOVA, P = 0.16 for UniFrac and 0.14 for Bray-

2520 Table 1

J Soils Sediments (2017) 17:2516–2523 The relative abundance (%, mean ± SD) of dominant classes in rhizosphere and bulk soils from columns with different capping layer

Dominant classes

No capping

Overburden

Tailings sand

Bulk soil

Rhizosphere

Bulk soil

Rhizosphere

Bulk soil

Rhizosphere

Alphaproteobacteria Thermoleophilia

18.7 ± 0.11 9.1 ± 0.95

19.4 ± 0.66 8.8 ± 0.04

19.0 ± 0.66 10.4 ± 0.84

18.9 ± 0.38 9.8 ± 0.59

18.7 ± 0.14 10.2 ± 0.55

18.9 ± 0.24 10.3 ± 1.15

Actinobacteria

10.1 ± 0.63

10.0 ± 0.3

8.5 ± 0.34

9.3 ± 0.58

8.9 ± 0.39

9.9 ± 0.52

Acidobacteria.6 Betaproteobacteria

6.3 ± 0.73 6.4 ± 0.20

6.0 ± 0.01 6.4 ± 0.12

7.0 ± 0.20 6.2 ± 0.14

6.7 ± 0.54 6.3 ± 0.16

6.5 ± 0.36 6.3 ± 0.11

6.2 ± 0.47 6.2 ± 0.29

Ellin6529 Deltaproteobacteria

5.3 ± 0.53 5.2 ± 0.44

5.4 ± 0.21 5.2 ± 0.13

5.3 ± 0.17 5.2 ± 0.21

5.3 ± 0.23 5.3 ± 0.20

5.5 ± 0.29 5.2 ± 0.19

5.6 ± 0.30 5.0 ± 0.28

Acidimicrobiia

4.3 ± 0.18

4.2 ± 0.08

4.3 ± 0.05

4.2 ± 0.14

4.4 ± 0.08

4.4 ± 0.09

Gammaproteobacteria MB.A2.108

4.2 ± 0.29 2.8 ± 0.13

4.3 ± 0.17 2.8 ± 0.01

4.1 ± 0.21 2.8 ± 0.04

4.2 ± 0.06 2.7 ± 0.09

4.1 ± 0.16 2.9 ± 0.12

4.1 ± 0.19 2.8 ± 0.07

Curtis), but that in the rhizosphere soil was significantly different between the OB and TS treatments (PERANOVA, P = 0.04 for UniFrac and 0.03 for Bray-Curtis). Both the taxonomic-based and phylogenetic-based dissimilarity indices show that the bacterial community structure was different between the rhizosphere and the bulk soils in the TS treatment (PERANOVA, P = 0.015 for UniFrac and 0.013 for BrayCurtis), but not in the NC treatment (PERANOVA, P = 0.67 for UniFrac and 0.38 for Bray-Curtis). Under the OB treatment, the phylogenetic-based dissimilarity of bacterial communities was different between the rhizosphere and bulk soils (PERANOVA, P = 0.034), but the taxonomic-based dissimilarity was marginally different (PERANOVA, P = 0.067). The differentiation between the rhizosphere and bulk soils was along the first axis under the NC and OB treatment but along

Logarithmic odd ratio

a 2 1 0 −1 −2 −3 NC

OB

TS

Capping treatment

b Count numbers

Fig. 2 The response of dominant OTUs (relative abundance >0.01%) to different capping strategies. a The distribution of odds ratio values in the no capping (NC), overburden (OB), and tailings sand (TS) treatments. b The number of OTUs in dominant classes accumulated or depleted in the rhizosphere relative to the bulk soil in the no capping (NC), overburden (OB), and tailings sand (TS) treatments

the second axis under the TS treatment, indicating that the environmental drivers for the rhizosphere bacterial communities were different between treatments. The WSON values were correlated with the variation of the community structure along the first axis for the bacterial community structure between rhizosphere and bulk soils in the NC and OB treatment (Fig. 4). Soil EC values were correlated with the variation of the community structure along the second axis for the bacterial community structure between rhizosphere and bulk soils in the TS treatment. The contributions of soil pH (14.6), EC (8.5), and WSON (9.6%) in the variation in community composition were much higher than that of TC (2.3), TN (3.1), and WSOC (2.9%). However, soil pH, EC, TC, TN, WSOC, and WSON only explained 19.3% of the total variation in bacterial community structure.

All

NC

OB

TS

Depleted Enriched

Depleted Enriched

Depleted Enriched

Depleted Enriched

150

100

50

0


2521

Fig. 3 The non-metric multidimensional scaling (NMDS) ordination of bacterial communities in rhizosphere and bulk soils in the no capping (NC), overburden (OB), and tailings sand (TS) treatments

Bray−Curtis

UniFrac

0.03

Capping treatment

0.02

NC

NMDS2

0.01

OB TS

0.00 −0.01

Sample type Bulk soil

−0.02

Rhizosphere −0.03 −0.025

0.000

0.025

−0.025

0.000

0.025

NMDS1

3.4 Capping material effects on the potential functional profiles in the rhizosphere The clustering groups in the heatmap for the predicted metagenomes (Fig. 5) suggest that the potential functional profiles were different between the TS and the other two treatments in the rhizosphere soil and different among the three treatments in the bulk soil. The potential functional profiles in the rhizosphere of the TS treatment were enriched in pathways related to nutrient metabolism (e.g., pathways for carbohydrate, amino acid, and lipid metabolism) and nutrient transportation (e.g., pathways for membrane transport). Conversely, the relative abundance of pathways related to environmental adaptation, replication and repair, and cell motility was enriched in the potential functional profiles in the rhizosphere of the NC and OB treatments and in the bulk soil of all three treatments.

2

pH

TC Capping treatment

TN CCA 2 (5.0%)

NC OB

0

WSON

TS

WSOC Sample type EC

−2

Bulk soil Rhizosphere

−4 −2

0

2

4

CCA 1 (5.9%)

Fig. 4 The constrained corresponding analysis (CCA) of the soil bacterial communities. pH soil pH, EC electrical conductivity, WSOC watersoluble organic carbon, WSON water-soluble organic nitrogen, TC total carbon, TN total nitrogen

4 Discussion The key finding from this column-based study is that capping materials affect the structure and potential function of the rhizosphere bacterial community in the cover soil. The rhizosphere effect significantly influenced the bacterial community structure in the soil in the TS and OB treatments. The changes of bacterial community structure in the rhizosphere can be associated with the differentiation of nutrient availability, which is modified in the rhizosphere by plant uptake and by changes in soil properties (Bulgarelli et al. 2013). The correlation between the variation in the community structure and the WSON concentration in the OB treatment indicates that the OB capping material influenced nitrogen supply in the PMM. This result is supported by a previous study in which key response variables for nutrient availability was NH4+ and NO 3 − in a reclamation site with saline overburden (MacKenzie and Quideau 2010). The possible explanation is that plant root activities changed the availability of nitrogen in the rhizosphere, hence affected rhizosphere microbial community. The variation of community structure in the TS treatment was correlated with soil EC and pH, which were more different between the rhizosphere and the bulk soils in the TS treatment (Fig. 1). This result suggests that microbial communities in the PMM layer of the TS treatment were affected by EC, which could be alleviated in the rhizosphere (Elmajdoub et al. 2014). The higher EC values in the rhizosphere could have been caused by the higher ion concentration induced by root activities (Qasim et al. 2016). Soil pH is one of the most important edaphic features that affect bacterial communities (Lauber et al. 2009). The decrease of rhizosphere soil pH could be ascribed to the organic anions and H+ released from plant roots. However, the rhizosphere soil pH could be increased when more cations than anions are taken up by plants (Hinsinger et al. 2003). Moreover, another explanation for the equivocal changes of rhizosphere soil pH could be the negative correlation between EC and pH in soils (Aini et al. 2014).

2522


Fig. 5 The predicted functional pathway profiles in the rhizosphere (R) and bulk soil (B) in the no capping (NC), overburden (OB), and tailings sand (TS) treatments. The values in each column were scaled

However, the variation explained by these edaphic features was low in our study, indicating that environmental variables not measured in this study contributed to variations in the bacteria community structure. The changes in the relative abundance of the dominant OTUs support the variation in the bacterial community structure between the rhizosphere and the bulk soils. The greater number of OTUs depleted than those enriched in the rhizosphere indicates a higher evenness of the bacterial community in the rhizosphere, representing changes in community structure (Fig. 2a). We found an intriguingly opposite tendency that high proportions of the OTUs from the classes Alphaproteobacteria and Thermoleophilia were depleted in the rhizosphere of the OB treatment but enriched in the rhizosphere of the TS treatment. The previous study found a significant correlation between soil pH with Thermoleophilia at the continental scale (Lauber et al. 2009) and with Alphaproteobacteria along elevation (Shen et al. 2 0 1 3 ) . A c c o r d i n g l y, t h e d i f f e r e n t t e n d e n c y o f Alphaproteobacteria and Thermoleophilia in TS and OB treatments might be related to soil pH, which increased in the

rhizosphere of the OB treatment but decreased in the rhizosphere of the TS treatment (Fig. 1). The clusters of the predicted functional profiles also confirm the significant difference in bacterial community structure between the rhizosphere and the bulk soil in the TS treatment. Changes in bacterial community function indicate different biogeochemical processes in the rhizosphere associated with the rhizosphere effect. The greater relative abundance of pathways for nutrient transportation and metabolism and the lower WSOC in the rhizosphere than in the bulk soils in the TS treatment suggest higher nutrient utilization activities in the rhizosphere than in the bulk soils in the TS treatment (González-Cabaleiro et al. 2015). Conversely, the potential functional profiles of the NC and OB treatments were similar between the rhizosphere and the bulk soils, indicating that biogeochemical processes in the rhizosphere and bulk soil were similar and that the effect on the bacterial community function in the rhizosphere of the NC and OB treatments was weak. The greater relative abundance of the pathway for environmental adaptation in the bulk soil, which includes genes


that enable cells to rapidly adapt to adverse environmental conditions (Cases et al. 2003), suggests that there were unfavorable soil properties in the bulk soil. We need to interpret the functional profiles with caution because PICRUSt predicts metagenomes from a limited number of completed sequencing genomes (Langille et al. 2013). The traits for strains with close phylogenetic distance may have a large discrepancy (Ngugi et al. 2016). Given this limitation, we will only focus our analysis on the pathways with large relative abundance in the predicted functional profiles to reduce the risk of including rare functional genes in our analysis.

5 Conclusions In conclusion, this study supports our hypothesis that the type of capping material used for oil sand reclamation influences the structure and function of bacterial communities in the rhizosphere soil. The rhizosphere effect on bacterial communities was greater in the TS than in the NC and OB treatments. Given the critical role of rhizosphere microbiomes in building soil function and restoring disturbed ecosystems, we suggest that, in designing capping strategies, tailings sand rather than overburden is preferred to be used immediately below the cover soil in oil sand reclamation to foster the development of a rhizosphere bacterial community that is beneficial for plant growth and ecosystem rebuilding.

Acknowledgements This research was supported by grants from Total E&P Canada Ltd. and the NSERC CREATE program. We thank Canadian Natural Resources Limited for providing the experimental soils and Janusz Zwiazek, Yuanpei Gao, Kunfeng Ren, Philip Auer, Sang-sun Lim, Xiaofei Lyu, Min Duan, Lei Sun, Jinhyeob Kim, Kangyi Lou, Xuzhong Song, Yanjiang Cai, Yang Liu, Hye In Yang, Lixia Zhu, Lijing Wang, Yike Shen, Shirin Zahraei, Abdelhafid Dugdug, Prem Pokharel, and Mark Baah-Acheamfour from the University of Alberta, Jagtar Bhatti from the Canadian Forest Service, and Bonnie Drozdowski, Jay Woosaree, Marshall McKenzie, Elise Martin, Jeff Newman, Andrew Underwood, Dani Degenhardt, and Victor Bachmann from Alberta Innovates-Technology Futures for assistance during the research.

References Ahad JME, Pakdel H (2013) Direct evaluation of in situ biodegradation in Athabasca oil sands tailings ponds using natural abundance radiocarbon. Environ Sci Technol 47:10214–10222 Aini IN, Ezrin MH, Aimrun W (2014) Relationship between soil apparent electrical conductivity and pH value of Jawa series in oil palm plantation. Agric Agric Sci Procedia 2:199–206 Barberán A, Bates ST, Casamayor EO, Fierer N (2012) Using network analysis to explore co-occurrence patterns in soil microbial communities. ISME J 6:343–351 Brunner SM, Goos RJ, Swenson SJ et al (2015) Impact of nitrogen fixing and plant growth-promoting bacteria on a phloem-feeding soybean herbivore. Appl Soil Ecol 86:71–81

2523 Bulgarelli D, Schlaeppi K, Spaepen S et al (2013) Structure and functions of the bacterial microbiota of plants. Annu Rev Plant Biol 64:807–838 Caporaso JG, Kuczynski J, Stombaugh J et al (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336 Cases I, de Lorenzo V, Ouzounis CA (2003) Transcription regulation and environmental adaptation in bacteria. Trends Microbiol 11:248–253 Davis L, Sumner M, Stasolla C, Renault S (2014) Salinity-induced changes in the root development of a northern woody species, Cornus sericea. Botany 92:597–606 Duan L, Sebastian J, Dinneny J (2015) Salt-stress regulation of root system growth and architecture in Arabidopsis seedlings. Methods Mol Biol 1242:105–122 Elmajdoub B, Barnett S, Marschner P (2014) Response of microbial activity and biomass in rhizosphere and bulk soils to increasing salinity. Plant Soil 381:297–306 Glenn TC (2011) Field guide to next-generation DNA sequencers. Mol Rcology Resour 11:759–769 González-Cabaleiro R, Ofiţeru ID, Lema JM, Rodríguez J (2015) Microbial catabolic activities are naturally selected by metabolic energy harvest rate. ISME J 9:2630–2641 Hinsinger P, Plassard C, Tang C, Jaillard B (2003) Origins of rootmediated pH changes in the rhizosphere and their responses to environmental constraints: a review. Plant Soil 248:43–59 Jamro GM, Chang SX, Naeth MA et al (2015) Fine root dynamics in lodgepole pine and white spruce stands along productivity gradients in reclaimed oil sands sites. Ecol Evol 5:4655–4670 Langille M, Zaneveld J, Caporaso JG et al (2013) Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol 31:814–821 Lauber CL, Hamady M, Knight R, Fierer N (2009) Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale. Appl Environ Microbiol 75:5111–5120 Li X, Chang SX, Salifu KF (2013) Soil texture and layering effects on water and salt dynamics in the presence of a water table: a review. Environ Rev 22:41–50 MacKenzie MD, Quideau SA (2010) Microbial community structure and nutrient availability in oil sands reclaimed boreal soils. Appl Soil Ecol 44:32–41 McMurdie PJ, Holmes S (2014) Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput Biol 10:e1003531 Ngugi DK, Blom J, Stepanauskas R, Stingl U (2016) Diversification and niche adaptations of Nitrospina-like bacteria in the polyextreme interfaces of Red Sea brines. ISME J 10:1383–1399 Oburger E, Dell’mour M, Hann S et al (2013) Evaluation of a novel tool for sampling root exudates from soil-grown plants compared to conventional techniques. Environ Exp Bot 87:235–247 Olatuyi SO, Leskiw LA (2014) Long-term changes in soil salinity as influenced by subsoil thickness in a reclaimed coal mine in eastcentral Alberta. Can J Soil Sci 94:605–620 Philippot L, Raaijmakers JM, Lemanceau P, van der Putten WH (2013) Going back to the roots: the microbial ecology of the rhizosphere. Nat Rev Microbiol 11:789–799 Qasim B, Motelica-Heino M, Bourgerie S et al (2016) Rhizosphere effects of Populus euramericana Dorskamp on the mobility of Zn, Pb and Cd in contaminated technosols. J Soils Sediments 16:811–820 Reinhold-Hurek B, Bünger W, Burbano CS et al (2015) Roots shaping their microbiome: global hotspots for microbial activity. Annu Rev Phytopathol 53:403–424 Shen C, Xiong J, Zhang H et al (2013) Soil pH drives the spatial distribution of bacterial communities along elevation on Changbai Mountain. Soil Biol Biochem 57:204–211 Stoddard SF, Smith BJ, Hein R et al (2015) rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development. Nucleic Acids Res 43: D593–D598