Introduction
Archaea compose a considerable fraction of the microbial biomass on the earth and play a crucial role in the global geochemical cycles [26]. However, until the early 1990s, archaea were perceived to thrive in extreme habitats [36]. Over the past two decades, environmental surveys using molecular screening tools have detected numerous archaeal sequences throughout the biosphere, including in freshwater environments [9,35], marine sediments [20], and agricultural habitats [14] in addition to the extreme environments previously reported to be associated with archaea. However, according to the investigations on the global distribution of dominant archaeal populations, archaea have been found to inhabit a far more restricted ecological niche [4,5]. Furthermore, studies have shown that several environmental parameters affect the archaeal communities, such as soil pH [6] and C/N ratios [5].
Because of different land management strategies, changes in land use can significantly influence the majority of soil properties [21,24], thereby affecting the microbial community structure and diversity [1,40]. Previous report has investigated shifts in archaeal biogeographical patterns among several types of land use and focused on land-use conversions between forests and cultivated fields using denaturing gradient gel electrophoresis [31]. Studies have also examined archaeal communities in upland [28,29] and paddy soils [19,22], respectively. The archaeal phylum Euryarchaeota involved in greenhouse gas production was recently examined in various ecosystems, including paddy soils and upland soils [16]. Euryarchaeota, especially the class Methanomicrobia, was reported to prefer paddy fields [16]. The ammonia-oxidizing archaea, the potential contributors to nitrification, represent a significant shift in the communities after conversion of uplands to paddy fields [2,39]. These studies always focused on partial archaeal communities within a certain period of time; thus, variations of total archaeal diversity and composition based on agricultural ecosystem change are not fully understood. Furthermore, different microbial communities occur at different soil depths [13,17,42], but it is still unclear whether the responses of archaeal communities to land-use change are dependent on soil depth.
Paddy cultivation provides one of the most important food sources and is still expanding to meet the demands of an increasing population [38]. A complete perspective of the archaeal community and its variability after a change in land use from upland to paddy fields has not been reported; therefore, in the present work, we investigated archaeal communities that have been exposed to land-use changes over the course of decades. Our study focused on archaea that inhabit a unique set of paddy fields that were gradually established over the course of 40 years on land that was once characterized as uplands. Our main objectives were to (i) assess the composition and diversity of the soil archaeal communities from upland and paddy fields as a function of duration in the Songnen Plain (farmland area accumulating 55,900 km2) in Northeast China using 454 barcoded pyrosequencing, (ii) investigate whether the changes in archaeal communities following a land-use change from upland to paddy fields over the specified time period is dependent on the soil depth, and (iii) identify the most important soil factors that influence the archaeal communities. The results of this study provide a duration-related dynamic reconstitution of the archaeal community following land-use changes at two soil depths and will expand our understanding of archaea and vital factors that influence the agricultural ecosystem.
Materials and Methods
Soil Sampling and Chemical Analyses
The study sites included paddy fields that were established on former croplands in the Songnen Plain (46.83~46.89°N, 127.09~127.11°E). The details of sampling sites are listed in Table S1. A total of seven time points (0, 1, 5, 10, 20, 30, and 40 years) after a land-use change were examined. Before the fields were used as paddy fields, they had been planted with maize with a conventional tillage management for more than 100 years. All fields were similar in soil type, the level topography, climate, and in irrigation and fertilizer use practices (except the upland) [18]. Specifically, 400 kg/ha NPK (N:P2O5:K2O = 12:18:15) and 300 kg/ha NPK (N:P2O5:K2O = 28:14:12) were annually applied in paddy fields and upland, respectively; in addition, 105 and 120 kg/ha urea were applied after the tillering stage of paddy fields and large bell stage of upland, respectively. Soil samples were collected after the rice-growing seasons on 15th October 2012. For each field, five random cores were collected from the surface soils in the top 20 cm and the subsurface soils at 20-40 cm, respectively. The soil samples were stored at -80℃ prior to the molecular analyses and at 4℃ before the chemical analyses. For the chemical analyses, each sample was air dried, sieved through a 2.0 mm mesh, and stored at an ambient laboratory temperature. The soil pH was determined using 1:15 (w/w) soil/BaCl2 (0.1 M) suspension using a glass electrode [15]. The samples were sifted through a 100-mesh (0.15 mm) sieve for the total carbon, nitrogen, and phosphorus analyses. Total carbon and total nitrogen were determined using a Vario MACRO cube analyzer (Elementar Analysensysteme Vario MACRO cube, Germany). Total phosphorus was determined using the molybdate method following perchloric acid (HClO4) digestion [33]. Olsen phosphorus was extracted using sodium bicarbonate [32] and examined.
Genomic DNA Extraction and 454 Pyrosequencing
The same amount in grams of each random soil sample for one time point and one layer was thoroughly mixed to form one sample for the following experiments. The total genomic DNA was extracted from 1.0 g of each mixed soil sample using the E.Z.N.A. Soil DNA Kit (Omega, USA) following the manufacturer’s instructions. The concentration and quality of the DNA were determined using a NanoDrop ND 2000 spectrophotometer (USA). The hypervariable V2-V4 regions of the 16S rDNA were amplified using the universal primers Arch344F/Arch915R (5’-ACGGGG YGCAGCAGGCGCGA/ 5’-GTGCTCCCCCGCCAATTCCT) [35]. Both primers incorporated the FLX Titanium adaptors and a sample barcode sequence. The PCR experiments were performed in triplicate 20 μl reactions as follows: 5 min initial denaturation at 95℃, 25 cycles of denaturation at 95℃ (30 sec), annealing at 55℃ (30 sec), elongation at 72℃ (30 sec), and final extension at 72℃ for 5 min. The pooled triplicate reactions were purified using the AxyPrepDNA Gel Extraction Kit (Axygen, USA) according to the manufacturer’s recommendations. The DNA concentration was determined using the QuantiFluor-ST PicoGreen double-stranded DNA assay (Promega, USA), and quality was controlled for using an Agilent 2100 bioanalyzer (Agilent, USA). The pyrosequencing was performed using a Roche GS FLX+ system (Roche, Switzerland) at Majorbio Bio-Pharm Technology Co., Ltd. (China). The sequence data were submitted to the GenBank database under the biosample accession numbers 2442368 to 2442381.
Processing Pyrosequencing Data
QIIME software (http://bio.cug.edu.cn/qiime/) was employed to trim all the pyrosequencing reads according to the sliding window of 50 bp and minimum average quality score of 20. After trimming, the reads that were shorter than 200 bp, contained any ambiguous bases, or exhibited a homopolymer longer than 10 bp were removed. All the trimmed sequences were normalized to the same sequencing depth using Mothur ver. 1.26.0 software (http://www.mothur.org/wiki/Main_Page). The operational taxonomic units (OTUs) were clustered with a 97% similarity cutoff using UPARSE (ver. 7.1; http://drive5.com/uparse/), and the chimeric sequences were identified and removed using UCHIME. Alpha diversity was estimated using QIIME. Shifts in the overall archaeal community structure were visualized using a principal coordinate analysis of the pairwise Bray-Curtis dissimilarity matrices based on OTUs at a 97% similarity, using the vegan package for R statistical software (http://www.r-project.org). The phylogenetic affiliation of each 16S rDNA gene sequence was analyzed using the RDP Classifier (http://rdp.cme.msu.edu/) against the SILVA (SSU115) 16S rDNA database, using a 70% confidence threshold. Redundancy analyses was performed using the vegan package to test the effects of the soil characteristic property gradients on the abundance of OTUs from the phylum to genus levels. The correlation between the microbial groups and soil properties was assessed by the function permutest and envfit. In addition to the soil chemical properties, the duration of the land-use change was also introduced. Linear regression was used to compare the changes in archaeal OTU richness with the duration and gradients of the soil chemical properties. The rate of changes was defined as the varying relative abundance of Euryarchaeota per year. The variations were calculated by subtracting the value at one time point from the value at the next time point.
Results and Discussion
Changes in Soil Chemical Properties Following Land-Use Change
The trends in most soil properties following a land-use change from upland to paddy fields over time were similar between the two different depths (Fig. 1). The total carbon, total nitrogen, total phosphorus, and C/N ratio increased after the change and then decreased, except for the time point of 40 years (Figs. 1A-1D). Additionally, the soil pH initially decreased after the land-use change, and the minimum was achieved after 5 years; the soil pH then increased and eventually stabilized at about 5.5 (Fig. 1E). However, after land-use change, Olsen phosphorus from samples at the surface changed little at all time points except for the 40-year period; Olsen phosphorus from samples at the subsurface changed without adequate law, which suddenly decreased at the time points of 20 and 30 years (Fig. 1F).
Fig. 1.Soil properties by time point, including total nitrogen (A), total carbon (B), total C/N ratio (C), C/N phosphorus (D), pH_BaCl2 (E), and Olsen phosphorus (F). “S” and “Sb” represent the surface and subsurface, respectively. The values are the mean ± SEM (n = 5).
Alterations of Archaeal Communities Following Land-Use Change
To minimize the error from site-specific differences, five random soil samples were collected from one site and mixed to generate a homogeneous sample for DNA sequencing. It should be pointed out that a mixed sample may introduce ecological implications and replications should be carried out in future sequencing experiments. Fortunately, soil properties of each replication were determined and a small error value was detected, suggesting a very unusual sample was not existent. A total of 92,457 high-quality archaeal 16S rDNA gene sequences were produced, with an average length of 475 bp, and then normalized to 3,905 sequences per sample. Of the total 54,670 normalized sequences, we estimated 604 OTUs at the 97% similarity level. Nevertheless, this sequencing did not cover the full extent of archaeal diversity, and the Chao1 richness estimates suggested that our sequencing efforts included more than 80% of the estimated archaeal diversity on average (Table S2). After land-use change, the archaeal OTU richness from soils at the surface increased at the time point of 1 year; but from samples at the subsurface, the OTU richness decreased in the early years of study (Fig. 2A). The sequences were identified to two phyla: Crenarchaeota and Euryarchaeota. Changes in the euryarchaeotal OTU richness showed a similar trend with archaeal OTU richness (Fig. 2B), whereas the OTU richness of Crenarchaeota decreased slightly by the end of the study (Fig. 2C).
Fig. 2.Variations in the OTU richness of the archaea (A), Euryarchaeota (B), and Crenarchaeota (C) at the 97% similarity level over time. “S” and “Sb” represent the surface and subsurface, respectively.
Then, the similarity/dissimilarity of the archaeal communities across the 14 samples was measured using principal coordinate analyses for the pairwise Bray-Curtis dissimilarity matrices (Fig. S1). Alterations of the archaeal community structure were noticed at the time point of 1 year after the change from upland fields to paddy fields. Clear deviations have been found between the two depths since the 5-year time point, and the archaeal community structure at the two depths did not cluster again until the end of the study. Moreover, the archaeal community structure varied more at the subsurface than the surface on the Y-axis.
When considering the relative abundance, Crenarchaeota was the dominant phylum at the zero time point (i.e., in the upland) and composed of 93.73% and 93.75% of the total sequences at the surface and subsurface, respectively (Fig. 3A). When the upland soils were converted to paddy fields, the relative abundance of the phylum Euryarchaeota increased at both depths. The euryarchaeotal relative abundance at the surface palpably increased even at the time point of 1 year and reached to the maximum at the time point of 5 years after the land-use change, whereas a more gradual increase was detected at the subsurface throughout the entire testing period (Fig. 3A). Nevertheless, the relative abundance of Euryarchaeota at the two depths increased to a similar value by the end of the study, accounting for 75.70% and 68.48% at the surface and subsurface, respectively (Fig. 3A).
Fig. 3.A comparison of the taxonomic classifications for the archaeal 16S rDNA gene sequence relative abundances among the time points at the phylum level (A) and lower taxonomic levels, including the class (B) and order (C). “S” and “Sb” represent the surface and subsurface, respectively.
The identified sequences were further assigned to different taxa levels. In total, we identified 4 classes, 6 orders, 19 families, and 25 genera in the phylum Euryarchaeota and 8 classes, 11 orders, 11 families, and 8 genera from Crenarchaeota (Figs. 3B-3C and S2). The differences between the changes in archaeal community structure over time at the two depths were more obvious at low taxonomic levels, including class, order, family, and genus (Figs. 3B-3C and S2), although the archaeal community at both depths began to converge at the end of the study.
Depth-Dependence of the Archaeal Response to the Land-Use Changes
The soil profile chemical characteristics that vary with depth can provide numerous microenvironments that favor different microbial lineages [30]. In this study, the data from two depths also suggest that the archaeal response to the land-use change at the surface might not be identical to that of the subsurface. To quantify the differences in the archaeal community changes between the two depths, the rate of changes in the relative abundance was calculated at the given time intervals. Variations in the archaeal relative abundance at the phylum level were much steadier at the subsurface and characterized by a similar low rate of change per unit time (i.e., 1 year) (Fig. 4). The microbial composition at the subsurface was always relatively more uniform than at the surface [12]; thus, it seemed reasonable that the subsurface included more gradual variations in the archaeal communities than did the surface. We also inferred that the surface was more easily controlled by external conditions that may not have been recorded in this study, such as temperature, irrigation water, etc. [12]. As shown in Fig. 2, similar trends of OTU richness were detected between total archaea and Euryarchaeota, suggesting that the shift in total archaeal OTU richness was highly dependent on the phylum Euryarchaeota, which are typically considered to be anaerobes [3,16]. Therefore, compared with the subsurface, the conditions at the surface that were created by flooding regulation were more favorable for Euryarchaeota [4] and, thus, promoted the proliferation of these bacteria.
Fig. 4.Variations in the rate of changes for the euryarchaeotal relative abundance as a function of the duration. “S” and “Sb” represent the surface and subsurface, respectively.
Influence of Soil Chemical Properties on the Archaeal Distribution Patterns
Compared with the upland fields, the paddy fields are flooded constantly during the rice-growing season, which can promote rapid oxygen depletion and help establish oxygen-limited conditions [25]. It also should be noted that a chemical fertilizer with a different ratio of NPK was applied after the land-use change, which could also influence the soil properties [41]. Variable soil properties can affect the microbial distribution and may promote an increase in the relative abundance of archaeal groups that prefer the new habitat [23,34]. A number of environmental factors have been analyzed, and the C/N ratio and soil pH are often reported as the main chemical factors influencing the archaeal communities [4,5,16]. In this study, the C/N ratio and soil pH were significantly related with archaeal community composition at the class, order, and OTU levels (Table 1).
Table 1.*p < 0.05; **p < 0.01, ***p < 0.001. The p values are based on 999 permutations.
Moreover, among the chemical properties detected, a significant connection between the archaeal community structure and total phosphorus was detected at the class, order, and OTU levels, and Olsen phosphorus showed a significant correlation with archaeal composition at each taxonomic level except for the phylum (Table 1). Long-term observations indicated that the phosphorus content may be related to the archaeal relative abundance and community structure [8,27]. Phosphorus availability was reported to have a strong influence over bacterial and fungal growth and composition in some systems [8]. Additionally, soil pH could control the environmental availability of phosphorus [10,11], and there was certain correlation, although small and nonlinear, between Olsen phosphorus and pH in this study (Fig. S3). Therefore, it is proposed that the important role of Olsen phosphorus on archaeal community may go together with soil pH.
The Vital Role of the Duration of Land-Use Change
Finally, the duration of land-use change exhibited a significant relationship with the archaeal community composition at several taxonomic levels (Table 1), and archaeal OTU richness could be best predicted by the duration positively (Fig. S4). Environmental changes may modify the ancestral communities over time, and the communities evolve to counter these environmental changes [37]. Crenarchaeota was reported as the dominant archaea in upland soils [26]; thus, it is reasonable that the relative abundance of the soil crenarchaeotic group (SCG), which belongs to Crenarchaeota and is the main ammonia-oxidizing archaea in soil [2,5], was negatively correlated with the duration (Fig. S5). However, the relative abundance of the Marine Benthic Group A (MBG_A), Marine Benthic Group B (MBG_B), and miscellaneous crenarchaeotal group (MCG) exhibited opposite trends (Fig. S5a). These groups appear to prefer anaerobic habitats [20], which may explain their rise in relative abundance after the upland fields were changed to paddy fields. In addition, the relative abundance of all the classes/orders, except for Thermoplasmata/Thermoplasmatales, within the phylum Euryarchaeota, which was positively related to the duration (Fig. S5). Thermoplasmata is always dominant in uplands and methanogens (Methanobacteria and Methanomicrobia) prefer anoxic conditions [16], and thus the negative and positive relationship was reasonable. However, Halobacteriales was reported to be a minor order in paddy fields [16]. It has even been proposed that members of these microbes can be met in specific locations where salt accumulates due to evaporation or diffusion of water [7]. We indeed detected an increase in the sodium concentration with duration in this area studied (Fig. S6), which indicates that a change from upland fields to paddy fields may introduce changes in soil salinity. There are limited reports on this phenomenon; therefore, additional chemical and microbial experiments should be conducted.
In conclusion, through pyrosequencing of the archaeal 16S rDNA genes within the soil samples over a time series after a land-use change from upland fields to paddy fields, this study has comprehensively shown variations in the archaeal community composition and diversity. Both the euryarchaeotal relative abundance and diversity increased over time after the land-use change, although at different rates for different soil depths. From the 20-year time point to the end of the study, the proportion of Euryarchaeota was stable at the surface and converged towards the subsurface concentration, and the archaeal and euryarchaeotal OTU richness steadily increased. However, whether the soil properties and the archaeal communities stabilized or continued to change was not clear and requires further investigation.
References
- Acosta-Martinez V, Dowd S, Sun Y, Allen V. 2008. Tag-encoded pyrosequencing analysis of bacterial diversity in a single soil type as affected by management and land use. Soil Biol. Biochem. 40: 2762-2770. https://doi.org/10.1016/j.soilbio.2008.07.022
- Alam MS, Ren GD, Lu L, Zheng Y, Peng XH, Jia ZJ. 2013. Conversion of upland to paddy field specifically alters the community structure of archaeal ammonia oxidizers in an acid soil. Biogeosciences 10: 5739-5753. https://doi.org/10.5194/bg-10-5739-2013
- Angel R, Claus P, Conrad R. 2012. Methanogenic archaea are globally ubiquitous in aerated soils and become active under wet anoxic conditions. ISME J. 6: 847-862. https://doi.org/10.1038/ismej.2011.141
- Auguet JC, Barberan A, Casamayor EO. 2010. Global ecological patterns in uncultured Archaea. ISME J. 4: 182-190. https://doi.org/10.1038/ismej.2009.109
- Bates ST, Berg-Lyons D, Caporaso JG, Walters WA, Knight R, Fierer N. 2011. Examining the global distribution of dominant archaeal populations in soil. ISME J. 5: 908-917. https://doi.org/10.1038/ismej.2010.171
- Bengtson P, Sterngren AE, Rousk J. 2012. Archaeal abundance across a pH gradient in an arable soil and its relationship to bacterial and fungal growth rates. Appl. Environ. Microbiol. 78: 5906-5911. https://doi.org/10.1128/AEM.01476-12
- Bomberg M, Timonen S. 2007. Distribution of cren- and euryarchaeota in scots pine mycorrhizospheres and boreal forest humus. Microbial Ecol. 54: 406-416. https://doi.org/10.1007/s00248-007-9232-3
- Chen YL, Hu HW, Han HY, Du Y, Wan SQ, Xu ZW, Chen BD. 2014. Abundance and community structure of ammoniaoxidizing Archaea and Bacteria in response to fertilization and mowing in a temperate steppe in Inner Mongolia. FEMS Microbiol. Ecol. 89: 67-79. https://doi.org/10.1111/1574-6941.12336
- Deutzmann JS, Schink B. 2011. Anaerobic oxidation of methane in sediments of Lake Constance, an oligotrophic freshwater lake. Appl. Environ. Microbiol. 77: 4429-4436. https://doi.org/10.1128/AEM.00340-11
- Devau N, Cadre EL, Hinsinger P, Jaillard B, Gérard F. 2009. Soil pH controls the environmental availability of phosphorus: experimental and mechanistic modelling approaches. Appl. Geochem. 24: 2163-2174. https://doi.org/10.1016/j.apgeochem.2009.09.020
- Devau N, Hinsinger P, Le Cadre E, Colomb B, Gérard F. 2011. Fertilization and pH effects on processes and mechanisms controlling dissolved inorganic phosphorus in soils. Geochim. Cosmochim. Acta 75: 2980-2996. https://doi.org/10.1016/j.gca.2011.02.034
- Eilers KG, Debenport S, Anderson S, Fierer N. 2012. Digging deeper to find unique microbial communities: the strong effect of depth on the structure of bacterial and archaeal communities in soil. Soil Biol. Biochem. 50: 58-65. https://doi.org/10.1016/j.soilbio.2012.03.011
- Fierer N, Schimel JP, Holden PA. 2003. Variations in microbial community composition through two soil depth profiles. Soil Biol. Biochem. 35: 167-176. https://doi.org/10.1016/S0038-0717(02)00251-1
- Gattinger A, Hofle MG, Schloter M, Embacher A, Bohme F, Munch JC, Labrenz M. 2007. Traditional cattle manure application determines abundance, diversity and activity of methanogenic Archaea in arable European soil. Environ. Microbiol. 9: 612-624. https://doi.org/10.1111/j.1462-2920.2006.01181.x
- Hendershot W, Lalande H, Duquette M. 2007. Ion exchange and exchangeable cations, pp. 167-176. In Carter MR, Gregorich EG (eds.). Soil Sampling and Methods of Analysis, 2nd Ed. Canadian Society of Soil Science.
- Hu HW, Zhang LM, Yuan CL, He JZ. 2013. Contrasting Euryarchaeota communities between upland and paddy soils exhibited similar pH-impacted biogeographic patterns. Soil Biol. Biochem. 64: 18-27. https://doi.org/10.1016/j.soilbio.2013.04.003
- Huang J, Sheng X, He L, Huang Z, Wang Q, Zhang Z. 2013. Characterization of depth-related changes in bacterial community compositions and functions of a paddy soil profile. FEMS Microbiol. Lett. 347: 33-42. https://doi.org/10.1111/1574-6968.12218
- Jiang N, Wei K, Chen L. 2016. Long-term chronological shifts in bacterial communities and hydrolytic extracellular enzyme activities in the forty years following a land-use change from upland fields to paddy fields. Pedobiologia 59: 17-26. https://doi.org/10.1016/j.pedobi.2015.12.002
- Ke X, Lu Y, Conrad R. 2014. Different behaviour of methanogenic archaea and Thaumarchaeota in rice field microcosms. FEMS Microbiol. Ecol. 87: 18-29. https://doi.org/10.1111/1574-6941.12188
- Kubo K, Lloyd KG, Biddle JF, Amann R, Teske A, Knittel K. 2012. Archaea of the Miscellaneous Crenarchaeotal Group are abundant, diverse and widespread in marine sediments. ISME J. 6: 1949-1965. https://doi.org/10.1038/ismej.2012.37
- Lauber CL, Strickland MS, Bradford MA, Fierer N. 2008. The influence of soil properties on the structure of bacterial and fungal communities across land-use types. Soil Biol. Biochem. 40: 2407-2415. https://doi.org/10.1016/j.soilbio.2008.05.021
- Liesack W, Schnell S, Revsbech NP. 2000. Microbiology of flooded rice paddies. FEMS Microbiol. Rev. 24: 625-645. https://doi.org/10.1111/j.1574-6976.2000.tb00563.x
- Logares R, Lindstrom ES, Langenheder S, Logue JB, Paterson H, Laybourn-Parry J, et al. 2013. Biogeography of bacterial communities exposed to progressive long-term environmental change. ISME J. 7: 937-948. https://doi.org/10.1038/ismej.2012.168
- Moritsuka N, Nishikawa T, Yamamoto S, Matsui N, Inoue H, Li KZ, Inamura T. 2013. Changes in soil physicochemical properties following land use change from paddy fields to greenhouse and upland fields in the southeastern basin of Dianchi Lake, Yunnan Province, China. Pedosphere 23: 169- 176. https://doi.org/10.1016/S1002-0160(13)60004-1
- Nicolaisen MH, Risgaard-Petersen N, Revsbech NP, Reichardt W, Ramsing NB. 2004. Nitrification-denitrification dynamics and community structure of ammonia oxidizing bacteria in a high yield irrigated Philippine rice field. FEMS Microbiol. Ecol. 49: 359-369. https://doi.org/10.1016/j.femsec.2004.04.015
- Offre P, Spang A, Schleper C. Archaea in biogeochemical cycles. Annu. Rev. Microbiol. 67: 437-457. https://doi.org/10.1146/annurev-micro-092412-155614
- Peimbert M, Alcaraz LD, Bonilla-Rosso G, Olmedo-Alvarez G, Garcia-Oliva F, Segovia L, et al. 2012. Comparative metagenomics of two microbial mats at Cuatro Cienegas Basin I: ancient lessons on how to cope with an environment under severe nutrient stress. Astrobiology 12: 648-658. https://doi.org/10.1089/ast.2011.0694
- Pester M, Schleper C, Wagner M. 2011. The Thaumarchaeota: an emerging view of their phylogeny and ecophysiology. Curr. Opin. Microbiol. 14: 300-306. https://doi.org/10.1016/j.mib.2011.04.007
- Poplawski AB, Martensson L, Wartiainen I, Rasmussen U. 2007. Archaeal diversity and community structure in a Swedish barley field: specificity of the EK510R/(EURY498) 16S rDNA primer. J. Microbiol. Methods 69: 161-173. https://doi.org/10.1016/j.mimet.2006.12.018
- Ranjard L, Richaume A. 2001. Quantitative and qualitative microscale distribution of bacteria in soil. Res. Microbiol. 152: 707-716. https://doi.org/10.1016/S0923-2508(01)01251-7
- Shen JP, Cao P, Hu HW, He JZ. 2013. Differential response of archaeal groups to land use change in an acidic red soil. Sci. Total Environ. 461-462: 742-749. https://doi.org/10.1016/j.scitotenv.2013.05.070
- Sims JT. 2000. Soil test phosphorus, pp. 20-21. In Olsen P(ed.). Methods for Phosphorus Analysis for Soils, Sediments, Residuals and Water. Kansas State University, Manhattan.
- Sparks DL, Page A, Helmke P, Loeppert R, Soltanpour P, Tabatabai M, et al. 1996. Methods of Soil Analysis. Part 3. Chemical Methods. Soil Science Society of America Inc.
- Tamames J, Abellan JJ, Pignatelli M, Camacho A, Moya A. 2010. Environmental distribution of prokaryotic taxa. BMC Microbiol. 10: 85. https://doi.org/10.1186/1471-2180-10-85
- Teske A, Sorensen KB. 2008. Uncultured archaea in deep marine subsurface sediments: have we caught them all? ISME J. 2: 3-18. https://doi.org/10.1038/ismej.2007.90
- Thauer RK, Kaster AK, Seedorf H, Buckel W, Hedderich R. 2008. Methanogenic archaea: ecologically relevant differences in energy conservation. Nat. Rev. Microbiol. 6: 579-591. https://doi.org/10.1038/nrmicro1931
- Tischer K, Kleinsteuber S, Schleinitz KM, Fetzer I, Spott O, Stange F, et al. 2013. Microbial communities along biogeochemical gradients in a hydrocarbon-contaminated aquifer. Environ. Microbiol. 15: 2603-2615. https://doi.org/10.1111/1462-2920.12168
- Wang J, Gu JD. 2013. Dominance of Candidatus Scalindua species in anammox community revealed in soils with different duration of rice paddy cultivation in Northeast China. Appl. Microbiol. Biotechnol. 97: 1785-1798. https://doi.org/10.1007/s00253-012-4036-x
- Wang J, Wang W, Gu JD. 2014. Community structure and abundance of ammonia-oxidizing archaea and bacteria after conversion from soybean to rice paddy in albic soils of Northeast China. Appl. Microbiol. Biotechnol. 98: 2765-2778. https://doi.org/10.1007/s00253-013-5213-2
- Wu T, Chellemi DO, Graham JH, Martin KJ, Rosskopf EN. 2008. Comparison of soil bacterial communities under diverse agricultural land management and crop production practices. Microb. Ecol. 55: 293-310. https://doi.org/10.1007/s00248-007-9276-4
- Wu Y, Lu L, Wang B, Lin X, Zhu J, Cai Z, et al. 2011. Longterm field fertilization significantly alters community structure of ammonia-oxidizing bacteria rather than archaea in a paddy soil. Soil Sci. Soc. Am. J. 75: 1431. https://doi.org/10.2136/sssaj2010.0434
- Yang SZ, Wen X, Jin HJ, Wu QB. 2012. Pyrosequencing investigation into the bacterial community in permafrost soils along the china-russia crude oil pipeline (CRCOP). PLoS One 7: e52730. https://doi.org/10.1371/journal.pone.0052730