Effects of reforestation on ammonia-oxidizing

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Apr 24, 2018 - nitrifiers, especially AOA abundance in acidic forest soils. ... to developmental status of revegetated forests for management through microbial analysis. ...... served in another reforestation project also in southern China.
Applied Microbiology and Biotechnology (2018) 102:5309–5322 https://doi.org/10.1007/s00253-018-8873-0


Effects of reforestation on ammonia-oxidizing microbial community composition and abundance in subtropical acidic forest soils Ruo-Nan Wu 1 & Han Meng 1 & Yong-Feng Wang 2,3 & Ji-Dong Gu 1,4 Received: 27 August 2017 / Revised: 3 February 2018 / Accepted: 10 February 2018 / Published online: 24 April 2018 # Springer-Verlag GmbH Germany, part of Springer Nature 2018

Abstract Forest ecosystems have great ecological values in mitigation of climate change and protection of biodiversity of flora and fauna; reforestry is commonly used to enhance the sequestration of atmospheric CO2 into forest storage biomass. Therefore, seasonal and spatial dynamics of the major microbial players in nitrification, ammonia-oxidizing archaea (AOA) and bacteria (AOB), in acidic soils of young and matured revegetated forests were investigated to elucidate the changes of microbial communities during forest restoration, and compared to delineate the patterns of community shifts under the influences of environmental factors. AOA were more abundant than AOB in both young and matured revegetated forest soils in both summer and winter seasons. In summer, however, the abundance of amoA-AOA decreased remarkably (p < 0.01), ranging from 1.90 (± 0.07) × 108 copies per gram dry soil in matured forest to 5.04 (± 0.43) × 108 copies per gram dry soil in young forest, and amoA-AOB was below detection limits to obtain any meaningful values. Moreover, exchangeable Al3+ and organic matter were found to regulate the physiologically functional nitrifiers, especially AOA abundance in acidic forest soils. AOB community in winter showed stronger correlation with the restoration status of revegetated forests and AOA community dominated by Nitrosotalea devanaterra, in contrast, was more sensitive to the seasonal and spatial variations of environmental factors. These results enrich the current knowledge of nitrification during reforestry and provide valuable information to developmental status of revegetated forests for management through microbial analysis. Keywords Ammonia-oxidizing archaea (AOA) . Ammonia-oxidizing bacteria (AOB) . Ammonia monooxygenase subunit A (amoA) gene . Forest restoration . Organic matter . Aluminum

Introduction Natural forests play vital roles in not only biodiversity maintenance, erosion, and preservation of soils, but also * Yong-Feng Wang [email protected] * Ji-Dong Gu [email protected] 1

Laboratory of Environmental Microbiology and Toxicology, School of Biological Sciences, Faculty of Science, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, People’s Republic of China


Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangdong Academy of Forestry, Guangzhou, People’s Republic of China


Laboratory of Microbial Ecology and Toxicology, Guangdong Academy of Forestry, Guangzhou, People’s Republic of China


State Key Laboratory in Marine Pollution, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, People’s Republic of China

climate mitigation at regional and global scales. Nonetheless, human activities of logging cause massive losses of forest biomass, and greenhouse gas emission from fossil fuel consumption and the anthropogenic impacts are evident in Americas, Asia, and Africa (Flannigan et al. 2005; Gillett et al. 2004; Laurance 1999). With the increasing awareness of sustainable development, forest restoration as an effective strategy in dealing with climate change is being taken by our society. Related research was conducted to elucidate the best approaches on recovery of the ecological functions and services of forests, mainly focusing on selection of plant species, determination of limiting nutrients, comparison of different practices, and detection of nitrification or denitrification rate during forest restoration to assess the availability of nitrogen as an essential nutrient to forest productivity (Amazonas et al. 2011; Liu et al. 2007; Mo et al. 2016). Available information about the microbial communities responsible to the crucial biogeochemical processes in the process of forest restoration is scarce. Nitrogen cycling, one of the most important biochemical processes, controls the net primary productivity in forests and


is primarily regulated by microorganisms and their activities. Nitrification, a rate-limiting step of nitrogen cycle, bridges the oxidized and reduced forms of nitrogen and makes them available to plants, but is also subject to loss due to high mobility of negative charged NO3− and NO2−. Therefore, understanding the dynamics of microorganisms responsible for nitrification in forest soils can provide valuable insights into forest restoration and effectiveness of the practice. Nitrification in acidic forest soils was first believed to be restricted to ammonia-oxidizing bacteria (AOB) as the sole group of ammonia oxidizers initially realized and they cannot be cultured at pH conditions lower than 5.5 (Hankinson and Schmidt 1988; Jiang and Bakken 1999). In addition, the rate of heterotrophic nitrification was low contributing to less than 5% of the total nitrogen mineralization rate in forest soils (Pedersen et al. 1999). Later, the discovery of ammonia-oxidizing archaea (AOA) broadened the knowledge on the responsible microorganisms for nitrification, and their greater abundance and wider ecological distribution warrant AOA as the most promising ammonia oxidizers for active nitrification in acidic forest soils, but so far neglected organisms (Francis et al. 2005; Konneke et al. 2005; Venter et al. 2004). Recently, the first obligate acidophilic AOA, Nitrosotalea devanaterra, were obtained in pure culture from agricultural acidic soils with pH 4.5 (Lehtovirta-Morley et al. 2011). But our knowledge on AOA is still limited, especially about the community compositions, and their seasonal and spatial dynamics during the forest restoration process at acidic pH. Nanling National Forest Reserve has unique geographical features and nourishes a rich flora and fauna resources with 3115 species of vascular plants, belonging to 227 genera and 1048 families (Tian et al. 2013). Due to the rich biological resources and important geographical location, plants play an important ecological role in the protection of the Pearl River Basin to the southern slope of Nanling Mountain as well as the Xiang River Basin to the north (Zhang et al. 2007). Part of the vegetation in this subtropical evergreen broadleaved forests at the low elevation around 600 m; however, it was severely affected by anthropogenic activities from deforestation to land clearing for small agriculture. In order to restore the vegetation coverage, forest restoration was carried out in the spring of 1998 by planting Chinese fir (Cunninghamia lanceolata), followed by a second round in 2008. Therefore, the closely located young (8 years) and matured (18 years) revegetated fir forests provided the basis to investigate the ammonia oxidizers in the acidic forest soils during the restoration process of revegetated forests to provide valuable insights into forest restoration and practices on scientific ground. In addition, the seasonal transition and spatial variations of AOA and AOB abundance and community compositions in both young and matured revegetated fir forest soils were used for a more comprehensive understanding of nitrification during the restoration process of revegetated forests.

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Materials and methods Site description and sample collection Soil samples were collected from two revegetated forests in the Nanling National Nature Reserve (24°37′–24°57′ N, 112°30′–113°04′ E) Guangdong province of China on 8th January 2015 (winter) and 5th August 2015 (summer). The young (Y) and matured (M) revegetated fir forests share comparable geographical locations in the Nanling Mountains and were planted with the same Chinese fir (C. lanceolata), but at different restoration stages, i.e., 8 and 18 years respectively. For each forest, both surface layer (A0 layer, 0–2 cm, with the removal of litter coverage) and lower layer (B layer, 18–20 cm) soil samples were collected from triplicated locations with randomization as the layers of soil were found with differentiated nutrient levels and microbial activities in the previous studies (Gan et al. 2016; Meng et al. 2016). The homogenized soil samples of each replicate were kept in a cooler with ice bags on site and immediately transported to laboratory for the follow-up soil physiochemical and molecular analyses. Soil samples subjected to DNA extraction were stored at − 20 °C.

Physicochemical analysis Physicochemical analyses of soil samples was conducted following the Methods of Agriculture Chemical Analysis (Lu, 2000). Briefly, pH was detected at soil to water ratio of 1:1 (Starter 3C, OHAUS, Pine Brook, NJ, USA). Organic carbon was measured using the sulfuric acid dichromate digestion method and the corresponding organic matter content was calculated with a ratio of organic matter to organic carbon of 1.724 (Nelson and Sommers 1996). Soil extracts using 2 M KCl were analyzed for NH4+–N and NO3−–N with Nessler’s reagent colorimetry and ultra-violet spectrophotometry (UV– Vis spectrophotometer, 752 N type, Shanghai Jingke Co., Shanghai, China). Soil exchangeable Al3+ extracted with 2 M KCl was quantified by using ICP-OES (Perkin Elmer Optima 8300, Waltham, MA, USA).

Nucleic acid extraction Genomic DNA was extracted from each replicate of the soil samples in duplicates and conducted individually using the PowerSoil DNA Isolation Kit (MO BIO, Carlsbad, CA, USA), according to the manual of the manufacturer. The duplicated DNA extracts of each replicate were pooled together and stored under − 20 °C to serve as templates for subsequent polymerase chain reactions (PCR). Quality and concentration of the acquired DNA were detected using the Nanodrop Spectrophotometer ND-1000 (ThermoFisher, Waltham, MA, USA).

Appl Microbiol Biotechnol (2018) 102:5309–5322

Real-time PCR In order to minimize the variations by soil heterogeneity rather than different forest types, mixture of DNA extracts from the replicates of the same soil layer of each forest type were used as templates to determine the gene copies of amoA-AOA and amoA-AOB in iTaq Universal SYBR Green Supermix (BIORAD, Hercules, CA, USA) by real-time PCR (ABI StepOnePlus, ABI, Life Tech., Foster City, CA, USA). Realtime PCR was performed according to the manufacturer’s instructions and the primer sets used here are shown in Table 1. An internal control method was implemented as described previously to calibrate the potentially inhibitory effects from extract matrix (Wu et al. 2017). Briefly, plasmid DNA (pUC19-plasmid DNA, Invitrogen, Carlsbad, CA, USA) was used as the internal control and amplified under the identical PCR conditions of amoA-AOA or amoA-AOB gene amplification by the same primer set M13 R/F to measure the differences of PCR efficiency among samples for calibration (Horz et al. 2004). Melting curve analysis was performed to determine the melting points of the amplification products to assess the reaction specificity.

amoA gene amplification General PCR amplification of amoA-AOA and amoA-AOB was performed using the same primer sets mentioned in the real-time PCR (Table 1) and the reaction mixture (50 μL) contained 2 μL of DNA template (20–40 ng per reaction), 1 μL of bovine serum albumin (BSA) (100 mg mL −1; Roche), 5 μL of 10× GoTaq Flexi buffer (Promega, Hong Kong), 1 μL of forward and 1 μL of reverse primers (20 μM), and 0.5 μL of GoTaq Flexi polymerase (5 U μL−1; Promega, Hong Kong). The PCR condition was set as 95 °C for 5 min followed by 30 cycles (amoA-AOA) or 35 cycles (amoA-AOB) of 95 °C for 45 s, 53 °C (amoA-AOA) or 55 °C (amoA-AOB) for 60 s, and 72 °C for 60 s. For samples with amoA-AOB in very low abundance, nested PCR was carried out according to the previous studies by using primer set A189 and amoA-2R for the first-round amplification and amoA-1F/ 2R for the second (Horz et al., 2004) (Table 1).

Clone library construction and sequencing Clone libraries were constructed based on the amplified amoA-AOA and amoA-AOB genes through general PCR with specific primers. PCR products were obtained from sizeverified gel bands and purified by Illustra GFX PCR DNA and Gel Band Purification Kits (GE Healthcare Sciences, Little Chalfont, Buckinghamshire, UK). The purified DNA fragments ligated to pMD18 T-vector (pMD™ 18-T Vector Cloning Kit, Takara, Japan) and transformed into Escherichia coli DH5α competent cells (pMD™ 18-T Vector Cloning Kit,


Takara International, Hong Kong) subjected to clone library construction, following the manufacturer manual. The triplicates of the same soil layer of each forest were analyzed separately. A total of 30 colonies for each clone library were randomly selected for sequencing after size verification of the PCR amplicons using M13 F/R primer set. Sequencing was performed with the ABI 3730xl DNA analyzer (Applied Biosystems, Foster City, CA, USA).

Phylogenetic analysis Sequences from short or failed reads or of apparent chimeric origin were excluded from further analysis. The remaining quality sequences were fed to the RDP FunGene analyzing platform (Fish et al. 2013). The nucleotide sequences were translated into amino acid sequences using Framebot to detect and correct frameshifts, followed by alignment using the HMMER3 aligner. The deduced amino acid sequences were clustered into operational taxonomic units (OTUs) by mcCLUST (RDP) executed by the complete-linkage clustering method with distance cutoff of 3%. The cutoff is selected based on the pairwise distances of amoA protein sequences of the known AOA species (Wu et al. 2017). The representative sequences were selected from each OTU and were aligned with well-defined phylogenetic relatives retrieved from the GenBank database using Protein BLAST (National Center For Biotechnology Information) by the method of ClusterW in MEGA 6 software (Tamura et al. 2013; Thompson et al. 1994). The aligned sequences were used to construct the phylogenetic trees using the maximum likelihood method implemented in the PhyML program (v3.0) (Guindon et al., 2010) with 1000 bootstraps.

Statistical analysis The sequence diversity was evaluated by Chao1 and Shannon indices calculated with cutoff of 3% based on deduced amino acid sequences by the RDP FunGene analyzing platform (Fish et al. 2013). Student’s t test was used to differentiate the statistical differences among two groups. Multiple group comparisons were made by one-way ANOVA with the Tukey post test (Version 5.0, GraphPad Software Inc., La Jolla, CA) and considered significantly different at p < 0.05. The correlation between two variables was tested by the Pearson productmoment correlation method (SPSS, 16.0, IBM, Armonk, New York, USA).

DNA sequence accession numbers The amoA gene sequences reported in this study have been deposited in GenBank under accession numbers KX619853 KX619934 (AOA) and KX619935 - KX620007 (AOB).

5312 Table 1

Appl Microbiol Biotechnol (2018) 102:5309–5322 PCR amplification primers and reaction conditions

Microbe/amplified DNA

Primer name

Sequence (5′-3′)

Annealing temperature (°C)






Francis et al. 2005




Francis et al. 2005


pUC19-plasmid DNA

amoA-F (amoA332)



Rotthauwe et al. 1997

amoA-R (amoA822)



Rotthauwe et al. 1997




Horz et al. 2004




Van Hoek et al. 1998




Van Hoek et al. 1998

Results Physicochemical characteristics of the revegetated forests The seasonal and spatial changes of pH, organic matter, NO3−–N, NH4+–N, and exchangeable Al3+ are shown in Table 2 and C:N ratio was calculated to indicate the nutritional status and mineralization potential. The contents of organic matter were generally higher in summer than in winter (young revegetated forest surface layer (YS), matured revegetated forest surface layer (MS), and matured revegetated forest lower layer (ML), p < 0.05). A more remarkable seasonal change of organic matter was found in mature forest than in young forest, possibly due to relative higher organic accumulation of Table 2

litters in matured forest with larger trees and denser canopies. The higher organic matter contents in the surface soil layers for both young and mature forests in summer and winter further supported that decomposition of deposition on the surface was the main source of organic carbon detected (YS-winter/summer (W/S) and young revegetated forest lower layer (YL)-W/S, p < 0.05; MSW/S and ML-W/S, p < 0.05). Similar to organic matter, NO3− and NH4+ levels were generally higher in the corresponding soil surface layers (YS-W and YL-W, NO3−– N, p < 0.05; MS-W and ML-W, NO 3 − –N, NH 4 + –N, p < 0.05). The concentrations of exchangeable Al3+ were statistically comparable in both the surface and lower soil layers for both young and mature forests, but exchangeable Al3+ in matured forest, unlike in young forest, did not fluctuate greatly between the seasons. The calculated

Physicochemical parameters of the forest soil samples used in this study

Forest type



Young Surface layer (YS) Winter revegetated forest (YS-W) Summer (Y) (YS-S) Lower layer (YL) Winter (YL-W) Summer (YL-S) Matured Surface layer (MS) Winter revegetated forest (MS-W) Summer (M) (MS-S) Lower layer (ML) Winter (ML-W) Summer (ML-S)

NO3−–N (mg kg−1)

NH4+–N (mg kg−1)

Exchangeable Al3+ C:N (cmol kg−1) (mass)

4.45 ± 0.07 64.83 ± 7.01*× 12.48 ± 1.94×

43.48 ± 7.08

9.43 ± 0.39*

17.38 ± 3.43*×

4.38 ± 0.12 85.75 ± 2.19*× 9.99 ± 1.62

46.67 ± 11.97

7.21 ± 0.22*

14.83 ± 1.01*

4.51 ± 0.04 39.80 ± 9.07×

6.97 ± 0.28×

28.09 ± 5.06

8.65 ± 0.92

12.34 ± 0.40×

4.32 ± 0.04 45.37 ± 6.21×

4.55 ± 2.13

28.40 ± 5.33

6.95 ± 0.73

16.02 ± 4.49

4.26 ± 0.09 75.83 ± 7.08*× 13.56 ± 1.84*× 42.11 ± 9.21×

7.46 ± 0.65

15.46 ± 2.02

4.36 ± 0.11 96.43 ± 0.57*× 9.36 ± 0.88*

63.68 ± 21.12

8.62 ± 0.28

15.43 ± 1.35

4.31 ± 0.12 40.90 ± 3.21*× 5.54 ± 0.49×

25.61 ± 5.21*× 7.46 ± 0.27

13.91 ± 1.87

4.26 ± 0.01 59.10 ± 3.60*× 5.99 ± 0.60

45.74 ± 11.79* 7.46 ± 0.62

15.11 ± 1.17


Organic mater (g kg−1)

Data were displayed in the form of mean ± SD (n = 3); one-way ANOVA, Tukey post hoc multiple comparisons and Student’s t test are used to detect the significance of difference *Variables with significant seasonal differences (p < 0.05, two-tailed) ×

Spatial variation by soil depth (p < 0.05, two-tailed)

Spatial variation by soil depth by different forest types (p < 0.05, two-tailed)

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C:N ratio among all sampling sites was lower than 20, implying a relatively active turnover rates of nutrients through decomposition and mineralization by microorganisms in the two revegetated forests.

Seasonal and spatial variation of amoA-AOA and amoA-AOB gene abundances The abundances of AOA and AOB of the two revegetated forests were estimated by the gene copy number of amoAAOA and amoA-AOB genes through real-time PCR as shown in Fig. 1. In winter, the copy number of amoA-AOA gene ranged from 3.96 (± 0.58) × 109 (YL) to 6.34 (± 0.66) × 1010 (MS) and amoA-AOB ranged from 1.38 (± 0.19) × 105 (MS) to 1.73 (± 0.29) × 105 (YS). amoA-AOA gene was numerically dominant over amoA-AOB significantly (p < 0.05). In summer, however, the abundance of amoA-AOA decreased remarkably (p < 0.01), ranging from 1.90 (± 0.07) × 108 (MS) to 5.04 (± 0.43) × 108 (YS), and amoA-AOB was below detection limits to obtain any meaningful values. For the spatial variation by soil depth, amoA-AOA gene abundances in surface layers were significant higher

Fig. 1 Abundance of amoA-AOA and amoA-AOB genes in winter and summer. Significant spatial variation by soil depth is labeled by different letters, a or b (p < 0.05); significant spatial variation by forest types is labeled by letter m or n (p < 0.05).


than those in the corresponding lower layers in winter. However, in summer, an opposite trend was observed in the matured forest but not in the young forest. Besides, abundances of amoA-AOA in mature forest were much higher than that in young forest for both surface and lower soil layers in winter (p < 0.05). Therefore, soil stratification, seasonality, and restoration stage of the revegetated forests may all contribute to AOA survival, proliferation, and even their physiological functions.

Phylogeny reconstruction of AOA and AOB based on amoA genes All amoA-AOA representative sequences in summer and winter were grouped into six clusters based on the relative similarity to phylogenetic reference sequences (Fig. 2). Cluster 1 sequences, detected among all sampling sites in both winter and summer, showed the same identity index with all the reference sequences in Nitrososphaera/ group 1.1b/soil AOA and formed a new mirrored structure, namely the Nitrososphaera sister group. Sequences identified as N. gargensis-like AOA were grouped into cluster 2 (94–95%), cluster 3 (91%), and cluster 4 (95–98%) belonging to Nitrososphaera/group 1.1b/soil AOA, and the majority of them were recovered from lower soil layers in winter. The rest of the sequences were identified as N. devanaterra or Nitrosotalea Nd2-like AOA, belonging to Nitrosotalea/group 1.1a-associated AOA and divided into two clusters, namely cluster 5 and cluster 6. In cluster 5, sequences were less similar to N. devanaterra or Nitrosotalea Nd2 (91–93%) and only detected in lower soil layers of matured and young revegetated forests in winter and summer. Cluster 6 sequences showed higher identity indices to N. devanaterra or Nitrosotalea Nd2 (94–98%). No cluster was found to be exclusive to one specific restoration stage of the revegetated forests. In winter, amoA-AOB was detected at all sampling sites. But, in summer, nested PCR was performed and was able to recover amoA-AOB from only one or two replicates in YS-S, YL-S, and ML-S, and none from MS-S. The retrieved sequences, however, showed high similarities from each other. All verified amoA-AOB representative sequences from winter and summer, together with both cultured and uncultured reference sequences, formed a reliable phylogenetic structure (Fig. 3). Both Nitrosospira- and Nitrosomonas-like sequences were detected. Sequenced belonging to Nitrosospira were further divided into seven clusters. Cluster 1 sequences were defined as Nitrosospira briensis-like (96–99%) and Nitrosospira NI5-like (99%) AOB, and mainly recovered from the lower soil layers. Sequences in cluster 2 were affiliated to Nitrosospira sp. Nsp1 (99%) and only found in matured forest. Cluster 3 and cluster 4 were composed of Nitrosospira sp. Nsp 39-19-like and Nitrosospira sp. En13-


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Fig. 2 Maximum likelihood method-constructed phylogenetic tree based on deduced amoAAOA amino acid sequences. Bootstrap value is set to 1000 replicates and only the values above 50% are shown Cluster 1

Nitrososphaera sister group

Cluster 2

Cluster 3 Nitrososphaera / Group 1.1b /soil Cluster 4 Nitrosocaldus/ ThAOA/HWCGIII Cluster 5

Nitrosotalea/ Group 1.1a associated Cluster 6

Nitrosoarchaeum, Nitrosopumilis/ Group 1.1a /marine

like AOB, respectively. Cluster 5 containing a few sequences from the matured forest to be Nitrosospira tenuis-like, but located far away from N. tenuis reference sequences in the reconstructed phylogenetic tree with high bootstrap support, may indicate a new cluster which is not widely recognized. Cluster 6 and cluster 7 included the sequences similar to another two Nitrosospira species, Nitrosospira multiformis (97– 99%), and Nitrosospira AF (99%). In Nitrosomonas, only Nitrosomonas europaea/mobilis lineage-like (99%) sequences were retrieved and grouped into cluster 8. In summer, sequences from young forest were mainly grouped into cluster 4 and cluster 7, and N. europaea/

mobilis-like AOB were only found in matured forest. The unique clusters, such as cluster 2, cluster 3, and cluster 5, were specific to AOB communities in matured forest, which may imply a higher microbial diversity of matured forest and the presence of newly evolved AOB species along the restoration development of the revegetated forests.

Seasonal and spatial variation of AOA and AOB diversity and community structure The high coverage indices suggested the sufficient sampling efforts for both AOA and AOB communities (Table 3). AOA

Appl Microbiol Biotechnol (2018) 102:5309–5322 Fig. 3 Maximum likelihood method-constructed phylogenetic tree based on deduced amoAAOB amino acid sequences. Bootstrap value is set to 1000 replicates and only the values above 50% are shown


Cluster 1

Cluster 2 Cluster 3

Cluster 4


Cluster 5

Cluster 6

Cluster 7

Cluster 8

and AOB communities showed clear spatial variations by soil depth, as that the diversity (Shannon) and richness (Chao1) of lower layers were higher in the corresponding surface layers of both young and mature forests. Moreover, AOA and AOB communities in matured forest were generally more diverse than those in young forest. All verified AOA sequences in summer and winter were combined to make comparisons among microbial community structures through principal coordinates analysis (PCoA) based on weighted UniFrac distances executed by Mothur (v. 1.30.0) (http://www.mothur.org) (Schloss et al. 2009) (Fig. 4). Summer AOA communities tended to cluster at one


side of the axis with the highest explanation percentage, P1 (64.66%), with some overlapping with winter AOA communities. For winter AOA communities, soil stratification tended to separate them apart by soil layers as located at the opposite sides of P1 (64.66%). In contrast, summer AOA community structures were slightly under the influence of restoration development of revegetated forests, as the AOA communities of young and matured forests were shown at the different sides of P2 (17.03%). Besides the similarity, AOA community of YS in winter was far away from the rest, indicating its distinguished and unique community compositions.

Matured revegetated forest (M)

OTUs were clustered based on the deduced amino acid sequences; Diversity (Shannon) and richness (Chao1) indexes were calculated with 3% cutoff; coverage were calculated in a formula, Coverage = 1(NO. Of OTU/NO. Of verified sequences)

77.14 2.02 29.33 24 86.08 1.89 11.25 11 85.59 19.75 16


81.05 1.86 27.33 18 88.24 1.84 8.00 8 93.04 8.00 8


84.91 2.29 17.50 16 85.29 1.78 11.00 10 85.26 14.50 14


2.09 15.50 15 84.38 1.61 17.50 10 96.08 1.06

Surface layer (YS) Lower layer (YL) Surface layer (MS) Lower layer (ML) Young revegetated forest (Y)


Shannon (3%) Chao 1 (3%) Coverage (%) Shannon (3%) Chao 1 (3%)


Shannon (3%) Chao 1 (3%) No. of OTU (3%) No. of OTU (3%)

No. of OTU (3%)

Winter Summer Winter

Coverage (%)

AOB AOA Depth Forest type

Diversity characteristics of AOA and AOB communities at Nanling Forest Nature Reserve Table 3


Appl Microbiol Biotechnol (2018) 102:5309–5322 Coverage (%)


Seasonal and spatial variation of AOA and AOB community compositions Summer and winter sequences were compiled together, clustered into OTUs (3%), and displayed in the heatmaps to show the numerical contribution of each OTU to the microbial community (Fig. 5a, c). The identified OTUs were further grouped into species according to the inference of the closest phylogenetic references. The proportions of the detected species in each soil sample are shown in Fig. 5b, d. OTU1 to OTU8 belonged to Nitrosotalea/group 1.1a-associated-like AOA, and OTU9 to OTU14 were Nitrososphaera sister group-like AOA. The rest of the OTUs were classified as Nitrososphaera/group 1.1b/soil AOA (Fig. 5a). Summer AOA communities among all sampling sites tended to share more OTUs with each other rather than with winter communities, which was consistent with the observation in PCoA. Among OTUs with relative abundances higher than 1% in at least one sample, OTU4, OTU5, and OTU6 (Nitrosotalea/group 1.1aassociated AOA); OTU12 and OTU13 (Nitrososphaera sister group); and OTU18 and OTU19 (Nitrososphaera/group 1.1b/ soil AOA) were specific to summer AOA communities. In contrast, OTU7 (Nitrosotalea/group 1.1a-associated AOA) and OTU17 and OTU21 (Nitrososphaera/group 1.1b/soil AOA) were winter AOA community-specific. The shift in OTU patterns from winter-specific to summer-specific AOA implies the transition of microbial communities in response to the seasonality. A clear spatial variation by soil depth can also be observed for similar patterns in OTUs of the same layers, especially in OTU1, OTU2, and OTU3 (Nitrosotalea/group 1.1a-associated AOA), but was not revealed in PCoA. Same as for the results in PCoA, the heatmap pattern of YS in winter was different from the rest of the AOA communities, as that the dominant group of AOA was recognized as the Nitrososphaera sister group and few Nitrosotalea/group 1.1a-associated AOA were recovered. The AOA community in matured forest presented a broader

Fig. 4 Principal coordinates analysis (PCoA) using weighted UniFrac algorithm of AOA communities in winter and summer

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Fig. 5 Community compositions of AOA (winter and summer) and AOB (winter). 21 OTUs of AOA communities were included and plotted in heatmap a; identified OTUs further grouped into species and displayed in

b; 21 OTUs of AOB communities were shown in heatmap c and the proportions of identified species were in d

phylogenetic distribution as possessing more OTUs than in young forest. N. devanaterra and the Nitrososphaera sister group were the major AOA species among all sampling sites in both winter and summer. AOA belonging to the Nitrososphaera sister group were most abundant in winter (except for YL-W) and summer AOA communities were dominated by N. devanaterra (except for MS-S). The relative abundances of N. gargensis and the Nitrososphaera sister group decreased from winter to summer, while N. devanaterra increased among all the sampling sites. Therefore, seasonal

transitions and spatial variation (soil depth) of the sampling sites play a more active role on AOA community compositions than the restoration stage of the revegetated forests. For winter AOB communities, the dominant AOB in YS, MS, and ML, belonging to genus Nitrosospira, were mainly composed of Nitrosospira multiformis, Nitrosospira sp. En13, Nitrosospira sp. Nsp1, Nitrosospira sp. Nsp 39-19, Nitrosospira AF, Nitrosospira tenuis, Nitrosospira sp. Nl5, and Nitrosospira briensis-like sequences, among which N. briensis-like AOB weighed highest in MS and ML, and


Nitrosospira sp. En13 was the dominant AOB in YS. In YL, N. europaea/mobilis-like AOB were the most abundant and the rest contributed for only a minor proportion. OTU1 (N. briensis-like AOB) was shared among all sampling sites. Young forest possessed a lower proportion of OTU1, OTU2, and OTU3 (N. briensis-like AOB), but with higher proportion of OTU18, OTU19, and OTU21 (N. europaea/mobilis), compared to matured forest. AOB from the same restoration stage tended to share more OTUs and AOB communities of surface and lower soil layers were more similar in matured forest. Unlike AOA communities, the community composition of AOB in winter was mainly driven by the restoration stage of revegetated forests.

Discussion Functional dominance of AOA and the increased abundance during reforestation Average nitrification activity and abundance of ammonia oxidizers are two main determinants of their potentially functional dominance in nitrification. The nitrification activity of soil AOA is generally 10 times less efficient than that of soil AOB. Therefore, AOA can be regarded to potentially dominate nitrification only if the ratio of AOA to AOB biomass or cell abundance is larger than 10 (Prosser and Nicol 2012). The general consistency of the relative abundances between amoA gene and transcript at the same sampling sites in our previous study indicates the active function of ammonia oxidizers and their comparable expression levels (Wu et al. 2017). Therefore, amoA gene can be used as the indicators to reveal the potential activity of ammonia oxidizers and the abundance difference with magnitude of orders implies the relatively functional dominance between AOA and AOB. Due to the nature of acidic soils, AOA to AOB ratio of both young and matured revegetated forests in winter was much higher than 10, when 2.5 copies of amoA gene in a soil AOB cell and one in a soil AOA cell are assumed (Hallam et al. 2006; Norton et al. 2002), and AOB in summer were rarely to be detected. The dominance of archaeal ammonia oxidation is consistent with other acidic soil studies (Gubry-Rangin et al. 2010; He et al. 2007; Nicol et al. 2008; Yao et al. 2011; Zhang et al. 2012). The numerical advantage of AOA over AOB may suggest their potentially functional dominance. In addition, AOB abundance in winter did not show any significant differences among sampling sites, and AOA abundance, on the contrary, did fluctuate a lot along with environmental gradients. Thus, due to the abundant dominance of AOA over AOB and their active responses to the environmental changes of the sampling sites, AOA may be the active ammonia oxidizers responsible for nitrification in acidic soils of revegetated forests under restoration process.

Appl Microbiol Biotechnol (2018) 102:5309–5322

Moreover, the functionally important ammonia oxidizers, AOA, were generally more abundant in matured forest than young forest, in both surface and lower layers in winter and lower layer in summer as well. Matured revegetated forest may have higher capability in nitrification, therefore making AOA abundance a potent bio-indicator of nitrification ability in acidic forest soils during the process of forest restoration. In a reforestation study in subtropical eastern Australia, where forests were previously destroyed into pasture or agriculture, N cycling including the nitrification rate was partially recovered at the revegetated sites mainly by restoring the disturbed soil properties such as soil bulk densities, pH, and phosphate levels (Paul et al. 2010). Similarly, the increased net nitrification and N mineralization rate were observed in another reforestation project also in southern China and consistently changed along with the stand age in all types of tested plantations (Mo et al. 2016). Therefore, increased abundance of potentially active ammonia oxidizers, AOA in acidic soils here, may indicate recovery of nitrification ability during reforestation.

Season and soil depth play a more important role in shaping AOA communities 1.1a associated and 1.1b thaumarchaea were also recovered as the active ammonia oxidizes in other related acidic soil research (Gubry-Rangin et al. 2010; Zhang et al. 2012). In this studies, we further point out the sister group with a different phylogenetic placement from 1.1a-associated AOA as one of the major groups. There are no drastic differences of AOA communities between young and matured revegetated forest but the matured forest presented a greater diversity as possessing more OTUs than those in young forests, making the matured revegetated forest more stable under fluctuations of environmental conditions. Therefore, the potentially functional ammonia oxidizer communities tend to be relatively stable in composition but possibly improve the ecological activity by increasing their abundance. PCoA and OTU analyses which illustrated seasonal and spatial variation can better tell apart AOA communities as great similarities in community structures and compositions were shared only among summer AOA. Furthermore, seasonally specific OTUs identified within the three main AOA species further suggest that AOA communities actively respond to the seasonality. The seasonal changes of relative abundance of three main AOA species during the restoration process of the revegetated forests were consistent for all sampling sites as the proportion of N. gargensis-like and Nitrososphaera sister group-like AOA decreased from winter to summer, while the proportion of N. devanaterra-like AOA increased. As mentioned in OTU analysis on the spatial variation by soil depth, organic matter was found to accumulate more in

Appl Microbiol Biotechnol (2018) 102:5309–5322

the surface layers than the corresponding lower layers in both young and matured revegetated forests. The concurrence on the changes in organic matter concentration and shifts in AOA community composition may suggest that organic matter is also an important environmental parameter in shaping AOA communities and leading to the seasonal and spatial variation of the microbial communities during the restoration process of the revegetated forests. In general, AOA community compositions and structures, unlike AOA abundance, may be more sensitive to the seasonal and spatial (soil depth) variations of environmental factors than the restoration stage of the revegetated forests, among which organic matter might play an important influence upon.

AOB communities and restoration process Apart from the strong seasonal variation of AOB abundance found during the restoration, recovered AOB community compositions in winter showed stronger correlation with restoration stage rather than the spatial variation by soil depth. Nitrosolobus sp. Nl5- and Nitrosospira sp. Nsp1-like AOB were only retrieved from the lower layer of matured forest and Nitrosospira AF-like AOB was found to be young forest-specific. Besides, the young revegetated forest possessed a lower proportion of N. briensis-like AOB, while a higher proportion of N. europaea/mobilis-like AOB, compared to the matured revegetated forest. The increasing dominance of N. briensislike AOB and the decreasing proportion of N. europaea/ mobilis-like AOB may be sensitive indicators of forest restoration, as the AOB communities in the matured natural forests previously investigated in Nanling Mountains were also found dominated by N. briensis while with a minor composition of N. europaea/mobilis (Wu et al. 2017). N. europaea/mobilis lineage belonging to the genus Nitrosomonas was first reported to be the dominant βProteobacteria ammonia oxidizers in acidic forest soils (Carnol et al. 2002), consistent with observation in young revegetated forest of this study. But they were later replaced by Nitrosospira during the forest restoration, probably because of the nitrogen deposition, since Nitrosospira are more frequently retrieved from high-nitrogen loading soils such as forest (Schmidt et al. 2007). The transition of microbial AOB community compositions suggests that acidic pH is an acute environmental factor determining the dominant AOB species and ones which favor and adapt to the amended environment after reforestation will evolve and further count for major species in acidic soils of revegetated forests. Therefore, studying the dynamic patterns of evolved AOB species adapting to the restored forest soils can reflect the different sensitivities to environmental factors and inform the restoration status of the revegetated forests as well.


Influence of environmental factors on AOA communities The concentration of organic matter was generally higher in the soil of matured forests. The increased plant biomass deposited in soil and well-developed root system in mature revegetated forests assisting to fix atmospheric carbon can increase soil carbon storage (Chen et al. 2017; De Camargo et al. 1999). C/N ratio here, however, did not vary much along the reforestation process. Deposition of nitrogen, possibly organic nitrogen, is potentially higher in mature revegetated forest soils since nitrate and ammonia concentrations did not show much differences, which may reflect on the higher AOA abundances, while the availability of nitrogen may limit its direct impact on ammonia oxidizers due to the organic form and/or redistribution of C and N from soil to plants after reforestation (Parolari et al. 2017). Therefore, further investigation of carbon-nitrogen condition and modeling during reforestation is needed. In the matured forest, exchangeable Al3+ did not fluctuate a lot, suggesting that matured revegetated forest may be able to actively mitigate the toxicity from dissociation of Al3+, rather than selecting Al-tolerant species as winter AOA communities did not differ from each other according to forest types. In summer, exchangeable Al3+ was negatively correlated with AOA abundance (p < 0.01; Table 4), suggesting that dissociated Al3+ can pose a negative effect on AOA growth. Acidic pH, either resulting from soil indigenous property or proton surplus due to nitrate leaching, can mobilize Al species that are toxic to cells (Kochian et al. 2015; Matson et al. 2002). Besides the exchangeable Al3+-regulated AOA abundance, Al also plays a crucial role in shaping AOA community compositions. For instance, distinct from other sampling sites, the winter AOA community in the surface layer of the young forest (YS-W) was dominated by the Nitrosotalea sister group but few Nitrosotalea/group 1.1a-associated AOA were recovered. The concentration of exchangeable Al3+, a toxic substance to ammonia oxidizers, was also found to be highest in YS-W, while lowest in summer, parallel to the drastic shift of community compositions and the seasonal specific AOA species found in YS-W. As a result, AOA abundance is sensitive to the toxicity of dissociated Al3+ and organic acids in acidic soils, making it a qualified indicator to inform the environmental status. AOA abundance dropped drastically in both young and matured revegetated forests in summer when organic matter was accumulated. As suggested previously, the potential toxicity of organic acids in acidic soils and/or the induced indirect competition with heterotrophs might contribute to the decrease of AOA abundance in summer

5320 Table 4



Appl Microbiol Biotechnol (2018) 102:5309–5322 A summary of correlation analysis (Pearson correlation) Correlation coefficient


Organic matter





− 0.14


− 0.29


− 0.74

Organic matter NO3−–N NH4+–N

− 0.14 0.22 − 0.29 0.52

1.00 0.75** 0.75** 0.33

0.74** 1.00 0.74** 0.43

0.75** 0.74** 1.00 0.60

0.33 0.43 0.60 1.00

0.53 0.18 0.42 − 0.51

− 0.74** 1.00

0.53 0.15

0.18 0.26

0.42 − 0.21

− 0.51 − 0.24

1.00 − 0.14

0.15 0.26 − 0.21 − 0.24

1.00 0.67* 0.71** 0.76**

0.66* 1.00 0.63* 0.37

0.71** 0.63* 1.00 0.73**

0.76** 0.37 0.73** 1.00

− 0.58 − 0.02 − 0.29 − 0.71**

− 0.14

− 0.58

− 0.02

− 0.29

− 0.71**


Exchangeable Al3+ AOA abundance pH Organic matter NO3−-N NH4+-N Exchangeable Al3+ AOA abundance

Exchangeable Al

AOA abundance

*Correlation is significant at the 0.05 level (2-tailed) **Correlation is significant at the 0.01 level (2-tailed)

(Baker-Austin and Dopson 2007; Lehtovirta-Morley et al. 2014; Pennington and Ellis 1993; Wu et al. nonpublished results). For spatial variation by soil depth in winter, the concentrations of organic matter and AOA abundance were all higher in surface layers, which is different from the previous observation and may suggest a second mechanism of the interactions. Organic carbon loading in winter was not as high as in summer to exert a negative effect on AOA survival and may serve as a main source of microbial available nitrogen through mineralization, evidenced by a significantly positive correlation between organic matter and NH 4 + –N (p < 0.01; Table 4) and higher levels of NH4+–N and AOA abundance in the surface soil layers (Booth et al. 2005; Stopnisek et al. 2010). Therefore, the quantity of organic matter and acidity of forest soils are two of the main determinants to AOA abundance. In conclusion, AOA, rather than AOB, were the potentially functional ammonia oxidizers in extremely acidic forest soils regardless of the re-forestry stage. Matured forest possesses more abundant and complex AOA communities than young forest. Thus, intervention of preserving diverse AOA communities may enhance forest restoration process. The correlation analysis further suggests the underlying abiotic factors influencing the functional ammonia oxidizers. The dual roles of organic matter, providing microbial available nitrogen through mineralization while through protonation and generation of toxic low-molecular-weight organic acids at higher concentration, possibly led to the seasonal and spatial patterns of microbial communities. Acidic soils are selective for the adapted ones to the niches and liberate Al3+ from soil matrix posing cellular toxicity to ammonia oxidizers. As a result, organic matter, soil acidity, and Al3+ affect the microbial abundances and community structures, and therefore, the relevant

mitigation approaches may be crucial to the success of acidic forest restoration. Funding This study was funded by National Natural Science Foundation of China (grant no. 31470562 to YFW) and by a PhD Fellowship of The University of Hong Kong (RW).

Compliance with ethical standards Conflict of interest All authors declare that they have no conflict of interest. Ethical approval This article does not contain any studies with human participants or animals performed by any of the authors.

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