Long-term net transformation and quantitative molecular mechanisms of soil nitrogen during natural vegetation recovery of abandoned farmland on the Loess Plateau of China

Science of the Total Environment 607–608 (2017) 152–159

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

Long-term net transformation and quantitative molecular mechanisms of soil nitrogen during natural vegetation recovery of abandoned farmland on the Loess Plateau of China Honglei Wang a,⁎, Na Deng a, Duoyang Wu a, Shu Hu a, Meng Kou b a b

State Key Laboratory of Soil Erosion and Dry Land Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A & F University, Yangling 712100, Shaanxi, China College of Natural Resources & Environment and History & Culture, Xianyang Normal University, Shaanxi, Xianyang 712000, China

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• The soil capability to deliver NH+ 4 and NO− 3 can recover with abandonment time. • Vegetation restoration significantly affected the enrichment of functional N genes. • N transformation processes were coupled at the molecular level (functional genes). • Relative abundance of functional gene is a good predictor of N transformation rate.

a r t i c l e

i n f o

Article history: Received 12 May 2017 Received in revised form 30 June 2017 Accepted 2 July 2017 Available online 27 July 2017 Editor: Jay Gan Keywords: Functional gene Nitrification Denitrification Grassland Loess Plateau

a b s t r a c t The availability of nitrogen (N) can alter vegetation species composition and diversity in degraded ecosystems. A − comprehensive understanding of the dynamic fate of ammonium (NH+ 4 -N) and nitrate (NO3 -N) processing and the underlying mechanisms are still lacking, particularly in arid to semi-arid degraded ecosystems. We compared and quantified the changes in the rates of net ammonification (Ra), nitrification (Rn) and total mineralization (Rm) and the abundance of bacteria, archaea, and microbial genes related to N transformation on the northern Loess Plateau of China across a 40-year chronosequence of farmland undergoing spontaneous restoration. We found that Ra, Rn, and Rm decreased in grassland soils (0–30-y sites) of different ages and exhibited significant in− creases at the 40-y sites. The capabilities of the soil to deliver NH+ 4 -N and NO3 -N were not a limiting factor during the growing season after 40 years of vegetation recovery. Soil mineral nitrogen may be not suitable for predicting and assessing the long-term (approximately 40 years) restoration success and progress. The abundance of functional N genes showed differences in sensitivity to natural vegetation recovery of abandoned farmland, which likely reflects the fact that the multi-pathways driven by N functional microbial communities had a large influence on the − dynamic fate of NH+ 4 -N and NO3 -N. Quantitative response relationships between net N transformation rates and microbial genes related to N transformation were established, and these relationships confirmed that different N transformation processes were strongly linked with certain N functional genes, and collaboratively contributed to N transformation as vegetation recovery progressed. Specifically, Ra was controlled by AOA-amoA, AOB-amoA, and nxrA; Rn was governed by napA, narG, nirK, nirS, and nosZ; and Rm was controlled by nifH, apr, AOA-amoA, AOB-amoA, nirS, and nirK. © 2017 Elsevier B.V. All rights reserved.

⁎ Corresponding author at: Institute of Soil and Water Conservation, Northwest A & F University, No. 26, Xinong Road, Yangling, Shaanxi 712100, China. E-mail address: [email protected] (H. Wang).

http://dx.doi.org/10.1016/j.scitotenv.2017.07.014 0048-9697/© 2017 Elsevier B.V. All rights reserved.

H. Wang et al. / Science of the Total Environment 607–608 (2017) 152–159

1. Introduction Restoration of natural vegetation has been considered a traditional practice to improve soil characteristics and restore degraded ecosystems (Lozano et al., 2014). The availability of nitrogen (N) can alter the vegetation species composition and diversity in degraded ecosystems (LeBauer and Treseder, 2008; Rowe et al., 2014; Stiles et al., 2017). Soil microorganisms are key drivers of ecosystem N cycling (Canfield et al., 2010). However, our understanding of N transformation and the functional microorganisms involved in N cycling during longterm natural vegetation recovery is still poor, especially in the degraded ecosystems of arid to semi-arid regions (Foster and Tilman, 2000; Lozano et al., 2014). − − − Nitrification (NH+ 4 -N → NO2 -N → NO3 -N), denitrification (NO3 -N − → NO2 -N → NO/N2O → N2), N2 fixation (N2 → organic N), and ammonification (organic N → NH+ 4 -N) are the four primary microbiological processes associated with supplying, leaching, and transforming N in soil systems (Burger and Jackson, 2003; Pereira e Silva et al., 2011; Petersen et al., 2012; Tang et al., 2016). The amoA gene has been extensively used to study ammonia-oxidizing bacteria (AOB) and ammonia− oxidizing archaea (AOA) (NH+ 4 -N → NO2 -N) in soil systems (Petersen et al., 2012; Schleper, 2010). The nxrA gene has been extensively used − to study nitrite oxidation (NO− 2 -N → NO3 -N) (Canfield et al., 2010). Denitrification is the sequential dissimilatory reduction during which NO− 3 -N is transformed into N2 by different groups of bacteria. The first − step of denitrification (NO− 3 -N → NO2 -N) is catalyzed by nitrate reductases encoded by the narG and napA genes. The second step (NO− 2 -N → NO) is catalyzed by two different nitrite reductases (NIRs) encoded by the nirK (copper-containing) and nirS (cytochrome cd1-containing) genes. The last step (N2O → N2) is catalyzed by nitrous oxide reductase (NOS), with nosZ being used as the gene marker. The nifH gene is often used as a marker of diazotrophic bacteria (Canfield et al., 2010; Rösch et al., 2002). The alkaline metalloprotease (apr) gene has been extensively used to study ammonification (Sakurai et al., 2007). Previous studies have focused on the general trends of nitrifier and denitrifier communities (Jurburg et al., 2017; Pan et al., 2016); linkages among soil, plants, and bacterial communities (Andreote and Pereira e Silva, 2017; Fry et al., 2017; Jurburg et al., 2017; Lozano et al., 2014); and potential N mineralization rates during natural vegetation recovery (Risch et al., 2015; Vourlitis and Fernandez, 2015; Wei et al., 2011; Xiao et al., 2017). The N cycle is a network of interlinked processes that are responsible for N fluctuations (increases and losses) through increasing NH+ 4 + − N (N2 → NH+ 4 -N and organic N → NH4 -N); the leaching of NO3 -N and NO; and the emissions of N2O or N2 caused by azotobacters, proteolytic bacteria, nitrifiers, and denitrifiers (Canfield et al., 2010; Petersen et al., 2012; Sakurai et al., 2007). However, relatively few studies have focused on soil microbial properties or N-transforming microbes during longterm natural vegetation recovery of abandoned farmland, and very little − is known regarding the dynamic fate of NH+ 4 -N and NO3 -N processing − and the underlying mechanisms that govern the NH+ 4 -N and NO3 -N transformation processes during natural vegetation recovery. The northern part of the Chinese Loess Plateau is a region that has been traditionally used for agriculture and pastoral land and suffers from extensive and severe water- and wind-driven soil erosion (Wei et al., 2011). Since the 1970s, many farmlands with slopes N 15° have been abandoned so that natural recovery will occur and soil erosion will be prevented (Wei et al., 2011). Several studies have reported the effects of vegetation recovery on the N characteristics of soil, bacterial communities, and enzymatic activities (Ren et al., 2016; Zhang et al., 2016), but very little is known regarding the shift in net soil N transformation rates, the functional groups of microorganisms involved in the N cycle, and the underlying N transformation mechanisms. Therefore, this study was conducted in the northern part of the Loess Plateau to investigate the dynamics of soil N transformation rates and N-transforming microbes at sites representing 40 years of natural vegetation recovery of abandoned farmland on the Loess Plateau. The

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following three specific objectives were pursued: (1) the evaluation of the net N transformation rates during the 40 years of vegetation recovery after agricultural abandonment; (2) the quantification of the absolute abundance of N functional genes and the determination of the quantitative link between N transformation rates and functional genes; and (3) the determination of primary N transformation pathways and the identification of the key functional genes that shape N transformation. 2. Materials and methods 2.1. Study area The field sites were located in the Zhifanggou watershed (109°15′E, 36°44′N, mean elevation of 1220 m), which is a hilly loess landscape on the Loess Plateau. The climate is semi-arid with an annual rainfall of 437 mm, with N77% falling from June to September. The mean annual temperature is 8.8 °C, ranging from − 9.7 °C in January to 23.7 °C in July. The soil is a Huangmian soil (a Calcaric Cambisol according to FAO classification). The main grassland species are Artemisia sacrorum, Sophora davidii, Bothriochloa ischaemum, Rubia cordifolia, and Patrinia heterophylla. Different ages of plant communities are widely distributed throughout the watershed, and there is no human disturbance. Standardized chronosequence methods for long-term ecological research were employed to monitor the changes in plant communities and soils under similar climatic conditions following the sequence of vegetation development (Felske et al., 2000; Lozano et al., 2014; Tscherko et al., 2004; Walker et al., 2010). This method makes the critical assumptions that each site in a sequence differs only in age and that the same abiotic and biotic component histories can be traced at each site (Johnson and Miyanishi, 2008). We used the chronosequence method to evaluate the responses of the soil bacterial, archaeal, and Ntransforming communities to the natural succession of abandoned farmland. A total of 15 sites at the 0-, 10-, 20-, 30-, and 40-y stages of recovery were randomly selected as the experimental sites (5 m × 5 m). All plots were located as close as possible (b1 km) and shared similar soil and climatic conditions and topographic positions. The active sloped farmland was fertilized each year with 2200–2500 kg ha−1 goat manure, 600–900 kg ha−1 N urea and 400–600 kg ha−1 phosphorus pentoxide (P2O5). 2.2. Soil chemical parameters and net N transformation rates We collected soil samples during the growing season from 20 June to 19 July 2016. In the experiments, the soil mean temperature was 22.4 °C, and the average precipitation was 119.5 mm. Soil moisture was determined gravimetrically in fresh soils at 105 °C overnight, and the water content is expressed as a percentage of the dry weight. Soil bulk density, organic carbon, total phosphorus, available phosphorus, − NH+ 4 -N, and NO3 -N were measured using previously described methods (Tang et al., 2016; Zhang et al., 2016). The total nitrogen (TN) content was determined using the Kjeldahl method (Bremner and Mulvaney, 1982). The soil pH was determined using a glass electrode meter in 1:2.5 soil:water suspensions. Standardized soil methods for long-term ecological research were employed to quantify the in situ net N mineralization rates (Adams et al., 1989; Robertson et al., 1999). In each plot, three PVC cores (8 cm diameter × 22 cm long) were randomly selected from locations within the plots. The PVC cores were inserted 20 cm into the soil and covered with a permeable plastic film to segregate the water in the soil and allow gas exchange. Paired soil samples were collected from 0 to 20 cm to analyze the initial N conditions. The cores were incubated in the field for 28–30 days. The rates of net ammonification (Ra), nitrification (Rn) and total mineralization (Rm) during the incubation period were calculated from the difference between the initial (T0) and final − + (T1) concentrations of NH+ 4 -N, NO3 -N, and total mineral N (NH4 -N

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+ NO− 3 -N) as follows:

3. Results and discussion


Ra ¼ NH4 þ −NT0 −NH4 þ −NT1 =ðT1 −T0 Þ

3.1. Vegetation and soil characteristics during vegetation recovery

−

The main crops (millet and soybean) on the farmland were harvested, so the plant cover was not quantified at 0-year sites. The plant cover significantly increased as the vegetation recovery progressed and ranged from 13.28% to 37.20% in native grasslands (Table S2). This result was similar to other studies that reported that plant communities in semi-arid environments underwent a secondary succession process, which leads to increases in species richness and plant cover (Lozano et al., 2014; Meng et al., 2016). Significant differences in soil characteristics were found between sites as the vegetation recovery progressed (Table 1). The content of soil organic C, total P and C/N showed similar trends and significantly increased with time after site abandonment. − The content of soil total N, NH+ 4 -N, NO3 -N, and water at the 10-y sites had steadily decreased compared to the 0-y sites and then significantly increased as vegetation recovery progressed. The decline of NH+ 4 -N and NO− 3 -N during the first 10 years was largely attributed to the cessation − of input from fertilizers (Table 1). The content of NH+ 4 -N and NO3 -N showed a similar trend and significantly increased with time after site abandonment, which is in agreement with (Lozano et al., 2014) and Zhang et al. (2016), who suggested that the natural recovery of abandoned farmland had a positive impact on increasing soil N content. The bulk densities of the soils significantly decreased at the 0–40-y sites. Similarly, Jiao et al. (2011) indicated that natural vegetation recovery had a positive effect on the decrease in soil bulk density. This decrease in the soil bulk density attenuated soil permeability (not measured in this study), which led to enhanced soil aerobiotic conditions favorable for the enrichment of aerobic microorganisms (Firestone et al., 1980). The soil pH ranged from 8.41 to 8.68 between the 0–40-y sites. These differences may have a significant influence on the soil microorganisms.

−

Rn ¼ ðNO3 −NT0 −NO3 −NT1 Þ=ðT1 −T0 Þ Rm ¼ Ra þ Rn

2.3. Quantitative polymerase chain reaction (qPCR) Soil community DNA was extracted from 0.5–1.0 g of soil using the E.Z.N.A.™ Soil DNA Kit D5625-01 (Omega Biotek, USA) according to the manufacturer's instructions. The primers for bacterial 16S rRNA (bacteria), archaeal 16S rRNA (archaea), and functional N genes: (i.e., AOA-amoA, AOB-amoA, nxrA, narG, napA, nirK, nirS, nosZ, and nifH) are presented in Table S1. Each primer concentration was 10 pmol/mL. qPCR was performed in a CFX Real-Time PCR Detection System (Bio-Rad, USA) via a three-step thermal cycling procedure, with a 20-μL reaction mixture consisting of 10 μL of SYBR Green I PCR Master Mix (Applied Biosystems, USA), 1 μL of template DNA (sample DNA or plasmid DNA for standard curves), 1 μL of forward and reverse primers, and 7 μL of sterile water (Millipore, USA). The protocol and parameters for each target gene are presented in Table S1.

2.4. Statistical analysis The standard deviations (SDs) of the gene abundance data were calculated using three replicates measured via qPCR and plotted as error bars to assess the variations in the data and measurement errors. The differences in plant cover, soil properties, and absolute abundance of bacterial, archaeal, and functional N genes were calculated using one-way analysis of variance (ANOVA) and a least significant difference (LSD) multiple comparison (P b 0.05). We performed a principal component analysis (PCA) of the soil properties, plant cover, bacteria, archaea, and functional N genes using CANOCO software 5.0. Pearson correlation coefficients were calculated to evaluate the ecological associations between functional N genes using SPSS Statistics 20 (IBM, USA). The quantitative response relationships between the N transformation rates and functional genes were quantified using multivariate stepwise regression analysis in the SPSS Statistics software package (IBM, USA).

3.2. Soil net nitrogen transformation rates A comparison of the net N transformation rates between the 0–40-y sites is shown in Fig. 1. Overall, significant differences in Ra, Rn, and Rm were found between the 0-y sites and the 10–30-y sites. The present study showed that Ra, Rn, and Rm were greater at the 0-y sites than in the grassland soils of different ages (10–30-y sites), which is consistent with the findings of Antheunisse et al. (2007), who also observed that the net N transformation rates in active sloped farmland soils were greater than in grassland soils. N transformations are a microbially mediated processes, and it has been established that the quality of organic matter input, which is a factor associated with increases in species

Table 1 Soil physicochemical properties during natural vegetation recovery of abandoned farmland. Soil properties

Farmland 0-y

AF 10-y

AF 20-y

AF 30-y

AF 40-y

F values

Organic C (g kg−1) Total N (g kg−1) Total P (g kg−1) Available P (mg kg−1) −1 ) (T0) NH+ 4 -N (mg kg −1 ) (T1) NH+ 4 -N (mg kg − −1 NO3 -N (mg kg ) (T0) − −1 NO3 -N (mg kg ) (T1) pH Bulk density (g cm−3) Water content (%) C/N

3.27 ± 0.11 d 0.52 ± 0.02 b 0.55 ± 0.02 b 1.74 ± 0.06 a 7.93 ± 0.28 a 6.58 ± 0.4 a 4.23 ± 0.15 a 1.63 ± 0.46 c 8.41 ± 0.02 d 1.30 ± 0.02 a 18.25 ± 0.04 a 6.29 ± 0.22 d

3.3 ± 0.05 d 0.37 ± 0.01 e 0.56 ± 0.01 b 1.78 ± 0.03 a 4.08 ± 0.06 e 4.8 ± 0.33 ab 2.56 ± 0.04 d 0.67 ± 0.24 d 8.52 ± 0.05 a 1.21 ± 0.03 b 14.45 ± 0.04 c 8.92 ± 0.13 c

3.73 ± 0.09 c 0.39 ± 0.01 d 0.56 ± 0.01 b 0.77 ± 0.02 b 4.36 ± 0.11 d 4.81 ± 0.32 b 3.54 ± 0.09 c 2.92 ± 0.27 b 8.68 ± 0.02 c 1.15 ± 0.04 d 13.74 ± 0.12 d 9.56 ± 0.24 b

6.53 ± 0.19 b 0.43 ± 0.01 c 0.57 ± 0.02 b 0.6 ± 0.02 b 4.79 ± 0.14 c 6.49 ± 0.92 a 4.58 ± 0.14 b 3.68 ± 0.6 a 8.54 ± 0.04 b 1.14 ± 0.03 d 10.50 ± 0.07 e 15.19 ± 0.46 a

9.09 ± 0.53 a 0.59 ± 0.03 a 0.67 ± 0.04 a 0.58 ± 0.03 b 5.61 ± 0.33 bc 4.52 ± 0.26 a 8.45 ± 0.49 a 3.85 ± 0.17 a 8.45 ± 0.04 b 1.17 ± 0.02 c 15.86 ± 0.04 b 15.41 ± 0.89 a

77.075⁎⁎ 92.143⁎⁎ 23.826⁎ 12.509⁎⁎ 80.111⁎⁎ 11.940⁎⁎ 168.574⁎⁎ 38.500⁎⁎ 183.574⁎⁎ 231.833⁎⁎ 323.179⁎⁎ 546.341⁎⁎

AF: abandoned farmland; Values are expressed as the mean ± standard error (n = 3). Different letters indicate significant differences (P b 0.05) among soils for the individual variables based on one-way ANOVA followed by an LSD test. The last column shows the F values of the general linear model and significance (* and ** at P b 0.01 and 0.001, respectively). NH+ 4 -N (T0) + − − − and NH+ 4 -N (T1) are the concentrations of NH4 -N in the samples before and after incubation; NO3 -N (T0) and NO3 -N (T1) are the concentrations of NO3 -N in the samples before and after incubation.

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recovery. This result suggests that soil mineral nitrogen (i.e., NH+ 4 -N and NO− 3 -N) may not be a suitable indicator for predicting and assessing the long-term (approximately 40 years) restoration success and progress. 3.3. Changes in functional genes during vegetation recovery To understand the quantitative link between the net nitrogen transformation rates and the microscale functional genes at the 0–40-y sites, we quantified the abundances of the nine functional genes associated with N cycling using quantitative PCR (Fig. 2).

− Fig. 1. Net transformation rates of NH+ 4 -N (Ra), NO3 -N (Rn) and total mineralization (Rm) during the 40 years of natural vegetation recovery. The different letters indicate significant differences (P b 0.05) among the sites for the individual variables based on one-way ANOVA followed by an LSD test.

richness and plant cover, can positively affect and stimulate the microbial community, the soil physical and chemical properties and ultimately the soil N transformation processes (Accoe et al., 2004; Kandeler et al., 1999; Lang et al., 2010). In this study, the active farmland (0-y sites) was fertilized with nitrogenous fertilizer, and the abandoning farmland (10– 30-y sites) had substantially lower total nitrogen content in the soils due to the cessation of input from fertilizers (Table 1). This difference might also explain the corresponding lower Ra, Rn, and Rm values at the 10–30-y sites compared to those at the 0-y sites. The negative values of Ra at the 10–30-y sites indicated that soil NH+ 4 -N had accumulated, which is consistent with the results by Wei et al. (2011) and suggested abundant NH+ 4 -N availability in the soil during specific stages of vegetation recovery in this area. No significant differences appeared between the 0-y sites and the 40-y sites in terms of Ra. Moreover, all of the Rn and Rm values at the 40-y sites reached the levels of the active farmland (0-y sites). There− fore, the capabilities of the soil to deliver NH+ 4 -N and NO3 -N were not a limiting factor during the growing season after 40 years of vegetation

3.3.1. Abundance of bacteria and archaea As vegetation recovery proceeded, the abundances of bacteria and archaea first decreased compared with those at the 0-y sites and then steadily increased (Fig. 2a). Significant differences in the absolute abundance of bacteria and archaea were found between sites as the vegetation recovery progressed. The abundance of bacteria was 0.66- to 3.34-fold higher than the abundance of archaea across all sites. The absolute abundances of bacteria and archaea reached the levels of those at the farmland (0-y sites) and exceeded these levels at the 30–40-y sites (there was a significant difference between these two sites). This finding is supported by previous studies that showed that the changes in vegetation cover and soil nutrients along a chronosequence have a significant impact on the enhancement of the bacterial and archaeal communities (Blaalid et al., 2012; Zhang et al., 2016). 3.3.2. Abundance of nitrifying microorganisms The absolute abundances of the AOA-amoA, AOB-amoA, and nxrA genes, which are the three functional genes associated with NH+ 4 -N oxidation, were significantly different among the sites (Fig. 2b). AOAamoA was 1.8–16.3-fold more abundant than AOB-amoA, suggesting that AOA were involved in the dominant NH+ 4 -N oxidation pathway − (NH+ 4 -N → NO2 -N) as reported by (Adair and Schwartz, 2008; Leininger et al., 2006) in semi-arid and grassland soils. Previous studies have suggested that niche partitioning occurs between AOA and AOB, with soil ammonium concentrations and pH representing the main environmental factors shaping the ecological niches of ammonium

Fig. 2. The absolute abundances of bacteria, archaea, and functional nitrogen genes during the 40-y vegetation recovery of abandoned farmland. (a): bacteria and archaea; (b): AOA-amoA, AOB-amoA, and nxrA; (c): narG, napA, nirK, nirS and nosZ; (d): nifH and apr. The absolute abundances (copies g−1) are shown on a log10 scale (y-axis). The standard deviations of the three replicates are indicated by error bars. Invisible error bars indicate that the standard deviations are smaller than the marker size. Different letters indicate significant differences (P b 0.05) among the sites for the individual variables based on one-way ANOVA followed by an LSD test.

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oxidizers (Prosser and Nicol, 2012; Schleper, 2010). In this study, all investigated sites exhibited a simultaneous fluctuating distribution of AOA and AOB (Fig. 2b), suggesting a coexistence of the two groups of ammonia oxidizers. The five sites (0–40-y sites) were shaped by low ammonium concentrations (4.08–7.93 mg N kg−1) and optimum pH (8.41–8.68) (Table 1), leading to reduced capacities to separate the niches of AOA and AOB (Keil et al., 2011). The absolute abundance of the nxrA gene exhibited a similar variation trend as the AOA-amoA and AOB-amoA genes (Fig. 2b). The abundance of the nxrA gene initially decreased compared with that at the 0-y sites and subsequently followed a similar increasing pattern at the 10–40-y sites. The ecological associations between nitrifying microorganisms were further identified using PCA (Fig. 3) and Pearson correlation coefficients (Table 2). The Pearson correlation coefficients between the AOA-amoA-nxrA and AOB-amoA-nxrA genes all exceeded R2 = 0.57 (P b 0.05). This associated pattern of fluctuation was due to the similar environmental adaptations and ecological interactions between AOA, AOB, and nitrite-oxidizing bacteria (NOB) (Leininger et al., 2006). In ad− dition, AOA perform NH+ 4 -N to NO2 -N oxidation, which provides a sub− strate for NOB to use for nitrite oxidation (NO− 2 -N to NO3 -N) (Schleper, 2010). This phenomenon might also explain the corresponding lower abundance of the nxrA gene compared to the AOA-amoA gene. 3.3.3. Abundance of denitrifying microorganisms Our results show that the abundances of the napA and narG genes exhibited different fluctuating trends as the vegetation recovery progressed (Fig. 2c). These genes were significantly affected by increases in soil organic C and NO− 3 -N (Fig. 3), which is similar to other studies that reported that the abundances of the narG and napA genes were positively correlated with organic C and NO− 3 -N (Kandeler et al., 2009). These results agree with previous research that showed that the narG gene is easily promoted by increases in soil nutrients (Ji et al., 2013; Tang et al., 2016). The narG gene was more abundant than the napA gene in the 10-y and 20-y sites, which is similar to the study that reported that the narG gene was more insensitive than the napA gene to the variations in soil nutrients (Cheneby et al., 2009). In addition, the napA gene had a significantly higher abundance than the narG gene at both the 30-y sites and 40-y sites, which was similar to the study that reported that the napA gene is dominant compared to the narG gene under aerobic conditions (Galloway et al., 2008). The

Fig. 3. Principal component analysis of plant cover, soil properties, bacteria, archaea, and functional nitrogen genes during the 40-y vegetation recovery of abandoned farmland. TN: total nitrogen; OC: organic carbon; BD: bulk density; AP: available phosphorus; TP: total phosphorus. The total variation is 7.215, and the first two PCA axes explain 72.13% of the total variance.

abundance of the nirK and nirS genes varied greatly as the vegetation recovery progressed (Fig. 2d), which suggested that nirK- and nirS-type bacteria choose different habitats after substantial variations in soil physicochemical properties occur (Levy-Booth et al., 2014). This notion is supported by previous studies showing that the niches of these two types of nir-harboring bacteria are responsible for their different behaviors (Tang et al., 2016). The ordination stressed the trends observed in Fig. 3, showing a strong positive correlation between the nirS gene and soil organic C. This result is similar to other studies reporting that the nirS gene was strongly influenced by soil C and more sensitive to the increases of soil organic C than the nirK gene (Levy-Booth et al., 2014). A steady increase in the abundance of the nosZ gene was observed as the vegetation recovery progressed. The steady increase in the nosZ gene (from 4.54 × 103 to 1.50 × 106 copies g−1 soil) enhanced the last step in the denitrification pathway, suggesting an enhanced reduction of emissions of the greenhouse gas N2O (not measured in this study) (Zhi and Ji, 2014). Of particular interest, we found that the ratios of (nirK + nirS)/nosZ (indicating N2O emissions) at the 0-y sites were higher than that at the 10–40-y sites (Fig. S1), suggesting the suppression of N2O emissions as the vegetation recovery progressed. Ecological associations between the five denitrifying genes were further identified by PCA (Fig. 3) and Pearson correlation coefficients (Table 2). The Pearson correlation coefficients between napA-nirS, napA-nosZ, narG-nirS, narG-nosZ, nirK-nosZ, and nirS-nosZ all exceeded R2 = 0.54, confirming an interaction and ecological association between the denitrifying microorganisms. The associated enrichment of these denitrifying microorganisms was due to their similar environmental adaptations and interrelated but distinct ecological niches. The conversion − of NO− 3 -N to NO2 -N, which is catalyzed by napA and narG codases, provided a substrate for nitrite reduction (NO− 2 -N → NO), which is related to the nirK and nirS genes. Nitrous oxide (N2O), which is derived from the NO produced by the nirK and nirS codases, was provided as a substrate for the final reaction step in the denitrification pathway (N2O/ N2) performed by the product of the nosZ gene (Čuhel et al., 2010). 3.3.4. Abundance of N2-fixing microorganisms The absolute abundance of the nifH gene exhibited a continuous decrease from 5.57 × 104 copies g− 1 soil at the 0-y sites to 3.37 × 103 copies g−1 soil at the 20-y sites (Fig. 2e), which led to the attenuated N-fixation activity responsible for decreasing the NH+ 4 -N supply. The nifH gene exhibited an increase at the 30–40-y sites, which led to enhanced N2-fixation activity. Soil pH was identified as an important parameter controlling nifH gene abundances (Pereira e Silva et al., 2013). Our results showed that the small increase in pH observed at the 20-y sites had an overall negative effect on the decrease in the nifH gene abundance, which is in agreement with Collavino et al. (2014) and Pereira e Silva et al. (2013), who suggested that the fluctuation of pH had negative effects upon the abundance of the N2-fixing community. 3.3.5. Abundance of ammonifying microorganisms The absolute abundance of the apr gene exhibited a continuous decrease from 3.29 × 105 copies g− 1 soil at the 0-y sites to 2.46 × 104 copies g− 1 soil at 10-y sites (Fig. 2f), which led to the attenuated ammonifying activity responsible for decreasing the NH+ 4 -N supply (organic N → N2). The increased organic matter often stimulates the activity of alkaline metalloprotease encoded by the apr gene (Sakurai et al., 2007). In our study, organic C significantly increased as the vegetation recovery progressed (Table 1). We found that the apr gene exhibited an increase at the 10–40-y sites, which led to enhanced ammonifying activity. These results indicate that the absolute abundance of the apr gene increased in response to vegetation recovery and that the mineralization of organic nitrogen was immediately induced due to alkaline metalloprotease action. Overall, our results showed that the abundance of functional N genes responded distinctly and differentially to the natural vegetation recovery of abandoned farmland. Moreover, under each single- or multi-

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Table 2 Pearson correlation coefficients between nitrogen transformation genes (n = 15). Pearson

AOA

AOB

nxrA

AOA AOB nxrA napA narG nirK nirS nosZ nifH apr

1.000 0.431 0.571⁎ −0.44 −0.307 −0.178 0.416 −0.474 0.046 0.393

1.000 0.951⁎⁎ 0.063 0.18 0.316 0.048 0.047 0.064 −0.343

1.000 0.09 0.306 0.12 0.063 0.021 −0.378 −0.162

napA

narG

1.000 0.840⁎⁎ 0.488 0.995⁎⁎ 0.982⁎⁎

1.000 0.017 0.855⁎⁎ 0.790⁎⁎

0.181 −0.119

0.324 −0.097

nirK

nirS

nosZ

nifH

apr

1.000 0.46 0.548⁎ −0.354 −0.305

1.000 0.991⁎⁎ 0.159 −0.175

1.000 0.164 −0.239

1.000 0.561⁎

1.000

⁎ Statistically significant (P b 0.05, two-sided test). AOA: AOA-amoA; AOB: AOB-amoA. ⁎⁎ Statistically significant (P b 0.01, two-sided test).

factorial environmental change, the abundance of the functional N genes showed differences in sensitivity, which likely reflected the fact that various microbial functional groups involved in N cycling exhibit different environmental adaptations and ecological interactions.

3.3.6. Nitrogen transformation pathway The N transformation processes and pathways varied as the vegetation recovery progressed. The results in Fig. 4 show that the nitrate reductases encoded by the napA gene governed the fate of Rn at the 0-y sites. However, the fate of Rn was governed by the nitrate reductases encoded by the narG gene at the 10–20-y sites and by the nitrate reductases encoded by the napA gene at the 30–40-y sites. The first step of nitrification performed by ammonium monooxygenase encoded by the AOA-amoA and AOB-amoA genes was the secondary pathway at the 0y sites, which led to lower Ra (relative to Rn). The AOA-amoA gene presented a dominant higher contribution (10-y, 20-y, and 40-y sites) than its counterpart AOB-amoA, which is responsible for NH+ 4 -N transformation (except at the 30-y sites). Both the AOA-amoA and AOB-amoA genes represented the restricted and secondary pathway over the entire recovery period. Greenhouse gas (N2O) emissions from denitrification

and NO− 3 -N leaching are two pathways for N losses from soils (Petersen et al., 2012). The N2 emission pathway (Fig. 4 and Fig. S1) was enhanced as the vegetation recovery progressed, which suggests decreased greenhouse gas emissions and increased N loss. Based on these results, the enrichment of functional genes further confirmed that the multi-pathway coupled cooperation and competition of the functional gene community had a large influence on the import, transformation, and loss of soil N.

3.4. Quantitative response relationships A series of stepwise regression models were built to provide a linear quantitative measure of the genes associated with net N transformation rates (Table 3). The Ra was jointly determined by AOA-amoA, AOBamoA, and nxrA (R2 = 0.951, P = 0.002). The variable AOA-amoA/ (AOB-amoA + nxrA), indicating NH+ 4 -N oxidation, showed a positive relationship with the NH+ 4 -N transformation rates. This relationship existed because AOA are primarily involved in NH+ 4 -N oxidation, as previously discussed. The Rn was jointly determined from napA, narG, nirS, nirK, and nosZ (R2 = 0.910, P = 0.012). The variable (napA + narG)/

Fig. 4. Nitrogen transformation processes and pathways during the 40-y vegetation recovery of abandoned farmland. The nitrogen transformation processes and pathways were classified into three groups according to their relative richness values. The relative richness values were defined as the ratio of absolute richness of a functional N gene/absolute richness of all functional N genes. The main pathway was defined as a relative richness value of N10%, the secondary pathway was defined as a relative richness value between 1% and 10%, and the restricted pathway was defined as a relative richness value of b1%.

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Table 3 Quantitative response relationships between net nitrogen transformation rates (mg N kg−1 d−1) and functional gene abundance (copies g−1) along natural vegetation recovery of abandoned farmland. R2

P value

AOA −0:113 AOB þ nxrA

0.951

0.002

napA þ narG þ 0:001 napA þ narG þ nirK þ nirS þ nosZ

0.910

0.012

0.999

0.015

Stepwise regression models (equations) Ra ðNH4 þ −NÞ ¼ 1:634

Rn ðNO3−−NÞ ¼ 0:197

Rm ¼ 0:009

nifH þ apr nirS þ nirK − þ 0:007 AOA þ AOB AOA

AOA: AOA-amoA; AOB: AOB-amoA.

(napA + narG + nirS + nirK + nosZ) was identified as the NO− 3 -N transformation in the denitrification process. The high ratio of this variable represents the extent of NO− 3 -N reduction. Rm was jointly determined by (nifH + apr)/(AOA-amoA + AOB-amoA) and (nirS + nirK)/AOAamoA (R2 = 0.999, P = 0.015). The variable (nifH + apr)/(AOA-amoA + AOB-amoA), indicating NH+ 4 -N accumulation, and showed a positive relationship with the Rm transformation. The nifH and apr genes are involved in NH+ 4 -N production (Francis et al., 2007), whereas the AOAamoA and AOB-amoA genes were responsible for NH+ 4 -N consumption (Canfield et al., 2010). The ratio of (nifH + apr)/(AOA-amoA + AOBamoA) represents the accumulation level of NH+ 4 -N (increased). The variable (nirS + nirK)/AOA-amoA, indicating NO− 2 -N consumption, showed a negative relationship with Rm transformation. The nirS and nirK genes are responsible for NO− 2 -N consumption, whereas the AOA+ amoA gene is responsible for NO− 2 -N production via NH4 -N reduction. The consumption and production ratio, therefore, represents the extent − of NH+ 4 -N consumption, and the higher the NO2 -N accumulation is, the − − lower the NO− 3 -N production (NO2 -N → NO3 -N) is. Overall, our results indicated that the relative abundances, rather than the absolute abundances, of functional N genes were responsible for the relationship be− tween the NH+ 4 -N and NO3 -N transformation rates in soils. 4. Conclusions Our results suggested that the net transformation rates of Ra, Rn, and Rm were greater at the 0-y sites than in grassland soils (10–30-y sites) of different ages. Ra, Rn and Rm at the 40-y sites reached the levels of active − farmland. The deliverable capabilities of soil NH+ 4 -N and NO3 -N could recover with increasing abandonment time. The microbial genes associated with nitrogen cycling showed differences in sensitivity to the changes in vegetation and soil characteristics during vegetation recovery. The various microbial functional groups involved in N cycling show different environmental adaptations and ecological interactions. The enrichment of functional microbial communities involved in N cycling further confirmed that the multi-pathway coupled cooperation and competition of the functional microbial communities had a large influence on the import, transformation, and loss of soil N. Ra was collectively controlled by AOA-amoA, AOB-amoA, and nxrA; Rn was governed by napA, narG, nirK, nirS, and nosZ; and Rm was jointly controlled by nifH, apr, AOA-amoA, AOB-amoA, nirS, and nirK. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2017.07.014. Acknowledgments This work was supported by the Fundamental Research Funds for the Central Universities (Z109021711), the Start-up Funds of Northwest A & F University to Honglei Wang (Z109021610), and Special-Funds of Scientific Research Programs of State Key Laboratory of Soil Erosion

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