Different responses of soil bacterial species diversity and phylogenetic diversity to short-term nitrogen input in an alpine steppe at the source of Brahmaputra

Abstract

The Qinghai-Tibet Plateau has experienced an increase in N deposition/input due to global change. However, it remains unclear how the responses and whether the responses of soil bacterial diversity to short-term N input are consistent at different levels. Here, we investigated soil bacterial species and phylogenetic α-diversity and community composition based on a short-term nitrogen input experiment (five levels: 0, 2.5, 5, 10, and 20 g N m⁻² y⁻¹) in an alpine steppe at the source of Brahmaputra, using high-throughput sequencing technology. Short-term nitrogen input did not affect the species α-diversity and β-diversity of soil bacteria. However, soil bacterial phylogenetic α-diversity and dissimilarity increased with increasing nitrogen input. Different relative contributions and correlations of primary factors to species and phylogenetic diversity under short-term nitrogen input may result in different responses, in which ecological processes also play a role. Therefore, studying the response of soil bacteria to short-term nitrogen input should take into account not only the species level but also the phylogenetic level. We should pay close attention to the potential influence of short-term nitrogen deposition/fertilization on the soil bacterial community in the alpine steppe on the Tibetan Plateau.

Introduction

Nitrogen (N) is a vital factor that controls species composition and diversity in terrestrial ecosystems (Zechmeister-Boltenstern et al., 2011). In the last century, human activities have dramatically increased nitrogen deposition globally (Galloway et al., 2004; Bobbink et al., 2010). On the one hand, in a nitrogen-deficient ecosystem, elevated nitrogen deposition can relieve nitrogen limitation in the system. On the other hand, excessive nitrogen would result in nitrogen pollution due to fossil combustion and deliberate N fertilization (Gruber and Galloway, 2008), which would greatly affect the biogeochemical cycles of C and N in terrestrial ecosystems. One of the most plentiful soil microbes in terrestrial ecosystems is bacteria, which play vital roles in promoting vital biogeochemical procedures in soils (Bardgett and van der Putten, 2014; Delgado-Baquerizo et al., 2019; Zhang et al., 2020). Thus, understanding how the soil bacterial community responds to N enrichment is of great value for predicting the effects of nitrogen deposition on subterranean terrestrial ecosystems.

With the development of high-throughput sequencing technology, a growing number of studies have studied the response of the soil bacterial community to nitrogen input in wetland (Li et al., 2019a), forests (Nie et al., 2018; Wang et al., 2021), grasslands (Zhang and Han, 2012; Ling et al., 2017), and alpine regions on the Tibetan Plateau (Li et al., 2020a, 2021; Mu et al., 2021; Yang et al., 2021). However, how different nitrogen input rates affect the response of soil bacterial species diversity to short-term nitrogen input still remains controversial (Li et al., 2020a; Zhang et al., 2022). Although Zhang et al. (2022) reported that different nitrogen input rates increased soil bacterial α-diversity on the Loess Plateau, Li et al. (2020a) found that different nitrogen input rates decreased soil bacterial α-diversity on the Qinghai-Tibetan Plateau. In addition, Bradley et al. (2006) found that short-term (1–2 months) N application (0, 5.44, and 27.2 g N m⁻² y⁻¹) had insignificant effects on soil bacterial α-diversity in a grassland at the Cedar Creek LTER in Minnesota, USA. These inconsistent results may have been caused by different nitrogen input rates, durations, climatic conditions, vegetation conditions, and land-use types among these studies. In addition to the unclear response of soil bacterial species diversity to short-term nitrogen input, as well as soil bacterial phylogenetic diversity. Soil bacterial diversity contains not only species diversity but also phylogenetic diversity, which can all deduce community assembly mechanisms (Zhou and Ning, 2017). Some previous studies have reported that phylogenetic diversity reveals more information about community construction than taxonomic diversity (Jia and Du, 2014) and has a strong connection with stability (Zhang et al., 2019), which is an important index. Although Turlapati et al. (2013) have reported that chronic N-amended can increase the phylogenetic diversity of soil bacteria, as well as species diversity. However, little attention has been given to the effects of phylogenetic diversity during changes in soil bacterial communities in response to short-term nitrogen input, and whether the effects on species diversity and phylogenetic diversity are consistent.

The Qinghai-Tibet Plateau is known as the “Roof of the World” and the “Third Pole of the Earth,” which is an important barrier to the ecological security of China and Asia (Sun et al., 2012). The high altitude and low temperature of the Qinghai-Tibet Plateau make it very sensitive to global change. From the 1980s to the 2000s, the dose of N deposition increased significantly, ranging from 4 to 13.8 kg N ha⁻¹ y⁻¹ on the Tibetan Plateau (Liu et al., 2013). At the same time, nitrogen fertilizer application is used to manage degraded grasslands, improve soil fertility and increase plant productivity on the Tibetan Plateau (Zhao and Zhou, 1999; Wang et al., 2020; Li et al., 2020b). However, few studies have examined the effect of different nitrogen input rates on soil bacterial phylogenetic diversity, particularly in the alpine steppe in the western Tibetan Plateau. The Brahmaputra River basin originates west of the Tibetan Plateau, which links Bangladesh, Bhutan, China, and India and is an important international river (Barua, 2018). Therefore, it is important to study the effect of different nitrogen input rates on the alpine steppe at the source of Brahmaputra.

In this study, we investigated the responses of soil bacterial species and phylogenetic diversity to short-term (<1 year) N input based on a field nitrogen input experiment with five levels (i.e., 0, 2.5, 5, 10, and 20 g N m⁻² y⁻¹) in an alpine steppe at the source of Brahmaputra, using the high-throughput Illumina sequencing technology. Specifically, we mainly aimed to investigate how the responses of soil bacterial species and phylogenetic diversity to short-term (<1 year) nitrogen input and whether the effects were consistent in the alpine steppe at the source of Brahmaputra.

Materials and methods

Study sites

This study was conducted in an alpine steppe of Zhongba County (29° 37′ N, 82° 21′ E, 4,763 m above sea level), Tibet Autonomous Region, China. The mean annual temperature is approximately 5.1°C, and the mean annual precipitation is approximately 320 mm. The dominant species in this steppe is Potentilla bifurca, accompanied by Microula sikkimensis, Chenopodium glaucum, Heteropappus semiprostratus, Carex atrofusca, and Carex thibetica Franch. The soil texture type is sandy loam belonging to alpine steppe soil. The soil organic carbon, soil moisture, soil bulk density, and pH values are 0.57%–0.81%, 5.44%–6.13%, 1.49–1.66 g/cm³, and 8.27–8.47, respectively.

Experimental design

We designed a one-way factorial design (nitrogen application) with five treatments: 0 (control), 2.5, 5, 10, and 20 g N m⁻² y⁻¹ and were characterized by N0 (control), N2.5, N5, N10, and N20, respectively. In August 2021, a total of 25 5 × 5 m plots were laid out based on a randomized design, and each treatment had five replicates. The distance between any two neighboring plots was approximately 3 m. Nitrogen was applied in the form of urea, which was applied in the afternoon on a cloudy day.

Plant community investigation, soil sampling, and high-throughput sequencing

In September 2021, we recorded the number of plant species, height, and coverage of each plant species within a 0.5 m × 0.5 m quadrat in the middle of each plot (Zhang and Fu, 2021; Tian and Fu, 2022). In each plot, five 3.8 cm diameter soil cores (0–10 cm and 10–20 cm) were collected from the four corners and the middle of each quadrat in cross diagonals after plant community investigation. We mixed and sieved the soil samples through a 2-mm mesh to remove roots and stones. Some of the soil samples were promptly placed in a nitrogen canister and brought back to the laboratory to measure the soil bacterial community, and some of the soil samples retained freshness in the refrigerator to measure the soil physicochemical properties.

High-throughput sequencing procedures are described at length in the Supplementary material. Through analysis, there were 20,850 operational taxonomic units in the surface soil and 19,624 operational taxonomic units in the subsurface soil of the soil bacterial community across the 50 samples.

Statistical analysis

We calculated the response ratio to assess the effect size of N addition for a specific variable (Fu and Shen, 2016; Fu and Shen, 2017).

where Ni is the N addition rate, and N0 is the control treatment.

One-way ANOVA was used to measure the effects of N input on the soil properties, plant α-diversity, and species α-diversity of the soil bacterial community. The microeco package was used to obtain the α-diversity (OTUs, ACE, Chao1, Shannon, and Simpson) and β-diversity of the soil bacterial species (Yu et al., 2019; Zong and Fu, 2021). The picante package was used to calculate soil bacterial phylogenetic α-diversity (PD, MPD, MNTD, NRI, and NTI) and β-diversity (Sun et al., 2021). The linear discriminant analysis (LDA) effect size (LEfSe) method in microeco package was used to recognize significant differences in soil bacteria, and then Duncan’s multiple comparison test was used to calculate the differential species of soil bacteria. RandomForest package was used to calculate the relative contribution to soil bacterial species and phylogenetic α-diversity of each concerned variable. We calculated the correlations between species and phylogenetic α-diversity of the soil bacterial community and environmental characteristics. The microeco package was used to perform the Mantel test between species and the phylogenetic community composition of soil bacteria and environmental variables. The iCAMP package was used to calculate the community assembly processes of the soil bacterial community (Zhou and Ning, 2017; Han et al., 2022; Zhong and Fu, 2022). When the βNTI was < −2, the community turnover was Homogeneous Selection. When the βNTI was >2, the community turnover was Heterogeneous Selection. When the βNTI was between −2 and 2, and the RC_Bray was < −0.95, the community turnover was Homogenizing Dispersal. When the βNTI was between −2 and 2, and the RC_Bray was >0.95, the community turnover was Dispersal Limitation. When the βNTI was between −2 and 2, and the RC_Bray was between −0.95 and 0.95, the community turnover may be weak selection, weak dispersal, diversification, and drift. The software used in this study was R4.0.2, SPSS 25, and Origin 2022.

Results

Variations in abiotic and biotic characteristics along the N input gradient

Nitrogen input significantly increased soil available nitrogen (NH₄⁺-N, NO₃⁻-N, AN:AP, and NH₄⁺-N:NO₃⁻-N) in both surface and subsurface soils (Supplementary Table S1). Compared to N0, the soil NH₄⁺-N contents of the surface and subsurface soils under N20 all increased by 16.42-and 6.57-fold, respectively. Compared to N0, the soil NO₃⁻-N contents of the surface and subsurface soils under N20 all increased by 19.27-and 12.67-fold, respectively. Compared to N0, the soil AN:AP of the surface and subsurface soils under N20 all increased by 22.39- and 8.24-fold, respectively. Soil NH₄⁺-N:NO₃⁻-N was also significantly changed by N input in both surface and subsurface soils. However, plant α-diversity, soil pH, SM, SOC, TN, TP, AP, and soil enzymes did not significantly change along the N input gradient (Supplementary Tables S1, S2).

Variations in soil bacterial species and phylogenetic α-diversity along the N input gradient and their relationships with abiotic and biotic characteristics

The effect size of soil bacterial species α-diversity showed no relationships with the nitrogen input rate in either the surface or subsurface soil (Supplementary Figure S1). The effect size of soil bacterial phylogenetic α-diversity, including MPD in surface soil and NRI in subsurface soil, increased with the nitrogen input rate (Figures 1A,B). However, the effect size of soil bacterial phylogenetic α-diversity, including PD, MNTD, NRI, and NTI in surface soil and PD, MPD, MNTD, and NTI in subsurface soil, showed no relationships with the nitrogen input rate (Supplementary Figure S2).

Figure 1

The relative contributions of environmental variables to the R_OTUs variation in surface soil were listed in the following order: R_TN, R_TP, R_{C: N}, R_SM, etc., and they together explained 69.41% of the R_OTUs variation along the N input gradient (Supplementary Figure S3a). The relative contributions of environmental variables to the R_ACE variation in surface soil were listed in the following order: R_TN, R_UA, R_{C: N}, R_SM, R_CL, etc., and they together explained 72.8% of the R_ACE variation along the N input gradient (Supplementary Figure S3b). The relative contributions of environmental variables to the R_Chao1 variation in surface soil were listed in the following order: R_UA, R_{C: N}, R_TN, R_{C: P}, etc., and they together explained 72.68% of the R_Chao1 variation along the N input gradient (Supplementary Figure S3c). The relative contributions of environmental variables to the R_Shannon variation in surface soil were listed in the following order: R_SM, R_SRplant, R_SOC, R_{C: N}, R_UA, etc., and they together explained 81.14% of the R_Shannon variation along the N input gradient (Supplementary Figure S3d). The relative contributions of environmental variables to the R_Simpson variation in surface soil were listed in the following order: R_SM, R_{C: N}, R_{C: P}, R_SRplant, R_SC, R_SOC, R_ALP, etc., and they together explained 84.59% of the R_Simpson variation along the N input gradient (Supplementary Figure S3e).

The relative contributions of environmental variables to the R_OTUs variation in subsurface soil were listed in the following order: R_SM, R_NO3--N, R_Shannonplant, R_ALP, etc., and they together explained 68.75% of the R_OTUs variation along the N input gradient (Supplementary Figure S4a). The relative contributions of environmental variables to the R_ACE variation in subsurface soil were listed in the following order: R_SM, R_TP, R_UA, R_{C: N}, R_TN, etc., and they together explained 66.73% of the R_ACE variation along the N input gradient (Supplementary Figure S4b). The relative contributions of environmental variables to the R_Chao1 variation in subsurface soil were listed in the following order: R_UA, R_TP, R_SM, R_{C: N}, R_AP, R_pH, R_NH4 + -N, R_NO3--N, etc., and they together explained 64.5% of the R_Chao1 variation along the N input gradient (Supplementary Figure S4c). The relative contributions of environmental variables to the R_Shannon variation in subsurface soil were listed in the following order: R_CL, R_{C: N,}R_SM, R_AP, R_TP, etc., and they together explained 58.48% of the R_Shannon variation along the N input gradient (Supplementary Figure S4d). The relative contributions of environmental variables to the R_Simpson variation in subsurface soil were listed in the following order: R_NO3--N, R_CT, R_CL, etc., and they together explained 90.25% of the R_Simpson variation along the N input gradient (Supplementary Figure S4e).

The relative contributions of environmental variables to the R_MPD variation in surface soil were listed in the following order: R_SM, R_TP, R_SC, etc., and they together explained 66% of the variation in the R_MPD along the N input gradient (Figure 2A). The relative contributions of environmental variables to the R_NRI variation in surface soil were listed in the following order: R_SM, R_TP, R_TN, R_SOC, R_pielouplant, R_{C: N}, R_NO3--N, R_ALP, R_{C: N}, etc., and they together explained 73.48% of the variation in the R_NRI along the N input gradient (Supplementary Figure S5a). The relative contributions of environmental variables to the R_PD variation in surface soil were listed in the following order: R_TP, R_SM, R_TN, R_{C: N}, etc., and they together explained 79.36% of the variation in the R_PD along the N input gradient (Supplementary Figure S5b). The relative contributions of environmental variables to the R_MNTD variation in surface soil were listed in the following order: R_SM, R_CL, R_{NH4 + -N:NO3--N}, R_CT, etc., and they together explained 73.26% of the variation in the R_MNTD along the N input gradient (Supplementary Figure S5c). The relative contributions of environmental variables to the R_NTI variation in surface soil were listed in the following order: R_TN, R_ALP, R_TP, R_NH4 + -N, R_SM, etc., and they together explained 88.17% of the variation in the R_NTI along the N input gradient (Supplementary Figure S5d).

Figure 2

The relative contributions of environmental variables to the R_MPD variation in subsurface soil were listed in the following order: R_CL, R_TP, R_{C: N}, R_AP, R_CT, R_NH4 + -N, etc., and they together explained 65.36% of the variation in the R_MPD along the N input gradient (Supplementary Figure S5e). The relative contributions of environmental variables to the R_NRI variation in subsurface soil were listed in the following order: R_pielouplant, R_SC, R_ALP, R_NH4 + -N, R_TP, R_NO3--N, etc., and they together explained 42.8% of the variation in the R_NRI along the N input gradient (Figure 2B). The relative contributions of environmental variables to the R_PD variation in subsurface soil were listed in the following order: R_TP, R_SM, R_TN, R_UA, R_{C: N}, etc., and they together explained 68.08% of the variation in the R_PD along the N input gradient (Supplementary Figure S5f). The relative contributions of environmental variables to the R_MNTD variation in subsurface soil were listed in the following order: R_CL, R_{C: N}, R_TP, R_UA, etc., and they together explained 70.63% of the variation in the R_MNTD along the N input gradient (Supplementary Figure S5g). The relative contributions of environmental variables to the R_NTI variation in subsurface soil were listed in the following order: R_UA, R_SM, R_TN, R_ALP, R_CL, R_{C: N}, etc., and they together explained 64.22% of the variation in the R_NTI along the N input gradient (Supplementary Figure S5h).

Variations in soil bacterial species and phylogenetic community composition along the N input gradient and their relationships with abiotic and biotic characteristics

For the soil bacterial species community, soil bacterial species β-diversity had no relationships with nitrogen input dose in either surface or subsurface soil (Supplementary Figure S6). There were 28 differential groups of soil bacterial communities in the surface soil, including 4 classes, 4 orders, 6 families, and 14 genus, and they displayed dissimilar variation tendencies with the N input gradient (Figure 3A; Supplementary Table S3). There were 26 differential groups of soil bacterial communities in the subsurface soil, including 4 classes, 6 orders, 4 families, 11 genus, and 1 species, and they displayed dissimilar variation tendencies with the N input gradient (Figure 3B; Supplementary Table S4). Duncan multiple comparison showed that c__Chthonomonadetes, c__Lineage_IIa, and c__Lineage_IIb under the control treatment were significantly higher than those under the N20 treatment, and c__S0134_terrestrial_group under the N20 treatment was significantly higher than that under the control treatment in surface soil (Supplementary Table S3). According to the results of the Mantel test, the soil bacterial species community composition was significantly correlated with SOC, TP, TN, C: N, and SC (p < 0.05) and marginally significantly correlated with C:P, and ALP in the surface soil (p < 0.1). The soil bacterial species community composition was significantly correlated with SM, TP, and TN (p < 0.05) and marginally significantly interrelated with SOC and SC in subsurface soil (Table 1, p < 0.1).

Figure 3

The soil bacterial phylogenetic β-diversity between the control and nitrogen addition treatments significantly increased with increasing nitrogen addition rates in both the surface and subsurface soils (Figure 4, p < 0.05). According to the results of the Mantel test, the soil bacterial phylogenetic community composition was significantly interrelated with TP, NH₄⁺-N:NO₃⁻-N, and SC (p < 0.05) and marginally significantly interrelated with pH, NO₃⁻-N, and C:P in the surface soil (p < 0.1). The soil bacterial phylogenetic community composition was significantly interrelated with NO₃⁻-N and AN:AP and marginally significantly correlated with NH₄⁺-N, CT, and ALP in the subsurface soil (Table 1, p < 0.1).

Figure 4

Response of the community assembly of the soil bacterial community to nitrogen input

Changes in the effect size of nitrogen input on “Heterogeneous Selection,” “Homogeneous Selection,” “Dispersal Limitation,” “Homogenizing Dispersal,” and “Drift and Others” in both surface and subsurface soil are shown in Figure 5 and Supplementary Figure S7. ‘Homogenizing Dispersal’ significantly decreased and “Drift and Others” marginally significantly increased with the nitrogen input rates in surface soil (Figures 5A,B), while others showed no relationships with the nitrogen input rates (Supplementary Figure S7).

Figure 5

Discussion

Variations in species and phylogenetic α-diversity of the soil bacterial community along the N input gradient

We found that the species α-diversity and phylogenetic α-diversity of the soil bacterial community had different responses to nitrogen input in the alpine steppe at the Brahmaputra site, which was likely a result of one or more of the following reasons. First, soil moisture is an important factor in determining the species and phylogenetic α-diversity of the soil bacterial community (Li et al., 2021; Liu et al., 2022). However, there were no significant changes in soil moisture along the nitrogen input gradient (Supplementary Table S1). Second, plant α-diversity can still affect soil bacterial richness and α-diversity (Bakker et al., 2010; Zhang and Han, 2012; Ren et al., 2018). The response ratio of nitrogen input to the plant Pielou index increased with increasing nitrogen input dose (Supplementary Figure S8a), and had a significant positive correlation with phylogenetic α-diversity (Supplementary Table S5), but had no significant relationship with species α-diversity (Supplementary Table S6). Third, TP is also correlated with soil bacterial α-diversity (Feng et al., 2017; Zhang et al., 2017; Yang et al., 2020). The response ratio of nitrogen input to total phosphorus decreased with increasing nitrogen input dose (Supplementary Figure S8b), and had a significant negative correlation with phylogenetic and species α-diversity (Supplementary Tables S5, S6). Furthermore, the relative contribution of total phosphorus to phylogenetic α-diversity was higher than that to species α-diversity in this study. Fourth, the soil bacterial community correlated with soil enzyme activities (Li et al., 2019b). The response ratio of nitrogen input to soil sucrase decreased with increasing nitrogen input dose (Supplementary Figure S8c), and had a significant negative correlation with phylogenetic and species α-diversity (Supplementary Tables S5, S6). In this study, soil sucrase had great importance on phylogenetic α-diversity rather than species α-diversity. Fifth, the relative contributions of other environmental factors to the species and phylogenetic α-diversity of the soil bacterial community in both the surface and subsurface soils were negligible. The different relative contributions of dominant factors to species and phylogenetic α-diversity may led to different responses.

Variations in species and phylogenetic community composition of soil bacteria along the N input gradient

In this study, we also found that the responses of phylogenetic β-diversity and species β-diversity to short-term nitrogen input were different in the alpine steppe at the Brahmaputra site. This phenomenon was likely caused by the following several reasons. First, the diversity in the different dimensions of the soil microbial community may be related to environmental factors in different ways (Zong and Fu, 2021; Zhong and Fu, 2022). In this study, soil NH₄⁺-N and NO₃⁻-N contents increased with increasing nitrogen input (Supplementary Table S1). Furthermore, the soil NH₄⁺-N and NO₃⁻-N contents were marginally significantly and significantly correlated with phylogenetic community composition, but had no correlation with species community composition (Table 1). Second, phylogenetic information is better than taxonomic information in identifying some ecological processes during community assembly (Zhou and Ning, 2017). That is, ecological processes are more closely linked to phylogenetic diversity than taxonomic diversity. Some previous studies have shown that the “Homogenizing Dispersal” process leads to more similarity in communities, while the “Drift” process results in relatively low similarity in communities (Zhou and Ning, 2017). In this study, the “Homogenizing Dispersal” process decreased and the “Drift” process increased with increasing nitrogen input (Figures 4A,B), thus leading to an increase in phylogenetic β-diversity with increasing nitrogen input. The different correlations of environmental factors and ecological processes with species and phylogenetic β-diversity perhaps resulted in different responses.

Conclusion

Based on a short-term (<1 year) field nitrogen input experiment in an alpine steppe at the source of Brahmaputra, we found that short-term nitrogen input did not change the species diversity of soil bacteria, but greatly affected phylogenetic diversity. The increased magnitude of soil bacterial phylogenetic α-diversity and β-diversity increased with increasing nitrogen input dose. The different responses of soil bacterial species and phylogenetic diversity to short-term nitrogen input were likely due to differences in their relative contributions to major factors and relationships with primary factors, in which ecological processes also play a role. This study proved that the responses of the soil bacterial phylogenetic community were more sensitive than those of the species community to short-term nitrogen input. It also highlighted the importance of taking into account the phylogenetic level when studying the response of short-term nitrogen input to the soil bacterial community. Given that grasslands on the Tibetan Plateau are receiving increased N input, it is critical to understand the response of soil bacterial diversity to N-enriched conditions. Considering that prolonged nitrogen deposition may have different and more profound effects on soil bacterial communities in different dimensions, future studies are needed.

Funding

This research was supported by the Effects of short-term fertilization on soil microbial community structure in degraded alpine steppe at the source of Brahmaputra (XZ202201ZR0064G), Youth Innovation Promotion Association of Chinese Academy of Sciences (2020054), the National Natural Science Foundation of China (31600432), Bingwei Outstanding Young Talents Program of Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (2018RC202), Tibet Science and Technology Major Projects of the Pratacultural Industry (XZ202101ZD0003N), and Construction Project of Fixed Observation and Experimental Station of Support System for Agricultural Green Development in Zhongba County.

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