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Article

Differential Responses of Bacterial and Fungal Community Structure in Soil to Nitrogen Deposition in Two Planted Forests in Southwest China in Relation to pH

by
Zheng Hou
1,2,3,4,†,
Xiaohua Zhang
1,5,†,
Wen Chen
1,
Ziqi Liang
1,
Keqin Wang
6,7,
Ya Zhang
2,3,4,* and
Yali Song
6,7,*
1
College of Ecology and Environment, Southwest Forestry University, Kunming 650224, China
2
Kunming General Survey of Natural Resources Center, China Geological Survey, Kunming 650100, China
3
Technology Innovation Center for Natural Ecosystem Carbon Sink, Ministry of Natural Resources, Kunming 650100, China
4
Innovation Base for Eco-Geological Evolution, Protection and Restoration of Southwest Mountainous Areas, Geological Society of China, Kunming 650100, China
5
School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
6
School of Soil and Water Conservation, Southwest Forestry University, Kunming 650224, China
7
Yuxi Forestry Ecosystem Research Station of National Forestry and Grassland Administration, Kunming 650224, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Forests 2024, 15(7), 1112; https://doi.org/10.3390/f15071112
Submission received: 23 May 2024 / Revised: 23 June 2024 / Accepted: 25 June 2024 / Published: 27 June 2024
(This article belongs to the Special Issue Forest Plant, Soil, Microorganisms and Their Interactions)
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Abstract

:
Increased nitrogen deposition profoundly impacts ecosystem nutrient cycling and poses a significant ecological challenge. Soil microorganisms are vital for carbon and nutrient cycling in ecosystems; however, the response of soil microbial communities in subtropical planted coniferous forests to nitrogen deposition remains poorly understood. This study carried out a four-year nitrogen addition experiment in the subtropical montane forests of central Yunnan to explore the microbial community dynamics and the primary regulatory factors in two coniferous forests (P. yunnanensis Franch. and P. armandii Franch.) under prolonged nitrogen addition. We observed that nitrogen addition elicited different responses in soil bacterial and fungal communities between the two forest types. In P. yunnanensis Franch. plantations, nitrogen supplementation notably reduced soil bacterial α-diversity but increased fungal diversity. In contrast, P. armandii Franch. forests showed the opposite trends, indicating stand-specific differences. Nitrogen addition also led to significant changes in soil nutrient dynamics, increasing soil pH in P. yunnanensis Franch. forests and decreasing it in P. armandii Franch. forests. These changes in soil nutrients significantly affected the diversity, community structure, and network interactions of soil microbial communities, with distinct responses noted between stands. Specifically, nitrogen addition significantly influenced the β-diversity of fungal communities more than that of bacterial communities. It also reduced the complexity of bacterial interspecies interactions in P. yunnanensis Franch. forests while enhancing it in P. armandii Franch. forests. Conversely, low levels of nitrogen addition improved the stability of fungal networks in both forest types. Using random forest and structural equation modeling, soil pH, NH4+-N, and total nitrogen (TN) were identified as key factors regulating bacterial and fungal communities after nitrogen addition. The varied soil nutrient conditions led to different responses in microbial diversity to nitrogen deposition, with nitrogen treatments primarily shaping microbial communities through changes in soil pH and nitrogen availability. This study provides essential insights into the scientific and sustainable management of subtropical plantation forest ecosystems.

1. Introduction

Increased atmospheric nitrogen (N) deposition is a significant environmental issue that affects global change [1,2,3]. Historical data indicate that atmospheric nitrogen deposition has increased from 3.4 × 1013 g·N·a−1 to 1.0 × 1014 g·N·a−1 between 1860 and 1995, with projections suggesting a rise to 2.0 × 1014 g·N·a−1 by 2050, demonstrating a clear upward trend [4]. Soil microorganisms, particularly bacteria and fungi, serve as primary decomposers in forest ecosystems and are crucial for ecosystem functionality [5]. They facilitate the cycling of materials and the flow of energy within ecosystems [6]. An increase in nitrogen deposition can enhance net primary production, which subsequently alters the availability of microbial nutrients such as carbon and nitrogen in the soil, affecting their physiological activities [7,8]. These changes can impact the composition of microbial communities, potentially having profound implications on the global carbon and nitrogen cycles and influencing climate change [8].
The impact of atmospheric nitrogen deposition on soil microbiomes, particularly in nitrogen-rich tropical and subtropical forests, has become a pivotal area of study within the ecological sciences. This interest stems from the profound effects that nitrogen deposition has on forest soil microbial communities [9,10,11,12]. Recent meta-analyses have attempted to clarify the general response of soil microbial diversity and composition to nitrogen enrichment. These studies have consistently found that nitrogen addition typically diminishes both bacterial and fungal diversity [13,14]. However, the data from these meta-analyses are often heterogeneous, complicating the task of distinguishing responses between different ecosystems, such as natural versus plantation forests. This variability limits the precision and applicability of the findings. Notably, soil microorganisms in tropical nitrogen-rich ecosystems exhibit marked changes in nutrient content and soil properties following nitrogen addition. For instance, in coastal mangrove ecosystems, nitrogen supplementation has been linked to decreased bacterial abundance and increased fungal presence [15]. In subtropical forests in southeastern China, similar nitrogen additions have generally reduced both bacterial and fungal abundances, with fungi showing a more pronounced sensitivity to nitrogen changes [6]. In tropical forests, nitrogen inputs have curtailed microbial growth in acidic soils, with fungi demonstrating better adaptability to these acidic conditions compared to bacteria [16,17]. Despite these insights, the effects of nitrogen deposition on soil microbial communities in nitrogen-rich tropical and subtropical forests remain incompletely understood. Clarifying how soil bacterial and fungal communities and their diversity respond to nitrogen deposition is essential to assess the resilience of forest ecosystems to global changes induced by nitrogen enrichment.
Since the 20th century, the subtropical Central Yunnan Plateau has witnessed extensive vegetation restoration efforts, notably converting farmland back to forests and establishing planted afforestation projects [18,19]. These initiatives have predominantly led to the creation of pure coniferous forests primarily composed of P. yunnanensis Franch. and P. armandii Franch. However, these forests now face escalating pressures from increased nitrogen deposition, a consequence of rising reactive nitrogen emissions from expanding industrial and agricultural activities in the region [20]. Afforestation has markedly altered species richness, diversity, and soil physicochemical properties within these ecosystems, significantly affecting the diversity and composition of soil microbial communities [21,22]. Soil acidity is a key factor in both soil biogeochemical cycles and the growth environment of soil microorganisms [23]. Previous research indicates that nitrogen addition typically promotes soil acidification, thereby influencing microbial composition and diversity through reduced soil pH [24,25]. Yet, these studies have predominantly focused on naturally complex forests, with limited research directed towards plantation forests characterized by single-species stands and simpler structures. Different tree species exhibit unique nitrogen nutrient utilization strategies, which can lead to variations in soil pH [26,27], influencing the resilience of soil microorganisms to environmental changes [28]. For instance, soil microorganisms in monoculture fir forests are particularly vulnerable to changes in soil pH and nutrient dynamics resulting from nitrogen addition [9,29], whereas planted broadleaf forests demonstrate greater soil-buffering capacities and lower sensitivity to long-term nitrogen impacts compared to their natural counterparts [30]. Clearly, the impacts of nitrogen addition on nitrogen-rich planted forests and natural ecosystems vary and are not uniformly applicable across different tree species. Thus, understanding the responses of soil microbial communities to nitrogen addition in differentiated plantation forests of major tree species is crucial for assessing the impacts of global change on subtropical forest ecosystems.
To explore the effects of long-term nitrogen addition on soil microbial communities in the subtropical Central Yunnan region, we carried out extended simulated nitrogen addition experiments at the Yuxi Forest Ecosystem National Positioning Observation and Research Station. These experiments were concentrated on the subalpine planted coniferous forests, predominantly consisting of P. yunnanensis Franch. and P. armandii Franch. Our study aimed to fill the gap in understanding the microbial response to nitrogen addition in this specific subalpine area of Central Yunnan and to examine how soil microbial communities adapt to environmental changes and stress caused by prolonged nitrogen addition. Given that subtropical forests are nitrogen-rich ecosystems, nitrogen additions may lead to soil nitrogen enrichment, resulting in soil acidification, nutrient imbalances [31], and adverse effects on soil bacterial and fungal communities. Accordingly, we hypothesized that (1) soil microbial diversity is affected by nitrogen addition, with variations in plantation types driving distinct responses in soil microbial diversity to nitrogen enrichment; (2) nitrogen addition significantly impacts bacterial communities, while fungal communities are relatively less affected; and (3) nitrogen addition primarily influences soil microbial communities through changes in soil pH and nitrogen availability in both types of coniferous forests. The findings of this research are pivotal for the scientific management of subtropical plantation ecosystems in relation to nitrogen deposition and augment our understanding of soil microbial functions and ecosystem processes amidst global changes.

2. Materials and Methods

2.1. Site Description

The study area is located at the Yunnan Yuxi Forest Ecosystem National Positioning Observation and Research Station (23°46′18″~23°54′34″ N, 101°16′06″~101°16′12″ E) (Figure 1), with an altitude ranging from 1260.0 to 2614.4 m. This area features a subtropical low-latitude plateau monsoon climate characterized by typical mountain climate features. The seasons are distinctly split into dry (November to April) and wet (May to October) periods, with rain and heat coinciding and concentrated rainfall occurring from June to August [32]. The average annual precipitation is 1050 mm, and the average annual temperature is 15 °C. The highest recorded temperature is 33 °C in June, while the lowest drops to −2.2 °C in February. Forest coverage in the study area is approximately 86%, consisting primarily of primary and secondary primeval forests, which are predominantly semi-humid evergreen broad-leaved forests. The area’s vegetation is diverse, encompassing 98 families, 137 genera, and 324 species, including A. palisotii (Desv.) Alston, Reevesia pubescens Mast., and R. delavayi Franch., among others. The distribution of forests exhibits a vertical arrangement corresponding to increasing altitude. The primary forest vegetation types include natural forests such as subtropical evergreen broad-leaved forests and high mountain dwarf forests, as well as planted forests like mixed coniferous and broad-leaved forests and pure coniferous forests. P. yunnanensis Franch. and P. armandii Franch. forests are the most abundant species of planted forests in the region, coexisting in a relatively small area with similar terrain and microclimate conditions. Both plantations have been established for about 40 years. The predominant soil type is Argi-Udic ferrosols, with localized areas of Hapli-Udic argosols (World Reference Base for Soil Resource).

2.2. Experimental Design

This study focused on two types of planted forests, P. yunnanensis Franch. and P. armandii Franch., located within the research station, approximately 2.6 km apart. Nitrogen fertilization commenced in January 2019. After thorough on-site field investigations (Table S1), representative areas were selected for each forest type. Three 20 m × 20 m sample plots were established for each type, maintaining at least 10 m of separation between plots. A split-plot design was utilized within each plot, consisting of four smaller 3 m × 3 m quadrats. These quadrats were designated for the control group and three nitrogen fertilization gradients, creating a total of 12 small quadrats to provide three replicates for each treatment. Based on the atmospheric wet nitrogen deposition flux in Southwest China [33], the nitrogen deposition during dry and wet seasons (15 g·N·m−2·a−1 and 10 g·N·m−2·a−1, respectively) [34], and the annual increase in nitrogen deposition (0.05 g·N·m−2·a−1) in Southwest China [32], we adjusted the nitrogen application to reflect the annual level of 3.84 g·N·m−2·a−1. The nitrogen gradients were set as follows: 0 g·N·m−2·a−1 (CK), 10 g·N·m−2·a−1 (N10), 20 g·N·m−2·a−1 (N20), and 25 g·N·m−2·a−1 (N25). Experimental urea (CO(NH2)2 analytical grade, >=99.0%) was used as the nitrogen source. The annual nitrogen application was divided into 12 equal parts, with each portion dissolved in 1000 mL of water and applied monthly using a backpack sprayer. The control plots received an equivalent volume of water.

2.3. Soil Sampling

Soil samples were collected in early March 2023, four years and two months after the initiation of the simulated nitrogen deposition. Sampling began by removing the litter layer from the quadrat surface. Using the five-point sampling technique, soil from the top 20 cm was extracted with an auger. Soil from the three replicate quadrats under the same treatment was mixed thoroughly and sieved through a 2 mm nylon mesh to remove visible roots and stones. The sieved soil was then divided into two equal portions: one was immediately stored at −80 °C for subsequent DNA extraction and high-throughput sequencing analysis, and the other was air-dried for chemical property analysis.

2.4. Measurement of Soil Chemical Properties

The measurement of soil chemical properties was conducted using the methods outlined by Bao [35]. Soil pH was determined with a pH meter (msoil:Vwater = 1:5). Total nitrogen (TN) content was assessed via the semi-micro Kjeldahl method. Available phosphorus (AP) was quantified using inductively coupled plasma emission spectrometry. Potassium ions (K+) were measured by extraction with 1 mol·L−1 neutral ammonium acetate, followed by flame photometer analysis. Soil organic matter (SOM) content was determined using the potassium dichromate volumetric method with external heating to ascertain organic carbon, which was then converted to organic matter using a conversion factor of 1.724. Ammonium nitrogen (NH4+-N) in the soil was quantified using the indophenol blue method, and soil nitrate nitrogen (NO3−-N) was measured via ultraviolet spectrophotometry using the colorimetric method.

2.5. DNA Extraction and Illumina Sequencing

Total DNA from the samples was extracted using the EZNA™ Mag-Bind Soil DNA Kit from OMEGA Bio-tek. The extracted DNA samples were sent to Sangon Biotech (Shanghai) Co., Ltd. (Shanghai, China) for high-throughput sequencing. For soil bacteria, the V3–V4 variable region was PCR-amplified using primers 341F (5′-CCTACGGGNGGCWGCAG-3′) and 805R (5′-GACTACHVGGGTATCTAATCC-3′) [36]. For soil fungi, the ITS region was targeted using primers ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) [37] and ITS2R (5′-GCTGGCTTTCTTCATCGATGC-3′) [38]. Both bacterial and fungal amplifications involved two rounds of PCR. In the first round, we used 16SV3-V4 primers for bacteria and ITS1-ITS2 primers for fungi, with a 30 µL reaction mix (15 µL 2 × Hieff® Robust PCR Master Mix, 1 µL of each primer, 10–20 ng of PCR products, and 9–12 µL of H2O). The PCR conditions were an initial denaturation at 94 °C for 3 min, followed by 5 cycles at 94 °C for 20 s, annealing at 45 °C for 20 s, and extension at 65 °C for 30 s; then 20 cycles at 94 °C for 20 s, 55 °C for 20 s, and 72 °C for 30 s, with a final extension at 72 °C for 5 min and storage at 10 °C. In the second round, Illumina bridge PCR-compatible primers were used with a similar reaction mix and conditions: pre-denaturation at 95 °C for 3 min, followed by 5 cycles of denaturation at 94 °C for 20 s, annealing at 55 °C for 20 s, and extension at 72 °C for 30 s, concluding with a final extension at 72 °C for 5 min and storage at 10 °C. The PCR products were verified via 2% agarose gel electrophoresis, and library concentrations were measured using a Qubit 3.0 fluorometer. After confirming library quality, sequencing was conducted on the Illumina MiSeq platform.

2.6. Microbial Data Analysis and Co-Occurrence Network Construction

After quality control filtering of the sequencing data, Usearch 11.0.667 software [39] was used to cluster non-redundant sequences (excluding single sequences) at a 97% similarity threshold for operational taxonomic unit (OTU). Chimeras were removed during the clustering process, with similarity assessments conducted after comparing 0.1% of the sequences [40]. The sequences were preprocessed by trimming adapter sequences and removing low-quality reads using the FastQC and Trimmomatic tools. The SILVA database (version 132) was used for the identification of bacterial community composition, while the UNITE database (version 8.0) was used for the identification of fungal community composition. Microbial α-diversity and richness were calculated using Mothur 1.43.0. The Shannon index [41] was employed to quantify community diversity, while the Chao index [42] was used to estimate community richness. The relative abundance of bacterial and fungal communities was considered when constructing networks involving OTUs with a relative abundance above 0.1%. OTUs with a relative abundance of zero in two-thirds of the samples were excluded. Random matrix theory (RMT) was applied to determine the optimal similarity threshold, and the pairwise similarity matrix was calculated based on Spearman correlation. All analyses were performed using the Molecular Ecological Networks (MENs) analysis platform (iNAP platform, updated on 6 June 2023, https://inap.denglab.org.cn/, accessed on 20 June 2023) [43]. Nodes and edges were exported and processed using Gephi 0.9.2 software to generate co-occurrence networks for the bacterial and fungal communities.

2.7. Statistical Analysis

We investigated the effects of nitrogen addition on the soil chemical properties and the bacterial and fungal communities in the P. yunnanensis Franch. and P. armandii Franch. forests. Initially, homogeneity of variance tests were performed using SPSS 25.0 software (SPSS Inc., Chicago, IL, USA). Upon confirming homogeneity of variance, analysis of variance (ANOVA) was utilized to evaluate the impacts of different nitrogen addition treatments on soil chemical properties and microbial α-diversity. For cases of heterogeneous variance, the Welch correction method was applied prior to variance analysis. In the R software (v4.3.1; http://www.r-project.org/, accessed on 25 June 2023), the “vegan” [44] and “ggplot2” [45] packages were utilized for principal coordinate analysis (PCoA) and similarity analysis (ANOSIM) based on microbial genus-level classification to detect differences in microbial community composition using Bray–Curtis distance. Redundancy analysis (RDA) was conducted to ascertain whether soil properties were key factors influencing the composition of bacterial and fungal communities in these forests. Subsequently, the “randomForest” package was used for random forest analysis to assess the importance of individual soil chemical properties on the composition of microbial communities in P. yunnanensis Franch. and P. armandii Franch. forests, where community composition was represented by the first axis of PCoA. A structural equation model (SEM) was established using Amos 24.0 software to evaluate the effects of nitrogen addition and soil properties (TN, NH4+-N, and pH) on microbial communities. The goodness of fit of the model was assessed using the chi-square test (χ2), p-value, and root mean square error of approximation (RMSEA).

3. Results

3.1. Soil Properties in Response to N Addition

As depicted in Table 1, significant differences were observed in soil nutrients between the two forest stands, primarily attributed to variations in tree species. Additionally, nitrogen input significantly influenced soil nutrients in both stands. Compared to CK, the soil SOM and K+ content in the P. yunnanensis Franch. forest were significantly higher than in the P. armandii Franch. forest. Conversely, the levels of pH, NH4+-N, and NO3−-N were notably lower in the P. yunnanensis Franch. forest. In the P. yunnanensis Franch. forest, an increase in nitrogen input was correlated with a gradual rise in soil pH and initial increases followed by decreases in NH4+-N and NO3−-N. On the other hand, in the P. armandii Franch. forest, escalating nitrogen input resulted in a progressive decrease in soil pH and K+ content, while NO3−-N, SOM, and AP content showed an increase. The content of NH4+-N initially rose and then diminished with increased nitrogen input.

3.2. Soil Microbial Diversity in Response to N Addition

Utilizing α-diversity indices to evaluate soil microbial diversity and richness under control conditions (CK), the P. yunnanensis Franch. forest exhibited significantly higher numbers of OTUs, Shannon index, and Chao index for soil bacterial communities compared to the P. armandii Franch. forest. However, the trend was reversed for fungal communities. In the P. yunnanensis Franch. forest, nitrogen addition notably decreased the OTUs, Shannon index, and Chao index of bacterial communities in a dose-dependent manner (CK > N10 > N20 > N25). Conversely, in the P. armandii Franch. forest, nitrogen supplementation led to increases in these indices for bacterial communities, with the most pronounced effects observed at the lowest level of nitrogen addition (N10). Regarding soil fungal communities in the P. yunnanensis Franch. forest, nitrogen addition had a stimulatory effect on the OTUs, Shannon index, and Chao index, with the N20 treatment showing more significant enhancement than the N10 and N25 treatments. However, in the P. armandii Franch. forest, nitrogen addition resulted in decreased OTUs and Chao index for fungal communities, while the Shannon index increased. Overall, the varying levels of nitrogen addition and the distinct characteristics of the two forest types significantly influenced the α-diversity of both soil bacterial and fungal communities in the subalpine forests of central Yunnan. These effects were found to be statistically significant (p < 0.001; Table 2).
Notably, significant alterations were observed in the fungal communities of both forest types (p < 0.05), whereas the bacterial communities exhibited no substantial changes, revealing that the composition of fungal species is more responsive to nitrogen addition compared to most bacterial species (Figure 2).

3.3. Effects of N Addition on Soil Microbial Community Composition

The predominant bacterial taxa in both the P. yunnanensis Franch. and P. armandii Franch. forest soils were Acidobacteria and Proteobacteria, constituting approximately 58.82% to 68.39% of the total community. In a similar pattern, the dominant fungal taxa were Basidiomycota and Ascomycota, comprising about 79.17% to 91.79% of the community. The Acidobacteria phylum is about twice as abundant in P. yunnanensis Franch. forests compared to P. armandii Franch. forests. Conversely, the Proteobacteria phylum was significantly more abundant in P. armandii Franch. forests (p < 0.05; Figure 3a). However, the difference in the relative abundance of fungal taxa between the two forests was not substantial (Figure 3b).
In P. yunnanensis Franch. forests, the relative abundance of the Acidobacteria phylum within the soil bacterial community significantly increased at low nitrogen levels and decreased markedly at higher nitrogen levels (N10 > N20 > N25 > CK), while other bacterial phyla showed no notable response to nitrogen addition (Figure 3a; Table S2). For soil fungal taxa, the Rozellomycota phylum significantly declined with increasing nitrogen addition. Ascomycota showed a notable increase only at the N10 level, and Mucoromycota increased significantly at N25. Correlation analysis indicated a significant positive correlation between the Acidobacteria phylum and NO3−-N (p < 0.001) and a significant negative correlation between the Rozellomycota phylum and both NH4+-N and pH (p < 0.05) (Table S3). In P. armandii Franch. forests (Table S4), nitrogen addition significantly affected the relative abundance of the Acidobacteria and Chloroflexi phyla in soil bacteria, with an increase observed at low nitrogen levels and a decrease at high levels. The relative abundance of Proteobacteria was substantially reduced, showing no significant differences among the various nitrogen levels. Acidobacteria were positively correlated with NH4+-N, whereas Proteobacteria showed a significant negative correlation with NO3−-N and AP and a positive correlation with K+. The Actinobacteria phylum was positively correlated with AP and negatively with K+ (Table S4). Compared to CK, nitrogen addition significantly increased the relative abundance of Ascomycota and decreased that of Basidiomycota in fungal taxa. The relative abundance of Mortierellomycota was highest at the lowest nitrogen input level (N10) but was suppressed at N20 and N25. Correlation analyses revealed a significant positive correlation of Basidiomycota with pH and negative correlations with SOM and TN. Ascomycota showed significant negative correlations with pH and positive correlations with SOM and TN; Mortierellomycota were significantly positively correlated with NH4+-N (Table S5).

3.4. Soil Microbial Co-Occurrence Networks

In the P. yunnanensis Franch. and P. armandii Franch. forests, the total number of nodes in the bacterial co-occurrence networks was comparable to those of their respective controls (CKs). However, the network of the P. yunnanensis Franch. forest exhibited a 39.5% increase in connecting edges compared to that of the P. armandii Franch. forest (Figure 4). This difference underscores the greater complexity of bacterial interspecies interactions within the P. yunnanensis Franch. forest. With increased nitrogen application in the P. yunnanensis Franch. forest, there was a notable decrease in the total number of nodes, the number of connecting edges, and the average degree of the soil bacterial co-occurrence network, accompanied by an increase in modularity value. Conversely, in the P. armandii Franch. forest, these parameters initially decreased and then increased as nitrogen levels rose, reaching their peak in the N20 treatment. The ratios of modularity values and positively correlated edges exhibited an inverse trend, suggesting that the complexity of bacterial interspecies relationships was reduced with increased nitrogen in the P. yunnanensis Franch. forest, whereas it was augmented in the P. armandii Franch. forest, reaching significant enhancement at the N20 treatment level and indicating a threshold for nitrogen-induced promotion.
The properties of the fungal co-occurrence networks in both forests demonstrated trends opposite to those observed in their bacterial counterparts (Figure 5). In both forest types, the number of total nodes under control conditions (CKs) was comparable, yet the total number of connected edges in the fungal network of the P. yunnanensis Franch. forest was significantly lower than that in the P. armandii Franch. forest, indicating lesser complexity in fungal interspecies relationships in the former. For both forests, the total number of nodes, the number of connecting edges, and the average degree of the soil fungal co-occurrence network initially increased and then decreased following nitrogen addition treatments. Conversely, the modularity values exhibited a decrease followed by an increase, peaking in the N20 treatments. These patterns suggest that lower levels of nitrogen addition promote stabilization and complexity of fungal networks in both forests, whereas higher levels of nitrogen do not sustain this positive effect and may even inhibit it.

3.5. Relationships between Microbial Community and Soil Chemical Properties

Soil properties emerged as key determinants of the differences in bacterial and fungal community compositions across the forest types. RDA supported this observation, revealing that environmental factors accounted for 63.67% and 85.89% of the variations in soil bacterial communities and 81.03% and 77.04% in the fungal communities of P. yunnanensis Franch. and P. armandii Franch. forests, respectively (Figure S1). Random forest analysis identified NH4+-N as a crucial factor influencing the composition and abundance of soil bacterial and fungal communities in the P. yunnanensis Franch. forest and the bacterial communities in the P. armandii Franch. forest. Additionally, AP was pinpointed as a primary variable impacting the soil bacterial communities in the P. armandii Franch. forest. Soil pH also played a significant role in these community dynamics (Figure 6a). We further explored the effects of nitrogen addition on soil-microbe diversity in these subalpine planted forests through a structural equation model (Figure 6b). The model exhibited a good fit for the P. yunnanensis Franch. forest (χ2 = 4.515, df = 7, p = 0.719, RMSEA < 0.001) and for the P. armandii Franch. forest (χ2 = 11.496, df = 6, p = 0.074, RMSEA < 0.05). In the P. yunnanensis Franch. forest model, soil pH negatively influenced bacterial α-diversity, while NH4+-N content positively affected fungal α-diversity. TN content had a negative impact. In the P. armandii Franch. forest model, soil pH negatively affected both bacterial and fungal α-diversity. NH4+-N content positively influenced bacterial diversity, and TN content positively affected fungal diversity. A significant negative interaction between bacteria and fungi was also observed in this model (Figure 6b). In conclusion, NH4+-N and pH were identified as the primary factors influencing the soil bacterial and fungal communities in both forest types.

4. Discussion

With the influence of global environmental changes and human activities, atmospheric nitrogen deposition in forest ecosystems in subtropical regions of China continues to increase. The study of soil microbial community response to nitrogen deposition in subtropical artificial coniferous forests provides an important basis for predicting the ecological consequences of the future increase in atmospheric nitrogen deposition as well as the scientific and sustainable management of the ecosystem. In this study, four nitrogen application gradients were established for long-term simulated nitrogen deposition experiments, and the response of soil microbial diversity and community composition of subtropical plantation forests to long-term nitrogen deposition in different stand types was systematically investigated. Our research found that different afforestation tree species have varying effects on soil pH, nutrient content, and microbial communities. Additionally, sustained high levels of nitrogen addition negatively impact microbial community diversity, with fungal communities being more sensitive to nitrogen addition than bacterial communities. Soil pH and nitrogen availability jointly regulate the diversity of soil bacterial and fungal communities.

4.1. Afforestation Tree Species Differences Lead to Distinct Responses of Soil Microbial Diversity to Nitrogen Addition

Consistent with our hypothesis, the continuous four-year nitrogen addition significantly altered soil microbial diversity in two planted forests, each exhibiting distinct responses to the nitrogen input. The divergence among ecosystem types and background pH values contributes to variations in soil resistance and stability in response to nitrogen deposition [31]. It is generally accepted that metal cations in soils act as the primary mechanism for buffering against soil acidification, which is typically balanced by the interaction between potassium (K+) and acidic (hydrogen, H+) cations [46,47]. Despite both forests being coniferous and sharing acidic soil characteristics within the same research area, their responses to nitrogen addition varied markedly. In the P. yunnanensis Franch. forest, nitrogen addition led to an increase in soil pH (from 4.17 to 4.35) and K+ content. Conversely, in the P. armandii Franch. forest, both soil pH (from 4.71 to 4.18) and K+ content gradually decreased, highlighting a notable difference in their buffering capacities against nitrogen disturbances. The well-known process of soil acidification in the nitrogen cycle occurs as bacteria oxidize ammonium to nitrate, producing hydrogen ions during nitrification [48], which was evident from the decrease in pH observed in the P. armandii Franch. forest, where ammonium and nitrate nitrogen showed opposing trends. Additionally, a significant increase in SOM content was observed in the P. armandii Franch. forest following nitrogen addition. From a microbial perspective, nitrogen addition typically reduces SOC mineralization, which is interpreted as a reduction in microbial nitrogen mining, thereby retaining more carbon in the soil [49]. Furthermore, the nitrogen-induced increase in SOM may also enhance soil cation exchange capacity (CEC) and contribute to a reduction in soil pH levels [47].
It is widely accepted that nitrogen addition generally has a negligible effect on the diversity of fungal communities [50]. Fungi, compared to bacteria, typically require less nitrogen [51] and are capable of degrading complex organic compounds more slowly [25]. This resistance to changes is primarily because fungi are not sensitive to alterations in soil pH, which are significantly influenced by nitrogen addition [47]. Contrary to our second hypothesis, our research revealed that the diversity of fungal communities was impacted by nitrogen addition in a manner similar to that of bacterial communities. This unexpected outcome could be attributed to the presence of polymerized phenolic compounds, such as lignin and tannins, in pine forest soils, which represent complex, low-quality carbon sources that are difficult to decompose. Interestingly, fungi do not necessarily favor these tough-to-degrade sources of organic matter [51]. Furthermore, a microculture experiment demonstrated that both fungi and bacteria were inefficient at utilizing these low-quality carbon sources during the later stages of apoplastic decomposition [52]. This suggests that additional nitrogen might have comparable effects on both bacterial and fungal communities. After nitrogen addition, the β-diversity of soil fungal communities in both P. yunnanensis Franch. and P. armandii Franch. forests exhibited more pronounced differences compared to bacterial communities. This highlights the heightened sensitivity of fungal communities, which play a crucial role in soil carbon cycling in organically rich soils, to nitrogen addition [53].

4.2. Nitrogen Addition Alters the Relative Abundance Composition of Microbial Communities

In the P. yunnanensis Franch. planted forests, the OTUs, Chao index, and Shannon index of soil bacteria significantly declined following nitrogen addition. Conversely, in the P. armandii Franch. forests, these indices for soil bacteria notably increased post-nitrogen addition compared to CK, although values were lower at N20-N25 levels than at N10. This indicates a threshold effect in nitrogen-induced microbial growth stimulation, potentially due to pH reductions at higher nitrogen levels (N20-N25) leading to magnesium/calcium deficiencies and aluminum toxicity in the soil, adversely affecting soil bacteria [54,55]. While tree species differences caused variations in soil bacterial responses to nitrogen addition, the observed inhibition at high nitrogen levels in the P. armandii Franch. forest suggests that prolonged high nitrogen addition could detrimentally affect the soil bacterial community in subtropical coniferous forests, albeit to varying extents [56]. The N10 and N20 treatments enhanced the α-diversity and richness of soil fungal communities in the P. yunnanensis Franch. forest. However, the α-diversity and richness in the N25 treatment were lower than those in the N10 and N20 treatments, signifying a nutrient limitation threshold. This could be due to increased nitrogen at N25 leading to limitations in other nutrients, such as phosphorus and potassium, thus reducing the diversity of root-associated fungi [57,58]. In contrast, nitrogen addition at all levels significantly reduced the OTU number and Chao index of soil fungal communities in the P. armandii Franch. forest while only increasing the Shannon index. Given the Chao index’s sensitivity to changes in rare taxa [50], this suggests that nitrogen addition negatively impacts the soil fungal community in the P. armandii Franch. forest, although the impact is less pronounced than in the P. yunnanensis Franch. forest. Several studies have noted large differences in root exudation between species [59], which is a key mediator of plant–microbe–soil interactions, affecting soil organic matter decomposition, nutrient cycling, and microbial community composition [60,61]. Different patterns of root exudation in P. yunnanensis Franch. and P. armandii Franch. may differentially respond to additional nitrogen, leading to variations in changes in the relative abundance of soil microbes.
Notably, the relative abundance of Acidobacteria was about twice as high in the P. yunnanensis Franch. forest compared to the P. armandii Franch. forest, while Proteobacteria were significantly more abundant in the P. armandii Franch. forest than in the P. yunnanensis Franch. forest. This disparity can be linked to differences in soil pH and nitrogen availability between the two forest types. Acidobacteria, which are typically oligotrophic, favor acidic environments [62], whereas Proteobacteria often thrive in nutrient-rich conditions [63,64]. The levels of NO3−-N and NH4+-N were substantially higher in the soil of the P. armandii Franch. forest, providing a nitrogen-rich environment conducive to Proteobacteria growth. Elevated nitrogen levels in the soil can increase competition for resources and alter soil nutrients, thereby affecting the ecological niches of certain microbial taxa and, thus, their relative abundance within the overall community [65]. Nitrogen addition significantly increases the relative abundance of Chloroflexi, which are involved in the second step of nitrification [66]. The higher soil NO3−-N content resulting from nitrogen addition in the P. armandii Franch. forest provides ample nutrients for Chloroflexi growth, peaking in the N20 treatment [67]. However, nutrient enrichment from high-level nitrogen addition (N25) is not conducive to Chloroflexi reproduction, possibly due to close interactions between Chloroflexi and other microorganisms, with high levels of added nitrogen having a toxic effect on other microbial community members.
Unlike previous studies, although the fungal community composition of P. yunnanensis Franch. and P. armandii Franch. forests was similar, their responses to nitrogen addition differed significantly [68]. In the P. yunnanensis Franch. forest, most fungal phyla exhibited strong resilience against nitrogen-induced environmental stress, except for a significant decrease in Rozellomycota with increasing nitrogen levels. Simultaneously, a significant negative correlation was observed between the relative abundance of Rozellomycota and soil pH. This observation suggests that Rozellomycota may have higher competitive survival capabilities in acidic environments. However, due to the presence of numerous parasitic fungi within Rozellomycota [69], further investigation is warranted to elucidate its ecological adaptability and biological characteristics. In the P. armandii Franch. forest, nitrogen addition significantly reduced the relative abundance of Basidiomycota and increased that of Ascomycota. Ascomycota, known for their responsiveness to high nutrient levels, play a critical role in decomposing organic matter in the soil [65]. Here, a significant positive correlation was found between Ascomycota’s relative abundance and SOM, which increased with higher nitrogen content [70]. Basidiomycota, crucial for soil carbon cycling processes like litter and lignin decomposition in fertile forests [71], represents a slower-growing fungal type [72]. It competes with Ascomycota for resources in limited ecological niches. The decrease in Basidiomycota’s relative abundance might reduce competition for resources, thereby facilitating the increase in Ascomycota’s abundance [73].
Ecosystem stability hinges not only on community composition but also on the associations and co-occurrence networks among microbial communities [74,75]. In our study, we analyzed microbial community networks using correlations among OTUs, noting that positive and negative relationships among OTUs do not imply direct physical interactions but rather indicate co-occurrence [76]. Our results demonstrated that based on co-occurrence network attributes, bacterial interaction complexity was higher in P. yunnanensis Franch. forests than in P. armandii Franch. forests. Conversely, fungal interaction complexity was lower in P. yunnanensis Franch. forests. This disparity reflects the varying capacities of microbial communities to withstand nitrogen-induced disturbances influenced by differences in soil pH and nutrient availability. In P. yunnanensis Franch. forests, nitrogen addition led to reductions in the number of nodes, edge connections, and average degree in bacterial networks, paralleled by increased modularity and reduced network complexity. This underscores the detrimental impacts of nitrogen on bacterial communities in these forests, potentially due to constrained carbon (C) and phosphorus (P) resources following nitrogen addition, thereby diminishing their diversity and network complexity [77]. In P. armandii Franch. forests, bacterial interaction complexity was augmented with nitrogen addition, but a threshold was observed beyond continuous high-level nitrogen addition (N20), corroborating the α-diversity findings. This suggested that sustained high-level nitrogen addition could negatively impact soil bacterial communities in subtropical coniferous forests, with varying degrees of influence. In both forests, the fungal networks exhibited increases in nodes, edge connections, and average degree with nitrogen application, peaking at N20, revealing that low-level nitrogen addition fosters fungal community growth while continuous high-level nitrogen addition impedes this enhancement, adversely affecting fungal co-occurrence and network stability in both forest types.

4.3. Drivers of Microbial Community Responses to Nitrogen Addition

Consistent with our third hypothesis, nitrogen addition significantly influenced soil pH and nitrogen availability in two coniferous forests, consequently affecting soil microbial communities. The random forest model identified NH4+-N, pH, and AP as key factors shaping the composition and abundance of bacterial and fungal communities in both forest types. Further, the structural equation model demonstrated that nitrogen addition altered soil chemical properties (pH, NH4+-N, and TN), significantly impacting the alpha diversity of bacterial and fungal communities in both forests. Thus, NH4+-N and pH emerged as the primary factors regulating these soil communities. Nitrogen inputs into ecosystems contribute to soil acidification mechanisms [31]. The conversion of urea to NH4+-N in the soil, either fixed or volatilized by microorganisms or plants [78], generates H+, contributing to acidity. The oxidation of NH4+ to NO3− also increases net H+ production, further promoting soil acidification. Additionally, the rise in organic nitrogen can enhance root biomass, potentially increasing the uptake of alkaline cations (e.g., Ca2+, Mg2+, and K+), thus reducing soil buffering capacity and inducing acidification [79], which detrimentally affects microbial communities. This is also the underlying cause of pH reduction in P. armandii Franch. forests. Conversely, nitrogen addition can accelerate the release of alkaline cations from litter and roots by promoting decomposition [80], enhancing soil buffering capacity, and mitigating acidification. The increase in soil pH in P. yunnanensis Franch. forests may be related to this process. NH4+-N positively affected fungal community abundance in P. yunnanensis Franch. forests and bacterial communities in P. armandii Franch. forests, likely due to excess nitrogen leading to NH4+ accumulation, to which many microorganisms are sensitive [81], thus alleviating resource limitations and enabling specific species to thrive. TN exhibited contrasting effects on fungal α-diversity in the two forest types, possibly due to differing nitrogen utilization abilities among fungi. For example, in P. yunnanensis Franch. forests, the abundance of Ascomycota was positively correlated with TN, while the adverse impact of TN on fungal abundance in these forests may be linked to such differences [82]. AP, as a crucial factor in regulating the bacterial communities in P. armandii Franch. forests, could be attributed to low nitrogen addition, which enhances microbial phosphorus acquisition and stimulates microbial growth. However, continuous nitrogen increases may lead to phosphorus limitations in the ecosystem, causing an N and P nutrient imbalance and thus affecting the bacterial communities and abundance in P. armandii Franch. forests.

5. Conclusions

In conclusion, our study demonstrates that after four years of continuous nitrogen addition, the soil microbial communities in subtropical planted coniferous forests exhibit varied responses that are dependent on the afforestation tree species. This variability is reflected in changes to soil pH, nutrient content, and the dynamics of microbial communities. Notably, prolonged high-level nitrogen addition has consistently led to detrimental effects on microbial community diversity. Fungal communities, in particular, show greater sensitivity compared to bacterial communities, with significant changes observed in their diversity, community structure, and network properties in response to nitrogen addition. This study underscores that soil pH and nitrogen availability are crucial factors influencing the diversity of soil bacterial and fungal communities in these forests. These findings offer valuable theoretical insights into the long-term effects of nitrogen deposition on soil microbes in subtropical planted coniferous forests and elucidate the complex relationships between soil microbial communities and soil properties.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f15071112/s1, Table S1: Site characteristics of two forest types.; Table S2: Response to N addition at the bacterial/fungal phylum level in P. yunnanensis Franch. forest soil. Table S3: Correlation of soil bacterial/fungal phylum levels and soil chemical properties in P. yunnanensis Franch. forests. Table S4: Response to N addition at the bacterial/fungal phylum level in P. armandii Franch. forest soil. Table S5: Correlation of soil bacterial/fungal phylum levels and soil chemical properties in P. armandii Franch. forests. Figure S1: RDA analysis of bacterial and fungal community structure in relation to environmental factors.

Author Contributions

Investigation, Methodology, Formal analysis, Writing—Original draft, Writing—Review and Editing, Z.H. Conceptualization, Visualization, Methodology, Data curation, Writing—Original draft, X.Z. Investigation, Methodology, Data curation, W.C. Investigation, Validation, Software, Z.L. Resources, Funding acquisition, Supervision, Project administration, K.W. Funding acquisition, Supervision, Y.Z. Project administration, Supervision, Writing—Review and Editing, Y.S. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Agricultural Joint Special Project of Yunnan Province (202301BD070001-059), the project of China Geological Survey (No. DD20230482), the Scientific Research Foundation of Education Department of Yunnan Province (2022J0510), First-class Discipline Construction Project of Yunnan Province ([2022] No. 73), Natural Ecology Monitoring Network Project Operation Project of Yuxi Forest Ecological Station in Yunnan Province (2022-YN-13), Long-term Scientific Research Base of Yuxi Forest Ecosystem National in Yunnan Province (2020132550), the National Natural Science Foundation of China (No. 42271094), funded by Science and Technology Innovation Foundation of Command Center of Integrated Natural Resources Survey Center (No. KC20230019, KC20230021).

Data Availability Statement

The data are available upon request from the corresponding author.

Acknowledgments

We are particularly grateful to Yali Song (School of Soil and Water Conservation, Southwest Forestry University), who provided great support to this study and provided us with writing assistance, which enabled this study to be carried out smoothly.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Overview map of the study area.
Figure 1. Overview map of the study area.
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Figure 2. Principal coordinate analysis (PCoA) was performed to analyze the bacterial and fungal communities in different forest stands under varying levels of nitrogen addition using an OTU table. Abbreviations: CK, 0 g·N·m−2·a−1; N10, 10 g·N·m−2·a−1; N20, 20 g·N·m−2·a−1; and N25, 25 g·N·m−2·a−1. YB, the bacterial community of P. yunnanensis Franch. forest; YF, the fungal community of P. yunnanensis Franch. forest; HB, the bacterial community of P. armandii Franch. forest; HF, the fungal community of P. armandii Franch. forest.
Figure 2. Principal coordinate analysis (PCoA) was performed to analyze the bacterial and fungal communities in different forest stands under varying levels of nitrogen addition using an OTU table. Abbreviations: CK, 0 g·N·m−2·a−1; N10, 10 g·N·m−2·a−1; N20, 20 g·N·m−2·a−1; and N25, 25 g·N·m−2·a−1. YB, the bacterial community of P. yunnanensis Franch. forest; YF, the fungal community of P. yunnanensis Franch. forest; HB, the bacterial community of P. armandii Franch. forest; HF, the fungal community of P. armandii Franch. forest.
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Figure 3. The relative abundance of bacteria and fungi at the phylum level. Relative abundance at the bacterial phylum level (a); relative abundance at the fungal phylum level (b). Abbreviations: CK, 0 g·N·m−2·a−1; N10, 10 g·N·m−2·a−1; N20, 20 g·N·m−2·a−1; and N25, 25 g·N·m−2·a−1. YB, the bacterial community of P. yunnanensis Franch. forest; YF, the fungal community of P. yunnanensis Franch. forest; HB, the bacterial community of P. armandii Franch. forest; HF, the fungal community of P. armandii Franch. forest.
Figure 3. The relative abundance of bacteria and fungi at the phylum level. Relative abundance at the bacterial phylum level (a); relative abundance at the fungal phylum level (b). Abbreviations: CK, 0 g·N·m−2·a−1; N10, 10 g·N·m−2·a−1; N20, 20 g·N·m−2·a−1; and N25, 25 g·N·m−2·a−1. YB, the bacterial community of P. yunnanensis Franch. forest; YF, the fungal community of P. yunnanensis Franch. forest; HB, the bacterial community of P. armandii Franch. forest; HF, the fungal community of P. armandii Franch. forest.
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Figure 4. Soil bacterial co-occurrence network-based OTU profile (a). Characterization of the properties of bacterial co-occurrence networks (b). Abbreviation: n, total nodes; L, total linking edges. CK, 0 g·N·m−2·a−1; N10, 10 g·N·m−2·a−1; N20, 20 g·N·m−2·a−1; and N25, 25 g·N·m−2·a−1. Y: P. yunnanensis Franch. forest; H: P. armandii Franch. forest. Node size indicates the connection size of the module, red connecting lines indicate cooperative relationships between species, and green connecting lines indicate competitive relationships.
Figure 4. Soil bacterial co-occurrence network-based OTU profile (a). Characterization of the properties of bacterial co-occurrence networks (b). Abbreviation: n, total nodes; L, total linking edges. CK, 0 g·N·m−2·a−1; N10, 10 g·N·m−2·a−1; N20, 20 g·N·m−2·a−1; and N25, 25 g·N·m−2·a−1. Y: P. yunnanensis Franch. forest; H: P. armandii Franch. forest. Node size indicates the connection size of the module, red connecting lines indicate cooperative relationships between species, and green connecting lines indicate competitive relationships.
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Figure 5. Soil fungal co-occurrence network-based OTU profile (a). Characterization of the properties of fungal co-occurrence networks (b). Abbreviations: n, total nodes; L, total linking edges. CK, 0 g·N·m−2·a−1; N10, 10 g·N·m−2·a−1; N20, 20 g·N·m−2·a−1; and N25, 25 g·N·m−2·a−1. Y: P. yunnanensis Franch. forest; H: P. armandii Franch. forest. Node size indicates the connection size of the module, red connecting lines indicate cooperative relationships between species, and green connecting lines indicate competitive relationships.
Figure 5. Soil fungal co-occurrence network-based OTU profile (a). Characterization of the properties of fungal co-occurrence networks (b). Abbreviations: n, total nodes; L, total linking edges. CK, 0 g·N·m−2·a−1; N10, 10 g·N·m−2·a−1; N20, 20 g·N·m−2·a−1; and N25, 25 g·N·m−2·a−1. Y: P. yunnanensis Franch. forest; H: P. armandii Franch. forest. Node size indicates the connection size of the module, red connecting lines indicate cooperative relationships between species, and green connecting lines indicate competitive relationships.
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Figure 6. Soil properties drive the variation of soil bacterial/fungal community structure and richness. Random forests were used to determine the importance of the variable (a). Structural equation modeling (SEM) in soil-microbial community systems in response to N addition (b). Abbreviations: * indicates p < 0.05, ** indicates p < 0.01; pH, pondus hydrogenii; SOM, soil organic matter; NH4+-N, soil ammonium N; NO3−-N, soil nitrate N; TN, total nitrogen; AP, available phosphorus; K+, potassium ion; B. α index: bacterial α index; F. α index: fungal α index; YB: the bacterial community of P. yunnanensis Franch. forest; YF: the fungal community of P. yunnanensis Franch. forest; HB: the bacterial community of P. armandii Franch. forest; HF: the fungal community of P. armandii Franch. forest. Red arrows indicate significant positive correlations (p < 0.05), green arrows indicate significant negative correlations (p < 0.05), and gray arrows indicate non-significant relationships (p > 0.05).
Figure 6. Soil properties drive the variation of soil bacterial/fungal community structure and richness. Random forests were used to determine the importance of the variable (a). Structural equation modeling (SEM) in soil-microbial community systems in response to N addition (b). Abbreviations: * indicates p < 0.05, ** indicates p < 0.01; pH, pondus hydrogenii; SOM, soil organic matter; NH4+-N, soil ammonium N; NO3−-N, soil nitrate N; TN, total nitrogen; AP, available phosphorus; K+, potassium ion; B. α index: bacterial α index; F. α index: fungal α index; YB: the bacterial community of P. yunnanensis Franch. forest; YF: the fungal community of P. yunnanensis Franch. forest; HB: the bacterial community of P. armandii Franch. forest; HF: the fungal community of P. armandii Franch. forest. Red arrows indicate significant positive correlations (p < 0.05), green arrows indicate significant negative correlations (p < 0.05), and gray arrows indicate non-significant relationships (p > 0.05).
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Table 1. Soil properties analysis.
Table 1. Soil properties analysis.
Forest TypesTreatmentsSoil Physicochemical Properties
pHSOMNH4+-NNO3−-NAPK+TN
(g·kg−1)(mg·kg−1)(mg·kg−1)(mg·kg−1)(mg·kg−1)(g·kg−1)
P. yunnanensis Franch. ForestCK4.17(0.04) c64.67(4.13) a11.62(0.34) c1.09(0.18) c0.19(0.01) ab29.19(7.02) b0.28(0.01) b
N104.25(0.02) b70.73(11.27) a14.92(0.28) b1.64(0.08) a0.20(0.01) ab19.81(1.23) c0.30(0.00) a
N204.32(0.04) ab64.67(4.59) a16.14(0.34) a1.36(0.13) b0.17(0.04) b40.97(2.41) a0.29(0.01) ab
N254.35(0.04) a64.27(3.69) a15.08(0.20) b1.04(0.06) d0.22(0.02) a21.42(1.23) b0.31(0.02) a
P armandii Franch. ForestCK4.71(0.02) a47.18(4.91) b14.20(0.98) c1.60(0.22) d0.13(0.02) b25.17(2.32) a0.27(0.03) b
N104.53(0.05) b58.88(2.21) a18.53(0.29) a3.64(0.49) c0.19(0.02) a22.49(1.39) ab0.32(0.02) a
N204.42(0.04) c48.16(2.44) b15.39(0.16) b8.80(0.24) b0.21(0.03) a19.28(1.61) b0.26(0.03) b
N254.18(0.04) d62.00(3.84) a11.40(0.57) d9.71(0.21) a0.18(0.02) ab21.42(1.23) b0.33(0.02) a
TotalN0.000 ***0.020 *0.000 ***0.000 ***0.041 *0.000 ***0.001 **
Forest types0.000 ***0.000 ***0.035 *0.000 ***0.1030.000 ***0.864
N× Forest types0.000 ***0.0930.000 ***0.000 ***0.009 **0.000 ***0.17
(1) Data are presented as means (standard errors), and the different letters within columns indicate significant differences among treatments in the same stand (p < 0.05). (2) * indicates p < 0.05, ** indicates p < 0.01, *** indicates p < 0.001. (3) Abbreviations: CK, 0 g·N·m−2·a−1; N10, 10 g·N·m−2·a−1; N20, 20 g·N·m−2·a−1; and N25, 25 g·N·m−2·a−1. SOM, soil organic matter; TN, total nitrogen; AP, available phosphorus; K+, potassium ion.
Table 2. Soil bacterial and fungal alpha diversity analysis.
Table 2. Soil bacterial and fungal alpha diversity analysis.
Forest Types BacteriaFungi
TreatmentsOTUsShannonChaoOTUsShannonChao
P. yunnanensis Franch. ForestCK3416(189) a5.92(0.05) a4068(201) a481(28) c2.69(0.11) c487(34) c
N102787(17) bc5.85(0.04) ab3524(112) b884(4) a3.21(0.07) b1087(34) ab
N202578(95) c5.82(0.05) b3200(190) b886(33) a3.83(0.22) a1128(58) a
N252819(118) b5.78(0.03) b3322(231) b793(16) b3.07(0.02) b1028(10) b
P. armandii Franch. ForestCK2388(153) c5.63(0.06) c2778(59) c741(37) a2.76(0.06) a973(57) a
N102979(103) a6.00(0.05) a3758(87) a287(51) c3.20(0.07) b305(34) c
N202689(65) b5.99(0.02) a3161(176) b363(15) bc2.80(0.02) a456(44) b
N252217(148) cd5.83(0.10) b2683(65) c434(57) b3.93(0.14) c444(60) b
TotalN0.000 ***0.000 ***0.000 ***0.2910.000 ***0.014 *
Forest types0.000 ***0.3070.000 ***0.000 ***0.510.000 ***
N×Forest types0.000 ***0.000 ***0.000 ***0.000 ***0.000 ***0.000 ***
(1) Data are presented as means (standard errors), and the different letters within columns indicate significant differences among treatments in the same stand (p < 0.05). (2) * indicates p < 0.05, *** indicates p < 0.001. (3) Abbreviations: CK, 0 g·N·m−2·a−1; N10, 10 g·N·m−2·a−1; N20, 20 g·N·m−2·a−1; and N25, 25 g·N·m−2·a−1.
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Hou, Z.; Zhang, X.; Chen, W.; Liang, Z.; Wang, K.; Zhang, Y.; Song, Y. Differential Responses of Bacterial and Fungal Community Structure in Soil to Nitrogen Deposition in Two Planted Forests in Southwest China in Relation to pH. Forests 2024, 15, 1112. https://doi.org/10.3390/f15071112

AMA Style

Hou Z, Zhang X, Chen W, Liang Z, Wang K, Zhang Y, Song Y. Differential Responses of Bacterial and Fungal Community Structure in Soil to Nitrogen Deposition in Two Planted Forests in Southwest China in Relation to pH. Forests. 2024; 15(7):1112. https://doi.org/10.3390/f15071112

Chicago/Turabian Style

Hou, Zheng, Xiaohua Zhang, Wen Chen, Ziqi Liang, Keqin Wang, Ya Zhang, and Yali Song. 2024. "Differential Responses of Bacterial and Fungal Community Structure in Soil to Nitrogen Deposition in Two Planted Forests in Southwest China in Relation to pH" Forests 15, no. 7: 1112. https://doi.org/10.3390/f15071112

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