Characteristics of ecological enzymes and nutrients mediated by soil microorganisms in a subtropical evergreen broad-leaved forest under nitrogen deposition 

Characteristics of ecological enzymes and nutrients mediated by soil microorganisms in a subtropical evergreen broad-leaved forest under nitrogen deposition | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Characteristics of ecological enzymes and nutrients mediated by soil microorganisms in a subtropical evergreen broad-leaved forest under nitrogen deposition Xiaodong Li, Lianbo SU, Keqin Wang, Chenggong Song, Yali Song This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4561535/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Feb, 2025 Read the published version in Scientific Reports → Version 1 posted 5 You are reading this latest preprint version Abstract Microorganisms are critical in forest ecosystems, where they secrete soil ecological enzymes and mediate nutrient cycling. These processes are essential in determining how these ecosystems respond to nitrogen (N) deposition inputs. In this study, an N deposition experiment was conducted with three levels of N addition treatments in a subtropical evergreen broad-leaved forest in southwest China. The aim was to identify the effects of low (LN: 10 g·m −2 ·yr −1 ), medium (MN: 20 g·m −2 ·yr −1 ), and high N addition (HN: 25 g·m −2 ·yr −1 ) on soil microbial community structure, diversity, ecological enzyme activities, and nutrient content, and to explore whether and how soil microorganisms influence ecological enzyme activity and nutrient cycling. Our observations indicated that surface soil exhibited the highest microbial diversity, ecological enzyme activities, and nutrient contents. N deposition led to a reduction in soil bacterial and fungal diversity, with bacterial diversity consistently higher than fungal diversity. Moreover, bacterial community structures were generally more diverse and complex compared to fungal communities. The study emphasized that bacteria were relatively enriched under LN treatment, while fungi exhibited higher relative abundance under control conditions. Different soil microbial groups exhibited distinct responses to N deposition, with an inhibitory effect on enzyme activities such as invertase (Inv), urease (Ure), and acid phosphatase (ACP), and an enhancement of catalase (CAT) activity. With increasing N deposition levels, soil organic carbon (SOC), total N (TN), and total phosphorus (TP) contents decreased, whereas total potassium (TK), nitrate N (NO 3 — -N), and ammonium N (NH 4 + -N) exhibited the opposite trend. Co-linearity network analysis revealed stronger interactions among soil bacteria compared to fungi. The dominant bacterial phyla Proteobacteria and Verrucomicrobia showed stronger correlations with Ure and ACP, respectively, while Acidobacteria exhibited a higher correlation with TP. Among the dominant fungal phyla, Basidiomycota had stronger correlations with CAT, NO 3 — -N, and NH 4 + -N, while Ascomycota was notably associated with Inv. These results suggest that soil bacteria have stronger correlations with ecological enzymes, whereas soil fungi are more closely related to nutrient dynamics. This implies that bacteria and fungi have distinct advantages in enzyme secretion and nutrient mediation, leading to a trend of nutritional complementarity. Biological sciences/Ecology/Forest ecology Biological sciences/Ecology/Forestry microbial community soil enzymes soil nutrients nitrogen deposition evergreen broad-leaved forest Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Nitrogen (N) is a critical element in terrestrial ecosystems, playing a fundamental role in biogeochemical cycles 1 . The rise in atmospheric N concentrations is primarily linked to fossil fuel combustion 2 , fertilizer production and application 3 , human activities, and the expansion of livestock farming 4,5 . In China, annual atmospheric N deposition surged significantly from 7.6 Tg in 1978 to 20 Tg by 2010 6 , profoundly impacting soil nutrient circulation, biological vitality, and forest ecosystem functions. While moderate N deposition enhances inorganic N availability in forest soils, improving soil fertility and facilitating plant N absorption and utilization, N saturation can induce shifts in microbial biomass and community composition, influencing carbon and N retention in forest soil ecosystems worldwide. This can modify soil productivity, biogeochemical cycles, and energy dynamics 7–9 . Soil microbial communities, as dynamic elements of the subsurface ecosystem 10 , play a pivotal role in balancing soil organic matter turnover rates, substrate ratios, and nutrient management, impacting ecological processes in ecosystems 11 . These communities exhibit high sensitivity to N deposition 12 . Soil ecological enzymes and nutrient levels are critical indicators for assessing soil quality 13 and for understanding soil degradation and restoration processes 14,15 , effectively reflecting the extent and nature of biochemical activities in the soil. Alterations in ecological enzyme activities and nutrient concentrations due to N deposition can influence carbon, N, and phosphorus dynamics in forest soil ecosystems 16 . However, existing research yields conflicting results regarding the impact of N deposition on microbial-secreted ecological enzyme activities and nutrient modulations. Research by 17 found that N deposition enhances forest soil microbial biomass by augmenting external N availability, thereby boosting soil extracellular enzyme activity, which transitions soil microbial biomass from N-degrading enzymes to carbon-degrading enzymes. Litter-derived organic matter is a primary nutrient source in soil, with microorganisms facilitating decomposition through extracellular enzyme production 18 . Fukami et al. 19 and Wallenstein et al. 20 illustrated that N deposition can affect microbial community diversity, potentially reducing decomposition rates, limiting soil carbon sequestration, and constraining soil ecological functions. Conversely, Freedman et al. 21 and Carey et al. 22 argued that shifts in soil microbial abundance under N deposition contribute to decreased organic matter breakdown or enhanced ecosystem carbon storage. In a study by Entwistle et al. 23 , N deposition was found to increase phenolic dissolved organic carbon content, alter microbial community composition, and lead to incomplete microbial lignin degradation, additionally reducing extracellular enzyme activity and gene transcripts encoding these enzymes. Furthermore, N deposition may adversely affect soil microbial growth by increasing leaching of base cations (calcium and magnesium) and mobilizing aluminum 24 . The enrichment of N can also lower the fungi-to-bacteria ratio 25,26 , resulting in a shift towards more bacteria-dominated communities 27,28 . N deposition indirectly impacts soil microorganisms by changing micro-environmental factors such as soil moisture, texture, temperature, and nutrient profiles, particularly N, driven by shifts in plant composition and productivity at regional scales. These changes ultimately affect climate change 29 . To deepen our understanding, it is essential to explore how microorganisms, enzymes, and nutrient status respond to N input in forest ecosystems and how they interact with each other. The dry and wet zones in southwest China receive significant N deposition, with values of 15 and 10 g N·m − 2 ·yr − 1 , respectively 30,31 , which are remarkably higher than the national average. These high N input levels limit litter decomposition and nutrient release by microorganisms in forest areas. Currently, N deposition in evergreen broad-leaved forests has continued into the third dry season (as of April 30, 2022). Previous studies in various forests have shown that N addition decreases soil microbial diversity, network complexity 32,33 , and soil carbon cycle enzyme activities 34 . However, the response of soil microorganisms to N deposition, especially under continuous N deposition, should also consider their secreted ecological enzyme activities and nutrient mediation 35 . This study explores the interplay between soil microorganisms, ecological enzymes, and nutrients by analyzing shifts in soil microorganisms (such as structural composition, abundance variations, and diversity), soil ecological enzyme activities, and nutrients in response to N deposition. The goal is to enhance our understanding of the comprehensive impact of N deposition on microbial life activities in subtropical evergreen broad-leaved forests. We hypothesize that ( 1 ) N deposition decreases soil bacterial and fungal diversity; ( 2 ) the structural composition of soil bacterial and fungal communities displays group-specific responses to N deposition; and ( 3 ) N deposition influences subtropical forest microbial communities, potentially impacting soil ecological enzymes and nutrients. 2. Materials and methods We ensure that who have permission to do the field study in the forest from the forest authority. As a national field positioning research station, this forest is managed by us (Southwest Forestry University) in a unified manner. 2.1 Overview of the study area The evergreen broad-leaved forest selected for this study is located in the Mopan Mountain region (23 ◦ 46′18′′–23 ◦ 54′34′′ N, 101 ◦ 16′06′′–101 ◦ 16′12′′ E, 2270 m a.s.l.), within the National Positioning Observation and Research Station in the Yuxi Forest Ecosystem, Southwestern China. This area is characterized by a low-latitude and high-altitude environment with typical mountain climate features. The altitude ranges from 1260.0 to 2614.4 meters, resulting in significant height variations and distinct vertical climate changes. The climate is classified as a mid-subtropical plateau, with 2380 hours of sunshine annually. The lowest temperature recorded is -2.2°C, the highest is 33.0°C, and the region experiences distinct dry and wet seasons. The dry season spans from November to April and is characterized by ample sunshine, dry air, and reduced precipitation, while the wet season, from May to October, is marked by less sunlight, high humidity, and increased precipitation. The mean annual temperature (MAT) over the past decade was 15.1°C, and the mean annual precipitation (MAP) was 1050 mm. The soil in this area consists mainly of mountainous red and yellow-brown soil. The soil layer thickness varies, with some areas having thin soil layers, about 60–80 cm deep in the study area. This region is primarily composed of primary and secondary original forest areas with a forest coverage rate of 86%. The dominant tree species in this subtropical evergreen broad-leaved forest include Castanopsis carlesii (60%), Lithocarpus mairei , Betula utilis , Rhododendron delavayi , and Dichotomanthes tristaniicarpa . 2.2 Design of plot and fertilization A representative evergreen broad-leaved forest was selected based on field surveys to ensure uniform stand structures and high representativeness. Three standard plots, each measuring 20 × 20 m 2 , were randomly established for observation and study. Table 1 provides an overview of the plot conditions. Additionally, within each standard plot, four smaller 3 × 3 m 2 subplots were randomly placed to apply varying levels of N deposition. To prevent mutual interference, a distance of over 10 meters was maintained between these subplots. Table 1 Characteristics of the sample plots in subtropical evergreen broad-leaved forest. Stand Altitude/m Slope/(°) Age/a DBH/ cm Mean tree H /m Canopy density Aspect Soil type 1 2258 13 23 9 9 0.85 NW Mountainous red soil 2 2193 15 21 9.2 9.2 0.90 NW 3 2236 16 23 8.9 8.9 0.87 NW Based on China's current annual N deposition increment of 0.05 g·m − 2 ·yr − 1 36 and the wet N deposition amount in the study area of 3.84 g·m − 2 ·yr − 1 , along with China's average N deposition range up to 2000, which ranges from 2.11 to 6.35 g·m − 2 ·yr − 1 37 , and the N deposition in the Huaxi Rain Screen Region of 9.5 g·m − 2 ·yr − 1 38 , as well as the dry N deposition in Southwest China, which ranges from 0.60 to 5.46 g·m − 2 ·yr − 1 39 . This study also references N deposition experiments conducted at the Harvard Forest in North America 40 , the Ailao Mountain National Nature Reserve in China 41 , and the evergreen broad-leaved forest in Guizhou 42 . The study established control (CK, 0 g·m − 2 ·yr − 1 ), low N (LN, 10 g·m − 2 ·yr − 1 ), medium N (MN, 20 g·m − 2 ·yr − 1 ), and high N (HN, 25 g·m − 2 ·yr − 1 ) treatment levels, each with three replicates. The research group had previously conducted simulated N deposition for two years. In this study, during the third year's dry season, we continued the simulated N deposition experiment. Urea [CO(NH 2 ) 2 ] was used as the N source for treatment, dissolved in 1 L of water. N treatment was carried out in the middle of every month using a hand-held sprayer, according to the aforementioned levels. There was no substantial difference in the soil moisture content or temperature following control and different treatments of N addition. 2.3 Sample collection and analytical determination Soil samples were collected during the dry season of the third year following N deposition (April 30, 2022). A soil auger was used to extract five cores from each quadrat randomly using a random number positioning method. These cores were then combined into a composite sample. Gravel, roots, and other debris were removed from the soil samples, which were then placed in sterile bags and transported to the laboratory. A portion of the fresh soil was preserved at 4°C for the analysis of soil invertase (Inv), urease (Ure), acid phosphatase (ACP), catalase (CAT), nitrate N (NO 3 − -N), and ammonia N (NH 4 + -N). The remaining portion was air-dried and sieved through 0.25 and 2 mm sieves for the determination of soil organic carbon (SOC), total N (TN), total phosphorus (TP), and total potassium (TK). The remaining soil samples were sealed in sterile bags and stored in a refrigerator at -180°C for DNA extraction and high-throughput sequencing. Five grams of fresh soil samples were weighed, and the total DNA of soil microorganisms was extracted using the OMEGA EZNATM Mag-Bind Soil DNA Kit. The integrity, concentration, and purity of the genomic DNA were assessed qualitatively through agarose gel electrophoresis. The extracted DNA was stored at -20°C for future use. For each soil sample, primers 341F (CCTACGGN GGCWGCAG) and 805R (GACTACHVGGGGTATTCTA ATCC) targeting the V3-V4 region of the bacterial 16S rRNA gene were used to amplify gene fragments of relevant microbial taxa. PCR reaction conditions followed the kit instructions. Subsequently, DNA recovery was performed using the Biochem agarose recovery kit (cat. SK8131). The genomic DNA was accurately quantified using the Qubit 2.0 DNA Detection Kit to determine the appropriate amount of DNA for addition to the PCR reaction. All samples were combined in equal proportions and thoroughly mixed before being used for library construction and sequencing. The kit was used according to the provided instructions. The purified and enriched library was then analyzed using 2% agarose gel electrophoresis to isolate and purify the final library fragments. Based on the PCR product concentration, all successfully amplified products were pooled in equal proportions and subjected to paired-end 250 bp sequencing on the Illumina MiSeq platform. The sequencing library preparation and high-throughput sequencing were outsourced to Shanghai Sangong Bioengineering Co., Ltd. Subsequently, the raw data underwent quality control, filtering, splicing, removal of chimeras, comparison with a custom reference database, and verification of index and adapter integrity. Valid sequences from each sample were analyzed using the RDP classifier to identify bacterial sequences. Species richness and diversity statistics were calculated using Mothur. An OTU table was then constructed based on the number of sequences in each OTU within each sample. Rare OTUs with abundance values lower than 0.001% of the total sample sequencing amount were removed. The resulting OTU abundance matrix was used for further analyses. Additionally, Table 2 was referenced to calculate specific indicators. Table 2 Alpha diversity indices of soil microorganisms. Index name Computing formula Reference URL Chao1 index \({S}_{chao1}={S}_{obs}+\frac{{n}_{1}({n}_{1}-1)}{2({n}_{2}+1)} \left(1\right)\) http://www.mothur.org/wiki/Chao Shannon index \({H}_{shannon}=-\sum _{i=1}^{{S}_{obs}}\frac{{n}_{i}}{N}\text{ln}\frac{{N}_{i}}{N} \left(2\right)\) http://www.mothur.org/wiki/Shannon Simpson index \({D}_{simpson}=\frac{{\sum }_{i=1}^{{S}_{obs}}{n}_{i}({n}_{i}-1)}{N(N-1)} \left(3\right)\) http://www.mothur.org/wiki/Simpson Enzymes involved in the carbon, N, and phosphorus cycles, such as Inv, Ure, and ACP, were analyzed spectrophotometrically. CAT, an enzyme involved in hydrogen peroxide metabolism, was determined using potassium permanganate titration 43–46 . Toluene was used as the inhibitor for biological activity. Soil ecological enzyme activities were assessed within one week of sampling. Detailed methods are provided in Table 3 . Table 3 Substrates, culture conditions, assay products, and references used for measuring soil ecological enzyme activities. Enzyme Substrate Incubation temperature(℃) and time assay product Methodological references Invertase Sugar 37/24 h Glucose (mg˖g − 1 ˖24 − 1 ) Hu et al., 43 Urease Urea 37/24 h NH 4 + (mg˖g − 1 ˖24 − 1 ) David et al., 44 Acid phosphatase Disodium Benzene Phosphate 37/24 h Phenol (mg˖g − 1 ˖24 − 1 ) Sun et al., 45 Catalase Hydrogen peroxide 24/20 min Potassium permanganate (mg˖g − 1 ˖20 − 1 ) Guan et al., 46 SOC was determined using external heating with potassium dichromate. TN was measured using the semi-micro Kjeldahl method. TP was analyzed via molybdenum antimony colorimetry, and TK was determined using flame photometry. NO 3 — -N was quantified using UV spectrophotometry, and NH 4 + -N was measured using KCl extraction followed by indigo blue colorimetry 47 . 2.4 Analytical processing of data Microsoft Excel 2010 was used for initial data processing. Soil microbial community alpha diversity, ecological enzyme activities, and nutrient data were assessed using SPSS 26.0 (Chicago, IL, USA) for single-factor analysis of variance (ANOVA), least significant difference (LSD), and multiple comparisons (α = 0.05). Constrained principal coordinate analysis (PCoA) was performed using the Lianchuan Biological Cloud Platform ( https://www.omicstudio.cn/ ). The structural composition and relative abundance of soil microorganisms, as well as bar charts of ecological enzyme activities, were generated using Origin 2022 Pro (Origin Lab, Northampton, MA, USA). The network topology diagram illustrating the relationships between soil microbial communities, ecological enzyme activities, and nutrients was created using R (3.6.3) software. 3. Results 3.1 Influence of N deposition on the structural composition of soil microbial communities Representative sequences, selected based on the highest abundance for each OTU, were aligned with the Silva database. Soil bacteria in all samples were annotated across 21 phyla, 59 classes, 84 orders, 151 families, 239 genera, and 2,215 species. Soil fungi were annotated across 15 phyla, 45 classes, 126 orders, 279 families, 574 genera, and 920 species. Community composition analysis of soil bacteria and fungi in the evergreen broad-leaved forest at the phylum level revealed some bacteria and fungi with unclear classification status. Among the annotated bacteria, those with an overall composition proportion exceeding 1% included Acidobacteria, Proteobacteria, Actinobacteria, Planctomycetes, Verrucomicrobia, unclassified_Bacteria, Chloroflexi, Firmicutes, and Bacteroidetes. For fungi, the identified taxa included Basidiomycota, Ascomycota, Mortierellomycota, and Rozellomycota (Fig. 1 a,b). Acidobacteria and Proteobacteria were the dominant phyla among soil bacteria, each comprising more than 20% of the composition. Notably, N deposition levels did not significantly affect the relative abundance of Acidobacteria and Proteobacteria ( p > 0.05). Conversely, soil fungi were predominantly represented by Basidiomycota and Ascomycota, each constituting more than 20% of the composition. HN deposition levels significantly affected the relative abundance of Basidiomycota and Ascomycota ( p < 0.05). The ternary diagram shows that bacteria are more concentrated in LN-treated soil, while fungi are more concentrated in control (CK) soil. Both soil bacteria and fungi exhibit a trend of gradually shifting towards the middle and bottom layers in response to varying levels of N deposition (Fig. 1 c-j). 3.2 Influence of N deposition on the diversity of soil microbial communities This study employed the Chao1, Shannon, and Simpson indices to evaluate the richness and diversity of soil bacterial and fungal communities, along with the alpha diversity index statistics across three soil layers. The results are presented in Table 4 . In the surface soil layer, the Chao1 and Shannon indices were higher compared to the middle and bottom layers, while the Simpson index was lower, indicating greater richness and diversity in the surface soil. The Chao1 indices of both soil bacteria and fungi significantly decreased under HN and MN treatments ( p < 0.05), implying a reduction in richness and diversity due to N deposition. While N deposition had a minor impact on the Shannon indices of bacteria and fungi and a slight effect on their Simpson indices, these changes were not statistically significant ( p > 0.05). In summary, N deposition led to a decline in the richness and diversity of soil bacteria and fungi. Table 4 Analysis of soil microbial alpha diversity under N deposition (mean ± SD). The differences among different N deposition levels within the same soil layer are statistically significant ( p < 0.05), indicated by lowercase letters. The same is true below. Treatments Bacteria Fungi Chao1 Shannon Simpson Chao1 Shannon Simpson C1A 1741.05 ± 69.46a 5.648 ± 0.200a 0.0093 ± 0.0032a 1423.82 ± 36.31a 4.348 ± 0.432a 0.0288 ± 0.0134a C1B 1731.64 ± 68.20a 5.758 ± 0.169a 0.0077 ± 0.0052ab 1313.25 ± 79.45ab 4.237 ± 0.087a 0.0310 ± 0.0008a C1C 1674.32 ± 90.58ab 5.696 ± 0.011a 0.0079 ± 0.0068ab 1120.00 ± 67.98b 4.195 ± 0.464a 0.0652 ± 0.0096ab C1D 1621.24 ± 20.91b 5.564 ± 0.107a 0.0104 ± 0.0031a 1415.31 ± 71.14a 4.284 ± 0.594a 0.0297 ± 0.0180a C2A 1715.04 ± 107.85a 5.478 ± 0.019a 0.0121 ± 0.0030a 1300.06 ± 132.50a 4.261 ± 0.429a 0.0300 ± 0.0221a C2B 1657.00 ± 132.39ab 5.524 ± 0.10a 0.0080 ± 0.0070ab 1226.85 ± 21.84ab 4.224 ± 0.132a 0.0424 ± 0.0073a C2C 1636.44 ± 135.87ab 5.52 ± 0.056a 0.0089 ± 0.0042ab 1101.64 ± 35.01b 4.047 ± 0.089a 0.0680 ± 0.0003ab C2D 1596.39 ± 23.98b 5.415 ± 0.520a 0.0132 ± 0.0016a 1228.24 ± 77.99ab 4.237 ± 0.422a 0.0329 ± 0.0069a C3A 1660.71 ± 38.47a 5.362 ± 0.121a 0.0138 ± 0.0012a 1164.16 ± 53.20a 4.211 ± 0.029a 0.0327 ± 0.0018a C3B 1650.77 ± 37.60a 5.462 ± 0.259a 0.0087 ± 0.0020ab 1153.49 ± 142.81a 3.950 ± 0.228a 0.0477 ± 0.0022a C3C 1623.47 ± 64.86a 5.431 ± 0.047a 0.0096 ± 0.0007ab 1151.29 ± 38.45a 3.771 ± 0.147a 0.0850 ± 0.0057ab C3D 1591.12 ± 28.92ab 5.403 ± 0.101a 0.0139 ± 0.0012a 1158.60 ± 151.33a 3.981 ± 0.107a 0.0343 ± 0.0242a Principal Coordinate Analysis (PCoA) was carried out using the UniFrac distance metric to examine the grouping patterns among soil bacterial and fungal communities. This investigation aimed to evaluate the dissimilarities in these communities across different levels of N deposition, as illustrated in Fig. 2 a and 2 b. The figures illustrate the extent of overlap and divergence observed among various N deposition levels. Additionally, the similarity of soil bacterial and fungal communities under different N deposition levels was assessed using Anosim in combination with the weighted UniFrac distance algorithm, along with non-parametric tests. The results revealed that, at the OTUs level, there was no significant difference in the beta diversity of soil bacterial and fungal communities across varying N deposition levels (R = 0.216, P = 0.964; R = 0.018, P = 0.459). Through the analysis of Venn diagrams, the numbers of shared and unique OTUs among soil bacterial and fungal communities were compared under different N deposition levels. As illustrated in Figs. 3 a-f, the surface soil across varying N deposition levels shared 759 OTUs, while the middle and deep layers had 870 and 775 shared OTUs, respectively. Compared to CK, the number of distinct bacterial OTUs in the upper soil layer decreased across all N deposition levels (61, 112, and 92 for LN, MN, and HN, respectively). A total of 462 identical fungal OTUs were identified among various N deposition levels in the upper soil layer, while the middle and bottom layers contained 447 and 392 identical OTUs, respectively. The number of unique fungal OTUs in the upper soil layer decreased under LN and MN treatments (121 and 125, respectively), with an increase observed under HN treatment, albeit not statistically significant. In the middle and lower soil layers, the number of unique sequences of soil bacteria and fungi increased compared to the CK. Specifically, under the HN treatment, there were 129 and 128 unique sequences of soil bacteria in the middle and lower layers, respectively, while soil fungi had 196 and 170 unique sequences, respectively. This observation highlights the variation in the relative abundance of soil bacteria and fungi across different soil layers in response to varying N deposition levels (Fig. 1 c-j). 3.3 Influence of N deposition on soil ecological enzymes and nutrients The results presented in Fig. 4 a-d demonstrated that, at the same N deposition level, the activities of soil Inv, Ure, ACP, and CAT exhibited an increasing trend with soil depth. Inv activity in the surface soil is notably higher, ranging from 31.53–149.06%, compared to the middle and bottom layers. Similarly, urease activity showed an increase of 19.17–53.23%, acid phosphatase activity was 23.25–35.07% higher, and catalase activity was 10.37–27.45% higher. Notably, Inv activity displayed the most significant variation among different soil layers, while catalase activity exhibited the least variation. The changes in enzyme activities under continuous N deposition levels varied significantly. N deposition generally suppressed soil Inv, Ure, and ACP activities, while it enhanced soil CAT activity. Specifically, compared to the CK, the HN treatment resulted in the most notable decreases of 39.90%, 35.87%, and 14.08% in Inv, Ure, and ACP activities, respectively. Conversely, CAT activity in the HN treatment showed the highest increase of 18.81%. As illustrated in Fig. 5 a-f, under consistent N deposition levels, there was a steady increase in SOC, TN, TP, TK, NO 3 − -N, and NH 4 + -N with soil depth. Specifically, the surface soil showed a 48.41–59.37% higher SOC content compared to the middle and bottom layers. Similarly, TN content increased by 26.86–51.57%, TP by 17.55–65.98%, and TK by 43.58–66.87%. Notably, the most significant variations were observed in NO 3 − -N and NH 4 + -N levels across different soil layers, with increases ranging from 206.85–428.37% and 148.30–186.15%, respectively. The impact of N deposition on soil nutrient contents varied significantly. N deposition generally suppressed SOC, TN, and TP, while it enhanced TK, NO 3 − -N, and NH 4 + -N. Compared to CK, the highest reductions in soil SOC, TN, and TP were observed under the HN treatment, decreasing by 67.95%, 36.71%, and 45.37%, respectively. Conversely, the HN treatment resulted in the most notable increases in soil TK, NO 3 − -N, and NH 4 + -N, rising by 19.59%, 839.96%, and 195.57%, respectively. 3.4 Relationships among soil microorganisms, ecological enzymes, and nutrients under N deposition To investigate the relationships between soil bacteria and fungi with ecological enzyme activities and nutrient content following N deposition, a co-linearity network analysis was conducted (Fig. 6 a-d). The analysis revealed stronger interactions among soil bacteria compared to fungi. The dominant bacterial phyla, Proteobacteria and Verrucomicrobia, showed strong correlations with Ure and ACP, respectively. Acidobacteria exhibited a significant correlation with TP. Among the prominent fungal phyla, Basidiomycota had stronger correlations with CAT, NO 3 − -N, and NH 4 + -N, while Ascomycota was more closely linked with Inv. 4. Discussion Surface soil biochemical processes play a crucial role in maintaining ecosystem stability. Our study revealed that the surface soil had the highest levels of microbial diversity, ecological enzyme activities, and nutrient content. These findings are consistent with the research conducted by Wang et al. 48 , Yuan et al. 49 and Xu et al. 50 , who investigated soil microbial diversity, enzyme activities, and vertical variations in soil nutrients following N deposition in Pinus massoniana-Quercus variabilis mixed forests and Cunninghamia lanceolata forests. The surface soil layer likely facilitates rapid organic matter transformation due to its higher bulk density, increased biomass of microorganisms and root systems, favorable hydrothermal conditions, and superior aeration. These conditions promote microbial activity and enzyme secretion in the soil, thereby enhancing nutrient cycling. The study identified Acidobacteria and Proteobacteria as the dominant phyla in the soil bacteria of evergreen broad-leaved forests, each accounting for more than 10% of the total composition. Similarly, Basidiomycota and Ascomycota were the dominant phyla among soil fungi, with each comprising over 10% of the total. These results align with previous research by Lagomarsino et al. 51 and Lin et al. 52 . This consistency could be attributed to the broad ecological range of these four phyla that are exhibited in forest environments. N deposition did not significantly impact the relative abundance of the bacterial phyla Acidobacteria and Proteobacteria. These two bacteria play a crucial role in the conversion of ammonia to nitrite during N-cycling 53 . They dominate bacterial communities under acidic and nitrate-rich conditions 54 and possess strong adaptability and resilience, resulting in minimal changes in their relative abundance under N deposition. The relative abundance of the fungal phylum Basidiomycota was notably higher in HN, while the relative abundance of the fungal phylum Ascomycota was significantly lower in HN. Both Basidiomycota and Ascomycota are known for decomposing complex carbon sources 55 . The contrasting shifts in their relative abundance under HN conditions could be attributed to differing N utilization strategies or heightened competitive interactions, ultimately impacting their respective abundances. In this study, soil bacteria were relatively concentrated in the LN treatment, whereas soil fungi were more concentrated in the CK treatment. Bacteria generally have faster growth rates and reproductive capabilities compared to fungi, enabling them to utilize a broader range of organic matter. In contrast, fungi exhibit specificity in their selection of organic matter, making them more sensitive to environmental conditions. HN concentration in the LN treatment compared to the CK treatment may favor bacterial growth, while the conditions in the CK treatment may better support the original fungal communities 56 . This finding supports hypothesis 2, indicating that different soil microbial groups (bacteria and fungi) exhibit specific responses to N deposition. The study also observed that soil bacterial and fungal relative abundances tended to shift towards the middle and lower soil layers with varying N deposition levels. This trend was further supported by the quantitative differences in soil bacteria and fungi across soil layers, as shown in Fig. 3 a-f. Increasing N deposition enriched the soil with N, subsequently impacting soil respiration, N transformation, microbial metabolism, and interactions with plants. While surface soil may not currently provide the most conducive environment for microbial survival, it is susceptible to changes in N leaching due to factors like temperature and rainfall. Consequently, surface soil exposed to high levels of N deposition may eventually revert to a state favorable for microbial habitats. Excessive N deposition can disrupt the microbial community's diversity and suppress biomass, hampering the soil carbon cycle and reducing carbon storage, especially in forests subjected to medium to long-term N deposition or HN levels. The impact on microorganisms is more pronounced in such conditions 57 . Our study observed a decline in the diversity of soil bacteria and fungi, supporting our hypothesis that N deposition decreases microbial diversity. This observation aligns with similar findings reported in various studies by Song et al. 58 , Wang et al. 59 , and Freedman et al. 60 . Soil acidification resulting from N deposition has been shown to alter the soil microbial community's structure 61 , reduce microbial biomass, and limit carbon source utilization by microorganisms, consequently diminishing microbial diversity. However, differences in life history traits and ecological network relationships among species can lead to varied reductions in soil bacterial and fungal diversity. Notably, under N deposition, soil bacterial diversity was found to be higher than fungal diversity, possibly due to the interplay between soil bacterial and fungal communities and their respective habitats and behaviors. Bacteria, with their diverse metabolic pathways and broad lifestyles, play a critical role in organic matter decomposition and carbon and N cycling, as emphasized by Shao et al. 62 . Bacteria tend to prefer readily available carbon sources. In contrast, soil fungi typically target recalcitrant organic matter decomposition, resulting in a narrower ecological niche for fungi in the soil. In this study, N deposition was observed to generally inhibit soil Inv, Ure, and ACP activities, while promoting soil CAT activity. The suppression of Inv activity by N deposition likely results from the reduced decomposition rate of soil organic matter, leading to decreased substrate availability for Inv and subsequent inhibition of its activity. The decline in Ure activity due to N deposition may be attributed to its role in the N cycle, particularly in catalyzing urea decomposition into NH 4 + and CO 2 , the form of N readily usable by plants. Previous studies have indicated that N deposition can impede soil N mineralization rates 63 , disrupting the N cycle and consequently reducing Ure activity. Furthermore, N deposition inhibits ACP activity, possibly due to its function in converting organic phosphorus to inorganic phosphorus 64 . This nutrient imbalance in the soil, caused by N deposition, could diminish phosphorus uptake by microorganisms, hindering ACP secretion and resulting in reduced ACP activity 65 . CAT participates in the soil humification process and decomposes hydrogen peroxide. N deposition enhanced CAT activity, likely due to its impact on litter decomposition inhibition 66 and humification reduction. Consequently, as the decomposition rate of litter organic matter decreases and residual litter accumulates, CAT activity increases to degrade the remaining organic matter. However, contrasting findings were reported in another study 67 . Possible explanations include higher litter input and sustained CAT activity levels under N deposition in the study region. Alternatively, the current N deposition level may not produce toxic concentrations of compounds like nitrate during N metabolite processes, thus not affecting CAT structure. In this study, N deposition generally suppressed soil SOC, TN, and TP, while enhancing soil TK, NO 3 − -N, and NH 4 + -N. N deposition has the potential to impact the soil microbial ecosystem function 68 , triggering redox reactions that prompt the release of a substantial amount of CO 2 from microbial carbon, thereby reducing soil SOC accumulation. Soil organic matter decomposition generates organic acids, which may stimulate nitrifying and ammonifying bacteria activity under acidic conditions, leading to elevated levels of NO 3 − -N and NH 4 + -N in the soil. Nevertheless, N-fixing microorganisms might outcompete others in N-rich environments, potentially diminishing their physiological requirements and competitive edge in N fixation, resulting in reduced TN biological fixation in the soil. Additionally, N deposition could impede microorganisms from decomposing phosphorus-containing organic matter, consequently reducing TP release. Moreover, N deposition is likely to enhance the soil's TK content by increasing the exchange capacity of K + with Ca + and Mg + ions. N deposition has the potential to influence the allocation of microorganisms toward the production of ecological enzymes and the abundance of specific enzymes synthesized by soil microorganisms 69 . It can also impact nutrient levels such as carbon, N, and phosphorus 70 , thereby regulating microbial physiological characteristics to establish a new equilibrium between resources and microorganisms 71 , which in turn can influence critical biochemical processes within the ecosystem 72 . This study employed a collinear network analysis to explore the microbial community, enzymatic secretion, and nutrient interrelationships. The results indicated that soil bacteria engaged in a higher level of interactions compared to soil fungi due to their numerous populations, rapid growth, fast metabolism, diverse metabolic pathways, and robust environmental adaptability. Proteobacteria and Verrucomicrobia showed notable correlations with Ure and ACP, while the bacterial phylum Acidobacteria exhibited strong correlations with TP. Proteobacteria, a significant group of diazotrophs, along with Verrucomicrobia, demonstrated the ability to convert atmospheric N 2 into bioavailable forms 73 . Verrucomicrobia are proficient at converting organic matter into a form usable by other microorganisms. Nitrification enzyme Ure and phosphatase ACP play pivotal roles in catalyzing these processes for plant absorption and utilization. Acidobacteria can solubilize organic phosphorus in soil through the secretion of acidic metabolites, including organic acids and acidic polysaccharides. This mechanism is vital for phosphorus recycling and its availability in the soil, as it transforms organic phosphorus into inorganic phosphorus, which is essential for plant growth. The fungus Basidiomycota showed a strong association with CAT, while Ascomycota exhibited a significant correlation with Inv. Basidiomycota also displayed strong correlations with NO 3 − -N and NH 4 + -N. Both Basidiomycota and Ascomycota play critical roles in decomposing lignin and other complex organic compounds 74 . Basidiomycota secretes CAT to accelerate the breakdown of these compounds. To sustain this process, Basidiomycota relies on vital nutrients such as soil NO 3 − -N and NH 4 + -N for growth and metabolism, enhancing their N utilization efficiency. Conversely, Ascomycota releases Inv, an enzyme that hydrolyzes carbohydrates like sucrose to provide carbon sources for growth and metabolism. The robust interaction between soil bacteria and fungi in this ecosystem is evident, displaying a strong correlation with soil enzymes and nutrients, supporting our hypothesis that N deposition alters soil enzyme activities and nutrient levels, influencing microbial interactions. Microorganisms release specialized enzymes to access necessary nutrients for their metabolic functions. 5. Conclusions In general, N treatments, especially high N addition, tended to inhibit the diversity of soil bacteria and fungi, but bacteria exhibited higher tolerance to N compared to fungi, which might influence their strategies in secreting enzymes, mediating nutrients, and surviving across different soil layers. The differences in soil enzyme activities were primarily influenced by enzyme types. This may be related to the effects of N input on the availability of soil nutrients and changes in soil microorganisms in subtropical areas. Additionally, N deposition might alter the abundance and composition of microbial communities, thereby affecting enzyme activities and nutrients. Therefore, the effect of N input on soil microbial communities, ecological enzyme activities, nutrients and how they interact with each other in a subtropical evergreen broad-leaved forest further study. Declarations Ethical approval : The authors and I declare that the methods used for collecting soil samples, handling and processing samples, and performing chemical experiments were in accordance with relevant institutional, national, and international guidelines, regulations, and laws. All methods were carried out in accordance with the applicable guidelines and there were no instances of malpractice or non-compliance. In addition, appropriate literature references have been provided to support the methods used. Data availability: The data that support our research findings are available from the corresponding author on request. Acknowledgments: We thank the following people for their help with this research: Jinmei Xing, Xiaohua Zhang, and Qian Wang provided field assistance. Author contributions: Conceptualization, Y.S.; funding acquisition, Y.S.; methodology, Y.S.; supervision, Y.S., K.W.; writing—original draft, X.L.; formal analysis, X.L., C.S., L.S.; investigation, X.L., L.S.; writing—review and editing, Y.S. All authors have read and agreed to the published version of the manuscript. Funding: This research was supported by the Agricultural Joint Special Project of Yunnan Province (202301BD070001-059), the First-Class Discipline Construction Project of Yunnan Province ([2022] No. 73), the Natural Ecology Monitoring Network Project Operation Project of Yuxi Forest Ecological Station in Yunnan Province (2024-YN-13), and the Long-term Scientific Research Base of Yuxi Forest Ecosystem National in Yunnan Province (2020132550). Competing interests: The authors declare no competing interests. Additional information: Supplementary Information Correspondence and requests for materials should be addressed to Y.S. 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Are land use and short time climate change effective on soil carbon compositions and their relationships with soil properties in alpine grassland ecosystems on Qinghai-Tibetan Plateau? Science of the total environment. 625, 539–546 (2018). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 14 Feb, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 20 Jun, 2024 Editor assigned by journal 19 Jun, 2024 Editor invited by journal 18 Jun, 2024 Submission checks completed at journal 14 Jun, 2024 First submitted to journal 11 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4561535","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":316863999,"identity":"8359b299-aae4-43be-a42e-9d5505bbd507","order_by":0,"name":"Xiaodong Li","email":"","orcid":"","institution":"Southwest Forestry University","correspondingAuthor":false,"prefix":"","firstName":"Xiaodong","middleName":"","lastName":"Li","suffix":""},{"id":316864001,"identity":"deccd1bf-dc37-41fa-a0ca-762fecbc90a2","order_by":1,"name":"Lianbo SU","email":"","orcid":"","institution":"Yangbi Walnut Research Institute, Yunnan Provincial Academy of Forestry and Grassland Sciences","correspondingAuthor":false,"prefix":"","firstName":"Lianbo","middleName":"","lastName":"SU","suffix":""},{"id":316864002,"identity":"1e899395-0a0b-4499-b8fe-45356ea0aa2e","order_by":2,"name":"Keqin Wang","email":"","orcid":"","institution":"Southwest Forestry University","correspondingAuthor":false,"prefix":"","firstName":"Keqin","middleName":"","lastName":"Wang","suffix":""},{"id":316864003,"identity":"7ffd6396-cc8e-4b98-a65a-0aed05088925","order_by":3,"name":"Chenggong Song","email":"","orcid":"","institution":"Southwest Forestry University","correspondingAuthor":false,"prefix":"","firstName":"Chenggong","middleName":"","lastName":"Song","suffix":""},{"id":316864004,"identity":"36501fac-ba0a-4c18-91a4-f6f2314b1233","order_by":4,"name":"Yali Song","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYPACCx5+IPkBiBkbiNQiwSPZwMA4gyQtDAYHiNUi3957+DVPjYSM8fkzhs08DDayGw4wP3uAT4vBmXNp1jzHJHjMbuSAtKQZbzjAZm6AV4tEjpkxDxtIC+/2xzwMhxM3HABy8TpsBkjLPwke4/6zG4G2/CesheFGjvFj3jYJHgOGXJCWA4S1GJw5Y8Y4t0+CR+JG/sfGOQbJxjMPs5nhd1h7j/GHN99s7Pn7jyU2vKmwk+073vwMv8MYGNikeBCWAjEzAfUgJR9/EFY0CkbBKBgFIxkAAPyKRZKuyw7vAAAAAElFTkSuQmCC","orcid":"","institution":"Southwest Forestry University","correspondingAuthor":true,"prefix":"","firstName":"Yali","middleName":"","lastName":"Song","suffix":""}],"badges":[],"createdAt":"2024-06-11 06:00:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4561535/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4561535/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-87327-7","type":"published","date":"2025-02-14T15:57:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60024945,"identity":"868ff759-a6bc-4349-a032-96f17f6d0450","added_by":"auto","created_at":"2024-07-10 17:01:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":89185,"visible":true,"origin":"","legend":"\u003cp\u003eThe composition and relative abundance of soil microorganisms at the phylum level under different N deposition levels across soil layers. X and Z represent bacteria and fungi, respectively, in the context of C, which represents an evergreen broad-leaved forest. The numbers 1, 2, and 3 correspond to the surface, middle, and bottom layers at depths of 0~5 cm, 5~10 cm, and 10~20 cm. Additionally, A, B, C, and D correspond to the four N deposition levels of CK, LN, MN, and HN, respectively. The same is true below. a and b represent the structural compositions of soil bacteria and fungi, respectively. c, d, e, and f depict ternary plots for soil bacterial composition across different soil layers under N deposition, while g, h, i, and j show ternary plots for soil fungal composition across different soil layers under N deposition.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4561535/v1/395fe6b97962274f08b071c3.png"},{"id":60025589,"identity":"7329bec8-6721-492c-a9a3-618d44a99b48","added_by":"auto","created_at":"2024-07-10 17:09:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":37093,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Coordinate Analysis (PCoA) based on weighted UniFrac distances of soil bacteria and fungi under N deposition. a and b represent the PCoA for soil bacteria and fungi, respectively.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4561535/v1/9f5069e49d74ca37b9fcc87e.png"},{"id":60024951,"identity":"0018ecb9-83b4-41f7-9b04-15ff6378402a","added_by":"auto","created_at":"2024-07-10 17:01:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":155092,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagrams illustrating shared and unique soil bacteria and fungi under N deposition. a, b, and c represent the number of OTUs of soil bacteria in different soil layers under N deposition, whereas d, e, and f represent the number of OTUs of soil fungi in different soil layers under N deposition.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4561535/v1/1c127ba63d80271060a96560.png"},{"id":60024947,"identity":"b9b62fbc-12b6-437f-8cbb-4594a45c6111","added_by":"auto","created_at":"2024-07-10 17:01:26","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":47498,"visible":true,"origin":"","legend":"\u003cp\u003eImpacts of N deposition on soil ecological enzyme activities. a, b, c, and d represent soil invertase, urease, acid phosphatase, and catalase, respectively.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4561535/v1/f117a384d25a98ba0a970354.png"},{"id":60024949,"identity":"9e4586df-0387-405c-b26c-5fc12c8c426d","added_by":"auto","created_at":"2024-07-10 17:01:26","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":79455,"visible":true,"origin":"","legend":"\u003cp\u003eImpacts of N deposition on soil nutrient content. a, b, c, d, e, and f represent soil organic carbon, total N, total phosphorus, total potassium, nitrate N, and ammonium N, respectively.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4561535/v1/755c2d42e0d86c6791559f13.png"},{"id":60024948,"identity":"aa9a3d1a-33b8-4b45-970b-5c8207b91b45","added_by":"auto","created_at":"2024-07-10 17:01:26","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":63363,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationships among soil microorganisms, ecological enzyme activities, and nutrients under N deposition. In the figure, the more connections a microorganism has, the larger its representation, indicating a stronger relationship between a particular soil enzyme or nutrient and the microorganism. a and c represent the relationships between soil bacteria with enzymes and nutrients, while b and d represent the relationships between soil fungi with enzymes and nutrients, respectively.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4561535/v1/414b6e4cdd8e03f2919c74bb.png"},{"id":76487758,"identity":"d351e3c0-38cc-4568-b1ca-a573afe4e7c1","added_by":"auto","created_at":"2025-02-17 16:12:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1508277,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4561535/v1/ee0a0418-167e-447c-b599-bd65fea148c3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Characteristics of ecological enzymes and nutrients mediated by soil microorganisms in a subtropical evergreen broad-leaved forest under nitrogen deposition ","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNitrogen (N) is a critical element in terrestrial ecosystems, playing a fundamental role in biogeochemical cycles\u003csup\u003e1\u003c/sup\u003e. The rise in atmospheric N concentrations is primarily linked to fossil fuel combustion\u003csup\u003e2\u003c/sup\u003e, fertilizer production and application\u003csup\u003e3\u003c/sup\u003e, human activities, and the expansion of livestock farming\u003csup\u003e4,5\u003c/sup\u003e. In China, annual atmospheric N deposition surged significantly from 7.6 Tg in 1978 to 20 Tg by 2010 \u003csup\u003e6\u003c/sup\u003e, profoundly impacting soil nutrient circulation, biological vitality, and forest ecosystem functions. While moderate N deposition enhances inorganic N availability in forest soils, improving soil fertility and facilitating plant N absorption and utilization, N saturation can induce shifts in microbial biomass and community composition, influencing carbon and N retention in forest soil ecosystems worldwide. This can modify soil productivity, biogeochemical cycles, and energy dynamics\u003csup\u003e7\u0026ndash;9\u003c/sup\u003e. Soil microbial communities, as dynamic elements of the subsurface ecosystem\u003csup\u003e10\u003c/sup\u003e, play a pivotal role in balancing soil organic matter turnover rates, substrate ratios, and nutrient management, impacting ecological processes in ecosystems\u003csup\u003e11\u003c/sup\u003e. These communities exhibit high sensitivity to N deposition\u003csup\u003e12\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSoil ecological enzymes and nutrient levels are critical indicators for assessing soil quality\u003csup\u003e13\u003c/sup\u003e and for understanding soil degradation and restoration processes\u003csup\u003e14,15\u003c/sup\u003e, effectively reflecting the extent and nature of biochemical activities in the soil. Alterations in ecological enzyme activities and nutrient concentrations due to N deposition can influence carbon, N, and phosphorus dynamics in forest soil ecosystems\u003csup\u003e16\u003c/sup\u003e. However, existing research yields conflicting results regarding the impact of N deposition on microbial-secreted ecological enzyme activities and nutrient modulations. Research by\u003csup\u003e17\u003c/sup\u003e found that N deposition enhances forest soil microbial biomass by augmenting external N availability, thereby boosting soil extracellular enzyme activity, which transitions soil microbial biomass from N-degrading enzymes to carbon-degrading enzymes. Litter-derived organic matter is a primary nutrient source in soil, with microorganisms facilitating decomposition through extracellular enzyme production\u003csup\u003e18\u003c/sup\u003e. Fukami et al.\u003csup\u003e19\u003c/sup\u003e and Wallenstein et al.\u003csup\u003e20\u003c/sup\u003e illustrated that N deposition can affect microbial community diversity, potentially reducing decomposition rates, limiting soil carbon sequestration, and constraining soil ecological functions. Conversely, Freedman et al.\u003csup\u003e21\u003c/sup\u003e and Carey et al.\u003csup\u003e22\u003c/sup\u003e argued that shifts in soil microbial abundance under N deposition contribute to decreased organic matter breakdown or enhanced ecosystem carbon storage. In a study by Entwistle et al.\u003csup\u003e23\u003c/sup\u003e, N deposition was found to increase phenolic dissolved organic carbon content, alter microbial community composition, and lead to incomplete microbial lignin degradation, additionally reducing extracellular enzyme activity and gene transcripts encoding these enzymes. Furthermore, N deposition may adversely affect soil microbial growth by increasing leaching of base cations (calcium and magnesium) and mobilizing aluminum\u003csup\u003e24\u003c/sup\u003e. The enrichment of N can also lower the fungi-to-bacteria ratio\u003csup\u003e25,26\u003c/sup\u003e, resulting in a shift towards more bacteria-dominated communities\u003csup\u003e27,28\u003c/sup\u003e. N deposition indirectly impacts soil microorganisms by changing micro-environmental factors such as soil moisture, texture, temperature, and nutrient profiles, particularly N, driven by shifts in plant composition and productivity at regional scales. These changes ultimately affect climate change \u003csup\u003e29\u003c/sup\u003e. To deepen our understanding, it is essential to explore how microorganisms, enzymes, and nutrient status respond to N input in forest ecosystems and how they interact with each other.\u003c/p\u003e \u003cp\u003eThe dry and wet zones in southwest China receive significant N deposition, with values of 15 and 10 g N\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively\u003csup\u003e30,31\u003c/sup\u003e, which are remarkably higher than the national average. These high N input levels limit litter decomposition and nutrient release by microorganisms in forest areas. Currently, N deposition in evergreen broad-leaved forests has continued into the third dry season (as of April 30, 2022). Previous studies in various forests have shown that N addition decreases soil microbial diversity, network complexity\u003csup\u003e32,33\u003c/sup\u003e, and soil carbon cycle enzyme activities\u003csup\u003e34\u003c/sup\u003e. However, the response of soil microorganisms to N deposition, especially under continuous N deposition, should also consider their secreted ecological enzyme activities and nutrient mediation\u003csup\u003e35\u003c/sup\u003e. This study explores the interplay between soil microorganisms, ecological enzymes, and nutrients by analyzing shifts in soil microorganisms (such as structural composition, abundance variations, and diversity), soil ecological enzyme activities, and nutrients in response to N deposition. The goal is to enhance our understanding of the comprehensive impact of N deposition on microbial life activities in subtropical evergreen broad-leaved forests. We hypothesize that (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) N deposition decreases soil bacterial and fungal diversity; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) the structural composition of soil bacterial and fungal communities displays group-specific responses to N deposition; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) N deposition influences subtropical forest microbial communities, potentially impacting soil ecological enzymes and nutrients.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003eWe ensure that who have permission to do the field study in the forest from the forest authority. As a national field positioning research station, this forest is managed by us (Southwest Forestry University) in a unified manner.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Overview of the study area\u003c/h2\u003e\n \u003cp\u003eThe evergreen broad-leaved forest selected for this study is located in the Mopan Mountain region (23\u003csup\u003e◦\u003c/sup\u003e46\u0026prime;18\u0026prime;\u0026prime;\u0026ndash;23\u003csup\u003e◦\u003c/sup\u003e54\u0026prime;34\u0026prime;\u0026prime; N, 101\u003csup\u003e◦\u003c/sup\u003e16\u0026prime;06\u0026prime;\u0026prime;\u0026ndash;101\u003csup\u003e◦\u003c/sup\u003e16\u0026prime;12\u0026prime;\u0026prime; E, 2270 m a.s.l.), within the National Positioning Observation and Research Station in the Yuxi Forest Ecosystem, Southwestern China. This area is characterized by a low-latitude and high-altitude environment with typical mountain climate features. The altitude ranges from 1260.0 to 2614.4 meters, resulting in significant height variations and distinct vertical climate changes. The climate is classified as a mid-subtropical plateau, with 2380 hours of sunshine annually. The lowest temperature recorded is -2.2\u0026deg;C, the highest is 33.0\u0026deg;C, and the region experiences distinct dry and wet seasons. The dry season spans from November to April and is characterized by ample sunshine, dry air, and reduced precipitation, while the wet season, from May to October, is marked by less sunlight, high humidity, and increased precipitation. The mean annual temperature (MAT) over the past decade was 15.1\u0026deg;C, and the mean annual precipitation (MAP) was 1050 mm. The soil in this area consists mainly of mountainous red and yellow-brown soil. The soil layer thickness varies, with some areas having thin soil layers, about 60\u0026ndash;80 cm deep in the study area. This region is primarily composed of primary and secondary original forest areas with a forest coverage rate of 86%. The dominant tree species in this subtropical evergreen broad-leaved forest include \u003cem\u003eCastanopsis carlesii\u003c/em\u003e (60%), \u003cem\u003eLithocarpus mairei\u003c/em\u003e, \u003cem\u003eBetula utilis\u003c/em\u003e, \u003cem\u003eRhododendron delavayi\u003c/em\u003e, and \u003cem\u003eDichotomanthes tristaniicarpa\u003c/em\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Design of plot and fertilization\u003c/h2\u003e\n \u003cp\u003eA representative evergreen broad-leaved forest was selected based on field surveys to ensure uniform stand structures and high representativeness. Three standard plots, each measuring 20 \u0026times; 20 m\u003csup\u003e2\u003c/sup\u003e, were randomly established for observation and study. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e provides an overview of the plot conditions. Additionally, within each standard plot, four smaller 3 \u0026times; 3 m\u003csup\u003e2\u003c/sup\u003e subplots were randomly placed to apply varying levels of N deposition. To prevent mutual interference, a distance of over 10 meters was maintained between these subplots.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of the sample plots in subtropical evergreen broad-leaved forest.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStand\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAltitude/m\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSlope/(\u0026deg;)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge/a\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDBH/ cm\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean tree H /m\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCanopy density\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAspect\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSoil type\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" align=\"left\"\u003e\n \u003cp\u003eMountainous\u003c/p\u003e\n \u003cp\u003ered soil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNW\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNW\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eBased on China\u0026apos;s current annual N deposition increment of 0.05 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;yr\u003csup\u003e\u0026minus;\u0026thinsp;1 36\u003c/sup\u003e and the wet N deposition amount in the study area of 3.84 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, along with China\u0026apos;s average N deposition range up to 2000, which ranges from 2.11 to 6.35 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;yr\u003csup\u003e\u0026minus;\u0026thinsp;1 37\u003c/sup\u003e, and the N deposition in the Huaxi Rain Screen Region of 9.5 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;yr\u003csup\u003e\u0026minus;\u0026thinsp;1 38\u003c/sup\u003e, as well as the dry N deposition in Southwest China, which ranges from 0.60 to 5.46 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;yr\u003csup\u003e\u0026minus;\u0026thinsp;1 39\u003c/sup\u003e. This study also references N deposition experiments conducted at the Harvard Forest in North America\u003csup\u003e40\u003c/sup\u003e, the Ailao Mountain National Nature Reserve in China\u003csup\u003e41\u003c/sup\u003e, and the evergreen broad-leaved forest in Guizhou\u003csup\u003e42\u003c/sup\u003e. The study established control (CK, 0 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), low N (LN, 10 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), medium N (MN, 20 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and high N (HN, 25 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) treatment levels, each with three replicates. The research group had previously conducted simulated N deposition for two years. In this study, during the third year\u0026apos;s dry season, we continued the simulated N deposition experiment. Urea [CO(NH\u003csub\u003e2\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e] was used as the N source for treatment, dissolved in 1 L of water. N treatment was carried out in the middle of every month using a hand-held sprayer, according to the aforementioned levels. There was no substantial difference in the soil moisture content or temperature following control and different treatments of N addition.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Sample collection and analytical determination\u003c/h2\u003e\n \u003cp\u003eSoil samples were collected during the dry season of the third year following N deposition (April 30, 2022). A soil auger was used to extract five cores from each quadrat randomly using a random number positioning method. These cores were then combined into a composite sample. Gravel, roots, and other debris were removed from the soil samples, which were then placed in sterile bags and transported to the laboratory. A portion of the fresh soil was preserved at 4\u0026deg;C for the analysis of soil invertase (Inv), urease (Ure), acid phosphatase (ACP), catalase (CAT), nitrate N (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N), and ammonia N (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N). The remaining portion was air-dried and sieved through 0.25 and 2 mm sieves for the determination of soil organic carbon (SOC), total N (TN), total phosphorus (TP), and total potassium (TK). The remaining soil samples were sealed in sterile bags and stored in a refrigerator at -180\u0026deg;C for DNA extraction and high-throughput sequencing.\u003c/p\u003e\n \u003cp\u003eFive grams of fresh soil samples were weighed, and the total DNA of soil microorganisms was extracted using the OMEGA EZNATM Mag-Bind Soil DNA Kit. The integrity, concentration, and purity of the genomic DNA were assessed qualitatively through agarose gel electrophoresis. The extracted DNA was stored at -20\u0026deg;C for future use. For each soil sample, primers 341F (CCTACGGN GGCWGCAG) and 805R (GACTACHVGGGGTATTCTA ATCC) targeting the V3-V4 region of the bacterial 16S rRNA gene were used to amplify gene fragments of relevant microbial taxa. PCR reaction conditions followed the kit instructions. Subsequently, DNA recovery was performed using the Biochem agarose recovery kit (cat. SK8131). The genomic DNA was accurately quantified using the Qubit 2.0 DNA Detection Kit to determine the appropriate amount of DNA for addition to the PCR reaction. All samples were combined in equal proportions and thoroughly mixed before being used for library construction and sequencing. The kit was used according to the provided instructions. The purified and enriched library was then analyzed using 2% agarose gel electrophoresis to isolate and purify the final library fragments. Based on the PCR product concentration, all successfully amplified products were pooled in equal proportions and subjected to paired-end 250 bp sequencing on the Illumina MiSeq platform. The sequencing library preparation and high-throughput sequencing were outsourced to Shanghai Sangong Bioengineering Co., Ltd. Subsequently, the raw data underwent quality control, filtering, splicing, removal of chimeras, comparison with a custom reference database, and verification of index and adapter integrity. Valid sequences from each sample were analyzed using the RDP classifier to identify bacterial sequences. Species richness and diversity statistics were calculated using Mothur. An OTU table was then constructed based on the number of sequences in each OTU within each sample. Rare OTUs with abundance values lower than 0.001% of the total sample sequencing amount were removed. The resulting OTU abundance matrix was used for further analyses. Additionally, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e was referenced to calculate specific indicators.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAlpha diversity indices of soil microorganisms.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndex name\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eComputing formula\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReference URL\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChao1 index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({S}_{chao1}={S}_{obs}+\\frac{{n}_{1}({n}_{1}-1)}{2({n}_{2}+1)} \\left(1\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.mothur.org/wiki/Chao\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003eShannon index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({H}_{shannon}=-\\sum _{i=1}^{{S}_{obs}}\\frac{{n}_{i}}{N}\\text{ln}\\frac{{N}_{i}}{N} \\left(2\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.mothur.org/wiki/Shannon\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSimpson index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({D}_{simpson}=\\frac{{\\sum }_{i=1}^{{S}_{obs}}{n}_{i}({n}_{i}-1)}{N(N-1)} \\left(3\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.mothur.org/wiki/Simpson\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eEnzymes involved in the carbon, N, and phosphorus cycles, such as Inv, Ure, and ACP, were analyzed spectrophotometrically. CAT, an enzyme involved in hydrogen peroxide metabolism, was determined using potassium permanganate titration\u003csup\u003e43\u0026ndash;46\u003c/sup\u003e. Toluene was used as the inhibitor for biological activity. Soil ecological enzyme activities were assessed within one week of sampling. Detailed methods are provided in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSubstrates, culture conditions, assay products, and references used for measuring soil ecological enzyme activities.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEnzyme\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSubstrate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIncubation temperature(℃) and time\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eassay product\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMethodological references\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvertase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSugar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37/24 h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlucose (mg˖g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e˖24\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHu et al.,\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37/24 h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e (mg˖g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e˖24\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDavid et al.,\u003csup\u003e44\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAcid phosphatase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDisodium Benzene Phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37/24 h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhenol (mg˖g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e˖24\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSun et al.,\u003csup\u003e45\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCatalase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHydrogen peroxide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24/20 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePotassium permanganate (mg˖g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e˖20\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGuan et al.,\u003csup\u003e46\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSOC was determined using external heating with potassium dichromate. TN was measured using the semi-micro Kjeldahl method. TP was analyzed via molybdenum antimony colorimetry, and TK was determined using flame photometry. NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026mdash;\u003c/sup\u003e-N was quantified using UV spectrophotometry, and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N was measured using KCl extraction followed by indigo blue colorimetry\u003csup\u003e47\u003c/sup\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Analytical processing of data\u003c/h2\u003e\n \u003cp\u003eMicrosoft Excel 2010 was used for initial data processing. Soil microbial community alpha diversity, ecological enzyme activities, and nutrient data were assessed using SPSS 26.0 (Chicago, IL, USA) for single-factor analysis of variance (ANOVA), least significant difference (LSD), and multiple comparisons (\u0026alpha;\u0026thinsp;=\u0026thinsp;0.05). Constrained principal coordinate analysis (PCoA) was performed using the Lianchuan Biological Cloud Platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.omicstudio.cn/\u003c/span\u003e\u003c/span\u003e). The structural composition and relative abundance of soil microorganisms, as well as bar charts of ecological enzyme activities, were generated using Origin 2022 Pro (Origin Lab, Northampton, MA, USA). The network topology diagram illustrating the relationships between soil microbial communities, ecological enzyme activities, and nutrients was created using R (3.6.3) software.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Influence of N deposition on the structural composition of soil microbial communities\u003c/h2\u003e\n \u003cp\u003eRepresentative sequences, selected based on the highest abundance for each OTU, were aligned with the Silva database. Soil bacteria in all samples were annotated across 21 phyla, 59 classes, 84 orders, 151 families, 239 genera, and 2,215 species. Soil fungi were annotated across 15 phyla, 45 classes, 126 orders, 279 families, 574 genera, and 920 species. Community composition analysis of soil bacteria and fungi in the evergreen broad-leaved forest at the phylum level revealed some bacteria and fungi with unclear classification status. Among the annotated bacteria, those with an overall composition proportion exceeding 1% included Acidobacteria, Proteobacteria, Actinobacteria, Planctomycetes, Verrucomicrobia, unclassified_Bacteria, Chloroflexi, Firmicutes, and Bacteroidetes. For fungi, the identified taxa included Basidiomycota, Ascomycota, Mortierellomycota, and Rozellomycota (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea,b). Acidobacteria and Proteobacteria were the dominant phyla among soil bacteria, each comprising more than 20% of the composition. Notably, N deposition levels did not significantly affect the relative abundance of Acidobacteria and Proteobacteria (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Conversely, soil fungi were predominantly represented by Basidiomycota and Ascomycota, each constituting more than 20% of the composition. HN deposition levels significantly affected the relative abundance of Basidiomycota and Ascomycota (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The ternary diagram shows that bacteria are more concentrated in LN-treated soil, while fungi are more concentrated in control (CK) soil. Both soil bacteria and fungi exhibit a trend of gradually shifting towards the middle and bottom layers in response to varying levels of N deposition (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec-j).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Influence of N deposition on the diversity of soil microbial communities\u003c/h2\u003e\n \u003cp\u003eThis study employed the Chao1, Shannon, and Simpson indices to evaluate the richness and diversity of soil bacterial and fungal communities, along with the alpha diversity index statistics across three soil layers. The results are presented in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. In the surface soil layer, the Chao1 and Shannon indices were higher compared to the middle and bottom layers, while the Simpson index was lower, indicating greater richness and diversity in the surface soil. The Chao1 indices of both soil bacteria and fungi significantly decreased under HN and MN treatments (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), implying a reduction in richness and diversity due to N deposition. While N deposition had a minor impact on the Shannon indices of bacteria and fungi and a slight effect on their Simpson indices, these changes were not statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In summary, N deposition led to a decline in the richness and diversity of soil bacteria and fungi.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAnalysis of soil microbial alpha diversity under N deposition (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). The differences among different N deposition levels within the same soil layer are statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicated by lowercase letters. The same is true below.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTreatments\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eBacteria\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eFungi\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChao1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eShannon\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSimpson\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChao1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eShannon\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSimpson\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC1A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1741.05\u0026thinsp;\u0026plusmn;\u0026thinsp;69.46a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.648\u0026thinsp;\u0026plusmn;\u0026thinsp;0.200a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0093\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0032a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1423.82\u0026thinsp;\u0026plusmn;\u0026thinsp;36.31a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.348\u0026thinsp;\u0026plusmn;\u0026thinsp;0.432a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0288\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0134a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC1B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1731.64\u0026thinsp;\u0026plusmn;\u0026thinsp;68.20a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.758\u0026thinsp;\u0026plusmn;\u0026thinsp;0.169a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0077\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0052ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1313.25\u0026thinsp;\u0026plusmn;\u0026thinsp;79.45ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.237\u0026thinsp;\u0026plusmn;\u0026thinsp;0.087a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0310\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0008a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC1C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1674.32\u0026thinsp;\u0026plusmn;\u0026thinsp;90.58ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.696\u0026thinsp;\u0026plusmn;\u0026thinsp;0.011a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0079\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0068ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1120.00\u0026thinsp;\u0026plusmn;\u0026thinsp;67.98b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.195\u0026thinsp;\u0026plusmn;\u0026thinsp;0.464a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0652\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0096ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC1D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1621.24\u0026thinsp;\u0026plusmn;\u0026thinsp;20.91b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.564\u0026thinsp;\u0026plusmn;\u0026thinsp;0.107a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0104\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0031a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1415.31\u0026thinsp;\u0026plusmn;\u0026thinsp;71.14a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.284\u0026thinsp;\u0026plusmn;\u0026thinsp;0.594a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0297\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0180a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC2A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1715.04\u0026thinsp;\u0026plusmn;\u0026thinsp;107.85a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.478\u0026thinsp;\u0026plusmn;\u0026thinsp;0.019a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0121\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0030a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1300.06\u0026thinsp;\u0026plusmn;\u0026thinsp;132.50a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.261\u0026thinsp;\u0026plusmn;\u0026thinsp;0.429a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0300\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0221a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC2B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1657.00\u0026thinsp;\u0026plusmn;\u0026thinsp;132.39ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.524\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0080\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0070ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1226.85\u0026thinsp;\u0026plusmn;\u0026thinsp;21.84ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.224\u0026thinsp;\u0026plusmn;\u0026thinsp;0.132a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0424\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0073a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC2C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1636.44\u0026thinsp;\u0026plusmn;\u0026thinsp;135.87ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.056a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0089\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0042ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1101.64\u0026thinsp;\u0026plusmn;\u0026thinsp;35.01b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.047\u0026thinsp;\u0026plusmn;\u0026thinsp;0.089a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0680\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC2D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1596.39\u0026thinsp;\u0026plusmn;\u0026thinsp;23.98b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.415\u0026thinsp;\u0026plusmn;\u0026thinsp;0.520a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0132\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0016a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1228.24\u0026thinsp;\u0026plusmn;\u0026thinsp;77.99ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.237\u0026thinsp;\u0026plusmn;\u0026thinsp;0.422a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0329\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0069a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC3A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1660.71\u0026thinsp;\u0026plusmn;\u0026thinsp;38.47a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.362\u0026thinsp;\u0026plusmn;\u0026thinsp;0.121a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0138\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0012a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1164.16\u0026thinsp;\u0026plusmn;\u0026thinsp;53.20a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.211\u0026thinsp;\u0026plusmn;\u0026thinsp;0.029a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0327\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0018a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC3B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1650.77\u0026thinsp;\u0026plusmn;\u0026thinsp;37.60a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.462\u0026thinsp;\u0026plusmn;\u0026thinsp;0.259a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0087\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0020ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1153.49\u0026thinsp;\u0026plusmn;\u0026thinsp;142.81a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.950\u0026thinsp;\u0026plusmn;\u0026thinsp;0.228a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0477\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0022a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC3C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1623.47\u0026thinsp;\u0026plusmn;\u0026thinsp;64.86a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.431\u0026thinsp;\u0026plusmn;\u0026thinsp;0.047a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0096\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0007ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1151.29\u0026thinsp;\u0026plusmn;\u0026thinsp;38.45a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.771\u0026thinsp;\u0026plusmn;\u0026thinsp;0.147a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0850\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0057ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC3D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1591.12\u0026thinsp;\u0026plusmn;\u0026thinsp;28.92ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.403\u0026thinsp;\u0026plusmn;\u0026thinsp;0.101a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0139\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0012a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1158.60\u0026thinsp;\u0026plusmn;\u0026thinsp;151.33a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.981\u0026thinsp;\u0026plusmn;\u0026thinsp;0.107a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0343\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0242a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003ePrincipal Coordinate Analysis (PCoA) was carried out using the UniFrac distance metric to examine the grouping patterns among soil bacterial and fungal communities. This investigation aimed to evaluate the dissimilarities in these communities across different levels of N deposition, as illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb. The figures illustrate the extent of overlap and divergence observed among various N deposition levels. Additionally, the similarity of soil bacterial and fungal communities under different N deposition levels was assessed using Anosim in combination with the weighted UniFrac distance algorithm, along with non-parametric tests. The results revealed that, at the OTUs level, there was no significant difference in the beta diversity of soil bacterial and fungal communities across varying N deposition levels (R\u0026thinsp;=\u0026thinsp;0.216, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.964; R\u0026thinsp;=\u0026thinsp;0.018, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.459).\u003c/p\u003e\n \u003cp\u003eThrough the analysis of Venn diagrams, the numbers of shared and unique OTUs among soil bacterial and fungal communities were compared under different N deposition levels. As illustrated in Figs. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea-f, the surface soil across varying N deposition levels shared 759 OTUs, while the middle and deep layers had 870 and 775 shared OTUs, respectively. Compared to CK, the number of distinct bacterial OTUs in the upper soil layer decreased across all N deposition levels (61, 112, and 92 for LN, MN, and HN, respectively). A total of 462 identical fungal OTUs were identified among various N deposition levels in the upper soil layer, while the middle and bottom layers contained 447 and 392 identical OTUs, respectively. The number of unique fungal OTUs in the upper soil layer decreased under LN and MN treatments (121 and 125, respectively), with an increase observed under HN treatment, albeit not statistically significant. In the middle and lower soil layers, the number of unique sequences of soil bacteria and fungi increased compared to the CK. Specifically, under the HN treatment, there were 129 and 128 unique sequences of soil bacteria in the middle and lower layers, respectively, while soil fungi had 196 and 170 unique sequences, respectively. This observation highlights the variation in the relative abundance of soil bacteria and fungi across different soil layers in response to varying N deposition levels (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec-j).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Influence of N deposition on soil ecological enzymes and nutrients\u003c/h2\u003e\n \u003cp\u003eThe results presented in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea-d demonstrated that, at the same N deposition level, the activities of soil Inv, Ure, ACP, and CAT exhibited an increasing trend with soil depth. Inv activity in the surface soil is notably higher, ranging from 31.53\u0026ndash;149.06%, compared to the middle and bottom layers. Similarly, urease activity showed an increase of 19.17\u0026ndash;53.23%, acid phosphatase activity was 23.25\u0026ndash;35.07% higher, and catalase activity was 10.37\u0026ndash;27.45% higher. Notably, Inv activity displayed the most significant variation among different soil layers, while catalase activity exhibited the least variation. The changes in enzyme activities under continuous N deposition levels varied significantly. N deposition generally suppressed soil Inv, Ure, and ACP activities, while it enhanced soil CAT activity. Specifically, compared to the CK, the HN treatment resulted in the most notable decreases of 39.90%, 35.87%, and 14.08% in Inv, Ure, and ACP activities, respectively. Conversely, CAT activity in the HN treatment showed the highest increase of 18.81%.\u003c/p\u003e\n \u003cp\u003eAs illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea-f, under consistent N deposition levels, there was a steady increase in SOC, TN, TP, TK, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N with soil depth. Specifically, the surface soil showed a 48.41\u0026ndash;59.37% higher SOC content compared to the middle and bottom layers. Similarly, TN content increased by 26.86\u0026ndash;51.57%, TP by 17.55\u0026ndash;65.98%, and TK by 43.58\u0026ndash;66.87%. Notably, the most significant variations were observed in NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N levels across different soil layers, with increases ranging from 206.85\u0026ndash;428.37% and 148.30\u0026ndash;186.15%, respectively. The impact of N deposition on soil nutrient contents varied significantly. N deposition generally suppressed SOC, TN, and TP, while it enhanced TK, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N. Compared to CK, the highest reductions in soil SOC, TN, and TP were observed under the HN treatment, decreasing by 67.95%, 36.71%, and 45.37%, respectively. Conversely, the HN treatment resulted in the most notable increases in soil TK, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, rising by 19.59%, 839.96%, and 195.57%, respectively.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Relationships among soil microorganisms, ecological enzymes, and nutrients under N deposition\u003c/h2\u003e\n \u003cp\u003eTo investigate the relationships between soil bacteria and fungi with ecological enzyme activities and nutrient content following N deposition, a co-linearity network analysis was conducted (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ea-d). The analysis revealed stronger interactions among soil bacteria compared to fungi. The dominant bacterial phyla, Proteobacteria and Verrucomicrobia, showed strong correlations with Ure and ACP, respectively. Acidobacteria exhibited a significant correlation with TP. Among the prominent fungal phyla, Basidiomycota had stronger correlations with CAT, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, while Ascomycota was more closely linked with Inv.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eSurface soil biochemical processes play a crucial role in maintaining ecosystem stability. Our study revealed that the surface soil had the highest levels of microbial diversity, ecological enzyme activities, and nutrient content. These findings are consistent with the research conducted by Wang et al.\u003csup\u003e48\u003c/sup\u003e, Yuan et al.\u003csup\u003e49\u003c/sup\u003e and Xu et al.\u003csup\u003e50\u003c/sup\u003e, who investigated soil microbial diversity, enzyme activities, and vertical variations in soil nutrients following N deposition in \u003cem\u003ePinus massoniana-Quercus variabilis\u003c/em\u003e mixed forests and \u003cem\u003eCunninghamia lanceolata\u003c/em\u003e forests. The surface soil layer likely facilitates rapid organic matter transformation due to its higher bulk density, increased biomass of microorganisms and root systems, favorable hydrothermal conditions, and superior aeration. These conditions promote microbial activity and enzyme secretion in the soil, thereby enhancing nutrient cycling.\u003c/p\u003e \u003cp\u003eThe study identified Acidobacteria and Proteobacteria as the dominant phyla in the soil bacteria of evergreen broad-leaved forests, each accounting for more than 10% of the total composition. Similarly, Basidiomycota and Ascomycota were the dominant phyla among soil fungi, with each comprising over 10% of the total. These results align with previous research by Lagomarsino et al.\u003csup\u003e51\u003c/sup\u003e and Lin et al.\u003csup\u003e52\u003c/sup\u003e. This consistency could be attributed to the broad ecological range of these four phyla that are exhibited in forest environments. N deposition did not significantly impact the relative abundance of the bacterial phyla Acidobacteria and Proteobacteria. These two bacteria play a crucial role in the conversion of ammonia to nitrite during N-cycling\u003csup\u003e53\u003c/sup\u003e. They dominate bacterial communities under acidic and nitrate-rich conditions\u003csup\u003e54\u003c/sup\u003e and possess strong adaptability and resilience, resulting in minimal changes in their relative abundance under N deposition. The relative abundance of the fungal phylum Basidiomycota was notably higher in HN, while the relative abundance of the fungal phylum Ascomycota was significantly lower in HN. Both Basidiomycota and Ascomycota are known for decomposing complex carbon sources\u003csup\u003e55\u003c/sup\u003e. The contrasting shifts in their relative abundance under HN conditions could be attributed to differing N utilization strategies or heightened competitive interactions, ultimately impacting their respective abundances. In this study, soil bacteria were relatively concentrated in the LN treatment, whereas soil fungi were more concentrated in the CK treatment. Bacteria generally have faster growth rates and reproductive capabilities compared to fungi, enabling them to utilize a broader range of organic matter. In contrast, fungi exhibit specificity in their selection of organic matter, making them more sensitive to environmental conditions. HN concentration in the LN treatment compared to the CK treatment may favor bacterial growth, while the conditions in the CK treatment may better support the original fungal communities\u003csup\u003e56\u003c/sup\u003e. This finding supports hypothesis 2, indicating that different soil microbial groups (bacteria and fungi) exhibit specific responses to N deposition. The study also observed that soil bacterial and fungal relative abundances tended to shift towards the middle and lower soil layers with varying N deposition levels. This trend was further supported by the quantitative differences in soil bacteria and fungi across soil layers, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-f. Increasing N deposition enriched the soil with N, subsequently impacting soil respiration, N transformation, microbial metabolism, and interactions with plants. While surface soil may not currently provide the most conducive environment for microbial survival, it is susceptible to changes in N leaching due to factors like temperature and rainfall. Consequently, surface soil exposed to high levels of N deposition may eventually revert to a state favorable for microbial habitats.\u003c/p\u003e \u003cp\u003eExcessive N deposition can disrupt the microbial community's diversity and suppress biomass, hampering the soil carbon cycle and reducing carbon storage, especially in forests subjected to medium to long-term N deposition or HN levels. The impact on microorganisms is more pronounced in such conditions\u003csup\u003e57\u003c/sup\u003e. Our study observed a decline in the diversity of soil bacteria and fungi, supporting our hypothesis that N deposition decreases microbial diversity. This observation aligns with similar findings reported in various studies by Song et al.\u003csup\u003e58\u003c/sup\u003e, Wang et al.\u003csup\u003e59\u003c/sup\u003e, and Freedman et al.\u003csup\u003e60\u003c/sup\u003e. Soil acidification resulting from N deposition has been shown to alter the soil microbial community's structure\u003csup\u003e61\u003c/sup\u003e, reduce microbial biomass, and limit carbon source utilization by microorganisms, consequently diminishing microbial diversity. However, differences in life history traits and ecological network relationships among species can lead to varied reductions in soil bacterial and fungal diversity. Notably, under N deposition, soil bacterial diversity was found to be higher than fungal diversity, possibly due to the interplay between soil bacterial and fungal communities and their respective habitats and behaviors. Bacteria, with their diverse metabolic pathways and broad lifestyles, play a critical role in organic matter decomposition and carbon and N cycling, as emphasized by Shao et al.\u003csup\u003e62\u003c/sup\u003e. Bacteria tend to prefer readily available carbon sources. In contrast, soil fungi typically target recalcitrant organic matter decomposition, resulting in a narrower ecological niche for fungi in the soil.\u003c/p\u003e \u003cp\u003eIn this study, N deposition was observed to generally inhibit soil Inv, Ure, and ACP activities, while promoting soil CAT activity. The suppression of Inv activity by N deposition likely results from the reduced decomposition rate of soil organic matter, leading to decreased substrate availability for Inv and subsequent inhibition of its activity. The decline in Ure activity due to N deposition may be attributed to its role in the N cycle, particularly in catalyzing urea decomposition into NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and CO\u003csub\u003e2\u003c/sub\u003e, the form of N readily usable by plants. Previous studies have indicated that N deposition can impede soil N mineralization rates\u003csup\u003e63\u003c/sup\u003e, disrupting the N cycle and consequently reducing Ure activity. Furthermore, N deposition inhibits ACP activity, possibly due to its function in converting organic phosphorus to inorganic phosphorus\u003csup\u003e64\u003c/sup\u003e. This nutrient imbalance in the soil, caused by N deposition, could diminish phosphorus uptake by microorganisms, hindering ACP secretion and resulting in reduced ACP activity\u003csup\u003e65\u003c/sup\u003e. CAT participates in the soil humification process and decomposes hydrogen peroxide. N deposition enhanced CAT activity, likely due to its impact on litter decomposition inhibition\u003csup\u003e66\u003c/sup\u003e and humification reduction. Consequently, as the decomposition rate of litter organic matter decreases and residual litter accumulates, CAT activity increases to degrade the remaining organic matter. However, contrasting findings were reported in another study\u003csup\u003e67\u003c/sup\u003e. Possible explanations include higher litter input and sustained CAT activity levels under N deposition in the study region. Alternatively, the current N deposition level may not produce toxic concentrations of compounds like nitrate during N metabolite processes, thus not affecting CAT structure.\u003c/p\u003e \u003cp\u003eIn this study, N deposition generally suppressed soil SOC, TN, and TP, while enhancing soil TK, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N. N deposition has the potential to impact the soil microbial ecosystem function\u003csup\u003e68\u003c/sup\u003e, triggering redox reactions that prompt the release of a substantial amount of CO\u003csub\u003e2\u003c/sub\u003e from microbial carbon, thereby reducing soil SOC accumulation. Soil organic matter decomposition generates organic acids, which may stimulate nitrifying and ammonifying bacteria activity under acidic conditions, leading to elevated levels of NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N in the soil. Nevertheless, N-fixing microorganisms might outcompete others in N-rich environments, potentially diminishing their physiological requirements and competitive edge in N fixation, resulting in reduced TN biological fixation in the soil. Additionally, N deposition could impede microorganisms from decomposing phosphorus-containing organic matter, consequently reducing TP release. Moreover, N deposition is likely to enhance the soil's TK content by increasing the exchange capacity of K\u003csup\u003e+\u003c/sup\u003e with Ca\u003csup\u003e+\u003c/sup\u003e and Mg\u003csup\u003e+\u003c/sup\u003e ions.\u003c/p\u003e \u003cp\u003eN deposition has the potential to influence the allocation of microorganisms toward the production of ecological enzymes and the abundance of specific enzymes synthesized by soil microorganisms\u003csup\u003e69\u003c/sup\u003e. It can also impact nutrient levels such as carbon, N, and phosphorus\u003csup\u003e70\u003c/sup\u003e, thereby regulating microbial physiological characteristics to establish a new equilibrium between resources and microorganisms\u003csup\u003e71\u003c/sup\u003e, which in turn can influence critical biochemical processes within the ecosystem\u003csup\u003e72\u003c/sup\u003e. This study employed a collinear network analysis to explore the microbial community, enzymatic secretion, and nutrient interrelationships. The results indicated that soil bacteria engaged in a higher level of interactions compared to soil fungi due to their numerous populations, rapid growth, fast metabolism, diverse metabolic pathways, and robust environmental adaptability. Proteobacteria and Verrucomicrobia showed notable correlations with Ure and ACP, while the bacterial phylum Acidobacteria exhibited strong correlations with TP. Proteobacteria, a significant group of diazotrophs, along with Verrucomicrobia, demonstrated the ability to convert atmospheric N\u003csub\u003e2\u003c/sub\u003e into bioavailable forms\u003csup\u003e73\u003c/sup\u003e. Verrucomicrobia are proficient at converting organic matter into a form usable by other microorganisms. Nitrification enzyme Ure and phosphatase ACP play pivotal roles in catalyzing these processes for plant absorption and utilization. Acidobacteria can solubilize organic phosphorus in soil through the secretion of acidic metabolites, including organic acids and acidic polysaccharides. This mechanism is vital for phosphorus recycling and its availability in the soil, as it transforms organic phosphorus into inorganic phosphorus, which is essential for plant growth. The fungus Basidiomycota showed a strong association with CAT, while Ascomycota exhibited a significant correlation with Inv. Basidiomycota also displayed strong correlations with NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N. Both Basidiomycota and Ascomycota play critical roles in decomposing lignin and other complex organic compounds\u003csup\u003e74\u003c/sup\u003e. Basidiomycota secretes CAT to accelerate the breakdown of these compounds. To sustain this process, Basidiomycota relies on vital nutrients such as soil NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N for growth and metabolism, enhancing their N utilization efficiency. Conversely, Ascomycota releases Inv, an enzyme that hydrolyzes carbohydrates like sucrose to provide carbon sources for growth and metabolism. The robust interaction between soil bacteria and fungi in this ecosystem is evident, displaying a strong correlation with soil enzymes and nutrients, supporting our hypothesis that N deposition alters soil enzyme activities and nutrient levels, influencing microbial interactions. Microorganisms release specialized enzymes to access necessary nutrients for their metabolic functions.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIn general, N treatments, especially high N addition, tended to inhibit the diversity of soil bacteria and fungi, but bacteria exhibited higher tolerance to N compared to fungi, which might influence their strategies in secreting enzymes, mediating nutrients, and surviving across different soil layers. The differences in soil enzyme activities were primarily influenced by enzyme types. This may be related to the effects of N input on the availability of soil nutrients and changes in soil microorganisms in subtropical areas. Additionally, N deposition might alter the abundance and composition of microbial communities, thereby affecting enzyme activities and nutrients. Therefore, the effect of N input on soil microbial communities, ecological enzyme activities, nutrients and how they interact with each other in a subtropical evergreen broad-leaved forest further study.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors and I declare that the methods used for collecting soil samples, handling and processing samples, and performing chemical experiments were in accordance with relevant institutional, national, and international guidelines, regulations, and laws. All methods were carried out in accordance with the applicable guidelines and there were no instances of malpractice or non-compliance. In addition, appropriate literature references have been provided to support the methods used.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support our research findings are available from the corresponding author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the following people for their help with this research: Jinmei Xing, Xiaohua Zhang, and Qian Wang provided field assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConceptualization, Y.S.; funding acquisition, Y.S.; methodology, Y.S.; supervision, Y.S., K.W.; writing\u0026mdash;original draft, X.L.; formal analysis, X.L., C.S., L.S.; investigation, X.L., L.S.; writing\u0026mdash;review and editing, Y.S. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Agricultural Joint Special Project of Yunnan Province (202301BD070001-059), the First-Class Discipline Construction Project of Yunnan Province ([2022] No. 73), the Natural Ecology Monitoring Network Project Operation Project of Yuxi Forest Ecological Station in Yunnan Province (2024-YN-13), and the Long-term Scientific Research Base of Yuxi Forest Ecosystem National in Yunnan Province (2020132550).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrespondence\u003c/strong\u003e and requests for materials should be addressed to Y.S.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReprints and permissions information\u003c/strong\u003e is available at\u0026nbsp;\u003ca href=\"www.nature.com/reprints\"\u003ewww.nature.com/reprints\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublisher\u0026rsquo;s note\u003c/strong\u003e Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLucas, R. 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Are land use and short time climate change effective on soil carbon compositions and their relationships with soil properties in alpine grassland ecosystems on Qinghai-Tibetan Plateau? Science of the total environment. 625, 539\u0026ndash;546 (2018).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"microbial community, soil enzymes, soil nutrients, nitrogen deposition, evergreen broad-leaved forest","lastPublishedDoi":"10.21203/rs.3.rs-4561535/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4561535/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicroorganisms are critical in forest ecosystems, where they secrete soil ecological enzymes and mediate nutrient cycling. These processes are essential in determining how these ecosystems respond to nitrogen (N) deposition inputs. In this study, an N deposition experiment was conducted with three levels of N addition treatments in a subtropical evergreen broad-leaved forest in southwest China. The aim was to identify the effects of low (LN: 10 g·m\u003csup\u003e−2\u003c/sup\u003e·yr\u003csup\u003e−1\u003c/sup\u003e), medium (MN: 20 g·m\u003csup\u003e−2\u003c/sup\u003e·yr\u003csup\u003e−1\u003c/sup\u003e), and high N addition (HN: 25 g·m\u003csup\u003e−2\u003c/sup\u003e·yr\u003csup\u003e−1\u003c/sup\u003e) on soil microbial community structure, diversity, ecological enzyme activities, and nutrient content, and to explore whether and how soil microorganisms influence ecological enzyme activity and nutrient cycling. Our observations indicated that surface soil exhibited the highest microbial diversity, ecological enzyme activities, and nutrient contents. N deposition led to a reduction in soil bacterial and fungal diversity, with bacterial diversity consistently higher than fungal diversity. Moreover, bacterial community structures were generally more diverse and complex compared to fungal communities. The study emphasized that bacteria were relatively enriched under LN treatment, while fungi exhibited higher relative abundance under control conditions. Different soil microbial groups exhibited distinct responses to N deposition, with an inhibitory effect on enzyme activities such as invertase (Inv), urease (Ure), and acid phosphatase (ACP), and an enhancement of catalase (CAT) activity. With increasing N deposition levels, soil organic carbon (SOC), total N (TN), and total phosphorus (TP) contents decreased, whereas total potassium (TK), nitrate N (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e—\u003c/sup\u003e-N), and ammonium N (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N) exhibited the opposite trend. Co-linearity network analysis revealed stronger interactions among soil bacteria compared to fungi. The dominant bacterial phyla Proteobacteria and Verrucomicrobia showed stronger correlations with Ure and ACP, respectively, while Acidobacteria exhibited a higher correlation with TP. Among the dominant fungal phyla, Basidiomycota had stronger correlations with CAT, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e—\u003c/sup\u003e-N, and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, while Ascomycota was notably associated with Inv. These results suggest that soil bacteria have stronger correlations with ecological enzymes, whereas soil fungi are more closely related to nutrient dynamics. This implies that bacteria and fungi have distinct advantages in enzyme secretion and nutrient mediation, leading to a trend of nutritional complementarity.\u003c/p\u003e","manuscriptTitle":"Characteristics of ecological enzymes and nutrients mediated by soil microorganisms in a subtropical evergreen broad-leaved forest under nitrogen deposition ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-10 17:01:21","doi":"10.21203/rs.3.rs-4561535/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-20T12:18:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-19T06:08:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-18T13:25:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-14T04:39:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-06-11T05:59:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f4dbe96a-7f4d-4311-806c-6a6ad00b6e78","owner":[],"postedDate":"July 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33506282,"name":"Biological sciences/Ecology/Forest ecology"},{"id":33506283,"name":"Biological sciences/Ecology/Forestry"}],"tags":[],"updatedAt":"2025-02-17T16:06:46+00:00","versionOfRecord":{"articleIdentity":"rs-4561535","link":"https://doi.org/10.1038/s41598-025-87327-7","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-02-14 15:57:48","publishedOnDateReadable":"February 14th, 2025"},"versionCreatedAt":"2024-07-10 17:01:21","video":"","vorDoi":"10.1038/s41598-025-87327-7","vorDoiUrl":"https://doi.org/10.1038/s41598-025-87327-7","workflowStages":[]},"version":"v1","identity":"rs-4561535","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4561535","identity":"rs-4561535","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}