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) addition inputs. In this study, an N addition 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 year−1), medium (MN: 20 g m− 2 year− 1), and high N addition (HN: 25 g m− 2 year− 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 addition 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 addition, 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 addition levels, soil organic carbon (SOC), total N (TN), and total phosphorus (TP) contents decreased, whereas total potassium (TK), nitrate N (NO3−-N), and ammonium N (NH4+-N) exhibited the opposite trend. Co-linearity network analysis revealed stronger interactions among soil bacteria compared to fungi. The dominant bacterial phyla Pseudomonadota and Verrucomicrobiota showed stronger correlations with Ure and ACP, respectively, while Acidobacteriota exhibited a higher correlation with TP. Among the dominant fungal phyla, Basidiomycota had stronger correlations with CAT, NO3−-N, and NH4+-N, while Ascomycota was notably associated with Inv. The results showed that soil bacteria had a strong correlation with ecological enzymes, while soil fungi had a strong correlation with nutrients. This implies that bacteria and fungi have distinct advantages in enzyme secretion and nutrient mediation, leading to a trend of nutritional complementarity.
Similar content being viewed by others
Introduction
Ecological enzymes are various extracellular enzymes secreted into the environment by different organisms (microorganisms, plants, and soil animals) within an ecosystem. They can catalyze the degradation and transformation of organic matter, serving as important biochemical mediators that connect living organisms with their environment1,2. Nitrogen (N) is a critical element in terrestrial ecosystems, playing a fundamental role in biogeochemical cycles. The rise in atmospheric N concentrations is primarily linked to fossil fuel combustion, fertilizer production and application3, human activities, and the expansion of livestock farming4,5. In China, atmospheric N deposition surged significantly from 7.6 Tg in 1978 to 20 Tg by 20106, profoundly impacting soil nutrient circulation, biological vitality, and forest ecosystem functions. While moderate N addition 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 biogeochemical cycles and energy dynamics7,8,9. Soil microbial community is an active component of belowground ecosystem10, playing a pivotal role in balancing soil organic matter turnover rates, substrate ratios, and nutrient management, impacting ecological processes in ecosystems11. These communities exhibit high sensitivity to N addition12.
Soil ecological enzymes and nutrient levels are critical indicators for assessing soil quality13 and for understanding soil degradation and restoration processes14,15, effectively reflecting the extent and nature of biochemical activities in the soil. One of the most important themes is how increased N addition affects the dynamics of soil microbial diversity and community composition in forest ecosystems. Soil microbes constitute the largest portion of terrestrial biodiversity and they regulate the functional processes of terrestrial ecosystems16, such as decomposition and carbon cycling, providing fundamental ecological underpinnings for improved ecosystem function35. However, the results from numerous studies were inconsistent, showed positive17, no-changed18, and negative19 effects of N addition. For example, Treseder et al.20 and Liu et al.21 demonstrated that soil microbial biomass decreased by an average of 15%~20% under conditions of N enrichment; Li et al.22 found that experimental N addition significantly reduced microbial diversity, induced shifts in major microbial life histories, and enriched copiotrophic microbial communities; another study reported that bacterial diversity did not respond to N addition23. Changes in soil microbial diversity and composition can affect the functioning of forest ecosystems, particularly in tropical and subtropical forests, N addition has been reported to reduce forest carbon and N degradation enzyme activity, directly due to a decrease in soil microbial diversity24. Nitrogen addition may decrease or increase the abundance and composition of soil microorganisms, further reducing or enhancing the interactions between microorganisms and plant roots, hindering the decomposition of soil organic matter or promoting nitrification25,26,27,28. N addition indirectly impacts soil microorganisms by changing micro-environmental factors such as soil moisture, texture, and nutrient profiles, particularly N, driven by shifts in plant composition and productivity at regional scales. These changes ultimately affect climate change29. 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 addition, with values of 15 and 10 g N m− 2 year− 1, respectively30,31, which are remarkably higher than the national average. This increases soil acidity in areas with high N deposition, reducing microbial activity, thereby limiting the decomposition of litter and nutrient release by microorganisms in forest areas. Currently, the evergreen broadleaf forest has continued into the third year of N addition during the dry season (as of April 30, 2022). Previous studies in various forests have shown that N addition decreases soil microbial diversity, network complexity32,33, and soil carbon cycle enzyme activities34. However, the response of soil microorganisms to N addition, especially under continuous N addition, should also consider their secreted ecological enzyme activities and nutrient mediation35. 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 addition. The goal is to enhance our understanding of the comprehensive impact of N addition on microbial metabolic activities in subtropical evergreen broad-leaved forests. We hypothesize that (1) N addition decreases soil bacterial and fungal diversity; (2) the structural composition of soil bacterial and fungal communities displays group-specific responses to N addition; and (3) N addition influences subtropical forest microbial communities, potentially impacting soil ecological enzymes and nutrients.
Materials and methods
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 m, resulting in significant height variations and distinct vertical climate changes. The climate is classified as a mid-subtropical plateau, with 2380 h 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.
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 m2, 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 m2 subplots were randomly placed to apply varying levels of N addition. To prevent mutual interference, a distance of over 10 m was maintained between these subplots.
China is now the third largest N deposition area in the world, total N deposition to China was 19.6 ± 2.5 Tg year− 136. According to the wet N addition amount in the study area of 3.84 g m− 2 year− 1, along with China’s average N addition range up to the year 2000, which ranges from 2.11 to 6.35 g m− 2 year− 137, and the N addition in the Huaxi Rain Screen Region of 9.5 g m− 2 year− 138, as well as the dry N addition in Southwest China, which ranges from 0.60 to 5.46 g m− 2 year− 139. This study also referred to N addition experiments conducted at the Harvard Forest in North America40, the Ailao Mountain National Nature Reserve in China41, and the evergreen broad-leaved forest in Guizhou42. The study established control (CK, 0 g m− 2 year− 1), low N (LN, 10 g m− 2 year− 1), medium N (MN, 20 g m− 2 year− 1), and high N (HN, 25 g m− 2 year− 1) treatment levels, each with three replicates. The research group had previously conducted simulated N addition for two years. In this study, during the third year’s dry season, we continued the simulated N addition experiment. Urea [CO(NH2)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.
Sample collection and analytical determination
Soil samples were collected during the dry season of the third year following N addition (April 30, 2022). Sampling began by removing the litter layer from the quadrat surface. Using the five-point sampling technique, soil from the top 20 cm was extracted with an auger. Soil from the three replicate quadrats under the same treatment was mixed thoroughly and sieved through a 2 mm nylon mesh to remove visible roots and stones, 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 (NO3−-N), and ammonia N (NH4+-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 -80 °C for DNA extraction and high-throughput sequencing.
Total DNA from the samples was extracted using the EZNA™ Mag-Bind Soil DNA Kit from OMEGA Bio-tek. The extracted DNA samples were sent to Sangon Biotech (Shanghai) Co., Ltd. (Shanghai, China) for high-throughput sequencing. For soil bacteria, the V3–V4 variable region was PCR-amplified using primers 341 F (5′-CCTACGGGNGGCWGCAG-3′) and 805R (5′-GACTACHVGGGTATCTAATCC-3′). For soil fungi, the ITS region was targeted using primers ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2R (5′-GCTGGCTTTCTTCATCGATGC-3′). Both bacterial and fungal amplifications involved two rounds of PCR. In the first round, we used 16SV3-V4 primers for bacteria and ITS1-ITS2 primers for fungi, with a 30 µL reaction mix (15 µL 2 × Hieff® Robust PCR Master Mix, 1 µL of each primer, 10–20 ng of PCR products, and 9–12 µL of H2O). The PCR conditions were an initial denaturation at 94 °C for 3 min, followed by 5 cycles at 94 °C for 20 s, annealing at 45 °C for 20 s, and extension at 65 °C for 30 s; then 20 cycles at 94 °C for 20 s, 55 °C for 20 s, and 72 °C for 30 s, with a final extension at 72 °C for 5 min and storage at 10 °C. In the second round, Illumina bridge PCR-compatible primers were used with a similar reaction mix and conditions: pre-denaturation at 95 °C for 3 min, followed by 5 cycles of denaturation at 94 °C for 20 s, annealing at 55 °C for 20 s, and extension at 72 °C for 30 s, concluding with a final extension at 72 °C for 5 min and storage at 10 °C. The PCR products were verified via 2% agarose gel electrophoresis, and library concentrations were measured using a Qubit 3.0 fluorometer. After confirming library quality, sequencing was conducted on the Illumina MiSeq platform. Additionally, Table 2 was referenced to calculate specific indicators.
After quality control software (QIIME) filtering of the sequencing data, Usearch 11.0.667 software was used to cluster non-redundant sequences (excluding single sequences) at a 97% similarity threshold for operational taxonomic unit (OTU). Chimeras were removed during the clustering process, with similarity assessments conducted after comparing 0.1% of the sequences. The sequences were preprocessed by trimming adapter sequences and removing low-quality reads using the FastQC and Trimmomatic tools. The SILVA database (version 138.1) was used for the identification of bacterial community composition, while the UNITE database (version 8.0) was used for the identification of fungal community composition. Microbial α-diversity and richness were calculated using Mothur 1.43.0. The Shannon index was employed to quantify community diversity, while the Chao index was used to estimate community richness.
Each soil sample for enzyme activity had three replicates. Soil invertase activity was determined according to Hu et al.43 method. The mixture system for assessing soil invertase activity was obtained by mixing soil with the solution of 8% sucrose at a ratio of 1:3, followed by adding the 5 mL of phosphate buffer and 5 mL of toluene. After incubation for 24 h in a constant temperature incubator at 37 °C, the supernatant was separated by filtration. Immediately following the absorbance of the filtrate was determined at 485 nm using a spectrophotometer. Invertase activity was expressed by the glucose released by soil.
Soil urease activity was determined according to Fernández-Calviño et al.44 method. 10 g soil and 2.0 mL methylbenzene were mixed in a 100 mL volumetric flask first. After standing for 15 min. 10 mL urea (10%) and 20 mL citrate buffer (pH = 6.7) were added to the reaction system, followed by a gentle shaking. Then the system was incubated at 37 °C for 3 h, diluted with ultrapure water (38 °C) to 100 mL, cleared of methylbenzene and then filtrated. After that, 1.0 mL filtrates, 19.0 mL ultrapure water, 4.0 mL sodium phenate and 3.0 mL hypochlorite were mixed in another 50 mL volumetric flask with a gentle shaking, followed by a 20 min standing for the chromogenic reaction. Finally, the mixture was diluted to 50 mL with ultrapure water and its absorbance at 578 nm was measured using an ultraviolet-visible spectrophotometer (U-V spectrophotometer, UV-2600, Shimadzu, Japan) in 1 h. The urease activity was expressed as mg NH4+-N produced by per kilogram of dry soil per 24 h.
Activity of the acid phosphatase was tested as Sun et al.45 described: 1.0 g soil was mixed with 0.2 mL methylbenzene, 4.0 mL modified universal buffer (MUB, pH 6.5) and 1.0 mL Disodium Benzene Phosphate (0.05 M) in a 50 mL conical flask and incubated at 37 °C for 1 h. Then the action was ended by adding 1 mL of 0.5 M CaCl2 and 4 mL of 0.5 M NaOH. After a filtration, the filtrate was diluted 10 times by MUB (pH 6.5). Finally, the content of Disodium Benzene Phosphate in the filtrate was measured at 410 nm.
Activity of the catalase was tested as Wang et al.46 described: 2 g air-dried soil and 40 mL distilled water was placed in a 100 mL conical flask, then 5 mL 0.3% H2O2 was added, the flask was closed with a cotton plug, and the mixture was shaken gently for 20 min. Then, 1 mL saturated potash alum solution was added, and the mixture was filtered into another flask containing 5 mL 1.5 N H2SO4. The absorbance of the mixture was measured at 240 nm.
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. NO3−-N was quantified using UV spectrophotometry, and NH4+-N was measured using KCl extraction followed by indigo blue colorimetry47.
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). Data have been uploaded on the link: https://www.scidb.cn/en/anonymous/YkV6NkJy. The network topology diagram illustrating the relationships between soil microbial communities, ecological enzyme activities, and nutrients was created using R (3.6.3) software.
Results
Influence of N addition 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 in the evergreen broad-leaved forest at the phylum and genus levels revealed some bacteria with unclear classification status (Fig. 1a, b). Among the annotated phylum and genus bacteria, those with an overall composition proportion exceeding 10% included Acidobacteriota, Pseudomonadota, Gp1 and Gp2 communities. Notably, Compared to CK, the relative abundance of Acidobacteriota, Gp1, and Gp2 communities initially increased and then decreased along the N addition gradient, while Pseudomonadota communities showed a reversed pattern, decreasing first and then increasing. However, N addition levels did not significantly affect the relative abundance of them (p > 0.05).
The relative abundance of soil bacteria at the phylum and genus levels under different N addition levels across soil layers. “B” represent the bacteria, the acronym of “1”, “2”, and “3” represent soil depths of 0 ~ 5 cm, 5 ~ 10 cm, and 10 ~ 20 cm. Additionally, CK, LN, MN, and HN correspond to control and three N addition levels, respectively. Figure (a) and (b) represent the structural compositions of soil phylum and genus bacteria, respectively.
Community composition analysis of soil fungi in the evergreen broad-leaved forest at the phylum and genus levels revealed some fungi with unclear classification status (Fig. 2a, b). Among the annotated phylum and genus fungi, those with an overall composition proportion exceeding 10% included Basidiomycota, Ascomycota, Archaeorhizomyces, Russula and Sebacina communities. Notably, Compared to CK, the relative abundance of Basidiomycota and Sebacina communities initially increased and then decreased along the N addition levels, while Ascomycota communities showed a reversed pattern, decreasing first and then increasing, The relative abundance of Archaeorhizomyces and Russula communities were consistently reduced across all three N addition levels. N addition levels significantly affected the relative abundance of them (p < 0.05).
The relative abundance of soil fungi at the phylum and genus levels under different N addition levels across soil layers. “F” represent the fungi, the acronym of “1”, “2”, and “3” represent soil depths of 0 ~ 5 cm, 5 ~ 10 cm, and 10 ~ 20 cm. Additionally, CK, LN, MN, and HN correspond to control and three N addition levels, respectively. Figure (a) and (b) represent the structural compositions of soil phylum and genus fungi, respectively.
The ternary diagram shows that bacteria are more concentrated in LN-treated soil, while fungi are more concentrated in 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 addition (Fig. 3a–h).
Ternary plots of soil bacteria and fungi in different soil layers under N addition. “B” and “F” represent the bacteria and fungi, the acronym of “1”, “2”, and “3” represent soil depths of 0 ~ 5 cm, 5 ~ 10 cm, and 10 ~ 20 cm. Additionally, CK, LN, MN, and HN correspond to control and three N addition levels, respectively. Figure (a–h) depict ternary plots for soil bacterial and fungal degree of aggregation and fragmentation across different soil layers under CK, LN, MN, and HN, respectively.
Influence of N addition 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 3. 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 addition. While N addition 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 addition led to a decline in the richness and diversity of soil bacteria and fungi.
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 addition, as illustrated in Fig. 4a, b. The figures illustrate the extent of overlap and divergence observed among various N addition levels. Additionally, the similarity of soil bacterial and fungal communities under different N addition 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 addition levels (R = 0.216, P = 0.964; R = 0.018, P = 0.459).
Principal Coordinate Analysis (PCoA) based on weighted UniFrac distances of soil bacteria and fungi under N addition. Figure (a) and (b) represent the PCoA for soil bacteria and fungi, respectively.
Through the analysis of Venn diagrams, the numbers of shared and unique OTUs among soil bacterial and fungal communities were compared under different N addition levels. As illustrated in Fig. 5a-f, the surface soil across varying N addition 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 addition levels (61, 112, and 92 for LN, MN, and HN, respectively). A total of 462 identical fungal OTUs were identified among various N addition 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 addition levels (Fig. 3a-h).
Venn diagrams illustrating shared and unique soil bacteria and fungi under N addition. Figure (a–c) represent the number of OTUs of soil bacteria in different soil layers under N addition, whereas Figure (d–f) represent the number of OTUs of soil fungi in different soil layers under N addition. The acronym of “B” and “F” in the figure represent bacteria and fungi, respectively; the acronym of “1”, “2”, and “3” represent soil depths of 0 ~ 5 cm, 5 ~ 10 cm, and 10 ~ 20 cm. CK, LN, MN, and HN represent four N addition levels, respectively.
Influence of N addition on soil ecological enzymes and nutrients
The results presented in Fig. 6a–d demonstrated that, at the same N addition level, the activities of soil Inv, Ure, ACP, and CAT exhibited a decreasing trend with soil depth. Inv activity in the surface soil is notably higher, ranging from 31.53 to 149.06%, compared to the middle and bottom layers. Similarly, urease activity showed a decrease 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 addition levels varied significantly. N addition 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%.
Impacts of N addition on soil ecological enzyme activities. Different lowercase letters above the bars represent significant differences between different levels of nitrogen addition (p < 0.05). Figure (a–d) represent soil invertase, urease, acid phosphatase, and catalase activities, respectively.
As illustrated in Fig. 7a-f, under consistent N addition levels, there was a steady decrease in SOC, TN, TP, TK, NO3−-N, and NH4+-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 NO3−-N and NH4+-N levels across different soil layers, with increases ranging from 206.85 to 428.37% and 148.30–186.15%, respectively. The impact of N addition on soil nutrient contents varied significantly. N addition generally suppressed SOC, TN, and TP, while it enhanced TK, NO3−-N, and NH4+-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, NO3−-N, and NH4+-N, rising by 19.59%, 839.96%, and 195.57%, respectively.
Impacts of N addition on soil nutrients. Different lowercase letters above the bars represent significant differences between different levels of nitrogen addition (p < 0.05). Figure (a–f) represent soil organic carbon, total N, total phosphorus, total potassium, nitrate N, and ammonium N, respectively.
Relationships among soil microorganisms, ecological enzymes, and nutrients under N addition
To investigate the relationships between soil bacteria and fungi with ecological enzyme activities and nutrient content following N addition, a co-linearity network analysis was conducted (Fig. 8a–d). The analysis revealed stronger interactions among soil bacteria compared to fungi. The dominant bacterial phyla, Pseudomonadota and Verrucomicrobiota communities, showed strong correlations with Ure and ACP, respectively. Acidobacteriota communities exhibited a significant correlation with TP. Among the prominent fungal phyla, Basidiomycota communities had stronger correlations with CAT, NO3−-N, and NH4+-N, while Ascomycota communities was more closely linked with Inv.
The relationships among soil microorganisms, ecological enzyme activities, and nutrients under N addition. In the figure, the more lines of connection between a microorganism and soil enzymes or nutrients, the closer their relationship is indicated to be. Figure (a) and (b) represent the relationships between soil bacteria with enzymes and nutrients, while figure (c) and (d) represent the relationships between soil fungi with enzymes and nutrients, respectively.
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 addition 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 Acidobacteriota, Pseudomonadota, and Gp1and Gp2 communities as the dominant phyla and genus, respectively, in the soil bacteria of evergreen broad-leaved forest. Each of them accounted for more than 10% of the total composition. Similarly, Basidiomycota, Ascomycota, and Archaeorhizomyces, Russula and Sebacina communities were the dominant phyla and genus, respectively, in the 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 can be attributed to the broad ecological range exhibited by these microbial communities in forest environments. Compared to CK, the relative abundance of bacterial communities (Acidobacteriota, Gp1, Gp2) and fungal communities (Basidiomycota, Sebacina) initially increased and then decreased along the N addition levels, while bacterial communities (Pseudomonadota) and fungal communities (Ascomycota) showed a reversed pattern, decreasing first and then increasing. This may be due to the fact that Acidobacteriota, Gp1, Gp2, Basidiomycota, and Sebacina communities are no longer suitable for survival in soil environments with HN levels, where the soil pH under LN or MN allows them to maintain normal metabolic activities. Pseudomonadota, Ascomycota communities may be more resilient and competitive in the environment, resulting in higher relative abundance in HN environments. The relative abundance of Archaeorhizomyces and Russula communities were consistently reduced across all three N addition levels. This may be due to the fact that N addition increases the available N in the soil, leading to N saturation, and a gradual disadvantage for this group of fungi to survive in HN environment. In this study, N addition did not significantly impact the relative abundance of the Acidobacteriota, Pseudomonadota, Gp1 and Gp2 communities. These bacterial communities play a crucial role in the conversion of ammonia to nitrite during N-cycling53. The continuous N addition in the study might have allowed them to acclimate to the prevailing soil environment. Simultaneously, They dominate bacterial communities under acidic and nitrate-rich conditions54 and possess strong adaptability and resilience, resulting in minimal changes in their relative abundance under N addition. N addition significantly impact the relative abundance of the Ascomycota, Basidiomycota, Archaeorhizomyces, Russulaand and Sebacina communities. These fungal communities are known for decomposing complex carbon sources55. N addition may have either strengthened or weakened their C mineralization. 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 exhibited specificity in their selection of organic matter, making them more sensitive to environmental conditions. Compared to CK treatment, LN treatment has a higher N concentration, which may reduce the activity of soil fungi and adversely affect their ability to utilize nutrients56. This finding supports hypothesis 2, indicating that different soil microbial groups (bacteria and fungi) exhibited specific responses to N addition. The study also observed that soil bacterial and fungal relative abundances tended to shift towards the middle and lower soil layers with varying N addition levels. This trend was further supported by the quantitative differences in soil bacteria and fungi across soil layers, as shown in Fig. 3a-f. The reason for the difference of microbial aggregation in different soil layers under N deposition may be that some trophic microorganisms tend to the soil layers with high nutrient content.
Excessive N addition 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 addition or HN levels57. The impact on microorganisms is more pronounced in such conditions57. Our study observed a decline in the diversity of soil bacteria and fungi, supporting our hypothesis that N addition 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. The reason may be that soil acidification caused by N addition has altered soil porosity and colloidal charge, affecting soil aeration, water retention, and nutrient adsorption, which in turn impacts the structure of soil microbial communities61, leading to the aforementioned results. Notably, under N addition, 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 addition was observed to generally inhibit soil Inv, Ure, and ACP activities, while promoting soil CAT activity. The suppression of Inv activity by N addition likely results from the reduced decomposition rate of soil organic matter, leading to decreased substrate availability for Inv and subsequent inhibition of its activity49. The potential reason for the decline in Ure activity due to N addition may be that added N hinders soil N mineralization rates, disrupting N cycling, which in turn reduced Ure activity63. Furthermore, N addition inhibits ACP activity, possibly due to its function in converting organic phosphorus to inorganic phosphorus64. N addition inhibits the ability of phosphorus-solubilizing fungi and other microorganisms to utilize phosphorus65, thereby reducing the activity of ACP. CAT participates in the soil humification process and decomposes hydrogen peroxide. N addition enhanced CAT activity, likely due to its impact on litter decomposition inhibition 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 matter66. However, contrasting findings were reported in another study67. Possible explanations include higher litter input and sustained CAT activity levels under N addition in the study region.
In this study, N addition generally suppressed soil SOC, TN, and TP, while enhancing soil TK, NO3−-N, and NH4+-N. N addition has the potential to impact the soil microbial ecosystem function68, triggering redox reactions that prompt the release of a substantial amount of CO2 from microbial carbon, thereby reducing soil SOC accumulation. The direct N input due to N addition increases the content of NO3−-N and NH4+-N in the soil. Nevertheless, Ure and ACP are enzymes that hydrolyze urea and organic phosphates into biologically available NH4+ and inorganic phosphorus, directly related to N and phosphorus dynamics63,64. The decrease in Ure and ACP activities reduces soil N and P elements mineralization rates. Additionally, plants may increase their uptake of N and P elements while decreasing K element uptake, leading to decreased TN and TP contents in the soil and increased TK content.
N addition has the potential to influence the allocation of microorganisms toward the production of ecological enzymes and the abundance of specific enzymes synthesized by soil microorganisms69. It can also impact nutrient levels such as carbon, N, and phosphorus70, thereby regulating microbial physiological characteristics to establish a new equilibrium between resources and microorganisms71, which in turn can influence critical biochemical processes within the ecosystem72. 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. Pseudomonadota and Verrucomicrobiota communities showed notable correlations with Ure and ACP, while the Acidobacteriota communities exhibited strong correlations with TP. Pseudomonadota communities, a significant group of diazotrophs, along with Verrucomicrobiota communities, demonstrated the ability to convert atmospheric N2 into bioavailable forms73. Verrucomicrobiota communities 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. Acidobacteriota communities 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 Basidiomycota communities showed a strong association with CAT, while Ascomycota communities exhibited a significant correlation with Inv. Basidiomycota communities also displayed strong correlations with NO3−-N and NH4+-N. Basidiomycota and Ascomycota communities play critical roles in decomposing lignin and other complex organic compounds74. Basidiomycota communities secret CAT to accelerate the breakdown of these compounds. To sustain this process, Basidiomycota communities relies on vital nutrients such as soil NO3−-N and NH4+-N for growth and metabolism, enhancing their N utilization efficiency. Conversely, Ascomycota communities 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 communities in this ecosystem is evident, displaying a strong correlation with soil enzymes and nutrients, supporting our hypothesis that N addition alters soil enzyme activities and nutrient levels, influencing microbial interactions. Microorganisms communities release specialized enzymes to access necessary nutrients for their metabolic functions.
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 addition 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.
Data availability
The datasets generated during the current study are available at https://doi.org/10.57760/sciencedb.20011.
References
Luan, L., Liu, L., Gu, E. Y., Sun, J. X. & X. & Effects of litter manipulation and nitrogen addition on soil ecoenzymatic stoichiometry in a mixed pine and oak forest. Acta Ecol. Sin. 40, 9220–9233 (2020).
Forstner, S. J. et al. Vertical patterns of ecoenzyme activities in forest soils after 20 years of simulated nitrogen deposition. EGU General Assembly Conference Abstracts. 17, 10858 (2015).
Feng, C. et al. Soil enzyme activities increase following restoration of degraded subtropical forests. Geoderma 351, 180–187 (2019).
Du, E., Fenn, M. E., Vries, W. D. & Ok, Y. S. Atmospheric nitrogen deposition to global forests: Status, impacts and management options. Environ. Pollut. 250, 1044–1048 (2019).
Tateno, R., Imada, S., Watanabe, T., Fukuzawa, K. & Shibata, H. Reduced snow cover changes nitrogen use in canopy and understory vegetation during the subsequent growing season. Plant. Soil. 438, 157–172 (2019).
Cui, S., Shi, Y., Groffman, P. M., Schlesinger, W. H. & Zhu, Y. Centennial-scale analysis of the creation and fate of reactive nitrogen in China (1910–2010). Proc. Nat. Acad. Sci. 110, 2052–2057 (2013).
Guerrieri, R. et al. Climate and atmospheric deposition effects on forest water-use efficiency and nitrogen availability across Britain. Sci. Rep. 10, 1–16 (2020).
Huang, X. L. et al. Simulated atmospheric nitrogen deposition inhibited the leaf litter decomposition of Cinnamomum migao H. W. Li in Southwest China. Sci. Rep. 11, 1–13 (2021).
Chiwa, M., Tateno, R., Hishi, T. & Shibata, H. Nitrate leaching from Japanese temperate forest ecosystems in response to elevated atmospheric N deposition. J. for. Res. 24, 1–15 (2019).
Grandy, A. S., Wieder, W. R., Wickings, K. & Kyker, S. E. Beyond microbes: are fauna the next frontier in soil biogeochemical models? Soil Biol. Biochem. 102, 40–44 (2016).
Crowther, T. W. et al. Biotic interactions mediate soil microbial feedbacks to climate change. Proc. Natl. Acad. Sci. 112, 7033–7038 (2015).
Shi, L. et al. Consistent effects of canopy vs. understory nitrogen addition on the soil exchangeable cations and microbial community in two contrasting forests. Sci. Total Environ. 553, 349–357 (2016).
Mcguire, K. L., Zak, D. R., Edwards, I. P., Blackwood, C. B. & Upchurch, R. Slowed decomposition is biotically mediated in an ectomycorrhizal, tropical rain forest. Oecologia 164, 785–795 (2010).
Graham, E. B. et al. Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes? Front. Microbiol. 7, 214. https://doi.org/10.3389/fmicb.2016.00214 (2016).
Lu, M. & Hedin, L. O. Global plant–symbiont organization and emergence of biogeochemical cycles resolved by evolution-based trait modelling. Nat. Ecol. Evol. 3, 239–250 (2019).
Zhang, J. et al. How microbes cope with short-term N addition in a Pinus tabuliformis forest-ecological stoichiometry. Geoderma 337, 630–640 (2019).
Li, Q., Song, X., Gu, H. & Gao, F. Nitrogen deposition and management practices increase soil microbial biomass carbon but decrease diversity in Moso bamboo plantations. Sci. Rep. 6, 28235 (2016).
Li, J. et al. Effects of nitrogen and phosphorus addition on soil microbial community in a secondary tropical forest of China. Biol. Fertil. Soils. 51, 207–215 (2015).
Liu, L. et al. Interactive effects of nitrogen and phosphorus on soil microbial communities in a tropical forest. PloS One. 8, e61188 (2013).
Treseder, K. K. Nitrogen additions and microbial biomass: a meta-analysis of ecosystem studies. Ecol. Lett. 11, 1111–1120 (2008).
Liu, L. & Greaver, T. L. A global perspective on belowground carbon dynamics under nitrogen enrichment. Ecol. Lett. 13, 819–828 (2010).
Li, H. et al. Responses of soil bacterial communities to nitrogen deposition and precipitation increment are closely linked with aboveground community variation. Microb. Ecol. 71, 974–989 (2016).
Boot, C. M., Hall, E. K., Denef, K. & Baron, J. S. Long-term reactive nitrogen loading alters soil carbon and microbial community properties in a subalpine forest ecosystem. Soil Biol. Biochem. 92, 211–220 (2016).
Pajares, S., Bohannan, B. J. M. & Souza, V. The role of microbial communities in tropical ecosystems. Front. Microbiol. 7, 1805 (2016).
Ramirez, K. S., Craine, J. M. & Fierer, N. Consistent effects of nitrogen amendments on soil microbial communities and processes across biomes. Glob. Change Biol. 18, 1918–1927 (2012).
Carey, C. J., Dove, N. C., Beman, J. M., Hart, S. C. & Aronson, E. L. Meta-analysis reveals ammonia-oxidizing bacteria respond more strongly to nitrogen addition than ammonia-oxidizing archaea. Soil Biol. Biochem. 99, 158–166 (2016).
Zhou, S., Xiang, Y., Xiao, Y., Huang, C. & Liang, K. Response of culturable soil microorganisms to simulated nitrogen deposition in a natural evergreen broadleaf forest in the Rainy Area of Western China. Acta Ecol. Sin. 37, 1191–1198 (2017).
Camenzind, T. et al. Opposing effects of nitrogen versus phosphorus additions on mycorrhizal fungal abundance along an elevational gradient in tropical montane forests. Soil Biol. Biochem. 94, 37–47 (2016).
Zhou, J. et al. Microbial mediation of carbon-cycle feedbacks to climate warming. Nat. Clim. Change. 2, 106–110 (2012).
Tu, L. et al. Nitrogen addition significantly affects forest litter decomposition under high levels of ambient nitrogen deposition. PLoS One. 9, e88752. https://doi.org/10.1371/journal.pone.0088752 (2014).
Chen, G. et al. Effect of nitrogen additions on root morphology and chemistry in a subtropical bamboo forest. Plant. Soil. 412, 441–451 (2017).
Wu, J. et al. Long-term nitrogen addition changes soil microbial community and litter decomposition rate in a subtropical forest. Appl. Soil. Ecol. 142, 43–51 (2019).
Wei, S. et al. Nitrogen and phosphorus co-addition stimulates soil respiration in a subtropical evergreen broad-leaved forest. Plant. Soil. 450, 171–182 (2020).
Tie, L. et al. Responses of soil C, N, and P stoichiometric ratios to N and S additions in a subtropical evergreen broad-leaved forest. Geoderma 379, 114633. https://doi.org/10.1016/j.geoderma.2020.114633 (2020).
Cusack, D. F. et al. Global change effects on humid tropical forests: evidence for biogeochemical and biodiversity shifts at an ecosystem scale. Rev. Geophys. 54, 523–610 (2016).
Yu, G. et al. Stabilization of atmospheric nitrogen deposition in China over the past decade. Nat. Geosci. 12, 424–429 (2019).
Lu, J. et al. Research progress on effects of nitrogen deposition on soil nitrogen cycling in grassland ecosystems. Acta Prataculturae Sinica. 31, 221–234 (2022).
Tie, L. et al. Effects of simulated Nitrogen and Sulfur Deposition on Lignin Degradation during Foliar Litter decomposition in Evergreen Broad-Leaved Forest in the Rainy Area of West China. For. Res. 32, 25–31 (2019).
Zhou, H. et al. Numerical simulation of distribution characteristics of regional nitrogen dry deposition. Acta Sci. Circum. 42, 129–137 (2022).
Magill, A. H. et al. Ecosystem response to 15 years of chronic nitrogen additions at the Harvard Forest LTER, Massachusetts, USA. For. Ecol. Manag. 196, 7–28 (2004).
Song, L., Liu, W. Y., Ma, W. Z. & Qi, J. H. Response of epiphytic bryophytes to simulated N deposition in a subtropical montane cloud forest in southwestern China. Oecologia 170, 847–856 (2012).
Huang, R., Wang, X., Ma, G., Zhu, J. & Zhou, H. Effects of simulated Nitrogen deposition on Soil Physicochemical properties and enzyme activities in Alpine Wetland. Acta Agrestia Sinica. 30, 1343–1349 (2022).
Hu, X. F. et al. Effects of mining wastewater discharges on heavy metal pollution and soil enzyme activity of the paddy fields. J. Geochem. Explor. 147, 139–150 (2014).
Fernández-Calviño, D. et al. Enzyme activities in vineyard soils long-term treated with copper-based fungicides. Soil Biol. Biochem. 42, 2119–2127 (2010).
Sun, X. et al. Toxic effects of ionic liquid 1-octyl-3-methylimidazolium tetrafluoroborate on soil enzyme activity and soil microbial community diversity. Ecotoxicol. Environ. Saf. 135, 201–208 (2017).
Wang, Y. et al. Effects of biochar on the growth of apple seedlings, soil enzyme activities and fungal communities in replant disease soil. Sci. Hort. 256, 108641. https://doi.org/10.1016/j.scienta.2019.108641 (2019).
Bao, S. Soil Agrochemical Analysis. 3rd Edition (China Agricultural, 2000).
Wang, L. J. et al. Effects of nitrogen addition on soil microbial biomass and enzyme activities of Pinus massoniana-Quercus variabilis mixed plantations in the Three Gorges Reservoir Area. Chin. J. Appl. Ecol. 33, 42–50 (2022).
Yuan, Y. H. et al. Effects of simulated Nitrogen deposition on soil enzyme activities and Microbial Community Functional diversities in a Chinese Fir Plantation. Adv. Mater. Res. 45, 120–128 (2013).
Xu, L. Impacts of nitrogen deposition on physical-chemical properties and enzyme activities of soil in Chinese-fir plantation forest. Fuzhou: Fujian Agriculture and Forestry University (2007). https://d.wanfangdata.com.cn/thesis/Y1175354.
Lagomarsino, A. et al. Soil biochemical indicators as a tool to assess the short-term impact of agricultural management on changes in organic C in a Mediterranean environment. Ecol. Ind. 9, 518–527 (2009).
Lin, L. Precipitation overrides warming in mediating soil nitrogen pools in an alpine grassland ecosystem on the Tibetan Plateau. Sci. Rep. 6, 1–9 (2016).
Hu, Y. L., Jung, K., Zeng, D. H. & Chang, S. X. Nitrogen-and sulfur-deposition-altered soil microbial community functions and enzyme activities in a boreal mixedwood forest in western Canada. Can. J. for. Res. 4, 777–784 (2013).
Green, S. J. et al. Denitrifying bacteria from the genus Rhodanobacter dominate bacterial communities in the highly contaminated subsurface of a nuclear legacy waste site. Appl. Environ. Microbiol. 78, 1039–1047 (2012).
Boer, W., Folman, L. B., Summerbell, R. C. & Boddy, L. Living in a fungal world: impact of fungi on soil bacterial niche development. FEMS Microbiol. Rev. 29, 795–811 (2005).
Lu, X., Mao, Q., Gilliam, F. S., Luo, L. & Mo, J. Nitrogen deposition contributes to soil acidification in tropical ecosystems. Glob. Change Biol. 20, 3790–3801 (2014).
Diepen, L. T. A. V. et al. Simulated Nitrogen Deposition causes a decline of intra- and Extraradical Abundance of Arbuscular Mycorrhizal Fungi and Changes in Microbial Community structure in northern hardwood forests. Ecosystems 13, 683–695 (2010).
Song, B. et al. Soil acidification under long-term N addition decreases the diversity of soil bacteria and fungi and changes their community composition in a semiarid grassland. Microb. Ecol. 85, 221–231 (2023).
Wang, C. et al. Responses of soil microbial community to continuous experimental nitrogen additions for 13 years in a nitrogen-rich tropical forest. Soil Biol. Biochem. 121, 103–112 (2018).
Freedman, Z. B., Zak, D. R. & Atmospheric N deposition alters connectance, but not functional potential among saprotrophic bacterial communities. Mol. Ecol. 24, 3170–3180 (2015).
Huang, G., Cao, Y. F., Wang, B. & Li, Y. Effects of nitrogen addition on soil microbes and their implications for soil C emission in the Gurbantunggut Desert, center of the eurasian continent. Sci. Total Environ. 515–516, 215–224 (2015).
Shao, Y. et al. Plants mitigate detrimental nitrogen deposition effects on soil biodiversity. Soil Biol. Biochem. 127, 178–186 (2018).
Zheng, X. R. et al. Effects of simulated Nitrogen deposition on soil enzyme activity in subalpine forests in Central Yunnan, China. For. Res. 30, 50–62 (2021).
Liang, J. et al. Study on Vertical distribution characteristics and influencing factors of Soil Phosphorus in different vegetation types in Red Soil Erosion Area. J. Soil Water Conserv. 37, 208–217 (2023).
Xia, Y. et al. Effects of simulated nitrogen deposition on soil microbial community and functional potential of phosphate-solubilizing microorganisms in a subtropical Castanopsis carlesii forest. Acta Ecol. Sin. 44, 1727–1736 (2024).
Song, Y. et al. Decomposition and Carbon and Nitrogen releases of Twig and Leaf Litter were inhibited by Increased Level of Nitrogen Deposition in a subtropical Evergreen Broad-Leaved Forest in Southwest China. Forests 15, 492. https://doi.org/10.3390/f15030492 (2024).
Carrara, J. E. et al. Differences in microbial community response to nitrogen fertilization result in unique enzyme shifts between arbuscular and ectomycorrhizal-dominated soils. Glob. Change Biol. 27, 2049–2060 (2021).
Liu, J., Zhang, R., Zhu, M. & Zhao, Z. Nitrogen addition regulates cascade effects of food webs on grassland insects. J. Plant. Prot. 51, 12–19 (2024).
Weand, M. P., Arthur, M. A., Lovett, G. M., McCulley, R. L. & Weathers, K. C. Effects of tree species and N additions on forest floor microbial communities and extracellular enzyme activities. Soil Biol. Biochem. 42, 2161–2173 (2010).
Zhu, Y. et al. Seasonal precipitation and soil microbial community influence plant growth response to warming and N addition in a desert steppe. Plant. Soil. 482, 245–259 (2023).
Jiang, C. et al. Comparative transcriptome analysis of genes involved in the drought stress response of two peanut (Arachis hypogaea L.) varieties. BMC Plant Biol. 21, 1–14 (2021).
Ma, S. et al. Inconsistent responses of soil microbial community structure and enzyme activity to nitrogen and phosphorus additions in two tropical forests. Plant. Soil. 460, 453–468 (2021).
Levy-booth, D. J., Prescott, C. E. & Grayston, S. J. Microbial functional genes involved in nitrogen fixation, nitrification and denitrification in forest ecosystem. Soil Biol. Biochem. 75, 11–25 (2014).
Zhao, Z. et al. 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? Sci. Total Environ. 625, 539–546 (2018).
Acknowledgements
We thank the following people for their help with this research: Jinmei Xing, Xiaohua Zhang, and Qian Wang provided field assistance.
Funding
This research was supported by the Agricultural Joint Special Project of Yunnan Province (202301BD070001-059), Yunnan Fundamental Research Projects (202401AT070262), the First-Class Discipline Construction Project of Yunnan Province ([2022] No. 73), The National Undergraduate Innovation and Entrepreneurship Training Program (202310677024), and First-Class Discipline in Soil and Water Conservation and Desertification Prevention in Yunnan Province (SBK20240044).
Author information
Authors and Affiliations
Contributions
Conceptualization, Y.S.; funding acquisition, Y.S., M.J.; methodology, Y.S.; supervision, Y.S., K.W.; writing—original draft, X.L., M.J.; 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.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
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.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Li, X., Su, L., Jing, M. et al. Nitrogen addition restricts key soil ecological enzymes and nutrients by reducing microbial abundance and diversity. Sci Rep 15, 5560 (2025). https://doi.org/10.1038/s41598-025-87327-7
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-025-87327-7
