Study on phyllosphere microbial community diversity of poplar

Poplar is the core tree species for ecological protection forests and artificial afforestation in northern China, and it holds significant ecological and economic value. Phyllosphere microorganisms that colonize leaf surfaces play a crucial role in regulating plant growth, disease resistance, and environmental adaptation. This study aims to reveal the differences in phyllosphere microbial communities among different poplar varieties and to clarify the driving mechanisms of leaf nutrients on microbial community assembly. The study focused on four hybrid poplar varieties in Xinmin City, Liaoning Province. Leaf total carbon, total nitrogen, total phosphorus, soluble sugar, and starch contents were measured. High-throughput sequencing technology was used to identify the taxonomic composition of phyllosphere bacteria and fungi, analyze diversity differences among varieties, and explore correlations between leaf nutrients and microbial communities using statistical methods. Significant differences in leaf nutrient contents were detected among the four poplar varieties. The dominant microbial groups in the phyllosphere were overall stable: fungi mainly belonged to the phyla Ascomycota and Basidiomycota, while bacteria mainly belonged to Proteobacteria and Actinobacteria. However, species richness and community composition differed significantly among varieties. Correlation analysis revealed that leaf total nitrogen and total phosphorus were the key nutrient factors shaping phyllosphere microbial community composition. This study confirms that phyllosphere microbial communities of different poplar varieties exhibit obvious host specificity. Leaf nutrients are important driving factors regulating community structure. These findings provide a scientific basis for the management of artificial poplar forests and the utilization of microbial resources.

Since the Industrial Revolution, the intensity and impact of human efforts to transform nature have continued to increase. With the steady improvement of the level of social and economic development, a series of ecological problems that are difficult to completely avoid have emerged: aggravated soil erosion, continued deterioration of the greenhouse effect, and the gradual decline of forest carbon sequestration capacity (Zeng, 2022).To address these challenges, the ecological value of ecological vegetation has gradually gained attention from all sectors. Among them, the role of tree species such as poplar has drawn particular attention. China’s Three-North (Northwest, North, and Northeast China) Shelter Forest System, the world’s largest ecological construction project, undertakes national strategic functions including windbreak and sand fixation, soil and water conservation, and biodiversity conservation. In this vast and ecologically fragile area, the poplar tree (Populus × canadensis), due to its strong adaptability and rapid growth characteristics, has become the main tree species for artificial afforestation, forming the backbone of the regional ecological security barrier.

Among the numerous tree species planted in our country, the poplar tree has the widest distribution range. Its natural populations grow extensively in the subtropical, warm temperate, and mid-temperate regions of China. The genus Populus (poplars) is primarily classified into five taxonomic sections: Sect. Turanga, Sect. Populus (white poplars), Sect. Aigeiros (black poplars), Sect. Tacamahaca, and Sect. Leucoides (large-leaf poplars). Among them, Sect. Tacamahaca has the largest number of species, with its core distribution concentrated in northern China; the core representative species of the section. Aigeiros are the European black poplar (Populus nigra) and the American black poplar (Populus deltoides). Poplar trees are characterized by their outstanding reproductive capacity, fast growth rate, wide environmental adaptability, and remarkable resistance to diseases and pests. They are pioneering tree species for vegetation ecological restoration in China and possess extremely high ecological value. At the same time, poplar also has significant economic value and is an important raw material source for the paper industry.

Trees can drive the nutrient cycling process by mediating the microbial community (Liu et al., 2026). Plants can provide diverse ecological niches for endophytic and epiphytic microbial communities (Nelson, 2018; Reinhold-Hurek et al., 2015). These microorganisms colonize on the surface (Ding et al., 2024) of plants and within their underground internal tissues (Vorholt, 2012), forming complex interactions. They play a crucial role in nutrient absorption, growth promotion (Mendes et al., 2013; Orozco-Mosqueda et al., 2018; Vandenkoornhuyse et al., 2015), disease resistance, and stress tolerance. Microorganisms are the core driving force for the decomposition of waste (Lin et al., 2020; Wang et al., 2020).Community ecology focuses on the species abundance, composition patterns within the community, and the driving processes thereof (Cui et al., 2025).Compared with large organisms, the species definition of microorganisms is relatively vague (Koonin et al., 2001; Soanes and Richards, 2014). In different organs of plants, microorganisms form specific community structures, and the colonization process exhibits significant spatial heterogeneity. The total of all microbial communities colonizing within and on the surface of plants is called the plant microbiome (Mendes et al., 2013; Schlaeppi and Bulgarelli, 2015). Microorganisms are a key component of forest ecosystems and play a significant ecological role for trees. They are crucial for the sustainable management of the system, as well as for its recovery and transformation after degradation (Liu et al., 2023).

The litter layer in the ecosystem serves as both the core carrier of nutrients and the key hub for material circulation (Liu et al., 2024). The microorganisms that colonize the surface of plant leaves are called phyllosphere microorganisms (Jia et al., 2018; Yao et al., 2019). In fact, the total surface area of the biosphere is approximately twice that of the Earth’s surface, supporting a vast array of biological species and forming a significant microbial ecosystem.Bacteria represent the most abundant component of epiphytic microorganisms, with bacterial abundance on leaf surfaces varying between 10 7 and 10 8 CFU·cm − ² (Morris et al., 2002; Lindow and Brandl, 2003; Monier and Lindow, 2004). The rhizosphere is currently the largest known habitat for microorganisms. The microorganisms that colonize here are crucial for the health, growth, reproduction, and stress resistance of the host plants (Cui and Wu, 2023), and they also possess multiple ecological functions, such as promoting plant growth and maintaining the biogeochemical cycle (Li et al., 2026; Meng et al., 2025). The temporal and spatial patterns of the leaf-associated habitats fluctuate greatly, resulting in significant differences in the community composition of epiphytic bacteria across micro-spatial scales, short time periods, and different growing seasons (Hirano and Upper, 1989; Ercolani, 1991; Thompson et al., 1993).

The study of microorganisms at the interface of soil belongs to the field of microecology. As an important component of forest biodiversity, the epiphytic microorganisms play a crucial role in maintaining the health of plants, strengthening the host’s defense system, and participating in global biogeochemical cycles and other ecological processes (Wang et al., 2022). These microorganisms attach to the surface of plant leaves and interact with the host and other microbial groups, forming complex interspecies relationships such as parasitism, symbiosis, and mutualism (Gong and Xin, 2011).Among them, the symbiotic model is dominant. The plant leaves provide diverse habitats for microorganisms. The phyllosphere microorganisms, through their interactions with the host, play significant roles in promoting plant growth, facilitating nutrient absorption, and enhancing the plant’s resilience to complex environments (Zhu et al., 2026; Liu et al., 2026). The different leaf habitats of various plants will select out distinct groups, causing the leaf-associated microorganisms to exhibit significant host specificity.

The leaf-associated habitats provide suitable conditions for microbial colonization. The microbial communities play a crucial role in enhancing the environmental adaptability of plants, maintaining plant health, and resisting pathogen infections. With the continuous advancement of cell biology research, the previously overlooked surface habitat of leaves has now been recognized as a micro-environment with significant ecological value. As a special type of microbial habitat, the phyllosphere of plants supports a structurally complex and dynamically balanced microbial community (Partida-Martínez and Heil, 2011;Manzotti et al., 2020), encompassing various groups such as bacteria, fungi, protists (Sapp et al., 2017), algae (Zhu et al., 2018), and bacteriophages (Morella et al., 2025).Even at the scale of phyllosphere micro-habitats, bacterial populations maintain a high biomass load. Early field surveys demonstrated that phyllospheres may support bacterial densities ranging from 10 6 to 10 7 cells per square centimeter, with the bacterial population accumulating up to 10 8 cells per gram of recovered leaf tissue (Meyer and Leveau, 2012; Liu et al., 2020; Bashir et al., 2022).From the taxonomic perspective, the bacterial community on the phyllosphere is mainly composed of the Proteobacteria, Actinobacteria, and Bacteroidetes phyla, among which the Proteobacteria phylum plays a dominant role in the community (Singh et al., 2019; Liu et al., 2022).The fungal microbiome at the leaf interface is dominated by two major groups: the Ascomycota and the Basidiomycota. The typical representatives of the Ascomycota include the Aureobasidium, Cladosporium, and Taphrina genera; in the Basidiomycota, the Cryptococcus and Sporobolomyces genera are common in the leaf interface environment.

The formation of the microbial community on the phyllosphere of plants is a complex ecological process regulated by multiple factors in coordination. The survival and diversity maintenance of the leaf-associated microorganisms are essentially the result of the concurrent action of various ecological processes such as immigration, emigration, reproduction, dispersion, and extinction. In this study,plants of four hybrid poplar cultivars (Y1: DM-9-18, Y2: DX-08-01, Y3: 2111, Y4: 9216) — derived from crosses between Populus cathayana and Populus deltoides and planted in the Xinmin region of Liaoning Province — were used as research materials. Leaf samples were collected from poplars of different cultivars, and MiSeq high-throughput sequencing technology was employed to sequence phyllosphere bacteria and fungi, aiming to elucidate the differences in microbial communities among different poplar cultivars and their underlying influencing factors.

Sample information

Four different poplar varieties were selected as the experimental subjects in this study. They are Y1:DM-9-18 (Populus deltoides×Populus maackii) and Y2:DX-08-01 (Populus maximowiczii×Populus pseudosimonii), respectively, Kitag. Y3:2111 (Populus deltoides×Populus suaveolens), and Y4:9216 (Populus deltoides×Populus These samples (deltoidescv. ‘Shanhaiguanensis’) were all from Xinmin City, Shenyang City, Liaoning Province. Each variety was planted in 6 rows with 5 plants per row, with 4 replicates for each variety, totaling 16 plots. On both sides of the sample plots, two rows of poplar trees were planted as protective rows. This study collected leaf samples, measured the nutrients in the leaves, and investigated the nutrient differences among different varieties of poplar trees; it also measured the microbial communities at the leaf interface and explored the main influencing factors of these microbial communities.

Collection and processing of leaves

Four varieties of poplar trees were selected. For each variety, 3 poplar trees with similar growth were randomly chosen. The distance between the two trees was more than 10 meters. Four directions (east, west, south, and north) at a height of 6–8 meters from the ground were selected for each tree. Branches were cut using high-branch shears. Sterile gloves were worn to uniformly pick 4 complete, uniform in size, healthy, and free of pest and disease spots leaves from each branch. The leaves of the 3 poplar trees in each plot were mixed into one sample, which was placed in a sterilized sealed bag and recorded as one repetition. A total of 16 bags were collected for the 4 varieties. All plant samples were collected on the same day and stored in an ice box at 4 °C in the laboratory. Some were dried for physicochemical property determination, and some were used for extracting leaf-associated microorganisms for subsequent analysis.

Place 10g of leaf samples in a 500ml sterile conical flask, and then add 200ml of sterile PBS buffer (pH 7.4, 1-fold phosphate buffer). To wash the microbial cells on the leaves, ultrasonicate the leaves in an ultrasonic cleaning bath at a frequency of 40 kHz for 6 minutes, then oscillate at 200 r/min at 30 °C for 20 minutes, and then ultrasonicate again (at a frequency of 40 kHz) for 3 minutes. Filter the cell suspension through a 0.22 μm × 50 mm sterile nylon membrane to separate the microbial cells from the leaves. Store the membrane samples in a -80 °C freezer. This mild ultrasonic-assisted elution procedure was adopted from validated phyllosphere microbial extraction protocols, which can efficiently detach epiphytic microorganisms from leaf surfaces while limiting the risk of microbial cell lysis under the given instrumental settings (Ding et al., 2024; Jia et al., 2018).

Method for determining the chemical properties of samples

The soluble sugar and starch contents of the leaves were measured using a UV-8000 spectrophotometer, with the anthrone colorimetric method at a wavelength of 625 nm to determine the absorbance values. Finally, the contents of soluble sugar and starch were calculated. The total nitrogen and total carbon of the leaves were determined using an elemental analyzer (Elemental Vario EL III, Germany). The total phosphorus was measured using the molybdenum-sulfur antimony colorimetric method, with the absorbance value measured at a wavelength of 700 nm using the UV-8000 spectrophotometer, and the total phosphorus content of the leaves was calculated.

Microbial extraction

Total DNA was extracted using the Fast ® DNA SPIN kit (MP Biomedicals, USA). The quantity and quality of the DNA were determined using a Nanodrop NC2000 spectrophotometer (Thermo Fisher Scientific) and agarose gel electrophoresis. The 16S rRNA gene V3-V4 region was amplified using the forward primer 338F and the reverse primer 806R (the primers contain 7-bp sample-specific barcodes), and the ITS rRNA gene V1 region was amplified using the forward primer ITS5 and the reverse primer ITS2. The DNA purity was evaluated using the Nanodrop NC2000 spectrophotometer. After purifying the PCR amplification products with Vazyme VAHTSTM DNA Clean Beads (Nanjing, China), the amplification products were quantified using the Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen, USA). The amplified products were quantified separately and then pooled in equal amounts. The sequencing was performed using the Illumina NovaSeq platform and the NovaSeq 6000 SP kit at Shanghai Pansen Bio-Technology Co., Ltd., with 2×250 bp dual-end sequencing.

Data processing and analysis

Using R scripts and the VennDiagram package, a Venn diagram was generated from the ASV abundance table to analyse shared and unique ASVs across samples. For alpha-diversity analysis, rarefaction curves were produced in QIIME2 (2019.4) to compare ASV counts among samples at equal sequencing depth. Species richness was represented by Chao1 and Observed species; community diversity was represented by Shannon and Simpson indices; phylogenetic diversity was represented by Faith’s PD; community evenness was represented by Pielou’s evenness; and sequencing coverage was assessed using Good’s coverage. Boxplots were plotted with R scripts. Significance of differences between groups was analyzed through the Kruskal-Wallis rank-sum test followed by Dunn’s post-hoc test with Benjamini-Hochberg correction for multiple comparisons. Based on the feature table excluding singletons, QIIME2 (2019.4) and self-written Perl scripts were used to call “qiime taxa barplot” to generate species-composition bar charts from phylum to species level. Based on the Bray-Curtis distance matrix, clustering was performed via the UPGMA algorithm using the uclust function from the R stat package, and clustering results were visualized with the ggtree package. Using the LEfSe package, R, and the ggtree package for analysis, filtering, and visualization were performed based on the average species abundance. The correlation heatmap was drawn by the online platform genecsloud based on the Spearman correlation coefficient. The three-line table was made using Excel, and the significance analysis was completed using SPSS.

Redundancy analysis (RDA) was performed to quantify the relationship between leaf nutrient traits and phyllosphere microbial community composition. The genus-level abundance matrices were Hellinger-transformed, and the environmental variables (total carbon, total nitrogen, total phosphorus, soluble sugar, and starch) were standardized (z-score) prior to analysis. The significance of the global RDA model and each axis was assessed by permutation tests (999 permutations). Variance partitioning analysis (VPA) was further conducted to decompose the total explained variation into independent contributions of macronutrients (TC, TN, TP) and carbohydrates (soluble sugar, starch), as well as their shared fraction. All analyses were performed in R using the vegan package.

Analysis of leaf nutrient differences

As shown in Table 1, the contents of total phosphorus (f = 44.6012, p = 0.0000), total carbon (f = 6.8225, p = 0.0082), total nitrogen (f = 340.3763, p = 0.0000), soluble sugar (f = 0.0593, p = 1.0153), and starch (f = 3.8012, p = 0.0481) in the four types of poplar trees (Y1, Y2, Y3, Y4) are different. Among the total phosphorus content, sample Y3 has the highest content of 4.68mg/g, while sample Y1 has the lowest content of 1.42mg/g. The maximum and minimum values of total phosphorus differ by 3.26mg/g. According to the significance analysis, the total phosphorus content of sample Y1 is significantly lower than that of sample Y3, and there is no significant difference from the other two types of poplar trees. Among the total carbon contents, sample Y3 had the highest content of 500.11mg/g, while sample Y4 had the lowest content of 482.66mg/g. According to the significance analysis, the total carbon content of sample Y3 was significantly higher than that of the other three poplar species. In terms of total nitrogen content, sample Y3 had the highest content of 34.08mg/g, while sample Y1 had the lowest content of 17.96mg/g. According to the significance analysis, the content of sample Y3 was significantly higher than that of the other three poplar species, while the content of sample Y1 was significantly lower than that of the other three poplar species. Regarding the carbon-to-nitrogen ratio, sample Y3 was significantly lower than the other three groups of samples. According to the one-way analysis of variance, there were significant differences in the carbon-to-nitrogen ratio among the four groups of poplar trees. In terms of soluble sugar content, sample Y2 had the highest content, at 23.03mg/g, while sample Y3 had the second-highest content, at 21.89mg/g. Based on the significance analysis, there were no significant differences among the four samples. In terms of starch content, sample Y3 had the highest content, at 29.21mg/g, while sample Y2 had the lowest content, at 14.63mg/g. According to the significance difference analysis, the starch content of sample Y2 was significantly lower than that of the other three samples (Table 1).

Analysis of microbial communities in the leaves of poplar trees

After quality filtering and denoising of sequencing reads, the amplicon sequence variants (ASVs) of phyllosphere bacteria and fungi were obtained. The number of shared and unique ASVs among different poplar cultivars was calculated, and the composition characteristics of leaf-associated microbial communities were further analyzed.

Differential ASV analysis of poplar phyllosphere microbiota

ASV can compare the differences in leaf-associated microbial communities under different plant species, life forms, or environmental conditions. Among the bacterial communities at the leaf interface, after noise removal or clustering, a total of 12,681 high-quality sequences were obtained. On average, each sample contained 3,170 high-quality sequences. Among them, the number of unique ASVs specific to Y1 was 2,445, to Y2 was 1,834, to Y3 was 3,056, and to Y4 was 3,903. The total number of ASVs common to all four samples was 264. The number of ASVs common to Y1 and Y2 was 920, to Y1 and Y3 was 582, to Y1 and Y4 was 592, to Y2 and Y3 was 492, to Y2 and Y4 was 583, and to Y3 and Y4 was 414. Samples Y1 and Y2 shared the highest number of ASVs, indicating relatively similar phyllosphere microbial communities. Samples Y3 and Y4 shared the fewest ASVs, revealing apparent compositional dissimilarity between these two groups (Figure 1A).

Among the leaf-associated fungi, after noise removal or clustering, a total of 2269 high-quality sequences were obtained, with an average of 567 high-quality sequences per sample. The number of ASVs unique to samples Y1, Y2, Y3, and Y4 was 432, 508, 437, and 692, respectively. A total of 24 ASVs were shared across all four samples. Pairwise comparison revealed that 126 ASVs were common to Y1 and Y2, 101 to Y1 and Y3, 46 to Y1 and Y4, 102 to Y2 and Y3, 56 to Y2 and Y4, and 35 to Y3 and Y4.Samples Y1 and Y2 shared the largest set of ASVs, indicating a high degree of similarity in their fungal community composition. In contrast, Y3 and Y4 had the fewest shared ASVs, reflecting substantial differentiation in their fungal community structure (Figure 1B).

Based on the above analysis, the species richness of bacteria in the phyllosphere is higher than that of fungi in the phyllosphere, which is in line with the general rule of leaf-associated microorganisms and indicates that the leaf-associated bacteria have a broader adaptability to the leaf environment.

Analysis of the compositional differences at the microbial community level in the interstitial environment

At the species composition level of the lichen fungal kingdom, we identified the top five fungal groups in terms of relative abundance, which are the Ascomycota, Basidiomycota, Mucoromycota, Chytridiomycota, and Mortierellomycota, and other biological groups. Among them, the Ascomycota is the dominant fungal group in the lichen microbial fungal kingdom at the species composition level, followed by the Basidiomycota. The Ascomycota have the highest relative abundance in sample Y1, at 97.81%, and the lowest relative abundance in sample Y2, at 85.32%; the Basidiomycota have the highest relative abundance in sample Y2, at 9.64%, and the lowest relative abundance in sample Y1, at 1.68%; the relative abundances of Mucoromycota, Chytridiomycota, and Mortierellomycota are relatively low. The relative abundances of other groups are slightly higher in sample Y2 (Figure 2A).

At the phylum level of epilithic bacteria, we identified the top ten bacterial groups in terms of relative abundance, which include Proteobacteria, Actinobacteria, Bacteroidota, Cyanobacteria, Myxococcota, Firmicutes, Deinococcota, Chloroflexi, Acidobacteria, Gemmatimonadota, and other biological groups. Among them, Proteobacteria is the dominant bacterial group in the epilithic microbial community, followed by Actinobacteria. Proteobacteria has the highest relative abundance in sample Y3, at 79.3%, and the lowest in sample Y2, at 46.79%; Actinobacteriota has the highest relative abundance in sample Y2, at 42.72%, and the lowest in sample Y3, at 10.59%; Bacteroidota has the highest relative abundance in sample Y4, and the lowest in sample Y3, at 12.11% and 2.17% respectively; Cyanobacteria has the highest relative abundance in sample Y4, and the lowest in sample Y2, at 6.57% and 0.81% respectively; the relative abundances of trace groups such as Myxococcota, Firmicutes, etc. show no significant differences among the samples (Figure 2B).

Analysis of the compositional differences at the microbial community level in the interstitial environment

At the species composition level of the leaf-associated fungi, we identified the top ten fungal groups in terms of relative abundance, which were Nothophoma, Cryptocline, Cercospora, Alternaria, Pseudopeyronellaea, Phyllozyma, Cladosporium, Zymoseptoria, Sphaerulina, and Acremonium, among others. Among them, the Nothophoma genus had the highest relative abundance in all four samples, indicating that it was the dominant group in the four samples. In sample Y4, the relative abundance was the highest at 41.71%, while in sample Y3, it was the lowest at 15.56%. The Cryptocline genus had the highest relative abundance in sample Y3, at 38.74%, with no significant difference in relative abundance in the other three samples. The Cercospora genus had the highest relative abundance in sample Y2, at 13.84%, and the lowest in sample Y3, at 1.76%. The Alternaria genus had the highest relative abundance in sample Y1 and the lowest in sample Y4, at 8.12% and 4.28%, respectively (Figure 3A).

At the species composition level of the rhizosphere bacteria, we identified the top ten microbial groups in terms of relative abundance. They are Methylobacterium-Methylorubrum, Sphingomonas, Curtobacterium, Hymenobacter, Pseudomonas, Chloroplast, Rosenbergiella, Pantoea, Roseomonas, and Nocardioides. Among them, Methylobacterium-Methylorubrum had the highest relative abundance in sample Y1, at 27.18%, and the lowest in sample Y3, at 11.64%; Sphingomonas had the highest relative abundance in sample Y4, followed by sample Y2, at 17.71% and 17.26% respectively, and the lowest in sample Y3, at 3.94%; Curtobacterium had the highest relative abundance in sample Y2, at 33.49%, and the lowest in sample Y3, at 4.76% (Figure 3B).

Leaf-associated microbial LEfSe analysis

The LEfSe (Linear discriminant analysis Effect Size) analysis is a core analytical method used in microbial diversity research for screening species with significant differences between groups. It combines the advantages of statistical significance and biological correlation assessment, and the results are intuitive and highly practical. The taxonomic branching diagram shows the hierarchical classification relationships of the main taxonomic units from phylum to genus (from the inner circle to the outer circle) in the sample communities. Among them, the hollow circles represent microbial communities without significant differences, and the colored circles represent microbial communities with significant differences.

In the LEfSe analysis of interleaf fungal communities, the main microbial group marked at the phylum level was Ascomycota, which was mainly enriched in sample Y1. The main microbial groups marked at the genus level are Kondoa, Pseudo Cercospora, Cladosporium, Dissoconium, Epicoccum, Trichoderma, Pseudogymnoascus, Nigrospora, Phyllosticta, and Diaporthe. The genera Neosetophoma, Phaeosphaeria, and Venturia, among which Kondoa and Pseudo Cercospora are mainly enriched in Group Y1. The genera Cladosporium, Dissoconium, Epicoccum, Trichoderma, and Pseudogymnoascus were mainly enriched in Group Y2. The genera Nigrospora, Phyllosticta, and Diaporthe are mainly enriched in Group Y3. Neosetophoma, Phaeosphaeria, and Venturia were mainly enriched in group Y4 (Figure 4A).

In the microbial community at the phyllosphere, the main microbial groups identified at the phylum level are Acidobacteriota, Actinobacteriota, Bacteroidota, Bdellovibrionota, Chloroflexi, Deinococcota, Myxococcota, and Proteobacteria. These microbial groups are mainly enriched in different treatment groups as follows: Acidobacteriota is mainly enriched in the Y3 group, Actinobacteriota, Chloroflexi, and Deinococcota are mainly enriched in the Y2 group, Bacteroidota, Myxococcota, and Proteobacteria are mainly enriched in the Y4 group, and Bdellovibrionota is mainly enriched in the Y1 group.

The main microbial groups identified at the genus level are Pseudomonas, Rosenbergiella, Methylobacterium-Methylorubrum, Hymenobacter, Acinetobacter, Sphingomonas, and Pantoea. Among them, Pseudomonas and Rosenbergiella are mainly enriched in group Y1; Methylobacterium-Methylorubrum and Hymenobacter are mainly enriched in group Y2; Acinetobacter and Sphingomonas are mainly enriched in group Y3; and Pantoea is mainly enriched in group Y4 (Figure 4B).

Analysis of alpha diversity of microbial communities at the benthic level

Good’s coverage values were ≥ 0.9996 across all samples, confirming that the sequencing depth was sufficient to capture the phyllosphere microbial diversity.

For the phyllosphere fungal community, the Chao1 index was significantly higher in the Y2 group than in the Y1 group (p = 0.0074), indicating that Y2 harbored the highest fungal species richness while Y1 had the lowest. The Shannon index did not differ significantly among the four cultivars (p = 0.52), suggesting that fungal community evenness and overall diversity were relatively stable across cultivars (Figure 5A).

For the phyllosphere bacterial community, the Chao1 index was significantly higher in the Y4 group than in the Y2 group (p = 0.041), indicating that Y4 supported the highest bacterial species richness. The Shannon index showed a similar trend, with the highest value in Y4 and the lowest in Y2, although the difference did not reach statistical significance (p = 0.13) (Figure 5B).

Overall, cultivar identity significantly affected fungal species richness (Y2 highest, Y1 lowest) but not fungal diversity. For bacteria, both richness and diversity tended to be highest in Y4 and lowest in Y2, with richness reaching statistical significance.

Analysis of beta diversity of microbial communities at the interface of leaves

The non-metric multidimensional scaling (NMDS) ordination was used to visualise the similarity and compositional differences of microbial communities among samples. A Stress value below 0.2 indicates that the NMDS ordination reliably reflects community similarity. For the fungal community, the Stress value was 0.0805; for the bacterial community, the Stress value was 0.0758. Both were well below the 0.2 threshold, confirming that the NMDS ordinations accurately represented the compositional differences of the phyllosphere microbial communities.

In the microbial community of the substrate fungi, both Y1 and Y2 are located in the negative area of NMDS1, with a relatively close spatial distance, indicating that the similarity of the fungal community composition is high; Y3 and Y4 samples are concentrated in the positive area of NMDS1, completely separated from Y1 and Y2 in space, with a significant spatial difference. This suggests that the fungal community compositions of Y3 and Y4 have a great difference from those of Y1 and Y2, and the Beta diversity of the fungal community affected by different treatments is significant (Figure 6A).

In the microbial community of the substrate bacteria, both Y1 and Y2 are located in the positive region of NMDS1, with a relatively close spatial distance, indicating that the similarity of the bacterial community composition is high; the Y3 sample is completely concentrated in the negative region of NMDS1, completely separated from Y1 and Y2 in space, with a significant spatial difference, suggesting that the bacterial community compositions of Y3 and Y1, Y2 have a great deal of difference; Y4 is distributed in the middle-right region of NMDS1, with a certain spatial distance from Y1 and Y2, and there are also obvious differences in the community composition, and different treatments also have a significant impact on the Beta diversity of the bacterial community (Figure 6B).

Analysis of the correlation between microbial composition in the soil surface and nutrient content in leaves

Analysis of the correlation between the composition of leaf-associated fungal communities and leaf nutrient content

The Spearman correlation heatmap can visualize data and show the intensity and direction of pairwise correlations among multiple variables. ** indicates a significant difference at the 0.01 level, and * indicates a significant difference at the 0.05 level. In this study, the dominant microbial communities at the phylum and genus levels of the phyllosphere were selected, and the Spearman correlation heatmap was used to analyze the relationship between the composition of the phyllosphere microbial community and leaf nutrients.

At the microbial phylum level, the total phosphorus, total nitrogen, total carbon, soluble sugar, and starch contents of the leaves were analyzed in relation to the relative abundance and total phosphorus, total nitrogen, total carbon, soluble sugar, and starch contents in the microbial phylum level community at the phyllosphere. Spearman correlation analysis was conducted to reveal the regulatory effect of substrate physical and chemical factors on the composition of fungal communities (Figure 7A). The results showed that the response patterns of different fungal phyla to substrate factors were significantly differentiated: the Ascomycota phylum showed a strong positive correlation trend with starch content, while the Basidiomycota phylum showed a positive correlation trend with total phosphorus and total nitrogen; the Ustilago phylum showed a similar response pattern to starch as the Ascomycota phylum, while the Mucor phylum did not show a specific association.

At the level of the genus level of ectomycorrhizal fungi, genera such as Cryptocline, Rhodotorula, and Nigrospora showed significant positive correlations with total phosphorus, total nitrogen, and total carbon, indicating that their relative abundances increased with the increase in total phosphorus, total nitrogen, and total carbon content; Acremonium was significantly positively correlated with starch, indicating its relative abundance; Cladosporium was significantly negatively correlated with starch, suggesting that its relative abundance was negatively regulated by starch; Endosporium showed significant positive correlation with TC, and Golubevia showed significant negative correlation with TC.

At the level of the Phaeosphaeriales genus, the total phosphorus content was significantly positively correlated with the Cryptocline genus, the Rhodotorula genus, the Zasmidium genus, and the Nigrospora genus, indicating that the relative abundance of these genera increased with the increase in total phosphorus content; the starch content was significantly negatively correlated with the Cladosporium genus and significantly positively correlated with the Acremonium genus, suggesting that the relative abundance of the Cladosporium genus was negatively regulated by starch content, and the relative abundance of the Acremonium genus was positively regulated by starch content; the total nitrogen content was significantly positively correlated with the Rhodotorula genus and the Nigrospora genus, indicating that their relative abundance increased with the increase in total nitrogen content; the total carbon (TC) content of the substrate was significantly positively correlated with the Cryptocline genus, the Rhodotorula genus, the Endosporium genus, and the Nigrospora genus, and significantly negatively correlated with the Golubevia genus, suggesting that the relative abundance of the Cryptocline genus, the Rhodotorula genus, the Endosporium genus, and the Nigrospora genus increased with the increase in total carbon content, while the relative abundance of the Golubevia genus decreased with the increase in total carbon content; the remaining fungal genera did not show significant correlations with the physicochemical factors in this study, indicating that the relative abundance of these genera was less affected by the above environmental factors (Figure 7B).

Analysis of the correlation between the composition of bacterial communities at the leaf interface and the nutrients in the leaves

At the community composition level of the bacterial phyla in the phyllosphere, the total phosphorus content was significantly negatively correlated with the Bacteroidota phylum, and extremely significantly negatively correlated with the Bdellovibrionota and Abditibacteriota phyla. This indicates that the relative abundances of the Bacteroidota, Bdellovibrionota, and Abditibacteriota phyla decreased as the total phosphorus content increased. The soluble sugar content did not show a significant correlation with any of the bacterial phyla in this study, suggesting that the soluble sugar content had a minor effect on these phyla. The starch content showed a positive trend with the Bdellovibrionota and Abditibacteriota phyla, but did not reach a significant level. The total nitrogen content was extremely significantly negatively correlated with the Bdellovibrionota phylum and significantly negatively correlated with the Abditibacteriota phylum, indicating that the relative abundances of the Bdellovibrionota and Abditibacteriota phyla were negatively regulated by the total nitrogen content. The total carbon content was significantly negatively correlated with the Deinococcota and Bdellovibrionota phyla, and significantly negatively correlated with the phosphorus, starch, and nitrogen contents. This indicates that the relative abundances of the Deinococcota and Bdellovibrionota phyla decreased as the total carbon content increased. The Bacteroidota phylum had no significant correlation with the total nitrogen and total carbon contents, and the Deinococcota phylum had no significant correlation with the phosphorus, starch, and nitrogen contents (Figure 8A).

At the bacterial genus level of community composition, the total phosphorus content was highly significantly negatively correlated with the Methylobacterium-Methylorubrum genus, significantly negatively correlated with the Hymenobacter genus, and highly significantly positively correlated with the Rosenbergiella genus. This indicates that the relative abundances of the Methylobacterium-Methylorubrum genus and the Hymenobacter genus decreased with the increase in total phosphorus content, while the relative abundance of the Rosenbergiella genus increased with the increase in total phosphorus content, being positively regulated by total phosphorus content. The soluble sugar and starch contents did not show significant correlations with any of the genera, indicating that these carbohydrate components had a relatively small impact on the above bacterial genera. The total nitrogen content of the substrate was highly significantly negatively correlated with the Methylobacterium-Methylorubrum genus, indicating that the relative abundance of the Methylobacterium-Methylorubrum genus decreased with the increase in total nitrogen content, and was highly significantly positively correlated with the Rosenbergiella genus, suggesting that the relative abundance of the Rosenbergiella genus increased with the increase in total nitrogen content. The total carbon content was significantly negatively correlated with the Methylobacterium-Methylorubrum genus and significantly positively correlated with the Rosenbergiella genus, indicating that the relative abundance of the Methylobacterium-Methylorubrum genus was negatively regulated by the total carbon content, while the relative abundance of the Rosenbergiella genus was positively regulated by the total carbon content. The Hymenobacter genus had no significant correlations with the soluble sugar, starch, total nitrogen, or total carbon content (Figure 8B).

Analysis of the correlation between alpha diversity index of the microbial community at the leaf interface and leaf nutrients

In order to study the relationship between the Alpha diversity index of the microbial community at the leaf interface and the nutrient content of the leaves, we used a Spearman correlation heatmap to visualize the data.

In the microbial community of substrate fungi, the Chao1 index and the Observed Species index are correlated with leaf nutrients. Among them, the starch content shows a significant negative correlation with both the Chao1 index and the Observed Species index, indicating that the species richness of the substrate fungal microbial community decreases as the starch content increases; the contents of total phosphorus (TP), soluble sugar, total nitrogen (TN), and total carbon (TC) in the substrate have a relatively weak correlation with the species richness index of the substrate fungal microorganisms, and do not reach the significant level; however, the diversity index has a negative correlation with the total carbon content, suggesting that the contents of total phosphorus, soluble sugar, total nitrogen, and total carbon have a relatively weak impact on the species richness of the substrate fungal microbial community. The Pielou_e index of the community has a significant correlation with leaf nutrients. The contents of total phosphorus (TP), soluble sugar, total nitrogen (TN), and total carbon (TC) all show a significant positive correlation with the Pielou_e index. Particularly, the correlation of total carbon (TC) content is significant, indicating that the species evenness of the microbial community in the substrate fungi increases with the increase of total phosphorus, soluble sugar, total nitrogen, and total carbon contents. Starch content has a weak positive correlation with the Pielou_e index, but it does not reach a significant level, suggesting that starch content has a weak regulatory effect on the species evenness of the microbial community in the substrate fungi (Figure 9A).

In the bacterial microbial community, the Pielou_e index, Shannon index, and Simpson index are correlated with leaf nutrients. Among them, the total phosphorus (TP) content has a significant negative correlation with the Simpson index, and also has a strong negative impact on the Pielou_e index and Shannon index, indicating that excessive phosphorus content in the substrate may reduce the uniformity and comprehensive diversity of the bacterial community; the contents of soluble sugar and starch have a weak positive correlation with the bacterial diversity index, but do not reach a significant level, suggesting that the contents of soluble sugar and starch have a weak regulatory effect on the uniformity and diversity of the bacterial community; the total nitrogen (TN) and total carbon (TC) contents have a negative correlation with the bacterial diversity index, but do not reach a significant level, indicating that the total nitrogen and total carbon contents have a weak impact on the uniformity and diversity of the bacterial microbial community (Figure 9B).

Redundancy analysis (RDA) was performed to quantify the relationship between leaf nutrient traits and phyllosphere microbial community composition. Based on all 16 replicate samples, the global RDA model was significant for both the bacterial community (F = 2.595, p = 0.004; adjusted R 2 = 34.72%) and the fungal community (F = 3.637, p = 0.001; adjusted R 2 = 46.78%), indicating that leaf nutrients significantly structured phyllosphere microbial communities, with a stronger explanatory power for fungi than for bacteria. Variance partitioning analysis (VPA) further revealed that macronutrients (TC, TN, and TP) independently explained 30.79% of the bacterial and 52.73% of the fungal community variation, whereas carbohydrates (soluble sugar and starch) independently explained only 1.47% and nearly 0% of the bacterial and fungal variation, respectively; the shared fraction between the two nutrient groups was small (2.46% for bacteria). Among individual nutrients, total nitrogen showed the highest marginal explanatory power (34.85% for bacteria, 52.23% for fungi), followed by total phosphorus and total carbon, while soluble sugar and starch had negligible independent effects. However, due to strong collinearity among TC, TN, and TP --all three were concurrently highest in cultivar Y3 --no single nutrient factor reached significance in the marginal (Type III) test, indicating that these macronutrients jointly rather than individually drive phyllosphere community assembly. The RDA ordination plots based on cultivar means further illustrated the taxon -nutrient associations. For the bacterial community, the first two axes explained 61.35% and 25.75% of the variation (cumulative 87.11%) (Figure 10A); starch, soluble sugar, and total carbon were the main nutrient gradients, with Proteobacteria, Acidobacteriota, Gemmatimonadota, and Chloroflexi positively associated with starch and total carbon, whereas Actinobacteria and Deinococcota were positively correlated with soluble sugar. For the fungal community, the first two axes explained 52.92% and 33.4% of the variation (cumulative 86.32%) (Figure 10B); total carbon, total nitrogen, and starch all projected positively along Axis-1, with Cryptocline and Acremonium positively associated with these nutrients, whereas Cladosporium, Nothophoma, Cercospora, Phyllozyma, and Sphaerulina clustered on the negative side of Axis-1; Alternaria, Pseudopeyronellaea, and Zymoseptoria were positively associated with Axis-2 but showed weak correlations with the measured nutrients.

Host genotype is increasingly recognized as a major filter shaping the phyllosphere microbiome, yet the relative contribution of leaf nutrient traits versus genetic background remains poorly resolved in hybrid poplar systems (Cregger et al., 2018). In this study, four hybrid poplar cultivars grown under identical site conditions exhibited pronounced differentiation in both leaf nutrient profiles and phyllosphere microbial community structure, providing direct evidence that host-mediated nutrient filtering operates at the cultivar level even when environmental sources of microbial inoculum are shared.

The four cultivars differed significantly in total carbon, total nitrogen, total phosphorus, and starch content, whereas soluble sugar did not vary significantly. Cultivar Y3 (Populus deltoides x Populus suaveolens) consistently showed the higher levels of total carbon, total nitrogen, total phosphorus, and starch, suggesting a more active photosynthetic metabolism and nutrient assimilation capacity. In contrast, Y1 (Populus deltoides x Populus maackii) had the lowest total nitrogen and total phosphorus and the highest C:N ratio, indicating a relatively nutrient-conservative leaf strategy (Wright et al., 2004). Such inter-cultivar nutrient heterogeneity creates distinct microhabitats on the phyllosphere, which in turn select for taxonomically and functionally divergent microbial assemblages. This finding aligns with previous reports that leaf chemical traits, particularly nitrogen and phosphorus availability, are primary determinants of phyllosphere community assembly in woody perennials (Ding et al., 2024).

The significant negative correlation between starch content and fungal species richness is particularly noteworthy. High starch accumulation in leaves may reflect reduced carbon exudation to the phyllosphere or altered osmotic conditions, both of which could restrict fungal colonization. Conversely, the positive correlation between total carbon, total nitrogen, total phosphorus, and soluble sugar with fungal Pielou_e evenness suggests that higher nutrient availability promotes a more equitable distribution of fungal taxa, potentially by relaxing competitive exclusion among species (Meyer and Leveau, 2012). For bacteria, total phosphorus was negatively correlated with the Simpson index, indicating that excessive phosphorus may reduce bacterial community evenness by favoring a small number of phosphorus-responsive dominant taxa. These diversity–nutrient relationships are consistent with ecological theory predicting that nutrient enrichment can either increase or decrease diversity depending on the degree of competitive dominance and the heterogeneity of resource supply (Meyer and Leveau, 2012).

Correlation analysis revealed that total nitrogen (TN) and total phosphorus (TP) were the predominant nutrient factors structuring phyllosphere microbial community composition, exceeding the influence of carbon-related variables such as total carbon (TC) and soluble sugars. This finding is consistent with the established paradigm that N and P availability act as primary bottom-up regulators of microbial community assembly in nutrient-limited habitats, including the phyllosphere (Bringel and Couée, 2015). Kembel et al. (2014) demonstrated across 17 neotropical tree species that leaf nitrogen and phosphorus concentrations were significantly correlated with phyllosphere bacterial community composition, and Laforest-Lapointe et al. (2016) similarly identified host species identity and associated leaf traits as major drivers of temperate tree phyllosphere bacterial structure.

This study conducted an analysis and summary on different varieties of poplar trees, covering aspects such as the nutrient content and distribution of leaves, the structure and function of the inter-leaf microbial community, as well as the composition and dynamic changes of the overall microbial community and the key influencing factors. The following conclusions were drawn.

In terms of leaf nutrient content, the contents of total phosphorus, soluble sugar, and starch were higher in sample Y3, indicating that sample Y3 has stronger photosynthetic and metabolic capabilities as well as osmotic regulation capabilities. The contents of total carbon and total nitrogen were the highest in sample Y3, suggesting that the metabolic capacity and nutrient absorption ability of the Y3 sample are stronger.

The α-diversity analysis revealed that cultivar differences significantly affected species richness but not overall community diversity of the phyllosphere microbiome. For the fungal community, the Chao1 richness index differed significantly among the four cultivars (p = 0.0074), with Y2 exhibiting the highest fungal species richness and Y1 the lowest, whereas the Shannon diversity index showed no significant difference among cultivars (p = 0.52). For the bacterial community, the Chao1 richness index also differed significantly (p = 0.041), with Y4 showing the highest bacterial species richness and Y2 the lowest, while the Shannon diversity index did not reach a significant level (p = 0.13). These results indicate that poplar cultivar differences primarily regulate the number of microbial taxa colonizing the phyllosphere, without significantly altering the evenness and overall diversity distribution within the community. Notably, the contrasting richness patterns between fungi and bacteria—Y2 supporting the highest fungal richness but the lowest bacterial richness—suggest that the two microbial kingdoms respond to different facets of the host leaf environment.

The phyllosphere microbial communities of the four poplar cultivars were dominated by Ascomycota and Basidiomycota for fungi, and Proteobacteria and Actinobacteriota for bacteria, but the relative abundances of these dominant phyla varied substantially among cultivars. Specifically, Proteobacteria was most abundant in Y3, whereas Actinobacteriota peaked in Y2; Ascomycota was most dominant in Y1, while Basidiomycota reached its highest relative abundance in Y2. This phylum-level turnover among cultivars demonstrates that host identity quantitatively reshapes the conserved core phyllosphere microbiome, rather than all dominant taxa responding uniformly to a single cultivar.

Through correlation analysis, it can be found that in the composition of the inter-leaf microbial community, total phosphorus, total nitrogen, soluble sugar, and starch all have a significant impact on the microbial community. Especially, total phosphorus and total nitrogen have the most significant overall impact on the composition of the inter-leaf microbial community.