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Article

The Assembly Mechanisms of Arbuscular Mycorrhizal Fungi in Urban Green Spaces and Their Response to Environmental Factors

by
Jianhui Guo
1,*,
Yue Xin
1,
Xueying Li
2,
Yiming Sun
1,
Yue Hu
1 and
Jingfei Wang
1
1
College of Fine Arts, Henan University, Kaifeng 475001, China
2
College of Life Sciences, Henan Agricultural University, No.63 Agricultural Road, Zhengzhou 450002, China
*
Author to whom correspondence should be addressed.
Diversity 2025, 17(6), 425; https://doi.org/10.3390/d17060425
Submission received: 29 April 2025 / Revised: 9 June 2025 / Accepted: 13 June 2025 / Published: 16 June 2025
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Abstract

:
Urban green spaces are integral components of city ecosystems, supporting essential belowground microbial communities such as arbuscular mycorrhizal fungi (AMF). Understanding how green space types influence AMF communities is key to promoting urban ecological function. This study examines AMF diversity, community assembly, and co-occurrence network structures in two urban green space types—park and roadside—in Kaifeng, Henan Province, China. Soil samples were collected from both sites, and AMF community composition was assessed using high-throughput sequencing. Environmental variables, including total nitrogen (TN), available phosphorus (AP), available potassium (AK), water content, and pH, were measured to evaluate their influence on AMF communities. The results indicate marked differences between the two green space types. Park soils support significantly greater AMF species richness and more complex co-occurrence networks than roadside soils. These differences are correlated with higher nutrient levels in park soils. By contrast, AMF communities in roadside soils are more strongly associated with soil water content and pH, resulting in reduced diversity and more homogeneous community structures. Stochastic processes predominantly govern community assembly in both green space types, with roadside green spaces being more influenced by stochastic processes than park green spaces. These findings highlight the influence of urban landscape type on AMF communities and provide guidance for enhancing urban biodiversity through targeted landscape planning and soil management. In future work, we will implement long-term AMF monitoring across different green-space types and evaluate specific management practices to optimize soil health and ecosystem resilience.

1. Introduction

Urban green spaces function as essential ecological units, significantly contributing to the improvement of air quality, regulation of microclimates, enhancement of biodiversity, and facilitation of carbon sequestration [1,2]. The primary objective of green space management is to maximize ecological benefits, optimize plant growth conditions, and maintain soil ecosystem stability [3]. However, current management practices predominantly emphasize plant species composition, landscape aesthetics, and infrastructure maintenance [4]. In contrast, relatively limited attention has been directed toward soil microbial communities.
Soil microorganisms play a vital role in maintaining ecosystem function and facilitating plant growth [5]. Among these microorganisms, arbuscular mycorrhizal fungi (AMF), one of the most prevalent symbiotic fungi, establish mutualistic associations with the majority of terrestrial plants [6]. AMF secrete signaling molecules—lipo-chitooligosaccharides (LCOs)—which are recognized by plant receptors to activate the signaling pathways required for symbiosis establishment [7]. In addition, AMF enhance the uptake of water and essential nutrients by host plants through their extensive hyphal networks, promote plant resilience to drought, salinity, and soil-borne pathogens, and significantly contribute to soil aggregation and nutrient cycling [8]. These ecological functions highlight the critical role of AMF in sustaining ecosystem stability [9]. A comprehensive understanding of AMF community composition and the environmental factors influencing their distribution is therefore essential.
Urban green spaces comprise various types, each characterized by different environmental conditions and management strategies. For example, park green spaces typically exhibit greater vegetation diversity and richer soil nutrients, supported by intensive management practices such as regular pruning, irrigation, fertilization, and soil amendments [10]. In contrast, roadside green spaces face more severe anthropogenic disturbances, including traffic-related pollution, soil compaction, and water stress. These stressors often result in degraded soil conditions and require broader, less targeted management approaches [11]. Such differences may significantly influence AMF diversity, co-existence patterns, and assembly mechanisms [12]. Currently, the assembly of AMF communities is influenced by both deterministic processes (such as environmental filtering and species interactions) and stochastic processes (including random dispersal, extinction, and chance events) [13]. However, due to differences in soil properties and spatial factors across regions, significant variations exist in the assembly processes of AMF communities [14]. However, research on AMF community structure and ecological adaptation across various urban green space types remains limited [15]. In particular, whether AMF co-existence mechanisms differ between park and roadside green spaces remains unclear.
In this study, high-throughput sequencing technology was employed to characterize the structure and diversity of AMF communities in soils from park and roadside green spaces. By incorporating soil physicochemical properties, we identified the key environmental factors influencing AMF community composition. Furthermore, we investigated the mechanisms driving AMF community assembly. The main objectives of this study were to (1) determine whether significant differences exist in AMF community structure and diversity between park and roadside green spaces; (2) identify the key environmental factors driving variations in AMF communities; and (3) investigate the relative contributions of deterministic and stochastic processes to AMF community assembly. This research enhances our understanding of the ecological functions of AMF within urban green space ecosystems and contributes to the development of informed and sustainable management practices.

2. Materials and Methods

2.1. Study Area

Kaifeng City is situated in the central-eastern region of Henan Province (34°23′–35°01′ N, 114°30′–115°15′ E), within the eastern part of the North China Plain [16]. The topography is predominantly flat, with elevations ranging from 70 to 80 m. Kaifeng experiences a warm temperate monsoon climate characterized by four distinct seasons. The average annual temperature is approximately 14 °C, with January being the coldest month, averaging −0.5 °C, and July the hottest, with an average of 27.5 °C [17]. Annually, the city receives about 600 mm of precipitation, primarily occurring between June and September, whereas annual evaporation reaches 1800 mm. This disparity results in a transition of the region from a semi-humid to a semi-arid climate [18,19].
Kaifeng features a well-structured system of green spaces, comprising roadside green areas, urban parks, and riverfront ecological belts, which play a critical role in sustaining the urban ecological environment [20]. Roadside green spaces are primarily located along major thoroughfares and street medians, whereas park green spaces are more centralized, exhibiting relatively stable ecological conditions and greater vegetation diversity [2].

2.2. Sampling Design and Determination of the Physical and Chemical Properties of Soil

A total of 18 sampling plots were established within urban green spaces of Kaifeng, consisting of 9 plots in park green areas and 9 in roadside green spaces. Each plot measured 10 m × 10 m (Figure 1). The vegetation primarily included trees and herbaceous plants, exhibiting consistent community types and dominant species across the plots. Ligustrum lucidum was identified as the dominant tree species, whereas Cynodon dactylon was predominant in the herbaceous layer.
In this study, urban green spaces with an area exceeding 1 hectare and a vegetation establishment period of more than three years were selected as sampling sites. A total of 18 sampling plots were established within these green spaces. At each site, one 10 m × 10 m plot was set up for vegetation investigation and soil sampling. To minimize spatial autocorrelation and ensure sampling independence, all plots were located at least 1 km apart. Within each 10 m × 10 m plot, all woody plants with a diameter at breast height (DBH) greater than 1 cm were identified, tagged, measured, and recorded by species and individual count. Each plot was further subdivided into four 5 m × 5 m subplots. In each subplot, a 1 m × 1 m quadrat was established to investigate herbaceous vegetation. All herbaceous species and individuals within these quadrats were recorded. Species richness of both woody and herbaceous plants was calculated at the 10 m × 10 m plot level and used in subsequent ecological analyses.
Following the removal of surface debris, soil samples were collected from a depth of 20 cm using the five-point sampling method. The samples were processed through a 2 mm sieve to eliminate debris and stones, resulting in a representative soil sample for each plot. A portion of the soil sample was transferred into 5 mL centrifuge tubes, stored in an icebox, and transported to the laboratory for high-throughput sequencing. Additionally, a subsample was placed in sterile sealed bags for soil physicochemical analysis [21]. A total of 18 soil samples were collected, including 9 from park green spaces and 9 from roadside green spaces. Rarefaction curve analysis confirmed that the sampling effort was sufficient to robustly capture the diversity patterns of AMF communities (Supplementary Figure S1).
Soil samples were dried to a constant weight and sieved through a 60-mesh sieve prior to analysis. Soil pH was measured using a 1 M KCl solution at a 1:2.5 ratio [22]. Soil organic matter (SOM) was determined via the dichromate oxidation method [23], total nitrogen (TN) was assessed using the Kjeldahl method [23], available phosphorus (AP) was measured with the molybdenum-blue colorimetric method, and available potassium (AK) was quantified using flame photometry [23]. Soil water content (SWC) was determined by oven-drying at 105 °C for 24 h [24].

2.3. Determination of Soil AMF Community

Total DNA from AMF communities in soil samples was extracted using the DNeasy PowerSoil Kit (QIAGEN, Hilden, North Rhine-Westphalia, Germany) [25]. DNA concentration and purity were quantified using a NanoDrop2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), and DNA integrity was evaluated via 1% agarose gel electrophoresis [26]. The AMF internal transcribed spacer (ITS) region was amplified using the primer pair AMV4-5NF and AMDGR [27]. Polymerase chain reaction (PCR) products were verified via 2% agarose gel electrophoresis, purified utilizing the AxyPrep DNA Gel Extraction Kit (Axygen, Corning Inc., Union City, CA, USA), and quantified using the QuantiFluor™-ST (Promega Corporation, Madison, WI, USA) blue fluorescence quantification system [15].
The library construction was conducted using the NEXTFLEX Rapid DNA-Seq Kit (PerkinElmer, Inc., Waltham, MA, USA), followed by sequencing on the Illumina platform (Illumina, Inc., San Diego, CA, USA). The sequencing procedure entailed DNA fragment immobilization on a chip, bridge amplification, linearization, fluorescently labeled dNTP extension, and fluorescence signal detection. The raw sequences were quality-filtered using Trimmomatic, merged using Flash, and clustered into operational taxonomic units (OTUs) at a 97% similarity threshold using Uparse. Chimeric sequences were eliminated, and an OTU table was compiled. Taxonomic classification was performed using the Unite fungal database and the RDP classifier in the Qiime platform, with a confidence threshold of 0.7 [15].

2.4. Statistical Analyses

To illustrate the relative abundances of AMF across various taxonomic levels (order, family, genus, and species) in different types of urban green spaces, stacked bar charts were constructed utilizing the “ggplot2” package in R (version 4.4.2) [28]. Bray–Curtis non-metric multidimensional scaling (NMDS) was employed to assess variations in fungal community composition across different green space types [29]. The goodness-of-fit of the NMDS ordination was evaluated using stress values, with values below 0.2 indicating a reliable representation of community dissimilarity [30]. A Venn diagram was created using the “Venndiagram (version 4.4.2)” package to illustrate the number of unique and shared OTUs among different green space types [31]. For the alpha diversity analysis, species richness and the Shannon–Wiener index were calculated utilizing the “picante” and “vegan” packages, with boxplots employed to visually present differences in AMF taxon richness [32]. The Wilcoxon method was used for statistical analysis of these differences (p < 0.05 considered significant) [33]. A co-occurrence network analysis was conducted by calculating Spearman correlations between OTUs, with the network constructed using the “igraph” package. The visualization of co-occurrence networks was executed using Gephi (0.10.1) to elucidate species associations and topological network structures [34]. The DCA results showed that the gradient length of the first axis was greater than 4, indicating that the community data were suitable for canonical correspondence analysis (CCA) [35].
A permutation test with 999 iterations was performed to evaluate the association between sample distribution and environmental factors [36]. To quantify the contribution of various ecological processes to AMF community assembly in different green space types, β-nearest taxon index (βNTI) analysis was applied [36,37]. The βNTI metric describes phylogenetic turnover in community composition over space and time, where |βNTI| > 2 indicates that community turnover is primarily driven by deterministic processes (environmental filtering), with βNTI > 2 suggesting heterogeneous selection (variations in environmental conditions drive community divergence) and βNTI < −2 indicating homogeneous selection (similar environmental conditions lead to community convergence), whereas |βNTI| < 2 suggests that stochastic processes (e.g., dispersal-driven processes) dominate community assembly [38]. Furthermore, RCBray < 0.95 represents a homogeneous dispersal process, RCBray > 0.95 indicates dispersal limitation, and |βNTI| < 0.95 suggests no dominant process [39,40].

3. Results

3.1. Differences in AMF Community Composition Across Green Space Types

The taxonomic composition of AMF communities exhibited significant differences between park green spaces and roadside green spaces, spanning multiple taxonomic levels including order, family, genus, and species. At the order level (Figure 2A), both green space types were dominated by Glomerales and unclassified groups, with Glomerales being slightly more abundant in park green spaces (65.60%) than in roadside green spaces (63.20%). At the family level (Figure 2B), Glomeraceae and unclassified groups were dominant in both habitats, with Glomeraceae being more prevalent in roadside green spaces (63.20%) compared to park green spaces (2.08%). At the genus level (Figure 2C), Acaulospora and Pacispora were exclusively found in park green spaces. The relative abundance of Glomus was higher in roadside green spaces (63.42%) than in park green spaces (2.03%). At the species level (Figure 2D), unclassified taxa accounted for the highest proportions in both green space types, with 62.43% in parks and 55.00% in roadsides.

3.2. Differences in AMF Community Structure Across Urban Green Space Types

A NMDS analysis revealed significant differences in AMF community structure between park green spaces and roadside green spaces, with a stress value of 0.19, indicating a reliable ordination (Figure 3A). The Venn diagram illustrated that park green spaces contained 128 unique AMF species, whereas roadside green spaces contained 82 unique species. A total of 153 species were shared between the two green space types (Figure 3B). The species richness boxplot indicated that AMF communities in park green spaces exhibited significantly higher species richness than those in roadside green spaces (Figure 3C). Similarly, the Shannon index was consistently higher in park green spaces compared to roadside green spaces, suggesting greater AMF diversity in park environments (Figure 3D).

3.3. Community Assembly Processes of AMF in Different Green Space Types

The βNTI values for AMF communities in both park green spaces and roadside green spaces were predominantly distributed between −2 and 2, whereas RCBray values primarily ranged from 0.95 to 0.95. These patterns indicate that stochastic processes were the primary forces shaping AMF community assembly in both green space types. Further quantification based on the null model framework demonstrated that undominated stochastic processes predominantly drove community assembly across both roadside and park green spaces (Figure 4). Homogeneous dispersal was identified as a secondary process contributing to community structure. Notably, stochastic processes exerted a relatively stronger influence on AMF communities in roadside green spaces compared to park green spaces, suggesting an increased degree of randomness in assembly mechanisms under roadside conditions.

3.4. Co-Occurrence Patterns of AMF Communities in Different Urban Green Spaces

The AMF co-occurrence network was constructed using the complete AMF dataset and was partitioned into nine modules (Figure 5A). The modularity of the network reflects its structural complexity and ecological stability. Modules 1, 3, 5, and 8 were primarily associated with park green spaces, whereas modules 2, 4, and 6 were more closely related to roadside green spaces. Modules 7 and 9 exhibited a more balanced distribution across both green space types.
Clear structural differences were observed in the co-occurrence networks between park and roadside green spaces (Figure 5B). The network in park green spaces contained a greater number of nodes (283) compared to that in roadside green spaces (219). Similarly, the number of edges was higher in park green spaces (1803) than in roadside green spaces (1610), indicating a denser network. However, the average degree, which represents the average number of connections per node, was greater in roadside green spaces (14.703) than in park green spaces (12.742), suggesting tighter local connectivity in roadside environments. Additionally, the modularity index, which measures the extent to which the network can be divided into separate modules, was higher in park green spaces (0.858) than in roadside green spaces (0.810), reflecting a more compartmentalized network structure. In contrast, the average clustering coefficient, indicating the tendency of nodes to form tightly connected clusters, was greater in roadside green spaces (0.922) than in park green spaces (0.833).

3.5. Correlation of AMF Communities with Soil Environmental Factors in Different Urban Green Spaces

The CCA results showed a clear separation between park green spaces and roadside green spaces along the first two canonical axes (CCA1: 19.6%, CCA2: 13.4%), which together explained 33.0% of the total variation in AMF community composition constrained by environmental factors (Figure 6). Among all measured environmental variables, soil pH had the strongest influence on community distribution, explaining the largest proportion of variation (64.8%). This finding was further supported by permutation tests, in which pH exhibited the highest R² value (>0.8) and was highly significant (p < 0.001). In addition, soil water content (SWC) and total nitrogen (TN) were also significantly associated with community structure (p < 0.05).
The AMF community composition was influenced by different environmental factors across the two types of green spaces. In park green spaces, community variation was mainly associated with pH, SWC, SOM, and plant richness. In contrast, in roadside green spaces, AP and TN were the dominant environmental drivers shaping the AMF community structure.

4. Discussion

4.1. Differences in AMF Community Structure and Diversity Across Different Green Space Types

This study identifies significant compositional differences in AMF communities across taxonomic levels between two types of urban green spaces [32]. These results suggest that the two green space types provide distinct habitat conditions that shape AMF community structure and the distribution of dominant taxa. In terms of species richness, park green spaces harbor significantly more AMF species than roadside green spaces, with 128 unique species identified in the former and 82 in the latter. This difference suggests that environmental conditions in park green spaces are more favorable for sustaining AMF diversity, potentially due to greater soil nutrient availability [41,42].
The management practices of park and roadside green spaces may be critical factors contributing to the significant differences observed in AMF community composition and diversity [41,42]. In comparison to roadside green spaces, park green spaces typically benefit from more refined management practices, including regular fertilization, appropriate irrigation, and periodic vegetation renewal. These practices help maintain a more stable physico-chemical environment [43], thereby providing more favorable habitats for the maintenance and proliferation of AMF. In addition, the greater plant species diversity in park green spaces offers a broader range of potential host plants for AMF, supporting higher community diversity and structural complexity [44]. Conversely, roadside green spaces are more frequently subjected to anthropogenic disturbances, such as soil compaction, vehicular pollution, and inconsistent soil management. These factors diminish the availability of water and nutrients, directly limiting the development and structural differentiation of AMF communities [45]. Compared to park green spaces, roadside environments are also more exposed to external stressors such as drought, runoff erosion, and pollutant deposition. These conditions tend to homogenize the AMF community and contribute to reduced species richness. Therefore, AMF communities in roadside green spaces exhibit less diversity and complexity than those in park green spaces, which benefit from more intensive management and richer vegetation [46]. In addition to the factors mentioned above, climatic conditions [47], spatial and geographical factors [48], and environmental pollution [49] can also influence the composition of AMF communities.
Furthermore, the study revealed that AMF communities in park and roadside green spaces are shaped by different key soil environmental factors, consistent with previous research findings [50]. The CCA results showed that in park green spaces, pH, soil water content (SWC), soil organic matter (SOM) and plant richness had the greatest influence on AMF community composition. In contrast, the AMF community structure in roadside green spaces was primarily shaped by available phosphorus (AP) and total nitrogen (TN). This may be because nutrient levels such as TN and available phosphorus (AP) determine the extent of mutual benefits in plant–fungus symbiosis [51,52]. In organic farming systems where available phosphorus is limited, plants tend to rely more heavily on AMF to acquire and supply phosphorus and other nutrients [53]. In addition, soil pH not only directly affects the physiological state and ecological niche of fungi, but also indirectly influences fungal communities by regulating the availability of nutrients [54]. Water, as a medium for transporting nutrients and metabolites, plays a key role in AMF nutrient uptake in soils [55]. As obligate symbionts [56], AMF require host plants to complete their life cycle [57] and depend on them for resource acquisition [58]. These findings indicate that plant richness plays an important role in influencing AMF communities. As obligate symbiotic fungi, AMF benefit from plant root exudates—such as organic acids, enzymes, and signaling molecules—which provide chemical cues and nutritional support, thereby promoting symbiotic diversity [59]. Plant roots are sensitive to changes in soil conditions and are the first biological structures to be affected by the soil environment, playing a crucial role in maintaining normal plant growth [60]. Therefore, differences in plant composition between urban parks and roadside green spaces play a determining role in shaping soil microbial communities.

4.2. AMF Community Structure and Assembly Mechanisms in Different Urban Types of Green Spaces

The co-occurrence network analysis revealed notable differences in the AMF community structures between park and roadside green spaces. Specifically, the AMF community in roadside green spaces exhibited relative homogeneity and stability. In contrast, the AMF community in park green spaces demonstrated higher spatial heterogeneity. This contrast may be attributed to variations in long-term management practices and environmental conditions [61]. The homogeneity observed in roadside green spaces may result from frequent anthropogenic disturbances, such as soil compaction and pollutant deposition. These disturbances contribute to community stability but may also limit species diversity. In comparison, park green spaces typically include a greater variety of vegetation types and benefit from refined management practices, including regular fertilization and planned landscaping. These factors can enhance species richness and spatial heterogeneity in AMF communities. Furthermore, roadside green spaces tend to experience heightened environmental stress and maintain more uniform vegetation types. These conditions may amplify the role of environmental filtering, leading to reduced diversity whereas promoting structural uniformity. Conversely, park green spaces provide improved soil conditions and greater resource availability. These features facilitate complex interactions among AMF species and support increased community richness.
The study also investigated the assembly mechanisms of AMF communities utilizing a null model framework. The results indicated that stochastic processes played a more dominant role than deterministic processes in community assembly across both types of green spaces [62,63]. However, stochastic processes were more prevalent in roadside green spaces compared to park green spaces, suggesting a reduced influence of environmental filtering in roadside areas. In contrast, AMF communities within park green spaces exhibited higher species richness and a more complex and stable network structure. These communities were more strongly affected by soil nutrient conditions, including soil TN, soil AP, and soil AK [64]. The elevated nutrient levels in parks likely enhanced environmental filtering, favoring species adapted to nutrient-rich habitats, thereby promoting community complexity and stability [65]. Conversely, the AMF community in roadside green spaces demonstrated lower diversity and greater homogeneity. Its structure was relatively unstable and strongly constrained by SWC and soil pH. This instability was likely exacerbated by poor soil nutrient availability and heightened anthropogenic disturbances. These conditions diminished the effects of environmental filtering, rendering the community more susceptible to random events such as dispersal and local extinction. Therefore, the AMF community became more homogenized and less stable [66]. In summary, AMF community assembly in park green spaces is more influenced by environmental factors, particularly soil nutrients such as total nitrogen (TN). In contrast, assembly in roadside green spaces is primarily shaped by stochastic processes. These differences contribute to the observed variation in species diversity, community stability, and spatial heterogeneity between the two types of urban green spaces.

5. Conclusions

This study examines the responses of AMF community assembly mechanisms to various environmental factors in different types of urban green spaces. The results reveal significant differences in AMF community composition between park and roadside green spaces. In park green spaces, AMF communities are primarily influenced by soil nutrients, whereas soil moisture and soil pH serve as the main limiting factors in roadside green spaces. Compared to park green spaces, the community structure in roadside green spaces is more homogeneous and stable, whereas park green spaces exhibit higher spatial heterogeneity. Furthermore, stochastic processes play a more dominant role in shaping AMF communities in roadside green spaces, whereas environmental filtering is more prominent in park green spaces. These findings enhance our understanding of how different types of urban green spaces influence AMF community dynamics through varied ecological processes. This study contributes to the expanding field of urban microbial biogeography and offers practical insights for improving soil health and ecological stability through informed and targeted green space planning and management. In future research, we will focus on a greater variety of green space types and monitor more environmental factors (e.g., heavy metals and urban microclimate) to conduct more in-depth studies.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/d17060425/s1, Figure S1: Rarefaction curves of AMF richness in roadside and park green spaces.

Author Contributions

J.G.: Investigation, Formal analysis, Data curation, Funding acquisition. Y.X.: Investigation, Software, Validation, Formal analysis, Writing—original draft. X.L.: Methodology, Writing-review and editing. Y.S.: Formal analysis, Data curation. Y.H.: Formal analysis, Data curation. J.W.: Formal analysis, Data curation. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Special Project on Cultural Research for the Revitalization of Culture Project in Henan Province (2023XWH130), the Graduate Education Reform Project of Henan Province (2023SJGLX256Y), and the Postgraduate Education and Teaching Reform and Quality Enhancement Project of Henan University (SYL2025YJSKC10).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data analyzed in this study are included within the paper.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Study area map. Left panel shows the geographic location of Kaifeng City in China, marked by a red star. Right panel displays the distribution of sampling sites, where yellow dots indicate roadside green spaces and blue dots indicate park green spaces.
Figure 1. Study area map. Left panel shows the geographic location of Kaifeng City in China, marked by a red star. Right panel displays the distribution of sampling sites, where yellow dots indicate roadside green spaces and blue dots indicate park green spaces.
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Figure 2. Differences in the composition of AMF communities between park green spaces and roadside green spaces at the order, family, genus, and species levels. (A) Relative abundance of AMF at the order level in different green space types. (B) Relative abundance of AMF at the family level in different green space types. (C) Relative abundance of AMF at the genus level in different green space types. (D) Relative abundance of AMF at the species level in different green space types.
Figure 2. Differences in the composition of AMF communities between park green spaces and roadside green spaces at the order, family, genus, and species levels. (A) Relative abundance of AMF at the order level in different green space types. (B) Relative abundance of AMF at the family level in different green space types. (C) Relative abundance of AMF at the genus level in different green space types. (D) Relative abundance of AMF at the species level in different green space types.
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Figure 3. Comparative analysis of AMF community structure and diversity across different urban green space types. (A) Non-metric multidimensional scaling (NMDS) based on Bray–Curtis dissimilarity to assess differences in AMF community structure, with various colors representing different types of green spaces. (B) Venn diagram illustrating AMF OTUs in various urban green spaces, where numbers indicate the count of unique or shared OTUs. (C) Box plot depicting species richness, comparing the distribution of AMF species richness across different green space types. (D) Box plot of the Shannon index, employing the Wilcoxon rank-sum test to compare α-diversity among different green space types.
Figure 3. Comparative analysis of AMF community structure and diversity across different urban green space types. (A) Non-metric multidimensional scaling (NMDS) based on Bray–Curtis dissimilarity to assess differences in AMF community structure, with various colors representing different types of green spaces. (B) Venn diagram illustrating AMF OTUs in various urban green spaces, where numbers indicate the count of unique or shared OTUs. (C) Box plot depicting species richness, comparing the distribution of AMF species richness across different green space types. (D) Box plot of the Shannon index, employing the Wilcoxon rank-sum test to compare α-diversity among different green space types.
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Figure 4. The ecological processes of AMF communities in urban green spaces. The outer circle represents the contribution proportion of community assembly, while the inner circle indicates the specific ecological processes.
Figure 4. The ecological processes of AMF communities in urban green spaces. The outer circle represents the contribution proportion of community assembly, while the inner circle indicates the specific ecological processes.
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Figure 5. Co-occurrence network of AMF communities in urban green spaces. (A) Each node’s color represents an OTU, and green lines indicate negative correlations (SparCC |r| > 0.6; p < 0.05). (B) Network topological characteristics of AMF communities in urban green spaces.
Figure 5. Co-occurrence network of AMF communities in urban green spaces. (A) Each node’s color represents an OTU, and green lines indicate negative correlations (SparCC |r| > 0.6; p < 0.05). (B) Network topological characteristics of AMF communities in urban green spaces.
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Figure 6. Correlation analysis between arbuscular mycorrhizal fungal (AMF) communities and environmental factors in urban green spaces. The left panel shows canonical correspondence analysis (CCA) results illustrating the relationships between AMF community composition and key soil environmental factors across two types of urban green spaces: roadside green spaces and park green spaces. Each point represents a sample, and red arrows indicate environmental variables (AK: available potassium; AP: available phosphorus; pH: soil acidity/alkalinity; SOM: soil organic matter; SWC: soil water content; TN: total nitrogen). The length of each arrow reflects the relative influence of the corresponding factor on AMF community structure. The right panel displays the explanatory power (R²) of each environmental variable on AMF community variation. Asterisks indicate levels of statistical significance (* p < 0.05, *** p < 0.001).
Figure 6. Correlation analysis between arbuscular mycorrhizal fungal (AMF) communities and environmental factors in urban green spaces. The left panel shows canonical correspondence analysis (CCA) results illustrating the relationships between AMF community composition and key soil environmental factors across two types of urban green spaces: roadside green spaces and park green spaces. Each point represents a sample, and red arrows indicate environmental variables (AK: available potassium; AP: available phosphorus; pH: soil acidity/alkalinity; SOM: soil organic matter; SWC: soil water content; TN: total nitrogen). The length of each arrow reflects the relative influence of the corresponding factor on AMF community structure. The right panel displays the explanatory power (R²) of each environmental variable on AMF community variation. Asterisks indicate levels of statistical significance (* p < 0.05, *** p < 0.001).
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Guo, J.; Xin, Y.; Li, X.; Sun, Y.; Hu, Y.; Wang, J. The Assembly Mechanisms of Arbuscular Mycorrhizal Fungi in Urban Green Spaces and Their Response to Environmental Factors. Diversity 2025, 17, 425. https://doi.org/10.3390/d17060425

AMA Style

Guo J, Xin Y, Li X, Sun Y, Hu Y, Wang J. The Assembly Mechanisms of Arbuscular Mycorrhizal Fungi in Urban Green Spaces and Their Response to Environmental Factors. Diversity. 2025; 17(6):425. https://doi.org/10.3390/d17060425

Chicago/Turabian Style

Guo, Jianhui, Yue Xin, Xueying Li, Yiming Sun, Yue Hu, and Jingfei Wang. 2025. "The Assembly Mechanisms of Arbuscular Mycorrhizal Fungi in Urban Green Spaces and Their Response to Environmental Factors" Diversity 17, no. 6: 425. https://doi.org/10.3390/d17060425

APA Style

Guo, J., Xin, Y., Li, X., Sun, Y., Hu, Y., & Wang, J. (2025). The Assembly Mechanisms of Arbuscular Mycorrhizal Fungi in Urban Green Spaces and Their Response to Environmental Factors. Diversity, 17(6), 425. https://doi.org/10.3390/d17060425

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