Relationship Between Tree Species Diversity and Soil Ecological Biochemistry Characteristics in Urban Wetland: A Case Study of International Important Wetland in Hangzhou, China
1
Hangzhou Xixi National Wetland Park Ecology & Culture Research Center, Hangzhou 310012, China
2
Zhejiang Xixi Wetland Ecosystem Research Station, Hangzhou 310012, China
3
Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China
4
College of Life Sciences, Zhejiang University, Hangzhou 310012, China
5
East China Survey and Planning Institute of National Forestry and Grassland Administration, Hangzhou 311300, China
*
Author to whom correspondence should be addressed.
Diversity 2025, 17(12), 817; https://doi.org/10.3390/d17120817
Submission received: 27 September 2025
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Revised: 21 November 2025
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Accepted: 22 November 2025
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Published: 27 November 2025
(This article belongs to the Section Plant Diversity)
Abstract
Tree species diversity in forest ecosystems is crucial for maintaining ecosystem stability and functionality. However, its underlying mechanisms linking to subsurface ecological processes—such as soil nutrient cycling—remain unclear, particularly in urban wetland ecosystems. This study, conducted at Xixi Wetland, an internationally important wetland, also a typical subtropical urban wetland in Hangzhou, Zhejiang Province, China, analyzed the relationship between tree species diversity and soil ecometabolic ratios based on species diversity surveys. Results indicate that mulberry and paper mulberry dominate Xixi Wetland, with diversity indices comparable to other subtropical forests in China. Tree species diversity and soil physicochemical properties showed significant positive correlations with total soil nitrogen and organic carbon, but no significant effect on total phosphorus. Together, tree species diversity and soil physicochemical properties explained 65.88% of the variance in soil ecological–chemical ratios. Tree species diversity significantly influenced soil nitrogen cycling in Xixi Wetland but had limited effects on phosphorus cycling. Enhanced tree species richness not only promotes organic carbon accumulation in coarse aggregates, providing a scientific basis for wetland carbon sink management, but also maintains nutrient cycling stability by strengthening soil resilience to biotic disturbances. This holds significant practical value for ecological design in urban wetland parks. This study provides scientific support for managing subtropical wetland ecosystems.
1. Introduction
Investigating the relationship between biodiversity and ecosystems constitutes a major focus of ecological research [1,2]. Wetland ecosystems harbor rich biodiversity [3], and among them, urban wetlands play a unique role—they are not only important “ecological lungs” for mitigating urban heat islands and purifying water bodies but also face frequent human disturbances (such as tourism activities, infrastructure construction, and landscape management) that easily reshape vegetation composition and soil nutrient status [4]. Unlike natural wetlands, where ecological processes are primarily driven by hydrological and biological factors, urban wetlands like Xixi are characterized by fragmented habitats and sustained anthropogenic input, which may lead to distinct patterns in tree-soil interactions. This makes the exploration of the relationship between tree species diversity and ecosystem functions in urban wetlands a key topic in current wetland ecological research. Tree species diversity in wetland ecosystems plays a crucial role in maintaining both the diversity and functional stability of these ecosystems [5]. Increased tree species diversity enhances interactions within the community vegetation, thereby facilitating the realization of wetland ecosystem functions [6]. However, research findings on the relationship between tree species diversity and ecosystem functions vary across wetland ecosystems of different climatic types [7].
A significant gap exists in global ecosystem research, necessitating cross-ecosystem comparative studies. Specifically, while the importance of biodiversity is well-established, studies focusing on the link between tree species diversity and soil ecological stoichiometry (C:N:P) in urban wetlands remain scarce. Most existing research has concentrated on natural ecosystems or single components within wetlands, leaving a critical gap in understanding the integrated nutrient dynamics within human-dominated wetland parks. To address this gap, ecological stoichiometry provides a powerful tool. Biochemical ratios serve as crucial indicators for revealing wetland ecosystem functions (material cycling and energy flow) [8,9]. In wetland ecosystems, the stoichiometric ratios of carbon (C), nitrogen (N), and phosphorus (P) in plants, soil nutrients, and soil microorganisms effectively characterize soil fertility dynamics, nutrient limitation in plant growth, and litter decomposition rates [10,11]. Xixi National Wetland Park, also known as Xixi International Important Wetland (hereinafter referred to as “XXIIW”), located in Hangzhou, China, is a typical subtropical urban wetland that has maintained a balance between urban development and ecological conservation; it is listed in the Ramsar Convention’s List of Wetlands of International Importance and has representative vegetation communities and soil characteristics of subtropical urban wetlands. Within wetland ecosystems, vegetation, root systems, and soil form a complex and tightly interconnected unity [12]. Investigating soil C, N, and P content and their stoichiometric ratios in relation to tree species biodiversity can better reveal the patterns of nutrient cycling and interrelationships among ecosystem components [13].
In wetland ecosystems, litter, fine roots, soil, and microorganisms form a tightly integrated nutrient cycling network through litter decomposition, root exudation, and microbial activity [14,15]. Plants respond to soil nutrient limitations by enhancing reabsorption capacity, thereby altering leaf nutrient content and influencing litter nutrient composition. Fine roots absorb nutrients from the soil and supply them to the plant body [16]. Overall, a tightly coupled relationship exists between the ecogeochemical characteristics of litter, soil, soil microbial biomass, and fine roots [17]. Investigating tree species diversity and its ecogeochemical traits for C, N, and P in XXIIW helps elucidate the mechanisms of element interactions among trees and soil components in wetland ecosystems. This is crucial for understanding element interactions and balancing mechanisms across different ecosystem components, and for providing a reference for the ecological management of other subtropical urban wetlands.
Investigating the relationship between subtropical tree species diversity and soil chemotrophic traits can reveal underlying mechanisms of element cycling in subtropical wetland ecosystems, providing critical scientific insights for understanding their ecological functions. As tree species diversity varies, differences emerge in litter and fine root characteristics, exerting substantial impacts on soil nutrients and soil microorganisms [17]. Tree species diversity influences microenvironments by altering vegetation cover, canopy structure, and litter layers [18], while increased diversity also elevates soil surface moisture content [19]. During mixed litter decomposition, increased species diversity enhances leaf dry weight loss rates and N loss rates. By diversifying litter types, it provides varied C sources for soil microorganisms, promoting microbial community diversity and accelerating organic matter mineralization [20]. Tree species diversity and soil physicochemical properties significantly influence fine root biomass and turnover rates [21]. Current studies on chemotrophic characteristics primarily focus on single-component ecochemistry in wetland ecosystems. Therefore, it is possible to bridge the gap by quantifying the specific contributions of tree species diversity and soil properties to soil stoichiometric ratios, with a particular focus on the urban wetland context. The integrated approach not only elucidates the mechanisms of nutrient cycling under anthropogenic influence but also provides a scientific basis for ecological management strategies, such as optimizing tree species composition to enhance C sequestration and maintain nutrient balance in urban wetland parks.
In this study, we conducted research on tree species and soil stoichiometry in XXIIW to explore the relationship between soil physicochemical properties and tree species. Specifically, we evaluated the tree species diversity index, dominance index, and soil physicochemical properties in a typical location in XXIIW. The purpose of this study is twofold: (1) to investigate the typical tree species and physicochemical properties of soils at the study site; (2) to quantify the contribution of soil stoichiometry to tree species diversity. We hypothesized that (i) there would be an influence between tree species diversity and C, N, P contents, as well as their stoichiometric ratios, with a hierarchical influence ranking; (ii) tree species diversity in urban wetlands would be potentially enhanced by altering the content or stoichiometric ratios of specific elements in the soil.
2. Materials and Methods
2.1. Study Area Overview and Sampling Methods
XXIIW is located in the western part of Hangzhou City, Zhejiang Province (Figure 1), spanning Xihu District and Yuhang District, approximately 5 km from West Lake. Its geographical coordinates are 30°15′–30°16′ N, 120°02′–120°05′ E, and average elevation is about 1.5 m. The park covers a total area of 10.38 km2 and exhibits a typical subtropical monsoon climate. The annual average temperature ranges between 16 and 17 °C, with annual precipitation between 1400 and 1600 mm, characterized by hot, rainy summers and mild, dry winters [22]. The area is dominated by fish ponds, interspersed with a network of rivers, harbors, lakes, and ponds, narrow pond embankments, and larger islands, forming a typical artificial wetland [23]. XXIIW is China’s first national wetland park integrating urban, agricultural, and cultural elements. Listed in the Ramsar Convention’s List of Wetlands of International Importance in 2009, it holds representative and exemplary value in ecological conservation, scientific research, and public education.
The wetland’s hydrological characteristics reveal a water system primarily composed of natural rivers, artificial ponds, and marshy depressions, forming a unique plain river network system where water bodies cover nearly 70% of the area [24]. Water quality is influenced by both seasonal rainfall variations and artificial management measures, with well-protected ecological zones achieving Class III surface water standards. Ecosystem survey data indicate the presence of 971 vascular plant species within the area, including the nationally protected wild plant Glycine soya, which holds significant conservation value. Additionally, 224 bird species have been recorded, such as the ecological indicator species Garzetta egretta. Together with diverse fish and insect resources, these elements collectively form a complete wetland biotic community. Soil surveys reveal the predominant development of marsh soils and paddy soils. Surface layers exhibit high organic matter content (3–5%), while subsoils consist mainly of clayey textures, displaying typical characteristics of subsoil development. As a representative secondary wetland ecosystem adjacent to urban areas, XXIIW provides an ideal research site for studying the composition, structure, and ecological functions of subtropical wetland ecosystems.
As a typical urban wetland, XXIIW is disturbed by human activities in its central area, which limits the distribution of arbors and sub-arbors. Most of its terrain is made up of pond embankments—these embankments are narrow and overgrown with shrubs, leaving few areas suitable for setting up standard sample plots. To address this, we conducted a full survey of XXIIW’s entire area and selected sample plots based on specific principles: well-preserved plot conditions, minimal human interference, and easy accessibility. Meanwhile, we ensured the selected plots had vegetation with representativeness and originality, a rich spatial hierarchical structure of vegetation, and ecosystems with high biodiversity—all while guaranteeing the feasibility of long-term monitoring and research. Eventually, we picked relatively suitable, typical, and representative wetland arbor communities, along with relatively typical dominant species. The arbors in these 7 sample plots are able to reflect and represent the typical features of arbors in XXIIW.
This study surveyed seven 20 m × 20 m plot units within the evergreen broadleaf forest in 2024 (Table 1). For each plot, all woody plants with a diameter at breast height (DBH) ≥ 5 cm were recorded by tree count and species name, with measurements of canopy cover, height, and species identification. Within each plot, five soil samples were collected from the 0 to 20 cm topsoil layer using a soil ring knife at five locations. These samples were mixed and placed into soil bags for subsequent determination of soil indicators, including soil organic carbon (SOC), total carbon (TC), total nitrogen (TN), and total phosphorus (TP). Three replicates were measured for each soil sample.
2.2. Method for Calculating Tree Species Diversity Index
The tree species diversity index is calculated using the number of tree species, with the formula as follows:
Richness Index R = S,
Shannon–Wiener Diversity Index H’ = −∑Pi (lnPi)
Simpson’s Diversity Index D = 1 − ∑Pi2
Pielou Uniformity Index Jsw = H’/lnS
2.3. Methods for Determining Indicators
2.3.1. Soil N Components, C and P Contents
Soil TN content was determined using the Kjeldahl method, ammonium nitrogen (NH4+-N) content was determined using the indophenol blue colorimetric method, nitrate nitrogen (NO3−-N) was measured using a UV spectrophotometer, and dissolved organic nitrogen (DON) was calculated as the difference between soluble TN and inorganic nitrogen. Soil organic carbon content (TOC, equal to SOC) was determined using the potassium permanganate oxidation method; TP was measured using the molybdenum-antimony colorimetric method.
2.3.2. Soil Physicochemical Properties
Soil bulk density (BD) was measured using the ring-cutting method, soil moisture (SM) was determined by air-drying, soil pH was measured with a pH meter, and soil electrical conductivity (EC) was assessed using an EC meter.
2.4. Data Analysis Methods
SPSS 25.0 statistical software was used to perform one-way analysis of variance (ANOVA) to compare differences in soil N components across tree species diversity gradients. Pearson correlation analysis was used to examine relationships between tree species diversity (H’, D, and Jsw), tree diameter at breast height (DBH), soil physicochemical properties (BD, soil moisture content (MC), pH, and EC), and soil C, N, and N component indices; Employed R software (R 4.5.0, DescTools package) to conduct variance analysis of the relative explanatory power of these indicators on soil N component variation; Used redundancy analysis (RDA) (OriginPro 2024b) to rank the explanatory power of tree species diversity, DBH, and soil physicochemical indicators on soil N components.
3. Results
3.1. Species Composition Analysis
XXSD-S07 exhibited the highest Richness (22) and Pielou evenness (0.69) due to its abundant species count and uniform individual distribution. XXSD-S05 demonstrated the highest Shannon (1.57) and Simpson (0.62) indices, attributed to its larger species count (12) and more balanced species distribution (Table 2). In the tree layer survey of seven long-term monitoring plots (XXSD-S01 to XXSD-S07) in XXIIW, a total of 482 woody plant individuals with DBH ≥ 1 cm were recorded, belonging to 29 species across 29 genera and 25 families (Table 3). Moraceae (Morus spp.) exhibited the highest proportion (26.76%), followed by paper mulberry (Broussonetia papyrifera, 17.43%). Species abundance exhibited significant spatial heterogeneity across plots: Plot XXSD-S01 had the highest density (149 individuals), while Plot XXSD-S06 recorded only 18 individuals, reflecting the regulatory role of wetland microhabitats on plant community structure.
3.2. Correlation Between Tree Species Diversity, Soil Physicochemical Properties, and Chemical Ratios
Soil C content showed extremely significant positive correlations (p < 0.001) with soil N content, soil C:N ratio, and soil C:P ratio. It exhibited strongly significant positive correlations (p < 0.01) with soil NH4+-N content and significant positive correlations (p < 0.05) with soil NO3−-N content and soil pH. Soil N:P showed a highly significant positive correlation with soil N content (p < 0.01). Soil C:P and soil N:P exhibited extremely significant negative correlations with soil P content (p < 0.001). Soil C:P and soil N:P demonstrated extremely significant positive correlations (p < 0.001) (Figure 2).
Analyze the soil nutrient indicators (TN, TOC, TP, and their ratios) of 7 plots (S01 to S07) (Table 4 and Table 5). The TN content ranges from 2.06 to 22.03 g/kg, with Pterocarya stenoptera-Broussonetia papyrifera community being significantly the highest (22.03) and Pterocarya stenoptera-Ulmus parvifolia community being significantly the lowest (2.06). There was a significant difference in TOC (1.46–34.19 g/kg), with Cinnamomum camphorum-Pterocarya stenoptera community being the highest (34.19) and Cinnamomum camphorum-Prunus mume community being the lowest (1.46). The TP range is 0.57–0.94 g/kg, with Cinnamomum camphorum-Pterocarya stenoptera community being the highest (0.94) and Salix matsudana-Morus alba community being the lowest (0.57). The stoichiometric ratio shows that C: N ranges from 9.16 to 13.75, with Morus alba-Broussonetia papyrifera community being the highest; C: The P range is between 20.72 and 37.17, with S03 being the highest (36.67); N: The P range is 2.18–3.49, with Pterocarya stenoptera-Broussonetia papyrifera community being the highest (3.4). The data shows significant heterogeneity (p < 0.05) in nutrient content and ecological stoichiometry characteristics among different points.
3.3. Contribution of Tree Species Diversity and Soil Physicochemical Properties to Stoichiometric Ratios
Using RDA analysis (Figure 2), the top 10 explanatory factors for variations in soil C, N, P content, and their stoichiometric ratios—including soil physicochemical properties, N content, and stoichiometric ratio factors—accounted for 62.20% of the variation. The first axis explained 59.57% of the variance, with the second axis explaining 6.31%. The influencing factors, ranked from highest to lowest explanatory power, were: soil NH4+-N content, soil MC, diversity index, P content, soil C:P ratio, soil pH, and soil C:N ratio. Among these, soil NH4+-N content exhibited the highest explanatory power (9.7%). Its influence, along with soil MC (5.8%), and P content (4.5%), significantly affected variations in soil C, N, P content, and stoichiometric ratios (p < 0.05).
4. Discussion
The content of major soil nutrient elements in wetland ecosystems, particularly C, N, and P, reflects soil fertility and serves as the primary source of nutrients required for plant growth [28]. Soil physical properties such as pH and soil MC primarily indicate soil structure and water-holding capacity [29]. The results of this study indicate that there were no significant differences in soil C, N, P, NO3−-N, NH4+-N content, or soil MC among different sampling sites. Notably, in plots with high tree species diversity gradients, organic layer soil contained higher C, N, and P levels than those with low diversity gradients. Concurrently, average NO3−-N and NH4+-N contents significantly increased (p < 0.01), indicating that tree species diversity substantially promotes soil nutrient cycling.
The significant role of tree species diversity in promoting soil N and TOC accumulation underscores its functional importance in maintaining ecosystem stability. This can be interpreted through the lens of the biodiversity-ecosystem stability theory: a community with higher tree species richness, encompassing a wider array of functional traits (e.g., in litter quality and root exudates), fosters a more complex and buffered belowground environment. This complexity enhances the system’s resistance and resilience to biotic and abiotic disturbances, thereby securing the stability of nutrient cycling. From a practical management perspective, these insights provide a scientific foundation for optimizing vegetation configurations in urban wetland parks across the subtropical regions of China.
Soil pH and soil MC did not exhibit this pattern, which differs from the findings of Cao Rui et al. [30]. This discrepancy may arise from the distinct responses of topsoil and mineral soil layers to environmental factors. This study found that increased tree species diversity elevated C, N, and P content in the surface soil of the study area, consistent with the findings of Tan Ling et al. [31]. By comparing soil nutrients in pure Pinus massoniana stands and mixed forests, they discovered that Pinus massoniana-Pinus koraiensis mixed forests exhibited higher soil fertility than pure Pinus massoniana stands. Soil nutrient content does not exhibit a linear relationship with tree species diversity but instead fluctuates, reaching peaks and troughs at specific diversity combinations. This contrasts with other studies linking tree species diversity to soil nutrients, such as that by Marie et al. [32], who found plant diversity positively enhances soil C storage, and Huang [33] and Wang et al. [34], who observed that converting pure stands to mixed forest patterns improved soil fertility.
Soil C:N:P stoichiometric ratios serve as crucial indicators reflecting soil organic matter composition, soil quality, and ecosystem health. Soil C:N effectively reflects soil quality and influences C and N cycling. In this study, the average soil C:N ratios in both the organic and mineral horizons across all tree diversity gradients exceeded the national Chinese average (12.01) [10], indicating higher soil C content relative to N content in the study area. Furthermore, previous research suggests that lower soil C:N ratios correlate with faster rates of soil organic matter decomposition and mineralization [28], implying slower decomposition and mineralization rates in the study area’s soils. The trends in soil C:N ratios within the organic and mineral horizons did not align as tree species diversity increased, likely because the organic horizon is more susceptible to litterfall influences than the mineral horizon. Soil C:P ratios reflect P mineralization capacity [35]. Lower soil C:P ratios indicate faster P mineralization rates, which also favor microbial decomposition of organic matter. Across all tree species diversity gradients in this study area, the average soil C:P ratio significantly exceeded the national Chinese average (25.77) [36]. This indicates slower P mineralization in the study area soils, revealing pronounced P limitation.
Microbial organic matter decomposition is more readily constrained by P, a phenomenon attributable to the widespread P limitation prevalent in subtropical regions. Furthermore, this study found that organic horizons in other forest stands exhibited lower C:P ratios than those in pure stands, while mineral horizons showed no such trend. This suggests increased species diversity may reduce soil C:P ratios, as high species diversity enhances microbial decomposition of organic matter in organic horizons, partially alleviating soil P limitation. Soil N:P ratios serve as a key indicator for assessing soil N saturation and determining nutrient limitation thresholds. Lower soil N:P ratios indicate higher P availability. Soil N:P content in the study area was significantly higher than the Chinese soil average (2.1) [37]. This indicates lower P activity in the study area soils. The prevalent P limitation, as evidenced by the elevated soil C:P and N:P ratios, is likely a pivotal factor controlling microbial metabolism and the decomposition of organic matter within this urban wetland. In a sense, soil ecological stoichiometric ratios can serve as sensitive indicators of subsurface nutrient cycling. RDA revealed that among the variations in soil C, N, P, and their stoichiometric ratios across different tree species diversities, the most influential factor was soil NH4+-N content, followed by soil MC and P content. This suggests that compared to tree species diversity, soil physicochemical properties exert a greater influence on soil ecological stoichiometric ratios.
Although the overall similarity of wetland environments and the distribution of tree species among sampling sites may lead to certain convergence in diversity indices (Table 1), the micro-environmental heterogeneity between regional plots—such as subtle hydrological variations, light conditions, and differences in local shrub/grass coverage—still drives differentiation in the abundance of dominant tree species and other species through subtle influences on soil physicochemical properties. Lohbeck [38] found that biomass was the main driver of changes in ecosystem process rates during forest succession, according to the altering community and functional diversity. This largely shaped the soil microbial community, fluctuating the ecological biochemistry characteristics of the soil, which mutually influence distinct plant formations and communities [39]. The observed patterns may be driven not only by biodiversity itself but also by specific floristic composition, particularly the functional traits of dominant species in each plot. While the composition and distribution of typical dominant communities vary across regions, the differences in biodiversity ultimately remain at a low to moderate level in our study, with certain limitations in sample size potentially affecting the generalizability of these results. However, as a typical urban wetland, XXIIW has a relatively limited geographic scope (bounded by urban roads outside its boundaries), and the selected plots have already covered all typical vegetation communities in the area. Ultimately, RDA was successfully conducted, yielding statistically significant results with ecological implications.
Subsequent plans include expanding sample sizes and screening ranges, establishing multi-level diversity index gradients, and further disentangling the effects of species richness and composition on ecosystem functioning. And comparative analyses of soil vertical profiles could be conducted to validate the vertical consistency of the stoichiometric driver, which would help elucidate the coupling mechanisms between wetland floristic composition and soil nutrient cycling. Furthermore, expanding the research to other subtropical urban wetlands to validate the broad applicability of the XXIIW pattern.
5. Conclusions
This chapter investigated the effects of tree species diversity on soil physicochemical properties and their stoichiometric ratios. It analyzed the correlations among soil physicochemical properties, soil, soil C, N, P, and their stoichiometric ratios, elucidated the influencing factors of soil, soil C, N, P content, and their stoichiometric ratios, and drew the following conclusions: Soil NO3−-N and NH4+-N contents exhibit significant variations across different tree species diversity gradients. The interaction effects of varying tree species diversity significantly influence soil NH4+-N content. Soil physicochemical properties are closely linked to soil C, N, and P contents and their stoichiometric ratios. Soil NH4+-N content, soil MC, and P content are key factors driving variations in soil C, N, and P content and their stoichiometric ratios.
Author Contributions
Methodology, C.L. and W.L.; Software, C.L.; Validation, C.L., Y.L. and W.L.; Formal analysis, C.L.; Investigation, K.Y., C.L., Y.L. and W.L.; Resources, Y.L. and W.L.; Data curation, K.Y. and W.L.; Writing—original draft, K.Y., C.L., Y.L. and W.L.; Writing—review & editing, K.Y. and W.L.; Supervision, W.L.; Project administration, K.Y. and W.L.; Funding acquisition, K.Y. and W.L. All authors have read and agreed to the published version of the manuscript.
Funding
This research was supported by funding Construction of Long term Monitoring Site for Biodiversity in Xixi Wetland (2024-Y196).
Institutional Review Board Statement
Not applicable.
Data Availability Statement
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.
Conflicts of Interest
The authors declare no conflicts of interest.
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Figure 1.
Distribution map of sampling points.
Figure 2.
Redundancy Analysis Diagram. Note: MAT stands for average temperature; MAP stands for average precipitation; SOC is equal to TOC; Both Mz and D represent soil particle size, where Mz denotes soil particle diameter, and D represents the fractal dimension of soil particles.
Figure 2.
Redundancy Analysis Diagram. Note: MAT stands for average temperature; MAP stands for average precipitation; SOC is equal to TOC; Both Mz and D represent soil particle size, where Mz denotes soil particle diameter, and D represents the fractal dimension of soil particles.
Table 1.
Basic information for XXIIW plot.
| Plot Name | Coordinates | Dominant Tree Species |
|---|---|---|
| XXSD-S01 | E 120.06172, N 30.26787 | Salix matsudana, Morus alba |
| XXSD-S02 | E 120.04979, N 30.26012 | Cinnamomum camphora, Prunus mume |
| XXSD-S03 | E 120.08299, N 30.27183 | Pterocarya stenoptera, Broussonetia papyrifera |
| XXSD-S04 | E 120.05582, N 30.27628 | Morus alba, Broussonetia papyrifera |
| XXSD-S05 | E 120.06263, N 30.27299 | Pterocarya stenoptera, Ulmus parvifolia |
| XXSD-S06 | E 120.07545, N 30.26597 | Cinnamomum camphora, Pterocarya stenoptera |
| XXSD-S07 | E 120.06172, N 30.26787 | Cinnamomum camphora, Celtis sinensis |
Table 2.
Tree species composition and number of individuals in XXIIW plots.
| Plot | R | H’ | D | Jsw |
|---|---|---|---|---|
| XXSD-S01 | 6 | 1.32 | 0.56 | 0.62 |
| XXSD-S02 | 8 | 1.36 | 0.42 | 0.56 |
| XXSD-S03 | 8 | 1.45 | 0.36 | 0.63 |
| XXSD-S04 | 7 | 1.23 | 0.58 | 0.58 |
| XXSD-S05 | 12 | 1.57 | 0.62 | 0.55 |
| XXSD-S06 | 9 | 1.22 | 0.49 | 0.62 |
| XXSD-S07 | 22 | 1.31 | 0.52 | 0.69 |
Note: R stands for Richness Index; H’ stands for Shannon–Wiener Diversity Index; D stands for Simpson’s Diversity Index; Jsw stands for Pielou Uniformity Index.
Table 3.
Composition and structural characteristics of the tree layer plant communities in XXIIW.
| Family | Genus | Species | Number | % |
|---|---|---|---|---|
| Cupressaceae | Metasequoia | Metasequoia glyptostroboides | 2 | 0.41 |
| Magnoliaceae | Yulania | Yulania denudata | 3 | 0.62 |
| Lauraceae | Phoebe | Phoebe sheareri | 1 | 0.21 |
| Camphora | Camphora officinarum | 62 | 12.86 | |
| Ulmaceae | Ulmus | Ulmusparvifolia | 7 | 1.45 |
| Cannabaceae | Celtis | Celtis sinensis | 19 | 3.94 |
| Moraceae | Morus | Morus alba | 129 | 26.76 |
| Broussonetia | Broussonetia papyrifera | 84 | 17.43 | |
| Juglandaceae | Pterocarya | Pterocarya stenoptera | 47 | 9.75 |
| Fagaceae | Castanopsis | Castanopsis jucunda | 1 | 0.21 |
| Theaceae | Camellia | Camellia sinensis | 1 | 0.21 |
| Elaeocarpaceae | Elaeocarpus | Elaeocarpus sylvestris | 3 | 0.62 |
| Salicaceae | Salix | Salix matsudana | 27 | 5.60 |
| Ebenaceae | Diospyros | Diospyros kaki var. silvestris | 10 | 2.07 |
| Rosaceae | Eriobotrya | Eriobotrya japonica | 5 | 1.04 |
| Prunus | Prunus mume | 13 | 2.70 | |
| Fabaceae | Robinia | Robinia pseudoacacia | 5 | 1.04 |
| Nyssaceae | Camptotheca | Camptotheca acuminata | 4 | 0.83 |
| Celastraceae | Euonymus | Euonymus maackii | 8 | 1.66 |
| Aquifoliaceae | Ilex | Ilex chinensis | 2 | 0.41 |
| Euphorbiaceae | Triadica | Triadica sebifera | 2 | 0.41 |
| Sapindaceae | Koelreuteria | Koelreuteria bipinnata var. integrifoliola | 1 | 0.21 |
| Anacardiaceae | Rhus | Rhus chinensis | 7 | 1.45 |
| Meliaceae | Melia | Melia azedarach | 8 | 1.66 |
| Rutaceae | Citrus | Citrus maxima | 1 | 0.21 |
| Araliaceae | Fatsia | Fatsia japonica | 1 | 0.21 |
| Lamiaceae | Clerodendrum | Clerodendrum trichotomum | 14 | 2.90 |
| Oleaceae | Ligustrum | Ligustrum lucidum | 12 | 2.49 |
| Oleaceae | Osmanthus | Osmanthus fragrans | 3 | 0.62 |
Table 4.
Analysis of soil physical and chemical properties in different plots.
| Plot | pH | BD | EC | SM | Community | TN | TOC | TP | C:N | C:P | N:P |
|---|---|---|---|---|---|---|---|---|---|---|---|
| g/cm3 | μs/cm | % | g/kg | g/kg | g/kg | ||||||
| S01 | 5.69 c | 1.36 a | 0.04 c | 42.40 a | SMC | 17.16 b | 1.87 c | 0.57 d | 9.16 c | 30.11 a | 3.28 ab |
| S02 | 5.57 c | 1.30 ab | 0.04 c | 32.10 b | CPC | 13.96 b | 1.46 c | 0.68 bcd | 9.54 c | 20.72 b | 2.18 c |
| S03 | 6.98 b | 1.30 ab | 0.21 a | 27.75 bc | PBC | 22.03 a | 2.09 c | 0.60 cd | 10.51 bc | 36.67 a | 3.49 a |
| S04 | 7.56 a | 1.17 b | 0.06 bc | 13.15 d | MBC | 2.25 c | 30.13 ab | 0.83 ab | 13.75 a | 37.17 a | 2.76 bc |
| S05 | 7.72 a | 1.24 ab | 0.28 a | 16.50 d | PUC | 2.06 c | 25.03 b | 0.77 abc | 12.45 ab | 32.58 a | 2.65 bc |
| S06 | 6.57 b | 1.20 ab | 0.17 ab | 16.68 d | CPC | 2.73 c | 34.19 a | 0.94 a | 12.54 ab | 36.24 a | 2.89 abc |
| S07 | 5.44 c | 1.34 ab | 0.04 c | 20.65 cd | CCC | 2.48 c | 28.36 ab | 0.83 ab | 11.36 bc | 34.35 a | 3.02 ab |
Note: BD stands for bulk density; EC stands for electrical conductivity; SM stands for soil moisture; TN stands for total nitrogen; TOC stands for soil organic carbon; TP stands for total phosphorus; C stands for carbon; N stands for nitrogen; P stands for phosphorus. Community: SMC stands for Salix matsudana-Morus alba community; CPC stands for Cinnamomum camphorum-Prunus mume community; PBC stands for Pterocarya stenoptera-Broussonetia papyrifera community; MBC stands for Morus alba-Broussonetia papyrifera community; PUC stands for Pterocarya stenoptera-Ulmus parvifolia community; CPC stands for Cinnamomum camphorum-Pterocarya stenoptera community; CCC stands for Cinnamomum camphorum-Celtis sinensis community. Values within a column followed by different lowercase letters are significantly different at the 0.05 probability level.
Table 5.
Soil chemical properties of plots.
| Sample ID | Sampling Point ID | pH | TC | TN | TP | Available P | NH4+-N | NO3−-N |
|---|---|---|---|---|---|---|---|---|
| g/kg | g/kg | g/kg | mg/kg | mg/kg | mg/kg | |||
| A | S01-1.1 | 6.6 | 12.71 | 1.38 | 0.52 | 11.4 | 3.84 | 14.12 |
| B | S01-3.1 | 5.4 | 15.67 | 1.79 | 0.55 | 13.23 | 2.29 | 36.29 |
| C | S01-3.3 | 5.3 | 18.02 | 1.93 | 0.55 | 17.93 | 1.13 | 27.16 |
| D | S01-1.3 | 5.47 | 22.23 | 2.38 | 0.64 | 12.47 | 1.91 | 14.25 |
| A | S02-1.1 | 5.39 | 15.64 | 1.65 | 0.7 | 12.27 | 0.75 | 1.53 |
| B | S02-3.1 | 5.95 | 12.89 | 1.35 | 0.72 | 13.55 | 0.67 | 2.59 |
| C | S02-3.3 | 5.4 | 14.59 | 1.49 | 0.64 | 19.9 | 1.69 | 5.85 |
| D | S02-1.3 | 5.52 | 12.7 | 1.36 | 0.64 | 11.4 | 1.07 | 2.78 |
| A | S03-1.1 | 6.98 | 20.98 | 2.04 | 0.59 | 11.55 | 2.96 | 23.87 |
| B | S03-3.1 | 6.98 | 22.21 | 2.1 | 0.6 | 17.25 | 0.6 | 12.94 |
| C | S03-3.3 | 6.9 | 20.06 | 1.96 | 0.59 | 12.7 | 0.52 | 13.41 |
| D | S03-1.3 | 7.05 | 24.86 | 2.27 | 0.62 | 12.3 | 0.7 | 15.13 |
| A | S04-1.1 | 7.13 | 26.9 | 2.43 | 0.68 | 28.13 | 1.27 | 21.35 |
| B | S04-3.1 | 7.52 | 31.08 | 2.62 | 1.04 | 61.5 | 1.93 | 33.11 |
| C | S04-3.3 | 7.72 | 31.56 | 1.79 | 0.7 | 18.7 | 2.38 | 18.98 |
| D | S04-1.3 | 7.85 | 30.99 | 2.15 | 0.91 | 48.76 | 1.57 | 23.47 |
| A | S05-1.1 | 7.71 | 26.28 | 2.34 | 0.84 | 21.98 | 3.64 | 12.79 |
| B | S05-3.1 | 8.06 | 20.42 | 1.37 | 0.61 | 18.68 | 3 | 4.89 |
| C | S05-3.3 | 7.84 | 25.95 | 2.15 | 0.85 | 36.23 | 1.96 | 17.75 |
| D | S05-1.3 | 7.25 | 27.47 | 2.37 | 0.78 | 28.37 | 1.94 | 24.55 |
| A | S06-1.1 | 6.57 | 38.34 | 3.03 | 1.08 | 53.34 | 1.62 | 17.33 |
| B | S06-3.1 | 6.49 | 30.43 | 2.44 | 0.85 | 20.15 | 1.95 | 17.96 |
| C | S06-3.3 | 6.63 | 42.05 | 3.33 | 0.98 | 44.1 | 1.85 | 27.97 |
| D | S06-1.3 | 6.59 | 25.92 | 2.1 | 0.85 | 39.92 | 1.88 | 18.4 |
| A | S07-1.1 | 5.52 | 27.54 | 2.35 | 0.72 | 20.05 | 0.54 | 15.44 |
| B | S07-3.1 | 5.19 | 29 | 2.66 | 0.75 | 19.35 | 2.27 | 18.61 |
| C | S07-3.3 | 5.48 | 21.07 | 1.96 | 0.89 | 19.95 | 1.63 | 13.52 |
| D | S07-1.3 | 5.57 | 35.82 | 2.96 | 0.97 | 19.45 | 1.61 | 17.78 |
Note: TC stands for bulk total carbon; TN stands for total nitrogen; TP stands for total phosphorus; C stands for carbon; N stands for nitrogen; P stands for phosphorus; NH4+-N stands for ammonium nitrogen; NO3−-N stands for nitrate nitrogen.
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Yao, K.; Li, C.; Luo, Y.; Li, W. Relationship Between Tree Species Diversity and Soil Ecological Biochemistry Characteristics in Urban Wetland: A Case Study of International Important Wetland in Hangzhou, China. Diversity 2025, 17, 817. https://doi.org/10.3390/d17120817
AMA Style
Yao K, Li C, Luo Y, Li W. Relationship Between Tree Species Diversity and Soil Ecological Biochemistry Characteristics in Urban Wetland: A Case Study of International Important Wetland in Hangzhou, China. Diversity. 2025; 17(12):817. https://doi.org/10.3390/d17120817
Chicago/Turabian StyleYao, Kekan, Chuanliang Li, Yuheng Luo, and Weicheng Li. 2025. "Relationship Between Tree Species Diversity and Soil Ecological Biochemistry Characteristics in Urban Wetland: A Case Study of International Important Wetland in Hangzhou, China" Diversity 17, no. 12: 817. https://doi.org/10.3390/d17120817
APA StyleYao, K., Li, C., Luo, Y., & Li, W. (2025). Relationship Between Tree Species Diversity and Soil Ecological Biochemistry Characteristics in Urban Wetland: A Case Study of International Important Wetland in Hangzhou, China. Diversity, 17(12), 817. https://doi.org/10.3390/d17120817
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