Effects of mixed plantations on soil microbial diversity and ecosystem multifunctionality across China: a meta-analysis

Mixed plantations have emerged as a key afforestation strategy for enhancing the stability and sustainability of forest ecosystems. However, their effects on soil microbial diversity and ecosystem multifunctionality (EMF) remain inconsistent. Here, we compiled a dataset from 121 peer-reviewed publications and conducted a meta-analysis to evaluate the effects of different mixed plantation strategies on soil microbial diversity and EMF. The results showed that mixed plantations significantly increased bacterial and fungal Shannon indices by 1.43 and 7.4%, respectively, compared to monocultures. In addition, mixed plantations enhanced key ecosystem functions, including increased soil organic carbon, nutrient availability, and moisture retention, while reducing soil bulk density. Collectively, these improvements resulted in a 19.25% increase in the EMF index. Further analysis revealed significant positive correlations between both bacterial and fungal diversity and EMF, as well as significant associations between EMF and key soil physical properties. Moreover, the effects of mixed plantations on microbial diversity and ecosystem functions varied depending on the mixing strategy. Overall, our findings highlight the ecological benefits of mixed plantations for soil microbial diversity and EMF, supporting more effective and sustainable afforestation practices.

1 Introduction

Biodiversity loss disrupts ecosystem structure and functioning, posing a major threat to long-term ecological stability and human wellbeing (Jaureguiberry et al., 2022). Forest ecosystems cover approximately 31% of the Earth’s terrestrial surface and play a crucial role in maintaining global biodiversity and providing ecosystem services and functions, including carbon storage, nutrient cycling, water conservation, and climate regulation (FAO, 2024). In recent decades, with the growing demand for ecosystem services and the need to avoid the ecological crises caused by excessive logging of natural forests, the area of forest plantations now comprises approximately 7% of the global forest cover (Liu S. et al., 2018). Notably, China has established the world’s largest area of forest plantations through a series of major afforestation projects, representing more than 25% of the global planted forest area (Ma et al., 2025). China’s forest plantations possess several distinctive characteristics that set them apart globally. In terms of dominant species, they are predominantly composed of fast-growing timber trees such as Populus species (Populus tomentosa) and Cunninghamia lanceolata, which are managed for high-yield timber production (Sui et al., 2022). Beyond their economic value, these plantations are strategically established to fulfill critical ecological functions, most notably soil and water conservation, which is vital for rehabilitating degraded land across the country. Among various afforestation models, monoculture plantations have become the prevailing afforestation model owing to their high productivity and management simplicity (Li T. et al., 2022). However, long-term, large-scale monoculture plantations are known to cause a range of ecological problems, such as soil erosion, declines in soil quality, reduced biodiversity, and diminished ecosystem service capacity (Li et al., 2021; Li P. et al., 2022; Zhou et al., 2024). In contrast, mixed plantations are receiving increasing attention due to their potential to enhance biodiversity, improve ecosystem resilience, and maintain multiple ecosystem functions (Gamfeldt et al., 2013; Xie et al., 2018; Zhou et al., 2024).

Soil microbial communities, as a vital component of global biodiversity, play key roles in ecosystem functioning (Delgado-Baquerizo et al., 2016; Bastida et al., 2021). Studies have shown that mixed plantations can influence soil microbial diversity by altering soil moisture content, pH, and nutrient availability (An et al., 2019; Ding et al., 2022; Xu et al., 2022). Despite increasing research on how mixed plantations affect soil microbial communities, results remain inconsistent and no clear consensus has emerged. Some studies report that mixed plantations significantly enhance soil microbial diversity (Xu et al., 2022; Liu L. et al., 2023; Li N. et al., 2024), while others report either negative effects or no significant differences compared to monocultures (Xu et al., 2021; Pan et al., 2023; Yang et al., 2024). Variations in tree species composition, stand age, and planting density may contribute to the variable effects on soil microbial diversity (Zhang et al., 2023; Zhang et al., 2024).

Biodiversity has been widely recognized as a key driver of ecosystem multifunctionality (EMF) in numerous studies (Lefcheck et al., 2015; Mensah et al., 2020; Yan et al., 2023). Earlier research tended to focus on the relationship between plant diversity and EMF (Maestre et al., 2012; van der Plas et al., 2016; Gross et al., 2017). The relationship between soil microbial diversity and EMF has received growing attention with the rapid advancement of molecular biology (Shu et al., 2023; Sun et al., 2023; Zhang et al., 2025). Previous studies have found a significant positive correlation between soil microbial diversity and EMF (Delgado-Baquerizo et al., 2020). As research has become more nuanced, some studies have revealed that fungal diversity positively influences EMF (Duan et al., 2021), whereas bacterial diversity appears to have a less pronounced effect (Chen et al., 2023). These findings suggest that trade-offs may exist between different types of soil microbial diversity and their contributions to EMF (Sun et al., 2023).

Although mixed plantations are increasingly adopted in afforestation practices, the specific relationships between mixed plantations, soil microbial diversity, and EMF remain unclear. Previous field-based empirical studies have been largely confined to local or small spatial scales, limiting their applicability to broader regions. Moreover, existing meta-analyses on mixed plantations have primarily focused on either soil microbial diversity or specific ecosystem functions (Gong et al., 2021; Yan et al., 2021; Xiang et al., 2022), with few attempts to quantitatively integrate both aspects. To address these gaps, this study conducts a quantitative meta-analysis across China, a representative region for large-scale plantation development, to simultaneously evaluate the effects of mixed plantations on soil microbial diversity and EMF. This integrated approach provides new insights for optimizing mixed plantation management and promoting ecosystem sustainability.

Here, we compiled a comprehensive database comprising 332 paired observations from monoculture and mixed plantations for meta-analysis to evaluate soil microbial diversity and EMF. Based on our meta-analysis, we aimed to (1) quantify the impact of mixed plantations on soil microbial diversity; (2) evaluate their effects on various ecosystem functions and EMF; and (3) explore the relationships between microbial diversity and EMF in mixed plantation systems. For robust assessment of microbial alpha diversity, we employed the Shannon index as our primary metric, following established methodologies (He et al., 2013). Furthermore, we hypothesized that factors such as the presence or absence of nitrogen-fixing tree species, the age structure of mixed plantations, and species mixture type significantly influence soil microbial diversity and ecosystem functioning.

2 Materials and methods

2.1 Data collection

We conducted a comprehensive literature search of peer-reviewed journal articles published before 31 December 2024, using the Web of Science and China National Knowledge Infrastructure (CNKI) databases. The literature screening was performed following the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) (Moher et al., 2009; Figure 1). Various keyword combinations were used for the search, such as: (mixed forest or mixed plantation or plantation or different forest stand types) AND (soil microbial diversity or soil fungal diversity or soil bacteria diversity or soil microbial biomass or soil microbial community) AND (ecosystem multifunctionality or soil physical and chemical properties). Additionally, relevant peer-reviewed literature was further supplemented by cross-checking the reference lists of the included articles. The studies were subsequently screened according to the following criteria: (1) only studies conducted within China were included; (2) only field studies conducted in plantation forests with at least three replicates were included, excluding those conducted in natural forests; (3) to ensure comparability, each study had to include both mixed plantations (treatment; composed of two tree species) and monoculture plantations (control; consisting of one of these two species) at the same experimental site; (4) only studies focusing on the entire community of soil bacteria and fungi were included, excluding those that focused on specific microbial taxa; (5) data were extracted only from the 0 to 20 cm soil layer; (6) the diversity index of soil microbial community was calculated based on the high-throughput sequencing method (Wang et al., 2023); (7) if a publication included multiple experiments under different treatments, seasons or years, stand ages, or mixing proportions, each independent experiment was considered as one observation in the meta-analysis.

FIGURE 1

Figure 1. PRISMA diagram showing the process of locating publications included in this meta– analysis.

2.2 Data extraction

For each study included in this meta-analysis, we extracted key variables, including the mean, standard deviation (SD), and sample size for plant properties [litter biomass (LB), root biomass (RB)], soil physicochemical properties [bulk density (BD), soil moisture content (SM), soil pH (pH), soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), available phosphorus (AP), and available potassium (AK), ammonium nitrogen (NH₄^–-N), nitrate nitrogen (NO₃^–-N), SOC/TN ratio (C/N)], microbial attributes [microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), bacterial Shannon index, and fungal Shannon index, and enzyme activity urease activity (URE)].

All original data were extracted from the figures, tables, and supplementary material of the publications. Specifically, data presented in tables were directly extracted, whereas graphical data were digitized using the GetData Graph Digitizer (version 2.24). When only the median, range, or interquartile range was reported, we estimated the mean and standard deviation using the method proposed by Wan et al. (2014). If the original studies reported standard errors (SE) instead of SD, we converted SE to SD using the formula SD = SE* $\sqrt{\mathrm{n}}$. Additionally, we collected site characteristics, including geographic location (latitude and longitude), elevation, mean annual temperature, mean annual precipitation, mixed plantation type, mixing ratio, and stand age. Stand age was defined as the number of years between forest establishment (or species introduction) and sampling. Based on these criteria, the databases used for the Meta-analysis comprise 332 observations at 104 sites from 121 peer-reviewed publications. The study sites included in this study are shown in Figure 2.

FIGURE 2

Figure 2. Distribution of all study sites included in this meta-analysis across China.

We categorized the collected data based on three mixing strategy classifications:

(1) Nitrogen-fixing status (N-fixing status): classified based on the presence or absence of nitrogen-fixing tree species as nitrogen-fixing mixed plantations (NF) and non-nitrogen-fixing mixed plantations (NNF).

(2) Age structure: classified as uneven-aged mixed plantations (UA) and even-aged mixed plantations (EA).

(3) Species mixture: classified as coniferous–broadleaf mixed plantations (CB) and broadleaf–broadleaf mixed plantations (BB). Coniferous–coniferous mixed plantations were excluded from the classification due to an insufficient number of available studies (n < 3).

2.3 Assessment of ecosystem multifunctionality index

We selected 13 indicators related to ecosystem functioning from the database to assess EMF, including LB, RB, SOC, TN, TP, AP, AK, NO₃^–-N, NH₄^–-N, MBC, MBN, C/N, and URE. These indicators were selected because they have been recognized in previous studies as good descriptors of ecosystem functions and services (Yuan et al., 2021; Liu et al., 2025). To ensure consistency in directional change, the values of the C/N ratio were multiplied by –1, since higher values represent a negative effect on ecosystem functioning (Ma et al., 2021). The EMF index was calculated as the mean of effect sizes across the 13 selected indicators, following the averaging approach widely used in multifunctionality studies (Shu et al., 2024). This approach was adopted because it provides an intuitive and easily interpretable metric that gives balanced consideration to the overall performance of multiple ecosystem functions.

2.4 Meta-analysis

We used the natural log-transformed effect size (RR) to quantify the impact of mixed plantations on soil microbial diversity and individual ecosystem functions (Hedges et al., 1999), as shown in Eq. (1):

$\text{RR}=\ln (\mathrm{Xt}/\mathrm{Xc})=\ln (\mathrm{Xt})-\ln (\mathrm{Xc})(1)$

where Xt and Xc are the average values of the selected variables in the mixed plantation (treatment group) and monoculture plantation (control group), respectively.

The variance (v) of RR was calculated using Eq. (2):

$\text{V}=\frac{S{D}_t^2}{N_t{X}_t^2}+\frac{S{D}_C^2}{N_c{X}_c^2}(2)$

where Nt and Nc represent the sample size of mixed plantation and monoculture plantation, respectively; SDt and SDc denote the standard deviations (SD) of the mixed plantation and monoculture plantation, respectively. If the SD was unavailable and could not be estimated, it was imputed as 10% of the corresponding mean, following Li X. et al. (2020).

To facilitate interpretation, the weighted effect sizes (lnRR) were back-transformed and presented as percentage changes using Eq. (3) (Wang et al., 2023):

$\mathrm{Percentage}\mathrm{change}(\%)=(\exp (\mathrm{lnRR})-1)\times 100\%(3)$

We used the “metafor” package (version 4.6.0) in R to perform a meta-analysis with a random-effects model (Viechtbauer, 2010). This model was chosen to account for heterogeneity arising from differences in site conditions and experimental designs among the included studies, which cannot be addressed by a fixed-effects model. The “rma” function was employed to calculate the lnRR and the corresponding 95% confidence interval (CI). If the 95% CI did not overlap with zero, the effect of mixing on the given variable was considered significant (p < 0.05).

We used between-group heterogeneity tests (Q_B) to compare effect sizes across different mixing strategies. A significant Q_B value (P_QB < 0.05) indicates significant differences in the weighted effect sizes between groups for a given variable.

To examine whether soil microbial diversity affected EMF, we used ordinary least squares regressions to analyze the relationships between soil bacterial and fungal diversity and EMF. In addition, we also analyzed the relationships between soil physical properties and EMF. For the regression model, we used the Shapiro-Wilk test to assess the normality of the residuals and the Breusch-Pagan test to examine homoscedasticity (Zhang et al., 2022). For both tests, p > 0.05 was considered to indicate that the assumptions of normality and homoscedasticity were not violated.

Given that some variables lacking reported SD were included in this meta-analysis, we conducted a sensitivity analysis to assess the possible bias introduced by this inclusion (Gao et al., 2021). Specifically, we calculated and compared the lnRR and 95% CIs using all available data and a subset excluding studies without SD. If the lnRR were similar and their 95% CIs overlapped, the inclusion of all data for that variable was deemed acceptable for our meta-analysis. Furthermore, we employed both Egger’s regression test and Fail-Safe N analysis to comprehensively assess potential publication bias in this meta-analysis (Egger et al., 1997; Rosenberg, 2005). If the Fail-Safe N exceeded 5n + 10 (where n is the sample size), the results were considered robust and free from publication bias. Sensitivity analysis indicated that the inclusion of data without SD did not change the direction and statistical significance of our results (Table 1), and no potential publication bias was detected (Table 2).

TABLE 1

Table 1. Sensitivity analysis for the effects of mixed plantations on soil microbial diversity and ecosystem multifunctionality.

TABLE 2

Table 2. Results of publication bias.

All statistical analyses and visualizations were performed in R version 4.4.1 (R Core Team, 2024).

3 Results

3.1 Effects of mixed plantations on soil microbial diversity

The Shannon indices of bacterial and fungal communities were both significantly higher in mixed plantations than in monocultures, with increases of 1.43% (p < 0.01) and 7.4% (p < 0.001), respectively (Figure 3). Further analysis revealed that this increase was significant regardless of the age structure of the mixed plantations. Specifically, the Shannon indices of bacteria and fungi increased by 2.00 and 14.56%, respectively, in uneven-aged mixed plantations, and by 1.53 and 5.59% in even-aged mixed plantations (all p < 0.05) (Figure 3). While nitrogen-fixing mixed plantations did not significantly affect the bacterial Shannon index (p > 0.05) (Figure 3A), they significantly increased the fungal Shannon index by 7.14% (p < 0.05) (Figure 3B). In contrast, broadleaf–broadleaf mixed plantations significantly increased the bacterial Shannon index by 2.38% (p < 0.05) (Figure 3A), but had no significant effect on the fungal Shannon index (p > 0.05) (Figure 3B).

FIGURE 3

Figure 3. Weighted effect sizes (A) of soil bacterial Shannon index and (B) of soil fungal Shannon index in mixed plantations under different mixing strategies. Error bars represent 95% confidence intervals (CIs) of the weighted effect sizes. An effect is considered statistically significant if the 95% CI does not overlap with zero (p < 0.05). Sample sizes for each variable are shown in parentheses next to the corresponding labels. ***, **, and * denote p < 0.001, p < 0.01, and p < 0.05, respectively. NF, nitrogen-fixing mixed plantations; NNF, non-nitrogen-fixing mixed plantations; UA, uneven-aged mixed plantations; EA, even-aged mixed plantations; CB, coniferous-broadleaf mixed plantations; BB, broadleaf-broadleaf mixed plantations.

3.2 Effects of mixed plantations on ecosystem functions

Mixed plantations significantly increased plant biomass compared to monocultures, with LB and RB rising by 31.52 and 40.71%, respectively (p < 0.001) (Figure 4). Mixed plantations exhibited higher levels of SM, pH, SOC, TN, TP, AP, AK, NH₄^–-N, and NO₃^–-N concentrations, with varying magnitudes across indicators (Figure 4). Among all indicators, the NO₃^–-N concentration showed the largest increase, rising by 25.04% overall (p < 0.001) (Figure 4), and by 61.91% specifically in nitrogen-fixing mixed plantations (p < 0.001) (Figure 5A). In contrast, the BD level in mixed plantations decreased by 5.66% (p < 0.001) (Figure 4). Notably, the C/N ratio decreased significantly by 13.39%, but only in uneven-aged mixed plantations (p < 0.001) (Figure 5B).

FIGURE 4

Figure 4. Weighted effect sizes of individual ecosystem functions (LB, RB, SOC, TN, TP, AP, AK, NH₄^–-N, NO₃^–-N, C/N, MBC, MBN, and URE) and soil properties, including physical (BD, SM) and chemical (pH) characteristics, in mixed plantations. Error bars represent 95% confidence intervals (CIs) of the weighted effect sizes. An effect is considered statistically significant if the 95% CI does not overlap with zero (p < 0.05). Sample sizes for each variable are shown in parentheses next to the corresponding labels. *** denote p < 0.001, respectively. LB, litter biomass; RB, root biomass; BD, bulk density; SM, soil moisture content; pH, soil pH; SOC, soil organic carbon; TN, soil total nitrogen; TP, soil total phosphorus; AP, soil available phosphorus; AK, soil available potassium; NH₄^–-N, soil ammonium nitrogen; NO₃^–-N, soil nitrate nitrogen; C/N, SOC/TN ratio; MBC, microbial biomass carbon; MBN, microbial biomass nitrogen; URE, urease activity.

FIGURE 5

Figure 5. Effects of (A) N-fixing status (NF, nitrogen-fixing mixed plantations; NNF, non-nitrogen-fixing mixed plantations), (B) age structure (UA, uneven-aged mixed plantations; EA, even-aged mixed plantations), and (C) species mixture (CB, coniferous-broadleaf mixed plantations; BB, broadleaf-broadleaf mixed plantations) on multiple ecosystem functions and soil physical properties. Error bars represent 95% confidence intervals (CIs) of the weighted effect sizes. An effect is considered statistically significant if the 95% CI does not overlap with zero (p < 0.05). Sample sizes for each variable are shown in parentheses next to the corresponding labels. ***, **, and * denote p < 0.001, p < 0.01, and p < 0.05, respectively. See Figure 4 caption for abbreviation definitions.

Microbial biomass was significantly greater in mixed plantations, with MBC and MBN increasing by 21.74 and 25.38%, respectively, compared to monocultures (p < 0.001) (Figure 4).

Soil urease activity also increased significantly in mixed plantations, showing a 22.98% rise compared to monocultures (p < 0.001) (Figure 4). This stimulatory effect on urease activity was consistent across all examined mixing strategies (Figures 5A–C).

3.3 Effects of mixed plantations on EMF and its drivers

Compared to monoculture plantations, mixed plantations significantly increased the EMF index by 19.25% (p < 0.001) (Figure 6). This positive effect was consistent across all mixing strategies, although the magnitude of the increase did not differ significantly among them (p > 0.05) (Table 3). Linear regression analysis showed that the EMF index was positively correlated with both bacterial and fungal Shannon indices (p < 0.05) (Figure 7 and Table 4). Additionally, among soil physical properties, EMF was positively associated with SM and negatively associated with BD (both p < 0.001) (Figure 8 and Table 4).

FIGURE 6

Figure 6. Percent change in ecosystem multifunctionality (EMF) across different mixing strategies in mixed plantations. NF, nitrogen-fixing mixed plantations; NNF, non-nitrogen-fixing mixed plantations; UA, uneven-aged mixed plantations; EA, even-aged mixed plantations; CB, coniferous-broadleaf mixed plantations; BB, broadleaf-broadleaf mixed plantations.

TABLE 3

Table 3. Between-group heterogeneity (Q_b and P-values) for each variable under different mixing strategies.

FIGURE 7

Figure 7. Relationships between the effect sizes (RR) of soil bacterial and fungal Shannon indices and the RR of ecosystem multifunctionality (EMF). Light gray areas indicate the 95% confidence intervals, with the central lines representing linear regressions.

TABLE 4

Table 4. Linear relationships between the effect sizes (RR) of soil microbial diversity and physical properties, and the RR of ecosystem multifunctionality (EMF).

FIGURE 8

Figure 8. Relationships between the effect sizes (RR) of soil moisture content (SM, A) or soil bulk density (BD, B) and the RR of ecosystem multifunctionality (EMF). Light gray areas indicate the 95% confidence intervals, with the central lines representing linear regressions.

4 Discussion

4.1 Positive effects of mixed plantations on soil microbial diversity

Our meta-analysis showed that the effect sizes of mixed plantations on the Shannon index were positive (Figures 3a,b), suggesting an overall increase in soil microbial biodiversity. Previous studies have found that mixed plantations generally support higher microbial diversity than monocultures, mainly due to their more diverse tree species composition, which provides diverse organic inputs and fosters heterogeneous microhabitats (Li et al., 2015; Khlifa et al., 2017). Litter and root exudates from different tree species offer diverse nutritional substrates for microbes, while also improving the soil microenvironment and increasing the availability of soil nutrients, thereby supporting a more diverse microbial community (Li et al., 2015; Khlifa et al., 2017). Higher microbial diversity is widely recognized as an indicator of healthier soils, promoting more efficient nutrient cycling, organic matter decomposition, and resistance to pests and diseases (Zhu et al., 2021). Notably, microbial diversity is not determined solely by tree species composition; it is also shaped by multiple biotic and abiotic factors, such as pH, nutrient availability, and microbial interactions, which may influence the observed patterns (Ding et al., 2022; Wang Y. et al., 2022).

Moreover, our results revealed that different mixing strategies had divergent effects on bacterial and fungal diversity. Specifically, nitrogen-fixing mixed plantations significantly increased the fungal Shannon index, while bacterial diversity showed no significant response (Figure 3). This pattern suggests that fungal communities may be more responsive than bacterial communities to the presence of nitrogen-fixing species (Zhang et al., 2020; Liu et al., 2022). Introducing nitrogen-fixing species into monocultures may enhance plant nutrient-use efficiency, increasing the input of structurally complex plant residues and root exudates rich in macromolecular organic matter (Wu et al., 2025). Fungi, as primary decomposers of recalcitrant compounds such as lignin and cellulose, may benefit from these additional resources, potentially contributing to the observed increase in fungal diversity. While nitrogen-fixing species may contribute to higher fungal diversity, this effect likely operates together with other environmental and biological factors (Li N. et al., 2024). Moreover, bacterial diversity remained largely unaffected, possibly reflecting a lower sensitivity to tree species composition and a greater influence of abiotic factors such as soil depth and moisture (Xu Z. et al., 2023). In contrast, broadleaf–broadleaf mixed plantations increased the bacterial Shannon index only (Figure 3A), likely because faster decomposition of broadleaf litter accelerates nutrient turnover, providing more labile carbon and nutrients for bacterial communities (Wang et al., 2018; Zhuang et al., 2023). Collectively, these results suggest that bacterial and fungal communities exhibit distinct responses to different mixing strategies (Bai et al., 2025; Xiao et al., 2022).

4.2 Improved ecosystem functions in response to various mixing strategies

Our findings showed that mixed plantations significantly increased LB and RB compared to monocultures (Figure 4). This pattern may be driven by more efficient resource use and niche complementarity in mixed plantations. For instance, mixed plantations often develop stratified canopies that enable species to optimize light capture through vertical niche differentiation. This structural advantage persists over time, resulting in higher litter production in mixed plantations than in monocultures, thereby increasing litter biomass (Wu et al., 2019). Moreover, root niche partitioning and complementary resource use in mixed plantations likely enhance fine root biomass by facilitating more efficient use of belowground resources (Ma and Chen, 2016).

Plants primarily absorb nitrogen in the forms of ammonium (NH₄^–) and nitrate (NO₃^–) from the soil (Wang et al., 2005). Mixed plantations have been shown to enhance the concentrations of both NH₄^–-N and NO₃^–-N in the soil (Yu et al., 2015; Zhou et al., 2023). In our study, the concentrations of NH₄^–-N and NO₃^–-N were both significantly increased in mixed plantations (Figure 4). Notably, NO₃^–-N levels increased by 61.91% in nitrogen-fixing mixed plantations (Figure 5A), which was significantly higher than in non-nitrogen-fixing mixed plantations (Table 3). This finding aligns with previous studies, suggesting that nitrogen-fixing species enhance soil nitrogen availability (Hoogmoed et al., 2014). This increase is likely attributable to the ability of the associated tree species to fix nitrogen symbiotically, leading to greater nitrogen input into the soil (Mus et al., 2016). Furthermore, mixed plantations may promote nitrification by soil microbes, accelerating the conversion of NH₄^–-N to NO₃^–-N and further increasing NO₃^–-N levels (Liu C.-A et al., 2018). While this shift improves nitrogen availability and promotes plant growth, it may also increase the risk of nitrogen loss, an aspect requiring further investigation (Liang et al., 2020).

In addition, we found that only uneven-aged mixed plantations significantly reduced the C/N ratio (Figure 5B). The C/N ratio is a proxy for nitrogen mineralization potential, with lower values typically indicating higher rates of nutrient release (Liu and Lu, 2024). The decrease in the C/N ratio in uneven-aged mixed plantations may be associated with the timing of species introduction and the resulting age structure (Ling et al., 2022). As new species are introduced, the quantity and quality of surface litter increase, providing more substrates for soil microbes. This stimulates microbial activity, leading to faster decomposition and increased nitrogen mineralization and release, significantly increasing soil nitrogen content and thereby reducing the C/N ratio (Ling et al., 2022; Zhang et al., 2023).

Our study also found that mixed plantations reduced BD (Figure 4). Lower bulk density improves soil aeration, which facilitates root respiration and enhances root growth and nutrient uptake, consistent with the findings of Guo et al. (2023). The reduction in soil bulk density often stems from the complementary distribution of deep and shallow roots in mixed plantations, which increases soil porosity (Liu et al., 2021). Additionally, the greater litter input and faster decomposition in mixed plantations promote the formation of soil aggregates via humus accumulation, thereby improving soil pore structure (Qin et al., 2013). In contrast, monocultures, with limited root distribution and lower, slower-decomposing litter input, tend to have higher soil bulk density (Qin et al., 2013; Liu et al., 2021). Furthermore, mixed plantations significantly increased SM (Figure 4), possibly due to the thick litter and debris layer retaining moisture and reducing water loss through evaporation (Liu B. et al., 2023). Mixed plantations have been confirmed to be more effective than monocultures in enhancing soil water retention (Gong et al., 2024). Therefore, from the perspective of soil and water conservation, afforestation with mixed species is preferable to monoculture.

Changes in soil microbial biomass reflect shifts in microbial community structure and serve as key indicators of soil fertility and microbial metabolic activity (Zhang et al., 2014). Urease activity, closely linked to soil nitrogen availability, is also a crucial indicator of soil quality (Dong et al., 2023). In this study, mixed plantations led to marked increases in MBC, MBN, and urease activity (Figure 4). Their higher species diversity results in a broader range of organic inputs, providing diverse substrates that stimulate microbial activity (Singh et al., 2012). Furthermore, differences in species composition in mixed plantations lead to higher nitrogen content and lower C/N ratios in litter, accelerating decomposition and enhancing microbial activity (Peng et al., 2025), thus increasing MBC and MBN relative to monocultures. However, it is worth noting that while litter can enhance microbial biomass, it may also trigger the priming effect, accelerating the decomposition of native soil organic carbon and potentially resulting in a net loss or reduced stability of soil carbon stocks (Feng et al., 2022). The increase in urease activity may be due to the elevated levels of inorganic nitrogen in mixed plantations, which provide more substrates for urease and stimulate its activity (Luo et al., 2022). Other studies have suggested that enhanced enzyme activity is often the result of multiple interacting factors, including increased soil pH, improved aeration, and higher availability of nutrients (Guo et al., 2023).

4.3 Correlations between the EMF and soil microbial diversity and physical properties

Numerous studies have demonstrated that mixed plantations generally outperform monocultures across a range of ecosystem functions (Pretzsch et al., 2015; Gong et al., 2021; Dai et al., 2023). Building on these findings, our study adopted an integrative perspective by examining EMF, and showed that mixed plantations significantly enhanced overall ecosystem performance (Figure 6), consistent with previous findings (Xu H. et al., 2023). This result highlights the ecological advantage of mixed plantations in simultaneously promoting multiple ecosystem functions. However, other studies have suggested that differences in EMF between mixed and monoculture plantations may depend on the specific tree species used in afforestation (Li X. et al., 2024). Species composition influences interspecific interactions—such as complementarity or competition—which in turn significantly affect EMF levels. These underlying mechanisms merit further investigation.

Regression analyses indicated a significant correlation between EMF and both soil microbial diversity and physical properties. Soil microbial communities were key predictors of EMF and important indicators for forest management (Wang J. et al., 2022). Consistent with previous findings (Shi et al., 2021; Li et al., 2023), the EMF index showed significant positive correlations with both bacterial and fungal Shannon indices (Figure 7). Such positive relationships may arise from multifunctional niche complementarity and interspecific functional dissimilarity among microbial taxa (Luo et al., 2018). Soil microbial communities contribute directly to essential processes such as organic matter decomposition and nutrient mineralization, which support multiple ecosystem functions (Delgado-Baquerizo et al., 2016). Moreover, EMF was positively correlated with SM but negatively correlated with BD (Figures 8A,B), indicating that improved soil structure and moisture conditions can enhance EMF. High bulk density may reduce soil porosity and aeration, constraining root growth and microbial activity and ultimately decreasing EMF (Niu et al., 2024), whereas optimal soil moisture facilitates nutrient transport and plant growth, thereby enhancing multiple ecosystem functions (Li P. et al., 2022; Wang et al., 2024). Although these factors were significantly correlated with EMF, they explained only a small proportion of its variation (Table 4), suggesting that other unmeasured factors such as aboveground biodiversity, litter quality, and climatic conditions likely also contribute to EMF regulation.

4.4 Limitations and future directions

Our meta-analysis demonstrates that mixed plantations generally exert positive effects on soil microbial diversity and a range of ecosystem functions. In addition, it provides insights into the drivers of EMF. Nonetheless, several limitations should be acknowledged. The main limitations of this study include: (1) a focus on widely reported factors, which precluded the inclusion of other key variables like mixing proportion and stand age due to data scarcity; (2) a restricted geographic scope and limited sample size, which reduced the representation of diverse mixing ratios; and (3) the lack of consideration for microbial communities in deeper soil horizons. Consequently, future studies should aim to broaden geographic coverage, investigate deeper soil profiles, and examine a wider range of species compositions to advance our understanding of how mixed plantations shape microbial diversity and ecosystem processes.

5 Conclusion

This meta-analysis revealed that mixed plantations increased soil microbial diversity and enhanced EMF. Importantly, the positive correlation between microbial diversity and EMF underscores a potential central role of soil microbial communities in sustaining multiple ecosystem functions. Moreover, the significant relationships between EMF and soil physical properties underscore the importance of a well-structured soil environment in supporting ecosystem functioning. Although the study confirms the general benefits of mixed plantations, it also reveals that their effectiveness varies with N-fixing status, age structure, and species mixture type. In summary, mixed plantations offer significant ecological advantages over monocultures by enhancing soil microbial diversity and improving multiple ecosystem functions. Consequently, mixed plantations are a more effective afforestation strategy than monocultures in maintaining biodiversity and enhancing ecosystem multifunctionality.

Data availability statement

The original contributions presented in this study are included in this article/Supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

KX: Conceptualization, Data curation, Formal analysis, Methodology, Software, Validation, Visualization, Writing – original draft. YX: Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing. XL: Conceptualization, Funding acquisition, Methodology, Supervision, Writing – review & editing.

Funding

The author(s) declare financial support was received for the research and/or publication of this article. This work was funded by the National Key R&D program of China (grant 2023YFE0112801).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that no Generative AI was used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/ffgc.2025.1694630/full#supplementary-material

References

An, R., Ma, F., Cui, H., Qin, G., Huang, Y., and Tian, Q. (2019). Analysis of bacterial community structure and diversity characteristics of mixed forest of Robinia pseudoacacia and Ailanthus altissima and there pure forest in the Yellow River Delta. Acta Ecol. Sin. 39, 7960–7967. doi: 10.5846/stxb201809041886

Crossref Full Text | Google Scholar

Bai, Y., Zhou, Y., Du, J., Zhang, X., Feng, J., and Feng, J. (2025). Tree species influence microbiome-mediated nutrient sequestration in soil aggregates of subtropical plantations in China. Appl. Soil Ecol. 209:106034. doi: 10.1016/j.apsoil.2025.106034

Crossref Full Text | Google Scholar

Bastida, F., Eldridge, D. J., Garcia, C., Kenny Png, G., Bardgett, R. D., and Delgado-Baquerizo, M. (2021). Soil microbial diversity-biomass relationships are driven by soil carbon content across global biomes. ISME J. 15, 2081–2091. doi: 10.1038/s41396-021-00906-0

PubMed Abstract | Crossref Full Text | Google Scholar

Chen, C., Yin, G., Hou, L., Jiang, Y., Sun, D., Liang, X., et al. (2023). Reclamation of tidal flats to paddy soils reshuffles the soil microbiomes along a 53-year reclamation chronosequence: Evidence from assembly processes, co-occurrence patterns and multifunctionality. Environ. Int. 179:108151. doi: 10.1016/j.envint.2023.108151

PubMed Abstract | Crossref Full Text | Google Scholar

Dai, J., Li, Y., and Wang, L. (2023). Mixed-species plantations alleviate deep soil water depletion and facilitate hydrological niche partitioning compared to pure plantations. For. Ecol. Manage. 539:121017. doi: 10.1016/j.foreco.2023.121017

Crossref Full Text | Google Scholar

Delgado-Baquerizo, M., Maestre, F. T., Reich, P. B., Jeffries, T. C., Gaitan, J. J., Encinar, D., et al. (2016). Microbial diversity drives multifunctionality in terrestrial ecosystems. Nat. Commun. 7:10541. doi: 10.1038/ncomms10541

PubMed Abstract | Crossref Full Text | Google Scholar

Delgado-Baquerizo, M., Reich, P. B., Trivedi, C., Eldridge, D. J., Abades, S., Alfaro, F. D., et al. (2020). Multiple elements of soil biodiversity drive ecosystem functions across biomes. Nat. Ecol. Evol. 4, 210–220. doi: 10.1038/s41559-019-1084-y

PubMed Abstract | Crossref Full Text | Google Scholar

Ding, K., Zhang, Y., Yrjälä, K., Tong, Z., and Zhang, J. (2022). The introduction of Phoebe bournei into Cunninghamia lanceolata monoculture plantations increased microbial network complexity and shifted keystone taxa. For. Ecol. Manage. 509:120072. doi: 10.1016/j.foreco.2022.120072

Crossref Full Text | Google Scholar

Dong, Q., Wang, H., Du, X., Zou, J., Cui, X., and Zhao, H. (2023). Characteristics of soil urease activity in typical stand types in low mountainous area of Northeast China. Chin. J. Appl. Environ. Biol. 29, 690–695. doi: 10.19675/j.cnki.1006-687x.2022.03050

Crossref Full Text | Google Scholar

Duan, B. B., Ren, Y. Z., Zhang, L. Q., Suzhou, C. X., Chen, G. Q., Cui, P., et al. (2021). Fungal diversity rather than bacterial diversity drives the ecosystem multifunctionality of vineyards in a semi-arid region. Int. J. Agric. Biol. Eng. 14, 126–136. doi: 10.25165/j.ijabe.20211406.5560

Crossref Full Text | Google Scholar

Egger, M., Davey Smith, G., Schneider, M., and Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ 315, 629–634. doi: 10.1136/bmj.315.7109.629

PubMed Abstract | Crossref Full Text | Google Scholar

FAO (2024). The State of the World’s Forests 2024: Forest-Sector Innovations Towards a More Sustainable Future. Rome: Food and Agriculture Organization of the United Nations.

Google Scholar

Feng, J., He, K., Zhang, Q., Han, M., and Zhu, B. (2022). Changes in plant inputs alter soil carbon and microbial communities in forest ecosystems. Global Change Biol. 28, 3426–3440. doi: 10.1111/gcb.16107

PubMed Abstract | Crossref Full Text | Google Scholar

Gamfeldt, L., Snäll, T., Bagchi, R., Jonsson, M., Gustafsson, L., Kjellander, P., et al. (2013). Higher levels of multiple ecosystem services are found in forests with more tree species. Nat. Commun. 4:1340. doi: 10.1038/ncomms2328

PubMed Abstract | Crossref Full Text | Google Scholar

Gao, D., Bai, E., Yang, Y., Zong, S., and Hagedorn, F. (2021). A global meta-analysis on freeze-thaw effects on soil carbon and phosphorus cycling. Soil Biol. Biochem. 159:108283. doi: 10.1016/j.soilbio.2021.108283

Crossref Full Text | Google Scholar

Gong, C., Tan, Q., Liu, G., and Xu, M. (2021). Impacts of species mixture on soil nitrogen stocks in the Loess Plateau of China. For. Ecol. Manage. 491:119145. doi: 10.1016/j.foreco.2021.119145

Crossref Full Text | Google Scholar

Gong, C., Tan, Q., Liu, G., and Xu, M. (2024). Positive effects of mixed-species plantations on soil water storage across the Chinese Loess Plateau. For. Ecol. Manage. 552:121571. doi: 10.1016/j.foreco.2023.121571

Crossref Full Text | Google Scholar

Gross, N., Bagousse-Pinguet, Y. L., Liancourt, P., Berdugo, M., Gotelli, N. J., and Maestre, F. T. (2017). Functional trait diversity maximizes ecosystem multifunctionality. Nat. Ecol. Evol. 1:0132. doi: 10.1038/s41559-017-0132

Crossref Full Text | Google Scholar

Guo, J., Feng, H., McNie, P., Liu, Q., Xu, X., Pan, C., et al. (2023). Species mixing improves soil properties and enzymatic activities in Chinese fir plantations: A meta-analysis. CATENA 220:106723. doi: 10.1016/j.catena.2022.106723

Crossref Full Text | Google Scholar

He, Y., Zhou, B.-J., Deng, G.-H., Jiang, X.-T., Zhang, H., and Zhou, H.-W. (2013). Comparison of microbial diversity determined with the same variable tag sequence extracted from two different PCR amplicons. BMC Microbiol. 13:208. doi: 10.1186/1471-2180-13-208

PubMed Abstract | Crossref Full Text | Google Scholar

Hedges, L. V., Gurevitch, J., and Curtis, P. S. (1999). The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156. doi: 10.2307/177062

Crossref Full Text | Google Scholar

Hoogmoed, M., Cunningham, S. C., Baker, P. J., Beringer, J., and Cavagnaro, T. R. (2014). Is there more soil carbon under nitrogen-fixing trees than under non-nitrogen-fixing trees in mixed-species restoration plantings? Agricult. Ecosyst. Environ. 188, 80–84. doi: 10.1016/j.agee.2014.02.013

Crossref Full Text | Google Scholar

Jaureguiberry, P., Titeux, N., Wiemers, M., Bowler, D. E., Coscieme, L., Golden, A. S., et al. (2022). The direct drivers of recent global anthropogenic biodiversity loss. Sci. Adv. 8:eabm9982. doi: 10.1126/sciadv.abm9982

PubMed Abstract | Crossref Full Text | Google Scholar

Khlifa, R., Paquette, A., Messier, C., Reich, P. B., and Munson, A. D. (2017). Do temperate tree species diversity and identity influence soil microbial community function and composition? Ecol. Evol. 7, 7965–7974. doi: 10.1002/ece3.3313

PubMed Abstract | Crossref Full Text | Google Scholar

Lefcheck, J. S., Byrnes, J. E. K., Isbell, F., Gamfeldt, L., Griffin, J. N., Eisenhauer, N., et al. (2015). Biodiversity enhances ecosystem multifunctionality across trophic levels and habitats. Nat. Commun. 6:6936. doi: 10.1038/ncomms7936

PubMed Abstract | Crossref Full Text | Google Scholar

Li, J., Zhou, X., Yan, J., Li, H., and He, J. (2015). Effects of regenerating vegetation on soil enzyme activity and microbial structure in reclaimed soils on a surface coal mine site. Appl. Soil Ecol. 87, 56–62. doi: 10.1016/j.apsoil.2014.11.010

Crossref Full Text | Google Scholar

Li, N., Zhang, Y., Qu, Z., Liu, B., Huang, L., Ming, A., et al. (2024). Mixed and continuous cropping eucalyptus plantation facilitated soil carbon cycling and fungal community diversity after a 14-year field trail. Indust. Crops Prod. 210:118157. doi: 10.1016/j.indcrop.2024.118157

Crossref Full Text | Google Scholar

Li, P., Yang, Z., Yan, P., and Wu, D. (2022). Quality evaluation of mixed plantations of Pinus massoniana and Castanopsis hystrix based on the soil erosion characteristics and soil physical and chemical properties. J. Central S. Univ. For. Technol. 42, 104–116. doi: 10.1016/j.foreco.2017.08.025

Crossref Full Text | Google Scholar

Li, S., Huang, X., Lang, X., Shen, J., Xu, F., and Su, J. (2020). Cumulative effects of multiple biodiversity attributes and abiotic factors on ecosystem multifunctionality in the Jinsha River valley of southwestern China. For. Ecol. Manage. 472:118281. doi: 10.1016/j.foreco.2020.118281

Crossref Full Text | Google Scholar

Li, S., Huang, X., Tang, R., Li, J., Zhu, B., and Su, J. (2023). Soil microbial diversity and network complexity sustain ecosystem multifunctionality following afforestation in a dry-hot valley savanna. CATENA 231:107329. doi: 10.1016/j.catena.2023.107329

Crossref Full Text | Google Scholar

Li, T., Wu, S., Wang, L., Lv, F., and Lan, Z. (2022). Progress in National and International Research on Mixed Forest. World For. Res. 35, 42–48. doi: 10.13348/j.cnki.sjlyyj.2022.0039.y

Crossref Full Text | Google Scholar

Li, W. Q., Huang, Y. X., Chen, F. S., Liu, Y. Q., Lin, X. F., Zong, Y. Y., et al. (2021). Mixing with broad-leaved trees shapes the rhizosphere soil fungal communities of coniferous tree species in subtropical forests. For. Ecol. Manage. 480:118664. doi: 10.1016/j.foreco.2020.118664

Crossref Full Text | Google Scholar

Li, X., Liu, Y., Wu, G., Lie, Z., Sheng, H., Aguila, L. C. R., et al. (2024). Mixed plantations do not necessarily provide higher ecosystem multifunctionality than monoculture plantations. Sci. Total Environ. 914:170156. doi: 10.1016/j.scitotenv.2024.170156

PubMed Abstract | Crossref Full Text | Google Scholar

Li, X., Wang, T., Chang, S. X., Jiang, X., and Song, Y. (2020). Biochar increases soil microbial biomass but has variable effects on microbial diversity: a meta-analysis. Sci. Total Environ. 749:141593. doi: 10.1016/j.scitotenv.2020.141593

PubMed Abstract | Crossref Full Text | Google Scholar

Liang, K., Jiang, Y., Qi, J., Fuller, K., Nyiraneza, J., and Meng, F.-R. (2020). Characterizing the impacts of land use on nitrate load and water yield in an agricultural watershed in Atlantic Canada. Sci. Total Environ. 729:138793. doi: 10.1016/j.scitotenv.2020.138793

PubMed Abstract | Crossref Full Text | Google Scholar

Ling, G., Shen, H., Fan, R., Zhang, N., Xia, C., and Hu, W. (2022). Growth and stoichiometry characteristics of C, N and P in Soil under Mixed Plantation of Different Aged Cunninghamia lanceolata and Phoebe bournei. J. Zhejiang For. Sci. Technol. 42, 14–20. doi: 10.3969/j.issn.1001-3776.2022.06.003

Crossref Full Text | Google Scholar

Liu, B., Zhen, B., Pan, Q., and He, Z. (2023). Study on soil remediation effect of open-pit mine dump under different reclamation modes. J. Anhui Agric. Sci. 51, 53–57. doi: 10.1016/j.catena.2024.108193

Crossref Full Text | Google Scholar

Liu, C.-A., Nie, Y., Zhang, Y.-M., Tang, J.-W., and Siddique, K. H. M. (2018). Introduction of a leguminous shrub to a rubber plantation changed the soil carbon and nitrogen fractions and ameliorated soil environments. Sci. Rep. 8:17324. doi: 10.1038/s41598-018-35762-0

PubMed Abstract | Crossref Full Text | Google Scholar

Liu, H., and Lu, X. (2024). Leaf–Soil C:N:P Stoichiometry and Homeostasis Characteristics of Plantations in the Yellow River Floodplain in Western Shandong, China. Forests 15:1433. doi: 10.3390/f15081433

Crossref Full Text | Google Scholar

Liu, H., Liang, Y., Liu, J., Zhang, Q., Liu, Y., Zeng, J., et al. (2025). Long-term no-tillage enhanced soil multifunctionality and reduced microbial metabolic entropy. Appl. Soil Ecol. 206:105876. doi: 10.1016/j.apsoil.2025.105876

Crossref Full Text | Google Scholar

Liu, J., Wei, Y., Du, H., Zhu, W., Zhou, Y., and Yin, Y. (2022). Effects of intercropping between morus alba and nitrogen fixing species on soil microbial community structure and diversity. Forests 13:1345. doi: 10.3390/f13091345

Crossref Full Text | Google Scholar

Liu, L., He, T., Zhu, N., Peng, Y., Gao, X., Liu, Z., et al. (2023). Effects of afforestation patterns on soil nutrient and microbial community diversity in rocky desertification areas. Forests 14:2370. doi: 10.3390/f14122370

Crossref Full Text | Google Scholar

Liu, S., Yang, Y., and Wang, H. (2018). Development strategy and management countermeasures of planted forests in China: transforming from timber-centered single objective management towards multi-purpose management for enhancing quality and benefits of ecosystem services. Acta Ecol. Sin. 38, 1–10. doi: 10.5846/stxb201712072201

Crossref Full Text | Google Scholar

Liu, X., Su, S., Li, Y., and Wang, W. (2021). Study on the ecological benefits of a plantation mixed forest model in the Loess Plateau. Arid Zone Res. 38, 380–391. doi: 10.1016/j.foreco.2023.121571

Crossref Full Text | Google Scholar

Luo, G., Rensing, C., Chen, H., Liu, M., Wang, M., Guo, S., et al. (2018). Deciphering the associations between soil microbial diversity and ecosystem multifunctionality driven by long-term fertilization management. Funct. Ecol. 32, 1103–1116. doi: 10.1111/1365-2435.13039

Crossref Full Text | Google Scholar

Luo, H., Liu, W., Yang, M., Ye, S., and Cheng, F. (2022). Differences of soil physicochemical property, phenolic acid and enzyme activities in different Eucalyptus mixed plantations. J. Northwest A F Univ. 50:76. doi: 10.13207/j.cnki.jnwafu.2022.12.007

Crossref Full Text | Google Scholar

Ma, L., Ma, J., Yan, P., Tian, F., Peñuelas, J., Rao, M. P., et al. (2025). Planted forests in China have higher drought risk than natural forests. Glob. Change Biol. 31:e70055. doi: 10.1111/gcb.70055

PubMed Abstract | Crossref Full Text | Google Scholar

Ma, X., Geng, Q., Zhang, H., Bian, C., Chen, H. Y. H., Jiang, D., et al. (2021). Global negative effects of nutrient enrichment on arbuscular mycorrhizal fungi, plant diversity and ecosystem multifunctionality. New Phytol. 229, 2957–2969. doi: 10.1111/nph.17077

PubMed Abstract | Crossref Full Text | Google Scholar

Ma, Z., and Chen, H. Y. H. (2016). Effects of species diversity on fine root productivity in diverse ecosystems: a global meta-analysis. Global Ecol. Biogeogr. 25, 1387–1396. doi: 10.1111/geb.12488

Crossref Full Text | Google Scholar

Maestre, F. T., Quero, J. L., Gotelli, N. J., Escudero, A., Ochoa, V., Delgado-Baquerizo, M., et al. (2012). Plant species richness and ecosystem multifunctionality in Global Drylands. Science 335, 214–218. doi: 10.1126/science.1215442

PubMed Abstract | Crossref Full Text | Google Scholar

Mensah, S., Salako, K. V., Assogbadjo, A., Glèlè Kakaï, R., Sinsin, B., and Seifert, T. (2020). Functional trait diversity is a stronger predictor of multifunctionality than dominance: Evidence from an Afromontane forest in South Africa. Ecol. Indicat. 115:106415. doi: 10.1016/j.ecolind.2020.106415

Crossref Full Text | Google Scholar

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., and The, P. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 6:e1000097. doi: 10.1371/journal.pmed.1000097

PubMed Abstract | Crossref Full Text | Google Scholar

Mus, F., Crook, M. B., Garcia, K., Garcia Costas, A., Geddes, B. A., Kouri, E. D., et al. (2016). Symbiotic nitrogen fixation and the challenges to its extension to nonlegumes. Appl. Environ. Microbiol. 82, 3698–3710. doi: 10.1128/AEM.01055-16

PubMed Abstract | Crossref Full Text | Google Scholar

Niu, W., Ding, J., Fu, B., Zhao, W., Han, Y., Zhou, A., et al. (2024). Ecosystem multifunctionality is more related to the indirect effects than to the direct effects of human management in China’s drylands. J. Environ. Manage. 368:122259. doi: 10.1016/j.jenvman.2024.122259

PubMed Abstract | Crossref Full Text | Google Scholar

Pan, C., Sun, C., Yu, W., Guo, J., Yu, Y., and Li, X. (2023). Mixed planting enhances soil multi-nutrient cycling by homogenizing microbial communities across soil vertical scale. Land Degrad. Dev. 34, 1477–1490. doi: 10.1002/ldr.4547

Crossref Full Text | Google Scholar

Peng, S., Liu, Y., Mao, R., Liu, Y., Fan, Y., Zhou, Y., et al. (2025). Dynamic effects of Pinus massoniana replanted with broad-leaved of Schima superba on soil microbial biomass carbon and nitrogen. J. Guangxi Normal Univ. 43, 150–160. doi: 10.16088/j.issn.1001-6600.2024062801

Crossref Full Text | Google Scholar

Pretzsch, H., del Rio, M., Ammer, C., Avdagic, A., Barbeito, I., Bielak, K., et al. (2015). Growth and yield of mixed versus pure stands of Scots pine (Pinus sylvestris L.) and European beech (Fagus sylvatica L.) analysed along a productivity gradient through Europe. Eur. J. For. Res. 134, 927–947. doi: 10.1007/s10342-015-0900-4

Crossref Full Text | Google Scholar

Qin, J., Tang, X., and Yang, X. (2013). Effects of soil physical and chemical properties on different forest types of Pinus massoniana. Ecol. Environ. Sci. 22, 598–604. doi: 10.16258/j.cnki.1674-5906.2013.04.012

Crossref Full Text | Google Scholar

R Core Team (2024). R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing.

Google Scholar

Rosenberg, M. S. (2005). The file-drawer problem revisited: a general weighted method for calculating fail-safe numbers in meta-analysis. Evolution 59, 464–468. doi: 10.1111/j.0014-3820.2005.tb01004.x

Crossref Full Text | Google Scholar

Shi, X., Wang, J., Lucas-Borja, M. E., Wang, Z., Li, X., and Huang, Z. (2021). Microbial diversity regulates ecosystem multifunctionality during natural secondary succession. J. Appl. Ecol. 58, 2833–2842. doi: 10.1111/1365-2664.14015

Crossref Full Text | Google Scholar

Shu, X., Liu, W., Hu, Y., Xia, L., Fan, K., Zhang, Y., et al. (2023). Ecosystem multifunctionality and soil microbial communities in response to ecological restoration in an alpine degraded grassland. Front. Plant Sci. 14:1173962. doi: 10.3389/fpls.2023.1173962

PubMed Abstract | Crossref Full Text | Google Scholar

Shu, X., Ye, Q., Huang, H., Xia, L., Tang, H., Liu, X., et al. (2024). Effects of grazing exclusion on soil microbial diversity and its functionality in grasslands: a meta-analysis. Front. Plant Sci. 15:1366821. doi: 10.3389/fpls.2024.1366821

PubMed Abstract | Crossref Full Text | Google Scholar

Singh, K., Singh, B., and Singh, R. R. (2012). Changes in physico-chemical, microbial and enzymatic activities during restoration of degraded sodic land: Ecological suitability of mixed forest over monoculture plantation. CATENA 96, 57–67. doi: 10.1016/j.catena.2012.04.007

Crossref Full Text | Google Scholar

Sui, J., Yu, Q., Yang, K., Yang, J., Li, C., and Liu, X. (2022). Effects of Bacillus subtilis T6-1 on the rhizosphere microbial community structure of continuous cropping poplar. Biology 11:791. doi: 10.3390/biology11050791

PubMed Abstract | Crossref Full Text | Google Scholar

Sun, K., Cai, J., Liu, X., Yang, L., Li, H., Wang, G., et al. (2023). Effects of nitrogen and phosphorus supply levels and ratios on soil microbial diversity-ecosystem multifunctionality relationships in a coastal nontidal wetland. Sci. Total Environ. 874:162472. doi: 10.1016/j.scitotenv.2023.162472

PubMed Abstract | Crossref Full Text | Google Scholar

van der Plas, F., Manning, P., Allan, E., Scherer-Lorenzen, M., Verheyen, K., Wirth, C., et al. (2016). Jack-of-all-trades effects drive biodiversity–ecosystem multifunctionality relationships in European forests. Nat. Commun. 7:11109. doi: 10.1038/ncomms11109

PubMed Abstract | Crossref Full Text | Google Scholar

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor Package. J. Stat. Softw. 36, 1–48. doi: 10.18637/jss.v036.i03

Crossref Full Text | Google Scholar

Wan, X., Wang, W., Liu, J., and Tong, T. (2014). Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med. Res. Methodol. 14:135. doi: 10.1186/1471-2288-14-135

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, B., Yang, X., Zhu, Y., Tu, Y., Wang, D., and Indree, T. (2024). Plant diversity mediates the response of ecosystem multifunctionality to climate factor in Eastern Eurasian Steppe. Glob. Ecol. Conserv. 50:e02827. doi: 10.1016/j.gecco.2024.e02827

Crossref Full Text | Google Scholar

Wang, J., Shi, X., Lucas-Borja, M. E., Lam, S. K., Wang, Z., and Huang, Z. (2022). Plants, soil properties and microbes directly and positively drive ecosystem multifunctionality in a plantation chronosequence. Land Degrad. Dev. 33, 3049–3057. doi: 10.1002/ldr.4371

Crossref Full Text | Google Scholar

Wang, X., Feng, J., Ao, G., Qin, W., Han, M., Shen, Y., et al. (2023). Globally nitrogen addition alters soil microbial community structure, but has minor effects on soil microbial diversity and richness. Soil Biol. Biochem. 179:108982. doi: 10.1016/j.soilbio.2023.108982

Crossref Full Text | Google Scholar

Wang, X., Guo, Y., Zhao, H., Meng, F., and Liu, G. (2018). Decomposition characteristics and its nutrient dynamics of the leaf litter mixtures of Larix principis-rupprechtii and Betula platyphylla. For. Ecol. Sci. 33, 29–36. doi: 10.13466/j.cnki.lyzygl.2018.03.017

Crossref Full Text | Google Scholar

Wang, Y., Ma, L., Liu, Z., Chen, J., Song, H., Wang, J., et al. (2022). Microbial interactions play an important role in regulating the effects of plant species on soil bacterial diversity. Front. Microbiol. 13:984200. doi: 10.3389/fmicb.2022.984200

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, Y., Zou, G., Fu, H., and Liu, H. (2005). Development and advance of soil nitrogen mineralization. Chin. Agric. Sci. Bulle. 21, 203–208. doi: 10.3969/j.issn.1000-6850.2005.10.056

Crossref Full Text | Google Scholar

Wu, W., Zhou, X., Wen, Y., Zhu, H., You, Y., Qin, Z., et al. (2019). Coniferous-broadleaf mixture increases soil microbial biomass and functions accompanied by improved stand biomass and litter production in subtropical China. Forests 10:879. doi: 10.3390/f10100879

Crossref Full Text | Google Scholar

Wu, Y., Zhang, S., Xie, G., Shao, Y., Shi, S., Lin, J., et al. (2025). Response of leaf functional traits and rhizosphere microbial communities of Castanopsis hystrix in three subtropical plantations with leguminous or non-leguminous trees. Forests 16:367. doi: 10.3390/f16020367

Crossref Full Text | Google Scholar

Xiang, Y., Li, Y., Luo, X., Liu, Y., Huang, P., Yao, B., et al. (2022). Mixed plantations enhance more soil organic carbon stocks than monocultures across China: implication for optimizing afforestation/reforestation strategies. Sci. Total Environ. 821:153449. doi: 10.1016/j.scitotenv.2022.153449

PubMed Abstract | Crossref Full Text | Google Scholar

Xiao, Y., Huang, Z., Li, Y., Zhang, Y., and Wang, M. (2022). Soil microbial community structure and diversity of typical vegetation types in Chishui River Basin. Res. Soil Water Conserv. 29, 275–283. doi: 10.13869/j.cnki.rswc.2022.06.003

Crossref Full Text | Google Scholar

Xie, H., Wang, G. G., and Yu, M. (2018). Ecosystem multifunctionality is highly related to the shelterbelt structure and plant species diversity in mixed shelterbelts of eastern China. Glob. Ecol. Conserv. 16:e00470. doi: 10.1016/j.gecco.2018.e00470

Crossref Full Text | Google Scholar

Xu, H., Wei, X., and Cheng, X. (2023). Fungal diversity dominates the response of multifunctionality to the conversion of pure plantations into two-aged mixed plantations. Sci. Total Environ. 866:161384. doi: 10.1016/j.scitotenv.2022.161384

PubMed Abstract | Crossref Full Text | Google Scholar

Xu, Y., Li, C., Zhu, W., Wang, Z., Wu, L., and Du, A. (2022). Effects of enrichmemt planting with native tree species on bacterial community structure and potential impact on Eucalyptus plantations in southern China. J. For. Res. 33, 1349–1363. doi: 10.1007/s11676-021-01433-6

Crossref Full Text | Google Scholar

Xu, Y., Ren, S., Liang, Y., Du, A., Li, C., Wang, Z., et al. (2021). Soil nutrient supply and tree species drive changes in soil microbial communities during the transformation of a multi-generation Eucalyptus plantation. Appl. Soil Ecol. 166:103991. doi: 10.1016/j.apsoil.2021.103991

Crossref Full Text | Google Scholar

Xu, Z., Hu, Z., Jiao, S., Bell, S. M., Xu, Q., Ma, L., et al. (2023). Depth-dependent effects of tree species identity on soil microbial community characteristics and multifunctionality. Sci. Total Environ. 878:162972. doi: 10.1016/j.scitotenv.2023.162972

PubMed Abstract | Crossref Full Text | Google Scholar

Yan, K., Dong, Y., Gong, Y., Zhu, Q., and Wang, Y. (2021). Climatic and edaphic factors affecting soil bacterial community biodiversity in different forests of China. CATENA 207:105675. doi: 10.1016/j.catena.2021.105675

Crossref Full Text | Google Scholar

Yan, P., Fernández-Martínez, M., Van Meerbeek, K., Yu, G., Migliavacca, M., and He, N. (2023). The essential role of biodiversity in the key axes of ecosystem function. Glob. Change Biol. 29, 4569–4585. doi: 10.1111/gcb.16666

PubMed Abstract | Crossref Full Text | Google Scholar

Yang, X., Tian, X., and Wu, Q. (2024). Soil bacterial community diversity of different forest types in southern subtropical Guangxi and their correlation to soil chemical properties. J. S. Agric. 55, 954–963. doi: 10.3969/j.issn.2095-1191.2024.04.005

Crossref Full Text | Google Scholar

Yu, X., Liu, X., Zhao, Z., Liu, J., and Zhang, S. (2015). Effect of monospecific and mixed sea-buckthorn (Hippophae rhamnoides) plantations on the structure and activity of soil microbial communities. PLoS One 10:e0117505. doi: 10.1371/journal.pone.0117505

PubMed Abstract | Crossref Full Text | Google Scholar

Yuan, Z. Q., Ali, A., Loreau, M., Ding, F., Liu, S. F., Sanaei, A., et al. (2021). Divergent above- and below-ground biodiversity pathways mediate disturbance impacts on temperate forest multifunctionality. Glob. Change Biol. 27, 2883–2894. doi: 10.1111/gcb.15606

PubMed Abstract | Crossref Full Text | Google Scholar

Zhang, L., Li, H., Wu, C., Linghu, G., Zhu, H., Khamphilavong, K., et al. (2023). Far-reaching effects on soil properties and underground microbial ecosystem after the introduction of black locusts in forest. Front. Ecol. Evolut. 11:1210498. doi: 10.3389/fevo.2023.1210498

Crossref Full Text | Google Scholar

Zhang, M., Wan, Z., Gao, W., and Zhang, Y. (2024). Effects of Chinese fir retention density on soil bacterial community structure in Chinese Fir and Betula luminifera mixed forests plantations in China. Forests 15:2107. doi: 10.3390/f15122107

Crossref Full Text | Google Scholar

Zhang, R., Tian, D., Chen, H. Y. H., Seabloom, E. W., Han, G., Wang, S., et al. (2022). Biodiversity alleviates the decrease of grassland multifunctionality under grazing disturbance: a global meta-analysis. Global Ecol. Biogeogr. 31, 155–167. doi: 10.1111/geb.13408

Crossref Full Text | Google Scholar

Zhang, Y., Hou, L., Li, Z., Zhao, D., Song, L., Shao, G., et al. (2020). Leguminous supplementation increases the resilience of soil microbial community and nutrients in Chinese fir plantations. Sci. Total Environ. 703:134917. doi: 10.1016/j.scitotenv.2019.134917

PubMed Abstract | Crossref Full Text | Google Scholar

Zhang, Y., Luo, Z., Li, L., Nian, L., Li, L., Niu, Y., et al. (2025). Nitrogen fertilization shapes soil microbial diversity and ecosystem multifunctionality by modulating soil nutrients. Microorganisms 13:540. doi: 10.3390/microorganisms13030540

PubMed Abstract | Crossref Full Text | Google Scholar

Zhang, Y., Ni, J., Zhou, C., Fan, F., and Xie, D. (2014). Effects of configuration mode of crop-mulberry system in purple arid hillside field on SMBC and SMBN in the Three Gorges Reservoir. Chin. J. Eco-Agricult. 22, 766–773. doi: 10.3724/SP.J.1011.2014.40377

Crossref Full Text | Google Scholar

Zhou, C., Gao, Q., Tigabu, M., Wang, S., Cao, S., and Yu, Y. (2024). Continuous planting of Chinese fir monocultures significantly influences dissolved organic matter content and microbial assembly processes. Sci. Total Environ. 926:171943. doi: 10.1016/j.scitotenv.2024.171943

PubMed Abstract | Crossref Full Text | Google Scholar

Zhou, J., Zhang, J., Tian, S.-T., and Chen, E. (2023). Soil carbon and nitrogen contents and aggregate composition of different forest types in Southeast Henan. J. Northwest For. Univ. 38, 74–81. doi: 10.3969/j.issn.1001-7461.2023.04.09

Crossref Full Text | Google Scholar

Zhu, Y., Peng, J., Wei, Z., Shen, Q., and Fusuo, Z. (2021). Linking the soil microbiome to soil health. Sci. Sin. 51, 1–11. doi: 10.1360/SSV-2020-0320

Crossref Full Text | Google Scholar

Zhuang, J., Liu, Z., Huang, Y., Zhou, H., Xian, J., Sun, S., et al. (2023). Community characteristics of soil bacteria and fungi in Robinia pseudoacacia plantations based on high-throughput sequencing. J. Central S. Univ. For. Technol. 43, 92–100. doi: 10.14067/j.cnki.1673-923x.2023.04.010

Crossref Full Text | Google Scholar