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Article

The Impacts of Tree Species on Soil Properties in Afforested Areas: A Case Study in Central Subtropical China

by
Miao Hu
1,2,
Yiping Wang
3,
Huihu Li
2,
Liping Hu
3,
Qiaoli Liu
2,
Fan Zhou
3,
Aihong Yang
2,
Faxin Yu
2,* and
Xunzhi Ouyang
1,*
1
College of Forestry, Jiangxi Agricultural University, Nanchang 330045, China
2
Jiangxi Provincial Key Laboratory of Improved Variety Breeding and Efficient Utilization of Native Tree Species, Institute of Biological Resources, Jiangxi Academy of Sciences, Nanchang 330096, China
3
Gannan Arboretum, Ganzhou 341299, China
*
Authors to whom correspondence should be addressed.
Forests 2024, 15(6), 895; https://doi.org/10.3390/f15060895
Submission received: 26 April 2024 / Revised: 13 May 2024 / Accepted: 20 May 2024 / Published: 22 May 2024
(This article belongs to the Special Issue Forest Soil Physical, Chemical, and Biological Properties)
Browse Figures
Versions Notes

Abstract

:
Afforestation plays a critical role in ecosystem restoration and carbon sequestration. However, there continues to be insufficient knowledge about the long-term effects of different tree species on the forest soil in central subtropical China. In this study, five indigenous afforestation tree species commonly used in the region, including Bretschneidera sinensis, Liriodendron chinense, Schima superba, Phoebe bournei, and Cunninghamia lanceolata, were selected to explore their long-term effects on the forest soil. The soil’s physicochemical properties, organic carbon content, enzyme activity, and respiration were investigated. Our results revealed significant differences in the soil physicochemical properties, enzyme activity, organic carbon content, and soil respiration among the different tree species even with the same tree species types. Broad-leaved species, particularly L. chinense and P. bournei, exhibited superior soil physicochemical properties, higher amounts of organic carbon contents, enzyme activity, and soil respiration compared to coniferous species C. lanceolata. Notably, for the two studied evergreen tree species, P. bournei seemed to improve the forest soil quality more than S. superba. Hence, increasing the proportion of broad-leaved tree species may have a beneficial effect on the soil’s physicochemical properties and microecology. Furthermore, considering tree species’ compositions in afforestation will help to optimize soil quality and ecosystem health.

1. Introduction

The restoration of trees stands as one of the most efficacious strategies for mitigating climate change [1]. The existing research indicates that afforestation possesses substantial carbon sequestration potential [2,3]. This not only serves to alleviate the impacts of climate change, but also plays a crucial role in the conservation of forest ecosystems [4,5]. Afforestation can significantly impact the soil’s nutrient status and improve the soil’s microbial ecology [6,7]. Forests harbor diverse microbial populations crucial for ecosystem decomposition, material cycling, and energy flow [8,9,10].
Forest soil attributes, including the size and quality of the soil’s organic carbon (SOC) reserves, are subject to intricate interactions among climates, soil types, management practices, and tree species [11,12,13]. The soil is a complex system where chemical, physical, and biological factors interact, maintaining a dynamic equilibrium [14]. Trees impact the soil through a variety of mechanisms. Their canopy influences light exposure and precipitation, while their root structures change the soil’s physical properties, creating a habitat for microorganisms. Additionally, litterfall and root exudates can alter soil properties [15]. When natural forests are converted into artificial forests, changes occur in the quantity and quality of litter input, as well as in the soil’s physicochemical properties and microbial community [16]. Different monocultures of tree species exhibit variations in their impacts on soil properties such as soil moisture, soil carbon storage, the C/N ratio, and pH [17,18]. These factors also directly or indirectly influence the soil’s microbial communities [8,19,20,21,22,23]. These microorganisms are vital for nutrient cycling and soil carbon sequestration in artificial forests, exerting a positive influence on the soil’s physicochemical properties and tree health [24]. Detailed investigations into soil characteristic changes following afforestation with different tree species over time are essential for understanding the impact of land-use changes on soil nutrient dynamics and supplies [25].
Tree species can influence soil characteristics through various mechanisms, such as altering light availability [26], changing litter inputs [27], modifying root exudates [6], and affecting soil properties [28]. Additionally, tree species can indirectly impact soil properties by influencing other biota [8,29]. Extensive research has been conducted on the impact of tree species on forest soil characteristics [16,17,30]. Increasing evidence suggests that the effects of tree species on soil properties vary [31,32,33]. Under identical conditions, planting different tree species as monocultures can result in substantial soil differences [23], and even in mixed forests, the influence of individual tree species can be discerned in the surface soil [34]. Such differences may arise from both deciduous and coniferous tree species and may also stem from native versus exotic tree species [35,36,37,38]. Therefore, the accurate assessment of the impact of tree species on soil is imperative when undertaking afforestation.
Currently, to further enhance forest quality, the planting proportion of broad-leaved tree species in the subtropical regions of Central China continues to increase. Indigenous, precious tree species such as Bretschneidera sinensis, Liriodendron chinense, Schima superba, Phoebe bournei, and Cunninghamia lanceolata are increasingly utilized in afforestation. However, there is a limited amount of research assessing the impact of these afforestation tree species on the soil in this region, especially concerning long-term evaluations of the forest soil. The research objectives of the present study include: (1) investigating the differences in the long-term effects on soil properties caused by the prolonged cultivation of various tree species in the subtropical region over 30 years, (2) assessing whether the soil properties of forest land with broad-leaved tree species are superior to coniferous tree species, and (3) assessing whether the soil properties of forests within conifer, deciduous and evergreen broad-leaved categories of trees were different.

2. Materials and Methods

2.1. Site Description

The study was conducted in the Gannan Arboretum in Ganzhou City, Jiangxi Province. Situated on the eastern slopes of the Luoxiao Mountains in southeastern China, the region features a mid-subtropical monsoon climate (25°50′35″ N, 114°22′01″ E). This study focused on five tree species commonly used for afforestation in the region. C. lanceolata, which is widely planted in subtropical China [16], was selected as a coniferous species in this study. L. chinense, a fast-growing, native, broad-leaved species, and B. sinensis, valued for its rarity as a timber species [39], both hold significant potential for afforestation in the region. Consequently, L. chinense and B. sinensis were selected as deciduous broad-leaved tree species for this study. P. bournei, known for its excellent wood quality, is considered to be a valuable timber species [40]. S. superba, known for its adaptability, is extensively utilized in forest fire prevention zones and timber production [41]. Therefore, P. bournei and S. superba were selected as evergreen broad-leaved tree species for this experiment.
The experimental forest was established around January 1992, with seedlings of different tree species planted in multiple separate plots. Each plot covered an area of no less than 50 m × 50 m, and these plots were randomly distributed. Following afforestation, there was no human interference, allowing the forest to grow naturally. The five tree species selected for this experiment were distributed across the same mountainside. We randomly selected three plots for each tree species, and then randomly designated a 20 m × 20 m quadrat within each plot. The distribution of trees within each plot was uniform with a consistent slope orientation, although there were occasional instances of tree mortality. Afforestation records indicate that the soil within the experimental area is relatively consistent.

2.2. Climatic Conditions

The experimental site is situated at the convergence of the central subtropical and south subtropical regions. The climate falls under the category of a humid subtropical monsoon climate, characterized by an average annual temperature of 18.5 °C and an average annual rainfall of 1515 mm. The majority of the precipitation occurs during the period from April to June. The soil type at the experimental site is classified as a ferric Acrisol according to the FAO soil classification system. These soils result from the weathering of granite, phyllite, and shale, and typically have a soil layer thickness ranging from 40 to 100 cm.

2.3. Sampling and Analysis

The experiment was conducted in forest stands characterized by a consistent slope aspect and slope position. For each tree species, three sample plots were established, each featuring a designated 20 m × 20 m quadrat. The quadrats were demarcated using soil respiration rings. Five points within each quadrat were selected for soil sampling. Soil samples were collected at three different depths (0–20 cm, 20–40 cm, and 40–60 cm) for each species. To ensure accuracy and minimize errors, data collection occurred during the season following leaf fall, specifically, from 25 January to 27 January.
The soil samples were subjected to air-drying in the laboratory and sieving through a 2 mm nylon sieve. Following this, the processed samples were meticulously packed into polythene bags and appropriately labeled for subsequent analysis in accordance with established standards. The analysis of the soil samples adhered to the following procedural steps.
Soil pH was potentiometrically measured using a pH meter with a combined glass electrode in a 1:2.5 soil-to-water ratio [42]. Soil electrical conductivity (EC) was determined in a 1:5 soil-to-water ratio. The alkaline nitrogen (N) content in the soil was determined through the diffusion method, where boracic acid absorbed the hydrochloric acid and was titrated [43].
The SOC content was determined via chemical oxidation using a K2Cr2O7 solution [44]. The microbial biomass carbon (MBC) was measured using the fumigation-extraction method [45,46]. Soil dissolved organic carbon (DOC) was analyzed through dichromate oxidation titration [47]. The easily oxidized organic carbon (EOC) in the soil was analyzed using a 333 mmol·L−1 potassium permanganate (KMnO4) oxidation method [48].
The soil bulk density was determined using the Kachinskii method [49]. Three soil profiles were excavated in each plot, and with the use of a soil ring knife, two undisturbed soil samples were collected from each of the three soil layers (0–20 cm, 20–40 cm, and 40–60 cm). One set of samples was utilized for bulk density and moisture content measurements, while the other set was employed for determining water retention characteristics, including the field capacity (FC), the maximum water-holding capacity (MWHC), and the capillary water-holding capacity (CWHC) [50].
Soil urease activity was determined using the indophenol blue colorimetric method, with urease activity expressed as the mass of NH3-N (mg NH3-N·g−1·d−1) produced per gram of dry soil within 24 h. Soil sucrase activity was assessed using the 2,4-dinitrosalicylic acid colorimetric method. This enzyme catalyzes the degradation of sucrose, generating reducing sugars. The further reaction with 3,5-dinitrosalicylic acid produces brownish-red amino compounds, with sucrase activity quantified as the amount of glucose (mg glucose·g−1·d−1) produced per gram of dry soil within 24 h. Hydrogen peroxide enzyme activity was measured using the ultraviolet spectrophotometric method, and its activity was expressed as the quantity of H2O2(mg H2O2·g−1·d−1) catalyzed per gram of dry soil within 24 h. Acid phosphatase activity was determined using the phosphorus benzene sodium colorimetric method, with activity expressed as the micrograms of phenol (mg phenol·g−1·d−1) produced per gram of dry soil within 24 h.
Within each quadrat, five PVC soil respiration rings (20 cm in height, 20 cm in inner diameter, buried to a depth of approximately 16 cm) were randomly positioned at four corners and the center point. The soil respiration rings were inserted into the soil 24 h in advance. Following the removal of any weeds within the rings, soil respiration rates (Rs) were measured using the Li-8100a Soil Respiration Measurement System (Li-Cor, Lincoln, NE, USA). Soil respiration measurements were conducted during clear, windless weather conditions between 8:00 a.m. and 12:00 p.m. Each soil respiration ring underwent three repeated measurements, and the average was calculated.

2.4. Data Analysis

SPSS 25.0 and Origin 2021 software were used to process the data. Utilizing a single factor analysis of variance (ANOVA), soil parameters across various soil layers were examined to analyze the disparities among different tree species in forested areas. Irrespective of tree species, distinctions in soil properties across different soil layers were analyzed (LSD, α = 0.05). A Pearson correlation analysis was used to determine the relationships between soil properties. A PCA (principal component analysis) was used for analyzing the contribution of various soil properties to the disparities in the surface soil layers among tree species. A hierarchical cluster analysis was conducted using the group average method, with the Pearson correlation distance type, resulting in the formation of three clusters. Surface soil indicators were selected as variables to conduct the hierarchical cluster analysis on sampling points of different tree species.

3. Results

3.1. Soil Physical Properties

The physical properties of the soil exhibit variations among different artificial forest stands with distinct tree species (Figure 1). Significant differences (p < 0.05) are observed in the soil bulk density, MWHC, and CWHC across different soil layers. Soil bulk density tends to increase with soil depth, while MWHC, CWHC, and FC decrease with increasing soil depth (Figure 1). Specifically, in the 0–20 cm soil layer, the soil bulk density of pure stands of L. chinense and P. bournei is significantly lower than that of other tree species (p < 0.05). However, in the deeper soil layers of 20–40 cm and 40–60 cm, there is no significant difference in soil bulk density (Figure 1A). On the other hand, MWHC, CWHC, and FC have significant differences in the 20–40 and 40–60 layers, C. lanceolata shows favorable indicators in the 20–40 cm layer but performs poorly in the 40–60 cm layer, whereas L. chinense exhibits favorable indicators across multiple depths (Figure 1B–D).

3.2. Soil Chemical Properties

We found significant differences for all the four soil chemical properties among the different tree species, and nearly the same trend of all the values for the five tree species was found across the three soil layers (Figure 2A, p < 0.05) The soil pH among the different soil layers was not significant (Figure 2A). Within each soil layer, the pH values of the L. chinense and P. bournei were higher than those of the other three tree species (Figure 2A), especially in the 0–20 cm layer. Additionally, the other three soil chemical properties for the five tree species decreased with increasing soil depth, and the differences between soil layers were significant. Specifically, we found differences in the concentrations of available nutrients across all three soil layers. P. bournei exhibited significantly higher soil-available potassium (K) compared to the other tree species, while L. chinense showed significantly higher alkaline nitrogen (N) in different soil layers than other tree species did (Figure 2C,D, p < 0.05). Notably, the nutrient content in the soil under S. superba and C. lanceolata stands was relatively lower.

3.3. SOC Components

The SOC content in the soils of the different tree species exhibited a decreasing trend with increasing soil depth (Figure 3A), and this trend became more gradual with the deepening of the soil layers. Comparable trends were observed for the DOC across different soil layers (Figure 3B). Among various tree species, L. chinense showed a significantly higher SOC content in the 0–20 cm soil layer compared to that of other species (p < 0.05). S. superba exhibited a relatively higher DOC content in the 0–20 cm soil layer, significantly surpassing that of P. bournei, which, in turn, had a relatively lower SOC content, significantly lower than that of L. chinense, B. sinensis, and P. bournei (p < 0.05).
The EOC content increased with soil depth, showing significant differences in different soil layers (Figure 3C, p < 0.05). In the 0–20 cm layer, the EOC in L. chinense stands was significantly lower than that in stands of S. superba, C. lanceolata, and B. sinensis (p < 0.05). Similarly, in the 20–40 cm layer, the EOC in L. chinense stands was lower, significantly below that of B. sinensis (p < 0.05). In the 40–60 cm soil layer, there were no significant differences among different tree species.
The MBC content in soils of different tree species decreased with increasing soil depth, and significant differences were observed among different soil layers (Figure 3D, p < 0.05). Specifically, in the 0–20 cm layer, the MBC content in the L. chinense soil was significantly higher than that for other species (p < 0.05). Additionally, the soil MBC content for P. bournei was significantly higher than that for C. lanceolata, S. superba, and B. sinensis (p < 0.05). In the 40–60 cm layer, the soil MBC for L. chinense and B. sinensis was significantly higher than that for C. lanceolata, S. superba, and P. bournei (p < 0.05).

3.4. Soil Enzyme Activity

The soil acid phosphatase activity in the soils of different tree species exhibited a decrease with increasing soil depth (Figure 4B), and significant differences were observed among the different soil layers (p < 0.05). In the 0–20 cm soil layer, the soil acid phosphatase activity in B. sinensis stands was lower, significantly below that of P. bournei and C. lanceolata (p < 0.05). In the 20–40 cm and 40–60 cm soil layers, the soil acid phosphatase activity in B. sinensis stands was higher, significantly surpassing that of S. superba and P. bournei (p < 0.05).
The soil urease activity in the soils of different tree species decreased significantly with increasing soil depth (Figure 4A, p < 0.05). In P. bournei stands, the soil urease activity was higher in different soil layers, significantly above that of C. lanceolata and S. superba in the 0–20 cm, 20–40 cm, and 40–60 cm soil layers (p < 0.05). In the 0–20 cm soil layer, L. chinense stands showed higher soil urease activity, but in the 20–40 cm and 40–60 cm soil layers, the soil urease activity was lower.
The soil catalase activity decreased with increasing soil depth, and was significantly higher in the 0–20 cm soil layer compared to deeper layers (Figure 4C, p < 0.05). The soil catalase activity in the C. lanceolata stands was relatively higher, especially in the 0–20 cm soil layer, significantly surpassing that of the other tree species (p < 0.05).
The soil sucrase activity decreased significantly with increasing soil depth (Figure 4D, p < 0.05). In the 0–20 cm soil layer, the soil catalase activity in P. bournei stands was significantly higher than that in S. superba stands (p < 0.05).

3.5. Soil Respiration

Significant differences in the soil respiration rate were observed among different tree species in the forest stands (Figure 5, p < 0.05). The soil respiration rate in the understories of L. chinense, S. superba, and P. bournei were significantly higher compared to those in the stands of P. bournei and C. lanceolata.

3.6. Correlation Analysis of Surface Soil Indicators

A correlation analysis was conducted on different soil indicators using SPSS. A Pearson correlation analysis was conducted on the surface soil (0–20 cm layer) of the five tree species to investigate the relationships among the soil physicochemical properties, enzyme activity, soil organic carbon content, and other indicators. The results revealed a significant correlation between the soil respiration rate (SR), soil urease activity, and the pH (Figure 6, p < 0.01). The SR also showed a significant correlation with the SOC (Figure 6, p < 0.05). The SOC exhibited a highly significant correlation with the EOC, alkaline N, the soil urease activity, the pH, the available K, the soil bulk density, and the soil water content (SWC) (p < 0.01), as well as a significant correlation with the SR, MBC, MWHC, and CWHC (Table S1, p < 0.05). The soil urease activity was found to be highly correlated with the pH, available K, alkaline N, SOC, EOC, and the SR (p < 0.01). In contrast, the acid phosphatase activity, catalase activity, and sucrase activity showed no significant correlation with the soil physicochemical properties (p < 0.05). Compared to other soil enzyme activity indicators, urease activity showed stronger correlations with the soil physicochemical properties.

3.7. Hierarchical Cluster Analysis and PCA Analysis

A hierarchical cluster analysis was performed on the surface soil (0–20 cm layer) properties of the different tree species using Origin. It was observed that the three sample points of L. chinense clustered together with the two sample points of P. bournei. The three sample points of C. lanceolata clustered together with the three sample points of S. superba, while the three sample points of B. sinensis clustered together with one sample point of P. bournei (Figure 7). In the PCA analysis (Figure 8), it can be observed that the cumulative contribution rate of the first two principal components reached 59.8%, which comprehensively reflects the dominant factors of soil differences among the different tree species. The first principal component explained 45.3% of the total variance, indicating that the first principal component could account for 45.3% of the soil impacts of various physicochemical factors, mainly including the alkaline N, SOC, pH, and EOC (Table S2). The second principal component explained 14.5% of the total variance, with EC and Sucrase being the main contributors. In the first principal component, the soil SOC, pH, and Alkaline N showed a positive correlation with the soil nutritional status, with the loading order being Alkaline N > SOC > pH > EOC (Figure 8, Table S2).

4. Discussion

4.1. Differences in the Soil Physicochemical Properties among the Different Tree Species

The physicochemical properties of the soil are fundamental attributes and essential characteristics that affect the flow of water, nutrients, heat, and air in forest ecosystems, thereby exerting significant influences on productivity and nutrient cycling in forest ecosystems. A soil survey of a 34-year-old pure C. lanceolata forest revealed a decrease in the soil’s organic carbon with increasing soil depth. The organic carbon content ranged from 19.76 to 20.66 g·kg−1 in the surface layer (0–10 cm) and declined to be from 5.98 to 6.74 g·kg−1 at a depth of 40–60 cm [51]. In this study, the impacts of five tree species, namely P. bournei, B. sinensis, C. lanceolata, L. chinense, and S. superba, on the soil’s structure, nutrients, microorganisms, and enzyme activity decrease with increasing soil depth. This decline is primarily due to limitations imposed by factors such as moisture, light, and air, which reduce the biological influence on the soil with increasing depth [52,53].
The effects of P. bournei, B. sinensis, C. lanceolata, L. chinense, and S. superba on surface soil (0–20 cm) properties, including pH, EC, soil bulk density, available K, alkaline N, MBC, DOC, SOC, EOC, acid phosphatase activity, urease activity, sucrase activity, catalase activity, and soil respiration, differed significantly. This variation is primarily attributed to differences in the microbial community structure, litter, and root exudate composition among the tree species. Moreover, differences exist in litter decomposition rates, nutrient return, and nutrient cycling rates, all of which influence the soil environments in different forestlands [8,19,54]. In this study, the surface soil pH under C. lanceolata was significantly lower compared to that under P. bournei, B. sinensis, and L. chinense, possibly due to long-term spruce cultivation leading to soil acidification. This could be a primary reason for the relatively low physicochemical properties, soil enzyme activity, and soil respiration indicators in spruce forest soils.
The effects of different tree species on surface soil nutrients indicate an overall positive impact of L. chinense, which exhibits relatively favorable physicochemical properties compared to B. sinensis, S. superba, and C. lanceolata forestlands. In comparison to Tsuga canadensis, the pH, Ca, Mg, K, and mineralizable nitrogen contents are generally higher beneath L. tulipifera canopies. L. tulipifera foliage has a relatively high nutrient content compared to Tsuga canadensis, leading to better soil conditions under its canopy [55]. Due to the unique structure and properties of its papery leaves, L. chinense leaves decompose rapidly upon litterfall, resulting in a low C/N ratio and faster decomposition rates compared to Betula alleghaniensis. The fallen leaves of L. chinense are abundant and readily decomposable, facilitating their rapid conversion into soil nutrients. Additionally, the soil fertility in pure L. chinense forests, as well as that in mixed forests of C. lanceolata and L. chinense, C. lanceolata, and Schima wallichii, is higher than that in pure C. lanceolata forests [56,57]. The nutrient content of L. tulipifera litter, particularly its nitrogen, phosphorus, and potassium, is the highest among tree species such as Betula lenta, Prunus serotina, and Acer saccharum, conferring certain advantages in nutrient return [58]. These findings suggest that the long-term cultivation of L. chinense, a fast-growing broadleaf species, helps maintain soil structure and fertility more effectively. Additionally, broadleaf trees generally enhance soil structure and fertility compared to conifers. Pure forests of P. bournei exhibit significantly better soil conditions than those of C. lanceolata. Overall, the long-term cultivation of broadleaf tree species such as P. bournei, B. sinensis, and L. chinense has a positive, promoting effect on the soil’s physicochemical properties.
Previous studies have indicated differences in soil characteristics between coniferous and broad-leaved trees [33,59]. However, the clustering analysis of different tree species in this study revealed that L. chinense and B. sinensis, two deciduous, broad-leaved tree species, did not cluster together. Similarly, P. bournei and S. superba, two evergreen, broad-leaved tree species, also did not cluster together. This suggests that artificial monocultures of the same type of tree species may have significant differences in their effects on soil. The characteristics of specific tree species, such as the allelopathy exhibited by S. superba, may lead to unique impacts on the soil [60]. However, it is important to note that the limited number of experimental samples in this study, due to objective constraints, resulted in limitations in the experimental results. Overall, broad-leaved tree species have a better influence on soil compared to coniferous species. Therefore, in future afforestation efforts, increasing the proportion of broad-leaved tree species could be considered. Additionally, since different tree species have varied impacts on soil, afforestation strategies should involve mixed-species planting to fully leverage the advantages of each species.

4.2. The Differences in Microbial Activity among the Different Tree Species

Different tree species can directly or indirectly influence soil microbial communities [8,19]. The increase in soil microbial abundance and diversity has a positive impact on soil physicochemical properties [24]. Previous research has demonstrated that the soil’s microbial metabolic processes and their metabolites positively influence soil aggregates, contributing to improvements in the soil’s physicochemical properties and physical structure [61]. Our study has revealed a significant positive correlation between soil microbial biomass carbon, soil urease activity, and soil moisture. Specifically, MBC shows significant positive correlations with pH, alkaline N, and SWC in the surface soil (the 0–20 cm soil layer). The SR exhibits positive significant correlations with pH and urease activity in the surface soil. Soil enzymes mediate the decomposition of soil organic matter and catalyze carbon and nitrogen transformations [62,63].
Previous studies have indicated a positive correlation between soil enzyme activity and SOC fractions [64]. In this study, soil urease activity was found to be highly correlated with pH, available K, alkaline N, SOC, EOC, and the soil respiration rate in the surface soil. Research by William Landesman et al. (2014) [65] indicates that tree species can influence soil microbial β-diversity by affecting soil pH. Soil pH is an important characteristic of soil properties and a significant factor influencing the composition and diversity of soil microbial communities [66]. A decrease in pH will affect the activity of soil microbes [24]. The soil microbial biomass carbon and pH content in the surface soil of pure C. lanceolata forests are significantly lower than those in mixed forests of spruce and broad-leaved tree species, with bacterial communities being more diverse in the surface soil [57]. Studies on pure C. lanceolata forests have shown a significant decrease in soil microbial biomass carbon and urease activity following C. lanceolata planting [16]. In this study, the MBC content in the surface soil, as well as the urease activity, is significantly higher in L. chinense and P. bournei stands compared to those of C. lanceolata, while soil respiration is significantly higher in L. chinense and P. bournei stands compared to C. lanceolata stands. These differences may be attributed to variations in soil pH in the surface soil layer. Coniferous litter has a high C/N ratio, and the combined action of coniferous root exudates leads to soil acidification, which is consistent with the results of this study [67]. Broad-leaved trees elevate the soil pH compared to coniferous trees, thereby enhancing soil urease activity [68].
The soil respiration rate under S. superba forests is significantly lower compared to that under P. bournei, B. sinensis, and L. chinense, and the microbial biomass carbon is significantly lower compared to that under C. lanceolata and P. bournei. This may be due to the allelopathic effects of S. superba litter, leading to lower microbial abundance and activity, resulting in a lower soil respiration rate. Additionally, the soil microbial environment is better under broad-leaved tree species compared to coniferous tree species. Increasing the proportion of broad-leaved tree species such as L. chinense and P. bournei in afforestation has a positive effect on improving the soil microecological environment.

5. Conclusions

Research on five commonly used tree species in the central subtropical region of China has revealed significant differences in the soil mineralization activity, soil physicochemical properties, and organic carbon content among different tree species. In 30-year-old, artificial, pure forests, broad-leaved tree species exhibit relatively better soil physicochemical properties compared to coniferous tree species. The organic carbon content in the soil is relatively higher, and the soil microecological status is relatively better. Afforestation with broad-leaved species has a more positive long-term impact on the soil compared to coniferous trees in the experimental region. Even among tree species within the same category, such as evergreen broad-leaved and deciduous broad-leaved species, there are significant differences in soil impacts. L. chinense, whose leaves are more easily decomposed, outperforms other tree species in its nutrient return. L. chinense, as a fast-growing broad-leaved tree species, has advantages in soil carbon accumulation, its improvement of the soil microecological environment, and its maintenance of the soil nutrient status after long-term planting. The study on the long-term effects of different tree species on soil properties provided data support for evaluating and predicting the long-term soil fertility maintenance potential of artificial forests. However, the factors contributing to interspecies differences still require more comprehensive and in-depth research.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f15060895/s1, Table S1: Correlation among soil physicochemical properties, enzyme activity, and soil respiration. * indicates correlation with p < 0.05, ** indicates correlation with p < 0.01; Table S2: Principal component analysis (PCA) loadings.

Author Contributions

Formal analysis, Q.L.; Investigation, Y.W., H.L., L.H. and F.Z.; Writing—original draft, M.H.; Writing—review & editing, A.Y.; Project administration, F.Y. and X.O. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Training Program for Academic and Technical Leaders of Major Disciplines in Jiangxi Province (20212BCJ23032); the National Natural Science Foundation of China (No.32060312); the National Government Boot Fund for Regional Science and Technology Development (20192ZDD01004); the Jiangxi Provincial Academy of Sciences Provincial-Level Comprehensive Responsibility Project (2021YSBG22019, 2023YSBG22002, 2021YSBG22016); and the Key Research and Development Program of Jiangxi Province (20203BBF63025).

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. The differences in soil physical properties among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). (A) Variations in soil bulk densities across different soil layers among the five tree species (p < 0.05). (B) Variations in soil field capacities (FCs) across different soil layers among the five tree species (p < 0.05). (C) Variations in soil capillary water-holding capacities (CWHCs) across different soil layers among the five tree species (p < 0.05). (D) Variations in soil maximum water-holding capacities (MWHCs) across different soil layers among the five tree species (p < 0.05). The uppercase letters A–C and the blue lines indicate significant differences among different soil layers (p < 0.05). The lowercase letters a–c indicate significant differences between tree species within the same soil layer (p < 0.05).
Figure 1. The differences in soil physical properties among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). (A) Variations in soil bulk densities across different soil layers among the five tree species (p < 0.05). (B) Variations in soil field capacities (FCs) across different soil layers among the five tree species (p < 0.05). (C) Variations in soil capillary water-holding capacities (CWHCs) across different soil layers among the five tree species (p < 0.05). (D) Variations in soil maximum water-holding capacities (MWHCs) across different soil layers among the five tree species (p < 0.05). The uppercase letters A–C and the blue lines indicate significant differences among different soil layers (p < 0.05). The lowercase letters a–c indicate significant differences between tree species within the same soil layer (p < 0.05).
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Figure 2. The differences in the soil chemical properties among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). (A) Variations in the soil pH across different soil layers among the five tree species (p < 0.05). (B) Variations in the soil electrical conductivity (EC) across different soil layers among the five tree species (p < 0.05). (C) Variations in the soil-available potassium (K) across different soil layers among the five tree species (p < 0.05). (D) Variations in the soil alkaline nitrogen (N) across different soil layers among the five tree species (p < 0.05). The uppercase letters A–C and the blue lines indicate significant differences among different soil layers (p < 0.05). The lowercase letters a–d indicate significant differences between tree species within the same soil layer (p < 0.05).
Figure 2. The differences in the soil chemical properties among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). (A) Variations in the soil pH across different soil layers among the five tree species (p < 0.05). (B) Variations in the soil electrical conductivity (EC) across different soil layers among the five tree species (p < 0.05). (C) Variations in the soil-available potassium (K) across different soil layers among the five tree species (p < 0.05). (D) Variations in the soil alkaline nitrogen (N) across different soil layers among the five tree species (p < 0.05). The uppercase letters A–C and the blue lines indicate significant differences among different soil layers (p < 0.05). The lowercase letters a–d indicate significant differences between tree species within the same soil layer (p < 0.05).
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Figure 3. The differences in the soil organic carbon components among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). (A) Variations in the soil total organic carbon (SOC) content across the different soil layers among the five tree species (p < 0.05). (B) Variations in the soil dissolved organic carbon (DOC) content across the different soil layers among the five tree species (p < 0.05). (C) Variations in the soil’s easily oxidizable organic carbon (EOC) content across the different soil layers among the five tree species (p < 0.05). (D) Variations in the soil microbial biomass carbon (MBC) content across the different soil layers among the five tree species (p < 0.05). The blue lines indicate significant differences among the different soil layers (p < 0.05). The uppercase letters A–C and the blue lines indicate significant differences among different soil layers (p < 0.05). The lowercase letters a–d indicate significant differences between tree species within the same soil layer (p < 0.05).
Figure 3. The differences in the soil organic carbon components among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). (A) Variations in the soil total organic carbon (SOC) content across the different soil layers among the five tree species (p < 0.05). (B) Variations in the soil dissolved organic carbon (DOC) content across the different soil layers among the five tree species (p < 0.05). (C) Variations in the soil’s easily oxidizable organic carbon (EOC) content across the different soil layers among the five tree species (p < 0.05). (D) Variations in the soil microbial biomass carbon (MBC) content across the different soil layers among the five tree species (p < 0.05). The blue lines indicate significant differences among the different soil layers (p < 0.05). The uppercase letters A–C and the blue lines indicate significant differences among different soil layers (p < 0.05). The lowercase letters a–d indicate significant differences between tree species within the same soil layer (p < 0.05).
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Figure 4. The differences in the soil enzyme activity among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). (A) Variations in the soil urease activity across the different soil layers among the five tree species (p < 0.05), where Uu represents the mass of NH3-N (mg NH3-N·g−1·d−1) produced per gram of dry soil within 24 h. (B) Variations in the soil acid phosphatase activity across the different soil layers among the five tree species (p < 0.05), where Ua represents the micrograms of phenol (mg phenol·g−1·d−1) produced per gram of dry soil within 24 h. (C) Variations in the soil catalase activity across the different soil layers among the five tree species (p < 0.05), where Uc represents the quantity of H2O2(mg H2O2·g−1·d−1) catalyzed per gram of dry soil within 24 h. (D) Variations in the soil sucrase activity across the different soil layers among the five tree species (p < 0.05), where Us represents the amount of glucose (mg glucose·g−1·d−1) produced per gram of dry soil within 24 h. The uppercase letters A–C and the blue lines indicate significant differences among different soil layers (p < 0.05). The lowercase letters a–d indicate significant differences between tree species within the same soil layer (p < 0.05).
Figure 4. The differences in the soil enzyme activity among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). (A) Variations in the soil urease activity across the different soil layers among the five tree species (p < 0.05), where Uu represents the mass of NH3-N (mg NH3-N·g−1·d−1) produced per gram of dry soil within 24 h. (B) Variations in the soil acid phosphatase activity across the different soil layers among the five tree species (p < 0.05), where Ua represents the micrograms of phenol (mg phenol·g−1·d−1) produced per gram of dry soil within 24 h. (C) Variations in the soil catalase activity across the different soil layers among the five tree species (p < 0.05), where Uc represents the quantity of H2O2(mg H2O2·g−1·d−1) catalyzed per gram of dry soil within 24 h. (D) Variations in the soil sucrase activity across the different soil layers among the five tree species (p < 0.05), where Us represents the amount of glucose (mg glucose·g−1·d−1) produced per gram of dry soil within 24 h. The uppercase letters A–C and the blue lines indicate significant differences among different soil layers (p < 0.05). The lowercase letters a–d indicate significant differences between tree species within the same soil layer (p < 0.05).
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Figure 5. The differences in the soil respiration rate among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). The lowercase letters a, b indicate differences between tree species (p < 0.05).
Figure 5. The differences in the soil respiration rate among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). The lowercase letters a, b indicate differences between tree species (p < 0.05).
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Figure 6. The correlations among soil physicochemical properties, enzyme activity, and soil respiration. * indicates a correlation with a p < 0.05, ** indicates a correlation with a p < 0.01.
Figure 6. The correlations among soil physicochemical properties, enzyme activity, and soil respiration. * indicates a correlation with a p < 0.05, ** indicates a correlation with a p < 0.01.
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Figure 7. The hierarchical cluster analysis of the surface soil physicochemical properties, enzyme activity, and soil respiration among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). The red line represents cluster 1, the blue line represents cluster 2, and the green line represents cluster 3.
Figure 7. The hierarchical cluster analysis of the surface soil physicochemical properties, enzyme activity, and soil respiration among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata). The red line represents cluster 1, the blue line represents cluster 2, and the green line represents cluster 3.
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Figure 8. The PCA analysis of the surface soil physicochemical properties among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata).
Figure 8. The PCA analysis of the surface soil physicochemical properties among the five tree species. The five tree species are Bretschneidera sinensis (B. sinensis), Liriodendron chinense (L. chinense), Schima superba (S. superba), Phoebe bournei (P. bournei), and Cunninghamia lanceolata (C. lanceolata).
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Hu, M.; Wang, Y.; Li, H.; Hu, L.; Liu, Q.; Zhou, F.; Yang, A.; Yu, F.; Ouyang, X. The Impacts of Tree Species on Soil Properties in Afforested Areas: A Case Study in Central Subtropical China. Forests 2024, 15, 895. https://doi.org/10.3390/f15060895

AMA Style

Hu M, Wang Y, Li H, Hu L, Liu Q, Zhou F, Yang A, Yu F, Ouyang X. The Impacts of Tree Species on Soil Properties in Afforested Areas: A Case Study in Central Subtropical China. Forests. 2024; 15(6):895. https://doi.org/10.3390/f15060895

Chicago/Turabian Style

Hu, Miao, Yiping Wang, Huihu Li, Liping Hu, Qiaoli Liu, Fan Zhou, Aihong Yang, Faxin Yu, and Xunzhi Ouyang. 2024. "The Impacts of Tree Species on Soil Properties in Afforested Areas: A Case Study in Central Subtropical China" Forests 15, no. 6: 895. https://doi.org/10.3390/f15060895

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