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Article

Differences in Soil Solution Chemistry and Their Vertical Variation Between Moso Bamboo Forests and Japanese Cedar Plantations in Western Japan

by
Dongchuan Fu
1 and
Masaaki Chiwa
2,*
1
Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, 744 Motooka, Fukuoka 819-0395, Japan
2
Kyushu University Forest, Faculty of Agriculture, Kyushu University, 394 Tsubakuro, Fukuoka 811-2415, Japan
*
Author to whom correspondence should be addressed.
Forests 2025, 16(10), 1519; https://doi.org/10.3390/f16101519
Submission received: 7 August 2025 / Revised: 19 September 2025 / Accepted: 24 September 2025 / Published: 26 September 2025
(This article belongs to the Section Forest Soil)
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Abstract

Bamboo invasion into adjacent forests highlights the need to clarify its ecological impacts, particularly on soil solution chemistry, which influences forest nutrient availability and downstream water quality. This study examined how bamboo invasion alters base cations and anion concentrations, their vertical distribution, and the distinct ionic compositions maintaining charge balance in soil solution by comparing Moso bamboo (BF) and adjacent Japanese cedar (CF) forests. In surface soil solution (5 cm), most ion concentrations were significantly higher in CF than in BF, likely attributable to a greater interception of atmospheric nitrogen resulting from taller tree height in CF. In vertical distribution, CF showed generally higher ion concentrations in surface soil solution than at 50 cm, whereas in BF, this phenomenon was observed only for NO3−, NH4+, and K+, consistent with bamboo’s high demand for macronutrients. Significant correlations between the concentration of NO3− and those of Ca2+ and Mg2+ were absent only in BF soil leachate. Conversely, a deficit of strong anions showed a significant correlation with the concentration of Ca2+ and Mg2+ in BF soil leachate, with HCO3− identified as a potentially major component. Our findings provide insights into the concomitant-ion relationships between base cations and NO3− across forest types and soil depths.

1. Introduction

Bamboo species are widely recognized for their commercial value, including providing timber and bamboo shoots, primarily due to their rapid growth characteristics [1]. Owing to their versatility, bamboos are cultivated globally, with approximately 35 million hectares of bamboo forest distributed across tropical, subtropical, and temperate regions [2,3]. Despite their significant socio-economic role, some monopodial bamboo species also pose a threat to the adjacent habitats [4]. For example, Phyllostachys edulis (Carrière) J.Houz. (Moso bamboo), a widespread large bamboo species predominantly found in East Asia including China and Japan [5,6,7], is known to invade adjacent forest ecosystems through extensive rhizome systems that enable clonal recruitment [3,4]. This issue is particularly pronounced in Japan’s Satoyama, a unique socioecological forest landscape [4,8,9]. Here, reduced market demand for bamboo timber and labor shortages have led to the widespread abandonment of bamboo forest management and harvesting [10]. Consequently, bamboo forests rapidly expand into neighboring forests, and their invasion poses a growing threat to species composition and ecological functions of forest ecosystems, raising increasing concern [5,11,12].
Bamboo invasion is generally reported to negatively affect species diversity and aboveground plant biomass in forests [4,11,13]. Regarding impacts on nutrient cycling, many studies focus on how bamboo’s superior clonal reproduction and flexible fine root competition strategy, accompanied by substantial resource acquisition abilities [11,14,15,16], lead to subsequent changes in soil nutrient storage and cycling rates [4,12,17]. A meta-analysis of 72 local studies on the impact of bamboo invasion on soil biochemical properties [18] indicates that, overall, bamboo invasion increases soil pH and NH4+ availability and reduces soil NO3− and potassium (K) availability. Most of these studies focus on soil as the primary carrier of nutrients. However, although soil solution serves as the direct medium for the movement and transformation of nutrients in the soil [19], the effects of bamboo invasion on soil solution chemistry remain poorly understood. Compared with forest stands, bamboo stands have a higher proportion of stemflow, which results in a unique rainwater distribution and significantly alters rainwater pH and ion concentrations [20,21]. The majority of stemflow and throughfall eventually reach the soil surface, where plant roots absorb and utilize nutrient ions and simultaneously modify the chemistry of the surface soil solution through root exudation. Highly mobile ions then percolate from the surface to deeper layers, thereby further influencing the chemistry of the subsurface soil solution. Despite this, studies on the impact of bamboo invasion on soil solution chemistry are limited to Zhou et al. [21] and Fu and Chiwa [16]. Their studies mainly focus on nitrogen (N) cycling, reporting that bamboo forests reduce NO3− concentrations in soil leachate. The effects on other major ionic components, including Ca2+, Mg2+, and K+, remain less clear.
Soil solution chemistry is crucial for understanding nutrient cycling in forests. Surface soil solution chemistry reflects soil fertility, as it represents the net effect of nutrient inputs from rainwater and litter decomposition as well as nutrient uptake by plants [19]. It has been reported that the decomposition of plant leaf litter including bamboo can strongly influence soil chemical properties, and this effect may also extend to soil solution, since soluble nutrients such as NH4+, K+, Ca2+, and NO3− constitute an important component [22,23]. Less mobile ions, such as NH4+, are readily adsorbed by the surface soil exchange complex and exchanged with other cations [24]. Highly mobile nutrients, like NO3− and Ca2+, by contrast, percolate downward with soil water into deeper layers, imparting soil leachate with distinct chemical properties [25,26]. This soil leachate is also regarded as a direct pathway for nutrient leaching into streams [27].
Tree species are a primary factor influencing soil solution chemistry in forests. Firstly, tree roots directly absorb dissolved nutrients from the soil solution, rather than from the solid soil matrix, and different tree species exhibit distinct fine root biomass and nutrient uptake capacities [28,29,30]. Secondly, differences in litter quality and quantity among tree species lead to variations in decomposition and nutrient leaching rates, which are reflected in the soil solution [26,30]. For instance, Cryptomeria japonica (Thunb. ex L.f.) D.Don (Japanese cedar), a common commercial plantation species in East Asia, is reported to have unique calcium (Ca) cycling characteristics [26,31]. It releases more organic acids in its root exudates than other coniferous species like Chamaecyparis obtusa (Siebold & Zucc.) Endl. and broadleaf species such as Fagus crenata Blume, Quercus myrsinifolia Blume, Quercus crispula Blume, and Quercus serrata Murray [32]. The high concentrations of organic acids promote weathering and increase Ca availability in the soil. Furthermore, as Ca2+ acts as a primary concomitant for NO3− in forest soil [33,34], both frequently move downward into deeper layers with percolating soil water, resulting in higher soil NO3− concentrations in deeper layers in cedar forests compared with natural forests [34]. This Japanese cedar-induced Ca mobilization mechanism also contributes to increased Ca2+ concentrations in headwater streams [26], illustrating that forest soil nutrient cycling significantly influences adjacent aquatic ecosystems. Considering these complex interactions, alterations in species composition induced by bamboo invasion could substantially impact the chemical composition of soil solution and even stream water, underscoring the need for careful attention.
Our previous study in Japan investigated the differences in NO3− concentrations in surface soil solutions (5 cm) and soil leachate (50 cm) between bamboo forests and adjacent forests [16]. This was achieved by employing a space-for-time substitution method [35], treating bamboo-dominated forests as invaded forests and adjacent woody forests as uninvaded forests, thereby indirectly predicting changes following bamboo invasion. NO3− concentrations were lower in both surface and subsurface layers of bamboo forests compared with adjacent forests, which was attributed to high NO3− uptake by the abundant fine roots of bamboo. In soil solutions, the concentrations of anions and cations are generally coupled due to the requirement of electroneutrality. This coupling suggests potential linkages between NO3− dynamics and base cations; yet, how differences in soil NO3− dynamics interact with concomitant cations, such as Ca2+ and Mg2+, across soil depths remains insufficiently understood. In bamboo forests, the consistently low levels of NO3− may alter the concentrations of base cations in both surface and subsurface layers, whereas in Japanese cedar forests the high availability of NO3− is expected to facilitate their downward co-leaching with base cations. Accordingly, compared with our previous study, which focused primarily on differences in forest NO3− cycling, the present study aims to examine a broader range of anions and cations and their interactions across soil depths.
The objectives of this study are: (1) to compare the concentrations and vertical distribution patterns of major cations (Ca2+, K+, Mg2+, Na+, NH4+) and anions (NO3−, Cl−, SO42−, and the deficit of strong anions, DSA) in soil solution between Moso bamboo (BF) and Japanese cedar (CF) forests at different depths (5 cm and 50 cm); and (2) to evaluate the concomitant ion relationship between major anions (NO3− and DSA) and major cations (Ca2+ and Mg2+) in soil solutions within each forest type and at both soil depths. This study underscores the importance of clarifying how concomitant-ion relationships differ among soil layers and contributes to a deeper understanding of how bamboo invasion modifies soil chemical properties.

2. Materials and Methods

2.1. Site Description and Soil Solution Points

This study was conducted in an abandoned Moso bamboo forest (BF) and an adjacent Japanese cedar plantation (CF), both located in the Kasuya Research Forest (33°37′ N, 130°32′ E) of Kyushu University, Kyushu Island, Japan (Figure 1). Atmospheric N deposition has been high in this region, averaging 10.3 kg N ha−1 yr−1 from 2009 to 2018, primarily due to long-range transport of air pollutants from China [36]. The mean annual temperature and precipitation were 17.4 °C and 1880 mm, respectively [37]. The soil and substrate were brown forest soil developed on Sangun metamorphic rock, corresponding to Cambisols in the WRB classification [38]. Both BF and CF were located on a steep slope (~40°) at 180–280 m a.s.l. [11] (Figure 1). The BF was an abandoned Moso bamboo forest, established around the 1970s, without fertilization, thinning, or cutting. The CF was approximately 75 years old and dominated by the evergreen coniferous tree Cryptomeria japonica, the main plantation species in Japan. Understory cover was very low in both BF and CF. Based on our field observations, new bamboo shoots and culms were observed along the margins of both BF and CF (Figure 1a). This suggests that bamboo invasion in these areas is in the initial stages. However, as Japanese cedar remained the dominant tree species in the transition area, we did not establish experimental sites in the transition area. For soil solution sampling, in March 2021, we randomly selected nine points (10 cm × 10 cm) within both BF and CF, located along an elevation of 200–250 m. Within each forest type, the distance between any two points was greater than 10 m (Figure 1).

2.2. Soil Solution Collection and Chemical Analysis

We conducted soil solution sampling on 11 separate dates between April 2021 and September 2022 (April, May, June, November, and December 2021; and January, March, May, June, July, and August 2022). Soil solution was collected using a tension lysimeter consisting of a PVC tube connected to a porous ceramic cup (Daiki Rika Kogyo Co., Ltd., Tokyo, Japan; models DIK-8392, DIK-8393) and a pressure syringe from the randomly selected points (Figure 1). At each point, a lysimeter (18 mm in diameter, 50 cm in length) was inserted at a depth of 50 cm to collect soil leachate samples. Another lysimeter (8 mm in diameter, 5 cm in length) was installed in the shallow forest soil layer (0–5 cm) to collect surface soil solutions (Figure S1). All lysimeters were initially installed in March 2021 and remained installed at the sampling points until the end of the soil solution collection. On each sampling date, lysimeters were set up for more than 24 h, and then the soil solutions in the syringes were collected by bottles. After collection, the samples in bottles were transported to the laboratory within 2 h and immediately filtered through syringe filters (0.45-μm, Ekicrodisc Acro LC3CR, Nihon Pall Ltd., Tokyo, Japan). The pH of soil solution in November 2021 was measured using a pH meter (F-54, Horiba, Japan). The concentrations of major cations (Ca2+, K+, Mg2+, Na+, NH4+) and anions (NO3−, Cl−, SO42−) were measured by Ion chromatography (cations: Dionex ICS-1000, Thermo Fisher Scientific; anions: Dionex Aquion, Thermo Fisher Scientific, Waltham, MA, USA). DSA was calculated by subtracting total anion (NO3−, Cl−, SO42−) concentration from total cation (Ca2+, K+, Mg2+, Na+, NH4+) concentration, following a modified method based on Inagaki et al. [39]. We did not include H+ concentration in the calculation of DSA, as the pH of the soil solution ranged from 6.08 to 7.05 and H+ concentration can be assumed to be negligible to calculate DSA (Table 1).

2.3. Statistical Analysis

To evaluate both the overall variation in soil solution chemistry and the individual ion-level responses to forest type (BF vs. CF) and soil depth (surface soil solution vs. soil leachate), we employed complementary statistical approaches. Firstly, redundancy analysis (RDA) was performed using the vegan package in R software version 4.3.3 after Hellinger transformation of soil solution chemistry [40]. Forest type and soil depth were included as explanatory variables, while sampling date was treated as a covariate to account for temporal variation. Secondly, we employed linear mixed-effects models (LMMs) to examine the effects of forest type, soil depth, and their interaction on the concentrations of each studied ion. In the models, forest type and soil depth were treated as fixed effects, each cation and anion were treated as a response variable, and sampling dates and sampling points were included as random effects to account for variation due to repeated measures across time and space. Tukey-adjusted post hoc pairwise comparisons were conducted within each forest type and within each soil depth. The differences in soil solution pH between forest types were evaluated using independent samples t-tests. Statistical significance was set at p < 0.05. To assess the correlations between major anion concentrations (NO3− and DSA) and major cations (Ca2+ and Mg2+), data were analyzed separately for each forest type and soil depth using Pearson correlation analysis. For visualization, linear regression models (LMs) were also fitted to the data. The resulting regression equations, along with Pearson’s r and its associated p-values (p < 0.05), were presented in the figures. All statistical analyses were conducted in R software (version 4.3.3) [41].

3. Results

3.1. Multivariate Analysis of Soil Solution Chemistry

The redundancy analysis (RDA) revealed a clear separation of soil solution chemistry between forest types along the first axis (RDA1, 54.9% of variance explained by the constraints) (Figure 2). CF soil solution chemistry was characterized by higher NO3− and Ca2+ concentrations. In contrast, BF soil solution chemistry was associated with higher NH4+, K+, and DSA concentrations, indicating distinct ionic signatures between forest types. The second axis (RDA2, 10.3%) primarily reflected differences between soil depths. In both forest types, surface soil solution chemistry tended to separate from soil leachate. The overall model was significant (adjusted R2 = 0.51, p = 0.001) (Table S1).

3.2. Soil Solution Chemistry in Different Forest Types

In the surface soil solution (0–5 cm), concentrations of Na+, Mg2+, Ca2+, Cl−, and NO3− were significantly lower in BF (mean values: 200.9, 69.1, 128.1, 284.7, and 110.3 μmol L−1, respectively) than in CF (233.2, 88.7, 257.6, 383.9, and 354.1 μmol L−1, respectively) (Figure 3; Table 2). In contrast, K+, NH4+, and SO42− concentrations were significantly higher in BF (80.6, 24.5, and 56.2 μmol L−1, respectively) than in CF (50.0, 6.8, and 47.5 μmol L−1, respectively). In the soil leachate (50 cm), only Ca2+ and NO3− concentrations were significantly lower in BF (126.0 and 47.5 μmol L−1, respectively) than in CF (189.8 and 305.6 μmol L−1, respectively). While NH4+ concentrations were lower in CF, NH4+ concentrations in both BF and CF were notably low (1.7–24.5 μmol L−1) when compared with other ion concentrations at these two depths.

3.3. Vertical Distribution Patterns of Soil Solution Chemistry

In BF, only NH4+ and K+ concentrations were significantly higher in the surface soil solution than in the soil leachate (Table 2). However, in CF, almost all anion and cation concentrations were higher in the surface layer than in the deeper layer, with SO42− being the only exception that showed no significant difference.

3.4. Correlations Between NO3− and Major Cations (Ca2+, Mg2+)

In the surface soil solution of BF, NO3− was positively and significantly correlated with both Ca2+ (slope = 0.68, r2 = 0.80) and Mg2+ (slope = 0.41, r2 = 0.68) (Figure 4a,b), and both slopes were significant. However, in the soil leachate of BF, NO3− did not show a significant correlation with either. In CF, significant positive correlations between NO3− and both Ca2+ and Mg2+ were observed in both the surface soil solution (Ca2+: slope = 0.83, r2 = 0.55; Mg2+: slope = 0.29, r2 = 0.67) and in the soil leachate (Ca2+: slope = 0.60, r2 = 0.55; Mg2+: slope = 0.23, r2 = 0.54).

3.5. Deficit of Strong Anions (DSA) and Its Correlations with Ca2+ and Mg2+

DSA in soil solution showed distinct patterns between forest types and depths (Figure S3). In the surface soil solution, DSA in BF was higher than in CF, although the difference was not significant. In the soil leachate, DSA in BF was significantly higher than in CF.
The correlation between Ca2+ and DSA was significant only in the BF soil leachate (slope = 0.17, r2 = 0.58) (Figure 5a). This relationship was absent in the BF surface solution and in both the surface soil solution and soil leachate of CF. The correlation between Mg2+ and DSA was significant in the soil leachate of both BF (slope = 0.10, r2 = 0.72) and CF (slope = 0.10, r2 = 0.40) (Figure 5b). Conversely, no significant correlations were detected in the surface soil solution of either BF or CF.

4. Discussion

4.1. Mechanisms Underlying Differences in Soil Solution Chemistry Between BF and CF

In surface soil solutions, concentrations of Mg2+ and Ca2+ in CF were significantly higher than in BF (Figure 3). This can be explained by several mechanisms. Firstly, rock weathering is often an important source of major cations in forest soils. The Sangun metamorphic rock, which is the predominant rock type at this study site, consists primarily of silicate minerals that may release Ca2+, Mg2+, and other cations upon reaction with acids [42]. The study site, located approximately 15 km from the city of Fukuoka, experiences high levels of atmospheric N deposition (10.3 kg N ha−1 yr−1) [36]. Therefore, atmospheric N deposition may enhance the rate of rock weathering. Particularly, Japanese cedar trees are known for their physiological characteristics that can accelerate the chemical weathering rate of bedrock [26]. For instance, Japanese cedar produces particularly strongly acidic stemflow [43] and exudates organic acids rapidly from its roots [32]. Both processes can accelerate the rate of chemical weathering in CF.
Secondly, NO3− concentrations in the CF surface soil solution were approximately three times higher than in BF (Figure 2 and Figure 3), requiring the acquisition of more Ca2+ and Mg2+ to maintain electroneutrality in the soil solution. This study site has experienced high levels of atmospheric acid deposition and is documented as an N-saturated ecosystem [44]. N saturation implies that atmospheric N input exceeds the uptake capacity of plants and microbes, leading to abundant NO3− availability in the surface soil [27]. In BF, bamboo develops extensive root systems that support rapid growth and substantial nutrient uptake [14,17]. Conversely, Japanese cedar employs a more conservative nutrient uptake strategy; indeed, fine root biomass in Japanese cedar plantations has been reported to be about 16 times lower than in adjacent bamboo forests [11]. Consequently, due to lower NO3− uptake in CF compared with BF, more NO3− tends to persist in the CF surface soil and can be transported downward through percolation to the soil leachate [16]. In addition, the much greater height and rougher crown surface of the Japanese cedar stands compared with the Moso bamboo stands likely enhance the interception of atmospheric N deposition (Table 1), which may further contribute to the higher NO3− concentrations observed in CF surface soil solution. To maintain electroneutrality in the soil solution, more cations, such as Ca2+ and Mg2+, may therefore be released from the soil cation exchange complex and litter decomposition. This is further supported by the positive correlations observed between the concentration of NO3− and those of Ca2+ and Mg2+ in the surface soil solution (Figure 4a,b).
In soil leachate, only Ca2+ and NO3− concentrations were significantly lower in BF than in CF (Figure 3). Given that NO3− is a highly mobile ion, moving readily with water flow [45], the sustained high concentrations of NO3− in CF soil leachate suggest substantial downward percolation and leaching of surface NO3− into deeper layers. In CF, Ca2+, as a primary concomitant ion for NO3−, moved together with it, as supported by the positive correlation between NO3− and Ca2+ observed in both the surface soil solution and soil leachate (Figure 4a). In contrast, in BF, the soil leachate NO3− concentration was only approximately half of that in the surface soil solution (Figure 2 and Figure 3, Table 2), which may indicate significant NO3− uptake by bamboo roots during downward percolation. Correspondingly, the Ca2+ concentration in the surface soil solution of BF showed no significant difference from that in the soil leachate (Table 2), suggesting limited Ca2+ downward percolation.

4.2. Differences in Vertical Distribution Patterns for Major Ions Between BF and CF

In CF, almost all major cations and anions (excluding SO42−) exhibited significantly higher concentrations in the surface soil solution than in the soil leachate (Table 2). This indicates a typical pattern of nutrient surface enrichment, where the surface soil receives nutrient inputs from atmospheric deposition, litter decomposition, and intense biological activity [45,46,47]. Even with the downward percolation and leaching of NO3− and Ca2+ in CF, nutrient ions appear to be continuously supplied to the surface soil water. However, in BF, only NO3−, NH4+, and K+ exhibited significantly higher concentrations in the surface soil solution than in the soil leachate (Table 2). This reflects the high productivity and vigorous nutrient demand of bamboo, particularly for the primary macronutrients like N and K, which may be required in greater amounts compared with other nutrients such as Ca and Magnesium (Mg). Bamboo’s extensive root system efficiently absorbs N and K, facilitating rapid nutrient cycling where elements are quickly reabsorbed and incorporated into biomass after input from litter decomposition in surface soil [11,16,48]. This rapid nutrient cycling may shorten the residence time for soluble ions in the soil, resulting in less accumulation in deeper soil layers, thus explaining the low NO3− and K+ concentrations in BF soil leachate. In addition, denitrification may also contribute to the lower NO3− concentrations in BF leachate compared with the surface soil solution. Fang et al. [49] reported that denitrification dominates soil NO3− dynamics across East Asian forest ecosystems, including Japanese forests, although the proportion of N lost via denitrification relative to NO3− leaching decreases with increasing atmospheric N deposition. However, we did not collect direct evidence of hydromorphic features or soil redox conditions in this study. Future studies quantifying gaseous N fluxes and subsoil hydromorphic conditions would be valuable for clarifying the relative contribution of plant uptake versus denitrification to the lower NO3− concentrations in BF leachate.

4.3. Possible Mechanisms for Vertical Differences in Ionic Composition Maintaining Charge Balance (Ca2+, Mg2+, NO3−, Deficit of Strong Anions) Between BF and CF

In CF, NO3− concentration was significantly positively correlated with Ca2+ and Mg2+ concentrations in both the surface soil solution and the soil leachate (Figure 4a,b). As discussed in Section 4.1, to maintain electroneutrality in soil solution, Ca2+ and Mg2+ move downward together with substantial NO3− percolation. This mechanism explains the significant positive correlations between NO3− and these cations observed even in the soil leachate of CF (Figure 4a,b).
In BF, the significant positive correlation between the concentration of NO3− and those of Ca2+ and Mg2+ disappeared in the soil leachate due to the substantial NO3− uptake by bamboo roots during percolation (Figure 4a,b). Consequently, the Ca2+ and Mg2+ derived from rock weathering in the BF leachate had to be balanced by other anions to maintain electroneutrality. We observed a significant positive correlation between Ca2+, Mg2+, and DSA in BF (Figure 5a,b), suggesting the presence of unmeasured anions serving as concomitant ions for Ca2+ and Mg2+. In this study, the pH of the soil leachate in BF was 7.05 (Table 1). Under such near-neutral pH conditions, concentration of H+ is considered negligible, thus HCO3− likely constitutes a significant portion of the DSA [39,50]. Therefore, we infer that HCO3− served as the dominant concomitant ion for cations in the BF soil leachate. This inference is supported by previous research. Firstly, according to Nye [51], when plant roots absorb NO3−, the total anion influx (NO3− + SO42− + Cl−) into the root often exceeds the total cation influx (K+ + Na+ + Mg2+ + Ca2+). Thus, to maintain electroneutrality in the rhizosphere, plants commonly release HCO3− from their roots [51]. Secondly, to meet its rapid biomass growth and high nutrient uptake, bamboo requires vigorous root respiration to provide energy [52]. The CO2 produced during soil respiration, under near-neutral pH conditions, may readily form HCO3− in soil solution. Previous studies also reported that atmospheric N deposition significantly increases soil respiration in Moso bamboo forests [53]. Huang et al. [54] also reported that fertilization significantly increased both heterotrophic and autotrophic respiration in Moso bamboo forests. As our study site is in an area with high atmospheric N deposition, this likely promoted soil respiration in BF. In summary, we attribute the potentially higher soil respiration rate in BF, promoted by high atmospheric N deposition, to the enhanced formation of HCO3−. This HCO3− may have served as the dominant concomitant ion for cations, maintaining charge balance in the BF soil leachate where NO3− was limited.

4.4. Practical Implications, Limitations and Future Perspectives

Our research confirms the differences in soil solution chemistry between bamboo forests and adjacent woody forests. We demonstrate that the vertical distribution of ion concentrations in soil solutions, as well as the stoichiometric relationships between major anions and cations, differ fundamentally in bamboo forests compared with woody forests. Given that these chemical compositions differ in both surface and deep soils, bamboo invasion likely has important implications for both surface soil fertility and the quality of water that subsequently leaches into streams. In N-saturated ecosystems, this effect is particularly noteworthy; the high nutrient demand from bamboo’s rapid growth and extensive root system can mitigate the leaching of excess nutrients, which would otherwise be considered pollutants. However, these implications should be interpreted with caution because our measurements were limited to a local region and did not continuously assess all parameters, such as HCO3− and soil solution pH. It should be noted that in our study sites, soil solution pH was close to neutral (Table 1); thus, we did not consider base cations to be coupled with H+. However, in some acidic soils, elevated base cation inputs may exchange with H+ on soil matrix surfaces, thereby reducing H+ concentration in the soil solution and resulting in higher pH. Therefore, future research in acidic forest soils is warranted to clarify the potential effects of increased base cations input on soil pH. In addition, despite the paired-site design for Moso bamboo forest and adjacent Japanese cedar plantation, we cannot completely rule out the possibility that subtle differences in microtopography or soil heterogeneity contributed to the observed differences in ion concentrations. Additionally, the installation of the soil solution lysimeter may have caused mechanical disturbance, which could have resulted in an artificial mobilization of NO3− depending on site-specific factors such as humus content, soil pH, and microbial community composition. Nevertheless, our time-series ion concentration measurements (Figure S2) suggest that the concentrations of NO3−, Ca2+, and Mg2+ in April 2021 and April 2022 were comparable, which suggests that the mechanical disturbance introduced by lysimeter installation was relatively minor. Taken together, future studies across different regions and bamboo invasion stages will be required to generalize and extend these findings. Overall, our study advances our understanding of how invasive plant species affect the dynamics of chemical elements in forest ecosystems and provides insights into the concomitant-ion relationships across forest types and soil depths.

5. Conclusions

This study investigated soil solution chemistry in bamboo forests and adjacent conifer forests, showing clear differences in major ion concentration, their vertical distribution, and the distinct ionic compositions maintaining charge balance. We found that CF generally showed higher ion concentrations in surface soil solution, likely driven by accelerated rock weathering. In addition, greater soil NO3− availability, resulting from lower N uptake and enhanced deposition associated with the larger and rougher crown surface of cedar, may also explain the higher ion concentrations in CF [16]. In contrast, BF exhibited lower cation concentrations and distinct vertical patterns, with bamboo’s high NO3− uptake altering the concomitant ion relationship between NO3− and the base cations of Ca2+ and Mg2+ in the deeper soil layer, where HCO3− likely serves as the dominant concomitant ion for Ca2+ and Mg2+. The findings of this study thus indicate that bamboo invasion may alter anion and cation concentrations in soil solutions and their concomitant ion relationships in both soil surface and subsoil layers. Such changes may also reduce the export of NO3− and base cations from soil leachate into deeper seepage and subsequently into stream water, potentially mitigating downstream eutrophication and acidification.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f16101519/s1, Table S1. Results of redundancy analysis (RDA) with sampling date as a covariate. The table shows the overall model significance, variance explained by each explanatory variable (forest type and soil depth), and significance of the first two canonical axes. Significance was assessed by permutation tests (999 permutations); Figure S1. Soil solution tension lysimeter (length of 5 cm and 50 cm, a) with porous ceramic cups and pressure syringe (b). The pressure syringes were covered by an aluminum foil during sampling; Figure S2: Temporal changes in mean concentrations (μmol L−1) of major cations and anions in Moso bamboo forest (BF) and adjacent Japanese cedar plantation (CF). The left panel presents results for surface soil solution, and the right panel for soil leachate. Vertical error bars represent standard errors (n = 9); Figure S3: Mean concentrations (μeq L−1) of deficit of strong anions in Moso bamboo forest (BF) and adjacent Japanese cedar plantation (CF). The left panel presents results for surface soil solution, and the right panel for soil leachate. Vertical error bars represent standard errors. Red asterisks over the same element indicate significant differences between BF and CF at the 0.05 level. Statistical differences were based on Tukey-adjusted post hoc pairwise comparisons (BF versus. CF, conducted within each soil depth) following a Linear Mixed-Effects Model (LMMs) analysis. In the LMMs, forest type (i.e., BF and CF) and soil depth (i.e., surface soil solution and soil leachate) were treated as fixed effects, and sampling date (n = 11) and sampling points (n = 9) were included as random effects.

Author Contributions

Conceptualization, D.F. and M.C.; Methodology, D.F. and M.C.; Investigation, D.F. and M.C.; Data Curation, D.F. and M.C.; Writing—Original Draft Preparation, D.F.; Writing—Review & Editing, M.C.; Visualization, D.F.; Supervision, M.C. All authors have read and agreed to the published version of the manuscript.

Funding

This study was financially supported by JST SPRING (grant number JPMJSP2136) and by JSPS KAKENHI (grant numbers JP22H02386).

Data Availability Statement

The data will be made available upon request to the corresponding author.

Acknowledgments

We thank the faculty members, staff, and students of the Laboratory of Ecohydrology, Kyushu University Forest, especially Hayato Abe, Zhouqiang Li and Tomonori Kume for their assistance with data acquisition and for helpful discussions. We also thank Siho Han and Ayumi Katayama of Kyushu University and Takuo Hishi of Fukuoka University for their constructive suggestions on the statistical analysis.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
BFMoso bamboo forest
CFJapanese cedar plantation
NNitrogen
CaCalcium
MgMagnesium
KPotassium
DSADeficit of strong anions

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Figure 1. Schematic illustration of the study site and experimental design. (a) Map of the Japanese archipelago showing the location of Kasuya Research Forest (KRF) study site, marked with a square; (b) topographic map with 10 m contour intervals obtained from the Geospatial Information Authority of Japan, where circles indicate selected sampling points for soil solution collection and different colors denote forest types (CF and BF); (c,d) photographs of the Japanese cedar plantation site (CF) and the Moso bamboo forest site (BF).
Figure 1. Schematic illustration of the study site and experimental design. (a) Map of the Japanese archipelago showing the location of Kasuya Research Forest (KRF) study site, marked with a square; (b) topographic map with 10 m contour intervals obtained from the Geospatial Information Authority of Japan, where circles indicate selected sampling points for soil solution collection and different colors denote forest types (CF and BF); (c,d) photographs of the Japanese cedar plantation site (CF) and the Moso bamboo forest site (BF).
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Figure 2. Redundancy analysis (RDA) of soil solution chemistry in Moso bamboo forests (BF) and Japanese cedar forests. The explanatory variables were forest type and soil depth (surface soil solution, 5 cm; soil leachate, 50 cm), with sampling date treated as a covariate. Soil solution variables are shown as arrows: nitrate (NO3−), ammonium (NH4+), chloride (Cl−), sulfate (SO42−), calcium (Ca2+), magnesium (Mg2+), potassium (K+), sodium (Na+), and dissolved strong acid anions (DSA). Each circle and triangle represent the monthly mean of all sampling points within a given forest type and soil depth. 95% confidence ellipses are drawn for each group (BF surface, BF leachate, CF surface, CF leachate). The first two RDA axes explained 54.9% and 10.3% of the constrained variance, respectively, with an adjusted R2 of 0.51.
Figure 2. Redundancy analysis (RDA) of soil solution chemistry in Moso bamboo forests (BF) and Japanese cedar forests. The explanatory variables were forest type and soil depth (surface soil solution, 5 cm; soil leachate, 50 cm), with sampling date treated as a covariate. Soil solution variables are shown as arrows: nitrate (NO3−), ammonium (NH4+), chloride (Cl−), sulfate (SO42−), calcium (Ca2+), magnesium (Mg2+), potassium (K+), sodium (Na+), and dissolved strong acid anions (DSA). Each circle and triangle represent the monthly mean of all sampling points within a given forest type and soil depth. 95% confidence ellipses are drawn for each group (BF surface, BF leachate, CF surface, CF leachate). The first two RDA axes explained 54.9% and 10.3% of the constrained variance, respectively, with an adjusted R2 of 0.51.
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Figure 3. Mean concentrations (μmol L−1) of major cations and anions in Moso bamboo forest (BF) and adjacent Japanese cedar plantation (CF). The left panel presents results for surface soil solution, and the right panel for soil leachate. Vertical error bars represent standard errors. * indicate significant differences between BF and CF at the 0.05 level. Statistical differences were based on Tukey-adjusted post hoc pairwise comparisons (BF versus. CF, conducted within each soil depth) following a linear mixed-effects model (LMMs) analysis. In the LMMs, forest type (i.e., BF and CF) and soil depth (i.e., surface soil solution and soil leachate) were treated as fixed effects, each cation and anion were treated as a response variable, and sampling date (n = 11) and sampling points (n = 9) were included as random effects. NO3− and NH4+ concentration data were obtained from Fu and Chiwa [16].
Figure 3. Mean concentrations (μmol L−1) of major cations and anions in Moso bamboo forest (BF) and adjacent Japanese cedar plantation (CF). The left panel presents results for surface soil solution, and the right panel for soil leachate. Vertical error bars represent standard errors. * indicate significant differences between BF and CF at the 0.05 level. Statistical differences were based on Tukey-adjusted post hoc pairwise comparisons (BF versus. CF, conducted within each soil depth) following a linear mixed-effects model (LMMs) analysis. In the LMMs, forest type (i.e., BF and CF) and soil depth (i.e., surface soil solution and soil leachate) were treated as fixed effects, each cation and anion were treated as a response variable, and sampling date (n = 11) and sampling points (n = 9) were included as random effects. NO3− and NH4+ concentration data were obtained from Fu and Chiwa [16].
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Figure 4. Correlations between NO3− concentrations and (a) Ca2+ and (b) Mg2+ concentrations. BF and CF represent different forest types (Moso bamboo forest and Japanese cedar plantation). Surface and leachate represent different sampling depths of soil solution (surface soil solution and soil leachate). r2 values and p-values correspond to the results of Pearson correlation analysis. The formula shows the linear regression equation. A black solid line indicates the regression trend line when the relationship is statistically significant (p < 0.05).
Figure 4. Correlations between NO3− concentrations and (a) Ca2+ and (b) Mg2+ concentrations. BF and CF represent different forest types (Moso bamboo forest and Japanese cedar plantation). Surface and leachate represent different sampling depths of soil solution (surface soil solution and soil leachate). r2 values and p-values correspond to the results of Pearson correlation analysis. The formula shows the linear regression equation. A black solid line indicates the regression trend line when the relationship is statistically significant (p < 0.05).
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Figure 5. Correlations between DSA and (a) Ca2+ and (b) Mg2+ concentrations. BF and CF represent different forest types (Moso bamboo forest and Japanese cedar plantation). Surface and leachate represent different sampling depths of soil solution (surface soil solution and soil leachate). r2 values and p-values correspond to the results of Pearson correlation analysis. The formula shows the linear regression equation. A black solid line indicates the regression trend line when the relationship is statistically significant (p < 0.05).
Figure 5. Correlations between DSA and (a) Ca2+ and (b) Mg2+ concentrations. BF and CF represent different forest types (Moso bamboo forest and Japanese cedar plantation). Surface and leachate represent different sampling depths of soil solution (surface soil solution and soil leachate). r2 values and p-values correspond to the results of Pearson correlation analysis. The formula shows the linear regression equation. A black solid line indicates the regression trend line when the relationship is statistically significant (p < 0.05).
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Table 1. Stand characteristics and pH of soil solution in Moso bamboo forest (BF) and Japanese cedar plantation (CF). ns and * show no significant difference and significant difference between different forest types based on independent samples t-test at p < 0.05. Data on stem density, stem diameter, and plant height were obtained from Shimono et al. [11].
Table 1. Stand characteristics and pH of soil solution in Moso bamboo forest (BF) and Japanese cedar plantation (CF). ns and * show no significant difference and significant difference between different forest types based on independent samples t-test at p < 0.05. Data on stem density, stem diameter, and plant height were obtained from Shimono et al. [11].
BFCF
Stem density (No. ha−1)69001020
Stem diameter (cm)8.634.1
Plant height (m)10.923.6
Soil solution pH (5 cm depth)6.086.32 ns
Soil solution pH (50 cm depth)7.056.82 *
Table 2. Mean concentrations (μmol L−1) of major cations and anions in soil solutions with different soil depths (surface soil solution, 5 cm; soil leachate, 50 cm) in Moso bamboo forest (BF) and in Japanese cedar plantation (CF). Bold p-values represent significant differences between soil depths at the 0.05 level. Statistical differences were based on Tukey-adjusted post hoc pairwise comparisons (surface vs. leachate, conducted within each forest type) following a linear mixed-effects model (LMMs) analysis. In the LMMs, forest type (BF and CF) and soil depth (surface soil solution and soil leachate) were treated as fixed effects, each cation and anion were treated as a response variable, and sampling date (n = 11) and sampling points (n = 9) were included as random effects. NO3− and NH4+ concentration data were obtained from Fu and Chiwa [16].
Table 2. Mean concentrations (μmol L−1) of major cations and anions in soil solutions with different soil depths (surface soil solution, 5 cm; soil leachate, 50 cm) in Moso bamboo forest (BF) and in Japanese cedar plantation (CF). Bold p-values represent significant differences between soil depths at the 0.05 level. Statistical differences were based on Tukey-adjusted post hoc pairwise comparisons (surface vs. leachate, conducted within each forest type) following a linear mixed-effects model (LMMs) analysis. In the LMMs, forest type (BF and CF) and soil depth (surface soil solution and soil leachate) were treated as fixed effects, each cation and anion were treated as a response variable, and sampling date (n = 11) and sampling points (n = 9) were included as random effects. NO3− and NH4+ concentration data were obtained from Fu and Chiwa [16].
SurfaceLeachatep Value
     BF
Na+200.9210.10.336
NH4+24.57.0<0.001
K+80.616.7<0.001
Ca2+128.1126.00.773
Mg2+69.169.20.706
Cl−284.7214.10.186
NO3−110.347.50.030
SO42−56.250.10.259
     CF
Na+233.2207.40.044
NH4+6.81.70.008
K+50.015.4<0.001
Ca2+257.6189.8<0.001
Mg2+88.775.70.045
Cl−383.9264.4<0.001
NO3−354.1305.60.036
SO42−47.550.90.394
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Fu, D.; Chiwa, M. Differences in Soil Solution Chemistry and Their Vertical Variation Between Moso Bamboo Forests and Japanese Cedar Plantations in Western Japan. Forests 2025, 16, 1519. https://doi.org/10.3390/f16101519

AMA Style

Fu D, Chiwa M. Differences in Soil Solution Chemistry and Their Vertical Variation Between Moso Bamboo Forests and Japanese Cedar Plantations in Western Japan. Forests. 2025; 16(10):1519. https://doi.org/10.3390/f16101519

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Fu, Dongchuan, and Masaaki Chiwa. 2025. "Differences in Soil Solution Chemistry and Their Vertical Variation Between Moso Bamboo Forests and Japanese Cedar Plantations in Western Japan" Forests 16, no. 10: 1519. https://doi.org/10.3390/f16101519

APA Style

Fu, D., & Chiwa, M. (2025). Differences in Soil Solution Chemistry and Their Vertical Variation Between Moso Bamboo Forests and Japanese Cedar Plantations in Western Japan. Forests, 16(10), 1519. https://doi.org/10.3390/f16101519

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