Next Article in Journal
Simulating Biomass Production and Water Use of Poplars in a Plantation Using a STELLA-Based Model
Previous Article in Journal
Effects of Precipitation and Soil Moisture on the Characteristics of the Seedling Bank under Quercus acutissima Forest Plantation in Mount Tai, China
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Forests
Volume 13
Issue 4
10.3390/f13040546
forests-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Forest Conversion and Soil Depth Can Modify the Contributions of Organic and Inorganic Colloids to the Stability of Soil Aggregates

by
Chong Li
1,
Zizhou Yu
1,
Jie Lin
1,
Miaojing Meng
1,
Youpeng Zhao
2,
Zhaohui Jia
1,
Xiaonan Peng
1,
Xin Liu
1 and
Jinchi Zhang
1,*
1
Co-Innovation Center for Sustainable Forestry in Southern China, Jiangsu Province Key Laboratory of Soil and Water Conservation and Ecological Restoration, Nanjing Forestry University, 159 Longpan Road, Nanjing 210037, China
2
Jiangsu Province Water Engineering Sci-Tech Consulting Co., Ltd., Nanjing 210029, China
*
Author to whom correspondence should be addressed.
Forests 2022, 13(4), 546; https://doi.org/10.3390/f13040546
Submission received: 20 March 2022 / Revised: 29 March 2022 / Accepted: 30 March 2022 / Published: 31 March 2022
(This article belongs to the Section Forest Soil)
Browse Figures
Versions Notes

Abstract

:
The stability of soil aggregates is critical for maintaining soil structures and is positively correlated with soil resident organic and inorganic colloids. Forest conversion and soil depth affects the formation of soil aggregates; however, the detailed mechanisms involved in their stabilization have not been well investigated. Therefore, to explore the main factors that influence the stability of soil aggregates for different forest types and soil depths, twelve soil samples were collected from four types of forests (native, mixed, Chinese fir, and bamboo forest) and three soil depths (0–10 cm, 10–20 cm, and 20–30 cm) in subtropical forests. The results revealed that the distributions and mean weight diameters (MWDs) of large macroaggregates in the bamboo forest were significantly lower than those in the other forest types at all soil depths (p < 0.05). Organic and inorganic colloids (organically-complexed Fe oxide and fulvic acid) in the soil directly impacted the stability of soil aggregates, while soil properties (e.g., pH and bulk density) indirectly promoted soil aggregate stability through the modification of colloids. In both native and bamboo forests, organic colloids contributed most to the stability of soil aggregates, reaching 80.31% and 61.37%, respectively. The contributions of organic colloids were found to decrease with soil depth, which was primarily due to changes in the organic matter caused by the decomposition of litter. Elucidating and promoting the specific contributions of organic and inorganic colloids on the stability of soil aggregates will be increasingly important for the optimal management of different forest types.

1. Introduction

The structural composition of soil is one of its fundamental properties, which determines its capacity to transport and retain water, air, and nutrients, while providing a suitable habitat for microbes and animals [1]. Soil structures are determined by the combination of individual soil particles [2], which are cemented together by organic and inorganic colloids and compounds to form stable microaggregates, which then form large aggregates under the action of transient cements such as root exudates [3]. Consequently, soil aggregates are intimately related to the structural composition of soils.
The stability of soil aggregates is vital for directly or indirectly maintaining a number of physical attributes related to it, such as root penetration [4]. Soil aggregate stability is also positively correlated with major colloids [5], such as soil organic matter (SOM) [6,7], and Fe/Al oxide [1,8]. Humus is a component of soil organic matter [9] that is also considered to be a colloid related to the stabilization of soil aggregates [3]. In previous studies, researchers suggested that 84.3% of the changes in soil aggregates could be explained by soil organic matter and Fe/Al oxide [10]. Consequently, a focus on soil resident organic matter (e.g., soil organic carbon, SOC in mineral-associated organic matter, SOC in particulate organic matter, humus, humic acid, and fulvic acid) and Fe/Al oxides (e.g., free Fe/Al oxides, amorphous Fe/Al oxides, and organically complexed Fe/Al oxides) is critical for elucidating the stabilization of soil aggregates.
Subtropical evergreen broadleaved forests have significant environmental and economic importance worldwide [11]. In China’s subtropical regions, the large-scale conversion of natural forests to secondary or plantation forests has proceeded over the last few decades to meet the rapid increases in timber demands [12,13]. Thus, ecosystems have been significantly negatively impacted. In previous studies, the conversion of evergreen broadleaved forests to Chinese fir forests decreased the SOC [14], altered the availability of carbon for soil microorganisms [13], reduced the soil’s p availability [15], and decreased the soil respiration rate [12].
The conversion from evergreen broadleaf forests to bamboo forests altered the chemical structures of SOC and labile C pools, and decreased the content of SOC [16]. The conversion of evergreen broadleaved forests to Chinese fir/broadleaved mixed forests modified the nanoscale pores in the soil [17] but did not alter the diversity of soil bacteria [18]. However, the impacts of forest conversion on soil aggregates and the organic and inorganic colloids that facilitate their stability have not been investigated.
Plant roots have the capacity to effectively control soil erosion and stabilize soil structures, which play critical roles in the formation of soil aggregates [19]. Soil depth might effectively regulate the composition of humus [20], aggregate-associated SOC saturation behavior [21], and soil aggregate stability [22]. The stability of soil aggregates is also significantly influenced by land use or land cover types [23]. Therefore, forest conversion and soil depth might alter soil aggregate stabilization through changes in the SOM (affected by root exudates, decomposed roots, and litter) and Fe/Al oxides (affected by root growth and soil pores). Our primary objective was to explore the main factors that influenced the stability of soil aggregates for different forest types and soil depths.
According to previous studies, we proposed the following hypotheses: (1) forest conversion alters the distribution of water-stable aggregate sizes within the soil and increases the stability of soil aggregates; (2) the soil aggregate stability of different forest types or soil depths is determined by various organic or inorganic colloids; (3) the soil depth also affects the distribution of water-stable aggregate sizes; and (4) the soil stability of soil aggregates continues to increase with soil depth. These results will be useful in guiding the management of converted forests.

2. Materials and Methods

2.1. Study Site and Experimental Design

The field experiments were conducted at the Feng Yang Mountain Nature Reserve (119°06′ E~119°15′ E, 27°46′ N~27°58′ N) in Zhejiang, China. This region resides in a warm and humid subtropical climate zone, with a mean annual temperature and precipitation of 12.3 °C and 2438 mm, respectively.
Our study included four forest types—native forest, Chinese fir/broadleaved mixed forest, Chinese fir forest, and bamboo forest—that ranged from 1300 to 1400 m above sea level. For each of the four forest types, we randomly selected three replicate plots (the dimensions of every plot were 20 m × 20 m), for a total of 12 sample stand plots. The experimental plots (20 × 20 m) had the same geographical and environmental characteristics as the control plots, such as altitude (1340–1400 m), soil type (yellow brown soil), slope (10–15°), and aspect (south).

2.2. Soil Sampling

Soil samples were taken from five random locations at every site from three soil depth layers (0–10 cm, 10–20 cm, and 20–30 cm). These soil samples were combined in the laboratory to produce one composite soil sample, after which the following measurements were made.

2.3. Measurement of Soil Physicochemical Properties and Enzyme Activities

The soil pH was measured using a PB-10 pH meter (Sartorius GmbH, Göttingen, Germany), whereas the soil TN was quantified via an elemental analyzer (Vario EL III, ELementar, Hanau, Germany). The bulk density and total capillary porosity were determined using the ring knife method [24]. The activities of soil enzymes were calculated based on the method described in a previous study [25].

2.4. Soil Aggregate Distribution and Stability Analysis

A wet-sieving method was employed to determine the soil aggregate size fraction [26]. First, the samples were sifted through 2.0 mm, 0.25 mm, and 0.53 mm sieves, to obtain four size fractions, namely >2.0 mm (large macroaggregates), 0.25–2.0 mm (small macroaggregates), 0.053–0.25 mm (microaggregates), and <0.053 mm (small microaggregates). Second, according to the mass percentage of the aggregates obtained from dry sieving, a composite soil for wet sieving was prepared. The measurement of water-stable soil aggregates was conducted using an aggregate analyzer, where the set of sieves were kept consistent with those used for dry sieving (2.0 mm, 0.25 mm, and 0.53 mm). Third, the aggregate analyzer was shaken for 30 min, after which the soil was rinsed from every sieve, oven-dried, and weighed. The mean weight diameter (MWD) was expressed by the following relationships:
M W D = ∑ n = 1 n x i × w i
where x i is the average soil aggregate diameter with i and w i is the mass percentage of soil aggregates with i.

2.5. Measurement of Organic and Inorganic Soil Colloids

The total soil organic carbon (SOC) content was measured via a potassium dichromate method [27], where 20 g of an air-dried soil sample (through a 2 mm sieve) was placed in a 250 mL flask to which 100 mL (NaPO3)6 (5 g/L) was also introduced. The flask was then shaken for 18 h under a constant temperature (90 r/min). The resulting slurry was then transferred and spread on a reciprocal sieve shaker with a 53 μm sieve, and repeatedly washed with distilled water until the water was clear on the screen. All fractions were calculated by drying at 60 °C for 24 h. The SOC in the particulate organic matter (POC) and mineral-associated organic matter (MOC) were then obtained [28].
The humic substances in the bulk soil, or every aggregate fraction, were extracted from the soil using pyrophosphate-sodium hydroxide-sodium in a 50 °C water bath. The suspended materials were then separated by centrifugation at 3500 rpm for 5 min. The residues were then dialyzed with pyrophosphate-sodium hydroxide-sodium until the solution was colorless, and the supernatant was humus [26]. Furthermore, to extract the humic acid from humus, the supernatant was acidified with H2SO4 (pH ≤ 1.5) and heated at 80 °C for 30 min. The suspended materials were filtered in the laboratory overnight, and the residues on the filter paper were percolated with H2SO4 until the precipitate was colorless. Finally, the remaining residues were dissolved at 60 °C with NaOH to separate the humic acids. The fulvic acid was measured by subtracting the humic acid from the humus [26].
The free Fe/Al oxides were extracted with citrate-biocarbonate-dithionite, whereas the amorphous Fe/Al oxides were extracted by ammonium oxalate, and the organically-complexed Fe/Al oxides were extracted using sodium pyrophosphate [29].

2.6. Statistical Analysis

One-way analysis of variance (ANOVA) (SPSS, version 26.0, Chicago, IL, USA) was applied to evaluate the statistical significance of the soil physicochemical properties, soil enzyme activities, soil aggregates, and soil organic and inorganic colloids. Two-way analysis of variance (ANOVA) (SPSS 26) was applied to evaluate the effects of forest type and soil depth on the soil physicochemical properties, soil enzyme activities, soil aggregates, and soil organic and inorganic colloids. Pearson correlation (R, https://www.r-project.org/ (accessed on 29 April 2021) and Hemi 1.0, http://hemi.biocuckoo.org/ (accessed on 29 April 2021)) was used to evaluate the stability of the soil aggregates and soil physical–chemical properties, soil enzyme activities, and soil organic and inorganic colloids.
Structural equation model (SEM) analysis (Amos, version 26.0, Chicago, IL, USA) was employed to estimate the direct and indirect effects of soil organic or inorganic colloids and soil properties on the soil aggregate stability. Some indices (χ2, p value, GFI, and RMSEM) were utilized to test the goodness of fit of the model: p value > 0.05, GFI > 0.9, RMSEM < 0.08. Boosted regression tree (BRT) analysis (R 4.1.0) was conducted to estimate the contributions of organic and inorganic soil colloids to the stability of soil aggregates. Other figures were completed in Origin (Origin, version 2015, Northampton, MA, USA).

3. Results

3.1. Soil Physicochemical Properties and Enzyme Activities

Within the 0–10 cm layer, the pH in the mixed forest was significantly lower than the pH in the bamboo forest (p < 0.05) (Figure S1A), and there were no significant differences between the native forest and other forest types (Figure S1A). Within the other soil layers, forest conversion did not significantly affect the soil pH. Further, forest conversion did not significantly affect the soil TN, total capillary porosity, and bulk density (Figure S1B–D). For the Chinese fir forest, the TN in the 0–10 cm layer was significantly higher than that in the 20–30 cm layer (p < 0.05) (Figure S2B). For the other forest types, soil depth did not significantly impact the soil properties (Figure S2A,C,D).
The soil urease activities in the mixed forest were significantly lower than those in the native forest across all soil layers (p < 0.05) (Figure S3A). The soil phosphatase activities in the mixed and bamboo forests were significantly lower than those in the native forest across all soil layers (p < 0.05) (Figure S3B). The soil urease activities in the mixed, Chinese fir, and bamboo forests were significantly lower than those in native forest across all soil layers (p < 0.05) (Figure S3C). The soil catalase activities in the mixed and Chinese fir forests were significantly lower than those in the native forest within the 10–20 cm layer. Forest conversion also significantly decreased the activities of soil catalase in the 20–30 cm layer (p < 0.05) (Figure S3D). Additionally, the activities of soil enzymes decreased significantly with the soil depth (Figure S4, Table S1).

3.2. Soil Aggregate Distribution and Stability

Within all soil layers, the distribution of large macroaggregates in the bamboo forest was significantly lower than that of in the other forest types. The distribution of small macroaggregates in the bamboo forest was significantly higher than that of in the other forest types (p < 0.05) (Figure 1). Furthermore, forest conversion did not significantly affect the distribution of microaggregates (Table S1). Within the 20–30 cm layer, the distribution of large macroaggregates in the native forest was significantly lower than that in the Chinese fir forest; however, the small macroaggregate distribution in the native forest was significantly higher than that in the Chinese fir forest (p < 0.05) (Figure 1C). Across all soil layers, the MWDs in the bamboo forest were significantly lower than those in the other forest types (p < 0.05) (Figure 2A). Furthermore, the soil depth had no significant effects on the distribution and stability of soil aggregates (Figure 2B, Table S1).

3.3. Soil Organic Colloid

The conversion of the native forest to other forest types had no significant effects on the SOC and POC contents (Figure 3A,B, Table S1). However, the MOC content in the Chinese fir forest was significantly lower than that in the native forest across all soil layers (p < 0.05) (Figure 3). Within the 20–30 cm layer, the MOC content in the mixed forest was also significantly lower than that in the native forest (p < 0.05). Further, there was a significant decrease in the SOC and POC contents with soil depth (p < 0.05) (Figure S6, Table S1).
For the 20–30 cm layer, the humus content in the native forest was significantly lower than that in the mixed and bamboo forests (p < 0.05) (Figure 4A), whereas the fulvic acid content in the native forest was significantly lower than in the mixed forest (p < 0.05) (Figure 4B). Within the 10–20 cm layer, the humic acid content in the bamboo forest was significantly higher than the other forest types (p < 0.05) (Figure 4C). Further, the humus, humic acid, and fulvic acid contents were significantly decreased (p < 0.01) with soil depth (Figure S7, Table S1).

3.4. Soil Inorganic Colloid

Within the 0–10 cm layer, the free Fe oxide in the native forest was significantly lower than that in the Chinese fir forest (p < 0.05) (Figure 5A). Within the 10–20 cm and 20–30 cm layer, the conversion of the native forest to other forest types had no significant effects on the free Fe oxide and amorphous Fe oxide (Figure 5A,B). The organically complexed Fe oxides in the native forest were significantly higher than those in the bamboo forest within the 0–10 cm and 20–30 cm layers (p < 0.05) (Figure 5C). In addition, soil depth had no significant effects on the free Fe oxide or organically complexed Fe oxide (Figure S8A,C). For the bamboo forest, the amorphous Fe oxide decreased with the soil depth (Figure S8B).
For the free Al oxide, there were no significant differences between the various forest types across all soil layers (Figure 6A, Table S1). Within the 0–10 cm layer, the amorphous Al oxide in the native forest was significantly lower than that in the other forest types (p < 0.05) (Figure 6B). Within the 10–20 cm layer, the amorphous Al oxide in the native forest was significantly lower than that in the bamboo forest (p < 0.05). Within the 20–30 cm layer, the amorphous Al oxide in the native forest was significantly lower than that in the mixed forest (p < 0.05).
For the 0–10 cm and 20–30 cm layers in the various forest types, the organically-complexed Al oxides, in significantly decreasing order, were as follows: native, mixed, Chinese fir, and bamboo forest (p < 0.05) (Figure 6C). Within the 10–20 cm layer, the organically complexed Al oxide in the native forest was significantly higher than that in the Chinese fir and bamboo forests (p < 0.05). Furthermore, the soil depth had no significant effects on the free Al oxides for all forest types (Figure S9A) but had significant effects on the amorphous Al oxide and organically complexed Al oxide (p < 0.01) (Table S1).

3.5. Correlation and SEM Analysis

The results of the Pearson correlation analysis revealed that the MWD was positively correlated with the bulk density and organically complexed Fe oxide, but negatively correlated with the pH, urease activity (Figure 7a, Table S2), and humic acid. The SOC, POC, humus, humic acid, and fulvic acid were positively correlated with the TN, total capillary porosity, urease, invertase, and catalase activity, but negatively correlated with the bulk density. The humus, humic acid, and fulvic acid were positively correlated with the SOC and POC. The free Fe oxide and amorphous Fe oxide were positively correlated with free Al oxide, but negatively correlated with the urease activity. The organically complexed Al oxide was positively correlated with phosphatase, invertase, catalase activity, and MOC, but negatively correlated with pH.
To estimate the direct and indirect effects of the organic or inorganic soil colloids and soil properties on the stability of soil aggregates, the aggregate stability was determined based on the mean weight diameter (MWD) [30]. The structural equation model (SEM) showed that the organically complexed Fe oxide (path coefficient = 0.408; p < 0.001) and fulvic acid (path coefficient = 0.377; p < 0.01) had direct positive effects on the soil aggregate stability, whereas the pH had an indirect effect through the regulation of organically complexed Fe oxide and fulvic acid. The bulk density (path coefficient = 0.322; p < 0.05) had direct positive impacts on the stability of the soil aggregates, and also had an indirect effect by regulating the organically complexed Fe oxide (Figure 7b).
The standardized total effects of the different parameters were analyzed to further assess the comprehensive regulatory effects of the driving factors on the soil aggregate stability (Figure 7c). The results revealed that the bulk density had the greatest positive integrated effect on soil aggregate stability, followed by organically complexed Fe oxide and fulvic acid. In addition, the organically complexed Fe oxide and fulvic acid had completely standardized direct effects, whereas the bulk density had completely standardized indirect effects on soil aggregate stability. In contrast to the above parameters, the pH had a highly negative total effect on the stability of soil aggregates, which confirmed the contribution of soil acidification to the aggregation process.

3.6. Main Factors Affecting Soil Aggregate Stability for Different Forest Types and Soil Depths

The results of the Pearson correlation analysis are depicted in Figure 8. In the native forest, there was no significant correlation between the MWD and all other factors (Figure 8a). In the mixed forest, the MWD was significantly negatively correlated only with the total capillary porosity. In the Chinese fir forest, the MWD was significantly negatively correlated with TN and free Al oxide, and significantly positively correlated with bulk density. In the bamboo forest, the MWD was significantly negatively correlated with the pH, TN, total capillary porosity, and humic acid, and significantly positively correlated with the bulk density (Figure 8a).
For the 0–10 cm soil layer, the MWD was significantly negatively correlated with the humic acid and amorphous Al oxide, and significantly positively correlated with the bulk density. Within the 10–20 cm soil layer, the MWD was significantly negatively correlated with the SOC, MOC, and humic acid, and significantly positively correlated with the organically complexed Fe oxide (Figure 8b). For the 20–30 cm soil layer, the MWD was significantly negatively correlated with the pH and amorphous Al oxide, and significantly positively correlated with the organically complexed Fe oxide (Figure 8b).
The boosted regression tree (BRT) model analyzed the contribution of the organic and inorganic soil colloids to MWD for different forest types and soil depths (Figure 9 and Figure 10). The results signified that in the native forest (Figure 9A), the greatest contributors to the MWD were humus, SOC, fulvic acid, and organically complexed Al oxide. In the mixed forest (Figure 9B), the largest contributors to the MWD were the amorphous Fe oxide, POC, and organically complexed Fe oxide. In the Chinese fir forest (Figure 9C), the most significant contributors to the MWD were humus, amorphous Fe, free Al oxide, and organically complexed Fe oxide. In the bamboo forest (Figure 9D), the greatest contributors to the MWD were free Al oxide, humic acid, and MOC.
For the 0–10 cm soil layer (Figure 10A), the greatest contributors to the MWD were fulvic acid and humic acid. The contribution rate of the organic soil colloid to the MWD was 82.52% (Table S3); Within the 10–20 cm soil layer (Figure 10B), the biggest contributors to the MWD were MOC, organically complexed Fe oxide, and SOC. The contribution rate of the organic soil colloid to the MWD was 62.35% (Table S3). For the 20–30 cm soil layer (Figure 10C), the greatest contributors to the MWD were amorphous Al, amorphous Fe, and free Al oxide. The contribution rate of the inorganic soil colloid to the MWD was 77.43% (Table S3).

4. Discussion

4.1. Effects of Forest Conversion and Soil Depth on Soil Properties and Enzyme Activities

The forest type had significant effects on the soil pH, bulk density, and enzyme activities (Table S1). This was consistent with previous studies, which observed that forest conversion could alter exchangeable cations to modify the soil pH [31]. Forest conversion could affect the activities of soil enzymes by altering the distribution of soil particle sizes, soil water contents, and soil pH values [32,33]. Changes in the soil bulk density were also correlated with soil enzyme activities [34].
The pH value and bulk density of the soil were increased, whereas the TN content and total capillary porosity were decreased with soil depth, which aligned with earlier studies. Rock weathering resulted in the release and leaching of large quantities of Ca2+ and Mg2+ in the soil profile, which might decrease the soil pH [35]. However, the lower rock weathering rate with soil depth resulted in higher pH values along the soil profiles [36]. Greater soil compaction in the deeper soil layers increased the soil bulk density [37], which decreased the total capillary porosity [38].
At greater soil depths, plant litter components and root exudates decrease with the lower distribution of plant roots, which likely results in a lower TN content than in the soil surface layers [39]. Furthermore, the activities of soil enzymes are typically decreased at greater soil depths. The reason for this might be that in contrast to subsoil layers, trees have higher litter inputs within the surface and topsoil, where soil aeration is better [40]. The higher density of plant roots and soil fauna in the topsoil might be another explanation for the greater activities of soil enzymes in topsoil [41].

4.2. Effects of Forest Conversion and Soil Depth on Organic Soil Colloids

The conversion from native forest to other forest types did not alter the SOC and POC contents (Figure 3), which was not consistent with previous studies [42,43]. The reason might have been that the conversion time was quite rapid. Cook et al. [44] observed that thirty-four years following the conversion of a broadleaved to coniferous forest, the SOC pool did not change (i.e., it remained at similar levels); thus, the recovery of these disturbed soils may be a very long-term process. The SOC and POC contents decreased with soil depth (Figure S6), and because they had a strong correlation with root C inputs, other organic residues tended to accumulate on the soil surface [45]. Additionally, soil organisms (e.g., earthworms) also absorbed topsoil organic matter and translocated SOC and POC into deeper soil levels via bioturbation [46].
It has been often believed that MOC represents the recalcitrant C pool; thus, the conversion of native forest to Chinese fir forest could significantly decrease the MOC content (Figure 3). In the native forest, the quantity of aboveground and belowground litter, high population of fine roots, and greater number of root exudates influenced the accumulation of the non-protected C fraction, thus maintaining the MOC content and soil C stability [47]. However, the MOC content of the native forest could increase, and that of the Chinese fir forest could decrease with soil depth (Figure S6), which was consistent with previous studies. In the native forest, the higher recalcitrance indices of the deep soil in contrast to the topsoil indicated that the deep soil C was more stable than that of the topsoil. However, for the Chinese fir forest, the stability of the SOC in the deep soil layers was increased [47,48].
The forest type had no significant effects on the soil humus and fulvic acid, but did on the soil humic acid (Table S1). The humic acid in the bamboo forest was significantly higher than that in other forest types at the 10–20 soil depth (Figure 4C). The reason might be that the bamboo forest had higher annual growth and turnover rates [49]. Furthermore, the soil humus, humic acid, and fulvic acid were decreased with soil depth (Figure S7). The reason might be consistent with the decreases in SOC and POC [45,46].

4.3. Effects of Forest Conversion and Soil Depth on Inorganic Soil Colloids

The forest type had significant effects on the free Fe oxide, amorphous Fe oxide, and organically complexed Fe oxide (Table S1). The reason might have been that the Fe oxides were bound with organic polymers to form organo-mineral complexes [1], and the Fe oxides were correlated with the SOC (Figure 7); thus, the Fe oxides might have been affected by the SOC. The soil depth had no significant impacts on the free Fe oxide and organically complexed Fe oxide; however, the deepening of soil depth increased the amount of amorphous Fe oxide (Table S1). The amorphous Fe oxide possessed reactive sites that were exposed to multivalent oxyanions [50], where the pH value increased and hydrogen ions decreased with soil depth. Consequently, changes in the amorphous Fe oxide were correlated with those of the pH value.
The amorphous Al oxide in the bamboo forest was significantly higher than that of the native forest within the topsoil (Figure 6). The reason might have been that bamboo is a typical Si accumulator [51], where the high Si uptake by bamboo roots might lead to an increase in amorphous Al oxide [49,52]. The organically complexed Al oxides in the Chinese fir and bamboo forests were significantly lower than those of the native forest. The reason might have been that the root distribution and growth in the native forest were more robust than for the other forests. Root exudates and metabolism were major sources of dissolved organic matter [53,54], which strongly influenced the content of organically complexed Al oxide. Further, the soil depth had significant effects on both the amorphous Al oxide and organically complexed Al oxide (Table S1). The reason may have been that they were affected by the soil organic matter [55], which could be modified with soil depth.

4.4. Effects of Forest Conversion and Soil Depth on Distribution and Stability of Soil Aggregates

The distributions of soil aggregate sizes and aggregate stability were significantly affected by the conversion of the native forest to bamboo forest (Figure 1 and Figure 2). In this study, significant decreases in the mass proportions of large-macroaggregates (>2 mm) and the values of MWD were found in the bamboo forest, in contrast to the other forest types. This suggested that the conversion of the native to bamboo forest exerted negative effects on the soil aggregate structures. The reason behind this phenomenon was that the canopy densities of the native, mixed, and Chinese fir forests were higher than those of the bamboo forest, which generated a greater quantity of litter [56].
Increased litter input aided in the production of macroaggregates and improved soil aggregate stability [57]. Additionally, a significant increase in the mass proportions of small-macroaggregates (0.25–2 mm) was found in the bamboo forest compared to the other forest types. This might have been due to the high rooting density of bamboo that initiated the formation of small-macroaggregates [49]. Compared to forest conversion, the soil depth had no significant effects on the distribution and stability of soil aggregates. There were two possible explanations for this. One was that the study sites were managed (e.g., logging) in 1970, and there was no significant disturbance (such as tillage) subsequently [58]. Another was that the plant root length of the four forest types can reach 30 cm, which might influence the stabilization of aggregates through the physical or chemical bonding of the soil [59]. Therefore, soil disturbances could be a major factor that drives the distribution and stability of soil aggregates with soil depth.

4.5. Relationships between Soil Properties, Enzyme Activities, Organic and Inorganic Soil Colloids, Soil Aggregate Distribution, and Stability in Subtropical Forests

The stability of soil aggregates was affected by soil properties [60], enzyme activities [32], organic colloids, and inorganic colloids [61]. In this study, the soil aggregate stability was significantly correlated with the pH, bulk density, and organically-complexed Fe oxide (Figure 7a, Table S2). In previous studies, the pH value could affect the soil stability through the modification of plant-derived inputs, thereby accelerating the activities of microbes. The microbial activities also affected the stability of soil aggregates via soil colloids [62,63].
The bulk density of the soil were significantly negatively correlated with the SOC and POC (Figure 7a, Table S2), and positive correlations between the soil organic matter and aggregate stability was also proven in other studies [64,65]. Consequently, we hypothesized that soil properties may indirectly alter soil aggregate stability through organic and inorganic soil colloids [66]. The SEM results verified our hypothesis (Figure 7b,c) that the organically complexed Fe oxide and fulvic acid could serve directly as organic and inorganic colloids that affected the stability of soil aggregates. The pH and bulk density indirectly but positively altered the soil aggregate stability by directly influencing the organically complexed Fe oxide and fulvic acid in subtropical forests. The effects of pH on the change of plant-derived inputs, internal decay rates, and macroaggregate turnover could explain the effect [62,67].

4.6. Main Factors Affecting Soil Aggregate Stability for Different Forest Types and Soil Depths

Through the analysis of soil properties, enzyme activities, soil organic colloids, inorganic colloids, and soil aggregate stability, we observed that the effects of different forest types or different soil depths were not consistent. Therefore, we needed to investigate the factors that affected the stability of soil aggregates for each forest type at each soil depth.
In the native and bamboo forests, organic soil colloids contributed most to the stability of soil aggregates, reaching 80.31% and 61.37%, respectively. In the mixed and Chinese fir forest, inorganic soil colloids contributed most to the soil aggregate stability, attaining 66.62% and 63.15%, respectively. This might have been because, compared to the mixed and Chinese fir forests, the vegetative ground cover and quantity of organic matter inputs in the native and bamboo forest were higher [32]. Large amounts of organic matter penetrated into the soil and affected the soil aggregate stability. Further, the contributions of organic colloids were decreased with soil depth (Figure 10, Table S3).
A large amount of litter was present on the soil surface, where the decomposition of litter formed more soil organic matter [68,69], thus increasing the distribution of organic colloids in the topsoil. At deeper soil levels, the soil density was increased and the organic matter was reduced [70], thus decreasing the distribution of organic colloids. Therefore, the contribution of colloids to the stability of soil aggregates might be due to changes in the soil organic matter caused by the decomposition of litter.

5. Conclusions

The results of this study indicated that forest conversion and soil depth affected soil properties, enzyme activities, organic and inorganic soil colloids, and the distribution and stability of soil aggregates in subtropical forests. Organically complexed Fe oxide and fulvic acid could directly serve as organic and inorganic colloids to facilitate the stability of soil aggregates. In subtropical forest conversion, the pH and bulk density indirectly but positively affected the soil aggregate stability by directly influencing the organically complexed Fe oxide and fulvic acid. The organic soil colloid was the primary contributor to the stability of soil aggregates in the native and bamboo forests. In contrast, the inorganic soil colloid was main contributor to soil aggregate stability in the mixed and Chinese fir forests. Finally, the inorganic soil colloid gradually replaced the organic soil colloid as the main contributor to the stability of soil aggregates with soil depth. In summary, these findings suggest that specific management strategies are required for different forest types to increase the stability of soil aggregates. After land-use conversion, management practices such as rational fertilization and natural sod cultivation (which increased organic C input into soil) are recommended to improve the soil aggregate stability of the bamboo forests.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f13040546/s1, Figure S1: Soil properties at depths of 0–30 cm for different forest types; Figure S2: Soil properties at depths of 0–30 cm for different forest types; Figure S3: Soil enzyme activities at depths of 0–30 cm for different forest types; Figure S4: Soil enzyme activities at depths of 0–30 cm for different forest types; Figure S5: Water-stable aggregate size distribution at depths of 0–30 cm for different forest types; Figure S6: SOC, POC, and MOC contents at depths of 0–30 cm for different forest types; Figure S7: The humic substance contents in bulk soil at depths of 0–30 cm for different forest types; Figure S8: The contents of Fe oxides at depths of 0–30 cm for dif-ferent forest types; Figure S9: The contents of Al oxides at depths of 0–30 cm for different forest types; Table S1: Two-way ANOVA analysis (p values) of the different forest types (F) and differ-ent soil depths (S) for all indexes; Table S2: Pearson correlation between soil physical–chemical properties, soil enzyme activities, soil aggregates, and organic and inorganic soil colloids; Table S3: The contribution of soil organic and inorganic colloids to MWD under different forest types and soil depths.

Author Contributions

Conceptualization, Y.Z., M.M. and J.Z.; methodology, Y.Z.; software, C.L. and Z.Y.; validation, C.L. and Z.J.; formal analysis, C.L.; investigation, X.P., X.L. and Z.Y.; resources, J.Z.; data curation, J.L., X.P., X.L., Z.J. and Y.Z.; writing—original draft preparation, C.L.; writing—review and editing, C.L.; visualization, C.L. and Z.Y.; supervision, J.Z.; project administration, J.Z.; funding acquisition, J.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX21_0915), Scientific Research Project of Baishanzu National Park (2021KFLY05, 2021ZDLY01), Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

We would thank Frank Boehm, from Lakehead University, for the language editing of this manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Peng, X.; Yan, X.; Zhou, H.; Zhang, Y.Z.; Sun, H. Assessing the contributions of sesquioxides and soil organic matter to aggregation in an Ultisol under long-term fertilization. Soil Tillage Res. 2015, 146, 89–98. [Google Scholar] [CrossRef]
  2. Nweke, I.A.; Nnabude, P.C. Aggregate size distribution and stability of aggregate fractions of fallow and cultivated soils. J. Exp. Biol. Agric. Sci. 2014, 7, 514–520. [Google Scholar]
  3. Gao, Y.; Song, X.; Liu, K.; Li, T.; Zheng, W.; Wang, Y.; Liu, Z.; Zhang, M.; Chen, Q.; Li, Z.; et al. Mixture of controlled-release and conventional urea fertilizer application changed soil aggregate stability, humic acid molecular composition, and maize nitrogen uptake. Sci. Total Envrion. 2021, 789, 147778. [Google Scholar] [CrossRef] [PubMed]
  4. Nsabimana, G.; Bao, Y.; He, X.; Nambajimana, J.d.D.; Yang, L.; Li, J.; Uwiringiyimana, E.; Nsengumuremyi, P.; Ntacyabukura, T. Soil aggregate stability response to hydraulic conditions in water level fluctuation zone of the Three Gorges Reservoir, China. Catena 2021, 204, 105387. [Google Scholar] [CrossRef]
  5. Xue, B.; Huang, L.; Huang, Y.; Zhou, F.; Li, F.; Kubar, K.A.; Li, X.; Lu, J.; Zhu, J. Roles of soil organic carbon and iron oxides on aggregate formation and stability in two paddy soils. Soil Tillage Res. 2019, 187, 161–171. [Google Scholar] [CrossRef]
  6. Sun, Q.; Meng, J.; Lan, Y.; Shi, G.; Yang, X.; Cao, D.; Chen, W.; Han, X. Long-term effects of biochar amendment on soil aggregate stability and biological binding agents in brown earth. Catena 2021, 205, 105460. [Google Scholar] [CrossRef]
  7. An, S.; Huang, Y.; Zheng, F.; Yang, J. Aggregate characteristics during natural revegetation on the loess plateau. Pedosphere 2008, 6, 809–816. [Google Scholar] [CrossRef]
  8. Xue, B.; Huang, L.; Huang, Y.; Yin, Z.; Li, X.; Lu, J. Effects of organic carbon and iron oxides on soil aggregate stability under different tillage systems in a rice–rape cropping system. Catena 2019, 177, 1–12. [Google Scholar] [CrossRef]
  9. Sander, S.; Mosley, L.M.; Hunter, K.A. Investigation of Interparticle Forces in Natural Waters: Effects of Adsorbed Humic Acids on Iron Oxide and Alumina Surface Properties. Environ. Sci. Technol. 2004, 38, 4791–4796. [Google Scholar] [CrossRef]
  10. Zhao, J.; Chen, S.; Hu, R.; Li, Y. Aggregate stability and size distribution of red soils under different land uses integrally regulated by soil organic matter, and iron and aluminum oxides. Soil Tillage Res. 2017, 167, 73–79. [Google Scholar] [CrossRef] [Green Version]
  11. Li, X.; Mao, F.; Du, H.; Zhou, G.; Xu, X.; Han, N.; Sun, S.; Gao, G.; Chen, L. Assimilating leaf area index of three typical types of subtropical forest in China from MODIS time series data based on the integrated ensemble Kalman filter and PROSAIL model. ISPRS J. Photogramm. Remote Sens. 2017, 126, 68–78. [Google Scholar] [CrossRef]
  12. Guo, J.; Yang, Z.; Lin, C.; Liu, X.; Chen, G.; Yang, Y. Conversion of a natural evergreen broadleaved forest into coniferous plantations in a subtropical area: Effects on composition of soil microbial communities and soil respiration. Biol. Fertil. Soils 2016, 52, 799–809. [Google Scholar] [CrossRef]
  13. Yang, Z.; Chen, S.; Liu, X.; Xiong, D.; Xu, C.; Arthur, M.A.; McCulley, R.L.; Shi, S.; Yang, Y. Loss of soil organic carbon following natural forest conversion to Chinese fir plantation. For. Ecol. Manag. 2019, 449, 117476. [Google Scholar] [CrossRef]
  14. Yang, L.; Chen, S.; Li, Y.; Wang, Q.; Zhong, X.; Yang, Z.; Lin, C.; Yang, Y. Conversion of Natural Evergreen Broadleaved Forests Decreases Soil Organic Carbon but Increases the Relative Contribution of Microbial Residue in Subtropical China. Forests 2019, 10, 468. [Google Scholar] [CrossRef] [Green Version]
  15. Yang, L.; Yang, Z.; Zhong, X.; Xu, C.; Lin, Y.; Fan, Y.; Wang, M.; Chen, G.; Yang, Y. Decreases in soil P availability are associated with soil organic P declines following forest conversion in subtropical China. Catena 2021, 205, 105459. [Google Scholar] [CrossRef]
  16. Wang, H.; Jin, J.; Yu, P.; Fu, W.; Morrison, L.; Lin, H.; Meng, M.; Zhou, X.; Lv, Y.; Wu, J. Converting evergreen broad-leaved forests into tea and Moso bamboo plantations affects labile carbon pools and the chemical composition of soil organic carbon. Sci. Total Envrion. 2020, 711, 135225. [Google Scholar] [CrossRef]
  17. Meng, M.; Chen, H.Y.H.; Lin, J.; Liu, X.; Guo, X.; Yuan, Y.; Zhang, J. Long term forest conversion affected soil nanoscale pores in subtropical China. Catena 2020, 185, 104289. [Google Scholar] [CrossRef]
  18. Meng, M.; Lin, J.; Guo, X.; Liu, X.; Wu, J.; Zhao, Y.; Zhang, J. Impacts of forest conversion on soil bacterial community composition and diversity in subtropical forests. Catena 2019, 175, 167–173. [Google Scholar] [CrossRef]
  19. Li, J.; Yuan, X.; Ge, L.; Li, Q.; Li, Z.; Wang, L.; Liu, Y. Rhizosphere effects promote soil aggregate stability and associated organic carbon sequestration in rocky areas of desertification. Agric. Ecosyst. Environ. 2020, 304, 107126. [Google Scholar] [CrossRef]
  20. Ndzelu, B.S.; Dou, S.; Zhang, X.; Zhang, Y.; Ma, R.; Liu, X. Tillage effects on humus composition and humic acid structural characteristics in soil aggregate-size fractions. Soil Tillage Res. 2021, 213, 105090. [Google Scholar] [CrossRef]
  21. Zhang, J.; Wei, D.; Zhou, B.; Zhang, L.; Hao, X.; Zhao, S.; Xu, X.; He, P.; Zhao, Y.; Qiu, S.; et al. Responses of soil aggregation and aggregate-associated carbon and nitrogen in black soil to different long-term fertilization regimes. Soil Tillage Res. 2021, 213, 105157. [Google Scholar] [CrossRef]
  22. Le Bissonnais, Y.; Prieto, I.; Roumet, C.; Nespoulous, J.; Metayer, J.; Huon, S.; Villatoro, M.; Stokes, A. Soil aggregate stability in Mediterranean and tropical agro-ecosystems: Effect of plant roots and soil characteristics. Plant Soil 2017, 424, 303–317. [Google Scholar] [CrossRef]
  23. Dorji, T.; Field, D.J.; Odeh, I.O.A.; Bhogal, A. Soil aggregate stability and aggregate-associated organic carbon under different land use or land cover types. Soil Use Manag. 2020, 36, 308–319. [Google Scholar] [CrossRef]
  24. Sheng, M.; Xiong, K.; Wang, L.; Li, X.; Li, R.; Tian, X. Response of soil physical and chemical properties to Rocky desertification succession in South China Karst. Carbonates Evaporites 2016, 33, 15–28. [Google Scholar] [CrossRef]
  25. Li, C.; Jia, Z.; Peng, X.; Zhai, L.; Zhang, B.; Liu, X.; Zhang, J. Functions of mineral-solubilizing microbes and a water retaining agent for the remediation of abandoned mine sites. Sci. Total Environ. 2021, 761, 143215. [Google Scholar] [CrossRef] [PubMed]
  26. Wei, Y.; Wu, X.; Zeng, R.; Cai, C.; Guo, Z. Spatial variations of aggregate-associated humic substance in heavy-textured soils along a climatic gradient. Soil Tillage Res. 2020, 197, 104497. [Google Scholar] [CrossRef]
  27. Cui, H.; Ma, K.; Fan, Y.; Peng, X.; Mao, J.; Zhou, D.; Zhang, Z.; Zhou, J. Stability and heavy metal distribution of soil aggregates affected by application of apatite, lime, and charcoal. Environ. Sci. Pollut. Res. 2016, 23, 10808–10817. [Google Scholar] [CrossRef]
  28. Chen, J.; Xiao, W.; Zheng, C.; Zhu, B. Nitrogen addition has contrasting effects on particulate and mineral-associated soil organic carbon in a subtropical forest. Soil Biol. Biochem. 2020, 142, 107708. [Google Scholar] [CrossRef]
  29. He, Y.; Gu, F.; Xu, C.; Wang, Y. Assessing of the influence of organic and inorganic amendments on the physical-chemical properties of a red soil (Ultisol) quality. Catena 2019, 183, 104231. [Google Scholar] [CrossRef]
  30. Kamamia, A.W.; Vogel, C.; Mwangi, H.M.; Feger, K.-H.; Sang, J.; Julich, S. Mapping soil aggregate stability using digital soil mapping: A case study of Ruiru reservoir catchment, Kenya. Geoderma Reg. 2021, 24, e0035. [Google Scholar] [CrossRef]
  31. Tripathi, B.M.; Edwards, D.P.; Mendes, L.W.; Kim, M.; Dong, K.; Kim, H.; Adams, J.M. The impact of tropical forest logging and oil palm agriculture on the soil microbiome. Mol. Ecol. 2016, 25, 2244–2257. [Google Scholar] [CrossRef] [PubMed]
  32. Luo, X.; Hou, E.; Zhang, L.; Zang, X.; Yi, Y.; Zhang, G.; Wen, D. Effects of forest conversion on carbon-degrading enzyme activities in subtropical China. Sci. Total Environ. 2019, 696, 133968. [Google Scholar] [CrossRef] [PubMed]
  33. Hou, E.; Chen, C.; Wen, D.; Liu, X. Phosphatase activity in relation to key litter and soil properties in mature subtropical forests in China. Sci. Total Environ. 2015, 515–516, 83–91. [Google Scholar] [CrossRef] [PubMed]
  34. Feng, J.; Xu, X.; Wu, J.; Zhang, Q.; Zhang, D.; Li, Q.; Long, C.; Chen, Q.; Chen, J.; Cheng, X. Inhibited enzyme activities in soil macroaggregates contribute to enhanced soil carbon sequestration under afforestation in central China. Sci. Total Environ. 2018, 640–641, 653–661. [Google Scholar] [CrossRef]
  35. Zhou, W.; Han, G.; Liu, M.; Zeng, J.; Liang, B.; Liu, J.; Qu, R. Determining the Distribution and Interaction of Soil Organic Carbon, Nitrogen, pH and Texture in Soil Profiles: A Case Study in the Lancangjiang River Basin, Southwest China. Forests 2020, 11, 532. [Google Scholar] [CrossRef]
  36. Zhao, Z.; Liu, G.; Liu, Q.; Huang, C.; Li, H.; Wu, C. Distribution Characteristics and Seasonal Variation of Soil Nutrients in the Mun River Basin, Thailand. Int. J. Environ. Res. Public Health 2018, 15, 1818. [Google Scholar] [CrossRef] [Green Version]
  37. Hao, J.; Chai, Y.N.; Lopes, L.D.; Ordóñez, R.A.; Wright, E.E.; Archontoulis, S.; Schachtman, D.P. The Effects of Soil Depth on the Structure of Microbial Communities in Agricultural Soils in Iowa (United States). Appl. Environ. Microbiol. 2021, 87, e02673-20. [Google Scholar] [CrossRef]
  38. Zhao, H.; Zheng, W.; Zhang, S.; Gao, W.; Fan, Y. Soil microbial community variation with time and soil depth in Eurasian Steppe (Inner Mongolia, China). Ann. Microbiol. 2021, 71, 21. [Google Scholar] [CrossRef]
  39. Truong, T.H.H.; Marschner, P. Respiration, available N and microbial biomass N in soil amended with mixes of organic materials differing in C/N ratio and decomposition stage. Geoderma 2018, 319, 167–174. [Google Scholar] [CrossRef]
  40. Avazpoor, Z.; Moradi, M.; Basiri, R.; Mirzaei, J.; Taghizadeh-Mehrjardi, R.; Kerry, R. Soil enzyme activity variations in riparian forests in relation to plant species and soil depth. Arab. J. Geosci. 2019, 12, 708. [Google Scholar] [CrossRef]
  41. Xiao, S.; You, H.; You, W.; Liu, J.; Cai, C.; Wu, J.; Ji, Z.; Zhan, S.; Hu, Z.; Zhang, Z.; et al. Rhizosphere and bulk soil enzyme activities in a Nothotsuga longibracteata forest in the Tianbaoyan National Nature Reserve, Fujian Province, China. J. For. Res. 2016, 28, 521–528. [Google Scholar] [CrossRef]
  42. Davari, M.; Gholami, L.; Nabiollahi, K.; Homaee, M.; Jafari, H.J. Deforestation and cultivation of sparse forest impacts on soil quality (case study: West Iran, Baneh). Soil Tillage Res. 2020, 198, 104504. [Google Scholar] [CrossRef]
  43. Don, A.; Schumacher, J.; Freibauer, A. Impact of tropical land-use change on soil organic carbon stocks—A meta-analysis. Glob. Chang. Biol. 2011, 17, 1658–1670. [Google Scholar] [CrossRef] [Green Version]
  44. Cook, R.L.; Binkley, D.; Mendes, J.C.T.; Stape, J.L. Soil carbon stocks and forest biomass following conversion of pasture to broadleaf and conifer plantations in southeastern Brazil. For. Ecol. Manag. 2014, 324, 37–45. [Google Scholar] [CrossRef]
  45. Yang, Y.; Guo, J.; Chen, G.; Yin, Y.; Gao, R.; Lin, C. Effects of forest conversion on soil labile organic carbon fractions and aggregate stability in subtropical China. Plant Soil 2009, 323, 153–162. [Google Scholar] [CrossRef]
  46. Achilles, F.; Tischer, A.; Bernhardt-Römermann, M.; Heinze, M.; Reinhardt, F.; Makeschin, F.; Michalzik, B. European beech leads to more bioactive humus forms but stronger mineral soil acidification as Norway spruce and Scots pine—Results of a repeated site assessment after 2020, 63 and 82 years of forest conversion in Central Germany. For. Ecol. Manag. 2021, 483, 118769. [Google Scholar] [CrossRef]
  47. Lyu, M.; Xie, J.; Ukonmaanaho, L.; Jiang, M.; Li, Y.; Chen, Y.; Yang, Z.; Zhou, Y.; Lin, W.; Yang, Y. Land use change exerts a strong impact on deep soil C stabilization in subtropical forests. J. Soils Sediments 2016, 17, 2305–2317. [Google Scholar] [CrossRef]
  48. Lyu, M.; Noormets, A.; Ukonmaanaho, L.; Li, Y.; Yang, Y.; Xie, J. Stability of soil organic carbon during forest conversion is more sensitive in deep soil than in topsoil in subtropical forests. Pedobiologia 2021, 84, 150706. [Google Scholar] [CrossRef]
  49. Yang, C.; Zhang, X.; Ni, H.; Gai, X.; Huang, Z.; Du, X.; Zhong, Z. Soil carbon and associated bacterial community shifts driven by fine root traits along a chronosequence of Moso bamboo (Phyllostachys edulis) plantations in subtropical China. Sci. Total Environ. 2021, 752, 142333. [Google Scholar] [CrossRef]
  50. Zhao, Z.; Jin, R.; Fang, D.; Wang, H.; Dong, Y.; Xu, R.; Jiang, J. Paddy cultivation significantly alters the forms and contents of Fe oxides in an Oxisol and increases phosphate mobility. Soil Tillage Res. 2018, 184, 176–180. [Google Scholar] [CrossRef]
  51. Song, Z.; Liu, H.; Li, B.; Yang, X. The production of phytolith-occluded carbon in China’s forests: Implications to biogeochemical carbon sequestration. Glob. Chang. Biol. 2013, 19, 2907–2915. [Google Scholar] [CrossRef] [PubMed]
  52. Hobara, S.; Fukunaga-Yoshida, S.; Suzuki, T.; Matsumoto, S.; Matoh, T.; Ae, N. Plant silicon uptake increases active aluminum minerals in root-zone soil: Implications for plant influence on soil carbon. Geoderma 2016, 279, 45–52. [Google Scholar] [CrossRef]
  53. Li, X.; Gao, B.; Xu, H.; Sun, Y.; Shi, X.; Wu, J. Effect of root exudates on the stability and transport of graphene oxide in saturated porous media. J. Hazard. Mater. 2021, 413, 125362. [Google Scholar] [CrossRef] [PubMed]
  54. Xu, Z.; Lu, Z.; Zhang, L.; Fan, H.; Wang, Y.; Li, J.; Lin, Y.; Liu, H.; Guo, S.; Xu, M.; et al. Red mud based passivator reduced Cd accumulation in edible amaranth by influencing root organic matter metabolism and soil aggregate distribution. Env. Pollut. 2021, 275, 116543. [Google Scholar] [CrossRef] [PubMed]
  55. Che, M.; Gong, Y.; Xu, M.; Kang, C.; Lv, C.; He, S.; Zheng, J. Effects of elevation and slope aspect on the distribution of the soil organic carbon associated with Al and Fe mineral phases in alpine shrub-meadow soil. Sci. Total Envrion. 2021, 753, 141933. [Google Scholar] [CrossRef]
  56. Xu, Z.; Ward, S.; Chen, C.; Blumfield, T.; Prasolova, N.; Liu, J. Soil carbon and nutrient pools, microbial properties and gross nitrogen transformations in adjacent natural forest and hoop pine plantations of subtropical Australia. J. Soils Sediments 2008, 8, 99–105. [Google Scholar] [CrossRef]
  57. Yang, C.; Ni, H.; Zhong, Z.; Zhang, X.; Bian, F. Changes in soil carbon pools and components induced by replacing secondary evergreen broadleaf forest with Moso bamboo plantations in subtropical China. Catena 2019, 180, 309–319. [Google Scholar] [CrossRef]
  58. Feng, H.; Wang, S.; Gao, Z.; Pan, H.; Zhuge, Y.; Ren, X.; Hu, S.; Li, C. Aggregate stability and organic carbon stock under different land uses integrally regulated by binding agents and chemical properties in saline-sodic soils. Land Degrad. Dev. 2021, 32, 4151–4161. [Google Scholar] [CrossRef]
  59. Wang, B.; Zhang, G.-H.; Yang, Y.-F.; Li, P.-P.; Liu, J.-X. The effects of varied soil properties induced by natural grassland succession on the process of soil detachment. Catena 2018, 166, 192–199. [Google Scholar] [CrossRef]
  60. Bottinelli, N.; Angers, D.A.; Hallaire, V.; Michot, D.; Le Guillou, C.; Cluzeau, D.; Heddadj, D.; Menasseri-Aubry, S. Tillage and fertilization practices affect soil aggregate stability in a Humic Cambisol of Northwest France. Soil Tillage Res. 2017, 170, 14–17. [Google Scholar] [CrossRef]
  61. Yu, X.; Fu, Y.; Lu, S. Characterization of the pore structure and cementing substances of soil aggregates by a combination of synchrotron radiation X-ray micro-computed tomography and scanning electron microscopy. Eur. J. Soil Sci. 2017, 68, 66–79. [Google Scholar] [CrossRef] [Green Version]
  62. Egan, G.; Crawley, M.J.; Fornara, D.A. Effects of long-term grassland management on the carbon and nitrogen pools of different soil aggregate fractions. Sci. Total Environ. 2018, 613–614, 810–819. [Google Scholar] [CrossRef] [PubMed]
  63. Verchot, L.V.; Dutaur, L.; Shepherd, K.D.; Albrecht, A. Organic matter stabilization in soil aggregates: Understanding the biogeochemical mechanisms that determine the fate of carbon inputs in soils. Geoderma 2011, 161, 182–193. [Google Scholar] [CrossRef]
  64. Jakšík, O.; Kodešová, R.; Kubiš, A.; Stehlíková, I.; Drábek, O.; Kapička, A. Soil aggregate stability within morphologically diverse areas. Catena 2015, 127, 287–299. [Google Scholar] [CrossRef]
  65. Kodešová, R.; Rohošková, M.; Žigová, A. Comparison of aggregate stability within six soil profiles under conventional tillage using various laboratory tests. Biologia 2009, 64, 550–554. [Google Scholar] [CrossRef]
  66. Bronick, C.J.; Lal, R. Soil structure and management: A review. Geoderma 2005, 124, 3–22. [Google Scholar] [CrossRef]
  67. Jastrow, J.D.; Amonette, J.E.; Bailey, V.L. Mechanisms controlling soil carbon turnover and their potential application for enhancing carbon sequestration. Clim. Chang. 2007, 80, 5–23. [Google Scholar] [CrossRef]
  68. Yamagishi, K.; Kizaki, K.; Ito, S.; Hirata, R.; Mitsuda, Y. Effect of surface soil conservation by litter from shelterbelts on Chamaecyparis obtusa plantation. J. For. Res. 2017, 22, 69–73. [Google Scholar] [CrossRef]
  69. Shahzad, T.; Anwar, F.; Hussain, S.; Mahmood, F.; Arif, M.S.; Sahar, A.; Nawaz, M.F.; Perveen, N.; Sanaullah, M.; Rehman, K.; et al. Carbon dynamics in surface and deep soil in response to increasing litter addition rates in an agro-ecosystem. Geoderma 2019, 333, 1–9. [Google Scholar] [CrossRef]
  70. Laskar, S.Y.; Sileshi, G.W.; Pathak, K.; Debnath, N.; Nath, A.J.; Laskar, K.Y.; Singnar, P.; Das, A.K. Variations in soil organic carbon content with chronosequence, soil depth and aggregate size under shifting cultivation. Sci. Total Environ. 2021, 762, 143114. [Google Scholar] [CrossRef]
Forests 13 00546 g001 550
Figure 1. Distribution of water-stable aggregate sizes at depths of from 0 to 30 cm for different forest types. (A): 0–10 cm soil depth; (B): 10–20 cm soil depth; (C): 20–30 cm soil depth. Different letters indicate significant difference (p < 0.05) between different forest types.
Figure 1. Distribution of water-stable aggregate sizes at depths of from 0 to 30 cm for different forest types. (A): 0–10 cm soil depth; (B): 10–20 cm soil depth; (C): 20–30 cm soil depth. Different letters indicate significant difference (p < 0.05) between different forest types.
Forests 13 00546 g001
Forests 13 00546 g002 550
Figure 2. Soil aggregate stability characteristics at depths of from 0 to 30 cm for different forest types. (A): Different forest types; (B): different soil depths. Different letters indicate significant difference (p < 0.05) between different forest types.
Figure 2. Soil aggregate stability characteristics at depths of from 0 to 30 cm for different forest types. (A): Different forest types; (B): different soil depths. Different letters indicate significant difference (p < 0.05) between different forest types.
Forests 13 00546 g002
Forests 13 00546 g003 550
Figure 3. SOC, POC, and MOC contents at depths of from 0 to 30 cm for different forest types. (A): soil organic carbon (SOC); (B): SOC in particulate organic matter (POC); (C): SOC in mineral-associated organic matter (MOC). Different letters indicate significant difference (p < 0.05) between different forest types.
Figure 3. SOC, POC, and MOC contents at depths of from 0 to 30 cm for different forest types. (A): soil organic carbon (SOC); (B): SOC in particulate organic matter (POC); (C): SOC in mineral-associated organic matter (MOC). Different letters indicate significant difference (p < 0.05) between different forest types.
Forests 13 00546 g003
Forests 13 00546 g004 550
Figure 4. Humic substance contents of bulk soil at depths of from 0 to 30 cm for different forest types. (A): Humus; (B): humic acid; (C): fulvic acid. Different letters indicate significant difference (p < 0.05) between different forest types.
Figure 4. Humic substance contents of bulk soil at depths of from 0 to 30 cm for different forest types. (A): Humus; (B): humic acid; (C): fulvic acid. Different letters indicate significant difference (p < 0.05) between different forest types.
Forests 13 00546 g004
Forests 13 00546 g005 550
Figure 5. Contents of Fe oxides at depths of from 0 to 30 cm for different forest types. (A): Free Fe; (B): amorphous Fe oxides; (C): organically–complexed Fe oxides. Different letters indicate significant difference (p < 0.05) between different forest types.
Figure 5. Contents of Fe oxides at depths of from 0 to 30 cm for different forest types. (A): Free Fe; (B): amorphous Fe oxides; (C): organically–complexed Fe oxides. Different letters indicate significant difference (p < 0.05) between different forest types.
Forests 13 00546 g005
Forests 13 00546 g006 550
Figure 6. Contents of Al oxides at depths of from 0–30 cm for different forest types. (A): Free Al; (B): amorphous Al oxides; (C): organically-complexed Al oxides. Different letters indicate significant difference (p < 0.05) between different forest types.
Figure 6. Contents of Al oxides at depths of from 0–30 cm for different forest types. (A): Free Al; (B): amorphous Al oxides; (C): organically-complexed Al oxides. Different letters indicate significant difference (p < 0.05) between different forest types.
Forests 13 00546 g006
Forests 13 00546 g007 550
Figure 7. Pearson correlation and SEM analysis. (a): Pearson correlation between soil physical–chemical properties, soil enzyme activities, soil aggregates, and organic and inorganic soil colloids. Abbreviations are as follows: total nitrogen (TN), bulk density (BD), total capillary porosity (TCP), soil organic carbon (SOC), SOC in particulate organic matter (POC), SOC in mineral-associated organic matter (MOC), free Fe (F-Fe), amorphous Fe oxides (A-Fe), organically complexed Fe oxides (C-Fe), free Al (F-Al), amorphous Al oxides (A-Al), organically complexed Al oxides (C-Al). ** indicates significant correlation at p < 0.01, * indicates significant correlation at p < 0.05. (b): Structural equation model (SEM) analysis estimating the direct and indirect effects of organic or inorganic soil colloids and soil properties on soil aggregate stability. Boxes show variables included in the model. Test results of the goodness of model fit: Chi-square (χ2) = 13.183, p value = 0.282 > 0.05, goodness-of-fit index (GFI) = 0.918 > 0.9, root square mean error of approximation (RMSEA) = 0.075 < 0.08. Numbers on arrows are standardized path coefficients. Widths of arrows represent the strength of the relationships. Blue arrows indicate negative relationships, and red arrows indicate positive relationships. Solid arrows indicate significance (p < 0.05) and dashed arrows represent non-significance (p > 0.05) (the p value is calculated in terms of the nonnormalized path). (c): Standardized total effects (direct plus indirect effects) derived from the structural equation models depicted above.
Figure 7. Pearson correlation and SEM analysis. (a): Pearson correlation between soil physical–chemical properties, soil enzyme activities, soil aggregates, and organic and inorganic soil colloids. Abbreviations are as follows: total nitrogen (TN), bulk density (BD), total capillary porosity (TCP), soil organic carbon (SOC), SOC in particulate organic matter (POC), SOC in mineral-associated organic matter (MOC), free Fe (F-Fe), amorphous Fe oxides (A-Fe), organically complexed Fe oxides (C-Fe), free Al (F-Al), amorphous Al oxides (A-Al), organically complexed Al oxides (C-Al). ** indicates significant correlation at p < 0.01, * indicates significant correlation at p < 0.05. (b): Structural equation model (SEM) analysis estimating the direct and indirect effects of organic or inorganic soil colloids and soil properties on soil aggregate stability. Boxes show variables included in the model. Test results of the goodness of model fit: Chi-square (χ2) = 13.183, p value = 0.282 > 0.05, goodness-of-fit index (GFI) = 0.918 > 0.9, root square mean error of approximation (RMSEA) = 0.075 < 0.08. Numbers on arrows are standardized path coefficients. Widths of arrows represent the strength of the relationships. Blue arrows indicate negative relationships, and red arrows indicate positive relationships. Solid arrows indicate significance (p < 0.05) and dashed arrows represent non-significance (p > 0.05) (the p value is calculated in terms of the nonnormalized path). (c): Standardized total effects (direct plus indirect effects) derived from the structural equation models depicted above.
Forests 13 00546 g007
Forests 13 00546 g008 550
Figure 8. Correlation between MWD and other indexes for different forest types (a) and soil depths (b). Abbreviations are shown in Figure 7. ** indicates significant correlation at p < 0.01, * indicates significant correlation at p < 0.05.
Figure 8. Correlation between MWD and other indexes for different forest types (a) and soil depths (b). Abbreviations are shown in Figure 7. ** indicates significant correlation at p < 0.01, * indicates significant correlation at p < 0.05.
Forests 13 00546 g008
Forests 13 00546 g009 550
Figure 9. The contribution of organic and inorganic soil colloids to MWD under different forest types. Abbreviations are shown in Figure 7.
Figure 9. The contribution of organic and inorganic soil colloids to MWD under different forest types. Abbreviations are shown in Figure 7.
Forests 13 00546 g009
Forests 13 00546 g010 550
Figure 10. Contributions of soil organic and inorganic colloids to MWD at different soil depths. Abbreviations are shown in Figure 7.
Figure 10. Contributions of soil organic and inorganic colloids to MWD at different soil depths. Abbreviations are shown in Figure 7.
Forests 13 00546 g010
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Li, C.; Yu, Z.; Lin, J.; Meng, M.; Zhao, Y.; Jia, Z.; Peng, X.; Liu, X.; Zhang, J. Forest Conversion and Soil Depth Can Modify the Contributions of Organic and Inorganic Colloids to the Stability of Soil Aggregates. Forests 2022, 13, 546. https://doi.org/10.3390/f13040546

AMA Style

Li C, Yu Z, Lin J, Meng M, Zhao Y, Jia Z, Peng X, Liu X, Zhang J. Forest Conversion and Soil Depth Can Modify the Contributions of Organic and Inorganic Colloids to the Stability of Soil Aggregates. Forests. 2022; 13(4):546. https://doi.org/10.3390/f13040546

Chicago/Turabian Style

Li, Chong, Zizhou Yu, Jie Lin, Miaojing Meng, Youpeng Zhao, Zhaohui Jia, Xiaonan Peng, Xin Liu, and Jinchi Zhang. 2022. "Forest Conversion and Soil Depth Can Modify the Contributions of Organic and Inorganic Colloids to the Stability of Soil Aggregates" Forests 13, no. 4: 546. https://doi.org/10.3390/f13040546

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop