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Article

Spatial Heterogeneity of Total and Labile Soil Organic Carbon Pools in Poplar Agroforestry Systems

by
Bo Wang
1,
Xiaolong Su
1,
Tongli Wang
2,*,
Tao Yang
1,
Cheng Xu
1,
Zeyang Lin
1,
Di Tian
1 and
Luozhong Tang
1,*
1
Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing 210037, China
2
Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
*
Authors to whom correspondence should be addressed.
Forests 2023, 14(9), 1869; https://doi.org/10.3390/f14091869
Submission received: 3 August 2023 / Revised: 11 September 2023 / Accepted: 11 September 2023 / Published: 13 September 2023
(This article belongs to the Topic Forest Carbon Sequestration and Climate Change Mitigation)
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Abstract

:
Agroforestry systems are considered effective methods of carbon sequestration. In these systems, most of the carbon is stored in the soil, and the pattern of tree planting can influence the spatial distribution of organic matter input into the soil. However, limited information is available about the extent of this influence. In this study, the horizontal and vertical distributions of soil organic carbon (SOC) and labile fractions were investigated in four planting systems: a pure poplar (Populus deltoides cv. “35”) planting system, a wide-row (14 m spacing) poplar and wheat (Triticum aestivum L.) agroforestry system, a narrow-row (7 m spacing) poplar and wheat agroforestry system, and a pure wheat field. The results showed that although the poplar system had the highest vegetation biomass (147.50 t ha−1), the agroforestry systems overall had higher SOC contents than the pure poplar system and wheat fields. Especially in the wide-row agroforestry system, the SOC, readily oxidizable carbon, and dissolved organic carbon contents were, respectively, 25.3%, 42.4%, and 99.3% higher than those of the pure poplar system and 60.3%, 148.7%, and 6.3% higher than those of the wheat field in a 1 m soil profile, and it also had the highest fine root biomass. However, the microbial biomass carbon content was highest in the pure poplar system. The SOC of the three poplar planting systems was spatially heterogeneous, with the highest values occurring at 1.5 m in the narrow-row systems and within the tree rows in the wide-row system, similar to the distribution of fine root biomass. Additionally, we found that the larger the diameter at the breast height of the trees, the greater their positive effect on SOC at greater distances.

1. Introduction

Carbon dioxide (CO2) is a principal greenhouse gas on Earth [1]. Over recent years, the CO2 concentrations in the atmosphere have risen significantly due to increased human fossil fuel burning and land-use changes. Specifically, from 1980 to 2022, CO2 concentrations increased from 338 ppm to 417 ppm, representing a 50% increase compared to preindustrial revolution levels [2]. Exploring methods and technologies to reduce atmospheric CO2 concentrations is a major challenge facing the global community, and it is imperative to develop relatively low-cost and sustainable carbon storage methods. The soil carbon reservoir is widely acknowledged as a crucial carbon reservoir in terrestrial ecosystems, far surpassing the sum of the biological and atmospheric carbon reservoirs [3]. Agroforestry systems, as a viable land-use type, possess significant potential for carbon storage and sequestration [4]. They are widely recognized as an effective measure in mitigating global warming [5]. Compared with single agricultural systems or forestry systems, agroforestry systems can enhance soil available nitrogen, phosphorus, organic carbon, and microbial biomass [6]. In agroforestry systems, trees significantly impact the spatial distribution of the input of organic matter (OM) into the soil [7]. Generally, the closer to the tree, the greater the influence of the root on the soil. According to Upson and Burgess [8], soil organic carbon (SOC) levels were observed to be higher along the tree rows than between them and greater beneath the canopy than at a location 5 m away from a tree, even in deeper soil layers [9]. The SOC content was greater near the tree than in the surrounding area [10]. Thus, SOC in agroforestry systems has strong spatial heterogeneity. Previously, researchers typically regarded the system as a whole, neglecting the impact of positional effects. Furthermore, research on soil carbon has primarily concentrated on its distribution in the topsoil (<50 cm) [11,12].
Fine root turnover is the primary mechanism through which carbon enters the soil [8], accounting for 1/3 of global annual net primary productivity [13]. In contrast to aboveground plants, the root system undergoes senescence directly in the soil, and the organic matter obtained from root litter can effectively enhance the stabilization of soil minerals [14]. The role of fine root carbon in contributing to SOC varies depending on the land management practices, which are determined by factors such as root-system configuration, exudates, cycling rate, and mycorrhizal colonization [15]. In agroforestry systems, root system distribution may significantly influence soil organic carbon distribution. Quantifying and determining the root biomass distribution can elucidate the relationship between root dynamics and SOC fractions. However, information regarding below-ground carbon inputs in agroforestry systems remains scarce [16].
Labile SOC constitutes a relatively small yet highly active carbon pool in the soil [17]. It reflects fresh carbon input, microbial activity, and biogeochemical processes related to soil carbon [18]. Labile SOC serves as a substrate for microbial respiration [19] and a contributor of nutrients and SOC in the deeper soil layers [20]. Understanding these fractions of OM is crucial for assessing soil OM dynamics and forecasting the potential SOC stock [21,22]. A larger C pool can be obtained by enhancing the stability of SOC or reducing the rate of decomposition of labile SOC. Numerous studies have investigated the distribution of SOC [23,24,25], while there is a lack of comprehensive reporting on the distribution of the total and labile SOC fractions.
In the eastern coastal areas of China, a large area has been cultivated with poplar (Populus L.), mainly in agroforestry systems, but the modes vary, and the C sequestration capacity differs. This study investigates the spatial distributions of total and labile SOC pools in two agroforestry systems, both horizontally and vertically: a wide-row (14 m spacing) poplar and wheat (Triticum aestivum L.) agroforestry system (WPW) and a narrow-row (7 m spacing) poplar and wheat agroforestry system (NPW). A poplar planting system (P) and a wheat field (W) were used as controls. We hypothesize that: (1) Agroforestry systems contain more organic carbon and generate more labile carbon pools than control plots; (2) The narrow-row system has higher SOC contents than the wide-row system because the former system has higher density and aboveground biomass; (3) The SOC contents increase as proximity to the tree row decreases, and this is related to the distribution of the root system; (4) The various organic carbon components in the soil exhibit similar patterns of variation.

2. Materials and Methods

2.1. Study Area

The study site (33°19′ N, 120°46′ E) is located at the Dafeng Forest Farm, Yancheng County, Jiangsu Province, PRC, which is the transition zone between the subtropical zone and warm–wet zone with four distinct seasons, moderate temperature and abundant rainfall. The region experiences an average annual temperature of 14.1 °C, with a frost-free period lasting 213 days. It receives an annual precipitation of 1042.2 mm and enjoys 2238.9 h of sunshine. The rainfall is predominantly concentrated in summer in this experimental area, which primarily consists of intercropped farmland. The soil in the experimental area consists of alkaline sandy loam.

2.2. Experimental Design and Soil and Root Sampling

Through preliminary investigation, three typical poplar plantation systems and a farmland system of adjacent plots were selected: pure poplar plantation system (P), narrow-row poplar and wheat agroforestry system (NPW), wide-row poplar and wheat agroforestry system (WPW) and wheat field planting system (W). The agroforestry systems maintained a distance of 1 m between the crop and the tree row, and the distance between the four systems was less than 800 m. The specific information is presented in Table 1.
The poplar (Populus deltoides cv. “35”) plantation systems were planted in 2009, and wheat was sown in November every year and cultivated before sowing to a depth of approximately 20 cm. Most crop residues (mainly wheat straw and soybean straw) were harvested, and litter from trees was not removed. Excluding the pure poplar forest, the other three planting systems were annually supplied with diammonium phosphate (450 kg ha−1), urea (270 kg ha−1), and compound fertilizer (225 kg ha−1).
In May 2021, during the wheat-filling period, soil and root samples were collected. Three randomly selected plots, measuring 15 × 15 m each, were utilized for soil sampling in the W system, the distance between the sampling plots was at least 100 m. Soil samples were collected at depths of 0–20 cm, 20–40 cm, 40–60 cm, and 60–100 cm, and from five points using a soil drill (4 cm) along an S-shaped curve. The collected samples were then combined into composite samples using the quadripartite method. In the three typical poplar plantation systems, three plots, each measuring 28 × 30 m, were randomly selected, and four sampling locations with different distances were set, the distance between the sampling plots was at least 100 m. In the P and NPW systems, the plots were located at distances of 0 m, 1.5 m, 2.5 m, and 3.5 m from the poplar trees. In the WPW system, the rows were spaced at distances of 0 m, 1.5 m, 3.5 m, and 7 m from the poplar trees. The specific sampling methods are shown in Figure 1.
Five soil cores were drilled randomly from the same soil layer at each site, and the fine roots and litter debris were removed and combined into composite samples according to the four-section method. The collected soil samples were transported to the laboratory for testing in ice boxes. In addition, root samples were obtained by the continuous drilling soil sampling method [26], and the sampling plots were consistent with the soil sampling. The roots with a diameter ≤ 2 mm were selected and separated into tree roots and herbage roots. Subsequently, the dried root systems were measured.

2.3. Soil Analyses

Soil bulk density (BD) was measured using the cutting-ring method, SOC was analyzed using a modified Walkley and Black method [27]. The soil pH value was measured using a Sartorius PB-10 Basic pH meter. Total nitrogen (TN) was determined with the Kjeldahl method, ammonium nitrogen (NH4+) was quantified using the indigo blue colorimetric method, and nitrate nitrogen (NO3−) was measured with dual-band ultraviolet spectrophotometry. Total phosphorus (TP) was determined with a molybdenum colorimetric method, and soil available phosphorus (AP) was determined by sodium bicarbonate extraction and molybdenum–antimony colorimetry.
Soil microbial biomass carbon (MBC) was extracted by the chloroform fumigation-extraction method and measured by employing a liquid TOC analyzer (Elementar, Frankfurt, Germany). The potassium permanganate oxidation method was used to determine soil readily oxidizable carbon (ROC) [28]. Soil-dissolved organic carbon (DOC) was extracted by water (1:5 soil:water (w:v) ratio) at room temperature from fresh soil and determined using a liquid TOC analyzer.

2.4. Vegetation Analyses

In June 2021, an investigation was conducted on the understory vegetation biomass. Three 2 × 2 m plots were randomly selected in each system. All vegetation within the plots, including the root system, was harvested and the fresh weight was measured. A portion was taken back to the laboratory to determine the moisture content, and biomass estimation was conducted.
The total biomass of poplar trees is calculated according to the data on tree height and breast height diameter using the following formula.
W = 0.1236 (D2H) 0.8040 (r2 = 0.957)
where D is the breast height diameter (cm) of a poplar tree; H is the tree height; W is the dry weight of different components.

2.5. Statistical Analyses

We performed an analysis of variance (ANOVA) using SPSS version 24.0 (IBM, Chicago, IL, USA). The means of different treatments (n = 3) were compared using one-way ANOVA and Duncan’s multiple range test with a significance level set at 5%. Two-way ANOVA was used to analyze the main interaction effects of the planting systems, soil depths, and distances from the tree row on FRB, SOC, ROC, DOC, and MBC. Pearson’s correlation analysis was conducted using Origin version 2021 (OriginLab, Northampton, MA, USA).

3. Results

3.1. Biomass of Poplar and Understory Vegetation in Different Planting Systems

The overall vegetation biomass ranged from 23.63 t ha−1 to 147.50 t ha−1 in the four systems, and the P system had the highest overall vegetation biomass (Figure 2). Among the three poplar planting systems, the poplar biomass was much higher than the understory vegetation biomass. Specifically, in the P system, the poplar biomass reached 139.61 t ha−1, which was 15.9% and 41.5% higher than the NPW and WPW systems, respectively. The range of understory vegetation biomass in the four systems was from 7.89 t ha−1 to 23.63 t ha−1. The understory vegetation biomass based on wheat planting was significantly higher than in the P system (p < 0.001). Among them, the W system had the highest understory vegetation biomass, followed by WPW, with the P system having the lowest understory vegetation biomass.

3.2. Vertical and Horizontal Distribution of FRB

The distribution of FRB among different plants exhibited a decreasing trend across the four planting systems as soil depth increased (Figure 3). In the three poplar planting systems, the FRB of the poplar trees was significantly greater than that of the herbages, with the exception of the 7 m distance treatment in the WPW system. Additionally, as soil depth increased, the proportion of herbage FRB to the total FRB decreased progressively. The total FRB in the topsoil was higher near the tree row (at 0 and 1.5 m) in the WPW system than in the other treatments, while the lowest total FRB was observed in the middle of the tree row. In general, the P system exhibited higher FRB than the NPW system, whereas the W system showed lower total FRB compared to the other systems. In the P system, the highest total FRB was observed at 1.5 m from the tree row in the topsoil, whereas in deeper soil layers, the tree row exhibited the highest total FRB. Compared to the NPW system, the P system showed higher total FRB within the tree row. Moreover, the herbage FRB in the W system exceeded the other treatments, and the herbage FRB in the P system was lower than in the other systems.

3.3. Vertical and Horizontal Distributions of the SOC Content

The W system exhibited the lowest SOC content, particularly in the topsoil, while the WPW system exhibited the highest SOC content (Figure 4). Among the three poplar planting systems, the SOC content at the center of the tree row was lower than that at the other distances, consistent with the spatial distribution of total FRB. In the P and NPW systems, the contents and variation trends of SOC were similar, and the higher SOC content was measured at 1.5 m from the tree row in the 0–20 and 20–40 cm depth. In the WPW system, the highest SOC content was measured within the tree row in the topsoil. The distribution of SOC did not consistently align with that of total FRB when comparing across different systems. In the surface soil at a 7 m distance in the WPW system, even if the total FRB was lower than in the W system, the SOC content was significantly higher than in the W system. Similarly, compared to the P system, while the NPW system had a lower total FRB, there was no significant difference in SOC content between the two systems. Furthermore, in the deep soil, the SOC content in the NPW system was higher compared to the P system. A significant interaction between tree row distance and soil depth on SOC was observed in both the P and WPW systems. Additionally, the soil depth and planting system had a significant interaction with SOC (Table 2).

3.4. Vertical and Horizontal Distributions of the Soil ROC Content

The overall trend of ROC content was similar to that of SOC. Throughout the whole soil profile, the ROC content in the WPW system exhibited a significant increase compared to the other systems (p < 0.001, Figure 5). The W system demonstrated the lowest ROC content, and it was significantly lower compared to the other systems, except for the 60–100 cm soil layer (p < 0.001). Within the P system, the ROC content showed minimal variation across different distances throughout the whole soil profile. The distribution of ROC in the two agroforestry systems differed from that of SOC; the ROC content near the tree row in the topsoil was lower compared to other distances. However, there was minimal variation at different distances in the deeper soil. The soil depth and planting system had a significant interaction with the ROC (Table 2).

3.5. Vertical and Horizontal Distributions of the Soil DOC Content

The trend of DOC variation differed from those of SOC and ROC. Overall, the DOC content in the topsoil was higher in the two agroforestry systems than in the two monoculture systems, and the DOC content in the WPW system was significantly higher than that in the two monoculture systems (Figure 6). The P system had the lowest DOC content across the entire soil profile, except the topsoil. The horizontal distribution of DOC content was similar in the two narrow-row systems, and compared to other distances, the DOC content at 2.5 m from the tree row was lower in the 0–20 cm and 20–40 cm layers. In the P system, the DOC content at 0 m from the tree row was higher than that at other distances throughout the whole soil profile except for the 60–100 cm soil layer, and in the NPW system, the DOC content at 0 m and 1.5 m was higher in the whole soil profile. Throughout the whole soil profile, the DOC content at 1.5 m and 3.5 m was lower than that at the other distances in the WPW system. A significant interaction effect was observed between the tree row distance and soil depth on the DOC content in the P system (Table 2).

3.6. Vertical and Horizontal Distributions of the Soil MBC Content

The MBC content generally decreased as soil depth increased (Figure 7). Except for the 60–100 cm soil layer, the P system exhibited the highest MBC content, while the W system had the lowest MBC content. Additionally, the MBC content in the NPW system exceeded that in the WPW system. These patterns differed from the variations observed in SOC, ROC, and DOC. The horizontal distribution within each of the three poplar planting systems was opposite to the variation observed in DOC. In comparison to other distances within the P system, the MBC content was consistently higher at a distance of 2.5 m from the tree row across the entire soil profile. Moreover, compared to the other treatments, it was significantly higher in the topsoil (p < 0.001). In the P system, the MBC content was lower within the tree row than at other distances in the topsoil. However, in the 20–40 cm and 40–60 cm soil layers, it exhibited higher MBC content at 1.5 m and 3.5 m. Except for the tree row, the MBC content at other distances had little difference throughout the whole soil profile and was significantly higher than that within the tree row (p < 0.001). In the PWN system, the MBC content at 1.5 m, 2.5 m, and 3.5 m had little difference throughout the whole soil profile and was significantly higher than that at 0 m from the tree row (p < 0.001). In the WPW system, the MBC content in the soil profile at a distance of 3.5 m from the tree row was significantly higher than that at other distances (p < 0.001), except for the 40–60 cm soil layer. A significant interaction between tree row distance and soil depth on MBC was observed in the three poplar planting systems (Table 2).

3.7. Relationship between FRB, Soil Properties and Soil Organic Fractions

A linear fitting method was used to study the relationship between SOC, ROC, DOC, and MBC. Except for DOC in the W system, there was a significant positive correlation between each indicator (p < 0.01; Figure 8). Specifically, there was a strong linear correlation between FBR, SOC, and ROC. The correlation between MBC and DOC was weaker. Due to the introduction of different spacing treatments in the three poplar systems, the Pearson r2 for some indicators was lower than that in the W system. Overall, the correlations among the indicators in the WPW system were weaker than those in the two narrow-row systems. Additionally, the ROC/SOC, MBC/SOC, and MBC/DOC values in the W system were lower than in the other systems, while the DOC/ROC value was lower than in other systems.
The soil organic carbon fractions demonstrated a noteworthy positive correlation with various FRB (p < 0.001, Figure 9), with the most robust correlation observed in TFRB (r2 = 0.798; r2 = 0.513; r2 = 0.738; r2 = 0.611, respectively) and the least pronounced correlation in HFRB (r2 = 0.464; r2 = 0.342; r2 = 0.457; r2 = 0.524, respectively). Strong positive correlations (p < 0.001, Figure 9) were found between soil organic fractions and TN, NO3-, TP, and AP. Among these, TN exhibited particularly strong associations. Additionally, soil organic fractions showed negative correlations with BD and pH (p < 0.001).

4. Discussion

Trees have a greater capacity than crops for sequestering carbon in the soil [16]. Perennial trees had the potential to alter the amount of carbon input from subterranean residues [29]. Even though there was higher wheat biomass in the W system, the biomass of trees in poplar plantation systems far surpassed the biomass of wheat. Furthermore, in the W system, most photosynthetically fixed carbon was harvested, with only around 10% of crop residues remaining in the soil. In poplar plantation systems, the presence of trees also altered the quality of carbon inputs [29]. The roots of the trees can promote the formation of agglomerates and mineral-associated OM [30] and introduce additional C input microbiota, which increases the stability of soil C. The C sources generated by poplar are mostly biodegradable organic compounds such as lignin [31] and certain phenolic compounds, which can form stable carbon complexes with the soil. Compared to labile OC, these recalcitrant OC compounds have a complex chemical structure and lower microbial availability, resulting in a longer persistence time in the soil. Wheat and other vegetation generate more C-source in the form of sugars; these sugars are readily consumed by microorganisms and do not tend to be efficiently stored in the soil for extended periods [32]. In our study, the DOC/SOC value of the W system was much higher than that of other systems. A higher DOC proportion indicates that there are more easily decomposable carbon sources in the soil. This could potentially lead to an increase in soil microbial activity, thereby accelerating the breakdown and release of carbon. Additionally, intensive agricultural activities lead to rapid mineralization of SOC and the conversion of excess carbon into air [33].
The SOC content in the two agroforestry systems was also higher than that in the P system, consistent with our hypothesis 1. Although the vegetation biomass in the two agroforestry systems was lower compared to the P system, and the surface soil total FRB of the NPW system significantly decreased (Figure 3), the biomass of crops in the two agroforestry systems exceeded the weed biomass in the P system. Moreover, the postharvest stubble and poplar litter entered the soil with tillage practices, which was more conducive to the conversion of litter into SOC. In addition, while the FRB in the topsoil of the NPW system decreased, the total FRB in the deeper soil increased (Figure 3), thereby enhancing the SOC content in the deep soil [34]. Overall, the total SOC in the agroforestry systems surpassed that of the P system.
Overall, the variation pattern of SOC in different systems was similar to the trend of total FRB. Our findings revealed a highly significant positive correlation between SOC and total FRB (Figure 9). Moreover, the FRB of poplar trees significantly contributed to SOC, whereas the relationship between herbage FRB and SOC was relatively weak. Plant roots, especially fine roots, play a vital role in carbon cycling within terrestrial ecosystems [35,36]. Numerous studies have consistently confirmed their significant contribution to the accumulation of SOC [37,38,39,40,41]. Following the death of fine roots, they can directly decompose in the soil, forming stable OM and increasing the storage capacity of SOC [38]. In addition, mycorrhizal fungi associated with roots play a vital role in carbon input into the soil and serve as important carbon reservoirs in the soil [30].
In the three poplar plantation systems, consistent with the spatial distribution of total FRB, the lowest SOC content occurred at the farthest distance from the tree rows. The spatial distributions of the SOC content were similar in the two narrow-row systems, while contrary to our initial hypothesis 2, the highest SOC content was observed at 1.5 m from the tree rows. The WPW system had the highest SOC content within the tree rows, which differed from the two narrow-row systems. Several studies on SOC distribution have also yielded different results. Guillot et al. [42] and Peichl et al. [12] suggested that the SOC content exhibited higher values within tree rows compared to inter-rows. The observed disparity can be attributed to the higher density of fine roots, increased litter inputs, and the absence of tillage practices. Similar conclusions were also drawn by Upson and Burges [8]. Similarly, Muñoz et al. [43] found significantly higher SOC content under the canopy in natural forests and agroforestry systems. In the oak forest systems of central-western Spain, the SOC content in the topsoil gradually decreased with increasing distance from the trees [9]. Cardinael et al. [23] observed that the distance of trees had no significant effect on SOC at all depths, attributing it to the uniform distribution of litter in the field. Bambrick et al. [11] suggested that the low-carbon inputs from crop residues near tree rows could be offset by the high input of fine root mortality from trees. The distribution pattern of SOC varies across different studies due to variations in planting systems and site conditions. For instance, tree age may influence the distribution of SOC [11]. Our study indicated that the distributions of SOC were mainly affected by the planting method of the poplar trees.
However, the distribution of SOC did not fully correspond to the distribution of total FRB, and the increased SOC in the agroforestry system can be attributed to a variety of mechanisms and processes [30]. In addition to roots, other factors such as aboveground litter, tillage, fertilization, intercropping, soil texture, and microclimate within forest systems also significantly influence SOC [34,40,44]. In the surface soil, carbon sources from leaf litter and woody debris made significant contributions to SOC. Despite lower total FRB compared to croplands, the SOC content in the WPW system remained significantly higher at locations farthest from the trees. The litter produced by tall trees can have a more uniform impact on intercropping spaces [11].
Some researchers proposed that the density of trees increased the aboveground biomass, and a high-density stand could sequester more C than a low-density stand [34,45,46]. However, contrary to our hypothesis 3, the SOC content in the wide-row system was higher than that in the narrow-row system. We found that DBH had a more positive impact on SOC accumulation. Moreover, a larger DBH had the ability to influence SOC at a greater distance, as evidenced by the SOC content in the WPW system at 3.5 m, which remained higher than that at all sites in the narrow-row systems. According to the findings of Morais et al. [40], a significant correlation was observed between average DBH and increased SOC, while the correlation with forest basal area was less pronounced. The growth rate of trees has a significant impact on OC accumulation, as observed in agroforestry systems where older trees show less pronounced trends in increasing SOC [30], and also reduced stability of microbial residues [47]. The amount of OC input to the soil (leaf litter, fine roots) was lower for slow-growing trees at the same age [23], thus reducing the increase in SOC. Similarly, fast-growing broad-leaf forest forests had higher carbon sequestration capacity than coniferous forests [29,34]. The vitality and growth of trees, reflected by larger DBH, lead to a more developed root system and a greater contribution to SOC [48]. Higher-density forests intensify competition, resulting in slower tree growth, which in turn affects the distribution of fine roots. Additionally, in the WPW system, a larger average DBH and sufficient nutrient availability can enhance fine root turnover [36].
Soil labile carbon pools, including MBC, ROC, and DOC, are crucial for soil nutrient retention and energy provisioning for microbial activity [49]. Various land-use practices exert considerable influence on the labile fractions of SOC, with significantly higher MBC and ROC contents observed in the three poplar plantation systems compared to farmland. The tree plantation-based system exhibited a more stable microclimate, greater vegetation cover and species diversity, and more abundant soil resources (e.g., carbon, nitrogen, and water) [16,29,30]. These factors had a significant impact on microbial abundance and community composition [50,51], thus affecting the turnover of ROC. However, contrary to our hypothesis 1, the two poplar agroforestry systems enhanced soil ROC and DOC content by supplying a greater amount of fresh carbon sources [52]. However, the MBC content was higher in the P system than in the two agroforestry systems due to the presence of more diverse understory vegetation [53] and being undisturbed by cultivation practices [40].
Due to their diverse sources and influencing factors, the four systems exhibited distinct variations in the labile fractions of SOC, and the distribution trend within the systems was notably different from that of SOC, contrary to our hypothesis 4. In addition to SOC, soil moisture and nutrients also have important effects on soil MBC [42,54]. The soil MBC contents at 2.5 m from the tree rows in the two narrow-row systems, as well as at 3.5 m from the tree rows in the wide-row system, exhibited higher values compared to other distances within the respective systems. The SOC at these distances was higher, and there was little competition between poplar and wheat for soil water and nutrients. The distribution pattern of soil ROC within the poplar plantation systems was also different from that of SOC. The ROC was influenced by the type of carbon input. Despite the lower SOC content in the center of the tree rows in the three poplar planting systems compared to other distances, the ROC content was at a higher level instead. The closer the distance to the tree rows, the greater the soil was affected by poplar and the less by wheat. As previously mentioned, wheat can produce more unstable carbon. The DOC was mainly derived from the physical, chemical, and biological decomposition of SOM, as well as being a carbon source that can be directly utilized by soil microorganisms [19], strongly affected by soil microorganisms. In the three poplar planting systems, the spatial distribution trend of the soil DOC content was opposite to that of soil MBC. With the increase in soil microorganisms, the consumption of DOC increased, which also explained why the SOC content in the P system was much higher than that in the W system and why the DOC content was lower in the P system due to the higher soil MBC.
There were strong correlations between the SOC fractions and soil TN (Figure 9). The quantity and quality of N can affect system productivity and thus the amount of plant litter [55]. In addition, higher N utilization helps microorganisms produce putrefactive compounds from fresh litter and convert preexisting putrefactive compounds into SOC fractions [56]. The availability of N in the soil also affects the cycling rate of SOM [57]. Our study revealed a significant positive correlation between SOC and ammonium N, as well as nitrate N. The availability of P can impact tree biomass and litter quality [58], promote the production of belowground carbon distribution products, and contribute to the nucleic acid synthesis and energy generation of soil microorganisms [59]. In our study, there was a significant correlation between P components, especially AP, and the soil organic carbon components. The BD and SOC fractions were significantly negatively correlated, compacted soil inhibited root infiltration, reduced underground biomass [60], weakened soil microbial activity [61], and thus may reduce SOC input. There was also a significant negative correlation between pH and SOC, and organic acids were produced in the process of litter decomposition, which reduced the soil pH [62].

5. Conclusions

In this study, we observed that trees in poplar planting systems demonstrated increased biomass, most notably in the P system, where the vegetation biomass was the highest. The SOC levels were significantly higher in agroforestry systems, particularly in the deeper soil layers compared to conventional planting systems. Moreover, the WPW system was more effective in sequestering SOC compared to the NPW system. This effect was attributed to the WPW system’s ability to stimulate tree growth and enhance the total FRB. We also noted the horizontal distribution of SOC across the three poplar planting systems displayed distinct patterns. These patterns were influenced by the planting methods used for the poplar trees and aligned with the distribution trends of total FRB. Further investigation revealed interactions among different SOC fractions in the soil. However, these fractions displayed varying change trends. The ROC was more aligned with the overall SOC trends, whereas MBC and DOC showed contrasting horizontal distribution trends in their respective poplar planting systems. Our Pearson correlation analysis revealed that basic soil properties, especially TN, exerted a substantial influence on SOC fraction formation. Overall, our study offers valuable insights for choosing an effective planting system aimed at maximizing carbon sequestration as a strategy for mitigating climate change. Future research could explore the development of tree-based agro-ecosystems with expanded ecosystem service options, including enhanced carbon sequestration and soil health improvements.

Author Contributions

Writing—original draft preparation, investigation, B.W.; writing, and revising original draft, X.S. and T.W.; visualization, T.Y., C.X., Z.L. and D.T.; writing—review and editing, L.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by The National Key Research and Development Program of China [2021YFD2201202], The Scholarship for Studying Abroad by the China Scholarship Council [202108320281], and The Postgraduate Research & Practice Innovation Program of Jiangsu Province [KYCX22_1117].

Data Availability Statement

Data are available on request from the corresponding author.

Conflicts of Interest

The authors declare that they have no conflict of interest.

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Figure 1. Sample photographs and sampling methods of different planting systems. (A) Pure poplar plantation system (P); (B) narrow-row of the poplar and wheat agroforestry system (NPW); (C) wide-row of the poplar and wheat agroforestry system (WPW); and (D) wheat field planting system (W).
Figure 1. Sample photographs and sampling methods of different planting systems. (A) Pure poplar plantation system (P); (B) narrow-row of the poplar and wheat agroforestry system (NPW); (C) wide-row of the poplar and wheat agroforestry system (WPW); and (D) wheat field planting system (W).
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Figure 2. Biomass of poplar and understory vegetation in different planting systems. Different lowercase letters indicate significant differences in poplar biomass in different planting systems at the p < 0.05 level. Different capital letters indicate significant differences in understory vegetation biomass in different planting systems at the p < 0.05 level. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
Figure 2. Biomass of poplar and understory vegetation in different planting systems. Different lowercase letters indicate significant differences in poplar biomass in different planting systems at the p < 0.05 level. Different capital letters indicate significant differences in understory vegetation biomass in different planting systems at the p < 0.05 level. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
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Figure 3. Vertical and horizontal distributions of poplar and herbage fine root biomass (g kg−1) in different planting systems. Different lowercase letters indicate significant differences among thirteen treatments at the p < 0.05 level within the same soil layer. (A) 0–20 cm soil layer; (B) 20–40 cm soil layer; (C) 40–60 cm soil layer; and (D) 60–100 cm soil layer. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
Figure 3. Vertical and horizontal distributions of poplar and herbage fine root biomass (g kg−1) in different planting systems. Different lowercase letters indicate significant differences among thirteen treatments at the p < 0.05 level within the same soil layer. (A) 0–20 cm soil layer; (B) 20–40 cm soil layer; (C) 40–60 cm soil layer; and (D) 60–100 cm soil layer. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
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Figure 4. Vertical and horizontal distributions of the soil organic carbon content in different planting systems. Different lowercase letters indicate significant differences among 13 treatments at the p < 0.05 level within the same soil layer. (A) 0–20 cm soil layer; (B) 20–40 cm soil layer; (C) 40–60 cm soil layer; and (D) 60–100 cm soil layer. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
Figure 4. Vertical and horizontal distributions of the soil organic carbon content in different planting systems. Different lowercase letters indicate significant differences among 13 treatments at the p < 0.05 level within the same soil layer. (A) 0–20 cm soil layer; (B) 20–40 cm soil layer; (C) 40–60 cm soil layer; and (D) 60–100 cm soil layer. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
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Figure 5. Vertical and horizontal distributions of the soil readily oxidizable carbon content in different planting systems. Different lowercase letters indicate significant differences among thirteen treatments at the p < 0.05 level within the same soil layer. (A) 0–20 cm soil layer; (B) 20–40 cm soil layer; (C) 40–60 cm soil layer; and (D) 60–100 cm soil layer. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
Figure 5. Vertical and horizontal distributions of the soil readily oxidizable carbon content in different planting systems. Different lowercase letters indicate significant differences among thirteen treatments at the p < 0.05 level within the same soil layer. (A) 0–20 cm soil layer; (B) 20–40 cm soil layer; (C) 40–60 cm soil layer; and (D) 60–100 cm soil layer. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
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Figure 6. Vertical and horizontal distributions of the soil dissolved organic carbon content in different planting systems. Different lowercase letters indicate significant differences among thirteen treatments at the p < 0.05 level within the same soil layer. (A) 0–20 cm soil layer; (B) 20–40 cm soil layer; (C) 40–60 cm soil layer; and (D) 60–100 cm soil layer. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
Figure 6. Vertical and horizontal distributions of the soil dissolved organic carbon content in different planting systems. Different lowercase letters indicate significant differences among thirteen treatments at the p < 0.05 level within the same soil layer. (A) 0–20 cm soil layer; (B) 20–40 cm soil layer; (C) 40–60 cm soil layer; and (D) 60–100 cm soil layer. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
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Figure 7. Vertical and horizontal distributions of the soil microbial biomass carbon content in different planting systems. Different lowercase letters indicate significant differences among thirteen treatments at the p < 0.05 level within the same soil layer. (A) 0–20 cm soil layer; (B) 20–40 cm soil layer; (C) 40–60 cm soil layer; and (D) 60–100 cm soil layer. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
Figure 7. Vertical and horizontal distributions of the soil microbial biomass carbon content in different planting systems. Different lowercase letters indicate significant differences among thirteen treatments at the p < 0.05 level within the same soil layer. (A) 0–20 cm soil layer; (B) 20–40 cm soil layer; (C) 40–60 cm soil layer; and (D) 60–100 cm soil layer. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
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Figure 8. Relationships between the (A) SOC and ROC; (B) SOC and MBC; (C) SOC and DOC; (D) ROC and MBC; (E) ROC and DOC; (F) DOC and MBC. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
Figure 8. Relationships between the (A) SOC and ROC; (B) SOC and MBC; (C) SOC and DOC; (D) ROC and MBC; (E) ROC and DOC; (F) DOC and MBC. P, pure poplar plantation system; NPW, narrow-row poplar, and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
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Figure 9. Correlation coefficients (r) between soil carbon fractions, fine root biomass, and soil properties. The asterisks indicate significant levels of correlations: ** p < 0.01, and *** p < 0.001. TFRB, the total fine root biomass; PFRB, the poplar fine root biomass; HFRB, the herbage fine root biomass.
Figure 9. Correlation coefficients (r) between soil carbon fractions, fine root biomass, and soil properties. The asterisks indicate significant levels of correlations: ** p < 0.01, and *** p < 0.001. TFRB, the total fine root biomass; PFRB, the poplar fine root biomass; HFRB, the herbage fine root biomass.
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Table 1. Basic profile of the poplar plantation sites.
Table 1. Basic profile of the poplar plantation sites.
TreatmentsAge
(yrs)		Planting Density (m × m)Area
(km2)		Mean DBH
(cm)		Mean Height
(m)
P123 × 70.525.16 ± 2.9824.41 ± 1.92
NPW123 × 70.523.71 ± 2.6423.27 ± 1.38
WPW123 × 14228.51 ± 3.8624.48 ± 2.02
W––2––
Notes: P, pure poplar plantation system; NPW, narrow-row poplar and wheat agroforestry system; WPW, wide-row poplar, and wheat agroforestry system; W, wheat field planting system.
Table 2. Results of the analysis of variance of fine root biomass (total FRB), soil organic carbon (SOC), soil microbial biomass carbon (MBC), soil readily oxidizable carbon (ROC), soil dissolved organic carbon (DOC) and SOC stocks with distance from the tree row and soil depth, land-use type and soil depth.
Table 2. Results of the analysis of variance of fine root biomass (total FRB), soil organic carbon (SOC), soil microbial biomass carbon (MBC), soil readily oxidizable carbon (ROC), soil dissolved organic carbon (DOC) and SOC stocks with distance from the tree row and soil depth, land-use type and soil depth.
Planting SystemsSource of
Variation		TFRBSOCMBCROCDOC
dfFdfFdfFdfFdfF
PD39.544 ***312.587 ***322.627 ***30.36327.026 ***
S3151.309 ***3603.586 ***3175.571 ***3567.787 ***374.071 ***
D×S98.125 ***95.416 ***910.27 ***91.898913.456 ***
NPWD36.809 **328.745 ***349.896 ***33.146313.568 ***
S3190.931 ***3605.156 ***3200.754 ***3361.723 ***3107.116 ***
D×S99.053 ***93.159 **92.726 *91.90491.189
WPWD341.396 ***314.838 ***350.354 ***30.792310.069 ***
S3262.239 ***3636.584 ***3186.378 ***3135.184 ***375.269 ***
D×S928.631 ***92.468 *911.434 ***90.70392.465 *
Total systemPS35.546 **326.888 ***313.207 ***374.074 ***341.783 ***
S362.406 ***3475.441 ***360.73 ***3374.202 ***344.785 ***
PS×S94.134 ***93.052 **92.944 **98.698 ***94.487 ***
Notes: D, distances Notes: D, distances from tree row; PS, planting system; S, soil depth, * p < 0.05, ** p < 0.01, and *** p < 0.001.
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Wang, B.; Su, X.; Wang, T.; Yang, T.; Xu, C.; Lin, Z.; Tian, D.; Tang, L. Spatial Heterogeneity of Total and Labile Soil Organic Carbon Pools in Poplar Agroforestry Systems. Forests 2023, 14, 1869. https://doi.org/10.3390/f14091869

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Wang B, Su X, Wang T, Yang T, Xu C, Lin Z, Tian D, Tang L. Spatial Heterogeneity of Total and Labile Soil Organic Carbon Pools in Poplar Agroforestry Systems. Forests. 2023; 14(9):1869. https://doi.org/10.3390/f14091869

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Wang, Bo, Xiaolong Su, Tongli Wang, Tao Yang, Cheng Xu, Zeyang Lin, Di Tian, and Luozhong Tang. 2023. "Spatial Heterogeneity of Total and Labile Soil Organic Carbon Pools in Poplar Agroforestry Systems" Forests 14, no. 9: 1869. https://doi.org/10.3390/f14091869

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