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Article

Effects of Biochar on Soil Organic Carbon in Relation to Soil Nutrient Contents, Climate Zones and Cropping Systems: A Chinese Meta-Analysis

by
Longjia Tian
,
Guangcheng Shao
*,
Yang Gao
,
Enze Song
and
Jia Lu
College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China
*
Author to whom correspondence should be addressed.
Land 2024, 13(10), 1608; https://doi.org/10.3390/land13101608
Submission received: 21 August 2024 / Revised: 29 September 2024 / Accepted: 1 October 2024 / Published: 3 October 2024
Browse Figures
Figure 1
<p>Map showing the distribution of the 101 experimental sites involved in this meta-analysis. The red triangle marks represent the locations of the experimental sites. Note that the numbers represent the number of studies represented by each mark.</p> "> Figure 2
<p>A flowchart summarizing the retrieval process and the division of moderating variables in the manuscript and the <a href="#app1-land-13-01608" class="html-app">Supplementary Information</a>.</p> "> Figure 3
<p>Map showing the China climate zone based on the Köppen–Geiger climate classification. The use of color is described in <a href="#app1-land-13-01608" class="html-app">Table S2 of the Supplementary Information</a>.</p> "> Figure 4
<p>Normal distribution of paired comparisons according to changes in SOC content under biochar application relative to the control (no biochar application).</p> "> Figure 5
<p>Forest plots revealing that changes in soil organic carbon content following biochar application relative to the control varied with categories of (<b>a</b>) soil organic matter content, (<b>b</b>) soil available N content, (<b>c</b>) soil total N content, (<b>d</b>) soil available P content, (<b>e</b>) soil total P content and (<b>f</b>) soil available K content. Points represent the mean effect, and bars represent 95% confidence intervals. Numbers in parentheses in the right column show the number of paired comparisons (<b>left</b>) and the total number of replicates (<b>right</b>) for each analysis.</p> "> Figure 6
<p>Forest plots revealing that changes in soil organic carbon content following biochar application relative to the control varied with categories of (<b>a</b>) climate zone, (<b>b</b>) planting pattern and (<b>c</b>) soil tillage method. Points stand for the mean effect, and bars represent 95% confidence intervals. Numbers in parentheses in the right column show the number of paired comparisons (<b>left</b>) and the total number of replicates (<b>right</b>) for each analysis.</p> "> Figure 7
<p>The relative importance of the moderating variables in regulating the response of soil organic carbon changes to biochar application. Variable 1, climate zone; Variable 2, soil tillage method; Variable 3, soil total N content; Variable 4, soil total P content; Variable 5, soil available P content; Variable 6, soil available K content.</p> "> Figure 8
<p>The effects of changes in plants and microbes under low P availability on soil organic carbon. + means that the change leads to an increase in soil organic carbon. − means that the change leads to a decrease in soil organic carbon.</p> ">
Versions Notes

Abstract

:
Biochar application is an effective way to improve soil organic carbon (SOC) content and ensure food security. However, there were differences in SOC content following biochar application under different conditions. We collected 637 paired comparisons from 101 articles to determine the following: (1) the average effect of biochar application on SOC content and (2) the response of SOC content to different soil nutrient contents, climate zones and cropping systems following biochar application. The results showed that the soil available phosphorus (P) content and soil available potassium (K) content reached the highest level in the category of <10 mg kg−1 and >150 mg kg−1, respectively. Soil total P content subgroups achieved maximum increase in the intermediate category. The Cw zone (temperate, without dry season) obtained the maximum level of SOC content. Compared with plough tillage, rotary tillage presented significantly higher SOC content. Therefore, low available P and K contents, moderate soil total N and P contents, rotary tillage and the Cw zone were more effective in increasing SOC content. Furthermore, the results of a random forest algorithm showed that soil nutrient contents were the most important variables. This study provided a scientific basis for SOC sequestration and improving soil fertility.

1. Introduction

Continuous tillage has led to soil degradation and a decline in soil fertility worldwide [1]. With the decline in soil productivity, soil degradation has been considered a global threat [2,3]. As the most populous country, China is facing serious food security challenges. In the context of decreasing arable land, improving soil fertility is one of the funda-mental ways to ensure food security in China. As an essential component of the terrestrial carbon (C) pool [4,5], soil organic carbon (SOC) provides essential nutrients for plant and microbial life and contributes to the formation of the soil bulk structure, which plays a crucial role in maintaining ecosystem productivity [6]. Therefore, SOC is a key indicator of soil fertility. Biochar is a C enrichment material produced by the high-temperature pyrolysis of waste biomass in anoxic environments and is an eco-friendly soil amendment [7,8,9]. It has been shown to achieve effective SOC replenishment by importing stable C into the soil for conservation [10,11,12]. Therefore, biochar is considered a practical C sequestration strategy that provides a viable path to improve soil structure and restore soil fertility.
Numerous studies have confirmed the positive effects of biochar application on SOC storage [13,14]. However, there were differences in the response of SOC to biochar application under different conditions. Pang et al. [15] added biochar to soils with low SOC content. The results showed that SOC content increased by 17.28%. Joseph et al. [16] added biochar to soils with high SOC content but found a lower increase in SOC content. The C sequestration potential of biochar may be weakened by its promotion of decomposition of native soil organic matter [17]. Hasnat et al. [18] found through a soil mineralization experiment that high nitrogen (N) availability increased C loss from soil respiration. The increase in soil C mineralization was also observed under low N availability conditions [19]. In a biochar-added pot experiment, Tian et al. [20] found that SOC content under high phosphorus (P) availability was 3.87% lower than that under low P availability. Temperature and moisture significantly impact SOC mineralization sequestration [21]. The dominance of water and temperature varies from different regions due to differences in climate characteristics [22]. Exploring climate effects on biochar C sequestration potential is essential. In addition, various agronomic practices may lead to differences in SOC changes under biochar application due to different soil disturbances and microbial abundances [23,24]. These factors remain uncertain in relation to the effects of biochar on SOC. Kuppusamy et al. [25] found that the soluble component in biochar was usually less than 10%. The results of the soil mineralization experiments showed that approximately 10–20% of the soluble components were rapidly mineralized to CO2 within a short time when biochar was added to the soil [26]. This process consumes very little SOC. Therefore, it was reasonable to assume that the differences in SOC content were not associated with the rapid enhancement of soil respiration in the short-term following biochar application, which was mainly caused by the difference in stable organic C decomposition rate and crop C input. Considering the understanding above, we determined whether we could explore the response of SOC to biochar application based on different conditions to provide guidance for the rational use of biochar.
Meta-analysis allows a more precise estimation of the imposed effects by integrating related studies rather than individual studies. Several scholars have applied meta-analysis to SOC-related areas. Schmidt et al. [27] found that biochar application was generally beneficial for agronomic parameters including SOC. Gross et al. [28] used meta-analysis to conclude that SOC increased by an average of 29% following biochar application. Xu et al. [29] found that soil pH and biochar C/N ratio were the key determinants of the effect of biochar application on SOC with a meta-analysis. Sun et al. [30] found that the effect size of biochar was greatest for SOC compared with soil C/N ratio and soil pH. Liu et al. [31] found that an appropriate N and P fertilizer dosage was more conducive to SOC retention. Zhang et al. [32] concluded that biochar was more effective in increasing SOC content in tropical zones (75.73% on average), compared with temperate zones. These studies have conducted more research on biochar properties as well as soil texture and soil pH. Soil nutrient contents and cropping systems have not received sufficient attention regarding their impact on SOC. Furthermore, most studies of climate zones have been focused on the tropics and temperate zones. China’s climate zone was not carefully analyzed. In this study, we conducted a meta-analysis to determine (1) the average effect of biochar application on SOC content; (2) the response of SOC content to different soil nutrient contents, climate zones and cropping systems following biochar application; and (3) the relative importance of these moderating variables by a random forest algorithm.

2. Materials and Methods

2.1. Data Source

Articles were searched in China National Knowledge Internet and Web of Science databases until December 2023. We used the following keywords to access articles related to the effects of biochar application on SOC content: (1) ‘biochar’ and ‘soil organic carbon’, (2) ‘biochar’ and ‘soil properties’ and (3) ‘biochar’ and ‘soil fertility’. Articles with non-Chinese experimental sites and duplicates were firstly excluded. Then, the collected literature was further screened using the following criteria: (1) articles that did not include SOC were removed, (2) articles that used soil mineralization experiments were removed, except for articles that included both soil mineralization experiments and planting experiments, (3) articles that did not grow crops were removed and (4) articles where it was difficult to obtain data from graphs were removed. Finally, 101 articles were screened as useful for this paper. The experimental distribution of the 101 articles involved in this paper is shown in Figure 1.

2.2. Data Collection

The data collected from the articles were the mean (mean) of SOC content, standard deviation (sd) and repetition times (n). SOC content was determined using the external heating method of potassium dichromate and concentrated sulfuric acid. Plot Digitizer 2.6.9 software was used for data extraction when the results were presented only in figures. A total of 637 paired comparisons (with and without biochar) were obtained from 101 articles.
In addition to the necessary data (mean, sd and n), we recorded all moderating variables mentioned in the collected articles that might influence SOC content following biochar application. These moderating variables included soil properties (soil pH, soil organic matter content, soil available N content, soil total N content, soil available P content, soil total P content and soil available potassium (K) content), biochar properties (biochar feedstock, biochar maximum pyrolysis temperature, biochar pH, biochar C content, biochar N content, biochar P content and biochar K content), climate zones, cropping systems (planting pattern and soil tillage method) and experimental conditions (experiment type and crop type). This paper focused on the analysis of the effects of soil nutrient contents, climate zones and cropping systems on SOC content. The results of the other subgroups were presented in the Supplementary Information. The retrieval process and the division of moderating variables in the manuscript and the Supplementary Information are summarized in a flowchart (Figure 2).

2.3. Data Categorisation

To test the effects of different moderating variables on SOC content following biochar application and maximize in-group homogenization, the paired comparisons were subdivided into groups based on moderating variables. Soil pH was divided into <6.5, 6.5–7.5 and >7.5. Soil depth was divided into 0–20cm and >20 cm. The remaining soil properties were classified according to the soil nutrient classification standard of the second land census in China [33]. The specific groups were as follows: soil organic matter content (<10, 10–20 and >20 g kg−1), soil available N content (<90, 90–120 and >120 mg kg−1), soil total N content (<0.75, 0.75–1, 1.01–1.5 and >1.5 g kg−1), soil available P content (<10, 10–20 and >20 mg kg−1), soil total P content (<0.4, 0.4–0.7 and >0.7 g kg−1) and soil available K content (<100, 100–150 and >150 mg kg−1). According to the classification method of Gao et al. [34], biochar feedstock and biochar maximum pyrolysis temperature were classified as herbs and wood, <550 °C and ≥550 °C. The remaining biochar properties were grouped as follows: biochar pH (>9, 9–10 and <10), biochar C content (<50%, 50–70% and >70%), biochar N content (<0.6%, 0.6–1.2% and >1.2%), biochar P content (<0.2%, 0.2–0.8% and >0.8%) and biochar K content (<1.5%, 1.5–2.5% and >2.5%). The climate of the experimental sites was classified based on the Köppen–Geiger climate classification [35]. The climate distribution in China is shown in Figure 3. The climate types of the experimental sites mainly included BS (arid, steppe), Cf (temperate, no dry season), Cw (temperate, dry winter) and Dw (cold, dry winter). The remaining cropping systems and experimental conditions were grouped according to the collected article accounts: planting pattern (monoculture and crop rotation), soil tillage method (plough tillage and rotary tillage), biochar application amount (<10 Mg ha−1, 10–20 Mg ha−1 and >20 Mg ha−1), biochar application duration (≤1 year (yr), 1.01–4.99 yr and ≥5 yr), experiment type (field and pot) and crop type (herbs and industrial crops or cereals).

2.4. Meta-Analysis

To perform the meta-analysis, the effect size and variance of each paired comparison were first calculated. Then, weights were assigned to each paired comparison. Finally, a weighted average of these effect sizes was calculated [34]. Because the SOC data were measured in physical units, the response ratio (R) was used to calculate the effect size of each SOC content value. To maintain a symmetrical distribution of data, it should be calculated on a logarithmic scale. Therefore, ln(R) is calculated using the following equation [35]:
ln(R) = ln(XT/XC)
where XT and XC are the average values of SOC content in the biochar treatment and control (without biochar) groups.
Because there are significant differences in the data in this study (I2 = 99.0% >50%), a random-effects model should be adopted [36]. R is a programming language and open-access software that is maintained and managed through a comprehensive R network. Constructing and conducting meta-analysis in R have become one of the main choices for meta-analysis. In this paper, the random-effects model established by the software package of R 4.3.2 software was used for meta-analysis. To make the forest plot clearer, all effect sizes were expressed as a percentage of the ratio of biochar application to control SOC content decreased by 1, i.e., (R − 1) × 100%. In the forest plot, points represent the mean effect, and bars represent 95% confidence intervals (95% CIs). Numbers in parentheses in the right column show the number of paired comparisons (left) and the total number of replicates (right) for each analysis. When there is no overlap in the 95% confidence intervals between two categories, the two categories are considered to be statistically significantly different [37]. Random forest algorithms can handle large numbers of variables without presupposing causality [38]. We used random forest algorithms to calculate the relative importance of all moderating variables with significant differences.

3. Results

3.1. Overall Effects

By screening the existing literature, this study found 101 papers and 637 paired comparisons that met the criteria for inclusion in this meta-analysis study. The percentage increase in SOC content under biochar application ranged from −12.92% to 236.05% compared with no biochar application. Figure 4 shows the frequency distribution of the changes in SOC content under biochar application compared with the control for all pairs of data. Only 26 of the 637 paired comparisons showed a suppressive effect of biochar application on SOC content, and the majority of the data showed a positive effect. Nearly 73.00% of these paired comparisons were between 0% and 40%, which is consistent with the results of our meta-analysis that biochar application had a statistically significant positive effect on the increase in SOC content (p < 0.0001, results of the meta-analysis). Biochar application increased SOC content by an average of 26.02% (95% CI: 24.21% to 27.85%), compared with the control group. However, we found high heterogeneity between paired comparisons (I2 = 99.0% >75%). Subgroup analysis was performed to determine the potential causes of the variation.

3.2. Soil Nutrient Contents

The degree of response of SOC content to biochar depended on soil nutrient contents, such as soil organic matter content, soil available N content, soil total N content, soil available P content, soil total P content and soil available K content. We tried to analyze the change pattern of SOC content following biochar application based on these indicators (Figure 5).
Figure 5a shows the response of SOC content to biochar addition under different soil organic matter categories. Under three soil organic matter contents (<10 g kg−1, 10–20 g kg−1, >20 g kg−1), biochar application increased SOC content by 38.78% on average (95% CI: 26.52% to 52.25%), 30.45% on average (95% CI: 26.77% to 34.23%) and 31.01% on average (95% CI: 26.63% to 35.54%), respectively. The percentage increase in SOC content was statistically significant in all categories. There was no significant difference among the three categories.
Considering the possible influence of N on SOC content, soil available N and soil total N contents were included in the subgroup analysis. There was no significant difference in SOC content among the different soil available N categories (Figure 5b), but we observed a trend that SOC content decreased with an increase in soil available N content following biochar application. SOC content increased by 26.54% on average (95% CI: 23.00% to 30.18%), 22.06% on average (95% CI: 18.95% to 25.25%) and 20.65% on average (95% CI: 16.59% to 24.86%).
Figure 5c shows that the increase in SOC content following biochar application reached the highest level in the 0.75–1 g kg−1 soil total N content category (27.43% on average, 95% CI: 21.81% to 33.31%). Significant differences were observed between the 1.01–1.5 g kg−1 and >1.5 g kg−1 categories. In general, SOC content following biochar application first increased and then decreased as the soil total N content increased.
As shown in Figure 5d, different soil available P contents had significant effects on changes in SOC content following biochar application. As soil available P content increased, SOC content increased by 34.18% on average (95% CI: 27.56% to 41.15%), 25.99% on average (95% CI: 22.66% to 29.42%) and 24.29% on average (95% CI: 21.31% to 27.34%).
There were significant differences in SOC content among three soil total P content categories (Figure 5e). The <0.4 g kg−1 category had the lowest increase in SOC content (12.48% on average, 95% CI: 9.77% to 15.27%). High SOC contents were obtained in the 0.4–0.7 g kg−1 category (35.46% on average, 95% CI: 30.33% to 40.79%) and >0.7 g kg−1 category (23.00% on average, 95% CI: 18.84% to 27.30%).
The results in Figure 5f show that the percentage increase in SOC content reached the minimum (19.62% on average, 95% CI: 16.90% to 22.41%) when the soil available K content was between 100 and 150 mg kg−1. SOC content significantly increased in the <100 mg kg−1 and >150 mg kg−1 categories, with average increases of 30.54% on average (95% CI: 25.34% to 35.96%) and 30.14% on average (95% CI: 26.51% to 33.88%), respectively.

3.3. Climate Zones and Cropping Systems

To investigate the differences in SOC content caused by biochar application under different climate zones and cropping systems, we collected data on climate zone, planting pattern and soil tillage method to investigate the effect of biochar application on SOC content (Figure 6).
We divided the climate zones into four categories: BS, Cf, Cw and Dw (Figure 6a). The Dw category presented the minimum increase in SOC content (18.99% on average, 95% CI: 15.80% to 22.27%), which was significantly different from the Cf category (29.12% on average, 95% CI: 23.78% to 34.68%) and Cw category (29.83% on average, 95% CI: 26.79% to 32.94%). However, significance was not reflected between the BS category and the other climate categories.
As shown in Figure 6b, biochar application under monoculture and crop rotation significantly increased SOC content. However, there was no significant difference between monoculture and crop rotation. The percentage increase in SOC content in the two categories was 23.95% on average (95% CI: 19.90% to 28.14%) and 28.47% on average (95% CI: 24.16% to 32.92%), respectively.
The results in Figure 6c show a significant difference in SOC content between plough tillage and rotary tillage. Rotary tillage was more effective in retaining more SOC than plough tillage. Compared with plough tillage (20.66% on average, 95% CI: 17.16% to 24.26%), rotary tillage reached a higher percentage increase in SOC content (29.63% on average, 95% CI: 25.87% to 33.51%).

3.4. The Relative Importance of Moderating Variables

From Figure 5 and Figure 6, in the groups of climate zones, soil tillage method, soil total N content, soil total P content, soil available P content and soil available K content there existed significant differences. These moderating variables were selected to calculate the relative importance. The relative importance of moderating variables influencing SOC content changes following biochar application is shown in Figure 7. Soil available P content, soil available N content and soil available K content were found as the three most important variables influencing the responses in SOC content changes to biochar application. Furthermore, the climate zone is a significant variable that cannot be disregarded.

4. Discussion

4.1. Overall Effects of Biochar Application on SOC Content

The results of this study showed that SOC content responded positively to biochar application. The percentage increase in SOC content following biochar application was 26.02% on average (95% CI: 24.21% to 27.85%). This was because the unstable SOC content was rapidly mineralized by microorganisms when biochar was applied to the soil [39]. Biochar C contains only 3–4% labile organic C [40]. Most C was retained in the soil because of its stable structure and the inclusion of soil aggregates. At the same time, we noticed that there were very few data showing that the SOC content following biochar application was lower than that of the control group. A review of relevant data showed that these data were obtained from deep soil and paddy. In general, biochar is an effective strategy for enhancing SOC content. However, the response of SOC to biochar application varies depending on soil nutrient contents, climate zones and cropping systems.

4.2. Effects of Soil Nutrient Contents on SOC Content Responses to Biochar Application

The effects of soil organic matter on SOC are two-sided: on the one hand, soils with higher organic matter content can retain more SOC. Soil organic matter can promote the formation of soil aggregates and can enhance the stability of SOC. A higher soil organic matter content enhances soil water retention [41]. This reduces the loss of organic C from rainfall and irrigation. On the other hand, soils rich in organic matter provide a more abundant microbial habitat and available C [42]. According to Lagomarsino et al. [43], this environment enhances soil microbial activity, resulting in increased decomposition of SOC. More soil organic matter provides favorable conditions for crop growth and root development. It has been shown that plant roots destabilize SOC and promote SOC decomposition [44,45]. As shown in Figure 5a, the protective effect of soil organic matter on SOC was more obvious than the depleting effect. Meanwhile, it should not be ignored that the fluctuation of SOC content caused by biochar application in soils with high soil organic matter content was smaller.
N limitation is prevalent in natural terrestrial ecosystems [46]. In response to this dilemma, plants secured N acquisition through various pathways. Legumes and non-legumes could help fix N2 from the air by supplying energy from the root system to rhizobia and Frankia around the root margin [47,48]. At the same time, the input of C from the root system to the mycorrhizal fungi on the root surface or within the roots allowed the fungi to extend their mycelium over a wider area of the soil [49], which not only expanded the range of soils in which plants could take up nutrients but also greatly enhanced the ability of plants to obtain N from soil organic matter [50]. In addition, the decomposition of SOC provided available N for plants and microorganisms [51]. As shown in Figure 5b, the supplementation of SOC by plants was stronger than the decomposition of SOC by plants and microorganisms under low N conditions. The results of a meta-analysis suggest that N application enhances soil respiration [52]. It is reasonable to assume that elevated N effectiveness can promote soil respiration. This may be the main reason that the percentage increase in SOC content decreased with increasing soil available N content. No statistical significance is found across the categories of soil available N content, a phenomenon potentially linked to biochar applications augmenting the soil N pool. This perspective aligns with the findings of Lu et al. [53], who reported a 30% increase in soil available N and total N content following biochar application.
P is one of the nutrients necessary for many physiological processes such as energy metabolism and nucleic acid synthesis. The effects of changes in plants and microbes under low P availability on SOC are summarized in Figure 8. When the available P level is insufficient, crops promote root development and carboxylate release [54,55,56]. Carboxylates act as easy-to-decompose C fractions that increase C availability, while disrupting soil aggregate structure and mineral-associated organic matter. The P limitation encourages plants and microorganisms to increase the release of phosphatases to enhance P availability by decomposing soil organic P [20,57,58,59]. Meanwhile, plants can establish associations with fungi. Mycorrhizal fungi can extend their mycelium into the soil around the plant. P is taken up from the soil and is transferred to the plant. In exchange, the plant transfers C to the fungus [60]. In addition, high P levels reduce the transfer of crop photosynthesis products to the ground [61]. Overall, low soil available P content increases the stronger complementary effects of crops and microorganisms on SOC. Low soil available P content significantly reduces soil respiration throughout the farming system [62]. The combination of high input and low consumption of SOC at low available P content resulted in a decrease in the percentage increase in SOC content with an increase in soil available P content (Figure 5d).
Total N and total P contents are the maximum values of N and P in the soil that may be used for crops and microorganisms. However, over 90% of the total soil N content is present as organic matter [63]. Similarly, most P is tightly bound in soil [64]. There was no match between the soil total element content and available element content. This may be the main reason that the responses of SOC content to biochar application between soil total element content and soil available element content were different (Figure 5b–e). In addition, soil total N content was significantly related to SOC content [65,66]. Similarly, soil organic P content was observed to increase significantly with an increase in SOC content [67]. Therefore, the initial SOC content was generally higher with an increase in soil total N content and soil total P content. A higher SOC content facilitated the protection of SOC added by biochar application (Figure 5c,e).
K is a key nutrient in terrestrial ecosystems. It plays a crucial role in controlling osmotic pressure and promoting solute transport [68]. K is involved in enzyme activation to maintain pH stability [69]. When soil available K content is low (<100 mg kg−1), the lack of available K in the soil could hinder the optimal use of N and P in the soil by plants, resulting in reduced plant productivity [70,71]. A meta-analysis showed that K deficiency reduced root biomass by 38% and root length by 23.2% on average [72]. This reduced the damage to soil aggregates because of root development. Fungi have also been observed to participate in the weathering of minerals by secreting organics such as citrate and oxalate [73]. Meanwhile, Yang et al. [74] showed that tobacco roots release large amounts of organic acids when soil available K content is deficient. Numerous studies have demonstrated that appropriate concentrations of available K could improve crop yield and quality [75,76]. However, excessive soil K (>150 mg kg−1) could adversely affect plant performance and growth by inhibiting the uptake of other nutrients such as N, Mg or Fe [77,78]. Consequently, as the soil available K content increased, the percentage increase in SOC content initially exhibited a decline and followed by a subsequent rise (Figure 5f).

4.3. Effects of Climate Zones and Cropping Systems on SOC Content Responses to Biochar Application

Compared with the Dw zone, the Cw and Cf zones had a higher average annual temperature. In addition, Yang et al. [79] found that the seasonal water changes in the Cw and Cf zones were smaller than those in the Dw zone by analyzing the soil moisture data in China from 2002 to 2011. Temperature and moisture were the key factors affecting SOC content: (1) warming increased root biomass and significantly increased soil respiration [80], (2) higher soil moisture significantly increased soil respiration and facilitated the conversion of soil macro-aggregates to micro-aggregates [81], (3) increased moisture variability tended to reduce soil microbial abundance [81] and (4) crops differed in their response to temperature and moisture in different humid zones. Temperature was the main control of crop productivity in humid zones, and moisture was the main control of crop productivity in arid and semi-arid zones [82]. Significantly higher increases in SOC content in the Cw and Cf zones than in Dw were the result of a combination of higher intensity soil respiration and increased plant C inputs to the soil (Figure 6a). In addition, we noticed that the experiments in the Dw zone were mainly distributed in northeast China. The richer SOC stocks in black soil were one of the reasons for the lower fluctuation of SOC content following biochar application. The percentage increase in SOC content in the BS zone fell between Dw and Cf zones. This result could be explained by the lower soil moisture in the BS zone [79].
As shown in Figure 6b, the average percentage increase in SOC was higher in crop rotation than in monoculture. The healthier soil environment resulting from crop rotation led to less susceptibility of plants to pathogens [83]. Healthy growth led to increased crop productivity [84,85]. The amount and weight of plant residues entering the soil after harvest were higher [86]. In addition, crop rotation reduced CO2 emissions [87], thereby reducing soil C loss. In addition, we were concerned with studies showing that the abundance of bacteria and fungi in soils under a 5-year crop rotation was significantly higher than that under a 5-year continuous crop [88], which led to a higher rate of SOC decomposition under crop rotation. The simultaneous increase and depletion were the reasons that there was no significant difference in SOC content between two planting patterns.
Different soil tillage methods had significant effects on SOC content [24]. Plough tillage increased the nutrient assimilation capacity of plants compared with rotary tillage [89]. Higher crop productivity improved the C input from the plant to the soil. Meanwhile, plough tillage had higher microbial abundance due to the retention of relatively intact soil [90]. The results in Figure 5c indicated that the decomposition of SOC by crops and microorganisms was significantly higher than the crop C input to the soil, which was consistent with the results of Gao et al. [91]. In addition, plough tillage promoted soil infiltration as well as CH4 release [92,93]. More C loss was also a crucial reason for the lower percentage increase in SOC content in plough tillage category.

4.4. The Relative Importance of Moderating Variables Influencing SOC Change Due to Biochar Application

Soil nutrition contents are more important than climatic zones and soil tillage methods, which is because soil nutrition content has significant influences on soil enzyme activities [94] and affects the mineralization process of SOC [95]. There were differences in SOC mineralization rates in soils with different nutrient supplies [96]. As the most important moderating variable, the research showed that soil available P content was positively correlated with soil enzyme activities [94]. The increase in N availability decreased microbial biomass [97] and significantly improved the mineralization rate of SOC [98]. The results in Figure 6 show that soil available K content also had an important influence on SOC content. This may be because soil exchangeable K content is related to the stability of soil aggregates [99]. This view was likely to be supported by the results that the contents of exchangeable K in >2 mm soil aggregates increased linearly with the increase in SOC content [100]. Climate zones were also the important factors affecting the change in SOC content. This is consistent with the findings by Benbi et al. [101] and Yu et al. [102] that soil moisture and temperature have significant effects on SOC content.

5. Conclusions

Biochar is recognized as a way to increase SOC content. We performed a meta-analysis to clarify differences in the effects of biochar application on SOC under different conditions. The results showed that biochar application increased SOC by an average of 26.02%, indicating that biochar application is a viable way to increase SOC content. Meanwhile, it was also demonstrated that the response of SOC to biochar application was different under different soil nutrient contents, climate zones and cropping systems. The maximum average effect of soil organic matter was achieved in the <10 g kg−1 category, but no significant effect was observed. The effects of soil available N and soil available P on SOC content decreased with an increase in nutrient content. The difference between the two is that there was a significant difference among the categories of soil available P, and there is no observed difference among the categories of soil available N. The soil available K content category of <100 mg kg−1 reached the maximum increase in SOC content, significantly surpassing the increase observed between the 100–150 mg kg−1 category. Both soil total N and soil total P contents reached their maximum values in the moderate content category (0.75–1 g kg−1, 0.4–0.7 g kg−1). SOC content in the Cw and Cf zones had the highest degree of change, and the Dw zone had the least effect on SOC content. Compared with monoculture, crop rotation showed a higher average SOC content percentage increase. Rotary tillage had a more significant advantage over plough tillage in SOC sequestration. In summary, lower soil available P and K contents, moderate soil total N and P contents, the Cw zone and rotary tillage were considered the most beneficial classes of biochar in each subgroup. Soil nutrient contents were the most important indicators of changes in SOC content following biochar application. In future research, more sophisticated gradient experiments should be conducted to determine the critical values for the most favorable soil nutrient content classes obtained in this study. In addition, more long-term experiments should be conducted to explore a long-term effective method of biochar utilization.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/land13101608/s1, Figures S1–S13. Forest plots revealing that changes in SOC content following biochar application relative to the control varied with categories of different experiment conditions (soil pH, soil depth, biochar feedstock, biochar maximum pyrolysis temperature, biochar pH, biochar N content, biochar P content, biochar K content, biochar application amount, biochar application duration, experiment type and crop type). Table S1. Overview of the studies used for this meta-analysis. Table S2. Color usage instructions in China based on the Köppen–Geiger climate classification (Figure 3 of the corresponding manuscript). Text S1. Studies used in the meta-analysis. References [103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131] are cited in the Supplementary Materials. Text S2. Studies used in the meta-analysis.

Author Contributions

L.T.: conceptualization, visualization, formal analysis, investigation, methodology, formal analysis, writing—original draft and writing—review and editing. G.S.: conceptualization, methodology, project administration and writing—review and editing. Y.G.: conceptualization, methodology and writing—review and editing. E.S.: writing—review and editing and supervision. J.L.: formal analysis and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (51879072), the National Nature & Science Foundation of China (52309045) and the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation (GZC20230669).

Data Availability Statement

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

Acknowledgments

The authors extend their gratitude to the editor and anonymous reviewers for substantial comments on an earlier version of this paper.

Conflicts of Interest

No conflicts of interest exist in the submission of this manuscript, and the manuscript is approved by all authors for publication.

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Figure 1. Map showing the distribution of the 101 experimental sites involved in this meta-analysis. The red triangle marks represent the locations of the experimental sites. Note that the numbers represent the number of studies represented by each mark.
Figure 1. Map showing the distribution of the 101 experimental sites involved in this meta-analysis. The red triangle marks represent the locations of the experimental sites. Note that the numbers represent the number of studies represented by each mark.
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Figure 2. A flowchart summarizing the retrieval process and the division of moderating variables in the manuscript and the Supplementary Information.
Figure 2. A flowchart summarizing the retrieval process and the division of moderating variables in the manuscript and the Supplementary Information.
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Figure 3. Map showing the China climate zone based on the Köppen–Geiger climate classification. The use of color is described in Table S2 of the Supplementary Information.
Figure 3. Map showing the China climate zone based on the Köppen–Geiger climate classification. The use of color is described in Table S2 of the Supplementary Information.
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Figure 4. Normal distribution of paired comparisons according to changes in SOC content under biochar application relative to the control (no biochar application).
Figure 4. Normal distribution of paired comparisons according to changes in SOC content under biochar application relative to the control (no biochar application).
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Figure 5. Forest plots revealing that changes in soil organic carbon content following biochar application relative to the control varied with categories of (a) soil organic matter content, (b) soil available N content, (c) soil total N content, (d) soil available P content, (e) soil total P content and (f) soil available K content. Points represent the mean effect, and bars represent 95% confidence intervals. Numbers in parentheses in the right column show the number of paired comparisons (left) and the total number of replicates (right) for each analysis.
Figure 5. Forest plots revealing that changes in soil organic carbon content following biochar application relative to the control varied with categories of (a) soil organic matter content, (b) soil available N content, (c) soil total N content, (d) soil available P content, (e) soil total P content and (f) soil available K content. Points represent the mean effect, and bars represent 95% confidence intervals. Numbers in parentheses in the right column show the number of paired comparisons (left) and the total number of replicates (right) for each analysis.
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Figure 6. Forest plots revealing that changes in soil organic carbon content following biochar application relative to the control varied with categories of (a) climate zone, (b) planting pattern and (c) soil tillage method. Points stand for the mean effect, and bars represent 95% confidence intervals. Numbers in parentheses in the right column show the number of paired comparisons (left) and the total number of replicates (right) for each analysis.
Figure 6. Forest plots revealing that changes in soil organic carbon content following biochar application relative to the control varied with categories of (a) climate zone, (b) planting pattern and (c) soil tillage method. Points stand for the mean effect, and bars represent 95% confidence intervals. Numbers in parentheses in the right column show the number of paired comparisons (left) and the total number of replicates (right) for each analysis.
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Figure 7. The relative importance of the moderating variables in regulating the response of soil organic carbon changes to biochar application. Variable 1, climate zone; Variable 2, soil tillage method; Variable 3, soil total N content; Variable 4, soil total P content; Variable 5, soil available P content; Variable 6, soil available K content.
Figure 7. The relative importance of the moderating variables in regulating the response of soil organic carbon changes to biochar application. Variable 1, climate zone; Variable 2, soil tillage method; Variable 3, soil total N content; Variable 4, soil total P content; Variable 5, soil available P content; Variable 6, soil available K content.
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Figure 8. The effects of changes in plants and microbes under low P availability on soil organic carbon. + means that the change leads to an increase in soil organic carbon. − means that the change leads to a decrease in soil organic carbon.
Figure 8. The effects of changes in plants and microbes under low P availability on soil organic carbon. + means that the change leads to an increase in soil organic carbon. − means that the change leads to a decrease in soil organic carbon.
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Tian, L.; Shao, G.; Gao, Y.; Song, E.; Lu, J. Effects of Biochar on Soil Organic Carbon in Relation to Soil Nutrient Contents, Climate Zones and Cropping Systems: A Chinese Meta-Analysis. Land 2024, 13, 1608. https://doi.org/10.3390/land13101608

AMA Style

Tian L, Shao G, Gao Y, Song E, Lu J. Effects of Biochar on Soil Organic Carbon in Relation to Soil Nutrient Contents, Climate Zones and Cropping Systems: A Chinese Meta-Analysis. Land. 2024; 13(10):1608. https://doi.org/10.3390/land13101608

Chicago/Turabian Style

Tian, Longjia, Guangcheng Shao, Yang Gao, Enze Song, and Jia Lu. 2024. "Effects of Biochar on Soil Organic Carbon in Relation to Soil Nutrient Contents, Climate Zones and Cropping Systems: A Chinese Meta-Analysis" Land 13, no. 10: 1608. https://doi.org/10.3390/land13101608

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