Long-term successive biochar application increases plant lignin and microbial necromass accumulation but decreases their contributions to soil organic carbon in rice–wheat cropping system

Abstract

Biochar application is widely recognized as an effective approach for increasing soil organic carbon (SOC) and mitigating climate change in agroecosystems. However, the effects of biochar application on net accumulations and relative contributions of different SOC sources remain unclear. Here, we explored the effects of biochar application on plant-derived (PDC) and microbial necromass C (MNC) in a 10-year experimental rice–wheat rotation field receiving four different intensities of biochar application (0, 2.25, 11.5, and 22.5 t ha⁻¹ for each crop season), using phospholipid fatty acids (PLFAs), lignin phenols and amino sugars as biomarkers of microbial biomass, PDC and MNC, respectively. Our results showed that biochar application increased SOC content and stock by 32.6%–203% and 26.4%–145%, respectively. Higher biochar application (11.5 and 22.5 t ha⁻¹) increased soil pH, total nitrogen (TN), total phosphorus (TP), SOC/TN, and root biomass. In addition, higher biochar application enhanced bacterial, fungal, and total microbial biomass. Plant lignin phenols and MNC contents significantly increased, whereas their contributions to SOC significantly decreased with the increase in biochar application rates due to the disproportionate increase in PDC and MNC, and SOC. Fungal necromass had a greater contribution to SOC than bacterial necromass. The fungal/bacterial necromass decreased from 2.56 to 2.26 with increasing biochar application rates, because of the higher abundances of bacteria than that of fungi as indicated by PLFAs under higher biochar application rates. Random forest analyses revealed that pH, TP, and SOC/TN were the main factors controlling plant lignin and MNC accumulation. Structural equation modeling revealed that biochar application increased lignin phenols by stimulating root biomass, whereas enhanced MNC accumulation was primarily from increased microbial biomass and lignin phenols. Overall, our findings suggest that biochar application increases the accumulation of the two SOC sources but decreases their contributions to SOC in paddy soils.

INTRODUCTION

Soil organic carbon (SOC) is considered to be the largest carbon pool in terrestrial ecosystems and it is estimated that 1500 Pg of organic C is stored 0–100 cm belowground globally (Balesdent et al., 2018; Scharlemann et al., 2014). The stability of SOC strongly influences carbon dioxide (CO₂) emissions and global climate change (Lal, 2004). In terrestrial agroecosystems, SOC is a critical indicator of soil health and sustaining crop productivity, thus playing a pivotal role in securing global food demand (Chen et al., 2017; Luan et al., 2021). Rice paddy soil accounts for approximately 9% of global cropland soil and provides staple food for approximately 50% of the global population (Liu, Ge, et al., 2021). Because inundation leads to slower decomposition, paddy soils often contain higher stores of SOC (18 Pg SOC belowground 0–100 cm globally) and account for 14% of the total SOC in agricultural ecosystems (Liu, Ge, et al., 2021).

Emerging evidence has shown that SOC preservation greatly depends on organic C retention by both plants and microbes (Whalen et al., 2022). Increasing evidence shows that, similar to plant residues, microbial necromass comprises a proportion of the stable SOC pool, reaching up to 50% of SOC in some soils (Liang, 2020; Liang et al., 2019; Ma et al., 2018; Yang et al., 2022). A meta-analysis showed that microbial residual carbon accounts for 35%–51% of SOC in terrestrial soils (Wang et al., 2021). Soil microorganisms can convert plant residues into microbial biomass for cell proliferation, which subsequently becomes a soil microbial necromass after cell death (Liang et al., 2007, 2017).

Plant lignin phenols and amino sugars are typically used to quantify the retention of plant debris and microbial necromass in soils (Angst et al., 2021; Glaser et al., 2004; Ma et al., 2018; Otto et al., 2005). Lignin phenols can be divided into cinnamyl- (C), syringyl- (S), and vanillyl-type (V) monomers (Otto & Simpson, 2006), and the ratios of acid to aldehyde for V- and S-type phenols have been used to denote the degree of side-chain oxidation of plant lignin phenols (Li et al., 2020). Additionally, different amino sugars can be used to trace the origins of microbes. For example, glucosamine (GlcN) originates mainly from fungal chitin, although some bacteria also contribute GlcN (Joergensen, 2018; Reay et al., 2019). Muramic acid (MurA) is exclusively derived from the peptidoglycan of bacterial cell walls and can, therefore, indicate soil bacterial necromass (Ding et al., 2019; Glaser et al., 2004; Gunina & Kuzyakov, 2015; Joergensen, 2018). Thus, the ratio of GlcN to MurA content can be used to estimate the fungal versus bacterial contributions to necromass (Amelung, 2001; Engelking et al., 2007; He et al., 2006). The origin of some major types of amino sugars, such as galactosamine (GalN), remains unclear, despite its significant contribution to soil amino sugars (17%–42%) (Joergensen, 2018).

China produces more than 7.95 × 10⁸ t of crop straw each year, which is approximately one-third of the total straw production worldwide (Xia et al., 2014). Straw incorporation is widely recommended for enhancing SOC accumulation because of its rich organic C (Xu et al., 2011). The rice–wheat cropping regime is widely implemented in rice paddy fields in southeastern China, where the combined straw yield of rice and wheat is approximately 13 t ha⁻¹ annually (Chen et al., 2017; Yang et al., 2015). However, owing to the large production of crop straw and the relatively short fallow period between rotations (He et al., 2022), the majority of crop straw is discarded as part of agricultural management, reducing the storage of soil C and other nutrient from important plant sources (Huang et al., 2013; Xia et al., 2014). Alternatively, the application of straw-derived biochar, which provides an external C source, is currently used as common practice in many crop systems.

Biochar application has been recognized as a promising method for increasing and stabilizing SOC, leading to the sustainability and improvement of soil productivity and mitigation of greenhouse gas emissions (Biederman & Harpole, 2013; Lehmann et al., 2011; Wu et al., 2016). It has been reported that biochar application can affect SOC from both lignin phenols and microbial necromass (Chen, Ding, et al., 2021; Zhang et al., 2022). Biochar amendment decreases the donation of plant residues to the SOC pool in rice paddy fields (Chen, Ding, et al., 2021; Sun et al., 2021), although it positively affects the microbial necromass content, mainly from fungi, in brown soil in northeast China over the long term (Sun et al., 2022). Biochar application can also change microbial diversity, composition and ecosystem functioning in soils (Chen et al., 2013, 2016; Sheng & Zhu, 2018), and thus may affect microbial necromass formation and structure. However, little is known about the long-term effects of biochar application on the storage of plant- and microbe-derived C, and how it affects SOC dynamics in paddy soils.

In this study, we assessed the effects of biochar application on the accumulation of plant- and microbe-derived C and their contributions to SOC in paddy soil after a 10-year biochar application. We hypothesized that (1) long-term successive biochar application would increase plant lignin and microbial necromass accumulation via enhancing soil nutrients and crop root biomass; and (2) biochar application would decrease the contribution of PDC and MNC to SOC due to direct contribution of biochar to SOC. The main objectives of our study were to (1) determine how soil lignin phenols and MNC accumulate and their contributions to SOC change with long-term biochar application; (2) verify the factors that regulate the accumulation of plant lignin and MNC in response to biochar application in a rice–wheat cropping system.

METHODS AND MATERIALS Study site and experimental design

The long-term field experiment was set up in the Yixing Agri-Environmental Research Base (119°54′ E, 31°16′ N), National Agro-Ecosystem Observation and Research Station of Changshu, Chinese Academy of Sciences. The primary cropping regimes were rice in summer and wheat in winter. The tested soil belongs to the Gleyi-Stagnic Anthrosol (He et al., 2022), with the original soil physiochemical properties determined before the long-term experiment as follows: pH 6.1; SOC 15.4 g kg⁻¹; total nitrogen (TN) 1.79 g kg⁻¹; sand: clay: silt = 8.3:10.2:81.5.

The field experiment began in June 2010, in which four treatments were designed in randomized field plots (5 m × 4 m) with three replicates. The treatments consisted of rice straw biochar (BC) application for each crop season at rates of 0 (BC0), 2.25 (BC2.25), 11.3 (BC11.3), and 22.5 t ha⁻¹ (BC22.5). Biochar was applied twice a year, before the rice seedlings were transplanted and wheat was sowed. Rice straw biochar was passed through a 2-mm sieve and incorporated into soil by plowing (10–15 cm). All plots received urea-based fertilizer (46% N by weight) at rates of 240 kg N ha⁻¹ during the rice season and 200 kg N ha⁻¹ during the wheat season (40% at the sowing stage, 30% top-dressing at the tillering stage, and the remaining 30% at the booting stage). Phosphorus and K fertilizers were applied during the same period as urea fertilization at rates of 60 kg P₂O₅ ha⁻¹ and 60 kg K₂O ha⁻¹, respectively. The crop straw was removed from all plots after crop harvesting. All field management practices followed those adopted by local farmers.

The biochar applied in this study was made from the pyrolysis of rice straw under an oxygen-limited condition for 8 h at 500°C. The biochar was passed through a 2-mm sieve before it was applied into soil. The biochar's physical and chemical properties were as follows: pH 9.17; ash 131 g kg⁻¹; organic C 590 g kg⁻¹; TN 13.3 g kg⁻¹; C/N 44.3; and cation exchange capacity (CEC) 18.9 cmol kg⁻¹.

Soil sampling

Topsoil (0–20 cm) was collected in May 2020 after the wheat harvest. Five soil cores were collected from each plot at random locations and homogenized to form a single sample. The soil sample from each plot was passed a 2-mm sieve and divided into three parts: one subsample was air-dried for determination of soil physiochemical properties, including lignin phenols and amino sugars; one was immediately used for dissolved organic carbon (DOC) analysis; and the third soil subsample was lyophilized and stored at −60°C for determining phospholipid fatty acid (PLFA) content.

Root biomass and soil properties analysis

In each plot, we collected all the roots from a depth of 0–20 cm in a randomly selected subplot (1 m × 1 m) after the crop was harvested. The root samples were rinsed with tap water and dried at 70°C to reach a stable weight. Root biomass was estimated as the sum of the rice and wheat root biomass. The SOC, TN, Total phosphorus (TP) DOC, and soil pH were measured according to Lu (2000). The cutting-ring method was used to measure soil bulk density, and the SOC stock in the 0–20 cm soil layer was calculated according to Yang et al. (2022).

Phospholipid fatty acids (PLFAs) analysis

The PLFAs contents of the microbial biomass were measured using the method depicted by Wu et al. (2009). Lyophilized soil (3 g) was used for PLFA extraction in a chloroform-methanol-citrate mixture at a ratio of 1:2:0.8. The phospholipids were separated in a silica-bonded phase and converted into free methyl esters via mild alkaline methanolysis. The methyl esters content was then determined by a gas chromatography (GC, Agilent Technologies, CA, USA) and identified using a MIDI peak identification system (MIDI Inc., DE, USA). The abundance of each PLFA was calculated using an internal standard (19:0). The representative Gram-positive and Gram-negative bacteria and fungi PLFAs were identified according to previous studies (Fierer et al., 2003; Frostegård & Bååth, 1996; Zelles, 1999).

Measurement of lignin phenols

The soil lignin phenols content was determined according to Otto and Simpson (2006). Two grams of each soil sample (<0.15 mm) were put into 15 mL 2 M of N₂-purged NaOH solution containing 100 mg of Fe(NH₄)₂(SO4)₂·6H₂O and 1 g of CuO in a Teflon vessel. The vessel was then flushed with N₂ and digested for 2 h at 170°C in an oven, and standard ethyl vanillin added after cooling. The resultant product was titrated to pH 2 using HCl (6 M), and the solution was incubated for 1 h in the dark at room temperature. After centrifugation, the products extracted from the supernatant were dissolved in transcinnamic acid (the second internal standard) before drying under N₂. Dried residues were derivatized with pyridine and N, O-bis-(trimethylsilyl) trifluoroacetamide (BSTFA) for 1 h at 70°C. Lignin phenol derivatives were separated and identified using a GC mass spectrometer (Thermo Fisher Scientific, MA, USA).

The total content of plant lignin phenols was estimated as the sum of V-, S-, and C-type monomers. The ratios of syringyl-to-vanillyl phenol (S/V), cinnamyl-to- vanillyl phenol (C/V), and acid-to-aldehyde in vanillyl and syringyl phenols [(Ac/Ad)v and (Ac/Ad)s] were used to suggest the degree of biotransformation and oxidation of plant lignin (Abiven et al., 2011; Li et al., 2020).

Amino sugars analysis

The soil amino sugars content was determined following the method described by Zhang and Amelung (1996). In brief, an air-dried soil sample was hydrolyzed in an HCl solution (6 M) at 105°C for 8 h. After hydrolysis, myo-inositol was added to the solution as an internal standard and the mixture was filtered. The filtered solution was adjusted to pH 6.6–6.8 before centrifugation, and the supernatant was lyophilized. The residues were re-dissolved in 5 mL of methanol before drying under N₂ flux at 45°C. The recovered residues were converted into aldononitrile derivatives by reaction with a derivatization reagent at 75–80°C for 30 min. The derivatization reaction contained 4-(dimethylamino)-pyridine (40 mg mL⁻¹) and hydroxylamine hydrochloride (32 mg mL⁻¹) in a mixture of pyridine and methanol (4/1, v/v). The derivatives of amino sugars were separated and analyzed using gas chromatography (GC; Agilent 6890A, Agilent Technology, CA, USA).

The total amino sugars content was summed as GlcN, GalN, and MurA. The fungal necromass C (FNC) and bacterial necromass C (BNC) contents were estimated according to the method adopted by Engelking et al. (2007) and Liang et al. (2019).[Image Omitted. See PDF][Image Omitted. See PDF]where 179.17 represents the molecular weight of GlcN and 251.23 represents the molecular weight of MurA. Total microbial necromass C (MNC) includes FNC and BNC.

Statistical analysis

One-way analysis of variance (ANOVA) was used to test for significant differences between treatments, followed by Tukey's test using SPSS 22.0 (SPSS Inc., IL, USA). We used random forest analysis to assess the relative importance of different soil parameters on the contents of lignin phenols and MNC, as well as their contributions to SOC using the package of “randomForest” in R (Version 4.2.2). We estimated the significance of each predictor using the package of “rfPermute” in R. The “A3” package in R was used to calculate the models' significance and cross-validated R², followed by 1000 permutations of each response variable. We performed Pearson correlation to establish relationships between soil physicochemical properties, and plant- and microbe-derived C. The structural equation model (SEM) was conducted using AMOS 22.0 (Smallwaters Corporation, IL, USA).

RESULTS Soil physicochemical properties, root, and microbial biomass

Biochar application increased the SOC content by 32.6%–202.8% compared with BC0 (Figure 1). SOC stock was 1.26–2.45 times higher with biochar application than with BC0. The SOC content and stock increased with increasing biochar application rate. Both of soil pH and SOC/TP increased with increasing biochar application rate (Table S1). Higher biochar application (BC11.3 and BC22.5) significantly increased soil TN, DOC, SOC/TP, and root biomass compared to BC0, but no significant differences were found between BC0 and BC2.25 treatments. Soil TP was significantly higher with biochar application than with BC0.

FIGURE 1. Soil organic carbon content (a) and stock (b) under different treatments in the topsoil (0–20 cm). Error bars represent means ± standard errors (n = 3). Different letters indicate significant differences between the four treatments (p [less than] 0.05). BC0–BC22.5: biochar application rates with 0, 2.25, 11.3, and 22.5 t ha−1 season−1, respectively.

The total biomass of microorganisms, fungi, and bacteria was significantly higher under the higher application rates (BC11.3 and BC22.5) than in the soil without biochar application (BC0) or the lowest application rate (BC2.25) (Figure 2). In contrast, the fungal/bacterial PLFA ratio (F/B) was lower in BC11.3 and BC22.5 than that in BC0 and BC2.25.

FIGURE 2. Phospholipid fatty acids (PLFAs) contents under different treatments: (a) total PLFAs, (b) bacterial PLFA, (c) fungal PLFA, and (d) ratio of fungal and bacterial PLFA in the topsoil (0–20 cm). Error bars represent means ± standard errors (n = 3). Different letters indicate significant differences between the four treatments (p [less than] 0.05). BC0–BC22.5: biochar application rates with 0, 2.25, 11.3, and 22.5 t ha−1 season−1, respectively.

Soil lignin phenols

Biochar increased the total lignin phenols contents in all biochar-treated soils compared to BC0 treatment, and a higher application rate led to a significantly higher lignin phenols content (Figure 3a). Compared to BC0, biochar application increased V-type phenols by 38.7%–159%. The BC22.5 treatment resulted in a higher S-type phenol content, but only had a slight impact on the content of C-type phenols compared to BC11.3. No significant differences were found in the content of S-type and C-type phenols between BC0 and BC2.25 treatments. The lignin contents for both S-type and C-type in BC0 and BC2.25 were significantly lower than those in BC11.3 and BC22.5.

FIGURE 3. Lignin phenols contents in soil (a) and the proportion of lignin phenols in soil organic carbon (b) under different treatments in the topsoil (0–20 cm). Error bars represent means ± standard errors (n = 3). Different letters indicate significant differences between the four treatments (p [less than] 0.05). BC0–BC22.5: biochar application rates with 0, 2.25, 11.3, and 22.5 t ha−1 season−1, respectively.

The SOC-normalized contents of lignin phenols ranged from 16.5 to 23.5 mg g⁻¹ SOC (Figure 3b). There was a decreasing trend in these proportions with higher biochar application rates. The highest biochar application rates (BC11.3 and BC22.5) led to a 24.2%–30.0% decrease in the proportion of total lignin phenol content relative to SOC, compared to BC0, but the lowest application rate (BC2.25) did not induce such an effect (Figure 3b). The lowest proportion of V-type phenols in SOC was found in BC11.3, which was 19.9%–34.5% lower than other treatments. Higher application rates also reduced the proportion of V-type (only BC11.3) and S-type (B2.25–B22.5) lignin phenols relative to the total SOC compared to BC0 treatment. In contrast, biochar application (only BC11.3) significantly increased the proportion of C-type lignin phenols relative to the total SOC.

Soil amino sugars and microbial necromass

Long-term biochar application increased the total amino sugar content by 12.7%–36.2% compared to BC0 (Figure 4a), with an increasing application rate resulting in a higher amino sugar content. A similar trend was observed for the GlcN, GlaN, and MurA, which increased by 12.5%–33.3%, 12.3%–40.1%, and 18.3%–48.9%, respectively, after biochar application compared to BC0. However, no notable differences were found in the content of either GlaN or MurA between BC2.25 and BC11.3. Biochar application led to a 15.9%–55.5% reduction in the proportion of amino sugars relative to total SOC, compared to BC0 (Figure 4b). Similarly, biochar application significantly decreased the proportion of GlcN in the total SOC, especially at higher application rates (BC11.3 = BC22.5 > BC2.25 > BC0). Biochar application also reduced the proportions of GalN and MurA relative to SOC, but only under higher application rates (BC11.3 = BC22.5 > BC2.25 = BC0).

FIGURE 4. Amino sugars contents in soil (a) and the proportion of amino sugars in soil organic carbon (b) under different treatments in the topsoil (0–20 cm). Error bars represent means ± standard errors (n = 3). Different letters indicate significant differences between the four treatments (p [less than] 0.05). GlcN: glucosamine; GalN: galactosamine; MurA: muramic acid. BC0–BC22.5: biochar application rates with 0, 2.25, 11.3, and 22.5 t ha−1 season−1, respectively.

Long-term biochar application increased the MNC content by 13.7%–36.4% (Figure 5a). In particular, FNC (Figure 5c) and BNC (Figure 5e) increased by 11.9%–31.5% and 18.3%–48.9%, respectively, following biochar application. Fungi contributed twice as much necromass C as bacteria (FNC/BNC ratio between 2.26–2.56), and different biochar application rates had little impact on the FNC/BNC ratio. The proportions of both MNC and FNC in SOC significantly decreased (by 16.4%–56.9% compared to BC0) with increasing biochar application rates (Figure 5b,d), whereas the proportion of BNC in SOC only significantly declined (by 41.9%–51.4% compared to BC0) at higher biochar application rates (BC11.3 and BC22.5) (Figure 5f).

FIGURE 5. Microbial necromass carbon contents (a, c, e) and their contributions to soil organic carbon (b, d, f) and ratio of fungal to bacterial necromass carbon (g) under different treatments in the topsoil (0–20 cm). Error bars represent means ± standard errors (n = 3). Different letters indicate significant differences between the four treatments (p [less than] 0.05). BC0–BC22.5: biochar application rates with 0, 2.25, 11.3 and 22.5 t ha−1 season−1, respectively.

Controls on plant- and microbial-derived SOC

The random forest model explained 91.07% and 53.67% of the total variance in plant lignin content and its contribution to SOC, respectively, and 81.16% and 81.47% of the total variance in the MNC concentration and its contribution to SOC, respectively (Figure 6). The top-ranked factors that explained the net accumulation of lignin phenols and MNC were C/N, pH, and TP (Figure 6a,c). The relative contribution of lignin phenols to SOC was mainly explained by C/P, F/B, TN, C/N, root biomass, and total PLFA (Figure 6b; p < 0.001). The relative contribution of MNC to the SOC pool was significantly influenced by C/N, root biomass, pH, TN, total PLFA, and bacterial PLFA (Figure 6d; p < 0.001).

FIGURE 6. Relative importance of soil abiotic and biotic properties controlling contents (a, c) and contributions (b, d) of plant lignin (a, b) and microbial necromass carbon (c, d) to soil organic carbon by the percentage increase of the mean squared error (%IncMSE) using Random Forest analysis. SOC: soil organic carbon; TN: total nitrogen; TP: total phosphorus; DOC: dissolved organic carbon; Root biomass: the sum of rice and wheat root biomass; Total PLFA: total phospholipid fatty acids; F/B: fungal/bacterial PLFA.

The SEM explained 95.3% and 94.0% of the variance in plant lignin and MNC contents, respectively (Figure 7). Biochar application indirectly increased SOC from plant residues and microbial necromass by increasing root and microbial biomass, respectively. Root biomass indirectly affected microbial-derived C by increasing plant lignin, whereas soil microbial biomass negatively affected the accumulation of plant lignin phenols (path coefficient = −0.276, p < 0.05).

FIGURE 7. Structural equation model (SEM) of the effects of biochar application on soil fertility, root biomass, microbial biomass, plant lignin phenols, and microbial necromass carbon. Red and blue solid arrows represent positive and negative relationships, respectively. Dotted line arrows represent no significant association. Soil fertility represents the first component from the was indicated by a principle component analysis (PCA) conducted for the variables, such as pH, soil organic carbon, total nitrogen, total phosphorus, and dissolved organic carbon. Microbial biomass represents fungal and bacterial phospholipid fatty acids (PLFAs). *p [less than] 0.05; **p [less than] 0.01; ***p [less than] 0.001.

DISCUSSION

The long-term application of biochar produced from rice straw significantly increased SOC content and SOC stock in the soil (Figure 1), which is supported by the results of previous studies on paddy soils under a similar rice–wheat cropping regime (Wu et al., 2019; Zhang et al., 2020; Zhao et al., 2014). The size of the SOC pool depends on the rates of exogenous organic C input and mineralization of the existing SOC (Wang et al., 2015). It is widely accepted that biochar-derived C can persist in soils for decades to centuries owing to its high stability and recalcitrance to decomposition, thereby leading to a direct input of stable SOC (Chagas et al., 2022; Wang et al., 2015). A four-year outdoor column trial estimated a recovery rate of 83.3%–98.8% for biochar-derived C in soils (Bi et al., 2021), supporting the low degradation rate of biochar in paddy soils. Additionally, biochar has a negative priming effect on SOC and can lower the SOC mineralization rate (Wang et al., 2015; Weng et al., 2017). Similar to SOC, biochar application also improved soil fertility, such as TN, TP, and DOC (Table S1). Many studies have shown that biochar has potential to increased SOC and improve soil fertility (Biederman & Harpole, 2013; Chagas et al., 2022; Ding et al., 2016). While, the SOC/TN ratio increased with increasing biochar application rate, which indicates that long-term successive and higher biochar application (BC22.5) may reduce soil N availability (Kavitha et al., 2018). Biochar application has been shown to enhance aboveground plant and root biomass (Biederman & Harpole, 2013; Kavitha et al., 2018). Similarly, our study demonstrated that biochar amendment increased crop root biomass by 4.1%–27.4% (Table S1), which contributed to the increase in SOC in the paddy soil.

In this study, soil lignin phenols primarily originated from crop roots, because both rice and wheat straw were discarded from the field after the crops were harvested, and the lignin content in the biochar was much lower than that in the fresh crop residue (Chen, Ding, et al., 2021). Therefore, the higher accumulation of plant residue-derived C was mainly due to the higher root biomass under biochar application (Figures 3a and 7; Table S1). Our results also showed that lignin phenol content was positively correlated with root biomass (Figures S2 and S3). Previous studies have shown that plant roots are among the most important factors regulating SOC derived from plant residues (Luo et al., 2022; Yang et al., 2022). Furthermore, higher C/V ratios under the biochar application treatments (except for BC2.25) suggest a lower level of microbial degradation of plant lignin (Luo et al., 2022; Sun et al., 2021). However, the increased ratio of (Ad/Al)v under BC11.3 and BC22.5 treatments (Figure S1), indicated increased side-chain oxidation of lignin phenol by soil microbes (Abiven et al., 2011; Li et al., 2020). Soil microbial biomass and communities can also affect lignin decomposition, which is predominantly fungus-driven (Li et al., 2020; Luo et al., 2022). The results of this study revealed that higher rates of biochar application (BC11.3 and BC22.5) significantly increased fungal biomass, but decreased the F/B ratio compared to BC0. Li et al. (2020) found that the increased growth of bacteria compared to fungi as a result of biochar application did not affect the lignin degradation rate because of the possible cooperation between soil bacteria and fungi in the decomposition of plant lignin.

In this study, the microbial necromass C content increased with biochar application (Figure 5). This can be attributed to several factors. First, biochar provides diverse substrates that promote microbial growth (Lehmann et al., 2011), resulting in an increased accumulation of microbial necromass through entombing effects (Liang et al., 2017). Second, improved soil physical and chemical properties resulting from biochar amendment (Figure 1; Table S1) were conducive to microbial metabolism and growth (Jing et al., 2021; Zhang et al., 2021), leading to higher microbial biomass (as indicated by PLFA; Figure 2). Finally, increased crop root biomass owing to biochar application may supply more C resources and energy derived from root litter to soil microorganisms, thus stimulating microbial biomass and ultimately increasing microbial necromass accumulation (Jing et al., 2022; Liu et al., 2023; Sokol et al., 2019; Zhu et al., 2020). In the present study, MNC content, including both FNC and BNC content, was positively correlated with the total PLFAs and fungal or bacterial biomass (Figure S3), supporting our hypothesis that biochar application increases MNC by stimulating the growth of different microbial taxa (Khan et al., 2016).

Fungal necromass contributed more to the total microbial necromass than bacterial necromass in the tested paddy soil, irrespective of biochar application (Figure 5e), which was similarly observed in a previous study at a global scale (Wang et al., 2021). Fungi generally have a higher C-use efficiency than bacteria, resulting in higher biomass (Gunina & Kuzyakov, 2015; Wang et al., 2021; Zhou et al., 2022). Additionally, fungal necromass in soils is less prone to degradation than bacterial necromass (Liu, Liu, et al., 2021; Shao et al., 2019; Sun et al., 2022). In our study, the FNC: BNC ratio decreased when the biochar application rate reached its maximum in our study. The main reason for this is that higher application rates of biochar stimulates the growth of bacteria more than that of fungi (Chen et al., 2013), leading to a greater accumulation of bacterial necromass than fungal necromass.

The proportions of SOC from plant and microbial residues in the total SOC pools provide important evidence for understanding SOC formation (Chen, Hu, et al., 2021). Higher biochar application (BC11.3 and BC22.5) decreased the contributions of both lignin phenols and MNC to the total SOC pool (Figures 3b and 5b). This can be explained by the direct increase in the contribution of biochar as an SOC source, which is recalcitrant to degradation (Lehmann et al., 2006; Wang et al., 2015). Additionally, biochar can improve the stabilization and accumulation of SOC by increasing the formation of microaggregates (Weng et al., 2017). Therefore, the dilution effect of both lignin phenols and MNC in the SOC pool was mostly attributed to the nonlinear accumulation of lignin phenols and MNC with increasing biochar application rate; however, a linear increase in biochar-derived C was retained in the soils (Zhang et al., 2021; Zhou et al., 2023). Indeed, the biochar-induced increase in SOC was higher than that of lignin phenols and MNC, leading to a decrease in the relative contributions of lignin phenols and MNC to the SOC pool. A global meta-analysis using 481-paired observations from farmland soils found that biochar application had little influence on microbial necromass accumulation, but greatly improved SOC content, thus leading to a decrease in the contribution of MNC to the SOC pool (Zhou et al., 2023).

CONCLUSIONS

The current study provides novel insights into the pattern of SOC sources in paddy soils subjected to long-term straw-derived biochar amendments. The high-level application of straw-derived biochar significantly increased the accumulation of lignin phenols and MNC but reduced their relative contributions to SOC, indicating that other sources of SOC, such as the direct input of biochar-derived C, are likely attributable to SOC accumulation. Biochar application increased root biomass, and thus enhanced lignin phenols content. MNC accumulation increased following long-term biochar application, owing to increased microbial biomass and plant lignin. The FNC/BNC ratio decreased with increasing biochar application rate because of faster growth of bacteria than that of fungi at higher biochar application rates. These findings are valuable for enhancing the mechanistic understanding of plant and microbial roles in SOC sustainability and stabilization in paddy soils after long-term successive biochar addition. Further studies are required to assess the accumulation of biochar-derived C and its donation to the stabilization and accumulation of SOC in rice paddy soils under long-term successive biochar applications.

AUTHOR CONTRIBUTIONS

Zhaoming Chen: Conceptualization; data curation; methodology; writing – original draft; writing – review and editing. Lili He: Investigation; writing – original draft; writing – review and editing. Jinchuan Ma: Data curation; software. Junwei Ma: Formal analysis; investigation; visualization. Jing Ye: Data curation; methodology. Qiaogang Yu: Data curation. Ping Zou: Data curation; methodology. Wanchun Sun: Investigation; methodology. Hui Lin: Visualization; writing – original draft. Feng Wang: Formal analysis; software. Xu Zhao: Data curation; methodology. Qiang Wang: Conceptualization; funding acquisition; project administration; writing – original draft; writing – review and editing.

ACKNOWLEDGMENTS

This work was supported by the Key Research and Development Program of Zhejiang Province of China (2023C02005, 2023C02015, and 2023C02020), the Science and Technology Development Plant Project of Hangzhou (202204T05), the National Key Research and Development Program of China (2023YFD1902904), and the Innovation Leading Plan for Science and Technology of Zhejiang Province of China (2021R52045).

CONFLICT OF INTEREST STATEMENT

The authors declare that they have no competing financial interests or personal relationships that may have influenced the work reported in this paper.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are openly available in figshare at: https://doi.org/10.6084/m9.figshare.25426342.