Journal of Soils and Sediments

, Volume 18, Issue 4, pp 1569–1578 | Cite as

Labile organic carbon fractions and carbon pool management index in a 3-year field study with biochar amendment

  • Xu Yang
  • Di Wang
  • Yu Lan
  • Jun Meng
  • Linlin Jiang
  • Qiang Sun
  • Dianyun Cao
  • Yuanyuan Sun
  • Wenfu Chen
Soils, Sec 3 • Remediation and Management of Contaminated or Degraded Lands • Research Article



The aims of this research were to (i) systematically investigate the soil organic carbon (SOC) and labile SOC fraction dynamics over a period of 3 years under biochar amendment, (ii) reveal the relations of labile SOC fractions to SOC, and (iii) evaluate the sensitivity of SOC to biochar added at different rates by determining C pool management index (CPMI).

Materials and methods

The SOC, labile SOC fractions, and the CPMI in the 0–20-cm layer were analyzed via a 3-year field experiment of maize. Four biochar treatments were studied, with application rates of 0, 15.75, 31.5, and 47.25 t ha−1 (CK, BC1, BC2, and BC3, respectively). Biochar was applied manually before sowing only in the first year of this experiment; an equal mineral NPK fertilizer was applied to each treatment annually.

Results and discussion

The average data of this 3-year field study demonstrated that biochar incorporation significantly increased SOC, particulate organic carbon (POC), easily oxidizable carbon (EOC), light fraction organic carbon (LFOC), and microbial biomass carbon (MBC) by 31.75–83.62, 92.72–323.30, 29.90–51.55, 194.30–437.37, and 31.13–93.12%, respectively, compared to the control; their concentrations increased with increasing biochar addition rates, except for MBC. In addition, EOC, POC, and LFOC were significantly positively related with SOC. Compared to the control, the DOC contents were reduced after biochar addition, but the specific reasons for this finding need to be further studied.


Biochar incorporation could not only significantly improve the soil quality via increasing the soil organic C fractions, but also increase C sequestration rates in the long term by increasing the non-labile C pool (NLC). The CPMI could be used as a representative index in evaluating the impacts of biochar on SOC content and soil quality.


Biochar C pool management index C sequestration Labile organic carbon fractions 

1 Introduction

The organic carbon (C) in soil is three times of the atmosphere (Lal 2004). Soil organic carbon (SOC) is a core component which determines the soil quality and productivity owing to its contribution to physical, chemical, and biological properties of soil (Loveland et al. 2003; Liu et al. 2014; Kundu et al. 2007). However, the quantity of SOC is only a balanced result of input and decomposition rates, which cannot reflect any changes of SOC quality. In addition, small or short-term changes in SOC are not easy to monitor because the soil contains tremendous C background with variability (Blair et al. 1995; Yang et al. 2005). Labile organic carbon refers to the fractions with a high activity and is therefore sensitive to plant and microbial activities, which is highly susceptible to be oxidized and decomposed (Chen et al. 2010). A growing literature body suggests that labile organic carbon is a useful indicator which can indicate the impacts of soil tillage practices more sensitively than SOC, and it has become a representative index to estimate soil quality and productivity (Cambardella and Elliott 1992; VonLutzow et al. 2000; Davidson and Janssens 2006; Purakayastha et al. 2008; Lin et al. 2012; Sun et al. 2014; Yang et al., 2017a, b). Labile SOC fractions can mainly be characterized as particulate organic C (POC), dissolved organic C (DOC), easily oxidizable organic C (EOC), light fraction organic C (LFOC), and microbial biomass C (MBC) (Blair et al. 1995; Plaza-Bonilla et al. 2014). These fractions, which display different turnover rates and stabilities, are easily influenced by agricultural soil tillage practices, and they can be used to detect the changes in SOC initially and sensitively (Chan et al. 2002; Morrissey et al. 2014). To assess the changes of SOC activity levels, according to changes of SOC and EOC, Blair et al. (1995) advanced the carbon pool management index (CPMI) which is also a significant parameter to evaluate SOC variation rates in response to soil management practices. The CPMI depends on the SOC content and C lability, and it can reflect the function of soil management practices in promoting soil quality.

In the last few years, biochar which used as a soil amendment has received wide attention from the scientific community (Ding et al. 2010; Lin et al. 2012). Biochar is a solid residue of biomass pyrolysis at high temperatures under anoxic conditions, and it is rich in carbon, pores, oxygen functional groups, and aromatic structures (Lehmann and Joseph, 2009; Sun et al. 2016). Biochar plays a significant role in improving soil quality by storing organic C, thereby improving sustainability of agro-ecosystem (Xu et al. 2013; Lehmann 2007). Its aromatic structures are highly resistant to microbial decomposition and reduce greenhouse gas emissions from soils, hence mitigating global warming (Zimmerman et al. 2011; Verhoeven et al. 2017). Many researchers have found that biochar application could increase SOC sequestration rates; however, few papers about how biochar impacts SOC and labile SOC fractions in long-term field trial were published. To evaluate changes in SOC quality after biochar application, determining the labile SOC fractions is a necessary step. The effects of biochar on individual C fractions vary with soil type, climate, crop production, fertilization, and the characteristics of the biochar itself, resulting in inconsistencies with SOC dynamics (Jones et al. 2012; Yang et al. 2017). Northeast China is the main area of maize (Zea mays L.) cultivation in China, and soil quality has declined there because of excessive mineral fertilizer inputs under continuous cropping conditions. Although stover return can increase SOC, it can also promote greenhouse gas (GHG) emissions, thereby offsetting potential C sequestration benefits (Yang et al. 2017b). In a previous study, we have compared the effects of the application of maize stover and its biochar in each year on labile SOC fractions (Yang et al. 2017a). To supplement our previous research, the research purposes were to (i) systematically investigate SOC and labile SOC fraction dynamics (DOC, POC, EOC, MBC, LFOC) over the next 3 years under the conditions of biochar applied one-off in different rates before first sowing, (ii) reveal the relationships between labile SOC fractions and SOC, and (iii) determine the sensitivity of SOC to biochar added at different rates over a period of 3 years by applying CPMI in this field experiment.

2 Materials and methods

2.1 Biochar preparation

The maize stover biochar used for the experiment was purchased from the Jinhefu Agriculture Development Company, Liaoning, China. The biochar production process was described detailedly by Yang et al. (2017b). Basic properties of the maize stover biochar are as follows: a pH of 9.2, total C of 660 g kg−1, total N 12.7 g kg−1, ash content of 15.6%, surface area of 8.9 m2 g−1, average pore size of 16.2 nm, and volatile matter 21.9%.

2.2 Site description and experimental design

This field experiment was carried out from May 2013 to October 2015 at Shenyang Agricultural University (41°49′N, 123°33′E). This site experiences a continental monsoon climate with an average annual precipitation of 705 mm and temperature of 7.9 °C (An et al. 2015). The soil in this area is Hapli-Udic Cambisol as qualified by FAO classification. Particle size analysis of the 0–20 cm interval indicated that the soil was composed of 16.7% sand, 58.4% silt, and 24.9% clay (Wang et al. 2006). The topsoil (0–20 cm) properties before experiment were as follows: a pH of 7.4, bulk density of 1.31 g cm−3, SOC content of 11.0 g kg−1, and total N content of 1.2 g kg−1.

Four biochar treatments were studied, with application rates of 0, 15.75, 31.5, and 47.25 t ha−1 (CK, BC1, BC2, and BC3, respectively). All treatments had the same mineral fertilizer application rates annually of N 120 kg ha−1, P2O5 of 60 kg ha−1, and K2O of 60 kg ha−1 (urea, calcium superphosphate, and potassium sulfate). All the mineral fertilizers were broadcasted as basal fertilizer before sowing. Biochar was distributed manually before rotary tillage only in the first year. Maize was mechanically sown in early May and manually harvested at the end of September. The planting density was 60,000 stalks per hectare. The plots in the experiment were established in a randomized block design in triplicate with an area of 3.6 m × 10 m of each one.

2.3 Sampling and analysis

After maize harvest in October every growing season, topsoil samples were collected in each plot by randomly selecting five soil cores. A portion of a fresh moist sample was used for analyzing MBC, and the remaining sample was air-dried in the shade for 1 week. Before analyzing, soil samples were to pass through a 2-mm mesh. Subsamples sieved through a 0.15-mm mesh were prepared for determining SOC content. The soil DOC content was measured as described by Jones and Willett (2006). Briefly, soil sample was extracted with distilled water for 30 min (soil/water ratio of 1:5); then, they were shaken at 230 rpm and centrifuged at 4000 rpm. The extracted fluid was filtered through a 0.45-μm filter for total organic C concentration analysis of the sample using a multi N/C analyzer (Analytik Jena 3100, Germany). The soil MBC content of each sample was analyzed by the chloroform fumigation method (Wu et al.1990). After fumigating soil samples for 24 h with chloroform vapor, a 0.5 mol L−1 K2SO4 solution was applied to extract organic C of fumigated and unfumigated samples, respectively; the 0.45 was applied as an extraction efficiency factor to calculate MBC. For POC analysis, disperse oven-dried soil with sodium hexametaphosphate ((NaPO3)6) solution of 5 g L−1 (solid/liquid ratio of 1:3), and then shake it horizontally for 18 h. The slurry was then poured over a 0.053-mm mesh. The suspended material was oven-dried at 60 °C for 24 h. The POC was the organic C which remains in the suspended material (Cambardella and Elliott 1992). Blair et al. (1995) advanced the method of determining the EOC. Shortly, a soil sample containing about 15 mg of C was added into 50-mL centrifuge tubes and was reacted with 25-mL 333 mM KMnO4 for 1 h on a shaker, and then centrifuged at 4000 rpm for 5 min. After being diluted with ultrapure water, supernatant absorbance was read at 565 nm spectrophotometrically. Based on the changes in the concentration of KMnO4, the oxidized C could be estimated under the assumption that required 1 mM of KMnO4 was required to oxidize 9 mg of C. The LFOC was measured based on density fractionation described by Gregorich and Janzen (1996), according to differences between the fresh organic materials and stable organic matter in density. Specifically, 10 g of air-dried soil sample was added in a plastic centrifuge tube, and then reacted with 50 mL of NaI solution (1.70 g cm−3). After shaking and centrifuging, the suspension with the floating particles was vacuum filtered. In the process of filtration, hyperpure water was used to rinse the remanent NaI on the floating particles, and then, C contents of the particles were analyzed.

The pH values of soil and biochar were measured at solid-water ratio of 1:2.5 and1:10, respectively. Total organic C and total N of the sample were measured by with an Elementar Vario max Analyzer (Elementer Macro Cube, Germany). The methods of determining biochar properties were detailed in Yang et al. (2017b).

2.4 Calculation and statistical analysis

Blair et al. (1995) advanced the C lability and CPMI could be calculated by KMnO4 oxidation. When the CPMI was calculated, the reference was replaced by the CK in this study. The ratio of SOC contents in other treatments to the CK was carbon pool index (CPI), and it was calculated as follows:
$$ CPI={SOC}_s/{SOC}_r $$
where SOCs is the SOC concentration of other treatment and SOCr is the SOC concentration of CK. Based on the EOC that is oxidized by KMnO4, non-labile C (NLC) could be obtained by subtracting the EOC from SOC, and the C lability (L) was the ratio of EOC to NLC, and calculated as follows:
$$ {\displaystyle \begin{array}{c} NLC= SOC- EOC\\ {}L= EOC/ NLC\end{array}} $$
The lability index (LI) was the C lability ratio of the sample soil to the reference soil C of the following:
$$ \mathrm{LI}={\mathrm{L}}_{\mathrm{s}}/{\mathrm{L}}_{\mathrm{r}} $$
where Ls and Lr are the C lability of the sample soil and reference soil, respectively. Accordingly, the CPMI was calculated as follows:
$$ \mathrm{CPMI}=\mathrm{CPI}\times \mathrm{LI}\times 100 $$

All data collected was subjected to SPSS version 21.0 (SPSS Incorporated, USA) to statistical analysis and given as means ± standard error (SE) based on the triplicated field treatment. We used one-way ANOVA to examine differences of measured parameters (SOC, EOC, MBC, POC, LFOC, DOC, CPMI, and the ratios of each C fraction to SOC) among the treatments, with separation of means tested by the least significant difference method (LSD) at the 95% confidence level. Pearson’s correlation coefficients were computed to investigate the relationships between each C fraction and SOC.

3 Results and discussion

3.1 Biochar effects on SOC

The SOC content showed a consistent pattern after harvest in the three crop seasons and was significantly increased as the biochar application amount increase (Fig. 1a) and higher than CK by 38.77–92.61, 27.08–83.36, and 29.14–74.82% in 2013, 2014, and 2015, respectively. The SOC content in the different treatments followed the order BC3 > BC2 > BC1 > CK, and the differences were all significant in each year. Biochar had a direct effect on the increase of SOC, and over time, this significant difference still existed, which suggests that biochar was relatively stable. Previous studies have confirmed that adding biochar could significantly improve SOC levels (Tammeorg et al. 2014; Yang et al. 2017). The main reason for higher SOC levels in biochar treatments is the high C content of biochar; in addition, biochar contains lots of aromatic organic compounds which are more difficult to be biodegraded by microorganisms than other carbon-rich matters (Downie et al. 2009; Sohi et al. 2010). Besides, the SOC contents of BC1, BC2, and BC3 showed a tendency to decrease over time. This suggests that biochar also contains some labile C, which is either readily decomposed by microorganisms or lost by leaching. Unfortunately, each C loss path could not be analyzed quantitatively in this study.
Fig. 1

Effects of biochar on a soil organic carbon (SOC), b dissolved organic carbon (DOC), c easily oxidizable organic carbon (EOC), d light fraction organic carbon (LFOC), e microbial biomass carbon (MBC), and f particulate organic carbon (POC). Different lowercase letters in a single column indicate differences (p < 0.05) among the treatments in each year, and different capital letters in a single column indicate differences of the same treatment in different years. Bars represent standard errors (n = 3)

3.2 Biochar effects on DOC

Although DOC represents only a small part of the soil C pool, it appears to be involved in a large number of soil processes (Chantigny2003) and is a potential indicator of C availability to soil microorganisms (Li et al. 2010; Li et al. 2017). The DOC concentrations were also significantly affected by biochar (Fig. 1b), although the contents differed with crop years. A similar trend of DOC changes was observed among different biochar rates from 2013 to 2015. The DOC concentrations of BC1, BC2, and BC3 treatments were significantly lower than that of CK by 5.59–10.48, 13.36–26.67, and 17.29–26.55% over the experimental period of 3 years. On average, DOC/SOC ratios of BC1, BC2, and BC3 were significantly lower than those of CK over the 3-year period (Table 1). The DOC was not significantly correlated with SOC (Fig. 2a). Moreover, the DOC changes of each treatment showed a downward trend over time. Leaching loss, crop uptake, and microbial decomposition could be the main causes for this phenomenon. Zhang et al. (2017) showed that applying biochar increased the content of DOC significantly in the Loess Plateau; however, Zhu et al. (2017) and Demisie et al. (2014) found that DOC was decreased in biochar treatments. These inconsistent conclusions are mainly due to the different soil types, feedstock of biochar, and cultivation measures. The lower DOC contents from under the condition of biochar application could be explained by the fact that (i) biochar may adsorb DOC on the surface or encapsulate it in the pores (Pietikäinen et al. 2000) and (ii) biochar contained a certain amount of Ca2+ (Cao et al. 2010), which could have a complexation behavior with DOC (Römkens et al. 1996). Moreover, in this experiment, biochar increased the MBC contents (Fig. 1), suggesting that microorganisms might have consumed the DOC rapidly and the effects of biochar on soil DOC were probably to be short-term.
Table 1

The proportions of labile SOC fractions accounting for SOC. The average of 3-year data was applied to calculations








0.71 ± 0.00a

17.77 ± 0.60a

25.70 ± 0.75d

1.10 ± 0.01b

18.88 ± 0.06d


0.47 ± 0.00b

17.47 ± 0.32a

57.43 ± 1.43c

1.38 ± 0.02a

27.54 ± 0.19c


0.38 ± 0.01c

16.67 ± 0.09a

70.54 ± 1.43b

1.37 ± 0.01a

32.10 ± 0.36b


0.29 ± 0.00d

14.67 ± 0.14b

75.21 ± 0.57a

0.85 ± 0.00c

43.45 ± 0.15a

SOC soil organic C, POC soil particulate organic C, DOC dissolved organic C, LFOC light fraction organic C, EOC easily oxidizable organic C, MBC microbial biomass C

Different letters indicated significant differences (p < 0.05)

Fig. 2

Relationships between soil labile organic C fractions and SOC. SOC, soil organic C; POC, soil particulate organic C; DOC, dissolved organic carbon; LFOC, light fraction organic carbon; EOC, easily oxidizable organic carbon; MBC, microbial biomass C. ** indicate significance at p < 0.01

3.3 Biochar effects on EOC

The different biochar inputs affected EOC contents in the experimental period (Fig. 1c), and EOC contents showed a consistent pattern after harvest in each crop season. Compared with CK in the 3-year period, the BC1, BC2, and BC3 treatments increased the EOC by 21.40–47.34, 24.89–56.80, and 36.24–64.50%, respectively. In 2013, the difference between CK and BC1 was not significant; however, the EOC contents of BC1 were significantly higher than those of CK in the following 2 years. In addition, the difference between BC1 and BC2 was not significant in each season, and only in 2014, the difference between BC3 and BC2 was remarkable. The EOC/SOC of biochar addition treatments was decreased, and the difference between BC3 and CK was significant (Table 1). In addition, the EOC was significantly positively (r 2 = 0.65) correlated with SOC (Fig. 2b). The EOC is a type of C fraction easily affected by the environment and susceptible to soil microbial decomposition, which also can affect soil nutrients, soil physicochemical properties, plant growth, and global climate change (Yang et al. 2017). According to Abiven et al. (2015), biochar could not only increase root biomass, but also could meliorate root structure, which increased the root exudates and microbial activities, thereby increasing EOC contents. Besides, the maize stover biochar we used in the present study was pyrolyzed at 350–550 °C, resulting in incomplete oxidization; thus, the EOC of the biochar contributed to the increase of soil EOC.

3.4 Biochar effects on LFOC

The changes of LFOC contents in each treatment are shown in Fig. 1d. The LFOC contents increased with increasing amounts of biochar. The LFOC contents of treatments BC1, BC2, and BC3 were significantly higher than those of CK, namely by 187.90–202.86, 288.61–350.35, and 354.64–506.03% in the 3-year period. The average LFOC contents of three crop seasons in CK, BC1, BC2, and BC3 were 2.81, 8.27, 11.55, and 15.10 g kg−1, respectively. The LFOC/SOC ratio in the different treatments had an identical trend as the LFOC contents and followed the order BC3 > BC2 > BC1 > CK, and the differences were significant (Table 1). Moreover, the LFOC was significantly positively (r 2 = 0.94) correlated with SOC (Fig. 2c). The traditional conception of the LFOC was that it consisted of decomposing animal and plant residues with fast turnover rates and a lower specific density, and thus could be plant nutrient source (Post et al. 2000). The LFOC content is determined by organic residue input and decomposition rates (Malhi et al. 2011). The increased LFOC values for biochar-treated soils also support the findings of Graham et al. (2002), who concluded that a high organic matter input could increase soil LFOC. In the present study, the LFOC of the biochar-applied treatment mainly consisted of biochar particles added due to the chemical and biological stability of biochar which was different from the traditional sense of the light fractions. Biochar, as a highly stable carbon-rich material, was difficult to unite with soil minerals. However, some researchers reported that biochar could combine with soil clay minerals and become a part of heavy C fraction of soil (Brodowski et al. 2007; Llorente et al. 2010).

3.5 Biochar effects on MBC

As shown in Fig. 1e, the MBC contents of BC1 and BC2 were significantly increased by 52.49 and 59.84% in 2013, 68.87 and 95.35% in 2014, and 86.01 and 118.23% in 2015, respectively, compared with CK. The difference between CK and BC3 was not significant in 2013 and 2014; however, the MBC content of BC3 was significantly higher than that of CK by 35.98% in 2015. With the exception of BC3, the MBC content of each treatment in 2015 was significantly higher than that in 2013. Our experiment showed that the highest MBC contents appeared in BC2 in each year. Microbial growth could be accelerated by applying biochar; nevertheless, MBC contents did not increase with biochar application rates. The MBC/SOC ratio of BC1 and BC2 was significantly higher than that of CK; however, the ratio of BC3 was lower than that of CK significantly (Table 1), and MBC was not significantly correlated with SOC (Fig. 2d). There are inconsistencies in the literature findings about the impacts of biochar on soil MBC, and both conclusions of promoting and inhibiting were made (Kolb et al. 2008; Dempster et al. 2012). Biochar type and input amount were deemed as the primary parameters affecting soil microorganisms (Steinbeiss et al. 2009). For this experiment, the soil MBC growth after adding biochar might mainly due to the large specific surface and porous structure of biochar, which could provide a good habitat for microorganisms by maintaining water and air (Hale et al. 2015). Moreover, biochar supplies the carbon source for soil microbial growth (Fowles 2007), and the aromatic constituents of biochar may contribute to the development of a new microbial community (Knicker et al.2013).

3.6 Biochar effects on POC

Figure 1f shows the changes of POC in the 3 years after biochar addition. The POC in the different treatments followed the order: BC3 > BC2 > BC1 > CK, and the differences were significant in each season. Compared with CK in the 3-year period, the treatments BC1, BC2, and BC3 increased the POC contents by 73.58–125.40, 116.59–211.64, and 252.53–425.40%, respectively. The proportions of the POC accounting for SOC were increased with increasing biochar rates (Table 1), and all differences were significant. Moreover, the POC had a significant and positive (r 2 = 0.96) correlation with SOC (Fig. 2e). The POC fraction is mainly composed of plant-derived residues and microbial and micro faunal debris and acts as an energy source for microorganisms and a reservoir of relatively labile SOC and plant nutrients (Christensen 2001; Purakayastha et al. 2008). Biochar can increase the return of organic materials, thus contributing to a POC concentration in the surface soil. In addition, biochar may stimulate root exudates due to its porous structure, and its nutrients can encourage root development, which will benefit biochar agglomeration with soil to increase soil POC (Shang et al. 2015). Some researchers showed that biochar was effective at improving soil aggregate formation and stability (Burrell et al. 2016); increased soil aggregation helps to protect POC from rapid decomposition, which also could explain the increased POC levels in our study.

3.7 Biochar effects on CPMI

The CPMI is useful in revealing the general patterns of the response of SOC to changes in agricultural land use and soil management practices; it can also be used to assess soil quality based on information related to soil organic C dynamics (Blair et al. 2006; Xu et al. 2013). Overall, biochar application exerted a clear influence on the NLC contents as well as on the CPMI, as presented in Table 2. The NLC contents and the CPI increased with increasing biochar rates in each year. The NLC contents in BC1, BC2, and BC3 were 1.29–1.63 times, 1.57–1.63 times, and 1.63–2.00 times higher than those in CK in the 3-year period, which suggests that biochar could improve the SOC for long periods of time because it consists of a stable structure with numerous aromatic compounds. Compared with CK, the CPMI values of BC1, BC2, and BC3 were significantly increased by 50.44, 59.78, and 76.49%, respectively. The present study reconfirmed that CPMI was useful in exploring the general patterns of the response of SOC to changes in the soil management practices, and providing a dependable indicator of SOC quality for appraising the function of biochar in soil improvement. The CPMI changes with CPI and LI. Meanwhile, the SOC and EOC contents dominate the CPI and LI. In this study, biochar addition significantly increased the SOC and EOC.
Table 2

Effects of biochar addition on soil carbon pool management index



NLC (g kg−1)







9.24 ± 0.12d

0.20 ± 0.02a

1.00 ± 0.08a

1.00 ± 0.00d

100.00 ± 7.86c


12.73 ± 0.22c

0.18 ± 0.00ab

0.89 ± 0.02ab

1.39 ± 0.00c

124.22 ± 3.42b


14.48 ± 0.03b

0.18 ± 0.01ab

0.92 ± 0.03ab

1.57 ± 0.00b

144.82 ± 4.05a


18.44 ± 0.02a

0.16 ± 0.00b

0.79 ± 0.01b

1.93 ± 0.01a

152.74 ± 1.23a



8.53 ± 0.04d

0.27 ± 0.01a

1.00 ± 0.02a

1.01 ± 0.00d

100.00 ± 2.30b


10.97 ± 0.09c

0.25 ± 0.01a

0.95 ± 0.04a

1.30 ± 0.00c

122.94 ± 5.19a


13.71 ± 0.06b

0.21 ± 0.00b

0.78 ± 0.02b

1.40 ± 0.00b

108.79 ± 2.57b


16.72 ± 0.09a

0.19 ± 0.01b

0.70 ± 0.02b

1.76 ± 0.01a

122.66 ± 4.11a



9.19 ± 0.09c

0.18 ± 0.01b

1.00 ± 0.06b

1.00 ± 0.00d

100.00 ± 6.27c


11.56 ± 0.05b

0.22 ± 0.00a

1.17 ± 0.03a

1.29 ± 0.00c

150.44 ± 3.48b


12.48 ± 0.03b

0.21 ± 0.00a

1.15 ± 0.02a

1.39 ± 0.00b

159.78 ± 2.23b


14.99 ± 0.62a

0.19 ± 0.01b

1.01 ± 0.05b

1.75 ± 0.01a

176.49 ± 8.20a

NLC non-labile C, L lability, LI lability index, CPI carbon pool index, CPMI carbon pool management index

Different lowercase letters in a single column indicate differences (p < 0.05) among the treatments in each year

4 Conclusions

The results of this 3-year field study demonstrate that biochar incorporation significantly increased SOC, EOC, LFOC, MBC, and POC when compared to the control, and their contents were increased with increasing additions of biochar, except for MBC. In addition, EOC, LFOC, and POC had a significant and positive correlation with SOC. Compared to the control, the DOC contents were reduced after biochar addition, and the reasons for this are still unclear. According to our results, biochar could not only significantly improve the soil quality mainly via increasing the soil organic C fractions and CPMI, but could also increase NLC values. Thus, biochar incorporation represents an efficient method to improve soils and increase C sequestration rates simultaneously in the long term.



This study was funded by the Special Fund for Agro-scientific Research in the Public Interest of China (No. 201503136 and No. 201303095), the National Natural Science Foundation of China (No. 41401325), Program for Science and technology plan of Shenyang (17-182-9-00). We would like to thank the anonymous reviewers and the editor for their constructive comments to improve the manuscript.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Xu Yang
    • 1
    • 2
  • Di Wang
    • 1
    • 2
  • Yu Lan
    • 1
    • 2
  • Jun Meng
    • 1
    • 2
  • Linlin Jiang
    • 1
    • 2
  • Qiang Sun
    • 1
    • 2
  • Dianyun Cao
    • 1
    • 2
  • Yuanyuan Sun
    • 1
    • 2
  • Wenfu Chen
    • 1
    • 2
  1. 1.Agronomy CollegeShenyang Agricultural UniversityShenyangChina
  2. 2.Liaoning Biochar Engineering &Technology Research CenterShenyangChina

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