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Effect of biochar on carbon fractions and enzyme activity of red soil
Catena 121 (2014) 214–221
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Effect of biochar on carbon fractions and enzyme activity of red soil Walelign Demisie a,b, Zhaoyun Liu a, Mingkui Zhang a,⁎ a b
Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental & Resource Sciences, Zhejiang University, Hangzhou, 310058, China Department of Dry Land Crop Science, Jijiga University, Ethiopia
a r t i c l e
i n f o
Article history: Received 4 July 2013 Received in revised form 6 March 2014 Accepted 20 May 2014 Available online xxxx Keywords: Biochar Total organic carbon Labile organic carbon Macroaggregate Carbon management index
a b s t r a c t To evaluate the changes in the pool of organic carbon fractions, aggregate stability and activity of enzymes, degraded red soil was amended with three different rates (0.5, 1.0 and 2%) of oak wood biochar (W0.5, W1.0, W2.0) and bamboo biochar (B0.5, B1.0, B2.0), with control as 0%. After 372 days, the incubated soils were analyzed for total organic C (TOC), potassium permanganate oxidizable C (POXC), light fraction organic C (LFOC), water soluble organic C (WSC), hot-water extractable C (HWC) and microbial biomass C (MBC), macroaggregates (N0.25 mm), dehydrogenase, β-glucosidase and urease. The highest macroaggregates, POXC, LFOC, HWC, MBC and enzyme activities were measured in the lowest rates (W0.5 and B0.5). MBC positively correlated with all labile organic C and macroaggregates, indicating that microbial activities result in mineralization of organic matter (OM) and contribute on bonding agent for macroaggregation. The C/N of the experimental soil negatively correlated with most of labile organic carbons and macroaggregates, which could be the effect of limited N availability on labile organic carbon fraction and aggregation. As compared to the control, lability index (LI) (changes in the lability of soil carbon) increased in W0.5 and B0.5 by 4 and 6%, respectively, whereas the carbon management index (CMI) (changes of the total carbon in the soil and its lability) increased by ranges of 50 to 286% in the treatments, and implies sequestration of organic C in soil. The high CMI is largely caused by high C sequestration and low lability differences between the treatments. Our results suggest that biochar application increases total organic carbon, stimulates microbial activities, in turn increases macroaggregation, and thus soil quality. © 2014 Elsevier B.V. All rights reserved.
1. Introduction To meet ever increasing nutrition demands of the expanding human populations and make sustainable agriculture, restoration of degraded soil and improvement its quality is indisputable. The red soils of China are highly weathered and very susceptible to erosion (Zhang et al., 1996). Red soils occupy approximately 2.04 million km2 in the southern China and are the most important soil resources in tropical and subtropical regions of China (Xu et al., 2003). These soils are typical of similar red soils that occur throughout tropical and sub-tropical South America, Africa and South East Asia; so that if the red soils of China could be successfully utilized then this would have wider implications for agriculture in other countries. Red soils have high productivity potential. However, the long-term inappropriate utilization and management have caused severe degradation (Zhang and Xu, 2005). Depletion of soil organic matter, soil erosion and decline in soil structure are the major degradative processes. To sustain arable cropping systems there must be careful management on
⁎ Corresponding author at: Yuhangtang Rd. 388 Hangzhou 310058, China. Tel.: +86 571 86946076. E-mail address: [email protected] (M. Zhang).
http://dx.doi.org/10.1016/j.catena.2014.05.020 0341-8162/© 2014 Elsevier B.V. All rights reserved.
Chinese red soils. In other words, considerable attention has been focused on the restoration of soil organic matter and soil structure. Zhang and Xu (2005) reported that degraded red soils could be greatly ameliorated through increasing the content of organic carbon (C) and improving soil aggregation. Similarly, Tisdall and Oades (1982) and Cerdà (1998) suggested that soil organic C is closely related to the formation and stability of soil aggregates. The increase in organic C and aggregate stability reduces soil losses (García-Orenes et al., 2012). Soil organic matter contributes to nutrient supply, improvement of soil physical properties, and protection from erosion and thus there would be a positive correlation between its content and soil quality (Janzen et al., 1997). The soil organic carbon is a complex pool which is divided into labile pool with residence time of years to a few decades and recalcitrant pool with mean residence time of hundreds to thousands of years (Cheng et al., 2007). Fractions of soil organic carbon are more important in maintaining soil fertility and are, therefore, more sensitive indicators of the effects of management practices compared with the soil total organic carbon (Freixo et al., 2002; Lützow et al., 2000). Due to their rapid response to environmental changes, the microbial biomass organic C (MBC) and light fraction of organic C (LFOC) are important fractions of soil organic matter, and play essential role in the short-term turnover of nutrients in soils (Alvarez et al., 1998). The
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ease of oxidation of the soil organic C by KMnO4, permanganate oxidizable organic carbon (POXC), is a larger pool than that commonly measured as soil microbial biomass (Blair et al., 1995). Water-soluble carbon (WSC) is another labile fraction that can be used as an indicator of short-term changes in C status of soils (Haynes, 2000). The hot-water extractable carbon (HWC) being a component of the labile soil organic matter and also being closely related to soil microbial biomass and micro aggregation could therefore be used as one of the soil quality indicator (Ghani et al., 2003). Many scientists showed interest in using biochar as soil amendment (Lehmann and Joseph, 2009; Sohi et al., 2010). Biochar is a highly stable compound created when biomass is heated to a temperature between 350 °C and 600 °C in the absence of oxygen. Biochar, as a soil amendment, can increase concentrations of soil organic matter, especially water-extractable organic carbon (Lin et al., 2012) and stimulate soil microbial activity (Lehmann et al., 2011). Microorganisms are largely responsible for decomposition of the organic matter via a variety of enzymes and hence, application of biochar is a method of replenishing degraded soil quality through improvement of the biological status of the soil, which usually implies an increase in enzyme activity (Albiach et al., 2000). We hypothesized that biochar increases organic matter in soils; therefore increases labile organic carbon, enzyme activity, and aggregate formation and, in turn improves soil quality. To identify changes in soil organic carbon quality as influenced by biochar applications, measurements of the more active fractions of soil labile organic carbon are very important. To our knowledge, there is little information on the effect of biochar on organic carbon fractions and enzyme activity on red soil. Therefore, the objectives of this study were to evaluate the effect of biochar application on the amount of total organic C (TOC), labile soil organic C fractions (LFOC, POXC, WSC, HWC and MBC), enzyme activity, aggregate formation and the quality of the soil.
Teller) surface areas was measured via N2 adsorption multilayer theory using a Nova 2200e surface area analyzer (Quantachrome, Boynton Beach, FL) (Chen et al., 2008).
2. Materials and methods
The light soil organic carbon fraction (LFOC) was determined using the density fractionation method as described by Gregorich and Janzen (1996). Briefly, 10 g of air-dried soil (b 2 mm) was placed in a 100 ml centrifuge tube with 50 ml of NaI solution (1.70 g cm−3). After shaking about 10 times by hand, the tube was sonicated using an ultrasonic disintegrator for 15 min at 400 W, and then centrifuged at 1200 g for 10 min. The supernatant with floating particles was decanted into a vacuum filter unit with a glass-fiber filter (Whatman GF/C) and the NI solution was collected for reuse. The process repeated twice without sonication. The light fraction collected on the filter was washed three times with 0.01 mol/l CaCl2 to remove excess NaI, and then washed three times with deionized water. The three subfractions were combined, oven-dried at 60 °C for 48 h, weighed and stored for analysis. Water soluble carbon (WSC) and hot-water extractable carbon (HWC) were measured as described by Ghani et al. (2003). Soil samples (equivalent to 3 g oven dry weight) were weighed into 50 ml polypropylene centrifuge tubes. These were extracted with 30 ml of distilled water for 30 min on an end-over-end shaker at 30 rpm and at 20 °C, centrifuged for 20 min at 3500 rpm and all the supernatant was filtered through 0.45 μm cellulose nitrate membrane filter into separate vials for carbon analysis. This fraction of the soil organic carbon was classified as water soluble C (WSC). A further 30 ml of distilled water was added to the sediments in the same tubes. These tubes were shaken on a vortex shaker for 10 s to suspend the soil in the water. The tubes were capped and left for 16 h in a hot-water bath at 80 °C. At the end of the extraction period, each tube was shaken for 10 s on a vortex shaker to ensure that HWC released from the SOM was fully suspended in the extraction medium. These tubes were then centrifuged for 20 min at 3500 rpm. The supernatants were filtered through 0.45 μm cellulose nitrate membrane filters. The extract was analyzed for carbon with a multi N/C analyzer. Permanganate oxidizable C was measured as described by Blair et al. (1995). Finely ground air-dried soil samples were reacted with 333 mM KMnO4 by shaking at 60 rpm for 1 h. The suspension
2.1. Soil sampling and analysis A laboratory experiment was conducted to study the influence of biochar on total organic carbon, labile soil organic carbon and enzyme activity. The experimental red soil for this study was sampled at Meijiawu, suburban of Hangzhou. The soil is highly weathered (Plinthic Hapli Udic Ferrosols in Chinese Soil Taxonomic Classification System; and Typic plinthustults in USAD Soil Taxonomy), derived from quaternary red clay parent material and characterized by low pH. The present land-use is tea garden. Particle size distribution was determined by a pipette method. Soil pH was determined through a suspension sample with a soil (airdried) to water (w/v) ratio of 1:2.5 and measured with a pH meter (Pansu and Gautheyrou, 2006). Soil organic carbon was determined by dichromate oxidation (Nelson and Sommers, 1982). Total nitrogen (TN) in soil was measured using the Kjeldahl method after H2SO4 digestion in the presence of K2SO4–CuSO4–Se catalyst (Bremner, 1996). 2.2. Biochar analysis The oak wood (Quercus phillyraeoides) and bamboo (Phyllostachy edulis) biochar used for this study, was pyrolyzed at 600 °C for 2 h (was purchased from Linan Yaoshi charcoal production Limited company located in Hangzhou City). The pH was determined in deionized water at the ratio of 1:10 wt/v (Gaskin et al., 2008) by Orion 720 pH meter. The carbon, hydrogen, and nitrogen contents of the biochars were determined using a CHN elemental analyzer (Flash EA 1112, Thermo Finnigan). The oxygen content was estimated by mass difference (100% — C, H, N and ash %). The ash content was determined according to ASTM D-1762-84 (2007) by combusting the biochar at 750 °C for 6 h in open crucibles on a dry weight basis. The BET (Brunauer–Emmet–
2.3. Incubation experiment The soil sample was passed through 5 mm sieve whereas the biochars through 0.25 mm sieve. Based on the mass of the soil (total 2 kg), the biochars were added at a rates of (0.5, 1.0 and 2%) of oak wood biochar (W0.5, W1.0, W2.0) and bamboo biochar (B0.5, B1.0, B2.0), with control as 0%. After mixing the soil and the biochars thoroughly, they were wetted with deionized water to about 30% water holding capacity of the experimental soil. All pots were covered with plastic film and then a small hole was made to allow gaseous exchange. The pots were incubated at a constant temperature of 25 °C. Based on evaporation loss, the soil moisture was kept constant by regular weighing of the pots. For each treatment, triplicate samples were prepared. The samples were arranged in complete randomized design. After 372 days, the incubated soils were used to analyze water-stable aggregate, TOC, TN, LFOC, POXC, WSC, HWC, MBC and dehydrogenase, β-glucosidase and urease. 2.4. Aggregate stability The fraction of aggregates was measured using a wet sieving method (Kemper, 1986). Air-dried soil samples of 50 g were placed at the top of a stack of sieves (2, 1, 0.5 and 0.25 mm). The screen was lowered to the water surface to allow the dry soils to become moist via capillary action, and then soils were sieved for 10 min with a stoke length of 10 cm and a frequency of 35 strokes per minute. Soils that remained in each sieve were transferred to a container, dried (60 °C), and weighed. 2.5. Labile organic carbon fractions
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was then centrifuged at 2000 rpm for 5 min. The supernatant was diluted and measured spectrophotometrically at 565 nm. Microbial biomass C (MBC) was determined by fumigation extraction method (Vance et al., 1987). Microbial biomass C was calculated as follows: Microbial biomass C ¼
EC KEC
where EC = [(organic C extracted from fumigated soils) minus (organic C extracted from non-fumigated soils)] and KEC (extractable part of microbial biomass C) = 0.45 (Wu et al., 1990). Based on experimental and literature data, Joergensen (1995) confirmed that the KEC values of Vance et al. (1987) and Wu et al. (1990) remain valid. The KEC value may vary in different soils but in this experiment only one soil type was used. Hence, we used a constant value (KEC = 0.45).
sample was incubated at 37 °C for 24 h. After incubation, the solution was diluted to 100 ml and filtered. Of the filtrate, 1 ml was taken into 50 ml volumetric flask, and 10 ml distilled water, 4 ml of sodium phenolate and 3 ml of sodium hypochlorite were added. Then, it was mixed and made the volume to 50 ml with distilled water, and absorbance of color was checked at 578 nm.
2.8. Statistical analysis The data collected was subjected to analysis of variance (ANOVA) using SAS statistical analysis software version 9.1. One-factor ANOVA was deployed to compare treatment effects. The least significant difference (LSD at 0.05 level of probability) test was applied to assess the differences among the means. Pearson's coefficient analysis was used for correlation.
2.6. Carbon management index A carbon management index (CMI) was developed based on changes in the total C in the soil and its lability as determined by KMnO4 oxidation (Blair et al., 1995). Calculation of the CMI was done taking treatments as samples of the soil of interest and the control as the reference. Accordingly, based on changes in total organic carbon between the treatments and control, Carbon Pool Index (CPI) was calculated as: CPI ¼
TOCtreatment : TOCcontrol
Based on C fraction oxidized by KMnO4 (POXC), lability of carbon (L) was calculated as: L¼
Carbon in fraction oxidized by KMnO4 : Carbon remaining unoxidized by KMnO4
Based on changes in the proportion of labile C, a lability index (LI) was calculated as: LI ¼
Ltreatment : Lcontrol
Taking the two indices (CPI and LI), the CMI was calculated as: CMI ¼ CPI LI 100: Higher CPI (CPI N 1) or lower (CPI b 1) indicates higher organic C accumulation or loss, respectively. Similarly, higher LI (LI N 1) indicates higher labile organic C content which can be due to more organic matter decomposition. On the contrary, lower (LI b 1) indicates lower labile organic C content which is directly related to less decomposition of organic matter. The CMI expresses the soil quality in terms of increments in the total C content and in the proportion of labile C fraction compared to the control which arbitrarily has a CMI of 100. Hence, higher CMI (CMI N 100) or lower CMI (CMI b 100) indicates increase or decrease in soil quality, respectively. 2.7. Enzyme activity Soil dehydrogenase activity was measured by the reduction of triphenyl tetrazolium chloride (TTC) to triphenyl formazan (TPF) as described by Tabatabai (1994). β-glucosidase activity was measured following the method described by Tabatabai (1982). This method is based on the colorimetric estimation of the p-nitrophenol (PNP) formed by the hydrolysis of the p-nitro-phenyl-β-D-glucopiranoside (PNG) at 37 °C for 1 h. The estimation of urease activity was carried out following the method described by Li (1996). Briefly, 10 g soil sample was taken into 100 ml conical flask, and 10 ml of (100 g l−1) urea solution and 20 ml citric acid buffer (pH 6.7) were added into the flask. The soil
3. Results 3.1. Total organic carbon and total nitrogen The soil used was degraded red soil with low in C (5.50 g kg− 1), whereas the C content of oak wood and bamboo biochar was 758.10 and 759.20 g kg−1, respectively which had only 0.11% differences (Table 1). The content of total N (TN) in oak wood biochar was 6.40 g kg−1 whereas in bamboo biochar was 11.6 g kg−1 (Table 1). Our results showed that total organic carbon (TOC) significantly increased with increasing both biochar rates (Fig. 1). The highest TOC was recorded in W2.0 (23.91 g kg−1) followed by B2.0 (20.48 g kg−1) whereas the lowest was in control (5.39 g kg−1). The concentration of TN slightly increased in B2.0, while no statistical differences were found among the rest of the treatments. Due to lack of significant differences among treatments in TN, the C/N ratio kept similar trend with TOC, the maximum was in W2.0 and the minimum was in control (Fig. 1).
3.2. Labile organic carbon Application of biochar affected labile organic C, where W0.5 and B0.5 generally had the highest content of LFOC (66.27%), HWC (0.38%), POXC (6.94%) and MBC (0.77%), of the total TOC, while W2.0 had the lowest content of these organic carbons. As to WSC, no clear trend was observed, however the highest was measured in the control (Table 2). The proportion of the labile organic C accounting for the total organic C was higher in the control than the rest of the treatments (Table 3). The proportions of the five labile organic fractions accounting for total organic carbon with their decreasing order are shown as follows: Soil LFOC N POXC N MBC N HWC ≈ WSC. Soil LFOC composed the highest and WSC the lowest active carbon proportions among the six main fractions with 17.46%–85.00% and 0.12%–0.58% of soil TOC, respectively. Table 1 Basic property of soil and oak wood and bamboo biochar. Property
Soil
Oak wood biochar
Bamboo biochar
Sand % Silt% Clay% Texture pH Total organic C (g kg−1) Total N (g kg−1) Hydrogen % Oxygen % Base-hydrolytical-N (mg kg−1) Ash% Surface area (m2 g−1)
22 40 38 Clay loam 4.57 5.50 0.94 ND ND 120.0 ND ND
ND ND ND ND 10.25 758.1 6.4 1.12 10.49 7.35 11.94 154.6
ND ND ND ND 10.22 759.2 11.6 2.11 6.45 16.1 14.36 137.7
ND—not detected, Oxygen% = 100% − (C% + N% + H% + Ash%).
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3.6. Enzyme activity The highest dehydrogenase activity was measured in W 0.5 (7.03 μg TPF g−1 soil 24 h−1) followed by B0.5 (6.94 μg TPF g−1 soil 24 h−1) and the lowest was in B2.0 (5.46 μg TPF g−1 soil 24 h−1), however there were no significant differences among the treatments except in B2.0 which is significantly lower than the rest of the treatments (Fig. 2). The maximum β-glucosidase activity was measured in B0.5 (1.93 mg PNP g−1 soil h−1) and B1.0 (1.93 mg PNP g−1 soil h−1) and the minimum in W2.0 (1.51 mg PNP g−1 soil h−1) which is significantly lower than the rest of the treatments (Fig. 3). Urease activity was significantly higher in W 2.0 (1020.00 μg NH 3 –N g − 1 soil 24 h –1 ), B0.5 (1018.33 μg NH3–N g−1 soil 24 h−1) and W0.5 (1017.50 μg NH3–N g−1 soil 24 h−1) than the rest of the treatments (Fig. 4).
Fig. 1. Soil total organic carbon (TOC), total nitrogen (TN) and C/N ratio among treatments. Bars represent the standard deviation of the mean (n = 3). Different letters over the bars indicate significant differences (p b 0.05) among treatments.
4. Discussion
3.3. Water aggregate stability
Our results showed that increasing application of biochar rates increased TOC (Lin et al., 2012) and its labile fractions (Leifeld et al., 2002) which improved the soil quality by increasing the microbial activities, aggregation and sequestration of C in the soil. Soil C/N ratio can indicate microbial transformation process (Wang et al., 2012). Increasing the biochar rates increased the C/N ratio, indicating a slow transformation and recycling of organic matter (Kindler et al., 2011). The lowest C/N ratio was observed in B0.5, W0.5 and B1.0. These treatments particularly the lowest rates (W0.5 and B0.5) had higher dehydrogenase and β-glucosidase activities, suggesting that higher microbial activities had contribution in carbon mineralization. Our experiment showed the highest MBC in the lowest biochar rates (W0.5 and B0.5) which suggests more intensive activity of microorganisms and thus more decomposition of soil organic matter and labile organic carbon. The positive correlation of HWC with MBC (r = 0.63 p b 0.01) supports this context. Similarly, Sparling et al. (1998) also suggested that hot-water extractable pool of C relates well with microbial biomass-C. Labile C and nutrients (N, S and P) are extracted by hot-water extractable C (HWC) (Ghani et al., 2003) which is a rapid indicator for estimates of labile soil organic matter constituents (Henriksen and Breland, 1999). The POXC was significantly higher in W0.5 and B0.5 than the control because relatively of the higher labile carbon inputs associated with these biochar rates which resulted in higher lability index (LI), indicating that permanganate oxidized organic C is a sensitive indicator of changes in soil quality for soil management. Water soluble carbon (WSC) is the main energy source of soil microorganisms (Huang and Song, 2010) which results from soil organic matter decomposition. Our results showed that WSC decreased in all treatments as compared to the control. This is due to the ease availability of WSC for microbial growth in the first few weeks, which may have resulted in decrease after 372 days of incubation. Moreover, the proportion of WSC accounting for total organic carbon is lower than the other
In all treatments, the macroaggregates (N 0.25 mm) accounted for 40.32 to 55.43% of the dry soil weight (Table 4). Compared to the control, B0.5, B1.0 and W0.5 significantly increased the proportion of macroaggregates. It shows that the lowest biochar rates had higher aggregate formation than the highest rates.
3.4. Relationships among organic carbon fractions As shown in Table 5, in connection to microbial activities in aggregate formation as well as contribution to labile organic C, MBC positively correlated with macroaggregates (N0.25 mm) (r = 0.49 p b 0.05), and LFOC (r = 0.48 p b 0.05), POXC (r = 0.68 p b 0.01), HWC (r = 0.63 p b 0.01) and WSC (r = 0.45 p b 0.05). Moreover, the C/N, the important factor in microbial activities, negatively correlated with HWC (r = −0.86 p b 0.001), POXC (r = − 0.87 p b 0.001) and macroaggregates (r = −0.63 p b 0.01).
3.5. Carbon management index To determine the degree of lability of the treatments, we used potassium permanganate (KMnO4) to oxidize a proportion of the carbon in the treatments and measured the fractions which represent carbon of different labilities. Accordingly, lability index (LI) decreased with increasing biochar rates, the highest was in W0.5 and B0.5, whereas the lowest in W2.0 and B2.0 (Table 6). As compared to the control, lability index (LI) increased in W0.5 and B0.5 by 4% and 6%, respectively. The carbon pool index (CPI) and carbon management index (CMI) increased with increasing biochar rates (Table 6). CMI showed the minimum increase in B0.5 (50.34%) and the maximum in W2.0 (286.33%) (Table 6).
4.1. Biochar effect on carbon fractions
Table 2 Light fraction organic carbon (LFOC), permanganate oxidizable carbon (POXC), microbial biomass carbon (MBC), hot-water extractable carbon (HWC) and water soluble carbon (WSC) among treatments. Treatment
LFOC (g kg−1)
POXC (mg kg−1)
MBC (mg kg−1)
HWC (mg kg−1)
WSC (mg kg−1)
Control W0.5 W1.0 W2.0 B0.5 B1.0 B2.0
4.55 5.72 5.31 4.17 5.70 5.68 5.49
575.41 606.00 537.92 514.15 605.51 593.71 538.88
56.36 66.31 55.58 55.11 64.30 54.70 55.58
31.28b 32.82 30.53 22.60 32.75 29.45 27.26
31.23 30.11 28.11 30.21 30.82 27.68 28.42
± ± ± ± ± ± ±
0.10d 0.11a 0.13c 0.23e 0.14ab 0.00ab 0.06bc
± ± ± ± ± ± ±
4.50c 1.00a 0.95d 3.45e 2.95a 1.20b 1.31d
± ± ± ± ± ± ±
1.01b 2.25a 1.21b 0.39b 1.51a 0.64b 0.43b
± ± ± ± ± ± ±
0.58c 0.96a 0.94 cd 1.02f 1.04ab 0.91d 0.52e
All values were expressed as mean ± standard deviation (n = 3). Different letters in the same column indicated significant differences (p b 0.05).
± ± ± ± ± ± ±
0.23a 0.21b 0.47c 0.82ab 0.89ab 0.52c 0.77c
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Table 3 The proportions of labile organic carbon fractions accounting for soil organic carbon. Treatment
LFOC/TOC (%)
POXC/TOC (%)
MBC/TOC (%)
HWC/TOC (%)
WSC/TOC (%)
Control W0.5 W1.0 W2.0 B0.5 B1.0 B2.0
85.00 66.27 35.05 17.46 73.64 51.90 26.79
10.75 6.94 3.55 2.15 8.02 5.43 2.63
1.05 0.77 0.37 0.23 0.85 0.50 0.27
0.58 0.38 0.20 0.09 0.43 0.27 0.13
0.58 0.35 0.19 0.12 0.41 0.25 0.14
± ± ± ± ± ± ±
7.86a 1.83b 0.85d 0.72e 9.18b 5.28c 0.24d
± ± ± ± ± ± ±
1.06a 0.07c 0.01e 0.09f 0.99b 0.56d 0.05ef
± ± ± ± ± ± ±
0.09a 0.04b 0.01d 0.01e 0.10b 0.06c 0.01e
± ± ± ± ± ± ±
0.05a 0.01b 0.01d 0.01e 0.06b 0.03c 0.01e
± ± ± ± ± ± ±
0.06a 0.01c 0.01e 0.01f 0.05b 0.03d 0.01ef
All values were expressed as mean ± standard deviation (n = 3). TOC, total organic C; LFOC, light fraction organic C; POXC, permanganate oxidizable organic C; MBC, microbial biomass C; HWC, hot-water extractable carbon; WSC, water soluble organic C. Different letters in the same column indicated significant differences (p b 0.05).
labile organic C, indicating that it had been consumed by microorganisms earlier. The LFOC positively correlated with MBC (r = 0.48 p b 0.05) and macroaggregate (N0.25 mm) (r = 0.57 p b 0.01), suggests that the high LFOC in W0.5 and B0.5 contributed to increase MBC and macroaggregation which implies the LFOC enhances soil structure. Kay (1998) also reported the importance of LFOC in the formation and stability of soil structure, especially in the stabilization of soil macroaggregates (N0.25 mm). Generally, the labile C (LFOC, WSC, HWC, POXC and MBC) to TOC ratio is higher in control which indicates the rapid decomposition of organic matter in control as compared to biochar treated ones. This shows the accumulation of organic carbon pool with biochar treatments. Of the six labile organic C proportions accounting for TOC, the high MBC/TOC ratio, in control, implies that soil organic matter decomposed rapidly, which would be detrimental to soil quality to some degree as described by Jiang et al. (2006). Soil organic matter content (pool size) is a balance between addition and decomposition rates (turnover rates) and, as such, changes in agricultural practices can result in marked changes in both the pool size and turnover rate of soil organic matter, carbon and therefore, nutrients (Blair et al., 1995). Carbon management index (CMI) can be used to monitor differences in soil C dynamics between treatments (Blair et al., 1995). The CMI can be used to assess soil quality based on information related to soil organic C dynamics. This index expresses the soil quality in terms of increments in the total C content and in the proportion of labile C fraction compared to the control which arbitrarily has a CMI of 100. In our study, generally, increasing biochar rates decreased lability index (LI) (except in W0.5 and B0.5), which indicates the reduction of labile organic C, whereas carbon pool index (CPI) increased which suggests the accumulation of organic C. The increase in CPI resulted in increase in CMI. The TOC reduction under the critical limit affects soil properties and productivity very negatively and, hence balanced organic matter turnover is necessary for sustainable soil management and carbon sequestration (King et al., 2005; Stewart et al., 2008). However, in this study, the maximum contribution of biochar to LI (labile organic C) was 4% (W0.5) and 6% (B0.5) which was very low as compared to the maximum CPI (carbon accumulation) 344% and 280%. This could be due to the increased C/N ratio (less amount of N) which reduced microbial activities in mineralization of organic matter, however contributed in sequestration of carbon in soil. Therefore,
we hypothesize that application of appropriate amount of N could enhance microbial activities and increase labile organic C for improving soil quality. Taking into consideration that high mineralization rates are only good for soil quality in the short term. At high rates labile C is removed fast and then only stable fractions remain, which are, however, important for soil quality in the long term.
4.2. Biochar effect on aggregate stability The soil type used in this study is ferralsols which is highly degraded under intensive cropping from erosion, therefore restoration of the soil by enhancing aggregate formation is unquestionable. Soil aggregation is an important factor in sustainable agriculture because of its impact on soil biological and physical properties. Aggregate formation in soils depends on the binding agents in soil. The impact of organic product addition on aggregate stability was generally larger when the C content of the soil was low (Fortun et al., 1996). The soil used in this experiment was low in carbon content; hence the organic carbon had impact on its aggregation. The higher macroaggregate, the more sensitive indicator to changes of soil management (Kocyigit and Demirci, 2012), was observed in treatments (B0.5 and B1.0). This could be due to the highest microbial abundance that contributed on bonding agent responsible for macroaggregation. The microbial biomass and β-glucosidase activity were higher in B0.5 which indicates that the aggregating mechanisms are related to polysaccharide (Schjønning et al., 2002). Polysaccharides synthesized by microorganisms during decomposition are hydrophilic and tend to adsorb to mineral particles and increase their interparticle cohesion (Chenu, 1989). The positive correlation of MBC with macroaggregate (N 0.25 mm) (r = 0.49 p b 0.05) confirms the reports of Watts et al. (2005) who suggested that biological mechanisms plays important role in aggregate formation. Moreover, the C/N ratio negatively correlated with macroaggregation (r = 0.63 p b 0.01) implies that C/N is the main factor to enhance microbial activities that are responsible for aggregate formation. This context is supported by the previous researches' results which showed that positive correlations between CO2–C concentrations release and aggregate stability in short and long time (Martens and Frankenberger, 1992; Sonnleitner et al., 2003) after organic carbon inputs, indicating that increases in aggregate stability were related to microbial activity.
Table 4 Changes in soil water aggregate stability (%) at different treatments. Treatment
Particle size distribution N2 mm
Control W0.5 W1.0 W2.0 B0.5 B1.0 B2.0
4.37 4.69b 4.74b 4.17 6.12 6.71 4.10
± ± ± ± ± ± ±
0.22c 0.55c 1.94c 0.54c 0.73ab 1.05a 0.40c
1–2 mm
0.5–1 mm
0.25–0.5 mm
N0.25 mm
4.42 7.92 5.77 5.37 4.24 4.93 4.55
11.98 11.42 10.14 10.67 13.10 20.85 12.81
23.56 24.21 22.35 19.65 31.96 21.13 18.86
44.33 48.24 43.01 39.85 55.43 53.62 40.32
± ± ± ± ± ± ±
0.26b 1.40a 1.28b 0.96b 0.37b 1.03b 0.21b
± ± ± ± ± ± ±
3.51b 1.57b 2.70b 4.46b 2.75b 1.96a 3.01b
± ± ± ± ± ± ±
2.76b 2.99b 3.48b 3.13b 1.98a 4.77b 4.50b
All values were expressed as mean ± standard deviation (n = 3). Different letters in the same column indicated significant differences (p b 0.05).
± ± ± ± ± ± ±
4.78bc 1.01b 1.16bc 2.96c 4.85a 2.09a 1.89c
W. Demisie et al. / Catena 121 (2014) 214–221
219
Table 5 Correlations among soil organic carbon fractions and aggregate stability. Pools of carbon
C/N
LFOC
WSC
HWC
POXC
MBC
TOC
N0.25 macro aggregate C/N LFOC WSC HWC POXC MBC
−0.63⁎⁎ 1
0.57⁎⁎ −0.41 1
0.06 −0.32 −0.40 1
0.62⁎⁎ −0.86⁎⁎⁎ 0.62⁎⁎
0.82⁎⁎⁎ −0.87⁎⁎⁎ 0.64⁎⁎
0.49⁎ 0.48⁎ 0.48⁎ 0.45⁎ 0.63⁎⁎ 0.68⁎⁎
−0.63⁎⁎ 0.98⁎⁎⁎
−0.18 1
0.22 0.81⁎⁎⁎ 1
−0.37 −0.35 −0.87⁎⁎⁎ −0.87⁎⁎⁎ −0.51⁎
1
TOC, total organic C; C/N, carbon to nitrogen ration; LFOC, light fraction organic C; WSC, water soluble organic C; HWC, hot-water soluble organic C; POXC, permanganate oxidizable organic C; MBC, microbial biomass C. ⁎ Is significant at P b 0.05. ⁎⁎ Is significant at P b 0.01. ⁎⁎⁎ Is significant at P b 0.001.
Mineralization of soil organic matter (SOM) is an important microbially-mediate process by which carbon, nitrogen, and other nutrients are converted from organic forms into inorganic forms. Soil microbes must produce soil enzymes to catalyze the breakdown of soil organic matter and to make readily-usable dissolved compounds for growth and metabolisms. Martens et al. (1992) reported the rapid response β-glucosidase to management-induced change in soil. βglucosidase is an extracellular enzyme involved in carbon mineralization, while dehydrogenase is an intracellular enzyme and its activity in soil has been considered as a general index for evaluating soil microbial activity (Brookes et al., 2008). Moreover, dehydrogenase activity has been used successfully as a parameter for the evaluation of degree of
recovery of degraded soils (Gil-Sotres et al., 2005). Based on our finding the dehydrogenase activity was higher in W0.5 and B0.5, indicating that biochar at rate of 0.5% could ameliorate the degraded red soil. βglucosidase activity was higher in bamboo biochar treated soils (B0.5 and B1.0). Based on our findings the two biochars showed various βglucosidase activities which could be due to differences in their chemical composition. The activity of urease has been observed to increase due to organic fertilization (Chakrabarti et al., 2000). In this study, urease activity was higher in W2.0, W0.5 and B0.5 which could be due to the higher microbial biomass in the treatments released more urease enzyme than the other treatments.
β-glucosidase (mg PNP g-1 soil h-1)
4.3. Biochar effects on activity of enzymes
Table 6 Changes in soil CMI for different treatments. Treatment
CPI
LI
CMI
Control W0.5 W1.0 W2.0 B0.5 B1.0 B2.0
1.00 1.60 2.81 4.44 1.41 2.04 3.80
1.00 1.04 0.93 0.87 1.06 1.02 0.93
100.00 167.13 260.62 386.33 150.34 209.23 352.54
3 2
ab
ab
a
a
ab
B0.5
B1.0
B2.0
b
2 1 1 0 con
LI, lability index; CPI, carbon pool index; CMI, carbon management index.
ab
W0.5
W1.0
W2.0
Treatment 9 a
a
a ab
7
ab
ab
b 1200
6
a
a
Urease (µg NH3-N g-1soil 24h-1)
Dehydrogenase (µg TPF g-1soil 24h-1)
8
Fig. 3. β-Glucosidase activity at different biochar treatments. Bars represent the standard deviation of the mean (n = 3). Different letters over the bars indicate significant differences (p b 0.05) among treatments.
5 4 3 2 1
1000
a
b
b
B1.0
B2.0
b c
800
600
400
200
0 con
W0.5
W1.0
W2.0
B0.5
B1.0
B2.0
Treatment Fig. 2. Dehydrogenase activity at different biochar treatments. Bars represent the standard deviation of the mean (n = 3). Different letters over the bars indicate significant differences (p b 0.05) among treatments.
0 con
W0.5
W1.0
W2.0
B0.5
Treatment Fig. 4. Urease activity at different biochar treatments. Bars represent the standard deviation of the mean (n = 3). Different letters over the bars indicate significant differences (p b 0.05) among treatments.
220
W. Demisie et al. / Catena 121 (2014) 214–221
Both biochars had nearly similar effect on labile C which resulted in the corresponding treated soils to keep similar trend in microbial activities and macroaggregation. 5. Conclusion The long-term inappropriate utilization and management have caused severe degradation in red soil. Depletion of soil organic matter, soil erosion and decline in soil structure are the major degradative processes. Application of oak and bamboo biochar could ameliorate this soil through increasing the content of organic carbon and improving soil aggregation. Both biochars had less lability but more accumulation of organic C which could contribute in sequestration of C in soil. Oak wood and bamboo biochar can be used at rate of 0.5%, particularly, the bamboo for its better microbial activities and macroaggregate formation than the oak wood. The increase in organic matter, microbial activities and macroaggregation can be viewed as improvement in soil quality. However, application of these biochars at highest rates (more than 0.5%) decrease macroaggregation and which, in turn, can cause erodibility and loss in soil quality. Acknowledgments This research was financially supported by National Key Technology Support Program (No. 2012BAD05B00). We thank Hao Wang and Dong-wei Yang for their unlimited support in this research. We also thank the anonymous reviewers for their valuable comments. References Albiach, H., Canet, R., Pomares, F., Ingelmo, F., 2000. Microbial biomass content and enzymatic activities after the application of organic amendments to a horticultural soil. Bioresour. Technol. 75, 43–48. Alvarez, C.R., Alvarez, R., Grigera, M.S., Lavado, R.S., 1998. Associations between organic matter fractions and the active soil microbial biomass. Soil Biol. Biochem. 6, 767–773. American Society for Testing and Materials (ASTM), 2007. Standard methods for chemical analysis of wood charcoal. ASTM D1762-84. ASTM International, Pennsylvania, USA. Blair, G.J., Lefroy, R.D.B., Lisle, L., 1995. Soil carbon fractions based on their degree of oxidation, and the development of a carbon management index for agricultural system. Aust. J. Agric. Res. 46, 1459–1466. Bremner, J.M., 1996. Total nitrogen. In: Sparks, D.L., et al. (Eds.), Methods of Soil Analysis, Part 3. Chemical Methods. SSSA, ASA, Madison, Wisconsin, USA, pp. 1085–1122. Brookes, P.C., Cayuela, M.L., Contin, M., De Nobili, M., Kemmitt, S.J., Mondini, C., 2008. The mineralization of fresh and humified soil organic matter by the soil microbial biomass. Waste Manag. 28, 716–722. Cerdà, A., 1998. Soil aggregate stability under different Mediterranean vegetation types. Catena 32, 73–86. Chakrabarti, K., Sarkar, B., Chakraborti, A., Banik, P., Bakchi, D.K., 2000. Organic recycling for soil quality conservation in a sub-tropical plateau region. J. Agron. Crop Sci. 184, 137–142. Chen, B., Zhou, D., Zhu, L., 2008. Transitional adsorption and partition of non polar and polar aromatic contaminants by biochar of pine needles with different pyrolytic temperatures. Environ. Sci. Technol. 42, 5137–5143. Cheng, L., Leavitt, S.W., Kimball, B.A., 2007. Dynamics of labile and recalcitrant soil carbon pools in a sorghum free-air CO2 enrichment (FACE) agroecosystem. Soil Biol. Biochem. 39, 2250–2263. Chenu, C., 1989. Influence of a fungal polysaccharide, scleroglucan, on clay microstructures. Soil Biol. Biochem. 21, 299–305. Fortun, A., Tomas, R., Fortun, C., 1996. Effect of bituminous materials on soil aggregation. Arid Soil Res. Rehabil. 10, 161–168. Freixo, A.A., Machado, P.L., Santos, H.P., 2002. Soil organic carbon and fractions of a Rhodic Ferralsol under the influence of tillage and crop rotation systems in Southern Brazil. Soil Tillage Res. 64, 221–230. García-Orenes, F., Roldán, A., Mataix-Solera, J., Cerdà, A., Campoy, M., Arcenegui, V., Caravaca, F., 2012. Soil structural stability and erosion rates influenced by agricultural management practices in a semi-arid Mediterranean agro-ecosystem. Soil Use Manag. 28, 571–579. Gaskin, J.W., Steiner, C., Harris, K., Das, K.C., Bibens, B., 2008. Effect of low temperature pyrolysis conditions on biochar for agricultural use. Trans. ASABE 51, 2061–2069. Ghani, A., Dexter, M., Perrott, K.W., 2003. Hot-water extractable carbon in soils: a sensitive measurement for determining impacts of fertilization, grazing and cultivation. Soil Biol. Biochem. 35, 1231–1243. Gil-Sotres, F., Trasar-Cepeda, C., Leiros, M.C., Seoane, S., 2005. Different approaches to evaluating soil quality using biochemical properties. Soil Biol. Biochem. 37, 877–887.
Gregorich, E.G., Janzen, H.H., 1996. Storage of soil carbon in the light fraction and macroorganic matter. In: Carter, M.R., Stewart, B.A. (Eds.), Advances in Soil Science. Structure and Organic Matter Storage in Agricultural Soils. CRC Lewis, Boca Raton, pp. 167–190. Haynes, R.J., 2000. Labile organic matter as an indicator of organic matter quality in arable and pastoral soils in New Zealand. Soil Biol. Biochem. 32, 211–219. Henriksen, T.M., Breland, T.A., 1999. Decomposition of crop residues in the field; evaluation of a simulation model developed from microcosm studies. Soil Biol. Biochem. 31, 1423–1434. Huang, J.Y., Song, C.C., 2010. Effects of land use on soil water soluble organic C and microbial biomass C concentrations in the Sanjiang Plain in northeast China. Acta Agric. Scand. Sect. B Soil Plant 60, 182–188. Janzen, H.H., Campbell, C.A., Ellert, B.H., Bremer, E., 1997. Soil organic matter dynamics and their relationship to soil quality. In: Gregorich, E.G., Carter, M.R. (Eds.), Soil Quality for Crop Production and Ecosystem Health. Developments in Soil Science, vol. 25. Elsevier, Amsterdam, pp. 277–292. Jiang, P.K., Xu, Q.F., Xu, Z.H., Cao, Z.H., 2006. Seasonal changes in soil labile organic carbon pools within a Phyllostachys praecox stand under high rate fertilization and winter mulch in subtropical China. For. Ecol. Manag. 236, 30–36. Joergensen, R.G., 1995. The fumigation–extraction method to estimate soil microbial biomass: calibration of the KEC value. Soil Biol. Biochem. 28, 25–31. Kay, B.D., 1998. Soil structure and organic carbon, a review. In: Lal, R., et al. (Eds.), Soil Processes and the Carbon Cycle. CRC Press, Boca Raton, FL, pp. 169–197. Kemper, W.D., 1986. Aggregate stability and size distributions. Methods of Soil Analysis. Part I. Physical and mineralogical methods, In: Klute, A. (Ed.), 2nd ed. Agro. Monoger., 9. ASA and SSSA, Madison, WI, pp. 383–411. Kindler, R., Siemens, J., Kaiser, K., et al., 2011. Dissolved carbon leaching from soil is a crucial component of the net ecosystem carbon balance. Glob. Chang. Biol. 17, 1167–1185. King, J.A., Bradley, R.I., Harrison, R., 2005. Current trends of soil organic carbon in English arable soils. Soil Use Manag. 21, 189–195. Kocyigit, R., Demirci, S., 2012. Long-term changes of aggregate-associated and labile soil organic carbon and nitrogen after conversion from forest to grassland and cropland in northern Turkey. Land Degrad. Dev. 23, 475–482. Lehmann, J., Joseph, S., 2009. Biochar for environmental management: an introduction. In: Lehmann, J., Joseph, S. (Eds.), Biochar for Environmental Management: Science and Technology. Earthscan, London, pp. 1–12. Lehmann, J., Rillig, M.C., Thies, J., Masiello, C.A., Hockaday, W.C., Crowley, D., 2011. Biochar effects on soil biota—a review. Soil Biol. Biochem. 43, 1812–1836. Leifeld, J., Siebert, S., Kogel-Knabner, I., 2002. Changes in the chemical composition of soil organic matter after application of compost. Eur. J. Soil Sci. 53, 299–309. Li, F.D., 1996. Analysis of soil enzyme activity. In: Li, F.D., et al. (Eds.), Experimental Techniques in Agricultural Microbiology. Agricultural Press, Beijing, pp. 137–139 (in Chinese). Lin, Y., Munroe, P., Joseph, S., Henderson, R., Ziolkowski, A., 2012. Water extractable organic carbon in untreated and chemical treated biochar. Chemosphere 87, 151–157. Lützow, M., Leifeld, J., Kainz, M., Kogel-Knabner, I., Munch, J.C., 2000. Indications for soil organic matter quality in soils under different management. Geoderma 105, 243–258. Martens, D.A., Frankenberger, W.T., 1992. Modification of infiltration rates in an organicamended irrigated soil. Agron. J. 84, 707–717. Martens, D.A., Johnson, J.B., Frankenberger, W.T., 1992. Production and persistence of soil enzymes with repeated additions of organic residues. Soil Sci. 153, 53–61. Nelson, D.W., Sommers, L.E., 1982. Total carbon, organic carbon and organic matter. In: Page, A.L. (Ed.), Methods of Soil Analysis. Part 2. American Society of Agronomy, Madison, WI, pp. 539–579. Pansu, M., Gautheyrou, J., 2006. Handbook of Soil Analysis—Mineralogical, Organic and Inorganic Methods. Springer-Verlag, Heidelberg, pp. 551–578. Schjønning, P., Elmholt, S., Munkholm, L.J., Debosz, K., 2002. Soil quality aspects of humid sandy loams as influenced by organic and conventional long-term management. Agric. Ecosyst. Environ. 88, 195–214. Sohi, S., Krull, E., Lopez-Capel, E., Bol, R., 2010. A review of biochar and its use and function in soil. Adv. Agron. 105, 47–82. Sonnleitner, R., Lorbeer, E., Schinner, F., 2003. Effect of straw, vegetable oil and whey on physical and microbiological properties of a chernozem. Appl. Soil Ecol. 22, 195–204. Sparling, G.P., Vojvodic-Vukovic, M., Schipper, L.A., 1998. Hot-water soluble C as a simple measure of labile soil organic matter: the relationship with microbial biomass C. Soil Biol. Biochem. 1469-72. Stewart, C.E., Paustian, K., Conant, R.T., Plante, A.F., Six, J., 2008. Soil carbon saturation: evaluation and corroboration by long-term incubations. Soil Biol. Biochem. 21, 189–195. Tabatabai, M.A., 1982. Soil enzymes. In: Page, A.L. (Ed.), Methods of Soil Analysis, Part 2. American Society of Agronomy, pp. 903–948. Tabatabai, M.A., 1994. Soil enzymes. In: Weaver, R.W., et al. (Eds.), Methods of Soil Analysis. Soil Society of America, Madison, pp. 775–883. Tisdall, J.M., Oades, J.M., 1982. Organic matter and water-stable aggregates in soils. Soil Sci. 33, 141–163. Vance, E.D., Brookes, P.C., Jenkinson, D.S., 1987. Microbial biomass measurements in forest soils: the use of the chloroform fumigation incubation method for strongly acid soils. Soil Biol. Biochem. 19, 697–702. Wang, J., Song, C., Wang, X., Song, Y., 2012. Changes in labile soil organic carbon fractions in wet land ecosystems along a latitudinal gradient in North East China. Catena 96, 83–89.
W. Demisie et al. / Catena 121 (2014) 214–221 Watts, C.W., Whalley, W.R., Brookes, P.C., Devonshire, B.J., Whitmore, A.P., 2005. Biological and physical processes that mediate micro aggregation of clays. Soil Sci. 170, 573–583. Wu, J., Joergensen, R.G., Pommerening, B., Chaussod, R., Brookes, P.C., 1990. Measurement of soil microbial biomass C by fumigation–extraction: an automated procedure. Soil Biol. Biochem. 17, 837–842. Xu, R., Zhao, A., Li, Q., Kong, X., Ji, Q., 2003. Acidity regime of the Red Soils in a subtropical region of southern China under field conditions. Geoderma 115, 75–84.
221
Zhang, M.K., Xu, J.M., 2005. Restoration of surface soil fertility of an eroded red soil in southern China. Soil Tillage Res. 80, 13–21. Zhang, B., Zhang, T.L., Zhao, Q.G., 1996. Soil erosion in various farming systems in subtropical China. Pedosphere 6, 225–234.
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Effect of biochar on carbon fractions and enzyme activity of red soil Walelign Demisie a,b, Zhaoyun Liu a, Mingkui Zhang a,⁎ a b
Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental & Resource Sciences, Zhejiang University, Hangzhou, 310058, China Department of Dry Land Crop Science, Jijiga University, Ethiopia
a r t i c l e
i n f o
Article history: Received 4 July 2013 Received in revised form 6 March 2014 Accepted 20 May 2014 Available online xxxx Keywords: Biochar Total organic carbon Labile organic carbon Macroaggregate Carbon management index
a b s t r a c t To evaluate the changes in the pool of organic carbon fractions, aggregate stability and activity of enzymes, degraded red soil was amended with three different rates (0.5, 1.0 and 2%) of oak wood biochar (W0.5, W1.0, W2.0) and bamboo biochar (B0.5, B1.0, B2.0), with control as 0%. After 372 days, the incubated soils were analyzed for total organic C (TOC), potassium permanganate oxidizable C (POXC), light fraction organic C (LFOC), water soluble organic C (WSC), hot-water extractable C (HWC) and microbial biomass C (MBC), macroaggregates (N0.25 mm), dehydrogenase, β-glucosidase and urease. The highest macroaggregates, POXC, LFOC, HWC, MBC and enzyme activities were measured in the lowest rates (W0.5 and B0.5). MBC positively correlated with all labile organic C and macroaggregates, indicating that microbial activities result in mineralization of organic matter (OM) and contribute on bonding agent for macroaggregation. The C/N of the experimental soil negatively correlated with most of labile organic carbons and macroaggregates, which could be the effect of limited N availability on labile organic carbon fraction and aggregation. As compared to the control, lability index (LI) (changes in the lability of soil carbon) increased in W0.5 and B0.5 by 4 and 6%, respectively, whereas the carbon management index (CMI) (changes of the total carbon in the soil and its lability) increased by ranges of 50 to 286% in the treatments, and implies sequestration of organic C in soil. The high CMI is largely caused by high C sequestration and low lability differences between the treatments. Our results suggest that biochar application increases total organic carbon, stimulates microbial activities, in turn increases macroaggregation, and thus soil quality. © 2014 Elsevier B.V. All rights reserved.
1. Introduction To meet ever increasing nutrition demands of the expanding human populations and make sustainable agriculture, restoration of degraded soil and improvement its quality is indisputable. The red soils of China are highly weathered and very susceptible to erosion (Zhang et al., 1996). Red soils occupy approximately 2.04 million km2 in the southern China and are the most important soil resources in tropical and subtropical regions of China (Xu et al., 2003). These soils are typical of similar red soils that occur throughout tropical and sub-tropical South America, Africa and South East Asia; so that if the red soils of China could be successfully utilized then this would have wider implications for agriculture in other countries. Red soils have high productivity potential. However, the long-term inappropriate utilization and management have caused severe degradation (Zhang and Xu, 2005). Depletion of soil organic matter, soil erosion and decline in soil structure are the major degradative processes. To sustain arable cropping systems there must be careful management on
⁎ Corresponding author at: Yuhangtang Rd. 388 Hangzhou 310058, China. Tel.: +86 571 86946076. E-mail address: [email protected] (M. Zhang).
http://dx.doi.org/10.1016/j.catena.2014.05.020 0341-8162/© 2014 Elsevier B.V. All rights reserved.
Chinese red soils. In other words, considerable attention has been focused on the restoration of soil organic matter and soil structure. Zhang and Xu (2005) reported that degraded red soils could be greatly ameliorated through increasing the content of organic carbon (C) and improving soil aggregation. Similarly, Tisdall and Oades (1982) and Cerdà (1998) suggested that soil organic C is closely related to the formation and stability of soil aggregates. The increase in organic C and aggregate stability reduces soil losses (García-Orenes et al., 2012). Soil organic matter contributes to nutrient supply, improvement of soil physical properties, and protection from erosion and thus there would be a positive correlation between its content and soil quality (Janzen et al., 1997). The soil organic carbon is a complex pool which is divided into labile pool with residence time of years to a few decades and recalcitrant pool with mean residence time of hundreds to thousands of years (Cheng et al., 2007). Fractions of soil organic carbon are more important in maintaining soil fertility and are, therefore, more sensitive indicators of the effects of management practices compared with the soil total organic carbon (Freixo et al., 2002; Lützow et al., 2000). Due to their rapid response to environmental changes, the microbial biomass organic C (MBC) and light fraction of organic C (LFOC) are important fractions of soil organic matter, and play essential role in the short-term turnover of nutrients in soils (Alvarez et al., 1998). The
W. Demisie et al. / Catena 121 (2014) 214–221
215
ease of oxidation of the soil organic C by KMnO4, permanganate oxidizable organic carbon (POXC), is a larger pool than that commonly measured as soil microbial biomass (Blair et al., 1995). Water-soluble carbon (WSC) is another labile fraction that can be used as an indicator of short-term changes in C status of soils (Haynes, 2000). The hot-water extractable carbon (HWC) being a component of the labile soil organic matter and also being closely related to soil microbial biomass and micro aggregation could therefore be used as one of the soil quality indicator (Ghani et al., 2003). Many scientists showed interest in using biochar as soil amendment (Lehmann and Joseph, 2009; Sohi et al., 2010). Biochar is a highly stable compound created when biomass is heated to a temperature between 350 °C and 600 °C in the absence of oxygen. Biochar, as a soil amendment, can increase concentrations of soil organic matter, especially water-extractable organic carbon (Lin et al., 2012) and stimulate soil microbial activity (Lehmann et al., 2011). Microorganisms are largely responsible for decomposition of the organic matter via a variety of enzymes and hence, application of biochar is a method of replenishing degraded soil quality through improvement of the biological status of the soil, which usually implies an increase in enzyme activity (Albiach et al., 2000). We hypothesized that biochar increases organic matter in soils; therefore increases labile organic carbon, enzyme activity, and aggregate formation and, in turn improves soil quality. To identify changes in soil organic carbon quality as influenced by biochar applications, measurements of the more active fractions of soil labile organic carbon are very important. To our knowledge, there is little information on the effect of biochar on organic carbon fractions and enzyme activity on red soil. Therefore, the objectives of this study were to evaluate the effect of biochar application on the amount of total organic C (TOC), labile soil organic C fractions (LFOC, POXC, WSC, HWC and MBC), enzyme activity, aggregate formation and the quality of the soil.
Teller) surface areas was measured via N2 adsorption multilayer theory using a Nova 2200e surface area analyzer (Quantachrome, Boynton Beach, FL) (Chen et al., 2008).
2. Materials and methods
The light soil organic carbon fraction (LFOC) was determined using the density fractionation method as described by Gregorich and Janzen (1996). Briefly, 10 g of air-dried soil (b 2 mm) was placed in a 100 ml centrifuge tube with 50 ml of NaI solution (1.70 g cm−3). After shaking about 10 times by hand, the tube was sonicated using an ultrasonic disintegrator for 15 min at 400 W, and then centrifuged at 1200 g for 10 min. The supernatant with floating particles was decanted into a vacuum filter unit with a glass-fiber filter (Whatman GF/C) and the NI solution was collected for reuse. The process repeated twice without sonication. The light fraction collected on the filter was washed three times with 0.01 mol/l CaCl2 to remove excess NaI, and then washed three times with deionized water. The three subfractions were combined, oven-dried at 60 °C for 48 h, weighed and stored for analysis. Water soluble carbon (WSC) and hot-water extractable carbon (HWC) were measured as described by Ghani et al. (2003). Soil samples (equivalent to 3 g oven dry weight) were weighed into 50 ml polypropylene centrifuge tubes. These were extracted with 30 ml of distilled water for 30 min on an end-over-end shaker at 30 rpm and at 20 °C, centrifuged for 20 min at 3500 rpm and all the supernatant was filtered through 0.45 μm cellulose nitrate membrane filter into separate vials for carbon analysis. This fraction of the soil organic carbon was classified as water soluble C (WSC). A further 30 ml of distilled water was added to the sediments in the same tubes. These tubes were shaken on a vortex shaker for 10 s to suspend the soil in the water. The tubes were capped and left for 16 h in a hot-water bath at 80 °C. At the end of the extraction period, each tube was shaken for 10 s on a vortex shaker to ensure that HWC released from the SOM was fully suspended in the extraction medium. These tubes were then centrifuged for 20 min at 3500 rpm. The supernatants were filtered through 0.45 μm cellulose nitrate membrane filters. The extract was analyzed for carbon with a multi N/C analyzer. Permanganate oxidizable C was measured as described by Blair et al. (1995). Finely ground air-dried soil samples were reacted with 333 mM KMnO4 by shaking at 60 rpm for 1 h. The suspension
2.1. Soil sampling and analysis A laboratory experiment was conducted to study the influence of biochar on total organic carbon, labile soil organic carbon and enzyme activity. The experimental red soil for this study was sampled at Meijiawu, suburban of Hangzhou. The soil is highly weathered (Plinthic Hapli Udic Ferrosols in Chinese Soil Taxonomic Classification System; and Typic plinthustults in USAD Soil Taxonomy), derived from quaternary red clay parent material and characterized by low pH. The present land-use is tea garden. Particle size distribution was determined by a pipette method. Soil pH was determined through a suspension sample with a soil (airdried) to water (w/v) ratio of 1:2.5 and measured with a pH meter (Pansu and Gautheyrou, 2006). Soil organic carbon was determined by dichromate oxidation (Nelson and Sommers, 1982). Total nitrogen (TN) in soil was measured using the Kjeldahl method after H2SO4 digestion in the presence of K2SO4–CuSO4–Se catalyst (Bremner, 1996). 2.2. Biochar analysis The oak wood (Quercus phillyraeoides) and bamboo (Phyllostachy edulis) biochar used for this study, was pyrolyzed at 600 °C for 2 h (was purchased from Linan Yaoshi charcoal production Limited company located in Hangzhou City). The pH was determined in deionized water at the ratio of 1:10 wt/v (Gaskin et al., 2008) by Orion 720 pH meter. The carbon, hydrogen, and nitrogen contents of the biochars were determined using a CHN elemental analyzer (Flash EA 1112, Thermo Finnigan). The oxygen content was estimated by mass difference (100% — C, H, N and ash %). The ash content was determined according to ASTM D-1762-84 (2007) by combusting the biochar at 750 °C for 6 h in open crucibles on a dry weight basis. The BET (Brunauer–Emmet–
2.3. Incubation experiment The soil sample was passed through 5 mm sieve whereas the biochars through 0.25 mm sieve. Based on the mass of the soil (total 2 kg), the biochars were added at a rates of (0.5, 1.0 and 2%) of oak wood biochar (W0.5, W1.0, W2.0) and bamboo biochar (B0.5, B1.0, B2.0), with control as 0%. After mixing the soil and the biochars thoroughly, they were wetted with deionized water to about 30% water holding capacity of the experimental soil. All pots were covered with plastic film and then a small hole was made to allow gaseous exchange. The pots were incubated at a constant temperature of 25 °C. Based on evaporation loss, the soil moisture was kept constant by regular weighing of the pots. For each treatment, triplicate samples were prepared. The samples were arranged in complete randomized design. After 372 days, the incubated soils were used to analyze water-stable aggregate, TOC, TN, LFOC, POXC, WSC, HWC, MBC and dehydrogenase, β-glucosidase and urease. 2.4. Aggregate stability The fraction of aggregates was measured using a wet sieving method (Kemper, 1986). Air-dried soil samples of 50 g were placed at the top of a stack of sieves (2, 1, 0.5 and 0.25 mm). The screen was lowered to the water surface to allow the dry soils to become moist via capillary action, and then soils were sieved for 10 min with a stoke length of 10 cm and a frequency of 35 strokes per minute. Soils that remained in each sieve were transferred to a container, dried (60 °C), and weighed. 2.5. Labile organic carbon fractions
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was then centrifuged at 2000 rpm for 5 min. The supernatant was diluted and measured spectrophotometrically at 565 nm. Microbial biomass C (MBC) was determined by fumigation extraction method (Vance et al., 1987). Microbial biomass C was calculated as follows: Microbial biomass C ¼
EC KEC
where EC = [(organic C extracted from fumigated soils) minus (organic C extracted from non-fumigated soils)] and KEC (extractable part of microbial biomass C) = 0.45 (Wu et al., 1990). Based on experimental and literature data, Joergensen (1995) confirmed that the KEC values of Vance et al. (1987) and Wu et al. (1990) remain valid. The KEC value may vary in different soils but in this experiment only one soil type was used. Hence, we used a constant value (KEC = 0.45).
sample was incubated at 37 °C for 24 h. After incubation, the solution was diluted to 100 ml and filtered. Of the filtrate, 1 ml was taken into 50 ml volumetric flask, and 10 ml distilled water, 4 ml of sodium phenolate and 3 ml of sodium hypochlorite were added. Then, it was mixed and made the volume to 50 ml with distilled water, and absorbance of color was checked at 578 nm.
2.8. Statistical analysis The data collected was subjected to analysis of variance (ANOVA) using SAS statistical analysis software version 9.1. One-factor ANOVA was deployed to compare treatment effects. The least significant difference (LSD at 0.05 level of probability) test was applied to assess the differences among the means. Pearson's coefficient analysis was used for correlation.
2.6. Carbon management index A carbon management index (CMI) was developed based on changes in the total C in the soil and its lability as determined by KMnO4 oxidation (Blair et al., 1995). Calculation of the CMI was done taking treatments as samples of the soil of interest and the control as the reference. Accordingly, based on changes in total organic carbon between the treatments and control, Carbon Pool Index (CPI) was calculated as: CPI ¼
TOCtreatment : TOCcontrol
Based on C fraction oxidized by KMnO4 (POXC), lability of carbon (L) was calculated as: L¼
Carbon in fraction oxidized by KMnO4 : Carbon remaining unoxidized by KMnO4
Based on changes in the proportion of labile C, a lability index (LI) was calculated as: LI ¼
Ltreatment : Lcontrol
Taking the two indices (CPI and LI), the CMI was calculated as: CMI ¼ CPI LI 100: Higher CPI (CPI N 1) or lower (CPI b 1) indicates higher organic C accumulation or loss, respectively. Similarly, higher LI (LI N 1) indicates higher labile organic C content which can be due to more organic matter decomposition. On the contrary, lower (LI b 1) indicates lower labile organic C content which is directly related to less decomposition of organic matter. The CMI expresses the soil quality in terms of increments in the total C content and in the proportion of labile C fraction compared to the control which arbitrarily has a CMI of 100. Hence, higher CMI (CMI N 100) or lower CMI (CMI b 100) indicates increase or decrease in soil quality, respectively. 2.7. Enzyme activity Soil dehydrogenase activity was measured by the reduction of triphenyl tetrazolium chloride (TTC) to triphenyl formazan (TPF) as described by Tabatabai (1994). β-glucosidase activity was measured following the method described by Tabatabai (1982). This method is based on the colorimetric estimation of the p-nitrophenol (PNP) formed by the hydrolysis of the p-nitro-phenyl-β-D-glucopiranoside (PNG) at 37 °C for 1 h. The estimation of urease activity was carried out following the method described by Li (1996). Briefly, 10 g soil sample was taken into 100 ml conical flask, and 10 ml of (100 g l−1) urea solution and 20 ml citric acid buffer (pH 6.7) were added into the flask. The soil
3. Results 3.1. Total organic carbon and total nitrogen The soil used was degraded red soil with low in C (5.50 g kg− 1), whereas the C content of oak wood and bamboo biochar was 758.10 and 759.20 g kg−1, respectively which had only 0.11% differences (Table 1). The content of total N (TN) in oak wood biochar was 6.40 g kg−1 whereas in bamboo biochar was 11.6 g kg−1 (Table 1). Our results showed that total organic carbon (TOC) significantly increased with increasing both biochar rates (Fig. 1). The highest TOC was recorded in W2.0 (23.91 g kg−1) followed by B2.0 (20.48 g kg−1) whereas the lowest was in control (5.39 g kg−1). The concentration of TN slightly increased in B2.0, while no statistical differences were found among the rest of the treatments. Due to lack of significant differences among treatments in TN, the C/N ratio kept similar trend with TOC, the maximum was in W2.0 and the minimum was in control (Fig. 1).
3.2. Labile organic carbon Application of biochar affected labile organic C, where W0.5 and B0.5 generally had the highest content of LFOC (66.27%), HWC (0.38%), POXC (6.94%) and MBC (0.77%), of the total TOC, while W2.0 had the lowest content of these organic carbons. As to WSC, no clear trend was observed, however the highest was measured in the control (Table 2). The proportion of the labile organic C accounting for the total organic C was higher in the control than the rest of the treatments (Table 3). The proportions of the five labile organic fractions accounting for total organic carbon with their decreasing order are shown as follows: Soil LFOC N POXC N MBC N HWC ≈ WSC. Soil LFOC composed the highest and WSC the lowest active carbon proportions among the six main fractions with 17.46%–85.00% and 0.12%–0.58% of soil TOC, respectively. Table 1 Basic property of soil and oak wood and bamboo biochar. Property
Soil
Oak wood biochar
Bamboo biochar
Sand % Silt% Clay% Texture pH Total organic C (g kg−1) Total N (g kg−1) Hydrogen % Oxygen % Base-hydrolytical-N (mg kg−1) Ash% Surface area (m2 g−1)
22 40 38 Clay loam 4.57 5.50 0.94 ND ND 120.0 ND ND
ND ND ND ND 10.25 758.1 6.4 1.12 10.49 7.35 11.94 154.6
ND ND ND ND 10.22 759.2 11.6 2.11 6.45 16.1 14.36 137.7
ND—not detected, Oxygen% = 100% − (C% + N% + H% + Ash%).
W. Demisie et al. / Catena 121 (2014) 214–221
217
3.6. Enzyme activity The highest dehydrogenase activity was measured in W 0.5 (7.03 μg TPF g−1 soil 24 h−1) followed by B0.5 (6.94 μg TPF g−1 soil 24 h−1) and the lowest was in B2.0 (5.46 μg TPF g−1 soil 24 h−1), however there were no significant differences among the treatments except in B2.0 which is significantly lower than the rest of the treatments (Fig. 2). The maximum β-glucosidase activity was measured in B0.5 (1.93 mg PNP g−1 soil h−1) and B1.0 (1.93 mg PNP g−1 soil h−1) and the minimum in W2.0 (1.51 mg PNP g−1 soil h−1) which is significantly lower than the rest of the treatments (Fig. 3). Urease activity was significantly higher in W 2.0 (1020.00 μg NH 3 –N g − 1 soil 24 h –1 ), B0.5 (1018.33 μg NH3–N g−1 soil 24 h−1) and W0.5 (1017.50 μg NH3–N g−1 soil 24 h−1) than the rest of the treatments (Fig. 4).
Fig. 1. Soil total organic carbon (TOC), total nitrogen (TN) and C/N ratio among treatments. Bars represent the standard deviation of the mean (n = 3). Different letters over the bars indicate significant differences (p b 0.05) among treatments.
4. Discussion
3.3. Water aggregate stability
Our results showed that increasing application of biochar rates increased TOC (Lin et al., 2012) and its labile fractions (Leifeld et al., 2002) which improved the soil quality by increasing the microbial activities, aggregation and sequestration of C in the soil. Soil C/N ratio can indicate microbial transformation process (Wang et al., 2012). Increasing the biochar rates increased the C/N ratio, indicating a slow transformation and recycling of organic matter (Kindler et al., 2011). The lowest C/N ratio was observed in B0.5, W0.5 and B1.0. These treatments particularly the lowest rates (W0.5 and B0.5) had higher dehydrogenase and β-glucosidase activities, suggesting that higher microbial activities had contribution in carbon mineralization. Our experiment showed the highest MBC in the lowest biochar rates (W0.5 and B0.5) which suggests more intensive activity of microorganisms and thus more decomposition of soil organic matter and labile organic carbon. The positive correlation of HWC with MBC (r = 0.63 p b 0.01) supports this context. Similarly, Sparling et al. (1998) also suggested that hot-water extractable pool of C relates well with microbial biomass-C. Labile C and nutrients (N, S and P) are extracted by hot-water extractable C (HWC) (Ghani et al., 2003) which is a rapid indicator for estimates of labile soil organic matter constituents (Henriksen and Breland, 1999). The POXC was significantly higher in W0.5 and B0.5 than the control because relatively of the higher labile carbon inputs associated with these biochar rates which resulted in higher lability index (LI), indicating that permanganate oxidized organic C is a sensitive indicator of changes in soil quality for soil management. Water soluble carbon (WSC) is the main energy source of soil microorganisms (Huang and Song, 2010) which results from soil organic matter decomposition. Our results showed that WSC decreased in all treatments as compared to the control. This is due to the ease availability of WSC for microbial growth in the first few weeks, which may have resulted in decrease after 372 days of incubation. Moreover, the proportion of WSC accounting for total organic carbon is lower than the other
In all treatments, the macroaggregates (N 0.25 mm) accounted for 40.32 to 55.43% of the dry soil weight (Table 4). Compared to the control, B0.5, B1.0 and W0.5 significantly increased the proportion of macroaggregates. It shows that the lowest biochar rates had higher aggregate formation than the highest rates.
3.4. Relationships among organic carbon fractions As shown in Table 5, in connection to microbial activities in aggregate formation as well as contribution to labile organic C, MBC positively correlated with macroaggregates (N0.25 mm) (r = 0.49 p b 0.05), and LFOC (r = 0.48 p b 0.05), POXC (r = 0.68 p b 0.01), HWC (r = 0.63 p b 0.01) and WSC (r = 0.45 p b 0.05). Moreover, the C/N, the important factor in microbial activities, negatively correlated with HWC (r = −0.86 p b 0.001), POXC (r = − 0.87 p b 0.001) and macroaggregates (r = −0.63 p b 0.01).
3.5. Carbon management index To determine the degree of lability of the treatments, we used potassium permanganate (KMnO4) to oxidize a proportion of the carbon in the treatments and measured the fractions which represent carbon of different labilities. Accordingly, lability index (LI) decreased with increasing biochar rates, the highest was in W0.5 and B0.5, whereas the lowest in W2.0 and B2.0 (Table 6). As compared to the control, lability index (LI) increased in W0.5 and B0.5 by 4% and 6%, respectively. The carbon pool index (CPI) and carbon management index (CMI) increased with increasing biochar rates (Table 6). CMI showed the minimum increase in B0.5 (50.34%) and the maximum in W2.0 (286.33%) (Table 6).
4.1. Biochar effect on carbon fractions
Table 2 Light fraction organic carbon (LFOC), permanganate oxidizable carbon (POXC), microbial biomass carbon (MBC), hot-water extractable carbon (HWC) and water soluble carbon (WSC) among treatments. Treatment
LFOC (g kg−1)
POXC (mg kg−1)
MBC (mg kg−1)
HWC (mg kg−1)
WSC (mg kg−1)
Control W0.5 W1.0 W2.0 B0.5 B1.0 B2.0
4.55 5.72 5.31 4.17 5.70 5.68 5.49
575.41 606.00 537.92 514.15 605.51 593.71 538.88
56.36 66.31 55.58 55.11 64.30 54.70 55.58
31.28b 32.82 30.53 22.60 32.75 29.45 27.26
31.23 30.11 28.11 30.21 30.82 27.68 28.42
± ± ± ± ± ± ±
0.10d 0.11a 0.13c 0.23e 0.14ab 0.00ab 0.06bc
± ± ± ± ± ± ±
4.50c 1.00a 0.95d 3.45e 2.95a 1.20b 1.31d
± ± ± ± ± ± ±
1.01b 2.25a 1.21b 0.39b 1.51a 0.64b 0.43b
± ± ± ± ± ± ±
0.58c 0.96a 0.94 cd 1.02f 1.04ab 0.91d 0.52e
All values were expressed as mean ± standard deviation (n = 3). Different letters in the same column indicated significant differences (p b 0.05).
± ± ± ± ± ± ±
0.23a 0.21b 0.47c 0.82ab 0.89ab 0.52c 0.77c
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Table 3 The proportions of labile organic carbon fractions accounting for soil organic carbon. Treatment
LFOC/TOC (%)
POXC/TOC (%)
MBC/TOC (%)
HWC/TOC (%)
WSC/TOC (%)
Control W0.5 W1.0 W2.0 B0.5 B1.0 B2.0
85.00 66.27 35.05 17.46 73.64 51.90 26.79
10.75 6.94 3.55 2.15 8.02 5.43 2.63
1.05 0.77 0.37 0.23 0.85 0.50 0.27
0.58 0.38 0.20 0.09 0.43 0.27 0.13
0.58 0.35 0.19 0.12 0.41 0.25 0.14
± ± ± ± ± ± ±
7.86a 1.83b 0.85d 0.72e 9.18b 5.28c 0.24d
± ± ± ± ± ± ±
1.06a 0.07c 0.01e 0.09f 0.99b 0.56d 0.05ef
± ± ± ± ± ± ±
0.09a 0.04b 0.01d 0.01e 0.10b 0.06c 0.01e
± ± ± ± ± ± ±
0.05a 0.01b 0.01d 0.01e 0.06b 0.03c 0.01e
± ± ± ± ± ± ±
0.06a 0.01c 0.01e 0.01f 0.05b 0.03d 0.01ef
All values were expressed as mean ± standard deviation (n = 3). TOC, total organic C; LFOC, light fraction organic C; POXC, permanganate oxidizable organic C; MBC, microbial biomass C; HWC, hot-water extractable carbon; WSC, water soluble organic C. Different letters in the same column indicated significant differences (p b 0.05).
labile organic C, indicating that it had been consumed by microorganisms earlier. The LFOC positively correlated with MBC (r = 0.48 p b 0.05) and macroaggregate (N0.25 mm) (r = 0.57 p b 0.01), suggests that the high LFOC in W0.5 and B0.5 contributed to increase MBC and macroaggregation which implies the LFOC enhances soil structure. Kay (1998) also reported the importance of LFOC in the formation and stability of soil structure, especially in the stabilization of soil macroaggregates (N0.25 mm). Generally, the labile C (LFOC, WSC, HWC, POXC and MBC) to TOC ratio is higher in control which indicates the rapid decomposition of organic matter in control as compared to biochar treated ones. This shows the accumulation of organic carbon pool with biochar treatments. Of the six labile organic C proportions accounting for TOC, the high MBC/TOC ratio, in control, implies that soil organic matter decomposed rapidly, which would be detrimental to soil quality to some degree as described by Jiang et al. (2006). Soil organic matter content (pool size) is a balance between addition and decomposition rates (turnover rates) and, as such, changes in agricultural practices can result in marked changes in both the pool size and turnover rate of soil organic matter, carbon and therefore, nutrients (Blair et al., 1995). Carbon management index (CMI) can be used to monitor differences in soil C dynamics between treatments (Blair et al., 1995). The CMI can be used to assess soil quality based on information related to soil organic C dynamics. This index expresses the soil quality in terms of increments in the total C content and in the proportion of labile C fraction compared to the control which arbitrarily has a CMI of 100. In our study, generally, increasing biochar rates decreased lability index (LI) (except in W0.5 and B0.5), which indicates the reduction of labile organic C, whereas carbon pool index (CPI) increased which suggests the accumulation of organic C. The increase in CPI resulted in increase in CMI. The TOC reduction under the critical limit affects soil properties and productivity very negatively and, hence balanced organic matter turnover is necessary for sustainable soil management and carbon sequestration (King et al., 2005; Stewart et al., 2008). However, in this study, the maximum contribution of biochar to LI (labile organic C) was 4% (W0.5) and 6% (B0.5) which was very low as compared to the maximum CPI (carbon accumulation) 344% and 280%. This could be due to the increased C/N ratio (less amount of N) which reduced microbial activities in mineralization of organic matter, however contributed in sequestration of carbon in soil. Therefore,
we hypothesize that application of appropriate amount of N could enhance microbial activities and increase labile organic C for improving soil quality. Taking into consideration that high mineralization rates are only good for soil quality in the short term. At high rates labile C is removed fast and then only stable fractions remain, which are, however, important for soil quality in the long term.
4.2. Biochar effect on aggregate stability The soil type used in this study is ferralsols which is highly degraded under intensive cropping from erosion, therefore restoration of the soil by enhancing aggregate formation is unquestionable. Soil aggregation is an important factor in sustainable agriculture because of its impact on soil biological and physical properties. Aggregate formation in soils depends on the binding agents in soil. The impact of organic product addition on aggregate stability was generally larger when the C content of the soil was low (Fortun et al., 1996). The soil used in this experiment was low in carbon content; hence the organic carbon had impact on its aggregation. The higher macroaggregate, the more sensitive indicator to changes of soil management (Kocyigit and Demirci, 2012), was observed in treatments (B0.5 and B1.0). This could be due to the highest microbial abundance that contributed on bonding agent responsible for macroaggregation. The microbial biomass and β-glucosidase activity were higher in B0.5 which indicates that the aggregating mechanisms are related to polysaccharide (Schjønning et al., 2002). Polysaccharides synthesized by microorganisms during decomposition are hydrophilic and tend to adsorb to mineral particles and increase their interparticle cohesion (Chenu, 1989). The positive correlation of MBC with macroaggregate (N 0.25 mm) (r = 0.49 p b 0.05) confirms the reports of Watts et al. (2005) who suggested that biological mechanisms plays important role in aggregate formation. Moreover, the C/N ratio negatively correlated with macroaggregation (r = 0.63 p b 0.01) implies that C/N is the main factor to enhance microbial activities that are responsible for aggregate formation. This context is supported by the previous researches' results which showed that positive correlations between CO2–C concentrations release and aggregate stability in short and long time (Martens and Frankenberger, 1992; Sonnleitner et al., 2003) after organic carbon inputs, indicating that increases in aggregate stability were related to microbial activity.
Table 4 Changes in soil water aggregate stability (%) at different treatments. Treatment
Particle size distribution N2 mm
Control W0.5 W1.0 W2.0 B0.5 B1.0 B2.0
4.37 4.69b 4.74b 4.17 6.12 6.71 4.10
± ± ± ± ± ± ±
0.22c 0.55c 1.94c 0.54c 0.73ab 1.05a 0.40c
1–2 mm
0.5–1 mm
0.25–0.5 mm
N0.25 mm
4.42 7.92 5.77 5.37 4.24 4.93 4.55
11.98 11.42 10.14 10.67 13.10 20.85 12.81
23.56 24.21 22.35 19.65 31.96 21.13 18.86
44.33 48.24 43.01 39.85 55.43 53.62 40.32
± ± ± ± ± ± ±
0.26b 1.40a 1.28b 0.96b 0.37b 1.03b 0.21b
± ± ± ± ± ± ±
3.51b 1.57b 2.70b 4.46b 2.75b 1.96a 3.01b
± ± ± ± ± ± ±
2.76b 2.99b 3.48b 3.13b 1.98a 4.77b 4.50b
All values were expressed as mean ± standard deviation (n = 3). Different letters in the same column indicated significant differences (p b 0.05).
± ± ± ± ± ± ±
4.78bc 1.01b 1.16bc 2.96c 4.85a 2.09a 1.89c
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219
Table 5 Correlations among soil organic carbon fractions and aggregate stability. Pools of carbon
C/N
LFOC
WSC
HWC
POXC
MBC
TOC
N0.25 macro aggregate C/N LFOC WSC HWC POXC MBC
−0.63⁎⁎ 1
0.57⁎⁎ −0.41 1
0.06 −0.32 −0.40 1
0.62⁎⁎ −0.86⁎⁎⁎ 0.62⁎⁎
0.82⁎⁎⁎ −0.87⁎⁎⁎ 0.64⁎⁎
0.49⁎ 0.48⁎ 0.48⁎ 0.45⁎ 0.63⁎⁎ 0.68⁎⁎
−0.63⁎⁎ 0.98⁎⁎⁎
−0.18 1
0.22 0.81⁎⁎⁎ 1
−0.37 −0.35 −0.87⁎⁎⁎ −0.87⁎⁎⁎ −0.51⁎
1
TOC, total organic C; C/N, carbon to nitrogen ration; LFOC, light fraction organic C; WSC, water soluble organic C; HWC, hot-water soluble organic C; POXC, permanganate oxidizable organic C; MBC, microbial biomass C. ⁎ Is significant at P b 0.05. ⁎⁎ Is significant at P b 0.01. ⁎⁎⁎ Is significant at P b 0.001.
Mineralization of soil organic matter (SOM) is an important microbially-mediate process by which carbon, nitrogen, and other nutrients are converted from organic forms into inorganic forms. Soil microbes must produce soil enzymes to catalyze the breakdown of soil organic matter and to make readily-usable dissolved compounds for growth and metabolisms. Martens et al. (1992) reported the rapid response β-glucosidase to management-induced change in soil. βglucosidase is an extracellular enzyme involved in carbon mineralization, while dehydrogenase is an intracellular enzyme and its activity in soil has been considered as a general index for evaluating soil microbial activity (Brookes et al., 2008). Moreover, dehydrogenase activity has been used successfully as a parameter for the evaluation of degree of
recovery of degraded soils (Gil-Sotres et al., 2005). Based on our finding the dehydrogenase activity was higher in W0.5 and B0.5, indicating that biochar at rate of 0.5% could ameliorate the degraded red soil. βglucosidase activity was higher in bamboo biochar treated soils (B0.5 and B1.0). Based on our findings the two biochars showed various βglucosidase activities which could be due to differences in their chemical composition. The activity of urease has been observed to increase due to organic fertilization (Chakrabarti et al., 2000). In this study, urease activity was higher in W2.0, W0.5 and B0.5 which could be due to the higher microbial biomass in the treatments released more urease enzyme than the other treatments.
β-glucosidase (mg PNP g-1 soil h-1)
4.3. Biochar effects on activity of enzymes
Table 6 Changes in soil CMI for different treatments. Treatment
CPI
LI
CMI
Control W0.5 W1.0 W2.0 B0.5 B1.0 B2.0
1.00 1.60 2.81 4.44 1.41 2.04 3.80
1.00 1.04 0.93 0.87 1.06 1.02 0.93
100.00 167.13 260.62 386.33 150.34 209.23 352.54
3 2
ab
ab
a
a
ab
B0.5
B1.0
B2.0
b
2 1 1 0 con
LI, lability index; CPI, carbon pool index; CMI, carbon management index.
ab
W0.5
W1.0
W2.0
Treatment 9 a
a
a ab
7
ab
ab
b 1200
6
a
a
Urease (µg NH3-N g-1soil 24h-1)
Dehydrogenase (µg TPF g-1soil 24h-1)
8
Fig. 3. β-Glucosidase activity at different biochar treatments. Bars represent the standard deviation of the mean (n = 3). Different letters over the bars indicate significant differences (p b 0.05) among treatments.
5 4 3 2 1
1000
a
b
b
B1.0
B2.0
b c
800
600
400
200
0 con
W0.5
W1.0
W2.0
B0.5
B1.0
B2.0
Treatment Fig. 2. Dehydrogenase activity at different biochar treatments. Bars represent the standard deviation of the mean (n = 3). Different letters over the bars indicate significant differences (p b 0.05) among treatments.
0 con
W0.5
W1.0
W2.0
B0.5
Treatment Fig. 4. Urease activity at different biochar treatments. Bars represent the standard deviation of the mean (n = 3). Different letters over the bars indicate significant differences (p b 0.05) among treatments.
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Both biochars had nearly similar effect on labile C which resulted in the corresponding treated soils to keep similar trend in microbial activities and macroaggregation. 5. Conclusion The long-term inappropriate utilization and management have caused severe degradation in red soil. Depletion of soil organic matter, soil erosion and decline in soil structure are the major degradative processes. Application of oak and bamboo biochar could ameliorate this soil through increasing the content of organic carbon and improving soil aggregation. Both biochars had less lability but more accumulation of organic C which could contribute in sequestration of C in soil. Oak wood and bamboo biochar can be used at rate of 0.5%, particularly, the bamboo for its better microbial activities and macroaggregate formation than the oak wood. The increase in organic matter, microbial activities and macroaggregation can be viewed as improvement in soil quality. However, application of these biochars at highest rates (more than 0.5%) decrease macroaggregation and which, in turn, can cause erodibility and loss in soil quality. Acknowledgments This research was financially supported by National Key Technology Support Program (No. 2012BAD05B00). We thank Hao Wang and Dong-wei Yang for their unlimited support in this research. We also thank the anonymous reviewers for their valuable comments. References Albiach, H., Canet, R., Pomares, F., Ingelmo, F., 2000. Microbial biomass content and enzymatic activities after the application of organic amendments to a horticultural soil. Bioresour. Technol. 75, 43–48. Alvarez, C.R., Alvarez, R., Grigera, M.S., Lavado, R.S., 1998. Associations between organic matter fractions and the active soil microbial biomass. Soil Biol. Biochem. 6, 767–773. American Society for Testing and Materials (ASTM), 2007. Standard methods for chemical analysis of wood charcoal. ASTM D1762-84. ASTM International, Pennsylvania, USA. Blair, G.J., Lefroy, R.D.B., Lisle, L., 1995. Soil carbon fractions based on their degree of oxidation, and the development of a carbon management index for agricultural system. Aust. J. Agric. Res. 46, 1459–1466. Bremner, J.M., 1996. Total nitrogen. In: Sparks, D.L., et al. (Eds.), Methods of Soil Analysis, Part 3. Chemical Methods. SSSA, ASA, Madison, Wisconsin, USA, pp. 1085–1122. Brookes, P.C., Cayuela, M.L., Contin, M., De Nobili, M., Kemmitt, S.J., Mondini, C., 2008. The mineralization of fresh and humified soil organic matter by the soil microbial biomass. Waste Manag. 28, 716–722. Cerdà, A., 1998. Soil aggregate stability under different Mediterranean vegetation types. Catena 32, 73–86. Chakrabarti, K., Sarkar, B., Chakraborti, A., Banik, P., Bakchi, D.K., 2000. Organic recycling for soil quality conservation in a sub-tropical plateau region. J. Agron. Crop Sci. 184, 137–142. Chen, B., Zhou, D., Zhu, L., 2008. Transitional adsorption and partition of non polar and polar aromatic contaminants by biochar of pine needles with different pyrolytic temperatures. Environ. Sci. Technol. 42, 5137–5143. Cheng, L., Leavitt, S.W., Kimball, B.A., 2007. Dynamics of labile and recalcitrant soil carbon pools in a sorghum free-air CO2 enrichment (FACE) agroecosystem. Soil Biol. Biochem. 39, 2250–2263. Chenu, C., 1989. Influence of a fungal polysaccharide, scleroglucan, on clay microstructures. Soil Biol. Biochem. 21, 299–305. Fortun, A., Tomas, R., Fortun, C., 1996. Effect of bituminous materials on soil aggregation. Arid Soil Res. Rehabil. 10, 161–168. Freixo, A.A., Machado, P.L., Santos, H.P., 2002. Soil organic carbon and fractions of a Rhodic Ferralsol under the influence of tillage and crop rotation systems in Southern Brazil. Soil Tillage Res. 64, 221–230. García-Orenes, F., Roldán, A., Mataix-Solera, J., Cerdà, A., Campoy, M., Arcenegui, V., Caravaca, F., 2012. Soil structural stability and erosion rates influenced by agricultural management practices in a semi-arid Mediterranean agro-ecosystem. Soil Use Manag. 28, 571–579. Gaskin, J.W., Steiner, C., Harris, K., Das, K.C., Bibens, B., 2008. Effect of low temperature pyrolysis conditions on biochar for agricultural use. Trans. ASABE 51, 2061–2069. Ghani, A., Dexter, M., Perrott, K.W., 2003. Hot-water extractable carbon in soils: a sensitive measurement for determining impacts of fertilization, grazing and cultivation. Soil Biol. Biochem. 35, 1231–1243. Gil-Sotres, F., Trasar-Cepeda, C., Leiros, M.C., Seoane, S., 2005. Different approaches to evaluating soil quality using biochemical properties. Soil Biol. Biochem. 37, 877–887.
Gregorich, E.G., Janzen, H.H., 1996. Storage of soil carbon in the light fraction and macroorganic matter. In: Carter, M.R., Stewart, B.A. (Eds.), Advances in Soil Science. Structure and Organic Matter Storage in Agricultural Soils. CRC Lewis, Boca Raton, pp. 167–190. Haynes, R.J., 2000. Labile organic matter as an indicator of organic matter quality in arable and pastoral soils in New Zealand. Soil Biol. Biochem. 32, 211–219. Henriksen, T.M., Breland, T.A., 1999. Decomposition of crop residues in the field; evaluation of a simulation model developed from microcosm studies. Soil Biol. Biochem. 31, 1423–1434. Huang, J.Y., Song, C.C., 2010. Effects of land use on soil water soluble organic C and microbial biomass C concentrations in the Sanjiang Plain in northeast China. Acta Agric. Scand. Sect. B Soil Plant 60, 182–188. Janzen, H.H., Campbell, C.A., Ellert, B.H., Bremer, E., 1997. Soil organic matter dynamics and their relationship to soil quality. In: Gregorich, E.G., Carter, M.R. (Eds.), Soil Quality for Crop Production and Ecosystem Health. Developments in Soil Science, vol. 25. Elsevier, Amsterdam, pp. 277–292. Jiang, P.K., Xu, Q.F., Xu, Z.H., Cao, Z.H., 2006. Seasonal changes in soil labile organic carbon pools within a Phyllostachys praecox stand under high rate fertilization and winter mulch in subtropical China. For. Ecol. Manag. 236, 30–36. Joergensen, R.G., 1995. The fumigation–extraction method to estimate soil microbial biomass: calibration of the KEC value. Soil Biol. Biochem. 28, 25–31. Kay, B.D., 1998. Soil structure and organic carbon, a review. In: Lal, R., et al. (Eds.), Soil Processes and the Carbon Cycle. CRC Press, Boca Raton, FL, pp. 169–197. Kemper, W.D., 1986. Aggregate stability and size distributions. Methods of Soil Analysis. Part I. Physical and mineralogical methods, In: Klute, A. (Ed.), 2nd ed. Agro. Monoger., 9. ASA and SSSA, Madison, WI, pp. 383–411. Kindler, R., Siemens, J., Kaiser, K., et al., 2011. Dissolved carbon leaching from soil is a crucial component of the net ecosystem carbon balance. Glob. Chang. Biol. 17, 1167–1185. King, J.A., Bradley, R.I., Harrison, R., 2005. Current trends of soil organic carbon in English arable soils. Soil Use Manag. 21, 189–195. Kocyigit, R., Demirci, S., 2012. Long-term changes of aggregate-associated and labile soil organic carbon and nitrogen after conversion from forest to grassland and cropland in northern Turkey. Land Degrad. Dev. 23, 475–482. Lehmann, J., Joseph, S., 2009. Biochar for environmental management: an introduction. In: Lehmann, J., Joseph, S. (Eds.), Biochar for Environmental Management: Science and Technology. Earthscan, London, pp. 1–12. Lehmann, J., Rillig, M.C., Thies, J., Masiello, C.A., Hockaday, W.C., Crowley, D., 2011. Biochar effects on soil biota—a review. Soil Biol. Biochem. 43, 1812–1836. Leifeld, J., Siebert, S., Kogel-Knabner, I., 2002. Changes in the chemical composition of soil organic matter after application of compost. Eur. J. Soil Sci. 53, 299–309. Li, F.D., 1996. Analysis of soil enzyme activity. In: Li, F.D., et al. (Eds.), Experimental Techniques in Agricultural Microbiology. Agricultural Press, Beijing, pp. 137–139 (in Chinese). Lin, Y., Munroe, P., Joseph, S., Henderson, R., Ziolkowski, A., 2012. Water extractable organic carbon in untreated and chemical treated biochar. Chemosphere 87, 151–157. Lützow, M., Leifeld, J., Kainz, M., Kogel-Knabner, I., Munch, J.C., 2000. Indications for soil organic matter quality in soils under different management. Geoderma 105, 243–258. Martens, D.A., Frankenberger, W.T., 1992. Modification of infiltration rates in an organicamended irrigated soil. Agron. J. 84, 707–717. Martens, D.A., Johnson, J.B., Frankenberger, W.T., 1992. Production and persistence of soil enzymes with repeated additions of organic residues. Soil Sci. 153, 53–61. Nelson, D.W., Sommers, L.E., 1982. Total carbon, organic carbon and organic matter. In: Page, A.L. (Ed.), Methods of Soil Analysis. Part 2. American Society of Agronomy, Madison, WI, pp. 539–579. Pansu, M., Gautheyrou, J., 2006. Handbook of Soil Analysis—Mineralogical, Organic and Inorganic Methods. Springer-Verlag, Heidelberg, pp. 551–578. Schjønning, P., Elmholt, S., Munkholm, L.J., Debosz, K., 2002. Soil quality aspects of humid sandy loams as influenced by organic and conventional long-term management. Agric. Ecosyst. Environ. 88, 195–214. Sohi, S., Krull, E., Lopez-Capel, E., Bol, R., 2010. A review of biochar and its use and function in soil. Adv. Agron. 105, 47–82. Sonnleitner, R., Lorbeer, E., Schinner, F., 2003. Effect of straw, vegetable oil and whey on physical and microbiological properties of a chernozem. Appl. Soil Ecol. 22, 195–204. Sparling, G.P., Vojvodic-Vukovic, M., Schipper, L.A., 1998. Hot-water soluble C as a simple measure of labile soil organic matter: the relationship with microbial biomass C. Soil Biol. Biochem. 1469-72. Stewart, C.E., Paustian, K., Conant, R.T., Plante, A.F., Six, J., 2008. Soil carbon saturation: evaluation and corroboration by long-term incubations. Soil Biol. Biochem. 21, 189–195. Tabatabai, M.A., 1982. Soil enzymes. In: Page, A.L. (Ed.), Methods of Soil Analysis, Part 2. American Society of Agronomy, pp. 903–948. Tabatabai, M.A., 1994. Soil enzymes. In: Weaver, R.W., et al. (Eds.), Methods of Soil Analysis. Soil Society of America, Madison, pp. 775–883. Tisdall, J.M., Oades, J.M., 1982. Organic matter and water-stable aggregates in soils. Soil Sci. 33, 141–163. Vance, E.D., Brookes, P.C., Jenkinson, D.S., 1987. Microbial biomass measurements in forest soils: the use of the chloroform fumigation incubation method for strongly acid soils. Soil Biol. Biochem. 19, 697–702. Wang, J., Song, C., Wang, X., Song, Y., 2012. Changes in labile soil organic carbon fractions in wet land ecosystems along a latitudinal gradient in North East China. Catena 96, 83–89.
W. Demisie et al. / Catena 121 (2014) 214–221 Watts, C.W., Whalley, W.R., Brookes, P.C., Devonshire, B.J., Whitmore, A.P., 2005. Biological and physical processes that mediate micro aggregation of clays. Soil Sci. 170, 573–583. Wu, J., Joergensen, R.G., Pommerening, B., Chaussod, R., Brookes, P.C., 1990. Measurement of soil microbial biomass C by fumigation–extraction: an automated procedure. Soil Biol. Biochem. 17, 837–842. Xu, R., Zhao, A., Li, Q., Kong, X., Ji, Q., 2003. Acidity regime of the Red Soils in a subtropical region of southern China under field conditions. Geoderma 115, 75–84.
221
Zhang, M.K., Xu, J.M., 2005. Restoration of surface soil fertility of an eroded red soil in southern China. Soil Tillage Res. 80, 13–21. Zhang, B., Zhang, T.L., Zhao, Q.G., 1996. Soil erosion in various farming systems in subtropical China. Pedosphere 6, 225–234.