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Dynamics of soil labile organic carbon fractions and C-cycle enzyme activities under straw mulch in Chengdu Plain
Soil & Tillage Research 155 (2016) 289–297
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Dynamics of soil labile organic carbon fractions and C-cycle enzyme activities under straw mulch in Chengdu Plain Sen Lia,b , Shirong Zhanga,* , Yulin Pua , Ting Lia , Xiaoxun Xua , Yongxia Jiaa , Ouping Denga , Guoshu Gongc a b c
College of Resources and Environment, Sichuan Agricultural University, Wenjiang 611130, PR China Institute of Ecology and Environment, Sichuan Agricultural University, Wenjiang 611130, PR China Agricultural College, Sichuan Agricultural University, Wenjiang 611130, PR China
A R T I C L E I N F O
A B S T R A C T
Article history: Received 30 November 2014 Received in revised form 8 July 2015 Accepted 22 July 2015
Soil labile organic carbon fractions (LOCF) are valuable indicators of changes in soil quality and soil total organic carbon (TOC), and they are easily influenced by changes in soil management practice. To explore the sensitivity of LOCF and their enzymatic conversion under straw mulch for scientific management of crop straw use on the Chengdu plain, a straw mulch field experiment was conducted to observe the LOCF changes and explore their relationships with C-cycle enzymes during wheat growth. The treatments included no fertilizer or straw (Control), only mineral fertilizer (MF), 10% rice straw nitrogen (N) plus 90% fertilizer N (RS1), 20% rice straw N plus 80% fertilizer N (RS2), 30% rice straw N plus 70% fertilizer N (RS3), 100% rice straw (RS). The water-soluble organic carbon (WSOC) and microbial biomass carbon (MBC) under straw treatments in the 0–20 cm soil layer were significantly higher than those of Control and MF treatments from the seedling stage, and showed significant differences among straw treatments from the tillering stage. Correspondingly, the dissolved organic carbon (DOC) and permanganate oxidized carbon (POXC) showed no obvious differences among straw treatments in most growth stages. Therefore, WSOC and MBC were the most sensitive indicators for assessing soil organic carbon (SOC) change under straw mulch. Moreover, stepwise multiple linear regression revealed that cellulase and b-glucosidase were significantly positive impact factors for LOCF in the two soil layers, while polyphenol oxidase had both positive and negative impacts on WSOC at different soil layers, and peroxidase was a negative factor for LOCF. ã 2015 Elsevier B.V. All rights reserved.
Keywords: Straw mulch Total soil organic carbon Labile organic carbon fractions Soil C-cycle enzymes
1. Introduction Soil organic carbon (SOC) plays an important role in the function of agro-ecosystems because it provides energy and substrates for microbial metabolism, and promotes biological diversity (Loveland and Webb, 2003). Thus, its change has become an evaluation index of the variation of soil quality (Sparling and Schipper, 2004; Haynes, 2005). However, the change of total soil organic carbon (TOC) is not easily detected in the short term (Bhattacharyya et al., 2011; Gong et al., 2009). Compared with TOC, the labile organic carbon fractions (LOCF) including water-soluble organic carbon (WSOC), dissolved organic carbon (DOC), microbial biomass carbon (MBC), and permanganate oxidized carbon (POXC) have been considered as sensitive indicators of soil quality change
* Corresponding author. Fax: +86 28 86290983. E-mail address: [email protected] (S. Zhang). http://dx.doi.org/10.1016/j.still.2015.07.019 0167-1987/ ã 2015 Elsevier B.V. All rights reserved.
from management practices (Blair et al., 1995; Purakayastha et al., 2008; Plaza-Bonilla et al., 2014). Crop straw is a source of organic carbon that can influence the balance of SOC accumulation and decomposition (Bakht et al., 2009), especially the LOCF (Malhi et al., 2011). However, studies on the effects of straw practices on LOCF have presented diverse results. For instance, Nayak et al. (2012) reported that straw mulch with mineral fertilizer had a greater MBC concentration than that of mineral fertilizer only. In contrast, Yan et al. (2007) observed that straw mulch would decrease MBC concentrations compared with the mineral fertilizer only. With respect to WSOC concentrations after straw mulch, they showed positive (Whitbread et al., 2003), or no obvious (Xu et al., 2011) or negative effect (Ma et al., 2013) in 1–2-year experiments. Furthermore, SOC transformation involved a series of dynamic biochemical processes (Alvarez and Guerrero, 2000). Generally, hydrolytic enzymes are recognized as essential regulators to control SOC decomposition (Sinsabaugh, 1994; Grandy et al., 2009). For example, cellulase breaks cellulose
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down to cellobiose, fructose and glucose (Wickings et al., 2012); b-glucosidase can further decompose labile cellulose and other carbohydrate polymers into low molecular weight compounds (Liang et al., 2014). In contrast, soil phenol oxidase is proposed as an ‘enzymatic latch’ to protect SOC by phenolic-containing organics in oxygen-limited ecosystems such as peatlands (Freeman et al., 2001). Because low phenol oxidase activity is conducive to the accumulation of soluble phenolics and inhibits the activity of hydrolytic enzymes, and thus benefits soil carbon sequestration (Zibilske and Bradford, 2007; Sinsabaugh, 2010), soil enzymatic reactions can regulate soil biochemical processes including LOCF formation and decomposition (Bowles et al., 2014). However, researches on soil enzymes in LOCF transformation mainly focused on forest and wetland ecosystems (Keeler et al., 2009; Weand et al., 2010), and the information in agro-ecosystems under straw mulch was still limited, particularly during crop growth. Therefore, study of the effects of specific crop straw practices on the dynamics of LOCF and C-cycle enzyme activities during crop growth is necessary, and understanding their relationship can explore the underlying mechanism of SOC transformation under straw mulch (Fansler et al., 2005; Morrissey et al., 2014). The straw average output reached 40 Mt y1 with the development of intensive agriculture on the Chengdu Plain in Sichuan, China. A lot of straw is burned directly and this has caused serious environmental pollution in the last decade (Xiao, 2012). Straw mulch is one practice for effective disposal that can decrease air pollution and provide SOC (Soon and Lupwayi, 2012). Consequently, a comprehensive understanding of the effects of straw mulch on LOCF change is critical for scientific management of crop straw use on the Chengdu plain. Therefore, this study was conducted to: (1) investigate the dynamic changes of LOCF concentrations and Ccycle enzyme activities during wheat growth; (2) examine the sensitivity of the LOCF as early indicators of SOC change; and (3) quantify the relationships of different LOCF and C-cycle enzymes under straw mulch. 2. Materials and methods 2.1. Experimental site and design The experiment was conducted from November 2012 to May 2013 in Dujiangyan (31560 N, 103 440 E, altitude 636.3 m) on the Chengdu Plain in Sichuan, China. The experimental area has a humid mid-subtropical monsoon climate with an average annual precipitation of 1200 mm and annual temperature of 15.8 C. Derived from gray alluvium of the Minjiang River, the soil at the experimental site is a typical Ferric-Accumulic Stagnic Anthrosol. The basic soil properties in the 0–40-cm layer before experiment establishment are given in Table 1.
Table 2 Experimental design and application rates of mineral fertilizers and rice straw. Treatments
Control MF RS1 RS2 RS3 RS
Chemical nutrient additions (kg ha1) N
P2 O 5
K2O
– 150.0 134.5 119.0 103.5 88.0
– 60.0 55.4 50.8 46.2 41.6
– 90.0 66.8 43.6 20.4 –
Rice straw (kg ha1)
– – 1840.0 3680.0 5520.0 7360.0
Control: no fertilizer and straw; MF: only mineral fertilizer; RS1: 10% rice straw N plus 90% fertilizer N; RS2: 20% rice straw N plus 80% fertilizer N; RS3: 30% rice straw N plus 70% fertilizer N; RS: 100% rice straw.
Six treatments were designed and are shown in Table 2: (1) no fertilizer or straw (Control); (2) only mineral fertilizer (MF); (3) 10% rice straw nitrogen (N) plus 90% fertilizer N (RS1); (4) 20% rice straw N plus 80% fertilizer N (RS2); (5) 30% rice straw N plus 70% fertilizer N (RS3); and (6) 100% rice straw (RS). The percentages of nitrogen in RS1, RS2 and RS3 treatments reflect the percent of total nitrogen that was applied in the mineral fertilizer treatment. All treatments (excluding the Control) had the same N, phosphorus (P) and potassium (K) application rates equivalent to 150 kg ha1 N, 60 kg ha1 P2O5, and 90 kg ha1 K2O, in which urea, superphosphate and potassium chloride were used, respectively. The C, N, P2O5 and K2O contents of the rice straw were 384.6, 8.4, 2.5 and 12.6 g kg1, respectively. The shortages of N, P and K in different straw treatments were complemented by the mineral fertilizers. The experiment had a completely randomized block design in triplicate with a plot size of 5 5 m, and the tested wheat variety was Neimai 836. For fertilization, N, P and K fertilizers were applied as base fertilizer before sowing; the rice straw in all straw treatments uniformly covered the soil surface after sowing. 2.2. Soil sampling Soil samples were collected from 0 to 20 and 20 to 40 cm soil layers in the pre-sowing (10 November 2012, PS), seedling (15 December 2012, SS), tillering (12 January 2013, TS), jointing (5 March 2013, JS), heading (13 April 2013, HS) and maturing (18 May 2013, MS) wheat growth stages. In each plot, five cores (each 2.5 cm diameter) were excavated randomly and mixed as a composite sample in each wheat growth stage. The composite samples were placed in plastic bags and transported to the laboratory. Some of the soil samples were stored at 4 C for determining LOCF concentrations and enzyme activities within 4 days, and the other samples were air-dried at room temperature and sieved to 2 mm for determining TOC and other basic soil properties (Table 1). 2.3. Soil analysis
Table 1 Basic soil properties in different soil layers at the start of the experiment. Soil properties
pH (soil:water, 1:2.5) Sand (%) Silt (%) Clay (%) Bulk density (g cm3) Organic carbon (g kg1) Total N (g kg1) Total P (g kg1) Total K (g kg1) Available P (mg kg1) Available K (mg kg1)
Soil layers (cm) 0–20
20–40
7.0 21.7 59.8 18.5 1.18 21.5 1.8 0.9 21.9 10.6 57.8
7.7 23.6 62.5 15.8 1.22 10.3 1.0 0.6 20.9 3.4 39.5
TOC was determined by the Walkley–Black method (Nelson and Sommers, 1996). WSOC was determined using a modification of the method described by Zhang et al. (2012). Briefly, WSOC was extracted from moist soil (5.0 g) with a 1:5 ratio of soil to deionized water at 25 C, and shaken for 30 min at a speed of 250 rpm. The samples were subsequently centrifuged for 10 min at 5000 rpm, after which the supernatant was filtered using a 0.45 mm membrane filter. The filtrate was measured by dichromate oxidation. The DOC was extracted by 1 M KCl solution, and other operations were consistent with the WSOC. MBC was determined according to the CHCl3 fumigation-extraction method (Vance et al., 1987). POXC was determined using a modification of the method described by Blair et al. (1995). Briefly, moist soil (5.0 g) was weighed into plastic screw-cap centrifuge tubes, and 50 mL of a
S. Li et al. / Soil & Tillage Research 155 (2016) 289–297
0.02 M KMnO4 solution were added to each tube. Blank samples (containing no soil) were also analyzed during each run. The centrifuge tubes were tightly sealed and tumbled for 1 h at 200 rpm on a 15-cm-radius tumbler. Subsequently, the tubes were centrifuged for 10 min at 4000 rpm, and the supernatant solutions were diluted by 1:250 with deionized water. The absorbance of the diluted samples and standards was measured at 565 nm. The change in KMnO4 concentration was used to estimate the amount of oxidized C (assuming that 1 mM of KMnO4 was consumed in the oxidation of 9 mg of C). Cellulase (EC 3.2.1.4) activity was determined by the method of Schinner and Von Mersi (1990). Moist soil (5.0 g) was incubated with 5 mL of 1% carboxymethyl-cellulose in 5 mL of 2 M acetate buffer (pH 5.5) at 37 C for 24 h. The filtrates of soil-substrate slurries were subject to color reaction and the produced Prussian
291
blue was analyzed colorimetrically at 690 nm. The cellulase activity is expressed as nmol g1 h1. b-glucosidase (EC 3.2.1.21) activity was estimated using the substrates p-nitrophenyl– b-glucopyranoside and measuring the absorbance of the pnitrophenol (Parham and Deng, 2000). Moist soil (1.0 g) was incubated with 1 mL of the appropriate substrate solution and 4 mL of 50 mM acetate buffer at 37 C for 1 h, then 1 mL of 0.5 M CaCl2 and 4 mL of 0.5 M NaOH were added to terminate the reaction, and the filtrates were analyzed colorimetrically at 410 nm. The b-glucosidase activity was expressed as mmol g1 h1. The activities of phenol oxidase (EC 1.10.3.2) and peroxidase (EC 1.11.1.7) were determined using the method described by Shi et al. (2006). Moist soil (0.5 g) was incubated with 1 mL of 10 mM LDOPA and 4 mL of 50 mM acetate buffer and incubated at room temperature with constant shaking for 1 h, as were triplicate no-
Table 3 Dynamic changes of soil labile organic carbon fractions during wheat growth. LOCF
Soil layers (cm)
Treatments
PS
SS
TS
JS
HS
MS
WSOC (mg kg1)
0–20
Control MF RS1 RS2 RS3 RS Control MF RS1 RS2 RS3 RS
25.98 1.73a 27.40 3.22a 28.55 1.23a 30.83 0.25a 27.10 4.89a 30.76 3.02a 15.73 1.35a 16.44 3.70a 17.44 0.46a 17.28 1.63a 15.37 1.12a 16.82 1.17a
32.94 4.82c 40.11 1.34b 45.15 5.88ab 49.67 1.99a 52.23 3.53a 47.42 4.45a 19.33 4.01a 21.76 4.40a 23.68 1.11a 25.94 11.73a 25.39 4.91a 26.68 7.72a
37.99 4.72d 45.26 1.48c 50.22 5.97bc 54.75 1.94ab 57.44 3.11a 52.53 4.83ab 21.58 3.59c 26.31 1.31bc 32.11 1.67ab 36.25 7.19a 37.64 7.12a 36.64 7.83a
38.92 4.29e 45.40 3.68d 66.44 3.89c 70.53 6.13bc 77.41 3.78ab 81.28 9.00a 24.98 4.99c 28.95 6.81c 40.07 4.03b 43.52 3.55ab 46.01 5.40ab 50.18 3.98a
36.06 4.98c 52.28 3.43b 62.20 3.64b 79.17 6.56a 83.55 12.96a 76.43 9.93a 17.21 2.30b 23.45 11.34ab 25.75 2.23a 27.25 3.62a 30.20 2.75a 30.44 3.39a
28.63 0.47c 36.44 11.09bc 41.46 4.95abc 49.45 9.15ab 53.31 11.24a 48.19 5.11ab 26.18 0.50c 36.53 10.96bc 40.76 0.48ab 45.43 11.25ab 50.69 3.41a 48.39 5.08a
Control MF RS1 RS2 RS3 RS Control MF RS1 RS2 RS3 RS
24.16 1.62a 22.29 3.02a 23.42 1.53a 25.54 0.30a 23.44 0.86a 24.26 4.49a 15.15 1.93a 15.26 3.48a 14.27 0.29a 16.57 0.25a 14.69 0.30a 15.13 4.58a
24.73 3.88a 27.58 4.08a 29.36 1.55a 31.67 11.55a 31.70 6.23a 32.38 7.89a 14.85 3.69a 17.53 4.06a 19.11 1.13a 21.63 11.28a 14.89 1.07a 22.35 7.86a
28.17 4.52c 35.30 1.25bc 41.72 4.86b 44.68 10.38ab 54.17 4.83a 43.51 4.36b 18.53 3.88d 26.23 1.34c 32.71 1.67b 37.65 2.13ab 38.20 3.84a 33.72 3.79ab
31.81 4.35b 31.44 3.03b 59.21 5.58a 62.11 5.14a 65.25 3.74a 67.52 7.41a 22.38 4.86b 22.97 3.04b 40.61 2.02a 42.70 5.61a 39.58 3.82a 43.27 7.57a
33.00 5.00c 45.55 10.63b 50.20 3.98a 55.07 6.88a 57.54 4.90a 53.72 3.81a 14.83 3.10c 21.62 11.03c 20.65 8.04c 45.78 3.77a 38.32 10.94ab 26.88 6.48bc
23.59 4.16b 29.48 11.02ab 34.67 5.13ab 48.90 15.85a 45.91 10.88a 34.76 6.53a 22.08 3.06b 28.91 11.13b 37.73 8.01ab 46.40 12.86a 50.73 8.99a 44.50 6.52a
Control MF RS1 RS2 RS3 RS Control MF RS1 RS2 RS3 RS
183.54 15.17a 183.43 13.25a 183.40 4.75a 184.74 8.53a 179.35 12.21a 181.21 10.58a 30.64 2.29a 30.63 2.57a 31.19 2.19a 30.74 2.07a 30.74 2.85a 30.21 1.72a
193.61 13.43b 197.27 13.43b 249.88 15.29a 251.15 21.75a 277.10 27.02a 264.57 25.61a 33.66 3.17c 39.20 4.05bc 47.31 7.43ab 49.62 6.89ab 50.02 7.93ab 52.69 6.52a
203.30 9.43b 209.02 23.44b 256.11 50.95a 282.15 16.69a 284.70 24.07a 298.53 5.86a 50.74 5.28c 55.38 5.27bc 63.61 6.56ab 68.55 12.63ab 73.85 10.90a 65.42 5.78ab
200.50 18.03b 214.35 13.99b 267.35 24.90a 276.63 20.04a 281.94 37.99a 280.04 39.57a 41.50 3.76d 49.35 3.92cd 56.41 6.95bc 64.14 7.30ab 70.68 7.23a 68.05 5.68a
230.42 25.86d 251.92 31.77cd 283.26 24.11bc 315.84 34.78ab 328.40 26.24ab 331.96 10.10a 47.27 5.09d 57.98 6.92cd 65.13 6.68bc 77.59 10.17ab 85.60 10.74a 81.63 5.51a
251.18 23.02d 277.55 11.91cd 301.19 23.79bc 325.41 19.20ab 339.48 23.12a 317.98 11.89ab 61.68 4.81c 71.02 5.27bc 76.53 5.29ab 80.16 11.94ab 88.42 10.36a 81.60 5.57ab
Control MF RS1 RS2 RS3 RS Control MF RS1 RS2 RS3 RS
1.05 0.06a 1.03 0.03a 1.01 0.05a 1.07 0.05a 1.06 0.05a 1.08 0.03a 0.47 0.04a 0.41 0.08a 0.52 0.10a 0.43 0.04a 0.52 0.34a 0.48 0.24a
0.98 0.05b 1.07 0.09ab 1.04 0.15b 1.02 0.08b 1.23 0.14a 1.22 0.03a 0.49 0.15a 0.61 0.06a 0.65 0.06a 0.58 0.06a 0.52 0.13a 0.62 0.45a
1.05 0.07b 1.05 0.06b 1.10 0.05b 1.21 0.02a 1.28 0.05a 1.21 0.07a 0.50 0.04b 0.53 0.03b 0.75 0.09a 0.58 0.09b 0.55 0.02b 0.69 0.04a
1.06 0.22a 1.20 0.23a 1.31 0.08a 1.22 0.05a 1.31 0.14a 1.23 0.03a 0.55 0.08b 0.58 0.03ab 0.64 0.02a 0.60 0.03ab 0.59 0.03ab 0.57 0.04ab
1.02 0.11b 1.15 0.10ab 1.21 0.07a 1.23 0.11a 1.30 0.11a 1.23 0.02a 0.67 0.17a 0.70 0.08a 0.83 0.06a 0.77 0.12a 0.75 0.11a 0.80 0.10a
1.09 0.01b 1.16 0.05ab 1.18 0.17ab 1.19 0.03ab 1.31 0.08a 1.30 0.09a 0.55 0.08d 0.60 0.03cd 0.77 0.04a 0.70 0.06ab 0.65 0.05bc 0.66 0.04bc
20–40
DOC (mg kg1)
0–20
20–40
MBC (mg kg1)
0–20
20–40
POXC (g kg1)
0–20
20–40
LOMF: labile organic carbon fractions; WSOC: water-soluble organic carbon; DOC: dissolved organic carbon; MBC: microbial biomass carbon; POXC: permanganate oxidized carbon. Control: no fertilizer and straw; MF: only mineral fertilizer; RS1: 10% rice straw N plus 90% fertilizer N; RS2: 20% rice straw N plus 80% fertilizer N; RS3: 30% rice straw N plus 70% fertilizer N; RS: 100% rice straw. PS: pre-sowing; SS: seedling stage; TS: tillering stage; JS: jointing stage; HS: heading stage; MS: maturing stage. Means standard errors (n = 3). Different letters in the same column indicate significant differences among treatments at P < 0.05.
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extracted with neutral 1 M NH4OAc (Hanway and Heidel, 1952) and estimated by a flame photometer. Soil bulk density was measured by the gravimetric method based on soil volume. Clay, sand, and silt contents were determined by the pipette method (Gee and Bauder, 1986). Soil pH was measured in distilled water at a soilsolution ratio of 1:2.5.
sample and no L-DOPA Controls. The reaction was terminated by centrifugation at 5000 rpm for 10 min, and the absorbance of the reaction product was measured at 460 nm. The wells used for peroxidase activities were the same except they received 10 mL of 0.3% H2O2, including the no-sample and no L-DOPA controls. Enzyme activities were expressed as mmol g1 h1. Total N was determined by the Kjeldahl method (Bremmer and Mulvaney, 1982). Total P was calcined and extracted by NaOH, then measured by the molybdenum antimony colorimetry method (Dick and Tabatabai, 1977). Total K was calcined and extracted by NaOH and measured using a flame photometer (Hanway and Heidel, 1952). Olsen-P was extracted with 0.5 M NaHCO3 (pH 8.5) as outlined by Olsen et al. (1954), and the P concentration in the extract was determined using ascorbic acid as a reducing agent and spectrophotometry (Watanabe and Olsen, 1965). Available K was
2.4. Statistical analysis SPSS version 17.0 for Windows was used for all statistical analysis. A one-way analysis of variance (ANOVA) was employed to determine the effects of straw mulch on the LOCF concentrations and enzyme activities, with separation of means by least significant difference (LSD). The general linear-regression analysis and stepwise regression analysis were applied to investigate the
5.0
Cellulase
0-20 cm 4.0
a b c c d d
3.0 2.0
a b c c d e
0-20 cm
2.0
ß-glucosidase
a ab bc bc cd d
a a b b c d
1.6
a ab bc cd d d
1.2 0.8
a a ab b
a a ab ab bc c
c c
20-40 cm
a 2.0 b bc 1.6 c d 1.2 e
a a a a a a
0.8
a a 0.6 ab b
a b b b b b
0.4
Polyphenol oxidase
0.3
0-20 cm
2.0
a b b c c c
1.6
a a ab b c d
1.2
0.8 10.5
a ab ab b b c
a ab ab bc c
Peroxidase
0-20 cm
a b b b c d
9.0 7.5
a b bc cd cd d
6.0 4.5
PS
SS
a ab bc cd cd d TS
a ab b c cd d JS
HS
MF
a ab ab ab b b
0.4 0.0 a 8.0 bc bc bc
b
a a ab bc bc c
a a ab bc c
d a aa b b b
4.0 2.0 PS
SS
a a a a b c
a a ab ab ab b
d
a a a a b b
a b b bc c d
a ab b c cd d
TS
a a b b c c
a b b bc c
20-40 cm
6.0
d
a ab b b c c
a b b b c c
a a b b b b JS
HS
MS
Wheat growth stages
Wheat growth stages Control
a a a aa
20-40 cm
a ab 1.2 bc cd de 0.8 e
MS
b c
20-40 cm
0.5
c c
a ab ab bc c c
a a a a ab b
a aa a
RS1
RS2
RS3
RS
Fig. 1. Dynamic changes of soil enzyme activities during wheat growth. Activity is reported in nmol g1 h1 for cellulase, and in mmol g1 h1 for b-glucosidase, polyphenol oxidase and peroxidase. Control, no fertilizer and straw; MF, only mineral fertilizer; RS1, 10% rice straw N plus 90% fertilizer N; RS2, 20% rice straw N plus 80% fertilizer N; RS3, 30% rice straw N plus 70% fertilizer N; RS, 100% rice straw. PS, pre-sowing; SS, seedling stage; TS, tillering stage; JS, jointing stage; HS, heading stage; MS, maturing stage. Different lowercase letters indicate significant differences among treatments in the same growth stage at P <0.05. Vertical bars denote the standard error of the mean (n = 3).
S. Li et al. / Soil & Tillage Research 155 (2016) 289–297
relationships between LOCF and C-cycle enzyme activities. All effects were considered significant at P < 0.05. 3. Results 3.1. Dynamics of soil labile organic carbon fractions 3.1.1. Water-soluble organic carbon Distinct differences in WSOC concentrations among different treatments in the 0–20 cm soil layer were observed during the wheat growth stages (Table 3). Generally, the WSOC concentrations of all treatments increased at first and then decreased. The maximum WSOC values of the treatments occurred at jointing for the Control, RS1 and RS, or at heading for the MF, RS2 and RS3. The WSOC concentrations for straw treatments except for RS1 in topsoil were significantly higher than those of the Control and MF treatments from seedling to heading (P < 0.05). In the 20–40 cm soil layer, the WSOC concentrations of straw treatments were also significantly higher than those of the Control from tillering to maturing (P < 0.05), but the WSOC among them displayed no significant differences (P > 0.05, Table 3). 3.1.2. Dissolved organic carbon As shown in Table 3, DOC concentrations in the two soil layers for all straw treatments increased with wheat growth up to jointing and then decreased. In general, straw treatments showed higher DOC concentrations than those of the Control (P < 0.05). The differences among treatments began at tillering and gradually increased with the progression of growth stages. At heading, the DOC concentrations for straw treatments in the 0–20 cm soil layer were 52.12–74.36% higher than those of the control, and 10.21–26.32% higher than those of the MF (P > 0.05). However, the concentrations among all straw treatments showed no obvious difference at the seedling stage (P > 0.05). 3.1.3. Microbial biomass carbon The MBC concentrations for different treatments showed increasing trends with wheat growth, reaching a maximum value at heading or maturing (Table 3). The MBC concentrations in the two soil layers for straw treatments were significantly higher than those of the Control after the seedling stage (P < 0.05). This was similar to the WSOC in the 0–20 cm soil layer. Moreover, the MBC concentrations of all straw treatments in the 0–20 cm soil layer were significantly higher than those of the MF treatment from seedling to jointing (P < 0.05), and there were no significant differences among them (P > 0.05), likely because straw input can stimulate microbial activity, thereby significantly increasing the MBC.
293
3.1.4. Permanganate oxidized organic carbon As shown in Table 3, although the POXC concentrations for all treatments in the 0–20 cm soil layer showed obvious dynamic changes with wheat growth, there were no significant differences among the treatments in the same growth stage (P > 0.05) except for the control. Similar results were observed in the 20–40 cm soil layer, except that the POXC concentrations of the RS1 treatment were significantly higher than those of other treatments at tillering and maturing (P < 0.05, Table 3). 3.2. Dynamics of soil C-cycle enzyme activities 3.2.1. Cellulase Cellulase activities for the four straw treatments in the 0–20 cm soil layer increased at first from pre-sowing to the seedling stage, subsequently reduced at tillering, and then rose to the maximum at jointing or maturing (Fig. 1). The enzyme activities for the four straw treatments in the 0–20 cm soil layer were significantly higher than those of the Control and MF treatment after the seedling stage (P < 0.05) except at tillering. Inconsistent results were observed in the 20–40 cm soil layer; the enzyme activities for all treatments continuously increased from the seedling stage to maturing (Fig. 1). 3.2.2. b-glucosidase b-glucosidase activities for the different treatments showed obvious diversities during all of the wheat growth stages in the different soil layers (Fig. 1). Generally, b-glucosidase activities in the 0–20 cm soil layer for all treatments continuously increased, and the diversities varied with the change of growth stage. The enzyme activities of straw treatments were significantly higher than those of the Control from tillering to maturing, and higher than those of the MF treatment after heading (P < 0.05). However, the b-glucosidase activities only for RS2 and RS3 treatments in the 20–40 cm soil layer were significantly higher than those of the Control and MF at jointing and heading (P < 0.05). 3.2.3. Polyphenol oxidase Changes of polyphenol oxidase activities for all treatments showed similar trends during all growth stages at 0–40 cm (Fig. 1). In the 0–20 cm soil layer, the polyphenol oxidase activities of the four straw treatments were significantly higher than those of the Control from the seedling stage to maturing, and of the MF at jointing (P < 0.05). The highest activities among the four straw treatments were in the RS1 treatment in the 0–20 cm soil layer after jointing and in the RS3 treatment in the 20–40 cm soil layer after tillering.
Table 4 Dynamic changes of total soil organic carbon (g kg1) during wheat growth. Soil layers (cm)
Treatments
PS
SS
TS
JS
HS
MS
0–20
Control MF RS1 RS2 RS3 RS
21.54 0.05 a 21.55 0.14 a 21.56 0.05 a 21.52 0.10 a 21.53 0.01 a 21.55 0.06 a
21.54 0.01 a 21.55 0.05 a 21.55 0.07 a 21.57 0.03 a 21.56 0.06 a 21.57 0.08 a
21.55 0.07 21.55 0.07 21.58 0.05 21.60 0.09 21.62 0.04 21.61 0.04
a a a a a a
21.56 0.10 a 21.55 0.27 a 21.61 0.02 a 21.62 0.18 a 21.64 0.15 a 21.62 0.09 a
21.56 0.07 a 21.55 0.01 a 21.62 0.06 a 21.63 0.03 a 21.65 0.05 a 21.63 0.10 a
21.58 0.06 21.58 0.07 21.65 0.06 21.65 0.06 21.67 0.03 21.64 0.02
a a a a a a
20–40
Control MF RS1 RS2 RS3 RS
10.26 0.02 10.27 0.07 10.28 0.04 10.26 0.05 10.26 0.08 10.27 0.04
10.26 0.00 a 10.27 0.03 a 10.28 0.05 a 10.27 0.01 a 10.26 0.05 a 10.27 0.04 a
10.26 0.03 10.27 0.04 10.29 0.07 10.29 0.03 10.30 0.04 10.31 0.06
a a a a a a
10.28 0.09 a 10.28 0.06 a 10.31 0.09 a 10.33 0.09 a 10.34 0.07 a 10.33 0.03 a
10.29 0.05 10.28 0.06 10.32 0.01 10.33 0.04 10.35 0.03 10.34 0.02
10.29 0.02 10.30 0.01 10.33 0.05 10.34 0.06 10.35 0.04 10.35 0.05
a a a a a a
a a a a a a
a a a a a a
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showed no significant differences during wheat growth stages in the present study (P > 0.05, Table 4). This result was similar to those obtained in previous studies where TOC was insensitive to recent management practices (Mendham et al., 2002; Shafi et al., 2007; Xu et al., 2011). However, some labile carbon fractions including WSOC, DOC and MBC were sensitive to straw mulch in some growth stages because their concentrations between Control and straw treatments showed significant differences (P < 0.05, Table 3). For example, the WSOC concentrations of straw treatments except for RS1 were significantly higher than those of the Control and MF from the seedling stage to heading in the 0–20 cm soil layer (P < 0.05); the DOC were significantly higher than those of the Control after tillering (P < 0.05) and the MBC was significantly higher than those of the Control from the seedling to jointing stage (P < 0.05). Straw mulch could stimulate microorganisms and might produce more WSOC, DOC and MBC, so the net effect could consequently be predicted in the short term (Soon and Lupwayi, 2012). As a result, WSOC, DOC and MBC could be considered as sensitive indicators to straw mulch. However, the POXCs among fertilizer treatments showed no significant differences because of the relatively higher proportions of TOC (3.99–8.04%) in most of the growth stages (Blair et al., 1995; Bell et al., 1998), and it was unsuitable as an early indicator of TOC change under straw mulch. Change extents for each fraction also showed differences in various wheat stages in this study (Table 3). In the 0–20 cm soil layer, the differences of WSOC and MBC among different treatments were observed from the seedling stage, while DOC were observed from the tillering stage (P < 0.05). This indicated that the former two fractions can have faster responses to straw mulch than DOC. Meanwhile, the WSOC concentrations of all straw treatments in the 0–0 cm soil layer were 70.71–108.84% higher than those of the Control at the jointing stage, and the MBC concentrations were
3.2.4. Peroxidase Peroxidase activities for all treatments in the 0–20 cm soil layer decreased first and then increased, and gradually showed obvious differences among the treatments (Fig. 1). From the seedling stage to jointing, the enzyme activities of the MF treatment in the 0– 20 cm soil layer were significantly higher than those of the other treatments except for RS1 and RS2 (P < 0.05). However, the peroxidase activities of the RS2 treatment increased significantly after heading, and they were significantly higher than those of the Control and MF (P < 0.05). The enzyme activities in the 20–40 cm soil layer showed obviously different trends of change than those in the 0–20 cm soil layer (Fig. 1). 4. Discussion 4.1. Sensitivity of labile organic carbon fractions to straw mulch Soil labile organic carbon fractions have greater turnover rates, so their concentration changes can be easily detected in the shortand medium-terms (Haynes, 2005), although they only have a small proportion of TOC (McLauchlan and Hobbie, 2004). Many researchers thought that LOCF were sensitive indicators of changes in soil quality (Zagal et al., 2009; Banger et al., 2010), but many argue otherwise (Whitbread et al., 2003; Yan et al., 2007; Nayak et al., 2012). Therefore, it is necessary to examine whether LOCF are sensitive to straw mulch. In the present study, we will discuss the sensitivity of the LOCF from the concentration differences among treatments, change extents and correlations with TOC. The differences of LOCF concentrations among various treatments could be used to evaluate their sensitivity for agricultural management practices (Purakayastha et al., 2008; Xu et al., 2011). TOC concentrations between control and fertilizer treatments
Table 5 Correlation coefficients of soil labile organic carbon fractions and total organic carbon in different wheat growth stages. LOCF
0–20 cm
20–40 cm
TOC
WSOC
DOC
SS WSOC DOC MBC POXC
0.489* 0.458* 0.545* 0.410
1 0.726** 0.708** 0.643**
1 0.653** 0.492*
TS WSOC DOC MBC POXC
0.535* 0.488* 0.507* 0.488*
1 0.927** 0.660** 0.849**
1 0.632** 0.835**
JS WSOC DOC MBC POXC
0.678** 0.590* 0.589* 0.499*
1 0.981** 0.775** 0.832**
1 0.680** 0.827**
HS WSOC DOC MBC POXC
0.701** 0.592** 0.566* 0.546*
1 0.895** 0.837** 0.898**
1 0.715** 0.933**
MS WSOC DOC MBC POXC
0.703** 0.693** 0.661** 0.544*
1 0.916** 0.662** 0.771**
1 0.694** 0.594**
MBC
1 0.656**
1 0.727**
1 0.916**
1 0.850**
1 0.806**
POXC
TOC
WSOC
DOC
MBC
POXC
1
0.454* 0.451* 0.463* 0.480*
1 0.657** 0.544* 0.517*
1 0.496* 0.507*
1 0.586*
1
1
0.522* 0.559* 0.540* 0.539*
1 0.849** 0.559* 0.579*
1 0.774** 0.612**
1 0.661**
1
1
0.676** 0.650** 0.615** 0.559*
1 0.881** 0.814** 0.614**
1 0.760** 0.495*
1 0.622**
1
1
0.604** 0.575* 0.488* 0.538*
1 0.712** 0.677* 0.642**
1 0.587* 0.604**
1 0.669**
1
1
0.642** 0.597** 0.553* 0.510*
1 0.939** 0.683** 0.604**
1 0.663** 0.550*
1 0.635**
1
LOCF: labile organic carbon fractions; WSOC: water-soluble organic carbon; DOC: dissolved organic carbon; MBC: microbial biomass carbon; POXC: permanganate oxidized carbon; TOC: total soil organic carbon. SS: seedling stage; TS: tillering stage; JS: jointing stage; HS: heading stage; MS: maturing stage. * Correlation is significant at the 0.05 level. ** Correlation is significant at the 0.01 level.
S. Li et al. / Soil & Tillage Research 155 (2016) 289–297
22.93–44.07% higher than those of the Control at the heading stage (Table 3); however, their concentrations of all straw treatments (except for the WSOC of RS3) in the 0–20 cm soil layer showed no significant differences compared with the MF treatment at the maturing stage (Table 3, P > 0.05). Therefore, different sampling times may exhibit various results, indicating that the diverse effects of straw practices on WSOC may be caused by the inconsistent sampling time (Dolan et al., 2006; Malhi et al., 2011; Xu et al., 2011). Moreover, WSOC and MBC had higher mean proportions of TOC (0.13–0.39% and 0.83–1.57%, respectively) under straw treatments than those of the control (0.12–0.18% and 0.85–1.16%, respectively) in the 0–20 cm soil layer. Some researchers thought that the MBC relative amount of TOC was a useful assessment index for soil quality (Anderson and Domsch 1989; Sparling, 1992). Consequently, it was noteworthy that WSOC and MBC were sensitive to assess the effects of straw mulch on soil quality. Correlation analysis showed that WSOC and MBC had higher coefficients with TOC than other fractions in the 0–20 cm soil layer in most of growth stages (Table 5). Moreover, they were significantly correlated with other fractions (P < 0.05, Table 5). Some researchers suggested that the representative levels of LOCF to TOC should directly relate to their correlations with TOC (Dou et al., 2008; Moharana et al., 2012). Generally, these results indicated that different straw treatments showed significantly positive or no obvious effects on LOCF in various wheat growth stages, and the WSOC and MBC were the most sensitive to straw mulch in the 0–20 cm soil layer at the jointing and heading stage, respectively. 4.2. Relationships of SOC labile fractions and soil C-cycle enzyme activities A series of soil enzymes catalyze the decomposition and composition of SOC, thereby affecting the different SOC fractions (Sinsabaugh, 2010). To better understand the change characteristics of LOCF, it is necessary to observe the relationships of LOCF with C-cycle enzyme activities. 4.2.1. Relationship of SOC labile fractions with single soil C-cycle enzyme activities Soil C-cycle enzymes produced by microbes are directly involved in SOC transformations (Fansler et al., 2005; Shi et al., 2006), and each enzyme has its own substrate and ability to catalyze specific biochemical reactions (Salazar et al., 2011). In this study, cellulase and b-glucosidase activities were positively correlated with the LOCF (P < 0.05, Table 6). In general, cellulase and b-glucosidase can break celluloses down to form labile organic carbon (Wickings et al., 2012). Similar positive relationships were also reported by Wang et al. (2013) and Liang et al. (2014). However, the WSOC and DOC showed no obvious correlation with polyphenol oxidase in the 0–20 cm soil layer, and with peroxidase
295
in the 20–40 cm soil layer (P > 0.05, Table 6). This may be because the two fractions were probably both substrates and products of enzymic reactions (Bonnett et al., 2006), and the decomposition rate of hydrolytic enzymes is greater than the oxidation rate of oxidase. Moreover, the significantly positive correlation between MBC and enzyme activities indicated that soil microorganisms were the major source of soil enzymes. Thus, high biomass turnover could increase microbial biomass and enzyme activities, resulting in a directly positive relationship between MBC and enzyme activities (He et al., 2003; Sotomayor-Ramírez et al., 2009). In addition, the POXC was more weakly correlated with hydrolase activities than WSOC and DOC (Table 6). This was probably attributed to the easily oxidizable nature of POXC, and thus it was a common substrate for soil enzymes' hydrolysis and oxidation reaction (Wang et al., 2013). 4.2.2. Relationship of SOC labile fractions with multiple soil C-cycle enzyme activities To further understand the roles of different C-cycle enzymes in the SOC transformation process under straw mulch, stepwise multiple linear regression was used to analyze the major and minor effects of C-cycle enzymes on the LOCF. As shown in Table 7, the explained variance of the limited models ranged from 0.250 to 0.668 for the LOCF. The cellulase and b-glucosidase were significantly positive impact factors for WSOC and DOC in the two soil layers (P < 0.05), further indicating that the two enzymes were mainly to promote the formation of labile organic carbon, thereby they may increase the loss of SOC mineralization (Waldrop and Zak, 2006). Cellulase was a positive impact factor for POXC in the two soil layers (P < 0.05), indicating that POXC may contain the organics that were decomposed by cellulase catalysis (Wang et al., 2013). Soil oxidases have also been documented as the important regulator for SOC decomposition (Grandy et al., 2008). As has been observed in peatlands, an oxidative ‘enzymatic latch mechanism’ was used to elucidate SOC sequestration in oxygen-limited conditions where low phenol oxidase activity slows down degradation of phenolic compounds (Freeman et al., 2001). The phenolic toxicity to hydrolytic enzymes, and phenolic accumulation within soil solution could inhibit SOC hydrolysis, thereby leading to accumulation of low molecular weight compounds, i.e., soluble organic carbon (Freeman et al., 2004; Grandy et al., 2007). However, polyphenol oxidase was the negative impact factor for WSOC in the 0–20 cm soil layer in this study (Table 7). This was contradictory to the results of previous studies from wetlands or turf ecosystems (Freeman et al., 2004; Yao et al., 2012), probably because the oxygen supply is more adequate in cultivated surface soil. Therefore, the oxidative enzymes will oxidize soluble phenolic compounds into quinones, thereby promoting humification (Sinsabaugh, 2010; Burns et al., 2013). In contrast, polyphenol oxidase was the positive impact factor for WSOC in the 20–40 cm soil layer (Table 6). One possible explanation for this correlation
Table 6 Correlation coefficients of soil labile organic carbon fractions and C-cycle enzymes. LOCF
WSOC DOC MBC POXC
0–20 cm
20–40 cm
Cellulase
b-glucosidase
Polyphenol oxidase
Peroxidase
Cellulase
b-glucosidase
Polyphenol oxidase
Peroxidase
0.467** 0.594** 0.728** 0.441**
0.512** 0.519** 0.771** 0.563**
0.000 0.037 0.443** 0.169
0.267** 0.296** 0.513** 0.350**
0.496** 0.522** 0.642** 0.298**
0.492** 0.529** 0.462** 0.102
0.553** 0.577** 0.584** 0.119
0.011 0.183 0.357** 0.206*
LOCF: labile organic carbon fractions; WSOC: water-soluble organic carbon; DOC: dissolved organic carbon; MBC: microbial biomass carbon; POXC: permanganate oxidized carbon. * Correlation is significant at the 0.05 level. ** Correlation is significant at the 0.01 level.
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Table 7 Stepwise multiple regression analysis of the relationships between soil C-cycle enzymes and labile organic carbon fractions. Soil layers (cm)
LOCF
Models
R2
P
0–20
WSOC DOC MBC POXC
Y = 44.108 + 12.181 X1 + 18.881 X2 40.45 X3 Y = 34.839 + 7.011 X1 + 21.189 X2 32.212 X3 Y = 153.342 + 20.124 X1 + 100.549 X2 11.588 X4 Y = 0.915 + 0.082 X1
0.642 0.530 0.668 0.317
0.000 0.000 0.000 0.000
20–40
WSOC DOC MBC POXC
Y = 7.129 + 59.927 X2 + 19.104 X3 3.300 X4 Y = 2.586 + 59.875 X2 + 18.206 X3 1.611 X4 Y = 11.298 + 36.839 X1 Y = 0.194 + 0.616 X1 0.511 X3
0.476 0.401 0.412 0.250
0.000 0.000 0.000 0.000
LOCF: labile soil organic carbon fractions; WSOC: water-soluble organic carbon; DOC: dissolved organic carbon; MBC: microbial biomass carbon; POXC: permanganate oxidized carbon. Y, LOCF; X2, cellulase; X1, b-glucosidase; X3, polyphenol oxidase; X4, peroxidase.
would be a higher moisture and density in this soil layer, and thus the oxygen condition would be similar to wetland and turf ecosystems.. Therefore, the ‘enzymatic latch mechanism’ uncovered from peatlands may also be applicable to cultivated subsurface soils (Zibilske and Bradford, 2007). With respect to peroxidase, it was a negative factor for a few fractions in the 0–20 or 20–40 cm soil layer (Table 7). This is probably attributed to its necessary conditions of enzymatic reactions that are different to polyphenol oxidase, and it stimulates the oxidation of labile organic carbon. Overall, the present results suggested that cellulase and b-glucosidase were positive impact factors for the formation of labile organics, and polyphenol oxidase activities could contribute either positive or negative impacts for WSOC accumulation under the different environmental conditions of soil. 5. Conclusions Straw mulch showed significantly positive or no obvious effects on LOCF in the 0–20 cm soil layer at various wheat growth stages. The differences of WSOC and MBC concentration among treatments began in the seedling stage, and the greatest change extents of the two fractions were observed at the jointing and heading stage, respectively. However, DOCs among treatments began to show differences at the tillering stage, and POXCs showed no obvious differences in most of the growth stages. Moreover, WSOC and MBC had higher coefficients with TOC than the latter two fractions in most of the growth stages. These results indicated that different sampling times may exhibit various results, and the WSOC and MBC were the most sensitive to straw mulch that can be used as early indicators of SOC change. SOC transformation was strongly correlated with C-cycle enzyme activities. Cellulase and b-glucosidase were positive impact factors for LOCF, while polyphenol oxidase could contribute either positive or negative impacts for WSOC in different soil depths, and peroxidase was a negative factor for LOCF. It was concluded that cellulase and b-glucosidase were positive impact factors for the formation of labile organics, and polyphenol oxidase was conducive to SOC decomposition or humification under the different soil environmental conditions, and peroxidase would always promote LOCF oxidation. Acknowledgments This study was supported by the Projects of National Sci-tech Support, China (No. 2012BAD14B18-2), and Sichuan Sci-tech Support, China (No. 2014NZ0044). We thank Yalin Huang, Guiyin Wang, Xia Li, Ping Yao, Luoyi Xiao and Chuer Zhang of Sichuan Agricultural University, for assistance in the field and laboratory analyses.
References Alvarez, S., Guerrero, M.C., 2000. Enzymatic activities associated with decomposition of particulate organic matter in two shallow ponds. Soil Biol. Biochem. 32, 1941–1951. Anderson, T.H., Domsch, K.H., 1989. Ratios of microbial biomass carbon to total organic carbon in arable soils. Soil Biol. Biochem. 21, 471–479. Bakht, J., Shafi, M., Jan, M.T., Shah, Z., 2009. Influence of crop residue management, cropping system and N fertilizer on soil N and C dynamics and sustainable wheat (Triticum aestivum L.) production. Soil Tillage Res. 104, 233–240. Banger, K., Toor, G.S., Biswas, A., Sidhu, S.S., Sudhir, K., 2010. Soil organic carbon fractions after 16-years of applications of fertilizers and organic manure in a Typic Rhodalfs in semi-arid tropics. Nutr. Cycl. Agroecosyst. 86, 391–399. Bell, M.J., Moody, P.W., Connolly, R.D., Bridge, B.J., 1998. The role of active fractions of soil organic matter in physical and chemical fertility of Ferrosols. Aust. J. Soil Res. 36, 809–819. Bhattacharyya, R., Kundu, S., Srivastva, A.K., Gupta, H.S., Prakash, V., Bhatt, J.C., 2011. Long term fertilization effects on soil organic carbon pools in a sandy loam soil of the Indian sub-Himalayas. Plant Soil 341, 109–124. 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 systems. Aust. J. Agric. Res. 46, 1459–1466. Bonnett, S.A.F., Ostle, N., Freeman, C., 2006. Seasonal variations in decomposition processes in a valley-bottom riparian peatland. Sci. Total Environ. 370, 561–573. Bowles, T.M., Acosta-Martínez, V., Calderón, F., Jackso, L.E., 2014. Soil enzyme activities, microbial communities, and carbon and nitrogen availability in organic agroecosystems across an intensively-managed agricultural landscape. Soil Biol. Biochem. 68, 252–262. Bremmer, J.M., Mulvaney, C.S., 1982. Nitrogen: total. In: Page, A.L., Miller, R.H., Keeney, D.R. (Eds.), Methods of Soil Analysis, Part 2. Chemical and Microbiological Properties. American Society of Agronomy and Soil Science Society of America, Madison, WI, pp. 595–641. Burns, R.G., DeForest, J.L., Marxsen, J., Sinsabaugh, R.L., Stromberger, M.E., Wallenstein, M.D., Weintraub, M.N., Zoppini, A., 2013. Soil enzymes in a changing environment: current knowledge and future directions. Soil Biol. Biochem. 58, 216–234. Dick, W.A., Tabatabai, M.A., 1977. An alkaline oxidation method for determination of total phosphorus in soils. Soil Sci. Soc. Am. J. 41, 511–514. Dolan, M.S., Clapp, C.E., Allmaras, R.R., Baker, J.M., Molina, J.A.E., 2006. Soil organic carbon and nitrogen in a Minnesota soil as related to tillage, residue and nitrogen management. Soil Tillage Res. 89, 221–231. Dou, F.G., Wright, A.L., Hons, F.M., 2008. Sensitivity of labile soil organic carbon to tillage in wheat-based cropping systems. Soil Sci. Soc. Am. J. 72, 1445–1453. Fansler, S.J., Smith, J.L., Bolton, H., Baily, V.L., 2005. Distribution of two C cycle enzymes in soil aggregates of a prairie. Biol. Fert. Soils 42, 17–23. Freeman, C., Ostle, N.J., Kang, H., 2001. An enzymic ‘latch’ on a global carbon store—a shortage of oxygen locks up carbon in peatlands by restraining a single enzyme. Nature 409, 149. Freeman, C., Ostle, N.J., Fenner, N., Kang, H., 2004. A regulatory role for phenol oxidase during decomposition in peatland. Soil Biol. Biochem. 36, 1663–1667. Gee, G.W., Bauder, J.W., 1986. Particle-size analysis. In: Black, W.C. (Ed.), Methods of Soil Analysis, Part 1 Physical and mineralogical properties, including statistics and sampling. American Society of Agronomy, Madison, WI, pp. 398-–406. Gong, W., Yan, X.Y., Wang, J.Y., Hu, T.X., Gong, Y.B., 2009. Long-term manuring and fertilization effects on soil organic carbon pools under a wheat-maize cropping system in North China Plain. Plant Soil 314, 67–76. Grandy, A.S., Neff, J.C., Weintraub, M.N., 2007. Carbon structure and enzyme activities in alpine and forest ecosystems. Soil Biol. Biochem. 39, 2701–2711. Grandy, A.S., Sinsabaugh, R.L., Neff, J.C., Stursova, M., Zak, D.R., 2008. Nitrogen deposition effects on soil organic matter chemistry are linked to variation in enzymes, ecosystems and size fractions. Biogeochemistry 9, 37–49. Grandy, A.S., Strickland, M.S., Lauber, C.L., Bradford, M.A., Fierer, N., 2009. The influence of microbial communities, management, and soil texture on soil organic matter chemistry. Geoderma 150, 278–286. Hanway, J.J., Heidel, H., 1952. Soil analysis methods as used in Iowa State College Soil Testing Laboratory. Iowa Agric. 57, 1–31.
S. Li et al. / Soil & Tillage Research 155 (2016) 289–297 Haynes, R.J., 2005. Labile organic matter fractions as central components of the quality of agricultural soils: an overview. Adv. Agron. 85, 221–268. He, Z.L., Yang, X.E., Baligar, V.C., Calvert, D.V., 2003. Microbiological and biochemical indexing systems for assessing acid soil quality. Adv. Agron. 78, 89–138. Keeler, B.L., Hobbie, S.E., Kellogg, L.E., 2009. Effects of long-term N addition on microbial enzyme activity in eight forested and grassland sites: Implications for litter and soil organic matter decomposition. Ecosystems 12, 1–15. Liang, Q., Gao, R.T., Xi, B.D., Zhang, Y., Zhang, H., 2014. Long-term effects of irrigation using water from the river receiving treated industrial wastewater on soil organic carbon fractions and enzyme activities. Agric. Water Manag. 135, 100– 108. Loveland, P., Webb, J., 2003. Is there a critical level of organic matter in the agricultural soils of temperate regions: a review. Soil Tillage Res. 70 (1), 1–18. Ma, C., Zhou, J., Liu, M.Q., Zheng, X.B., Cui, J., Li, H.X., Kang, B.L., 2013. Effects of incorporation of pre-treated straws into field on soil nutrients and labile organic carbon in lime concretion black soil. Acta Pedol. Sin. 50, 70–76. Malhi, S.S., Nyborg, M., Solberg, E.D., McConkey, B., Dyck, M., Puurveen, D., 2011. Long-term straw management and N fertilizer rate effects on quantity and quality of organic C and N and some chemical properties in two contrasting soils in Western Canada. Biol. Fert. Soils 47, 785–800. McLauchlan, K.K., Hobbie, S.E., 2004. Comparison of labile soil organic matter fractionation techniques. Soil Sci. Soc. Am. J. 68, 1616–1625. Mendham, D.S., Samarian, K.V., O’Connell, A.M., Grove, T.S., 2002. Eucalyptus globulusharvest residue management effects on soil carbon and microbial biomass at 1 and 5 years after plantation establishment. Soil Biol. Biochem. 34, 1903–1912. Moharana, P.C., Sharma, B.M., Biswas, D.R., Dwivedi, B.S., Singh, R.V., 2012. Longterm effect of nutrient management on soil fertility and soil organic carbon pools under a 6-year-old pearl millet-wheat cropping system in an Inceptisol of subtropical India. Field Crops Res. 136, 32–41. Morrissey, E.M., Berrier, D.J., Neubauer, S.C., Franklin, R.B., 2014. Using microbial communities and extracellular enzymes to link soil organic matter characteristics to greenhouse gas production in a tidal freshwater wetland. Biogeochemistry 117, 473–490. Nayak, A.K., Gangwar, B., Shukla, A.K., Mazumdar, S.P., Kumar, A., Kumar, V., Rai, P.K., Mohan, U., 2012. Long-term effect of different integrated nutrient management on soil organic carbon and its fractions and sustainability of rice-wheat system in Indo Gangetic Plains of India. Field Crops Res. 127, 129–139. Nelson, D.W., Sommers, L.E., 1996. Total carbon, organic carbon, and organic matter: laboratory methods. In: Barteles, J.M., Bigham, J.M. (Eds.), Methods of Soil Analysis, Part 3 Chemical Methods. American Society of Agronomy and Soil Science Society of America, Madison, WI, pp. 961–1010. Olsen, S.R., Cole, C.V., Watanabe, F.S., Dean, L.A., 1954. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate. US Dept. of Agriculture circular No. 939, Washington, pp. 1–19. Parham, J.A., Deng, S.P., 2000. Detection, quantification and characterization of b-glucosaminidase activity in soil. Soil Biol. Biochem. 32, 1183–1190. Plaza-Bonilla, D., Álvaro-Fuentes, J., Cantero-Martínez, C., 2014. Identifying soil organic carbon fractions sensitive to agricultural management practices. Soil Till. Res. 139, 19–22. Purakayastha, T.J., Rudrappa, L., Singh, D., Swarup, A., Bhadraray, S., 2008. Long-term impact of fertilizers on soil organic carbon pools and sequestration rates in maize–wheat–cowpea cropping system. Geoderma 144, 370–378. Salazar, S., Sánchez, L.E., Alvarez, J., Valverde, A., Galindo, P., Igual, J.M., Peixa, A., Santa-Regina, I., 2011. Correlation among soil enzyme activities under different forest system management practices. Ecol. Eng. 37, 1123–1131.
297
Schinner, F., Von Mersi, W., 1990. Xylanase-, CM-cellulase- and invertase activity in soil: an improved method. Soil Biol. Biochem. 22, 511–515. Shafi, M., Bakht, J., Jan, M.T., Shah, Z., 2007. Soil C and N dynamics and maize (Zea mays) yield as affected by cropping systems and residue management in Northwestern Pakistan. Soil Tillage Res. 94, 520–529. Shi, W., Dell, E., Bowman, D., Iyyemperumal, K., 2006. Soil enzyme activities and organic matter composition in a turfgrass chronosequence. Plant Soil 288, 285– 296. Sinsabaugh, R.S., 1994. Enzymic analysis of microbial pattern and process. Biol. Fert. Soils 17, 69–74. Sinsabaugh, R.L., 2010. Phenol oxidase, peroxidase and organic matter dynamics of soil. Soil Biol. Biochem. 42, 391–404. Soon, Y.K., Lupwayi, N.Z., 2012. Straw management in a cold semi-arid region: impact on soil quality and crop productivity. Field Crops Res. 139, 39–46. Sotomayor-Ramírez, D., Espinoza, Y., Acosta-Martínez, V., 2009. Land use effects on microbial biomass C, b-glucosidase and b-glucosaminidase activities, and availability, storage, and age of organic C in soil. Biol. Fert. Soils 45, 487–497. Sparling, G., Schipper, L., 2004. Soil quality monitoring in New Zealand: trends and issues arising from a broad-scale survey. Agric. Ecosyst. Environ. 104, 545–552. Sparling, G.P., 1992. Ratio of microbial biomass to soil organic carbon as a sensitive indicator of changes in soil organic matter. Aust. J. Soil Res. 30, 195–207. Vance, E.D., Brookes, P.C., Jenkinson, D.S., 1987. An extraction method for measuring soil microbial biomass-C. Soil Biol. Biochem. 19, 703–707. Waldrop, M.P., Zak, D.R., 2006. Response of oxidative enzyme activities to nitrogen deposition effects soil concentrations of dissolved organic carbon. Ecosystems 9, 921–933. Wang, Q.K., Xiao, F.M., He, T.X., Wang, S.L., 2013. Responses of labile soil organic carbon and enzyme activity in mineral soils to forest conversion in the subtropics. Ann. For. Sci. 70, 579–587. Watanabe, F.S., Olsen, S.R., 1965. Test of an ascorbic acid method for determining phosphorus in water and NaHCO3 extracts from soils. Soil Sci. Soc. Am. J. 29, 677–678. Weand, M.P., Arthur, M.A., Lovett, G.M., McCulley, R.L., Weathers, K.C., 2010. Effects of tree species and N additions on forest floor microbial communities and extracellular enzyme activities. Soil Biol. Biochem. 42, 2161–2173. Whitbread, A., Blair, G., Konboon, Y., Lefroy, R., Naklang, K., 2003. Managing crop residues, fertilizers and leaf litters to improve soil C, nutrient balances, and the grain yield of rice and wheat cropping systems in Thailand and Australia. Agric. Ecosyst. Environ. 100, 251–263. Wickings, K., Grandy, A.S., Reed, S.C., Cleveland, C.C., 2012. The origin of litter chemical complexity during decomposition. Ecol. Lett. 15, 1180–1188. Xiao, Y., 2012. The analysis of straw burning and use. J. Green Sci. Tecnol. 11, 72–74. Xu, M.G., Lou, Y.L., Sun, X.L., Wang, W., Baniyamuddin, M., Zhao, K., 2011. Soil organic carbon active fractions as early indicators for total carbon change under straw incorporation. Biol. Fert. Soils 47, 745–752. Yan, D.Z., Wang, D.J., Yang, L.Z., 2007. Long-term effect of chemical fertilizer, straw, and manure on labile organic matter fractions in a paddy soil. Biol. Fert. Soils 44, 93–101. Yao, H.Y., Bowman, D., Rufty, T., Shi, W., 2012. Interactions between N fertilization, grass clipping addition and pH in turf ecosystems: Implications for soil enzyme activities and organic matter decomposition. Soil Biol. Biochem. 41, 1425–1432. Zagal, E., Muñoz, C., Quiroz, M., Córdova, C., 2009. Sensitivity of early indicators for evaluating quality changes in soil organic matter. Geoderma 151, 191–198. Zhang, S.R., Wen, J., Li, T., Xu, X.X., Deng, L.J., Gong, G.S., Hu, C., 2012. Soil carbon fractions of restored lands in Liusha River Valley, Sichuan. Ecol. Eng. 40, 27–36. Zibilske, L.M., Bradford, J.M., 2007. Oxygen effects on carbon, polyphenols, and nitrogen mineralization potential in soil. Soil Sci. Soc. Am. J. 71, 133–139.
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Dynamics of soil labile organic carbon fractions and C-cycle enzyme activities under straw mulch in Chengdu Plain Sen Lia,b , Shirong Zhanga,* , Yulin Pua , Ting Lia , Xiaoxun Xua , Yongxia Jiaa , Ouping Denga , Guoshu Gongc a b c
College of Resources and Environment, Sichuan Agricultural University, Wenjiang 611130, PR China Institute of Ecology and Environment, Sichuan Agricultural University, Wenjiang 611130, PR China Agricultural College, Sichuan Agricultural University, Wenjiang 611130, PR China
A R T I C L E I N F O
A B S T R A C T
Article history: Received 30 November 2014 Received in revised form 8 July 2015 Accepted 22 July 2015
Soil labile organic carbon fractions (LOCF) are valuable indicators of changes in soil quality and soil total organic carbon (TOC), and they are easily influenced by changes in soil management practice. To explore the sensitivity of LOCF and their enzymatic conversion under straw mulch for scientific management of crop straw use on the Chengdu plain, a straw mulch field experiment was conducted to observe the LOCF changes and explore their relationships with C-cycle enzymes during wheat growth. The treatments included no fertilizer or straw (Control), only mineral fertilizer (MF), 10% rice straw nitrogen (N) plus 90% fertilizer N (RS1), 20% rice straw N plus 80% fertilizer N (RS2), 30% rice straw N plus 70% fertilizer N (RS3), 100% rice straw (RS). The water-soluble organic carbon (WSOC) and microbial biomass carbon (MBC) under straw treatments in the 0–20 cm soil layer were significantly higher than those of Control and MF treatments from the seedling stage, and showed significant differences among straw treatments from the tillering stage. Correspondingly, the dissolved organic carbon (DOC) and permanganate oxidized carbon (POXC) showed no obvious differences among straw treatments in most growth stages. Therefore, WSOC and MBC were the most sensitive indicators for assessing soil organic carbon (SOC) change under straw mulch. Moreover, stepwise multiple linear regression revealed that cellulase and b-glucosidase were significantly positive impact factors for LOCF in the two soil layers, while polyphenol oxidase had both positive and negative impacts on WSOC at different soil layers, and peroxidase was a negative factor for LOCF. ã 2015 Elsevier B.V. All rights reserved.
Keywords: Straw mulch Total soil organic carbon Labile organic carbon fractions Soil C-cycle enzymes
1. Introduction Soil organic carbon (SOC) plays an important role in the function of agro-ecosystems because it provides energy and substrates for microbial metabolism, and promotes biological diversity (Loveland and Webb, 2003). Thus, its change has become an evaluation index of the variation of soil quality (Sparling and Schipper, 2004; Haynes, 2005). However, the change of total soil organic carbon (TOC) is not easily detected in the short term (Bhattacharyya et al., 2011; Gong et al., 2009). Compared with TOC, the labile organic carbon fractions (LOCF) including water-soluble organic carbon (WSOC), dissolved organic carbon (DOC), microbial biomass carbon (MBC), and permanganate oxidized carbon (POXC) have been considered as sensitive indicators of soil quality change
* Corresponding author. Fax: +86 28 86290983. E-mail address: [email protected] (S. Zhang). http://dx.doi.org/10.1016/j.still.2015.07.019 0167-1987/ ã 2015 Elsevier B.V. All rights reserved.
from management practices (Blair et al., 1995; Purakayastha et al., 2008; Plaza-Bonilla et al., 2014). Crop straw is a source of organic carbon that can influence the balance of SOC accumulation and decomposition (Bakht et al., 2009), especially the LOCF (Malhi et al., 2011). However, studies on the effects of straw practices on LOCF have presented diverse results. For instance, Nayak et al. (2012) reported that straw mulch with mineral fertilizer had a greater MBC concentration than that of mineral fertilizer only. In contrast, Yan et al. (2007) observed that straw mulch would decrease MBC concentrations compared with the mineral fertilizer only. With respect to WSOC concentrations after straw mulch, they showed positive (Whitbread et al., 2003), or no obvious (Xu et al., 2011) or negative effect (Ma et al., 2013) in 1–2-year experiments. Furthermore, SOC transformation involved a series of dynamic biochemical processes (Alvarez and Guerrero, 2000). Generally, hydrolytic enzymes are recognized as essential regulators to control SOC decomposition (Sinsabaugh, 1994; Grandy et al., 2009). For example, cellulase breaks cellulose
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down to cellobiose, fructose and glucose (Wickings et al., 2012); b-glucosidase can further decompose labile cellulose and other carbohydrate polymers into low molecular weight compounds (Liang et al., 2014). In contrast, soil phenol oxidase is proposed as an ‘enzymatic latch’ to protect SOC by phenolic-containing organics in oxygen-limited ecosystems such as peatlands (Freeman et al., 2001). Because low phenol oxidase activity is conducive to the accumulation of soluble phenolics and inhibits the activity of hydrolytic enzymes, and thus benefits soil carbon sequestration (Zibilske and Bradford, 2007; Sinsabaugh, 2010), soil enzymatic reactions can regulate soil biochemical processes including LOCF formation and decomposition (Bowles et al., 2014). However, researches on soil enzymes in LOCF transformation mainly focused on forest and wetland ecosystems (Keeler et al., 2009; Weand et al., 2010), and the information in agro-ecosystems under straw mulch was still limited, particularly during crop growth. Therefore, study of the effects of specific crop straw practices on the dynamics of LOCF and C-cycle enzyme activities during crop growth is necessary, and understanding their relationship can explore the underlying mechanism of SOC transformation under straw mulch (Fansler et al., 2005; Morrissey et al., 2014). The straw average output reached 40 Mt y1 with the development of intensive agriculture on the Chengdu Plain in Sichuan, China. A lot of straw is burned directly and this has caused serious environmental pollution in the last decade (Xiao, 2012). Straw mulch is one practice for effective disposal that can decrease air pollution and provide SOC (Soon and Lupwayi, 2012). Consequently, a comprehensive understanding of the effects of straw mulch on LOCF change is critical for scientific management of crop straw use on the Chengdu plain. Therefore, this study was conducted to: (1) investigate the dynamic changes of LOCF concentrations and Ccycle enzyme activities during wheat growth; (2) examine the sensitivity of the LOCF as early indicators of SOC change; and (3) quantify the relationships of different LOCF and C-cycle enzymes under straw mulch. 2. Materials and methods 2.1. Experimental site and design The experiment was conducted from November 2012 to May 2013 in Dujiangyan (31560 N, 103 440 E, altitude 636.3 m) on the Chengdu Plain in Sichuan, China. The experimental area has a humid mid-subtropical monsoon climate with an average annual precipitation of 1200 mm and annual temperature of 15.8 C. Derived from gray alluvium of the Minjiang River, the soil at the experimental site is a typical Ferric-Accumulic Stagnic Anthrosol. The basic soil properties in the 0–40-cm layer before experiment establishment are given in Table 1.
Table 2 Experimental design and application rates of mineral fertilizers and rice straw. Treatments
Control MF RS1 RS2 RS3 RS
Chemical nutrient additions (kg ha1) N
P2 O 5
K2O
– 150.0 134.5 119.0 103.5 88.0
– 60.0 55.4 50.8 46.2 41.6
– 90.0 66.8 43.6 20.4 –
Rice straw (kg ha1)
– – 1840.0 3680.0 5520.0 7360.0
Control: no fertilizer and straw; MF: only mineral fertilizer; RS1: 10% rice straw N plus 90% fertilizer N; RS2: 20% rice straw N plus 80% fertilizer N; RS3: 30% rice straw N plus 70% fertilizer N; RS: 100% rice straw.
Six treatments were designed and are shown in Table 2: (1) no fertilizer or straw (Control); (2) only mineral fertilizer (MF); (3) 10% rice straw nitrogen (N) plus 90% fertilizer N (RS1); (4) 20% rice straw N plus 80% fertilizer N (RS2); (5) 30% rice straw N plus 70% fertilizer N (RS3); and (6) 100% rice straw (RS). The percentages of nitrogen in RS1, RS2 and RS3 treatments reflect the percent of total nitrogen that was applied in the mineral fertilizer treatment. All treatments (excluding the Control) had the same N, phosphorus (P) and potassium (K) application rates equivalent to 150 kg ha1 N, 60 kg ha1 P2O5, and 90 kg ha1 K2O, in which urea, superphosphate and potassium chloride were used, respectively. The C, N, P2O5 and K2O contents of the rice straw were 384.6, 8.4, 2.5 and 12.6 g kg1, respectively. The shortages of N, P and K in different straw treatments were complemented by the mineral fertilizers. The experiment had a completely randomized block design in triplicate with a plot size of 5 5 m, and the tested wheat variety was Neimai 836. For fertilization, N, P and K fertilizers were applied as base fertilizer before sowing; the rice straw in all straw treatments uniformly covered the soil surface after sowing. 2.2. Soil sampling Soil samples were collected from 0 to 20 and 20 to 40 cm soil layers in the pre-sowing (10 November 2012, PS), seedling (15 December 2012, SS), tillering (12 January 2013, TS), jointing (5 March 2013, JS), heading (13 April 2013, HS) and maturing (18 May 2013, MS) wheat growth stages. In each plot, five cores (each 2.5 cm diameter) were excavated randomly and mixed as a composite sample in each wheat growth stage. The composite samples were placed in plastic bags and transported to the laboratory. Some of the soil samples were stored at 4 C for determining LOCF concentrations and enzyme activities within 4 days, and the other samples were air-dried at room temperature and sieved to 2 mm for determining TOC and other basic soil properties (Table 1). 2.3. Soil analysis
Table 1 Basic soil properties in different soil layers at the start of the experiment. Soil properties
pH (soil:water, 1:2.5) Sand (%) Silt (%) Clay (%) Bulk density (g cm3) Organic carbon (g kg1) Total N (g kg1) Total P (g kg1) Total K (g kg1) Available P (mg kg1) Available K (mg kg1)
Soil layers (cm) 0–20
20–40
7.0 21.7 59.8 18.5 1.18 21.5 1.8 0.9 21.9 10.6 57.8
7.7 23.6 62.5 15.8 1.22 10.3 1.0 0.6 20.9 3.4 39.5
TOC was determined by the Walkley–Black method (Nelson and Sommers, 1996). WSOC was determined using a modification of the method described by Zhang et al. (2012). Briefly, WSOC was extracted from moist soil (5.0 g) with a 1:5 ratio of soil to deionized water at 25 C, and shaken for 30 min at a speed of 250 rpm. The samples were subsequently centrifuged for 10 min at 5000 rpm, after which the supernatant was filtered using a 0.45 mm membrane filter. The filtrate was measured by dichromate oxidation. The DOC was extracted by 1 M KCl solution, and other operations were consistent with the WSOC. MBC was determined according to the CHCl3 fumigation-extraction method (Vance et al., 1987). POXC was determined using a modification of the method described by Blair et al. (1995). Briefly, moist soil (5.0 g) was weighed into plastic screw-cap centrifuge tubes, and 50 mL of a
S. Li et al. / Soil & Tillage Research 155 (2016) 289–297
0.02 M KMnO4 solution were added to each tube. Blank samples (containing no soil) were also analyzed during each run. The centrifuge tubes were tightly sealed and tumbled for 1 h at 200 rpm on a 15-cm-radius tumbler. Subsequently, the tubes were centrifuged for 10 min at 4000 rpm, and the supernatant solutions were diluted by 1:250 with deionized water. The absorbance of the diluted samples and standards was measured at 565 nm. The change in KMnO4 concentration was used to estimate the amount of oxidized C (assuming that 1 mM of KMnO4 was consumed in the oxidation of 9 mg of C). Cellulase (EC 3.2.1.4) activity was determined by the method of Schinner and Von Mersi (1990). Moist soil (5.0 g) was incubated with 5 mL of 1% carboxymethyl-cellulose in 5 mL of 2 M acetate buffer (pH 5.5) at 37 C for 24 h. The filtrates of soil-substrate slurries were subject to color reaction and the produced Prussian
291
blue was analyzed colorimetrically at 690 nm. The cellulase activity is expressed as nmol g1 h1. b-glucosidase (EC 3.2.1.21) activity was estimated using the substrates p-nitrophenyl– b-glucopyranoside and measuring the absorbance of the pnitrophenol (Parham and Deng, 2000). Moist soil (1.0 g) was incubated with 1 mL of the appropriate substrate solution and 4 mL of 50 mM acetate buffer at 37 C for 1 h, then 1 mL of 0.5 M CaCl2 and 4 mL of 0.5 M NaOH were added to terminate the reaction, and the filtrates were analyzed colorimetrically at 410 nm. The b-glucosidase activity was expressed as mmol g1 h1. The activities of phenol oxidase (EC 1.10.3.2) and peroxidase (EC 1.11.1.7) were determined using the method described by Shi et al. (2006). Moist soil (0.5 g) was incubated with 1 mL of 10 mM LDOPA and 4 mL of 50 mM acetate buffer and incubated at room temperature with constant shaking for 1 h, as were triplicate no-
Table 3 Dynamic changes of soil labile organic carbon fractions during wheat growth. LOCF
Soil layers (cm)
Treatments
PS
SS
TS
JS
HS
MS
WSOC (mg kg1)
0–20
Control MF RS1 RS2 RS3 RS Control MF RS1 RS2 RS3 RS
25.98 1.73a 27.40 3.22a 28.55 1.23a 30.83 0.25a 27.10 4.89a 30.76 3.02a 15.73 1.35a 16.44 3.70a 17.44 0.46a 17.28 1.63a 15.37 1.12a 16.82 1.17a
32.94 4.82c 40.11 1.34b 45.15 5.88ab 49.67 1.99a 52.23 3.53a 47.42 4.45a 19.33 4.01a 21.76 4.40a 23.68 1.11a 25.94 11.73a 25.39 4.91a 26.68 7.72a
37.99 4.72d 45.26 1.48c 50.22 5.97bc 54.75 1.94ab 57.44 3.11a 52.53 4.83ab 21.58 3.59c 26.31 1.31bc 32.11 1.67ab 36.25 7.19a 37.64 7.12a 36.64 7.83a
38.92 4.29e 45.40 3.68d 66.44 3.89c 70.53 6.13bc 77.41 3.78ab 81.28 9.00a 24.98 4.99c 28.95 6.81c 40.07 4.03b 43.52 3.55ab 46.01 5.40ab 50.18 3.98a
36.06 4.98c 52.28 3.43b 62.20 3.64b 79.17 6.56a 83.55 12.96a 76.43 9.93a 17.21 2.30b 23.45 11.34ab 25.75 2.23a 27.25 3.62a 30.20 2.75a 30.44 3.39a
28.63 0.47c 36.44 11.09bc 41.46 4.95abc 49.45 9.15ab 53.31 11.24a 48.19 5.11ab 26.18 0.50c 36.53 10.96bc 40.76 0.48ab 45.43 11.25ab 50.69 3.41a 48.39 5.08a
Control MF RS1 RS2 RS3 RS Control MF RS1 RS2 RS3 RS
24.16 1.62a 22.29 3.02a 23.42 1.53a 25.54 0.30a 23.44 0.86a 24.26 4.49a 15.15 1.93a 15.26 3.48a 14.27 0.29a 16.57 0.25a 14.69 0.30a 15.13 4.58a
24.73 3.88a 27.58 4.08a 29.36 1.55a 31.67 11.55a 31.70 6.23a 32.38 7.89a 14.85 3.69a 17.53 4.06a 19.11 1.13a 21.63 11.28a 14.89 1.07a 22.35 7.86a
28.17 4.52c 35.30 1.25bc 41.72 4.86b 44.68 10.38ab 54.17 4.83a 43.51 4.36b 18.53 3.88d 26.23 1.34c 32.71 1.67b 37.65 2.13ab 38.20 3.84a 33.72 3.79ab
31.81 4.35b 31.44 3.03b 59.21 5.58a 62.11 5.14a 65.25 3.74a 67.52 7.41a 22.38 4.86b 22.97 3.04b 40.61 2.02a 42.70 5.61a 39.58 3.82a 43.27 7.57a
33.00 5.00c 45.55 10.63b 50.20 3.98a 55.07 6.88a 57.54 4.90a 53.72 3.81a 14.83 3.10c 21.62 11.03c 20.65 8.04c 45.78 3.77a 38.32 10.94ab 26.88 6.48bc
23.59 4.16b 29.48 11.02ab 34.67 5.13ab 48.90 15.85a 45.91 10.88a 34.76 6.53a 22.08 3.06b 28.91 11.13b 37.73 8.01ab 46.40 12.86a 50.73 8.99a 44.50 6.52a
Control MF RS1 RS2 RS3 RS Control MF RS1 RS2 RS3 RS
183.54 15.17a 183.43 13.25a 183.40 4.75a 184.74 8.53a 179.35 12.21a 181.21 10.58a 30.64 2.29a 30.63 2.57a 31.19 2.19a 30.74 2.07a 30.74 2.85a 30.21 1.72a
193.61 13.43b 197.27 13.43b 249.88 15.29a 251.15 21.75a 277.10 27.02a 264.57 25.61a 33.66 3.17c 39.20 4.05bc 47.31 7.43ab 49.62 6.89ab 50.02 7.93ab 52.69 6.52a
203.30 9.43b 209.02 23.44b 256.11 50.95a 282.15 16.69a 284.70 24.07a 298.53 5.86a 50.74 5.28c 55.38 5.27bc 63.61 6.56ab 68.55 12.63ab 73.85 10.90a 65.42 5.78ab
200.50 18.03b 214.35 13.99b 267.35 24.90a 276.63 20.04a 281.94 37.99a 280.04 39.57a 41.50 3.76d 49.35 3.92cd 56.41 6.95bc 64.14 7.30ab 70.68 7.23a 68.05 5.68a
230.42 25.86d 251.92 31.77cd 283.26 24.11bc 315.84 34.78ab 328.40 26.24ab 331.96 10.10a 47.27 5.09d 57.98 6.92cd 65.13 6.68bc 77.59 10.17ab 85.60 10.74a 81.63 5.51a
251.18 23.02d 277.55 11.91cd 301.19 23.79bc 325.41 19.20ab 339.48 23.12a 317.98 11.89ab 61.68 4.81c 71.02 5.27bc 76.53 5.29ab 80.16 11.94ab 88.42 10.36a 81.60 5.57ab
Control MF RS1 RS2 RS3 RS Control MF RS1 RS2 RS3 RS
1.05 0.06a 1.03 0.03a 1.01 0.05a 1.07 0.05a 1.06 0.05a 1.08 0.03a 0.47 0.04a 0.41 0.08a 0.52 0.10a 0.43 0.04a 0.52 0.34a 0.48 0.24a
0.98 0.05b 1.07 0.09ab 1.04 0.15b 1.02 0.08b 1.23 0.14a 1.22 0.03a 0.49 0.15a 0.61 0.06a 0.65 0.06a 0.58 0.06a 0.52 0.13a 0.62 0.45a
1.05 0.07b 1.05 0.06b 1.10 0.05b 1.21 0.02a 1.28 0.05a 1.21 0.07a 0.50 0.04b 0.53 0.03b 0.75 0.09a 0.58 0.09b 0.55 0.02b 0.69 0.04a
1.06 0.22a 1.20 0.23a 1.31 0.08a 1.22 0.05a 1.31 0.14a 1.23 0.03a 0.55 0.08b 0.58 0.03ab 0.64 0.02a 0.60 0.03ab 0.59 0.03ab 0.57 0.04ab
1.02 0.11b 1.15 0.10ab 1.21 0.07a 1.23 0.11a 1.30 0.11a 1.23 0.02a 0.67 0.17a 0.70 0.08a 0.83 0.06a 0.77 0.12a 0.75 0.11a 0.80 0.10a
1.09 0.01b 1.16 0.05ab 1.18 0.17ab 1.19 0.03ab 1.31 0.08a 1.30 0.09a 0.55 0.08d 0.60 0.03cd 0.77 0.04a 0.70 0.06ab 0.65 0.05bc 0.66 0.04bc
20–40
DOC (mg kg1)
0–20
20–40
MBC (mg kg1)
0–20
20–40
POXC (g kg1)
0–20
20–40
LOMF: labile organic carbon fractions; WSOC: water-soluble organic carbon; DOC: dissolved organic carbon; MBC: microbial biomass carbon; POXC: permanganate oxidized carbon. Control: no fertilizer and straw; MF: only mineral fertilizer; RS1: 10% rice straw N plus 90% fertilizer N; RS2: 20% rice straw N plus 80% fertilizer N; RS3: 30% rice straw N plus 70% fertilizer N; RS: 100% rice straw. PS: pre-sowing; SS: seedling stage; TS: tillering stage; JS: jointing stage; HS: heading stage; MS: maturing stage. Means standard errors (n = 3). Different letters in the same column indicate significant differences among treatments at P < 0.05.
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extracted with neutral 1 M NH4OAc (Hanway and Heidel, 1952) and estimated by a flame photometer. Soil bulk density was measured by the gravimetric method based on soil volume. Clay, sand, and silt contents were determined by the pipette method (Gee and Bauder, 1986). Soil pH was measured in distilled water at a soilsolution ratio of 1:2.5.
sample and no L-DOPA Controls. The reaction was terminated by centrifugation at 5000 rpm for 10 min, and the absorbance of the reaction product was measured at 460 nm. The wells used for peroxidase activities were the same except they received 10 mL of 0.3% H2O2, including the no-sample and no L-DOPA controls. Enzyme activities were expressed as mmol g1 h1. Total N was determined by the Kjeldahl method (Bremmer and Mulvaney, 1982). Total P was calcined and extracted by NaOH, then measured by the molybdenum antimony colorimetry method (Dick and Tabatabai, 1977). Total K was calcined and extracted by NaOH and measured using a flame photometer (Hanway and Heidel, 1952). Olsen-P was extracted with 0.5 M NaHCO3 (pH 8.5) as outlined by Olsen et al. (1954), and the P concentration in the extract was determined using ascorbic acid as a reducing agent and spectrophotometry (Watanabe and Olsen, 1965). Available K was
2.4. Statistical analysis SPSS version 17.0 for Windows was used for all statistical analysis. A one-way analysis of variance (ANOVA) was employed to determine the effects of straw mulch on the LOCF concentrations and enzyme activities, with separation of means by least significant difference (LSD). The general linear-regression analysis and stepwise regression analysis were applied to investigate the
5.0
Cellulase
0-20 cm 4.0
a b c c d d
3.0 2.0
a b c c d e
0-20 cm
2.0
ß-glucosidase
a ab bc bc cd d
a a b b c d
1.6
a ab bc cd d d
1.2 0.8
a a ab b
a a ab ab bc c
c c
20-40 cm
a 2.0 b bc 1.6 c d 1.2 e
a a a a a a
0.8
a a 0.6 ab b
a b b b b b
0.4
Polyphenol oxidase
0.3
0-20 cm
2.0
a b b c c c
1.6
a a ab b c d
1.2
0.8 10.5
a ab ab b b c
a ab ab bc c
Peroxidase
0-20 cm
a b b b c d
9.0 7.5
a b bc cd cd d
6.0 4.5
PS
SS
a ab bc cd cd d TS
a ab b c cd d JS
HS
MF
a ab ab ab b b
0.4 0.0 a 8.0 bc bc bc
b
a a ab bc bc c
a a ab bc c
d a aa b b b
4.0 2.0 PS
SS
a a a a b c
a a ab ab ab b
d
a a a a b b
a b b bc c d
a ab b c cd d
TS
a a b b c c
a b b bc c
20-40 cm
6.0
d
a ab b b c c
a b b b c c
a a b b b b JS
HS
MS
Wheat growth stages
Wheat growth stages Control
a a a aa
20-40 cm
a ab 1.2 bc cd de 0.8 e
MS
b c
20-40 cm
0.5
c c
a ab ab bc c c
a a a a ab b
a aa a
RS1
RS2
RS3
RS
Fig. 1. Dynamic changes of soil enzyme activities during wheat growth. Activity is reported in nmol g1 h1 for cellulase, and in mmol g1 h1 for b-glucosidase, polyphenol oxidase and peroxidase. Control, no fertilizer and straw; MF, only mineral fertilizer; RS1, 10% rice straw N plus 90% fertilizer N; RS2, 20% rice straw N plus 80% fertilizer N; RS3, 30% rice straw N plus 70% fertilizer N; RS, 100% rice straw. PS, pre-sowing; SS, seedling stage; TS, tillering stage; JS, jointing stage; HS, heading stage; MS, maturing stage. Different lowercase letters indicate significant differences among treatments in the same growth stage at P <0.05. Vertical bars denote the standard error of the mean (n = 3).
S. Li et al. / Soil & Tillage Research 155 (2016) 289–297
relationships between LOCF and C-cycle enzyme activities. All effects were considered significant at P < 0.05. 3. Results 3.1. Dynamics of soil labile organic carbon fractions 3.1.1. Water-soluble organic carbon Distinct differences in WSOC concentrations among different treatments in the 0–20 cm soil layer were observed during the wheat growth stages (Table 3). Generally, the WSOC concentrations of all treatments increased at first and then decreased. The maximum WSOC values of the treatments occurred at jointing for the Control, RS1 and RS, or at heading for the MF, RS2 and RS3. The WSOC concentrations for straw treatments except for RS1 in topsoil were significantly higher than those of the Control and MF treatments from seedling to heading (P < 0.05). In the 20–40 cm soil layer, the WSOC concentrations of straw treatments were also significantly higher than those of the Control from tillering to maturing (P < 0.05), but the WSOC among them displayed no significant differences (P > 0.05, Table 3). 3.1.2. Dissolved organic carbon As shown in Table 3, DOC concentrations in the two soil layers for all straw treatments increased with wheat growth up to jointing and then decreased. In general, straw treatments showed higher DOC concentrations than those of the Control (P < 0.05). The differences among treatments began at tillering and gradually increased with the progression of growth stages. At heading, the DOC concentrations for straw treatments in the 0–20 cm soil layer were 52.12–74.36% higher than those of the control, and 10.21–26.32% higher than those of the MF (P > 0.05). However, the concentrations among all straw treatments showed no obvious difference at the seedling stage (P > 0.05). 3.1.3. Microbial biomass carbon The MBC concentrations for different treatments showed increasing trends with wheat growth, reaching a maximum value at heading or maturing (Table 3). The MBC concentrations in the two soil layers for straw treatments were significantly higher than those of the Control after the seedling stage (P < 0.05). This was similar to the WSOC in the 0–20 cm soil layer. Moreover, the MBC concentrations of all straw treatments in the 0–20 cm soil layer were significantly higher than those of the MF treatment from seedling to jointing (P < 0.05), and there were no significant differences among them (P > 0.05), likely because straw input can stimulate microbial activity, thereby significantly increasing the MBC.
293
3.1.4. Permanganate oxidized organic carbon As shown in Table 3, although the POXC concentrations for all treatments in the 0–20 cm soil layer showed obvious dynamic changes with wheat growth, there were no significant differences among the treatments in the same growth stage (P > 0.05) except for the control. Similar results were observed in the 20–40 cm soil layer, except that the POXC concentrations of the RS1 treatment were significantly higher than those of other treatments at tillering and maturing (P < 0.05, Table 3). 3.2. Dynamics of soil C-cycle enzyme activities 3.2.1. Cellulase Cellulase activities for the four straw treatments in the 0–20 cm soil layer increased at first from pre-sowing to the seedling stage, subsequently reduced at tillering, and then rose to the maximum at jointing or maturing (Fig. 1). The enzyme activities for the four straw treatments in the 0–20 cm soil layer were significantly higher than those of the Control and MF treatment after the seedling stage (P < 0.05) except at tillering. Inconsistent results were observed in the 20–40 cm soil layer; the enzyme activities for all treatments continuously increased from the seedling stage to maturing (Fig. 1). 3.2.2. b-glucosidase b-glucosidase activities for the different treatments showed obvious diversities during all of the wheat growth stages in the different soil layers (Fig. 1). Generally, b-glucosidase activities in the 0–20 cm soil layer for all treatments continuously increased, and the diversities varied with the change of growth stage. The enzyme activities of straw treatments were significantly higher than those of the Control from tillering to maturing, and higher than those of the MF treatment after heading (P < 0.05). However, the b-glucosidase activities only for RS2 and RS3 treatments in the 20–40 cm soil layer were significantly higher than those of the Control and MF at jointing and heading (P < 0.05). 3.2.3. Polyphenol oxidase Changes of polyphenol oxidase activities for all treatments showed similar trends during all growth stages at 0–40 cm (Fig. 1). In the 0–20 cm soil layer, the polyphenol oxidase activities of the four straw treatments were significantly higher than those of the Control from the seedling stage to maturing, and of the MF at jointing (P < 0.05). The highest activities among the four straw treatments were in the RS1 treatment in the 0–20 cm soil layer after jointing and in the RS3 treatment in the 20–40 cm soil layer after tillering.
Table 4 Dynamic changes of total soil organic carbon (g kg1) during wheat growth. Soil layers (cm)
Treatments
PS
SS
TS
JS
HS
MS
0–20
Control MF RS1 RS2 RS3 RS
21.54 0.05 a 21.55 0.14 a 21.56 0.05 a 21.52 0.10 a 21.53 0.01 a 21.55 0.06 a
21.54 0.01 a 21.55 0.05 a 21.55 0.07 a 21.57 0.03 a 21.56 0.06 a 21.57 0.08 a
21.55 0.07 21.55 0.07 21.58 0.05 21.60 0.09 21.62 0.04 21.61 0.04
a a a a a a
21.56 0.10 a 21.55 0.27 a 21.61 0.02 a 21.62 0.18 a 21.64 0.15 a 21.62 0.09 a
21.56 0.07 a 21.55 0.01 a 21.62 0.06 a 21.63 0.03 a 21.65 0.05 a 21.63 0.10 a
21.58 0.06 21.58 0.07 21.65 0.06 21.65 0.06 21.67 0.03 21.64 0.02
a a a a a a
20–40
Control MF RS1 RS2 RS3 RS
10.26 0.02 10.27 0.07 10.28 0.04 10.26 0.05 10.26 0.08 10.27 0.04
10.26 0.00 a 10.27 0.03 a 10.28 0.05 a 10.27 0.01 a 10.26 0.05 a 10.27 0.04 a
10.26 0.03 10.27 0.04 10.29 0.07 10.29 0.03 10.30 0.04 10.31 0.06
a a a a a a
10.28 0.09 a 10.28 0.06 a 10.31 0.09 a 10.33 0.09 a 10.34 0.07 a 10.33 0.03 a
10.29 0.05 10.28 0.06 10.32 0.01 10.33 0.04 10.35 0.03 10.34 0.02
10.29 0.02 10.30 0.01 10.33 0.05 10.34 0.06 10.35 0.04 10.35 0.05
a a a a a a
a a a a a a
a a a a a a
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showed no significant differences during wheat growth stages in the present study (P > 0.05, Table 4). This result was similar to those obtained in previous studies where TOC was insensitive to recent management practices (Mendham et al., 2002; Shafi et al., 2007; Xu et al., 2011). However, some labile carbon fractions including WSOC, DOC and MBC were sensitive to straw mulch in some growth stages because their concentrations between Control and straw treatments showed significant differences (P < 0.05, Table 3). For example, the WSOC concentrations of straw treatments except for RS1 were significantly higher than those of the Control and MF from the seedling stage to heading in the 0–20 cm soil layer (P < 0.05); the DOC were significantly higher than those of the Control after tillering (P < 0.05) and the MBC was significantly higher than those of the Control from the seedling to jointing stage (P < 0.05). Straw mulch could stimulate microorganisms and might produce more WSOC, DOC and MBC, so the net effect could consequently be predicted in the short term (Soon and Lupwayi, 2012). As a result, WSOC, DOC and MBC could be considered as sensitive indicators to straw mulch. However, the POXCs among fertilizer treatments showed no significant differences because of the relatively higher proportions of TOC (3.99–8.04%) in most of the growth stages (Blair et al., 1995; Bell et al., 1998), and it was unsuitable as an early indicator of TOC change under straw mulch. Change extents for each fraction also showed differences in various wheat stages in this study (Table 3). In the 0–20 cm soil layer, the differences of WSOC and MBC among different treatments were observed from the seedling stage, while DOC were observed from the tillering stage (P < 0.05). This indicated that the former two fractions can have faster responses to straw mulch than DOC. Meanwhile, the WSOC concentrations of all straw treatments in the 0–0 cm soil layer were 70.71–108.84% higher than those of the Control at the jointing stage, and the MBC concentrations were
3.2.4. Peroxidase Peroxidase activities for all treatments in the 0–20 cm soil layer decreased first and then increased, and gradually showed obvious differences among the treatments (Fig. 1). From the seedling stage to jointing, the enzyme activities of the MF treatment in the 0– 20 cm soil layer were significantly higher than those of the other treatments except for RS1 and RS2 (P < 0.05). However, the peroxidase activities of the RS2 treatment increased significantly after heading, and they were significantly higher than those of the Control and MF (P < 0.05). The enzyme activities in the 20–40 cm soil layer showed obviously different trends of change than those in the 0–20 cm soil layer (Fig. 1). 4. Discussion 4.1. Sensitivity of labile organic carbon fractions to straw mulch Soil labile organic carbon fractions have greater turnover rates, so their concentration changes can be easily detected in the shortand medium-terms (Haynes, 2005), although they only have a small proportion of TOC (McLauchlan and Hobbie, 2004). Many researchers thought that LOCF were sensitive indicators of changes in soil quality (Zagal et al., 2009; Banger et al., 2010), but many argue otherwise (Whitbread et al., 2003; Yan et al., 2007; Nayak et al., 2012). Therefore, it is necessary to examine whether LOCF are sensitive to straw mulch. In the present study, we will discuss the sensitivity of the LOCF from the concentration differences among treatments, change extents and correlations with TOC. The differences of LOCF concentrations among various treatments could be used to evaluate their sensitivity for agricultural management practices (Purakayastha et al., 2008; Xu et al., 2011). TOC concentrations between control and fertilizer treatments
Table 5 Correlation coefficients of soil labile organic carbon fractions and total organic carbon in different wheat growth stages. LOCF
0–20 cm
20–40 cm
TOC
WSOC
DOC
SS WSOC DOC MBC POXC
0.489* 0.458* 0.545* 0.410
1 0.726** 0.708** 0.643**
1 0.653** 0.492*
TS WSOC DOC MBC POXC
0.535* 0.488* 0.507* 0.488*
1 0.927** 0.660** 0.849**
1 0.632** 0.835**
JS WSOC DOC MBC POXC
0.678** 0.590* 0.589* 0.499*
1 0.981** 0.775** 0.832**
1 0.680** 0.827**
HS WSOC DOC MBC POXC
0.701** 0.592** 0.566* 0.546*
1 0.895** 0.837** 0.898**
1 0.715** 0.933**
MS WSOC DOC MBC POXC
0.703** 0.693** 0.661** 0.544*
1 0.916** 0.662** 0.771**
1 0.694** 0.594**
MBC
1 0.656**
1 0.727**
1 0.916**
1 0.850**
1 0.806**
POXC
TOC
WSOC
DOC
MBC
POXC
1
0.454* 0.451* 0.463* 0.480*
1 0.657** 0.544* 0.517*
1 0.496* 0.507*
1 0.586*
1
1
0.522* 0.559* 0.540* 0.539*
1 0.849** 0.559* 0.579*
1 0.774** 0.612**
1 0.661**
1
1
0.676** 0.650** 0.615** 0.559*
1 0.881** 0.814** 0.614**
1 0.760** 0.495*
1 0.622**
1
1
0.604** 0.575* 0.488* 0.538*
1 0.712** 0.677* 0.642**
1 0.587* 0.604**
1 0.669**
1
1
0.642** 0.597** 0.553* 0.510*
1 0.939** 0.683** 0.604**
1 0.663** 0.550*
1 0.635**
1
LOCF: labile organic carbon fractions; WSOC: water-soluble organic carbon; DOC: dissolved organic carbon; MBC: microbial biomass carbon; POXC: permanganate oxidized carbon; TOC: total soil organic carbon. SS: seedling stage; TS: tillering stage; JS: jointing stage; HS: heading stage; MS: maturing stage. * Correlation is significant at the 0.05 level. ** Correlation is significant at the 0.01 level.
S. Li et al. / Soil & Tillage Research 155 (2016) 289–297
22.93–44.07% higher than those of the Control at the heading stage (Table 3); however, their concentrations of all straw treatments (except for the WSOC of RS3) in the 0–20 cm soil layer showed no significant differences compared with the MF treatment at the maturing stage (Table 3, P > 0.05). Therefore, different sampling times may exhibit various results, indicating that the diverse effects of straw practices on WSOC may be caused by the inconsistent sampling time (Dolan et al., 2006; Malhi et al., 2011; Xu et al., 2011). Moreover, WSOC and MBC had higher mean proportions of TOC (0.13–0.39% and 0.83–1.57%, respectively) under straw treatments than those of the control (0.12–0.18% and 0.85–1.16%, respectively) in the 0–20 cm soil layer. Some researchers thought that the MBC relative amount of TOC was a useful assessment index for soil quality (Anderson and Domsch 1989; Sparling, 1992). Consequently, it was noteworthy that WSOC and MBC were sensitive to assess the effects of straw mulch on soil quality. Correlation analysis showed that WSOC and MBC had higher coefficients with TOC than other fractions in the 0–20 cm soil layer in most of growth stages (Table 5). Moreover, they were significantly correlated with other fractions (P < 0.05, Table 5). Some researchers suggested that the representative levels of LOCF to TOC should directly relate to their correlations with TOC (Dou et al., 2008; Moharana et al., 2012). Generally, these results indicated that different straw treatments showed significantly positive or no obvious effects on LOCF in various wheat growth stages, and the WSOC and MBC were the most sensitive to straw mulch in the 0–20 cm soil layer at the jointing and heading stage, respectively. 4.2. Relationships of SOC labile fractions and soil C-cycle enzyme activities A series of soil enzymes catalyze the decomposition and composition of SOC, thereby affecting the different SOC fractions (Sinsabaugh, 2010). To better understand the change characteristics of LOCF, it is necessary to observe the relationships of LOCF with C-cycle enzyme activities. 4.2.1. Relationship of SOC labile fractions with single soil C-cycle enzyme activities Soil C-cycle enzymes produced by microbes are directly involved in SOC transformations (Fansler et al., 2005; Shi et al., 2006), and each enzyme has its own substrate and ability to catalyze specific biochemical reactions (Salazar et al., 2011). In this study, cellulase and b-glucosidase activities were positively correlated with the LOCF (P < 0.05, Table 6). In general, cellulase and b-glucosidase can break celluloses down to form labile organic carbon (Wickings et al., 2012). Similar positive relationships were also reported by Wang et al. (2013) and Liang et al. (2014). However, the WSOC and DOC showed no obvious correlation with polyphenol oxidase in the 0–20 cm soil layer, and with peroxidase
295
in the 20–40 cm soil layer (P > 0.05, Table 6). This may be because the two fractions were probably both substrates and products of enzymic reactions (Bonnett et al., 2006), and the decomposition rate of hydrolytic enzymes is greater than the oxidation rate of oxidase. Moreover, the significantly positive correlation between MBC and enzyme activities indicated that soil microorganisms were the major source of soil enzymes. Thus, high biomass turnover could increase microbial biomass and enzyme activities, resulting in a directly positive relationship between MBC and enzyme activities (He et al., 2003; Sotomayor-Ramírez et al., 2009). In addition, the POXC was more weakly correlated with hydrolase activities than WSOC and DOC (Table 6). This was probably attributed to the easily oxidizable nature of POXC, and thus it was a common substrate for soil enzymes' hydrolysis and oxidation reaction (Wang et al., 2013). 4.2.2. Relationship of SOC labile fractions with multiple soil C-cycle enzyme activities To further understand the roles of different C-cycle enzymes in the SOC transformation process under straw mulch, stepwise multiple linear regression was used to analyze the major and minor effects of C-cycle enzymes on the LOCF. As shown in Table 7, the explained variance of the limited models ranged from 0.250 to 0.668 for the LOCF. The cellulase and b-glucosidase were significantly positive impact factors for WSOC and DOC in the two soil layers (P < 0.05), further indicating that the two enzymes were mainly to promote the formation of labile organic carbon, thereby they may increase the loss of SOC mineralization (Waldrop and Zak, 2006). Cellulase was a positive impact factor for POXC in the two soil layers (P < 0.05), indicating that POXC may contain the organics that were decomposed by cellulase catalysis (Wang et al., 2013). Soil oxidases have also been documented as the important regulator for SOC decomposition (Grandy et al., 2008). As has been observed in peatlands, an oxidative ‘enzymatic latch mechanism’ was used to elucidate SOC sequestration in oxygen-limited conditions where low phenol oxidase activity slows down degradation of phenolic compounds (Freeman et al., 2001). The phenolic toxicity to hydrolytic enzymes, and phenolic accumulation within soil solution could inhibit SOC hydrolysis, thereby leading to accumulation of low molecular weight compounds, i.e., soluble organic carbon (Freeman et al., 2004; Grandy et al., 2007). However, polyphenol oxidase was the negative impact factor for WSOC in the 0–20 cm soil layer in this study (Table 7). This was contradictory to the results of previous studies from wetlands or turf ecosystems (Freeman et al., 2004; Yao et al., 2012), probably because the oxygen supply is more adequate in cultivated surface soil. Therefore, the oxidative enzymes will oxidize soluble phenolic compounds into quinones, thereby promoting humification (Sinsabaugh, 2010; Burns et al., 2013). In contrast, polyphenol oxidase was the positive impact factor for WSOC in the 20–40 cm soil layer (Table 6). One possible explanation for this correlation
Table 6 Correlation coefficients of soil labile organic carbon fractions and C-cycle enzymes. LOCF
WSOC DOC MBC POXC
0–20 cm
20–40 cm
Cellulase
b-glucosidase
Polyphenol oxidase
Peroxidase
Cellulase
b-glucosidase
Polyphenol oxidase
Peroxidase
0.467** 0.594** 0.728** 0.441**
0.512** 0.519** 0.771** 0.563**
0.000 0.037 0.443** 0.169
0.267** 0.296** 0.513** 0.350**
0.496** 0.522** 0.642** 0.298**
0.492** 0.529** 0.462** 0.102
0.553** 0.577** 0.584** 0.119
0.011 0.183 0.357** 0.206*
LOCF: labile organic carbon fractions; WSOC: water-soluble organic carbon; DOC: dissolved organic carbon; MBC: microbial biomass carbon; POXC: permanganate oxidized carbon. * Correlation is significant at the 0.05 level. ** Correlation is significant at the 0.01 level.
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Table 7 Stepwise multiple regression analysis of the relationships between soil C-cycle enzymes and labile organic carbon fractions. Soil layers (cm)
LOCF
Models
R2
P
0–20
WSOC DOC MBC POXC
Y = 44.108 + 12.181 X1 + 18.881 X2 40.45 X3 Y = 34.839 + 7.011 X1 + 21.189 X2 32.212 X3 Y = 153.342 + 20.124 X1 + 100.549 X2 11.588 X4 Y = 0.915 + 0.082 X1
0.642 0.530 0.668 0.317
0.000 0.000 0.000 0.000
20–40
WSOC DOC MBC POXC
Y = 7.129 + 59.927 X2 + 19.104 X3 3.300 X4 Y = 2.586 + 59.875 X2 + 18.206 X3 1.611 X4 Y = 11.298 + 36.839 X1 Y = 0.194 + 0.616 X1 0.511 X3
0.476 0.401 0.412 0.250
0.000 0.000 0.000 0.000
LOCF: labile soil organic carbon fractions; WSOC: water-soluble organic carbon; DOC: dissolved organic carbon; MBC: microbial biomass carbon; POXC: permanganate oxidized carbon. Y, LOCF; X2, cellulase; X1, b-glucosidase; X3, polyphenol oxidase; X4, peroxidase.
would be a higher moisture and density in this soil layer, and thus the oxygen condition would be similar to wetland and turf ecosystems.. Therefore, the ‘enzymatic latch mechanism’ uncovered from peatlands may also be applicable to cultivated subsurface soils (Zibilske and Bradford, 2007). With respect to peroxidase, it was a negative factor for a few fractions in the 0–20 or 20–40 cm soil layer (Table 7). This is probably attributed to its necessary conditions of enzymatic reactions that are different to polyphenol oxidase, and it stimulates the oxidation of labile organic carbon. Overall, the present results suggested that cellulase and b-glucosidase were positive impact factors for the formation of labile organics, and polyphenol oxidase activities could contribute either positive or negative impacts for WSOC accumulation under the different environmental conditions of soil. 5. Conclusions Straw mulch showed significantly positive or no obvious effects on LOCF in the 0–20 cm soil layer at various wheat growth stages. The differences of WSOC and MBC concentration among treatments began in the seedling stage, and the greatest change extents of the two fractions were observed at the jointing and heading stage, respectively. However, DOCs among treatments began to show differences at the tillering stage, and POXCs showed no obvious differences in most of the growth stages. Moreover, WSOC and MBC had higher coefficients with TOC than the latter two fractions in most of the growth stages. These results indicated that different sampling times may exhibit various results, and the WSOC and MBC were the most sensitive to straw mulch that can be used as early indicators of SOC change. SOC transformation was strongly correlated with C-cycle enzyme activities. Cellulase and b-glucosidase were positive impact factors for LOCF, while polyphenol oxidase could contribute either positive or negative impacts for WSOC in different soil depths, and peroxidase was a negative factor for LOCF. It was concluded that cellulase and b-glucosidase were positive impact factors for the formation of labile organics, and polyphenol oxidase was conducive to SOC decomposition or humification under the different soil environmental conditions, and peroxidase would always promote LOCF oxidation. Acknowledgments This study was supported by the Projects of National Sci-tech Support, China (No. 2012BAD14B18-2), and Sichuan Sci-tech Support, China (No. 2014NZ0044). We thank Yalin Huang, Guiyin Wang, Xia Li, Ping Yao, Luoyi Xiao and Chuer Zhang of Sichuan Agricultural University, for assistance in the field and laboratory analyses.
References Alvarez, S., Guerrero, M.C., 2000. Enzymatic activities associated with decomposition of particulate organic matter in two shallow ponds. Soil Biol. Biochem. 32, 1941–1951. Anderson, T.H., Domsch, K.H., 1989. Ratios of microbial biomass carbon to total organic carbon in arable soils. Soil Biol. Biochem. 21, 471–479. Bakht, J., Shafi, M., Jan, M.T., Shah, Z., 2009. Influence of crop residue management, cropping system and N fertilizer on soil N and C dynamics and sustainable wheat (Triticum aestivum L.) production. Soil Tillage Res. 104, 233–240. Banger, K., Toor, G.S., Biswas, A., Sidhu, S.S., Sudhir, K., 2010. Soil organic carbon fractions after 16-years of applications of fertilizers and organic manure in a Typic Rhodalfs in semi-arid tropics. Nutr. Cycl. Agroecosyst. 86, 391–399. Bell, M.J., Moody, P.W., Connolly, R.D., Bridge, B.J., 1998. The role of active fractions of soil organic matter in physical and chemical fertility of Ferrosols. Aust. J. Soil Res. 36, 809–819. Bhattacharyya, R., Kundu, S., Srivastva, A.K., Gupta, H.S., Prakash, V., Bhatt, J.C., 2011. Long term fertilization effects on soil organic carbon pools in a sandy loam soil of the Indian sub-Himalayas. Plant Soil 341, 109–124. 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 systems. Aust. J. Agric. Res. 46, 1459–1466. Bonnett, S.A.F., Ostle, N., Freeman, C., 2006. Seasonal variations in decomposition processes in a valley-bottom riparian peatland. Sci. Total Environ. 370, 561–573. Bowles, T.M., Acosta-Martínez, V., Calderón, F., Jackso, L.E., 2014. Soil enzyme activities, microbial communities, and carbon and nitrogen availability in organic agroecosystems across an intensively-managed agricultural landscape. Soil Biol. Biochem. 68, 252–262. Bremmer, J.M., Mulvaney, C.S., 1982. Nitrogen: total. In: Page, A.L., Miller, R.H., Keeney, D.R. (Eds.), Methods of Soil Analysis, Part 2. Chemical and Microbiological Properties. American Society of Agronomy and Soil Science Society of America, Madison, WI, pp. 595–641. Burns, R.G., DeForest, J.L., Marxsen, J., Sinsabaugh, R.L., Stromberger, M.E., Wallenstein, M.D., Weintraub, M.N., Zoppini, A., 2013. Soil enzymes in a changing environment: current knowledge and future directions. Soil Biol. Biochem. 58, 216–234. Dick, W.A., Tabatabai, M.A., 1977. An alkaline oxidation method for determination of total phosphorus in soils. Soil Sci. Soc. Am. J. 41, 511–514. Dolan, M.S., Clapp, C.E., Allmaras, R.R., Baker, J.M., Molina, J.A.E., 2006. Soil organic carbon and nitrogen in a Minnesota soil as related to tillage, residue and nitrogen management. Soil Tillage Res. 89, 221–231. Dou, F.G., Wright, A.L., Hons, F.M., 2008. Sensitivity of labile soil organic carbon to tillage in wheat-based cropping systems. Soil Sci. Soc. Am. J. 72, 1445–1453. Fansler, S.J., Smith, J.L., Bolton, H., Baily, V.L., 2005. Distribution of two C cycle enzymes in soil aggregates of a prairie. Biol. Fert. Soils 42, 17–23. Freeman, C., Ostle, N.J., Kang, H., 2001. An enzymic ‘latch’ on a global carbon store—a shortage of oxygen locks up carbon in peatlands by restraining a single enzyme. Nature 409, 149. Freeman, C., Ostle, N.J., Fenner, N., Kang, H., 2004. A regulatory role for phenol oxidase during decomposition in peatland. Soil Biol. Biochem. 36, 1663–1667. Gee, G.W., Bauder, J.W., 1986. Particle-size analysis. In: Black, W.C. (Ed.), Methods of Soil Analysis, Part 1 Physical and mineralogical properties, including statistics and sampling. American Society of Agronomy, Madison, WI, pp. 398-–406. Gong, W., Yan, X.Y., Wang, J.Y., Hu, T.X., Gong, Y.B., 2009. Long-term manuring and fertilization effects on soil organic carbon pools under a wheat-maize cropping system in North China Plain. Plant Soil 314, 67–76. Grandy, A.S., Neff, J.C., Weintraub, M.N., 2007. Carbon structure and enzyme activities in alpine and forest ecosystems. Soil Biol. Biochem. 39, 2701–2711. Grandy, A.S., Sinsabaugh, R.L., Neff, J.C., Stursova, M., Zak, D.R., 2008. Nitrogen deposition effects on soil organic matter chemistry are linked to variation in enzymes, ecosystems and size fractions. Biogeochemistry 9, 37–49. Grandy, A.S., Strickland, M.S., Lauber, C.L., Bradford, M.A., Fierer, N., 2009. The influence of microbial communities, management, and soil texture on soil organic matter chemistry. Geoderma 150, 278–286. Hanway, J.J., Heidel, H., 1952. Soil analysis methods as used in Iowa State College Soil Testing Laboratory. Iowa Agric. 57, 1–31.
S. Li et al. / Soil & Tillage Research 155 (2016) 289–297 Haynes, R.J., 2005. Labile organic matter fractions as central components of the quality of agricultural soils: an overview. Adv. Agron. 85, 221–268. He, Z.L., Yang, X.E., Baligar, V.C., Calvert, D.V., 2003. Microbiological and biochemical indexing systems for assessing acid soil quality. Adv. Agron. 78, 89–138. Keeler, B.L., Hobbie, S.E., Kellogg, L.E., 2009. Effects of long-term N addition on microbial enzyme activity in eight forested and grassland sites: Implications for litter and soil organic matter decomposition. Ecosystems 12, 1–15. Liang, Q., Gao, R.T., Xi, B.D., Zhang, Y., Zhang, H., 2014. Long-term effects of irrigation using water from the river receiving treated industrial wastewater on soil organic carbon fractions and enzyme activities. Agric. Water Manag. 135, 100– 108. Loveland, P., Webb, J., 2003. Is there a critical level of organic matter in the agricultural soils of temperate regions: a review. Soil Tillage Res. 70 (1), 1–18. Ma, C., Zhou, J., Liu, M.Q., Zheng, X.B., Cui, J., Li, H.X., Kang, B.L., 2013. Effects of incorporation of pre-treated straws into field on soil nutrients and labile organic carbon in lime concretion black soil. Acta Pedol. Sin. 50, 70–76. Malhi, S.S., Nyborg, M., Solberg, E.D., McConkey, B., Dyck, M., Puurveen, D., 2011. Long-term straw management and N fertilizer rate effects on quantity and quality of organic C and N and some chemical properties in two contrasting soils in Western Canada. Biol. Fert. Soils 47, 785–800. McLauchlan, K.K., Hobbie, S.E., 2004. Comparison of labile soil organic matter fractionation techniques. Soil Sci. Soc. Am. J. 68, 1616–1625. Mendham, D.S., Samarian, K.V., O’Connell, A.M., Grove, T.S., 2002. Eucalyptus globulusharvest residue management effects on soil carbon and microbial biomass at 1 and 5 years after plantation establishment. Soil Biol. Biochem. 34, 1903–1912. Moharana, P.C., Sharma, B.M., Biswas, D.R., Dwivedi, B.S., Singh, R.V., 2012. Longterm effect of nutrient management on soil fertility and soil organic carbon pools under a 6-year-old pearl millet-wheat cropping system in an Inceptisol of subtropical India. Field Crops Res. 136, 32–41. Morrissey, E.M., Berrier, D.J., Neubauer, S.C., Franklin, R.B., 2014. Using microbial communities and extracellular enzymes to link soil organic matter characteristics to greenhouse gas production in a tidal freshwater wetland. Biogeochemistry 117, 473–490. Nayak, A.K., Gangwar, B., Shukla, A.K., Mazumdar, S.P., Kumar, A., Kumar, V., Rai, P.K., Mohan, U., 2012. Long-term effect of different integrated nutrient management on soil organic carbon and its fractions and sustainability of rice-wheat system in Indo Gangetic Plains of India. Field Crops Res. 127, 129–139. Nelson, D.W., Sommers, L.E., 1996. Total carbon, organic carbon, and organic matter: laboratory methods. In: Barteles, J.M., Bigham, J.M. (Eds.), Methods of Soil Analysis, Part 3 Chemical Methods. American Society of Agronomy and Soil Science Society of America, Madison, WI, pp. 961–1010. Olsen, S.R., Cole, C.V., Watanabe, F.S., Dean, L.A., 1954. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate. US Dept. of Agriculture circular No. 939, Washington, pp. 1–19. Parham, J.A., Deng, S.P., 2000. Detection, quantification and characterization of b-glucosaminidase activity in soil. Soil Biol. Biochem. 32, 1183–1190. Plaza-Bonilla, D., Álvaro-Fuentes, J., Cantero-Martínez, C., 2014. Identifying soil organic carbon fractions sensitive to agricultural management practices. Soil Till. Res. 139, 19–22. Purakayastha, T.J., Rudrappa, L., Singh, D., Swarup, A., Bhadraray, S., 2008. Long-term impact of fertilizers on soil organic carbon pools and sequestration rates in maize–wheat–cowpea cropping system. Geoderma 144, 370–378. Salazar, S., Sánchez, L.E., Alvarez, J., Valverde, A., Galindo, P., Igual, J.M., Peixa, A., Santa-Regina, I., 2011. Correlation among soil enzyme activities under different forest system management practices. Ecol. Eng. 37, 1123–1131.
297
Schinner, F., Von Mersi, W., 1990. Xylanase-, CM-cellulase- and invertase activity in soil: an improved method. Soil Biol. Biochem. 22, 511–515. Shafi, M., Bakht, J., Jan, M.T., Shah, Z., 2007. Soil C and N dynamics and maize (Zea mays) yield as affected by cropping systems and residue management in Northwestern Pakistan. Soil Tillage Res. 94, 520–529. Shi, W., Dell, E., Bowman, D., Iyyemperumal, K., 2006. Soil enzyme activities and organic matter composition in a turfgrass chronosequence. Plant Soil 288, 285– 296. Sinsabaugh, R.S., 1994. Enzymic analysis of microbial pattern and process. Biol. Fert. Soils 17, 69–74. Sinsabaugh, R.L., 2010. Phenol oxidase, peroxidase and organic matter dynamics of soil. Soil Biol. Biochem. 42, 391–404. Soon, Y.K., Lupwayi, N.Z., 2012. Straw management in a cold semi-arid region: impact on soil quality and crop productivity. Field Crops Res. 139, 39–46. Sotomayor-Ramírez, D., Espinoza, Y., Acosta-Martínez, V., 2009. Land use effects on microbial biomass C, b-glucosidase and b-glucosaminidase activities, and availability, storage, and age of organic C in soil. Biol. Fert. Soils 45, 487–497. Sparling, G., Schipper, L., 2004. Soil quality monitoring in New Zealand: trends and issues arising from a broad-scale survey. Agric. Ecosyst. Environ. 104, 545–552. Sparling, G.P., 1992. Ratio of microbial biomass to soil organic carbon as a sensitive indicator of changes in soil organic matter. Aust. J. Soil Res. 30, 195–207. Vance, E.D., Brookes, P.C., Jenkinson, D.S., 1987. An extraction method for measuring soil microbial biomass-C. Soil Biol. Biochem. 19, 703–707. Waldrop, M.P., Zak, D.R., 2006. Response of oxidative enzyme activities to nitrogen deposition effects soil concentrations of dissolved organic carbon. Ecosystems 9, 921–933. Wang, Q.K., Xiao, F.M., He, T.X., Wang, S.L., 2013. Responses of labile soil organic carbon and enzyme activity in mineral soils to forest conversion in the subtropics. Ann. For. Sci. 70, 579–587. Watanabe, F.S., Olsen, S.R., 1965. Test of an ascorbic acid method for determining phosphorus in water and NaHCO3 extracts from soils. Soil Sci. Soc. Am. J. 29, 677–678. Weand, M.P., Arthur, M.A., Lovett, G.M., McCulley, R.L., Weathers, K.C., 2010. Effects of tree species and N additions on forest floor microbial communities and extracellular enzyme activities. Soil Biol. Biochem. 42, 2161–2173. Whitbread, A., Blair, G., Konboon, Y., Lefroy, R., Naklang, K., 2003. Managing crop residues, fertilizers and leaf litters to improve soil C, nutrient balances, and the grain yield of rice and wheat cropping systems in Thailand and Australia. Agric. Ecosyst. Environ. 100, 251–263. Wickings, K., Grandy, A.S., Reed, S.C., Cleveland, C.C., 2012. The origin of litter chemical complexity during decomposition. Ecol. Lett. 15, 1180–1188. Xiao, Y., 2012. The analysis of straw burning and use. J. Green Sci. Tecnol. 11, 72–74. Xu, M.G., Lou, Y.L., Sun, X.L., Wang, W., Baniyamuddin, M., Zhao, K., 2011. Soil organic carbon active fractions as early indicators for total carbon change under straw incorporation. Biol. Fert. Soils 47, 745–752. Yan, D.Z., Wang, D.J., Yang, L.Z., 2007. Long-term effect of chemical fertilizer, straw, and manure on labile organic matter fractions in a paddy soil. Biol. Fert. Soils 44, 93–101. Yao, H.Y., Bowman, D., Rufty, T., Shi, W., 2012. Interactions between N fertilization, grass clipping addition and pH in turf ecosystems: Implications for soil enzyme activities and organic matter decomposition. Soil Biol. Biochem. 41, 1425–1432. Zagal, E., Muñoz, C., Quiroz, M., Córdova, C., 2009. Sensitivity of early indicators for evaluating quality changes in soil organic matter. Geoderma 151, 191–198. Zhang, S.R., Wen, J., Li, T., Xu, X.X., Deng, L.J., Gong, G.S., Hu, C., 2012. Soil carbon fractions of restored lands in Liusha River Valley, Sichuan. Ecol. Eng. 40, 27–36. Zibilske, L.M., Bradford, J.M., 2007. Oxygen effects on carbon, polyphenols, and nitrogen mineralization potential in soil. Soil Sci. Soc. Am. J. 71, 133–139.