Effects of Rice-Wheat Rotation and Afforestation on Microbial Biomass Carbon in Coastal Salt-Affected Soils of Eastern China

Pedosphere 27(5): 938–948, 2017 doi:10.1016/S1002-0160(17)60397-7 ISSN 1002-0160/CN 32-1315/P c 2017 Soil Science Society of China ⃝ Published by Elsevier B.V. and Science Press

Effects of Rice-Wheat Rotation and Afforestation on Microbial Biomass Carbon in Coastal Salt-Affected Soils of Eastern China JIN Wenhui, YANG Jingsong∗ , YAO Rongjiang, YU Shipeng, LIU Meixian and XIE Wenping State Key Laboratory of Soil and Sustainable Agriculture, Nanjing Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China) (Received April 11, 2016; Revised August 30, 2017)

ABSTRACT Rice-wheat rotation and poplar afforestation are two typical land use types in the coastal reclaimed flatlands of eastern China. This study investigated two rice-wheat rotation lands (one reclaimed from 1995 to 2004 and cultivated since 2005, RW1, and the other reclaimed from 1975 to 1995 and cultivated since 1996, RW2) and a poplar woodland (reclaimed from 1995 to 2004 and planted in 2004, PW1) to determine the effects of land use types and years of cultivation on soil microbial biomass and mineralizable carbon (C) in this coastal salt-affected region. The results showed that the soil in PW1 remained highly salinized, whereas desalinization was observed in RW1. The total organic C (TOC) in the top soil of PW1 and RW1 did not show significant differences, whereas at a soil depth of 20–30 cm, the TOC of RW1 was approximately 40%–67% higher than that of PW1. The TOC of 0–30-cm soil in RW2 was approximately 37% higher than that in RW1. Microbial biomass C (MBC) and mineralizable C (MNC) exhibited the trend of RW2 > RW1 > PW1. Sufficient nutrition with more abundant C substrates resulted in higher MBC and MNC, and soil respiration rates were negatively correlated with C/N in RW1 and RW2. Nutrient deficiency and high salinity played key roles in limiting MBC in PW1. These suggested that rice-wheat rotation was more beneficial than poplar afforestation for C accumulation and microbial biomass growth in the coastal salt-affected soils. Key Words:

carbon availability, flatland, land use, mineralizable carbon, nutrition availability, total organic carbon

Citation: Jin W H, Yang J S, Yao R J, Yu S P, Liu M X, Xie W P. 2017. Effects of rice-wheat rotation and afforestation on microbial biomass carbon in coastal salt-affected soils of eastern China. Pedosphere. 27(5): 938–948.

INTRODUCTION Numerous studies have analyzed the adverse effects of increased secondary salinity on crop production, soil organic carbon (SOC), microbial activity, and soil structure (such as aggregate dispersion) (Yan and Marschner, 2012; Kamble et al., 2014). Secondary salinity in soils is mainly caused by agricultural operations, such as artificial irrigation (Al-Ghobari, 2011), the application of chemical and organic fertilizers (Kamble et al., 2014), and monocrop plantation (Clarke et al., 2002). Surface soils with shallow groundwater can also accumulate salt through capillary movement (Rengasamy, 2006). High salt concentrations in soils cause increased osmolarity outside the plant roots and microbial cells (Wong et al., 2010) and increased sodium (Na+ ) or chloride (Cl− ) toxicity, which will compete with other cations, interfere with nutrient uptake (Rengasamy, 2006; Grewal, 2010), and eventually reduce crop production and carbon (C) input. Unlike secondarily salinized soils, coastal saline ∗ Corresponding

author. E-mail: [email protected].

soils originate from marine and fluvial deposits containing high salt concentrations and low organic C levels at the onset of soil formation (Jin et al., 2013). In the context of land resource stress, reclaimed coastal saline mudflats represent important land reserve resources. Indeed, in recent decades, many coastal tidal flatlands have been enclosed for land expansion in the developed coastal areas of China. For example, in the coastal areas of Jiangsu Province, China, 1.8 million ha of coastal mudflats were reclaimed from 1996 to 2008, and an additional 2.7 million ha of mudflats are expected to be reclaimed by 2020. These newly reclaimed flatlands are protected from seawater immersion by seawalls, and over time, the salt concentration declines because of rainfall. Vegetation succession proceeds from bare land to salt-tolerant plants, such as Suaeda sala, until Aeluropus littoralis flourishes as the dominant species. Farmers then cultivate the A. littoralis grassland, planting salt-tolerant crops, such as cotton, wheat, and rice. Poplar woodlands are also common landscapes that are initially used as coastal

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windbreaks. After reclamation and cultivation, the salt content in soil declines in the farmlands on the coastal mudflats, but it continues to be seasonally affected by the intrusion of seawater into the groundwater. The SOC in coastal saline soil is always low, and C inputs are restricted by the high salt content in the soil. This factor is important for improving soil quality, increasing water-holding capacity (Laird and Chang, 2013), providing nutrients for plants, and helping to stabilize soil aggregates (Six et al., 2000), among other effects. Additionally, SOC accumulation in soil contributes to decreasing atmospheric greenhouse gases (Setia et al., 2011). Land use and plant life exert substantial influences on SOC by altering the decomposition rates and C input. Many reports have demonstrated that intensive cultivation practices (such as tillage, irrigation, and fertilization) directly impact soil structure and microbial community and can substantially reduce SOC and microbial biomass C (MBC) (Bossio et al., 1998). The MBC is an important indicator of soil fertility and can be effectively used as an index to evaluate soil quality (Yadav, 2012). High MBC is always associated with high organic matter (Sabahi et al., 2010). Microbial biomass accumulation also contributes to C sequestration by generating fungal hyphae and organic macromolecules that improve soil aggregation (Liang et al., 2011). The mineralizable C (MNC), which reflects the bioavailability of the SOC, is also determined by the quality of SOC (J¨ager et al., 2011). Increased soil salinity has been reported to be associated with decreased microbial biomass and microbial activity (Pankhurst et al., 2001). These factors profoundly impact nutrient cycling, soil fertility, and SOC decomposition . Rice-wheat rotation and afforested poplar woodlands are two typical land use types in the coastal mudflats of eastern China. In this study, we selected rice-wheat rotation lands reclaimed over two different periods and a poplar woodland reclaimed during the same period as one of the rice-wheat rotation lands to investigate the effects of these two types of land use and the years of cultivation on soil MBC and MNC in the coastal salt-affected region.

precipitation is 1 100 mm (Wang et al., 2012). The soils in this region were formed from marine and fluvial deposits and always contain high salt concentrations. In the past decades, tidal flatlands were reclaimed in several periods. Rice-wheat rotation and afforested poplar woodlands are two typical land use types in this area. Two rice-wheat rotation lands selected in this study were operated by the same farm, but reclaimed in different periods. One (RW1) was reclaimed from 1995 to 2004, has been cultivated since 2005, and covers 1.83 km2 . The other (RW2) was reclaimed from 1975 to 1995, has been cultivated since 1996, and covers 3.81 km2 . The two rice-wheat rotation lands are separated by a seawall built in 1995. Farming management techniques in RW1 and RW2 were the same. Both were operated using large farming machines, and crop straw was returned to the soil after being shredded by harvesters. The farmlands were irrigated by groundwater, and the nitrogen (N) fertilizer inputs were approximately 600 kg N ha−1 year−1 in recent years. Because RW1 and RW2 were subjected to the same geographical conditions and agricultural management strategies, the effects of rice-wheat rotation on different time scales on microbial biomass can be studied. One studied poplar woodland (PW1) selected in this study was reclaimed in the same period as RW1. The poplar trees were planted in 2004 with no fertilizer input. Given that PW1 and RW1 share the same reclamation history, the effects of the two land use types on soil microbial biomass can be compared.

MATERIALS AND METHODS Study area The mudflats in Dongtai (32◦ 33′ –32◦ 57′ N, 120◦ 07′ –120◦ 53′ E) are representative of northern coastal mudflats in China and cover an area of 3 175 ha. The altitude of the flatland ranges from 1.4 to 5.1 m and the temperature from −7.5 to 35.9 ◦ C. The average annual

Sample collection and laboratory analysis Soil samples were collected in October 2014 after harvesting the rice but before plowing the soil. In each land use studied, 15 soil samples were collected at each soil depth (0–10, 10–20, 20–30, 30–50, 50– 70, and 70–100 cm). After collection, the soils were air dried, ground, and sieved. Soil particle size distribution was determined by the sieve-pipette method (FHZDZTR0007). Soils used for the determinations of electronic conductivity in the 1:5 soil:water extract (EC1:5 ) and pH were sieved using a 0.85-mm sieve and measured with an electrode. The electronic conductivity in the saturated extract (ECe ) was calculated from the EC1:5 value (Li et al., 2014). Soil total organic C (TOC), total N (TN), available N (AN), and available phosphorus (AP) were determined according to Bao (2000). Additionally, the soil bulk density (BD) and field water capacity (FWC) were measured using steel cylinders (Zhang et al., 2006). The labile C pool can exert considerable impacts on ecosystem functioning by influencing the microbial

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biomass and its activity and the transformation and supply of nutrients to vegetation (Belay-Tedla et al., 2009). Acid hydrolysis has been shown to be reasonably accurate for estimating the various SOC pools and is an easier method for the isolation of labile and recalcitrant fractions than physical or biological separation methods (Olk and Gregorich, 2006). In this study, the labile and recalcitrant C pools were separated by a twostep acid digestion with H2 SO4 as described by Rovira and Vallejo (2002). The isolated C pools were designated as labile pool I C (LPI-C), labile pool II C (LPIIC), and recalcitrant pool C (RP-C). The predominant components in LPI-C are polysaccharides from plants (such as hemicellulose and starch) and microorganisms (mostly microbial cell walls). The LPII-C is largely composed of cellulose. The proportion of LPII-C (PLII , %) in the total labile C, the sum of LPI-C and LPII-C, was calculated:

the mean respiration rate at 28 and 35 d of incubation was taken as the basal soil respiration (BSR) (Benbi et al., 2015). The ratio of BSR to MBC was taken as the metabolic quotient (qCO2 , µg CO2 -C h−1 µg−1 biomass C) (Dilly and Munch, 1998). The mineralization quotient (qM) was determined as the ratio of MNC to TOC (µg CO2 -C µg−1 TOC) (Pinzari et al., 1999).

PLII = [LPII-C/(LPI-C + LPII-C)] × 100

RESULTS

(1)

The RP-C mainly contains lignin, as well as suberins, resins, fats, and waxes (Rovira and Vallejo, 2002). The recalcitrance index (RIC , %) was determined as follows: RIC = (RP-C/TOC) × 100

(2)

Five sample replicates were selected from the 0–10 and 10–20 cm depths to analyze soil MBC and MNC in each land area. The selected samples were collected at locations separated by at least 300 m in each land area, and each replicate was collected from three points separated by 1 m. The MBC (expressed as mg kg−1 ) was determined by the chloroform fumigationextraction method (Vance et al., 1987). Soil microbial entropy (qmic ), which is defined as the ratio of MBC to TOC and expressed as µg biomass C µg−1 TOC (Benbi et al., 2015), is another important quantitative indicator of soil C dynamics and can be used to assess soil C accumulation or loss in soil ecosystems. Higher soil microbial entropy generally reflects higher soil C accumulation (Singh et al., 1989). The MNC was determined based on the CO2 evolved during a 35-d incubation period using 25 g soil samples. The soils were wetted to 60% of field capacity moisture and incubated at 25 ◦ C in sealed glass jars, which contained 10 mL of 1 mol L−1 NaOH solution. The CO2 evolved was measured at 1, 4, 9, 14, 21, 28, and 35 d and was expressed as mg CO2 -C kg−1 soil. After each measurement, thorough aeration was performed (Larney et al., 1997). The cumulative amount of CO2 -C evolved over the whole incubation period was taken as MNC, and

Statistical analysis The data were analyzed using the SPSS statistical analysis program (SPSS 16.0). Differences between the studied land use types were investigated using analysis of variance (ANOVA). When significant differences existed at P < 0.05, the data were subjected to least significant difference test (LSD). Additionally, Pearson correlation analysis was used to understand the relationships between the microbial indices and other soil properties.

Soil physicochemical properties Descriptive statistics for the selected soil physicochemical properties in the top soil (0–10 cm) and subsurface soil (10–20 cm) are summarized in Table I. The particle size distribution of a mixed soil sample of the two depths was silt dominant, and the soil textures in the three land use types were generally the same. The BD increased with soil depth in RW1 and RW2, and the minimum BD was observed in the top soil of RW2. The PW1 had higher BD than RW1 and RW2, and no difference was found between the two soil depths of PW1. The FWC and soil nutrients in both the soil depths all exhibited the following order of RW2 > RW1 > PW1. The TN in the top soil of RW2 was approximately 29.3% higher than that of RW1 and 33.9% higher than that of PW1. The AN and AP in the subsurface soil of PW1 were both less than half of that in RW1. These results indicated that long-term cultivation with rice-wheat rotation improved compact soils and increased soil water retention and nutrients. Soil salinity properties in soil profile The salt distribution in soil profile exhibited distinct characteristics in each of the three land use types evaluated (Fig. 1). The salt content in the soil of RW2 was the lowest. The mean ECe of PW1 ranged from 2.09 dS m−1 in the top soil (0–10 cm) to 7.85 dS m−1 in the bottom soil (70–100 cm), and the pH ranged from 8.81 to 9.60, indicating a clear salinization trend. The salt content in the soil of RW1 declined more than that of PW1. The soil pH of RW1 ranged from 8.68 in

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the top soil to 9.15 in the bottom soil, and it ranged from 8.77 to 9.60 in RW2. Both showed similar variation tendencies (Fig. 1). The ionic compositions at 0– 10 and 10–20 cm indicated that Na+ was the dominant cation (Table II). The variations in the bicarbonate ion

(HCO− 3 ) concentration in the three land use types reflected the differences in soil pH. Yu (1984) reported that the soil in coastal mudflats was readily alkalized because the salt in the soil in these land use types varied seasonally and was easily affected by groundwater

TABLE I Descriptive statistics of selected soil physicochemical properties at the soil depths of 0–10 and 10–20 cm under different land use types in coastal mudflats Land use typea) PW1 RW1 RW2

Soil depth cm 0–10 10–20 0–10 10–20 0–10 10–20

Silt

86.2 86.2 85.8 85.8 88.7 88.7

Sand

± ± ± ± ± ±

2.3b) ac) 2.3a 1.8a 1.8a 2.8a 2.8a

% 6.33 ± 6.33 ± 6.97 ± 6.97 ± 1.07 ± 1.07 ±

Clay

0.9a 0.9a 1.5a 1.5a 0.9b 0.9b

8.03 8.03 7.42 7.42 9.78 9.78

± ± ± ± ± ±

1.0b 1.0b 1.3b 1.3b 2.6a 2.6a

Bulk density

Field water Total capacity nitrogen

g cm−3 1.38 ± 0.05a 1.39 ± 0.02a 1.31 ± 0.05b 1.37 ± 0.02a 1.22 ± 0.03d 1.28 ± 0.07c

% 30.4 30.6 33.9 32.1 41.5 36.6

± ± ± ± ± ±

3.0c 0.8c 2.3b 0.5b 0.5a 4.1b

g kg−1 0.56 ± 0.04b 0.33 ± 0.12c 0.58 ± 0.05b 0.59 ± 0.04b 0.75 ± 0.04a 0.72 ± 0.06a

Available nitrogen 39.1 17.8 41.8 40.8 56.1 54.8

± ± ± ± ± ±

Available phosphorus

mg kg−1 1.73b 9.7 8.41c 5.5 3.52b 10.4 3.47b 12.5 3.22a 14.4 8.65a 18.6

± ± ± ± ± ±

2.8c 2.0d 2.1c 0.8c 1.9b 5.2a

a) PW1

= poplar woodland reclaimed from 1995 to 2004; RW1 = rice-wheat rotation land reclaimed from 1995 to 2004; RW2 = ricewheat rotation land reclaimed from 1975 to 1995. b) Means ± standard deviations (n = 15). c) Means followed by the same letter within each column are not significantly different at P < 0.05.

Fig. 1 Distributions of electronic conductivity of the saturated extract (ECe ) and pH in soil profile of 0–100 cm under different land use types in coastal mudflats. Horizontal bars indicate standard deviations of the means (n = 15). See Table I for the detailed descriptions of the land use types PW1, RW1, and RW2. TABLE II Percentages of salt ions in the total cations or anions at the soil depths of 0–10 and 10–20 cm under different land use types Land use Soil Cations typea) depth Na+ PW1 RW1 RW2 a) See

cm 0–10 10–20 0–10 10–20 0–10 10–20

49.7 47.4 52.6 56.2 40.0 45.4

± ± ± ± ± ±

Anions K+

Ca2+

2.2b) ac) 5.7 ± 1.9b 28.7 ± 0.5a 12.1 ± 6.7ab 19.4 ± 1.0a 4.9 ± 2.2b 28.0 ± 2.9a 6.9 ± 3.0ab 23.3 ± 3.0b 10.7 ± 1.3ab 33.9 ± 12.3ab 14.4 ± 6.3a 29.4 ±

Mg2+ 7.5a 1.8a 8.8a 11.9a 2.6a 6.7a

15.9 21.1 14.5 13.6 15.5 10.8

± ± ± ± ± ±

Cl− % 7.7ab 29.7 4.6a 42.3 6.3ab 50.1 6.0ab 43.6 3.2ab 18.9 2.0b 40.8

HCO− 3

SO2− 4 ± ± ± ± ± ±

21.5ab 7.8a 3.0a 2.2ab 6.4b 12.2ab

43.9 24.9 31.6 35.1 54.7 29.6

± ± ± ± ± ±

18.3a 16.2a 0.9a 2.3a 15.0a 13.1a

Table I for the detailed descriptions of PW1, RW1, and RW2. ± standard deviations (n = 15). c) Means followed by the same letter(s) within each column are not significantly different at P < 0.05. b) Means

26.5 28.0 18.3 20.6 25.4 28.3

± ± ± ± ± ±

CO2− 3 3.8a 14.7a 3.2a 1.6a 12.4a 1.4a

0.00 4.82 0.00 0.80 1.03 1.28

± ± ± ± ± ±

0.00b 3.12a 0.00b 1.39a 1.78a 2.21a

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containing abundant Na+ and HCO− 3 . The frequent movements of Na+ and HCO− throughout the soil pro3 file increased the amounts of Na+ and HCO− 3 absorbed by soil colloids; as a result, the soil became alkaline, and the pH increased with soil depth. Soil TOC properties and its pools Fig. 2 demonstrates that the TOC contents decreased with soil depth. The TOC content at the 50cm depth decreased by 78.6%, 82.8%, and 81.8% relative to that in the top soil in PW1, RW1, and RW2, respectively. The contents of TOC were similar in the top soils in PW1 (4.91 ± 0.09 g kg−1 ) and RW1 (4.89 ± 0.32 g kg−1 ), whereas at 20–30 cm, the TOC in RW1 was approximately 67% higher than that in PW1. The mean top soil TOC in RW2 was 6.26 ± 0.32 g kg−1 , and at 20–30 cm, the TOC in RW2 was approximately 37% higher than that in RW1. However, below 50 cm,

the TOC values in RW1 and RW2 were similar, but lower than that in PW1. These results may be due to that the roots of the poplar trees extend deeper into the soil than the roots of rice and wheat, thereby increasing C input in the deep soil in PW1. Table III summarizes the labile and recalcitrant C pools at the 0–10 and 10–20 cm soil depths in the three land use types studied. The LPI-C contents followed the order of RW2 > RW1 > PW1 at both depths, and the LPI-C was higher at the 0–10 cm depth than at the 10–20 cm depth in PW1, but not in RW1 and RW2. Generally, PLII was higher in the top soil (0–10 cm) than in the subsurface soil (10–20 cm) in the three land use types studied, and at each depth, the PLII values exhibited the following order of PW1 > RW2 > RW1. The RIC was lower in PW1 than in RW1 and RW2, and no significant differences were noted between RW1 and RW2. Soil MBC and MNC

Fig. 2 Distribution of total organic carbon (TOC) in soil profile of 0–100 cm under different land use types in coastal mudflats. Horizontal bars indicate standard deviations of the means (n = 15). See Table I for the detailed descriptions of the land use types PW1, RW1, and RW2.

Soil MBC at the 0–10 cm depth was significantly higher than that at the 10–20 cm depth in the three land use types (Fig. 3). At each depth, soil MBC followed the order of RW2 > RW1 > PW1, but no obvious difference was found between RW1 and PW1. Comparing the MBC in RW1 and RW2 revealed that MBC in the coastal salt-affected rice-wheat rotation lands increased as the years of cultivation increased. Kallenbach and Grandy (2011) analyzed MBC in 414 agriculture soil samples and found that the mean value was 365 ± 14.1 mg kg−1 . The highest MBC in this study was 179 ± 18.4 mg kg−1 , observed at a depth of 0–10 cm in RW2. This finding suggests that MBC in the coastal salt-affected rice-wheat rotation lands remains at low levels despite increasing. Differences in land use and years of cultivation did not influence qmic

TABLE III Labile and recalcitrant carbon poolsa) making up the total organic carbon at the soil depths of 0–10 and 10–20 cm under different land use types in coastal mudflats Land use typeb)

LPI-C 0–10 cm

LPII-C 10–20 cm

0–10 cm

PLII 10–20 cm

0–10 cm

RIC 10–20 cm

0–10 cm

10–20 cm

kg−1

PW1 RW1 RW2 a) LPI-C

2.05 ± 0.19c) bd) 2.13 ± 0.31ab 2.71 ± 0.48a

g % 1.58 ± 0.3b 1.89 ± 0.15a 0.93 ± 0.09b 48.0 ± 2.6a 37.3 ± 3.2a 14.3 ± 4.5b 20.0 ± 7.6a 2.40 ± 0.36a 1.75 ± 0.54a 1.30 ± 0.36ab 44.5 ± 4.9a 35.0 ± 9.5a 24.7 ± 2.3a 23.7 ± 4.9a 2.79 ± 0.32a 2.21 ± 0.36a 1.62 ± 0.42a 45.3 ± 7.7a 36.3 ± 3.8a 20.3 ± 2.5ab 26.7 ± 5.7a

= labile pool I carbon, mainly polysaccharides from plants and microorganisms; LPII-C = labile pool II carbon, mainly cellulose; PLII = proportion of LPII-C in the total labile carbon; RIC = recalcitrance index of carbon, i.e., proportion of recalcitrant pool carbon in the total organic carbon. b) See Table I for the detailed descriptions of PW1, RW1, and RW2. c) Means ± standard deviations (n = 15). d) Means followed by the same letter(s) within each column are not significantly different at P < 0.05.

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in RW1 and RW2; thereafter, RW2 had an obviously higher cumulative C mineralization than RW1. The mean qM at the two depths both followed the order of RW1 > RW2 > PW1, but no significant difference (P > 0.05) was noted between the two depths in each land use type (Table IV). The highest BSR was found in RW2, followed by RW1 and PW1. The mean qCO2 values in the rice-wheat rotation lands were higher than those in the poplar woodland (Table IV). Correlations between microbial indices and other soil properties

Fig. 3 Microbial biomass carbon (MBC) at the soil depths of 0– 10 and 10–20 cm under different land use types in coastal mudflats. Vertical bars indicate standard deviations of the means (n = 5). Bars with the same uppercase letter within a given soil depth are not significantly different at P < 0.05, and those with the same lowercase letter within a given land use type are not significantly different at P < 0.05. See Table I for the detailed descriptions of PW1, RW1, and RW2.

significantly (Table IV), indicating that soil microbial entropy is not a sensitive indicator of the soils in the coastal salt-affected areas. The higher qmic at the 0–10 cm depth compared to the 10–20 cm depth in RW1 and RW2 may be attributed to the quicker return and recycling of crop residues in the top soil, where the nutrients are more available to soil microbial activities (Follett, 1997). During the whole incubation period, the mean cumulative C mineralization values at the 0–10 and 10– 20 cm depths in PW1 were lower than those in RW1 and RW2 (Fig. 4), and especially after the 9th day, the differences were significant. Before the 15th day, the mean cumulative C mineralization values were similar

The Pearson’s correlation coefficients between soil microbial indices and other soil properties in each land use type are summarized in Table V. The results showed that in all three land use types studied, the MBC and AN were significantly positively correlated, and the MNC was highly correlated with labile pool C (mainly labile pool I). Positive relationships between AP and MBC (or MNC) were found only in PW1. In RW1 and RW2, both BSR and qCO2 increased as C/N decreased (Table V), whereas the microbial indices in PW1 showed no obvious relationship with C/N, suggesting that excess N input accelerates SOC decomposition. In PW1, higher FWC was always accompanied by lower BSR, unlike in RW2. This may reflect the effects of soil water content on MNC and BSR because soil water content of the incubated soils varied according to FWC. Negative relationships between BD and MNC were found in RW1 and RW2. These results also indicated that in PW1, both MNC and BSR were limited by ECe and pH. The ECe also negatively affected MBC and qmic in RW1 and RW2.

TABLE IV Microbial indicesa) at the soil depths of 0–10 and 10–20 cm under different land use types in coastal mudflats Soil depth

Land use typeb)

C/N

qmic

qM

BSR

qCO2

8.85 8.57 8.19 9.56 7.93 8.68

µg biomass C µg−1 TOCc) 0.026 ± 0.008Aa 0.027 ± 0.003Aa 0.029 ± 0.004Aa 0.023 ± 0.002Aa 0.020 ± 0.003Ab 0.023 ± 0.003Ab

µg CO2 -C µg−1 TOC 0.070 ± 0.009Ba 0.085 ± 0.005Aa 0.081 ± 0.002Aa 0.075 ± 0.009Aa 0.080 ± 0.010Aa 0.076 ± 0.013Aa

µg CO2 -C g−1 soil h−1 0.14 ± 0.05Ba 0.18 ± 0.04Ba 0.34 ± 0.07Aa 0.07 ± 0.03Bb 0.21 ± 0.02Aa 0.26 ± 0.06Ab

µg CO2 -C h−1 µg−1 biomass C 1.14 ± 0.43Ba 1.37 ± 0.39ABb 1.88 ± 0.23Ab 1.04 ± 0.38Ba 2.30 ± 0.28Aa 1.90 ± 0.80Aa

cm 0–10

10–20

PW1 RW1 RW2 PW1 RW1 RW2

± ± ± ± ± ±

0.54d) Abe) 0.11Aa 0.61Aa 0.88Aa 0.58Bb 0.49ABa

a) q mic = soil microbial entropy; qM = mineralization quotient; BSR b) See Table I for the detailed descriptions of PW1, RW1, and RW2. c) Total

= basal soil respiration; qCO2 = metabolic quotient.

organic carbon. ± standard deviations (n = 5). e) Means followed by the same uppercase letter within a given soil depth are not significantly different at P < 0.05, and those by the same lowercase letter within a given land use type are not significantly different at P < 0.05. d) Means

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Fig. 4 Cumulative carbon mineralization (Cmin ) during incubation for 35 d at 25 ◦ C at the soil depths of 0–10 and 10–20 cm under different land use types in coastal mudflats. Vertical bars indicate standard deviations of the means (n = 5). See Table I for the detailed descriptions of the land use types PW1, RW1, and RW2. TABLE V Correlation coefficients between microbial indicesa) and other soil propertiesb) under different land use types in coastal mudflats Land use typec)

Microbial SOC index

LPI-C

PW1

MBC MNC qmic qM BSR qCO2 MBC MNC qmic qM BSR qCO2 MBC MNC qmic qM BSR qCO2

0.928 – 0.833 – – −0.911 – – – – – 0.645 – −0.962 0.872 −0.632 – −0.943 – – −0.755 – – 0.899 – −0.615 0.790 – – – – – – – – –

RW1

RW2

0.734 0.899 – – 0.736 – 0.931 – 0.874 – – −0.783 – −0.660 – −0.920 −0.646 −0.789

PLII

RIC −0.785 −0.632 – – – – – – – – – – – −0.887 – −0.611 – –

TN

AN

0.642 – – – 0.625 – – – – – – –

0.681 0.687 – – – – 0.702 –

0.917 – 0.751 – – –

0.638 −0.723 – – 0.741 – – −0.611 −0.773

AP 0.804 0.658 0.704 – – – – – – −0.702 0.750 – – – – – – –

C/N

FWC

BD

ECe

pH

– – – – – – – – – – −0.787 −0.605 −0.745 – −0.917

– – – −0.625 −0.626 – 0.804 0.865 0.779 –

– –

– −0.696 – – −0.813 −0.712 −0.736

−0.679 −0.885 – – −0.776

−0.768 −0.613

−0.892 – 0.866 – 0.787 0.816 –

0.722 0.741 – – −0.899 −0.909 −0.861 – 0.705 0.903 – −0.849 – −0.788 −0.862 −0.790

−0.674 – – −0.689 −0.741 – −0.867 – – –

– −0.701 – −0.626 – – −0.753 – −0.812 – – –

a) MBC

= microbial biomass carbon; MNC = mineralizable carbon; qmic = soil microbial entropy; qM = mineralization quotient; BSR = basal soil respiration; qCO2 = metabolic quotient. b) SOC = soil organic carbon; LPII-C = labile pool II carbon, mainly cellulose; P LII = proportion of LPII-C in the total labile carbon; RIC = recalcitrance index of carbon, i.e., proportion of recalcitrant pool carbon in the total organic carbon; TN = total nitrogen; AN = available nitrogen; AP = available phosphorus; FWC = field water capacity; BD = bulk density; ECe = electronic conductivity of the saturated extract. c) See Table I for the detailed descriptions of PW1, RW1, and RW2.

DISCUSSION Effects of C availability on microbial biomass and activity De Nobili et al. (2001) and Demoling et al. (2007) reported that the growth of microbes was mainly influenced by organic C (OC) availability in all soils. Additionally, native soil organic matter has been shown to be primarily supplemented by inputs of fresh sub-

strates from plant roots, root exudates, and other plant and animal residues (De Nobili et al., 2001). Because the main components of root exudates are lowmolecular-weight organic compounds (such as sugars), which are easily decomposable and can stimulate microbial growth and activity, the soluble and insoluble OC from organic residues can be utilized by fast-growing microbes or decomposed by slow-growing microbes (Blagodatsky et al., 2000; Landi et al., 2006).

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Therefore, the MBC values in the top soils of PW1, RW1, and RW2 were all higher than those in the subsurface (Fig. 3). The highest TOC was found at the 0– 10 cm depth and mostly accumulated at the 0–30 cm depths in the three land use types studied (Fig. 2). Furthermore, the organic matter decreased with increasing depth and was reflected indirectly by the MBC contents because of the reduced critical energy and substrates for microbes provided by the decreasing plant residues, such as roots and exudates (Follett, 1997). The labile and recalcitrant C distributions in the soil profile are related to the spatial distribution of plant root residual inputs and decomposition (Cheng et al., 2006). The relatively low RIC in PW1 was caused by the low TOC contents compared to RW1 and RW2 (Table II). The higher PLII in PW1 implies that its C input resources differ from those in RW1 and RW2. Among the labile pool C resources, most of which are carbohydrates, cellulose is the most resistant to biodegradation. The PLII has been reported to decrease as decomposition proceeds (Rovira and Vallejo, 2002). Follett (1997) reported that soil microbes utilized only labile OC when soil OC input was limited, and once the labile OC supply was exhausted, soil microbial biomass began to decrease. This may account for the positive relationships between MBC and LPIC in PW1, where the TOC and labile C were lower than in RW1 and RW2. Soil microorganisms, which depend on the availability of C and nutrients, regulate C mineralization (Garc´ıa-Pausas et al., 2008; MolinaHerrera and Romany´ a, 2015). Furthermore, the MNC was positively related to the LPI-C, and during the incubation period, it followed the order of RW2 > RW1 > PW1, mainly because the TOC and labile C were lower in PW1 and RW1 than in RW2.

who found that the limitations imposed by N and P on respiration increased with soil depth; this finding implies that the subsurface of PW1 has a relatively inferior nutrient status. In addition, Manzoni et al. (2008) and Sinsabaugh et al. (2013) revealed that when growing on nutrient-poor substrates, microorganisms were prone to dispose of C via respiration so that the substrate could meet their nutritional demands. This may explain why qM in the subsurface of PW1 was higher than that in the top soil. In RW1 and RW2, significantly positive correlations between the MBC and AN were observed, whereas BSR and qCO2 exhibited negative correlations with C/N (Table IV). It should be noted that these results do not completely coincide with those of previous studies (Treseder, 2008; Lu et al., 2011), suggesting that inorganic fertilizers may suppress microbial biomass growth. Compared to PW1, fertilization management ensured sufficient N input in RW1 and RW2, facilitating the growth of crop and underground biomass and thus improving the C resources for microbial biomass development. In contrast, it was reported that sufficient N was correlated with enough C for the maintenance of microorganisms’ activities (Dignac et al., 2002; Guo and Gifford, 2002) and accelerated OC mineralization, which was indicated by higher MNC and BSR in RW1 and RW2. However, this trend does not contradict the fact that increased microbial biomass accompanies high microbial activity.

Effects of nutrient availability on microbial biomass and activity Organic compounds from plants are normally low in N and P, whereas microbes contain predominately proteins and other N- and P-rich compounds. Thus, large amounts of N and P should be required for microbial growth (Sylvia et al., 2005). In PW1, the MBC was significantly positively correlated with TN, AN, and AP. Therefore, the growth of microbial biomass was limited by nutrients (N and P), especially at the 10–20 cm soil depth, where TN, AN, and AP were 43.7%, 54.5%, and 43.3%, respectively, lower than in the top soil. The MNC of PW1 in the top soil, which was approximately 45% higher than in the subsurface (Fig. 4), increased as AN and AP increased (Table IV). Similar results were reported by Fierer (2003),

Effects of salinity and water content on microbial biomass and activity In PW1, MNC and BSR were significantly negatively correlated with ECe and pH, which is consistent with previous studies (Yuan et al., 2007; Setia et al., 2011). Additionally, previous research also reveals that respiration decreases as salinity increases, but increases as sodicity increases (Saviozzi et al., 2011). The reason for these trends might be that the original communities in these studies were not salt tolerant. The soil in PW1 originated from coastal saline soils, and thus, the original community was highly salt tolerant. Hence, the negative effect of salinity on soil respiration is likely indirect. In the original coastal saline soils, plant growth is poor because of high soil salinity, which results in low SOC. Under this condition, the SOC is frequently too low for the production of microbial biomass because of the low organic matter input (Yuan et al., 2007). In other words, the salinity influences the availability of C and N and limits the activities and growth of soil microbes. The negative relationships between qCO2 and ECe in PW1 are contrary to the results reported by

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Wong et al. (2008), who showed that as salinity increased, the qCO2 also increased. One explanation may be that C availability in the presence of high salinity limits microbial activity. Because of the desalinization in PW1, the increased above- and belowground biomass increased the C input and provided additional nutrient resources for microbial activity. Soil FWC, which represents the water retention capacity of soil, is an important physical property of soil. In this study, it was used to indicate soil water content during the soil incubation period. Microbial activity is strongly affected by soil water content, primarily because of the balance between gas and solute diffusion, which are limiting processes (Schjønning et al., 2011). Furthermore, low water content limits the diffusion of soluble substrates in soil, whereas high water content limits oxygen diffusion (Skopp et al., 1990). Some studies also revealed that soil CO2 evolution increased as water was added within a certain range (Miller and Johnson, 1964) and declined near saturation because of limited O2 (Skopp et al., 1990). The opposite relationships between FWC (or water content) and BSR in PW1 and RW2 may be attributed to the different water tolerance of soil microbial communities. The negative relationships between FWC and BSR in PW1 may imply that O2 limits the microbial activity in the presence of high water content. However, in RW2, the microbial community is accustomed to a high water content. As a result, as soil water content increased, the C availability also increased. This effect can induce high MNC and BSR. Furthermore, the water content also regulates the osmotic potential in salt-affected soils (Sall et al., 2015). Low water content can elevate the osmolarity outside microbial cells. It should be noted that Na+ was the dominant cation in these soils (Table II). However, Na+ concentrations in the halophilic bacteria cytoplasm are always lower than those in the surrounding medium. In addition, exporting Na+ from the cell against the concentration gradient consumes energy (Oren, 1999) and diverts resources from growth to survival mechanisms (Schimel et al., 2007). This may be one reason why the BSR was negatively related to FWC in PW1 and why the Na+ concentration was the highest in RW1. It may also indicate why qCO2 increased as the water content decreased. Effects of land uses on microbial biomass and activity Benbi et al. (2015) showed that cultivation caused 21%–36% depletion in soil TOC compared to uncultivated soils in northern India and that rice-wheat systems had significantly lower rates of soil C rehabilita-

tion than agroforestry systems. In addition, numerous studies reported that disturbances in cultivation depleted the TOC pool and inhibited microbial biomass growth (Elliott, 1986; Allison and Martiny, 2008; Meier et al., 2008). In contrast, in the coastal salt-affected reclamation flatlands of this study, the TOC accumulated in the rice-wheat systems was higher than that in the poplar woodland reclaimed during the same period. Furthermore, after a longer reclamation period and more years of cultivation, the TOC in the rice-wheat system was found to increase significantly. According to the discussion above, the main reasons could be summarized as follows. Firstly, the original compact soil texture was broken by tillage, which may also have reduced soil BD. This process aggravated water flow and material interchange. In RW1 and RW2, tillage has reduced soil BD, increased soil pores, and accelerated material interchange between the top and subsurface soils. All of these effects facilitated water and air flow and increased nutrient availability for microbial biomass growth. Secondly, water management accelerated salt leaching. Compared to the salt content in the soil of PW1, that in RW1 declined to a greater extent along the soil profile because of irrigation. Thus, the water management strategy applied in the rice-wheat rotation system accelerated the desalinization processes and alleviated the osmotic stress affecting plant growth and microorganisms. Thirdly, fertilization improved soil nutrient availability. The nutrients required for plant and microbial biomass growth were provided by the additional fertilization inputs into the ricewheat rotation system. In contrast, N and P were deficient in the poplar woodland, inhibiting microorganism development. Finally, all of these factors helped to improve soil quality and increase the C input in the ricewheat rotation land and increase microbial biomass growth. However, their long-term effects on changes in soil C require further study. CONCLUSIONS Compared to poplar afforestation, rice-wheat rotation contributed more to soil desalinization and C accumulation in coastal salt-affected soils. Nutrient deficiency seemed to be an important limitation on MBC in the soil of afforested land, whereas in the rice-wheat rotation systems, tillage accompanied by irrigation and fertilization management accelerated salt leaching and improved soil nutrition and C availability, thereby benefiting the growth of microbial biomass. In addition, both TOC and MBC increased as the years of cultivation increased in the rice-wheat rotation systems. In

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conclusion, these cultivation practices facilitated better soil desalinization and nutrition status, benefiting C accumulation and microbial biomass growth in ricewheat systems in coastal salt-affected soils.

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