Plant and Soil

, Volume 429, Issue 1–2, pp 335–348 | Cite as

Long-term fertilization management affects the C utilization from crop residues by the soil micro-food web

  • Shuyan Cui
  • Siwei Liang
  • Xiaoke Zhang
  • Yingbin Li
  • Wenju Liang
  • Liangjie Sun
  • Jingkuan Wang
  • T. Martijn Bezemer
  • Qi Li
Regular Article


Background and aims

Crop residue decomposition is a major component of carbon (C) cycling and provides energy and nutrients to the soil micro-food web. An in-situ field experiment was conducted to examine how exogenous organic C is incorporated into the soil micro-food web and how this is influenced by four different fertilization treatments: organic manure (M), urea fertilizer (U), the combined application of organic and urea fertilizer (MU) and unfertilized control.


The amount of 13C-enriched maize remained was traced in microbial phospholipid fatty acids (PLFAs) and in different trophic groups of the soil nematode community after a 183-day decomposition period.


The fertilization type influenced the incorporation of residue into the microbial community. Soil bacterial and fungal PLFAs utilized the least 13C-labeled crop residues in the U treatment. Both the nematode bacterial and the fungal pathways utilized more crop residues in the M treatment than in other treatments.


Given the ecological services provided by the soil organisms, our results suggest that long-term manure application increases the soil C pool directly. This also leads to more C from crop residues utilized by the soil food web, which in turn, can benefit crop growth or C accumulation in agroecosystems.


Stable 13C isotope Crop residue incorporation Long-term fertilization Micro-food web 


Soils are of central importance for delivering ecosystem services, such as food production and mitigation of climate change. These services strongly depend on C sequestration and are regulated by soil biota (de Vries et al. 2013). Agricultural management such as fertilizer application can influence the community composition and activity of soil biota (Frey et al. 2008) and lead to changes in ecosystem functioning (Altieri 1999). Previous research has reported that organic fertilization can increase the microbial biomass and the abundance of soil nematodes, and the increase of microbivorous nematodes may further increase the mineralization of nutrients immobilized in the microbial biomass (Chu et al. 2007; Ferris et al. 1998). The addition of chemical fertilizers can also alter the structure and composition of the microbial community, but typically results in a decrease in the diversity of the nematode assemblage (Caravaca et al. 2002; Ros et al. 2006). Such effects may also influence the functions of agroecosystems, such as C sequestration in the soil (Six et al. 2006).

The decomposer food web consists of a wide variety of organisms and has been classified into three energy channels according to the basal resources they use, namely bacteria, fungi or plant roots (Moore et al. 2005). Evidence suggests that the root channel is the major energy supplier of the soil food web (Pollierer et al. 2007). Agroecosystems that are dominated by bacterial or by fungal energy channels often differ in nutrient cycling and C sequestration (Six et al. 2006). In a Hapli-Udic Cambosol of Northeast China, Liang et al. (2009) found that after 20 years of organic manure application, the bacterial-based energy channel dominated in soil food webs possible due to high nutrient availability in the soil (Leroy et al. 2009; Neher 2010; Ugarte et al. 2013). In contrast, the fungal-based energy channel often dominates in soils with lower resource availability or resources that are of low quality (Fierer et al. 2009; Gebremikael et al. 2016). Although previous studies reported that fertilization management changed the structure and composition of the soil biotic community (Neher et al. 2003, 2005; O'Lear et al. 1996; Reed et al. 2009), shifts between bacterial and fungal energy channels within soil food webs and the consequences of such shifts for incorporating C into the soil food web remain poorly understood.

The interplay among crop residues, microorganisms and soil organic C (SOC) pools are critical for understanding C fluxes through the plant-soil system in agroecosystems (Yevdokimov et al. 2006). Studying C utilization by specific organisms is possible through isotope techniques (Elfstrand et al. 2008). This technique has been successfully used to study utilization of plant or straw by soil microbial communities through examining the incorporation of plant 13C into microbial phospholipid fatty acids (PLFAs) (Denef et al. 2009; Kohl et al. 2015; Rubino et al. 2010) and soil fauna (Albers et al. 2006; Chahartaghi et al. 2005; Crotty et al. 2014; Kudrin et al. 2015). In a 14 CO2 pulse labeling experiment, for example, bacterivorous nematodes incorporated more root-derived C than fungivorous nematodes after labeling 16 days (Pausch et al. 2016). An et al. (2015) reported that the competition of soil microbes for maize straw C as microbial substrate depended on the level of soil fertility. However, until now, most studies focused on the C derived from recent photosynthate or from roots over short time periods, typically less than one month (Ostle et al. 2007; Pausch et al. 2015). Our knowledge about how crop residue is incorporated into the soil micro-food web under field conditions over an entire growth period and how this is influenced by long-term fertilization is scarce.

To quantify how fertilization influences the crop residue C utilization by the soil micro-food web, we performed an in-situ field experiment at a long-term fertilization experimental station running for 28 years. We applied 13C-enriched maize residue to soil in plots exposed to four different fertilization treatments to trace C from the decomposing maize residue into different components of the soil micro-food web. We hypothesize that the SO13C and the metabolism of the maize residue will be greater in the manure treatments than in the urea fertilizer treatment, and the total amount of crop residue-C in soil microbes and nematodes will also be higher in treatments fertilized with manure than in treatments fertilized with urea fertilizer as organic fertilization can increase the microbial biomass and the abundance of soil nematodes (Briar et al. 2007). Further, as decomposed C sources such as maize residue often promote the bacterial energy channel within the soil food web (Pausch et al. 2016), we also hypothesized that the bacterial channel will have more crop residue-C than the fungal channel, and the strength of these channels will depend on the fertilization treatment with higher bacterial channel found in the treatments with manure applications.

Materials and methods

Site description and materials

This study was conducted at the long-term fertilization experimental station of Shenyang Agricultural University, Northeast China (41°49’N, 123°34′E). The mean annual temperature and precipitation are 7.9 °C and 705 mm, respectively. The long-term fertilization experiment was initiated in 1987 and has been maintained since. The soil is classified as Hapli-Udic Cambisol (FAO-UNESCO 1988). The experiment followed a complete randomized design with four treatments including unfertilized control (CK), application of organic manure (M, 135 kg N ha−1 year−1), application of urea fertilizer (U, 135 kg N ha−1 year−1), and combined application of organic manure (67.5 kg N ha−1 year−1) with urea (67.5 kg N ha−1 year−1) (MU). There were three replicate plots for each treatment; the area of each individual plot was 7.20 m × 9.60 m. The manure used was pig compost containing 22.53 ± 6.11% organic C (means ± SD, range from 15.00 to 31.30%), 2.20 ± 0.97% N (means ± SD, range from 1.00 to 3.42%) on a dry weight basis. Yearly, maize (Zea mays L.) was sown at 5 cm depth in early May and manually harvested in October followed by conventional tillage, the aboveground maize residues were annually removed from the field. Field management followed local practices during the experiment period, about 10 days after sowing, 50% of atrazine and acetochlor were used as herbicides in each plot at the rates of 1.50 kg ha−1 and 6.00 kg ha−1, respectively. No pesticides were used during the study period (Liang et al. 2009).

Production of 13C-labeled maize residue

During the seedling, shooting and tasseling stage in 2014, 20 maize plants were 13C pulse-labeled in a plot at a different location. 13CO2 was generated through a reaction between 30 ml of 2 mol L−1 HCl and 1.89 g Na213CO3 (99 atm% 13C, Sigma-Aldrich) to obtain a 13CO2 concentration of approximately 400 μl L−1. Portable labeling chambers (2.20 m length × 0.50 m width) covered the plants and consisted of a transparent sheet fitted around a steel frame (height adjusted). The labeling process started at 8:00 am on a bright and sunny day and lasted for 6 h on three consecutive days during each growth stage. A detailed description of the chamber system and labeling process is given by An et al. (2015). The labeled residues were homogenized, dried at 60 °C for 12 h and then finely ground (< 0.50 mm) for storage in sealed jars. The 13C-labeled straw residue had a C concentration of 40.45%, and the δ 13C value of labeled straw residue was 640‰.

Experimental design

Two cylindrical steel rings with a diameter of 50 cm and a height of 50 cm were randomly located within each plot as two subplots. One subplot was used for 13C-labeled maize residue addition, the other subplot without residue addition served as control. Approximately 45 kg of top soil (0–20 cm) was excavated from each subplot on April 28, 2015. Residue was added in a ratio of 0.20 g 13C-labeled maize residue per 100 g soil for the subplot with residue addition. After thoroughly mixing, the soil was put back immediately and packed to 20 cm depth to maintain a constant bulk density (1.13 g cm−3). The soil in the control subplot was also excavated from each plot and then mixed and returned in the same manner without residue addition. One maize plant was then planted in each subplot. Seeding rows were 60 cm wide for maize cultivation in the rest of the plot.

After maize harvest, soil samples were collected from all the subplots on 28th October, 2015, hence the decomposition period of the maize residue was 183 days (from April 28 to October 28, 2015). From each subplot (with and without residue addition), five soil cores of 2.50 cm diameter (0–20 cm depth) were randomly taken and homogenized into one sample. In total, there were 24 soil samples (4 treatments × 3 replicates × 2 subplots).

Soil physicochemical analysis

Soil moisture (SM) was determined by drying at 105 °C for 8 h. The total soil organic carbon (TOC) and total nitrogen (TN) were determined by an automatic elemental analyzer (Elemental Analyzer System Vario MACRO cube, Germany, standard deviation <0.20% rel.). Soil pH was determined with a glass electrode in 1:2.5 soil:water (w/v). Values of δ13C in the SOC were measured by a MAT 253 isotope ratio mass spectrometer (Thermo Electron, Bremen, Germany, sensitivity: 600 CO2 molecules per 44 ion mass).

Extraction and analysis of soil PLFA

Microbial community structure was assessed by phospholipid fatty acid (PLFA) analysis. Soil samples for PLFA analysis were sieved through 2 mm. All visibly remaining plant material was carefully removed with forceps. The PLFA extraction, quantification, and δ13C analysis methods were as described in other studies (Bossio and Scow 1995; Denef et al. 2007; Gomez et al. 2014). Briefly, the lipids were extracted from 4 g of freeze-dried soil with a single-phase chloroform-methanol-citrate buffer (1:2:0.8) on a horizontal shaker (250 rpm) for two and half hours at room temperature. After centrifugation for 10 mins at 4000 rpm, the supernatant was transferred to another glassware tube and the soil vortexed and re-extracted for 2 h with an additional volume of buffer (7.60 mL). The combined supernatant was split into two phases by adding citrate buffer (16 mL) and chloroform (16 mL) and left overnight to separate. The CHCl3 layer was then transferred to a new tube and dried under N2 at 30 °C. Phospholipids were separated from neutral lipids and glycolipids on standard SPE tube (6 mL, 500 mg, Part No 5982–2265, Supelco Inc., Bellefonte, PA, USA). The tube was first conditioned with CHCl3 (5 mL). The lipids were then transferred into the tube with CHCl3 (3 × 250 μL). Neutral lipids and glycolipids were eluted with chloroform (8 mL) and acetone (16 mL) separately. Phospholipids were obtained from methanol elution (8 mL) and dried under N2. For quantification, the internal FAME standard methy1 nonadecanoate fatty acid (19:0, Sigma-Aldrich, St. Louis, MO, USA) was added to the samples before methanolysis. Samples were analyzed with a Thermo Finnigan Trace GC-MS system. For δ13C determination, the 13C/12C ratios of individual PLFAs were determined using a Thermo Scientific Trace GC Ultra attached to a Finnigan MAT 253 IRMS (CuO/Pt Finnigan MAT Mark I combustion interface maintained at 850 °C), as described by Rubino et al. (2010).

The following PLFA biomarkers were used: bacterial PLFA: i15:0, a15:0, i16:0, i17:0 and a17:0; cy17:0, cy19:0, 16:1ω7c, 18:1ω7c (Bach et al. 2010), fungal PLFA: 18:2ω6c (Briar et al. 2011).

Extraction and analysis of soil nematodes

Soil nematodes were extracted from 100 g of fresh soil using a modified cotton-wool filter method (Oostenbrink 1960; Townshend 1963). The extractions were used for identification (at least 100 nematodes) to the genus level using a microscope (OLYMPUS BX51) at 100 × magnification (resolution: 0.25 μm) according to Bongers (1994) and Ahmad and Jairajpuri (2010). After identification (within one week), the same extraction of each sample was used to classify nematodes into different trophic groups (bacterivores, fungivores, plant-parasites and omnivores-predators) (Yeates et al. 1993). Nematodes of each trophic group in each soil sample were hand-picked using a cow eyelash under a dissecting microscope (LEICA DFC290), and transferred to a pre-weighed tin capsule (11 × 6 mm) containing one drop of deionized water. There were four capsules for each soil sample, one for each trophic group. The tin capsules containing the different nematode trophic groups were dried for 2 days at 60 °C, and then weighed again to obtain dry weights for each trophic group. The nematode samples were analyzed for δ13C using a stable isotope ratio mass spectrometer (Thermo Finnigan, DELTA Plux XP) interfaced with an elemental analyzer (Flash EA 1112). As nematode samples contained very low amounts of C, the Elemental Analyzer (EA) was fitted with smaller oxidation and reduction reactor tubes to allow lower carrier gas flow and increased sensitivity (Langel and Dyckmans 2014; Pausch et al. 2015).

The average fresh body mass of each nematode genus was estimated according to We then estimated dry weights of nematodes as 20% of fresh weight and the proportion of C in the body as 52% of dry weight (Persson et al. 1980). Based on the abundance and the biomass of the different trophic groups, we then calculated the stable C isotope values of nematodes per g dry soil.

To quantify the nematode bacterial and fungal energy channel in the micro-food web, we summed the C amount of crop residue (13C) of all nematode trophic groups contributing to these channels. Bacterivores and fungivores contributed fully to the bacterial and fungal channels, respectively. Omnivores and predators were not separated but treated as omnivores-predators. For omnivores-predators at the top trophic level, the contribution to each energy channel was calculated using density dependent feeding preferences (D) (Holtkamp et al. 2008). We assumed that feeding on a particular prey depends on the biomass of this prey (Hunt et al. 1987), each nematode energy channel was quantified as below:
  1. 1)

    13CBEC = 13CB + DB × 13COP

  2. 2)

    13CFEC = 13CF + DF × 13COP

  3. 3)

    Dij = WijBi /\( {\sum}_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{W}}_{\mathrm{i}\mathrm{j}}{\mathrm{B}}_{\mathrm{i}} \)


Where 1) 13CBEC is the amount of 13C-maize residue of the nematode bacterial energy channel, 13CB is the amount of 13C-maize residue of the bacterivores, 13COP is the amount of 13C-maize residue of the omnivores-predators. DB is the density dependent feeding preference of omnivores-predators for the bacterial energy channel. 2) 13CFEC is the amount of 13C-maize residue of the nematode fungal energy channel, 13CF is the amount of 13C of the fungivores, 13COP is the amount of 13C-maize residue of the omnivores-predators. DF is the density dependent feeding preference of omnivores-predators for the fungal energy channel. 3) Dij is the density dependent feeding preferences of j (predator) on i (prey), Wij is the density independent feeding preference of j on i. We assumed that all omnivores-predators had the same feeding preference. Therefore, the preference factor W for omnivores-predators feeding on bacterivores, fungivores, and plant-parasites was assumed to be 1 (Hunt et al. 1987). The number of nematode trophic groups is represented by n, and Bi is the 13C incorporation of prey species i (ng g−1 soil).

Isotope mass balance

The isotope ratios are reported in terms of δ13C (‰) values (Peterson and Fry 1987).
$$ {\updelta}^{13}\mathrm{C}\ \left({\mbox{\fontencoding{U}\fontfamily{wasy}\selectfont\char104}} \right)=\left({\mathrm{R}}_{\mathrm{sample}}/{\mathrm{R}}_{\mathrm{PDB}}-1\right)\times 1000 $$
where Rsample and RPDB is the 13C/12C ratio of sample and the Pee Dee Belemnite (PDB) standard, respectively.
As during the methylation step an additional C atom is added to the fatty acid molecule, the δ13C of each PLFA molecule was corrected using the mass balance equation:
$$ {\mathrm{n}}_{\mathrm{c}\mathrm{d}}{\updelta}^{13}{\mathrm{C}}_{\mathrm{c}\mathrm{d}}={\mathrm{n}}_{\mathrm{c}}{\updelta}^{13}{\mathrm{C}}_{\mathrm{c}}+{\mathrm{n}}_{\mathrm{d}}{\updelta}^{13}{\mathrm{C}}_{\mathrm{d}} $$

Where n is the number of C atoms, nc is the number of C atoms of underivatized compounds, nd is the number of C atoms of derivatized agents (Methanol, nd = 1 and the δ13C value of methanol was −29.33‰ measured by GC/IRMS), and ncd is the number of C atoms of corresponding derivatized compounds (Dungait et al. 2011; Pan et al. 2016; Tavi et al. 2013).

The fraction f of C derived from the maize residue in all C pools (SOC, PLFA C, nematode biomass C) was calculated using a mixing model (de Troyer et al. 2011):
$$ \mathrm{f}=\left({\updelta}^{13}{\mathrm{C}}_{\mathrm{sample}}-{\updelta}^{13}{\mathrm{C}}_{\mathrm{control}}\right)\times 100/\left({\updelta}^{13}{\mathrm{C}}_{\mathrm{maize}}-{\updelta}^{13}{\mathrm{C}}_{\mathrm{control}}\right) $$

Where the δ13Csample and δ13Ccontrol refer to the δ13C value in the subplots with maize residue addition and the corresponding subplot that did not receive any residue, respectively, and δ13C maize (640‰) is the δ13C value of the initially added maize residue.

The amount of Cmaize incorporated into a given fraction (i.e. physical fraction, FAME, nematode) was calculated with the following equation (Blaud et al. 2012):
$$ {\mathrm{C}}_{\mathrm{incorporated}}={\mathrm{C}}_{\mathrm{pool}}\times \mathrm{f}/100 $$

Where Cpool is the amount of C in the different pools (SOC, PLFA C, nematode biomass C).

The subplot in each plot that did not receive residue was needed to calculate the fraction f of C derived from the maize residue in all C pools by the isotopic mixing model, hence this study was not designed to examine the effects of residue addition. However, to test whether residue addition affected the soil biotic and abiotic characteristics, a general linear model analysis designed for split-plot was used with fertilization treatment and residue (nested in plot) as fixed factors. These results are presented in the Table 1. Residue addition only slightly influenced the soil pH, but the fertilization effects showed similar trends in treatments with and without residue additions (Table S1, S2, S3). Other soil characteristics were not significantly affected by residue addition.
Table 1

Effects of fertilization and residue addition on soil properties, soil microbial and nematode community






Basic soil properties





















Concentration in PLFA

(nmol g−1 soil)

Bacterial PLFA




Fungal PLFA




Nematode Biomass

(μg g−1 soil)

















*,** indicate significant differences at P < 0.05 and P < 0.01, respectively

Statistical analyses

We used one-way ANOVA followed by Tukey’s multiple comparison tests in SPSS version 19.0 (SPSS Inc., Chicago, IL) to compare the differences of each parameter among the fertilization treatments. Differences at P < 0.05 level were considered to be statistically significant. All data for ANOVA analyses were checked for normality (visual inspection of the Histogram) and for homogeneity of variances (Levene’s test). If necessary, the data were transformed to meet the assumptions of the ANOVA analyses. Principal component analysis (PCA) was performed to study soil microbial community and nematode community structure in different fertilization treatments based on the relative abundance of biomass in each PLFA and nematode genera. We used the standard settings in the program CANOCO (CANOCO version 5.0; ter Braak and Šmilauer 2012): data were log-transformed and centered by species. To examine the relationship between soil characteristics and maize residue C in soil biota, we calculated Bray-Curtis distance matrices for the PLFA and nematode community. The significance of the relationship with each soil characteristic was then tested using a Mantel test implemented in the R statistical enviroment (V 3.1.0). Linear regression analysis in SPSS version 19.0 (SPSS Inc., Chicago, IL) was also applied to examine the relationship between C from residue in microbes and in nematodes. The residuals were checked for normality by visual inspection of the normal probability plot.


Effects of fertilization on soil physicochemical properties

Manure application significantly influenced the amounts of SOC, TN, and SO13C (P < 0.01) with higher values observed in organic manure (M and MU) treatments than in the CK and U treatments (Table 2). The largest relative contribution of maize residue carbon to SOC was found in M plot. In comparison to other treatments, the U treatment significantly decreased the soil pH and this pattern was independent from the addition of residue (P < 0.01) (Table 1). Soil moisture content at the sampling time was also altered by the different fertilization treatments (P < 0.05).
Table 2

Basic soil properties in different fertilization treatments (Means ± SD)

Soil properties

Fertilization treatments





SO13C (g kg−1)

0.26 ± 0.02b

0.34 ± 0.05a

0.29 ± 0.02ab

0.23 ± 0.02b

SOC (g kg−1)

10.51 ± 0.61b

11.67 ± 0.39a

11.85 ± 0.25a

10.78 ± 0.28ab

Fraction (%)

2.46 ± 0.28ab

2.94 ± 0.25a

2.42 ± 0.20ab

2.12 ± 0.10b

TN (g kg−1)

1.00 ± 0.05b

1.11 ± 0.04a

1.13 ± 0.05a

1.01 ± 0.01b

SM (%)

16.43 ± 3.34ab

14.19 ± 1.07b

19.6 ± 0.27a

20.21 ± 0.49a

δ13C (‰)

−3.00 ± 0.90b

1.40 ± 0.48a

−2.65 ± 1.28b

−4.93 ± 1.40b


10.17 ± 0.12b

10.48 ± 0.02ab

10.52 ± 0.29ab

10.71 ± 0.22a


6.43 ± 0.16a

6.48 ± 0.06a

6.19 ± 0.04a

5.36 ± 0.16b

SO13C, 13C-maize residue in SOC; SOC, total soil organic C; Fraction (%), relative contribution of maize residue carbon to SOC; TN, total nitrogen; SM, soil moisture; C/N, the ratio of SOC to TN; CK, unfertilized control; M, organic manure; MU, combined application of organic manure with urea fertilizer; U, Urea fertilizer. Different lowercase letters represent significant differences among different fertilization treatments, as determined by a Tukey’s HSD test

Effects of fertilization on different C pools and fraction of residue C in the microbial community

Long-term fertilization significantly affected the total C pool and residue C pool. The greatest C content of bacterial and fungal PLFAs were found under manure fertilization. Manure application also significantly affected maize residue C recovered in bacterial PLFAs (P < 0.05) with higher values observed in the M and MU treatments than in the U treatment (Table 3). The fraction of maize-derived C in the bacterial PLFA C was significantly higher in the MU treatments than in the other treatments, but the fraction in fungal PLFA C did not differ between treatments (Table 3). The principal components analysis (PCA), based on the relative abundance of each PLFA showed that the U fertilization treatment clearly separated from the treatments with manure applications (M and MU) (Fig. 1). Specifically, the unsaturated fatty acids 18:1ω7c, 16:1ω7c and 18:2ω6c were important in the treatments with manure application (left side of the plot).
Table 3

Effect of fertilization on the total biomass, maize residue 13C and the fraction of maize residue 13C in micro-food web pools


Fertilization treatments





(A) Total C (ng g−1 soil)

 Microbial community

  Bacterial PLFA

2135.83 ± 331.89ab

3166.29 ± 113.94a

2615.03 ± 51.90ab

1861.80 ± 738.80b

  Fungal PLFA

415.87 ± 74.63b

737.18 ± 60.20a

636.44 ± 43.44a

393.35 ± 2.87b

 Nematode community


297.85 ± 115.03c

1603.19 ± 928.95a

1065.03 ± 897.88b

120.05 ± 36.86c


33.27 ± 1.45c

102.35 ± 8.00a

70.38 ± 16.27b

24.34 ± 6.81c


123.25 ± 36.89b

381.32 ± 100.73a

214.73 ± 52.49ab

17.81 ± 3.49b


292.72 ± 95.87a

218.11 ± 50.81a

164.91 ± 134.41a

66.73 ± 15.26a

(B) Maize derived C (ng g−1 soil)

 Microbial community

  Bacterial PLFA

114.52 ± 19.24ab

173.49 ± 28.49ab

177.77 ± 1.45a

99.61 ± 47.76b

  Fungal PLFA

18.27 ± 8.41b

38.84 ± 5.31a

28.10 ± 2.56ab

13.56 ± 9.90b

 Nematode community


8.51 ± 2.73b

29.56 ± 4.16a

16.37 ± 8.32ab

1.93 ± 1.32b


0.88 ± 0.03c

2.73 ± 0.16a

1.48 ± 0.66b

0.41 ± 0.28c


2.80 ± 1.17bc

8.08 ± 2.24a

5.12 ± 0.73ab

0.34 ± 0.01c


8.44 ± 2.25a

7.04 ± 1.14ab

5.48 ± 3.40ab

1.68 ± 0.37b

(C) Fraction of maize derived C (%)

 Microbial community

  Bacterial PLFA

5.36 ± 0.09b

5.46 ± 0.71b

6.80 ± 0.08a

5.19 ± 0.64b

  Fungal PLFA

4.26 ± 1.15a

5.33 ± 1.10a

4.41 ± 0.12a

3.45 ± 2.53a

 Nematode community


2.91 ± 0.21a

2.20 ± 0.95a

2.11 ± 1.17a

1.51 ± 0.85a


2.66 ± 0.06a

2.68 ± 0.30a

2.03 ± 0.54a

1.65 ± 0.94a


2.22 ± 0.32a

2.11 ± 0.04a

2.43 ± 0.40a

1.95 ± 0.33a


2.92 ± 0.33a

3.30 ± 0.57a

3.63 ± 1.22a

2.52 ± 0.20a

CK, unfertilized control; M, organic manure; MU, combined application of organic manure with urea fertilizer; U, Urea fertilizer. Different lowercase letters represent significant differences among different fertilization treatments, as determined by a Tukey’s HSD test

Fig. 1

Principle component analysis (PCA) based on the relative abundance of each phospholipid fatty acids (PLFA) (a) and nematode genera (b) under four fertilization treatments. CK, represents unfertilized control; M, represents organic manure; MU, represents combined application of organic manure with urea fertilizer; U, represents urea fertilizer. Percentage explained variance of each axis is also presented

Effects of fertilization on different C pools and fraction of residue C in the nematode community

Fertilization significantly influenced the total biomass C of nematode trophic groups and the amount of maize-derived C (13C) in soil nematodes. The total biomass C was highest in the M treatment followed by the MU treatment. The amount of residue C of bacterivores, fungivores and plant-parasites followed a similar pattern (P < 0.01), and was lowest in the U treatment (Table 3). The fraction of residue C did not differ between the fertilization treatments for all nematode groups. The principal components analysis (PCA), based on the relative abundance of biomass in nematode genera showed that the U fertilization treatment clearly separated from the treatment with manure fertilization by the PC1. Some nematode genera from plant-parasites were relatively important in the U treatments, such as Boleodorus and Malenchus.

Effects of fertilization on relative distribution of maize derived C among different groups of organisms, and relationships within the soil micro-food web

The relative distribution of maize derived C among the different groups in the soil micro-food web differed between the fertilization treatments. The proportion of residue C in bacterial PLFA was smallest in the M treatment and largest in the U treatment, while the proportion of residue C in bacterivorous nematodes was smallest in the U treatment and largest in the M treatment (Fig. 2). However, the proportions of residue C in fungal PLFA and fungivorous nematodes were not affected by different fertilization treatments (Fig. 2).
Fig. 2

The proportion of recovered maize residue-derived 13C in soil micro-food web pools under four treatments. CK, represents unfertilized control; M, represents organic manure; MU, represents combined application of organic manure with urea fertilizer; U, represents urea fertilizer. Different lowercase letters represent significant differences among different fertilization treatments, as determined by a Tukey’s HSD test

Residue C in bacterivores and fungivores was positively related to residue C in bacterial and fungal PLFA (Fig. 3a, b). Similarly, residue C in microorganisms (bacterial PLFA and fungal PLFA) was positively related to that in microbivorous nematodes (bacterivores and fungivores; Fig. 3c). However, there was no such relationship between residue C in prey and consumer nematodes. For both the microbial and nematode community, the variation in residue C was positively related to the variation in pH (Table 4). For nematodes there also was a positive relationship with variation in SOC and TN.
Fig. 3

Relationships between (a) the amount of 13C-maize residue in bacterial PLFA and bacterivores, (b) the amount of 13C-maize residue in fungal PLFA and fungivores; (c) the amount of 13C-maize residue in microorganisms (bacterial PLFA and fungal PLFA) and microbivores; and (d) the amount of 13C-maize residue in prey nematodes (including bacterivores, fungivores and plant-parasites) and predators (omnivores-predators). The statistical results of the linear regression analyses are also presented. *, ** indicated significant correlations at P < 0.05 and P < 0.01, respectively

Table 4

The relationship between soil properties and 13C (maize residue derived C content) incorporation in the microbial and nematode community

Soil properties

Microbial community

Nematode community










Soil moisture




















SOC, total soil organic C; TN, total nitrogen; C/N, the ratio of SOC to TN. The results are calculated from a dissimilarity matrix for each community and are based on a Mantel test

Effects of fertilization on the amount of residue C of nematode energy channels

Fertilization significantly influenced the amount of maize-derived C of the nematode energy channels. Overall, more residue C was found in the nematode bacterial energy channel than in the fungal energy channel. In both channels, more residue C was found in soil organisms in the M treatment than in the control and U treatments (P < 0.01) (Fig. 4).
Fig. 4

Total maize residue derived C (13C) in the nematode bacterial and fungal energy channel. CK, represents unfertilized control; M, represents organic manure; MU, represents combined application of organic manure with urea fertilizer; U, represents urea fertilizer. Different lowercase letters represent significant differences among different fertilization treatments, as determined by a Tukey’s HSD test


Effects of long-term fertilization on recovery of residue C in the soil micro-food web

Organic C-rich soils may more effectively maintain C derived from exogenous easily decomposable organic material than organic C-poor soils (Zhang et al. 2013). In our study, we indeed found that both the amount of residue C in SOC and the total SOC were highest in the manure addition treatment. Easily decomposable organic C is effectively maintained in soils through physical or physicochemical preservation by combining it with minerals, with humic materials, and/or via continuous recycling by soil microorganisms (Derrien et al. 2006; Sauheitl et al. 2005; von Lützow et al. 2006). We found that both soil microbial and nematode community differed between fertilization treatments (Fig. 1), with manure application increasing the total C content of micro-food web components (Table 3). These findings also support our first hypothesis, that long-term manure application results in changes in the utilization of exogenous residue by soil micro-food web due to an increase in the PLFA C and the biomass C of nematode comunity. It should be noted that lower residue C detected in PLFA C is not accompanied by more residue C remaining in SOC (SO13C) under U treatment. Therefore, this possibly indicates that relatively more residue C has been metabolized to CO2 as an equal amount of residue C was introduced into each plot. Two potential mechanisms can help to interpret this phenomenon. First, long-term N fertilizer addition (Urea) can lead to C limitation of the soil microbial community, which changes active microorganisms into a starvation and/or dormant state (Fisk and Schmidt 1996; Fontaine et al. 2003). Hence, microorganisms (especially r-strategy dominated microorganisms) in U-treated soil could strengthen the decay of maize residue to meet their energy demands compared with those in the M treatment, resulting in lower remaining C (SO13C) in the soil. On the other hand, it has been demonstrated that long-term N fertilizer addition might lower the substrate use efficiency of microbial community due to stress of soil acidification (Aciego Pietri and Brookes 2008). A recent study found that specific enzyme activities had a negative correlation with soil pH and positive correlation with available N in a 13-years simulated N deposition experiment (Wang et al. 2018). This may help to explain why less C from the same source was sequestrated in the soil fertilized with U.

Interestingly, the fraction of residue C in bacterial PLFA C was highest in the MU treatment. It is possible that manure application changed microbial community composition. Since gram-negative bacteria preferred to use plant material and gram-positive bacteria preferred to use substantial amounts of SOM C (Kramer and Gleixner 2006), the relatively higher contents of gram-negative bacterial PLFA (16:1ω7c and 18:1ω7c) in MU treatment may result in higher percentages of residue C in soil microbial components. The fractions of residue C for the other pools in the nematode trophic groups were not influenced by fertilization, even though the amount of residue C and the total biomass C of these pool were significantly increased by the manure application. Manure application favored the growth of soil nematodes, and this may result in the increase of total biomass C (Liu et al. 2016). The residue C accumulated in nematode trophic groups may also depend on their feeding behavior (De Mesel et al. 2004). However, both the total C pool and the residue C pool increased, and their fractions were not changed by the fertilization treatments. So our results further indicate that the fertilization treatments influenced the total pool sizes but not how residue C was used in nematode trophic groups. A similar conclusion can be drawn from the relative distribution of the residue C among the pools of the soil micro-food web. In the U treatment, a higher proportion of residue C was found in bacterial PLFA than in CK, while the opposite was true for the M treatment. The proportion of residue C in bacterivores was in turn, higher in the M treatment than in the U treatment. Since bacteria respond quickly to organic inputs and bacterivorous nematodes can rapidly increase in response (Ferris et al. 2001), these changes result in more residue C transferring from bacteria to bacterivorous nematodes under M treatment. Meanwhile, bacterivorous nematode activity may also stimulate bacterial growth (Ingham et al. 1985) resulting in a relatively higher absolute amount residue C in the soil of M treatment after 183 days decomposition.

Effects of fertilization on relationships within the soil food web and 13C utilized by the nematode energy channel

Although different experimental approaches have been used to elucidate trophic habits of soil organisms (Bjørnlund and Rønn 2008; Lundgren et al. 2009), direct observations of who eats whom among microorganism and mesofauna inhabiting natural soils are difficult (Sánchez-Moreno et al. 2011). We examined the relationship between different trophic levels by the remained residue C after 183 days decomposition. Within the soil micro-food web, the amount of maize residue carbon in soil microbes was positively correlated with those in microbivores. However, no significant relationships between omnivores-predators and their preys (bacterivores, fungivores and plant-parasites) were observed in our study. Similiar findings were reported by Carrillo et al. (2011) where microbivorous nematodes had a positive effect on microbial activity during decomposition. The response of organisms belonging to the next trophic level, such as omnivores-predators, may be slower (Mikola and Setälä 1998), because refuges provided by soil pores may limit predators to control their preys effectively (Mikola and Setälä 1998). These results also indicate that the soil micro-food web is controlled by bottom-up processes during crop residue decomposition.

The relative domninance of bacterial and fungal channels in decomposer soil food webs determines the nutrient cyling rates and C storage in soil ecosystems (Bardgett and Wardle 2010; Moore et al. 2005). In our study, more labeled residue within the bacterial energy channel was found in the M treatment. In an earlier study at the same field site, greater abundance of bacterivorous nematodes was found in treatments with manure applications (Liang et al. 2009), which may help to explain why more maize residue C was utilized by bacterial energy channel.

Using stable isotope techniques we now show that crop residue was not only found in the nematode-bacterial energy channel but also significantly increased the residue C utilization of the nematode-fungal energy channel. Our results were partially consistent with the outcome of a model analysis of de Vries and Caruso (2016), that fungal and bacterial populations can coexist in a stable state with large inputs into the labile C pool by plant residue decomposition or by organic fertilizers. This further indicates that these energy channels in soils are not distinctly separated, but, instead that there is a dynamic balance between the fungal and bacterial pathways. The two channels run simultaneously and there is C transfer between them (Ruess and Ferris 2004). The changes among primary decomposers result in a related succession from bacterivores to fungivores during organic matter decomposition (Ruess and Ferris 2004). Readily decomposable compounds are rapidly consumed by bacteria, which may result in the dominance of bacterivores such as Rhabditidae and Cephalobidae (Bouwman and Zwart 1994). When decomposition progresses, fungivores such as Aphelenchoididae and Tylenchidae become abundant (Bouwman and Zwart 1994), and this may result in a corresponding increase in the nematode fungal energy channel. Although a small amount of C-maize residue was found in the nematode energy channel after 183 days, our work demonstrates the 13C-labeled carbon could be traced to the predator level of soil micro-food web, and further highlight the need to put a greater emphasis on a temporal dynamic of C fluxes in the soil food web.


Our results provide evidence that long-term fertilization management affects the C utilization from crop residues by the soil micro-food web components. More residue 13C was utilized by the nematode bacterial channel in the M treatment. Given the important roles of the soil micro-food web in ecological processes, our results further suggest that long-term manure application can lead to more C from crop residues being utilized by soil food web, which will in turn feedback to crop growh and C accumulation in agroecosystems.



This manuscript greatly benefitted from the insightful comments from two reviewers. This research was supported by the National Natural Science Foundation of China (31330011), the National Key Research and Development Plan (2016YFD0300204 and 2017YFD0200602), the National Natural Science Foundation of China (41771280) and the Chinese Academy of Sciences Visiting Professorship Program for Senior International Scientists (2017VCA0004).

Supplementary material

11104_2018_3688_MOESM1_ESM.doc (72 kb)
ESM 1 (DOC 72 kb)


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Shuyan Cui
    • 1
    • 2
  • Siwei Liang
    • 3
  • Xiaoke Zhang
    • 1
  • Yingbin Li
    • 1
    • 2
  • Wenju Liang
    • 1
  • Liangjie Sun
    • 3
  • Jingkuan Wang
    • 3
  • T. Martijn Bezemer
    • 4
    • 5
  • Qi Li
    • 1
  1. 1.Institute of Applied EcologyChinese Academy of SciencesShenyangChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.College of Land and EnvironmentShenyang Agricultural UniversityShenyangChina
  4. 4.Department of Terrestrial EcologyNetherlands Institute of Ecology (NIOO-KNAW)WageningenThe Netherlands
  5. 5.Section Plant Ecology and Phytochemistry, Institute of BiologyLeiden UniversityLeidenThe Netherlands

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