Application of cattle manure increased the stability of organic carbon in the subsoil in Mollisols

doi:10.21203/rs.3.rs-3126950/v1

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Application of cattle manure increased the stability of organic carbon in the subsoil in Mollisols

https://doi.org/10.21203/rs.3.rs-3126950/v1

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published 24 Apr, 2024

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Aims: The cattle manure application to subsoil is an efficient and sustainable approach to increase soil fertility. However, the change of soil organic carbon (SOC) chemistry after manure amended in subsoil is remains elusive.

Methods: Here, a pot experiment was used to investigated the SOC chemical structure (¹³C-NMR and FTIR), as well as microbial community composition (PLFA), with cattle manure amended in topsoil (T1M), and subsoil (T2M) and without manure in topsoil (T1) and subsoil (T2).

Results: The utilization of cattle manure significantly improved SOC, total nitrogen (TN) content and PLFAs biomass, as well as the relative absorption of the band at 2920 cm^-1and 1640 cm^-1 of SOC, while decreased the C/N ratio by 15.7-50.5%. T1M increased the proporations of O-alkyl C and Aromatic C by 3.8%-17.6% compared to T1, but decreased the proporations of Alkyl C and Carbonyl C by 9.9%-11.5% and the ratio of Alkyl C/O-Alkyl C (A/OA) by 60.0%. However, T2M showed the opposited trend compared to T2. The fungal to bacterial ratio (F/B) of T2 was lower than that of T1, while it was greater in T2M than that in T1M. Both RDA and MRT analyses demonstrated that the Cyanobacteria, Acidobacteria and Ascomycota were negatively association with O-alkyl C, and the Actinobacteria, Verrucomicrobia and Cyanobacteria were negatively association with Alkyl C.

Conclusions: Our findings reveal application cattle manure in subsoil was more beneficial to decompose SOC owing the transfromation of bacterial to fungal and made the chemical structure of SOC more stabilization.

13C NMR

Soil microbial community

Manure application

PLFA

Soil organic carbon

Soil organic carbon (SOC) is a suitable indicator of soil fertility, varying greatly in chemical structure which is a key factor of C sequestration ((He et al. 2018; Ng et al. 2014; Rossel et al. 2019). Over half of the total carbon (C) stocks in terrestrial ecosystems are found in subsoil, which are a significant C pool (Balesdent et al. 2018; Luo et al. 2019) and is different from what is found in topsoil in nature characteristics (Rumpel and Koegel-Knabner 2011). Subsoils with a longer residence duration, for example, are carbon-unsaturated and have a larger potential for additional carbon sequestration (Schiedung et al. 2019), as well as simple microbial communities in the subsoil (Sradnick et al. 2014). The majority of investigations focused on the chemical structure of SOC in topsoil (Mustafa et al. 2022; Ng et al. 2014). Yet, globe subsoils may actively respond to fertilization, but this is currently unknown (Pries et al. 2017). For increased soil C stocks, we must examine not only the amount and form of C present in the topsoil, but also the amount and form of C present in the subsoil, as well as the influence this has on soil microbes participating in soil carbon cycling (Ng et al. 2014). To accomplish this objective, a greater understanding of their forms and quantities of SOC in subsoil is required, because the various forms of SOC differ in their resistance to decomposition.

In intensively managed agroecosystems, fertilization is frequently recommended to enhance soil organic matter (SOM) and fertility since it is the most widespread management strategy for bettering soil quality globally (He et al. 2018). Although organic and chemical fertilizers may result in changes in soil C chemistry (Li et al. 2018), there have been conflicting findings on the impact of fertilizer application on the chemical structure of SOC. For example, both organic and chemical fertilization resulted in an enhanced in the content of Alkyl-C (Wang et al. 2012). Another investigation showed that the fertilization treatments consistently enhanced the O-alkyl C (labile C) proportion, but not the alkyl C (persistent C) (He et al. 2018). Mustafa et al. (2021) reported that carbonyl-C was the form of SOC that was sequestered to the greatest degree (Mustafa et al. 2022). Further, long-term fertilization among Yan et al. (2013) had no impact on the chemical structure of SOC (Yan et al. 2013). However, there have only been a limited number of studies comparing C dynamics in topsoil and subsoil, so it's possible that there are substantial discrepancies (Salome et al. 2010). Fontaine et al. (2007), for instance, found that the chemical compositions of the topsoil and subsoil were quite comparable, except for relatively more aromatics in the subsoil (Fontaine et al. 2007). More protonated C was identified in the topsoils, while more non-protonated C was found in the subsoils, according to research examining the two (Zhang et al. 2018). Consequently, understanding the chemical composition of SOC under the application of cattle manure in both the top- and subsoil is crucial for improving soil fertility and promoting long-term C sequestration in agroecosystems.

Microorganisms in soil have a significant impact on the carbon cycle, including decomposition, stabilization, and formation of soil organic matter (Zhang et al. 2015a). Since fertilization enhances the amount of available substrate, it offers the potential to alter the amount of population, composition, variety, and activity of soil microorganisms (Wu et al. 2011). Fertilization of Halosol soil, for instance, considerably raised levels of total bacteria and Gram-positive contents (Wang et al. 2017). Copiotrophic bacterial taxa, such as Proteobacteria, were demonstrated to be stimulated by organic application due to an increase in SOC (Francioli et al. 2016). In general, organic manure and inorganic fertilizer decrease fungal biomass in agricultural soils (Bittman et al. 2005). While others found the different results (de Vries et al. 2007; Elfstrand et al. 2007). Microbial communities are predicted to be less active and/or expand at a slower rate in the subsoil due to increasing substrate (or nutrient) restrictions with soil depth (Sradnick et al. 2014), thus the microbial community of subsoil is relatively simple (Du et al. 2018). However, various studies suggested that deep soil microbial communities undoubtedly play crucial roles in regulating nutrient cycling and biogeochemical processes (Chu et al. 2016; Song et al. 2022; Zhou et al. 2014). A few studies have investigated the effect of fertilization on the microbial community composition of subsoil, such as Gram negative (G-) bacteriaare dominant in topsoil, Gram positive (G+) microorganisms prevail in subsoil (Blume et al. 2002), which results in the complete differentiation of the bacterial community structure in top- as well as subsoil (Eilers et al. 2012). Therefore, it is important to investigate whether microbial components exhibit different spatial distribution patterns and preservation along soil depths.

Few studies have examined the relationship between the chemical structure of SOC and the composition of key microbial groups under organic and inorganic fertilization, and the relationship remains inconclusive (Ng et al. 2014; Wang et al. 2016). Since the addition of organic amendments can alter the chemistry of SOC, and thus result in multiple modifications in microbial community composition (Elfstrand et al. 2007; Xu et al. 2006). For example, Baumann et al. (2009) found that alterations in the composition of microbial communities were related to alterations in soil C-chemistry (Baumann et al. 2009). Ng et al. (2014) observed that aryl C was the most important factor in determining the structure of soil microbial groups after the application of organic material (Ng et al. 2014). A further investigation discovered that alkyl formation was linked to greater bacterial growth, especially among G + bacteria that like to use labile C and contribute to preserving aliphatic chemicals (Wang et al. 2017). Yet, there isn't much known regarding how cattle manure strategies affect soil C chemistry, and the link between that and the structure and function of microbial communities needs more research, especially in subsoil. Understanding how the change in microbial community structure related to changes in the soil microenvironment and SOC formation patterns after fertilization could help develop sustainable management approaches to improve SOC sequestration and yields of crops.

In view of that, a pot experiment has been performed to investigate if modifying the amount and SOC chemistry through cattle manure apply changes the composition of the microbial community in the top-, and subsoil. Eight treatments including: with or without manure application in top-, and subsoil in two different sampling stages were imposed in an mollisol soil. We hypothesized that (i) manure application in top-, and subsoil would enhanced the potential of SOC stocks, and especially in topsoil; (ii) cattle manure's effect on the soil's microbial community would be reflected in the C in the soil's chemistry. A total of three objectives for our research: (1) to evaluate how manure application in the top-, and subsoil affects SOC and its chemical composition based on 13C-NMR and FTIR Spectrometer analysis; (2) to evaluate the impacts of cattle manure application in the top-, and subsoil on the composition of microbial communities based on PLFA analysis; (3) to determine how various categories of microorganisms respond to various chemical forms of SOC. Understanding the mechanisms responsible for SOC formation and stability throughout cattle the application of cattle manure becomes considerably simpler with the assistance of PLFA analysis combined with the NMR technique.

2.1 Experimental design

In the greenhouse at the Agricultural Ecology Station of the Northeast Institute of Geography and Agroecology of the Chinese Academy of Sciences in Changchun City, Jilin Province, a pot experiment was carried out. The following treatments were applied in a randomised block design: topsoil (T1), subsoil (T2), topsoil amended with cattle manure (T1 M), and subsoil modified with cattle manure (T2M). The parameters of the topsoil (0–25 cm) and subsoil (25–50 cm) that were obtained from mollisol farmlands are summarised in Table 1. The samples of soil were combed through to remove any roots, stones, and other elements that could have been present. After that, the water content of the soil was adjusted to the field's capacity. At a weight ratio of 5:1, one portion of the topsoil and subsoil was thoroughly combined with fresh cattle manure. The fresh cattle manure was obtained from a farm that specialised in fattening cows, and it contained 68.7% water and other characteristic as shown in Table 1. Each of the four different soil treatments (T1, T2, T1M, and T2M) were each put into nine duplicate pots with a weight of six kilogrammes each pot (height = 25 cm, diameter = 20 cm). On the 5th of June 2019, 2.0 grammes of oat seed were planted in each pot, and on the 20th of September 2019, the oats were harvested. During the growing phase, the plants were provided with moisture by artificial watering, and the volume of water that was provided for each container was the same.

Table 1

Soil properties of the experimental mollisol in topsoil and subsoil
	SOC (g/kg)	TN (g/kg)	TP (g/kg)	TK (g/kg)	AN (mg/kg)	AP (mg/kg)	AK (mg/kg)	C/N
Topsoil	15.6	1.3	0.4	55.6	170.5	36.9	161.0	12.5
Subsoil	12.8	0.6	0.3	46.7	163.2	33.5	154.1	20.4
Manure	134.2	36.7	2.06	1.42	2410	670	960	3.7

2.2 ¹³C-NMR (nuclear magnetic resonance) spectroscopy

Nuclear magnetic resonance (NMR) was used to figure out what chemicals were in soil C. Soil samples were treated five times with 50 mL of 10% HCl, 50 mL of 10% HF, and distilled water. The samples were then dried, pressed into 7-mm zirconia rotors, and spun at 6 kHz using a Bruker Avance III 400 spectrometer (Bruker BioSpin, Rheinstetten, Germany) with a resonance frequency of 100.62 MHz for 13C. Cross polarisation with total suppression of spinning sidebands (TOSS) pulse programme, contact time of 1000 s, relaxation delay of 0.5 s, ramp-contact and small phase incremental alternation with 64 steps (SPINAL64) decoupling pulse programme were used to improve the signal-to-noise ratio. The spectra were made by adding up the results of 15,000 scans. The methane C atoms in adamantine were used as an external reference (= 29.47 ppm) to measure the spectra. Estimates of wide C forms were made using the spectra between the following chemical shift limits: 0–45 ppm (alkyl C), 45–60 ppm (N-alkyl C), 60–90 ppm (O-alkyl C), 90–110 ppm (di-O-alkyl-C), 110–145 ppm (aryl C), 145–165 ppm (O-aryl-C), 165–190 ppm (Carbonyl C), 190–220 ppm (ketone C). The ratios between the relative intensities of the 0–45 and 45–110 ppm regions (alkyl C/O-alkyl C) and the 110–160 and 45–110 ppm regions (aryl C/O-alkyl C) were used as predictors of decomposition (Shrestha et al. 2015).

2.3 Fourier Transform Infrared Spectrometer (FTIR Spectrometer) analysis

In an agate mill, the sieved pieces ( 2 mm) were ground into a powder. One mg of the agate-milled samples that had been homogenised was mixed well with 100 mg of KBr (FT-IR grade). Using a press (15 t cm-2), a pellet with a width of 13 mm was made, and it was put into the sample box right away. At 22 1°C, an FT-IR spectrum was taken with a Perkin-Elmer 2000 FT-IR analyser. The range was 400–4000 cm-1, and the precision was set to 4 cm-1. In all cases, 20 scans were taken for each sample. The average of each spectrum was then used to fix the results, using the spectrum for outdoor air as the background. The EZ OMNIC (omnic32) was used to get the corrected peak heights. The following were the factors for each peak: Base 1/peak / Base 2 (in cm1): 3000/2920/2800; 1800/1730/1700; 1560/1510/1490; 1490/1450/1400; 1190/1050/900. The relative absorbance (rA) was found by dividing the corrected peak height of a distinct peak (like 2920, 2850, 1720, 1620, or 1420 cm-1) by the sum of the heights of all peaks at 2920, 2850, 1720, 1620, or 1420 cm-1 and multiplying by 100 (rA% of the sum of all peak heights from 2920 to 1420 cm-1). The band at about 3400 cm-1 is caused by bound and unbonded hydroxyl groups stretching when they vibrate. The C-H vibrations of aliphatic methyl and methylene groups are shown by the band at 2920 cm-1. The band at 1620 cm-1 is made up of C = O vibrations of carboxylates and aromatic vibrations. The band at 1420 cm-1 is caused by bending movements of CH and NH (amide II), vibrations of the molecular skeleton, and vibrations of the C–O bond.

2.4 Phospholipid fatty acid (PLFA) analysis

Phospholipid fatty acid (PLFA) research was used to figure out the make-up of the microbial species. PLFA are an important part of the membranes of all bacteria. They break down quickly when cells die, which makes them good signs of live things. So, study of microbial populations with PLFA makes it possible to directly identify, classify, and measure the makeup of microbial communities (Zhong et al. 2015). A single-phase mixture of chloroform, methanol, and citrate buffer (1:2:0.8, v/v/v-1; 0.15 M, pH 4.0) was used to remove dirt samples that had been frozen and dried. The fatty acid methyl esters that were made were then sorted and identified using a gas chromatograph (Agilent 7890 N, Wilmington, DE) with a flame-ionization detector (FID) and the MIDI Sherlock microbe identification system (Version 4.5, MIDI, Newark, NJ). An Agilent 19091B-102E Ultra 25% phenyl methyl siloxane column (25.0 m x 200 m x 0.33 m) was used to separate the substances. The temperature of the oven was raised to 190°C right away, then went up to 285°C at a rate of 10°C per minute, then went up to 310°C at a rate of 60°C per minute and stayed there for 2 minutes. The temperature of the pump was 250°C, and the temperature of the monitor was 300°C. At a flow rate of 30 mL min-1, ultra-pure hydrogen was used as the transport gas for the FID. Based on the amounts of the 19:0 internal standard, the concentrations of each PLFA were figured out. The amounts of each PLFA were written as nmol g-1 of dirt. Each fatty acid was measured as a proportion of the total number of fatty acids found in each sample. Taking into account how bacteria, fungi, actinomyces, and Gram-positive (G+) and Gram-negative (G) bacteria react differently, as Willers showed (Willers et al. 2015).

2.4 Statistical analyses

One-way analysis of variance (ANOVA) was used to observe if the relative amounts (%) of soil C molecular forms, microbial PLFA, and SOC content were significant (P < 0.05) using SPSS, ver. 22.0 (SPSS Inc., Chicago, IL, USA). Principal component analysis (PCA) was used to compare and analyse the relative abundances of PLFA. Redundancy analysis (RDA) was used to find out how the microbial community in the soil and its chemical traits were related in different methods. MRT research was also used to look at how C forms and the microbial community interact with each other. The statistical analyses were undertaken in R (v4.0.2; http://www.r-project.org/).

3.1 Characteristics of soil

The content of SOC and TN of the T1 were 25.35%-42.86% higher than that in the T2 under the 45 day (p < 0.05). In the T1, the SOC content was 1.28% lower than that in the T2, while TN content was 29.79% higher at 90 day (p < 0.05). The SOC and TN contents were 28.7–48.9% and 13.7–64.6% higher, respectively, with cow manure than that in the without cow manure soil under 45 day and 90 day (p < 0.05). The C/N ratio in T1M were 23.45% and 30.67% greater than that in T1 under 45 day and 90 day (p < 0.05), while in T2M were 36.86% and 18.18% lower than that in T2, respectively (p < 0.05, Fig. 1).

3.2 PLFA Content

The total PLFA, bacterial, G⁺ and G⁻ of T1 were 1.7, 1.6, 2.0 and 1.5 times higher than that of T2 (p < 0.05), and the fungi and actinomyces were 22.6–60.0% and 43.6–58.0% greater (p > 0.05). Total PLFA was significantly increased by cattle manure (T1M and T2M), especially in fungi group, which was exceed doubled compared with other groups (Fig. 2). T1M and T2M also increased bacterial, fungi, actinomyces, G⁺ and G⁻ biomass by 83.0-89.9%, 91.4–96.3%, 79.1–91.0% 84.5–92.1% and 78.6–87.2% compared to T1 and T2 (p < 0.05). The total PLFA of T1M was 8.5–12.1% greater than T2M (p < 0.05), and bacterial, fungi, actinomyces, G⁺ and G⁻ abundance of T1M were greater than that of T2M (p > 0.05). Application cattle manure significantly increased F/B ratio, and increased G+/G- ratio (p < 0.05). The ratio of F/B of T1M and T2M were 2.25 time than T1 and T2 (p < 0.05). The G+/G- ratio of T1 was 20.4–28.7% greater than T2, and of T1M was 5.1–10.0% higher than that of T2M (p < 0.05).

3.3 Fourier Infrared Spectroscopy

Figure 3 shows the FTIR spectra of topsoil and subsoil with or without manure in a black soil. In general, the spectra of the topsoil and subsoil with or withour manure are similar. Table 2 summarizes the differences in the relative absorption of specified regions in the topsoil and the subsoil with or without cattle manure application. The relative absorption of the band at 1640 cm^− 1 and 2850 cm^− 1 was greater in the T2 than in the T1, while at 2920 cm^− 1 was lower in T2 than in the T1. The band at 2920 cm^− 1 was higher in the T1M and T2M than that in the T1 and T2. For the band at 1640 cm^− 1 was less in the T1 and T2 versus the T1M and T2M

Table 2

Mean relative absorbance in percentage of the sum of all selected peak heights of the FTIR spectra of the topsoil and subsoil with or without manure
		2920 cm^− 1	2850 cm^− 1	1720 cm^− 1	1640 cm^− 1	1430 cm^− 1	1720/ 2920	1640/ 2920
45 d	T1	5.51	1.91	5.44	85.52	1.62	0.99	15.53
	T1M	11.22	2.28	2.82	82.89	0.78	0.25	7.39
	T2	2.82	2.48	0.32	92.41	1.98	0.11	32.77
	T2M	6.50	1.30	4.06	87.26	0.88	0.62	13.43
	T1	4.88	1.24	2.63	85.06	6.19	0.54	17.43
90 d	T1M	5.34	1.70	4.90	86.19	1.88	0.92	16.13
	T2	1.54	1.08	3.53	92.43	1.42	2.29	59.89
	T2M	5.93	0.74	6.85	85.56	0.92	1.16	14.43
Note: T1: topsoil without manure; T2: subsoil without manure; T1M: topsoil with manure; T2M: subsoil with manure.

3.4 ¹³C nuclear magnetic resonance (NMR) spectroscopy

The resonance peak at 23 ppm and 30 ppm in the ¹³C-NMR spectra of topsoil and subsoil treated with cattle manure or not (Fig. 4) was the alkyl C. At 56 ppm, 72 ppm, and 104 ppm, the O-alkyl C assignments were very strong. The peak resonance frequency for aromatic C was 128 ppm, while the signal at 150 ppm was very weak. At 172 ppm, the carbonyl C resonance peak was found.

Table 3

Integration of soil under manure ¹³C NMR spectra provides C functional group percentage contribution.
	Alkyl C (0–45 ppm)		O-Alkyl C (45–110)				Aromatic C (110–160 ppm)			Carbonyl C (160–220 ppm)			Alkyl C/ O-Alkyl C
		Alkyl C	N-alkyl/ methoxyl C	O-alkyl C	di-O- alkyl C	Total	Aryl C/ O-aryl C	Phenolic- C	Total	Amide-C	Ketone-C	Total		AL/AR
45D	T1	26.55	2.32	20.64	5.91	28.87	24.16	0.22	24.38	12.04	8.15	20.19	0.92	2.27
	T1M	21.23	9.78	29.11	9.11	47.99	12.51	6.31	18.83	11.56	0.39	11.96	0.44	3.68
	T2	16.43	9.19	37.21	8.25	54.65	12.59	4.38	16.97	11.98	0.06	12.03	0.30	4.19
	T2M	21.09	8.79	29.09	11.40	49.27	12.02	6.34	18.36	10.82	0.46	11.27	0.43	3.83
90D	T1	28.65	2.77	23.84	0.62	27.23	15.96	3.20	19.16	18.92	6.04	24.95	1.05	2.91
	T1M	18.74	7.07	29.34	8.39	44.79	17.16	5.80	22.97	13.25	0.25	13.50	0.42	2.77
	T2	19.98	8.26	26.22	7.87	42.35	19.68	5.92	25.60	11.63	0.44	12.07	0.34	3.17
	T2M	25.02	10.72	21.66	8.15	40.53	13.51	2.57	16.08	14.22	4.15	18.37	0.62	4.08
manure		10.69	5.49	41.37	13.09	59.94	11.09	5.94	17.03	11.83	0.51	12.34	0.18	4.15
Note: T1: topsoil without manure; T2: subsoil without manure; T1M: topsoil with manure; T2M: subsoil with manure. AL/AR:

The relatively spectral contributions of different functional groups of ¹³C-NMR spectra are listed in Table 2 and Fig. 4. The results showed that O-alkyl C accounted for most of the total functional group (27.23%-55.92%), followed by alkyl C (13.17%-28.65%), and aromatic C (14.96%-33.42%), the lowest was the carbonyl C (11.27%-24.95%). The alkyl C proporations of T1M were decreased compared with T1, while of T2M was increased. The O-alkyl C proporations were highest for the T2 (48.19%), decreasing in the order T1M (46.39%) > T2M(44.90%) > T1 (28.03%). In addition, the carbonyl C of T1M and T2M were decreased by 3.02%-4.66% compares to T1 and T2.

AL/AR and A/OA are widespread SOC stability indicators. The A/A-O of T1M were decreased by 0.48–0.63 compared with T1, while that of T2M were increased by 0.13–0.29 compared with T2. The A/A-O of T1M was lower than that of T2M, whilethe A/A-O of T1 was greater than that of T2. And from 45d to 90d, the A/A-O of topsoil and subsoil that with or withour manure were increased.

3.5 Integrating SOC forms to microbial community composition

Principal component analysis (PCA), multivariate regression tree (MRT) and redundancy analysis (RDA) and were used to investigate C chemistry and microbial community composition (Fig. 5). In PCA analysis, microbial community structures varied between T1,T2,T1M,T2M. PC1 was responsible for explaining 99.60% of the total variation, whereas PC2 was responsible for explaining 0.20% of it (Fig. 5a). We observed that RDA1 and RDA2 accounted for 89.12% and 8.23%, respectively, of the total variance in the microbial community when we used RDA for PLFA as the response variable and SOC chemical composition as the explanatory factors. The majority of the variance in the soil microbial community may be were responsible by alkyl C and aromatic C. The Alkyl C was positively related to microbial community composition. The SOC (60.6%, p = 0.001) was the most crucial variable in forward selection, followed by Alkyl C (34.1%, p = 0.008) and Aromatic C (23.2%, p = 0.035). The different C forms were linked to the changes in the soil microbial community caused by applying cattle manure to the topsoil and subsoil.

MRT analysis employing the relative proportions of C forms to separate the four treatments (Fig. 5c). O-alkyl C (</≥46.25) distinguished T2 apart from the other treatments and explains 59.88% of the difference in the first split. In the second split, Armatic C (b/≥13.5) distinguished T2M from the right treatments, accounting for 32.81% of the total variation. Alkyl C proportions were used to further categorize T1 and T1M treatments (</≥22). Bacteria formed 32.44% of the variation among microorganisms and explained 51.32% of that variation (Table 4).

PCA and RDA were used to explore how C chemistry affects the diversity of microorganisms (Fig. 5). The PC1 showed the most variation in diversity of microbial community between the four treatments. PC1 accounted for 79.1% of the variation, whereas PC2 accounted for 19.7% (Fig. 5a). RDA1 and RDA2 accounted for 98.66% and 1.03%, respectively, of the total diversity of microbial community variation. In terms of forwards selection, the SOC (97.5%, p = 0.001) was the most important factor, followed by Alkyl C (82.1%, p = 0.001), O-alkyl C (57.1%, p = 0.020) and Carbonyl C (87.5%, p = 0.006).

According to the RDA of the soil bacterial community composition for all phyla and soil C forms across all treatments, axis 1 was responsible for 85.18% of the variance (Fig. 7a). Increases in the relative abundances of Actinobacteria and Cyanobacteria correlated with the Aromatic C, while were negatively correlated with the Alkyl C. The O-alkyl C had a significant postively effect on the relative abundance of Proteobacteria and Firmicutes. Axis 1 accounted for 89.75% of the variance in the RDA of the soil fungus community composition across all phyla and the soil C forms for all treatments (Fig. 7b). While Ascomycota, Glomeromycota, and Mortierellomycota were negatively correlated with the O-alkyl C, the relative abundance of Basidiomycota and Chytridiomycota was positively correlated with the Aromatic C.

Table 4

Tree analysis explains soil microbial PLFA variation.
	OAC < 46.25	ARC > 22.98	AC < 22	Total tree	Total species
Bacterial	32.44	7.16	11.72	51.32	53.68
Fungi	13.87	3.47	5.22	22.57	23.80
Actinomyces	0.99	0.11	0.45	1.54	1.84
G+	8.06	1.56	3.07	12.69	13.33
G-	4.52	0.79	1.76	7.08	7.34
Total PLFAs	59.88	13.09	22.23	95.21	100.00

4.1 The effect of cattle manure on SOC chemical composition

In this study, cattle manure addition altered SOC chemical structure as well as SOC content (Fig. 1, Table 2). Irrespective of the soil layer (topsoil v/s subsoil) and sampling date (45d or 90 d) as well as with or without manure, SOC in this study was dominated by O-alkyl C (Table 2). Carbohydrates and lignin are particularly rich in this functional group, while proteins and lipids only contain minimal quantities (Ng et al. 2014). Consistent with previous research, this observation shows that carbon molecules generated from manure may have accumulated as O-alkyl C in the soil (Yan et al. 2013). For example, C compounds of the O-alkyl form were discovered to be the most abundant in an annual wheat-maize double-cropping system (He et al. 2018). In contrast, alkyl C was shown to be the most prevalent SOC type in a different research conducted in North China by (Zhang et al. 2009). These discrepancies in SOC functional group proportions may be linked to shifts in soil types, organic residue input quantities and types, and agricultural practices (He et al. 2018; Zhang et al. 2009). Further, the SOC also includes Alkyl C and Aromatic C, which contribute to the following group after O-alkyl C. The Aromatic C from cellulose and hemicellulose (Solomon et al. 2007), which might be associated with the lower activity of lignin degrading microbes, such as fungi, and thus selectively preserving OC substances from microbial decomposition (Mustafa et al. 2022). Alkyl-C may be present in proteins as well as lipids, waxes, cutins, suberins, and lignin (Baumann et al. 2009). Aromatic carbon often used together with Alkyl C to represent carbon compounds that are difficult to be utilized by microorganisms.

The SOC chemical nature of topsoil and subsoil was significantly different (Table 2). Topsoil induced higher alkyl C proportion but relatively lower O-alkyl C compared with subsoil. However, it was contrary to the findings of others studies, for example, Zhang et al. (2015) found that there was a lot more Alkyl C in the deep soil than in the top soil, but there was a lot less O-alkyl C in the deep soil (Zhang et al. 2015b). O-alkyl C typically decreases and alkyl C typically increases as decomposition proceeds (Baldock et al. 1992). According to these findings, which are in line with those of other research, topsoil sped up the decomposition of labile C group whereas subsoil slowed it down (Tian et al. 2016). Also, the alkyl C/O-alkyl C ratio (A/OA) was greater in topsoil than in subsoil, with a larger value indicating greater decomposition of soil C (Zhao et al. 2012) and subsequently greater rates of C loss (Shrestha et al. 2015). This finding provided evidence for the concept that the microbial community preferentially decomposes labile C, and that the resulting compounds help produce stable C (Cotrufo et al. 2013). As a result, the aliphatic C/aromatic C ratio (AL/AR) could be confirmed, indicating that the chemical composition of SOC in topsoil was more complicated than subsurface (Zhao et al. 2012).

The chemical composition of SOC in both the topsoil and the subsoil was drastically changed when cattle manure was added (Table 2). The decreased A/OA ratio of topsoil treated with manure and the decrease in Alkyl C and rise in O-alkyl C reveal that SOC the decomposition of topsoil with manure was delayed. While in another study, soil particle organic matter had minimal O-alkyl C after 18 years of organic fertilisation, but major levels of aromatic C and alkyl C (Zhou et al. 2010). Possible causes for the elevated O-alkyl C content in topsoil include the increase of root aboveground biomass after manure addition (Hu et al. 2023; Li et al. 2015), and, He et al. (2018) discovered that polysaccharides generated by bacteria led to the synthesis of O-alkyl C during the degradation of plant litter (He et al. 2018). Soil physical conditions, cation exchange, metal complexing processes, production of humic compounds, biological activity, and adsorption of polysaccharides by clay minerals may all be affected by the elevated O-alkyl C proportions of topsoil under manure (He et al. 2018). Soil C sequestration might result via improved particle aggregation and structure as a result of these alterations (Kundu et al. 2007). Due to the considerable potential for C sequestration in Chinese croplands, a delay of this type should be seriously examined (Di et al. 2017). However, the subsoil was the opposite. Decomposition of SOC in subsoil with cattle manure may have been facilitated by the observed rise in alkyl C and decrease in O-alkyl C. Further, the greater A/OA ratio of subsoil with manure shown that the labile C forms was consumed and resulted a greater recalcitrant C in subsoil. Thus, subsoil with manure was more favour SOC accumulation compare to than that without manure. Pisani et al. (2016) found that long-term inputs of organic wastes accelerated the decomposition of labile SOC and improved the sequestration of aliphatic chemicals in soil, and our findings corroborated these findings (Pisani et al. 2016). In summary, the topsoil with manure amended was more favour SOC accumulation, and the subsoil amended manure had high potential to sequestrated C.

Manure addition has different effects on SOC chemical composition in topsoil and subsoil under different stage. In the 45 day stage, the alkyl C and O-alkyl C proportion, as well as the A/OA and AL/AR ration were similar between topsoil amended manure and subsoil amended manure (Table 3). It indicated that the biochemical properties and chemical composition of topsoil and subsoil with application manure were similar. While at 90 day stage, the subosoil with manure amended had a greater proportion of alkyl C and a lower proportion of O-alkyl C, which indicated that the decomposition degree of subsoil amended manure is greater than that of topsoil amended manure. And the higher A/OA ratio of subsoil amended manure than that of topsoil amended manure could also be verified this. Our research showed that adding manure to subsoil resulted in a more complex SOC structure, while adding manure to topsoil resulted in a less complex SOC structure. It follows that topsoil amended with manure can serve to preserve SOC and promote the formation of a more resilient SOC structure.

4.2 The effect of cattle manure on microbial communities composition

The total PLFA, bacterial, fungi and actinomycete content of topsoil were greater than that of subsoil (Fig. 2). Decreased levels of soil nutrients including carbon, nitrogen, and phosphorus have an effect on the total amount of microorganisms in the soil (Naylor et al. 2022). Soil microbial biomass is reported to be lower in N-limited soil than in N-rich soil (Liu et al. 2022). Some researchers have found that soil C/N determined microbial community structure (Wan et al. 2015). Since the topsoil's C/N ratio was 11.70, which was significantly lower than the subsoil's (16.14), there should be sufficient N available for microbes in the topsoil. The significantly greater SOC content under treatments with the inclusion of cattle manure corresponded well with the significantly higher soil microbial biomass (bacterial, fungal, actinobacterial, G⁺ and G⁻ PLFAs content) (Fig. 2). Previous reports have shown comparable results (Wang et al. 2012; Zhao et al. 2010). As soil microbes are generally C limited, the addition of manure can offer a substrate that is either reasonably stable or labile, which is necessary to promote the development of microorganisms (van Groenigen et al. 2014), and thereby improve the quantity of total microorganisms abundances (Zhang et al. 2015). It is quite likely that changes in the composition of manure and SOM, and consequently, differences in the availability of substrates, are the basis for the observed variances in the abundance of particular microbial groups and community composition. There have been a variety of conclusions produced about the impact that fertilizations have had on the levels of G + and G-bacteria. For instance, Peacock et al. (2001) found that the addition of manure over a period of five years led to an increase in the G- bacterial biomass while leading to a decrease in the G + bacterial biomass (Peacock et al. 2001). On the other hand, Ai et al. (2012) presented evidence that a 31-year application of organic fertiliser led to an increase in the amount of G + bacteria (Ai et al. 2012). However, the percentage of actinomycetes in total PLFA was decreased in the top-, and subsoil applied manure, which was consistent with other studies (Clegg et al. 2003; Zhang et al. 2015). This is due to the fact that actinobacteria make relatively little use of newly generated or added organic C, but are highly well suited to metabolise older organic matter (Zhang et al. 2015). The increase in total PLFAs content was much larger in the subsoil compared to the topsoil, which showed that the microbes in the subsoil utilised the organic compound from manure to a greater extent than those in the topsoil (Angst et al. 2019). Similarly, research has shown that there is a trade-off between the production of microbial biomass and the maintenance of microbial activity, with the increase in microbial activity following labile C addition in subsoil being greater than that in topsoil (Tian et al. 2016).

Manure application not only increased the biomass of all microbial groups, but also changed microbial community structure (Fig. 2). In contray with previous research on agricultural soil (Marschner et al. 2003), we saw a considerable improvement in the F/B ratio after manure was added. Soil C sequestration has also been described using the F/B ratio. Fungal predominance in the microbiome is associated with slower rates of SOC turnover and greater SOC accumulations (Ananyeva et al. 2015; Malik et al. 2016). Networks of fungal hyphae contribute in the development of soil aggregates that are both strong and resistant to breakdown by microbes (Peng et al. 2013). Furthermore, necromass produced by fungi is chemically more stable than that produced by bacteria (Liang et al. 2017). The higher F/B ratio in both the top-, and subsoil after manure management was indicative of a larger prevalence of fungal growth. Fungi are the most abundant decomposers of external carbon input due to their wide arsenal of extracellular enzymes (Li et al. 2020). Before manure was applied, the F/B ratio of the topsoil was greater than that of the subsoil, but after manure was applied, the reverse was true. It showed that the fungal growth was stimulated by the increased availability of C substrates in the manure-amended subsoil. A decreased F/B ratio in manure-applied topsoil was consistent with previous research suggesting that bacteria would respond favourably to the increased availability of C substrates present in these soils (Wei et al. 2017; Zhong et al. 2010). In our research, manure was shown to increase fungal biomass in both the top and subsoil and to support SOC accumulation, particularly in the subsoil.

When the G+/G- ratio alterations, it shows that the surrounding environment is stressful, and the decreases in soil C availability result in a higher G+/G- ratio (Fanin et al. 2019; Rankoth et al. 2019). Since the G+/G- ratio in topsoil is higher than in subsoil, it is more favourable to G + bacteria. This is consistent with the chemical composition of SOC in topsoil that the lower O-alkyl C and the greater alkyl C (Table 3). At the 45 and 90 day, we discovered that the G + bacterial population increased in manure-applied soils, both in the topsoil and the subsoil (Fig. 2). Previous research has shown that when organic matter is added, a community succession effect occurs, wherein fast-growing G- bacteria proliferate initially, but then decrease, making way for slower-growing microbes like G + bacteria (Lazcano et al. 2013). G + bacteria are well suited to soils with poor substrate availability, hence the more resistant material in cattle manure could improve their competitive abilities (Zhang et al. 2015). More N-acetylglucosamine, a precursor of relatively decay-resistant soil organic matter, is found in the peptidoglycan of G + bacteria than in those of G- bacteria (Zhang et al. 2015). Therefore, our finding that the SOC content in the treatments under study was significantly positively linked with the G+/G bacterial ratio (Fig. S1).

4.3 Linking microbial community to SOC chemistry

The relationship between microbial community structure and soil C forms was studied using Principal component analysis (PCA), Redundant analysis (RDA) and Multivariate regression tree (MRT) (Fig. 5, 6, 7). We discovered that the microbial community was significantly (P < 0.05) related with SOC content, which was consistent with previous research (Dong et al. 2014; Schnecker et al. 2015). RDA analysis revealed that changes in the composition and diversity of soil microbial communities were best described by the chemical composition of SOC, correlating with comparable findings in earlier investigations (Wang et al. 2017). This confirmed our prediction that fertilization-induced changes in soil C chemistry would lead to changes in the composition and diversity of microbial communities. Therefore, compared to prior studies (> 50%), C forms accounted for a higher fraction (> 85%) of the variability in soil microbial composition in the current study (Ng et al. 2014).

As previously established, the soil microbial community composition definitely responded differentially to topsoil and subsoil carbon forms. The higher relative abundance of O-alkyl C and lower of alkyl C of the SOC in the T1M treatment may relying on the Proteobacteria, Firmicutes, and Bacteroidetes abundances, which were shown to be positively associated to O-alkyl C. It is most likely that the application of cattle manure in topsoil reduced native SOC decomposition, as seen by the decreased A/OA ratio of topsoil treated with manure. As alkyl C is inadequate and has a negative connection to the abundance of Actinobacteria, Verrucomicrobia, and Cyanobacteria, it is possible that these bacteria participate in its degradation. Actinobacteria, considered r-strategists with high affinity to a specific substrate, and can provide glycoside hydrolases for exogenous organic matter degradation (Trivedi et al. 2013). Members of the Verrucomicrobia have been claimed to break down refractory biological materials in the past (Fierer et al. 2013). The higher relative abundance of Alkyl C and lower of O-alkyl C of the SOC in the T2M treatment may rely on the Acidobacteria, Gemmatimonadetes, and Patescibacteria abundances, which were shown to have a favourable correlation with alkyl C. It may be possible that application cattle manure in subsoil promoted native SOC decomposition, showing the greater A/OA ratio of subsoil with manure. The phylum Acidobacteria includes many oligotrophic species. After the addition of new organic matter to the soil, communities of resistant SOC decomposers came to dominate native soil organic matter-degrading organisms. This was due to the fact that these organisms acted as decomposers of SOC (Pascault et al. 2013). In addition, the low abundance of O-alkyl C, together with the negative connection between O-alkyl C content and abundance of both members of Cyanobacteria and Acidobacteria and the fungus of Ascomycota, implies that these bacteria may be engaged in the breakdown of O-alkyl C. This is supported by the fact that there is a negative correlation between O-alkyl C content and abundance of both of these bacterial groups. Subsoil has the lower F/B ratio and A/OA ratio than topsoil, while subsoil with manure has a greater F/B ratio and A/OA ratio than topsoil with manure. This is indicated that application cattle manure in subsoil promoted the microbial community composition transform from bacterial to fungal, especially the members of Ascomycota, suggested that fungal community of subsoil was more sensitive to organic manure. Therefore, the subsoil with cattle manure has more decomposition degree of SOC when compared with topsoil, and improving the stability of SOC.

The RDA and MRT analyses both showed that O-alkyl C was the most important factor in explaining the differences in microbial composition. In addition, PLFA indicators for Actinobacteria, Firmicutes, and Bacteroidetes were predominantly related with O-alkyl C and aromatic C forms that differentiated T2 from T2M based on MRT. When resources are plentiful, the phyla of Firmicutes are able to expand rapidly due to their copiotrophic features, which allow them to preferentially consume labile soil organic C pools (Fierer et al. 2007). And it was found that bacteria belonging to the group Bacteroidetes favour a C-rich substrate (Fierer et al. 2007). There was a positive correlation between the phyla Firmicutes and Bacteroidetes and manure-amended subsoil, which makes sense given that the SOC in the subsoil decomposed more rapidly following manure application. In addition, MRT showed that aromatic C and alkyl C separated T1 from T1M, with the former being mostly related with PLFA indicators for bacteria like Acidobacteria and fungi like Basidiomycota and Ascomycot. The phylum Acidobacteria includes many oligotrophic species, Acidobacteria, operating as resistant SOC decomposers, were found to dominate native soil organic matter-degrading communities after the addition of fresh organic matter to the soil, as demonstrated by the research of (Pascault et al. 2013). Ascomycota and Basidiomycota fungi were traditionally recognised as the two most common saprophytic decomposers in soil (Sanaullah et al. 2016). These fungi may be representative of the community's capacity to break down cellulose and ligno-cellulose (Sanaullah et al. 2016). Meanwhile, these bacteria and fungal were positive association with topsoil that has a greater alkyl C (recalcitrant C) proportion. Taken as a whole, the disparate associations between microbial community composition and soil C composition emphasize the necessity to take both into account simultaneously.

This study found that application cattle manure in top-, and subsoil had different effects on SOC chemistry and microbial community structure. The quality of top-, and subsoil were different, and subsoil had lower decompostion degree of SOC owing to the lower Alkyl C/O-alkyl C (A/OA) ratio compared with topsoil. The topsoil with cattle manure amended decreased the A/OA ratio relative to without amendment, which indicated that application cattle manure on topsoil decreased the decomposition degree of SOC. This might be because there is an inverse relationship between the concentration of alkyl C and the number of Actinobacteria, Verrucomicrobia, and Cyanobacteria. However, application cattle manure on subsoil increased the A/OA ratio, and improved the decomposition degree of SOC, thus enhanced the stability of SOC. This might be because of the inverse relationship between O-alkyl C concentration and the numbers of Cyanobacteria, Acidobacteria, and the fungi of Ascomycete. Furthermore, subsoil with cattle manure made SOC more stable than topsoil with cattle manure, which may be attributed to the bacterial community transform from bacterial to fungal, especially greater of Ascomycota were observed. In conclusion, application cattle manure was beneficial to the decomposition and stabilization of SOC in the subsoil. After cattle manure was applied, the subsoil's SOC stability significantly improved above the topsoil's. For this reason, sustainable management practises such the application of manure that enhanced the quantity and recalcitrance of soil organic carbon need to be developed for use in the future, particularly in subsoil.

Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Acknowledgements

This research was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA28110202), and the Open Research Fund of Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences (2020ZKHT-04), and the Special Fund Project of Jilin Province and Chinese Academy of Sciences (2021SYHZ0003).

Author Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Qilin Zhang, Juan Hu and Daowei Zhou. The first draft of the manuscript was written by Qilin Zhang and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Interests Declarations

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Ai C, Liang G, Sun J, Wang X, Zhou W (2012) Responses of extracellular enzyme activities and microbial community in both the rhizosphere and bulk soil to long-term fertilization practices in a fluvo-aquic soil. Geoderma 173:330–338
Ananyeva ND, Castaldi S, Stolnikova EV, Kudeyarov VN, Valentini R (2015) Fungi-to-bacteria ratio in soils of European Russia. Arch Agron Soil Sci 61:427–446
Angst S, Harantova L, Baldrian P, Angst G, Cajthaml T, Strakova P, Blahut J, Vesela H, Frouz J (2019) Tree species identity alters decomposition of understory litter and associated microbial communities: a case study. Biol Fertil Soils 55:525–538
Baldock JA, Oades JM, Waters AG, Peng X, Vassallo AM, Wilson MA (1992) Aspects of the chemical-structure of soil organic materials as revealed by solid-state C-13 NMR-spectroscopy. Biogeochemistry 16:1–42
Balesdent J, Basile-Doelsch I, Chadoeuf J, Cornu S, Derrien D, Fekiacova Z, Hatte C (2018) Atmosphere-soil carbon transfer as a function of soil depth. Nature 559:599–
Baumann K, Marschner P, Smernik RJ, Baldock JA (2009) Residue chemistry and microbial community structure during decomposition of eucalypt, wheat and vetch residues. Soil Biol Biochem 41:1966–1975
Bittman S, Forge TA, Kowalenko CG (2005) Responses of the bacterial and fungal biomass in a grassland soil to multi-year applications of dairy manure slurry and fertilizer. Soil Biol Biochem 37:613–623
Blume E, Bischoff M, Reichert JM, Moorman T, Konopka A, Turco RF (2002) Surface and subsurface microbial biomass, community structure and metabolic activity as a function of soil depth and season. Appl Soil Ecol 20:171–181
Chu H, Sun H, Tripathi BM, Adams JM, Huang R, Zhang Y, Shi Y (2016) Bacterial community dissimilarity between the surface and subsurface soils equals horizontal differences over several kilometers in the western Tibetan Plateau. Environ Microbiol 18:1523–1533
Clegg CD, Lovell RDL, Hobbs PJ (2003) The impact of grassland management regime on the community structure of selected bacterial groups in soils. FEMS Microbiol Ecol 43:263–270
Cotrufo MF, Wallenstein MD, Boot CM, Denef K, Paul E (2013) The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob Change Biol 19:988–995
de Vries FT, Bloem J, van Eekeren N, Brusaard L, Hoffland E (2007) Fungal biomass in pastures increases with age and reduced N input. Soil Biol Biochem 39:1620–1630
Di J, Feng W, Zhang W, Cai A, Xu M (2017) Soil organic carbon saturation deficit under primary agricultural managements across major croplands in China. Ecosyst Health Sustain 3:1364047
Dong W-Y, Zhang X-Y, Dai X-Q, Fu X-L, Yang F-T, Liu X-Y, Sun X-M, Wen X-F, Schaeffer S (2014) Changes in soil microbial community composition in response to fertilization of paddy soils in subtropical China. Appl Soil Ecol 84:140–147
Du C, Xu CY, Jian JS, He WX, Hou L, Geng ZC (2018) Seasonal dynamics of bacterial communities in a Betula albosinensis forest. Eur J Soil Sci 69:666–674
Eilers KG, Debenport S, Anderson S, Fierer N (2012) Digging deeper to find unique microbial communities: The strong effect of depth on the structure of bacterial and archaeal communities in soil. Soil Biol Biochem 50:58–65
Elfstrand S, Hedlund K, Martensson A (2007) Soil enzyme activities, microbial community composition and function after 47 years of continuous green manuring. Appl Soil Ecol 35:610–621
Fanin N, Kardol P, Farrell M, Nilsson M-C, Gundale MJ, Wardle DA (2019) The ratio of Gram-positive to Gram-negative bacterial PLFA markers as an indicator of carbon availability in organic soils. Soil Biol Biochem 128:111–114
Fierer N, Bradford MA, Jackson RB (2007) Toward an ecological classification of soil bacteria. Ecology 88:1354–1364
Fierer N, Ladau J, Clemente JC, Leff JW, Owens SM, Pollard KS, Knight R, Gilbert JA, McCulley RL (2013) Reconstructing the Microbial Diversity and Function of Pre-Agricultural Tallgrass Prairie Soils in the United States. Science 342:621–624
Fontaine S, Barot S, Barre P, Bdioui N, Mary B, Rumpel C (2007) Stability of organic carbon in deep soil layers controlled by fresh carbon supply. Nature 450:277–U210
Francioli D, Schulz E, Lentendu G, Wubet T, Buscot F, Reitz T (2016) Mineral vs. Organic Amendments: Microbial Community Structure, Activity and Abundance of Agriculturally Relevant Microbes Are Driven by Long-Term Fertilization Strategies. Front Microbiol 7:1446
He YT, He XH, Xu MG, Zhang WJ, Yang XY, Huang SM (2018) Long-term fertilization increases soil organic carbon and alters its chemical composition in three wheat-maize cropping sites across central and south China. Soil & Tillage Research 177:79–87
Hu J, Zhou D, Zhong R, Zhao C, Li Q (2023) Response of microbial community diversity and subsoil properties to cow manure amendment in mollisols. Arch Agron Soil Sci 69:785–802
Kundu S, Bhattacharyya R, Prakash V, Ghosh BN, Gupta HS (2007) Carbon sequestration and relationship between carbon addition and storage under rainfed soybean-wheat rotation in a sandy loam soil of the Indian Himalayas. Soil Tillage Res 92:87–95
Lazcano C, Gomez-Brandon M, Revilla P, Dominguez J (2013) Short-term effects of organic and inorganic fertilizers on soil microbial community structure and function. Biol Fertil Soils 49:723–733
Li D, Chen L, Xu J, Ma L, Olk DC, Zhao B, Zhang J, Xin X (2018) Chemical nature of soil organic carbon under different long-term fertilization regimes is coupled with changes in the bacterial community composition in a Calcaric Fluvisol. Biol Fertil Soils 54:999–1012
Li Y, Zhang Q, Cai Y, Yang Q, Chang SX (2020) Minimum tillage and residue retention increase soil microbial population size and diversity: Implications for conservation tillage. Sci Total Environ 716:137164
Li Z, Zhao B, Wang Q, Cao X, Zhang J (2015) Differences in Chemical Composition of Soil Organic Carbon Resulting From Long-Term Fertilization Strategies. PLoS ONE 10:e0124359
Liang C, Schimel JP, Jastrow JD (2017) The importance of anabolism in microbial control over soil carbon storage. Nat Microbiol 2:17105
Liu X, Peng C, Zhang W, Li S, An T, Xu Y, Ge Z, Xie N, Wang J (2022) Subsoiling tillage with straw incorporation improves soil microbial community characteristics in the whole cultivated layers: A one-year study. Soil & Tillage Research 215:105188
Luo Z, Wang G, Wang E (2019) Global subsoil organic carbon turnover times dominantly controlled by soil properties rather than climate. Nat Commun 10:3688
Malik AA, Chowdhury S, Schlager V, Oliver A, Puissant J, Vazquez PGM, Jehmlich N, von Bergen M, Griffiths RI, Gleixner G (2016) Soil Fungal:Bacterial Ratios Are Linked to Altered Carbon Cycling. Front Microbiol 7:1247
Marschner P, Kandeler E, Marschner B (2003) Structure and function of the soil microbial community in a long-term fertilizer experiment. Soil Biol Biochem 35:453–461
Mustafa A, Frouz J, Naveed M, Zhu P, Sun N, Xu M, Nunez-Delgado A (2022) Stability of soil organic carbon under long-term fertilization: Results from 13C NMR analysis and laboratory incubation. Environ Res 205:112476
Naylor D, McClure R, Jansson J (2022) Trends in Microbial Community Composition and Function by Soil Depth. Microorganisms 10:540
Ng EL, Patti AF, Rose MT, Schefe CR, Wilkinson K, Smernik RJ, Cavagnaro TR (2014) Does the chemical nature of soil carbon drive the structure and functioning of soil microbial communities? Soil Biol Biochem 70:54–61
Pascault N, Ranjard L, Kaisermann A, Bachar D, Christen R, Terrat S, Mathieu O, Leveque J, Mougel C, Henault C, Lemanceau P, Pean M, Boiry S, Fontaine S, Maron P-A (2013) Stimulation of Different Functional Groups of Bacteria by Various Plant Residues as a Driver of Soil Priming Effect. Ecosystems 16:810–822
Peacock AD, Mullen MD, Ringelberg DB, Tyler DD, Hedrick DB, Gale PM, White DC (2001) Soil microbial community responses to dairy manure or ammonium nitrate applications. Soil Biol Biochem 33:1011–1019
Peng S, Guo T, Liu G (2013) The effects of arbuscular mycorrhizal hyphal networks on soil aggregations of purple soil in southwest China. Soil Biol Biochem 57:411–417
Pisani O, Lin LH, Lun OOY, Lajtha K, Nadelhoffer KJ, Simpson AJ, Simpson MJ (2016) Long-term doubling of litter inputs accelerates soil organic matter degradation and reduces soil carbon stocks. Biogeochemistry 127:1–14
Pries CEH, Castanha C, Porras RC, Torn MS (2017) The whole-soil carbon flux in response to warming. Science 355:1420–1422
Rankoth LM, Udawatta RP, Gantzer CJ, Jose S, Veum K, Dewanto HA (2019) Cover Crops on Temporal and Spatial Variations in Soil Microbial Communities by Phospholipid Fatty Acid Profiling. Agron J 111:1693–1703
Rossel RAV, Lee J, Behrens T, Luo Z, Baldock J, Richards A (2019) Continental-scale soil carbon composition and vulnerability modulated by regional environmental controls. Nat Geosci 12:547–
Salome C, Nunan N, Pouteau V, Lerch TZ, Chenu C (2010) Carbon dynamics in topsoil and in subsoil may be controlled by different regulatory mechanisms. Glob Change Biol 16:416–426
Sanaullah M, Chabbi A, Maron P-A, Baumann K, Tardy V, Blagodatskaya E, Kuzyakov Y, Rumpel C (2016) How do microbial communities in top-and subsoil respond to root litter addition under field conditions? Soil Biol Biochem 103:28–38
Schiedung M, Tregurtha CS, Beare MH, Thomas SM, Don A (2019) Deep soil flipping increases carbon stocks of New Zealand grasslands. Glob Change Biol 25:2296–2309
Schnecker J, Wild B, Takriti M, Alves RJE, Gentsch N, Gittel A, Hofer A, Klaus K, Knoltsch A, Lashchinskiy N, Mikutta R, Richter A (2015) Microbial community composition shapes enzyme patterns in topsoil and subsoil horizons along a latitudinal transect in Western Siberia. Soil Biol Biochem 83:106–115
Shrestha BM, Singh BR, Forte C, Certini G (2015) Long-term effects of tillage, nutrient application and crop rotation on soil organic matter quality assessed by NMR spectroscopy. Soil Use Manag 31:358–366
Solomon D, Lehmann J, Kinyangi J, Amelung W, Lobe I, Pell A, Riha S, Ngoze S, Verchot L, Mbugua D, Skjemstad J, Schaefer T (2007) Long-term impacts of anthropogenic perturbations on dynamics and speciation of organic carbon in tropical forest and subtropical grassland ecosystems. Glob Change Biol 13:511–530
Song L, Yang T, Xia S, Yin T, Liu X, Li S, Sun R, Gao H, Chu H, Ma C (2022) Soil depth exerts stronger impact on bacterial community than elevation in subtropical forests of Huangshan Mountain. Sci Total Environ 852:158438
Sradnick A, Oltmanns M, Raupp J, Joergensen RG (2014) Microbial residue indices down the soil profile after long-term addition of farmyard manure and mineral fertilizer to a sandy soil. Geoderma 226:79–84
Tian Q, Yang X, Wang X, Liao C, Li Q, Wang M, Wu Y, Liu F (2016) Microbial community mediated response of organic carbon mineralization to labile carbon and nitrogen addition in topsoil and subsoil. Biogeochemistry 128:125–139
Trivedi P, Anderson IC, Singh BK (2013) Microbial modulators of soil carbon storage: integrating genomic and metabolic knowledge for global prediction. Trends Microbiol 21:641–651
van Groenigen KJ, Qi X, Osenberg CW, Luo Y, Hungate BA (2014) Faster Decomposition Under Increased Atmospheric CO2 Limits Soil Carbon Storage. Science 344:508–509
Wan X, Huang Z, He Z, Yu Z, Wang M, Davis MR, Yang Y (2015) Soil C:N ratio is the major determinant of soil microbial community structure in subtropical coniferous and broadleaf forest plantations. Plant Soil 387:103–116
Wang H, Liu SR, Wang JX, Shi ZM, Xu J, Hong PZ, Ming AG, Yu HL, Chen L, Lu LH, Cai DX (2016) Differential effects of conifer and broadleaf litter inputs on soil organic carbon chemical composition through altered soil microbial community composition. Sci Rep 6:27097
Wang H, Nie Y, Butterly CR, Wang L, Chen Q, Tian W, Song B, Xi Y, Wang Y (2017) Fertilization alters microbial community composition and functional patterns by changing the chemical nature of soil organic carbon: A field study in a Halosol. Geoderma 292:17–24
Wang Q, Zhang L, Zhang J, Shen Q, Ran W, Huang Q (2012) Effects of compost on the chemical composition of SOM in density and aggregate fractions from rice–wheat cropping systems as shown by solid-state 13C‐NMR spectroscopy. J Plant Nutr Soil Sci 175:920–930
Wei M, Hu G, Wang H, Bai E, Lou Y, Zhang A, Zhuge Y (2017) 35 years of manure and chemical fertilizer application alters soil microbial community composition in a Fluvo-aquic soil in Northern China. Eur J Soil Biol 82:27–34
Willers C, van Rensburg PJJ, Claassens S (2015) Phospholipid fatty acid profiling of microbial communities-a review of interpretations and recent applications. J Appl Microbiol 119:1207–1218
Wu M, Qin H, Chen Z, Wu J, Wei W (2011) Effect of long-term fertilization on bacterial composition in rice paddy soil. Biol Fertil Soils 47:397–405
Xu JM, Tang C, Chen ZL (2006) Chemical composition controls residue decomposition in soils differing in initial pH. Soil Biol Biochem 38:544–552
Yan X, Zhou H, Zhu QH, Wang XF, Zhang YZ, Yu XC, Peng X (2013) Carbon sequestration efficiency in paddy soil and upland soil under long-term fertilization in southern China. Soil Tillage Res 130:42–51
Zhang H, Ding W, Yu H, He X (2015a) Linking organic carbon accumulation to microbial community dynamics in a sandy loam soil: result of 20 years compost and inorganic fertilizers repeated application experiment. Biol Fertil Soils 51:137–150
Zhang JJ, Dou S, Song XY (2009) Effect of long-term combined nitrogen and phosphorus fertilizer application on 13C CPMAS NMR spectra of humin in a Typic Hapludoll of northeast China. Eur J Soil Sci 60:966–973
Zhang Y, Yao S, Mao J, Olk DC, Cao X, Zhang B (2015b) Chemical composition of organic matter in a deep soil changed with a positive priming effect due to glucose addition as investigated by C-13 NMR spectroscopy. Soil Biol Biochem 85:137–144
Zhang YL, Li LJ, Yao SH, Mao JD, Schmidt-Rohr K, Olk DC, Cao XY, Cui JF, Zhang B (2018) Distinct changes in composition of soil organic matter with length of cropping time in subsoils of a Phaeozem and Chernozem. Eur J Soil Sci 69:868–878
Zhao B, Chen J, Zhang J, Qin S (2010) Soil microbial biomass and activity response to repeated drying-rewetting cycles along a soil fertility gradient modified by long-term fertilization management practices. Geoderma 160:218–224
Zhao H, Lv Y, Wang X, Zhang H, Yang X (2012) Tillage impacts on the fractions and compositions of soil organic carbon. Geoderma 189:397–403
Zhong W, Gu T, Wang W, Zhang B, Lin X, Huang Q, Shen W (2010) The effects of mineral fertilizer and organic manure on soil microbial community and diversity. Plant Soil 326:511–522
Zhong Y, Yan W, Zhouping S (2015) Impact of long-term N additions upon coupling between soil microbial community structure and activity, and nutrient-use efficiencies. Soil Biol Biochem 91:151–159
Zhou J, Deng Y, Zhang P, Xue K, Liang Y, Van Nostrand JD, Yang Y, He Z, Wu L, Stahl DA, Hazen TC, Tiedje JM, Arkin AP (2014) Stochasticity, succession, and environmental perturbations in a fluidic ecosystem. Proc Natl Acad Sci USA 111:E836–E845
Zhou P, Pan GX, Spaccini R, Piccolo A (2010) Molecular changes in particulate organic matter (POM) in a typical Chinese paddy soil under different long-term fertilizer treatments. Eur J Soil Sci 61:231–242

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published 24 Apr, 2024

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Application of cattle manure increased the stability of organic carbon in the subsoil in Mollisols

Status:

Journal Publication

Version 1

Abstract

Figures

1 Introduction

2 Materials and Methods

2.1 Experimental design

2.2 ¹³C-NMR (nuclear magnetic resonance) spectroscopy

2.3 Fourier Transform Infrared Spectrometer (FTIR Spectrometer) analysis

2.4 Phospholipid fatty acid (PLFA) analysis

2.4 Statistical analyses

3 Results

3.1 Characteristics of soil

3.2 PLFA Content

3.3 Fourier Infrared Spectroscopy

3.4 ¹³C nuclear magnetic resonance (NMR) spectroscopy

3.5 Integrating SOC forms to microbial community composition

4 Discussion

4.1 The effect of cattle manure on SOC chemical composition

4.2 The effect of cattle manure on microbial communities composition

4.3 Linking microbial community to SOC chemistry

5 Conclusion

Declarations

Data Availability

Acknowledgements

Author Contributions

Interests Declarations

References

Status:

Journal Publication

Version 1

Application of cattle manure increased the stability of organic carbon in the subsoil in Mollisols

Status:

Journal Publication

Version 1

Abstract

Figures

1 Introduction

2 Materials and Methods

2.1 Experimental design

2.2 13C-NMR (nuclear magnetic resonance) spectroscopy

2.3 Fourier Transform Infrared Spectrometer (FTIR Spectrometer) analysis

2.4 Phospholipid fatty acid (PLFA) analysis

2.4 Statistical analyses

3 Results

3.1 Characteristics of soil

3.2 PLFA Content

3.3 Fourier Infrared Spectroscopy

3.4 13C nuclear magnetic resonance (NMR) spectroscopy

3.5 Integrating SOC forms to microbial community composition

4 Discussion

4.1 The effect of cattle manure on SOC chemical composition

4.2 The effect of cattle manure on microbial communities composition

4.3 Linking microbial community to SOC chemistry

5 Conclusion

Declarations

Data Availability

Acknowledgements

Author Contributions

Interests Declarations

References

Status:

Journal Publication

Version 1

2.2 ¹³C-NMR (nuclear magnetic resonance) spectroscopy

3.4 ¹³C nuclear magnetic resonance (NMR) spectroscopy