Effects of Biochar and Organic Additives on CO₂ Emissions and the Microbial Community at Two Water Saturations in Saline–Alkaline Soil

Abstract

The nutrient-limiting conditions in saline–alkali soil as well as the salinity and alkalinity stress are successfully alleviated by water management measures and the addition of organic matter. However, the impacts of these two strategies on the microbe-driven CO₂ emissions in saline–alkaline soils are not yet clear. Therefore, a 150-day incubation experiment was conducted in this study to evaluate the short-term effects of water regulation and the addition of organic matter with different characteristics on CO₂ emissions and microbial community characteristics in saline–alkali soils under non-flooding conditions. This study was conducted at two water saturations, i.e., 50% WFPS and 80% WFPS. In addition, five organic matter treatments were conducted: CK: control; N: urea; SN: Straw + urea; SNH: Straw + urea + microbial agent; and SNB: Straw + urea + biochar. The results demonstrated that compared with 50% WFPS, 80% WFPS significantly increased cumulative CO₂ emission by 27.66%, but significantly decreased salt content and the fungal Chao1 and Shannon indices. The application of the biochar and microbial agent decreased the cumulative CO₂ emissions of the SN treatment by 27.39% and 14.92%, respectively. When sufficient carbon supply is available, the decrease in fungal diversity may reduce CO₂ emission. The findings demonstrated that SNH and SNB at 80% WFPS might decrease CO₂ emissions under straw carbon intake as well as the loss of labile organic carbon (LOC). Additionally, these treatments can alleviate microbial stress caused by salinity, which has a favorable impact on enhancing carbon storage in salinity-affected dryland soils.

1. Introduction

The current trend of global warming can lead to the expansion of the global dryland area to 56% of the total land surface area by the year 2100. Moreover, it can escalate the risk of dryland soil salinization [1,2]. High salinity and pH alter the species composition of soil microorganisms and plants as well as affect the dynamic balance between soil organic carbon (SOC) storage and soil respiration, which increases the ambiguity surrounding climate change [3,4]. Moreover, soil salinization has emerged as a critical environmental issue that threatens ecosystem balance, agricultural productivity, human health, and sustainable development [5,6]. Therefore, urgent and effective measures should be taken for the prevention of salinization and improvement of saline–alkali land in arid areas.

Extensive studies have demonstrated that the application of organic matter, such as crop straw, biochar, and green manure, may be an effective strategy for enhancing soil quality and improving soil organic matter in saline–alkaline land [7,8]. Additionally, there has been an increased research interest globally in practical water management techniques such as freshwater input, drip irrigation, and underground pipeline drainage technology because of their significant contribution to reducing the buildup of toxic ions in the soil and improving the physical conditions of saline–alkaline land [9,10]. Apart from reducing the negative effects of salinity on the ecosystem, the application of combined water management strategies and organic matter enrichment for the improvement of saline lands also increases the ability of arid zone soils to store carbon, creating a negative feedback loop impacting the global carbon cycle [2]. Extensive research studies have been carried out on water management techniques and organic fertilizer applications to improve soil properties in the saline–alkali soils. However, the research on microbe-driven CO₂ emissions during the improvement of saline–alkali soils by combining multiple measures is limited.

Numerous studies have demonstrated that the addition of organic matter, such as straw, improves the physicochemical properties of saline soils while enhancing microbial activity and increasing CO₂ emissions [11,12]. However, the application of microbial agents stimulates the deposition of microbe-derived stable carbon by accelerating the turnover of exogenous organic matter, which not only enhances the stability of the soil organic carbon pool but also effectively reduces CO₂ emissions during straw decomposition and primary soil organic carbon mineralization [13,14]. Biochar, an organic material with high aromatic structure and chemical biostability, is not easily decomposed and utilized by microorganisms and has shown great potential in enhancing organic carbon stock and reducing heterotrophic respiration (R_h) in saline soils [15,16]. One of the most important constraints of salty soils is macronutrient deficiency, and the ecosystem processes in saline soils are highly affected by nitrogen availability [17]. Studies have demonstrated that nitrogen addition leads to different effects on CO₂ emissions during microbial respiration by altering soil nitrogen availability and microbial community structure [18,19]. Extensive research has been carried out in China and globally on soil organic carbon and respiration in the farmland system response to the addition of organic matter such as biochar. However, an accurate understanding of CO₂ emissions driven by microorganisms during the improvement of saline–alkali soils using different combinations of organic matter is limited.

Numerous studies have demonstrated that water management can significantly improve soil physicochemical properties [20] by reducing the electrical conductivity (EC) and sodium sorption ratio (SAR) of saline soils [21] and increasing microbial biomass and microbial respiration [22], all of which are effective measures for improving soil organic carbon storage in saline soils. A key factor influencing both positive and negative feedback changes in the climate–carbon cycle is the availability of water, and under warmer conditions, generally, wet soil conditions stimulate net soil carbon uptake (negative feedback) [23]. Soil respiration increases with increasing moisture [24], but in humid environments, when soil moisture is saturated or flooded, the continuous rise in soil moisture restricts O₂ diffusion and lowers CO₂ generation [25]. This is mainly attributed to the different sensitivity of soil respiration components to soil moisture [3,26]. Although extensive research has been carried out on soil respiration in agricultural ecosystems and other ecosystems under effective water management strategies, the understanding of the impact of water management measures on microbe-driven CO₂ emissions in the current methods of remediation of saline–alkali soil is limited.

Extensive studies have demonstrated that additional applications of organic matter such as straw can affect microbial biomass, diversity, composition, and structure by causing changes in the soil physicochemical properties [27,28]. Soil microorganisms play dual and contrasting roles in the decomposition and mineralization of organic matter and the transformation of carbon input into stable organic forms [14]. By several ecological processes, such as the uptake and release of nutrients such as carbon in various forms, soil microbes play significant roles in determining the turnover of soil organic matter and climate feedback mechanisms [29,30]. Microbial community composition, along with microbial diversity and biomass, are significant microbial indicators for predicting soil CO₂ flux [31,32]. However, the effects of organic matter addition and water management measures on microbe-driven CO₂ emissions during the improvement of saline–alkali soil still remain unclear.

Formulating management measures to promote carbon storage in dryland soils and reducing the risk of salinization require a deeper comprehension of the effects of organic matter application and water regulation on CO₂ emission in the saline–alkali soil improvement process, as well as their biological and abiotic driving mechanisms. Therefore, a 150-day indoor incubation experiment was conducted in the saline–alkaline soil of Songnen Plain, China. The major objectives of this study were to determine the changes in microbe-driven CO₂ emission in saline–alkali soil at different water saturations and with different organic additives; to determine the effects of different water saturations and organic additives on the microbial community in the saline–alkali soil; and to explore the biological and abiotic regulation mechanisms driving CO₂ emissions from the saline–alkali soil at different water saturations and with different organic additives.

2. Materials and Methods

2.1. Properties of Soil and Organic Additives

Topsoil (0–20 cm) was collected for incubation experiments in November 2019 from a saline field located in Dulbert County, Heilongjiang Province, China (46°48′56″ N, 124°29′44″ E). The area is located in the middle and western parts of the Songnen Plain, with a mid-temperate continental climate and an average annual air temperature of 4 °C and precipitation of 400 mm. The soil samples were air-dried, cleaned by removing glass roots, crushed, homogenized, and passed through a 2 mm sieve. The soil contained 8.56 g kg⁻¹ total carbon, 0.11 g kg⁻¹ total nitrogen, 1.28 g cm⁻³ bulk density, and 12.08 g kg⁻¹ dissolved total salt, with a pH of 10.07. The soil texture was sandy loam with 75.63% sand (0.02–2 mm), 16.38% silt (0.002–0.02 mm) and 7.98% clay (<0.002 mm).

In the western part of the Songnen Plain, rice is being grown as a practical way to utilize saline land [33]. However, a lot of straw resources were not used in a sensible way during the cultivation of rice, and there were practices such as burning that polluted the environment [34]. We gathered rice straw from Dulbert County as a follow-up addition experiment so that we could take full advantage of the plentiful local saline and rice straw resources. Furthermore, it has been demonstrated that biochar made at higher pyrolysis temperatures has a larger surface area and a higher amount of aromatic carbon [35], which lowers soil CO₂ emissions after biochar addition and helps to improve soil carbon storage [36,37]. So, we settled on 500 °C as the pyrolysis temperature to produce biochar. Urea was obtained from Harbin Flower and Fish Market. The basic properties of the modifiers were determined by an elemental analyzer (Thermo Flash EA-1112, Costa Mesa, CA, USA) and a fully automatic specific surface area and pore size distribution analyzer (Autosorb-iQ, Boynton Beach, FL, USA) (

Table 1. Basic properties of soil additives (mean ± SD, n = 3).

Properties	Rice Straw	Biochar	Urea
TC (%)	54.58 ± 0.78	47.44 ± 0.22	19.72 ± 0.07
TN (%)	1.05 ± 0.1	2.16 ± 0.01	44.78 ± 0.12
H (%)	5.08 ± 0.06	2.38 ± 0.01	6.82 ± 0.05
Surface Area (m2 g−1)	-	10.22 ± 0.43	-
Pore Volume (cc g−1)	-	0.03 ± 0.002	-
Pore Diameter (nm)	-	3.72 ± 0.38	-

). The above soil additives were prepared for use by crushing and passing through a 2 mm sieve. The microbial agent utilized was W-18 straw decomposer, made of Bacillus subtilis, Bacillus megaterium, and jelly-like Bacillus, with an effective viable count ≥ 2.0 × 10⁸ mL⁻¹, created by Heilongjiang Huxufeng Ecological Technology Company (Harbin, China).

2.2. Experimental Design and Measurement of Soil CO₂ Emissions

Soil incubation experiments were established after pre-incubating the soil at 30% and 50% water-filled pore space (WFPS) under a soil temperature of 15 °C for 10 days for stabilization of the native soil microbial community [38]. The whole incubation experiment was divided into two parts: gas collection and soil physics and chemistry. The gas was collected in a 250 mL headspace bottle with a butyl rubber stopper containing 30 g of dry soil, while the soil physics and chemistry were determined in a 1 L glass wide-mouth bottle containing 200 g of dry soil. Each soil portion was subjected to two moisture saturations, five organic matter treatments, and three repetitions of each treatment.

The incubation experiments were set up with five organic material addition treatments: CK: control; N: urea; SN: straw + urea; SNH: straw + urea + microbial agent; and SNB: straw + urea + biochar, in which urea, rice straw, and biochar were added to the culture system at a ratio of 0.18 mg g⁻¹, 3.73 mg g⁻¹, and 7.67 mg g⁻¹ of dry soil, respectively. The proportion of rice straw added was based on the full amount of local rice straw returned to the field of 958.65 g m⁻² and the soil bulk density of the surface layer (0–20 cm) of saline soils; urea was added according to 5% of the added mass of straw; and the amount of biochar added was based on the recommended 2000 g m⁻² addition rate and soil capacity conversion. The study by Song et al. suggested a biochar application rate of 2000 g m⁻² to deal with rising atmospheric CO₂ concentrations, which is effective for resolving the challenges caused by climate change [39]. Urea was dissolved and added to the soil as a solution in order to thoroughly mix the nitrogen fertilizer (urea) with the soil that had been pre-incubated with different WFPS.The soil moisture was set to 50% WFPS and 80% WFPS at the start of the incubation experiment, and deionized water was added every 7 days to maintain the soil moisture constant according to the mass loss (the mouth of the bottle was covered with tin foil to reduce evaporation and ensure normal gas exchange). The temperature settings were based on the monthly average soil temperature at 20 cm depth from May to September, i.e., the growing season in Dulbert soil, thus simulating the natural warming during the growing season (temperature data were obtained from the daily ground temperature profiles of the Dulbert weather station in Heilongjiang Province from 2001 to 2010).

Soil CO₂ emissions were collected at the start of the incubation period, i.e., day 0 followed by days 4 and 7, and once a week thereafter for 147 days. At each gas sampling date, the headspace of each tank was first purged with fresh air for about 30 min, and the bottles were then sealed with caps fitted with plug valves and butyl rubber plugs. Headspace gas samples of 20 mL were obtained after 0 h, 1 h, and 3 h of sealing using a gas-tight syringe. CO₂ concentrations were quantified using gas chromatography (GC, Agilent 7890A, Santa Clara, CA, USA) with a flame ionization detector (FID). Soil CO₂ emission rates were calculated based on the changes in the gas concentrations over time. Soil cumulative CO₂ emissions were calculated based on the existing methods [40].

2.3. Soil Physicochemical and Microbial Sequencing Analysis

The soil samples were subjected to destructive techniques before and after culturing to determine their physical and chemical properties. Soil organic carbon was determined using a carbon and nitrogen analyzer (Multi C/N 3100, Germany). Labile organic carbon (LOC) was determined using a 333 mol.L⁻¹ potassium permanganate oxidation method [41]. Ammonium (NH₄⁺-N), nitrate (NO₃⁻-N), and total dissolved nitrogen (TDN) were determined using an intermittent flow analyzer (SKALAR SAN++, Delft, The Netherlands). Inductively coupled plasma mass spectrometry (ICP-MS, Agilent 7500CX, Santa Clara, CA, USA) was used for the analysis of basic soil cations (K⁺, Ca²⁺, Na⁺, and Mg²⁺) extracted using ammonium acetate [3]. The pH was determined in a soil–water suspension (1:2.5 w/v) using an acidity meter (PHSJ-3F, China); the total dissolved soil salts (TSS) content was measured according to the mass method [42]. Briefly, the 1:5 w/v soil–water extract was evaporated in a water bath, and the organic matter was removed from the soil–water extract with hydrogen peroxide solution, dried at 105 °C, and weighed using an electronic balance (Sartorius BSA224S, Germany) for calculation. The soil samples were collected from CK and N treatment groups at the start and end of the incubation period and stored at −80 °C for subsequent microbiological analysis.

The soil samples were sent to Personal Biotechnology Ltd. for deoxyribonucleic acid (DNA) extraction and PCR amplification (Shanghai, China). Deoxyribonucleic acid was extracted from three replicates of each soil sample. The extracted deoxyribonucleic acid quality was checked by 1.2% agarose gel electrophoresis and spectrophotometry (ratio of optical density at 260 nm and 280 nm and ratio of optical density at 260 nm and 230 nm). 16S rRNA V3–V4 and fungal ITS1 variable region were sequenced using the NovaSeqPE250 sequencing platform (Illumina, San Diego, CA, USA). Bacterial 16S rRNA was amplified using 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′), while the fungal ITS1 gene region was amplified using ITS1 (5′-GGAAGTAAAAGTCGTAACAAGG-3′) and ITS2 (5′-GCTGCGTTCTTCATCGATGC-3′) primers. The PCR procedure followed was initial denaturation at 98 °C for 2 min, denaturation at 98 °C for 15 s, annealing at 55 °C for 30 s, extension at 72 °C for 30 s, final extension at 72 °C for 5 min, and hold at 10 °C for 25–30 cycles. The amplicon mixture (25 μL) was applied to the NovaSeqPE250 sequencing platform and consisted of 5× reaction buffer (5 μL), 5× GC buffer (5 μL), 2.5 mM dNTP (2 μL), 10 µM forward primer (1 μL), 10 µM reverse primer (1 μL), deoxyribonucleic acid template (2 μL), ddH2O (8.75 μL), and Q5 deoxyribonucleic acid polymerase (0.25 μL). The community deoxyribonucleic acid fragments were then sequenced in the Illumina double-end (paired-end) sequencing platform according to the standard protocol. The DADA2 method of QIIME2 (2019.4) was used for de-priming, mass filtering, denoising, splicing, and chimerization [43]. High-quality sequences were clustered at a 97% similarity level using Usearch software (v2.13.4 Linux x86 64) and Cutadapt (v2.3) [44]. 16S rRNA and ITS gene sequences were compared to the Silva database and UNITE database using QIIME 2′s classify-sklearn algorithm for their species annotation [45].

2.4. Statistical Analysis

Soil physicochemical properties (pH, total dissolved soil salts, and basic cations, namely, K⁺, Ca²⁺, Na⁺, and Mg²⁺), soil carbon and nitrogen fractions, cumulative CO₂ emissions, and the Chao1 and Shannon indices of bacteria and fungi were analyzed with a two-way analysis of variance (ANOVA). Duncan’s multiple range test was used for testing the significance levels at p = 0.05. The graphs and plots were prepared using the package “ggplot2” in R v4.2.3. Before analysis, the Shapiro–Wilk test was applied to check if the data were normally distributed, and the results indicated that the data followed a normal distribution.

Redundancy analysis (RDA) of the gene cloud (https://www.genescloud.cn, accessed on 18 April 2023) was used to examine the link between soil characteristics and the composition of the soil microbial community (bacterial and fungal). Further, the correlation between soil properties and the relative abundance of bacteria and fungi at the class level was examined using the package “corrplot” in R v4.2.3. A structural equation model (SEM) was constructed using the package “lavaan” in R v4.2.3.

3. Results

3.1. Soil Physical and Chemical Properties

Compared with the contents in saline–alkali soil at 50% WFPS, the soil organic carbon and labile organic carbon contents in the soil at 80% WFPS increased by 9.66% and 3.56 times, respectively, but the total dissolved nitrogen, NH₄⁺-N, and NO₃⁻-N contents decreased by 15.08%, 12.55%, and 4.77%, respectively. The 80% WFPS reduced total dissolved soil salts and Ca²⁺ content by 29.05% and 8.49%, respectively, when compared with the 50% WFPS group. The basic physical and chemical properties of soil are shown in

Table 2. Effects of different treatments on soil properties after 150 days of incubation (mean ± SD, n = 3).

SAC	WFPS	SOC	LOC	TDN	NH4+-N	NO3−-N	pH	TSS	Ca2+
		(mg kg−1)	(mg kg−1)	(mg kg−1)	(mg kg−1)	(mg kg−1)		(g kg−1)	(mg kg−1)
CK	50%	4920 ± 88.88 Cb	1477.25 ± 1031.21 Ab	274.6 ± 43.56 Aa	2.87 ± 0.1 Aa	45.44 ± 3.15 Ca	10.23 ± 0.16 Ba	10.72 ± 0.16 Da	6111.67 ± 299.98 Ba
	80%	5530 ± 147.99 Ca	4178.76 ± 1091.48 Aa	242.54 ± 33.56 Ab	2.92 ± 0.28 Ab	34.23 ± 4.46 Cb	10.05 ± 0.14 Ba	4.88 ± 0.34 Db	6469 ± 333.8 Bb
N	50%	5186.67 ± 202.07 Cb	1997.44 ± 951.65 Ab	292.6 ± 4.02 Aa	3.65 ± 0.35 Aa	67.37 ± 1.06 Aa	10.16 ± 0.1 Ba	12.53 ± 0.93 Ca	6533 ± 627.51 ABa
	80%	5276.67 ± 150.11 Ca	3846.36 ± 340.77 Aa	234.75 ± 15.5 Ab	2.75 ± 0.1 Ab	68.12 ± 0.5 Ab	10.09 ± 0.06 Ba	5.09 ± 0.72 Cb	6588.67 ± 156.37 ABb
SN	50%	5076.67 ± 56.86 Cb	491.01 ± 361.65 Bb	290.57 ± 6.27 Aa	3.53 ± 0.61 Aa	66.18 ± 0.89 ABa	10.31 ± 0.13 Aa	8.27 ± 0.48 Da	6466 ± 614.53 Ca
	80%	5440 ± 200.75 Ca	2246.51 ± 946.33 Ba	263.86 ± 26.88 Ab	3 ± 0.35 Ab	65.67 ± 0.65 ABb	10.33 ± 0.06 Aa	6.49 ± 0.41 Db	4515 ± 83.29 Cb
SNH	50%	5136.67 ± 228.55 Bb	1277.23 ± 510.94 Ab	281.92 ± 7.65 Aa	3.13 ± 0.14 Aa	65.86 ± 1.65 Ba	10.26 ± 0.03 Aa	10.18 ± 0.12 Ba	7254.33 ± 348.45 Aa
	80%	5896.67 ± 23.09 Ba	4484.36 ± 344.87 Aa	241.28 ± 9.18 Ab	2.83 ± 0.06 Ab	61.9 ± 0.47 Bb	10.3 ± 0.1 Aa	10.42 ± 0.4 Bb	6439 ± 206.86 Ab
SNB	50%	7340 ± 257.1 Ab	790.02 ± 374.79 Ab	291.59 ± 4.85 Aa	3.15 ± 0.58 Aa	64.84 ± 0.36 Ba	10.32 ± 0.04 ABa	12.1 ± 0.62 Aa	7341.67 ± 334.37 Aa
	80%	8190 ± 160.93 Aa	5517.15 ± 847.44 Aa	233.02 ± 4.81 Ab	2.78 ± 0.16 Ab	64.99 ± 0.66 Bb	10.18 ± 0.02 ABa	11.28 ± 0.58 Ab	6833.33 ± 289.82 Ab
ANOVA		p values
SAC		***	*	ns	ns	***	**	***	***
WFPS		***	***	***	**	***	ns	***	***
SAC × WFPS		**	**	ns	ns	***	ns	***	***

Note: Different uppercase letters (organic matter added) and lowercase letters (water saturation) indicate significant differences at p = 0.05 (Duncan’s Multiple Range Test). CK, control treatment; N, urea; SN, straw + urea; SNH, straw + urea + microbial agent; SNB, straw + urea + biochar; SOC, soil organic carbon; LOC, labile organic carbon; TDN, dissolved total nitrogen; NH₄⁺-N, ammonia nitrogen; NO₃⁻-N, nitrate nitrogen; TSS, total soluble salt; and basic cations, namely, Ca²⁺. The p values for these factors were obtained from a two-way ANOVA for the addition of soil amendments with different characteristics (SAC), different water saturations (WFPS), and their interactions (SAC × WFPS), *** p < 0.001, ** p < 0.01, * p < 0.05, ns p > 0.05.

. The addition of soil amendments with different characteristics (SAC) significantly increased the soil organic carbon content in saline–alkali soil, with SNH and SNB increasing the soil organic carbon content by 5.58% and 48.61%, respectively (p < 0.001) when compared with CK and SN treatment reducing labile organic carbon content by 42.18%. The addition of soil amendments with different characteristics (SAC) significantly increased NO₃⁻-N supply in the saline–alkali soil when compared with CK, with the NO₃⁻-N content in the N, SN, SNH, and SNB groups increasing by 70.07%, 65.50%, 60.36%, and 62.97%, respectively (p < 0.001).

3.2. Soil CO₂ Emissions

The indoor incubation experiments demonstrated that the addition of soil amendments with different characteristics (SAC) and enhanced soil moisture (WFPS) significantly increased the CO₂ flux on the last day of the experiment as well as the cumulative CO₂ emission throughout the incubation period (p < 0.001) (Figure 1,

Table 3. The effects of different treatments on the Chao1 and Shannon indexes from bacteria and fungi and the CO₂ flux on the last day of the experiment as well as the cumulative CO₂ emission throughout the incubation period in saline–alkali soil (mean ± SD, n = 3).

SAC	WFPS	Bacterial Chao1	Bacterial Shannon	Fungal Chao1	Fungal Shannon	CO2 Fluxes	Cumulative CO2 Emissions
						(mg kg−1 d−1)	(mg kg−1)
CK	50%	4114.96 ± 590.16 Ba	9.82 ± 0.08 Aa	652.05 ± 96.62 Aa	7.09 ± 0.27 Aa	12.46 ± 4.24 Cb	2223.18 ± 378.43 Db
	80%	4161.34 ± 310.94 Ba	9.77 ± 0.25 Aa	462.16 ± 84.97 Ab	5.67 ± 1.26 Ab	12.76 ± 0.98 Ca	2146.45 ± 250.64 Da
N	50%	4627.86 ± 252.35A Ba	9.93 ± 0.06 Aa	537.05 ± 48.36 Aa	7.28 ± 0.26 Aa	10.64 ± 3.36Cb	2266.22 ± 377.47 CDb
	80%	4661.82 ± 304.94A Ba	9.78 ± 0.34 Aa	491.85 ± 71.69 Ab	4.65 ± 1.56 Ab	11.59 ± 1.02 Ca	2343.25 ± 99.72 CDa
SN	50%	4496.82 ± 76.29 Aa	9.73 ± 0.19 ABa	379.41 ± 40.43Ba	5.45 ± 0.12 Ba	13.05 ± 5.23 Ab	3016.72 ± 752.3 Ab
	80%	4455.35 ± 305.77 Aa	9.75 ± 0.06 ABa	270.41 ± 17.78 Bb	3.73 ± 0.27 Bb	30.48 ± 1.76 Aa	4650.9 ± 228.47 Aa
SNH	50%	4271.19 ± 229.74A Ba	9.61 ± 0.29 Ba	290.3 ± 84.51 Ca	3.35 ± 0.92 Ca	9.89 ± 1.48 ABb	2563.65 ± 244.89 Bb
	80%	4212.53 ± 102.08 ABa	9.52 ± 0.19 Ba	162.73 ± 30.85 Cb	2.28 ± 0.46 Cb	25 ± 5.1 ABa	3960.11 ± 517.57 Ba
SNB	50%	4371.15 ± 167.53 Aa	9.74 ± 0.14 Aa	421.04 ± 11.19 BCa	4.15 ± 0.83 Ca	11.49 ± 3.74 BCb	2553.19 ± 479.2 BCb
	80%	4274.64 ± 217.4Aa	9.94 ± 0.04 Aa	162.05 ± 27.62 BCb	2.68 ± 0.37 Cb	14.37 ± 2.01 BCa	3014.19 ± 235.65 BCa
ANOVA		p values
SAC		ns	*	***	***	***	***
WFPS		ns	ns	***	***	***	***
SAC × WFPS		ns	ns	ns	ns	***	**

Note: Different uppercase letters (organic matter added) and lowercase letters (water saturation) indicate significant differences at p = 0.05 (Duncan’s Multiple Range Test). CK, control treatment; N, urea; SN, straw + urea; SNH, straw + urea + microbial agent; SNB, straw + urea + biochar. The p values for these factors were obtained from a two-way ANOVA for the addition of soil amendments with different characteristics (SAC), different water saturations (WFPS), and their interactions (SAC×WFPS), *** p < 0.001, ** p < 0.01, * p < 0.05, ns p > 0.05.

). The CO₂ flux and cumulative CO₂ emission at 80% WFPS increased by 63.75% and 27.66%, respectively, when compared with those at 50% WFPS, while the CO₂ fluxes of SN, SNH, and SNB increased by 72.53%, 38.28%, and 2.53%, respectively, when compared with those of CK. However, the CO₂ flux of SN significantly decreased with the application of microbial agents and biochar. When compared with those of CK, the cumulative CO₂ emissions of N, SN, SNH, and SNB increased by 5.49%, 75.48%, 49.30%, and 27.41% respectively, while the application of microbial inoculum and biochar decreased the cumulative CO₂ emissions of SN by 14.92% and 27.39%, respectively. At day 30 of incubation, the cumulative CO₂ emission rate increased significantly in all treatment groups as the incubation temperature was adjusted (increased) and leveled off thereafter. Analysis of variance showed that CO₂ emissions in the saline–alkali soil were significantly affected by the addition of soil amendments with different characteristics (SAC), enhanced soil moisture (WFPS), and their interactions (p < 0.01) (Table 3).

3.3. Soil Microbial Community

The fungal Chao1 and Shannon indices of soil at 80% WFPS decreased by 27.21% and 24.56%, respectively (p < 0.01; Table 3), when compared with those of soil at 50% WFPS, while the bacterial Shannon index of the SNH group decreased by 2.9% when compared with that of CK. The fungal Chao1 index of N, SN, SNH, and SNB groups decreased by 3.83%, 29.38%, 50.77%, and 36.63%, respectively, while the fungal Shannon index decreased by 2.10%, 21.44%, 51.84%, and 41.63%, respectively, when compared with that of CK.

Alphaproteobacteria and Gammaproteobacteria were the dominant classes in the bacterial community of each treatment group, accounting for about 36% of the total bacterial abundance, while Sordariomycetes was the dominant class in the fungal community of the samples, accounting for about 50.3% of the total fungal abundance. The 80% WFPS increased the relative abundance of Alphaproteobacteria, Acidimicrobiia, Deltaproteobacteria, Thermoleophilia, Subgroup_6, Longimicrobia, Sordariomycetes, and Leotiomycetes, but decreased the relative abundance of Nitriliruptoria, Actinobacteria, Bacilli, Chloroflexia, and Pucciniomycetes (Figure 2). The addition of soil amendments with different characteristics (SAC) enhanced the relative abundance of Acidimicrobiia, Nitriliruptoria, Anaerolinea, and Sordariomycetes but reduced the relative abundance of Bacteroidia, Actinobacteria, Bacilli, Chloroflexia, Deltaproteobacteria, Thermoleophilia, Subgroup_6, Longimicrobia and Dothideomycetes, Eurotiomycetes, and Leotiomycetes (Figure 2).

3.4. Relationship between CO₂ Emissions and Soil Physicochemical Properties and Microbial Communities

In RDA, the combination of variables could explain 34.52% of the variations in bacterial (Figure 3a) and 54.6% in fungal (Figure 3b) communities. WFPS, total dissolved soil salts (TSS), and total dissolved nitrogen (TDN) had comprehensive impacts on the bacterial and fungal community composition (p < 0.05, Figure 3a,b). NH₄⁺-N was negatively correlated with WFPS and labile organic carbon (LOC), thus significantly affecting the bacterial community (p < 0.01, Figure 3a). Cumulative CO₂ emission was positively correlated with NO₃⁻-N and pH, thus significantly affecting the fungal community (p < 0.01, Figure 3b). The results of Spearman correlation analysis indicated that CO₂ emission had a significant positive relationship with soil moisture (WFPS), soil amendments with different characteristics (SAC), and pH (p < 0.05, Figure 4) at the end of the incubation period. However, it demonstrated a strong negative association with the fungal Chao1 and Shannon indices (p < 0.05). In addition, CO₂ emission was positively correlated with the relative abundance of Bacteroidia, Acidimicrobiia, Anaerolineae, Subgroup_6, and Sordariomycetes (p < 0.05), but negatively correlated with the relative abundance of Actinobacteria, Thermoleophilia, Nitriliruptoria, Dothideomycetes, and Eurotiomycetes (p < 0.05).

SEM models can explain 73% and 96% of the variations in CO₂ fluxes and cumulative CO₂ emissions in saline–alkali soils, respectively (Figure 5a). WFPS, pH (R² = 0.16), and the fungal Shannon index (R² = 0.77) demonstrated significant direct positive effects on CO₂ fluxes (R² = 0.73). Soil amendments with different characteristics (SAC) also had indirect positive effects on CO₂ fluxes by influencing pH and the fungal Shannon index, while the fungal Chao1 index (R² = 0.80) had direct negative effects on CO₂ fluxes (p < 0.05) and cumulative CO₂ emissions (R² = 0.96) through CO₂ fluxes. Soil amendments with different characteristics (SAC), NO₃⁻-N content (R² = 0.36), and CO₂ fluxes all demonstrated direct positive effects on the cumulative CO₂ emissions (p < 0.01), while WFPS, pH, and the fungal Shannon index all demonstrated indirect positive effects on cumulative CO₂ emissions through CO₂ fluxes.

The SEM model demonstrated that soil amendments with different characteristics (SAC), WFPS, pH, and fungal Shannon and Chao1 indices had comprehensive effects on CO₂ flux and cumulative CO₂ emission in the saline–alkali soils (Figure 5b). Generally, the increase in soil amendments with different characteristics (SAC), WFPS, pH, and the fungal Shannon index promoted CO₂ flux and cumulative CO₂ emissions, while the increase in the fungal Chao1 index decreased CO₂ flux and cumulative CO₂ emissions. In addition, the increase in NO₃⁻-N content and CO₂ flux in soils significantly stimulated the increase in cumulative CO₂ emissions.

4. Discussion

4.1. CO₂ Emissions from the Saline–Alkali Soil

Water availability is one of the primary drivers of positive and negative feedback changes in the climate–carbon cycle and soil carbon flux in the drylands [23]. In this study, it was observed that the cumulative CO₂ emission in the 80% WFPS group increased by 27.66% when compared with that in the 50% WFPS group (Figure 1), which was in agreement with the previous research results [24]. Similar to a majority of previous studies conducted in arid regions, this study focused entirely on CO₂ emission from saline–alkali soil during non-flooded incubation. Water is one of the key limiting factors in arid regions, and during dry periods, the feedback of the soil carbon cycle is particularly sensitive to the soil moisture-precipitation [2,23]. Rainfall or an increase in water content willresult in rapid microbial respiration and accumulation of accessible substrate in dry soil, resulting in enhanced microbial biomass and activity as well as considerable CO₂ emissions [25]. However, the rise in soil microbial respiration because of the rainfall episodes was relatively moderate. Microbial activity and CO₂ flow can decline from the restricted O₂ diffusion as the soil moisture levels increase till they reach saturation or submersion [3,46]. In addition, it was observed that 80% WFPS significantly increased the relative abundance of Sordariomycetes and Subgroup_6, which demonstrated a significant positive correlation with CO₂ emissions (p < 0.05, Figure 2 and Figure 4) and was consistent with a previous study [47]. Sordariomycetes and Subgroup_6 have been shown to play key roles in the carbon cycle [48]. Rainfall or water management can indirectly affect microbial community composition and CO₂ emissions by regulating soil aeration [49], carbon and nitrogen availability [50], salinity [20], and other soil characteristics [51]. The results indicated that 80% WFPS enhanced water availability in the saline–alkali soil, which could not only stimulate microbial activity directly but also increase the relative abundance of Sordariomycetes and Subgroup_6 related to SOM decomposition. This might be an important reason for an increase in microbe-driven CO₂ emissions owing to the increase in water under non-flooded conditions.

The characteristics of exogenous organic additives are the key factors determining the changes in CO₂ flux during the process of soil improvement [16]. It was observed that different organic additives significantly increased cumulative CO₂ emissions in the saline–alkali soil when compared with those in the CK group (Figure 1), which was in agreement with the results from a previous study [17]. Bhattacharyya reported that CO₂ emissions were affected by the amount of exogenous organic matter added and carbon stability [52]. It is noteworthy that SN treatment significantly reduced the labile organic carbon content of the soil while resulting in the highest amount of cumulative CO₂ emissions (Table 2 and Table 3). This may be attributed to the low stability of straw carbon. As straw carbon has rich energy and low specific surface area, it weakly combines with soil minerals and is easily utilized by the soil microorganisms, thereby rapidly releasing into the atmosphere in the form of CO₂, which is not conducive to the formation of stable carbon in soil [53]. The input of organic matter with poor stability may aggravate the mineralization process of native SOM, leading to a positive priming effect [54]. However, the application of microbial agents, as one of the effective strategies for climate change mitigation, can accelerate the process of natural carbon stabilization [55]. Studies have demonstrated that the application of microbial agents in conjunction with soil organic additives, such as the addition of straw to the soil, might significantly lower CO₂ emissions [13], which was also observed in this study. The microbial agents can accelerate the decomposition and transformation of straw C [56], increase microbial biomass, improve the turnover rate of exogenous organic matter, stimulate the production of more microbial residues and stable microbial carbon [14], and effectively reduce CO₂ emissions [13]. The availability of carbon substrate and temperature have a greater impact on soil heterotrophic respiration [57]. Previous research has demonstrated that global CO₂ emissions frequently rise in response to rising temperatures [58]. This is consistent with what we have seen. The cumulative CO₂ emission rate was found to significantly rise for each treatment group between days 30 and 60 of incubation. This might be connected to our heightened incubation temperature on day 30 (simulated warming of the growth season). The increase in soil temperature promotes microbial activity, speeds up the breakdown of organic materials in the soil, and raises CO₂ emissions [57]. In addition, we observed a slower rate of increase in cumulative CO₂ emissions for each treatment group after day 60. This may be related to the increase in temperature in the previous period, which caused a decrease in decomposition efficiency because of the rapid consumption of the more microbially accessible carbon fraction of the soil and the more decomposable fraction of the exogenous organic matter by microorganisms [59,60].

In this study, it was observed that the application of biochar (SNB) significantly reduced cumulative CO₂ emissions from SN treatment groups (Figure 1), which was consistent with the results from previous studies [15,16]. Because of its rich carbon, large specific surface area (SSA), high porosity, and aromatic structure, biochar can effectively impede the return of photosynthetically fixed carbon to the atmosphere and is considered a potential management practice to increase soil carbon storage and reduce CO₂ emission [16]. In addition, the SEM results also demonstrated that CO₂ fluxes and cumulative CO₂ emissions in the saline–alkali soils were significantly regulated by the characteristics of soil organic additives (Figure 5). The study results indicated that a combination of microbial inoculum and biochar can significantly reduce labile organic carbon (LOC) loss and cumulative CO₂ emissions in SN treatment. Additionally, the addition of soil amendments with different characteristics (SAC) increased the soil’s porosity and connectedness, boosting the number of big pores while lowering the bulk density (BD) of the soil [61]. Previous research has demonstrated that a drop in bulk density typically results in an increase in CO₂ emissions [62,63]. This is because enhanced soil porosity increases oxygen flux and aerobic microbial activity in the soil.

Large levels of soil inorganic carbon (SIC) in the form of carbonates are found in arid and semi-arid soils [64]. In calcareous soils, carbonate dissolution may be a significant source of CO₂ emissions [65]. The percentage of inorganic carbon (SIC) in surface calcareous soils that contributes to overall CO₂ emissions can range from 15% to 30% [64,66], according to a number of earlier studies. The effectiveness of Ca²⁺ or Mg²⁺, the pH of the soil solution, the degree of CO₂ partial pressure in the soil pore space, and other factors all affect carbonate dissolution [64,67,68]. In arid and semi-arid environments, soil inorganic carbon (SIC) concentration has been demonstrated to increase with irrigation or soil moisture [69]. Under dry conditions, an increase in soil moisture encourages microbial respiration and raises the CO₂ content of the soil. Increased CO₂ concentration encourages the creation of HCO₃⁻ and H⁺, which may drive soil carbonate breakdown and cause the release of CO₂ from inorganic salts when combined with suitable moisture conditions. This may be yet another significant factor contributing to the rise in cumulative CO₂ emissions in the 80% WFPS treatment group. Arid areas can store more organic and inorganic carbon through agricultural practices such as applying organic matter, according to several studies [67,70]. However, some research indicates that both mineral and organic fertilizers, particularly nitrogen fertilizers (urea), may increase soil acidification, which might hasten carbonate dissolution and the release of CO₂ from inorganic carbon sources [67,71]. The impact of various water management strategies and the enrichment of organic fertilizers on CO₂ emissions from sources of inorganic carbon in arid and semi-arid regions requires further investigation in order to be revealed and quantified.

4.2. Soil Microbial Community

Soil microbial diversity and community composition were affected by water management measures through the regulation of soil carbon and nitrogen substrates, water availability, pH, and other physicochemical properties [20,49,50]. The experimental results in this study demonstrated that the increase in water content (WFPS) significantly reduced the fungal Chao1 and Shannon indices (p < 0.01; Table 3), which was consistent with the results observed by McHugh et al. [72]. Several precipitation or water management techniques have distinct effects on the fungal alpha diversity index [72,73]. This is because water quality and water management techniques may have an impact on the responses of diverse microbial communities to soil water availability [74]. We discovered that 80% WFPS decreased the relative abundance of Nitriliruptoria and Actinobacteria, which demonstrated a significant positive correlation with total dissolved soil salts (TSS) while increasing the relative abundance of Deltaproteobacteria, Thermoleophilia, Subgroup_6, and Longimicrobia, which demonstrated a significant negative correlation with pH and total dissolved soil salts (TSS) (p < 0.05, Figure 2 and Figure 4). This was consistent with the results observed in some previous studies [75,76], and maybe occurred because of different strategies by which soil microorganisms living in water-managed environments respond to salinity and alkalinity stress [77]. RDA revealed that WFPS showed a weak negative correlation with pH, which had a significant impact on the composition of the fungal community but was negatively correlated with total dissolved soil salts (TSS) (p < 0.05), which had a significant impact on the bacterial and fungal community composition in the saline–alkaline soil (Figure 3). Saline–alkali stress can alter the osmotic pressure of the extracellular water of microorganisms and result in water loss from cells, which in turn has a toxic effect on the soil microbial cells [78]. However, precipitation or a reasonable water management system can effectively alleviate the soil alkalization stress [79] and reduce the pressure of soil salinity on the metabolism and growth of microorganisms [3]. However, this may reduce the competitive advantage of L-strategists (i.e., tolerance to saline–alkali stress) [77]. The study results demonstrated that 80% WFPS could effectively reduce the stress of salinity and pH on microorganisms. However, it would lead to the loss of the advantage of L-strategists to a certain extent, which might be an important reason for the decline in the α diversity of the fungal community in the saline–alkali soil.

Microbial diversity in the saline–alkali soil showed both positive and negative feedback to the addition of exogenous organic matter [80,81]. This was mainly attributed to the characteristics of soil organic additives (pH, C:N ratio, etc.) and the response of soil properties to the addition of organic matter [82]. It was observed that when compared with CK, SNH and SNB treatments increased the supply of soil organic carbon and NO₃⁻-N in the saline–alkali soil (Table 2) and significantly reduced the fungal Chao1 and Shannon indices (p < 0.01, Table 3). There was also a significant reduction in the bacterial Shannon index of SNH-treated soil (p < 0.05), which was consistent with the results from the previous studies [80,83]. With the addition of exogenous organic matter, saline areas will receive more carbon and nitrogen substrates, which will improve their nutrient-deficient circumstances. According to the evolutionary game concept, an enhancement in the availability of nutrients in the environment could cause microbes to switch from their initial cooperative style of resource mitigation to a competitive one [83]. Additionally, changes in environmental factors (such as pH) brought about by improved nutritional circumstances led to more harmful interactions between microbial species, which ultimately resulted in a loss of microbial diversity [84]. In addition, it was observed that SN treatment significantly reduced the labile organic carbon content (Table 2), while labile organic carbon significantly affected the bacterial community (p < 0.01, Figure 3a). Fu and Zhong reported that soil microbial communities are influenced by the characteristics of exogenous organic matter and the ability of microorganisms with different growth strategies to utilize fragile and stubborn carbon matrices [85,86]. In this study, it was observed that soil amendments with different characteristics (SAC) were positively correlated with the relative abundance of Sordariomycete and Acidimicrobiia (p < 0.05, Figure 4), which was consistent with the results observed in a previous study [87]. However, the results of Han et al. indicated that fertilization reduced the relative abundance of fungi such as Sordariomycetes in a corn field, which was different from this study results [88]. Soil type, fertilization methods, and negative interspecific interactions between microbial species under high nutrient circumstances may all be factors in the decline in the relative abundance of species such as Sordariomycetes. Under oligotrophic conditions, microorganisms tend to cooperate to alleviate resource constraints, while under eutrophic conditions, slow-growing k-strategists (oligotrophic or balanced species) are replaced by fast-growing r-strategists (symbiotic or opportunistic species) [83]. In this study, the results demonstrated that the addition of soil amendments with different characteristics (SAC) increased the carbon and nitrogen availability of saline–alkali soil, which expanded the competitive advantage of Sordariomycetes and Acidimicrobiia participating in SOM turnover and led to the decrease in the Shannon index of bacteria and fungi and the Chao1 index of fungi to a certain extent.

4.3. Relationship between CO₂ Emissions and Soil Physicochemical Properties and Microbial Communities

Soil pH is a key factor affecting the soil microbial communities and CO₂ emissions [3,4]. This study observed that SN, SNH, and SNB treatments increased soil pH to varying degrees when compared with the CK group (Table 2), which may be related to the release of basic components from biochar and organic fertilizer. Previous studies have reported an increase in the basic cations (K⁺, Ca²⁺, Na⁺, and Mg²⁺) with the combined application of biochar and organic fertilizer as well as the increase in the mass of retained organic matter in the soil [89]. SEM results also demonstrated that an increase in pH enhanced CO₂ flux and cumulative CO₂ emissions, which was consistent with the results from a previous study [90]. This study results indicated that an increase in pH could affect the stability of soil carbon and promote CO₂ emissions through the carbon use efficiency of soil microorganisms [90], the release of inorganic carbonates [91], and the interaction of adsorbed organic compounds and soil minerals [92], which was further proved by the Spearman correlation analysis. In addition, a significant negative correlation was observed between pH and the Shannon index of fungi (p < 0.05, Figure 5), which was consistent with the results from a previous study [93]. Because of the saline–alkali stress, microorganisms adapt to stress tolerance, resulting in reduced growth and biosynthesis rate, thereby decreasing microbial biomass and phylogenetic diversity [90]. Microbial diversity plays a more crucial role in regulating the soil carbon decomposition rate than abundance [52]. SEM results indicated that the fungal Shannon index had a significant positive effect on CO₂ flux and cumulative CO₂ emission (Figure 5b), which may be attributed to the positive biodiversity–stability relationships [94]. Higher microbial diversity usually accelerates the decomposition of native and exogenous SOM and stimulates CO₂ emissions [95]. The fungal Chao1 and Shannon indices in soil treated with SNH and SNB decreased significantly when compared with those in soil treated with SN (Table 3). This might be one of the important reasons for a significant reduction in the cumulative CO₂ emissions in the SN group after the application of biochar and microbial inoculum.

Soil NO₃⁻-N content and soil nitrogen availability play important roles in regulating CO₂ emissions in the saline–alkali soil [3,96]. However, the response of microbial respiration to nitrogen addition has not been elucidated and is mainly attributed to factors such as nitrogen forms, soil type, nitrogen application time, and soil nitrogen availability [17,18]. The SEM analysis in this study demonstrated that the addition of exogenous organic matter could stimulate cumulative CO₂ emissions by increasing the soil NO₃⁻-N supply (Figure 5), which was consistent with the results from studies by Luo and Bulseco et al. [96,97]. NO₃⁻-N promotes CO₂ emission and probably enhances the role of microorganisms in respiration-related processes by overcoming the limitation of microbial functional potential due to low energy (availability of electron donors) and thermodynamic limitation (availability of electron receptors) [97]. However, Ramirez et al. observed a contrasting result, hypothesizing that nitrogen input in the form of NO₃⁻-N can reduce the respiratory rate of microorganisms [18]. This study’s results demonstrated that the increase in NO₃⁻-N content can stimulate the microbe-driven CO₂ emission in nitrogen-limiting environments, such as saline–alkali soil. Considering the uncertainty of the response of CO₂ emission to nitrogen addition and nitrogen compounds in recent studies, further research is needed to explain the driving mechanism of the nitrogen supply influencing CO₂ emission in saline–alkali soil subjected to water management measures.

5. Conclusions

Based on a 150-day incubation experiment, increased water content and the addition of organic matter from various sources had significant impacts on the physicochemical properties, CO₂ emissions, and changes in the microbial communities of saline–alkali soil in arid regions. The 80% WFPS increased the labile organic carbon and soil organic carbon contents in saline–alkali soil to varying degrees and reduced the stress of salinity and pH on microorganisms. This expanded the competitive advantages of Sordariomycetes and Subgroup_6 related to SOM turnover, which might be an important reason for the stimulation of CO₂ emissions by wetting events under non-flooded conditions. It was observed that a microbial agent and biochar decreased labile organic carbon (LOC) loss in SN treatment and concurrently decreased the fungal Chao1 and Shannon indices to varying degrees. As a result, SNH and SNB treatments produced much less CO₂ than the SN treatment. Additionally, SEM findings revealed a substantial positive association between the fungal Shannon index and CO₂ emission. The results of this study indicated that 80% WFPS with SNH (straw + urea + microbial agent) and SNB (straw + urea + biochar) could reduce the loss of labile organic carbon and CO₂ emissions under straw carbon input, as well as the pressure of soil salinity on microorganisms, and this method has positive significance in improving the carbon storage of saline–alkali soil in arid regions.