Biochar (BC) was purchased from Henan Lize Environmental Technology Co., Ltd. The raw BC was purified by washing with ultrapure water (resistivity: 18.2 MΩ cm) until a neutral pH was achieved, followed by oven-drying at 80°C. The dried, neutralized BC was modified following the methodology of using Fe2O3 and ZnO at a concentration of 20 mg L^–1. Specifically, 250 g of BC was sieved to a particle size of < 0.25 μm and suspended in ultrapure water containing the nanomaterials. The weight ratio of the nanomaterial solution to BC was set at 1:40. The suspension was ultrasonically agitated for 2 h, then oven-dried at 80°C. Subsequently, the BC-nanomaterial mixture was pyrolyzed at 600°C for 30 min under a nitrogen (N2) atmosphere to produce nano-biochar. The obtained samples were thoroughly rinsed with deionized water to remove residual impurities and dried at 80°C. The overall modification process of raw biochar with nanoparticles was adapted (Ghassemi-Golezani and Rahimzadeh, 2022). Each 5 kg of pot received 50 g of nanomodified biochar and biochar.

A pot experiment was conducted in a randomized block design with three replicates during the early sowing season of 2023 under greenhouse conditions at Hainan University, China. Topsoil (0–20 cm) was collected from farmland of Lingao County near Haikou, China (19° 34’-20° 02’ N, 109° 3’ -109° 53’E). Four treatments; control (CK), biochar (BC), iron-modified biochar (FeBC), and zinc-modified biochar (ZnBC) Nano-modified biochar, amended with Fe2O3 and ZnO, was incorporated into the soil before sowing rice seedlings. The plants were irrigated with freshwater for 25 days, from germination to the tillering stage. A basal dose of 2 g of compound fertilizer was applied to the soil. After the tillering Stage, the plant was irrigated with saline water (0.6% NaCl) and the solution was applied gradually to the pots to avoid osmotic shock and to maintain uniform salinity throughout the experiment. The salt levels in the pots were measured using a salinometer (WS-200 PLUS). Crop management practices were consistently applied under local agricultural standards. In each pot, six rice seedlings were initially transplanted to ensure uniform establishment and survival. The total duration of the experiments was 80 days and Crop was harvested before reproductive maturity. After proper establishment (approximately 1 week after transplanting), the number of seedlings was thinned to four per pot to maintain uniform plant density and minimize competition for nutrients, water, and light. In this study, the standard agronomic practices for rice cultivation under saline conditions were followed. A basal dose of fertilizers was applied at the rate of 120 kg N, 60 kg P₂O₅, and 40 kg K₂O per hectare, with nitrogen supplied in three equal splits. Irrigation was maintained with non-saline water to keep a 2–3 cm water depth throughout the growth period, except during the salinity stress period when saline solution was applied to maintain the desired electrical conductivity levels. Regarding plant protection, no severe pest or disease outbreak was recorded during the experiment; however, a preventive fungicide spray of Carbendazim (0.1%) was applied at the tillering stage to minimize the risk of fungal infection. These details have been incorporated into the Materials and Methods section of the revised manuscript After harvesting the rice crop from the pots, soil sample were collected from this soil. The soil, which was initially Coastal sandy soil, is a typical ultisol with low fertility. Its pH is 6.07, and its OM content is 3.02 g/kg. In the original soil, TN, TP, TK, AP, AK, Nitrate N and Ammonium N in the original soil were 0.25 g kg, 0.31 g/kg, 0.88 g/kg, 7.2 mg/kg, 22.6 mg/kg, 1.25 mg/kg and 2.3 mg/kg, respectively.

Soil samples were collected from each pot and stored in plastic bags. A subsample of fresh soil was preserved at -80°C for enzyme activity analysis and DNA extraction, while the remaining soil was air-dried and sieved for chemical analysis. Soil chemical properties were assessed using standard methods. Soil pH was measured in a 1:2.5 soil-to-deionized water ratio using a pH meter (Mettler Toledo 320-S, Switzerland) following Inyang et al. (2012) (Inyang et al., 2012). SOM was measured by applying the K₂Cr₂O₇ volumetric method. Soil organic carbon (SOC) was determined by using the wet digestion method. Total nitrogen in biochar samples was analyzed with a CN analyzer (Vario Max, Elementar, Germany), while total phosphorus (TP) and total potassium (TK) were quantified via wet digestion (H₂SO₄-HClO₄). Available phosphorus (AP) was extracted using 0.5 M sodium bicarbonate (NaHCO₃) and measured via Mo-Sb spectrophotometry, whereas available potassium (AK) was determined using a 0.5 M ammonium acetate (NH4OAc) extraction method. Ammonium (NH₄⁺) and nitrate (NO₃^–) concentrations were analyzed from fresh soil samples extracted with 2 M KCl (1:10) and quantified using a San + + Continuous Flow Analyzer (Skalar, Netherlands). For urease enzymes, we used the method described by Yang et al. (2016). The activities of catalase (CAT) and β-glycosidase were measured according to the methods described by Tabatabai (1994). The catalase activity was determined based on the recovery of hydrogen peroxide (H₂O₂). Briefly, 2 g of air-dried soil samples were treated with 0.3% H₂O₂, with the resulting filtrate being subsequently titrated with 0.1 mol/L KMnO₄ after 20 min of reaction (Guan et al., 1986). For the determination of microbial biomass phosphorus (MBP), nitrogen (MBN), and carbon (MBC), we used the fumigation method (Brookes et al., 1982).

The soil samples were processed to extract total microbial genomic DNA via the E.Z.N.A.^® Soil DNA Kit (Omega Bio-Tek, Norcross, GA, United States). DNA quality and concentration were determined by 1.0% agarose gel electrophoresis and measurement with a NanoDrop 2000 spectrophotometer (Thermo Scientific), followed by storage at -80°C for subsequent analysis. The hypervariable region of the bacterial 16S rRNA gene was amplified with the primer pairs 338F (5’-ACTCCTACGGGAGGCAGCAG-3’) and 806R (5’-GGACTACHVGGGTWTCTAAT-3’) (Liu et al., 2016) via a T100 Thermal Cycler PCR system (Bio-Rad, United States). The PCR mixture was composed of 4 μL of 5 × fast buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of each primer (5 μM), 0.4 μL of Fast Pfu polymerase, 10 ng of template DNA, and ddH2O, adjusted to a total volume of 20 μL. The amplification protocol started with initial denaturation at 95°C for 3 min, followed by 27 cycles of denaturation at 95°C for 30 s, annealing at 55°C for 30 s, and extension at 72°C for 45 s. A final extension was performed at 72°C for 10 min, and the reaction mixture was then stored at 4°C. The PCR mixture was prepared by combining 4 μL of 5 × Fast Pfu buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of each 5 μM primer, 0.4 μL of Fast Pfu polymerase, 10 ng of template DNA, and ddH2O to achieve a final volume of 20 μL. The disinfected amplicons were combined at equimolar concentrations and then sequenced via paired-end sequencing on the Illumina NextSeq 2000 platform (San Diego, United States) according to the standard protocols provided by Majorbio Bio-Pharm Technology Co., Ltd. The raw sequencing data were processed for quality filtering and merging via Fastp and FLASH software. The optimized sequences were subsequently grouped into operational taxonomic units (OTUs) with a 97% similarity threshold via UPARSE 7.1 (Edgar, 2013).

One-way analysis of variance (ANOVA) followed by Duncan’s test was performed via IBM SPSS 25 to assess treatment differences at a significance level of p < 0.05. Bar graphs were generated using Prism 9.5 software, and microbial data were analyzed using R software. Principal component analysis (PCA) of the bacterial and fungal communities and soil properties was conducted via the R package “vegan” (Wang et al., 2023). Two-factor networks and co-occurrence networks were constructed with the R package “psych” and visualized via Gephi software (Fan et al., 2018). Spearman correlation analysis between biochars and the microbial abundance of bacteria and fungi was conducted using the R package “ggcorrplot” (Liu et al., 2022). Graphs were combined using Adobe Illustrator 2021 software.

As shown in Table 1, salinity adversely affects soil nutrient availability and activities. However, the application of pristine biochar (BC) and nanomodified biochar (FeBC and ZnBC) significantly increased soil nutrient levels in both soils. The results revealed that BC significantly increased the pH in both SS and NS soils, whereas nanobiochar slightly decreased the pH. The soil organic matter (SOM) content increased by 14–20% in the biochar and nanomodified treatments in the NS and SS soils. SOC was also increased with the addition of biochar and modified biochar to the NS and SS soils (Figure 1A). The TN increased by 6.3–12.86% and 16–27% in the saline and NS soils, respectively, after biochar addition. The total phosphorus in the soil also increased by 8–20.3% in response to biochar and modified biochar application in the SS and NS soils. The modified biochar increased the total potassium (TK) content by 5% under both soil conditions. Similarly, the available potassium and phosphorus contents increased by 5–16% and 6–23%, respectively, after the addition of BC, FeBC, and ZnBC. Compared with that in the CK treatment, the NO₃^–-N concentrations in both nanomodified biochar treatments increased by 34% in the NS soil, whereas that in the saline soil increased by 17% after ZnBC treatment. Compared with that in the control, the concentration of ammonium nitrogen after the biochar and nanobiochar treatments increased by 7–13% in the NS soil and 7–17% in the SS soil. Soil MBC and MBN were significantly greater in the nanomodified biochar treatment group in the pristine biochar treatment group and the CK group under SS and NS soils (Figures 1B,C). Urease and catalase activities were higher in the ZnBC and FeBC modified biochars among other treatments under the NS and SS soil conditions (Figures 1D,E). Compared with the other biochars and CK, the Fe-modified biochar increased the activity of β-glucosidase in the NS and SS soils (Figure 1F). Both types of modified biochar promote soil physicochemical properties and activities in the NS and SS soils.

The changes in the abundance of bacterial communities under different nanomodified biochar and pristine biochar applications in the SS and NS soils are shown in Figure 2A. Compared with that in the CK in the NS soil, the abundance of the phylum Proteobacteria in the ZnBC and FeBC treatments decreased by 15 and 17%, respectively. However, in the SS soil, compared with that in the CK, the abundance of Proteobacteria in the FeBC and ZnBC treatments increased by 25 and 22%, respectively. In the NS soil, the highest abundance of the phylum Chloroflexi was observed in the ZnBC treatment, whereas a lower abundance was detected in the FeBC treatment (Figure 2C). Compared with the CK treatment, the BC and ZnBC treatments presented 25 and 28% greater abundances of Chloroflexi, in the SS soil. The abundance of Firmicutes in the SS soil decreased in the BC and ZnBC treatments but significantly increased in the FeBC treatment. Compared with that in the CK treatment, the abundance of Cyanobacteria in the BC and ZnBC treatments increased in the NS soil, and ZnBC increased their abundance in the SS soil. The abundance of Bacteroides significantly increased with BC, FeBC, and ZnBC in the SS soil, but their abundance did not significantly differ in the NS soil.

There were significant changes in the abundance of the phyla Ascomycota, Chitridiomycota, Basidiomycota, and Rozellomycota across the different biochar treatments compared with those in the control in the SS and NS soils (Figure 2B). Ascomycota was the dominant fungal phylum in the SS and NS soils across all the treatments, constituting approximately 75–85% of the relative abundance. The relative abundance of Ascomycota increased with biochar application (BC > FeBC > ZnBC) in NS soil, whereas its relative abundance decreased with biochar application in saline soil compared with that in the control, and the lowest abundance was observed in the ZnBC treatment. The abundance of Basidiomycota increased with BC, FeBC, and ZnBC application in saline soil compared with that in NS soil. In the SS soil, the abundance of Chytridiomycota significantly increased in the FeBC treatments. Rozellomycota dominated only in the ZnBC treatment in the saline soil. The remaining phyla, including Chytridiomycota and Rozellomycota, contributed less than 5% of the overall fungal community.

The BC and Fe- and Zn-modified nanobiochars significantly enhanced the bacterial and fungal communities at the genus level in both the NS and the SS soils (Figure 3A). The abundance of the genus Bacillus slightly increased under the FeBC treatment in NS soil, whereas compared with those in the control, while the abundances in the BC and ZnBC treatments significantly decreased. The abundance of Tumabacillus significantly increased in all the biochar treatments, regardless of the soil conditions. Additionally, the abundance of Anaerolinea significantly increased in all the biochar treatments in the NS soil. The application of BC, FeBC, and ZnBC slightly affected the abundance of norank-o-opb41 in the NS soil, whereas it significantly increased only after ZnBC treatment in the saline soil compared with that in the CK. The abundance of Chloronema increased in the BC and ZnBC treatments in the SS soil. Alphaproteobacteria and Gammaproteobacteria were the predominant classes in the saline soil in FeBC, whereas Bacilli was the leading predominant class in the NS soil (Figure 4A).

The relative abundances of fungal genera subjected to different biochar treatments under both the SS and NS conditions are depicted in a bar plot in Figure 3B. Penicillium abundance was greater in the saline soil than in the NS soil, whereas it was lower in the BC, FeBC, and ZnBC treatments. The relative abundances of other genera, such as Curvularia, unclassified_p_Chytridiomycota, and Phialoparvum, trended to vary across the treatments, but the overall abundances of these genera were greater in the saline soil than in the NS soil. The most dominant class in the NS soil was Sordariomycetes, whereas the class Eurotiomycetes was the major class in the SS soil (Figure 4B).

Network analysis revealed complex interactions among the top ten bacterial phyla and treatments (Figures 5A,C). Proteobacteria, Chloroflexi, Firmicutes, Cyanobacteria, Acidobacteria, and Actinobacteria presented strong associations with the BC, FeBC, and ZnBC treatments in the non-saline soil, suggesting their central roles and improvements in the microbial community. In the saline soil, BC was strongly associated with changes in the abundances of Proteobacteria, Chloroflexi, Firmicutes, and Actinobacteria. Ascomycota, Basidiomycota, Mucoromycota, Chytridiomycota, Rozellomycota, and Fungi_Phy_Incertae_sedis were strongly associated with the BC, FeBC, and ZnBC treatments. Kickxellomycota was related only to the BC treatments in the NS and SS soils, and Mortierellomycota presented the fewest connections with BC and ZnBC in both soil types. The network also clearly differed between the SS and NS soil treatments, highlighting the significant impact of salinity on the bacterial and fungal community structure.

Network analysis is used to visualize the relationships between different microbial species (or genera) within a microbial community (Figures 5B,D). The network analysis results revealed that the genus Bacillus was strongly related to BC and FeBC in both soils. Changes in Ammoniphilus and Bryobacter were strongly related to the NS soil, whereas no connection was detected in the saline soil. Rhodopseudomonas was connected to the FeBC treatment in the saline soil, whereas the other treatments had weak connections. Norank_o__OPB41 was strongly related to all the treatments in the saline soil. Norank_o__SBR1031, norank_o__RBG-13–54–9, norank_f__Anaerolineaceae, and Anaerolinea were strongly related to the ZnBC treatment in the non-saline soil. Network analysis revealed a complex interplay between fungal genera and treatments (Figure 3). Penicillium was strongly associated with NS soil. Septochytrium was connected to only the BC treatment in the SS soil, whereas Scedosporium was connected to the FeBC treatment in the SS soil. Phialoparvum had stronger connections with ZnBC in both soils and with the BC and FeBC treatments in the SS soil.

A clustered heatmap was constructed and revealed the relationships of the top 10 bacterial phyla with the different biochar treatments under both soil conditions (Figure 6A). The bacterial phyla presented relatively high abundances and clustered together, suggesting strong similarities in their abundance patterns across the different treatments and soil types due to the dominance of Proteobacteria and the high relative abundances of Chloroflexi and Firmicutes in most samples. Compared with those of the other phyla, the Cyanobacteria phylum, with high abundance clustered together, indicating a response to the BC and ZnBC treatments under saline soil conditions. Compared with those in the SS soil, the Acidobacteria phylum in the NS soil presented high cluster abundances in all the treatments. The remaining phyla (Desulfobacteria, Bacteriodota, and Myxococcota) with the lowest abundances formed a distinct cluster. The results of the clustered heatmaps revealed the relationships of the different phyla with the biochar and modified biochar treatments in both soil types (Figure 6C). Ascomycota were more abundant and clustered together, suggesting a strong similarity in their abundance patterns across the BC, FeBC, and ZnBC treatments in the SS and NS soils. The Chytridiomycota and Basidiomycota phyla with high abundances were clustered together, indicating similar responses to FeBC and ZnBC in NS soil compared with those in SS soil. The remaining phyla (Rozellomycota, Fungi_phy_Incertae_sedis, Mucoromycota, Mortierellomycota, and Kickxellomycota) with the lowest abundances formed a distinct cluster (Figure 6C). These findings suggest that biochar treatments have some influence on the bacterial community, but their effects are more pronounced than those of salinity. The interaction effect between salinity and biochar likely influences the overall community structure.

Based on the results of the heatmap analysis, Bacillus was highly abundant in non-saline soil, and compared with BC, Zn BC, and FeBC resulted in a greater cluster. Tumebacillus was also significantly abundant in the NS soil in the BC treatment. The results further revealed that the abundances of Bryobacter, Candidatus_Solibacte, and Chloronema were relatively consistently lows across most treatments, indicating that they were less prominent. These data suggest notable microbial diversity and differences in community composition across the samples. Heatmap analysis revealed that salinity was the primary driver of fungal community composition at the genus level, with clear separation between the SS and NS soils (Figure 6B). Penicillium and Curvularia appeared to be the dominant genera across the BC, FeBC, and ZnBC treatments in both the saline and NS soils, indicating their ecological significance in these environments. The row dendrogram suggests potential ecological similarity or functional redundancy between Penicillium and Curvularia, as they cluster together. Other genera, such as Phialoparvum, Rozellomycota, Cladosporium, and Sterigmatomyces, exhibited more distinct abundance patterns and were more abundant in the saline soil than in the NS soil. Pseudallescheria and Septochytrium also clustered together and were less abundant in the NS group (Figure 6D). The column dendrogram highlights the strong influence of salinity on the fungal community, with clear separation between the SS and NS samples.

The relationships between soil physicochemical properties and microbial community composition were explained in NS and SS soils via principal component analysis (PCA). The NS biplot shows 80.8% of the total variance, Dim1 (55.4%) and Dim2 (25.4%), whereas the SS soil biplot displays 91.1% of the total change, Dim1 (56.2%) and Dim2 (27.9%), providing a robust representation of the data (Figure 7). The strong separation along Dim1 suggests that this dimension captures the primary gradient of variation in the dataset. The variables with longer vectors along the axis, such as Proteobacteria, Desulfobacterota, and Bacteroidota, and soil properties, such as TN, SOM, TP, and NH₄, were significant contributors to this variation. Similarly, Dim2 further explained the significant contributions of Chloroflexi, Cyanobacteria, and soil pH to the variation along this axis. The results also revealed positive correlations between TN, AP, TK, AK, Proteobacteria, Desulfobacterota, and Bacteroidota.

Salinity negatively affects soil properties, leading to reduced nutrient availability and impaired plant growth due to osmotic stress and ion toxicity. The introduction of biochar, especially when modified with nanoparticles such as Fe and Zn, enhances soil health by improving key physicochemical properties. The addition of BC significantly increased the pH of both soils due to the alkaline nature of the biochar, which increased the soil pH (Gao et al., 2019). The increase in pH is attributed to the basic cations on the biochar surface, which is consistent with the findings of Khan et al. (2022a,b), who reported a pH increase following the application of rice straw biochar. Furthermore, a slight decrease in the pH of the modified biochar treatments (FeBC) was detected at either level, which was due to the initial low pH of the modified biochar. Soil organic matter (SOM), a vital measure of soil fertility, is greatly enhanced by the application of BC (Khan et al., 2022a,b). Here, our results revealed a significant increase in the soil organic matter and AP contents with the addition of Fe- and Zn-modified biochar (Table 1). Previous reports have indicated that the improvement in SOM caused by biochar provides essential substances for microbial growth (Ren et al., 2018). Similarly, the application of ZnBC enriched with ZnO nanoparticles resulted in the most pronounced effects among all the treatments. These results indicate that zinc not only improves nutrient uptake but also significantly increases nitrogen availability, as evidenced by increases in both nitrate (NO₃^–-N) and ammonium nitrogen (NH₄⁺-N) levels (Xia et al., 2023; Abbas et al., 2024). The possible mechanism for the reduction in pH is associated with the effects of these treatments (FeBC and ZnBC), which create a more favorable environment for nutrient solubility and availability.

The mechanisms through which the treatments improve soil fertility are multifaceted. Both FeBC and ZnBC improve the cation exchange capacity of the soil, allowing for better retention of essential nutrients such as nitrogen, phosphorus, and potassium (Ghassemi-Golezani and Rahimzadeh, 2022) or the release of organic acids during biochar decomposition (Hafeez et al., 2022). The reduced pH could also be partly due to Zn, as it can generate zinc hydroxide complexes that influence the acidity (Xia et al., 2024). A decreased pH can increase the availability of certain nutrients, particularly phosphorus, in alkaline soils. The increase in SOM with ZnBC and FeBC application can be attributed to the high carbon content of biochar, which is resistant to decomposition (Ghassemi-Golezani and Rahimzadeh, 2022). The potential of zinc to stimulate microbial activity leads to increased organic matter turnover and accumulation (Lv et al., 2022). Similarly, the substantial 37.59% increase in TN with ZnBC can be explained by the high surface area and porosity of the biochar, which can adsorb and retain nitrogen compounds (Issa, 2022; Lv et al., 2022). Soil enzymes are mainly produced by microorganisms, and their activity is closely linked to microbial health. In the present research, catalase activity significantly increased with the addition of ZnBC and FeBC biochars. Wojewodzki et al. (2022) as well as Nie et al. (2018) also observed a significant increase in enzymatic activity after the addition of biochar. Furthermore, previous research has shown that the activity of soil enzymes would be affected by the surface area of biochar, mainly due to its retention potential and subsequent capacity for changing or rotating the active site of enzymes (Elzobair et al., 2016; Foster et al., 2018). The soil urease directly participates in the transformation of nitrogen-containing organic matter to N available to plants in the soil, and its active level is an indicator of the soil nitrogen level (Yan and Quan, 2013), involving in the redox reaction beneficial to plant metabolism (Oladele, 2019). In addition, the overall activities of soil enzymes at different soil layers and between various biochar treatments vary with the amount added, which is also common in previous studies.

Nano-BC has garnered increasing attention for its potential to remediate contaminated soil, as it possesses unique characteristics, such as a large surface area and effective hydrodynamic dispersion, which distinguish it from regular BC. The composition of the microbial community may significantly vary between the biochar-amended and control treatments due to high salinity (Kaoping et al., 2019; Fan et al., 2020). In high-salinity soil, the growth of microbes is suppressed, and the diversity of microbial communities is reduced (Feng et al., 2023). Only those microbes that can withstand high salt concentrations can live in high-salinity soil (Liu et al., 2023). The predominant saline–alkalinesoil microorganisms are Gemmatimonadetes, Chloroflexi, Acidobacteria, Firmicutes, Proteobacteria, and Actinobacteria. Currently, the abundances of phyla Chloroflexi, Actinobacteria, Bacteroidota, and Proteobacteria are strongly related to salinity and are abundant in saline soil (Figure 2). Multiple bacterial taxa have been discovered and reported in response to biochar, control, and nanobiochar treatments. In the present investigation, the dominant phyla were Chloroflexi (primarily norank_c__KD4-96 and Chloronemanorank_o__OPB41), Bacteroidota, Proteobacteria, and Firmicutes (Tumebacillus and Bacillus genera) (Figure 2). According to current studies, the Bacteroidota and Proteobacteria phyla are widely distributed and highly adaptable to saline environments (Wang et al., 2022). Because Actinobacteria and Chloroflexi are highly resilient to saline conditions, they are abundant and have been reported in various saline alkaline environments (Gobalakrishnan, 2022). Furthermore, phylotypes are linked to Bacteroidetes and Firmicutes, which are relatively highly salt-tolerant (Ren et al., 2018).

Biochar and nanomodified biochar increased the proportions of salt-resistant microbes of the phyla Chloroflexi, Bacteroidota, Actinobacteria, and Proteobacteria (Figure 2), consequently mitigating saline-alkali biochar stress and enhancing the metabolism and relationships of these microbes with plants. This investigation revealed that the abundances of Acidobacteria, Bacteroidetes, and Firmicutes increased in high-salt environments (Yang et al., 2021). Similarly, as mentioned above, to increase salinity stress, bacterial communities as well as certain phyla, Cyanobacteria, Bacillus, and Bacteroidetes, exhibit strong structural responses and tolerance mechanisms (Zhang M. et al., 2021). These microbes, which can withstand highly saline conditions, are highly beneficial for plant growth and development. These microbes can minimize the adverse effects of salinity, which increases agricultural production in saline soils (Abd El Daim et al., 2015; Egamberdieva et al., 2019). With the addition of biochar, the abundances of Bacteroidota and Proteobacteria are clear indicators that microbial activity increases due to the presence of organic carbon supplied by the addition of biochar to the soil (Ling et al., 2022). The addition of FeBC lower soil pH and consequently enhanced the abundance of Acidobacteriota, which proliferate best in acidic condition (Wu et al., 2019). Based on these evidences, we identified a greater number of core nodes bacterial coexisting networks under biochar treatments compared with CK. Moreover, the probiotic Bacteroidota, a type of Sphingomonas used in FBC treatment as a biomarker, is responsible for inhibiting antioxidation activity and soil pathogens (Deng et al., 2022; Wang et al., 2022). Our results suggest that reducing soil salt and increasing organic carbon and available nutrients under modified biochar application could provide a better habitat environment and nutrients for bacteria, which benefits soil health and plant growth.

Ther application of biochar significantly influenced the fungal community composition in both soil types, particularly at the phylum level. Ascomycota was the dominant fungal phylum, which is consistent with its known adaptability to various soil conditions (Treseder and Lennon, 2015). In the present study, the BC, FeBC, and ZnBC treatments increased the abundance of Ascomycota in the NS soil, likely due to improvements in soil structure, water retention, and nutrient availability, which promoted fungal proliferation (Gul et al., 2015). Conversely, in the saline soil, compared with the control treatment, the application of BC, FeBC, and ZnBC reduced the abundance of Ascomycota, suggesting that salinity stress, possibly exacerbated by biochar-induced changes in soil chemistry, negatively affects growth (Zhang G. et al., 2021; Baldrian et al., 2022). The relative abundance of Unclassified_k_Fungi increased with biochar application in both soil types, with higher levels in the saline soil, indicating the presence of stress-tolerant fungi that benefit from the role of biochar in mitigating extreme conditions (Zhang G. et al., 2021; Han et al., 2024). Additionally, Chytridiomycota and Basidiomycota were more prevalent in the saline soils than in the NS soils under biochar and modified biochar treatments, suggesting that biochar may increase the growth of opportunistic and ligninolytic fungi that contribute to organic matter decomposition and nutrient cycling (Runnel et al., 2025). These shifts in fungal community composition may be attributed to the influence of biochar on soil physicochemical properties, microbial competition, and salinity alleviation, which affect fungal functional dynamics (Lehmann et al., 2011; Baldrian et al., 2022). Overall, biochar amendments differentially modulated fungal communities under both SS and NS conditions, with potential implications for soil health and resilience (Khan et al., 2024).

The application of biochar significantly altered the fungal community composition at the genus level, highlighting its role in shaping microbial ecology in both saline and non-saline soils. Unclassified_k_Fungi was the dominant fungal group across all the treatments, with a notably greater abundance in saline soil under biochar application, particularly in BC, FeBC, and ZnBC, suggesting that biochar provides a suitable habitat for stress-tolerant fungal taxa (Treseder and Lennon, 2015; Feng et al., 2023; Li et al., 2023). The second most dominant genus,_Sordariales, was more abundant in NS soils, especially in the BC treatment, indicating its preference for more favorable soil conditions and its role in organic matter decomposition and nutrient cycling (Gul et al., 2015). Penicillium abundance increased significantly in the saline soil with biochar and modified biochar application, suggesting that Penicillium has a potential ecological function in saline environments because of its known salt tolerance, bioactive metabolite production, and plant growth-promoting properties (Li et al., 2021; Yin et al., 2021). Other fungal genera, including Curvularia, and Phialoparvum, exhibited varying trends across treatments, but their overall abundances were greater in saline soils, suggesting that biochar may increase fungal diversity by mitigating salt stress and creating microhabitats favorable for stress-adapted fungi (Baldrian et al., 2022; Li et al., 2023). The increased abundances of Penicillium in saline soil under biochar treatment may be attributed to improved soil properties, reduced salinity stress, and enhanced microbial interactions, as biochar is known to increase the soil cation exchange capacity, organic matter content, and microbial habitat stability (Lehmann et al., 2011). These findings suggest that biochar and nanomodified biochar amendments play crucial roles in modulating fungal community composition by promoting decomposers and nutrient-cycling fungi in NS soil while enhancing salt-tolerant and stress-adapted fungi in saline environments, ultimately improving soil microbial resilience and ecosystem functioning (Wang et al., 2020).