Rhizosphere effects and plant functional traits collectively determine the ecological strategy of Suaeda salsa across heterogeneous habitats in the Yellow River Delta

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Rhizosphere effects (REs) and plant functional traits (PFTs) are key components of plant adaptation strategies, but their synergistic contributions remain poorly understood. In this study, we selected Suaeda salsa , the pioneer species in coastal wetlands, to explore its ecological adaptation strategies under complex habitats. Methods We conducted a field experiment in the Yellow River Delta, selecting three sites with distinct salinity levels. REs, the key PFTs and soil microbial community compositions of rhizosphere soil (RS) and bulk soil (BS) of S. salsa were quantified. Results RS maintained lower soil pH, while higher soil moisture content, NH 4 + -N content and enzyme activities than BS. Soil microbial communities in RS were also more stabilized and stress-resilient. Concurrently, PFTs shifted under higher salinity. The increased specific leaf area, tissue proline content and sodium to potassium ratio indicate a resource-conservation strategy with enhanced osmotic adjustment. Soil NH 4 + -N and salinity were the most two important factors affecting the growth of S. salsa . Interestingly, we found a significantly negative correlation between soil salinity and plant individual biomass, which means smaller individuals tend to exhibit stronger rhizosphere-mediated responses to salt stress. Conclusions This study demonstrates the multidimensional integration strategy of S. salsa through both rhizosphere optimization and physiological trait plasticity. This mechanistic insight improves understanding of halophyte adaptation and informs strategies for restoring degraded coastal ecosystems. Plant functional traits Rhizosphere effect Soil microbiome composition Euhalophyte Coastal wetlands Ecological adaptation strategy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Since plant growth is significantly influenced by environmental conditions, the need to cope with heterogeneous environments constitutes a major challenge for plants, especially in the context of climate change (Steltzer and Post 2009 ; Wang et al. 2020 ). Therefore, understanding the diverse adaptive strategies of plants remains a central focus in plant ecology research. “Strategy” was explained as the mechanisms of a species to sustain a population, which has been investigated to express an understanding of the opportunities and selective forces that shape the ecologies of plants (Westoby 1998 ). Ecological strategies describe the way a species competes for resources, copes with disturbances, interacts with other species and its environment, and ultimately determines its fitness and performance (Gibb et al. 2023 ). A large amount of studies focused on the adjustment (or “trade-offs”) of functional traits to explain plant adaptive strategies (Grime 1974 ; Westoby 1998 ; Wright et al. 2004 ); recently, the critical role of belowground processes such as rhizosphere effect have also been constantly emphasized (Finzi et al. 2015 ; Han et al. 2020 ). Plant functional traits form the basis of adaptive strategies (Pérez-Harguindeguy et al. 2013 ), while rhizosphere effects act as the critical mediator of environmental responses (Gan et al., 2021 ; Li et al., 2021 ). Collectively, these two components constitute fundamental adaptive mechanisms‌ for plant environmental adaptation.‌ Plant functional traits (PFTs) represent core biological attributes that significantly influence plant establishment, survival, and fitness (Pérez-Harguindeguy et al. 2013 ). PFTs demonstrate strong correlations with plant adaptive capacity. For instance, higher specific leaf area (SLA) represents higher resource acquisition efficiency and higher water and nutrient consumption (Pierce et al. 2012 ); higher root to shoot ratio (RSR) indicates greater soil resources acquisition ability, generally associating with low nutrient conditions (Kurepa and Smalle 2022 ). Plant stoichiometric traits, such as tissue nitrogen or phosphorus content, also reflect plant resource acquisition and growth strategies (Luo et al. 2021 ; Pan et al. 2024 ). By modulating functional traits, plants regulate their responses to environmental drivers, modify interactions with other trophic levels, and drive ecosystem dynamics (Martin et al. 2017 ; Weemstra et al. 2021 ). Beyond adjusting their functional traits, plants can also employ rhizosphere effects (REs) to actively modify soil microenvironment. Rhizosphere is determined as the small volume of soil influenced by root activity (Hinsinger, 1998 ). Plant roots can release root exudates and rhizodeposits into rhizosphere soil and thus induce rhizosphere effect, resulting in differences in physical, chemical, and biological characteristics between rhizosphere and bulk soil (Hinsinger 1998 ; Gargallo-Garriga et al. 2018 ). Functioning as a pivotal interface for plant-environment interactions, REs have been widely studied as a soil improvement mechanism. In an European beech forests, plant rhizosphere soil maintained more water-extractable organic matter like sugar than bulk soil (De Feudis et al. 2017 ). At global scale, carbon and nitrogen content in rhizosphere soil were significantly higher than bulk soil (Liu et al. 2022 ; Ma et al. 2023 ). Under stress conditions, REs also function as an effective plant adaptive mechanism. For instance, mucilage secreted by roots can enhance the diffusive transport of nutrient under salinity conditions, thereby reducing risks of nutrient deficiency and salinity stress (Zarebanadkouki et al. 2019 ). Rhizosphere is also an intermediator for plants and microorganisms interactions. By mediating soil microbial communities, rhizosphere effect will in turn promote plant growth and stress tolerance with the help of microorganisms (Kong and Liu 2022 ; Trivedi et al. 2022 ). Studies showed that REs could improve soil microbial biomass and enzyme activities (Kumar and Garkoti 2022 ; Zhao et al. 2022 ), promote the growth and colonization of microorganisms (Wang et al. 2023 ), and recruit specific microbial communities (Shi et al. 2023 ). However, studies also discovered that soil characteristics exert stronger influences on microbial communities than rhizosphere effects, and the overall microbial community structure remains not affected as a result of the rhizosphere effects (Buyer et al. 2011 ; Zhou et al. 2016 ). Understanding the complex relationships among plants, their associated microbiomes, and environmental shifts is crucial for improving plant growth and survival (Addison et al. 2024 ). Coastal wetlands are situated at the interface between terrestrial and marine ecosystems. Although coastal wetlands represent only a small fraction of the Earth’s surface, they play a key role in ecosystem services, including sediment and carbon storage, contaminant removal, storm and flooding buffering, fisheries production, and climate mitigation (Ward et al. 2020 ; Baustian et al. 2022 ). In China, coastal zones encompass 13% of the nation's territory out of which 95% is located in an intertidal belt (Tian et al. 2016 ; Long et al. 2016 ). Yellow River Delta (YRD) is the most complete and youngest wetland ecosystem in the warm temperate zone of China (Wang et al. 2025 ; Guo et al. 2025 ). Characterized by dynamic land-sea interactions, YRD demonstrates large environmental heterogeneity (Guan et al. 2017 ), providing ideal conditions for studying plant performance across diverse ecological gradients. Suaeda salsa is an annual herbaceous euhalophyte in Amaranthaceae family, distributed widely in YRD (Li et al. 2012 ; Song and Wang 2015 ). This species is of high economic and ecological values. Its young vegetative tissues and seed oil are nutrient-rich, making them suitable for processing into human food products and animal fodder. Studies have demonstrated that cultivating and harvesting S. salsa significantly reduces soil salt and heavy metal content, making it an ideal candidate for ecological restoration (Song and Wang 2015 ). Additionally, it serves as an ideal model for studying halophyte salt-tolerance strategies (Cui et al. 2024 ). According to previous studies, S. salsa could employ both PFTs and REs to adapt to heterogenous environment. On one hand, it exhibits unique trait plasticity under different habitats, especially between the inland and intertidal zone. When growing in inland saline-alkali soils, this species maintains green branches and leaves throughout its growth cycle, whereas the coastal intertidal populations exhibit characteristic purplish-red pigmentation in their vegetative organs, primarily attributed to betacyanin accumulation (Song and Wang 2015 ; Cui et al. 2024 ). On the other hand, S. salsa can recruit microbiomes through rhizosphere effect under heterogenous environment. Studies indicated that rhizosphere soils of S. salsa harbored significantly greater abundances of plant growth-promoting microorganisms and salt stress-mitigating microbes compared to bulk soils (Tang et al., 2023 ). Nevertheless, integrated studies investigating the combined roles of functional traits and rhizosphere effects in S. salsa 's adaptation across heterogeneous habitats remain limited. Conducting such research would provide critical insights into the multidimensional response mechanisms of halophytes to heterogenous environment. Based on the previous studies, soil salinity is recognized the most important factor affecting the growth and physiological characters of S. salsa (Song and Wang 2015 ; Li et al. 2023 ). Consequently, we established study sites across three habitats with distinct salinity regimes to elucidate adaptive strategies in this halophyte through simultaneous quantification of plant functional traits and rhizosphere effects. We hypothesized that (1) soil properties and microbial communities between rhizosphere soil and bulk soil would exhibit distinct differences, especially in high soil salinity conditions; (2) functional traits of S. salsa would exhibit habitat-specific differentiation across three discrete salinity habitats, with trait expression correlating significantly with soil salinity levels; (3) microbial community compositions would be impacted by both habitats and plant rhizosphere effect. Materials and methods 2.1 Study site This study was conducted at the Yellow River Delta, Shandong Province, China (117°31′–119°18′ E, 36°55′–38°16′ N). The region is distinguished by a warm temperate monsoon climate, with the mean annual temperature ranging from 11.7°C to 12.8°C and annual precipitation of 580 mm. The soils are mainly coastal saline and tidal soils with severe salt erosion, and the salt content ranges from 0.1% to 1% (Wang et al. 2025 ). 2.2 Experimental design and sample collection In August 2022, we selected 3 typical habitats where S. salsa was the dominant species as our study sites. As soil salinity increased, the plots were designated Site1, Site2 and Site3 (Fig. 1 ). Site1 is located adjacent to the riverbank and is predominantly influenced by the Yellow River. Site2 is situated in the supratidal highlands, significantly influenced by seasonal precipitation, and characterized by a composite environment featuring typical salinization and alternating wet-dry cycles. Site3 is located in the supratidal zone at a lower elevation and experiences seasonal tides during the rainy season. Each site covered an area of at least 600 m 2 and had a relatively homogeneous species composition. In each site, five 1 m × 1 m plots were established with a distance of over 5 m between each plot. To represent the biomass of S. salsa , we selected a 0.5 m × 0.5 m sub-sample in each plot and excavated all the S. salsa in the sub-sample, i.e., a quarter of the biomass of S. salsa in each plot was collected. After divided into aboveground and underground parts, these samples were oven-dried, weighed to determine the biomass, and then used for the analysis of other functional traits (shoot and root element and ion concentrations, shoot proline concentrations). In addition, substantial fresh leaves of S. salsa were collected from the remaining area of each plot outside the sub-sample for the determination of SLA. To investigate the rhizosphere effect of S. salsa , both rhizosphere soil (RS) and bulk soil (BS) were collected in each plot, using the adhering soil method (Han et al., 2020 ; Phillips et al., 2006). Briefly, we dug out the whole plant with some soil on its root and then gently shook the root. Loose soil that can be easily shaken off was collected as the bulk soil. The remaining soil adhering to the surface of the root was carefully removed by the sterile brushes and collected as the rhizosphere soil. Following transportation to the laboratory, about 40 g of each fresh soil sample was immediately separated to determine the soil moisture content (MC). Then the remaining part of each sample was divided into two parts: one stored at -20℃ for the determination of soil inorganic N (NH 4 + -N and NO 3 − -N) concentration and the high-throughput sequencing of soil microorganisms, the other was air dried to analyze other soil properties including physiochemical properties (pH and electrical conductivity), stoichiometric indicators (organic carbon, total nitrogen and total phosphorus concentrations) and extracellular enzyme activities. 2.3 Measurement of soil properties and calculation of rhizosphere effect We determined the basic soil physical and chemical properties of both BS and RS to calculate rhizosphere effect. Before the determination of soil properties, fresh soil samples were passed through a 2 mm sieve while air-dried samples through a 0.25 mm sieve to achieve homogenization and exclude impurities. Soil moisture content (MC) was calculated as the percentage of water mass relative to the dry soil mass, determined by oven-drying approximately 40 g of fresh soil at 105℃. Fresh soil samples (5.0000 ± 0.0005 g) were dissolved into 25 ml of deionized water and vibrated for 60 minutes at 180 r min − 1 , then the solution was filtered by 0.45 µm filtration membranes and used to measure soil ammonium nitrogen (NH 4 + -N) and nitrate nitrogen (NO 3 − -N) concentration by a continuous-flow ion auto-analyzer (San++, Scalar, Breda, Netherlands). Soil pH and electricity conductivity (EC) were measured with the water to soil ratio = 2.5:1 (v:w), using the pH meter (FE28, Mettler Toledo, Shanghai, China) and electricity conductivity meter (FE38, Mettler Toledo, Shanghai, China) respectively. Soil organic carbon (SOC) was determined by potassium dichromate volume-external heating (oil bath heating) method. To determine soil total nitrogen (TN) and total phosphorus (TP) concentration, about 1g (1.0000 ± 0.0005 g) soil was digested with H 2 SO 4 at 400℃ for 1 hour, using CuSO 4 and K 2 SO 4 as catalysts. The solution was used to measure TN by a Kjeldahl apparatus (K9860, Hanon, Dezhou, China) and TP by UV-spectrophotometer (UA-5500, METASH, Shanghai, China) at 700 nm. Then we calculated soil nitrogen to phosphorus ratio (N:P) to reflect the nutrient balance in soil. Soil extracellular enzyme activities were quantified using enzyme activity assay kits (Solarbio life sciences, Beijing, China). Soil samples were processed following the standardized protocols, then the absorbance measurements were conducted on a UV-spectrophotometer (UA-5500, METASH, Shanghai, China) at 660 nm for soil acid phosphatase (ACP), while at 400 nm for N-acetyl-β-D-glucosidase (NAG) and β-glucosidase (β-GC). The rhizosphere effect (RE) of each indicator was calculated by diving the difference between rhizosphere soil and bulk soil by the value of bulk soil: $$\:\begin{array}{c}{RE}_{i}=\frac{{RS}_{i}-{BS}_{i}}{{BS}_{i}}\:\#\left(1\right)\end{array}$$ where REi is the rhizosphere effect of indicator i , RSi and BSi refers to the value of indicator i in rhizosphere soil and bulk soil respectively. 2.4 Determination of plant functional traits After bringing back to the laboratory, the fresh leaves of each plot were rehydrated, scanned with a flatbed scanner (LiDE120, Canon, Tokyo, Japan), then oven-dried and weighed. Leaf area was quantified using ImageJ ( https://imagej.net/imagej-wiki-static/Fiji ), and specific leaf area (SLA) was calculated as leaf area divided by leaf dry mass. Plant samples designated for biomass determination were separated into aboveground and belowground sections. After thorough rinsing to remove adhering soil, the samples were initially oven-dried at 105°C for 30 minutes to deactivate enzymes, followed by drying at 65°C until a constant weight. The dry weights of each section were recorded as their biomass (AGB and BGB). Afterwards, the total biomass in the sample (TB), individual biomass (IB) and root to shoot ratio (RSR) of S. salsa were calculated. Dry plant samples were then ground and sieved through a 100 mesh screen, for the determination of element (N and P), ion (Na + and K + ) and proline concentrations. Plant nitrogen (Shoot N, Root N) and phosphorus (Shoot P, Root P) content were determined by the same method as for soil, but with different sample weight (0.2000 ± 0.0005 g) and digesting temperature and time (200℃ for 40 minutes followed by 400℃ for 1 hour). After plant powder (1 ± 0.0005 g) was digested with nitric-perchloric acid, the solution was used to determine the sodium (Na + ) and potassium (K + ) ion concentrations by colorimetric method under 766.5 nm and 589 nm respectively (UA-5500, Metash, Shanghai, China). Proline in shoot tissues were extracted using sulfosalicylic acid, and the acidic ninhydrin method was used to determine proline content (Pro). 2.5 Soil DNA extraction and Illumina sequencing Soil DNA was extracted using DNA Extraction Kit (D6356-02, Magen, Shanghai, China). Concentration of DNA was verified with NanoDrop and agarose gel. The genome DNA was used as template for PCR amplification with the barcoded primers and Tks Gflex DNA Polymerase (Takara). For bacterial diversity analysis, the V3V4 region of 16SrRNA gene was amplified by primers 343F (5'-TACGGRAGGCAGCAG-3') and 798R (5'-AGGGTATCTAATCCT-3'). For fungal diversity analysis, the ITS gene was specifically amplified using primers ITS1F (5'-CTTGGTCATTTAGAGGAAGTAA-3') and ITS2 (5'-GCTGCGTTCTTCATCGATGC-3'). Amplicons were sequenced on an Illumina MiSeq platform (Illumina, Inc., San Diego, CA, USA). Cutadapt software was used to preprocess the raw data through detect and cut off the paired-end reads adapter. The original DNA data was processed by QIIME2, and the obtained effective sequences were clustered by the Amplicon Sequence Variant (ASV) abundance table for further analysis. 2.6 Statistical analysis Prior to data analysis, all datasets were subjected to normality (Shapiro-Wilk test) and homogeneity of variance (Levene's test) assessments, with log or power transformations applied when assumptions were violated. Statistical differences in functional traits, rhizosphere effects, and soil physicochemical properties of S. salsa across environmental conditions were evaluated using one-way analysis of variance (ANOVA) followed by Duncan multiple-comparison in SPSS 25.0 (SPSS Inc., Chicago, USA). One-sample t -tests were applied in SPSS 25.0 to assess whether the rhizosphere effects of individual soil properties significantly deviated from zero ( α = 0.05), thereby determining whether S. salsa induced significant rhizosphere effect. Two-way ANOVA was performed to examine the main effects and interactions of site and soil compartment on soil physicochemical properties, thus quantifying the modification of rhizosphere process driven by S. salsa on soil properties. Redundancy analysis (RDA) was conducted to assess the relationship between soil properties and plant functional traits. Following RDA, the hierarchical partitioning analysis was applied to disentangle the independent and joint contributions of soil properties to plant trait variation. For soil microorganisms, α-diversity and β-diversity metrics were quantified. The α-diversity indices were calculated using the following formulas: $$\:\begin{array}{c}Chao1={S}_{obs}+\frac{{n}_{1}\left({n}_{1}-1\right)}{2{n}_{2}-2}\#\left(2\right)\end{array}$$ $$\:\begin{array}{c}Shannon=\:-\sum\:_{i=1}^{{S}_{obs}}\frac{{n}_{i}}{N}{ln}\frac{{n}_{i}}{N}\#\left(3\right)\end{array}$$ where S obs is the observed ASVs count of bacteria or fungi, n 1 denotes the ASVs represented by a single sequence, and n 2 denotes the ASVs containing two sequences; N indicates the total sequence count in a sample, n i indicates the sequence count of i -th ASV. Differences in microbial composition between rhizosphere and bulk soils under three habitats were assessed using principal coordinate analysis (PCoA) based on Bray-Curtis distance. Statistical significance was evaluated using two-way permutational multivariate analysis of variance (PERMANOVA) with 999 permutations. Data visualization was implemented in R 4.3.3 (R Foundation for Statistical Computing, Vienna, Austria) with the ggplot2 package. RDA was conducted in vegan package, and hierarchical partitioning was implemented via rdacca.hp package. Spearman correlation analyses between variables were performed and graphically represented using the pheatmap package. Results 3.1 Differences of soil properties among three habitats Two-way ANOVA revealed that both site and soil compartment exerted significant main effects and interaction effects on soil properties (Table S1 ). Site exerted significant main effects on soil properties except MC, soil compartment did not exert significant main effects on EC and NO 3 − -N, and their interaction effects significantly affected SOC, enzyme activity and inorganic nitrogen content. Significant differences were found in BS physicochemical properties in different habitats (Fig. 2 ), indicating distinct environmental conditions among these sites. Site 1 exhibited the lowest EC and highest pH (Fig. 2 a, b), Site2 exhibited the lowest pH and highest SOC (Fig. 2 b, d), Site3 exhibited the highest EC and NH 4 + -N concentration (Fig. 2 b, f), as well as the lowest total nitrogen concentration and total N to P ratio (Fig. 2 g, i). Soil enzyme activity of BS showed no significance among three habitats (Fig. 2 j, k, l). For rhizosphere soils, they were conditioned to be more conducive to plant growth, with lower EC and pH levels, coupled with higher nutrient concentrations and enzyme activity, especially under high salinity conditions (Site2 and Site3). RS at both Site2 and Site3 had significantly higher soil MC, SOC, NH 4 + -N, TN, N:P and enzyme activities compared to BS (Fig. 2 c, d, f, g, i, j, k, l). 3.2 Intensity of rhizosphere effect of S. salsa under different habitats Rhizosphere effects exhibited marked variation across the three habitats except for MC, NO 3 − -N and TP (Fig. 3 ). As soil salinity elevated, S. salsa exhibited stronger rhizosphere effects on most of the soil parameters, whereas the negative rhizosphere effect on soil EC peaked under low-salinity condition (Site1) and diminished with the increasing salt content. The results of one-sample t -tests demonstrated similar patterns that S. salsa tend to exhibit more significant REs in Site2 and Site3. No significant rhizosphere effects were observed on soil nitrate nitrogen content or soil N:P in different habitats. 3.3 Divergence in microbial communities under different sites and soil compartments Microbial α-diversity indices also demonstrated strong responses to environmental heterogeneity (BS in Fig. S1 ). Site1 exhibited the highest microbial diversity, Site2 displayed the lowest bacterial diversity, and fungal diversity showed no significant difference between Site2 and Site3. In contrast, rhizosphere microbial communities demonstrated stronger resilience, maintaining stable bacterial diversity across three habitats while displaying fungal diversity variations only for the Shannon index (Fig. S1 ). The PCoA results showed that the first two axes explaining 19.41% and 12.1% of total variance for bacterial communities (Fig. 4 a), and 13.58% and 8.35% for fungal communities (Fig. 4 b). Two-factor PERMANOVA demonstrated significant main effects of habitat and soil, along with significant habitat × soil interaction effects (Tables S2 and S3; p < 0.05). Furthermore, bacterial and fungal community at Site1 were distinct from those at Site2 and Site3. Site2 exhibited a clear separation between rhizosphere and bulk soil microbial communities along the first two axes. Analysis of microbial community composition at phylum and genus level revealed that both habitat type and soil compartment significantly influenced soil microbial community structure (Fig. 5 ). For bacterial communities, the most abundant phyla was Proteobacteria, and it exhibited higher relative abundance in rhizosphere soils compared to bulk soils across all sampling sites, with Site2 showing the lowest overall Proteobacteria abundance (Fig. 5 a). Fungal communities were dominated by Ascomycota, followed by Basidiomycota and Rozellomycota (Fig. 5 c). Compared to rhizosphere soils, bulk soils at Site1 and Site2 exhibited ‌higher Ascomycota‌ but ‌lower Basidiomycota abundance‌. ‌In contrast, Site3 displayed the ‌opposite pattern‌ (Fig. 5 c). At genus level, the microbial communities composition also demonstrated significant differences (Fig. 5 b, d). For both bacterial and fungal communities, Site1 demonstrated similar composition between rhizosphere and bulk soils, while Site2 and Site3 showed differences among soils and sites. 3.4 Responses of functional traits of S. salsa to different habitats With the increasing soil salinity, biomass and RSR of S. salsa significantly decreased (Fig. 6 a, b; Fig. S2a-c), whereas proline content, shoot N concentration, shoot and root Na + concentration, Na + :K + and N:P increased (Fig. 6 d, e, f, i, j; Fig. S2e). P content in shoot and root parts of S. salsa first increased and then decreased with the increase of soil salinity, reaching the highest at Site2 (Fig. S4b, d). K + concentration did not change significantly in both shoot and root parts (Fig. S2f, h). Explanation of the first two axes of RDA was 61.49% and 15.14% respectively, collectively representing 76.63% of soil-driven variability in plant functional traits across all ordination axes (Fig. 7 a). Hierarchical partitioning analysis demonstrated that NH 4 + -N and EC had significant effects on plant functional traits, explaining 38.53% and 35.56% variation respectively (Fig. 7 b). NH 4 + -N was positively correlated with tissue Na + :K + and N:P, while negatively correlated with tissue K + content and biomass. EC was positively correlated with shoot Na + and proline content, while negatively correlated with plant biomass (Fig. 7 a). 3.5 Relationship between plant functional traits and rhizosphere effects Spearman correlations between functional traits and rhizosphere effects of S. salsa are shown in Fig. 8 . Biomass-related traits were generally negatively correlated with the magnitude of rhizosphere effects, whereas traits related to plant nutrient concentrations, metal ion content, and proline content were predominantly positively correlated with rhizosphere effects. Compared to rhizosphere effects on other soil parameters, REs on soil organic carbon and soil enzyme activities showed relatively strong correlations with plant functional traits. For the two parameters that significantly affected functional traits, S. salsa produced relatively weak rhizosphere effects. Rhizosphere effect on soil EC was significantly negatively correlated with individual biomass, and positively correlated with shoot N and tissue Na + concentrations. Rhizosphere effect on NH 4 + -N demonstrated significant correlation with proline content and tissue Na + concentrations. Discussion Using a typical coastal wetland halophyte species, this study examined the ecological adaptation strategies of Suaeda salsa to a natural saline gradient by comprehensively analyzing plant functional traits and rhizosphere effects, and further investigating the shaping impact of S. salsa rhizosphere effects on soil microbial communities. Our results demonstrated that S. salsa employed integrated strategies including targeted rhizosphere engineering, functional trait plasticity, and selective microbial recruitment to adapt to heterogeneous saline environments. Rhizosphere effect is an efficient adaptive strategy for S. salsa under heterogeneous habitats. In our results, rhizosphere soil showed significantly lower pH, but higher moisture and nutrient content compared to bulk soil especially under high salt habitats (Fig. 1 b-i). These variations may be closely related to the secretion of root exudates. Root exudates are fundamental drivers in establishing and sustaining the vitality and function of the rhizosphere micro-ecosystem. They can help regulate the microenvironment in the rhizosphere, improve the bioavailability of soil nutrients, and facilitate plant root-microbe interactions (Ahlawat et al., 2024 ; Chai and Schachtman, 2022 ). First, the mucilage in root exudates will enhance the moisture retention capacity of soil, sustaining higher moisture content in the rhizosphere (Young 1995 ; Carminati et al. 2010 ). Second, some components of root exudates like organic acids can regulate soil pH and help convert unavailable substances into effective nutrients for plant uptake, critically enhancing plant growth and abiotic stress tolerance (Dakora and Phillips 2002 ; Liu et al. 2021 ; Li et al. 2022 ). Third, nutrients activated by root exudates, and the inherent metabolites in exudates provide a suitable environment and serve as signals for specific microbial recruitment, while some enzymes and acids in the exudates impose selective filtering on microbial communities (Khan et al., 2021 ; Sasse et al., 2018 ). These mechanisms drive the assembly of specific rhizosphere microbiomes, thereby shaping plant-microbe interaction patterns. Soil enzyme activities are also strongly associated with root exudates (Schofield et al. 2019 ). Root-secreted enzymes and microbial-derived enzymes synergistically constitute the extracellular enzyme pool within rhizosphere soil. Our results demonstrated significantly higher extracellular enzyme activities in the rhizosphere of Site2 and Site3 compared to bulk soils (Fig. 2 j-l), indicating amplified rhizosphere effect and enhanced microbial metabolic activities under elevated salinity. In addition, we also found a significant increase in soil organic carbon content in the rhizosphere compared to the bulk soil under high salinity habitats (Fig. 2 d). This was also likely driven by the abundant organic matters in the root exudates, supporting the point that rhizosphere effects enhanced under high-salinity conditions. Variations in the magnitude of rhizosphere effects across salinity gradients (Fig. 3 ) provide evidence that plant modulation of the rhizosphere is strongly influenced by environmental conditions, particularly soil salinity. The magnitude of rhizosphere effects on soil pH, moisture, nutrients, and extracellular enzymes enhanced in high salinity habitats, which means under elevated salt stress, S. salsa can reduce soil alkalinity, improve water and nutrient acquisition, and recruit specific microbial communities more effectively through rhizosphere effect. This might be due to the increase of root exudation rate (Zhang et al. 2025 ). Nevertheless, the rhizosphere effect on soil EC followed a distinct pattern. The negative rhizosphere effect on soil EC was strongest in Site1, and diminished with the increasing soil salinity, becoming insignificant at higher salt conditions. This suggests S. salsa might exhibit limited ability on soil salinity regulation. Under low salinity habitats, S. salsa can actively modify its rhizosphere to reduce local salinity, avoid ionic toxicity and enhance water and nutrient availability (Arif et al. 2020 ). However, as soil salinity increase, maintaining a low salt level through rhizosphere modulation may be overwhelmed. Consequently, S. salsa shifts its strategy into allocating more resources on nutrient activation and the beneficial microorganisms recruitment to alleviate the nutrient imbalance under high salt stress (Wakeel 2013 ; Arif et al. 2020 ). As mentioned above, rhizosphere effect can exert profound structuring forces on soil microbial community assembly. Our analysis revealed that habitat alterations exerted significant impacts on α-diversity of both bacterial and fungal communities in bulk soil, yet showed no statistically significant influence on rhizosphere soil microbiota (Fig. S2). This phenomenon aligns with established salt stress adaptation mechanisms wherein plants actively recruit stress-adapted microbiomes through root exudate regulation (Li et al., 2021 ; Zhang et al., 2025 ). Under stress conditions, plants alter the composition and secretion rate of root exudates, which promote the diversity and evenness of microbial communities (Zhang et al. 2025 ). Such host-mediated microbial enrichment likely stabilizes rhizosphere communities against external diversity fluctuations, maintaining functional redundancy essential for plant resilience under environmental challenges (Xiao et al. 2024 ; Luo et al. 2025 ). Microbial β-diversity demonstrated congruent patterns between the two high-salinity sites and distinguished from Site1 (Fig. 4 ), suggesting salinity-driven environmental filtering governs microbiome assembly. The lower cumulative explanatory power for fungi (21.93%) than bacteria (31.51%) suggests stronger stochasticity or unmeasured niche-based processes governing fungal assembly (Guo et al. 2023 ). At the phylum level, Proteobacteria and Ascomycota exhibited the highest relative abundances among bacterial and fungal communities, respectively (Fig. 5 a, c). This finding is consistent with previous studies (Zhang et al. 2023 ; Liu et al. 2023 ), suggesting these phyla are likely well-adapted to the environment of Yellow River Delta. Proteobacteria exhibit strong tolerance to stressful conditions, enabling survival in extreme environments (Yang et al. 2023 ), and their abundance increases significantly under stable environment (Zhang et al. 2016 ). In this study, the abundance of Proteobacteria in rhizosphere soils were higher than bulk soils in all three habitats, indicating rhizosphere soils provide more stable and nutritious conditions, and Proteobacteria may help S. salsa adapt to high-salinity environment (Zhang et al. 2024 ). Ascomycota was predominantly observed as the dominant fungal phylum in coastal saline-alkali soils, with most species exhibiting saprophytic capabilities critical for soil organic matter decomposition (Zhang et al. 2024 ). At the genus level, the marked differentiation in microbial composition across three habitats highlights the significant shaping influence of environmental heterogeneity on microbial assembly (Fig. 5 b, d). Bacteria genera Sphingomonas and BIrii41, which were enriched in the rhizosphere soil of Site2 have been reported to promote plant growth (Asaf et al. 2020 ; Kong et al. 2023 ), indicating the attraction effect of rhizosphere on beneficial microbial populations that promote plant growth. Functional traits of S. salsa exhibited significant differentiation in response to environmental changes. According to our results, soil NH 4 + -N and EC served as the most important factors impairing the growth of S. salsa (Fig. 7 ). High salinity serves as a critical abiotic stress factor that impairs plant development. We found that plant individual biomass, biomass of the sample and root to shoot ratio were decreased as soil salinity increase (Fig. 6 a, b; Fig. S3). Plant biomass is a direct indicator of growth performance. As an euhalophyte, S. salsa achieves optimal growth at specific ionic concentrations, demonstrating an obligate requirement for ionic exposure rather than thriving in salt-excluded conditions (Jia et al., 2018 ; Li et al., 2011 ). The significant growth depression of S. salsa populations at Site3 may suggest that soil salinity in Site3 has exceeded the optimal threshold for S. salsa . One of the mechanisms that salt stress affects plant growth is the cytotoxicity due to excessive uptake of Na + and Cl − ions (Isayenkov et al., 2020 ; Isayenkov and Maathuis, 2019 ). For halophytes, they can assimilate and compartmentalize Na + into vacuoles to increase their tissue osmotic pressure and alleviate the cytotoxicity (Flowers and Colmer 2008 ; Song and Wang 2015 ). Maintaining a low Na + :K + in the cytosol is also recognized as an important salt-tolerance mechanism in halophytes (Flowers and Colmer 2008 ; Zhang et al. 2015 ). In our results, shoots and roots of S. salsa both exhibited significant Na + accumulation under high salinity (Fig. 6 e, f). The significantly elevated Na⁺:K⁺ ratio at Site3 suggests the excessive accumulation of sodium ions, which may cause ionic toxicity. Proline is an major organic osmotic regulation substances that often accumulates in cytosol under osmotic stress to maintain cytoplasmic homeostasis (Slama et al. 2015 ; Shang et al. 2020 ). Under seawater-induced salinity stress, ‌proline accumulated in S. salsa shoot tissues (Fig. 3 d)‌, indicating a specialized osmoregulatory adaptation via biosynthesis. Nitrogen plays an important role in plant growth and development. Nitrogen acquisition is fundamentally dependent on inorganic forms, with ammonium nitrogen represents a critical nitrogen acquisition form for rapid plant assimilation (Wang et al. 2021 ). Although NH₄⁺-N typically serves as a nitrogen source, its association with reduced plant biomass and increased tissue N:P ratio (Fig. 7 ) reveals a fundamental physiological trade-off under salinity stress. High rhizosphere NH₄⁺-N (Fig. 2 f) and elevated tissue N and Na⁺ concentrations at Site2 and Site3 (Fig. 6 e, f; Fig. S2d, e) suggest that S. salsa prioritizes nitrogen assimilation and osmotic adjustment over growth when exposed to ammonium-rich saline conditions. This aligns with studies demonstrating that excessive NH₄⁺ inhibits root development and induces metabolic costs in halophytes due to cytotoxicity and pH shifts in saline soils (Bittsánszky et al. 2015 ; Esteban et al. 2016 ). The interplay between functional traits and rhizosphere effects reveals adaptive strategies under saline stress. Although soil salinity and NH₄⁺-N were dominant drivers of trait variation, the rhizosphere effect on them did not show obvious correlations with functional traits (Fig. 8 ). This decoupling suggests that intrinsic physiological adjustments buffer external stress, allowing plants to modulate rhizosphere processes independently from immediate soil conditions (Xu et al. 2021 ). Interestingly, a strong negative correlation was observed between individual biomass of S. salsa and its rhizosphere effect on soil electrical conductivity, indicating that smaller individuals tend to induce stronger rhizosphere-mediated response to salt stress. This might be dominated by soil salinity. On one hand, high salinity inhibits plant growth; on the other hand, high salinity induces an enhancement of rhizosphere effects. Such specific allocation tradeoffs likely represents an evolutionary optimization strategy in S. salsa , where resource diversion from growth to stress acclimation for enhancing survival probability in marginal environments (Monson et al. 2022 ). Conclusions In conclusion, this study demonstrates that S. salsa employs synergistic interactions between rhizosphere effects and functional traits to develop multidimensional adaptive strategies in response to heterogeneous habitats in the Yellow River Delta. First, rhizosphere effects were significantly enhanced under high-salinity conditions, characterized by reduced soil pH, improved moisture content, nutrient availability, and elevated enzyme activities in rhizosphere soils. Second, microbial community composition was jointly shaped by habitat type and rhizosphere effects, suggesting selective enrichment of stress-adapted microbiota to enhance plant adaptation. Furthermore, soil ammonia nitrogen content and salinity significantly influenced the functional trait differentiation of S. salsa , reflecting the important role of soil nitrogen availability for plant growth under salinity environment. These findings underscore the pivotal role of coordinated rhizosphere effects and functional trait plasticity in driving plant adaptation to heterogeneous environments, providing critical insights into the multidimensional response mechanisms of halophytes and informing restoration strategies for degraded saline-alkali ecosystems. Declarations Competing Interests The authors have no relevant financial or non-financial interests to disclose. Funding This work was supported by the National Natural Science Foundation of China (No. 32471580; U22A20558), Key Laboratory of Ecological Prewarning, Protection and Restoration of Bohai Sea, Ministry of Natural Resources (No. 2024103), and the Natural Science Foundation of Shandong Province, China (No. ZR2024MC091). Author Contributions Luyao Gong: Writing – review & editing, Writing – original draft, Data curation, Visualization. Yixin Song: Writing – original draft, Data curation, Formal analysis, Investigation, Methodology. Luyu Qi: Methodology, Investigation. Puyi Zhang: Investigation. Wenlong Sun: Investigation. Wei Wang: Project administration, Writing – review & editing. Shijie Yi: Investigation. Xiaofei Yang: Investigation, Zijun Xu: Validation. Qingyun Yu: Validation. Yifei Song: Validation. Weihua Guo: Funding acquisition, Project administration. Ning Du: Conceptualization, Investigation, Funding acquisition, Project administration, Supervision Acknowledgments We would like to thank Jiaqi Jiang, Tianyu Ji, Gaode Meng and Haonan Chen for their assistance in the field survey. Data Availability The datasets generated during the current study are available from the corresponding author on reasonable request. References Addison SL, Rúa MA, Smaill SJ et al (2024) Partner or perish: Tree microbiomes and climate change. Trends Plant Sci 29:1029–1040. https://doi.org/10.1016/j.tplants.2024.03.008 Ahlawat OP, Yadav D, Walia N et al (2024) Root exudates and their significance in abiotic stress amelioration in plants: A review. J Plant Growth Regul 43:1736–1761. https://doi.org/10.1007/s00344-024-11237-7 Arif Y, Singh P, Siddiqui H et al (2020) Salinity induced physiological and biochemical changes in plants: An omic approach towards salt stress tolerance. Plant Physiol Biochem 156:64–77. https://doi.org/10.1016/j.plaphy.2020.08.042 Asaf S, Numan M, Khan AL et al (2020) Sphingomonas : from diversity and genomics to functional role in environmental remediation and plant growth. Crit Rev Biotechnol 40:138–152. https://doi.org/10.1080/07388551.2019.1709793 Baustian MM, Liu B, Moss LC et al (2022) Climate change mitigation potential of Louisiana’s coastal area: Current estimates and future projections. Ecol Appl 33:e2847. https://doi.org/10.1002/eap.2847 Bittsánszky A, Pilinszky K, Gyulai G et al (2015) Overcoming ammonium toxicity. Plant Sci 231:184–190. https://doi.org/10.1016/j.plantsci.2014.12.005 Buyer JS, Roberts DP, Russek-Cohen E (2011) Soil and plant effects on microbial community structure. Can J Microbiol. https://doi.org/10.1139/w02-095 Carminati A, Moradi AB, Vetterlein D et al (2010) Dynamics of soil water content in the rhizosphere. Plant Soil 332:163–176. https://doi.org/10.1007/s11104-010-0283-8 Chai YN, Schachtman DP (2022) Root exudates impact plant performance under abiotic stress. Trends Plant Sci 27:80–91. https://doi.org/10.1016/j.tplants.2021.08.003 Cui B, Liu R, Yu Q et al (2024) Combined genome and transcriptome provides insight into the genetic evolution of an edible halophyte Suaeda salsa adaptation to high salinity. Mol Ecol n/a:e17457. https://doi.org/10.1111/mec.17457 Dakora FD, Phillips DA (2002) Root exudates as mediators of mineral acquisition in low-nutrient environments. Plant Soil 245:35–47. https://doi.org/10.1023/A:1020809400075 De Feudis M, Cardelli V, Massaccesi L et al (2017) Altitude affects the quality of the water-extractable organic matter (WEOM) from rhizosphere and bulk soil in european beech forests. Geoderma 302:6–13. https://doi.org/10.1016/j.geoderma.2017.04.015 Esteban R, Ariz I, Cruz C et al (2016) Review: Mechanisms of ammonium toxicity and the quest for tolerance. Plant Sci 248:92–101. https://doi.org/10.1016/j.plantsci.2016.04.008 Finzi AC, Abramoff RZ, Spiller KS et al (2015) Rhizosphere processes are quantitatively important components of terrestrial carbon and nutrient cycles. Glob Change Biol 21:2082–2094. https://doi.org/10.1111/gcb.12816 Flowers TJ, Colmer TD (2008) Salinity tolerance in halophytes. New Phytol 179:945–963. https://doi.org/10.1111/j.1469-8137.2008.02531.x Gan D, Feng J, Han M et al (2021) Rhizosphere effects of woody plants on soil biogeochemical processes: A meta-analysis. Soil Biol Biochem 160:108310. https://doi.org/10.1016/j.soilbio.2021.108310 Gargallo-Garriga A, Preece C, Sardans J et al (2018) Root exudate metabolomes change under drought and show limited capacity for recovery. Sci Rep 8:12696. https://doi.org/10.1038/s41598-018-30150-0 Gibb H, Bishop TR, Leahy L et al (2023) Ecological strategies of (pl)ants: Towards a world-wide worker economic spectrum for ants. Funct Ecol 37:13–25. https://doi.org/10.1111/1365-2435.14135 Grime JP (1974) Vegetation classification by reference to strategies. Nature 250:26–31. https://doi.org/10.1038/250026a0 Guan B, Yu J, Hou A et al (2017) The ecological adaptability of Phragmites australis to interactive effects of water level and salt stress in the Yellow River Delta. Aquat Ecol 51:107–116. https://doi.org/10.1007/s10452-016-9602-3 Guo Q, Wen Z, Ghanizadeh H et al (2023) Stochastic processes dominate assembly of soil fungal community in grazing excluded grasslands in northwestern China. J Soils Sediments 23:156–171. https://doi.org/10.1007/s11368-022-03315-8 Guo X, Sun Z, Gao Y et al (2025) Haplotype-specific interactions of Phragmites australis with Spartina alterniflora under salt stress. J Environ Manage 384:125506. https://doi.org/10.1016/j.jenvman.2025.125506 Han M, Sun L, Gan D et al (2020) Root functional traits are key determinants of the rhizosphere effect on soil organic matter decomposition across 14 temperate hardwood species. Soil Biol Biochem 151:108019. https://doi.org/10.1016/j.soilbio.2020.108019 Hinsinger P (1998) How do plant roots acquire mineral nutrients? Chemical processes involved in the rhizosphere. Advances in Agronomy 64:pp 225–265. https://doi.org/10.1016/S0065-2113(08)60506-4 Isayenkov S, Hilo A, Rizzo P et al (2020) Adaptation strategies of halophytic barley Hordeum marinum ssp. marinum to high salinity and osmotic stress. Int J Mol Sci 21:9019. https://doi.org/10.3390/ijms21239019 Isayenkov SV, Maathuis FJM (2019) Plant salinity stress: Many unanswered questions remain. Front Plant Sci 10:80. https://doi.org/10.3389/fpls.2019.00080 Jia J, Huang C, Bai J et al (2018) Effects of drought and salt stresses on growth characteristics of euhalophyte Suaeda salsa in coastal wetlands. Phys Chem Earth Parts ABC 103:68–74. https://doi.org/10.1016/j.pce.2017.01.002 Khan N, Ali S, Shahid MA et al (2021) Insights into the interactions among roots, rhizosphere, and rhizobacteria for improving plant growth and tolerance to abiotic stresses: A review. Cells 10:1551. https://doi.org/10.3390/cells10061551 Kong W, Qiu L, Ishii S et al (2023) Contrasting response of soil microbiomes to long-term fertilization in various highland cropping systems. ISME Commun 3:81. https://doi.org/10.1038/s43705-023-00286-w Kong Z, Liu H (2022) Modification of rhizosphere microbial communities: A possible mechanism of plant growth promoting rhizobacteria enhancing plant growth and fitness. Front Plant Sci 13:920813. https://doi.org/10.3389/fpls.2022.920813 Kumar S, Garkoti SC (2022) Rhizosphere influence on soil microbial biomass and enzyme activity in banj oak, chir pine and banj oak regeneration forests in the central Himalaya. Geoderma 409:115626. https://doi.org/10.1016/j.geoderma.2021.115626 Kurepa J, Smalle JA (2022) Auxin/cytokinin antagonistic control of the shoot/root growth ratio and its relevance for adaptation to drought and nutrient deficiency stresses. Int J Mol Sci 23:1933. https://doi.org/10.3390/ijms23041933 Li CY, He R, Tian CY et al (2023) Utilization of halophytes in saline agriculture and restoration of contaminated salinized soils from genes to ecosystem: Suaeda salsa as an example. Mar Pollut Bull 197:115728. https://doi.org/10.1016/j.marpolbul.2023.115728 Li H, La S, Zhang X et al (2021) Salt-induced recruitment of specific root-associated bacterial consortium capable of enhancing plant adaptability to salt stress. ISME J 15:2865–2882. https://doi.org/10.1038/s41396-021-00974-2 Li H, Xu C, Han L et al (2022) Extensive secretion of phenolic acids and fatty acids facilitates rhizosphere pH regulation in halophyte Puccinellia tenuiflora under alkali stress. Physiol Plant 174:e13678. https://doi.org/10.1111/ppl.13678 Li X, Liu Y, Chen M et al (2012) Relationships between ion and chlorophyll accumulation in seeds and adaptation to saline environments in Suaeda salsa populations. Plant Biosyst 146:142–149. https://doi.org/10.1080/11263504.2012.727880 Li X, Zhang X, Song J et al (2011) Accumulation of ions during seed development under controlled saline conditions of two Suaeda salsa populations is related to their adaptation to saline environments. Plant Soil 341:99–107. https://doi.org/10.1007/s11104-010-0625-6 Liu HQ, Lu XB, Li ZH et al (2021) The role of root-associated microbes in growth stimulation of plants under saline conditions. Land Degrad Dev 32:3471–3486. https://doi.org/10.1002/ldr.3955 Liu S, He F, Kuzyakov Y et al (2022) Nutrients in the rhizosphere: A meta-analysis of content, availability, and influencing factors. Sci Total Environ 826:153908. https://doi.org/10.1016/j.scitotenv.2022.153908 Liu Z, Li J, Hou R et al (2023) Plant rhizospheres harbour specific fungal groups and form a stable co-occurrence pattern in the saline-alkali soil. Agronomy 13:1036. https://doi.org/10.3390/agronomy13041036 Long X, Liu L, Shao T et al (2016) Developing and sustainably utilize the coastal mudflat areas in China. Sci Total Environ 569–570:1077–1086. https://doi.org/10.1016/j.scitotenv.2016.06.170 Luo C, He Y, Chen Y (2025) Rhizosphere microbiome regulation: Unlocking the potential for plant growth. Curr Res Microb Sci 8:100322. https://doi.org/10.1016/j.crmicr.2024.100322 Luo Y, Peng Q, Li K et al (2021) Patterns of nitrogen and phosphorus stoichiometry among leaf, stem and root of desert plants and responses to climate and soil factors in Xinjiang, China. Catena 199:105100. https://doi.org/10.1016/j.catena.2020.105100 Ma Y, Yue K, Heděnec P et al (2023) Global patterns of rhizosphere effects on soil carbon and nitrogen biogeochemical processes. Catena 220:106661. https://doi.org/10.1016/j.catena.2022.106661 Martin AR, Rapidel B, Roupsard O et al (2017) Intraspecific trait variation across multiple scales: the leaf economics spectrum in coffee. Funct Ecol 31:604–612. https://doi.org/10.1111/1365-2435.12790 Monson RK, Trowbridge AM, Lindroth RL et al (2022) Coordinated resource allocation to plant growth–defense tradeoffs. New Phytol 233:1051–1066. https://doi.org/10.1111/nph.17773 Pan S, Ahmad Anees S, Yang X et al (2024) The stoichiometric characteristics and the relationship with hydraulic and morphological traits of the Faxon fir in the subalpine coniferous forest of Southwest China. Ecol Indic 159:111636. https://doi.org/10.1016/j.ecolind.2024.111636 Pérez-Harguindeguy N, Díaz S, Garnier E et al (2013) New handbook for standardised measurement of plant functional traits worldwide. Aust J Bot 61:167. https://doi.org/10.1071/BT12225 Pierce S, Brusa G, Sartori M et al (2012) Combined use of leaf size and economics traits allows direct comparison of hydrophyte and terrestrial herbaceous adaptive strategies. Ann Bot 109:1047–1053. https://doi.org/10.1093/aob/mcs021 Sasse J, Martinoia E, Northen T (2018) Feed your friends: Do plant exudates shape the root microbiome? Trends Plant Sci 23:25–41. https://doi.org/10.1016/j.tplants.2017.09.003 Schofield EJ, Brooker RW, Rowntree JK et al (2019) Plant-plant competition influences temporal dynamism of soil microbial enzyme activity. Soil Biol Biochem 139:107615. https://doi.org/10.1016/j.soilbio.2019.107615 Shang C, Wang L, Tian C et al (2020) Heavy metal tolerance and potential for remediation of heavy metal-contaminated saline soils for the euhalophyte Suaeda salsa . Plant Signal Behav 15:1805902. https://doi.org/10.1080/15592324.2020.1805902 Shi H, Yang J, Li Q et al (2023) Diversity and correlation analysis of different root exudates on the regulation of microbial structure and function in soil planted with Panax notoginseng . Front Microbiol 14:. https://doi.org/10.3389/fmicb.2023.1282689 Slama I, Abdelly C, Bouchereau A et al (2015) Diversity, distribution and roles of osmoprotective compounds accumulated in halophytes under abiotic stress. Ann Bot 115:433–447. https://doi.org/10.1093/aob/mcu239 Song J, Wang B (2015) Using euhalophytes to understand salt tolerance and to develop saline agriculture: Suaeda salsa as a promising model. Ann Bot 115:541–553. https://doi.org/10.1093/aob/mcu194 Steltzer H, Post E (2009) Seasons and life cycles. Science 324:886–887. https://doi.org/10.1126/science.1171542 Tang L, Zhan L, Han Y et al (2023) Microbial community assembly and functional profiles along the soil-root continuum of salt-tolerant Suaeda glauca and Suaeda salsa . Front Plant Sci 14:. https://doi.org/10.3389/fpls.2023.1301117 Tian B, Wu W, Yang Z et al (2016) Drivers, trends, and potential impacts of long-term coastal reclamation in China from 1985 to 2010. Estuar Coast Shelf Sci 170:83–90. https://doi.org/10.1016/j.ecss.2016.01.006 Trivedi P, Batista BD, Bazany KE et al (2022) Plant–microbiome interactions under a changing world: responses, consequences and perspectives. New Phytol 234:1951–1959. https://doi.org/10.1111/nph.18016 Wakeel A (2013) Potassium–sodium interactions in soil and plant under saline-sodic conditions. J Plant Nutr Soil Sci 176:344–354. https://doi.org/10.1002/jpln.201200417 Wang H, Liu H, Cao G et al (2020) Alpine grassland plants grow earlier and faster but biomass remains unchanged over 35 years of climate change. Ecol Lett 23:701–710. https://doi.org/10.1111/ele.13474 Wang S, Liu Y, Chen L et al (2021) Effects of excessive nitrogen on nitrogen uptake and transformation in the wetland soils of Liaohe estuary, northeast China. Sci Total Environ 791:148228. https://doi.org/10.1016/j.scitotenv.2021.148228 Wang Y, Feng H, Wang R et al (2023) Non-targeted metabolomics and 16s rDNA reveal the impact of uranium stress on rhizosphere and non-rhizosphere soil of ryegrass. J Environ Radioact 258:107090. https://doi.org/10.1016/j.jenvrad.2022.107090 Wang Y, Wu H, Wang J et al (2025) Leaf and root functional traits of woody and herbaceous halophytes and their adaptations in the Yellow River Delta. Plants 14:159. https://doi.org/10.3390/plants14020159 Ward ND, Megonigal JP, Bond-Lamberty B et al (2020) Representing the function and sensitivity of coastal interfaces in Earth system models. Nat Commun 11:2458. https://doi.org/10.1038/s41467-020-16236-2 Weemstra M, Freschet GT, Stokes A et al (2021) Patterns in intraspecific variation in root traits are species-specific along an elevation gradient. Funct Ecol 35:342–356. https://doi.org/10.1111/1365-2435.13723 Westoby M (1998) A leaf-height-seed (LHS) plant ecology strategy scheme. Plant Soil 199:213–227 Wright IJ, Reich PB, Westoby M et al (2004) The worldwide leaf economics spectrum. Nature 428:821–827. https://doi.org/10.1038/nature02403 Xiao E, Deng J, Shao L et al (2024) Increased microbial complexity and stability in rhizosphere soil: A key factor for plant resilience during mining disturbance. Sci Total Environ 956:177100. https://doi.org/10.1016/j.scitotenv.2024.177100 Xu J, Wang X, Zu H et al (2021) Molecular dissection of rice phytohormone signaling involved in resistance to a piercing-sucking herbivore. New Phytol 230:1639–1652. https://doi.org/10.1111/nph.17251 Yang Z, Sui H, Zhang T et al (2023) Response of surface soil microbial communities to heavy metals and soil properties for five different land-use types of Yellow River delta. Environ Earth Sci 82:599. https://doi.org/10.1007/s12665-023-11291-6 Young IM (1995) Variation in moisture contents between bulk soil and the rhizosheath of wheat ( Triticum aestivum L. cv. Wembley). New Phytol 130:135–139. https://doi.org/10.1111/j.1469-8137.1995.tb01823.x Zarebanadkouki M, Fink T, Benard P et al (2019) Mucilage facilitates nutrient diffusion in the drying rhizosphere. Vadose Zone J 18:190021. https://doi.org/10.2136/vzj2019.02.0021 Zhang C, Liu G, Xue S et al (2016) Soil bacterial community dynamics reflect changes in plant community and soil properties during the secondary succession of abandoned farmland in the Loess plateau . Soil Biol Biochem 97:40–49. https://doi.org/10.1016/j.soilbio.2016.02.013 Zhang H, Zhang G, Lü X et al (2015) Salt tolerance during seed germination and early seedling stages of 12 halophytes. Plant Soil 388:229–241. https://doi.org/10.1007/s11104-014-2322-3 Zhang XC, Zhai HL, Xu HY et al (2025) Different salt stress types regulated rhizosphere rare bacterial communities through root exudates and soil physicochemical properties. Plant Soil. https://doi.org/10.1007/s11104-025-07777-w Zhang Y, Wang H, Zhang X et al (2024) Effects of salt stress on the rhizosphere soil microbial communities of Suaeda salsa (L.) pall. in the Yellow River Delta. Ecol Evol 14:e70315. https://doi.org/10.1002/ece3.70315 Zhang Z, Sun J, Li T et al (2023) Effects of nitrogen and phosphorus imbalance input on rhizosphere and bulk soil bacterial community of Suaeda salsa in the Yellow River Delta. Front Mar Sci 10:. https://doi.org/10.3389/fmars.2023.1131713 Zhao X, Tian P, Sun Z et al (2022) Rhizosphere effects on soil organic carbon processes in terrestrial ecosystems: A meta-analysis. Geoderma 412:115739. https://doi.org/10.1016/j.geoderma.2022.115739 Zhou J, Deng Y, Shen L et al (2016) Temperature mediates continental-scale diversity of microbes in forest soils. 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13:11:41","extension":"html","order_by":48,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":191664,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/e8c0656ef6a7282c864b3d0e.html"},{"id":96634040,"identity":"7bd4bb43-767f-4672-8e4d-36da844a01dc","added_by":"auto","created_at":"2025-11-24 13:11:40","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":4209502,"visible":true,"origin":"","legend":"\u003cp\u003eLocations of three sampling sites and their vegetation conditions.\u003c/p\u003e","description":"","filename":"Figure1.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/d836667c7e7586a20496ae90.jpg"},{"id":96634042,"identity":"633eaed8-cf3b-4f3b-9323-736bca7600dd","added_by":"auto","created_at":"2025-11-24 13:11:40","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1865727,"visible":true,"origin":"","legend":"\u003cp\u003eSoil physical and chemical properties of three habitats in bulk soil (BS) and rhizosphere soil (RS). Different lowercase letters indicate significant difference among different habitats at the\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.05 level.\u003c/p\u003e","description":"","filename":"Figure2.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/69296dad99bcca61f7d89787.jpg"},{"id":96634039,"identity":"5f3e50a9-c9f9-48ef-bf50-f9ba0b052765","added_by":"auto","created_at":"2025-11-24 13:11:40","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":646928,"visible":true,"origin":"","legend":"\u003cp\u003eMagnitude of rhizosphere effects of \u003cem\u003eS. salsa\u003c/em\u003e among three habitats on soil properties. Different lowercase letters indicate significant differences among three habitats at the \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05 level, while unlabeled parameters indicate no significant intersite variation. Solid points indicate statistically significant rhizosphere effects (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), open points indicate insignificant rhizosphere effects.\u003c/p\u003e","description":"","filename":"Figure3.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/21264be1192e672c783850de.jpg"},{"id":96708994,"identity":"c9e32fb7-0f6f-4882-9686-a3dda2af3afb","added_by":"auto","created_at":"2025-11-25 10:07:01","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":752461,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Coordinates analysis (PCoA) of BS and RS microbial communities based on Bray-Curtis distance. Different colors represent different habitats, different shapes represent bulk or rhizosphere soil.\u003c/p\u003e","description":"","filename":"Figure4.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/3bb9c779c62e015d108e36ae.jpg"},{"id":96634052,"identity":"2b07aa25-98ec-4d6c-9949-8cdd51377c46","added_by":"auto","created_at":"2025-11-24 13:11:41","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":6294688,"visible":true,"origin":"","legend":"\u003cp\u003eSoil microbial community composition at phylum and genus level in different sites and soil. Staked bar charts illustrate the compositions of the top 10 predominant bacterial (a) and fungal (c) communities at the phylum level. Heatmaps show the top 30 communities of bacteria (b) and fungi (d) at the genus level.\u003c/p\u003e","description":"","filename":"Figure5.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/4d315908c505b91c52087abf.jpg"},{"id":96634043,"identity":"c21c2594-67fe-445b-9fdd-a4116aabd76a","added_by":"auto","created_at":"2025-11-24 13:11:40","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1664004,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences of some plant functional traits of \u003cem\u003eS. salsa\u003c/em\u003e in three habitats. Different lowercase letters indicate significant difference among 3 habitats at the \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 level and “ns” denotes no statistically significant difference among three habitats. (a) Individual average biomass in the sample; (b) root to shoot ratio; (c) specific leaf area; (d) proline content in aboveground tissues; (e) sodium content in aboveground tissues; (f) sodium content in belowground tissues; (h) potassium content in aboveground tissues; (f) potassium content in belowground tissues; (i) sodium to potassium ratio in aboveground tissues; (j) sodium to potassium ratio in belowground tissues; (k) nitrogen to phosphorus ratio in aboveground tissues; (l) nitrogen to phosphorus ratio in belowground tissues.\u003c/p\u003e","description":"","filename":"Figure6.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/0413dfa0b6e93e0f4f64de42.jpg"},{"id":96709056,"identity":"85d75d0c-2126-48af-b2d5-1c5b88551738","added_by":"auto","created_at":"2025-11-25 10:07:25","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1009824,"visible":true,"origin":"","legend":"\u003cp\u003eInfluence of soil properties on plant functional traits of \u003cem\u003eS. salsa\u003c/em\u003e. (a) Redundancy analysis (RDA) between 8 bulk soil properties and all measured plant functional traits. (b) Hierarchical partitioning analysis via RDA. Numbers above bars indicate the percentage of variance in plant functional traits explained by soil properties. Orange bars denote soil parameters with statistically significant contributions to trait variation (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), blue bars represent insignificant parameters (\u003cem\u003ep\u003c/em\u003e ≥ 0.05).\u003c/p\u003e","description":"","filename":"Figure7.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/0568d15442a685361daeec82.jpg"},{"id":96634048,"identity":"64254a65-9e8b-42e1-9889-2c43860e1d37","added_by":"auto","created_at":"2025-11-24 13:11:40","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":790720,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman’s correlation heatmap between plant functional traits and rhizosphere effects. Red represents a positive correlation and blue represents a negative correlation between PFTs and RE. Variables prefixed with “RE_” on the vertical axis denote the rhizosphere effects induced by \u003cem\u003eS. salsa\u003c/em\u003e on distinct soil parameters. *, \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05; **, \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.01; AGB, shoot biomass of \u003cem\u003eS. salsa\u003c/em\u003e; BGB, root biomass of \u003cem\u003eS. salsa\u003c/em\u003e; TB, total biomass of \u003cem\u003eS. salsa\u003c/em\u003e; IB, individual biomass of \u003cem\u003eS. salsa\u003c/em\u003e; RSR, root to shoot ratio; SLA, specific leaf area; Pro, proline content of aboveground tissue.\u003c/p\u003e","description":"","filename":"Figure8.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/179ffb4205a5e24d3027d949.jpg"},{"id":107350708,"identity":"eb61db7c-4d2c-475b-bf36-747f64275f82","added_by":"auto","created_at":"2026-04-20 16:00:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":17653400,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/c3fee926-bdd7-42c9-928d-363553e7beb2.pdf"},{"id":96709145,"identity":"83a9d02f-00f4-49a0-9e60-6a91518feff1","added_by":"auto","created_at":"2025-11-25 10:07:56","extension":"docx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":178888,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8013724/v1/4f03e3de4394a5474fa66dc7.docx"}],"financialInterests":"","formattedTitle":"Rhizosphere effects and plant functional traits collectively determine the ecological strategy of Suaeda salsa across heterogeneous habitats in the Yellow River Delta","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSince plant growth is significantly influenced by environmental conditions, the need to cope with heterogeneous environments constitutes a major challenge for plants, especially in the context of climate change (Steltzer and Post \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, understanding the diverse adaptive strategies of plants remains a central focus in plant ecology research. \u0026ldquo;Strategy\u0026rdquo; was explained as the mechanisms of a species to sustain a population, which has been investigated to express an understanding of the opportunities and selective forces that shape the ecologies of plants (Westoby \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Ecological strategies describe the way a species competes for resources, copes with disturbances, interacts with other species and its environment, and ultimately determines its fitness and performance (Gibb et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A large amount of studies focused on the adjustment (or \u0026ldquo;trade-offs\u0026rdquo;) of functional traits to explain plant adaptive strategies (Grime \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1974\u003c/span\u003e; Westoby \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Wright et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2004\u003c/span\u003e); recently, the critical role of belowground processes such as rhizosphere effect have also been constantly emphasized (Finzi et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Han et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Plant functional traits form the basis of adaptive strategies (P\u0026eacute;rez-Harguindeguy et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), while rhizosphere effects act as the critical mediator of environmental responses (Gan et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Collectively, these two components constitute fundamental adaptive mechanisms\u0026zwnj; for plant environmental adaptation.\u0026zwnj;\u003c/p\u003e\u003cp\u003ePlant functional traits (PFTs) represent core biological attributes that significantly influence plant establishment, survival, and fitness (P\u0026eacute;rez-Harguindeguy et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). PFTs demonstrate strong correlations with plant adaptive capacity. For instance, higher specific leaf area (SLA) represents higher resource acquisition efficiency and higher water and nutrient consumption (Pierce et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); higher root to shoot ratio (RSR) indicates greater soil resources acquisition ability, generally associating with low nutrient conditions (Kurepa and Smalle \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Plant stoichiometric traits, such as tissue nitrogen or phosphorus content, also reflect plant resource acquisition and growth strategies (Luo et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pan et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). By modulating functional traits, plants regulate their responses to environmental drivers, modify interactions with other trophic levels, and drive ecosystem dynamics (Martin et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Weemstra et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBeyond adjusting their functional traits, plants can also employ rhizosphere effects (REs) to actively modify soil microenvironment. Rhizosphere is determined as the small volume of soil influenced by root activity (Hinsinger, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Plant roots can release root exudates and rhizodeposits into rhizosphere soil and thus induce rhizosphere effect, resulting in differences in physical, chemical, and biological characteristics between rhizosphere and bulk soil (Hinsinger \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Gargallo-Garriga et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Functioning as a pivotal interface for plant-environment interactions, REs have been widely studied as a soil improvement mechanism. In an European beech forests, plant rhizosphere soil maintained more water-extractable organic matter like sugar than bulk soil (De Feudis et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). At global scale, carbon and nitrogen content in rhizosphere soil were significantly higher than bulk soil (Liu et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ma et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Under stress conditions, REs also function as an effective plant adaptive mechanism. For instance, mucilage secreted by roots can enhance the diffusive transport of nutrient under salinity conditions, thereby reducing risks of nutrient deficiency and salinity stress (Zarebanadkouki et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRhizosphere is also an intermediator for plants and microorganisms interactions. By mediating soil microbial communities, rhizosphere effect will in turn promote plant growth and stress tolerance with the help of microorganisms (Kong and Liu \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Trivedi et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Studies showed that REs could improve soil microbial biomass and enzyme activities (Kumar and Garkoti \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), promote the growth and colonization of microorganisms (Wang et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and recruit specific microbial communities (Shi et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, studies also discovered that soil characteristics exert stronger influences on microbial communities than rhizosphere effects, and the overall microbial community structure remains not affected as a result of the rhizosphere effects (Buyer et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Zhou et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Understanding the complex relationships among plants, their associated microbiomes, and environmental shifts is crucial for improving plant growth and survival (Addison et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCoastal wetlands are situated at the interface between terrestrial and marine ecosystems. Although coastal wetlands represent only a small fraction of the Earth\u0026rsquo;s surface, they play a key role in ecosystem services, including sediment and carbon storage, contaminant removal, storm and flooding buffering, fisheries production, and climate mitigation (Ward et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Baustian et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In China, coastal zones encompass 13% of the nation's territory out of which 95% is located in an intertidal belt (Tian et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Long et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Yellow River Delta (YRD) is the most complete and youngest wetland ecosystem in the warm temperate zone of China (Wang et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Guo et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Characterized by dynamic land-sea interactions, YRD demonstrates large environmental heterogeneity (Guan et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), providing ideal conditions for studying plant performance across diverse ecological gradients.\u003c/p\u003e\u003cp\u003e\u003cem\u003eSuaeda salsa\u003c/em\u003e is an annual herbaceous euhalophyte in Amaranthaceae family, distributed widely in YRD (Li et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Song and Wang \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This species is of high economic and ecological values. Its young vegetative tissues and seed oil are nutrient-rich, making them suitable for processing into human food products and animal fodder. Studies have demonstrated that cultivating and harvesting \u003cem\u003eS. salsa\u003c/em\u003e significantly reduces soil salt and heavy metal content, making it an ideal candidate for ecological restoration (Song and Wang \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Additionally, it serves as an ideal model for studying halophyte salt-tolerance strategies (Cui et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). According to previous studies, \u003cem\u003eS. salsa\u003c/em\u003e could employ both PFTs and REs to adapt to heterogenous environment. On one hand, it exhibits unique trait plasticity under different habitats, especially between the inland and intertidal zone. When growing in inland saline-alkali soils, this species maintains green branches and leaves throughout its growth cycle, whereas the coastal intertidal populations exhibit characteristic purplish-red pigmentation in their vegetative organs, primarily attributed to betacyanin accumulation (Song and Wang \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Cui et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). On the other hand, \u003cem\u003eS. salsa\u003c/em\u003e can recruit microbiomes through rhizosphere effect under heterogenous environment. Studies indicated that rhizosphere soils of \u003cem\u003eS. salsa\u003c/em\u003e harbored significantly greater abundances of plant growth-promoting microorganisms and salt stress-mitigating microbes compared to bulk soils (Tang et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Nevertheless, integrated studies investigating the combined roles of functional traits and rhizosphere effects in \u003cem\u003eS. salsa\u003c/em\u003e's adaptation across heterogeneous habitats remain limited. Conducting such research would provide critical insights into the multidimensional response mechanisms of halophytes to heterogenous environment.\u003c/p\u003e\u003cp\u003eBased on the previous studies, soil salinity is recognized the most important factor affecting the growth and physiological characters of \u003cem\u003eS. salsa\u003c/em\u003e (Song and Wang \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Consequently, we established study sites across three habitats with distinct salinity regimes to elucidate adaptive strategies in this halophyte through simultaneous quantification of plant functional traits and rhizosphere effects. We hypothesized that (1) soil properties and microbial communities between rhizosphere soil and bulk soil would exhibit distinct differences, especially in high soil salinity conditions; (2) functional traits of \u003cem\u003eS. salsa\u003c/em\u003e would exhibit habitat-specific differentiation across three discrete salinity habitats, with trait expression correlating significantly with soil salinity levels; (3) microbial community compositions would be impacted by both habitats and plant rhizosphere effect.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study site\u003c/h2\u003e\u003cp\u003eThis study was conducted at the Yellow River Delta, Shandong Province, China (117\u0026deg;31\u0026prime;\u0026ndash;119\u0026deg;18\u0026prime; E, 36\u0026deg;55\u0026prime;\u0026ndash;38\u0026deg;16\u0026prime; N). The region is distinguished by a warm temperate monsoon climate, with the mean annual temperature ranging from 11.7\u0026deg;C to 12.8\u0026deg;C and annual precipitation of 580 mm. The soils are mainly coastal saline and tidal soils with severe salt erosion, and the salt content ranges from 0.1% to 1% (Wang et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Experimental design and sample collection\u003c/h2\u003e\u003cp\u003eIn August 2022, we selected 3 typical habitats where \u003cem\u003eS. salsa\u003c/em\u003e was the dominant species as our study sites. As soil salinity increased, the plots were designated Site1, Site2 and Site3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Site1 is located adjacent to the riverbank and is predominantly influenced by the Yellow River. Site2 is situated in the supratidal highlands, significantly influenced by seasonal precipitation, and characterized by a composite environment featuring typical salinization and alternating wet-dry cycles. Site3 is located in the supratidal zone at a lower elevation and experiences seasonal tides during the rainy season. Each site covered an area of at least 600 m\u003csup\u003e2\u003c/sup\u003e and had a relatively homogeneous species composition.\u003c/p\u003e\u003cp\u003eIn each site, five 1 m \u0026times; 1 m plots were established with a distance of over 5 m between each plot. To represent the biomass of \u003cem\u003eS. salsa\u003c/em\u003e, we selected a 0.5 m \u0026times; 0.5 m sub-sample in each plot and excavated all the \u003cem\u003eS. salsa\u003c/em\u003e in the sub-sample, i.e., a quarter of the biomass of \u003cem\u003eS. salsa\u003c/em\u003e in each plot was collected. After divided into aboveground and underground parts, these samples were oven-dried, weighed to determine the biomass, and then used for the analysis of other functional traits (shoot and root element and ion concentrations, shoot proline concentrations). In addition, substantial fresh leaves of \u003cem\u003eS. salsa\u003c/em\u003e were collected from the remaining area of each plot outside the sub-sample for the determination of SLA.\u003c/p\u003e\u003cp\u003eTo investigate the rhizosphere effect of \u003cem\u003eS. salsa\u003c/em\u003e, both rhizosphere soil (RS) and bulk soil (BS) were collected in each plot, using the adhering soil method (Han et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Phillips et al., 2006). Briefly, we dug out the whole plant with some soil on its root and then gently shook the root. Loose soil that can be easily shaken off was collected as the bulk soil. The remaining soil adhering to the surface of the root was carefully removed by the sterile brushes and collected as the rhizosphere soil. Following transportation to the laboratory, about 40 g of each fresh soil sample was immediately separated to determine the soil moisture content (MC). Then the remaining part of each sample was divided into two parts: one stored at -20℃ for the determination of soil inorganic N (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N) concentration and the high-throughput sequencing of soil microorganisms, the other was air dried to analyze other soil properties including physiochemical properties (pH and electrical conductivity), stoichiometric indicators (organic carbon, total nitrogen and total phosphorus concentrations) and extracellular enzyme activities.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Measurement of soil properties and calculation of rhizosphere effect\u003c/h2\u003e\u003cp\u003eWe determined the basic soil physical and chemical properties of both BS and RS to calculate rhizosphere effect. Before the determination of soil properties, fresh soil samples were passed through a 2 mm sieve while air-dried samples through a 0.25 mm sieve to achieve homogenization and exclude impurities.\u003c/p\u003e\u003cp\u003eSoil moisture content (MC) was calculated as the percentage of water mass relative to the dry soil mass, determined by oven-drying approximately 40 g of fresh soil at 105℃. Fresh soil samples (5.0000\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0005 g) were dissolved into 25 ml of deionized water and vibrated for 60 minutes at 180 r min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, then the solution was filtered by 0.45 \u0026micro;m filtration membranes and used to measure soil ammonium nitrogen (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N) and nitrate nitrogen (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N) concentration by a continuous-flow ion auto-analyzer (San++, Scalar, Breda, Netherlands).\u003c/p\u003e\u003cp\u003eSoil pH and electricity conductivity (EC) were measured with the water to soil ratio\u0026thinsp;=\u0026thinsp;2.5:1 (v:w), using the pH meter (FE28, Mettler Toledo, Shanghai, China) and electricity conductivity meter (FE38, Mettler Toledo, Shanghai, China) respectively. Soil organic carbon (SOC) was determined by potassium dichromate volume-external heating (oil bath heating) method. To determine soil total nitrogen (TN) and total phosphorus (TP) concentration, about 1g (1.0000\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0005 g) soil was digested with H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e at 400℃ for 1 hour, using CuSO\u003csub\u003e4\u003c/sub\u003e and K\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e as catalysts. The solution was used to measure TN by a Kjeldahl apparatus (K9860, Hanon, Dezhou, China) and TP by UV-spectrophotometer (UA-5500, METASH, Shanghai, China) at 700 nm. Then we calculated soil nitrogen to phosphorus ratio (N:P) to reflect the nutrient balance in soil.\u003c/p\u003e\u003cp\u003eSoil extracellular enzyme activities were quantified using enzyme activity assay kits (Solarbio life sciences, Beijing, China). Soil samples were processed following the standardized protocols, then the absorbance measurements were conducted on a UV-spectrophotometer (UA-5500, METASH, Shanghai, China) at 660 nm for soil acid phosphatase (ACP), while at 400 nm for N-acetyl-β-D-glucosidase (NAG) and β-glucosidase (β-GC).\u003c/p\u003e\u003cp\u003eThe rhizosphere effect (RE) of each indicator was calculated by diving the difference between rhizosphere soil and bulk soil by the value of bulk soil:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\begin{array}{c}{RE}_{i}=\\frac{{RS}_{i}-{BS}_{i}}{{BS}_{i}}\\:\\#\\left(1\\right)\\end{array}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cem\u003eREi\u003c/em\u003e is the rhizosphere effect of indicator \u003cem\u003ei\u003c/em\u003e, \u003cem\u003eRSi\u003c/em\u003e and \u003cem\u003eBSi\u003c/em\u003e refers to the value of indicator \u003cem\u003ei\u003c/em\u003e in rhizosphere soil and bulk soil respectively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Determination of plant functional traits\u003c/h2\u003e\u003cp\u003eAfter bringing back to the laboratory, the fresh leaves of each plot were rehydrated, scanned with a flatbed scanner (LiDE120, Canon, Tokyo, Japan), then oven-dried and weighed. Leaf area was quantified using ImageJ (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://imagej.net/imagej-wiki-static/Fiji\u003c/span\u003e\u003cspan address=\"https://imagej.net/imagej-wiki-static/Fiji\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and specific leaf area (SLA) was calculated as leaf area divided by leaf dry mass. Plant samples designated for biomass determination were separated into aboveground and belowground sections. After thorough rinsing to remove adhering soil, the samples were initially oven-dried at 105\u0026deg;C for 30 minutes to deactivate enzymes, followed by drying at 65\u0026deg;C until a constant weight. The dry weights of each section were recorded as their biomass (AGB and BGB). Afterwards, the total biomass in the sample (TB), individual biomass (IB) and root to shoot ratio (RSR) of \u003cem\u003eS. salsa\u003c/em\u003e were calculated.\u003c/p\u003e\u003cp\u003eDry plant samples were then ground and sieved through a 100 mesh screen, for the determination of element (N and P), ion (Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e) and proline concentrations. Plant nitrogen (Shoot N, Root N) and phosphorus (Shoot P, Root P) content were determined by the same method as for soil, but with different sample weight (0.2000\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0005 g) and digesting temperature and time (200℃ for 40 minutes followed by 400℃ for 1 hour). After plant powder (1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0005 g) was digested with nitric-perchloric acid, the solution was used to determine the sodium (Na\u003csup\u003e+\u003c/sup\u003e) and potassium (K\u003csup\u003e+\u003c/sup\u003e) ion concentrations by colorimetric method under 766.5 nm and 589 nm respectively (UA-5500, Metash, Shanghai, China). Proline in shoot tissues were extracted using sulfosalicylic acid, and the acidic ninhydrin method was used to determine proline content (Pro).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Soil DNA extraction and Illumina sequencing\u003c/h2\u003e\u003cp\u003eSoil DNA was extracted using DNA Extraction Kit (D6356-02, Magen, Shanghai, China). Concentration of DNA was verified with NanoDrop and agarose gel. The genome DNA was used as template for PCR amplification with the barcoded primers and Tks Gflex DNA Polymerase (Takara). For bacterial diversity analysis, the V3V4 region of 16SrRNA gene was amplified by primers 343F (5'-TACGGRAGGCAGCAG-3') and 798R (5'-AGGGTATCTAATCCT-3'). For fungal diversity analysis, the ITS gene was specifically amplified using primers ITS1F (5'-CTTGGTCATTTAGAGGAAGTAA-3') and ITS2 (5'-GCTGCGTTCTTCATCGATGC-3'). Amplicons were sequenced on an Illumina MiSeq platform (Illumina, Inc., San Diego, CA, USA). Cutadapt software was used to preprocess the raw data through detect and cut off the paired-end reads adapter. The original DNA data was processed by QIIME2, and the obtained effective sequences were clustered by the Amplicon Sequence Variant (ASV) abundance table for further analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e\u003cp\u003ePrior to data analysis, all datasets were subjected to normality (Shapiro-Wilk test) and homogeneity of variance (Levene's test) assessments, with log or power transformations applied when assumptions were violated. Statistical differences in functional traits, rhizosphere effects, and soil physicochemical properties of \u003cem\u003eS. salsa\u003c/em\u003e across environmental conditions were evaluated using one-way analysis of variance (ANOVA) followed by Duncan multiple-comparison in SPSS 25.0 (SPSS Inc., Chicago, USA). One-sample \u003cem\u003et\u003c/em\u003e-tests were applied in SPSS 25.0 to assess whether the rhizosphere effects of individual soil properties significantly deviated from zero (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05), thereby determining whether \u003cem\u003eS. salsa\u003c/em\u003e induced significant rhizosphere effect. Two-way ANOVA was performed to examine the main effects and interactions of site and soil compartment on soil physicochemical properties, thus quantifying the modification of rhizosphere process driven by \u003cem\u003eS. salsa\u003c/em\u003e on soil properties. Redundancy analysis (RDA) was conducted to assess the relationship between soil properties and plant functional traits. Following RDA, the hierarchical partitioning analysis was applied to disentangle the independent and joint contributions of soil properties to plant trait variation.\u003c/p\u003e\u003cp\u003eFor soil microorganisms, α-diversity and β-diversity metrics were quantified. The α-diversity indices were calculated using the following formulas:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:\\begin{array}{c}Chao1={S}_{obs}+\\frac{{n}_{1}\\left({n}_{1}-1\\right)}{2{n}_{2}-2}\\#\\left(2\\right)\\end{array}$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:\\begin{array}{c}Shannon=\\:-\\sum\\:_{i=1}^{{S}_{obs}}\\frac{{n}_{i}}{N}{ln}\\frac{{n}_{i}}{N}\\#\\left(3\\right)\\end{array}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cem\u003eS\u003c/em\u003e\u003csub\u003e\u003cem\u003eobs\u003c/em\u003e\u003c/sub\u003e is the observed ASVs count of bacteria or fungi, \u003cem\u003en\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e denotes the ASVs represented by a single sequence, and \u003cem\u003en\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e denotes the ASVs containing two sequences; \u003cem\u003eN\u003c/em\u003e indicates the total sequence count in a sample, \u003cem\u003en\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e indicates the sequence count of \u003cem\u003ei\u003c/em\u003e-th ASV.\u003c/p\u003e\u003cp\u003eDifferences in microbial composition between rhizosphere and bulk soils under three habitats were assessed using principal coordinate analysis (PCoA) based on Bray-Curtis distance. Statistical significance was evaluated using two-way permutational multivariate analysis of variance (PERMANOVA) with 999 permutations.\u003c/p\u003e\u003cp\u003eData visualization was implemented in R 4.3.3 (R Foundation for Statistical Computing, Vienna, Austria) with the \u003cem\u003eggplot2\u003c/em\u003e package. RDA was conducted in \u003cem\u003evegan\u003c/em\u003e package, and hierarchical partitioning was implemented via \u003cem\u003erdacca.hp\u003c/em\u003e package. Spearman correlation analyses between variables were performed and graphically represented using the \u003cem\u003epheatmap\u003c/em\u003e package.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Differences of soil properties among three habitats\u003c/h2\u003e\u003cp\u003eTwo-way ANOVA revealed that both site and soil compartment exerted significant main effects and interaction effects on soil properties (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Site exerted significant main effects on soil properties except MC, soil compartment did not exert significant main effects on EC and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, and their interaction effects significantly affected SOC, enzyme activity and inorganic nitrogen content.\u003c/p\u003e\u003cp\u003eSignificant differences were found in BS physicochemical properties in different habitats (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating distinct environmental conditions among these sites. Site 1 exhibited the lowest EC and highest pH (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, b), Site2 exhibited the lowest pH and highest SOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, d), Site3 exhibited the highest EC and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentration (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, f), as well as the lowest total nitrogen concentration and total N to P ratio (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg, i). Soil enzyme activity of BS showed no significance among three habitats (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ej, k, l).\u003c/p\u003e\u003cp\u003eFor rhizosphere soils, they were conditioned to be more conducive to plant growth, with lower EC and pH levels, coupled with higher nutrient concentrations and enzyme activity, especially under high salinity conditions (Site2 and Site3). RS at both Site2 and Site3 had significantly higher soil MC, SOC, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, TN, N:P and enzyme activities compared to BS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, d, f, g, i, j, k, l).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Intensity of rhizosphere effect of S. salsa under different habitats\u003c/h2\u003e\u003cp\u003eRhizosphere effects exhibited marked variation across the three habitats except for MC, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N and TP (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). As soil salinity elevated, \u003cem\u003eS. salsa\u003c/em\u003e exhibited stronger rhizosphere effects on most of the soil parameters, whereas the negative rhizosphere effect on soil EC peaked under low-salinity condition (Site1) and diminished with the increasing salt content. The results of one-sample \u003cem\u003et\u003c/em\u003e-tests demonstrated similar patterns that \u003cem\u003eS. salsa\u003c/em\u003e tend to exhibit more significant REs in Site2 and Site3. No significant rhizosphere effects were observed on soil nitrate nitrogen content or soil N:P in different habitats.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Divergence in microbial communities under different sites and soil compartments\u003c/h2\u003e\u003cp\u003eMicrobial α-diversity indices also demonstrated strong responses to environmental heterogeneity (BS in Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Site1 exhibited the highest microbial diversity, Site2 displayed the lowest bacterial diversity, and fungal diversity showed no significant difference between Site2 and Site3. In contrast, rhizosphere microbial communities demonstrated stronger resilience, maintaining stable bacterial diversity across three habitats while displaying fungal diversity variations only for the Shannon index (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe PCoA results showed that the first two axes explaining 19.41% and 12.1% of total variance for bacterial communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), and 13.58% and 8.35% for fungal communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Two-factor PERMANOVA demonstrated significant main effects of habitat and soil, along with significant habitat \u0026times; soil interaction effects (Tables S2 and S3; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Furthermore, bacterial and fungal community at Site1 were distinct from those at Site2 and Site3. Site2 exhibited a clear separation between rhizosphere and bulk soil microbial communities along the first two axes.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis of microbial community composition at phylum and genus level revealed that both habitat type and soil compartment significantly influenced soil microbial community structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). For bacterial communities, the most abundant phyla was Proteobacteria, and it exhibited higher relative abundance in rhizosphere soils compared to bulk soils across all sampling sites, with Site2 showing the lowest overall Proteobacteria abundance (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Fungal communities were dominated by Ascomycota, followed by Basidiomycota and Rozellomycota (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). Compared to rhizosphere soils, bulk soils at Site1 and Site2 exhibited \u0026zwnj;higher Ascomycota\u0026zwnj; but \u0026zwnj;lower Basidiomycota abundance\u0026zwnj;. \u0026zwnj;In contrast, Site3 displayed the \u0026zwnj;opposite pattern\u0026zwnj; (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). At genus level, the microbial communities composition also demonstrated significant differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb, d). For both bacterial and fungal communities, Site1 demonstrated similar composition between rhizosphere and bulk soils, while Site2 and Site3 showed differences among soils and sites.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Responses of functional traits of S. salsa to different habitats\u003c/h2\u003e\u003cp\u003eWith the increasing soil salinity, biomass and RSR of \u003cem\u003eS. salsa\u003c/em\u003e significantly decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea, b; Fig. S2a-c), whereas proline content, shoot N concentration, shoot and root Na\u003csup\u003e+\u003c/sup\u003e concentration, Na\u003csup\u003e+\u003c/sup\u003e:K\u003csup\u003e+\u003c/sup\u003e and N:P increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed, e, f, i, j; Fig. S2e). P content in shoot and root parts of \u003cem\u003eS. salsa\u003c/em\u003e first increased and then decreased with the increase of soil salinity, reaching the highest at Site2 (Fig. S4b, d). K\u003csup\u003e+\u003c/sup\u003e concentration did not change significantly in both shoot and root parts (Fig. S2f, h).\u003c/p\u003e\u003cp\u003eExplanation of the first two axes of RDA was 61.49% and 15.14% respectively, collectively representing 76.63% of soil-driven variability in plant functional traits across all ordination axes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). Hierarchical partitioning analysis demonstrated that NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and EC had significant effects on plant functional traits, explaining 38.53% and 35.56% variation respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N was positively correlated with tissue Na\u003csup\u003e+\u003c/sup\u003e:K\u003csup\u003e+\u003c/sup\u003e and N:P, while negatively correlated with tissue K\u003csup\u003e+\u003c/sup\u003e content and biomass. EC was positively correlated with shoot Na\u003csup\u003e+\u003c/sup\u003e and proline content, while negatively correlated with plant biomass (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Relationship between plant functional traits and rhizosphere effects\u003c/h2\u003e\u003cp\u003eSpearman correlations between functional traits and rhizosphere effects of \u003cem\u003eS. salsa\u003c/em\u003e are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. Biomass-related traits were generally negatively correlated with the magnitude of rhizosphere effects, whereas traits related to plant nutrient concentrations, metal ion content, and proline content were predominantly positively correlated with rhizosphere effects. Compared to rhizosphere effects on other soil parameters, REs on soil organic carbon and soil enzyme activities showed relatively strong correlations with plant functional traits. For the two parameters that significantly affected functional traits, \u003cem\u003eS. salsa\u003c/em\u003e produced relatively weak rhizosphere effects. Rhizosphere effect on soil EC was significantly negatively correlated with individual biomass, and positively correlated with shoot N and tissue Na\u003csup\u003e+\u003c/sup\u003e concentrations. Rhizosphere effect on NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N demonstrated significant correlation with proline content and tissue Na\u003csup\u003e+\u003c/sup\u003e concentrations.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eUsing a typical coastal wetland halophyte species, this study examined the ecological adaptation strategies of \u003cem\u003eSuaeda salsa\u003c/em\u003e to a natural saline gradient by comprehensively analyzing plant functional traits and rhizosphere effects, and further investigating the shaping impact of \u003cem\u003eS. salsa\u003c/em\u003e rhizosphere effects on soil microbial communities. Our results demonstrated that \u003cem\u003eS. salsa\u003c/em\u003e employed integrated strategies including targeted rhizosphere engineering, functional trait plasticity, and selective microbial recruitment to adapt to heterogeneous saline environments.\u003c/p\u003e\u003cp\u003eRhizosphere effect is an efficient adaptive strategy for \u003cem\u003eS. salsa\u003c/em\u003e under heterogeneous habitats. In our results, rhizosphere soil showed significantly lower pH, but higher moisture and nutrient content compared to bulk soil especially under high salt habitats (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb-i). These variations may be closely related to the secretion of root exudates. Root exudates are fundamental drivers in establishing and sustaining the vitality and function of the rhizosphere micro-ecosystem. They can help regulate the microenvironment in the rhizosphere, improve the bioavailability of soil nutrients, and facilitate plant root-microbe interactions (Ahlawat et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Chai and Schachtman, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). First, the mucilage in root exudates will enhance the moisture retention capacity of soil, sustaining higher moisture content in the rhizosphere (Young \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Carminati et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Second, some components of root exudates like organic acids can regulate soil pH and help convert unavailable substances into effective nutrients for plant uptake, critically enhancing plant growth and abiotic stress tolerance (Dakora and Phillips \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Third, nutrients activated by root exudates, and the inherent metabolites in exudates provide a suitable environment and serve as signals for specific microbial recruitment, while some enzymes and acids in the exudates impose selective filtering on microbial communities (Khan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sasse et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These mechanisms drive the assembly of specific rhizosphere microbiomes, thereby shaping plant-microbe interaction patterns. Soil enzyme activities are also strongly associated with root exudates (Schofield et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Root-secreted enzymes and microbial-derived enzymes synergistically constitute the extracellular enzyme pool within rhizosphere soil. Our results demonstrated significantly higher extracellular enzyme activities in the rhizosphere of Site2 and Site3 compared to bulk soils (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ej-l), indicating amplified rhizosphere effect and enhanced microbial metabolic activities under elevated salinity. In addition, we also found a significant increase in soil organic carbon content in the rhizosphere compared to the bulk soil under high salinity habitats (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). This was also likely driven by the abundant organic matters in the root exudates, supporting the point that rhizosphere effects enhanced under high-salinity conditions.\u003c/p\u003e\u003cp\u003eVariations in the magnitude of rhizosphere effects across salinity gradients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) provide evidence that plant modulation of the rhizosphere is strongly influenced by environmental conditions, particularly soil salinity. The magnitude of rhizosphere effects on soil pH, moisture, nutrients, and extracellular enzymes enhanced in high salinity habitats, which means under elevated salt stress, \u003cem\u003eS. salsa\u003c/em\u003e can reduce soil alkalinity, improve water and nutrient acquisition, and recruit specific microbial communities more effectively through rhizosphere effect. This might be due to the increase of root exudation rate (Zhang et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Nevertheless, the rhizosphere effect on soil EC followed a distinct pattern. The negative rhizosphere effect on soil EC was strongest in Site1, and diminished with the increasing soil salinity, becoming insignificant at higher salt conditions. This suggests \u003cem\u003eS. salsa\u003c/em\u003e might exhibit limited ability on soil salinity regulation. Under low salinity habitats, \u003cem\u003eS. salsa\u003c/em\u003e can actively modify its rhizosphere to reduce local salinity, avoid ionic toxicity and enhance water and nutrient availability (Arif et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, as soil salinity increase, maintaining a low salt level through rhizosphere modulation may be overwhelmed. Consequently, \u003cem\u003eS. salsa\u003c/em\u003e shifts its strategy into allocating more resources on nutrient activation and the beneficial microorganisms recruitment to alleviate the nutrient imbalance under high salt stress (Wakeel \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Arif et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAs mentioned above, rhizosphere effect can exert profound structuring forces on soil microbial community assembly. Our analysis revealed that habitat alterations exerted significant impacts on α-diversity of both bacterial and fungal communities in bulk soil, yet showed no statistically significant influence on rhizosphere soil microbiota (Fig. S2). This phenomenon aligns with established salt stress adaptation mechanisms wherein plants actively recruit stress-adapted microbiomes through root exudate regulation (Li et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Under stress conditions, plants alter the composition and secretion rate of root exudates, which promote the diversity and evenness of microbial communities (Zhang et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Such host-mediated microbial enrichment likely stabilizes rhizosphere communities against external diversity fluctuations, maintaining functional redundancy essential for plant resilience under environmental challenges (Xiao et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Luo et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Microbial β-diversity demonstrated congruent patterns between the two high-salinity sites and distinguished from Site1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), suggesting salinity-driven environmental filtering governs microbiome assembly. The lower cumulative explanatory power for fungi (21.93%) than bacteria (31.51%) suggests stronger stochasticity or unmeasured niche-based processes governing fungal assembly (Guo et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). At the phylum level, Proteobacteria and Ascomycota exhibited the highest relative abundances among bacterial and fungal communities, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, c). This finding is consistent with previous studies (Zhang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), suggesting these phyla are likely well-adapted to the environment of Yellow River Delta. Proteobacteria exhibit strong tolerance to stressful conditions, enabling survival in extreme environments (Yang et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and their abundance increases significantly under stable environment (Zhang et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In this study, the abundance of Proteobacteria in rhizosphere soils were higher than bulk soils in all three habitats, indicating rhizosphere soils provide more stable and nutritious conditions, and Proteobacteria may help \u003cem\u003eS. salsa\u003c/em\u003e adapt to high-salinity environment (Zhang et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Ascomycota was predominantly observed as the dominant fungal phylum in coastal saline-alkali soils, with most species exhibiting saprophytic capabilities critical for soil organic matter decomposition (Zhang et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). At the genus level, the marked differentiation in microbial composition across three habitats highlights the significant shaping influence of environmental heterogeneity on microbial assembly (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb, d). Bacteria genera Sphingomonas and BIrii41, which were enriched in the rhizosphere soil of Site2 have been reported to promote plant growth (Asaf et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kong et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), indicating the attraction effect of rhizosphere on beneficial microbial populations that promote plant growth.\u003c/p\u003e\u003cp\u003eFunctional traits of \u003cem\u003eS. salsa\u003c/em\u003e exhibited significant differentiation in response to environmental changes. According to our results, soil NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and EC served as the most important factors impairing the growth of \u003cem\u003eS. salsa\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). High salinity serves as a critical abiotic stress factor that impairs plant development. We found that plant individual biomass, biomass of the sample and root to shoot ratio were decreased as soil salinity increase (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea, b; Fig. S3). Plant biomass is a direct indicator of growth performance. As an euhalophyte, \u003cem\u003eS. salsa\u003c/em\u003e achieves optimal growth at specific ionic concentrations, demonstrating an obligate requirement for ionic exposure rather than thriving in salt-excluded conditions (Jia et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The significant growth depression of \u003cem\u003eS. salsa\u003c/em\u003e populations at Site3 may suggest that soil salinity in Site3 has exceeded the optimal threshold for \u003cem\u003eS. salsa\u003c/em\u003e. One of the mechanisms that salt stress affects plant growth is the cytotoxicity due to excessive uptake of Na\u003csup\u003e+\u003c/sup\u003e and Cl\u003csup\u003e\u0026minus;\u003c/sup\u003e ions (Isayenkov et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Isayenkov and Maathuis, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For halophytes, they can assimilate and compartmentalize Na\u003csup\u003e+\u003c/sup\u003e into vacuoles to increase their tissue osmotic pressure and alleviate the cytotoxicity (Flowers and Colmer \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Song and Wang \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Maintaining a low Na\u003csup\u003e+\u003c/sup\u003e:K\u003csup\u003e+\u003c/sup\u003e in the cytosol is also recognized as an important salt-tolerance mechanism in halophytes (Flowers and Colmer \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In our results, shoots and roots of \u003cem\u003eS. salsa\u003c/em\u003e both exhibited significant Na\u003csup\u003e+\u003c/sup\u003e accumulation under high salinity (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee, f). The significantly elevated Na⁺:K⁺ ratio at Site3 suggests the excessive accumulation of sodium ions, which may cause ionic toxicity. Proline is an major organic osmotic regulation substances that often accumulates in cytosol under osmotic stress to maintain cytoplasmic homeostasis (Slama et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Shang et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Under seawater-induced salinity stress, \u0026zwnj;proline accumulated in \u003cem\u003eS. salsa\u003c/em\u003e shoot tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed)\u0026zwnj;, indicating a specialized osmoregulatory adaptation via biosynthesis.\u003c/p\u003e\u003cp\u003eNitrogen plays an important role in plant growth and development. Nitrogen acquisition is fundamentally dependent on inorganic forms, with ammonium nitrogen represents a critical nitrogen acquisition form for rapid plant assimilation (Wang et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although NH₄⁺-N typically serves as a nitrogen source, its association with reduced plant biomass and increased tissue N:P ratio (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) reveals a fundamental physiological trade-off under salinity stress. High rhizosphere NH₄⁺-N (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef) and elevated tissue N and Na⁺ concentrations at Site2 and Site3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee, f; Fig. S2d, e) suggest that \u003cem\u003eS. salsa\u003c/em\u003e prioritizes nitrogen assimilation and osmotic adjustment over growth when exposed to ammonium-rich saline conditions. This aligns with studies demonstrating that excessive NH₄⁺ inhibits root development and induces metabolic costs in halophytes due to cytotoxicity and pH shifts in saline soils (Bitts\u0026aacute;nszky et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Esteban et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe interplay between functional traits and rhizosphere effects reveals adaptive strategies under saline stress. Although soil salinity and NH₄⁺-N were dominant drivers of trait variation, the rhizosphere effect on them did not show obvious correlations with functional traits (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). This decoupling suggests that intrinsic physiological adjustments buffer external stress, allowing plants to modulate rhizosphere processes independently from immediate soil conditions (Xu et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Interestingly, a strong negative correlation was observed between individual biomass of \u003cem\u003eS. salsa\u003c/em\u003e and its rhizosphere effect on soil electrical conductivity, indicating that smaller individuals tend to induce stronger rhizosphere-mediated response to salt stress. This might be dominated by soil salinity. On one hand, high salinity inhibits plant growth; on the other hand, high salinity induces an enhancement of rhizosphere effects. Such specific allocation tradeoffs likely represents an evolutionary optimization strategy in \u003cem\u003eS. salsa\u003c/em\u003e, where resource diversion from growth to stress acclimation for enhancing survival probability in marginal environments (Monson et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, this study demonstrates that \u003cem\u003eS. salsa\u003c/em\u003e employs synergistic interactions between rhizosphere effects and functional traits to develop multidimensional adaptive strategies in response to heterogeneous habitats in the Yellow River Delta. First, rhizosphere effects were significantly enhanced under high-salinity conditions, characterized by reduced soil pH, improved moisture content, nutrient availability, and elevated enzyme activities in rhizosphere soils. Second, microbial community composition was jointly shaped by habitat type and rhizosphere effects, suggesting selective enrichment of stress-adapted microbiota to enhance plant adaptation. Furthermore, soil ammonia nitrogen content and salinity significantly influenced the functional trait differentiation of \u003cem\u003eS. salsa\u003c/em\u003e, reflecting the important role of soil nitrogen availability for plant growth under salinity environment. These findings underscore the pivotal role of coordinated rhizosphere effects and functional trait plasticity in driving plant adaptation to heterogeneous environments, providing critical insights into the multidimensional response mechanisms of halophytes and informing restoration strategies for degraded saline-alkali ecosystems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (No. 32471580; U22A20558), Key Laboratory of Ecological Prewarning, Protection and Restoration of Bohai Sea, Ministry of Natural Resources (No. 2024103), and the Natural Science Foundation of Shandong Province, China (No. ZR2024MC091).\u003c/p\u003e\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\u003cp\u003eLuyao Gong: Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Data curation, Visualization. Yixin Song: Writing \u0026ndash; original draft, Data curation, Formal analysis, Investigation, Methodology. Luyu Qi: Methodology, Investigation. Puyi Zhang: Investigation. Wenlong Sun: Investigation. Wei Wang: Project administration, Writing \u0026ndash; review \u0026amp; editing. Shijie Yi: Investigation. Xiaofei Yang: Investigation, Zijun Xu: Validation. Qingyun Yu: Validation. Yifei Song: Validation. Weihua Guo: Funding acquisition, Project administration. Ning Du: Conceptualization, Investigation, Funding acquisition, Project administration, Supervision\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eWe would like to thank Jiaqi Jiang, Tianyu Ji, Gaode Meng and Haonan Chen for their assistance in the field survey.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAddison SL, R\u0026uacute;a MA, Smaill SJ et al (2024) Partner or perish: Tree microbiomes and climate change. Trends Plant Sci 29:1029\u0026ndash;1040. https://doi.org/10.1016/j.tplants.2024.03.008\u003c/li\u003e\n\u003cli\u003eAhlawat OP, Yadav D, Walia N et al (2024) Root exudates and their significance in abiotic stress amelioration in plants: A review. J Plant Growth Regul 43:1736\u0026ndash;1761. https://doi.org/10.1007/s00344-024-11237-7\u003c/li\u003e\n\u003cli\u003eArif Y, Singh P, Siddiqui H et al (2020) Salinity induced physiological and biochemical changes in plants: An omic approach towards salt stress tolerance. Plant Physiol Biochem 156:64\u0026ndash;77. https://doi.org/10.1016/j.plaphy.2020.08.042\u003c/li\u003e\n\u003cli\u003eAsaf S, Numan M, Khan AL et al (2020) \u003cem\u003eSphingomonas\u003c/em\u003e: from diversity and genomics to functional role in environmental remediation and plant growth. Crit Rev Biotechnol 40:138\u0026ndash;152. https://doi.org/10.1080/07388551.2019.1709793\u003c/li\u003e\n\u003cli\u003eBaustian MM, Liu B, Moss LC et al (2022) Climate change mitigation potential of Louisiana\u0026rsquo;s coastal area: Current estimates and future projections. Ecol Appl 33:e2847. https://doi.org/10.1002/eap.2847\u003c/li\u003e\n\u003cli\u003eBitts\u0026aacute;nszky A, Pilinszky K, Gyulai G et al (2015) Overcoming ammonium toxicity. Plant Sci 231:184\u0026ndash;190. https://doi.org/10.1016/j.plantsci.2014.12.005\u003c/li\u003e\n\u003cli\u003eBuyer JS, Roberts DP, Russek-Cohen E (2011) Soil and plant effects on microbial community structure. Can J Microbiol. https://doi.org/10.1139/w02-095\u003c/li\u003e\n\u003cli\u003eCarminati A, Moradi AB, Vetterlein D et al (2010) Dynamics of soil water content in the rhizosphere. Plant Soil 332:163\u0026ndash;176. https://doi.org/10.1007/s11104-010-0283-8\u003c/li\u003e\n\u003cli\u003eChai YN, Schachtman DP (2022) Root exudates impact plant performance under abiotic stress. Trends Plant Sci 27:80\u0026ndash;91. https://doi.org/10.1016/j.tplants.2021.08.003\u003c/li\u003e\n\u003cli\u003eCui B, Liu R, Yu Q et al (2024) Combined genome and transcriptome provides insight into the genetic evolution of an edible halophyte \u003cem\u003eSuaeda salsa\u003c/em\u003e adaptation to high salinity. Mol Ecol n/a:e17457. https://doi.org/10.1111/mec.17457\u003c/li\u003e\n\u003cli\u003eDakora FD, Phillips DA (2002) Root exudates as mediators of mineral acquisition in low-nutrient environments. Plant Soil 245:35\u0026ndash;47. https://doi.org/10.1023/A:1020809400075\u003c/li\u003e\n\u003cli\u003eDe Feudis M, Cardelli V, Massaccesi L et al (2017) Altitude affects the quality of the water-extractable organic matter (WEOM) from rhizosphere and bulk soil in european beech forests. Geoderma 302:6\u0026ndash;13. https://doi.org/10.1016/j.geoderma.2017.04.015\u003c/li\u003e\n\u003cli\u003eEsteban R, Ariz I, Cruz C et al (2016) Review: Mechanisms of ammonium toxicity and the quest for tolerance. Plant Sci 248:92\u0026ndash;101. https://doi.org/10.1016/j.plantsci.2016.04.008\u003c/li\u003e\n\u003cli\u003eFinzi AC, Abramoff RZ, Spiller KS et al (2015) Rhizosphere processes are quantitatively important components of terrestrial carbon and nutrient cycles. Glob Change Biol 21:2082\u0026ndash;2094. https://doi.org/10.1111/gcb.12816\u003c/li\u003e\n\u003cli\u003eFlowers TJ, Colmer TD (2008) Salinity tolerance in halophytes. New Phytol 179:945\u0026ndash;963. https://doi.org/10.1111/j.1469-8137.2008.02531.x\u003c/li\u003e\n\u003cli\u003eGan D, Feng J, Han M et al (2021) Rhizosphere effects of woody plants on soil biogeochemical processes: A meta-analysis. Soil Biol Biochem 160:108310. https://doi.org/10.1016/j.soilbio.2021.108310\u003c/li\u003e\n\u003cli\u003eGargallo-Garriga A, Preece C, Sardans J et al (2018) Root exudate metabolomes change under drought and show limited capacity for recovery. Sci Rep 8:12696. https://doi.org/10.1038/s41598-018-30150-0\u003c/li\u003e\n\u003cli\u003eGibb H, Bishop TR, Leahy L et al (2023) Ecological strategies of (pl)ants: Towards a world-wide worker economic spectrum for ants. Funct Ecol 37:13\u0026ndash;25. https://doi.org/10.1111/1365-2435.14135\u003c/li\u003e\n\u003cli\u003eGrime JP (1974) Vegetation classification by reference to strategies. Nature 250:26\u0026ndash;31. https://doi.org/10.1038/250026a0\u003c/li\u003e\n\u003cli\u003eGuan B, Yu J, Hou A et al (2017) The ecological adaptability of \u003cem\u003ePhragmites australis\u003c/em\u003e to interactive effects of water level and salt stress in the Yellow River Delta. Aquat Ecol 51:107\u0026ndash;116. https://doi.org/10.1007/s10452-016-9602-3\u003c/li\u003e\n\u003cli\u003eGuo Q, Wen Z, Ghanizadeh H et al (2023) Stochastic processes dominate assembly of soil fungal community in grazing excluded grasslands in northwestern China. J Soils Sediments 23:156\u0026ndash;171. https://doi.org/10.1007/s11368-022-03315-8\u003c/li\u003e\n\u003cli\u003eGuo X, Sun Z, Gao Y et al (2025) Haplotype-specific interactions of \u003cem\u003ePhragmites australis\u003c/em\u003e with \u003cem\u003eSpartina alterniflora\u003c/em\u003e under salt stress. J Environ Manage 384:125506. https://doi.org/10.1016/j.jenvman.2025.125506\u003c/li\u003e\n\u003cli\u003eHan M, Sun L, Gan D et al (2020) Root functional traits are key determinants of the rhizosphere effect on soil organic matter decomposition across 14 temperate hardwood species. Soil Biol Biochem 151:108019. https://doi.org/10.1016/j.soilbio.2020.108019\u003c/li\u003e\n\u003cli\u003eHinsinger P (1998) How do plant roots acquire mineral nutrients? Chemical processes involved in the rhizosphere. Advances in Agronomy 64:pp 225\u0026ndash;265. https://doi.org/10.1016/S0065-2113(08)60506-4\u003c/li\u003e\n\u003cli\u003eIsayenkov S, Hilo A, Rizzo P et al (2020) Adaptation strategies of halophytic barley \u003cem\u003eHordeum marinum\u003c/em\u003e ssp. \u003cem\u003emarinum\u003c/em\u003e to high salinity and osmotic stress. Int J Mol Sci 21:9019. https://doi.org/10.3390/ijms21239019\u003c/li\u003e\n\u003cli\u003eIsayenkov SV, Maathuis FJM (2019) Plant salinity stress: Many unanswered questions remain. Front Plant Sci 10:80. https://doi.org/10.3389/fpls.2019.00080\u003c/li\u003e\n\u003cli\u003eJia J, Huang C, Bai J et al (2018) Effects of drought and salt stresses on growth characteristics of euhalophyte \u003cem\u003eSuaeda salsa\u003c/em\u003e in coastal wetlands. Phys Chem Earth Parts ABC 103:68\u0026ndash;74. https://doi.org/10.1016/j.pce.2017.01.002\u003c/li\u003e\n\u003cli\u003eKhan N, Ali S, Shahid MA et al (2021) Insights into the interactions among roots, rhizosphere, and rhizobacteria for improving plant growth and tolerance to abiotic stresses: A review. Cells 10:1551. https://doi.org/10.3390/cells10061551\u003c/li\u003e\n\u003cli\u003eKong W, Qiu L, Ishii S et al (2023) Contrasting response of soil microbiomes to long-term fertilization in various highland cropping systems. ISME Commun 3:81. https://doi.org/10.1038/s43705-023-00286-w\u003c/li\u003e\n\u003cli\u003eKong Z, Liu H (2022) Modification of rhizosphere microbial communities: A possible mechanism of plant growth promoting rhizobacteria enhancing plant growth and fitness. Front Plant Sci 13:920813. https://doi.org/10.3389/fpls.2022.920813\u003c/li\u003e\n\u003cli\u003eKumar S, Garkoti SC (2022) Rhizosphere influence on soil microbial biomass and enzyme activity in banj oak, chir pine and banj oak regeneration forests in the central Himalaya. Geoderma 409:115626. https://doi.org/10.1016/j.geoderma.2021.115626\u003c/li\u003e\n\u003cli\u003eKurepa J, Smalle JA (2022) Auxin/cytokinin antagonistic control of the shoot/root growth ratio and its relevance for adaptation to drought and nutrient deficiency stresses. Int J Mol Sci 23:1933. https://doi.org/10.3390/ijms23041933\u003c/li\u003e\n\u003cli\u003eLi CY, He R, Tian CY et al (2023) Utilization of halophytes in saline agriculture and restoration of contaminated salinized soils from genes to ecosystem: \u003cem\u003eSuaeda salsa\u003c/em\u003e as an example. Mar Pollut Bull 197:115728. https://doi.org/10.1016/j.marpolbul.2023.115728\u003c/li\u003e\n\u003cli\u003eLi H, La S, Zhang X et al (2021) Salt-induced recruitment of specific root-associated bacterial consortium capable of enhancing plant adaptability to salt stress. ISME J 15:2865\u0026ndash;2882. https://doi.org/10.1038/s41396-021-00974-2\u003c/li\u003e\n\u003cli\u003eLi H, Xu C, Han L et al (2022) Extensive secretion of phenolic acids and fatty acids facilitates rhizosphere pH regulation in halophyte \u003cem\u003ePuccinellia tenuiflora\u003c/em\u003e under alkali stress. Physiol Plant 174:e13678. https://doi.org/10.1111/ppl.13678\u003c/li\u003e\n\u003cli\u003eLi X, Liu Y, Chen M et al (2012) Relationships between ion and chlorophyll accumulation in seeds and adaptation to saline environments in \u003cem\u003eSuaeda salsa\u003c/em\u003e populations. Plant Biosyst 146:142\u0026ndash;149. https://doi.org/10.1080/11263504.2012.727880\u003c/li\u003e\n\u003cli\u003eLi X, Zhang X, Song J et al (2011) Accumulation of ions during seed development under controlled saline conditions of two \u003cem\u003eSuaeda salsa\u003c/em\u003e populations is related to their adaptation to saline environments. Plant Soil 341:99\u0026ndash;107. https://doi.org/10.1007/s11104-010-0625-6\u003c/li\u003e\n\u003cli\u003eLiu HQ, Lu XB, Li ZH et al (2021) The role of root-associated microbes in growth stimulation of plants under saline conditions. Land Degrad Dev 32:3471\u0026ndash;3486. https://doi.org/10.1002/ldr.3955\u003c/li\u003e\n\u003cli\u003eLiu S, He F, Kuzyakov Y et al (2022) Nutrients in the rhizosphere: A meta-analysis of content, availability, and influencing factors. Sci Total Environ 826:153908. https://doi.org/10.1016/j.scitotenv.2022.153908\u003c/li\u003e\n\u003cli\u003eLiu Z, Li J, Hou R et al (2023) Plant rhizospheres harbour specific fungal groups and form a stable co-occurrence pattern in the saline-alkali soil. Agronomy 13:1036. https://doi.org/10.3390/agronomy13041036\u003c/li\u003e\n\u003cli\u003eLong X, Liu L, Shao T et al (2016) Developing and sustainably utilize the coastal mudflat areas in China. Sci Total Environ 569\u0026ndash;570:1077\u0026ndash;1086. https://doi.org/10.1016/j.scitotenv.2016.06.170\u003c/li\u003e\n\u003cli\u003eLuo C, He Y, Chen Y (2025) Rhizosphere microbiome regulation: Unlocking the potential for plant growth. Curr Res Microb Sci 8:100322. https://doi.org/10.1016/j.crmicr.2024.100322\u003c/li\u003e\n\u003cli\u003eLuo Y, Peng Q, Li K et al (2021) Patterns of nitrogen and phosphorus stoichiometry among leaf, stem and root of desert plants and responses to climate and soil factors in Xinjiang, China. Catena 199:105100. https://doi.org/10.1016/j.catena.2020.105100\u003c/li\u003e\n\u003cli\u003eMa Y, Yue K, Heděnec P et al (2023) Global patterns of rhizosphere effects on soil carbon and nitrogen biogeochemical processes. Catena 220:106661. https://doi.org/10.1016/j.catena.2022.106661\u003c/li\u003e\n\u003cli\u003eMartin AR, Rapidel B, Roupsard O et al (2017) Intraspecific trait variation across multiple scales: the leaf economics spectrum in coffee. Funct Ecol 31:604\u0026ndash;612. https://doi.org/10.1111/1365-2435.12790\u003c/li\u003e\n\u003cli\u003eMonson RK, Trowbridge AM, Lindroth RL et al (2022) Coordinated resource allocation to plant growth\u0026ndash;defense tradeoffs. New Phytol 233:1051\u0026ndash;1066. https://doi.org/10.1111/nph.17773\u003c/li\u003e\n\u003cli\u003ePan S, Ahmad Anees S, Yang X et al (2024) The stoichiometric characteristics and the relationship with hydraulic and morphological traits of the \u003cem\u003eFaxon fir\u003c/em\u003e in the subalpine coniferous forest of Southwest China. Ecol Indic 159:111636. https://doi.org/10.1016/j.ecolind.2024.111636\u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez-Harguindeguy N, D\u0026iacute;az S, Garnier E et al (2013) New handbook for standardised measurement of plant functional traits worldwide. Aust J Bot 61:167. https://doi.org/10.1071/BT12225\u003c/li\u003e\n\u003cli\u003ePierce S, Brusa G, Sartori M et al (2012) Combined use of leaf size and economics traits allows direct comparison of hydrophyte and terrestrial herbaceous adaptive strategies. Ann Bot 109:1047\u0026ndash;1053. https://doi.org/10.1093/aob/mcs021\u003c/li\u003e\n\u003cli\u003eSasse J, Martinoia E, Northen T (2018) Feed your friends: Do plant exudates shape the root microbiome? Trends Plant Sci 23:25\u0026ndash;41. https://doi.org/10.1016/j.tplants.2017.09.003\u003c/li\u003e\n\u003cli\u003eSchofield EJ, Brooker RW, Rowntree JK et al (2019) Plant-plant competition influences temporal dynamism of soil microbial enzyme activity. Soil Biol Biochem 139:107615. https://doi.org/10.1016/j.soilbio.2019.107615\u003c/li\u003e\n\u003cli\u003eShang C, Wang L, Tian C et al (2020) Heavy metal tolerance and potential for remediation of heavy metal-contaminated saline soils for the euhalophyte \u003cem\u003eSuaeda salsa\u003c/em\u003e. Plant Signal Behav 15:1805902. https://doi.org/10.1080/15592324.2020.1805902\u003c/li\u003e\n\u003cli\u003eShi H, Yang J, Li Q et al (2023) Diversity and correlation analysis of different root exudates on the regulation of microbial structure and function in soil planted with \u003cem\u003ePanax notoginseng\u003c/em\u003e. Front Microbiol 14:. https://doi.org/10.3389/fmicb.2023.1282689\u003c/li\u003e\n\u003cli\u003eSlama I, Abdelly C, Bouchereau A et al (2015) Diversity, distribution and roles of osmoprotective compounds accumulated in halophytes under abiotic stress. Ann Bot 115:433\u0026ndash;447. https://doi.org/10.1093/aob/mcu239\u003c/li\u003e\n\u003cli\u003eSong J, Wang B (2015) Using euhalophytes to understand salt tolerance and to develop saline agriculture: \u003cem\u003eSuaeda salsa\u003c/em\u003e as a promising model. Ann Bot 115:541\u0026ndash;553. https://doi.org/10.1093/aob/mcu194\u003c/li\u003e\n\u003cli\u003eSteltzer H, Post E (2009) Seasons and life cycles. Science 324:886\u0026ndash;887. https://doi.org/10.1126/science.1171542\u003c/li\u003e\n\u003cli\u003eTang L, Zhan L, Han Y et al (2023) Microbial community assembly and functional profiles along the soil-root continuum of salt-tolerant \u003cem\u003eSuaeda glauca\u003c/em\u003e and \u003cem\u003eSuaeda salsa\u003c/em\u003e. Front Plant Sci 14:. https://doi.org/10.3389/fpls.2023.1301117\u003c/li\u003e\n\u003cli\u003eTian B, Wu W, Yang Z et al (2016) Drivers, trends, and potential impacts of long-term coastal reclamation in China from 1985 to 2010. Estuar Coast Shelf Sci 170:83\u0026ndash;90. https://doi.org/10.1016/j.ecss.2016.01.006\u003c/li\u003e\n\u003cli\u003eTrivedi P, Batista BD, Bazany KE et al (2022) Plant\u0026ndash;microbiome interactions under a changing world: responses, consequences and perspectives. New Phytol 234:1951\u0026ndash;1959. https://doi.org/10.1111/nph.18016\u003c/li\u003e\n\u003cli\u003eWakeel A (2013) Potassium\u0026ndash;sodium interactions in soil and plant under saline-sodic conditions. J Plant Nutr Soil Sci 176:344\u0026ndash;354. https://doi.org/10.1002/jpln.201200417\u003c/li\u003e\n\u003cli\u003eWang H, Liu H, Cao G et al (2020) Alpine grassland plants grow earlier and faster but biomass remains unchanged over 35 years of climate change. Ecol Lett 23:701\u0026ndash;710. https://doi.org/10.1111/ele.13474\u003c/li\u003e\n\u003cli\u003eWang S, Liu Y, Chen L et al (2021) Effects of excessive nitrogen on nitrogen uptake and transformation in the wetland soils of Liaohe estuary, northeast China. Sci Total Environ 791:148228. https://doi.org/10.1016/j.scitotenv.2021.148228\u003c/li\u003e\n\u003cli\u003eWang Y, Feng H, Wang R et al (2023) Non-targeted metabolomics and 16s rDNA reveal the impact of uranium stress on rhizosphere and non-rhizosphere soil of ryegrass. J Environ Radioact 258:107090. https://doi.org/10.1016/j.jenvrad.2022.107090\u003c/li\u003e\n\u003cli\u003eWang Y, Wu H, Wang J et al (2025) Leaf and root functional traits of woody and herbaceous halophytes and their adaptations in the Yellow River Delta. Plants 14:159. https://doi.org/10.3390/plants14020159\u003c/li\u003e\n\u003cli\u003eWard ND, Megonigal JP, Bond-Lamberty B et al (2020) Representing the function and sensitivity of coastal interfaces in Earth system models. Nat Commun 11:2458. https://doi.org/10.1038/s41467-020-16236-2\u003c/li\u003e\n\u003cli\u003eWeemstra M, Freschet GT, Stokes A et al (2021) Patterns in intraspecific variation in root traits are species-specific along an elevation gradient. Funct Ecol 35:342\u0026ndash;356. https://doi.org/10.1111/1365-2435.13723\u003c/li\u003e\n\u003cli\u003eWestoby M (1998) A leaf-height-seed (LHS) plant ecology strategy scheme. Plant Soil 199:213\u0026ndash;227\u003c/li\u003e\n\u003cli\u003eWright IJ, Reich PB, Westoby M et al (2004) The worldwide leaf economics spectrum. Nature 428:821\u0026ndash;827. https://doi.org/10.1038/nature02403\u003c/li\u003e\n\u003cli\u003eXiao E, Deng J, Shao L et al (2024) Increased microbial complexity and stability in rhizosphere soil: A key factor for plant resilience during mining disturbance. Sci Total Environ 956:177100. https://doi.org/10.1016/j.scitotenv.2024.177100\u003c/li\u003e\n\u003cli\u003eXu J, Wang X, Zu H et al (2021) Molecular dissection of rice phytohormone signaling involved in resistance to a piercing-sucking herbivore. New Phytol 230:1639\u0026ndash;1652. https://doi.org/10.1111/nph.17251\u003c/li\u003e\n\u003cli\u003eYang Z, Sui H, Zhang T et al (2023) Response of surface soil microbial communities to heavy metals and soil properties for five different land-use types of Yellow River delta. Environ Earth Sci 82:599. https://doi.org/10.1007/s12665-023-11291-6\u003c/li\u003e\n\u003cli\u003eYoung IM (1995) Variation in moisture contents between bulk soil and the rhizosheath of wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e L. cv. Wembley). New Phytol 130:135\u0026ndash;139. https://doi.org/10.1111/j.1469-8137.1995.tb01823.x\u003c/li\u003e\n\u003cli\u003eZarebanadkouki M, Fink T, Benard P et al (2019) Mucilage facilitates nutrient diffusion in the drying rhizosphere. Vadose Zone J 18:190021. https://doi.org/10.2136/vzj2019.02.0021\u003c/li\u003e\n\u003cli\u003eZhang C, Liu G, Xue S et al (2016) Soil bacterial community dynamics reflect changes in plant community and soil properties during the secondary succession of abandoned farmland in the \u003cem\u003eLoess plateau\u003c/em\u003e. Soil Biol Biochem 97:40\u0026ndash;49. https://doi.org/10.1016/j.soilbio.2016.02.013\u003c/li\u003e\n\u003cli\u003eZhang H, Zhang G, L\u0026uuml; X et al (2015) Salt tolerance during seed germination and early seedling stages of 12 halophytes. Plant Soil 388:229\u0026ndash;241. https://doi.org/10.1007/s11104-014-2322-3\u003c/li\u003e\n\u003cli\u003eZhang XC, Zhai HL, Xu HY et al (2025) Different salt stress types regulated rhizosphere rare bacterial communities through root exudates and soil physicochemical properties. Plant Soil. https://doi.org/10.1007/s11104-025-07777-w\u003c/li\u003e\n\u003cli\u003eZhang Y, Wang H, Zhang X et al (2024) Effects of salt stress on the rhizosphere soil microbial communities of \u003cem\u003eSuaeda salsa \u003c/em\u003e(L.) pall. in the Yellow River Delta. Ecol Evol 14:e70315. https://doi.org/10.1002/ece3.70315\u003c/li\u003e\n\u003cli\u003eZhang Z, Sun J, Li T et al (2023) Effects of nitrogen and phosphorus imbalance input on rhizosphere and bulk soil bacterial community of \u003cem\u003eSuaeda salsa\u003c/em\u003e in the Yellow River Delta. Front Mar Sci 10:. https://doi.org/10.3389/fmars.2023.1131713\u003c/li\u003e\n\u003cli\u003eZhao X, Tian P, Sun Z et al (2022) Rhizosphere effects on soil organic carbon processes in terrestrial ecosystems: A meta-analysis. Geoderma 412:115739. https://doi.org/10.1016/j.geoderma.2022.115739\u003c/li\u003e\n\u003cli\u003eZhou J, Deng Y, Shen L et al (2016) Temperature mediates continental-scale diversity of microbes in forest soils. Nat Commun 7:12083. https://doi.org/10.1038/ncomms12083\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Plant functional traits, Rhizosphere effect, Soil microbiome composition, Euhalophyte, Coastal wetlands, Ecological adaptation strategy","lastPublishedDoi":"10.21203/rs.3.rs-8013724/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8013724/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground and Aims:\u003c/h2\u003e\u003cp\u003eUnderstanding the adaptation strategies of plants to heterogeneous environments is crucial for elucidating plant and community distribution and dynamics. Rhizosphere effects (REs) and plant functional traits (PFTs) are key components of plant adaptation strategies, but their synergistic contributions remain poorly understood. In this study, we selected \u003cem\u003eSuaeda salsa\u003c/em\u003e, the pioneer species in coastal wetlands, to explore its ecological adaptation strategies under complex habitats.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe conducted a field experiment in the Yellow River Delta, selecting three sites with distinct salinity levels. REs, the key PFTs and soil microbial community compositions of rhizosphere soil (RS) and bulk soil (BS) of \u003cem\u003eS. salsa\u003c/em\u003e were quantified.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eRS maintained lower soil pH, while higher soil moisture content, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N content and enzyme activities than BS. Soil microbial communities in RS were also more stabilized and stress-resilient. Concurrently, PFTs shifted under higher salinity. The increased specific leaf area, tissue proline content and sodium to potassium ratio indicate a resource-conservation strategy with enhanced osmotic adjustment. Soil NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and salinity were the most two important factors affecting the growth of \u003cem\u003eS. salsa\u003c/em\u003e. Interestingly, we found a significantly negative correlation between soil salinity and plant individual biomass, which means smaller individuals tend to exhibit stronger rhizosphere-mediated responses to salt stress.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study demonstrates the multidimensional integration strategy of \u003cem\u003eS. salsa\u003c/em\u003e through both rhizosphere optimization and physiological trait plasticity. This mechanistic insight improves understanding of halophyte adaptation and informs strategies for restoring degraded coastal ecosystems.\u003c/p\u003e","manuscriptTitle":"Rhizosphere effects and plant functional traits collectively determine the ecological strategy of Suaeda salsa across heterogeneous habitats in the Yellow River Delta","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-24 13:11:36","doi":"10.21203/rs.3.rs-8013724/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2026-01-03T16:53:38+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-11-13T02:16:14+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-12T15:46:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Plant and Soil","date":"2025-11-10T07:58:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-10T04:46:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant and Soil","date":"2025-11-06T03:38:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1ae3a51c-9d2c-4c81-916a-28449928c4a2","owner":[],"postedDate":"November 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-20T16:00:13+00:00","versionOfRecord":{"articleIdentity":"rs-8013724","link":"https://doi.org/10.1007/s11104-026-08566-9","journal":{"identity":"plant-and-soil","isVorOnly":false,"title":"Plant and Soil"},"publishedOn":"2026-04-16 15:57:08","publishedOnDateReadable":"April 16th, 2026"},"versionCreatedAt":"2025-11-24 13:11:36","video":"","vorDoi":"10.1007/s11104-026-08566-9","vorDoiUrl":"https://doi.org/10.1007/s11104-026-08566-9","workflowStages":[]},"version":"v1","identity":"rs-8013724","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8013724","identity":"rs-8013724","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}