AM fungi and pathogen dissimilarity predicting plant-microbial interactions strength in graminoids and forbs

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The colonization of arbuscular mycorrhizal (AM) fungi and pathogen are often used to speculate on the effects of microorganisms on plant growth, i.e. plant-microbial interactions (PMI). However, empirical studies demonstrate the relationship between AM fungi or pathogen and PMI effects remains limited, especially under different biotic and abiotic conditions. Here, we evaluated the colonization rates of AM fungi and pathogen across 13 grassland species under individual or communal conditions, in both overgrazed and restored soil. Furthermore, we investigated the relationship between AM fungi or pathogen and PMI. Our results showed that forbs exhibited significantly higher rates of AM fungal colonization compared to graminoids in community condition and overgrazed soil while graminoid roots showed higher pathogen infestation compared to forbs in individual condition and overgrazed soil. Generally, there was a positive correlation between PMI and AM fungal colonization but a negative correlation between PMI and pathogen disease. The PMI of graminoids exhibited a negative correlation with pathogen disease in individual condition and overgrazed soil, but showed no correlation with AM fungal colonization. On the other hand, the PMI of forbs showed a positive correlation with AM colonization in both restored and overgrazed soil, as well as in both individual and community experiments. However, there was no correlation between PMI of forbs and pathogen disease. The PMI of graminoids and forbs in grassland ecosystems can be driven by distinct soil microorganisms. These insights enable us to better understand how soil mutualists and pathogen mediate PMI effects on plant growth, with implications for grassland management and restoration. plant-microbial interactions AM fungi pathogen functional group steppe Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Soil microbial communities play key roles in facilitating host nutrient absorption, growth, and physiological processes (Li et al. 2019b ), ultimately shaping plant community structure (Rasmussen et al. 2020 ). The plant-soil feedback (PSF) theory provides a powerful framework for understanding how plants respond to soil microbial communities that are modified by plants growing in that soil (Crawford et al. 2019 ). Accumulating evidence supports the contribution of PSF in ecological processes, such as interspecific competition (Xue et al. 2018a , b ), community succession (Zhang et al. 2021 ; Yandi et al. 2023 ), species coexistence (Li et al. 2020 ; in ’t Zandt et al. 2021 ), and so on. PSF can range from positive to negative. Positive PSF occurs when plants perform better in soils conditioned by themselves vs another species or sterilized soil, and negative PSF occurs if plants influence soil communities to suppress conspecific plants (Bever 2003 ). Positive and negative PSF are commonly linked to plant species co-existence, since dominant plants in a stable community often suffer from negative PSF, while other rare species benefit from positive plant-soil microbial feedbacks (Li et al. 2020 ). In PSF framework, symbionts, enemies and decomposers are considered as the main biotic mechanisms of PSF effects (van der Putten et al. 2016 ). Mutualists such as mycorrhizal fungi are often essential for plant nutrition and contribute to plant drought tolerance and pathogen resistance (Stevens et al. 2018 ; Tedersoo et al. 2020 ). This mutualistic interaction can lead to positive feedback such that reduce plant diversity, as the competitive ability of the plant species with strong mycorrhizal responses will be increased, suppressing other plant species in the community (Johnson et al. 2013 ). Conversely, mycorrhizal fungi can also increase plant diversity by promoting subdominant plant species. For example, mycorrhizal inoculation enhances community diversity during a short term succession process (Koziol and Bever 2019 ). Enemies, such as pathogen, are the main factors responsible for the negative PSF, as they reduce plant performance at multiple life history stages (Bennett and Klironomos 2019 ). The PSF driven by soil-borne pathogen is regarded as an important driver of species abundance (Mangan et al. 2010 ; Kempel et al. 2018 ), plant species coexistence (Bever et al. 2015 ), plant community diversity (Mommer et al. 2018 ), and community succession (Pfennigwerth et al. 2018 ). Most speculations of arbuscular mycorrhizal (AM) fungi and pathogen driving PSF were illustrated in some reviews (Bennett and Klironomos 2019 ), and few researches illustrated the positive role of AM fungi in PSF by treating soil with the fungicide triadimenol (García-Parisi and Omacini 2017 ). To date, few empirical studies have quantitatively considered the role of both AM fungi and pathogen in mediating the strength of PSF. The interaction between plants and microorganisms is significantly influenced by biotic or abiotic factors (Smith-Ramesh and Reynolds 2017 ; Lekberg et al. 2018 ) .Increased soil nutrient availability can shift plant-mycorrhizal interaction from mutualistic to parasitic (Jiang et al. 2017 ) and favor pathogen (Wedekind et al. 2010 ), thus reducing positive plant-microbial interactions (van der Putten et al. 2016 ). Conversely, higher soil fertility may result in less negative PSF by increasing plant defenses (Smith-Ramesh and Reynolds 2017 ). Generally, the modification of PSF by soil nutrient availability is likely linked to the competitive ability of plant species (Larios and Suding 2015 ). Higher soil nutrient levels can weaken negative PSF effects of high nutrient-demanding species, which tend to become superior competitors after nutrient enrichment (Klinerová and Dostál 2020 ). In addition, interspecific competition can also affect PSF by shaping resource availability (Beals et al. 2020 ). Dostál ( 2021 ) demonstrated the effects of nutrient availability and competition type on the PSF strength (Dostál 2021 ), but so far, the combined effects of soil nutrient availability and interspecific competition on PSF are still poorly explored in a high diversity community. Further, the role of AM fungi and pathogen in this process are incompletely understood. Here, we conducted a fully reciprocal experiment to explore the relationship between AM fungi or pathogen and PSF, and how they are associated with the responses of soil nutrient availability, in both no-competition or competition conditions. To this end, we cultivated plants of 13 grass species in live and sterilized soil, which were grown alone and together with interspecific competitor plants two different nutrient levels of soil. Soil microorganism inoculation was carried out by introducing sterile or unsterilized field soil in situ into sterile field soil. This approach allows us to investigate the impact of soil microorganism variations resulting from diverse steppe plant communities on plant growth. Given the absence of a standard training process for plant-soil feedback tests, we will use the term plant-microorganism interaction (PMI) to refer to this phenomenon. We aimed to answer the following specific questions: (1) How do interspecific competition and soil nutrient availability impact PMI, AM fungal colonization, and root disease severity? (2) Whether AM fungal colonization and root disease severity of plants modulate plant-soil microbial interaction? Are these relationships changed by interspecific competition and soil nutrient availability? Methods STUDY SYSTEM The experiments described here are based on our previous study (Li et al. 2020 ). We selected 13 grass species (4 graminoids and 9 forbs) commonly found in the steppe of China, with Leymus chinensis as the dominant species. Graminoids include Leymus chinensis , Elymus dahuricus , Stipa capillata and Agropyron cristatum , and forbs include Thermopsis lanceolata , Taraxacum mongolicum , Heteropappus hispidus , Saussurea japonica , Lepidium apetalum , Allium mongolicum , Sanguisorba officinalis , Erodium stephanianum and Plantago asiatica . Soil for inoculation and substrates were collected from the National Field Station of Grassland Ecosystem (Guyuan, Hebei province, China, 41°46′ N, 115°40′E) in July 2017. We used soil collected from overgrazed grassland (> 30 years) as a low-nutrient condition substrate, and soil obtained from restored grassland (>10 years) as a high-nutrient condition substrate. The inoculation soil was collected from restored grassland. The restored soil exhibited relatively higher soil nutrient levels compared to the overgrazed soil (Li et al. 2020 ). All soils were excavated from the top 20 cm, and the substrate soil and the inoculum soil used as controls were sterilized in an autoclave (120 min, 121°C, 103 kPa). PLANT-MICROBIAL INTERACTIONS All seeds were collected in the field in autumn and surface-sterilized by 75% ethanol and then 10% ‘84 disinfector’. We use wet filter paper or sterilized soil to germinate the seeds, and transplant them when the roots reach about 2 cm in length. In individual experiment, one seed from each species was transplanted into a single pot containing a 500 ml mixture of sterilized substrate and living or sterilized inoculum (6:1 V: V). Sterilized substrate is composed of sterilized field soil and sterilized fine vermiculite (2:1 V: V). In a community experiment, 13 species were established together in a pot containing 4500 ml of soil mixture. In general, we set two soil nutrient levels and two soil microbial conditions, with 3 replicates per treatment, resulting in a total of 156 individual pots (2 soil substrates × 2 soil microbial conditions × 13 plant species × 3 replicates) ་ 12 community pots (2 soil substrates × 2 soil microbial conditions × 3 replicates). PLANT MEASUREMENTS Plants were grown for 4 months after transplant. At harvest, the aboveground plant biomass was clipped flush with the soil, and the weight of the dried shoots for each species was measured separately after drying for 48 hours at 65°C. Fifty1-cm segments of each plant were used to estimate root disease and AM fungal root colonization. We visually quantified the incidence of root disease. The brown area was considered as disease (Schnitzer et al., 2011). For AM fungal colonization analysis, root segments were washed in 10% KOH at 90 ℃ until pellucid (about 1–2 h), followed by a rinse in deionized water, soaking in 2% HCl for 5 min, and staining with 0.05% Trypan blue for 90 min. Prior to microscopy, the root segments were soaked in a Glycerol-Lactic Acid solution for over 60 minutes (Trouvelot et al. 1986). DATA ANALYSIS Soil microbial effects were quantitatively represented as PMI (PMI = ln plant biomass in living soil - ln plant biomass in sterilized soil ). An index value greater than zero indicates a positive PMI, while a negative value indicates a negative PMI (Lepinay et al. 2018 ). We used a three-way ANOVA to analyze the effects of species, interspecific competition, soil substrates and their interactions on PMI, AM fungal colonization, and pathogen diseases. The effects of interspecific competition or soil substrates on PMI were analyzed using a t-test, and the differences in PMI, AM fungal colonization, and pathogen diseases were assessed between graminoids and forbs, as well as between overgrazed soil and restored soil, or between individual condition and community condition. Pearson correlation was employed to examine the relationship between PMI and AM fungal colonization or pathogen diseases in different treatments. Statistical analyses were performed using the statistical software R ver. 4.3.1 ‘car’, ‘pwr’ and ‘psych’. Results PLANT-MICROBIAL INTERACTIONS The strength of plant-microbial interactions (PMI) had significant difference between plant species, but not modified by interspecific competition and soil nutrient availability (Table 1 ). Interspecific competition had interaction effects with species (Table 1 , P < 0.001), for example, L.chinensis and E. dahuricus suffered more negative PMI in community experiment, while T. mongolicum and L. apetalum received more benefits from soil microorganisms in community experiment than individual experiment (Fig. 1 ). Plant functional group was found to be an important factor influencing the direction of PMI ( P < 0.001). Generally, graminoids exhibited a negative response to soil microorganisms, while forbs benefited from them (Fig. 2 ), interspecific competition strengthen the PMI. AM FUNGAL COLONIZATION AND ROOT DISEASE SEVERITY AM fungal colonization rate and percentage of disease roots among species were variable, and not affected by soil substrates origin (Table 1 ). Interspecific competition had a strong effect on AM fungal colonization rate (Table 1 ), with A. cris and H. hisp in restored soil and T. mong , H. hisp and S. offi in overgrazed soil showing a significant increased colonization rate in community experiment, while colonization rate decreased for S. japo in overgrazed soil (Fig. 3 ). Disease roots percentage was not modified by interspecific competition, but the species × interspecific competition interaction was significant (Table 1 ). Root disease incidence of specific species showed similar changes both in restored and overgrazed soil, with L. chin , S. capi , S. japo , A. mong and P. asia suffering alleviated disease in community experiment, while the others suffered more serious disease. At the functional group level (Fig. 4 ), there were significant difference of AM fungal colonization rate (ANOVA, P = 0.03) and percentage of disease roots (ANOVA, P < 0.001) between graminoids and forbs. AM fungal colonization rate of graminoids were not modified by interspecific competition (paired samples test, restored soil P = 0.49, overgrazed soil P = 0.81). In community experiments, forbs showed approximately 18.1% more AMF colonization rate than in individual experiments, both in restored ( P = 0.08) and overgrazed soil ( P = 0.07). No significant effects of interspecific competition on PDR (percentage of disease roots) of graminoids and forbs were detected, but graminoids suffered from 15.8% and 28.9% less disease incidence in community experiment vs. individual experiment respectively in restored soil and overgrazed soil. RELATIONSHIPS BETWEEN PMI AND AMF OR PATHOGEN We tested whether AM fungal colonization rate and percentage of disease roots are associated with the strength of PMI, and if these relationships were influenced by interspecific competition under varying soil nutrient availability. In general, the strength of PMI positively related with AM fungal colonization rate, especially in overgrazed soil or in community experiment (Table 2 , Fig. 5 ). Specific to functional groups, AM fungal colonization rate had no significant effects on the PMI of graminoids, but it played key and positive roles in forbs-microbial interactions. Both lower soil nutrient availability and interspecific competition reinforce this relationship. Taking all 13 species into account, negative relationship between percentage of disease roots and PMI was found in individual experiments (Table 2 , Fig. 6 ). Further, negative PMI of graminoids was enhanced significantly with increased root disease severity ( P = 0.008), but only in the individual experiment and low soil nutrient context. Forbs suffered less root disease severity than graminoids, while no relationship between percentage of disease roots and PMI was found. Discussion AM fungi can contribute positively to PMI due to their role in resource access and disease resistance, whereas pathogen give rise to negative PMI by causing root diseases (Schroeder et al. 2020 ). Our empirically results showed a statistical positive correlation between AM fungal colonization and PMI, as well as a negative correlation between pathogen disease and PMI. These observed relationships were largely caused by the difference between graminoids and forbs. Moreover, the correlativity between AM fungal colonization or pathogen disease and PMI varied for graminoids and forbs, indication that the relationship between PMI and its driving factors may vary depending on the plant functional group being considered. Additionally, interspecific competition and soil nutrient availability also play significant roles in this dynamic interaction. For example, the disease severity of graminoids was statistically negative related to their PMI effects in individual experiments in overgrazed soil, while the colonization of AM fungi was more positively related to the PMI of forbs in community experiment. Overall, we found that graminoids were suppressed by harmful microorganisms, particularly in resource limited context, whereas forbs benefited from AM fungi. These linkages between soil microorganisms and PMI can aid in the management and restoration of grassland vegetation by targeting specific plant function groups. Various plant-microbial interactions among different plant species contribute fundamentally to community diversity (Stein and Mangan 2020 ). Our findings reveal that L. chin , which is overwhelmingly dominant in steppe grassland of northern China, suffered from a negative PMI, suggesting that soil microorganisms suppress the growth of L. chin. This suppression may facilitate community richness by creating low-competitive conditions for other plant species. This phenomenon aligns with the concept of negative PMI, also known as PSF, frequently occurs when plant seedlings grow in conspecific soil (Mangan et al. 2010 ). Considering that our soil samples were collected from a grassland perennially dominant by L. chin (biomass accounting for > 40%), it is an unsurprising result that strong negative PMI would be exerted on L. chin . For other graminoids, E. dahu and A. cris exhibited a propensity for experiencing negative PMI, whereas the biomass of S. capi appeared to be simply reduced by soil microorganisms in overgrazed soil. According to previous studies, plant species that are closely related are more likely to have natural enemies (Kamble et al. 2024 ) and show more similar feedback effects due to their longer shared evolutionary history (Münzbergová and Šurinová 2015 ). Moreover, graminoids generally release similar semi-polar metabolites to each other (Dietz et al. 2019 , 2020 ). which are related to shaping soil microbial communities (Badri and Vivanco 2009 ). Our results showed that E. dahu and A. cris generally experienced a more comparable PMI with L. chin as compared to S. capi , possibly due to their close relation. Specifically, E. dahu , A. cris and L. chin were categorized as Triticeae while S. capi was classified as Stipeae. In contrast, eight plant forbs, with the exception of L. apet , exhibited a tendency to experience positive PMI, indicating that they were able to derive benefits from soil microorganisms. At the level of plant functional group, forbs suffered a more pronounced positive PMI compared to graminoids. This phenomenon could be attributed to the absence of specific pathogen that target forbs in the soil, as well as the relatively weaker nutrient competition ability of forbs (Li et al. 2020 ), which result in a greater reliance on mutualistic microorganisms for nutritional support. We conducted measurements of AM fungal colonization and the percentage of root disease in order to evaluate the mutualistic or antagonistic relationships between plant and soil microorganisms, as previously mentioned. The results revealed a significantly higher colonization rate of AM Fungi in forbs compared to graminoids in community experiments conducted under low nutrient level. Furthermore, forbs showed a significant positive correlation between PMI and AM fungal colonization in all biological (individual and community experiments) and abiotic treatments (restored and overgrazed soil), whereas the PMI of graminoids was not affected by AM Fungi. These results statistically suggested a weak effect of AM fungi on the growth of graminoids, correspond to the patterns that C3 grasses exhibited smaller responses to mycorrhizal inoculation than C4 grasses and non-N-fixing plants(Hoeksema et al. 2010 ), with the graminoids selected in this experiment following the C3 photosynthetic pathway. This weak effect of AM fungi on the growth of graminoids could also potentially be attributed to differences in root structures and physiology (Güsewell 2004 ), and the resulting nutrient uptake strategies. Specifically, AM fungi could benefit plants by enhancing their nutrient access through the exploration of hyphae in plant-fungal symbiosis (Bueno de Mesquita et al. 2018 ; Li et al. 2019a ). The lush root system of graminoids, particularly their fibrous root system, enables them to rapidly occupy soil space and efficiently absorb nutrients, whereas the root system of forbs is comparatively smaller in size, potentially limiting their nutrient uptake. Within the confined microcosmic system of our experiment, the expansive distribution of graminoids across a considerable soil has the potential to hinder the involvement of AM fungi in nutrient uptake processes. Conversely, forbs with their more restricted root range might exhibit a more pronounced increase in plant nutrient absorption facilitated by the hyphae. In individual experiments, it was observed that graminoids exhibited a higher percentage of root diseases caused by pathogen compared to forbs. This could be attributed to the legacy of a grassland plant community that was dominated by L. chin , which made the graminoids more susceptible to these diseases. We detected a significant negative linear relationship between the PMI of graminoids and the percentage of pathogen-induced diseases under overgrazed soil conditions. However, the PMI of forbs did not show any changes with respect to diseases percentage. This finding suggested that the PMI of graminoids was more reliant on their resistance to pathogen, particularly when these plants were unable to obtain sufficient nutrients. Gramineous plants in our research could be regarded as being ‘fast’ species with a high root length (Cortois et al. 2016 ). When nutrients in the soil are insufficient, their growth may be limited, resulting in a weakened immune system and increased susceptibility. On the other hand, ‘slow’ species such as forbs showed slower growth but higher disease resistance, which explains the lack of correlation between the PMI of forbs and pathogen diseases. Further, we did not observe significant effects of soil nutrients on AM fungal colonization and pathogen diseases, nor did we observe significant effects of interspecific competition on pathogen diseases. In our research, restored soil was consider to be more resource-rich than overgrazed soil, with the presents of interspecific competition allowed graminoids to obtain more resources. On the other hand, forbs were subject to greater resource competition influenced by variations in plant competitiveness, supporting the notion that the intensity of competition is similar along a resource gradient. These findings contradict the expectations of Lekberg et al. ( 2018 ), who predicted that plant-soil microbial interaction would be more negative in high resource environments (Lekberg et al. 2018 ). Additionally, these finds do not align with the results of Klinerova and Dostal (2019), who suggested that nutrient-demanding species would experience less negative plant-soil feedback (Klinerová and Dostál 2020 ). Nevertheless, we did find that the relationship between PMI and AM fungi or pathogen, which indicates the dependence of plant growth on specific microorganisms, could be influenced by soil nutrients and interspecific competition. In the case of plants grown in overgrazed soil and with interspecific competitors, the relationship between the PMI of forbs and AM fungi became even stronger compared to plants grown in restored soil and grown alone. We attributed this result in Plant's dependence to mycorrhizal fungi is enhanced in low-nutrient environments (Schultz et al. 2001 ). Parallelly, the relationship between the PMI of graminoids and root diseases was found to be significantly only in overgrazed soil and in individual experiment. This suggests that plant resistance to pathogen is enhanced by higher nutrient levels. Conclusion The interactions among plants, mutualists, and antagonists within the plant-soil microorganism system are highly intricate, posing a challenge in identifying the primary driving factor of plant-soil microorganism interactions (PMI). In this study, we propose an empirical approach to shed light on the outcomes of PMI by examining the relationship between PMI strength and colonization by AM fungi or pathogen. By considering the diversity of 13 grass species, two soil contexts, and two community conditions, we found that graminoids experienced a higher incidence of pathogen diseases, while forbs benefitted more from AM fungi. The PMI of graminoids appeared to be influenced by antagonists, whereas forbs relied on mutualists. We observed that these relationships were enhanced by low soil nutrient levels and interspecific competition. We argue that this conceptual framework could offer a more mechanistic understanding of plant-soil microorganism interactions. Additionally, we propose that colonization by AM fungi or pathogen may serve as key predictors of the direction and strength of PMI, but vary depending on the plant functional groups. Table 1 Three-way analysis of variance (ANOVA) for the effects of species, competition, soil substrates and their interactions on PMI, colonization rate of AM fungi (CAM) and percentage of disease roots (PDR) PMI CAM PDR Source of variation F p F p F p Species 12.171 < 0.001 12.063 < 0.001 12.171 < 0.001 Competition 0.002 0.966 7.167 0.009 0.002 0.966 Soil substrates (SS) 1.844 0.178 0.444 0.507 1.844 0.178 Species*Competition 8.203 < 0.001 1.641 0.092 8.203 < 0.001 SS*Species 0.912 0.538 0.981 0.472 0.912 0.538 Competition*SS 0.528 0.469 0.439 0.509 0.528 0.469 Species*Competition*SS 0.607 0.831 0.776 0.674 0.607 0.831 Statistically significant sources of variation are in bold ( p <0.05) Table 2 Pearson relationship between PMI and colonization rate of AM fungi (CAM) or percentage of disease roots (PDR) among different functional groups Individual experiments Community experiments r p r p Restored soil Total CAM-PMI 0.274 0.096 0.352 0.033 PDR-PMI -0.302 0.065 -0.229 0.187 Graminoids CAM-PMI -0.099 0.76 0.453 0.139 PDR-PMI 0.485 0.11 0.390 0.265 Forbs CAM-PMI 0.367 0.065 0.406 0.044 PDR-PMI -0.161 0.433 -0.263 0.203 Overgrazed soil Total CAM-PMI 0.432 0.006 0.156 0.002 PDR-PMI -0.472 0.002 -0.215 0.230 Graminoids CAM-PMI 0.371 0.235 0.204 0.524 PDR-PMI -0.719 0.008 0.119 0.728 Forbs CAM-PMI 0.414 0.032 0.516 0.002 PDR-PMI -0.252 0.205 -0.215 0.230 Statistically significant sources of variation are in bold ( p <0.05), and r means correlation index Declarations Author Contribution J.L. conceived and performed experiments. Z.D. performed experiments and wrote the manuscript. L.G. and B.R. provided advice on editorial guidance and edited language. S.Q. and L.B. provided advice on edited language. All authors commented on the manuscript and approved the final version. References Badri D V., Vivanco JM (2009) Regulation and function of root exudates. Plant, Cell Environ 32:666–681. https://doi.org/10.1111/j.1365-3040.2009.01926.x Beals KK, Moore JAM, Kivlin SN, et al (2020) Predicting plant-soil feedback in the field: Meta-analysis reveals that competition and environmental stress differentially influence psf. Front Ecol Evol 8:191. https://doi.org/10.3389/fevo.2020.00191 Bennett JA, Klironomos J (2019) Mechanisms of plant–soil feedback: interactions among biotic and abiotic drivers. New Phytol 222:91–96. https://doi.org/10.1111/nph.15603 Bever JD (2003) Soil community feedback and the coexistence of competitors: Conceptual frameworks and empirical tests. New Phytol 157:465–473. https://doi.org/10.1046/j.1469-8137.2003.00714.x Bever JD, Mangan SA, Alexander HM (2015) Maintenance of Plant Species Diversity by Pathogens. Annu Rev Ecol Evol Syst 46:305–325. https://doi.org/10.1146/annurev-ecolsys-112414-054306 Bueno de Mesquita CP, Martinez del Río CM, Suding KN, Schmidt SK (2018) Rapid temporal changes in root colonization by arbuscular mycorrhizal fungi and fine root endophytes, not dark septate endophytes, track plant activity and environment in an alpine ecosystem. Mycorrhiza 28:717–726. https://doi.org/10.1007/s00572-018-0863-7 Cortois R, Schröder-Georgi T, Weigelt A, et al (2016) Plant–soil feedbacks: role of plant functional group and plant traits. J Ecol 104:1608–1617. https://doi.org/10.1111/1365-2745.12643 Crawford KM, Bauer JT, Comita LS, et al (2019) When and where plant-soil feedback may promote plant coexistence: a meta-analysis. Ecol Lett 22:1274–1284. https://doi.org/10.1111/ele.13278 Dietz S, Herz K, Döll S, et al (2019) Semi-polar root exudates in natural grassland communities. Ecol Evol 9:5526–5541. https://doi.org/10.1002/ece3.5043 Dietz S, Herz K, Gorzolka K, et al (2020) Root exudate composition of grass and forb species in natural grasslands. Sci Rep 10:10691. https://doi.org/10.1038/s41598-019-54309-5 Dostál P (2021) The temporal development of plant-soil feedback is contingent on competition and nutrient availability contexts. Oecologia 196:185–194. https://doi.org/10.1007/s00442-021-04919-6 García-Parisi PA, Omacini M (2017) Arbuscular mycorrhizal fungi can shift plant-soil feedback of grass-endophyte symbiosis from negative to positive. Plant Soil 419:13–23. https://doi.org/10.1007/s11104-017-3216-y Güsewell S (2004) N:P ratios in terrestrial plants: Variation and functional significance. New Phytol 164:243–266. https://doi.org/10.1111/j.1469-8137.2004.01192.x Hoeksema JD, Chaudhary VB, Gehring CA, et al (2010) A meta-analysis of context-dependency in plant response to inoculation with mycorrhizal fungi. Ecol Lett 13:394–407. https://doi.org/10.1111/j.1461-0248.2009.01430.x in ’t Zandt D, Herben T, van den Brink A, et al (2021) Species abundance fluctuations over 31 years are associated with plant–soil feedback in a species-rich mountain meadow. J Ecol 109:1511–1523. https://doi.org/10.1111/1365-2745.13574 Jiang J, Moore JAM, Priyadarshi A, Classen AT (2017) Plant-mycorrhizal interactions mediate plant community coexistence by altering resource demand. Ecology 98:187–197. https://doi.org/10.1002/ecy.1630 Johnson NC, Angelard C, Sanders IR, Kiers ET (2013) Predicting community and ecosystem outcomes of mycorrhizal responses to global change. Ecol Lett 16:140–153. https://doi.org/10.1111/ele.12085 Kamble A, Michavila S, Gimenez-Ibanez S, Redkar A (2024) Shared infection strategy of a fungal pathogen across diverse lineages of land plants, the Fusarium example. Curr Opin Plant Biol 77:102498. https://doi.org/10.1016/j.pbi.2023.102498 Kempel A, Rindisbacher A, Fischer M, Allan E (2018) Plant soil feedback strength in relation to large-scale plant rarity and phylogenetic relatedness. Ecology 99:597–606. https://doi.org/10.1002/ecy.2145 Klinerová T, Dostál P (2020) Nutrient-demanding species face less negative competition and plant–soil feedback effects in a nutrient-rich environment. New Phytol 225:1343–1354. https://doi.org/10.1111/nph.16227 Koziol L, Bever JD (2019) Mycorrhizal feedbacks generate positive frequency dependence accelerating grassland succession. J Ecol 107:622–632. https://doi.org/10.1111/1365-2745.13063 Larios L, Suding KN (2015) Competition and soil resource environment alter plant-soil feedbacks for native and exotic grasses. AoB Plants 7:plu077. https://doi.org/10.1093/aobpla/plu077 Lekberg Y, Bever JD, Bunn RA, et al (2018) Relative importance of competition and plant–soil feedback, their synergy, context dependency and implications for coexistence. Ecol Lett 21:1268–1281. https://doi.org/10.1111/ele.13093 Lepinay C, Vondráková Z, Dostálek T, Münzbergová Z (2018) Duration of the conditioning phase affects the results of plant-soil feedback experiments via soil chemical properties. Oecologia 186:459–470. https://doi.org/10.1007/s00442-017-4033-y Li J, Meng B, Chai H, et al (2019a) Arbuscular mycorrhizal fungi alleviate drought stress in C3 (Leymus chinensis) and C4 (hemarthria altissima) grasses via altering antioxidant enzyme activities and photosynthesis. Front Plant Sci 10:499. https://doi.org/10.3389/fpls.2019.00499 Li J, Xie S, Wilson GWT, et al (2020) Plant–microbial interactions facilitate grassland species coexistence at the community level. Oikos 129:533–543. https://doi.org/10.1111/oik.06609 Li X, Jousset A, de Boer W, et al (2019b) Legacy of land use history determines reprogramming of plant physiology by soil microbiome. ISME J 13:738–751. https://doi.org/10.1038/s41396-018-0300-0 Mangan SA, Schnitzer SA, Herre EA, et al (2010) Negative plant-soil feedback predicts tree-species relative abundance in a tropical forest. Nature 466:752–755. https://doi.org/10.1038/nature09273 Mommer L, Cotton TEA, Raaijmakers JM, et al (2018) Lost in diversity: the interactions between soil-borne fungi, biodiversity and plant productivity. New Phytol 218:542–553. https://doi.org/10.1111/nph.15036 Münzbergová Z, Šurinová M (2015) The importance of species phylogenetic relationships and species traits for the intensity of plant-soil feedback. Ecosphere 6(11):234. https://doi.org/10.1890/ES15-00206.1 Pfennigwerth AA, Van Nuland ME, Bailey JK, Schweitzer JA (2018) Plant–soil feedbacks mediate shrub expansion in declining forests, but only in the right light. J Ecol 106:179–194. https://doi.org/10.1111/1365-2745.12833 Rasmussen PU, Bennett AE, Tack AJM (2020) The impact of elevated temperature and drought on the ecology and evolution of plant–soil microbe interactions. J Ecol 108:337–352. https://doi.org/10.1111/1365-2745.13292 Schroeder JW, Dobson A, Mangan SA, et al (2020) Mutualist and pathogen traits interact to affect plant community structure in a spatially explicit model. Nat Commun 11:2204. https://doi.org/10.1038/s41467-020-16047-5 Schultz PA, Michael Miller R, Jastrow JD, et al (2001) Evidence of a mycorrhizal mechanism for the adaptation of Andropogon gerardii (Poaceae) to high‐ and low‐nutrient prairies . Am J Bot 88:1650–1656. https://doi.org/10.2307/3558410 Smith-Ramesh LM, Reynolds HL (2017) The next frontier of plant–soil feedback research: unraveling context dependence across biotic and abiotic gradients. J Veg Sci 28:484–494. https://doi.org/10.1111/jvs.12519 Stein C, Mangan SA (2020) Soil biota increase the likelihood for coexistence among competing plant species. Ecology 101:1–11. https://doi.org/10.1002/ecy.3147 Stevens BM, Propster J, Wilson GWT, et al (2018) Mycorrhizal symbioses influence the trophic structure of the Serengeti. J Ecol 106:536–546. https://doi.org/10.1111/1365-2745.12916 Tedersoo L, Bahram M, Zobel M (2020) How mycorrhizal associations drive plant population and community biology. Science 367:867–874. https://doi.org/10.1126/science.aba1223 van der Putten WH, Bradford MA, Pernilla Brinkman E, et al (2016) Where, when and how plant–soil feedback matters in a changing world. Funct Ecol 30:1109–1121. https://doi.org/10.1111/1365-2435.12657 Wedekind C, Gessner MO, Vazquez F, et al (2010) Elevated resource availability sufficient to turn opportunistic into virulent fish pathogens. Ecology 91:1251–1256. https://doi.org/10.1890/09-1067.1 Xue W, Berendse F, Bezemer TM (2018a) Spatial heterogeneity in plant–soil feedbacks alters competitive interactions between two grassland plant species. Funct Ecol 32:2085–2094. https://doi.org/10.1111/1365-2435.13124 Xue W, Bezemer TM, Berendse F (2018b) Density-dependency and plant-soil feedback: former plant abundance influences competitive interactions between two grassland plant species through plant-soil feedbacks. Plant Soil 428:441–452. https://doi.org/10.1007/s11104-018-3690-x Yandi S, Tao M, Huakun Z, et al (2023) Characterization of the Plant‒Soil feedback index in alpine meadow degradation and recovery: A field experiment. Front Environ Sci 10:1097030. https://doi.org/10.3389/fenvs.2022.1097030 Zhang J, Ai Z, Xu H, et al (2021) Plant-microbial feedback in secondary succession of semiarid grasslands. Sci Total Environ 760:143389. https://doi.org/10.1016/j.scitotenv.2020.143389 Additional Declarations No competing interests reported. Supplementary Files Supportinginformation.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4157804","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":285699693,"identity":"60873108-545d-4ccd-b7d4-4b8db179297e","order_by":0,"name":"Zijian Ding","email":"","orcid":"","institution":"Shenyang Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Zijian","middleName":"","lastName":"Ding","suffix":""},{"id":285699694,"identity":"d3f7b983-2f03-412c-8041-54e1dd26be21","order_by":1,"name":"Long Bai","email":"","orcid":"","institution":"Shenyang Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Long","middleName":"","lastName":"Bai","suffix":""},{"id":285699695,"identity":"3c3ea819-b11c-4d40-beb7-4562d1dda34b","order_by":2,"name":"Baihui Ren","email":"","orcid":"","institution":"Shenyang Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Baihui","middleName":"","lastName":"Ren","suffix":""},{"id":285699696,"identity":"2533d7d2-619c-45c2-a31c-a5d3ffd23207","order_by":3,"name":"Sijun Qin","email":"","orcid":"","institution":"Shenyang Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Sijun","middleName":"","lastName":"Qin","suffix":""},{"id":285699697,"identity":"0eb94b96-0c75-423b-a893-cd5e598b4830","order_by":4,"name":"Jiahuan Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYBACPmaGNBAtw8/MfPgBUVrYoFp4JNvZ0gyI0wJGQC0G53kUJIjTws7w7MGHGhse48M8DAYMNTbRxDgs3XDGsTQes8O8Bx4wHEvLbSBCS5o0b8NhoBa+BAPGhsNEavkL1GLczGMgQbwWoEoeA2ZStEj2AP0icRgYyAnE+IWf/0yaxI8aGzn+/sOHQUFHWAswRhIQ7ARcilAB+wHi1I2CUTAKRsHIBQBPbzNJzD6ITAAAAABJRU5ErkJggg==","orcid":"","institution":"Shenyang Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Jiahuan","middleName":"","lastName":"Li","suffix":""},{"id":285699698,"identity":"531799b4-9012-4d40-b1cb-7cae787df6c2","order_by":5,"name":"Lizhu Guo","email":"","orcid":"","institution":"Chinese Academy of Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Lizhu","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2024-03-24 11:44:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4157804/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4157804/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53886243,"identity":"6746aad7-b1c5-4136-8645-19587e135e60","added_by":"auto","created_at":"2024-04-01 19:25:39","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":70006,"visible":true,"origin":"","legend":"\u003cp\u003ePlant-microbial interactions (PMI) for 13 species grown in restored and overgrazed soil in our individual and community experiments. Species abbreviations are described in Table S1. Positive or negative PMI are determined by subtracting sterile soil plant biomass (ln transformed) from live (inoculated) soil plant biomass (ln transformed). Significant PMI differences between individual and community experiments are indicated by an asterisk (\u003cem\u003ep \u003c/em\u003e\u0026lt;0.05)\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4157804/v1/028231289c8bd75aa1771b6d.jpeg"},{"id":53886244,"identity":"11f698e4-1478-4a8c-91bc-48be88b1ac6b","added_by":"auto","created_at":"2024-04-01 19:25:39","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":58672,"visible":true,"origin":"","legend":"\u003cp\u003eAverageplant-microbial interactions (PMI) for all plant species in individual (I-T) and community experiments (C-T), for graminoids in individual (I-G) and community experiments (C-G), and for forbs in individual (I-F) and community experiments (C-F) grown in restored and overgrazed soil. Box plots indicate interquartile range in the box area, median is solid line in the box, 25% and 75% percentiles are presented as lower and upper box margins. Significant PMI differences between individual and community experiments are indicated by an asterisk (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Significant PMI differences between graminoids and forbs are indicated by lowercase letter (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05)\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4157804/v1/40ae198daa23b544f631a778.jpeg"},{"id":53886246,"identity":"27b26f2d-13c8-4c4a-b477-ea0fd28f34cb","added_by":"auto","created_at":"2024-04-01 19:25:40","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":109353,"visible":true,"origin":"","legend":"\u003cp\u003eColonization rate of AM fungi (CAM) and percentage of disease roots (PDR) for 13 species \u0026nbsp;grown in restored and overgrazed soil in our individual and community experiments. Species abbreviations are described in Table S1. Significant MC or PDR differences between individual and community experiments are indicated by an asterisk (\u003cem\u003ep \u003c/em\u003e\u0026lt;0.05)\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4157804/v1/9cd9328075fed0ed6aa37a5b.jpeg"},{"id":53886250,"identity":"ba900c48-3f4e-4ccd-bee2-b53f25c0294b","added_by":"auto","created_at":"2024-04-01 19:25:40","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":97209,"visible":true,"origin":"","legend":"\u003cp\u003eColonization rate of AM fungi (CAM) and percentage of disease roots (PDR) for all plant species in individual (I-T) and community experiments (C-T), for graminoids in individual (I-G) and community experiments (C-G), and for forbs in individual (I-F) and community experiments (C-F) grown in restored and overgrazed soil. Box plots indicate interquartile range in the box area, median is solid line in the box, 25% and 75% percentiles are presented as lower and upper box margins. Significant PMI differences between individual and community experiments are indicated by an asterisk (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Significant PMI differences between graminoids and forbs are indicated by lowercase letter (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05)\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4157804/v1/f2f06dca75d88c3be5fc2ec5.jpeg"},{"id":53886248,"identity":"6f18eb38-cfa0-46a1-a048-d84040add945","added_by":"auto","created_at":"2024-04-01 19:25:40","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":96958,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between plant–microbial interactions (PMI) and colonization rate of AM fungi (CAM) in individual and community experiments with two soil substrates. Linear regression model analyses were utilized and the solid line indicates a significant correlation\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4157804/v1/d06b1cdb438d25aeca98b802.jpeg"},{"id":53886245,"identity":"5904d388-9b82-4293-b04c-bb80e22d31fa","added_by":"auto","created_at":"2024-04-01 19:25:39","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":101650,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between plant–microbial interactions (PMI) and percentage of disease roots (PDR) in individual and community experiments with two soil substrates. Linear regression model analyses were utilized and the solid line indicates a significant correlation\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4157804/v1/b15de71f0ca0f10278b320ef.jpeg"},{"id":56315438,"identity":"cc0c606a-46dd-4d3f-8586-421368a6e40d","added_by":"auto","created_at":"2024-05-11 19:31:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":960944,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4157804/v1/ff2f7bb2-5388-4c78-8744-e6751b1aa6bf.pdf"},{"id":53886242,"identity":"bbb5d1d3-76f6-475a-9b2c-253fcdf4ec48","added_by":"auto","created_at":"2024-04-01 19:25:39","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15528,"visible":true,"origin":"","legend":"","description":"","filename":"Supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-4157804/v1/0b0e9be8b5de3d8e3751706d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"AM fungi and pathogen dissimilarity predicting plant-microbial interactions strength in graminoids and forbs","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSoil microbial communities play key roles in facilitating host nutrient absorption, growth, and physiological processes (Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e), ultimately shaping plant community structure (Rasmussen et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The plant-soil feedback (PSF) theory provides a powerful framework for understanding how plants respond to soil microbial communities that are modified by plants growing in that soil (Crawford et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Accumulating evidence supports the contribution of PSF in ecological processes, such as interspecific competition (Xue et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003eb\u003c/span\u003e), community succession (Zhang et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yandi et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), species coexistence (Li et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; in \u0026rsquo;t Zandt et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and so on.\u003c/p\u003e \u003cp\u003ePSF can range from positive to negative. Positive PSF occurs when plants perform better in soils conditioned by themselves vs another species or sterilized soil, and negative PSF occurs if plants influence soil communities to suppress conspecific plants (Bever \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Positive and negative PSF are commonly linked to plant species co-existence, since dominant plants in a stable community often suffer from negative PSF, while other rare species benefit from positive plant-soil microbial feedbacks (Li et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In PSF framework, symbionts, enemies and decomposers are considered as the main biotic mechanisms of PSF effects (van der Putten et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Mutualists such as mycorrhizal fungi are often essential for plant nutrition and contribute to plant drought tolerance and pathogen resistance (Stevens et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Tedersoo et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This mutualistic interaction can lead to positive feedback such that reduce plant diversity, as the competitive ability of the plant species with strong mycorrhizal responses will be increased, suppressing other plant species in the community (Johnson et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Conversely, mycorrhizal fungi can also increase plant diversity by promoting subdominant plant species. For example, mycorrhizal inoculation enhances community diversity during a short term succession process (Koziol and Bever \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Enemies, such as pathogen, are the main factors responsible for the negative PSF, as they reduce plant performance at multiple life history stages (Bennett and Klironomos \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The PSF driven by soil-borne pathogen is regarded as an important driver of species abundance (Mangan et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kempel et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), plant species coexistence (Bever et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), plant community diversity (Mommer et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and community succession (Pfennigwerth et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Most speculations of arbuscular mycorrhizal (AM) fungi and pathogen driving PSF were illustrated in some reviews (Bennett and Klironomos \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and few researches illustrated the positive role of AM fungi in PSF by treating soil with the fungicide triadimenol (Garc\u0026iacute;a-Parisi and Omacini \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). To date, few empirical studies have quantitatively considered the role of both AM fungi and pathogen in mediating the strength of PSF.\u003c/p\u003e \u003cp\u003eThe interaction between plants and microorganisms is significantly influenced by biotic or abiotic factors (Smith-Ramesh and Reynolds \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lekberg et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) .Increased soil nutrient availability can shift plant-mycorrhizal interaction from mutualistic to parasitic (Jiang et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and favor pathogen (Wedekind et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), thus reducing positive plant-microbial interactions (van der Putten et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Conversely, higher soil fertility may result in less negative PSF by increasing plant defenses (Smith-Ramesh and Reynolds \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Generally, the modification of PSF by soil nutrient availability is likely linked to the competitive ability of plant species (Larios and Suding \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Higher soil nutrient levels can weaken negative PSF effects of high nutrient-demanding species, which tend to become superior competitors after nutrient enrichment (Klinerov\u0026aacute; and Dost\u0026aacute;l \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In addition, interspecific competition can also affect PSF by shaping resource availability (Beals et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Dost\u0026aacute;l (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) demonstrated the effects of nutrient availability and competition type on the PSF strength (Dost\u0026aacute;l \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), but so far, the combined effects of soil nutrient availability and interspecific competition on PSF are still poorly explored in a high diversity community. Further, the role of AM fungi and pathogen in this process are incompletely understood. Here, we conducted a fully reciprocal experiment to explore the relationship between AM fungi or pathogen and PSF, and how they are associated with the responses of soil nutrient availability, in both no-competition or competition conditions. To this end, we cultivated plants of 13 grass species in live and sterilized soil, which were grown alone and together with interspecific competitor plants two different nutrient levels of soil. Soil microorganism inoculation was carried out by introducing sterile or unsterilized field soil in situ into sterile field soil. This approach allows us to investigate the impact of soil microorganism variations resulting from diverse steppe plant communities on plant growth. Given the absence of a standard training process for plant-soil feedback tests, we will use the term plant-microorganism interaction (PMI) to refer to this phenomenon. We aimed to answer the following specific questions: (1) How do interspecific competition and soil nutrient availability impact PMI, AM fungal colonization, and root disease severity? (2) Whether AM fungal colonization and root disease severity of plants modulate plant-soil microbial interaction? Are these relationships changed by interspecific competition and soil nutrient availability?\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSTUDY SYSTEM\u003c/h2\u003e \u003cp\u003eThe experiments described here are based on our previous study (Li et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). We selected 13 grass species (4 graminoids and 9 forbs) commonly found in the steppe of China, with \u003cem\u003eLeymus chinensis\u003c/em\u003e as the dominant species. Graminoids include \u003cem\u003eLeymus chinensis\u003c/em\u003e, \u003cem\u003eElymus dahuricus\u003c/em\u003e, \u003cem\u003eStipa capillata\u003c/em\u003e and \u003cem\u003eAgropyron cristatum\u003c/em\u003e, and forbs include \u003cem\u003eThermopsis lanceolata\u003c/em\u003e, \u003cem\u003eTaraxacum mongolicum\u003c/em\u003e, \u003cem\u003eHeteropappus hispidus\u003c/em\u003e, \u003cem\u003eSaussurea japonica\u003c/em\u003e, \u003cem\u003eLepidium apetalum\u003c/em\u003e, \u003cem\u003eAllium mongolicum\u003c/em\u003e, \u003cem\u003eSanguisorba officinalis\u003c/em\u003e, \u003cem\u003eErodium stephanianum\u003c/em\u003e and \u003cem\u003ePlantago asiatica\u003c/em\u003e. Soil for inoculation and substrates were collected from the National Field Station of Grassland Ecosystem (Guyuan, Hebei province, China, 41\u0026deg;46\u0026prime; N, 115\u0026deg;40\u0026prime;E) in July 2017. We used soil collected from overgrazed grassland (\u0026gt;\u0026thinsp;30 years) as a low-nutrient condition substrate, and soil obtained from restored grassland (\u0026gt;10 years) as a high-nutrient condition substrate. The inoculation soil was collected from restored grassland. The restored soil exhibited relatively higher soil nutrient levels compared to the overgrazed soil (Li et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). All soils were excavated from the top 20 cm, and the substrate soil and the inoculum soil used as controls were sterilized in an autoclave (120 min, 121\u0026deg;C, 103 kPa).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePLANT-MICROBIAL INTERACTIONS\u003c/h2\u003e \u003cp\u003eAll seeds were collected in the field in autumn and surface-sterilized by 75% ethanol and then 10% \u0026lsquo;84 disinfector\u0026rsquo;. We use wet filter paper or sterilized soil to germinate the seeds, and transplant them when the roots reach about 2 cm in length. In individual experiment, one seed from each species was transplanted into a single pot containing a 500 ml mixture of sterilized substrate and living or sterilized inoculum (6:1 V: V). Sterilized substrate is composed of sterilized field soil and sterilized fine vermiculite (2:1 V: V). In a community experiment, 13 species were established together in a pot containing 4500 ml of soil mixture. In general, we set two soil nutrient levels and two soil microbial conditions, with 3 replicates per treatment, resulting in a total of 156 individual pots (2 soil substrates \u0026times; 2 soil microbial conditions \u0026times; 13 plant species \u0026times; 3 replicates) ་ 12 community pots (2 soil substrates \u0026times; 2 soil microbial conditions \u0026times; 3 replicates).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePLANT MEASUREMENTS\u003c/h2\u003e \u003cp\u003ePlants were grown for 4 months after transplant. At harvest, the aboveground plant biomass was clipped flush with the soil, and the weight of the dried shoots for each species was measured separately after drying for 48 hours at 65\u0026deg;C. Fifty1-cm segments of each plant were used to estimate root disease and AM fungal root colonization. We visually quantified the incidence of root disease. The brown area was considered as disease (Schnitzer et al., 2011). For AM fungal colonization analysis, root segments were washed in 10% KOH at 90 ℃ until pellucid (about 1\u0026ndash;2 h), followed by a rinse in deionized water, soaking in 2% HCl for 5 min, and staining with 0.05% Trypan blue for 90 min. Prior to microscopy, the root segments were soaked in a Glycerol-Lactic Acid solution for over 60 minutes (Trouvelot et al. 1986).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDATA ANALYSIS\u003c/h2\u003e \u003cp\u003eSoil microbial effects were quantitatively represented as PMI (PMI\u0026thinsp;=\u0026thinsp;ln\u003csub\u003eplant biomass in living soil\u003c/sub\u003e - ln\u003csub\u003eplant biomass in sterilized soil\u003c/sub\u003e). An index value greater than zero indicates a positive PMI, while a negative value indicates a negative PMI (Lepinay et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). We used a three-way ANOVA to analyze the effects of species, interspecific competition, soil substrates and their interactions on PMI, AM fungal colonization, and pathogen diseases. The effects of interspecific competition or soil substrates on PMI were analyzed using a t-test, and the differences in PMI, AM fungal colonization, and pathogen diseases were assessed between graminoids and forbs, as well as between overgrazed soil and restored soil, or between individual condition and community condition. Pearson correlation was employed to examine the relationship between PMI and AM fungal colonization or pathogen diseases in different treatments. Statistical analyses were performed using the statistical software R ver. 4.3.1 \u0026lsquo;car\u0026rsquo;, \u0026lsquo;pwr\u0026rsquo; and \u0026lsquo;psych\u0026rsquo;.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePLANT-MICROBIAL INTERACTIONS\u003c/h2\u003e \u003cp\u003eThe strength of plant-microbial interactions (PMI) had significant difference between plant species, but not modified by interspecific competition and soil nutrient availability (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Interspecific competition had interaction effects with species (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), for example, \u003cem\u003eL.chinensis\u003c/em\u003e and \u003cem\u003eE. dahuricus\u003c/em\u003e suffered more negative PMI in community experiment, while \u003cem\u003eT. mongolicum\u003c/em\u003e and \u003cem\u003eL. apetalum\u003c/em\u003e received more benefits from soil microorganisms in community experiment than individual experiment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Plant functional group was found to be an important factor influencing the direction of PMI (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Generally, graminoids exhibited a negative response to soil microorganisms, while forbs benefited from them (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), interspecific competition strengthen the PMI.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eAM FUNGAL COLONIZATION AND ROOT DISEASE SEVERITY\u003c/h2\u003e \u003cp\u003eAM fungal colonization rate and percentage of disease roots among species were variable, and not affected by soil substrates origin (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Interspecific competition had a strong effect on AM fungal colonization rate (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), with \u003cem\u003eA. cris\u003c/em\u003e and \u003cem\u003eH. hisp\u003c/em\u003e in restored soil and \u003cem\u003eT. mong\u003c/em\u003e, \u003cem\u003eH. hisp\u003c/em\u003e and \u003cem\u003eS. offi\u003c/em\u003e in overgrazed soil showing a significant increased colonization rate in community experiment, while colonization rate decreased for \u003cem\u003eS. japo\u003c/em\u003e in overgrazed soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Disease roots percentage was not modified by interspecific competition, but the species \u0026times; interspecific competition interaction was significant (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Root disease incidence of specific species showed similar changes both in restored and overgrazed soil, with \u003cem\u003eL. chin\u003c/em\u003e, \u003cem\u003eS. capi\u003c/em\u003e, \u003cem\u003eS. japo\u003c/em\u003e, \u003cem\u003eA. mong\u003c/em\u003e and \u003cem\u003eP. asia\u003c/em\u003e suffering alleviated disease in community experiment, while the others suffered more serious disease.\u003c/p\u003e \u003cp\u003eAt the functional group level (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), there were significant difference of AM fungal colonization rate (ANOVA, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03) and percentage of disease roots (ANOVA, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) between graminoids and forbs. AM fungal colonization rate of graminoids were not modified by interspecific competition (paired samples test, restored soil \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.49, overgrazed soil \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.81). In community experiments, forbs showed approximately 18.1% more AMF colonization rate than in individual experiments, both in restored (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.08) and overgrazed soil (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07). No significant effects of interspecific competition on PDR (percentage of disease roots) of graminoids and forbs were detected, but graminoids suffered from 15.8% and 28.9% less disease incidence in community experiment vs. individual experiment respectively in restored soil and overgrazed soil.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eRELATIONSHIPS BETWEEN PMI AND AMF OR PATHOGEN\u003c/h2\u003e \u003cp\u003eWe tested whether AM fungal colonization rate and percentage of disease roots are associated with the strength of PMI, and if these relationships were influenced by interspecific competition under varying soil nutrient availability. In general, the strength of PMI positively related with AM fungal colonization rate, especially in overgrazed soil or in community experiment (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Specific to functional groups, AM fungal colonization rate had no significant effects on the PMI of graminoids, but it played key and positive roles in forbs-microbial interactions. Both lower soil nutrient availability and interspecific competition reinforce this relationship.\u003c/p\u003e \u003cp\u003eTaking all 13 species into account, negative relationship between percentage of disease roots and PMI was found in individual experiments (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Further, negative PMI of graminoids was enhanced significantly with increased root disease severity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008), but only in the individual experiment and low soil nutrient context. Forbs suffered less root disease severity than graminoids, while no relationship between percentage of disease roots and PMI was found.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAM fungi can contribute positively to PMI due to their role in resource access and disease resistance, whereas pathogen give rise to negative PMI by causing root diseases (Schroeder et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Our empirically results showed a statistical positive correlation between AM fungal colonization and PMI, as well as a negative correlation between pathogen disease and PMI. These observed relationships were largely caused by the difference between graminoids and forbs. Moreover, the correlativity between AM fungal colonization or pathogen disease and PMI varied for graminoids and forbs, indication that the relationship between PMI and its driving factors may vary depending on the plant functional group being considered. Additionally, interspecific competition and soil nutrient availability also play significant roles in this dynamic interaction. For example, the disease severity of graminoids was statistically negative related to their PMI effects in individual experiments in overgrazed soil, while the colonization of AM fungi was more positively related to the PMI of forbs in community experiment. Overall, we found that graminoids were suppressed by harmful microorganisms, particularly in resource limited context, whereas forbs benefited from AM fungi. These linkages between soil microorganisms and PMI can aid in the management and restoration of grassland vegetation by targeting specific plant function groups.\u003c/p\u003e \u003cp\u003eVarious plant-microbial interactions among different plant species contribute fundamentally to community diversity (Stein and Mangan \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Our findings reveal that \u003cem\u003eL. chin\u003c/em\u003e, which is overwhelmingly dominant in steppe grassland of northern China, suffered from a negative PMI, suggesting that soil microorganisms suppress the growth of \u003cem\u003eL. chin.\u003c/em\u003e This suppression may facilitate community richness by creating low-competitive conditions for other plant species. This phenomenon aligns with the concept of negative PMI, also known as PSF, frequently occurs when plant seedlings grow in conspecific soil (Mangan et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Considering that our soil samples were collected from a grassland perennially dominant by \u003cem\u003eL. chin\u003c/em\u003e (biomass accounting for \u0026gt;\u0026thinsp;40%), it is an unsurprising result that strong negative PMI would be exerted on \u003cem\u003eL. chin\u003c/em\u003e. For other graminoids, \u003cem\u003eE. dahu\u003c/em\u003e and \u003cem\u003eA. cris\u003c/em\u003e exhibited a propensity for experiencing negative PMI, whereas the biomass of \u003cem\u003eS. capi\u003c/em\u003e appeared to be simply reduced by soil microorganisms in overgrazed soil. According to previous studies, plant species that are closely related are more likely to have natural enemies (Kamble et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and show more similar feedback effects due to their longer shared evolutionary history (M\u0026uuml;nzbergov\u0026aacute; and Šurinov\u0026aacute; \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Moreover, graminoids generally release similar semi-polar metabolites to each other (Dietz et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). which are related to shaping soil microbial communities (Badri and Vivanco \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Our results showed that \u003cem\u003eE. dahu\u003c/em\u003e and \u003cem\u003eA. cris\u003c/em\u003e generally experienced a more comparable PMI with \u003cem\u003eL. chin\u003c/em\u003e as compared to \u003cem\u003eS. capi\u003c/em\u003e, possibly due to their close relation. Specifically, \u003cem\u003eE. dahu\u003c/em\u003e, \u003cem\u003eA. cris\u003c/em\u003e and \u003cem\u003eL. chin\u003c/em\u003e were categorized as Triticeae while \u003cem\u003eS. capi\u003c/em\u003e was classified as Stipeae. In contrast, eight plant forbs, with the exception of \u003cem\u003eL. apet\u003c/em\u003e, exhibited a tendency to experience positive PMI, indicating that they were able to derive benefits from soil microorganisms. At the level of plant functional group, forbs suffered a more pronounced positive PMI compared to graminoids. This phenomenon could be attributed to the absence of specific pathogen that target forbs in the soil, as well as the relatively weaker nutrient competition ability of forbs (Li et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which result in a greater reliance on mutualistic microorganisms for nutritional support.\u003c/p\u003e \u003cp\u003eWe conducted measurements of AM fungal colonization and the percentage of root disease in order to evaluate the mutualistic or antagonistic relationships between plant and soil microorganisms, as previously mentioned. The results revealed a significantly higher colonization rate of AM Fungi in forbs compared to graminoids in community experiments conducted under low nutrient level. Furthermore, forbs showed a significant positive correlation between PMI and AM fungal colonization in all biological (individual and community experiments) and abiotic treatments (restored and overgrazed soil), whereas the PMI of graminoids was not affected by AM Fungi. These results statistically suggested a weak effect of AM fungi on the growth of graminoids, correspond to the patterns that C3 grasses exhibited smaller responses to mycorrhizal inoculation than C4 grasses and non-N-fixing plants(Hoeksema et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), with the graminoids selected in this experiment following the C3 photosynthetic pathway. This weak effect of AM fungi on the growth of graminoids could also potentially be attributed to differences in root structures and physiology (G\u0026uuml;sewell \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), and the resulting nutrient uptake strategies. Specifically, AM fungi could benefit plants by enhancing their nutrient access through the exploration of hyphae in plant-fungal symbiosis (Bueno de Mesquita et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e). The lush root system of graminoids, particularly their fibrous root system, enables them to rapidly occupy soil space and efficiently absorb nutrients, whereas the root system of forbs is comparatively smaller in size, potentially limiting their nutrient uptake. Within the confined microcosmic system of our experiment, the expansive distribution of graminoids across a considerable soil has the potential to hinder the involvement of AM fungi in nutrient uptake processes. Conversely, forbs with their more restricted root range might exhibit a more pronounced increase in plant nutrient absorption facilitated by the hyphae.\u003c/p\u003e \u003cp\u003eIn individual experiments, it was observed that graminoids exhibited a higher percentage of root diseases caused by pathogen compared to forbs. This could be attributed to the legacy of a grassland plant community that was dominated by \u003cem\u003eL. chin\u003c/em\u003e, which made the graminoids more susceptible to these diseases. We detected a significant negative linear relationship between the PMI of graminoids and the percentage of pathogen-induced diseases under overgrazed soil conditions. However, the PMI of forbs did not show any changes with respect to diseases percentage. This finding suggested that the PMI of graminoids was more reliant on their resistance to pathogen, particularly when these plants were unable to obtain sufficient nutrients. Gramineous plants in our research could be regarded as being \u0026lsquo;fast\u0026rsquo; species with a high root length (Cortois et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). When nutrients in the soil are insufficient, their growth may be limited, resulting in a weakened immune system and increased susceptibility. On the other hand, \u0026lsquo;slow\u0026rsquo; species such as forbs showed slower growth but higher disease resistance, which explains the lack of correlation between the PMI of forbs and pathogen diseases. Further, we did not observe significant effects of soil nutrients on AM fungal colonization and pathogen diseases, nor did we observe significant effects of interspecific competition on pathogen diseases. In our research, restored soil was consider to be more resource-rich than overgrazed soil, with the presents of interspecific competition allowed graminoids to obtain more resources. On the other hand, forbs were subject to greater resource competition influenced by variations in plant competitiveness, supporting the notion that the intensity of competition is similar along a resource gradient. These findings contradict the expectations of Lekberg et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), who predicted that plant-soil microbial interaction would be more negative in high resource environments (Lekberg et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Additionally, these finds do not align with the results of \u003cem\u003eKlinerova and Dostal\u003c/em\u003e (2019), who suggested that nutrient-demanding species would experience less negative plant-soil feedback (Klinerov\u0026aacute; and Dost\u0026aacute;l \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Nevertheless, we did find that the relationship between PMI and AM fungi or pathogen, which indicates the dependence of plant growth on specific microorganisms, could be influenced by soil nutrients and interspecific competition. In the case of plants grown in overgrazed soil and with interspecific competitors, the relationship between the PMI of forbs and AM fungi became even stronger compared to plants grown in restored soil and grown alone. We attributed this result in Plant's dependence to mycorrhizal fungi is enhanced in low-nutrient environments (Schultz et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Parallelly, the relationship between the PMI of graminoids and root diseases was found to be significantly only in overgrazed soil and in individual experiment. This suggests that plant resistance to pathogen is enhanced by higher nutrient levels.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe interactions among plants, mutualists, and antagonists within the plant-soil microorganism system are highly intricate, posing a challenge in identifying the primary driving factor of plant-soil microorganism interactions (PMI). In this study, we propose an empirical approach to shed light on the outcomes of PMI by examining the relationship between PMI strength and colonization by AM fungi or pathogen. By considering the diversity of 13 grass species, two soil contexts, and two community conditions, we found that graminoids experienced a higher incidence of pathogen diseases, while forbs benefitted more from AM fungi. The PMI of graminoids appeared to be influenced by antagonists, whereas forbs relied on mutualists. We observed that these relationships were enhanced by low soil nutrient levels and interspecific competition. We argue that this conceptual framework could offer a more mechanistic understanding of plant-soil microorganism interactions. Additionally, we propose that colonization by AM fungi or pathogen may serve as key predictors of the direction and strength of PMI, but vary depending on the plant functional groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThree-way analysis of variance (ANOVA) for the effects of species, competition, soil substrates and their interactions on PMI, colonization rate of AM fungi (CAM) and percentage of disease roots (PDR)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCAM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ePDR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of variation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompetition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.966\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil substrates (SS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies*Competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS*Species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompetition*SS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies*Competition*SS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eStatistically significant sources of variation are in bold (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePearson relationship between PMI and colonization rate of AM fungi (CAM) or percentage of disease roots (PDR) among different functional groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eIndividual experiments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eCommunity experiments\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eRestored soil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAM-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePDR-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGraminoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAM-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePDR-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForbs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAM-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePDR-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eOvergrazed soil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAM-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePDR-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.230\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGraminoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAM-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePDR-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForbs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAM-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePDR-PMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.230\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eStatistically significant sources of variation are in bold (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05), and r means correlation index\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.L. conceived and performed experiments. Z.D. performed experiments and wrote the manuscript. L.G. and B.R. provided advice on editorial guidance and edited language. S.Q. and L.B. provided advice on edited language. All authors commented on the manuscript and approved the final version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBadri D V., Vivanco JM (2009) Regulation and function of root exudates. Plant, Cell Environ 32:666\u0026ndash;681. https://doi.org/10.1111/j.1365-3040.2009.01926.x\u003c/li\u003e\n\u003cli\u003eBeals KK, Moore JAM, Kivlin SN, et al (2020) Predicting plant-soil feedback in the field: Meta-analysis reveals that competition and environmental stress differentially influence psf. Front Ecol Evol 8:191. https://doi.org/10.3389/fevo.2020.00191\u003c/li\u003e\n\u003cli\u003eBennett JA, Klironomos J (2019) Mechanisms of plant\u0026ndash;soil feedback: interactions among biotic and abiotic drivers. New Phytol 222:91\u0026ndash;96. https://doi.org/10.1111/nph.15603\u003c/li\u003e\n\u003cli\u003eBever JD (2003) Soil community feedback and the coexistence of competitors: Conceptual frameworks and empirical tests. New Phytol 157:465\u0026ndash;473. https://doi.org/10.1046/j.1469-8137.2003.00714.x\u003c/li\u003e\n\u003cli\u003eBever JD, Mangan SA, Alexander HM (2015) Maintenance of Plant Species Diversity by Pathogens. Annu Rev Ecol Evol Syst 46:305\u0026ndash;325. https://doi.org/10.1146/annurev-ecolsys-112414-054306\u003c/li\u003e\n\u003cli\u003eBueno de Mesquita CP, Martinez del R\u0026iacute;o CM, Suding KN, Schmidt SK (2018) Rapid temporal changes in root colonization by arbuscular mycorrhizal fungi and fine root endophytes, not dark septate endophytes, track plant activity and environment in an alpine ecosystem. Mycorrhiza 28:717\u0026ndash;726. https://doi.org/10.1007/s00572-018-0863-7\u003c/li\u003e\n\u003cli\u003eCortois R, Schr\u0026ouml;der-Georgi T, Weigelt A, et al (2016) Plant\u0026ndash;soil feedbacks: role of plant functional group and plant traits. J Ecol 104:1608\u0026ndash;1617. https://doi.org/10.1111/1365-2745.12643\u003c/li\u003e\n\u003cli\u003eCrawford KM, Bauer JT, Comita LS, et al (2019) When and where plant-soil feedback may promote plant coexistence: a meta-analysis. Ecol Lett 22:1274\u0026ndash;1284. https://doi.org/10.1111/ele.13278\u003c/li\u003e\n\u003cli\u003eDietz S, Herz K, D\u0026ouml;ll S, et al (2019) Semi-polar root exudates in natural grassland communities. Ecol Evol 9:5526\u0026ndash;5541. https://doi.org/10.1002/ece3.5043\u003c/li\u003e\n\u003cli\u003eDietz S, Herz K, Gorzolka K, et al (2020) Root exudate composition of grass and forb species in natural grasslands. Sci Rep 10:10691. https://doi.org/10.1038/s41598-019-54309-5\u003c/li\u003e\n\u003cli\u003eDost\u0026aacute;l P (2021) The temporal development of plant-soil feedback is contingent on competition and nutrient availability contexts. Oecologia 196:185\u0026ndash;194. https://doi.org/10.1007/s00442-021-04919-6\u003c/li\u003e\n\u003cli\u003eGarc\u0026iacute;a-Parisi PA, Omacini M (2017) Arbuscular mycorrhizal fungi can shift plant-soil feedback of grass-endophyte symbiosis from negative to positive. Plant Soil 419:13\u0026ndash;23. https://doi.org/10.1007/s11104-017-3216-y\u003c/li\u003e\n\u003cli\u003eG\u0026uuml;sewell S (2004) N:P ratios in terrestrial plants: Variation and functional significance. New Phytol 164:243\u0026ndash;266. https://doi.org/10.1111/j.1469-8137.2004.01192.x\u003c/li\u003e\n\u003cli\u003eHoeksema JD, Chaudhary VB, Gehring CA, et al (2010) A meta-analysis of context-dependency in plant response to inoculation with mycorrhizal fungi. Ecol Lett 13:394\u0026ndash;407. https://doi.org/10.1111/j.1461-0248.2009.01430.x\u003c/li\u003e\n\u003cli\u003ein \u0026rsquo;t Zandt D, Herben T, van den Brink A, et al (2021) Species abundance fluctuations over 31 years are associated with plant\u0026ndash;soil feedback in a species-rich mountain meadow. J Ecol 109:1511\u0026ndash;1523. https://doi.org/10.1111/1365-2745.13574\u003c/li\u003e\n\u003cli\u003eJiang J, Moore JAM, Priyadarshi A, Classen AT (2017) Plant-mycorrhizal interactions mediate plant community coexistence by altering resource demand. Ecology 98:187\u0026ndash;197. https://doi.org/10.1002/ecy.1630\u003c/li\u003e\n\u003cli\u003eJohnson NC, Angelard C, Sanders IR, Kiers ET (2013) Predicting community and ecosystem outcomes of mycorrhizal responses to global change. Ecol Lett 16:140\u0026ndash;153. https://doi.org/10.1111/ele.12085\u003c/li\u003e\n\u003cli\u003eKamble A, Michavila S, Gimenez-Ibanez S, Redkar A (2024) Shared infection strategy of a fungal pathogen across diverse lineages of land plants, the Fusarium example. Curr Opin Plant Biol 77:102498. https://doi.org/10.1016/j.pbi.2023.102498\u003c/li\u003e\n\u003cli\u003eKempel A, Rindisbacher A, Fischer M, Allan E (2018) Plant soil feedback strength in relation to large-scale plant rarity and phylogenetic relatedness. Ecology 99:597\u0026ndash;606. https://doi.org/10.1002/ecy.2145\u003c/li\u003e\n\u003cli\u003eKlinerov\u0026aacute; T, Dost\u0026aacute;l P (2020) Nutrient-demanding species face less negative competition and plant\u0026ndash;soil feedback effects in a nutrient-rich environment. New Phytol 225:1343\u0026ndash;1354. https://doi.org/10.1111/nph.16227\u003c/li\u003e\n\u003cli\u003eKoziol L, Bever JD (2019) Mycorrhizal feedbacks generate positive frequency dependence accelerating grassland succession. J Ecol 107:622\u0026ndash;632. https://doi.org/10.1111/1365-2745.13063\u003c/li\u003e\n\u003cli\u003eLarios L, Suding KN (2015) Competition and soil resource environment alter plant-soil feedbacks for native and exotic grasses. AoB Plants 7:plu077. https://doi.org/10.1093/aobpla/plu077\u003c/li\u003e\n\u003cli\u003eLekberg Y, Bever JD, Bunn RA, et al (2018) Relative importance of competition and plant\u0026ndash;soil feedback, their synergy, context dependency and implications for coexistence. Ecol Lett 21:1268\u0026ndash;1281. https://doi.org/10.1111/ele.13093\u003c/li\u003e\n\u003cli\u003eLepinay C, Vondr\u0026aacute;kov\u0026aacute; Z, Dost\u0026aacute;lek T, M\u0026uuml;nzbergov\u0026aacute; Z (2018) Duration of the conditioning phase affects the results of plant-soil feedback experiments via soil chemical properties. Oecologia 186:459\u0026ndash;470. https://doi.org/10.1007/s00442-017-4033-y\u003c/li\u003e\n\u003cli\u003eLi J, Meng B, Chai H, et al (2019a) Arbuscular mycorrhizal fungi alleviate drought stress in C3 (Leymus chinensis) and C4 (hemarthria altissima) grasses via altering antioxidant enzyme activities and photosynthesis. Front Plant Sci 10:499. https://doi.org/10.3389/fpls.2019.00499\u003c/li\u003e\n\u003cli\u003eLi J, Xie S, Wilson GWT, et al (2020) Plant\u0026ndash;microbial interactions facilitate grassland species coexistence at the community level. Oikos 129:533\u0026ndash;543. https://doi.org/10.1111/oik.06609\u003c/li\u003e\n\u003cli\u003eLi X, Jousset A, de Boer W, et al (2019b) Legacy of land use history determines reprogramming of plant physiology by soil microbiome. ISME J 13:738\u0026ndash;751. https://doi.org/10.1038/s41396-018-0300-0\u003c/li\u003e\n\u003cli\u003eMangan SA, Schnitzer SA, Herre EA, et al (2010) Negative plant-soil feedback predicts tree-species relative abundance in a tropical forest. Nature 466:752\u0026ndash;755. https://doi.org/10.1038/nature09273\u003c/li\u003e\n\u003cli\u003eMommer L, Cotton TEA, Raaijmakers JM, et al (2018) Lost in diversity: the interactions between soil-borne fungi, biodiversity and plant productivity. New Phytol 218:542\u0026ndash;553. https://doi.org/10.1111/nph.15036\u003c/li\u003e\n\u003cli\u003eM\u0026uuml;nzbergov\u0026aacute; Z, \u0026Scaron;urinov\u0026aacute; M (2015) The importance of species phylogenetic relationships and species traits for the intensity of plant-soil feedback. Ecosphere 6(11):234. https://doi.org/10.1890/ES15-00206.1\u003c/li\u003e\n\u003cli\u003ePfennigwerth AA, Van Nuland ME, Bailey JK, Schweitzer JA (2018) Plant\u0026ndash;soil feedbacks mediate shrub expansion in declining forests, but only in the right light. J Ecol 106:179\u0026ndash;194. https://doi.org/10.1111/1365-2745.12833\u003c/li\u003e\n\u003cli\u003eRasmussen PU, Bennett AE, Tack AJM (2020) The impact of elevated temperature and drought on the ecology and evolution of plant\u0026ndash;soil microbe interactions. J Ecol 108:337\u0026ndash;352. https://doi.org/10.1111/1365-2745.13292\u003c/li\u003e\n\u003cli\u003eSchroeder JW, Dobson A, Mangan SA, et al (2020) Mutualist and pathogen traits interact to affect plant community structure in a spatially explicit model. Nat Commun 11:2204. https://doi.org/10.1038/s41467-020-16047-5\u003c/li\u003e\n\u003cli\u003eSchultz PA, Michael Miller R, Jastrow JD, et al (2001) Evidence of a mycorrhizal mechanism for the adaptation of Andropogon gerardii (Poaceae) to high‐ and low‐nutrient prairies . Am J Bot 88:1650\u0026ndash;1656. https://doi.org/10.2307/3558410\u003c/li\u003e\n\u003cli\u003eSmith-Ramesh LM, Reynolds HL (2017) The next frontier of plant\u0026ndash;soil feedback research: unraveling context dependence across biotic and abiotic gradients. J Veg Sci 28:484\u0026ndash;494. https://doi.org/10.1111/jvs.12519\u003c/li\u003e\n\u003cli\u003eStein C, Mangan SA (2020) Soil biota increase the likelihood for coexistence among competing plant species. Ecology 101:1\u0026ndash;11. https://doi.org/10.1002/ecy.3147\u003c/li\u003e\n\u003cli\u003eStevens BM, Propster J, Wilson GWT, et al (2018) Mycorrhizal symbioses influence the trophic structure of the Serengeti. J Ecol 106:536\u0026ndash;546. https://doi.org/10.1111/1365-2745.12916\u003c/li\u003e\n\u003cli\u003eTedersoo L, Bahram M, Zobel M (2020) How mycorrhizal associations drive plant population and community biology. Science 367:867\u0026ndash;874. https://doi.org/10.1126/science.aba1223\u003c/li\u003e\n\u003cli\u003evan der Putten WH, Bradford MA, Pernilla Brinkman E, et al (2016) Where, when and how plant\u0026ndash;soil feedback matters in a changing world. Funct Ecol 30:1109\u0026ndash;1121. https://doi.org/10.1111/1365-2435.12657\u003c/li\u003e\n\u003cli\u003eWedekind C, Gessner MO, Vazquez F, et al (2010) Elevated resource availability sufficient to turn opportunistic into virulent fish pathogens. Ecology 91:1251\u0026ndash;1256. https://doi.org/10.1890/09-1067.1\u003c/li\u003e\n\u003cli\u003eXue W, Berendse F, Bezemer TM (2018a) Spatial heterogeneity in plant\u0026ndash;soil feedbacks alters competitive interactions between two grassland plant species. Funct Ecol 32:2085\u0026ndash;2094. https://doi.org/10.1111/1365-2435.13124\u003c/li\u003e\n\u003cli\u003eXue W, Bezemer TM, Berendse F (2018b) Density-dependency and plant-soil feedback: former plant abundance influences competitive interactions between two grassland plant species through plant-soil feedbacks. Plant Soil 428:441\u0026ndash;452. https://doi.org/10.1007/s11104-018-3690-x\u003c/li\u003e\n\u003cli\u003eYandi S, Tao M, Huakun Z, et al (2023) Characterization of the Plant‒Soil feedback index in alpine meadow degradation and recovery: A field experiment. Front Environ Sci 10:1097030. https://doi.org/10.3389/fenvs.2022.1097030\u003c/li\u003e\n\u003cli\u003eZhang J, Ai Z, Xu H, et al (2021) Plant-microbial feedback in secondary succession of semiarid grasslands. Sci Total Environ 760:143389. https://doi.org/10.1016/j.scitotenv.2020.143389\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"plant-microbial interactions, AM fungi, pathogen, functional group, steppe","lastPublishedDoi":"10.21203/rs.3.rs-4157804/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4157804/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePlant-microbial interactions (PMI) play a crucial role in plant growth, fitness and productivity, primarily through the mutualism and antagonism interactions between plants and soil microorganisms. The colonization of arbuscular mycorrhizal (AM) fungi and pathogen are often used to speculate on the effects of microorganisms on plant growth, i.e. plant-microbial interactions (PMI). However, empirical studies demonstrate the relationship between AM fungi or pathogen and PMI effects remains limited, especially under different biotic and abiotic conditions. Here, we evaluated the colonization rates of AM fungi and pathogen across 13 grassland species under individual or communal conditions, in both overgrazed and restored soil. Furthermore, we investigated the relationship between AM fungi or pathogen and PMI. Our results showed that forbs exhibited significantly higher rates of AM fungal colonization compared to graminoids in community condition and overgrazed soil while graminoid roots showed higher pathogen infestation compared to forbs in individual condition and overgrazed soil. Generally, there was a positive correlation between PMI and AM fungal colonization but a negative correlation between PMI and pathogen disease. The PMI of graminoids exhibited a negative correlation with pathogen disease in individual condition and overgrazed soil, but showed no correlation with AM fungal colonization. On the other hand, the PMI of forbs showed a positive correlation with AM colonization in both restored and overgrazed soil, as well as in both individual and community experiments. However, there was no correlation between PMI of forbs and pathogen disease. The PMI of graminoids and forbs in grassland ecosystems can be driven by distinct soil microorganisms. These insights enable us to better understand how soil mutualists and pathogen mediate PMI effects on plant growth, with implications for grassland management and restoration.\u003c/p\u003e","manuscriptTitle":"AM fungi and pathogen dissimilarity predicting plant-microbial interactions strength in graminoids and forbs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-01 19:25:34","doi":"10.21203/rs.3.rs-4157804/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2e18b61c-f8c8-45b1-b7b7-29073125e8b4","owner":[],"postedDate":"April 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-11T19:23:25+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-01 19:25:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4157804","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4157804","identity":"rs-4157804","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}