Plant traits and soil properties involved in nutrient and carbon exchange predict arbuscular mycorrhizal fungal communities under nature ambient precipitation gradients

doi:10.21203/rs.3.rs-2116691/v1

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Plant traits and soil properties involved in nutrient and carbon exchange predict arbuscular mycorrhizal fungal communities under nature ambient precipitation gradients

https://doi.org/10.21203/rs.3.rs-2116691/v1

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Aims

Despite several studies demonstrating that plant traits determine plant community response to precipitation changes and that precipitation indirectly affects arbuscular mycorhizal (AM) fungal communities by changes in plant community attributes. Yet the impacts of plant traits on AM fungal communities are still unknown under precipitation change.

Methods

We selected three sites extremely ideal to examine the effects of plant community functional traits and soil properties on AM fungal communities due to similar plant species and precipitation differences in an alpine meadow of Tibetan Plateau.

Results

We observed that high precipitation markedly enhanced AM fungal diversities, plant community functional diversities and soil nutrients. Total soil nitrogen and soil available phosphorus predicted variation in AM fungal diversities, while AM fungal biomass was predicted by plant community-weighed means of nitrogen and phosphorus ratio (CWM-N:P). Members of Glomus preferred to inhabit in the sites with low precipitation. A distance-based redundancy analysis (db-RDA) demonstrated that AM fungal community structure was predicted by CWM-N:P, plant community-weighed means of photosynthetic rate (CWM-P_n), total soil carbon and plant community functional dispersion (FD_is).

Conclusions

We conclude that plant traits and soil properties, which are involved in nutrient-carbon (C) exchange in AM fungal symbionts, shape AM fungal communities under ambient precipitation gradients. Our finding provided a novel insight into AM fungal community assembly from the perspective of nutrient-carbon exchange.

Arbuscular mycorrhizal fungal communities

Plant community functional traits

Nutrient-carbon exchange

Soil properties

Ambient precipitation gradients

Alpine meadows

In recent decades, human-induced climate changes are contributing to alterations in precipitation patterns and hydrological cycles (Hanasaki et al. 2013; Chen et al. 2014). Particularly, the magnitude, frequency and duration of extreme precipitation events are significantly enhanced by increased warming at the global, continental and regional scale (Westra et al. 2013; Sun et al. 2020). Grassland ecosystems, as an integral component of terrestrial ecosystems, are extremely sensitive to precipitation changes, because they are naturally limited by soil water availability (Knapp et al. 2015; Carroll et al. 2021). Precipitation changes, such as drought, are altering grassland plant community composition and structure, further affecting the ecosystem functioning (Grime et al. 2000; Yang et al. 2011; Liu et al. 2018). Plant community functional composition, defined by the single trait (community-weighed trait means, CWMs) and/or multiple traits (trait distribution within communities) has been linked to the responses of grassland ecosystem function to precipitation changes (Griffin-Nolan et al. 2019; Luo et al. 2021; Zuo et al. 2021). High functional diversities often facilitate overall resource utilization through complementarity among the species, conferring plant communities more resistance to precipitation changes (Gross et al. 2007; Valencia et al. 2015). Moreover, some plant traits mediate the impacts of grassland communities on soil moisture (Gross et al. 2008). For example, high canopy limits light radiation penetration, leading to an increase in soil moisture. Although plant traits have been proposed to play essential roles in soil function, the linkages between plant community functional composition and soil microbial communities are far from being fully understand (Faucon et al. 2017).

Arbuscular mycorrhizal (AM) fungi are known as most ubiquitous and widespread underground symbioses and form symbiotic associations with most grassland plant species (Davison et al. 2015). AM fungi improve plant fitness through the provision of nutritional and non-nutritional benefits for plant hosts (Bücking & Shachar-Hill 2005; Delavaux et al. 2017). For example, emerging evidences show AM hyphae directly provides water for host plants (Kakouridis et al. 2022). In return, plant hosts provide AM fungi with carbohydrates for the formation, maintenance and function of mycorrhizal structures (Smith & Read 2008). Simultaneously, AM fungi produce extensive hyphae in the roots and soils, leading to an intimate linkage between plants and soils (Smith & Read 2008). Therefore, the intimate relationships indicate that the responses of AM fungal communities to environmental changes should be driven by plant community functional composition and soil properties together. Several studies have demonstrated that precipitation changes alter AM fungal diversities and community composition and structure (Chen et al. 2017; Li et al. 2017; House & Bever 2018; Gao et al. 2018; Deveautour et al. 2018; Deveautour et al. 2019). For example, long-term drought increased AM fungal colonization of roots, while extraradical mycorrhizal hyphae densities in soils are reduced by long-term drought (Staddon et al. 2003). Rillig (2004) reanalyzes data (Johnson et al. 2003) from grasslands in Northern America and found a significant positive correlation (R² = 0.97) between AM fungal hyphae densities and precipitation. The responses of AM fungal communities to precipitation change have been known to be associated with induced-precipitation changes in plant community composition (Staddon et al. 2003; Li et al. 2015; Deveautour et al. 2019). In addition to closed association between AM fungal communities and plant communities under precipitation changes, plant community functional composition has been linked with the responses of plant community to precipitation changes (Griffin-Nolan et al. 2019; Zuo et al. 2021). Therefore, the study of AM fungal communities under precipitation changes from the perspective of plant community functional composition seems timely and crucial.

Alpine grasslands with extreme circumstances are extremely sensitive to precipitation changes (Chen et al. 2013; Ding et al. 2017). In recent decades, mean annual precipitation has been markedly enhanced in Qinghai plateau (He et al. 2021), but the water limitation for vegetation became stronger (Ding et al. 2018). Most plants in alpine grasslands of Tibetan Plateau were colonized by AM fungi (Gai et al. 2006) and AM fungi are abundant (Gao & Guo 2010). Thus advancing the understanding of the symbiotic associations between plants and AM fungi is essential for alpine grassland management and conservation under rapid climate change (He et al. 2021), because AM fungi play an important role in plant nutrient availability and plant community productivity and biodiversity (van der Heijden et al. 1998; Collins & Foster 2009). Here, we selected three sites with similar precipitation difference and plant species at the ambient precipitation gradients in the alpine meadow of the Tibetan plateau.We utilized the ambient gradient of mean annual precipitation (550-700 mm) and the precipitation differences (approx.70 mm) between neighing sites. Similar plant species and precipitation difference and the same vegetation type in three sites provide an ideal experiment to explore the responses of AM fungal communities to ambient precipitation gradients by linking plant functional composition with soil properties.We evaluated AM fungal diversities, biomass and community structure using Miseq sequencing and biomarker, and surveyed plant traits of most common species (accumulated abundance > 90%). Plant community functional composition was assessed by three indices of functional diversity (functional richness: FR_ic; functional evenness: FE_ve; functional dispersion: FD_is) and community-weighed trait means. Specific leaf area (SLA), leaf nitrogen concentration (LNC), leaf phosphorus concentration (LPC), the ratio of leaf nitrogen and phosphorus (N:P) ratio and photosynthetic rate (P_n) were involved in the calculation of plant community functional composition. SLA has been linked to plant growth strategies and the responses of plant communities to changing environments (Wright et al. 2004). LNC, LPC and N:P have been associated with primary nutrient function of AM fungi (Delavaux et al. 2017). P_nwasconsidered asa direct carbon resource of AM fungi (Smith & Read 2008). We expected that AM fungal communities should be predicted by plant community functional composition and soil properties.

Site selection

The study was conducted in an alpine meadow at eastern edge of Qinghai-Tibetan Plateau. We selected three sites in the same grassland type (Fig. S1, a). These sites possess similar plant species and precipitation difference. The first site was located in Hongyuan County, Sichuan Province, P.R, China (32^o48′N, 102^o33′E, a.s.l. 3500 m), with a mean annual precipitation of 690 mm and a mean annual temperature of 0.9 ℃ (Liu et al., 2011). The second site was located at Gannan Grassland Ecosystem National Observation and Research Station of Maqu County, Gansu Province, P.R China (33^o38′N, 101^o53′E, a.s.l. 3500 m), with a mean annual precipitation and temperature are 620 mm and 1.2 ^oC (Zhang et al. 2012). The third site was located at Gannan Grassland Ecosystem National Observation and Research Station of Hezuo brach station, Gansu Province, P.R, China (34°55′N, 102°53′E, a.s.l. 2960 m), with a mean annual precipitation and temperature are 560 mm and 2.0 ^oC (An et al. 2020). The anerage annual precipitation of the three plotes differed more than 60 mm (Fig. S1, b). Soils are classified as alpine meadow soil. The detailed information on soil properties and plant species was provided in the Table 1 and Table S1, respectively. These three sites are extremely ideal to examine the effects of plant community functional composition and soil properties on AM fungal communities due to similar plant species and precipitation differences in an alpine meadow. According to mean annual precipitation, three sites were called as high-precipitation site (HPS), medium-precipitation site (MPS) and low-precipitation site (LPS) in the following sections.

Field investigation and soil sample collection

To examine the effects of ambient precipitation to plant communities, we randomly selected 10 plots in each site. The coverage of individual plant species was visually measured in mid-August in 2020 using 1m × 1m quadrats with 100 equally distributed grids spaced 10 cm apart. Community coverage was summed across the species and relative coverage of individual species was calculated as coverage of individual species divided by community coverage.

After plant community investigation, five soil cores (top soil: 0-10 cm) were randomly collected from each plot. Then, these soil samples were homogenized and sieved through a 2-mm mesh after removing plant roots and stones. To avoid the contamination between soil samplings, tools were sterilized using burning ethanol. The soil samples were divided into three subsamples. The first subsample was immediately placed into ice boxes to transport into laboratory and stored at the -80 ℃ until analysis. The second subsample was used to determine the soil water contents. Specifically, the fresh soils were replaced in aluminum box, weighed, and then oven-dried at the 120 ℃ for 48 hours in the laboratory. The third subsample was air-dried and used to determine the soil pH, total carbon, total nitrogen, total phosphorus and available phosphorus.

Measurements of plant traits

In situ photosynthetic rate of individual plant species was measured on sunny days between 9:30 and 11:30 in mid-August of 2020 using the LI-6400 Portable Photosynthetic System (LI-COR, Lincoln, NE, USA). Specifically, mature and fully expanded leaves were selected and measured at least ten replicates plants at ambient CO₂ concentration of 400 µmol mol^-1 with the temperature of 20-25 ℃. Photosynthetic photon flux density was set at 1500 µmol quanta m^-2 s^-1 using a red-blue 6400-02B LED light source. All selected leaves were acclimated in the chamber under setting condition before measurement. Three values were recorded until all parameters remained stable. Mean values were calculated to be used in the following analysis.

After the measurements of photosynthetic rate, all leaves were collected to determine SLA, LNC and LPC. Briefly, all fresh leaves were scanned using Epson Expression 10000 XL desktop scanner. The leaf area was obtained from the scanned leaves using WinFOLIA software (Regent Instruments Inc., Quebec City, QC, Canada). Then, these leaves were oven dried at the 75 ^oC for 48 hours and weighed. SLA was calculated as leaf area divided by leaf weight. The leaf samples were digested using a mixture of sulphuric acid and hydrogen peroxide and determined LNC and LPC using a SmartChem® 140 Discrete Analyzer (WESTCO Scientific Instruments Inc).

Measurements of soil properties

Several soil parameters were measured using standard protocols below. Briefly, 5-g frozen soils were used to determine soil inorganic nitrogen (NH₄⁺-N and NO₃^--N) using a SmartChem® 140 Discrete Analyzer (WESTCO Scientific Instruments Inc) after extraction by 2 M KCl for 30 min at 25 ^oC. Soil available phosphorus was extracted by 0.5 M NaHCO₃ at the ratio 1:5 (w/v) and analyzed using UV-visible spectrophotometer (UV-2550; SHIMADZU Corporation, Japan). Soil pH was determined using 5 g air-dried soils at the ratio of 1:2.5 (soil : CO₂-free deionized water, w/v). Soil total nitrogen was determined using 0.5-g air-dried soils added 5-ml concentrated sulfuric acid oxidation elimination at 370 ^oC for 4 hours using a SmartChem® 140 Discrete Analyzer (WESTCO Scientific Instruments Inc). Soil total phosphorus was determined using 0.1-g air-dried soils successively added 5-ml concentrated sulfuric acid and 10 drops interval three times perchloric acid elimination at 370 ^oC for disboil solution clarify by SmartChem® 140 Discrete Analyzer. Soil total carbon was determined using 20-mg air-dried soils using fast combustion at high temperature by TOC elemental analyzer. Soil water content was determined gravimetrically with 10-g fresh soil into aluminum dishes that was oven-dried for 48 hours at 105±1℃.

Measurement of AM fungal biomass

Soil AM fungal biomass were determined using PLFA biomarker, which is an efficient approach to detect soil microbial biomass across different kingdoms (Broadbent et al. 2021). PLFA concentrations as soil microbial biomass were determined using standard proposal by Bossio & Scow (1998). Briefly, 8-g frozen soils were used to extract lipids. The PLFA extraction was described in detail by Bossio & Scow (1998). Fatty acid methyl esters were separated, quantified and identified using capillary gas chromatography. PLFA analyses were conducted with an agilent 6890 gas chronatograph (Agilent Technologies, USA). The individual FAs were identified with the MIDI Sherlock Microbial Identification System (MIDI Inc., USA) and quantified using the FAME 19:0 (Matreya Inc., USA) as an internal standard. 16:1ω5c FA concentrations were assigned as indicators of AM fungal biomass (Olsson et al. 1995).

Soil DNA extraction, PCR, Miseq sequencing

Soil DNA was extracted from approx 0.5 g frozen soils using Magnetic Soil and Stool DNA Kit (Tiangen Biotech, Beijing, China) according to the manufacturer’s instructions. We used AM fungi-specific primer sets AML1/AML2 (Lee et al. 2008) and AMV4-5NF/AMDGR (Krüger et al. 2009) to amplify AM fungal sequences.PCR amplification and library preparation were described in detailed in supplementary information. The amplicons were sequenced with 2 × 300-bp paired-end on an Illumina Miseq sequencer at Shanghai Biozeron Biological Technology Co. Ltd (Shanghai, China).

Bioinformatic analysis

The bioinformatic analyzes were preformed at the following steps. Firstly, after sequencing, raw sequences were demultiplexed and quality-filtered using the FASTP (Chen at al. 2013). The FLASH software was used to merge the reads with the criteria described by Zheng et al. (2018). Singleton OTUs and chimeras were removed using FLASH software (Magoč & Salzberg 2011). Secondly, operational taxonomic units (OTUs) were clustered at 97% similarity levels using UPARSE (Edgar 2013). A representative sequence of each OTU was selected and blasted against specific-AM fungal databases Maaji AM database (Öpik et al. 2010). Thirdly, sequences, which are specific to AM fungi, were picked up manually. Finally, the selected sequences were rarefied to the depth of the smallest sample using the function ‘rarefy’ with a step size of 20 iterations (Fig. S2). The AM fungal community diversity was expressed as Shannon-Weiner index at the phylotype level. For AM fungal community structure, we performed in-depth analyses by selecting phylotype with > 0.1% sequences at each sample (Harman et al. 2018).

Data analysis

All statistical analyses were performed in R software at the following steps (R Team, R version 4.02; 2020). All data were log-transformed to meet the normality and homogeneity of variance when necessary.

Firstly, we used the traits SLA, LNC, LPC, N: P and P_n to calculate the functional diversity (functional richness: FR_ic; functional evenness: FE_ve; functional dispersion: FD_is) and community-weighed trait means using the dbFD function in the ‘FD’ R-package. The significant differences in the variables (soil properties, functional diversity, community-weighed trait means, AM fungal diversity, AM fungal biomass and the relative abundance of the first fourth dominant genus) at the precipitation gradients were examined by one-way ANOVA with TukeyHSD test at the significant level of 0.05.

Secondly, to predict the variation in AM fungal diversity and biomass, variables with significant change at the precipitation were chosen for correlation analysis. Then, these variables with significantly correlated with AM fungal diversity or biomass were used for model selection, which was performed using the function dredge in the ‘MuMIn’ R-package (Barton 2016). The function dredge automatically constructs a complete model set with all possible combinations (Barton 2016). We compared all candidate models using Akaike Information Criterion (AIC), which corrects for small sample sizes, and the model with smallest AICc was selected as the best-fitted model (Burnham & Anderson 2002). The determination coefficient (R²) of the best-fitted model was calculated using the function r.squaredLR in the ‘MuMIn’ R-package.

Thirdly, to examine the effects of ambient precipitation on AM fungal community structure, the significant differences in AM fungal community structure at the precipitation gradients were examined by the function anosim with 999 permutations. AM fungal structure was evaluated by in-depth analyses at the phylotype level based on Bray-Curtis distance matrix using the relative abundance ( > 0.1%) of each phylotype sequences at the sample. Additionally, we used variables with significant changes at the precipitation gradients to predict AM fungal community structure with a partial distance-based redundancy analysis (db-RDA) using the function capscale. The best-fitted model was constructed using the function ordistep with 999 permutations and model’s significance was tested by the function anova with 999 permutations.

The responses of soil properties to ambient precipitation gradients

We observed that soil properties showed significant differences at the precipitation gradients (Table 1). Similar to precipitation, three sites significantly differed in soil water contents (F_{(2, 27)} = 152.4, P < 0.0001; Table 1). Specifically, soil water contents in the HPS were markedly higher than those in the MPS and LPS (Table 1) . Moreover, ambient precipitation significantly enhanced soil nutrient contents, such as total soil carbon, total soil nitrogen, total soil phosphorus, soil available phosphorus and nitrogen (Table 1). In contrast, enhanced precipitation led to a marked decrease in soil pH (Table 1).

The responses of AM fungal community to precipitation gradients

We observed that AM fungal communities in the HPS and LPS were co-dominated by Glomus and Acaulospora, while Glomus predominated in LPS (Fig. 1a). We further examined the responses of the dominant genus Glomus, Acaulospora, Scutellospora and Paraglomus to ambient precipitation. The dominant genus significantly differed in responses to ambient precipitation except Scutellospora (Fig.1b-e). Specifically, reduced precipitation significantly enhanced the relative abundance of Glomus (Fig. 1b), the relative abundance of Acaulospora and Paraglomus was increased by reduced precipitation (Fig. 1b, Fig. 1e).To examine the response of AM fungal community to precipitation gradients, we used Shannon-Wiener indexes and FLFA to assess the AM fungal diversities and biomass, respectively. We observed that AM fungal diversities significantly differed at the precipitation gradients (F_{(2, 27)} = 5.27, P = 0.01; Fig. 2a). HPS showed higher AM fungal diversity than that with low precipitation (P = 0.009). Enhanced precipitation significantly increased AM fungal diversities (Fig. 1). In contrast, we observed that AM fungal biomass marginally differed among sites (F_{(2, 27)} = 2.70, P = 0.08; Fig. 2b). AM fungal biomass in the MPS marginally lower than in the LPS (P = 0.07; Fig. 2b). Additionally, we observed that AM fungal community structure significantly differed at the precipitation gradients (ANOSIM R: 0.59, P < 0.0001; Fig. 3). The first and second axis explained 65.36% and 17.19% of variation in AM fungal structure (Fig. 3a).

The responses of plant community functional diversity and community-weighed trait means

Ambient precipitation significantly altered plant community functional diversity except FR_ic(Fig. 4a-d). Plant community functional diversities, such as FE_ve, and FD_is, were gradually reduced with declining precipitation (Fig.4b-d), while no significant changes in the FR_ic index were observed (F_(2,27) = 2.42, P = 0.11; Fig. 4a). We further examined community-weighed trait means and observed that most traits were significantly altered at the precipitation gradients except LNC (Fig.5a-e). Specifically, SLA was significantly enhanced by reduced precipitation (F_{(2, 27)}= 9.58, P < 0.0001; Fig.5a), while reduced precipitation significantly decreased P_n (F_{(2, 27)}= 17.58, P < 0.0001; Fig.5a). In contrast, LNC showed no marked responses to precipitation, while LPC in the MPS was significantly higher than in other sites, thus leading to a marked decrease in the N:P in the MPS (Fig. 5c-e).

Relationships between AM fungal communities vs plant community functional diversity, community-weighed trait means, and soil properties

To predict the responses of AM fungal communities to ambient precipitation gradients, we used correlation analyses, model selection and db-RDA. Correlation analyses demonstrated that most soil property parameters were significantly correlated with AM fungal diversities, while plant community-weighed trait means LPC and N:P were significantly correlated with AM fungal biomass (Fig.S3). Model selection further demonstrated that soil available P and soil total nitrogen explained 47% of variation in AM fungal diversities, while LPC explained 15 % of the variation of AM fungal biomass (Table 2). Moreover, db-RDA showed that soil total carbon, N: P, P_n and FD_is,significantly explained 40.25% of variation in AM fungal community structure (F_{(4, 25)} = 4.21, P = 0.001).

We assessed the impacts of precipitation changes on AM fungal communities, including the AM fungal diversities, biomass, and community composition and structure in an alpine meadow of the Tibetan Plateau using ambient precipitation gradients. Enhanced precipitation led to a marked increase in AM fungal diversities, which is fully consistent with the findings of Zhang et al. (2016), who observes that AM fungal diversities are gradually reduced with decreasing precipitation in the alpine steppe of the Tibetan Plateau. In recent study, long-term drought in an alpine steppe significantly reduces AM fungal diversities (Zheng et al. 2022), while AM fungal diversities in a mesic grassland show no significant responses to long-term drought (Deveautour et al. 2018). In contrast, 7-year enhanced precipitation significantly increased AM fungal richness in a steppe grassland of Inner Mongolia (Li et al. 2015). These results indicate that the responses of AM fungal diversities to precipitation changes might depend on grassland ecosystem properties, especially soil ambient nutrients. Correlation analysis and model selection demonstrated that AM fungal diversities were predicted by SAP and TSN, and a positive correlation between AM fungal diversities and both predictors. Our results mirror the finding of Liu et al. (2012), who observes that combination of N and P addition at the low dose enhanced AM fungal diversities and root colonization in an alpine meadow, while AM fungal diversities and root colonization were reduced by high-dose N and P addition. Our results, together with findings of Liu et al. (2012) suggest that AM fungi are N and P limited in alpine meadows. The limitation of soil N and P availability allows AM fungal taxa to compete for N and P from the soils because AM fungal tissue require more N and P than plant tissue (Treseder & Allen 2002). This enhanced competition may result in a marked decrease in AM fungal diversities (Treseder & Allen, 2002). Given that the threshold for nutrient limitation tends to be lower for AM fungi than for plants (Treseder & Allen 2002) , low-dose N and P addition often relieve AM fungal competition for N and P, leading to an increase in AM fungal diversities (Johnson et al., 2003; Egerton-Warburton et al., 2007; Porras-Alfaro et al. 2007). In contrast, high-dose N and P addition eliminates the N and P limitation for plants (Johnson et al. 2008). Plant hosts will reduce C allocation to AM fungi, which allows AM fungal taxa to compete for derived-plant C, leading to decreases in AM fungal diversities (Johnson et al. 2010; Grman & Robinson 2013). It is notable that we observed that AM fungal diversities and biomass differed in their response to ambient precipitation gradients. AM fungal biomass were slightly higher in the MPS than in the LPS. This may be due to plant community functional composition, especially the relative abundance of grasses and forbs (Hetrick 1992). In the MPS, the relative abundance of forbs may allow plant communities to require more P, because LPC in the forbs is markedly higher than in the grasses (Tian et al. 2021) and because forbs with thick roots are more dependent on AM fungal hyphal for nutrient capture than grasses with thin roots (Ma et al. 2018). Thus the observation in this study that AM fungal biomass was predicted by plant community weighted-LPC would be explained by the relative higher abundance and LPC of forbs.

We also observed that the members of Glomus predominated in the LPS. Egerton-Warburton et al. (2007) observe that Glomus predominate in the semiarid sites, while Scutellospora, Gigaspora and Acaulospora are abundant in the mesic sites. Recently, we observes that long-term drought enhances the relative abundance of Glomus in an alpine steppe (Zheng et al. 2022). This variation of response of AM fungal taxa/clades to precipitation may be partly due to their life history strategies based on functional traits (Chagnon et al. 2013). AM fungal taxa or clades differ in their C demand, C-use efficiency and hyphae traits (Hart & Read 2002). For example, members of Glomus are more effective at the carbon utilization and less carbon could maintain their hyphae growth and sporulation (Douds & Schenck 1999). Long-term drought often depresses canopy photosynthetic activities (Zheng et al. 2022) and reduces C allocation to AM fungi (Fuchslueger et al. 2014), possibly leading to predominance of Glomus. The carbon demands of different AM fungal taxa have been considered to be associated with their traits (Chagnon et al. 2013). For example, these AM fungal taxa with elicate hyphae and small spores require less carbon (Hart & Read 2002). Although the trait-based framework is theoretically proposed to explain the responses of AM fungal clades to environmental changes (Chagnon et al. 2013; Treseder et al. 2018; Dueñas et al. 2020), in situ tracking carbon allocation to different AM fungal taxa and evaluating individual AM fungal traits are challenging task. We only suppose the point, but the conjecture indicates that AM fungal communities maximize their own fitness under climate changes through altering their community composition (Chagnon et al. 2013; Dueñas et al. 2020).

Another important finding was that precipitation-induced variation in AM fungal community structure was predicted by plant community functional composition and soil properties. Several studies have demonstrated that precipitation changes significantly altered AM fungal community structures, but not AM fungal diversities (Chen et al. 20l7; Deveautour et al. 2018), suggesting the important roles of AM fungal community structure in response to precipitation changes, because changes in AM fungal community structure may have important consequences to ecosystems long before an AM fungal diversities are threatened by extinction. Thus, it is particularly important to consider AM fungal community structure for grassland management, conservation and restoration under climate changes. We observed that plant traits involved in carbon-nutrient economy predicted the variation in AM fungal community structure. The best predictors of AM fungal community structure were plant community-weighed N:P ratio, plant community-weighed P_n and total soil carbon. Previous models only predict the effects of soil N:P ratio on AM fungal communities (Treseder & Allen, 2002; Johnson 2010; Grman & Robinson 2013). Leaf N:P ratios are used to indicate plant nutrient availability and limitation, and play an essential role in plant photosynthetic activities (Reich et al. 2004; Schreeg et al. 2014). Few studies specifically focus on the effects of leaf N:P ratio on plant community level on AM fungal communities (Johnson et al. 2015). AM fungi can transfer P outside the depletion zone due to ramified hyphae and some AM fungi directly uptake organic P (Lambers et al. 2012). In contrast, AM fungal hyphae may not provide N uptake advantages over plant root due to higher mobility of nitrate and ammonium in soils (Johnson 2010). Yet a meta-analysis shows a significantly positive effects of AM fungi on N uptake (Delavaux et al. 2017). Several evidences have clearly demonstrated that AM fungal C availability stimulates N and P uptake and transport in the hyphal (Bücking & Shachar-Hill 2004; Fellbaum et al. 2012). Therefore, plant traits involved to nutrient-C exchange in AM fungal symbionts may play an important role in AM fungal community assembly. As a main provision of soil organic carbon, plant photosynthesis directly provides C for AM fungal growth and development (Smith & Read 2008). Indeed, AM fungi-derived C from plants in itself is an important fraction of total soil carbon (Rillig 2004). AM fungal hythae also exude some C compounds into soils, such as sugar, carbonxylates and amino acids (Bharadwaj et al. 2012; Zhang et al. 2022). Additionally, we also observed that FD_is significantly predicted AM fungal community structure in the best-fitted model (P < 0.05). FD_is reflects the degree of trait dispersion within the plant communities (Laliberte & Legendre 2010). High FD_is enhances overall resource utilization (e.g., lights and nutrients) through trait differentiation (Gross et al. 2007), and may further affect AM fungal community structure. Therefore, our results clearly demonstrate that plant functional composition and soil properties shape AM fungal communities under ambient precipitation gradients.

AM fungal diversities and community composition and structure significantly differed in response to ambient precipitation gradients, while their biomass remained stable. High ambient precipitation promoted high plant functional diversities, soil nutrients and AM fungal diversities, while low ambient precipitation enhanced the predominance of Glomus. Potential differences in AM fungal traits or their life history strategies may impact the responses of AM fungal community composition to precipitation changes. Plant traits and soil properties, which are associated with nutrient-carbon exchange in AM fungal symbionts, may shape AM fungal communities under precipitation changes.

Acknowledgements

This study was supported by National Natural Science Foundation of China (32060286; 31660160) and Natural Science Foundation of Gansu Province (20JR10RA075; 21JR7RA112). We thank Xin Li, Jing Wu and Xiaoxiao Sun for field assistance.

Author contribution

Z and S. Z conceived the ideas and designed methodology; Z.Z., Q.M, X.M., X.Y., Z.Y. and S. Z. collected samples in the field; Z.Z, Q.M. and X.M measured samples in the laboratory; Z. Z, Y. W and M. M analyzed the data. Z.Z. and S.Z wrote the manuscript.

Declarations

Conflicts of interest

The authors declare that they have no conflict of interest.

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Soil properties	Sites (mean±SE)
Soil properties	HPS	MPS	LPS
Soil water contents	55.47±1.70a	35.65±0.99b	28.57±0.48c
Soil pH	5.97±0.10b	6.34±0.13b	6.93±0.09a
Total soil carbon	64.06±1.54a	53.14±2.76b	35.78±0.77c
Total soil nitrogen	5.74±0.13a	4.96±0.26b	3.47±0.07c
Total soil phosphorus	0.84±0.08a	0.78±0.07ab	0.56±0.05b
Soil available phosphorus	3.6±0.36a	3.33±0.27ab	2.42±0.20b
Soil available nitrogen	4.59±0.37a	4.05±0.39ab	3.22±0.35b

Table 1. The results of one-way ANOVA for soil properties among sites at the precipitation gradient.

Note: Different letters indicate significant differences between sites.

Table 2. The best-fitted models were selected using dredge ‘function’ for AM fungal diversity and biomass.

Models	Selected variables	df	R²	ALCc	ΔAICc	Weight (wi)
Diversity	Soil available P, Soil total N	4	0.47	-106.4	0.00	0.08
Biomass	Leaf P concentration	3	0.15	-66.6	0.00	0.42

Onlinefloatimage6.png
Fig. S1. The location of the three sampling sites on the Qinghai-Tibetan Plateau (a), and the mean annual precipitation distubition of three sites (b), High-precipitation site (HPS), Medium-precipitation site (MPS) and Low-precipitation site (LPS)
Onlinefloatimage7.png
Fig. S2.Rarefaction curves showing AM fungal phylotype number across all samples
Onlinefloatimage8.png
Fig. S3. Pearson correlations between arbuscular mycorrhizal fungal diversities and biomass with plant community functional diversities, community-weighted trait means and soil properties. The diameter of circle indicates the magnitude of correlation. *, P < 0.05; **, P < 0.01; ***, P < 0.001. FR_ic: functional richness; FE_ve: functional evenness; FD_is: functional dispersion. SLA: specific leaf area; LNC:leaf nitrogen concentration; LPC:leaf phosphorus concentration; N:P: leaf nitrogen and phosphorus concentration ratio; P_n: photosynthetic rate; SWC: soil water content; TSC: total soil carbon; TSN: total soil nitrogen; TSP: total soil phosphorus; SAP: soil available phosphorus; SAN: soil available nitrogen.

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Plant traits and soil properties involved in nutrient and carbon exchange predict arbuscular mycorrhizal fungal communities under nature ambient precipitation gradients

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