Altitudinal distribution patterns of AM fungal assemblages in a Tibetan alpine grassland

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1 FEMS Microbiology Ecology, 91, 2015, fiv078 doi: /femsec/fiv078 Advance Access Publication Date: 3 July 2015 Research Article RESEARCH ARTICLE Altitudinal distribution patterns of AM fungal assemblages in a Tibetan alpine grassland Lei Liu 1, Miranda M. Hart 2, Junling Zhang 1, Xiaobu Cai 3, Jingping Gai 1,, Peter Christie 1, Xiaolin Li 1 and John N. Klironomos 2 1 College of Resources and Environmental Sciences, China Agricultural University, Beijing , China, 2 Department of Biology, University of British Columbia, Okanagan Campus, 3333 University Way, Kelowna, BC, Canada and 3 Tibet Agricultural and Animal Husbandry College, Tibet University, Linzhi , Tibet Corresponding author: 2 Yuanmingyuan West Road, College of Natural Resources and Environmental Sciences, China Agricultural University, Beijing , China. Tel: ; Fax: ; gaijp2009@hotmail.com One sentence summary: The study described here indicates that AM fungal communities exhibit significant spatial structures, and that the elevation patterns of these communities are regulated by the plant communities, properties and climatic conditions in this plateau montane ecosystem. Editor: Ian Anderson ABSTRACT A better understanding of biogeography of Glomeromycota is essential for the conservation of arbuscular mycorrhizal (AM) fungal species and the ecosystem services that they provide worldwide. We examined the spatial dynamics of AM fungi along two slopes (4149 m a.s.l. to the summit at 5033 m a.s.l.) of Mount Mila on the Tibetan Plateau. Our hypothesis was that AM fungal communities at higher elevation would show distinct assemblages with lower diversity in conditions of increasing environmental harshness. A total of 52 operational taxonomic units (OTUs) spanning all four orders were detected and some OTUs were habitat specific. Nearly 30% of the OTUs were new phylotypes, including two family-like clades. Distinct communities of AM fungi were found at the higher elevation, demonstrating potential niche differentiation along the elevation gradient. Elevation patterns of taxon richness/diversity differed between the two transects, decreasing with increasing elevation on the eastern slope and being unimodal (or lacking a pattern) on the western slope. Taken together, our findings provide evidence of a significant spatial structure of AM fungi across the elevation gradient, with the distribution patterns of these fungi regulated simultaneously by the plant communities, properties and climatic conditions in this plateau montane ecosystem. Keywords: arbuscular mycorrhizal fungi; community structure; Tibet; elevation; vegetation type; fungal diversity INTRODUCTION Arbuscular mycorrhizal (AM) fungi are key components of microbiomes and colonise the vast majority of terrestrial plant species (Smith and Read 1997). They acquire all of their carbon from their host plants and provide the hosts with a range of benefits, notably increased nutrient uptake and tolerance of or resistance to some diseases. As a result, AM fungi have profound effects on plant community dynamics and diversity (van der Heijden et al. 1998, 2006; Fitter 2005; Rosendahl 2008). Despite their prevalence in the environment and their importance within terrestrial ecosystems, much remains to be discovered about the diversity and biogeography of AM fungi. Recent studies using high-throughput sequencing illustrate the hitherto grossly underestimated levels of AM fungal diversity (Öpik et al. 2009, 2013), particularly in natural ecosystems that have had little anthropogenic disturbance (Ohsowski et al. 2014). Additionally, little is known about the factors that Received: 2 April 2015; Accepted: 1 July 2015 C FEMS All rights reserved. For permissions, please journals.permissions@oup.com 1

2 2 FEMS Microbiology Ecology, 2015, Vol. 91, No. 7 control AM fungal diversity and composition within communities, although some important such factors have been described, including properties (Johnson, Tilman and Wedin 1992; Djukic et al. 2010), plant species composition (Klironomos et al. 1993; Bever et al. 2001; Vandenkoornhuyse et al. 2003), and differences in temperature and moisture (Koske 1987; Ruotsalainen, Markkola and Kozlov 2009). A potential way to further this research on AM fungal diversity is to study it along elevation gradients. Elevation gradients provide a natural laboratory for studies of biodiversity and biogeography (Lomolino 2001; Rahbek 2005; Reche et al. 2005). Such gradients are characterized by dramatic changes in climate and biotic turnover across short geographic distances. Although the distribution of macro-organisms has been studied extensively along elevation gradients, very little is known of trends in microbial diversity along such gradients. On the basis of taxonomic richness, contrasting elevation patterns for microbes have been documented, including decreasing (Bryant et al. 2008), increasing (Wang et al. 2011), unimodal (Singh, Takahashi and Adams 2012a; Singh et al. 2012b) or hollow(wang et al. 2012; Singh et al. 2014) richness with increasing elevation, or a lack of pattern of richness (Fierer et al. 2011; Shen et al. 2012). Elevational variation in AM fungal communities, especially of AM fungi in s rather than in roots, has not been well studied with molecular techniques. Li et al. (2014, 2015) found that elevation gradients of OTU richness varied with plant identity, i.e. lacking a pattern in Kobresia sp and Kobresia pygmaea C.B. Clarke, and showing higher richness at intermediate elevations in Pennisetum centrasiaticum Grisebach and at low elevations in Carex pseudofoetida Kük on eastern slopes. Öpik et al. (2010) found no relationships between AM fungal richness and latitude, elevation or vascular plant richness. Other studies of spore communities have found a decreasing trend in diversity (Chaurasia, Pandey and Palni 2005; Lugo et al. 2008; Gai et al. 2012; Shi et al. 2014). Given the few existing studies of the molecular diversity of AM fungal communities in alpine/montane systems, we took a systems-based approach to better understand the patterns of AM fungi along elevation gradients. Mountain systems with extensive plateaux are especially desirable for such study (i.e. of high-elevation and large ecosystems) because they represent an extreme gradient in elevation (Lomolino 2001). When more observations of actual patterns have been made, a theoretical framework for AM fungal assemblages/diversity on mountains can be formulated and discussed in broader ecological terms. The Qinghai Tibet plateau is the highest region in the world and is also termed the third pole of the Earth. The plateau offers extremely hostile environments for organisms: low temperatures, high levels of ultraviolet (UV) radiation, low oxygen concentrations and short growth seasons, resulting in the selection of particular organisms (Wu et al. 1981; Niu et al. 2014). Mount Mila ( N, E), located in Tibet, is an excellent site for examining elevational variation in AM fungal communities because of its high elevation (from 4100 to 5033 m a.s.l.) and intact vertical vegetation belts. The objective of the study reported here was to describe the patterns of variation in AM fungal communities across a high elevation gradient of alpine grassland sites in Tibet. We tested the hypothesis that AM fungal communities at higher elevations will show decreased diversity in conditions of increasing environmental harshness. We further tested whether distinct communities of AM fungi exist at higher relative to lower elevations. MATERIALS AND METHODS Study site The study was based on field investigations of the AM fungal community along two elevational transects on Mount Mila ( N, E), a mountain with a typical alpine grassland climate and vegetation in southeast Tibet. According to ground meteorological observation data produced by an automatic climate station (29 48 N, E) located at Mila peak, Lhasa, the annual mean air temperature at the site was 1.5 o C(minimum 11.4 o C in January, maximum 6.8 o Cin July), and the total precipitation during the growth season was 688 mm (minimum 16.9 mm in October, maximum mm in July) in Annual mean precipitation varied from mm on the western slope (Mozhugongka County) of Mount Mila to mm on the eastern slope (Gongbujiangda County) (Luo et al. 2004; Pan, Zheng and Luo 2004). The highest temperature and precipitation months on Mount Mila are June September. The snow cover reaches its maximum in January and February and is completely melted on the peak of Mount Mila in early May (15 days later than at the lowest sites) (Tang et al. 2012). The annual numer of days of snow cover ranges from 4 to 12 days (Hu and Liang 2013). The area of the study has three distinct types of vegetation, consisting of montane temperate mixtures of conifers and broadleaved trees ( m a.s.l.), montane shrub and meadow ( m a.s.l.) and alpine meadow vegetation (>4700 m a.s.l.; Pan, Zheng and Luo 2004). The natural tree line on Mount Mila is at 4100 m a.s.l. Owing to the alpine environment, the plant communities in the area of the study are characterized by short growth periods and low primary production and diversity. The timing of the onset of spring vegetation growth is about mid-may in the montane shrub elevation and early June in the alpine meadow elevation. Vegetation reaches its maximum aboveground biomass in late July and early August. The timing of withering is about early October in the shrub and late September in the alpine meadow elevations, respectively (Chu et al. 2013). Sampling design Sampling was done at 11 sites/elevations on Mount Mila (4150, 4358, 4449, 4599 and 4796 m a.s.l. on the eastern slope; 4841, 4675, 4525, 4344 and 4149 m a.s.l. on the western slope and 5033 m a.s.l. on the peak) on 5 July The exact coordinates of the sampling sites are shown in Table 1. The spatial distances from the lowest elevation to the peak are 37.5 and 32.2 km on the eastern and western slopes, respectively. Within each study site, five quadrants (1 1m 2 ) separated by at least 10 m were selected for their representative herbaceous forbs and grasses and attributes for the elevation. Three cores (15 cm deep) were excavated within each quadrant and pooled to give one composite sample. Herb cover and plant abundance of each species were recorded (Table 1). A total of 55 samples (11 elevations 5 replicates) were collected, with the details of the and vegetation in the samples presented in Table 1. Soil analysis After collection, the fresh was homogenized using 1 mm sieves and stored at 20 o C for DNA extraction, with portions air-dried for chemical analysis. Total carbon and nitrogen in the samples were measured with an elemental analyzer (EA1108, Carlo Erba, Torino, Italy). Soil ph (1:2.5 /water),

3 Liu et al. 3 Table 1. Sampling sites on Mount Mila and vegetation details. Elevation (m) Latitude longitude Soil type Vegetation type Dominant herbaceous forbs and grasses Herb cover a (%) Plant diversity b Eastern slope N E Salix shrub and meadow Anaphalis DC., Polygonum L., Potentilla L., Carex L., Taraxacum F.H. Wigg., Kobresia Willd. Androsace L., Carex L., Kobresia Willd. 95 a 2.31 a N E Sabina procumbens shrub Sabina procumbens shrub 90 ab 2.01 a N E Potentilla L., Kobresia Willd., Carex L., Anaphalis DC., Kobresia Willd., Soreseris Stebb. Potentilla L., Kobresia Willd., Carex L. 90 ab 2.67 a N E Alpine Rhododendron shrub and meadow Alpine meadow 85 b 2.08 a N E Peak N E Alpine meadow Carex L., Oreosolen Hook. f., Kobresia Willd., Gentiana L. 95 a 2.20 a Alpine meadow /Alpine frozen Alpine meadow Oxytropis DC., Carex L., Kobresia Willd., Anaphalis DC. 72 c 2.34 a Western slope N E Alpine meadow Alpine meadow Anaphalis DC., Polygonum L., Carex L., Kobresia Willd., Oreosolen Hook. f. Androsace L., Lancea Hook. f. et Thoms., Carex L., Kobresia Willd., Anaphalis DC. Oreosolen Hook. f., CarexL., Kobresia Willd., Potentilla L., Anaphalis DC. Potentilla L., Aster L., Carex L., Kobresia Willd. 80 b 2.30 a N E Sabina procumbens shrub Sabina procumbens shrub Salix cupularis-sea buckthorn shrub Berberis shrub 82 b 2.37 a N E 89 ab 2.52 a N E 86 b 2.41 a N E Anaphalis DC., Carex L., Kobresia Willd., Gentiana Turrill. 80 b 1.36 b a, b Data are averages of five replicates at each elevation. Plant diversity is expressed by Shannon Wiener Index. The different letters represent significant differences among elevations within a column according to LSD at P < 0.05 by one-way analysis of variance. available P (Olsen and Sommers 1982) and organic matter content (Cambardella et al. 2001) were also determined, with the results shown in Table S1. Molecular analysis Extraction of DNA and nested polymerase chain reaction amplification Three 10 g samples were randomly collected from each homogenized sample and mixed thoroughly. The genomic DNA was extracted from a 0.5 g subsample of with a MoBio PowerSoil DNA Isolation Kit (MoBio Laboratories, Carlsbad, CA) following the manufacturer s protocol. All DNA samples were subjected to nested polymerase chain reaction (PCR), which was used to reduce the number of non- Glomeromycota clones. Triplicates of extracted DNA from each sample were subjected to the first PCR with the AM fungalspecific PCR primers AML1 AML2 (Lee, Lee and Young 2008). Polymerase chain reactions were done in a final volume of 25 μlwith1μl of template, 0.4 mm dntps, 0.2 pm for each primer, 2.5 μl 10 PCR buffer, 18 μl ddh 2 O, and 0.1 U Taq DNA polymerase (Promega) and were amplified with the following cycling conditions: 94 o C for 5 min; 34 (94 o C for 30 s; 58 o C for 60 s; 72 o C for 60 s); 72 o C for 10 min; 14 o C for 10 min; 4 o C thereafter. Using the successful products of the first amplification as templates, a second PCR was performed with another primer pair, AM1 NS31 (Helgason et al. 1998) and the reaction conditions described above. Cloning, sequencing and construction of clone libraries All PCR products were resolved on 1% (w/v) agarose gels and gel slices of the expected size gel (c. 550 bp) were purified with an E.Z.N.A. Cycle-Pure Kit (Omega Bio-Tek, Norcross, GA) according to the manufacturer s protocol, after which the

4 4 FEMS Microbiology Ecology, 2015, Vol. 91, No. 7 triplicates of the same sample were pooled with one another. Purified DNA fragments were ligated into a pgem-t Easy vector (Promega) and cloned into competent Escherichia coli JM109 according to the manufacturer s recommended protocol, resulting in 54 clone libraries (one replicate at 4149 m failed to amplify). In each library, clones containing the inserted DNA fragments were selected by blue/white screening and approximately 100 white colonies were picked off to grow overnight at 37 o Cwith 140 r in 1 ml 2 liquid Luria Bertani medium containing ampicillin (50 μg/ml). The inocula were amplified with the universal primer pair T7 SP6 with the following conditions: 94 o C for 5 min; 29 (94 o C for 30 s; 60 o C for 60 s; 72 o C for 60 s); 72 o Cfor10 min; 14 o C for 10 min; 4 o C thereafter. Polymerase chain reaction products were examined on a 1% (w/v) agarose gel with 1 Tris acetate EDTA (TAE) buffer and products of the expected length (c. 700 bp) were considered to be positive clones. In each clone library we observed from clones that were positive for plasmid inserts of the correct length. We evaluated the sampling effort in each SSU gene library with the equation for good coverage (C) C = [1 (n/n)] 100, where n is the number of monoclones and N is the total number of clones analysed in the corresponding library (Good 1953). Polymerase chain reaction products of the positive clones were digested with the restriction enzymes FastDigest HinfI (Thermo Fisher Scientific, Waltham, MA) following the protocol of Liu et al. (2014). Digested products were examined on a 2% (w/v) agarose gel before restriction fragment length polymorphism (RFLP) analysis. Scans of RFLP gels were analysed with Lab Image 3.0 software (Li et al. 2010). At least one randomly selected representative of each RFLP type was selected and the corresponding inocula were sequenced with primer T7 using a 3730xl DNA Analyzer (Thermo Fisher Scientific) at Biomed Corporation (Beijing, China). Phylogenetic sequence analysis All DNA sequences were compared with the GenBank databases (National Center for Biotechnology Information [NCBI], Bethesda, MD) using BLAST ( and then checked for chimeric sequences using the Chimera Check software of the Ribosomal Database Project (RDP, v. 2.7) (Jumpponen 2007). Non-Glomeromycota sequences were eliminated from the data set. Sequences with low numbers of clones ( 2) and those detected in only one replicate were also eliminated from analysis. The remaining sequences were aligned with ClustalX v (Thompson et al. 1997) and clustered into operational OTUs according to 97% sequence similarity using the furthest neighbor algorithm in the DOTUR program (Schloss and Handelsman 2005). Operational taxonomic units with 97% identity to published sequences were defined as new phylotypes in our study. To estimate phylogenetic relationships among OTUs, up to three representative sequences from each OTU were selected (all sequences were used if there were fewer than three sequences per OTU and three sequences were randomly selected if OTUs contained more than three sequences). A total of 122 representative sequences, along with 28 reference sequences representing all families of the Glomeromycota (obtained from the NCBI GenBank) were aligned to construct a neighbour-joining tree using distance criteria as implemented in PAUP v. 4.0 (Sworfford 2003) with Blastocladiella enersonii (X 54264) as the outgroup. Confidence in the resulting topology was tested by bootstrap analysis with 1000 replicates. Branches of the phylogenetic tree with less than 50% bootstrap replicates were allowed to collapse. Representative sequences obtained from this study were deposited in GenBank under accession numbers KM KM Statistical analysis Elevation-specific estimates of annual air temperature and erythemal UV dose rates were accompanied with the caveat that these estimates are only approximate. The mean annual air temperature at different sampling sites in 2011 was determined from weather records using an elapse rate of 0.53 o C/km for the eastern slope and 0.74 o C/km for the western slope, respectively, which were determined by using the climate data from 11 meteorological stations in the Mila Mountain region (29 N, E; 29 N, E for the eastern and western slopes, respectively; data provided by the Tibet Climate Data Center). Erythemal UV dose rates were estimated from the data of Dahlback et al. (2007), and showed an increasing rate of 7 8% per km for clear-sky and snow-free conditions from 3000 to 5000 m elevation at 29 Nlatitude in Tibet. Soil and vegetation characters are presented as the mean values (Table S1) and significant differences among elevations were tested by one-way analysis of variance (ANOVA) followed by Fisher s least significant difference (LSD) at P < Analysis was done with the SPSS for Windows v software package (SPSS Inc., Chicago, IL). AM fungal richness/diversity To assess the sampling intensity, we computed sampling effort curves of AM fungal richness (Mao Tau) using ESTIMATES v. 8.0 (Colwell 2006). Taxon richness was quantified as the total number of OTUs or phylotypes within each AM fungal community. The Shannon Wiener Index was calculated with the R package Vegan (Li et al. 2014). To assess the relationships between elevation, air temperature and UV radiation and the phylotype diversity of the AM fungal community, we performed linear regressions of OTU richness and the Shannon Wiener Index on elevation, annual air temperature and erythemal UV dose rates (SigmaPlot v. 10.0). Similarly, relative abundance (RA) of the most abundant AM fungal families (i.e. Acaulosporaceae and Glomeraceae) and taxa (i.e. Aca-1 and Glo-7) were fitted against elevation in the same manner as described above. Changes in AM fungal community level The community composition of AM fungi was calculated on the basis of the clone numbers of each phylotype in a sample. The dissimilarities of AM fungal communities among different samples were calculated by nonmetric multidimensional scaling (NMDS) with the Bray Curtis distance, using the library of the R package Vegan (Oksanen 2013). We used the mean scores of NMDS1 and NMDS2 at each elevation to plot the NMDS ordination to show clearly the dissimilarities of AM fungal communities among elevations and vegetation types. To explore the relationships between environmental variables and AM fungal community composition, we fitted the environmental variables (i.e. annual air temperature, herb cover, plant diversity, vegetation type, ph, elevation, slope, available phosphorus, organic matter, total carbon, and total nitrogen) as vectors onto the NMDS plots using the function envfit from the R package Vegan (Oksanen 2013). We tested significant differences in AM fungal community composition between the eastern and western slopes of Mount Mila and among elevations of certain slope transects with a permutation-based nonparametric multivariate ANOVA (Per- MANOVA) in PC-ORD v (McCune and Mefford 2006). The

5 Liu et al. 5 comparisons of AM fungal communities among sampling sites with the same vegetation type were conducted in the same way. To investigate whether there was an effect of vegetation regardless of elevation, we performed a permutational matrix-based multivariate ANOVA with the adonis function in the R package Vegan, using AM fungal abundance as a response variable and vegetation and elevation as factors (Singh et al. 2014). We conducted an indicator species analysis to determine whether particular species made a greater contribution than others to the differences in AM fungal communities. For this purposeweusedthedufrêne Legendre indicator analysis (Dufrêne and Legendre 1997) as implemented by the indval function in the R package Labdsv (Davison et al. 2011). This indexvaries from 0 to 1 and is maximal if all examples of an OTU are distributed among all individuals of only one elevation or vegetation type. Species with indval values 0.25 and a P value <0.05 were selected as strong indicators in our study. In addition, we used the online database MaarjAM ( Öpik et al. 2010; status as of June 2014) to compare the AM fungal phylotypes obtained in our study with the AM fungi detected in other ecosystems. RESULTS Taxonomic features of the AM fungal community on Mount Mila A total of 4311 clones positive for AM fungi were selected from the 54 clone libraries and subjected to RFLP analysis. Of these, 4086 clones belonged to Glomeromycota; 225 clones that were putatively non-glomeromycota were excluded from analysis (Table S2). Eight-hundred and twenty-seven RFLP groups were defined, and 881 clones were sequenced. Six hundred and ninety-two sequences belonged to AM fungi and 189 non-am fungal and chimeric sequences were excluded. Sequences were classified into 52 different OTUs (42 and 36 OTUs on the eastern and western slopes of Mount Mila, respectively; 10 OTUs on the peak) (Table S3) based on sequence similarities ( 97%) determined by DOTUR analysis. Rarefaction suggests that some undetected taxa remained on the mountain (Fig. S1). Phylogenetic analysis reveals that the AM fungal community consisted of Acaulosporaceae (1706 clones, 41.75%), Glomeraceae (1430 clones, 35.00%), Diversisporaceae (469 clones, 11.48%), Ambisporaceae (93 clones, 2.28%), Pacisporaceae (57 clones, 1.40%), Gigasporaceae (49 clones, 1.20%), Paraglomeraceae (17 clones, 0.42%), Archaeosporaceae (9 clones, 0.26%), Claroideoglomeraceae (10 clones, 0.24%) and Geosiphonaceae (5 clones, 0.12%), which covered 91% of families (except for Sacculosporaceae, with insufficient evidence) of the latest Glomeromycota taxonomy reported by Schüβler and Walker (2013). Three clades (Unknowns 1 3) in our study could not be placed into the known families, especially Unknown-1 (137 clones, 3.35%) and Unknown-3 (100 clones, 2.45%), which might be considered new family-like clades (Table S3, Fig. S2). Fifteen of 52 OTUs in our study were previously undescribed ( 97% identity with published sequences; Table S3, Fig. S2). Two phylotypes, Aca-1 (1012 clones, 24.77%) and Glo- 7 (637 clones, 15.59%) were the most abundant at all sampling sites (Table S3). Search against the MaarjAM database We also searched our OTUs against the MaarjAM database and found that half of the OTUs (26 of 52) could be related to virtual taxa (with >97% identity, Table S5). Twenty-six phylotypes showed low similarity ( 97%) to the sequences of this data base (Table S5). Only 8 OTUs (i.e. Aca-16, Div-1, Div-4, Glo-1, Glo-9, unk-1, Cla-1 and Amb-1) have been found in all five climate zones, and most taxa were restricted to certain ranges. The second dominant out, Glo-7 in this study, has been detected only in four studies of the MaarjAM database (Table S5). Some taxa seemed to specialize in this extreme habitat, e.g. Ambispora fennica (Amb-1), which was first isolated from a subarctic region in Finland (62 30 N; Walker et al. 2007) and which was also previously detected in Tibet (Liu et al. 2011), has been rarely detected in other climatic regions. Species richness/diversity across the elevation gradient of the two studied transects The Shannon Wiener index decreased monotonically from the lowest to highest elevations on the eastern slope of Mount Mila and followed a unimodal pattern with a maximum index at midelevations (Fig. 1c and d). The OTU richness mirrored taxonomic diversity on the eastern slope but followed no pattern on the western slope (Fig.1a and b). There was no significant difference in OTU richness (F = 2.022, P = 0.161) or Shannon Wiener index (F = 1.666, P = 0.202) between AM fungal assemblages on the two slopes. Community level effects of elevation in different transects The composition of AM fungal communities was highly variable across the study sites at different elevations (Figs 2 and S3). Both slope transects showed significant variability in the composition of AM fungal communities across the elevation gradient, but the community patterns observed on the two transects were different. Samples from the eastern slope formed five separate communities according to the sample elevation range, showing that samples belonging to the different elevation zones harboured distinct communities. The western slope had samples arranged in a pattern on the NMDS plot from left to right. The analysis with PerMANOVA supports the existence of different distinct communities of AM fungi between the two slopes ofmountmila (F = 3.134, P = 0.006). Arbuscular mycorrhizal fungal communities were significantly influenced by elevation gradient on both the eastern (F = 6.607, P = ) and western (F = 2.299, P = 0.005) slopes. Statistically distinct AM fungal communities were found at the five elevation sites of the eastern slope (Table S4), but only four community pairs were found to be different on the western slope, i.e vs m a.s.l. (t = 2.149, P = 0.031), 4149 vs m a.s.l. (t = 1.623, P = 0.024), 4344 vs m a.s.l. (t = 2.097, P = 0.016) and 4525 vs m a.s.l. (t = 1.747, P = 0.021). A point worth emphasizing is that AM fungal communities on the peak of Mount Mila were statistically distinct from almost all of the other communities of AM fungi on both slopes, except for communities at the 4599 m a.s.l. sites. Different indicator OTUs were found at the five sites on the eastern slope, but only two elevations on the western slope had indicator species. Aca-9 was the indicator OTU for 4525 m a.s.l. and Glo-1 was the indicator for 4149 m a.s.l. Amb-1 was the only indicator OTU for the peak (Table S3). The elevation trends of the dominant AM fungi are shown in Fig. 3. Acaulosporaceae were more abundant at higher elevations but Glomeraceae were more abundant at lower elevations (Fig. 3a and b). Aca-1 showed an increasing trend toward abundance with increasing elevation, and Glo-7 showed no trend (Fig. 3c and d). Moreover, 40% of OTUs (21 of 52) showed limited distribution ranges, with some occurring at a single elevation site (Table S3).

6 6 FEMS Microbiology Ecology, 2015, Vol. 91, No. 7 Figure 1. Variation in OTU richness and Shannon Wiener Index of AM fungal communities across the elevation gradient of the eastern (a, c) and western (b, d) slopes of Mount Mila. Effect of vegetation type The surveyed vegetation types varied from Salix shrub and meadow, Sabina procumbens shrub, alpine Rhododendron shrub to alpine meadow for all three species on the eastern slope, and changed from Berberis shrub and meadow, Salix cupularis Seabuckthorn shrub, and Sabina procumbens shrub to alpine meadow for all of these latter species. The co-occurring vegetation Sabina procumbens shrub occupied a slightly higher elevation on the western slope than on the eastern slope (Table 1). Analysis of variance shows that irrespective of elevation, the vegetation on Mount Mila had a significant effect on the taxonomic richness of AM fungi (F = 7.580, P = 0.000) and on the Shannon Wiener index (F = 4.571, P = 0.002). The permutational multivariate analysis shows that variance in community similarity was significantly related to vegetation (r 2 = 0.44, P < 0.001) when controlled for elevation. The results of NMDS indicate that vegetation type (r 2 = 0.231, P = 0.001), herb cover (r 2 = 0.306, P = 0.001) and plant diversity (r 2 = 0.214, P = 0.002) were biotic attributes strongly associated with microbial community structure (Figs 2 and 4). Except for the Sabina procumbens shrub and the meadow and alpine meadow types, all other vegetation types formed distinct communities NMDS axis ph DIV Available P AT HCOV SOM NMDS axis E 4358 E 4449 E 4599 E 4796 E 5033 E 4841 W 4675 W 4525 W 4344 W 4149 W Figure 2. Nonmetric multidimensional scaling (NMDS) pattern of AM fungal communities along the elevations studied on Mount Mila. The stress value is Each point represents the centroid of the AM fungal community of five replicates per elevation (except 4149 m, four replicates) with vertical and horizontal bars depicting standard errors of means. Open symbols represent AM fungal communities from the eastern slope and solid symbols represent communities from the western slope. Significant (P < 0.05) vegetation and variables are fitted as vectors onto each ordination plot. Available P = Olsen phosphorus, ph = acidity, SOM = organic matter content, HCOV = herb cover, DIV = plant diversity, AT = annual air temperature.

7 Liu et al. 7 Figure 3. Changes in dominant AM fungal taxa across the elevation gradient regardless of slope. RA = relative abundance. NMDS axis NMDS axis1 Al Pr Rh Se Be Sa alpine meadow. No significant indicator OTU was found for Salix cupularis Seabuckthorn shrub or Sabina procumbens shrub (Table S3). Moreover, about 44% of OTUs (23 of 52) showed limited distribution ranges, occurring with single vegetation types (Table S3). Some vegetation types, e.g. Sabina procumbens shrub and meadow and alpine meadow, occupied more than one elevation on both slopes of Mount Mila. Statistically distinct AM fungal communities were found among the three sampling sites for alpine meadow vegetation types (4796 vs m a.s.l., t = 2.529, p = 0.009; 4796 vs m a.s.l., t = 1.510, P = 0.018; 4841 vs m a.s.l., t = 1.794, P = 0.022), whereas most of the comparisons showed no significant difference for the Sabina procumbens shrub types, except for the pair 4358 vs m a.s.l. (t = 2.427, P = 0.009). Figure 4. Nonmetric multidimensional scaling (NMDS) pattern of AM fungal communities from different types of vegetation on Mount Mila. The stress value is Each point represents the centroid of the AM fungal community of six different vegetation types, with vertical and horizontal bars depicting the SEs of means. Vegetation types comprise Al = alpine meadow, Pr = Sabina procumbens shrub, Rh = alpine Rhododendron shrub, Se = Salix cupularis-sea buckthorn shrub, Be = Berberis shrub, Sa = Salix shrub. (Fig. 4). There were seven indicators (Aca-5, Aca-11, Div-1, Scu- 1, Glo-10, Glo-11 and Glo-12) for Salix shrub, one (Aca-1) for alpine Rhododendron shrub, two (Glo- 1, Glo-7) for Berberis shrub and one (Amb-1) for Effect of abiotic factors Soil ph on the eastern slope of Mount Mila decreased with increasing elevation (regression analysis, r 2 = 0.182, P = 0.019) but increased with elevation on the western slope (regression analysis, r 2 = 0.238, P = 0.007). Available P, total N, and total C on the eastern slope followed a hump-shaped pattern (regression analysis, r 2 = 0.315, P = 0.006; r 2 = 0.219, P = 0.036; r 2 = 0.253, P = 0.020, respectively), whereas organic matter (SOM), total N and total C tended to decrease with increasing elevation (regression analysis, r 2 = 0.259, P = 0.005; r 2 = 0.393, P = 0.000; r 2 = 0.297; P = 0.002, respectively).

8 8 FEMS Microbiology Ecology, 2015, Vol. 91, No. 7 Annual air temperature had a positive effect on the taxonomic richness of AM fungi (r 2 = 0.227, P = 0.000) and on the Shannon Wiener index (r 2 = 0.147, P = 0.004), whereas the erythemal UV dose rate was significantly negatively related to taxonomic richness (r 2 = 0.159, P = 0.000) and the Shannon Wiener index (r 2 = 0.108, P = 0.015). The NMDS ordination reveals that AM fungal community composition was significantly influenced by annual air temperature (r 2 = 0.120, P = 0.042), ph (r 2 = 0.150, P = 0.015), available phosphorus (r 2 = 0.186, P = 0.008) and organic matter (r 2 = 0.206, P = 0.003) (Fig. 2). Further analysis of the relationships between ph and RA of the most abundant families and phylotypes of AM fungi shows that the RA of Glomeraceae and Glo-7 decreased with increasing ph (r 2 = 0.199, P = 0.000; r 2 = 0.265, P = 0.000) whereas the abundance of Aca-1 increased with increasing ph on the western slope of Mount Mila (r 2 = 0.295, P = 0.003). DISCUSSION Diversity and richness patterns with altitude Our first hypothesis, namely that a low diversity of AM fungi occurs at higher elevations, was partly supported by the findings in our study. We found that taxon diversity followed a decreasing trend with increasing elevation on the eastern slope of Mount Mila. However, the taxon richness and Shannon Wiener index of detected AM fungal communities at the 4149 m a.s.l. site on the western slope were not higher than those at other sites. This might be due to aboveground vegetation, as the herb cover and diversity were relatively low at this site (Table 1). Several studies have demonstrated a positive relationship between AM fungal species richness and both the biodiversity and productivity of plant communities (van der Heijden et al. 1998; Vogelsang, Reynolds and Bever 2006). In our case, plant diversity did not appear to be the determinant of AM fungal diversity. In addition, we found that herb cover and plant diversity appeared to be strongly correlated with both AM fungal richness (r = 0.562, P = 0.000; r = 0.281, P = 0.039, respectively) and the Shannon Wiener index (r = 0.451, P = 0.000; r = 0.306, P = 0.025), which provides further support for our hypothesis. These results agree with the findings in previous studies on the Tibetan Plateau which indicated that vegetation cover was the most important factor influencing the composition of the AM fungal community in plant roots (Liu et al. 2011). The AM fungal community was significantly less diverse at the higher elevations on Mount Mila, reflecting the typical overdominance of a single AM fungal taxon that is consistently observed across the environmental gradient (Dumbrell et al. 2010). Further analysis shows that Aca-1 constituted 24.8% of the total AM fungal abundance and 66.7% of the total AM fungal abundance on the peak of Mount Mila (Fig. 3; Table S3). These observed changes in community consistency, and restrictions on the localized abundance of AM fungal taxa, may indicate that spatial changes in resource availability affect intraspecific competition and resource partitioning in AM fungal communities (May, Crawley and Sugihara 2007). Air temperatures along elevation gradients decrease as the result of decreasing air pressure (Körner 1999). This implies a lower effective temperature sum during the growing season at the higher altitudes than at the lower altitudes on Mount Mila, with the consequence of less photosynthate to be shared with symbiotic fungi at the higher altitudes, as proposed by Haselwandter (1979) and Väre, Vestberg and Ohtonen (1997). We can then predict that fewer AM fungi can be sustained at the higher elevations, and especially on the peak. This potential mechanism is a plausible hypothesis for the diversity of AM species at different elevations, but requires further testing. We observed that some phylotypes seemed to disappear with increasing elevation. For example, six OTUs were restricted to the lowest sites on Mount Mila but no OTU was restricted to the peak (Table S3). These results indicate that some phylogenetic groups may be more sensitive to the harsher conditions and become less abundant as elevation increases, owing to the stress effects of higher elevations (low temperature, high UV radiation, etc.). These groups might include families such as Gigasporaceae, Pacisporaceae and Paraglomeraceae, which were common at the low elevation sites but were not found on the peak of Mount Mila. Community composition patterns with altitude Our findings support our second hypothesis that distinct communities of AM fungi occur at higher elevations relative to lower elevations. We found clear patterns in the community composition of AM fungi on Mount Mila. In most cases, different elevation zones harbored distinct communities, especially at sites on the peak and the eastern slope (Fig. 2, Table S4). The key driver of these differences in the composition of AM fungal communities across elevations is not clear. However, considering the strong correspondence between AM fungal community composition and some identifiable biotic and abiotic factors (Figs 2 and 4), it is likely that the fungi constituting these communities are responding to changes in environmental conditions, further highlighting the potential for niche differentiation in structuring these communities (Dumbrell et al. 2010). The majority of OTUs show limited distribution ranges, occurring at single elevations or with single vegetation types. These patterns are in accordance with the findings of Öpik et al. (2010), who showed a degree of species specificity of in relation to geographical distribution, climatic zone and ecosystem type after summarizing publicly available Glomeromycota DNA sequence data and associated metadata in MaarjAM. Some identifiable environmental parameters including vegetation variables (vegetation type, herb cover and plant diversity), attributes and air temperature, were shown to be responsible for the patterns of association observed between AM fungal community and elevation. Vegetation distribution is itself partly a product of topographic variation within the montane environment, with elevation, aspect, and slope being the three main topographic variables (Titshall, O Connor and Morris 2000). With control for elevation, vegetation significantly explained 44% of the variance in similarity of AM fungal communities on Mount Mila, indicating that the effect of elevation on AM fungal richness/diversity is related to vegetation change. Indicator species analysis showed that some taxa have a preference for distinct vegetation types, e.g. Aca-5 and Scu-1 tended to distribute only in Salix shrub and meadow (Table S3). We also found that 44% of OTUs showed limited distribution ranges, occurring in a single vegetation type. In contrast to vegetation, we found that SOM and available P and ph were the most important identifiable factors shaping AM fungal communities (Fig. 2). These findings agree with the finding in other studies that these factors play important roles in determining the structure of AM fungal communities (Dumbrell et al. 2010; Li et al. 2010; Liu et al. 2011). In particular, some dominant families and taxa were sensitive to changes in

9 Liu et al. 9 ph, indicating that niche differentiation based on ph might be structuring these communities. Future studies are needed to assess how abiotic factors drive the differentiation of AM fungal communities across environmental gradients. In addition to edaphic factors, climatic scenarios on the Tibetan Plateau are an important consideration. Alpine grasslands are characterized by harsh climatic conditions. Higher altitudes are usually associated with increasing environmental hostility, i.e. cold climate, short growth season, unfavourable nutrient conditions and modified vegetation (decreased plant biomass and cover), which in turn influence microbial activity and communities (Johnson et al. 2003; Ma et al. 2004; Antoninka, Reich and Johnson 2011). Climatic factors have been shown in several studies to be the strongest positive factors shaping elevation-related taxonomic richness/diversity patterns (Currie et al. 2004; Forister et al. 2010; Griffiths et al. 2011). The present study shows that air temperature significantly influenced the composition of AM fungal communities (Fig. 2). In addition, seasonal freezing and thawing is a very important ecological process in the Qinghai Tibet Plateau. Alternating freezing and thawing affect microbial communities by directly affecting the metabolic activity and reproduction of microbes and also by indirectly changing physical properties such as temperature, moisture, and rock weathering that are closely related to mechanical composition such as clay content (Wang et al. 2015). All this evidence might explain the habitat filtering of AM fungal assemblages along the elevation gradient. Rarefaction suggests that some undetected taxa remained in our study (Fig. S1). The sampling in the study was therefore likely to have been coarse-grained and might therefore have resulted in a greater amount of environmental heterogeneity within samples. Some bias might also have existed in the molecular method used in the study. Although cloning and Sanger sequencing permitted the detection and identification of AM fungi in situ without the need for recognizable morphological features, some limitation still exists. Nested PCR can affect quantitative data on the abundance of specific taxa. We attempted to decrease the PCR-related bias in our study by using high template concentrations and mixing several replicate PCR amplications (Polz and Cavanaugh 1998). Next- generation sequencing (NGS) approaches have recently given us unprecedented insight into AM fungal communities with sufficient depth to recover even rare taxa. In conclusion, this study provides strong evidence for the spatial distribution of AM fungal assemblages along the elevation gradient used in the study. Most OTUs showed limited distribution ranges, being restricted to single elevation sites or vegetation types. Spatial changes in AM fungal assemblages corresponded to changes in some identifiable factors including vegetation (type, cover and diversity), attributes (SOM, ph, and available P) and climate-based elevation variables (air temperature and UV radiation). However, we still need to quantify the remaining axes of the elevation niche of AM fungal taxa and to identify the environmental factors to which AM fungi are most sensitive. This may help us to fully understand the mechanisms that regulate the diversity, structure and composition of communities of functionally important taxa on the Qinghai Tibet Plateau. SUPPLEMENTARY DATA Supplementary data are available at FEMSEC online. ACKNOWLEDGEMENTS This work was supported by the National Natural Science Foundation of China (NSFC, Projects and ) and the innovative group grant of NSFC (No ). Conflict of interest. None declared. REFERENCES Antoninka A, Reich PB, Johnson NC. 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