Arbuscular mycorrhizal fungal community recovers faster than plant community in historically disturbed Tibetan grasslands

Soil Biology and Biochemistry 134 (2019) 131–141

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Arbuscular mycorrhizal fungal community recovers faster than plant community in historically disturbed Tibetan grasslands

T

Lin Maoa,b,1, Jianbin Pana,1, Shengjing Jiangb, Guoxi Shic, Mingsen Qina, Zhiguang Zhaoa, Qi Zhanga, Lizhe Ana, Huyuan Fenga, Yongjun Liua,∗ a

MOE Key Laboratory of Cell Activities and Stress Adaptations, School of Life Sciences, Lanzhou University, Lanzhou, 730000, China State Key Laboratory of Grassland and Agro-Ecosystems, Lanzhou University, Lanzhou, 730000, China c College of Bioengineering and Biotechnology, Tianshui Normal University, Tianshui, 741000, China b

ARTICLE INFO

ABSTRACT

Keywords: Mycorrhiza Succession Alpine meadow Disturbance Land degradation Community structure

The potential of arbuscular mycorrhizal (AM) fungi in ecological restoration has been appreciated increasingly, yet the successional patterns of AM fungal community and their relatedness with plants and ecosystem functions during the recovery of degraded lands remain poorly understood. Here, we examined synchronously the rootassociated AM fungal and plant communities as well as the ecosystem multifunctionality (EMF) in paired historically disturbed (topsoil was removed in the early 1980s) and undisturbed habitats of eight Tibetan grasslands. We found that, after three decades of natural recovery, AM fungal richness and community composition were similar in disturbed and undisturbed habitats, whereas vegetation coverage and plant species richness were still lower in disturbed habitat than that in undisturbed habitat. Higher abundance of AM plants was established in disturbed habitat, while the undisturbed habitat was dominated by less- or non-AM plant species. AM fungal species composition showed tight relationship with the species composition of all plants only in the disturbed habitat, while it was always correlated with the species composition of AM plants regardless of the historical disturbance. The EMF index was lower in disturbed habitat compared to that in undisturbed habitat, and it correlated positively with AM fungal richness in disturbed habitat. Our study shows that AM fungal community is more resilient to disturbance than plant community in Tibetan grasslands, and the findings suggest that rapid recovery of AM fungal community in degraded lands may potentially drive vegetation development and enhance ecosystem functions in the early stages of ecosystem recovery.

1. Introduction

soil microbial communities show promise in ecosystem restoration (Harris, 2009), in-depth understanding of the compositional and functional dynamics of these hidden organisms during ecosystem recovery is a prerequisite if these approaches are to be effective. Among soil microorganisms, the arbuscular mycorrhizal (AM) fungi (subphylum Glomeromycotina; Spatafora et al., 2016), which form mutualistic associations with the roots of c. 80% of land plant species (Smith and Read, 2008), are particularly renowned because they can promote plant nutrient uptake, especially phosphorus (P) and nitrogen (N) (Smith and Smith, 2011), and enhance host tolerance to biotic and abiotic stresses (Aroca et al., 2007; Liang et al., 2015). These fungi also play key roles in facilitating seedling establishment (van der Heijden, 2004), determining plant biodiversity and community dynamics (van der Heijden et al., 1998; Klironomos et al., 2011; Bennett et al., 2017), regulating nutrient cycling (Hodge and Fitter, 2010; Bender et al.,

Human-induced land degradation is worsening worldwide and threatening biodiversity and ecosystem functioning (Vitousek et al., 1997; Johnson et al., 2017). How to efficiently restore degraded lands is one of the biggest challenges for our societies. In most terrestrial ecosystems, diverse microorganisms inhabit in soils where they interact with plants and play crucial roles in biogeochemical cycles (Wardle et al., 2004; Falkowski et al., 2008). Due to the tight linkages between plants and soil communities, the potential of soil microbes in ecological restoration has been acknowledged (Kardol and Wardle, 2010). For instance, increasing evidence shows that inoculation with soil microbial communities can facilitate vegetation succession (De Deyn et al., 2003; Carbajo et al., 2011; Liao et al., 2018) and steer the direction of plant community development (Wubs et al., 2016). Though manipulations of

Corresponding author. Room 327, Tianyan Building, Lanzhou University, 222 South Tianshui Road, Lanzhou, 730000, China. E-mail address: [email protected] (Y. Liu). 1 These authors contributed equally to this work. ∗

https://doi.org/10.1016/j.soilbio.2019.03.026 Received 14 January 2019; Received in revised form 21 March 2019; Accepted 26 March 2019 Available online 30 March 2019 0038-0717/ © 2019 Elsevier Ltd. All rights reserved.

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2015) and increasing soil aggregation (Rillig and Mummey, 2006; Leifheit et al., 2015); and consequently, they contribute significantly to a range of ecosystem functions (van der Heijden et al., 2015; Powell and Rillig, 2018). Given the substantial benefits of AM fungi to plant growth and ecosystem functioning, their potential in ecological restoration has been appreciated increasingly (e.g. Richter and Stutz, 2002; Asmelash et al., 2016; Koziol and Bever, 2017; Wang, 2017). Nonetheless, application of AM fungi in the restoration of degraded lands is still limited, which is due partly to our poor understanding of the successional patterns of AM fungal community and their interactions with plants during ecosystem recovery. Strong changes in the species diversity and species composition of AM fungal communities have been observed frequently during secondary succession (e.g. Johnson et al., 1991; García de León et al., 2016b; Neuenkamp et al., 2018), but the underlying mechanisms influencing AM fungal succession remain largely unclear. In principle, AM fungal succession may not only depend on the regional pools of AM fungal species and their dispersal ability (Liu et al., 2009; García de León et al., 2016a), but also relate with the succession of plant species composition (Martínez-García et al., 2015). While AM fungi apparently possess low dispersal ability, recent evidence shows that many AM fungal taxa exhibit strong dispersal ability at both global and regional scales (Davison et al., 2015, 2018; García de León et al., 2016b), indicating that AM fungal dispersal ability may be not very important in determining the successional patterns of AM fungal communities. Since AM fungi are obligate symbionts (Smith and Read, 2008), it seems that AM fungal succession should be mostly determined by plant succession. To date, however, whether AM fungal community follows the changes in plant community or vice versa remain debated (Hempel, 2018). Hart et al. (2001) proposed the Driver (AM fungal community drives plant community) and Passenger (AM fungal community follows changes in plant community) hypotheses to describe the possible mechanisms for plant and AM fungal community changes over time, and Zobel and Öpik (2014) further introduced the Habitat hypothesis, which postulates that both communities follow changes in abiotic conditions. These hypotheses are difficult to be tested because manipulation of the fungal component in the field is still an obstacle (Zobel and Öpik, 2014). As an alternative, examining synchronously the successional patterns of plant and AM fungal communities may facilitate us to address these hypotheses and to better understand the determinants of AM fungal succession. AM fungal community often correlates strongly with plant community in many natural ecosystems (e.g. Landis et al., 2004; Hiiesalu et al., 2014), and both communities co-vary along environmental gradient (Liu et al., 2012; Van Geel et al., 2018). Strong correlations between plant and AM fungal communities have also been observed in different stages of secondary succession (García de León et al., 2016b), but their mutual relationship may weaken or even vanish over time, depending on the changes in mycorrhizal type of dominant plants (Johnson et al., 1991; Barni and Siniscalco, 2000). Recently, a field investigation in western Estonia found that the correlation strength of plant and AM fungal communities gradually weakened during regeneration succession of grasslands, where the dominance of obligate AM plants decreased with succession (Neuenkamp et al., 2018). Therefore, we can expect that the relationship between AM fungal and plant communities may vary with the recovery process of degraded ecosystems, especially when vegetation succession towards dominance of less- or non-AM hosts. To better understand the successional patterns and the possible determinants of AM fungal communities during natural recovery of degraded ecosystems, we studied simultaneously the root-associated AM fungal and plant communities in two contrasting successional habitats in eight Tibetan grasslands with extremely high altitude: one belongs to historically disturbed habitat (topsoil was removed due to the construction of highway in the early 1980s) and the other belongs to undisturbed natural habitat. Furthermore, since ecosystem

degradation does not only affect the biotic composition of ecosystems but also their functions (Kollmann et al., 2016), we also quantified the ecosystem multifunctionality (EMF; Hector and Bagchi, 2007) and determined its relatedness with plant and AM fungal communities in these two habitats. Using the undisturbed habitat as a reference, we can evaluate the recovery status and recovery potential of both biotic communities and ecosystem functions in the historically disturbed habitat. We hypothesize that AM fungal community recovers faster than plant community in formerly disturbed region (H1), since AM fungi are more efficient in dispersal than plants during secondary succession (García de León et al., 2016b), and most plant species in Tibetan grasslands are heavily dependent on clonal reproduction (Dong et al., 2015) and the germination rates of their seeds are extremely low (e.g. Kobresia pygmaea [the most dominant species on Tibetan Plateau]; Miehe et al., 2019). We also hypothesize that the correlation strength of plant and AM fungal communities in the disturbed habitat is stronger than that in undisturbed habitat (H2), because the undisturbed natural vegetation on the Tibetan Plateau is dominated by less- or non-AM plants (Liu et al., 2011). Finally, we hypothesize that the EMF index in undisturbed habitat is higher than that in disturbed habitat and that the recovery of EMF is mostly dependent on the recovery of plant biodiversity (H3). 2. Material and methods 2.1. Study site and sampling procedure This study was conducted on the central Tibetan Plateau, where the elevation is above 4000 m a.s.l., the mean annual temperature ranges between −3 and −7 °C, the mean annual precipitation is less than 450 mm, and the vegetation types mainly belong to alpine meadow or alpine steppe. On the mid-August 2012, we chose eight study sites along the Qinghai-Tibet highway from Xidatan to Amdo (c. 450 km), where some regions nearby the highway were destroyed historically due to the construction of highway three decades ago (Fig. S1). These study sites were natural grasslands before the highway construction, and some sites had light grazing by livestock when we collected samples. In each site, five 0.5 × 0.5 m2 plots (c. 3–8 m interval) were randomly selected in the historically disturbed (topsoil was removed obviously; < 30 m from highway) and adjacent undisturbed habitats (> 60 m from highway), respectively (Fig. S1). In each plot, we visually estimated the vegetation coverage, and then identified all plant species and recorded the number of individuals of each species. Subsequently, all plants in each plot were clipped to the soil surface to measure shoot biomass and nutrient contents. Finally, five soil cores (3.8 cm diameter × 25 cm depth) were collected randomly from each plot and mixed adequately as one sample in a sealed bag, resulting in a total of 80 samples. Subsamples for measuring soil moisture were stored in sealed aluminium boxes, and the remaining samples were stored in refrigerators and transported to laboratory. Fine live roots were separated carefully from each soil sample, washed cleanly and divided into two subsamples: one for measuring AM fungal colonization (stored at 4 °C for several days) and the other for DNA extraction (stored at −20 °C). Soil samples were air-dried, sieved (6 mm) and used for the analyses of spore density and extraradical hyphal length density of AM fungi, water-stable soil aggregates, and soil chemistry. 2.2. Analyses of AM fungal colonization, spore density and extraradical hyphae Roots were randomly selected from the root samples, cut into c. 1cm segments, cleared in 10% KOH (m/v), acidified in 2% HCl (v/v) and stained with 0.05% trypan blue (m/v). Percent root length AM colonization (%RLC), arbuscular colonization (%AC) and vesicular colonization (%VC) were quantified using the magnified intersection method (McGonigle et al., 1990). AM fungal spores were separated from 25-g 132

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soil using wet-sieving and sucrose centrifugation (Brundrett et al., 1994), and the spore density was calculated. Extraradical hyphae were extracted from 5-g soil and stained with trypan blue using the methods of Brundrett et al. (1994). AM fungal hyphae were distinguished from other fungal hyphae at 200 × magnification according to staining color and morphology (Jiang et al., 2018a), and the hyphal length density was measured by the grid-line intersect method (Brundrett et al., 1994).

submitted to the GenBank database (accession numbers MK334682 MK335216). All AM fungal sequences were submitted to BLAST against the online MaarjAM database (http://maarjam.botany.ut.ee; accessed June 2015; Öpik et al., 2010), and each sequence was grouped into an AM fungal virtual taxon (VT) according to the sequence identity (≥97%), query coverage (≥97%), e-value (< 1e-50) and BLAST bit score (the highest). The VT delimitation was reconfirmed and corrected by examining the maximum likelihood (ML) phylogenetic tree (T92 + G model) of our AM fungal sequences and the representative sequences of VTs in MaarjAM database, using the same methods and criteria described by Liu et al. (2015a). To elucidate the phylogenetic affiliation of our obtained VTs, we constructed an ML phylogenetic tree (T92 + G model) using the sequences including the representative sequences of our VTs, the representative sequences of AM fungal families (according to the taxonomy on http://www.amf-phylogeny.com) and the most closely related sequences from GenBank database. We delimited each VT into a corresponding AM fungal family according to the phylogenetic tree, and if a VT is related with a described morphospecies, we regarded this as a cultured taxon.

2.3. Analyses of soil aggregates, soil chemistry, plant biomass and plant nutrients Soil water-stable aggregates were separated using a wet-sieving shaker machine in which four sets of nested sieves (top to bottom: 4 mm, 2 mm, 1 mm, 0.25 mm and 0.038 mm) were parallelly installed. Twenty-five grams of soil from each sample were placed on the top sieve and submerged in water for 10 min, and then the nested sieves were gently oscillated in water for 10 min (amplitude: 4 cm; frequency: 30 cycles min−1). For each sample, five aggregate size classes (> 4, 2–4, 1–2, 0.25–1 and 0.038–0.25 mm diameter) were collected, dried (105 °C for 24 h) and weighed. Sand and water contents were corrected using the same methods described by Wilson et al. (2009). We defined the 0.038–0.25 and 0.25–1 mm size fractions as microaggregates, and the other three > 1 mm size factions as macroaggregates. Soil moisture was measured gravimetrically (dried at 105 °C for 24 h), and soil pH was measured in 1 M KCl (1:5 w/v). Soil organic C and total N were analyzed using the CHNS-analyzer system (Elementar Analysensysteme GmbH, Hanau, Germany) with the burning method at 450 °C and 1250 °C, respectively. Soil available P was determined colorimetrically following Mehlich-3 extraction (Mehlich, 1984). Soil available N (NO3N + NH4-N) was extracted using 2 M KCl (1:5 w/v) and analyzed using a FIAstar 5000 Analyzer (FOSS, Hillerød, Denmark). Easily extractable Bradford-reactive soil protein (EE-BRSP; Rillig, 2004) was extracted from 2-g soil and quantified by the Bradford dye-binding assay (Wright and Upadhyaya, 1998). All shoot samples were weighed after drying at 80 °C for 48 h, and the dried plants were grinded to powder for analyzing tissue N and P contents. The shoot N concentration was measured using the same method as employed to measure soil total N, and the shoot P was measured using the molybdate-blue colorimetric method after digestion with sulfuric acid.

2.5. Statistical analysis The data matrix of plant species composition was calculated on the basis of the individual numbers of each species in each sampling plot, and the matrix of AM fungal VT composition was based on the clone numbers of each VT in each sample (clone library). Based on the community matrices, we calculated the species/VT richness and the relative abundance of each species/VT in each sample, and also we examined the sampling effort curves of species/VT richness using ‘rarecurve’ function from R package ‘vegan’ (Oksanen et al., 2015). The possible AM status of each plant species was identified according to the records by Akhmetzhanova et al. (2012), Wang and Qiu (2006), and the observations in our research group (see more details in Table S1). The index of ecosystem multifunctionality (EMF) in each sampling plot was calculated based on twelve variables that include vegetation coverage, shoot biomass, shoot total N, shoot total P, root length AM colonization, extraradical hyphal density of AM fungi, soil total N, soil organic C, soil available N, soil available P, soil protein content (EE-BRSP), and soil total water-stable aggregates. These variables were selected because they are highly related with some ecosystem functions (e.g. nutrient capture and cycling, and soil stability) and were commonly used to calculate the EMF index in previous studies (e.g. Maestre et al., 2012; Jing et al., 2015; Soliveres et al., 2016). This index was calculated by the standard averaging approach (Maestre et al., 2012), that is, calculating the average of the z-scores of each of the twelve variables measured. Before analysis, all measured data were tested for normality using Shapiro-Wilk's test (‘shapiroTest’ function from ‘fBasics’ package; Wuertz et al., 2017) and data were arcsine square root transformed (for percentage variables) or ln(x+1) transformed when needed. All statistical analyses were performed using R version 3.4.1 (https://www.rproject.org/). The effects of historical disturbance on soil physico-chemical properties, plant and AM fungal variables, and EMF index were analyzed by linear mixed-effects (LME) model in which disturbance was treated as a fixed effect and plot nested within site (for the data in all sites) or only plot (for the data in each site) as random effects (‘lme’ function from ‘nlme’ package). We did not include study site as a fixed effect because we only focused on the effect of historical disturbance and different study sites were treated as spatial replications. Relationships between AM fungal variables with plant variables or soil aggregates were assessed using partial linear regression models, in which the environmental effects (including latitude, longitude, altitude, and soil physico-chemical or chemical variables) were partialled out (‘lm’ and ‘residuals’ functions from ‘stats’ package). We also used the same method to examine the relationships between EMF index and

2.4. Molecular analysis of AM fungal communities colonizing roots Eighty root samples were used for molecular analysis. For each sample, DNA was extracted from 100 mg of randomly selected root fragments using a Plant DNA Extraction Kit according to the manufacturer's instructions (Tiangen Biotech, Beijing, China). AM fungal communities were identified by a PCR-cloning-sequencing approach using the same procedure and conditions described by Liu et al. (2012). Briefly, we used a nested PCR to amplify the partial 18S rRNA gene of AM fungi, with a first primer combination of GeoA2-Geo11 (Schwarzott and Schüßler, 2001) and a second AM fungal specific primer pair NS31AML2 (Liu et al., 2011). The second PCR products were purified and used to construct clone libraries (80 in total), and then 48 putative positive clones in each library were re-amplified with NS31-AML2 and screened using restriction fragment length polymorphism (RFLP) with restriction enzymes HinfI and Hin1II. The RFLP patterns were only compared within each sample. One representative clone of each RFLP type in each sample was sequenced (833 sequences in total), and the remaining clones were classified by RFLP typing. All DNA sequences were checked for chimeras using the Uchime v.6 (Edgar et al., 2011) and compared with the published databases using the online BLAST search tool (https://blast.ncbi.nlm.nih.gov; accessed June 2015). All non-AM fungal and possibly chimeric sequences were removed from the dataset, and the remaining 535 AM fungal sequences were analyzed further. In total, 2778 AM fungal clones (72.3%) were identified from 3840 clones. All AM fungal sequences obtained in this study have been 133

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plant or AM fungal species richness, with exception that only geographical factors were controlled because some edaphic variables were used to calculate the EMF index. The dissimilarities in species composition of plant or AM fungal communities among samples were computed by non-metric multidimensional scaling (NMDS) with square root transformed data and Bray-Curtis dissimilarity measurement using the ‘metaMDS’ function from R package ‘vegan’ (Oksanen et al., 2015). To explore the relationships between community composition with biotic and abiotic factors, the environmental (geographical and soil physico-chemical) and/or plant variables were fitted onto the corresponding NMDS plots using ‘envfit’ function from ‘vegan’ package. Effects of historical disturbance on community composition (based on Bray-Curtis distance) or soil properties (Euclidean distance) were determined by permutational multivariate analysis of variance (PERMANOVA) with constraining permutations within sites (‘adonis’ function from ‘vegan’ package). Relationships between the species composition of plant and AM fungal communities (Bray-Curtis distance) or between community composition with environmental factors or EMF index (Euclidean distance) were examined using partial Mantel test (‘mantel.partial’ function from

‘vegan’ package). 3. Results 3.1. Vegetation and soil physico-chemical properties After three decades of natural recovery, the vegetation coverage, plant species richness and shoot biomass in formerly disturbed habitat were still lower than that in undisturbed habitat (Fig. 1a–c). However, plant nutrient contents in disturbed habitat were similar (tissue N) or even higher (tissue P) than that in undisturbed habitat (Fig. 1d and e). Plant species composition also varied in two habitats (F = 10.2, P < 0.001; Fig. 2a), with abundant AM plants established in disturbed habitat (Fig. 1f, Table S1). Variation in plant species composition was highly correlated with the majority of environmental factors (Fig. 2a), of which longitude (R2 = 0.30, P < 0.001) and soil pH (R2 = 0.29, P < 0.001) were the most two related geographical and edaphic factors, respectively. Partial Mantel tests also revealed tight relationships between environmental factors with the species composition of all plants or AM plants regardless of the historical disturbance (Table 1).

Fig. 1. Plant and AM fungal variables varied in historically disturbed and undisturbed habitats. The effects of historical disturbance on each variable were determined using linear mixed-effects models and the P-values are shown. N = 40 for each habitat. 134

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Fig. 2. Nonmetric multidimensional scaling (NMDS) ordinations based on Bray-Curtis distance showing dissimilarities of plant species composition (a) and AM fungal virtual taxon (VT) composition (b) in historically disturbed and undisturbed habitats. The points represent the mean scores (n = 5) of NMDS axis 1 and axis 2 of disturbed or undisturbed samples in each site (XDT, Xidatan; WDL, Wudaoliang; BLH, Beiluhe; WL, Wuli; KXL, Kaixinling; YSP, Yanshiping; TGLS, Tanggulashan; AD, Amdo). Bars represent the standard errors of NMDS scores. Ellipses with different colors indicate 95% confidence ellipses for each habitat. Site names are indicated for each point. Correlations between each community ordination with environmental and/or plant variables were tested and the significant (P < 0.05, in blue) and marginally significant (0.05 < P < 0.1, in grey) variables were shown. EE-BRSP, easily extractable Bradford-reactive soil protein. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) Table 1 Partial Mantel tests for the relationships between AM fungal virtual taxon (VT) composition and plant species composition, and their relationships with environmental factors or ecosystem multifunctionality (EMF) index using the data collected from disturbed samples, undisturbed samples or all samples. Mantel r- and Pvalues are shown. Matrix of

Control for

Species composition of all plants Disturbed

Undisturbed

All

r = 0.443, P = 0.001 r = 0.142, P = 0.077

r = 0.291, P = 0.001 r = 0.192, P = 0.001

Environment EMF index

AM fungal VT composition AM fungal VT composition

r = 0.320, P = 0.001 r = 0.258, P = 0.001

Matrix of

Control for

Species composition of AM plants Disturbed

Undisturbed

All

r = 0.354, P = 0.001 r = 0.075, P = 0.126

r = 0.150, P = 0.003 r = 0.237, P = 0.001

Disturbed

Undisturbed

All

r = −0.065, P = 0.772 r = 0.172, P = 0.002 r = 0.180, P = 0.005 r = 0.068, P = 0.208

r = −0.018, P = 0.609 r = −0.008, P = 0.511 r = 0.115, P = 0.039 r = −0.094, P = 0.797

r = −0.040, P = 0.678 r = 0.048, P = 0.129 r = 0.096, P = 0.023 r = −0.014, P = 0.560

Environment EMF index

AM fungal VT composition AM fungal VT composition

r = 0.281, P = 0.002 r = 0.305, P = 0.001

Matrix of

Control for

AM fungal VT composition

Environment Species composition of all plants Species composition of AM plants EMF index

Species composition of all plants Environment Environment Species composition of all plants

AM plants, plants that can form arbuscular mycorrhizal symbiosis (the species list of AM plants identified in this study is shown in Table S1 in the supporting materials).

135

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abundance of AM plants (Fig. 3e and f). The VT composition of AM fungal communities did not vary in these two habitats (PERMANOVA: F = 0.65, P = 0.61; Fig. 2b). Vector fitting revealed that, of the twentythree biotic and abiotic factors, only three geographic variables significantly (all R2 > 0.10, P < 0.03), and soil available N marginally (R2 = 0.07, P = 0.067), correlated with the ordination of AM fungal communities (Fig. 2b). Furthermore, AM fungal VT composition did not relate with environmental factors in each habitat, whereas it showed significant relationships with the species composition of all plants in disturbed habitat and with the species composition of AM plants regardless of the historical disturbance (Table 1).

Table 2 Soil physico-chemical properties varied in historically disturbed and undisturbed habitats. The effects of historical disturbance on each variable were determined using linear mixed-effects models and the P-values are shown.

Soil moisture (%) Soil pH Soil available N (mg kg−1 soil) Soil available P (mg kg−1 soil) Soil available N:P ratio Soil organic C (%) Soil total N (%) Soil C:N ratio Proportion of total aggregates (%) Proportion of macroaggregates (%) Proportion of microaggregates (%) EE-BRSP (mg kg−1 soil)

Disturbed

Undisturbed

P value

12.01 ± 1.16 8.16 ± 0.04 7.52 ± 0.72 5.15 ± 0.38 1.76 ± 0.21 1.76 ± 0.20 0.07 ± 0.004 31.19 ± 6.00 44.51 ± 2.71 15.72 ± 1.48 28.79 ± 1.73 0.83 ± 0.06

15.03 ± 2.38 7.94 ± 0.04 7.23 ± 0.39 3.76 ± 0.24 2.12 ± 0.13 1.35 ± 0.10 0.12 ± 0.01 11.82 ± 0.34 51.28 ± 2.58 24.00 ± 2.55 27.29 ± 0.96 1.22 ± 0.09

0.004 < 0.0001 0.579 < 0.0001 0.008 0.002 < 0.0001 < 0.0001 0.007 < 0.0001 0.664 < 0.0001

3.3. Ecosystem multifunctionality (EMF) and its relatedness with plant and AM fungal communities Significantly lower EMF index was detected in the disturbed habitat compared to that in undisturbed habitat (t = 4.41, P = 0.0001), though exceptions existed in several study sites (Fig. 5a). The EMF index correlated positively with plant species richness when all samples were analyzed, whereas it correlated positively with AM fungal VT richness in the disturbed habitat (Fig. 5b and c). Partial Mantel tests revealed that EMF index was related significantly or marginally with the species composition of all plants or AM plants but not with AM fungal VT composition when the datasets of disturbed, undisturbed or combined habitats were examined separately (Table 1).

EE-BRSP, easily extractable Bradford-reactive soil protein; N = 40 for each habitat.

Soil physico-chemical properties varied in two habitats, with significantly higher soil pH, available P and C:N ratio but lower soil total N, soil macroaggregates and EE-BRSP content in disturbed habitat compared to that in undisturbed habitat (all P < 0.0001; Table 2). PERMANOVA analysis of the matrix of soil physico-chemical variables further confirmed the distinct difference in soil properties between disturbed and undisturbed habitats (F = 10.5, P < 0.001).

4. Discussion Severe anthropogenic disturbance often causes decline in biodiversity. In our study sites, we do not know the status of both plant and AM fungal communities in the first few years of post-disturbance, but we can imagine that their diversity should be very low in the disturbed habitat because our disturbed plots were selected from those regions where the topsoil was obviously removed. After three decades of natural recovery, we found that the recovery of AM fungal community, in terms of both species diversity and species composition, had reached the level of undisturbed community, whereas the vegetation coverage and plant species richness were still lower in disturbed habitat compared to that in undisturbed habitat (Figs. 1 and 2). These results support our first hypothesis (H1) and corroborate a recent study in Estonian grasslands showing that AM fungal taxa recovered faster than plants during the recovery succession of abandoned gravel pits (García de León et al., 2016b). High resilience of AM fungal communities to changes in soil, vegetation or land use on relatively short timescales (several years to decades) has been reported in several ecosystems with moderate climate (e.g. Urcelay et al., 2009; Xiang et al., 2015; CarrilloSaucedo et al., 2018). Our findings agree with this and provide first evidence showing that AM fungal community is more resilient to disturbance than plant community in alpine grasslands with extremely high altitude. The recovery rates of biotic communities in disturbed lands are often attributed to their abilities in dispersal and establishment (Turley et al., 2017). In our case, we cannot rule out the fact that some AM fungal propagules could inhabit in the deep soil layers (e.g. 50–70 cm; Oehl et al., 2005) and survive in soils for few years without hosts (Pietikäinen et al., 2007), but the rapid recovery of AM fungal communities observed here and in a big excavation pit in a nearby site (soils with c. 3–5 m depth were removed for constructing railway; Zhang, 2015) strongly indicates that these fungi are efficient in both dispersal and colonization in degraded lands. For the plants, however, it is possible that their slow recovery may be due to the co-limitation of dispersal and establishment, because most plant species in Tibetan grasslands heavily rely on clone reproduction (Dong et al., 2015; Miehe et al., 2019). Regardless of the possible mechanisms influencing plant and AM fungal recovery, it is clear that some AM-plant species, especially the Poa annua and Potentilla bifurca (Table S1), became dominant

3.2. AM fungal abundance, diversity and community composition The mean root length AM colonization (%RLC) in disturbed habitat was about twice that in undisturbed habitat (Fig. 1g). Similar patterns were also found for the arbuscular and vesicular colonization in roots (Fig. 1h and i), while inverse patterns were observed for the extraradical hyphal length density and spore density in soils (Fig. 1j and k). The %RLC was correlated positively with the relative abundance of AM plants but negatively with plant species richness in both disturbed samples and all samples (Fig. 3a and b). In addition, the extraradical hyphal density of AM fungi showed positive relationships with plant species richness regardless of the historical disturbance (Fig. 3d), and also positive with the proportion of soil macroaggregates in undisturbed samples (R2 = 0.13, P = 0.025) and all samples (R2 = 0.06, P = 0.035). Twenty-eight AM fungal VTs, belonging to eight families of Glomeromycotina, were identified in our root samples (Fig. 4). Fourteen VTs are affiliated with the described morphospecies of AM fungi (cultured taxa), making up 14.9% of total AM fungal clones. Inspection of the VT accumulation curves shows that the majority of AM fungal diversity was captured in disturbed and undisturbed samples in each or all sites (Fig. S2). Taken as a whole, VT143 (affiliated to an unknown genus within Glomeraceae) was the most dominant VT (45.0% of total AM fungal clone number), and followed by VT295 (uncultured Rhizophagus; 17.6%) and VT56 (uncultured Claroideoglomus; 15.1%). We did not observe significant differences in the relative abundance of the cultured taxa (LME model, t = −0.63, P = 0.534) and the top five dominant VTs (each or combined; all P > 0.1) between disturbed and undisturbed habitats. Nonetheless, six VTs (all rare VTs with < 1% of abundance) were only detected in disturbed habitat, and also six VTs (2 VTs with > 1% of abundance and 4 rare VTs) were specific for undisturbed habitat (Fig. 4). Similar VT richness of AM fungi was detected in disturbed and undisturbed habitats (Fig. 1l), while the mean VT richness per plant species in disturbed habitat (0.95 ± 0.14, mean ± SE) was significantly higher than that in undisturbed habitat (0.49 ± 0.06) (t = −4.25, P < 0.0001). AM fungal VT richness did not relate with plant species richness, but it was correlated positively with the relative 136

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Fig. 3. Partial linear regressions of root length colonization, extraradical hyphal length density and virtual taxon (VT) richness of AM fungi versus the relative abundance of AM plants and plant species richness. Regression relationships were tested using the data collected from disturbed samples, undisturbed samples or all samples, respectively. Significant linear relationships (P < 0.05) are indicated with regression lines (pink line, disturbed samples; green line, undisturbed samples; black line, all samples). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

in disturbed habitat, and that the relative abundance of AM plants showed positive effects on both AM fungal colonization and diversity (Fig. 3). These findings suggest that AM fungi may facilitate the establishment of some plant species in disturbed lands, and which in turn contribute to the recovery and maintaining of fungal community. Nevertheless, some ingenious studies, such as manipulation of plant or AM fungal components in natural or artificial conditions (Klironomos et al., 2011; Jiang et al., 2018a), are needed to accurately demonstrate the causal relationship between AM fungal recovery and the dominance of AM-plant species in our study region. Through investigating synchronously the plant and AM fungal

communities, we found that AM fungal VT composition was correlated significantly with the species composition of all plants in the disturbed habitat but not in the undisturbed habitat, and that AM fungal VT composition always interrelated with the species composition of AM plants regardless of the historical disturbance (Table 1). These results support our second hypothesis (H2) and highlight that the information of plant mycorrhizal types should be taken into account in future studies on the relationships between plant and AM fungal communities (Neuenkamp et al., 2018). It has been shown that changes in mycorrhizal type (e.g. obligately vs. facultatively; AM vs. ectomycorrhizal) of dominant plants could result in striking variations in plant-AM fungal 137

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Fig. 4. Maximum likelihood phylogenetic tree inferred from representative sequences (with bold) of each AM fungal virtual taxon (VT) identified in this study and referenced sequences from the GenBank database. The topology of phylogenetic tree is displayed and the bootstrap values above 60% are shown. The means of relative abundances (%, proportion of AM fungal clone numbers) of each AM fungal VT in historically disturbed (Dis) and undisturbed (Undis) samples are joined onto this figure. The nomenclature of AM fungal VTs is according to the MaarjAM database (http://maarjam.botany.ut.ee/), and the nomenclature of AM fungal families is according to the current taxonomy described on http://www.amf-phylogeny.com.

relationship during succession (Barni and Siniscalco, 2000; Neuenkamp et al., 2018). This may be the fact in our case, because the disturbed habitat was dominated by AM plants while the undisturbed vegetation by Kobresia sedges (Table S1) that are traditionally regarded as less/ non-AM or ectomycorrhizal hosts (Wang and Qiu, 2006; Gao and Yang, 2010). Furthermore, insignificant relationships between plant and AM fungal communities have been frequently reported in Tibetan sedge-

dominated grasslands (e.g. Shi et al., 2017; Jiang et al., 2018a; Jiang et al., 2018b), indicating that AM may be not the dominant mycorrhizal type on the Tibetan Plateau. Thus, we can speculate that AM fungi would gradually give way to ectomycorrhizal fungi or other root endophytic fungi (e.g. dark septate endophytes; Pan et al., 2013; Kotilínek et al., 2017) with the recovery succession going on in our study sites. Surprisingly, we found that AM fungal VT composition did not 138

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Fig. 5. Ecosystem multifunctionality (EMF) index varied in historically disturbed and undisturbed habitats in each study site (n = 5) or all sites (n = 40) (a), and its relatedness with plant species richness (b) and AM fungal virtual taxon (VT) richness (c). For (a), the effect of historical disturbance on EMF index was determined using linear mixed-effects models, and the P-values are shown for each site (XDT, Xidatan; WDL, Wudaoliang; BLH, Beiluhe; WL, Wuli; KXL, Kaixinling; YSP, Yanshiping; TGLS, Tanggulashan; AD, Amdo) or all sites (shaded column). For (b) and (c), partial linear regression relationships were tested using the data collected from disturbed samples, undisturbed samples or all samples, respectively. Significant linear relationships (P < 0.05) are indicated with regression lines (pink line, disturbed samples; green line, undisturbed samples; black line, all samples). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

relate with the matrixes of abiotic environmental factors (Table 1), and also did not with the matrixes of geographic or soil properties (data not shown). These results do not support the widely accepted conclusion of that abiotic environments are important in determining AM fungal communities (e.g. Dumbrell et al., 2010; Xiang et al., 2014; Horn et al., 2017; Schappe et al., 2017; Van Geel et al., 2018). Given the tight relationships between AM plants with AM fungal richness and community composition (Table 1, Fig. 3), it is possible that AM fungal communities in our study region may be mostly affected by the presence/dominance of AM plants rather than the abiotic environments. In contrast to the insensitivity of AM fungal community to changing abiotic environments, plant community was always related with environmental matrixes in our case. These findings likely disagree with the Habitat hypothesis (that is, co-variation of plant and AM fungal communities with changes in abiotic conditions; Zobel and Öpik, 2014) and indicate that the assembly mechanisms of plant and AM fungal communities may respond differentially to changing abiotic environments in Tibetan grasslands (Liu et al., 2015b). As expected, the EMF index in disturbed habitat was significantly lower than that in undisturbed habitat (H3), indicating that the recovery of ecosystem functions was slow in the formerly disturbed

region. The EMF index often shows positive relationships with both plant and soil microbial diversity in natural ecosystems (e.g. Maestre et al., 2012; Jing et al., 2015; Fanin et al., 2018), because high biodiversity at multiple trophic levels is needed to sustain multiple ecosystem functions (Soliveres et al., 2016). In our study, however, the EMF index was correlated positively with only the plant species richness when all sampling plots were analyzed, and it showed tight relationships with plant species composition but not with AM fungal VT composition (Fig. 5, Table 1). These findings suggest that the recovery of ecosystem functions in our study sites may be mostly dependent on the vegetation recovery. Nonetheless, a positive correlation between AM fungal richness and EMF index detected in the formerly disturbed habitat indicates that high AM fungal diversity may also benefit the recovery of ecosystem functions in degraded Tibetan grasslands. It is worthy to note that, in our case, the EMF index can only reflect a small portion of ecosystem functions because this index was calculated using relatively limited variables (12 in total); moreover, four vegetation variables and only two AM fungal variables used to calculate the EMF index may potentially magnify the importance of plant community in influencing ecosystem multifunctionality. More ecosystem functions or related variables, such as soil enzymic activities, nitrification rates, 139

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nutrient retention, and litter decomposition (Maestre et al., 2012; Soliveres et al., 2016), are needed, and only then can we fully understand how to recover ecosystem functions in the degraded Tibetan grasslands. In summary, our study reveals that three decades of natural recovery can nearly completely recover AM fungal richness and community composition but slowly improve vegetation and ecosystem multifunctionality in historically destroyed grasslands on the Tibetan Plateau. Rapid recovery of AM fungal communities in disturbed lands may potentially drive the early succession of vegetation (García de León et al., 2016b) and enhance ecosystem resilience (Martínez-García et al., 2017). To our best knowledge, this is the first comprehensive assessment of the natural recovery of both biotic communities and ecosystem functions in degraded Tibetan grasslands. Considering the fact that natural recovery of plant community was extremely slow in our study region, some restoration strategies, such as turf transplants (Aradottir, 2012) and inoculation with late successional soil communities (Wubs et al., 2016), are encouraged to be used for accelerating the recovery of degraded lands in this unique ecosystem.

biogeography: isolation shapes the life history characteristics but not diversity of root-symbiotic fungal communities. ISME Journal 12, 2211–2224. De Deyn, G.B., Raaijmakers, C.E., Zoomer, H.R., Berg, M.P., de Ruiter, P.C., Verhoef, H.A., Bezemer, T.M., van der Putten, W.H., 2003. Soil invertebrate fauna enhances grassland succession and diversity. Nature 422, 711–713. Dong, S.K., Wang, X.X., Liu, S.L., Li, Y.Y., Su, X.K., Wen, L., Zhu, L., 2015. Reproductive responses of alpine plants to grassland degradation and artificial restoration in the Qinghai-Tibetan plateau. Grass and Forage Science 70, 229–238. Dumbrell, A.J., Nelson, M., Helgason, T., Dytham, C., Fitter, A.H., 2010. Relative roles of niche and neutral processes in structuring a soil microbial community. ISME Journal 4, 337–345. Edgar, R.C., Haas, B.J., Clemente, J.C., Quince, C., Knight, R., 2011. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200. Falkowski, P.G., Fenchel, T., Delong, E.F., 2008. The microbial engines that drive Earth's biogeochemical cycles. Science 320, 1034–1039. Fanin, N., Gundale, M.J., Farrell, M., Ciobanu, M., Baldock, J.A., Nilsson, M.-C., Kardol, P., Wardle, D.A., 2018. Consistent effects of biodiversity loss on multifunctionality across contrasting ecosystems. Nature Ecology & Evolution 2, 269–278. Gao, Q., Yang, Z.L., 2010. Ectomycorrhizal fungi associated with two species of Kobresia in an alpine meadow in the eastern Himalaya. Mycorrhiza 20, 281–287. García de León, D., Moora, M., Öpik, M., Jairus, T., Neuenkamp, L., Vasar, M., Bueno, C.G., Gerz, M., Davison, J., Zobel, M., 2016a. Dispersal of arbuscular mycorrhizal fungi and plants during succession. Acta Oecologica 77, 128–135. García de León, D., Moora, M., Öpik, M., Neuenkamp, L., Gerz, M., Jairus, T., Vasar, M., Bueno, C.G., Davison, J., Zobel, M., 2016b. Symbiont dynamics during ecosystem succession: co-occurring plant and arbuscular mycorrhizal fungal communities. FEMS Microbiology Ecology 92 fiw097. Harris, J., 2009. Soil microbial communities and restoration ecology: facilitators or followers? Science 325, 573–574. Hart, M.M., Reader, R.J., Klironomos, J.N., 2001. Life-history strategies of arbuscular mycorrhizal fungi in relation to their successional dynamics. Mycologia 93, 1186–1194. Hector, A., Bagchi, R., 2007. Biodiversity and ecosystem multifunctionality. Nature 448, 188–190. Hempel, S., 2018. Passengers and drivers of arbuscular mycorrhizal fungal communities at different scales. New Phytologist 220, 952–953. Hiiesalu, I., Pärtel, M., Davison, J., Gerhold, P., Metsis, M., Moora, M., Öpik, M., Vasar, M., Zobel, M., Wilson, S.D., 2014. Species richness of arbuscular mycorrhizal fungi: associations with grassland plant richness and biomass. New Phytologist 203, 233–244. Hodge, A., Fitter, A.H., 2010. Substantial nitrogen acquisition by arbuscular mycorrhizal fungi from organic material has implications for N cycling. Proceedings of the National Academy of Sciences of the United States of America 107, 13754–13759. Horn, S., Hempel, S., Verbruggen, E., Rillig, M.C., Caruso, T., 2017. Linking the community structure of arbuscular mycorrhizal fungi and plants: a story of interdependence? ISME Journal 11, 1400–1411. Jiang, S., Liu, Y., Luo, J., Qin, M., Johnson, N.C., Öpik, M., Vasar, M., Chai, Y., Zhou, X., Mao, L., Du, G., An, L., Feng, H., 2018a. Dynamics of arbuscular mycorrhizal fungal community structure and functioning along a nitrogen enrichment gradient in an alpine meadow ecosystem. New Phytologist 220, 1222–1235. Jiang, S., Pan, J., Shi, G., Dorji, T., Hopping, K.A., Klein, J.A., Liu, Y., Feng, H., 2018b. Identification of root-colonizing AM fungal communities and their responses to shortterm climate change and grazing on Tibetan Plateau. Symbiosis 74, 159–166. Jing, X., Sanders, N.J., Shi, Y., Chu, H., Classen, A.T., Zhao, K., Chen, L., Shi, Y., Jiang, Y., He, J.S., 2015. The links between ecosystem multifunctionality and above- and belowground biodiversity are mediated by climate. Nature Communications 6, 8159. Johnson, C.N., Balmford, A., Brook, B.W., Buettel, J.C., Galetti, M., Guangchun, L., Wilmshurst, J.M., 2017. Biodiversity losses and conservation responses in the anthropocene. Science 356, 270–275. Johnson, N.C., Zak, D.R., Tilman, D., Pfleger, F., 1991. Dynamics of vesicular-arbuscular mycorrhizae during old field succession. Oecologia 86, 349–358. Kardol, P., Wardle, D.A., 2010. How understanding aboveground–belowground linkages can assist restoration ecology. Trends in Ecology & Evolution 25, 670–679. Klironomos, J., Zobel, M., Tibbett, M., Stock, W.D., Rillig, M.C., Parrent, J.L., Moora, M., Koch, A.M., Facelli, J.M., Facelli, E., Dickie, I.A., Bever, J.D., 2011. Forces that structure plant communities: quantifying the importance of the mycorrhizal symbiosis. New Phytologist 189, 366–370. Kollmann, J., Meyer, S.T., Bateman, R., Conradi, T., Gossner, M.M., Souza Mendonça, M., Fernandes, G.W., Hermann, J.-M., Koch, C., Müller, S.C., Oki, Y., Overbeck, G.E., Paterno, G.B., Rosenfield, M.F., Toma, T.S.P., Weisser, W.W., 2016. Integrating ecosystem functions into restoration ecology—recent advances and future directions. Restoration Ecology 24, 722–730. Kotilínek, M., Hiiesalu, I., Košnar, J., Šmilauerová, M., Šmilauer, P., Altman, J., Dvorský, M., Kopecký, M., Doležal, J., 2017. Fungal root symbionts of high-altitude vascular plants in the Himalayas. Scientific Reports 7, 6562. Koziol, L., Bever, J.D., 2017. The missing link in grassland restoration: arbuscular mycorrhizal fungi inoculation increases plant diversity and accelerates succession. Journal of Applied Ecology 54, 1301–1309. Landis, F.C., Gargas, A., Givnish, T.J., 2004. Relationships among arbuscular mycorrhizal fungi, vascular plants and environmental conditions in oak savannas. New Phytologist 164, 493–504. Leifheit, E.F., Verbruggen, E., Rillig, M.C., 2015. Arbuscular mycorrhizal fungi reduce decomposition of woody plant litter while increasing soil aggregation. Soil Biology & Biochemistry 81, 323–328. Liang, M., Liu, X., Etienne, R.S., Huang, F., Wang, Y., Yu, S., 2015. Arbuscular mycorrhizal fungi counteract the Janzen-Connell effect of soil pathogens. Ecology 96,

Acknowledgements We are grateful to Gang Cheng, Haozhi Long, Baogui Zhang, Wanji Guo, Yuxing Chai and Jiajia Luo for field and laboratory assistance. We thank the two anonymous reviewers and the Editor for comments on earlier versions of the manuscript. This work was financially supported by the National Natural Science Foundation of China (41430749, 31570512, 31670433, 31600424, 31870494), China Postdoctoral Science Foundation (2016M602891), the Fundamental Research Funds for the Central Universities (lzujbky-2014-201, lzujbky-2017-50), and the State Key Laboratory of Frozen Soil Engineering (SKLFSE201602). Appendix A. Supplementary data Supplementary data related to this article can be found at https:// doi.org/10.1016/j.soilbio.2019.03.026. References Akhmetzhanova, A.A., Soudzilovskaia, N.A., Onipchenko, V.G., Cornwell, W.K., Agafonov, V.A., Selivanov, I.A., Cornelissen, J.H.C., 2012. A rediscovered treasure: mycorrhizal intensity database for 3000 vascular plant species across the former Soviet Union. Ecology 93, 689–690. Aradottir, A.L., 2012. Turf transplants for restoration of alpine vegetation: does size matter? Journal of Applied Ecology 49, 439–446. Aroca, R., Porcel, R., Ruiz-Lozano, J.M., 2007. How does arbuscular mycorrhizal symbiosis regulate root hydraulic properties and plasma membrane aquaporins in Phaseolus vulgaris under drought, cold or salinity stresses? New Phytologist 173, 808–816. Asmelash, F., Bekele, T., Birhane, E., 2016. The potential role of arbuscular mycorrhizal fungi in the restoration of degraded lands. Frontiers in Microbiology 7, 1095. Barni, E., Siniscalco, C., 2000. Vegetation dynamics and arbuscular mycorrhiza in oldfield successions of the western Italian Alps. Mycorrhiza 10, 63–72. Bender, S.F., Conen, F., van der Heijden, M.G.A., 2015. Mycorrhizal effects on nutrient cycling, nutrient leaching and N2O production in experimental grassland. Soil Biology & Biochemistry 80, 283–292. Bennett, J.A., Maherali, H., Reinhart, K.O., Lekberg, Y., Hart, M.M., Klironomos, J., 2017. Plant-soil feedbacks and mycorrhizal type influence temperate forest population dynamics. Science 355, 181–184. Brundrett, M., Melville, L., Peterson, L., 1994. Practical Methods in Mycorrhiza Research. Mycologue Publication, Ontario. Carbajo, V., den Braber, B., van der Putten, W.H., De Deyn, G.B., 2011. Enhancement of late successional plants on ex-arable land by soil inoculations. PLoS One 6, e21943. Carrillo-Saucedo, S.M., Gavito, M.E., Siddique, I., 2018. Arbuscular mycorrhizal fungal spore communities of a tropical dry forest ecosystem show resilience to land-use change. Fungal Ecology 32, 29–39. Davison, J., Moora, M., Öpik, M., Adholeya, A., Ainsaar, L., Bâ, A., Burla, S., Diedhiou, A.G., Hiiesalu, I., Jairus, T., Johnson, N.C., Kane, A., Koorem, K., Kochar, M., Ndiaye, C., Pärtel, M., Reier, Ü., Saks, Ü., Singh, R., Vasar, M., Zobel, M., 2015. Global assessment of arbuscular mycorrhizal fungus diversity reveals very low endemism. Science 349, 970–973. Davison, J., Moora, M., Öpik, M., Ainsaar, L., Ducousso, M., Hiiesalu, I., Jairus, T., Johnson, N., Jourand, P., Kalamees, R., Koorem, K., Meyer, J.-Y., Püssa, K., Reier, Ü., Pärtel, M., Semchenko, M., Traveset, A., Vasar, M., Zobel, M., 2018. Microbial island

140

Soil Biology and Biochemistry 134 (2019) 131–141

L. Mao, et al.

of soil chemistry and plant neighbourhoods in structuring fungal communities in three Panamanian rainforests. Journal of Ecology 105, 569–579. Schwarzott, D., Schüßler, A., 2001. A simple and reliable method for SSU rRNA gene DNA extraction, amplification, and cloning from single AM fungal spores. Mycorrhiza 10, 203–207. Shi, G., Yao, B., Liu, Y., Jiang, S., Wang, W., Pan, J., Zhao, X., Feng, H., Zhou, H., 2017. The phylogenetic structure of AMF communities shifts in response to gradient warming with and without winter grazing on the Qinghai–Tibet plateau. Applied Soil Ecology 121, 31–40. Smith, S.E., Read, D.J., 2008. Mycorrhizal Symbiosis, third ed. Academic Press, London. Smith, S.E., Smith, F.A., 2011. Roles of arbuscular mycorrhizas in plant nutrition and growth: new paradigms from cellular to ecosystem scales. Annual Review of Plant Biology 62, 227–250. Soliveres, S., van der Plas, F., Manning, P., Prati, D., Gossner, M.M., Renner, S.C., Alt, F., Arndt, H., Baumgartner, V., Binkenstein, J., Birkhofer, K., Blaser, S., Blüthgen, N., Boch, S., Böhm, S., Börschig, C., Buscot, F., Diekötter, T., Heinze, J., Hölzel, N., Jung, K., Klaus, V.H., Kleinebecker, T., Klemmer, S., Krauss, J., Lange, M., Morris, E.K., Müller, J., Oelmann, Y., Overmann, J., Pašalić, E., Rillig, M.C., Schaefer, H.M., Schloter, M., Schmitt, B., Schöning, I., Schrumpf, M., Sikorski, J., Socher, S.A., Solly, E.F., Sonnemann, I., Sorkau, E., Steckel, J., Steffan-Dewenter, I., Stempfhuber, B., Tschapka, M., Türke, M., Venter, P.C., Weiner, C.N., Weisser, W.W., Werner, M., Westphal, C., Wilcke, W., Wolters, V., Wubet, T., Wurst, S., Fischer, M., Allan, E., 2016. Biodiversity at multiple trophic levels is needed for ecosystem multifunctionality. Nature 536, 456–459. Spatafora, J.W., Chang, Y., Benny, G.L., Lazarus, K., Smith, M.E., Berbee, M.L., Bonito, G., Corradi, N., Grigoriev, I., Gryganskyi, A., James, T.Y., O'Donnell, K., Roberson, R.W., Taylor, T.N., Uehling, J., Vilgalys, R., White, M.M., Stajich, J.E., 2016. A phylumlevel phylogenetic classification of zygomycete fungi based on genome-scale data. Mycologia 108, 1028–1046. Turley, N.E., Orrock, J.L., Ledvina, J.A., Brudvig, L.A., 2017. Dispersal and establishment limitation slows plant community recovery in post-agricultural longleaf pine savannas. Journal of Applied Ecology 54, 1100–1109. Urcelay, C., Díaz, S., Gurvich, D.E., Chapin III, F.S., Cuevas, E., Domínguez, L.S., 2009. Mycorrhizal community resilience in response to experimental plant functional type removals in a woody ecosystem. Journal of Ecology 97, 1291–1301. van der Heijden, M.G.A., 2004. Arbuscular mycorrhizal fungi as support systems for seedling establishment in grassland. Ecology Letters 7, 293–303. van der Heijden, M.G.A., Klironomos, J.N., Ursic, M., Moutoglis, P., Streitwolf-Engel, R., Boller, T., Wiemken, A., Sanders, I.R., 1998. Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature 396, 69–72. van der Heijden, M.G.A., Martin, F.M., Selosse, M.-A., Sanders, I.R., 2015. Mycorrhizal ecology and evolution: the past, the present, and the future. New Phytologist 205, 1406–1423. Van Geel, M., Jacquemyn, H., Plue, J., Saar, L., Kasari, L., Peeters, G., van Acker, K., Honnay, O., Ceulemans, T., 2018. Abiotic rather than biotic filtering shapes the arbuscular mycorrhizal fungal communities of European seminatural grasslands. New Phytologist 220, 1262–1272. Vitousek, P.M., Mooney, H.A., Lubchenco, J., Melillo, J.M., 1997. Human domination of Earth's ecosystems. Science 277, 494–499. Wang, B., Qiu, Y.L., 2006. Phylogenetic distribution and evolution of mycorrhizas in land plants. Mycorrhiza 16, 299–363. Wang, F., 2017. Occurrence of arbuscular mycorrhizal fungi in mining-impacted sites and their contribution to ecological restoration: mechanisms and applications. Critical Reviews in Environmental Science and Technology 47, 1901–1957. Wardle, D.A., Bardgett, R.D., Klironomos, J.N., Setala, H., van der Putten, W.H., Wall, D.H., 2004. Ecological linkages between aboveground and belowground biota. Science 304, 1629–1633. Wilson, G.W.T., Rice, C.W., Rillig, M.C., Springer, A., Hartnett, D.C., 2009. Soil aggregation and carbon sequestration are tightly correlated with the abundance of arbuscular mycorrhizal fungi: results from long-term field experiments. Ecology Letters 12, 452–461. Wright, S., Upadhyaya, A., 1998. A survey of soils for aggregate stability and glomalin, a glycoprotein produced by hyphae of arbuscular mycorrhizal fungi. Plant and Soil 198, 97–107. Wubs, E.R.J., van der Putten, W.H., Bosch, M., Bezemer, T.M., 2016. Soil inoculation steers restoration of terrestrial ecosystems. Nature Plants 2, 16107. Wuertz, D., Setz, T., Chalabi, Y., Maechler, M., 2017. fBasics: Rmetrics - Markets and Basic Statistics. R Package Version 3042.89. https://CRAN.R-project.org/package= fBasics. Xiang, D., Verbruggen, E., Hu, Y., Veresoglou, S.D., Rillig, M.C., Zhou, W., Xu, T., Li, H., Hao, Z., Chen, Y., Chen, B., 2014. Land use influences arbuscular mycorrhizal fungal communities in the farming-pastoral ecotone of northern China. New Phytologist 204, 968–978. Xiang, X., Gibbons, S.M., Yang, J., Kong, J., Sun, R., Chu, H., 2015. Arbuscular mycorrhizal fungal communities show low resistance and high resilience to wildfire disturbance. Plant and Soil 397, 347–356. Zhang, Q., 2015. Influences of Different Vegetation Restoration Strategies on Soil Microorganisms in a Tibetan Alpine Steppe Ecosystem. PhD Thesis. Lanzhou University, Lanzhou. Zobel, M., Öpik, M., 2014. Plant and arbuscular mycorrhizal fungal (AMF) communities – which drives which? Journal of Vegetation Science 25, 1133–1140.

562–574. Liao, H.X., Huang, F.F., Li, D.J., Kang, L.Y., Chen, B.M., Zhou, T., Peng, S.L., 2018. Soil microbes regulate forest succession in a subtropical ecosystem in China: evidence from a mesocosm experiment. Plant and Soil 430, 277–289. Liu, Y., He, J., Shi, G., An, L., Öpik, M., Feng, H., 2011. Diverse communities of arbuscular mycorrhizal fungi inhabit sites with very high altitude in Tibet Plateau. FEMS Microbiology Ecology 78, 355–365. Liu, Y., He, L., An, L., Helgason, T., Feng, H., 2009. Arbuscular mycorrhizal dynamics in a chronosequence of Caragana korshinskii plantations. FEMS Microbiology Ecology 67, 81–92. Liu, Y., Johnson, N.C., Mao, L., Shi, G., Jiang, S., Ma, X., Du, G., An, L., Feng, H., 2015a. Phylogenetic structure of arbuscular mycorrhizal community shifts in response to increasing soil fertility. Soil Biology & Biochemistry 89, 196–205. Liu, Y., Mao, L., Li, J., Shi, G., Jiang, S., Ma, X., An, L., Du, G., Feng, H., 2015b. Resource availability differentially drives community assemblages of plants and their root-associated arbuscular mycorrhizal fungi. Plant and Soil 386, 341–355. Liu, Y., Shi, G., Mao, L., Cheng, G., Jiang, S., Ma, X., An, L., Du, G., Johnson, N.C., Feng, H., 2012. Direct and indirect influences of 8 yr of nitrogen and phosphorus fertilization on Glomeromycota in an alpine meadow ecosystem. New Phytologist 194, 523–535. Maestre, F.T., Quero, J.L., Gotelli, N.J., Escudero, A., Ochoa, V., Delgado-Baquerizo, M., García-Gómez, M., Bowker, M.A., Soliveres, S., Escolar, C., García-Palacios, P., Berdugo, M., Valencia, E., Gozalo, B., Gallardo, A., Aguilera, L., Arredondo, T., Blones, J., Boeken, B., Bran, D., Conceição, A.A., Cabrera, O., Chaieb, M., Derak, M., Eldridge, D.J., Espinosa, C.I., Florentino, A., Gaitán, J., Gatica, M.G., Ghiloufi, W., Gómez-González, S., Gutiérrez, J.R., Hernández, R.M., Huang, X., Huber-Sannwald, E., Jankju, M., Miriti, M., Monerris, J., Mau, R.L., Morici, E., Naseri, K., Ospina, A., Polo, V., Prina, A., Pucheta, E., Ramírez-Collantes, D.A., Romão, R., Tighe, M., Torres-Díaz, C., Val, J., Veiga, J.P., Wang, D., Zaady, E., 2012. Plant species richness and ecosystem multifunctionality in global drylands. Science 335, 214–218. Martínez-García, L.B., De Deyn, G.B., Pugnaire, F.I., Kothamasi, D., van der Heijden, M.G.A., 2017. Symbiotic soil fungi enhance ecosystem resilience to climate change. Global Change Biology 23, 5228–5236. Martínez-García, L.B., Richardson, S.J., Tylianakis, J.M., Peltzer, D.A., Dickie, I.A., 2015. Host identity is a dominant driver of mycorrhizal fungal community composition during ecosystem development. New Phytologist 205, 1565–1576. McGonigle, T., Miller, M., Evans, D., Fairchild, G., Swan, J., 1990. A new method which gives an objective measure of colonization of roots by vesicular-arbuscular mycorrhizal fungi. New Phytologist 115, 495–501. Mehlich, A., 1984. Mehlich 3 soil test extractant: a modification of Mehlich 2 extractant. Communications in Soil Science and Plant Analysis 15, 1409–1416. Miehe, G., Schleuss, P.-M., Seeber, E., Babel, W., Biermann, T., Braendle, M., Chen, F., Coners, H., Foken, T., Gerken, T., Graf, H.-F., Guggenberger, G., Hafner, S., Holzapfel, M., Ingrisch, J., Kuzyakov, Y., Lai, Z., Lehnert, L., Leuschner, C., Li, X., Liu, J., Liu, S., Ma, Y., Miehe, S., Mosbrugger, V., Noltie, H.J., Schmidt, J., Spielvogel, S., Unteregelsbacher, S., Wang, Y., Willinghöfer, S., Xu, X., Yang, Y., Zhang, S., Opgenoorth, L., Wesche, K., 2019. The Kobresia pygmaea ecosystem of the Tibetan highlands – origin, functioning and degradation of the world's largest pastoral alpine ecosystem: Kobresia pastures of Tibet. Science of the Total Environment 648, 754–771. Neuenkamp, L., Moora, M., Öpik, M., Davison, J., Gerz, M., Männistö, M., Jairus, T., Vasar, M., Zobel, M., 2018. The role of plant mycorrhizal type and status in modulating the relationship between plant and arbuscular mycorrhizal fungal communities. New Phytologist 220, 1236–1247. Oehl, F., Sieverding, E., Ineichen, K., Ris, E.A., Boller, T., Wiemken, A., 2005. Community structure of arbuscular mycorrhizal fungi at different soil depths in extensively and intensively managed agroecosystems. New Phytologist 165, 273–283. Oksanen, J., Blanchet, F.G., Kindt, R., Legendre, P., Minchin, P.R., O'Hara, R.B., Simpson, G.L., Solymos, P., Stevens, M.H.H., Wagner, H., 2015. Package 'vegan': Community Ecology Package. R Package Version 2.2-1. https://CRAN.R-project.org/package= vegan. Öpik, M., Vanatoa, A., Vanatoa, E., Moora, M., Davison, J., Kalwij, J.M., Reier, Ü., Zobel, M., 2010. The online database MaarjAM reveals global and ecosystemic distribution patterns in arbuscular mycorrhizal fungi (Glomeromycota). New Phytologist 188, 223–241. Pan, J., Liu, Y., He, X., Kang, S., Hou, Y., An, L., Feng, H., 2013. Arbuscular mycorrhizal and dark septate endophytic fungi at 5,500 m on a glacier forefront in the QinghaiTibet Plateau, China. Symbiosis 60, 101–105. Pietikäinen, A., Kytöviita, M.-M., Husband, R., Young, J.P.W., 2007. Diversity and persistence of arbuscular mycorrhizas in a low-Arctic meadow habitat. New Phytologist 176, 691–698. Powell, J.R., Rillig, M.C., 2018. Biodiversity of arbuscular mycorrhizal fungi and ecosystem function. New Phytologist 220, 1059–1075. Richter, B.S., Stutz, J.C., 2002. Mycorrhizal inoculation of big sacaton: implications for grassland restoration of abandoned agricultural fields. Restoration Ecology 10, 607–616. Rillig, M.C., 2004. Arbuscular mycorrhizae, glomalin, and soil aggregation. Canadian Journal of Soil Science 84, 355–363. Rillig, M.C., Mummey, D.L., 2006. Mycorrhizas and soil structure. New Phytologist 171, 41–53. Schappe, T., Albornoz, F.E., Turner, B.L., Neat, A., Condit, R., Jones, F.A., 2017. The role

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