Introduction

Ectomycorrhizal symbioses formed between special groups of fungi and plant fine roots, which are essential for plant growth through improving water uptake and nutrient acquisition1. In addition, ectomycorrhizal fungi (EMF) can improve their host partner adaptation to diverse stress conditions, such as pathogenesis, heavy-metal toxicity2,3, drought conditions4 and etc. Approximately 20,000–25,000 EMF species are estimated to exist in nature5,6 and ectomycorrhizal plants are often colonized by diverse EMF species, which comprised the important part of forest ecosystem, woodland system and shrub land. However, EMF community structure is correlated with the plant community status and mediate plant competition and also influenced by the environmental factors. Under drought conditions, ectomycorrhizae can improve the drought tolerance of plants by enhancing water uptake from soil via huge mycelial networks7 and regulating aquaporin function8. In the last several decades, regional and local droughts became more frequent due to the global climate change9 and the response of EMF communities to drought conditions is consequently drawing much attention.

Although EMF communities in drought/alkaline condition have been concerned, the documents were still limited. Some studies found decreases in EMF diversity with increasing moisture stress10,11, while others observed contradictory relationships12,13. In addition, drought may also cause a shift in EMF composition14,15. Gehring et al.14 revealed a considerable difference in EMF community composition associated with the pinyon pine (Pinus edulis) between a cinder site (drought and infertile) and a sandy-loam site (higher moisture and nutrients)14. To improve our understanding of how EMF communities are affected by drought and confounding factors in arid regions, we require more data, especially in Asian regions where few data are available so far.

The Loess Plateau of China (LPC) covers an area of ca. 640,000 km2 and is characterized by an arid and semi-arid climate. Long-lasting and large-scale water shortages have resulted in ecosystem degradation and serious soil erosion. Asian dust originating from the degraded LPC seriously affects natural environments and human health in much of East Asia, including China, Korea and Japan. Natural vegetation zones in the LPC change from forest to desert with the declining precipitation gradient from southeast to northwest16. Forest patches and fragmented forests in this region are dominated by ectomycorrhizal host species, such as pine, poplar, oak and birch. So far, EMF communities have only been investigated in Quercus liaotungensis forests within a narrow area17,18. For a comprehensive understanding of EMF communities in the LPC, the study of EMF communities in other host species from a wider region is needed. Such studies may be important for the reforestation of these degraded sites, given the massive impact of the degrading LPC on nature and human society in East Asia.

In this study, we investigated EMF communities in Populus simonii and Pinus tabuliformis patches within the forest-steppe zone and pine forests within the transitional and forest zones in the LPC. We attempt to address the following questions: (1) Are there special EMF communities associated with the poplar and Chinese pine in this arid region? (2) How do EMF community composition and structure change from the forest zone to the forest-steppe zone along the precipitation gradient? (3) If EMF community composition does change, which factors determine the EMF community structure in this region?

Results

EMF molecular identification

In total, we morphotyped 20,332 ectomycorrhizal tips (9,795 from poplar and 10,537 from pine) from 114 root samples (45 for poplar and 69 for pine). In total, 546 poplar tips and 887 pine tips were subjected to molecular analysis. We selected one well-amplified ITS PCR product from each morphotype in a given root sample for direct sequencing. Finally, we obtained 188 unique sequences (available in the International Sequence Database under accession numbers LC013704–LC013891). These unique sequences were classified into 116 operational taxonomic units (OTUs) (including 1 non-EMF OTU) at the 97% identity level, of which 39 OTUs were associated with poplar and 84 OTUs with pine. In general, 107 OTUs were assigned to known species or genera, while 10 OTUs remained unknown because of low identity with their closest matches. Twenty-four OTUs (7 from poplar, 18 from pine) belonged to Ascomycota and 91 (32 from poplar, 66 from pine) belonged to Basidiomycota. Tomentella (35 OTUs), Inocybe (16), Sebacina (16) and Geopora (7) were the most OTU-rich genera, while others had less than five OTUs. As shown in Supplementary Table S1, pine EMF included 19 lineages while only eight lineages were detected from poplar. Tomentella was the most OTU-rich genus both in poplar (15) and pine (24). Poplar had more Inocybe OTUs (11 vs. 6), but significantly less Sebacina OTUs (1 vs. 15) than pine. In total, 38 OTUs were singletons detected in a single root sample and only eight OTUs were shared between the poplar and Chinese pine.

EMF community richness

As shown in Table 1, the three poplar patches showed similar levels of EMF richness per site (18–20) or per root (3.07); the pine root samples from YC2 also had low root richness (2.79 ± 0.88), but the other two pine sites showed higher richness/root sample (YA: 3.60 ± 1.12, HL: 4.90 ± 1.32). The OTU accumulation curves showed that three poplar EMF communities and two pine EMF communities (YC2, YA) nearly reached plateau at the sample size of 30 after extrapolation and did not differ significantly according to 95% confidence intervals at the sample sizes of 15 or 30. The accumulation curve for the EMF community in HL did not show any sign of reaching asymptote, indicating that far more EMF species would be found with additional sampling (Fig. 1).

Table 1 Ectomycorrhizal colonization and diversity indices for each sample site.
Figure 1
figure 1

Accumulation curves of rarefied operational taxonomic units (OTUs) and their 95% confidence intervals (lines with terminal bars) at sample sizes of 15 and 30 for six sites.

QJ1, QJ2 and YC1 were poplar EMF communities; YC2, YA and HL were Chinese pine EMF communities.

EMF community structure

As listed in Table 1, the three poplar EMF communities had similar Shannon H’ values (2.11–2.74), which were also close to the pine EMF community from YC (2.65). In contrast, the HL and YA pine EMF communities had higher values for Shannon H’ and the Simpson index 1/D (HL: 3.31 and 13.3; YA: 2.95 and 15.99). In addition, the Bray-Curtis dissimilarity index for each site highly ranged from 0.74–0.93.

In terms of OTU composition (Supplementary Table S2), the three poplar EMF communities showed high similarity, of which, five OTUs (Geopora sp.1, Inocybe exilis, Inocybe sp. 3, Tomentella sp. 11 and Tomentella sp. 20) were common among the three sites. In contrast, no OTUs were shared among the three pine EMF communities. The HL pine stand shared more OTUs with YA (10) than with YC2 or the three poplar EMF communities. The Mantel test also revealed that EMF community similarities were significantly correlated with geographic distance (R = 0.49, P = 0.029). At the higher taxonomic level, as shown in Fig. 2, Tomentella and Inocybe occurred at all six sites. According to the cluster analysis, the six communities were clustered into two groups, that is, pine and poplar; the three poplar EMF communities clustered together and were dominated by a few lineages. Although the pine EMF communities formed a single cluster, they comprised more diverse EMF lineages, especially in HL.

Figure 2
figure 2

Relative abundances of ectomycorrhizal fungal (EMF) taxa at each site and cluster analysis of the six sites based on EMF compositions using the unweighted pair group method with arithmetic mean (UPGMA) method based on Bray–Curtis distance (bootstrap = 999).

At the genus level, Tomentella was the most abundant taxon at all sites excluding QJ1, where Geopora and Inocybe were more abundant. As shown in Fig. 2, Hebeloma and Cortinarius were specific to poplar, while several lineages, such as Amphinema and Cenococcum, were abundant in pine communities but absent from poplar communities. The poplar EMF communities were overwhelmed by three lineages, Tomentella, Inocybe and Geopora. In association with poplar, Tomentella was the most abundant/frequent lineage, with 15 OTUs and was found on 41 of 45 trees, followed by Inocybe (10 OTUs) on 33 trees and Geopora (5 OTUs) on 22 trees. At the species level, Geopora sp. 1 was the most frequent OTU, found on 17 trees, followed by Tomentella sp. 11 on 12 trees and Inocybe sp. 3 on 11 trees. For the pine forests, Tomentella (24 OTUs) was again the most abundant/frequent lineage from all three sites. YC2 was similar to the poplar EMF communities and Inocybe and Geopora were again abundant with over 10% relative abundance. At YA, however, Sebacina was the second most abundant with 33.6% relative abundance. At HL, Cenococcum (23.4%) and Sebacina (21.6%) were the second and third most abundant taxa, following Tomentella.

Correlation of environmental factors with EMF distribution patterns

Canonical correspondence analyses (CCA) were performed to characterize the correlation of environmental factors with the distribution of EMF OTUs. Analyses revealed that five soil factors and altitude explained 19.3% of the variance structuring EMF communities. Environmental fitting tests (permutations = 999) revealed that precipitation, altitude and four soil parameters (soil organic matter [SOM], total nitrogen [TN], pH and total phosphorous [TP]) had significant effects on the EMF communities (Table S3). In addition, non-metric multidimensional scaling (NMDS) ordination revealed that pine and poplar EMF communities were clearly separated. Environmental fitting tests (permutations = 999) also revealed that host type, DBH, precipitation and four soil parameters (SOM, TN, pH, TP) had significant effects on the EMF communities (Fig. 3, Table S4). We also used a indicator species analysis to revealed significant host preference of the EMF-OTUs (Table 2). For example, Geopora sp.1, Tomentella sp.11, Inocybe exilis, Inocybe sp.3 significantly preferred P. simonii while Cenococcum geophilum2, Suillus luteus to P. tabuliformis (Table 2). Results of EMF–forest type association strength test by indicator species analysis indicated that C. geophilum2, Tomentella sp.16 significantly preferred forest zones, Geopora sp.1, Tomentella sp.11 to forest-steppe zones, Sebacina sp.9, Sebacina sp.4, T. ferruginea, Tomentella sp.10, Sebacina sp.1, Sebacina sp.6, Tricholoma terreum and Geopora sp.3 to the transitional regions (Table S5).

Table 2 Indicator species analysis showing host preference of EMF OTUs which had relative abundance >1% on any host species.
Figure 3
figure 3

Non-metrical multidimensional scaling (metaNMDS, Stress: 0.061) of OTUs occurring on more than one tree for six sites and correlation with soil nutrients, climatic foctors and host.

Only significant correlations between NMDS structure and factors are shown (P < 0.001). PRE, precipitation; ALT, altitude; SOM, soil organic matter content; TN, total nitrogen; TP, total phosphorus.

Discussion

The LPC is known worldwide for its unique geographical conditions and severe soil erosion regions. Ecological restoration is necessary to mitigate water shortages and soil salinization16. In the present study, a total of 115 EMF species were identified from Po. simonii and Pi. tabuliformis, which have never been used for EMF research in this region, greatly improving the local EMF inventory. However, EMF communities in the forest-steppe zone were clearly less diverse than those in the forest zone and the transitional zone in this study, as well as those documented in Q. liaotungensis mature forests in the forest region, that is, 70 species from 30 samples18 and 135 RFLP types from 81 samples by ITS-RFLP analysis17. Poplar and pine patches in the forest-steppe zone exhibited early successional stages, while the pine site at HL and Q. liaotungensis reported by Zhang et al.17,18 were in late successional stages. Thus, the LPC may still harbor rich EMF species under drought and alkaline-saline stress when the forests mature.

Vegetation succession is a very complex process and shows several visible changes, such as the community structure and physiognomy of vegetation. This phenomenon has also been extended to the below-ground EMF communities in temperate forests undergoing primary and secondary succession19,20 and in subtropical forests undergoing secondary succession21. In this study, the below-ground EMF community was also sharply changed among forest successional stage in the LPC region. We found the EMF lineages Geopora and Inocybe were abundant in poplar forest at the early succession stage, but Cenococcum and Sebacina were abundant in late-successional pine forest. Similar results were also reported in many other temperate forest20,22,23.

Complex environmental factors changed from the forests zone to the forest-steppe zone with the variation of succession stage, for example, SOM, N, precipitation and mean temperature increased toward the forest zone, while TP content decreased. In this study, NMDS ordination illustrated that soil nutrients (pH, TN, TP and SOM), DBH and climatic factors (altitude and precipitation) co-influenced the EMF species distribution significantly. In addition, cluster analysis and NMDS ordination showed a clear separation of the pine EMF and poplar EMF communities, which may be due to the host effect. Obviously, a great phylogenetic distance exists between the poplar (angiosperm) and pine (gymnosperm). Although there were not enough site replicates in each ecological zone for either host species, the host effect on the EMF community structure in the arid region should be taken into consideration.

Drought and alkaline-saline conditions were the major soil edaphic characteristics in the LPC, which could potentially affect EMF distribution. Among edaphic variables, Tedersoo et al.24 pointed out that soil pH was one of the most important predictors of fungal OTU richness24. Yamanaka also found that EMF richness was greatest in slightly acidic to neutral soils and that the growth of EMF is depressed at higher pH conditions25. In the present study, soil pH ranged from 7.7–8.47 and was especially high in the forest-steppe zone (up to pH 8.67) in the LPC. Although available information about EMF communities in highly alkaline habitats is limited, Ishida et al.26 identified 11 EMF species in 25 root samples of Mongolian willow (Salix linearistipularis) growing in alkaline-saline soil (up to pH 9.2) in northeastern China26. Because we did not have enough replicates, it is still uncertain whether or not the difference in EMF richness between the forest zone and the forest-steppe zone observed in this study is related to soil pH.

Among the 115 OTUs identified in this study, lineages Tomentella (35 OTUs), Inocybe (16), Sebacina (16) and Geopora (7) were the most OTU-rich lineages. Indicator species analysis revealed that different EMF showed significant host or forest-type preference. Lineages Geopora and Inocybe significantly preferred Po. simonii and forest-steppe zone, while lineage Cenococcum to Pi. tabuliformis and mature forest zone. Similarly, Ding et al. reported that most of common EMF species showed significant preference to host plant species in subtropical evergreen broad-leaved forests27.

Lineage Inocybe often occur as a pioneer fungi in primary succession sites28,29 and are also frequently found in disturbed ecological conditions, such as mine wastelands2,3,30 and post-fire forestland31. In the present study, Inocybe was present at all six sites, however, there was a clear decreasing trend in its relative abundance from north (QJ) to south (HL), which is displayed in Fig. 2. This suggests that lineage Inocybe prefers drought conditions and thus may have important ecological roles in the dry LPC.

In addition, the lineage Geopora (7 OTUs) was also abundant in the forest-steppe zone (QJ1, QJ2 and YC2) but disappeared in the forest zone (HL). The mycorrhizal Geopora distributed widely in North America, Europe and East Asia and also involved diverse host plants including coniferous and deciduous, as well as orchid. At the same time, mycorrhizal sequences also revealed Geopora species did not show distinct geographical populations32. As reviewed by Tamm et al.32 many Geopora species preferred alkaline conditions32. Ishida et al.26 found that Geopora also dominated the Mongolian willow root systems in a severe alkaline conditions (up to pH 9.2)26. More recently, Gehring et al.33 observed the abundance of genus Geopora positively responded to the high parasitism, high competition and high herbivory trees33. Considering some Geopora members were also abundant in the forest-steppe region of the LPC with drought & alkaline soil conditions, Geopora could be defined as an important mutual partner for host plant resisting to the stress conditions.

In contrast to lineages Inocybe and Geopora, a lineage Cenococcum was abundant in the forest region (HL), but disappeared in the forest-steppe region (Fig. 2). C. geophilum is globally distributed and has been described as a drought-tolerant EMF species34, as well as an efficient root protective agent against drought35. However, the majority of previous studies have found C. geophilum presenting in mature forests. For example, C. geophilum was a dominant EMF species in a Q. liaotungensis forest on Dongling Mountain36 and in a Mediterranean Quercus ilex forest37. C. geophilum depends on sclerotia for dispersal and thus has a limited capability for long distance dispersal38. This fact could explain that it may take a long time for C. geophilum to reach those fragmented forest patches although C. geophilum exists in the LPC.

Conclusion

We identified several indigenous EMF resources associated with Po. simonii and Pi. tabuliformis in the LPC and highlighted the changes in pine EMF community richness and composition along arid eco-zones. Environmental factors, including soil factors, host species, DBH and precipitation, were significantly related to EMF community structure, although we could not isolate their effects because these conditions are significantly correlated with each other and as well as with successional factors in the region. The preference of some EMF lineages, such as Geopora and Inocybe, for drier and high pH habitats could contribute to the future applications of these species for improving survival and growth of host plants under drought conditions.

Methods

Site description

Sampling sites were selected in three categories of vegetation zones in the LPC, the forest-steppe zone, the forest zone and the transitional region between the two zones, from the north to south in northern Shaanxi Province, as shown in Fig. 4. These sites were located in a typical hilly-gully region of the LPC. The climate in this region, including the sampling sites, is classified as a temperate semiarid zone. The mean annual temperature ranges from 7.0–10.8 °C and the mean annual precipitation ranges from 500 to 612 mm (decreasing northward), where most of the rainfall occurs during the rainy season (July to September).

Figure 4
figure 4

Locations of sampling sites in the Loess Plateau, China.

Circles indicate poplar plots; triangles indicate pine plots. Maps generated using Arcgis10.2 (ESRI Inc. 2014).

In total, six forest stands were selected for sampling: four stands within the forest-steppe zone, including two sites (QJ1 and QJ2) in Qingjian County and two stands (YC1 and YC2) in Yanchuan County; one stand (YA in Yan’an City) within the transitional zone; and one site (HL in Huanglong County) within the forest zone. In addition, these stands could be classified into two types according to the forest composition: poplar (Po. simonii in QJ1, QJ2 and YC1) and Chinese pine (YC2, YA and HL). The poplar and Chinese pine were the only two ectomycorrhizal tree species used in the afforestation program within the forest-steppe zone, thus we selected these two species in this study.

All selected stands were pure forest, the individuals of Po. simonii or Pi. tabuliformis represented more than 90% of the total tree individuals and the other trees made up less than 10%. The associated vegetation at Po. simonii sampling sites QJ1, QJ2 and YC1 were mainly various shrubs and herbs, including Platycladus orientalis, Armeniaca sibirica, Lonicera spp., Spiraea spp., Stipa bungeana and Artemisia sacrorum. In YC2 and YA stands, ground plant species were few; only Platycladus orientalis and Stipa bungeana occurred. At HL, located in the forest zone, in addition to P. tabuliformis, the only other EMF hosts were occasional Quercus liaotungensis trees. In the shrub layer, Rosa xanthina, Cotoneaster spp., Syringa spp., Berberis amurensis, Spiraea spp. and Sophora davidii were frequent. On the forest floor there were herb species such as Bothriochloa ischaemum, Pedicularis spp., A. sacrorum, Artemisia giraldii and S. bungeana. The detailed information of the six sites, including latitude/longitude, altitude, site history, annual rainfall and temperature range, are given in Table 3.

Table 3 Location, sampling, host, climatic and soil characteristics of the study sites on the Loess Plateau.

Sampling strategy

We selected 15 poplar trees for collecting fine root systems from sites QJ1, QJ2 and YC1, respectively and 24, 15 and 30 pine trees from sites YC2, YA and HL, respectively. At each sampling site, the distance between the selected trees was maintained at >10 m, in an attempt to secure the independence of the samples. From each selected tree, a main root (~15–30 cm in length) with fine root tips was gently collected from a soil depth of 0–30 cm. All root systems were traced from the trunk to confirm the identity of the roots. The rhizosphere soil (~100 mL) was collected for chemical analyses. Meanwhile, the diameter at breast height (DBH) of each sampled tree was measured. Geographical coordinates and altitude were recorded using a Garmin eTrex Venture HC GPS (Garmin International Ltd, Olathe, Kansas, US).

Ectomycorrhizal morphotyping and molecular identification

After returning to the laboratory, the collected root samples were immediately washed to remove soil particles and morphotyped under a stereomicroscope (EZ4HD, Leica Microsystems, Germany) as described by Huang et al.3. Living ectomycorrhizal root tips were counted to determine colonization and then sorted into different morphotypes according to Agerer39. Approximately 5–10 replicates of the healthy ectomycorrhizal tips (or all, if fewer than five tips were available) for each morphotype from each root system were randomly selected, individually placed into 2.0-mL tubes and lyophilized for DNA extraction using a freeze dryer (FD5-2.5, Sim International Group Co. Ltd, USA). The total genomic DNA of the dried ectomycorrhizal tips was extracted via a modified cetyltrimethylammonium bromide (CTAB) method according to Huang et al.2 using a bead beater (MM400, Restch, Germany). Amplification by polymerase chain reaction (PCR) was carried out in 30-μL reactions containing 1.5 μL of template DNA, 15 μL of 2 × Taq MasterMix (Kangwei, Beijing, China), 12.3 μL deionized water and 0.6 μL fungal-specific primers ITS1-F and ITS440,41. PCR cycling parameters were as follows: 94 °C for 5 min; 35 cycles of 94 °C for 30 s, 53 °C for 30 s and 72 °C for 1 min; and a final 5 min 72 °C extension. The obtained PCR products were verified by electrophoresis on 1.5% agarose gels with the Bio-Rad Gel DocTM XR + system (Bio-Rad, CA, USA). Then one representative sample with a unique electrophoretic band within a root sample was selected, the electrophoretic band was cut and purified for sequencing using a QIAquick PCR Purification Kit (Qiagen, Inc., Valencia, CA). The direct sequencing of the PCR products using primers ITS1-F/ ITS1/ ITS4 was performed on an ABI Prism 3730xl genetic analyzer (Applied Biosystems, Foster City, CA). Because we found that replicates from the same morphotype within the same root sample almost all had similar band sizes and sequences (sequence identity ≥99.5%), replicates from the same morphotype were usually treated as the same operational taxonomic unit (OTU).

The obtained sequences were first edited and manually corrected in BioEdit 7.0.8 (http://www.mbio.ncsu.edu/BioEdit/bioedit.html). The redundant sequences (the same sequence with the same/different length) were then removed, retaining the unique sequences for further analysis. The unique sequences were clustered into species-level OTUs at the 97% sequence identity threshold using BLASTclust (http://toolkit.tuebingen.mpg.de/blastclust)42. To further confirm distance, we performed pairwise alignment analysis on the sequences’ inner-OTUs and neighbor-OTUs using BioEdit. Annotation of OTUs was performed by running BLASTn and MegaBlast searches of sequences using one representative sequence from each OTU against UNITE and the International Sequence Database (DDBJ/EMBJ/GenBank), separately. Sequences with ≥97% ITS identity to a known fungal species were identified as that species and sequences with 90–97% identity to a known species were identified to the genus level43. When Blast results showed poor matches (<90% ITS identity), we treated the OTUs as unknown species. All sequences were submitted to the DNA Data Bank of Japan (DDBJ).

Soil chemical analyses

Soil samples were air-dried for one week and then stones and roots were removed. Half of each soil sample was then ground and passed through a 1-mm mesh screen for pH and electrical conductivity (EC) determination; the rest was passed through a 100- mesh sieve for soil elemental analyses. Soil pH and EC were measured using a FE20 pH meter (Mettler-Toledo Instrument Co., Ltd., Shanghai, China) and a DDS-307 Conductivity Meter (Shanghai REX Instrument Factory, Shanghai, China) after mixing the soil sample with deionized water at 1:2 and 1:5 ratios by volume, respectively. Soil organic matter (SOM) was determined by the Walkley–Black method44, by use of FeSO4 titration based on the oxidation of organic matter in soil by K2CrO7 and concentrated sulfuric acid. After digestion by sulfuric acid and perchloric acid, total phosphorus (TP) was determined by the molybdenum antimony colorimetric method45 using an ultraviolet spectrophotometer (UV-2450, Shimadzu Corporation, Kyoto, Japan) and total nitrogen (TN) was determined using the Kjeldahl method with a continuous flow analytical system (AutoAnalyzer3, Bran + luebbe, Hamburg, Germany).

Data analysis

One-way analysis of variance (ANOVA) was used to compare the soil parameters (SOM, TN, TP, pH, EC) among the six sites, respectively. The ectomycorrhizal rate was defined as the percentage of ectomycorrhizal root tips in each root sample and was also compared among the six sites by one-way ANOVA after log transformation. The relative abundance of a given EMF taxon in a root sample was calculated as its percentage in the ectomycorrhizal root tips. The relative abundance in each sample was pooled to calculate the relative abundance at a site. The frequency of each EMF taxon was the number of trees in which a given taxon was detected at each site.

To evaluate the potential species richness at each site and compare the species richness among the six sites, species accumulation curves were constructed using the rarefaction method and then extrapolated to the same sample size (n = 30) for those sites with <30 samples using EstimateS46. The richness estimators (Jackknife1, Jackknife2 and Chao2 estimators) and diversity indices (Shannon–Wiener H’ and Simpson’s 1/D) were also calculated for each site using EstimateS. In addition, one-way ANOVA was performed on the richness and diversity indices among different communities. The Bray-Curtis dissimilarity index was also calculated for each site to measure their beta diversity using ‘vegdist’ in the vegan package of R program. The similarity in OTU composition between sites was calculated using the Morisita–Horn index based on the presence/absence data matrix. Cluster analysis of the six sites was performed based on the EMF OTU compositions using unweighted pair group method with arithmetic mean (UPGMA) method (Bray–Curtis distances, bootstrap = 999).

The mantel test was used to evaluate the effect of distance isolation through correlation between geographical distances and Bray–Curtis distances of EMF composition47. The geographical distances were obtained from GPS coordinates of the six sites using the function “distm” in the ‘geosphere’ package in R. The following statistical analyses were performed using the ‘vegan’ package in R. The effect of EMF composition on site ordination was illustrated by non-metric multidimensional scaling (NMDS, meta-MDS function) based on Bray–Curtis distances. The correlation of soil and climate parameters with NMDS ordination structure was tested by permutation tests (environmental fitting test, Envfit function, 999 permutations). Canonical correspondence analysis (CCA) was performed to determine the effects of precipitation, altitude and soil parameters on EMF communities. Indicator species analysis was performed to evaluate the host and forest types preference of EMF-OTUs48,49. Point biserial correlation coefficient (rpb) was an available indices, which was computed between a quantitative variable of species abundance data and a binary variable indicating whether the site belongs to a site group combination under study, or not27. The detailed definition of rpb index see De Cáceres and Legendre48. Two independent tests had been conducted for the preference of EMF OTUs to hosts and forest type. A higher rpb value indicates a stronger association strength between EMF and hosts (forest types). Finally, the statistical significance of this relationship is tested using a permutation test. These statistical analyses were performed using the function multipatt () of the indicspecies package in R-language.

Software

Data analysis was completed by EstimateS 9.1.0 and R version 3.2.0. Figures were plotted by Arcgis10.2 and R 3.2.0.

Additional Information

How to cite this article: Long, D. et al. Ectomycorrhizal fungal communities associated with Populus simonii and Pinus tabuliformis in the hilly-gully region of the Loess Plateau, China. Sci. Rep. 6, 24336; doi: 10.1038/srep24336 (2016).