Ectomycorrhizal community structure varies among Norway spruce (Picea abies) clones

Authors


Author for correspondence: Tiina Korkama Tel: +358 10 2112400 Fax: +358 10 2112204 Email: tiina.korkama@metla.fi

Summary

  • • In northern boreal forests, the diversity of ectomycorrhizal (ECM) species is much greater than that of their host trees. This field study investigated the role of individual trees in shaping the ECM community.
  • • We compared ECM communities of eight Norway spruce (Picea abies) clones planted in a clear-cut area in 1994 with a randomized block design. In 2003, the ECM fungi were identified from randomly sampled root tips using denaturing gradient gel electrophoresis (DGGE) and rDNA internal transcribed spacer (ITS) sequence similarity.
  • • ECM diversity varied among clone groups, showing twofold growth differences. Moreover, according to detrended correspondence analysis (DCA), ECM community structure varied not only among but also within slow-growing or fast-growing clones.
  • • Results suggest that ECM diversity and community structure are related to the growth rate or size of the host. A direct or indirect influence of host genotype was also observed, and we therefore suggest that individual trees are partly responsible for the high diversity and patchy distribution of ECM communities in boreal forests.

Introduction

Ectomycorrhizal (ECM) communities of northern boreal forests are typically diverse and spatially heterogeneous (Lilleskov et al., 2004). The number of described macrofungal ECM species is more than 700 (Dahlberg, 2002) and the eventual tally of all ECM species is likely to be much higher. In contrast to the great diversity of ECM, the number of host tree species in Fennoscandia is very low. However, while Norway spruce (Picea abies), Scots pine (Pinus sylvestris) and two species of birch (Betula pendula and Betula pubescens) cover approximately 98% of the forest soil in Finland (Peltola, 2004), genetic variation within populations of conifers is high (Muona, 1990).

Host tree communities influence ECM diversity as a result of symbiotic specificities (Molina et al., 1992) and through variation in the quantity and quality of the resources they provide (Priha et al., 1999; Kernaghan et al., 2003). Nutrient partitioning, disturbance, competition and interaction with other organisms have been suggested to be important determinants of local ECM diversity (Bruns, 1995). Symbioses between fungi and trees are determined by soil type, environmental conditions, availability of inoculum, competition, existing microflora and microfauna, and the age, vigor and genotype of the host tree (Deacon & Fleming, 1992).

Plant resistance to pathogenic (Burdon, 2001) and endophytic fungi (Saikkonen et al., 2003) is known to have a genetic basis. Probably because of the practical difficulties of investigating the complex and delicate symbioses of ECM fungi and trees in the field, the influence of the genetic variation of the hosts on ECM fungi is poorly understood. Pairings of host trees and their ectomycorrhizas can be identified by tracing the roots by hand (Lilleskov et al., 2002), but nowadays molecular identification methods are also available (Saari et al., 2005). While variation in dominant ECM species among individual trees has been noted (Gehring et al., 1998), and it has been demonstrated that host tree genotype affects the degree of colonization by ECM isolates in vitro (Tonkin et al., 1989; Tagu et al., 2001, 2005), the patterns and interactions of individual trees and natural ECM communities remain largely unknown.

The aim of this study was to investigate the factors associated with ECM community structure in Norway spruce. We formed the hypothesis that ECM communities associated with individual trees of the same age and species vary significantly, and that differences in ECM community structure covary with differences in host tree growth rates. A trial of clonal Norway spruce with randomized blocks enabled a comparison of the ECM community structures of individual trees of the same age in situ and evaluation of the relationship between tree growth rate and ECM community.

Materials and Methods

Description of the study site and experimental design

The study was performed on a Norway spruce [Picea abies (L.) Karst.] clonal field trial established in 1994 by the Foundation for Forest Tree Breeding in Central Finland (62°10′ N, 27°16′E). The trial consisted of the cloned open-pollinated offspring of trees selected from the basic breeding population and the cloned offspring from controlled crosses among them. Maternal trees originated in southern Finland, Estonia and Germany (Table 1). All clones were generated in spring 1992 using rooting cuttings taken from seedlings a few years old and maintained under similar conditions in peat pots at the same location. Thus the nursery conditions provided seedlings with equivalent ECM inoculum before out-planting. The study site had a podsolized, fine sand moraine soil with an average humus depth of 5.9 cm. Before clear-cutting in 1991, the vegetation was Myrtillus type (MT) (Cajander, 1949) with the dominant tree species being Norway spruce. Nowadays, Festuca ovina L., Calamagrostis arundinacea (L.) Roth and Vaccinium vitis-idaea L. dominate the undergrowth vegetation.

Table 1.  Origins of the mother trees of the Norway spruce (Picea abies) clones and height of the spruce clones in autumn 2002
 Height (cm)Origin of mother trees of clones
  1. Values are means [± standard error (SE); n = 3]. Means (± SE; n = 12) of growth performance groups are shown in bold.

Slow-growing  spruce clones158.7 ± 7.9 
 S1142.0 ± 9.3Southern Finland/Germany
 S2161.5 ± 23.4Southern Finland
 S3161.7 ± 17.1Southern Finland/Germany
 S4169.8 ± 15.1Southern Finland × southern  Finland/Germany
Fast-growing  spruce clones280.4 ± 8.2 
 F1259.3 ± 14.9Southern Finland × southern  Finland/Germany
 F2267.0 ± 6.3Estonia
 F3292.2 ± 14.1Southern Finland
 F4303.1 ± 19.5Southern Finland

Trial trees were measured in autumn 2002 and eight healthy spruce clones from separate families with different growth performance were selected for study. We designated them slow-growing (S1–S4) and fast-growing (F1–F4) because the difference between the average heights of the two groups [slow-growing spruce clones (SGSC) and fast-growing spruce clones (FGSC)] was almost twofold (Table 1). The study plots were randomly organized into three replicate blocks in the 1-ha area (8 clone plots × 3 replicate blocks = 24 plots). Each plot (6 × 6 m) supported nine spruce cuttings planted 2 m apart.

Sampling

In October 2003, root tips were collected from five soil cores (4 cm diameter × 10 cm depth) taken randomly from each plot. Soil cores were packed in plastic and stored for less than 4 months at −20°C before processing. Depths of soil layers were measured, and the organic and mineral soil subsamples of each core were treated separately. Roots were washed over a 0.59-mm sieve and cut into 1–2-cm lengths. Root fragments were mixed and equal numbers of ECM root tips from each plot (5 per soil layer; 10 per soil core; 50 per plot; 150 per clone; 1200 in total) were sampled randomly under a dissection microscope (Taylor, 2002). ECM root tips were stored individually in 70% ethanol at −80°C before the extraction of nucleic acids. Root traits [density of root tips per length of fine root (< 2 mm), fine root total length and dry biomass] were also determined for each core subsample.

Molecular identification of ECM

Nucleic acids were extracted according to the protocols of Vainio et al. (1998) and Pennanen et al. (2005) with slight modifications. The protocol included cell disruption using quartz sand and a FastPrep® cell disrupter (Qbiogene, Inc., Cedex, France) for 3 × 20 s at 4 m s−1, one phenol:chloroform:isoamyl alcohol (50 : 49 : 1) and one chloroform:isoamyl alcohol (24 : 1) extraction, precipitation with polyethylene glycol (PEG) and drying. DNA was resuspended in 30 µl of TE buffer (10 mm Tris-HCl and 1 mm EDTA, pH 8.0). The internal transcribed spacer (ITS) region of the rDNA was amplified using primers ITS1F (Gardes & Bruns, 1993) and ITS2 or ITS4 (White et al., 1990). A GC-clamped ITS1F primer (5′-CGC CCG CCG CGC GCG GCG GGC GGG GCG GGG GCA CGG GGG GCT TGG TCA TTT AGA GGA AGT AA-3′) together with ITS2 was used to optimize separation of the amplification products in denaturing gradient gel electrophoresis (DGGE) analysis. PCR amplification of samples for DGGE analysis was performed with Biotools polymerase (B & M Laboratories, Madrid, Spain) and the thermal profile of Gardes & Bruns (1993) except that the annealing temperature was 58°C. For sequencing and cloning, amplification was performed with the ITS1F–ITS4 primer pair using Expand and FastStart High Fidelity PCR Systems (Roche, Penzberg, Germany), and High Fidelity PCR Enzyme Mix (Fermentas UAB, Vilnius, Lithuania) with the following thermal profile: initial denaturation for 8 min at 95°C, 35 cycles of denaturation for 1 min at 95°C, annealing for 1 min at 55°C, extension for 1 min at 72°C, and final extension for 10 min at 72°C. PCR products were purified with the High Pure PCR Product Purification Kit (Roche, Mannheim, Germany).

All PCR products of the ITS1 region were analyzed using the D-GENE denaturing gradient gel system (Bio-Rad, Hercules, CA, USA) using 7.5% weight/volume (w/v) acrylamide/bisacrylamide (37 : 5 : 1) gels (Pennanen et al., 2001). The 18–58% denaturing gradients were produced with 100% denaturing solution contained 40% deionized formamide and 7 m urea. The gels were run in TAE buffer (40 mm Tris-acetate, pH 8, and 1 mm EDTA) for 16 h at 75 V and 60°C. DNA fragments were stained with ethidium bromide solution and visualized under UV light. Samples were run and compared until they could be grouped according to their fingerprint (DGGE types).

Multiple-banded ITS DGGE types were ligated into pCR 2.1 vectors using the TOPO TA Cloning Kit (Invitrogen, Carlsbad, CA, USA). Recombinant plasmids were transformed and extracted as in Vainio & Hantula (2000). Eight cloned inserts per band were selected for each DGGE type and screened in DGGE using the same protocol as described above. To select clones for sequencing, the migrations of cloned inserts were compared with the original cloned DGGE type. Plasmids were isolated with the QIAprep® Spin Miniprep Kit (Qiagen, Hilden, Germany) before sequencing.

The ITS PCR products of different DGGE types were directly sequenced with the CEQ 8000 DNA analysis system and Quick Start Kit (Beckman Coulter Inc., Fullerton, CA, USA). Cloned inserts were sequenced with a 4200 L-2 NEN Global IR2 System (Li-Cor Inc., Lincoln, NE, USA) using the SequiTherm EXCELII sequencing kit (Epicentre, Madison, WI, USA). Sequences were manually aligned using Align IR Sequence Assembly and Alignment Software (Li-Cor Inc.). Consensus sequences were identified by comparing them with sequences deposited in GenBank (NCBI) and UNITE (Kõljalg et al., 2005; http://hermes.zbi.ee) databases using the blastn algorithm. Positional homology of similar sequences was assessed by creation of a multiple alignment using clustalw (Thompson et al., 1994) and a neighbor-joining tree using jalview (Clamp et al., 2004). All sequences were submitted to GenBank (DQ233734–DQ233904).

Microsatellite analysis of spruce clones

To verify the host tree genotype, microsatellite markers were screened in three randomly selected 2-cm root fragments from each study plot. Root fragments were collected from the same soil cores as root tips and stored in 70% ethanol at −80°C until DNA extraction. Buds from the spruce clones were taken for reference fingerprinting. DNA was extracted from root fragments and buds using the DNeasy Plant Mini Kit (Qiagen). PCR for nuclear microsatellite loci was performed using the primers SpAGG3, EATC3C05 and SpAGD1 (Scotti et al., 2002) in a total reaction volume of 15 µl containing 1.5 µl of 10× reaction buffer (Biotools), 1.5 pm of each dNTP, 6 pmol IRD-800 or IRD-700 labelled forward primer, 6 pmol reverse primer, 0.24 U Biotools polymerase and 10 ng of DNA. The thermal profile with primer SpAGG3 was as follows: initial denaturation for 5 min at 95°C, 35 cycles of 45 s at 94°C, 45 s at 57°C and 45 s at 72°C, and then 10 min at 72°C. Cycling parameters with primer EATC3C05 were identical except for an annealing temperature of 60°C. With the primer SpAGD1 the initial denaturation at 94°C for 4 min was followed by two cycles of 45 s at 94°C, annealing for 45 s at 57°C and extension for 30 s at 72°C. There then followed a multistep touchdown decreasing by 0.5°C each cycle: denaturation at 94°C for 45 s, annealing at 62–57°C for 45 s, and extension at 72°C for 45 s (10 cycles). The final part of this PCR protocol was 20 cycles of 45 s at 94°C, 45 s at 57°C and 30 s at 72°C, followed by 4 min at 72°C. The reactions were electrophoresed on a 6% Long Ranger sequencing gel using a NEN Global IR2 DNA sequencer (Li-Cor) and the sizes of the fragments were determined with SAGAGT-Generation 2 Software (Li-Cor). Finally, fingerprints of the roots were visually compared to bud references.

Statistical analyses and calculations

The relative abundance of an ECM fungal taxon in a plot was calculated by dividing the number of root tips for each taxon by the total number of ECM fungi examined. Relative abundances of all ECM taxa (with rare taxa down-weighted) were subjected to detrended correspondence analysis (DCA) using PC-ORD software version 4.34 (McCune & Mefford, 1999) to assess the ECM community structure of spruce clones. Richness, evenness and the Shannon diversity index were calculated using PC-ORD. To assess the sufficiency of the sampling effort, a species–area curve and first-order jackknife estimator of species richness were determined using PC-ORD. Analysis of variance (ANOVA) was used to detect the effect of clones; clone was the fixed factor and block was the random factor. Significant differences (P < 0.05) between means were tested by Tukey's test. Student's t-test was used for comparing slow- and fast-growing spruce clones. Parameters of organic and mineral soil were compared using the paired t-test. A correlation test was performed using Pearson's test. In parametric tests, densities of root tips and fine root, fine root biomass, and Shannon diversity index data were normalized with log10 transformations. Differences among ECM taxa were evaluated using nonparametic tests: the Kruskal–Wallis test and the Mann–Whitney U-test.

Results

Root traits and distribution

In the microsatellite fingerprinting analysis, roots from the adjacent spruce clone plots were not observed. Extraneous ectomycorrhizas still remain a possibility but contaminant ECM could have only attenuated the influence of the spruce clones on ECM communities. Root tip density, fine root total length and fine root biomass varied among spruce clones (Fig. 1). FGSC had higher average root tip density, fine root density and biomass than SGSC (P < 0.001, P = 0.001 and P = 0.001, respectively). Nevertheless, any positive correlations between root traits and height of the clone were not perceived within growth performance groups. Surprisingly, the tallest (F4) of the FGSC had the lowest root tip and fine root density and fine root biomass (Fig. 1). Conversely, the root traits of the shortest (F1) of the FGSC had the highest values. Of the slow-growing group, the root traits of S3 had the highest values which were comparable to those of the FGSC. Significantly, however, root traits within clone groups varied only in the case of clone S3, which differed from S1 and S2 with respect to root tip density (Tukey S3 vs S1 P = 0.029, S3 vs S2 P = 0.035). The organic soil layer, which was equal in depth for SCSC and FGSC (P = 0.952), contained more roots (P = 0.001 for fine root density; P < 0.001 for fine root biomass) and root tip density was higher (P < 0.001) compared with the mineral soil layer (Fig. 1).

Figure 1.

Root traits of slow-growing (S1–S4; open and light-gray columns) and fast-growing (F1–F4; black and dark-gray columns) Norway spruce (Picea abies) clones. White and black columns represent organic soil, and light-gray and dark-gray columns represent mineral soil. Root traits of clones (organic and mineral data combined) with different letters are significantly different from each other at the P < 0.05 level. Values are means (± standard error, n = 3).

ECM taxa at the study site

A total of 1200 root tips were taken from the study site and 94% of them were successfully amplified through PCR. Sixty-seven per cent of root tip samples (40 DGGE types) produced a single band in DGGE analysis and were sequenced directly. The remainder of the samples showed two to five bands in DGGE and had to be cloned. Many of them contained more than one ECM fungal species, but intragenomic variation in the ITS1 region was also found, especially within Tylospora asterophora. DGGE of ITS1 as a sorting method for ECM fungi was accurate (Anderson et al., 2003; Izzo et al., 2005) and bands with the same mobility were never identified as different species.

In total, 34 different ECM taxa were identified at the study site (Figs 2, 3, Table 2, and Supplementary Table S1, available online). The first-order jackknife estimator of ECM richness was 46.5. Hence, the observed number of ECM taxa was 73% of the estimated richness at the study site. Basidiomycetes comprised 84% of all identified ECM fungi and the remainder were ascomycetes. Fifty-one per cent belonged to Atheliaceae and 23% to Thelephoraceae. Tylospora asterophora (25%) and Thelephora terrestris (21%) were the most common ECM species, comprising almost half of the ECM fungi in the root tips.

Figure 2.

Relative abundance of ectomycorrhizal taxa between slow-growing (open columns) and fast-growing (closed columns) Norway spruce (Picea abies) clones. Taxa are in rank order. Values are means (± standard error, n = 12).

Figure 3.

Relative abundances of ectomycorrhizal taxa in organic (open columns) and mineral (closed columns) soil. Taxa are in rank order.

Table 2.  Relative abundance of ectomycorrhizal taxa and richness, evenness and Shannon diversity index of ectomycorrhizal communities associated with slow- and fast-growing Norway spruce (Picea abies) clones
 Slow-growing spruce clonesFast-growing spruce clones
S1S2S3S4MeanF1F2F3F4Mean
  • Values are means (n = 3). Means (± standard error; n = 12) of growth performance groups are shown in bold.

  • *

    Significantly (P < 0.05) different means.

Tylospora asterophora0.3090.0900.3690.375  0.0620.4230.1300.253 
Thelephora terrestris0.2690.4200.2180.091  0.1640.1180.1630.167 
Piloderma reticulatum0.0340.0560.0870.180  0.1080.1450.1690.043 
Amphinema byssoides0.0960.1100.1560.023  0.0200.0300.1190.024 
Phialophora finlandia0.0550.0790.0500.067  0.1030.0290.0940.103 
Amphinema sp. 10.0140.0830.0540.051  0.1810.0500.0970.045 
Wilcoxina sp. 10.1560.0640.0260.124  0.0290.0350.0070.000 
Clavulina sp.0.0540.0280.0190.008  0.0610.0410.0350.047 
Lactarius rufus0.0000.0000.0000.000  0.0000.0000.0000.139 
Pseudotomentella tristis0.0000.0000.0080.000  0.0000.0860.0000.013 
Dermocybe sp. 30.0000.0000.0000.000  0.0860.0070.0000.012 
Cenococcum geophilum0.0070.0000.0130.022  0.0390.0000.0000.013 
Wilcoxina sp. 20.0000.0000.0000.000  0.0270.0000.0070.000 
Boletus edulis0.0000.0000.0000.000  0.0000.0000.0000.058 
Russula adusta0.0000.0000.0000.000  0.0280.0000.0340.000 
Phialocephala fortinii0.0000.0000.0000.000  0.0070.0150.0140.006 
Piloderma fallax0.0000.0000.0000.000  0.0150.0000.0310.000 
Tomentellopsis submollis0.0070.0140.0000.008  0.0000.0000.0000.012 
Dermocybe sp. 20.0000.0000.0000.022  0.0000.0000.0140.006 
Cortinarius sp.0.0000.0000.0000.000  0.0000.0000.0380.000 
Inocybe sp.0.0000.0000.0000.000  0.0120.0000.0210.000 
Paxillus involutus0.0000.0000.0000.000  0.0000.0000.0000.029 
Tylospora sp. 20.0000.0000.0000.000  0.0000.0000.0280.000 
Phialophora sp.0.0000.0000.0000.000  0.0070.0000.0000.018 
Unidentified 10.0000.0000.0000.000  0.0150.0000.0000.012 
Tylospora fibrillosa0.0000.0140.0000.000  0.0000.0050.0000.000 
Amphinema sp. 20.0000.0000.0000.000  0.0000.0150.0000.000 
Unidentified 20.0000.0000.0000.000  0.0220.0000.0000.000 
Dermocybe sp. 10.0000.0000.0000.014  0.0000.0000.0000.000 
Tylospora sp. 10.0000.0070.0000.000  0.0000.0000.0000.000 
Piloderma sp. 10.0000.0000.0000.000  0.0070.0000.0000.000 
Piloderma sp. 20.0000.0000.0000.008  0.0000.0000.0000.000 
Inocybe soluta0.0000.0000.0000.007  0.0000.0000.0000.000 
Laccaria laccata0.0000.0000.0000.000  0.0070.0000.0000.000 
Richness7.007.336.678.007.25 ± 0.51*10.78.339.009.679.42 ± 0.85*
Evenness0.790.760.750.760.77 ± 0.04 0.850.800.890.810.84 ± 0.02
Shannon diversity index1.551.451.431.571.50 ± 0.10* 0.300.210.290.241.86 ± 0.12*

Differences in the vertical distribution of ECM taxa were observed between the organic and mineral soil layers (Fig. 3). Ascomycetes in general favored mineral soil (P < 0.001); Wilcoxina sp. 1 (P = 0.014) and Phialophora finlandia (P = 0.019) were significantly more common in mineral soil. Also, Clavulina sp. (P = 0.003) was more abundant in mineral soil. By contrast, the Atheliaceae (P < 0.001), in particular species of the genera Amphinema (P < 0.001) and Piloderma (P = 0.003), favored organic soil. Richness, evenness and Shannon diversity indexes of ECM communities were not significantly different between the two soil layers.

ECM communities of spruce clones

Ordination of ECM data showed segregation of communities between slow- and fast-growing spruce clones along DCA axis 1 (P = 0.016) (Fig. 4). The smallest clones were found to the left in the graph, whereas fast-growing clones were on the right. Differences in ECM community structure were also observed within SGSC (P = 0.046) and FGSC (P = 0.038) along DCA axis 2. F2 diverged from other FGSC, especially from F1 (P = 0.049) and F4 (P = 0.050). Separation of the clones within the groups was attributable to several ECM taxa (DCA loading plot not shown, but see the original data in Table 2). Tylospora asterophora, Wilcoxina sp. 1, Pseudotomentella tristris, Tylospora fibrillosa, and Amphinema sp. 2 were more common with clone F2, whereas Lactarius rufus, Cenococcum geophilum, Boletus edulis, Tomentellopsis submollis, Paxillus involutus, Phialophora sp., Unidentified 1 and 2, Piloderma sp. 1 and Laccaria laccata were not found with F2 but were found more or less frequently with F1 and/or F4 (Table 2). Among SGSC, S2 and S4 diverged noticeably from each other along DCA axis 2 (P = 0.033). Differences in relative abundances of T. asterophora, T. terrestris, Piloderma reticulatum, Amphinema byssoides, C. geophilum, Dermocybe sp. 2, T. fibrillosa, Dermocybe sp. 1, Tylospora sp. 1, Piloderma sp. 2 and Inocybe soluta with S2 and S4 were mainly responsible for their separation in DCA.

Figure 4.

Score plot of detrended correspondence analysis (DCA) of ectomycorrhizal communities on slow-growing (S1, open square; S2, open diamond; S3, open circle; S4, open triangle) and fast-growing (F1, closed square; F2, closed diamond; F3, closed circle; F4, closed triangle) Norway spruce (Picea abies) clones. Eigenvalues of DCA axes 1 and 2 are 0.304 and 0.193, respectively. Values are means (± standard error, n = 3).

The total number of ECM taxa observed in FGSC was 30 (13–20 taxa per clone), whereas only 18 ECM taxa (10–14 taxa per clone) were observed in SGSC (Fig. 2, Table 2). The first-order jackknife estimator of the total number of ECM taxa in FGSC was 40.1, varying from 14.9 in F2 to 26.7 in F1 (Fig. 5). With SGSC, the estimator was only 23.5 and varied from 12.9 in S3 to 19.8 in S4. Richness, evenness and Shannon diversity indices of ECM communities did not vary among spruce clones but a significant difference was observed among growth performance groups (Table 2). The evenness of ECM communities of FGSC was not significantly higher compared with SGSC. Instead, FGSC had higher ECM richness than SGSC, and hence had a higher Shannon diversity index. However, ECM richness and Shannon diversity index did not correlate with fine root biomass (r = 0.223, P = 0.296 and r = 0.219, P = 0.305, respectively; n = 24), density (r = 0.190, P = 0.374 and r = 0.208, P = 0.330, respectively; n = 24) or root tip density (r = 0.176, P = 0.412 and r = 0.232, P = 0.275, respectively; n = 24).

Figure 5.

Species–area curves for slow-growing (S1, open squares; S2, open diamonds; S3, open circles; S4, open triangles) and fast-growing (F1, closed squares; F2, closed diamonds; F3, closed circles; F4, closed triangles) Norway spruce (Picea abies) clones showing an increase in the number of observed ectomycorrhizal (ECM) taxa with increasing sampling effort. Each subsample (organic or mineral layer of a soil core) consisted of five root tips. *First-order jackknife estimate for the total number of taxa.

Tylospora asterophora and T. terrestris were the most abundant ECM taxa within SGSC (54%) and FGSC (37%) but their relative abundance was significantly higher within SGSC (P = 0.046). Furthermore, the abundance of T. asterophora and T. terrestris correlated negatively with ECM diversity (r = 0.856, n = 24, P < 0.001). Cortinariaceae and Russulaceae families tended to be more abundant in FGSC than in SGSC (P = 0.085 and P = 0.033, respectively). ECM taxa exclusive to FGSC included members of the genera Lactarius, Boletus, Russula and Cortinarius. Differences in the abundances of supposed functional groups of ECM fungi (Agerer, 2001) between SGSC and FGSC were not observed. Within SCSC the abundance of Dermocybe showed some indication of variation among clones (P = 0.088), as did that of Atheliaceae within FGSC (P = 0.063).

Discussion

Our study is among the first to show significant variation in ECM communities for populations of trees of the same age and species in the same environmental conditions. Under field conditions, we found that the Shannon diversity index of ECM taxa as well as ECM community structure varied among 11-year-old Norway spruce clones. Taller trees had higher ECM diversity (i.e. richness and Shannon diversity index) than shorter trees. The actual difference in ECM diversity between SGSC and FGSC is likely to be even higher, because the proportion of the ECM community investigated in FGSC was lower than that investigated in SGSC (Fig. 5). However, in DCA analysis, clones also diverged within growth performance groups according to their ECM community structures, and the size of the root system did not account for the variation observed. We therefore suspect that the genetic pedigree of the host may be responsible for the varying ECM community structure of the clones.

A total of 34 ECM taxa were found, of which 30 were from FGSC and 18 from SGSC. Bruns (1995) generalized that 20–35 species are typically present in small monoculture forests. Heinonsalo (2004) examined the ECM community of pine seedlings in Finland and over a 5-year sampling period he found 34 different ECM gross morphotypes. Yearly he found c. 20 ECM morphotypes. Thus, the Norway spruce clonal trial in this study showed normal ECM diversity with typical species and genera (Erland et al., 1999; Taylor et al., 2000).

Tylospora asterophora and T. terrestris were the two most common ECM species in SGSC and also in FGSC but their dominance was greater in SGSC. In FGSC, T. asterophora and T. terrestris were partly replaced by multi- or late-stage fungi, such as species of Russulaceae and Boletaceae. In previous studies, this kind of succession and increase in ECM diversity were observed as stand maturity increased (Deacon & Fleming, 1992; Visser, 1995; Kranabetter et al., 2005). Succession after clear-cutting is considered to be driven by changes in the biological, physical and chemical characteristics of the soil environment and shifts in the amount and type of inoculum (Jones et al., 2003). As the plots of SGSC and FGSC were randomly organized in the clonal trial and the depth of the organic layer as well as the humus nutrient concentrations did not greatly vary (T. Korkama et al., unpublished data), the clones seem to have affected the ECM community. Jones et al. (2003) stated in their review that host trees, in respect of their age and species, affect the structure of the ECM community. However, our study shows that the growth rate or size of the host trees also shapes the diversity of the local ECM community actively colonizing root tips. Individual trees and the forest ecosystem as a whole are likely to benefit from high ECM diversity in heterogeneous forest soils (provided that the community is functionally diverse) (Reddy & Natarajan, 1997; Baxter & Dighton, 2001; Jonsson et al., 2001) and the inclusion of more species in the ECM community in FGSC could possibly provide a further growth advantage to these trees (van der Heijden et al., 1998; Jonsson et al., 2001; Nara & Hogetsu, 2004).

Generally, ECM species diversity increases at the same time as the root system develops (Kranabetter & Friesen, 2002). In our study, root traits did not significantly correlate with ECM diversity, although the average density of fine roots and root tips in FGSC were higher than in SGSC. For example, the root system of S3 was of relatively good quality: fine root growth and root tip density were equal in magnitude to those in FGSC and almost double those of the root systems in other SGSC. Yet, the ECM diversity of S3 was the lowest observed. Thus it seems that, for tree growth, more important characters than the size and morphology of the root system might be its function and activity, which are largely dependent on ECM community structure (Agerer, 2001). However, in a natural forest the common mycelial network might diminish differences among ECM communities and hence diminish differences in vitality among individual trees (Simard et al., 1997; Jonsson et al., 1999; Kennedy et al., 2003).

Although ECM community structures within growth performance groups of clones resembled each other more than ECM community structures among clone groups, the perceived within-group dissimilarity suggests that ECM community structure also depends on other characteristics of the host tree in addition to its growth rate or size. Saari et al. (2005) tested a congruent hypothesis on ECM community differences among individual trees but they did not observe significant differences. Worth considering, however, is the uneven distribution of root tip samples among trees in that study. We propose that differences in clone specificity for ECM fungi or specificity of ECM fungi for certain clones might have caused the observed variation in our study. Further, host tree effects on ECM communities may be indirectly mediated through the quality of leaf litter (Bruns, 1995; Conn & Dighton, 2000), carbon allocation or some other factor. Also, the specificity and ECM diversity may depend on the origin of a host tree: the variety of ECM symbioses of native host tree species was found to be higher compared with that of recently introduced tree species by Newton & Haigh (1998). The mother tree of F2 originated from Estonia, whereas all the others were native or crosses between native and introduced trees. Therefore, the genotype of F2 might have been less adapted to local ECM fungi and thus exhibited a lower ECM diversity.

Our results suggest that individual trees might influence the patchy distribution of ECM fungi in monospecific stands. ECM fungi have been found to exhibit similarity on spatial scales up to c. 3 m (Lilleskov et al., 2004) and dominant ECM species to vary among individual trees (Gehring et al., 1998). There are indications that the community structure of ECM fungi affects the bacteria of the mycorrhizosphere (Olsson & Wallander, 1998; Timonen et al., 1998). Lindahl & Olsson (2004) suggested that translocation of nutrients in fungal mycelia not only responds to soil heterogeneity but also creates it. Thus, the comparable patchy distribution of soil bacteria, arbuscular mycorrhizal fungi (Pennanen et al., 1999) and nutrients (Liski, 1995) in monospecific stands may be partly related to the impact of individual trees on the ECM community.

The Norway spruce clonal field trial gave us a unique opportunity to study the impact of individual trees on the ECM community. Although the most obvious difference in ECM diversity and community structure was observed between slow- and fast-growing host tree clones, there were also differences in community structure within phenotypically similar clones. Thus our results indicate that both the growth and the genotype of the host tree directly or indirectly affect the ECM community structure. Furthermore, the high diversity and patchy distribution of ECM fungi, even in monospecific stands may partly be explained by the effect of individual host trees.

Acknowledgements

We thank Kaisa Pihlajamaa, Elina Laanto and Raimo Jaatinen for technical assistance, Annukka Korpijaakko and Seija Vanhakoski for help with the microsatellite analysis and Michael Hardman for revising the English. Marja-Leena Napola created the clonal field trial and provided us with information on the clones. This study was funded by the Academy of Finland (project no. 201178).

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