SEARCH

SEARCH BY CITATION

Keywords:

  • ectomycorrhizal diversity;
  • extracellular enzyme activities;
  • fast- and slow-growing seedlings;
  • fine roots;
  • Norway spruce (Picea abies (L.) Karst);
  • Piloderma sp.;
  • Tylospora asterophora;
  • Wilcoxina sp

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • We studied the role of taxonomical and functional ectomycorrhizal (ECM) fungal diversity in root formation and nutrient uptake by Norway spruce (Picea abies) seedlings with fast- and slow-growing phenotypes.
  • Seedlings were grown with an increasing ECM fungal diversity gradient from one to four species and sampled before aboveground growth differences between the two phenotypes were apparent. ECM fungal colonization patterns were determined and functional diversity was assayed via measurements of potential enzyme activities of eight exoenzymes probably involved in nutrient mobilization.
  • Phenotypes did not vary in their receptiveness to different ECM fungal species. However, seedlings of slow-growing phenotypes had higher fine-root density and thus more condensed root systems than fast-growing seedlings, but the potential enzyme activities of ectomycorrhizas did not differ qualitatively or quantitatively. ECM species richness increased host nutrient acquisition potential by diversifying the exoenzyme palette. Needle nitrogen content correlated positively with high chitinase activity of ectomycorrhizas.
  • Rather than fast- and slow-growing phenotypes exhibiting differing receptiveness to ECM fungi, our results suggest that distinctions in fine-root structuring and in the belowground growth strategy already apparent at early stages of seedling development may explain later growth differences between fast- and slow-growing families.

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

There has been growing interest in the mechanistic relationship between the taxonomic diversity of ectomycorrhizal (ECM) fungi and tree productivity (Baxter & Dighton, 2001, 2005; Jonsson et al., 2001; Kipfer et al., 2012). Correlative support for a positive relationship between tree growth and ECM fungal diversity was found in our previous field study with 11-yr-old Norway spruce (Picea abies (L.) Karst), in which the root systems of fast-growing clones supported higher ECM diversity and greater root tip numbers than the roots of slow-growing clones (Korkama et al., 2006). However, in that study it was not possible to partition causality among inherent differences in host growth, differential host receptiveness and functional responses to ECM colonization, and/or differences attributable to the functional diversity of the associated ECM community.

The growth of boreal forest trees is highly dependent on their ability to gain nutrients from forest soil. ECM fungal partners of trees mobilize nutrients from soil organic matter by secreting oxidative and hydrolytic exoenzymes (Bending & Read, 1995; Read & Perez-Moreno, 2003; Rineau & Courty, 2011). These enzymes are important in the transformations of both immobile phosphorus (P) and nitrogen (N), and enable hosts to utilize not only mineral but also organic sources of N and P (Chalot & Brun, 1998). As early as 1953, Melin suggested that different ECM fungi may vary in their ability to provide nutrients to their host. ECM fungi are now known to differ greatly in their N and P uptake capabilities (Bending & Read, 1995; Baxter & Dighton, 2001; Jones et al., 2009), although some degree of functional redundancy is thought to occur within natural ECM communities (Courty et al., 2010; Pritsch & Garbaye, 2011; Rineau & Courty, 2011). In the low-nutrient, highly heterogeneous soils of boreal forests, ECM functional diversity is likely to ensure a greater uptake of nutrients.

To understand the significance of ectomycorrhizas to forest productivity, it is important to understand the underlying mechanisms operating between ECM community diversity and growth of trees. The effect of ECM species richness on host productivity (assessed as above- and belowground biomass) has been shown to be strongly context dependent (Jonsson et al., 2001; Baxter & Dighton, 2005) but potentially enhancing shoot growth (Kipfer et al., 2012) and nutrient gain (Baxter & Dighton, 2001) of seedlings. However, there are difficulties predicting the growth performance parameters of adult trees based on experimental data from seedling growth (Sonesson et al., 2002).

There is evidence that tree genotype affects the development of ectomycorrhizas and controls short-root formation of young seedlings (Marx & Bryan, 1971; Kleinschmit & Smidht, 1977; Velmala et al., 2013). Thus, the genetically controlled variation in root tip densities may imply differences in growth strategies and in the potential for growing trees to assemble ECM fungi in forest soil, which in turn could affect the efficiency of water and nutrient exchange. However, we do not know whether the variable root characteristics of spruce genotypes also include genotype-specific selection of colonizing fungi, that is, host receptivity towards fungal symbionts. In addition, it is unknown if the linkage (found by Korkama et al., 2006, 2007) between ECM community diversity and spruce genotypes differing in their long-term growth rate is apparent in seedlings before differences in their aboveground growth are visible.

Therefore, our aim in the present study was twofold. Firstly, we aimed to determine if later growth performance of spruce is related to host receptiveness to ECM fungal colonization in early stages of development. Secondly, we aimed to assess whether ECM fungal diversity, community composition, and exoenzyme capacity relate to the long-term growth rate or nutrient gain of seedlings. These questions were addressed in a glasshouse experiment using slow- and fast-growing Norway spruce seedlings.

The effect of ECM diversity on host root growth and nutrient uptake was studied by using an increasing ECM fungal diversity gradient from one to four species. In order to test the effect of genetically different host trees, two types of spruce seed orchard families were selected; three from the best performing families in long-term field trials and three from poorly performing families that have already been excluded from the official afforestation program. In addition, nutrient foraging ability determined as needle N content was used as a measure of seedling fitness.

The hypotheses were that the seedlings representing fast-growing families would: have a higher ECM colonization percentage on their roots; establish a more diverse ECM fungal community than the slow-growing ones; and that ECM taxonomic richness enhances functional diversity, and thus the ECM communities on seedlings of fast-growing families display qualitatively and quantitatively higher potential enzyme activities than those on the slow-growing seedlings.

Materials and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Spruce material

The plant material used in this study consisted of six southern Finnish (59–62°N) Norway spruce (Picea abies (L.) Karst) seed orchard seed families which represented two contrasting growth performance groups showing good and poor growth in long-term field experiments at the age of 14 yr (Supporting Information Table S1). These spruce seedlings were exposed to 12 treatments, of which 11 included fungal inoculations and the twelfth was a noninoculated control treatment. Seedlings were grown for 1 yr under glasshouse conditions and sampled in spring a month after budburst when heavily colonized and before any systematic differences in shoot growth and thus in photosynthetic tissue size could be observed.

Ectomycorrhizal fungal strains

The ECM fungal strains Piloderma sp. (R-SP02), Wilcoxina sp. (706), Tylospora asterophora (R-NC01) and Hebeloma sp. (F-NB01) selected for this experiment represent asco- and basidiomycetous fungi found in association with Norway spruce both in nurseries (Flykt et al., 2008) and under field conditions. These ECM fungal species also differ in relative abundance on fast- and slow-growing clones (Korkama et al., 2006, 2007); Wilcoxina was found to be more abundant on slow-growing spruces and Piloderma on fast-growing ones. All four ECM fungal strains were inoculated as single cultures, as pairwise treatments and as a mixture of all four fungi (Table 1).

Table 1. Ectomycorrhizal (ECM) fungal treatment scheme used in the diversity experiment on Norway spruce (Picea abies) seedlings
Code [ECM richness]× 6 seed familiesInoculated ECM fungal speciesRealized fungal species after 1 yr of growth
  1. The columns show treatment code with realized ECM richness, number of replicates of each seed origin in each treatment, inoculated ECM fungal species and realized diversity at sampling. Thelephora terrestris colonized all treatments after 1 yr of growth as a contaminant.

c [1]4None Thelephora terrestris (T.t)
h [1]4Hebeloma sp. T. t
p [2]4Piloderma sp.Piloderma sp. and T. t
t [2]4 Tylospora asterophora T. asterophora and T. t
w [2]4Wilcoxina sp.Wilcoxina sp. and T. t
hp [2]4Piloderma sp. and Hebeloma sp.Piloderma sp. and T. t
hw [2]4Hebeloma sp. and Wilcoxina sp.Wilcoxina sp. and T. t
th [2]4T. asterophora and Hebeloma sp.T. asterophora and T. t
tp [3]4T. asterophora and Piloderma sp.T. asterophora, Piloderma sp. and T. t
tw [3]4T. asterophora and Wilcoxina sp.T. asterophora, Wilcoxina sp. and T. t
wp [3]4Piloderma sp. and Wilcoxina sp.Piloderma sp., Wilcoxina sp. and T. t
all [4]4All four ECM speciesT. asterophora, Piloderma sp., Wilcoxina sp. and T. t

Preparation of donor seedlings

The ECM fungal inoculum was spread from donor seedlings (Methods S1) which were precolonized by living ECM fungi and planted in conjunction with the recipient seedlings of interest (Fig. 1) to guarantee living mycelia of all strains in the experiment. These donor seedlings were produced 4 months before the start of the experiment by inoculating spruce seedlings repeatedly with homogenized liquid fungal hyphae in modified Melin–Norkrans medium (MMN) (Methods S1; modified from Marx (1969)). Seedlings treated only with MMN medium were used as noninoculated control donor seedlings.

image

Figure 1. Experimental design for the application of 12 diversity treatments to Norway spruce seedlings. Four different cultures of ectomycorrhizal fungi were inoculated as single, pairwise and mixture inoculums. The white central recipient seedlings show the placing of fast- and slow-growing seedlings, and the surrounding black, dark gray, light gray and ruled figures illustrate the donor seedlings.

Download figure to PowerPoint

Experimental design and growth conditions

In mid-May, four donor seedlings were transplanted into 1-dm3 plant pots according to the treatment scheme (Table 1, Fig. 1) and were left to stabilize for 14 d. In the course of transplantation the abundance of ECM fungal colonization of each donor seedling was verified under a stereomicroscope: roots of the seedlings inoculated with Piloderma sp. and Wilcoxina sp. were highly colonized (> 50%), Tylospora asterophora-treated seedlings had a lower colonization (c. 50%) and Hebeloma sp. seedlings were poorly colonized (< 10%). From T. asterophora and Hebeloma sp. treatments the best colonized seedlings were chosen for the mixed inoculum treatments. An additional liquid ECM inoculation (1 ml per donor seedling) was added 2 d after the replanting (Methods S1).

In early June, 48 nonmycorrhizal 6-wk-old seedlings from each of the six seed families (Table S1) were planted in the pots subjected to the 12 treatments, one seedling per pot (Table 1). Altogether 288 plant pots were established in a glasshouse, including four replicate pots per treatment. Randomizing of pot positions was repeated once a month during the experiment.

The glasshouse temperature was adjusted to follow outside mean temperatures of Loppi (60.713°N, 24.438°E) the growth season 2010–2011 and to add +4°C to that daily value. In November the glasshouse temperature was reduced to +2°C and kept steady for 5 months. The growth substrate comprised unfertilized autoclaved peat (10 min at 121°C) and vermiculite (9 : 1, v/v). Seedlings were irrigated with tap water and fertilized with 0.1% Kekkilä Superex (12% N–5% P–27% K; Kekkilä, Vantaa, Finland) liquid fertilizer once a week from June to August to keep the conductivity of peat at 1 mS cm−1. The total loads of N and P per seedling from growth medium and fertilizers during the experiment were 5 and 2 mg, respectively. Eight milliliters of boosting ECM inoculate grown in liquid Sipernat® 22S MMN culture (20 g of Sipernat per 1 l of fluid; Evonik Industries, Essen, Germany) was added to each pot, with 2 ml applied to the root system of each donor seedling, four times in the autumn and twice the next spring. To prevent over-dominance by the well-adapted Wilcoxina sp. against less competitive ECM, no additional inoculum was added in mixed treatments in spring.

Sample collection

Growth of seedlings started again in late March and glasshouse temperatures again followed the outside mean temperatures of Loppi with a +4°C addition to that daily value starting from April. One-year-old seedlings were sampled during the first 2 wk of May; replicate pots were harvested sequentially in a randomized order. Three randomly chosen replicate seedlings from each seed family in each treatment were subjected to the multi-enzyme assay and needle nitrogen analyses. All seedlings were kept in a growth chamber under artificial light at +20°C to keep the sampling conditions constant. Seedlings were rinsed carefully with tap water, the shoot height was measured, and the shoots and roots were separated. Immediately after washing, root tips were collected directly into the incubation buffer for the multi-enzyme assay. The rest of the roots were cut into 1–2-cm pieces in a Petri dish, and the ECM colonization was determined by morphotyping under a stereomicroscope from approx. 200 randomly selected root tips per seedling. Short-root density was assessed by dividing the number of root tips by the measured length (mm) of roughly 15 pieces of roots. Additionally, subsamples of roots representing different ECM morphotypes were collected from seedlings in mixed treatments, and used for molecular identification of the colonizing fungi to support the morphotyping. Root tips were stored frozen at −20°C in a 1.5-μl droplet of sterile water.

The shoots and roots of experimental seedlings were dried for 48 h at 42°C before weighing. Dry needles were homogenized with FastPrep® (FP120; Qbiogene, Cedex, France) in 2-ml polypropylene tubes with FastPrep® matrix A ceramic sphere. The needle N concentration was determined with a CHN-1000 analyzer (Leco Corp., St Joseph, MI, USA; analysis based on ISO 10694 and ISO 13878 standards) in the Central Laboratory of the Finnish Forest Research Institute, Vantaa, Finland.

Mycorrhizal identification

To identify ECM fungal species, the fungal internal transcribed spacer 2 region of ribosomal DNA (or rDNA) was amplified directly from single ECM root tips as described in detail in Velmala et al. (2013). Each frozen root tip was homogenized in 20 μl of Dilution buffer (Phire® Plant Direct PCR Kit; Thermo Scientific, Waltham, MA, USA) and 0.5 μl of this sample was used as a template for amplification with fITS7 (Ihrmark et al., 2012) −ITS4 (White et al., 1990) fungal-specific primer pairs. The PCR cycling was carried out on 96-well plates in a reaction volume of 20 μl as follows: 98°C for 5 min, cycling at 98°C for 5 s, 57°C for 10 s, and 72°C for 20 s repeated 40 times, and the final extension at 72°C for 60 s (S1000 Thermal Cycler; BioRad, Hercules, CA, USA).

These PCR products representing the ITS2 region were used for molecular identification of colonizing fungal species based on strain-specific restriction profiles. PCR products of sampled root tips were restricted with HinP1 (FastDigest®; Thermo Scientific, Waltham, MA, USA) restriction enzyme at 37°C for 20 min and separated in 0.9% Synergel (DivesifiedBiotec, Boston, MA, USA)/Agarose (Thermo Scientific) gel together with pure culture reference samples of the inoculated ECM fungal strains. Tylospora asterophora and Hebeloma sp. did not separate well in Synergel and they were separated by denaturing gradient gel electrophoresis (DGGE) as described in detail in Rajala et al. (2010). To generate PCR products suitable for DGGE from T. asterophora and Hebeloma sp., the fungal internal transcribed spacer 1 region of ribosomal DNA (or rDNA) region was amplified using ITS1F (Gardes & Bruns, 1993) with a GC clamp (Muyzer et al., 1993) and ITS2 (White et al., 1990) primers in a direct PCR reaction (Phire® Plant Direct PCR Kit; Thermo Scientific). The cycling was carried out as for primers fITS7-ITS4.

Multi-enzyme assay

Freshly collected spruce root tips were subjected to the multi-enzyme assay described in Pritsch et al. (2011), which was developed to measure the potential activities of eight hydrolytic and oxidative exoenzymes secreted by ectomycorrhizas. We assessed the potential activities of laccase (EC 1.10.3.2), hemicellulases (β-glucuronidase (EC 3.2.1.31) and β-xylosidase (EC 3.2.1.37)) and cellulases (cellobiohydrolase (EC 3.2.1.91) and β-glucosidase (EC 3.2.1.21)) involved in the decomposition of lignocelluloses as well as the enzymes degrading chitin (N-acetylglucosamide (EC 3.2.1.14)) and P- and N- containing organic compounds (acid phosphatase (EC 3.1.3.2) and leucine aminopeptidase (EC 3.4.11.1), respectively). The assay measures the functionality directly from ECM root tips (Pritsch et al., 2004, 2011) which comprise the root cortex cells, fungal material and other accompanying micro-organisms. For all enzyme activities except laccase, the assay is based on fluorescence development following enzymatic substrate cleavage, and it quantifies the potential enzyme activities derived from ECM root tips. Briefly, within 4 h from sampling, seven ECM root tips per morphotype from three replicate seedlings were placed on a 96-well filter plate (30–40 μm mesh size, AcroPrep 96 Filter Plate; PALL, Port Washington, NY, USA). In each row of the plate one well was left empty and contained only the reaction solutions and was used as a negative control. Root tips and control wells were incubated at room temperature in incubation buffers containing enzyme-specific 4-methylumbelliferone (MU) or 7-amino-4-methylcoumarine (AMC) substrate. After each incubation step, the incubation solution was transferred into stop buffer using a vacuum manifold (NucleoVac® 96 Vacuum Manifold; Macherey-Nagel, Düren, Germany) and fluorescence was measured using a Victor3 1420 multilabel plate counter (PerkinElmer, Waltham, MA, USA) at an excitation wave length of 355 nm and an emission wavelength of 460 nm. Between incubations, the root tips and wells were rinsed with the rinsing buffer. Finally, laccase activity was determined by incubating in buffer containing diammonium 2,2′-azinobis-3-ethylbenzothiazoline-6-sulfonate (ABTS) and measuring the degree of colorimetric reaction using a microplate spectrophotometer (iEMS Reader MF v.2.9-0; Labsystems, Vantaa, Finland) at 405 nm. Root tips were scanned in water and projected surface areas were determined by WinRhizo software (Regent Instruments, Quebec, Canada). Calibration curves for fluorometric measurements were measured from wells containing stop buffer, incubation buffer and MU or AMC solution, to give a final MU/AMC concentration of 0–5 μM. The identity of each ECM root tip subjected to the multi-enzyme assay was confirmed by direct PCR analysis following the same protocol used already for ECM identification.

Calculations and statistical analyses

The measurement of potential exoenzyme activities was replicated with five to seven root tips representing each fungal strain on each seedling. Enzymatic activity (EA) was calculated using the equation EA = (sample − negative control)/(a × pa × t), where ‘sample’ is the measured activity value of the sample, ‘negative control’ is the response of solutions without a sample, a is the slope of the regression line of the calibration curve (1/pmol), pa is the projection area of the root tip (mm−2) and t is the incubation time (min). For ABTS, a = (ε425 × pl)/V, where ε425 is the molar coefficient for ABTS (ε425 = 36 000 l mol−1 cm−1), and pl is the path length of the well (V/(πr2)), that is, 0.12 cm3/π (0.32 cm)2. Results were expressed as pmol mm−2 min−1 of released substrate.

From these raw data for five to seven replicate root tips, a single median value representing the potential activity of each ECM and nonmycorrhizal root tip was calculated for each sample. The total root tip number was estimated from total root biomass and the counted number of root tips in the analyzed and weighed subsample, which was further normalized with a coefficient generated by dividing the known root tip density of each sample by the mean value of root tip density in all samples. The ECM richness was calculated from the realized diversity from the realized diversity, which was determined using the true occurence of a certain ECM fungus; only four seedlings had richness higher than 3, and these samples were merged in this highest richness class. The potential enzyme activity of a root tip represents the combined mean value of the enzyme activities in all root tips from each sample. We also separately calculated the fungal-specific enzyme profiles as the mean activity of ECM root tips colonized by each of the fungal strains present in each sample to study the effect of increasing richness on the potential exoenzyme activities. The total potential enzyme activity represents the enzyme activity in the whole root system considering the ECM community, ECM abundance and the estimated total root tip number of a seedling.

We conducted a permutational multivariate analysis of variance {ADONIS: VEGAN} (Oksanen et al., 2012) to study the effect of growth performance group on ECM community composition and enzyme secretion matrixes. Distance matrices were based on Bray–Curtis dissimilarity (Bray & Curtis, 1957) and the significance was based on sequential sums of squares from 4999 permutations of the raw data with treatment as a random factor (stratum).

To further study the effect of growth performance group on (1) the abundance of single ECM species and (2) the potential enzyme activities of single enzymes in single root tips and on a total root system level, we used a classic multivariate analysis of variance {MANOVA: STATS}. As fixed factors in the models we used growth performance group together with treatment for the first model (1), and ECM fungal richness and the interaction of growth performance group and ECM richness for the latter models (2). The ECM fungal colonization data were arcsin-square root transformed to obtain an appropriate error distribution. We performed pairwise comparisons between enzyme activities of different ECM fungi and growth performance groups with pairwise t-test {PAIRWISE.T.TEST: STATS} with Holm's (1979) correction for multiple testing.

The effects of growth performance group, ECM richness and ECM abundance on shoot height, shoot and root biomass, shoot:root ratio, short-root density, N content and concentration, Shannon diversity index, ECM colonization percentage, ECM richness and root tip number were estimated as general and generalized linear models {LMER and GLMER: LME4} (Bates et al., 2011). The full model included the interaction of ECM richness and growth performance group as well as the abundances of each ECM fungus as fixed factors and the seed family as a random factor. The model was reduced by excluding insignificant (α > 0.1) explanatory variables, except for growth performance group which was always kept in the model. For proportion variables (%) we used a binomial and for counts a Poisson distribution with logit- and log-link functions, respectively. An LMER model does not provide P-values on its model estimates, so we considered explanatory variables with t-values > 1.8 as significant (α < 0.05). We used Pearson's and Spearman's rank (rho (ρ)) correlation tests to investigate the relationships between different traits in the data set for fast- and slow-growing seedlings separately.

For the analyses described in the preceding paragraphs and all graphics, the R 2.15.0 software (10 R Development Core Team, 2012) was used. For the figures we used the package ggplot2 (Wickham, 2009).

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

ECM colonization, growth and root structuring of spruce seedlings

After 1 yr of growth, there were no differences between fast- and slow-growing Norway spruce families in their ability to form ectomycorrhizas with the ECM fungal species present (Fig. 2). Future growth performance (fast/slow) had a marginally significant effect on the ECM community structure measured as ECM fungal colonization percentage (F1,285 = 0.48; R2 = 0.002; = 0.077) and the actual number of roots colonized by different fungi (F1,285 = 0.75; R2 = 0.003; = 0.065), whereas no effect was found on the species occurrence (F1,285 = −0.06; R2 = −0.002; = 0.749), or species richness of ECM fungi (Table 2). Thelephora terrestris, which occurred as a contaminant colonizer in most roots systems (Table 1, Fig. 2), was slightly more abundant on the roots of slow-growing families (F1,274 = 3.15; = 0.077), which probably partially explains the marginally significant trend in the ECM colonization percentage patterns. At sampling, three out of the four inoculated fungi were successfully established on the recipient spruce seedling roots, resulting in relatively high levels of ECM fungal colonization (86 ± 18 SD%) in all inoculated treatments (Table 1, Fig. 2). Wilcoxina sp., T. terrestris and Piloderma sp. were the most effective colonizers, and in the mixed inoculation treatments they clearly dominated the root systems. The abundance of T. asterophora was lower and it colonized on average 10 ± 16 SD% of root tips (Fig. 2). Hebeloma sp. was not found in any of the seedlings at the end of the experiment. No cross-contamination between treatments was found.

Table 2. Effects of growth performance group, ectomycorrhizal (ECM) fungal colonization percentage and ECM richness (± 1 SE) on different Norway spruce (Picea abies) seedling traits
General linear mixed models
TraitInterceptaInteractionc
Estimate of fast-growing seedlingsMeanc effect of slow-growing seedlingsThe mean effect of the colonization percentage of Piloderma sp.The mean effect of the colonization percentage of Wilcoxina sp.The mean effect of the colonization percentage of T. asterophoraThe mean effect of the colonization percentage of T. terrestrisThe mean effect of increasing richnessGrowth–richness
Shoot height (cm)8.54 ± 0.82−1.42 ± 0.930.92 ± 0.762.19 ± 0.6 −2.1 ± 1.41 2.39 ± 0.73 0.15 ± 0.27 0.68 ± 0.36
Shoot DW (g)0.168 ± 0.016−0.017 ± 0.023 −0.044 ± 0.014 −0.08 ± 0.036
Root DW (g) 0.093 ± 0.01−0.012 ± 0.014
Shoot:root ratio1.877 ± 0.0890.194 ± 0.121 −0.561 ± 0.145
Short root density (tips mm)0.576 ± 0.018 0.049 ± 0.024 −0.112 ± 0.029
N content (mg)1.054 ± 0.199 −0.634 ± 0.231 0.537 ± 0.118 0.542 ± 0.16 −0.042 ± 0.082 0.318 ± 0.11
Shannon diversity H’ 0.254 ± 0.0250.004 ± 0.035
Generalized linear mixed models
 InterceptaInteractionb
Estimate of fast-growing seedlingsMean effect of slow-growing seedlingsThe effect of Piloderma sp.%The effect of Wilcoxina sp.%The effect of Tylospora asterophora%The effect of Thelephora terrestris%The effect of increasing richnessGrowth–richness
  1. Results of linear mixed models show the estimates and effect sizes (compared with the intercept value) and directions of linear relationships between response and explanatory variables. Note that for general models ‘estimate’ is the mean value of a trait. For generalized models the ‘estimate’ does not show the original mean values because of the use of Poisson and binomial error distributions. Statistically significant effects are given in bold type (t-value > 1.8) and highly significant values are emphasized in italics and underlined (t-value > 3). n = 288.

  2. ‘–’ indicates that the explanatory variable has been removed from the full model.

  3. a

    The intercept column shows the ‘estimate’ of a trait of fast-growing seedlings when all the other explanatory variables are 0. The other columns show the effect size (compared with the estimate) and directions of linear relationships between response and explanatory variables. Negative values indicate that the particular variable results in a decrease in the mean value of a measured trait and vice versa.

  4. b

    The interaction term stands for the interaction of growth performance group and ECM fungal richness. A significant interaction indicates that the effect of ECM richness on a certain trait differs between growth performance groups.

  5. c

    The mean values for slow-growing seedlings can be calculated by summarizing the effect with the estimate (e.g. mean shoot height of slow-growing seedlings = 7.12).

  6. d

    Error distribution binomial.

  7. e

    Error distribution Poisson.

N%d−4.54 ± 0.940.037 ± 1.318
Mean ± SD1.06 ± 0.320.04 ± 0.08      
ECM colonization percentaged−3.01 ± 0.78−0.05 ± 0.40 5.79 ± 1.09 6.54 ± 0.98 5.98 ± 1.94 5.83 ± 1.13
Mean ± SD82.16 ± 22.703.02 ± 3.7      
ECM richnesse0.505 ± 0.0650.017 ± 0.091
Mean ± SD1.67 ± 0.750.06 ± 0.02      
Root tip numbere6.74 ± 0.100.172 ± 0.14 −0.53 ± 0.01 −0.28 ± 0.01 −0.7 ± 0.027 0.17 ± 0.01 0.05 ± 0.01 0.04 ± 0.01
Mean ± SD709 ± 403−62 ± 21      
image

Figure 2. Realized ectomycorrhizal (ECM) colonization patterns of Norway spruce seedlings. The bar chart shows the abundance of both nonmycorrhizal (nm) and ECM root tips of fast- and slow-growing spruce seedlings in 12 treatments inoculated with Tylospora asterophora (T.a), Piloderma sp. (P), and Wilcoxina sp. (W). The nursery contaminant Thelephora terrestris (T.t) colonized all treatments, and Hebeloma sp. was not present at all. Treatment codes are shown above the bars: c is the uninoculated treatment, h, p, t and w are treatments with only the named ECM fungi as inoculum, hp, hw, th, tp, tw and wp represent pairwise inoculations and the treatment ‘all’ contains Piloderma sp., Wilcoxina sp., T. asterophora and the nursery contaminant T. terrestris. See Table 1 for a more detailed explanation.

Download figure to PowerPoint

There were no statistically significant differences in shoot height or shoot and root biomass between the seedlings representing fast and slow growth performance groups when the growth, richness and ECM fungal colonization percentage were taken into account (Table 2). Shoot and root biomasses (Fig. S1) of seedlings were strongly correlated (r2 = 0.78; t283 = 21; < 0.0001).

ECM colonization improved the shoot biomass production of slow-growing families (r2 = 0.18; t139 = 2.2; = 0.03). The shoot height of slow-growing seedlings was also greater with increasing ECM fungal colonization (r2 = 0.27; t141 = 3.4; < 0.01) and marginally improved with increasing richness (r2 = 0.15; t141 = 1.8; = 0.07). ECM colonization and richness did not have significant effects on the shoot height of fast-growing seedlings (significant richness–growth group interaction in Table 2). However, we observed a marginally significant trend for biomass allocation; increasing ECM richness moved biomass allocation of fast-growing seedlings towards roots (r2 = −0.15; t142 = −1.8; = 0.08). ECM-related improved aboveground growth appeared to be associated with high abundance of Wilcoxina sp. (Table 2); on fast-growing seedlings it increased biomass allocation aboveground (r2 = 0.1; t142 = 1.9; = 0.05) and on slow-growing seedlings it also improved shoot biomass (r2 = 0.21; t139 = 2.6; = 0.01) and shoot height (r2 = 0.24; t141 = 3.0; < 0.01). Increasing colonization by Piloderma sp. (Fig. 3a) reduced the shoot:root ratio of both fast- (r2 = −0.29; t142 = −3.6; < 0.001) and slow-growing (r2 = −0.21; t139 = −2.5; < 0.02) spruce families, and evened out differences in root biomass and root tip number between seedlings (Table 2). Tree family affected growth more than the increasing ECM fungal richness; seed family 1162, a fast-growing family, had the highest overall shoot and root dry weight and family 427, a slow-growing family, had the lowest (Table S1, Fig. S1). However, the increase in root growth of family 427 after ECM colonization was the greatest recorded (data not shown).

image

Figure 3. The effect of Piloderma sp. colonization percentage on (a) shoot:root ratio and (b) short-root density of fast- and slow-growing Norway spruce families. Both traits were statistically significantly affected by the abundance of Piloderma sp. (for further details see Table 2). The dashed line shows the mean value for fast-growing families and the solid line shows the mean value for slow-growing families.

Download figure to PowerPoint

The root structures of the two growth performance groups were statistically significantly different; slow-growing seedlings had somewhat higher short-root density (Table 2); that is, a higher number of root tips per unit dry weight. However, in total the fast-growing families still had roughly the same number of root tips as the slow-growing ones as a result of the slightly bigger root systems (Table 2). ECM fungal colonization influenced short-root initiation strongly, although ECM fungal diversity did not affect the short-root density in general; high levels of Piloderma sp. colonization resulted in significantly lower short-root density (Table 2, Fig. 3b) on both fast- (r2 = −0.27; t142 = −3.3; < 0.01) and slow-growing (r2 = −0.18; t141 = −2.2; < 0.05) families.

Nitrogen acquisition by seedlings

Needle N concentration (% of dry weight) and the N content (mg) did not vary statistically significantly between fast- and slow-growing seedlings (Table 2). ECM fungal colonization had a positive relationship with N concentration (%) in needles on both fast- (ρ = 0.32; < 0.001) and slow-growing (ρ = 0.23; < 0.02) seedlings. Increasing ECM fungal richness had contrasting effects on the N contents (mg) of the fast- and slow-growing families, shown as the significant interaction of fungal richness and growth performance group (Table 2): in slow-growing seedlings the relationship was positive (ρ = 0.21; = 0.03), as increasing diversity triggered aboveground growth, and in the fast-growing group it was negative (ρ = −0.22; = 0.02), as increasing diversity shifted resource allocation belowground.

Potential exoenzyme activities in relation to plant growth phenotype and ECM fungal colonization

ECM fungal colonization increased potential exoenzyme activity in general compared with the nonmycorrhizal root tips (Fig. 4). The fungal-specific enzyme activity profiles were distinct and differed especially in their potential to mobilize N and P as well as lignocellulose compounds (Fig. 4); Piloderma sp. displayed the highest acid phosphatase and leucine aminopeptidase activities. Tylospora asterophora showed the highest lignocellulose-degrading laccase activity, and in contrast T. terrestris displayed moderate activity of all enzymes except laccase. Wilcoxina sp. clearly had the highest activities of chitinase, cellobiohydrolase and glucoronidase but no acid phosphatase or leucine aminopeptidase activity was detected.

image

Figure 4. Mean (± 1 standard error) of potential activities of cellobiohydrolase, β-glucuronidase, β-glucosidase, laccase, leucine aminopeptidase, chitinase, acid phosphatase and β-xylosidase of single root tips in fast- and slow-growing Norway spruce seedlings when nonmycorrhizal (nm) and colonized with Piloderma sp., Tylospora asterophora, Thelephora terrestris, and Wilcoxina sp. Potential enzyme activities did not differ between fast (F)- and slow (S)-growing seedlings. Different letters in the corners of each polygon show the ECM fungi that differed in their potential enzyme activity based on pairwise comparisons.

Download figure to PowerPoint

The potential exoenzyme activities of single root tips and at the whole root system level were independent of growth performance group (F1,285 = 0.48; R2 = 0.002; = 0.450 and F1,285 = 1.29; R2 = 0.005; = 0.183, respectively). There was a weak positive correlation between shoot height and the mean values of potential enzyme activities in single root tips of both cellobiohydrolase (ρ = 0.31; < 0.001) and xylosidase (ρ = 0.21; < 0.001). ECM fungal richness had a positive relationship with the mean of potential enzyme activities in single root tips involved in degradation of organic N and P compounds and lignocellulose – leucine aminopeptidase (ρ = 0.40; < 0.001), acid phosphatase (ρ = 0.26; < 0.001) and laccase (ρ = 0.21; P = 0.002) (Fig. 5). The effect of increasing ECM richness on potential laccase activity was stronger in the slow-growing seedlings than in the fast-growing ones (Fig. 5). None of the ECM fungi, except T. terrestris, showed different enzyme activity profiles in co-existence with other ECM species in mixed inoculated plants; T. terrestris potential exoenzyme activity in root tips increased with increasing ECM richness of the host plant (F1,80 = 0.33; < 0.001).

image

Figure 5. Mean values (± 1 SE) of potential enzyme activities of cellobiohydrolase, β-glucuronidase, β-glucosidase, laccase, leucine aminopeptidase, chitinase, acid phosphatase and β-xylosidase in single root tips under an increasing ectomycorrhizal (ECM) richness gradient. ECM richness represents the actual number of ECM fungi in the sample; class 3 includes also four seedlings in which ECM richness was four. The numbers of seedlings in different richness classes are given in the richness class headings. Potential enzyme activities did not differ between fast-growing (F) and slow-growing (S) Norway spruce seedlings. ‘*’ indicates statistically significant differences in potential root tip activities between richness classes. Increasing richness significantly affected the potential activity of leucine aminopeptidase (< 0.001), acid phosphatase (< 0.01) and laccase (< 0.001). The effect of increasing richness was much stronger in slow-growing spruce seedlings than in fast-growing ones (almost significant interaction of ECM richness and growth performance group; = 0.051). Results are based on multivariate analysis of variance with growth performance group, ECM richness and their interaction as fixed factors.

Download figure to PowerPoint

The effect of the potential exoenzyme activities in seedling root systems on N acquisition

The potential exoenzyme activities of the whole root systems of seedlings were approximated from the measured enzyme production potentials of single root tips considering root tip density, ECM colonization percentage and root biomass (Figs 6, S2). Hence, the abundance of a certain fungus in the roots determined the potential exoenzyme activities: a high amount of Wilcoxina sp.-infected root tips led to relatively high root system-level production of chitinase, cellulases and hemicellulases, whereas high production of enzymes degrading N- and P-containing compounds was associated with a high abundance of Piloderma sp. in seedling roots (Fig. S2).

image

Figure 6. Mean values (± 1 SE) of potential activities of cellobiohydrolase, β-glucuronidase, β-glucosidase, laccase, leucine aminopeptidase, chitinase, acid phosphatase and β-xylosidase in the whole root system of fast-growing (F) and slow-growing (S) Norway spruce seedlings under an increasing ECM richness gradient. The numbers of seedlings in different richness classes are noted in the richness class headings. ‘*’ indicates statistically significant differences in potential activities of laccase (< 0.05) and leucine aminopeptidase (< 0.05) between richness classes. Results are based on multivariate analysis of variance with the growth performance group, ECM richness and their interaction as fixed factors. In general the potential enzyme activities did not differ between fast- and- slow-growing seedlings. There was a marginally significant trend for the potential activity of acid phosphatase to be slightly higher in fast-growing families (= 0.102).

Download figure to PowerPoint

Enzymes targeting cellulose and hemicellulose compounds were produced regardless of ECM taxonomical richness (Fig. 6). Increasing ECM fungal richness improved in particular potential laccase and leucine aminopeptidase activities of the host seedling (Fig. 6). However, in this experiment high richness and the abundance of Piloderma sp. and T. asterophora were interlinked, and therefore the effect of increasing diversity cannot be separated from the effects of these two ECM fungi. Seedlings having multiple ECM fungal species associated with their roots or colonized by either T. asterophora or Piloderma sp. had the highest potential laccase and leucine aminopeptidase activities (Figs 6, S2).

The functional potential of seedling ECM root tips differed markedly according to the identity and abundance of colonizing fungi and also with respect to ECM fungal community structure (Figs 4-6, S2). High abundance of Wilcoxina sp. and T. terrestris was associated with increased needle N content (mg) (Table 2). Furthermore, the whole root system exoenzyme secretion significantly affected nutrient acquisition. The N content (mg) of needles correlated strongly with the potential exoenzyme activities of chitinase (ρ = 0.56; < 0.001) and cellulolytic enzymes like cellobiohydrolase (ρ = 0.53; < 0.001), β-glucosidase (ρ = 0.54; < 0.001), β-glucoronidase (ρ = 0.50; < 0.001) and β-xylosidase (ρ = 0.53; < 0.001). Secretions of these enzymes were also highly autocorrelated (ρ > 0.92; < 0.001).

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

We explored the possible mechanistic role of ECM fungi in the development of Norway spruce seedlings originating from seed families known to differ in their long-term growth rate before their growth differences became apparent. The fitness of the seedlings was assessed via several approaches. First, seedling material possessing a known long-term growth performance was used. Secondly, the needle N content was determined, as this is known to function as a future resource for needle growth through positive effects on stress tolerance (Grossnickle, 2000) and on the photosynthetic activity in needles (Evans, 1989). Finally, we measured the root and shoot biomass and shoot height of the 1-yr-old seedlings at the end of the experiment.

ECM community composition of fast- and slow-growing families

During their first year of development, fast- and slow-growing spruce families did not show a distinction in receptiveness to ECM fungal richness when exposed to Wilcoxina sp., Piloderma sp., T. asterophora and T. terrestris ECM fungi. The ECM communities of the fast- and slow-growing seedlings were very similar, apart from the nursery-originating T. terrestris which showed a marginally significant trend of being slightly more abundant on the roots of slow-growing families. This is consistent with the findings of Korkama et al. (2006) in 11-yr-old fast- and slow-growing spruce clones. However, based on our results we reject our first working hypothesis and conclude that, before the differences in growth rates were visible, both the fast- and slow-growing seed families had a uniform level of ECM fungal colonization, and they established an equally diverse ECM community. In addition, we have congruent data from the same seed families inoculated with homogenized forest humus which additionally reinforce the view that in the early stages of development there is no difference in ECM diversity between fast- and slow-growing seedlings (Velmala et al., unpublished).

Effect of ECM fungi on vitality of fast- and slow-growing families

The ECM richness per se had context-dependent effects on plant production, as reported in previous experiments examining the role of diversity (Baxter & Dighton, 2001, 2005; Jonsson et al., 2001; Kipfer et al., 2012). In addition to the environmental factors already noted to affect the impact of ECM diversity on a host tree, there appears to be an internal mechanism that directs these effects, as already suggested in 1971 by Marx and Bryan. The impact of ECM richness on aboveground growth and shoot nutrient gain of fast- and slow-growing seedlings were somewhat contradictory. In the early stages of development, the slow-growing families seemed to be more responsive and to allocate the benefit from ECM richness to their aboveground parts, whereas fast-growing families allocated more of the benefit to belowground parts. Similar responses have also been observed in other studies, where poorly performing spruce families exhibited a stronger positive growth response when colonized with ECM fungi than the better performing families (Boukcim & Plassard, 2003; Mari et al., 2003). Thus, it seems that the genetic variation of spruce that is connected to later growth rates has an influence on the biomass gain that seedlings obtain from ECM fungi during their very early years. Based on these results, and in agreement with Sonesson et al. (2002), we believe that the measurements based on aboveground growth of small seedlings fail to represent the true performance of trees with a long lifespan.

Previously we reported that there is a genetic component driving the short-root formation and root growth of Norway spruce (Velmala et al., 2013). In the present study, we found that, regardless of the associated ECM community, the structure of the root systems varied between fast- and slow-growing families and was constant between growth performance groups; slow-growers had denser root systems than fast-growers. In addition, the slow-growing seedlings produced significantly more fine roots per unit root biomass and presumably less thick second- and third-order laterals, resulting in a spatially less spread-out root system. The same phenomenon was also found in our nursery study (Velmala et al., unpublished) with a larger set of seedlings from the same six spruce families.

We therefore suggest a structural effect of host genotype on the belowground ECM community via root growth and short-root structuring. It seems plausible that the associated ECM fungal communities are to a great extent determined via root structuring, rather than direct susceptibility of the host to its symbionts. Furthermore, the observed differences between the fine roots of fast- and slow-growing seedlings might later affect their ability to assemble ECM diversity in spatially heterogeneous forest soil (Peay et al., 2011). Root architecture might indeed be the ‘unknown host mechanism’ suggested by Lang et al. (2013), resulting in spatial ECM species segregation and ensuring high diversity on an individual tree. In our experimental set-up, variable root structuring was not likely to affect the colonization as the growing medium in the pots was homogenous and abundantly inoculated with ECM fungal mycelia in order to give equal opportunities for the fungi to colonize the roots.

Potential activities of exoenzymes and N acquisition

As the functional potential of ectomycorrhizas was very similar between fast- and slow-growing seedlings, one could assume that the long-term superiority of fast-growing families does not lie in utilizing the assembled ECM fungi for qualitatively or quantitatively more efficient enzyme production. Thus, our results may suggest that the belowground investment of biomass by the fast-growing families happens primarily by controlling root architecture instead of preferential selection of ECM fungi or secretion of their exoenzymes.

As expected from previous research (Bueé et al., 2007), the functional abilities of ECM short roots differed greatly according to the identity of the colonizing fungi. Hence, both the number of active short roots and the ECM fungal community composition greatly affected the total potential enzyme production of the seedlings. The species-specific fungal enzyme profiles differed especially in their potential abilities for N and P mobilization and degradation of cell wall compounds, thus indicating functional complementarity of resource use. Piloderma sp. secreted hemicellulases and produced most hydrolytic enzymes involved in the mobilization of P and N from litter and amino acids, respectively. Piloderma species have previously been reported to increase the gain of organic P and N (Baxter & Dighton, 2005). Tylospora asterophora alone was capable of high laccase activity, which has been suggested to be involved in release of N and P bound in humic substances (Criquet et al., 1999). Wilcoxina sp. showed the greatest chitinase activity and also had the highest potential activity of glucose-releasing cellulases and hemicellulases, but in turn no hydrolytic activity involved in mobilization of P and release of amino acids. Thus, from the potential enzyme activity perspective, the higher diversity treatments were superior to every single ECM fungal treatment because of an enhanced functional complementary of the more diverse ECM fungal community, a phenomenon found previously in many studies (Allen et al., 1995; Cairney, 1999; Rineau & Courty, 2011). Tylospora asterophora and Piloderma sp. were always present in our high-diversity treatments, thus adding functional abilities on top of those of T. terrestris and Wilcoxina sp., resulting in higher activities of potential P release and protein- and lignocellulose-degrading enzymes. Therefore, the higher functional activity, in the high-diversity treatments, was a matter of functional reciprocity rather than a sampling effect (Wardle, 1999).

In heterogeneous forest soils, it is advantageous for a tree to be associated with ECM fungi that can simultaneously utilize both organic and inorganic N (Kemppainen et al., 2010; Avolio et al., 2012), because ECM fungi control host gain of recalcitrant N (Talbot et al., 2013). ECM fungi increase plant productivity in nutrient-limiting conditions by enhancing access to organically bound nutrients (Jonsson et al., 2001; Baxter & Dighton, 2005) and affect both the species composition and the diversity of the root-associated fungal community through interactions with other fungi (Johnson et al., 2012). In the present study, high activity of chitinase and cellulases had a strong positive relationship with needle N content. This is consistent with the field study of Jones et al. (2009) in which the abundance of Wilcoxina sp. was associated with high accumulation of N in both shoots and roots. Based on our measurements of potential enzyme activities, Wilcoxina sp. seemed to be effective in degrading chitin, which is a structural fungal cell wall polysaccharide and an abundant organic N reservoir in boreal forest soil.

Limitations of the approach

In our study, it is possible that the dominance of Wilcoxina sp. may have masked some of the possible effects of ECM community composition and diversity on nutrient acquisition and growth in mixed inoculum treatments. This competitive reduction of ECM colonization has also been found earlier in other fungal diversity gradient studies (Baxter & Dighton, 2001, 2005; Jonsson et al., 2001). To account for this, the fungi used were selected to represent the most common ECM species found in association with young Norway spruce in natural conditions (Korkama et al., 2006, 2007) and the laborious ‘inoculation using donor ECM seedlings’ method was used. In addition, the presence of nursery-originating T. terrestris in the uninoculated treatment prevents comparisons between nonmycorrhizal and ECM-inoculated seedlings, which would be interesting but of low practical value. Nevertheless, we were still able to create a gradient of increasing ECM richness with varying fungal combinations (e.g. T. asterophora, Piloderma sp. and T. terrestris), and the resulting colonization patterns represent closely the natural diversities of small seedlings (Vaario et al., 2009). However, it is still likely that, with an even colonization of the different ECM species, the effects of each fungus contributing to the increasing ECM richness may have been clearer.

Additionally, the limitation of the enzymatic assay used is that it does not include the functional activity of the extraradial mycelia, which has a crucial role in the transfer and mobilization of nutrients from organic matter in forests compared with ECM root tips (Perez-Moreno & Read, 2000; Talbot et al., 2013). However, our comparison concerns the same fungal strains colonizing different seedlings and thus these results are comparable between seedling groups.

Conclusions

Our approach challenges the traditional practice of determining the performance of long-lived trees by measuring only the short-term aboveground response of seedlings. In our experiment, in which there was a relatively low richness of ECM fungi, increasing species richness increased host nutrient acquisition potential by diversifying the exoenzyme palette. However, it is likely that there is a threshold of ECM taxonomical richness over which no added value of functionality is obtained, as numerous studies suggest that some degree of functional redundancy occurs in the naturally diverse environment (Allen et al., 1995; Dahlberg, 2001; Wellniz & Poff, 2001). Our study demonstrates the importance of functional diversity of ECM species for spruce seedling nutrient acquisition. Moreover, it suggests, in accordance with the arguments of Bengtsson (1998), that neither the richness of ECM species per se nor the functional efficiency of single ectomycorrhizas is a major factor underlying the superior long-term growth of fast-growing spruce families over slow-growing ones.

It seems likely that, from a long-term perspective, faster growth rates are achieved through the additive effects of enriching factors; optimal root structuring and growth, which might lead to increased ECM diversity and more importantly ECM functional diversity, and thus better growth performance of spruce in the field. It may also be noteworthy that, during the early years of their development, the fast-growing families allocate the benefit from ECM symbiosis more to their belowground parts compared with slow-growing families. Thus, we propose that the mechanistic link between high biomass production and ECM diversity is that spruce individuals showing fast growth in the course of time possess sparse root growth and thus the potential to assemble a functionally complementary ECM community, which in a spatially heterogeneous soil results in a positive circle of accumulating benefit, also called the ‘Matthew effect’ (Merton, 1968).

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

This work was funded by the Academy of Finland project number 128229. We are grateful for the work of Marja-Leena Napola, Satu Peltola, the staff of Haapastensyrjä nursery, Arja Tervahauta, Minna Oksanen, Matias Häyrynen, Vesa Hautala, Ritva Vanhanen, Adriana Villaverde Monar, Laura Hänninen and Tatu Uutela. We thank Dr Audrius Menkis for providing us with the Wilcoxina sp. isolate. We are thankful to three anonymous referees for their suggestions which greatly improved the manuscript.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • Allen EB, Allen MF, Helm DJ, Trappe JM, Molina R, Rincon E. 1995. Patterns and regulation of mycorrhizal plant and fungal diversity. In: Collins HP, Robertson GP, Klug MJ, eds. The significance and regulation of soil biodiversity. Dordrecht, the Netherlands: Kluwer Academic Publishers, 4762.
  • Avolio M, Müller T, Mpangara A, Fitz M, Becker B, Pauck A, Kirsch A, Wipf D. 2012. Regulation of genes involved in nitrogen utilization on different C/N ratios and nitrogen sources in the model ectomycorrhizal fungus Hebeloma cylindrosporum. Mycorrhiza 22: 515524.
  • Bates D, Maechler M, Bolker B. 2011. lme4: Linear mixed-effects models using S4 classes. R package version 0.999375-42 [WWW document]. URL http://CRAN.R-project.org/package=lme4 [accessed 10 January 2012].
  • Baxter JW, Dighton J. 2001. Ectomycorrhizal diversity alters growth and nutrient acquisition of grey birch (Betula populifolia) in host-symbiont culture conditions. New Phytologist 152: 139149.
  • Baxter JW, Dighton J. 2005. Phosphors source alters host plant response to ectomycorrhizal diversity. Mycorrhiza 15: 513523.
  • Bending GD, Read DJ. 1995. The structure and function of the vegetative mycelium of ectomycorrhizal plants. VI. Activities of nutrient mobilizing enzymes in birch litter colonized by Paxillus involutus (Fr.) Fr. New Phytologist 130: 411417.
  • Bengtsson J. 1998. Which species? What kind of diversity? Which ecosystem function? Some problems in studies of relations between biodiversity and ecosystem function. Applied Soil Ecology 10: 191199.
  • Boukcim H, Plassard C. 2003. Juvenile nitrogen uptake capacities and root architecture of two open-pollinated families of Picea abies. Effects of nitrogen source and ectomycorrhizal symbiosis. Journal of Plant Physiology 160: 12111218.
  • Bray JR, Curtis JT. 1957. An ordination of the upland forest communities of southern Wisconsin. Ecological Monographs 27: 325349.
  • Bueé M, Courty PE, Mignot D, Garbaye J. 2007. Soil niche effect on species diversity and catabolic activities in an ectomycorrhizal fungal community. Soil Biology & Biochemistry 39: 19471955.
  • Cairney JWG. 1999. Intraspecific physiological variation: implications for understanding functional diversity in ectomycorrhizal fungi. Mycorrhiza 9: 125135.
  • Chalot M, Brun A. 1998. Physiology of organic nitrogen acquisition by ectomycorrhizal fungi and ectomycorrhizas. FEMS Microbiology Reviews 22: 2144.
  • Courty PE, Buée M, Diedhiou AG, Frey-Klett P, Le Tacon F, Rineau F, Turpault MP, Uroz S, Garbaye J. 2010. The role of ectomycorrhizal communities in forest ecosystem processes: new perspectives and emerging concepts. Soil Biology & Biochemistry 42: 679698.
  • Criquet S, Tagger S, Vogt G, Iacazio G, Le Petit J. 1999. Laccase activity of forest litter. Soil Biology and Biochemistry 31: 12391244.
  • Dahlberg A. 2001. Community ecology of ectomycorrhizal fungi: an advancing interdisciplinary field. New Phytologist 150: 555562.
  • Evans JR. 1989. Photosynthesis and nitrogen relationships in leaves of C3 plants. Oecologia 78: 919.
  • Flykt E, Timonen S, Pennanen T. 2008. Variation of ectomycorrhizal colonization in Norway spruce seedlings in Finnish forest nurseries. Silva Fennica 42: 571585.
  • Gardes M, Bruns TD. 1993. ITS primers with enchanced specificity for basidiomycetes - an application to the identification of mycorrhizae and rust. Molecular Ecology 2: 113118.
  • Grossnickle SC. 2000. Ecophysiology of northern spruce species: the performance of planted seedlings. Ottawa, Canada: NRC Research Press.
  • Holm S. 1979. A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics 6: 6570.
  • Ihrmark K, Bödeker I, Cruz-Martinez K, Friberg H, Kubatova A, Schenck J, Strid Y, Stenlid J, Brandström-Durling M, Clemmensen CE et al. 2012. New primers to amplify the fungal ITS2 region – evaluation by 454-sequencing of artificial and natural communities. FEMS Microbiology Ecology 82: 666677.
  • Johnson D, Martin F, Cairney JWG, Anderson IC. 2012. The importance of individuals: intraspecific diversity of mycorrhizal plants and fungi in ecosystems. New Phytologist 194: 614628.
  • Jones M, Grenon F, Peat H, Fitgerald M, Holt L, Philip LJ, Bradley R. 2009. Differences in 15N uptake amongst spruce seedlings colonized by three pioneer ectomycorrhizal fungi in the field. Fungal Ecology 2: 110120.
  • Jonsson L, Nilsson MC, Wardle DA, Zacrkrisson O. 2001. Context dependent effects of ectomycorrhizal species richness on tree seedling productivity. Oikos 93: 353364.
  • Kemppainen MJ, Alvarez Crespo MC, Pardo AG. 2010. fHANT-AC genes of the ectomycorrhizal fungus Laccaria bicolor are not repressed by l-glutamine allowing simultaneous utilization of nitrate and organic nitrogen sources. Environmental Microbiology Reports 2: 541553.
  • Kipfer T, Wohlgemuth T, van der Heijden MGA, Ghazoul J, Egli S. 2012. Growth responce of drought- stresed Pinus sylvestris seedlings to single- and multi-species inoculation with ectomycorrhizal fungi. PLoS ONE 7: e35275.
  • Kleinschmit J, Smidht J. 1977. Experiences with Picea abies cuttings propagation in Germany and problems connected with large scale application. Silvae Genetica 26: 197203.
  • Korkama T, Fritze H, Pakkanen A, Pennanen T. 2007. Interactions between extraradical ectomycorrhizal mycelia, microbes associated with the mycelia and growth rate of Norway spruce. New Phytologist 173: 798807.
  • Korkama T, Pakkanen A, Pennanen T. 2006. Ectomycorrhizal community structure varies among Norway spruce (Picea abies) clones. New Phytologist 171: 815824.
  • Lang C, Finkeldey R, Polle A. 2013. Spatial patterns of ectomycorrhizal assemblages in a monospecific forest in relation to host tree genotype. Frontiers in Plant Science 4: 103.
  • Mari S, Jonsson A, Finlay R, Ericsson T, Kähr M, Erkisson G. 2003. Genetic variation in nitrogen uptake and growth in mycorrhizal and nonmycorrhizal Picea abies (L.) Karst. seedlings. Forest Science 49: 258267.
  • Marx D. 1969. The influence of ectomycorrhizal fungi on the resistance of pine roots to pathogenic infections: antagonism of mycorrhizal fungi to root pathogenic fungi and soil bacteria. Phytopathology 59: 153163.
  • Marx D, Bryan C. 1971. Formation of Ectomycorrhizae on Half-Sib Progenies of slash pine in aseptic culture. Forest Science 17: 488492.
  • Melin E. 1953. Physiology of mycorrhizal relations in plants. Annual Revision of Plant Physiology 4: 325346.
  • Merton RK. 1968. The Mathew effect in science. Science, New Series 159: 5663.
  • Muyzer G, de Waal E, Uitterlinden A. 1993. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Applied and Environmental Microbiology 59: 695700.
  • Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O'Hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H. 2012. vegan: Community Ecology Package. R package version 2.0-3. [WWW Document]. URL http://CRAN.R-project.org/package=vegan [accessed 3 September 2012].
  • Peay K, Kennedy P, Bruns T. 2011. Rethiking ectomycorrhizal succession: are root density and hyphal exploration types drivers of spatial and temporal zonation. Fungal Ecology 4: 233240.
  • Perez-Moreno J, Read D. 2000. Mobilization and transfer of nutrients from litter to tree seedling via the vegetative mycelium of ectomycorrhizal plants. New Phytologist 145: 301309.
  • Pritsch K, Corty PE, Churin JL, Cloutier-Hurteau B, Ali MA, Damon C, Duchemin M, Egli S, Ernst J, Fraissiniet-Tachet L et al. 2011. Optimized assay and storage conditions for enzyme activity profiling of ectomycorrhizae. Mycorrhiza 21: 589600.
  • Pritsch K, Garbaye J. 2011. Enzyme secretion by ECM fungi and exploitation of mineral nutrients from soil organic matter. Annals of Forest Science 68: 2532.
  • Pritsch K, Raidl S, Marksteiner E, Blaschke H, Agerer R, Schloter M, Hartman A. 2004. A rapid and highly sensitive method for measuring enzyme activities on single mycorrhizal tips using 4-methylumbelliferone-labelled fluorogenic substrates in a microplate system. Journal of Microbial Methods 58: 233241.
  • R Development Core Team. 2012. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. ISBN 3-900051-07-0. URL http://www.R-project.org/.
  • Rajala T, Peltoniemi M, Pennanen T, Mäkipää R. 2010. Relationship between wood-inhabiting fungi determined by molecular analysis (denaturing gradient gel electrophoresis) and quality of decaying logs. Canadian Journal of Forest Research 40: 23842397.
  • Read D, Perez-Moreno J. 2003. Mycorrhizas and nutrient cycling in ecosystems – a journey towards relevance. New Phytologist 157: 475492.
  • Rineau F, Courty PE. 2011. Secreted enzymatic activities of ectomycorrhizal fungi as a case study of functional diversity and functional redundancy. Annals of Forest Science 68: 6980.
  • Sonesson J, Jansson G, Eriksson G. 2002. Retrospective genetic testing of Picea abies under controlled temperature and moisture regimes. Canadian Journal of Forest Research 32: 8191.
  • Talbot JM, Bruns TD, Smith DP, Branco S, Glassman SI, Erlandson S, Vilgalys R, Peay KG. 2013. Independent roles of ectomycorrhizal and saprotrophic communities in soil organic matter decomposition. Soil Biology & Biochemistry 57: 282291.
  • Vaario LM, Tervonen A, Haukioja K, Haukioja M, Pennanen T, Timonen S. 2009. The effect of nursery substrate and fertilization on the growth and ectomycorrhizal status of containerized and outplanted seedlings of Picea abies. Canadian Journal of Forest Research 39: 6475.
  • Velmala SM, Rajala T, Haapanen M, Taylor AFS, Pennanen T. 2013. Genetic host tree effects on the ectomycorrhizal community and root characteristics of Norway spruce. Mycorrhiza 1: 2231.
  • Wardle DA. 1999. Is “sampling effect” a problem for experiments investigating biodiversity-ecosystem function relationships? Oikos 87: 403407.
  • Wellniz T, Poff NL. 2001. Functional redundancy in heterogeneous environments: implications for conservation. Ecology Letters 4: 177179.
  • White TJ, Bruns T, Lee S, Taylor J. 1990. Amplification and direct sequencing of fungal ribosomal RNA genesfor phylogenetics. In: Innis MA, Gelfand DH, Sninsky JJ, White T, eds. PCR protocols guide to methods and amplifications. San Diego, CA, USA: Academic Press, 315322.
  • Wickham H. 2009. ggplot2: elegant graphics for data analysis. New York, NY, USA: Springer.

Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Please note: Wiley Blackwell are not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

FilenameFormatSizeDescription
nph12542-sup-0001-TableS1-MethodS1-FigS1-S2.pdfapplication/PDF824K

Table S1. Origin, growth performance and seed collection year of the Norway spruce (Picea abies) seed orchards used in the study

Methods S1. Cultivation of donor Norway spruce (Picea abies) seedlings and ECM fungal strains.

Fig. S1. The growth characteristics (mean + 1 SE; = 12) of fast- and slow-growing Norway spruce (Picea abies) seed families after 1 yr of growth.

Fig. S2. The potential enzyme activities of ECM root systems of fast- and slow-growing Norway spruce (Picea abies) seed families in different ECM fungal diversity treatments.