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Species composition of an ectomycorrhizal fungal community along a local nutrient gradient in a boreal forest Blackwell Publishing Ltd
Jonas F. Toljander, Ursula Eberhardt, Ylva K. Toljander, Leslie R. Paul and Andy F. S. Taylor Department of Forest Mycology and Pathology, Swedish University of Agricultural Sciences, Box 7026, SE-750 07, Uppsala, Sweden
Summary Author for correspondence: Andy F. S. Taylor Tel: +46 18 67 27 97 Fax: +46 18 67 35 99 Email:
[email protected] Received: 19 January 2006 Accepted: 6 February 2006
• Soil abiotic factors are considered to be important in determining the distribution of ectomycorrhizal (ECM) fungal species; however, there are few field data to support this. Here, we relate ECM species distributions to changes in soil chemistry along a short (90-m), natural nutrient gradient. • The ECM community was characterized, using morphological and molecular techniques, in soil samples collected at 10-m intervals. • There were pronounced changes in ECM fungal community structure along the transect, with many taxa showing discrete distributions. Although there was a change of host from Pinus to Picea along the gradient, host-specific fungi did not account for the observed change in community structure. Ordination analyses showed that community structure was strongly correlated with soil characteristics, in particular extractable ammonium and base saturation. However, autocorrelation among soil parameters makes it difficult to isolate the effects of individual parameters. • The distinctive changes in soil and vegetation along the transect used in this study provided an exceptional opportunity to examine the local-scale impact of natural spatial heterogeneity on an ECM fungal community. Key words: ectomycorrhizal distribution, ectomycorrhizal fungi, edaphic factors, morphotyping, UNITE database. New Phytologist (2006) 170: 873–884 © The Authors (2006). Journal compilation © New Phytologist (2006) doi: 10.1111/j.1469-8137.2006.01718.x
Introduction Read (1991) and Read & Perez-Moreno (2003) discussed the interactive relationships between the dominance of plants associated with different types of mycorrhizas (ericoid mycorrhizas, arbuscular mycorrhizas, and ectomycorrhizas) and soil pH, humus type, and nitrogen (N) mineralization patterns. In general, the distribution of mycorrhizal plants and their associated fungi may be viewed as a gradient of recalcitrance of plant litter. Nutrient-rich soils support plants that produce easily degradable litter and whose roots are colonized by arbuscular mycorrhizal (AM) fungi, while soils with low soil pH and low mineralization rates support plants producing recalcitrant litter and forming ericoid and ectomycorrhizal (ECM) associations. The availability of the
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major plant nutrients N and phosphorus (P) differs markedly along this gradient, and the ability of mycorrhizal fungi within AM, ericoid and ECM associations to access these nutrients seems be a major factor in determining their broad distribution. The conceptual framework discussed by Read & Perez-Moreno (2003) provides compelling arguments for the regional distribution of mycorrhizal types, but little is known about the determinants of local (stand-scale) and microscale (cm to m) distributions of mycorrhizal fungal species. However, a logical extension of the concept would be that the local spatial distribution of individual taxa is influenced by the interplay between the physiological capabilities of taxa and the form and availability of nutrients in the soil environment. In the present study, we examine this idea by determining the distribution of ectomycorrhizal fungal taxa along a local
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gradient of nutrient availability in a boreal forest stand in northern Sweden. In boreal forests, most N is bound in organic form (Tamm, 1991). Mycorrhizal fungi with the capacity to mobilize nutrients from these organic residues should be favoured over those fungi lacking the necessary catabolic enzymes. In addition, the advantage should accrue with increasing reliance on organic nutrient sources. Elevated concentrations of soil mineral N, however, could be expected to favour fungi more specialized in the use of mineral N. Abuzinadah & Read (1986) pointed out that the distribution of fungi in the soil could be influenced by their relative abilities to utilize organic nutrients. They proposed that fungi found in the organic layers were adapted to using organic nutrients, while those in the mineral soil were more dependent upon mineral N. It is well established that many ECM fungi are sensitive to artificially increased concentrations of soil mineral N (see review by Wallenda & Kottke, 1998). Several studies on N fertilization in forest ecosystems have demonstrated decreases in below-ground species richness and shifts in relative abundance of ECM fungal species (e.g. Kårén & Nylund, 1997; Peter et al., 2001). However, the addition of large amounts of mineral N to otherwise N-limited systems may tell us little about the response of ECM fungi under natural conditions of increasing N availability. A less drastic scenario was provided by examining gradients of increasing N deposition on geographically separated sites (Taylor et al., 2000; Lilleskov et al., 2002). These studies also found dramatic changes in ECM structure with increasing mineral N availability, but site differences complicate the interpretation of these studies. An alternative approach would be to study local gradients, where abiotic soil factors may change, but climatic or other site conditions remain constant. Giesler et al. (1998) studied nutrient availability and plant community structure along a local nutrient gradient in a boreal forest at Betsele in northern Sweden. The nutrient-poor end of the gradient is dominated by Scots pine (Pinus sylvestris L.) and ericaceous shrubs but, with increasing soil mineral nutrient content, Norway spruce (Picea abies (L.) Karst.) and a tall herb understorey become increasingly dominant. The results of Giesler et al. (1998) strongly suggested that plant community structure and productivity were, to a great extent, influenced by availability of N and base cations. Nilsson et al. (2005) used specific phospholipid fatty acids (PLFAs) to examine the growth and biomass of mycorrhizal fungal mycelia along the same gradient and found evidence that the biomass of ECM and ericoid fungi declined and that of arbuscular mycorrhizal fungi increased from the poor end to the rich end of the gradient. The data would suggest community shifts within the mycorrhizal communities. However, no identification of fungal taxa was carried out. The Betsele site described by Giesler et al. (1998) represents an opportunity to investigate the below-ground ECM fungal community structure along a local nutrient gradient, which has previously been studied with respect to soil chemistry
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and plant communities. We hypothesized that the ECM fungal community below-ground would differ along the transect and that this could be related to changes in plant community and soil chemistry.
Materials and Methods Site description A 90-m transect that had been previously established along the nutrient gradient by Giesler et al. (1998) was utilized for this study. The transect (Fig. 1) is oriented in the north– south direction on the Umeå River valley side, north-west of Betsele in northern Sweden (64°39′ N, 18°30′ E, 235 m asl). The transect has a rather constant slope of 2%. Mean annual temperature and precipitation are 1.0°C and 570 mm, respectively. On average, the site is covered by snow from late October to early May. The vegetation may be divided into three forest types (Fig. 1): (i) dwarf shrub forest type (0–40 m), which occupies the upper nutrient-poor section of the gradient and is an open Scots pine (P. sylvestris) forest where the field layer is dominated by ericaceous dwarf shrubs; (ii) short herb forest type (50–80 m) – at approximately 40 m the dwarf shrubs gradually become mixed with short herbs and isolated Norway spruce (P. abies) and birch (Betula pubescens) trees; (iii) tall herb forest type at the nutrient-rich end of the gradient (80–90 m), where P. abies is the dominant tree species. Along the transect, the soils (classified as Haplic Podzols; see Giesler et al., 1998) are sandy with many boulders. Although the thickness of the total organic layer was relatively uniform, there were changes in the relative proportions of the F and H layers. Sampling procedure and preparation of samples Soil sampling was performed in August 2001. At 10-m intervals (from 0 to 90 m) along the transect, in accordance with Giesler et al. (1998), five soil samples were taken using plastic cores (2.8 cm diameter), yielding a total of 50 cores. The five samples were taken 20 cm from each other, on a line perpendicular to and centred on the transect. Soil cores were taken to ensure that the entire O horizon was collected. As the initial cores from the 80-m position did not contain any roots, new cores
Fig. 1 Schematic view of the investigated transect at Betsele, north Sweden, showing the changes in tree community ( , Pinus sylvestris; , Picea abies) and thickness of the F (heavy shading) and H (light shading) layers of the organic horizon along the transect. Forest zones: DS, dwarf shrub; SH, short herb; TH, tall herb.
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were collected 3 wk later from this position. The soil samples were stored separately in double plastic bags at 4°C for a maximum of 4 wk. The depth of the O horizon was measured before processing. Roots were extracted from the O horizon by soaking the sample in water for 30 min, then rinsed and collected using a combination of two sieves with mesh sizes of 1.0 and 0.5 mm. Live ECM root tips were studied macroscopically and microscopically and sorted into different morphotypes according to Agerer (1986–2002). The number of live tips per morphotype and sample was recorded. Whenever possible, host species was also recorded. One to five tips per morphotype and sample were saved and stored separately (for a maximum of 12 wk) in microcentrifuge tubes at −40°C until further analysis. Molecular identification of ECM morphotypes Representatives (1–5) of each morphotype underwent DNA analysis. DNA was extracted from single tips and the internal transcribed spacer region (ITS) of the fungal nuclear rDNA was amplified following the same procedure as Rosling et al. (2003), using the primer pairs ITS1 and ITS4 (White et al., 1990) for restriction fragment length polymorphism (ITS-RFLP) analysis. ITS-RFLP was carried out on 10-µl aliquots of polymerase chain reaction (PCR) product, using the restriction enzymes HinfI, MboI and TaqI and following the instructions of the manufacturer (Promega Corporation, Madison, WI, USA). Restriction fragments were separated on 2% MetaPhor® (Biowhittaker Molecular Applications, Rockland, ME, USA) agarose gels (3 h at 140 V). A GelDoc 2000 Gel documentation system (Bio-Rad Laboratories Svl, Segrate, Italy), equipped with the software QUANTITY ONE version 4.10 (Bio-Rad Laboratories Svl), was used to obtain digital images of the gels. The number and sizes of the restriction fragments were analyzed from these images using the program TAXOTRON® 2000 (Grimont, 2000). The patterns were compared with a reference library of ECM ITS-RFLP patterns available at the Department of Forest Mycology and Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden, described by Kårén et al. (1997). In TAXOTRON® 2000, the Unweighted Pair Group Method of Averages (UPGMA) was employed for constructing a neighbour-joining tree comprising all identified RFLP types, including the reference library. For samples that were not identifiable using the RFLP library, the ITS region was sequenced using either only ITS1F or a combination of ITS1 and ITS4 as sequencing primers. The PCR products were purified using the QIAquick™ PCR Purification Kit (Qiagen, Crawley, UK). Sequencing was carried out in 10-µl reaction volumes containing 2 µl of Terminator Ready Reaction Mix (ABI PRISM™ BigDye™ Terminator Cycle Seq Kit v1.1; Applied Biosystems, Foster City, CA, USA) following the instructions of the manufacturers, which were also followed for the subsequent purification steps using a sodium acetate-ethanol protocol. Electrophoresis
was carried out on an ABI PRISM™ 310 Genetic Analyzer (Applied Biosystems). SeqMan™ version 5.05 from the LASERGENE package (DNASTAR, Madison, WI, USA) or SEQUENCHER version 4.1.2 (Gene Codes, Ann Arbor, MI, USA) was employed for sequence editing. Multiple alignments were edited in SE-AL version 2.0a11 (Rambaut, 1996) and analyzed by PAUP version 4.0b10 (Swofford, 2002), using the neighbour joining method (Saitou & Nei, 1987) under the HasegawaKishino-Yano model (Hasegawa et al., 1985). Sequence identification was achieved using GenBank (http:// www.ncbi.nlm.nih.gov/) and the UNITE database (http:// unite.zbi.ee/; Kõljalg et al., 2005). Identifications that fulfilled the necessary criteria (see later in this paragraph) are listed in Supplementary Table S1. For Russulaceae, the database held by one of the authors (UE) was also used. The sequences obtained from ECM (minimum lengths 350 bp; in most cases more than 400 bp) were blasted against both databases. A blast result that was considered to represent a positive identification was required to meet the following criteria. First, the match should be close to 100% (minimum 98%), and include the entire blasted sequence (e.g. not resulting in major gaps or only including the conservative 5.8S region). The relatively broad margin for variation of up to 2% was allowed to accommodate variation resulting from sequence ambiguities and editing errors. Mismatches at the beginning and end of the sequences, ambiguous base pairs in either of the sequences, repetitive sequence motives, single base pair mutations and small indels were tolerated. Secondly, matched sequences had to be derived from sporocarps, preferably from taxonomic studies. The only exceptions to this rule were the identifications of Piloderma reticulatum (Litsch.) Jülich and Piloderma sp. 4, where identification was based on ECM sequences. The authors knew the identifications of these sequences to be reliable (see Rosling et al., 2003). In addition, the results of the blast search were scanned for (i) equally good matches with different names from reliable sources (e.g. taxonomic studies) and (ii) the next-best matches from reliable sources. This was done in order to obtain an estimate of the sequence variation within the group of fungi to which the query taxon belonged. Ideally, the next-best matches from different species varied quantitatively and qualitatively more from the query sequence than the best matches. In addition, two plausibility tests were carried out: (i) the credibility of the matching taxon to occur with the respective host in a boreal forest environment was examined, and (ii) the sequence identification was considered in relation to the morphology of the sequenced tip. Identifications that fulfilled all these criteria were considered as good matches and are listed in Supplementary Table S1 without ‘cf.’. When a good match could not be found, sequence alignments with the closest matches and allies were obtained (if available, using alignments from taxonomic studies as a template) and submitted to neighbour joining analysis. Fungal taxonomic specialists were consulted for the identification of fungi
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Position on transect (m)
Ext. NH42 Soil NO33 C:N ratio pH BS4
0
10
20
30
40
50
60
70
80
90
0.45 0.02 36.6 3.72 68.9
0.42 0.02 38.7 3.80 67.5
0.37 0.01 37.6 3.83 69.6
0.67 0.01 31.8 3.94 76.8
2.61 0.01 29.5 3.95 77.9
6.35 0.01 28.6 4.75 89.9
5.34 0.01 27.3 4.60 88.9
6.93 0.01 23.0 4.90 92.2
10.54 0.04 21.8 5.30 93.5
5.37 0.44 16.9 6.36 97.9
Table 1 Soil characteristics1 at 10-m intervals along a 90-m transect in a boreal forest in northern Sweden
1
Courtesy of Reiner Giesler (Abisko Research Station, Umeå University, Abisko, Sweden). 2.0 M KCl extractable NH4 (mmol kg−1 organic matter). 3 Soil solution NO3 (mmol kg−1 organic matter). 4 Base saturation percentage (K, Na, Ca and Mg). 2
forming resupinate basidiomes (Ellen and Karl-Henrik Larsson, Botanical Institute, Gothenburg University, Gothenburg, Sweden) and for the genus Cortinarius (Ursula Peintner, Institute of Microbiology, University of Innsbruck, Innsbruck, Austria). In the genera Cortinarius and Tomentella, several query sequences resulted in several close but not quite sufficient matches. In these cases, identification was only reported to genus, subgenus or section level. Soil data The soil data used in this study were kindly supplied by R. Giesler (Abisko Research Station, Umeå University, Abisko, Sweden). The soil parameters used to examine potential relationships between soil chemistry and ECM community composition were base saturation percentage [potassium (K), sodium (Na), calcium (Ca) and magnesium (Mg)], extractable NH4 (KClextractable), NO3 (soil solution), carbon:nitrogen (C:N) ratio, and pH. These soil data are derived from the more extensive data set of Giesler et al. (1998) and represented the main parameters that varied across the site. Mean values of these soil chemical parameters at each 10-m position on the transect are shown in Table 1. Statistical analysis In order to investigate the potential influence of measured soil parameters upon ECM community structure, detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) were carried out on the total number of mycorrhizal root tips in each morphotype (ter Braak & Smilauer, 1998). DCA represents an indirect gradient analysis that examines the total variation among the community samples. Canonical correspondence analysis is a direct gradient analysis where the ordination of one matrix (the ECM community data) is constrained by a multiple linear regression on variables (soil parameters) in a second matrix. An initial DCA of the data set demonstrated that the length of the main gradient was 4.296, indicating a unimodal relationship between taxa and nvironmental parameters (ter Braak, 1994). Canonical
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correspondence analysis was therefore chosen over redundancy analysis, which assumes a linear relationship. For the final CCA analysis, only those taxa that occurred at two or more positions on the transect were included in the analysis. The soil parameter NO3 was excluded from the final CCA as preliminary analyses indicated that it did not significantly influence the community composition. Including all 66 taxa resulted in a significant loss of variance explained by the first and second axes, without altering the relative positioning of the samples in the biplot. Detrended correspondence analysis and CCA were both performed using PC-ORD 4.25 (McCune & Mefford, 1999). Within the CCA, Monte Carlo permutation tests (n = 999) were performed to test the significance of the relationship between community data and the soil parameters. Estimates of the potential number of ECM species on the site were gained by obtaining first- and second-order jackknife estimates of species richness using PC-ORD. The effects of transect position on root parameters were examined using oneway analysis of variance (ANOVA) using Minitab© version 12 (Minitab, State College, PA, USA). Ectomycorrhizal fungi have been found to demonstrate patchiness at distances of between 0 and 17 m (Lilleskov et al., 2004). It is therefore possible that autocorrelation between sampling positions along the transect could influence the observed community structure. An attempt was therefore made to differentiate between the effects of soil parameters and spatial scale on community structure. This was done using Mantel tests (PC-ORD) to calculate the correlations between community similarities, soil parameters and spatial distance.
Results A total of 2442 mycorrhizal tips were extracted from the soil samples and sorted into morphotypes. A minimum of two root tips per morphotype per core underwent molecular analysis. In general, samples from the same morphotypes produced identical RFLP patterns. On only three occasions were different RFLP patterns obtained from two tips representing the same morphotype extracted from a single core. We were therefore confident that each morphotype represented a single taxon. In
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Fig. 2 The number of ectomycorrhizal root tips and fungal taxa found in soil cores sampled at 10-m intervals along a 90-m transect in a boreal forest in northern Sweden: (a) mean number of ectomycorrhizal tips per core, (b) mean number of taxa per core and (c) total taxon richness. In (a), bars sharing the same letter are not significantly different at P = 0.05. The dashed lines represent the mean values for each parameter.
a small number of cores, no attempt was made to distinguish between the two Tylospora species. Mycorrhizas were therefore recorded as the single morphotype Tylospora sp. In these cores, when PCR was not successful, the Tylospora morphotypes were assigned to genus level only. The mean number of tips extracted per core was 50.8 ± 33.1 (mean ± se), but typically there was a large variation among soil samples from each point along the transect (Fig. 2a). There was no systematic pattern between the average number of mycorrhizal tips recovered from samples and position along the transect (Fig. 2a). The only significant difference was between the mean number of mycorrhizas found at 30 m and at both 0 and 10 m (one-way ANOVA on mean number of mycorrhizas in cores at each position; F = 3.31; P = 0.005). A total of 66 taxa (Table 2) were distinguished on the roots with a mean of 3.1 ± 1.6 taxa per core (Fig. 2b). There was no significant difference among the transect positions with respect to taxon richness (one-way ANOVA on mean number of taxa in cores at each position; F = 1.48; P = 0.190). There was also no apparent relationship between total taxon richness and transect position (Fig. 2c).
Fig. 3 Rank abundance plot (log10 tips colonized) of the ectomycorrhizal fungal community in a boreal forest in northern Sweden.
When considering the ECM community as a whole, the most abundant taxon was Russula decolorans (Fr.: Fr.) Fr., which accounted for 23.7% of the mycorrhizas examined (Fig. 3, Table 2), with the next most abundant species, Tylospora asterophora (Bonord.) Donk, forming only 6.4% of the mycorrhizas (Table 2). However, both these taxa, like most taxa recorded, had discrete distribution patterns along the transect (Figs 4a,b). In general, most taxa were rarely encountered,
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Abbr.2
Amphinema byssoides (Pers. Fr.) J. Erikss. Cenococcum geophilum Fr. Cortinarius acutus agg. Cortinarius obtusus agg. Dermocybe sanguineus (Wulf. Fr.) Fr. Piceirhiza bicolorata Piloderma byssinum (P. Karst.) Jülich Piloderma fallax (Lib.) Stalpers Piloderma reticulatum (Litsch.) Jülich Russula decolorans (Fr. Fr.) Fr. Tomentella sp. 1 Tomentella sp. 3 Tomentelloid Tylospora asterophora (Bonord.) Donk Tylospora fibrillosa (Burt.) Donk Tylospora sp. Cf. Amphinema Cf. Dermocybe Cf. Hydnellum Cf. Inocybe Cortinarius cf. armillatus Cortinarius cf. obtusus Cortinarius duracinus Fr. Cortinarius sp. 1 Cortinarius sp. 6 Cortinarius sp. 7 Cortinarius subg. Telamonia sp. 1 Cortinarius subg. Telamonia sp. 2 Cortinarius subg. Telamonia sp. 3 Cortinarius subtortus (Pers. Fr.) Fr. Elaphomyces sp. E-type Hydnellum peckii Banker Hygrophorus olivaceoalbus (Fr. Fr.) Fr. Hymenoscyphus ericae agg. Lactarius sp. 1 Lactarius sp. 2 Lactarius sp. 4 Lactarius sp. 5 Lactarius tabidus Fr. Otidea tuomikoskii Harmaja Paxillus involutus (Batsch:Fr.) Fr. Piloderma sp. 4 Russula consobrina Fr. Russula nitida (Pers. Fr.) Fr. Russula paludosa Britzelm. Russula sp. 1 Russula sp. 12 Russula sp. 17 Russula vinosa Lindblad Suillus sp. Thelephora cf. terrestris Tomentella sp. 2 Tomentella sublilacina (Ellis & Holw.) Wakef. Tricholoma sp. Unidentified 1
A. bys. C. geo. C. acu. C. obt. D. san. P. bic. P. bys. P. fal. P. ret. R. dec. T. sp. 1 T. sp. 3 Tom. Ty. ast. Ty. fib. Ty. sp.
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0
10
20
7.7
30
40
50
60
7.2
3.8 3.8
15.0 3.2
2.3 11.3 1.9
4.8 5.7 0.8 7.3 39.0
1.0 4.9 18.2 9.1 88.9 11.1
0.8
9.2 1.2 27.3
2.3 35
2.1
0.9
90
3.9 6.4 8.7 5.7 1.0 0.3
0.5
8.2 9.3
19.2 9.6
0.5
4.7 0.7
0.7
25.8
27.1
0.7
1.6 31.3
3.2 6.5 15.8
14.7
80
0.3
4.7
22.0
70
2.7
7.0
14.6
26.1 0.7 0.7 2.2 0.7
18.4 2.8 0.5 13.3 4.0 6.5 18.3 12.6 5.5 2.7 18.3 1.6 5.0 1.2 2.7 5.7 1.7 1.6 2.6 13.2 0.7 8.0 2.2 9.4 25.4 18.2 0.8 2.1 47.6 5.9
17.6 4.9 4.7 21.1 1.4 11.9 14.4
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Table 2 Continued Ectomycorrhizal fungal abundance (%)1 Position on transect (m) Ectomycorrhizal fungal taxa
Abbr.2
0
Unidentified 2 Unidentified 3 Unidentified 4 Unidentified 5 Unidentified 6 Unidentified ascomycete Unidentified basidiomycete 7 Unidentified basidiomycete 8 Unidentified basidiomycete 9 Unidentified basidiomycete 10
10.6 2.4
Total no. colonized tips
123
10
20
30
40
50
60
70
80
90
2.1 1.1 8.5 2.6 3.3 1.9 15.0 4.8
143
468
414
260
187
213
299
153
182
1
Except for the last line of the table, which shows the total number of colonized tips. Abbr., abbreviations used in Fig. 6.
2
Fig. 5 Calculated taxon area curve based on data from the ectomycorrhizal fungal community sampled across a 90-m transect in a boreal forest in northern Sweden. Points are mean number of expected species ± 1 standard deviation.
Fig. 4 Total number of ectomycorrhizal tips colonized by (a) Russula decolorans, (b) Tylospora asterophora and (c) Cenococcum geophilum found in samples taken at 10-m intervals across a 90-m transect in a boreal forest in northern Sweden.
with the great majority (75%) recorded from single positions on the transect (Table 2). There was no spatial pattern to the number of these ‘unique’ taxa that occurred at each position (data not shown), with between 0 and 10 taxa (mean 5.1 ± 0.4 se) occurring at any given position. No taxon was recorded from all sampling positions. The most widespread taxon was Cenococcum
geophilum Fr., which was recorded in small numbers at seven positions on the transect (Fig. 4c, Table 2). The large number of single occurrences of taxa suggests that we sampled only a limited proportion of species at the site. The taxon sample curve produced from the data confirms this suggestion (Fig. 5). First- and second-order jackknife estimates of the species richness for the site as a whole were 112 and 149, respectively. Ordination The ordination diagram derived from the DCA (not shown) was essentially the same as that obtained from the CCA (Fig. 6). In the CCA, the communities of ECM fungi at the 10 sampling points were successfully segregated into groups corresponding to the three forest types distinguished on the transect (Figs 1 and 6). The total variance in the taxa data was 3.0326 and the eigenvalues of the first and second axes were 0.705 and 0.377,
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Fig. 6 Joint biplot derived from a canonical correspondence analysis (CCA) ordination of data from the ectomycorrhizal fungal community on roots along a 90-m transect in a boreal forest in northern Sweden. Closed triangles represent sampling positions on the gradient and open squares are taxa (for abbreviations, see Table 2). Vectors indicate quantitative soil parameters. Only taxa occurring at more than one position are included.
Table 3 Significance of correlation coefficients between selected soil parameters and axis 1 scores computed in a canonical correspondence analysis on data from the ectomycorrhizal community on a local nutrient gradient in northern Sweden and among soil parameters along the gradient
Axis 1 NH4 BS C:N
NH41
BS2
C:N
pH
− 0.958*** – – –
− 0.891*** 0.885*** – –
0.76** − 0.815** − 0.961*** –
− 0.681* 0.742* 0.907*** − 0.927***
*0.01 < P < 0.05; **0.001 < P < 0.01; ***P < 0.001. 1 2.0 M KCl extractable NH4 (mmol kg−1 organic matter). 2 Base saturation percentage (K, Na, Ca and Mg).
respectively. Using these data to determine variance explained by the first and second axes gave figures of 23.3% and 12.4%, respectively. The Monte Carlo permutation tests showed that only the first axis was significantly (P = 0.007) related to the soil parameters. Each of the parameters had strong positive or negative correlations with axis 1 (Table 3). However, strong autocorrelation among the soil parameters (Table 3) makes it difficult to determine the influence of the individual parameters in this combined analysis. Further CCA analyses were therefore carried out that examined the unique influence of each parameter on the community structure. These demonstrated that extractable NH4 individually explained the most variation (22.4%) followed
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by base saturation (BS) (20.8%) and that only these two parameters gave significant species–environment correlations (NH4, r = −0.981, P = 0.001; BS, r = −0.959, P = 0.017) when analyzed separately. In the individual analyses, the other two parameters C:N and pH accounted for 19.0% and 16.2%, respectively. The 90-m community appears between the dwarf shrub and short herb communities in the ordination diagram because all six taxa that occurred at this position also occurred in the other two forest types (Table 2). Analysis of the community data using CCA demonstrated that the composition and abundance of taxa were related to position on the transect (Fig. 6). One group of species, including Piloderma byssinum (P. Karst.) Jülich, Piloderma fallax (Lib.) Stalpers, P. reticulatum, R. decolorans, and Tylospora fibrillosa (Burt.) Donk, showed a clear preference for the poor end of the gradient. Although a small number of these species, in particular P. byssinum, also occurred elsewhere on the transect, the greatest numbers of mycorrhizas were found in samples from the dwarf shrub forest type (Table 2). A second group, Amphinema byssoides (Pers.: Fr.) J. Erikss., Cortinarius acutus agg., Cortinarius obtusus agg., Tomentella sp. 3, Tomentelloid, T. asterophora and Tylospora sp., were primarily found in samples from the middle of the gradient up to the 80-m position. Of this group, only T. asterophora and Tomentelloid also occurred at 90 m on the transect (Table 2). The remaining species, Dermocybe sanguineus (Wulf.: Fr.) Fr., C. geophilum, Piceirhiza bicolorata and Tomentella sp. 1, appear in the
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middle of the ordination diagram, reflecting the widespread occurrence of these species on the transect. Correlations among community structure, soil parameters and spatial distance The Mantel test demonstrated a very strong correlation (r = 0.914; P < 0.0001) between soil parameters and distance. Because of the strength of this relationship, correlations between community similarity and soil parameters (r = 0.411; P = 0.0065) and distance (r = 0.373; P = 0.013) were predictably similar.
Discussion In the present study, we determined the distribution of ectomycorrhizal fungal species along a local gradient of nutrients in a boreal forest stand in northern Sweden. Ordination of the ECM fungal data and soil characteristics resulted in a spatial pattern that corresponded to the forest types distinguishable on the transect. Giesler et al. (1998) related changes in vegetation composition and productivity along the same transect to soil pH and supply of base cations, via effects on the rate of N turnover: Higher turnover rates at the lower end of the transect resulted in higher productivity and litter with lower C:N ratios. In the present study, changes in plant litter chemistry coupled to the changing supply of base cations along the transect appeared to create conditions that significantly influenced the distribution of ECM. The observed patterns in ECM fungal distribution therefore mirrored the changes in both vegetation and soil chemistry. Conn & Dighton (2000) and Dighton et al. (2000) have previously demonstrated the importance of litter chemistry in determining the species composition of ECM fungi colonizing litter patches. Patterns in ECM communities may also arise as the result of founder effects, where individuals become established and then expand from the point of origin. As a consequence of increased spore rain, new individuals of the same species can then become established in the immediate area. This process would result in neighbouring areas of forest floor being more similar (autocorrelated) than those more spatially distant. These founder effects could potentially result in false correlations in studies, such as the present one, that use short transects to investigate the influence of environmental parameters on ECM fungi. It is important to consider this potential. The magnitude of the gradient utilized in this study was reflected in the strong correlation between soil parameters and spatial distance. Unfortunately, this means that there will always be a correlation between community similarity and both soil parameters and distance if either of these influences fungal community structure. However, the correlation between soil parameters and community structure was stronger than that between the latter and spatial distance. In addition, Lilleskov et al. (2004) found that, in the majority of forest stands they examined, spatial patchiness in ECM communities was
evident only at relatively small spatial scales (< 2.6 m). Taking these points together with the correspondence between the observed and published ecological preferences exhibited by some of the taxa, it seems unlikely that the observed changes in community structure along the transect were primarily caused by founder effects. Although the ordination suggested a strong influence of the soil parameters included, the significant changes in host species along the gradient could also have influenced the ECM communities: the three host species, birch, Scots pine and Norway spruce, had an uneven distribution along the gradient. However, only two known or potential host-specific taxa [Cortinarius cf armillatus (birch) and Hygrophorus olivaceoalbus (Fr.: Fr.) Fr. (spruce)] were identified in this study and neither of these was among the taxa included in the CCA. All of the other identified species (and Tylospora spp.) considered in the CCA are host generalists. In this study, therefore, the influence of host specificity upon the observed relationship between the ECM community and the soil parameters was probably not strong and limited to a small number of rarer species. Nantel & Neumann (1992) demonstrated that the soil factors affecting the distribution of ECM tree hosts were not necessarily the same factors that governed the distribution of the associated ECM fungi. In general, the fungi had a narrower niche width than the host plants. In the present study, some of the host-generalist fungi, most notably C. geophilum, had a wider niche width than the host tree species, while other generalist taxa exhibited similar distributions to some of the host plants, even though other potential hosts were present in other parts of the transect. Unfortunately, knowledge of the autecology of the fungal taxa found in this study is, with a few exceptions, very limited. The widespread distribution of C. geophilum, apparently independent of host and soil conditions, confirms the wide ecological amplitude of the taxon (LoBuglio, 1999). The restricted distributions of P. fallax and R. decolorans to the lownutrient, low-pH and high-C:N conditions of the poor end of the gradient also agree with laboratory studies on the former (Erland & Taylor, 1999) and the recorded sporocarp occurrence of the latter (Gminder et al., 2000). The distribution of T. fibrillosa, which occurred primarily at the poor end of the transect, is somewhat contradictory to what is known about this taxon. A number of studies have found increases in the abundance of T. fibrillosa with increasing soil mineral N content (Taylor et al., 2000; Lilleskov et al., 2002). One explanation for this anomaly could be that mycorrhizas included within the Tylospora sp. category are actually T. fibrillosa or a mixed pool of this species and T. asterophora. Of the four soil parameters included in the CCA analysis, extractable NH4 was the strongest determinant of the ECM community. The identification of NH4 as a major influence on ECM fungal species supports the findings from numerous N fertilization experiments that have demonstrated dramatic
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impacts of treatment on the species composition of ECM communities (Wallenda & Kottke, 1998). A frequent observation from N fertilization experiments is a decline in ECM species richness, a marked decrease in ECM morphotypes producing abundant extramatrical mycelium (EMM) and, consequently, a decline in soil mycelium (Nilsson & Wallander, 2003). There is no evidence in the present study that there was a decline in ECM fungal species richness with increasing concentrations of soil mineral N. There was also no indication of a decrease in morphotypes with abundant mycelia along the transect. Mycorrhizas formed by members of the Russulaceae, considered to produce little EMM, were found along the whole transect. Similarly, Cortinarius species, which produce very abundant EMM, were also found over the whole transect. Some Cortinarius species (C. acutus and C. obtusus) were actually only found at the rich end of the transect. In addition to a strong nutrient gradient, the transect also represents a moisture gradient as a result of the increasing discharge of groundwater from c. 40 m to the end of the transect at 90 m (Giesler et al., 1998). It is therefore likely that moisture availability may also influence ECM fungal distribution. van der Heijden et al. (1999) previously demonstrated the importance of moisture in influencing ECM community development on Salix repens. However, with the exception of drought-tolerant taxa, for example C. geophilum (LoBuglio, 1999), it may be very difficult to differentiate a direct effect of moisture availability on ECM fungi and the indirect influence of moisture on other soil processes that influence ECM fungi. Nilsson et al. (2005) used specific PLFAs to examine the growth and biomass of mycorrhizal fungal mycelia along the Betsele gradient and found evidence that the biomass of mycelium produced by ECM and ericoid fungi declined from the poor end to the rich end of the gradient in samples collected in 2000. However, they pointed out that the observed decline could have resulted from a reduction in root density of ericaceous shrubs along the transect. A visual assessment of mycelial production in ingrowth cores (presumed to be from ECM fungi) found the greatest production in the short herb forest type, with very little mycelium recovered from the tall herb zone. Differences between the present study and that of Nilsson et al. (2005) may be a result of natural spatial variation during sampling and year of sampling. Compared to soil nitrogen concentrations produced by N fertilization treatments (Persson et al., 2001; Micks et al., 2004) and, in some areas, chronic N deposition (Persson et al., 2000; Lilleskov et al., 2002) the range of N concentrations along the studied gradient was of a much smaller magnitude. Despite this small range, distinct changes in the ECM community structure were observed. It is therefore hardly surprising that management practices such as N applications usually result in dramatic alterations of ECM communities. In addition, studies on the effects of N deposition on ECM fungi that utilize sites that are already affected by albeit low levels of N
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deposition may already have missed an important initial phase of ECM response to N loading. Increased concentrations of nitrate have been shown to influence ECM communities (see Wallenda & Kottke, 1998). In the present study, the concentrations of nitrate in the soil solution were only elevated at the final sampling position and no effect of the ion could therefore be detected in the ordination analysis. Ectomycorrhizal fungal communities are typically species rich and consist of a small number of common species, colonizing the major proportion of the fine roots, and a large number of rarer species (Horton & Bruns, 2001). The ECM community identified at the Betsele site is therefore representative of these species-rich communities. In addition to the commonly encountered ECM fungal genera (e.g. Cortinarius and Russula), the ascomycete Otidea tuomikoskii Harmaja was also identified as a mycobiont on roots in this study. This is only the second report of an Otidea species directly associated with ECM tips (Kennedy et al., 2003), supporting the proposal by Hobbie et al. (2002) that at least some species in the genus Otidea are ectomycorrhizal. Most previous studies that have examined the influence of edaphic factors on ECM community structure have involved determining the response of the community to perturbations (e.g. nitrogen, lime and ash applications; see review by Erland & Taylor, 2002) at either a local scale (i.e. experimental plots) or on long-distance transects covering gradients of deposition (e.g. Taylor et al., 2000; Lilleskov et al., 2002). In the present study, the distinctive changes in soil properties and associated vegetation along the short, 90-m transect provided an ideal opportunity to examine the impact of natural spatial heterogeneity in soil properties on the ECM community at a local scale. This effectively avoided potential climatic and sitespecific influences and the need to interpret responses by ECM to artificially altered soil conditions.
Acknowledgements We would like to thank Katarina Ihrmark for her assistance with DNA sequencing and Reiner Giesler for supplying the unpublished soil data relating to the Betsele site. This work was supported by Grant 2002-0288 from The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS) to AT. We are very grateful for the helpful comments provided by the anonymous reviewers.
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Supplementary Material The following material is available for this article online: Table S1 Identification of ectomycorrhizal (ECM) fungi from internal transcribed spacer (ITS) sequence data. Numbers given in the comment column refer to GenBank accession numbers. Details of identification process are given in the Materials and Methods section. This material is available as part of the online article from http://www.blackwell-synergy.com
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