Editor: Philippe Lemanceau
Influence of host species on ectomycorrhizal communities associated with two co-occurring oaks (Quercus spp.) in a tropical cloud forest
Version of Record online: 6 MAY 2009
© 2009 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved
FEMS Microbiology Ecology
Volume 69, Issue 2, pages 274–287, August 2009
How to Cite
Morris, M. H., Pérez-Pérez, M. A., Smith, M. E. and Bledsoe, C. S. (2009), Influence of host species on ectomycorrhizal communities associated with two co-occurring oaks (Quercus spp.) in a tropical cloud forest. FEMS Microbiology Ecology, 69: 274–287. doi: 10.1111/j.1574-6941.2009.00704.x
- Issue online: 6 JUL 2009
- Version of Record online: 6 MAY 2009
- Received 19 December 2008; revised 14 April 2009; accepted 22 April 2009.Final version published online 5 June 2009.
- ectomycorrhizal communities;
- host preference;
- tropical cloud forest;
- Quercus crassifolia;
- Quercus laurina
- Top of page
- Materials and methods
- Supporting Information
Interactions between host tree species and ectomycorrhizal fungi are important in structuring ectomycorrhizal communities, but there are only a few studies on host influence of congeneric trees. We investigated ectomycorrhizal community assemblages on roots of deciduous Quercus crassifolia and evergreen Quercus laurina in a tropical montane cloud forest, one of the most endangered tropical forest ecosystems. Ectomycorrhizal fungi were identified by sequencing internal transcribed spacer and partial 28S rRNA gene. We sampled 80 soil cores and documented high ectomycorrhizal diversity with a total of 154 taxa. Canonical correspondence analysis indicated that oak host was significant in explaining some of the variation in ectomycorrhizal communities, despite the fact that the two Quercus species belong to the same red oak lineage (section Lobatae). A Tuber species, found in 23% of the soil cores, was the most frequent taxon. Similar to oak-dominated ectomycorrhizal communities in temperate forests, Thelephoraceae, Russulaceae and Sebacinales were diverse and dominant.
- Top of page
- Materials and methods
- Supporting Information
Ectomycorrhizal fungi are an important component of many forest ecosystems and play key roles in biogeochemical cycling, plant community dynamics and maintenance of soil structure (Baxter & Dighton, 2001; Jonsson et al., 2001; Rillig & Mummey, 2006). The use of molecular methods to identify ectomycorrhizal fungi on roots has greatly increased our understanding of the diversity and composition of below-ground ectomycorrhizal communities (Horton & Bruns, 2001). Most ectomycorrhizal community studies have been carried out in the temperate zone despite the fact that many important ectomycorrhizal hosts (e.g. Pinaceae, Fagaceae, Dipterocarpaceae) occur in tropical forests (Taylor & Alexander, 2005). Few studies have used molecular methods to assess tropical ectomycorrhizal communities (Haug et al., 2005; Moyersoen, 2006; Tedersoo et al., 2007).
Tropical montane cloud forests are characterized by frequent cloud cover and abundant rainfall. These warm, mesic habitats support high levels of biodiversity and large numbers of endemic species (Gentry, 1992). These ecosystems are also hydrologically significant because they play an important role in local and regional watersheds by intercepting water from fog and clouds (Hamilton et al., 1995; Still et al., 1999). This globally threatened habitat type is under increasing pressure from deforestation, fragmentation and conversion to agriculture. In Mexico, <10% of the original tropical montane cloud forest cover still exists (Cayuela et al., 2006). A better understanding of ectomycorrhizal communities in tropical montane cloud forests is important for conservation and restoration of this unique habitat.
Traditionally, it was thought that ectomycorrhizal fungi were abundant in temperate and boreal regions but were uncommon or insignificant in tropical ecosystems (Brundrett, 2002; Alexander, 2006). However, ectomycorrhizal fungi are increasingly recognized for their ecological importance in tropical forests (Torti et al., 2001; Taylor & Alexander, 2005; McGuire, 2007; Tedersoo et al., 2008). Although species richness of many phylogenetic groups is higher in tropical latitudes compared with temperate latitudes (e.g. birds, trees, orchids, ants and lizards; Schall & Pianka, 1978; Currie & Paquin, 1987; Rahbek & Graves, 2001), little is known about variation in ectomycorrhizal diversity relative to latitude (Allen et al., 1995).
Some recent studies reported tropical ecosystems depauperate in ectomycorrhizal diversity (Andrade et al., 2000; Kottke et al., 2004; Chambers et al., 2005; Haug et al., 2005) whereas other studies reported ecosystems rife with ectomycorrhizal diversity (Henkel, 2003; Riviere et al., 2007; Tedersoo et al., 2007). Although there is not yet a consensus, it is possible that ectomycorrhizal communities are more diverse in the tropics because of higher temperatures, longer growing seasons or abundant rainfall. Mexico's ectomycorrhizal diversity is thought to be among the highest in the world but supporting data are limited (Varela & Estrada-Torres, 1997).
Host tree species and heterogeneity of soil resources are two factors that can influence ectomycorrhizal communities (Molina et al., 1992; Bruns, 1995). Host tree effects have been demonstrated for host species from different families (Ishida et al., 2007; Tedersoo et al., 2008) but can also occur in host trees within the same genus (Morris et al., 2008b). In a previous study, we detected differences in ectomycorrhizal communities on two Quercus hosts that occur in a scattered distribution with mostly nonoverlapping canopies in an arid California woodland (Morris et al., 2008b). In order to test the effect of congeneric host species on ectomycorrhizal communities in a different ecosystem, we selected a tropical montane cloud forest where Quercus species co-occur in dense stands with overlapping canopies. We compared diversity and community structure of ectomycorrhizal fungi associated with deciduous Quercus crassifolia Humb. & Bonpl. and evergreen Quercus laurina Humb. & Bonpl. by sampling at various spatial scales on two dates. Because of their contrasting phenologies, we hypothesized that we would find differences in the ectomycorrhizal communities on the two Quercus host species. Soil properties were analyzed in order to examine their influence on ectomycorrhizal composition. Furthermore, we tested the hypothesis that ectomycorrhizal diversity is higher in a tropical cloud forest than in a Mediterranean Quercus forest. To facilitate this comparison, we used similar sampling protocols, comparable sampling efforts and related host plants in this study and in our recent Mediterranean oak woodland study (Morris et al., 2008b).
Materials and methods
- Top of page
- Materials and methods
- Supporting Information
The study site is located at Huizteco Park, c. 4.5 km north of Taxco, Guerrero state, southern Mexico (18°36′N, 99°36′W). The park is managed for recreation and conservation by the municipality of Taxco de Alarcón. Huizteco is part of the Sierra de Taxco mountain range, which forms a portion of the western extension of the Trans-Mexican Volcanic Belt. Elevation ranges between 2450 and 2550 m and the climate is humid-subtropical (Trewartha, 1954). Total annual precipitation varies between 1200 and 1500 mm, with a rainy season from June to October and a dry period from November to May. Soils are Haplic Phaeozem (Hapludolls), which are characterized by a surface layer with high humus content.
Vegetation is classified as tropical montane cloud forest or humid montane forest (Rzedowski, 1981) and is estimated to be ≥80 years old. The overstory is dominated by several oak species including Q. crassifolia, Q. laurina, Quercus magnoliifolia Née and Quercus canstanea Née (Valencia-Avalos, 1995; Martinez et al., 2004). Other overstory trees include Clethra spp. (Clethraceae) and Oreopanax sp. (Araliaceae); all are considered nonectomycorrhizal hosts (Wang & Qiu, 2006). The ectomycorrhizal shrub Arctostaphylos sp. (Ericaceae) occurs at the site, but not near our sampling areas. The understory contains scattered but diverse herbaceous angiosperms. Epiphytes (bromeliads, mosses, lichens) are abundant in the canopy.
We sampled ectomycorrhizal communities on Q. crassifolia and Q. laurina because both oak species were common at the study site and often occurred in a clumped distribution. This allowed us to sample plots where only Q. crassifolia or Q. laurina were present and decreased the probability of encountering roots from any other Quercus species. Quercus crassifolia and Q. laurina are Mexican red oaks (subgenus Quercus, section Lobatae) that have a broad distribution in Mexico (Sierra Madre Occidental, Sierra Madre del Sur and the Trans-Mexican Volcanic Belt) and extend into Central America (Romero et al., 2002). Quercus laurina is an evergreen species found in pine-oak forests and tropical montane forests at elevations of 1900–3000 m. Quercus crassifolia is a deciduous tree found in oak forests, pine-oak forests and tropical montane cloud forests at elevations of 1400–2700 m (Valencia-Avalos, 1995). Leaf fall for Q. crassifolia occurs at the beginning of the dry season in November. Average DBH was 30 and 37 cm for Q. crassifolia and Q. laurina, respectively. Oak voucher specimens were deposited at the UC Davis Herbarium (DAV).
Ectomycorrhizal root sampling
We randomly selected four plots (10 × 10 m) dominated by Q. crassifolia (no other Quercus spp. were present) and four plots dominated by Q. laurina (no other Quercus spp. were present) for ectomycorrhizal root sampling. Plots were distributed within c. 3-ha area of forest and were at least 50 m from each other. Each plot contained between three and six mature oak trees. Five soil cores (10-cm diameter × 12-cm depth) were taken in each plot at the beginning (17 June 2004) and the middle of the rainy season (21 August 2004) for a total of 40 soil cores at each sampling date. Soil cores were collected in 2-m transects at distances of 0, 0.75, 1, 1.25 and 2 m. August soil cores were collected in parallel 2-m transects c. 50 cm from soil cores taken in June. Transects were located randomly in relation to tree stems. Litter depth was measured and then the litter was removed before collection of soil cores.
Soil cores were transported to the laboratory on ice and processed within 15 days. Fine roots (<2-mm diameter) were washed over a 300-μM sieve and 100 healthy ectomycorrhizal root tips were randomly selected from each soil core following the protocols of Morris et al. (2008b). We considered root tips to be colonized by ectomycorrhizal fungi based on color, branching and the presence of a fungal mantle. Pooled root tips were cleaned with deionized water and freeze dried for DNA analysis. We used pooled root tips because a previous study (Morris et al., 2008a) demonstrated that many individual root tips are colonized by multiple fungal species making DNA sequencing of single root tips impractical for large samples. Pooling root tips is an efficient method that allows detection of a high diversity of ectomycorrhizal fungi (Morris et al., 2008b).
DNA extraction and PCR
DNA was extracted from pooled samples of ectomycorrhizal root tips with the Qiagen DNeasy Plant Mini Kit (Valencia, CA) followed by purification with UltraClean soil DNA kit (Mo Bio Laboratories, Carlsbad, CA). The internal transcribed spacer (ITS) and partial 28S rRNA gene were amplified with primers ITS1F and LR3 (Gardes & Bruns, 1993; Hopple & Vilgalys, 1994) following the protocols of Morris et al. (2008b), except 15 cycles were used instead of 20.
Cloning and RFLP screening
PCR products from four replicate reactions were pooled and cloned using the TOPO TA cloning kit (Invitrogen, Carlsbad, CA) following the manufacturer's protocols. For each sample, 72 transformed Escherichia coli colonies were randomly selected and used as template for PCR amplification with ITS1F and LR3. Plasmids were amplified according to Morris et al. (2008b) and amplicons were digested with restriction enzymes HinFI and AluI. Fragments were run simultaneously on 1.5% agarose gels stained with SYBR Green I (Applied Biosystems, Foster City, CA) and scored visually. Restriction fragment length polymorphism (RFLP) patterns were compared only within cores and not across cores.
Sequencing and identification of ectomycorrhizal root tips
From each sample, six representative clones for each unique RFLP pattern were sequenced when available, otherwise all available clones were sequenced with ITS1F using BigDye v3.1 Sequencing Kit (Applied Biosystems) on an ABI 3730 XL sequencer at the UC Davis College of Agriculture and Environmental Sciences Genomics Facility. When sequences from a single RFLP pattern resulted in multiple taxa, all clones from that RFLP type were sequenced. From the 80 clone libraries, 2270 clones were successfully sequenced. Sequences were edited using sequencher v4.2 (Gene Codes, Ann Arbor, MI) and examined by blast searches against GenBank, UNITE and to a database of sequences from locally collected fruiting bodies (Morris et al., 2008a).
Sequences from clones with <97% sequence similarity were considered to be unique taxa. Sequences from ectomycorrhizal roots that matched those from sporocarps are designated by MHM collection numbers. For root samples whose sequences did not match sporocarps, identification was based on a combination of blast searches, sequence alignments and phylogenetic analysis. When ITS sequences were insufficient for identification, we sequenced part of the 28S rRNA gene using LR3 and performed similar analysis as above.
Amplification of environmental samples containing mixed DNA templates may result in chimeric sequences. We attempted to reduce chimeras using long extension times (4 min) and a low number of PCR cycles (15). Clones occurring in only one core were checked with manual alignments and by chimera and genecov programs of the Recombination Detection Program (Martin & Rybicki, 2000).
Soil analyses were performed on the soil remaining after ectomycorrhizal roots were removed. We measured gravimetric water content, pH (saturated paste in deionized water), total carbon (C) (combustion method) and total Kjeldahl nitrogen. Available phosphorus (P) was determined colorimetrically (using the molybdenum-blue method, Murphy & Riley, 1962).
Ectomycorrhizal diversity was assessed using Shannon diversity index (H′), Simpson index (1−D) and evenness (H′/ln S, where S=number of taxa) (Magurran, 2004). These indices were calculated for ectomycorrhizal communities on Q. crassifolia, Q. laurina and the community as a whole with frequency data using palaeontological statistics v1.40 (Hammer et al., 2001). First and second order jackknife species richness estimates were calculated for each oak host and for the overall community using estimates v.8.0 (Colwell, 2006).
In order to examine the variation in ectomycorrhizal community composition and relationships with measured environmental variables, we conducted correspondence analysis (CA) and canonical correspondence analysis (CCA) using canoco v4.54 (Biometris, Wageningen, the Netherlands). CA and CCA were used because detrended correspondence analysis (DCA) demonstrated that the length of the longest gradient was 4.31, indicating a unimodal distribution of species along the environmental gradient (Lepš & Šmilauer, 2003). Ordination analyses were performed using frequency of each ectomycorrhizal species/plot. We conducted CA and CCA with and without singletons because rare species may have a disproportionately large influence on the analysis. For CCA, environmental variables (oak host, soil pH, total N, total C, available P, litter depth) were tested for their contribution to the variation in the ectomycorrhizal species data using Monte Carlo permutation tests. Gravimetric water content was excluded from the analyses because soils were saturated on both sampling dates due to heavy rain. Variance partitioning was used to determine the amount of variance explained by significant environmental variables (Lepš & Šmilauer, 2003).
To test for an effect of sampling date on ectomycorrhizal community composition we conducted CCA using sampling date as an environmental variable and as a covariable. We also used cluster analysis to evaluate the similarity of ectomycorrhizal communities at different sampling dates. Cluster analysis was preformed with palaeontological statistics v1.40 using unweighted pair group method with arithmetic mean and three different distance measures (Jaccard, Bray–Curtis and CHORD).
We tested for differences in the distribution of ectomycorrhizal families on Q. laurina and Q. crassifolia at each sampling date using Fisher's exact test. Jaccard similarity indices were calculated to determine the similarity of ectomycorrhizal communities between soil cores. To test for fine-scale effects of distance (0.25, 0.5, 0.75, 1.0 and 1.25 m) on similarity between soil cores at each sampling date, we used a linear mixed model anova with oak species and distance as fixed effects and an unstructured within-plot correlation matrix. Pairwise comparisons of mean similarity coefficients for the five distance classes were made using the Tukey–Kramer adjustment. Model aptness was assessed using graphical analysis of residuals, Shapiro–Wilks test for normality and Levene's test for homogeneity of variances. Residuals showed no departures from assumptions of normality and homogeneity of variances.
- Top of page
- Materials and methods
- Supporting Information
Ectomycorrhizal diversity and community structure
Molecular analysis of 8000 ectomycorrhizal root tips from 80 soil cores revealed a total of 154 ectomycorrhizal taxa in this tropical montane cloud forest (Table 1). Ectomycorrhizal taxa were identified to the level of species (six taxa), genus (76 taxa), family (50 taxa), order (20 taxa) and phylum (two taxa). Eighteen sequence types from root tips were matched to sequences from sporocarps. Sequences from the 28S region were used for the taxonomic placement of 47 species (31%) and all others were determined by ITS alone or by sporocarp matches.
|Taxa||No. of cores||No. of clones||Accession no.||rRNA match*||Closest blast match||Identity†|
|Amanita flavoconia (MHM196)||0||2||0||28||FJ196893||ITS||Amanita flavoconia||100(654)|
|Amanita pantherina (MHM119)||2||6||40||199||FJ196894||ITS||Amanita pantherina||99(641)|
|Amanita sp. MHM186 (rubescens group)||0||1||0||3||FJ196895||ITS||Amanita rubescens||98(660)|
|Amanita sp. 1||0||3||0||12||FJ196896||ITS||Amanita pantherina var. multisquamosa||99(647)|
|Amanita sp. 2||0||1||0||1||FJ196897||ITS||Amanita lanei||97(621)|
|Atheliaceae1||1||0||4||0||FJ196899||ITS and 28S||Piloderma lanatum||90(1214)|
|Basidiomycota1 (Sistotrema clade)||1||0||8||0||EU563507||ITS and 28S||Sistotrema alboluteum||90(1141)|
|Basidiomycota3 (Sistotrema clade)||1||0||24||0||FJ196900||ITS and 28S||Sistotrema alboluteum||91(1136)|
|Boletellus russellii (MHM166)||6||3||214||42||FJ196901||28S||Boletellus russellii||98(547)|
|Boletus frostii (MHM069)||0||2||0||18||FJ196902||28S||Boletus coniferarum||95(575)|
|Boletus aff. variipes (MHM163)||2||3||18||9||FJ196903||ITS||Boletus aereus||95(803)|
|Cenococcum geophilum||3||2||4||4||FJ456977||ITS||Cenococcum geophilum||97(973)|
|Cortinarius sp. 3||0||2||0||23||FJ196913||ITS||Cortinarius umbrinolens||95(562)|
|Cortinarius sp. 4||2||0||27||0||FJ196914||ITS||Cortinarius alboviolaceus||96(564)|
|Cortinarius sp. 5||0||2||0||8||FJ196915||ITS||Cortinarius calopus||95(568)|
|Cortinarius sp. 6||0||2||0||4||FJ196916||ITS||Cortinarius sertipes||97(562)|
|Cortinarius sp. 7||0||1||0||1||FJ196917||ITS||Cortinarius cacaocolor||91(576)|
|Cortinarius sp. 8||1||0||2||0||FJ196918||ITS||Cortinarius anisatus||93(567)|
|Cortinarius sp. 9||0||1||0||37||FJ197010||ITS||Cortinarius evernius||94(567)|
|Cortinarius sp. 10||0||1||0||2||FJ196909||ITS||Cortinarius alboviolaceus||96(566)|
|Cortinarius sp. 11||1||0||1||0||FJ196910||ITS||Cortinarius ochrophyllus||96(656)|
|Cortinarius sp. 12||0||3||0||44||FJ196911||ITS||Cortinarius umbrinolens||96(559)|
|Cortinarius sp. 13||0||6||0||26||FJ196912||ITS||Cortinarius fulvescens||97(558)|
|Craterellus sp. 1||0||5||0||80||EU563479||28S||Craterellus lutescens||93(567)|
|Entoloma sp. 1||1||0||2||0||FJ196920||28S||Entoloma alpicola||98(565)|
|Entolomataceae1||1||0||1||0||FJ196919||ITS and 28S||Entoloma nitidum||90(1107)|
|Genea sp. 1||5||4||17||6||FJ197017||ITS and 28S||Genea hispidula||95(615)|
|Genea sp. 2||0||1||0||5||FJ197023||ITS||Genea hispidula||85(667)|
|Genea sp. 3 (arenaria group)||0||3||0||36||FJ197011||28S||Genea arenaria||100(553)|
|Hebeloma sp. 1||0||3||0||5||FJ196921||ITS||Hebeloma saliciphilum||95(663)|
|Helotiales2||4||2||6||3||EU563501||ITS and 28S||Hyphodiscus hymeniophilus||93(1088)|
|Helotiales3||1||0||1||0||EU563495||ITS and 28S||c.f. Hymenoscyphus sp.||92(1078)|
|Helotiales4||0||2||0||2||FJ197016||ITS and 28S||Meliniomyces bicolor||98(1399)|
|Humaria sp. 1||2||1||25||7||FJ197018||28S||Humaria hemsiphaerica||96(555)|
|Hydnum sp. 1||2||0||73||0||FJ196922||28S||Hydnum repandum||98(563)|
|Hygrophorus sp. 1||2||0||13||0||FJ196923||28S||Hygrophorus agathosmus||96(556)|
|Hygrophorus sp. 2||1||0||2||0||FJ196924||ITS and 28S||Hygrophorus chrysodon||86(1167)|
|Inocybe sp. 1||0||1||0||18||EU563499||28S||Inocybe godeyi||96(589)|
|Inocybe sp. 3||2||0||14||0||EU563500||28S||Inocybe godeyi||98(580)|
|Inocybe sp. 4||1||0||2||0||EU563510||28S||Inocybe cf. reisneri||95(597)|
|Inocybe sp. 5||1||0||31||0||FJ196927||ITS and 28S||Inocybe cf. flocculosa||90(1263)|
|Inocybe sp. 6||1||3||5||4||FJ196928||ITS and 28S||Inocybe pudica||86(1283)|
|Inocybe sp. 7||0||1||0||1||FJ196929||ITS and 28S||Inocybe flocculosa||94(1218)|
|Inocybe sp. 8||0||2||0||14||FJ196930||ITS and 28S||Inocybe pudica||87(1281)|
|Inocybe sp. 9||1||0||3||0||FJ196931||ITS and 28S||Inocybe whitei||89(1124)|
|Inocybe sp. 10||0||1||0||1||FJ196925||ITS and 28S||Inocybe aff. lanuginosa||86(1187)|
|Inocybe sp. 11||0||2||0||69||FJ196926||ITS and 28S||Inocybe pudica||91(1257)|
|Lactarius chrysorrheus (MHM143)||6||6||89||160||FJ196932||ITS||Lactarius chrysorrheus||95(700)|
|Lactarius sp. MHM308||4||9||59||169||FJ196936||ITS||Lactarius yazooensis||99(702)|
|Lactarius sp. 1||3||5||56||44||FJ196933||ITS||Lactarius fumosus||98(661)|
|Lactarius sp. 2||2||2||9||18||FJ196934||ITS||Lactarius subindigo||95(694)|
|Lactarius sp. 3||1||0||3||0||FJ196935||ITS||Lactarius repraesentaneus||94(633)|
|Pachyphloeus sp. 1||0||1||0||6||FJ197022||ITS and 28S||Pachyphloeus sp.||90(1018)|
|Pezizaceae1||6||1||109||19||EU563481||ITS and 28S||Pachyphloeus sp.||90(986)|
|Pezizaceae2||0||4||0||43||FJ197019||ITS and 28S||Peziza badia||89(1169)|
|Pezizaceae3||0||1||0||1||FJ197012||ITS and 28S||Peziza badia||95(1148)|
|Pezizaceae4||1||1||1||2||FJ197015||ITS and 28S||Pachyphloeus sp.||90(1010)|
|Pezizaceae5||1||0||2||0||FJ197014||ITS and 28S||Hydnobolites californicus||87(586)|
|Pezizaceae6||2||0||5||0||FJ197020||ITS and 28S||Pachyphloeus sp.||91(1014)|
|Pezizaceae7||0||1||0||1||FJ197013||ITS and 28S||Hydnobolites californicus||87(589)|
|Pseudotomentella sp. 1 (tristis group)||1||8||3||68||EU563503||ITS||Pseudotomentella tristis‡||98(448)|
|Pseudotomentella sp. 2||0||1||0||1||EU563488||ITS||Pseudotomentella tristis‡||93(567)|
|Pseudotomentella sp. 3||1||0||2||0||FJ196937||ITS||Pseudotomentella atrofusca‡||97(555)|
|Pseudotomentella sp. 4||1||0||3||0||FJ196938||ITS||Pseudotomentella atrofusca‡||97(636)|
|Ramaria aff. botrytis (MHM156)||0||1||0||1||FJ196939||28S||Ramaria sp.||99(588)|
|Ramaria aff. flava (MHM312)||0||1||0||2||FJ196940||ITS||Ramaria flava||88(647)|
|Ramaria sp. 1||0||1||0||1||FJ196941||ITS and 28S||Ramaria cf. formosa||86(1231)|
|Ramaria sp. 2||0||1||0||1||FJ196942||ITS and 28S||Ramaria cystidiophora||86(1027)|
|Ramaria sp. 3||0||1||0||1||FJ196943||ITS and 28S||Ramaria cystidiophora||88(1030)|
|Russula sp. 1||5||5||107||111||EU563497||ITS||Russula betularum||96(668)|
|Russula sp. 2||0||2||0||70||EU563492||ITS||Russula integriformis||93(670)|
|Russula sp. 3||0||2||0||12||FJ196944||ITS||Russula risigallina||94(666)|
|Russula sp. 4||3||5||41||20||FJ196945||ITS||Russula risigallina||97(662)|
|Russula sp. 5||0||1||0||10||FJ196946||ITS||Russula romellii||95(643)|
|Russula sp. 6||3||0||39||0||FJ196947||ITS||Russula romellii||93(646)|
|Russula sp. 7||1||0||43||0||FJ196948||ITS||Russula aff. delica||94(674)|
|Russula sp. 8||1||0||3||0||FJ196949||ITS||Russula aff. delica||91(599)|
|Russula sp. 9||0||1||0||1||FJ196950||ITS||Russula crustosa||93(673)|
|Russula sp. MHM015||0||2||0||2||FJ196951||ITS||Russula raoultii||96(656)|
|Russula sp. MHM071||4||0||31||0||FJ196952||ITS||Russula flavida||97(677)|
|Russula sp. MHM079||0||1||0||5||FJ196953||ITS||Russula integriformis||94(668)|
|Russula sp. MHM087||2||0||91||0||FJ196954||ITS||Russula basifurcata||96(630)|
|Russula sp. MHM096||2||7||8||14||FJ196955||ITS||Russula risigallina||95(668)|
|Russula sp. MHM097||9||1||78||35||FJ196956||ITS||Russula persicina||97(640)|
|Russula sp. MHM108||0||1||0||19||FJ196957||ITS||Russula cf. maculata||90(689)|
|Scleroderma sp. 1||0||2||0||14||FJ196958||ITS and 28S||Scleroderma areolatum||99(724)|
|Sebacinales7||2||3||39||61||FJ196971||ITS||Sebacina aff. epigaea||97(570)|
|Sebacinales9||0||2||0||68||FJ196973||ITS||Sebacina aff. epigaea||94(580)|
|Tarzetta sp. 1||3||0||48||0||FJ197021||28S||Tarzetta catinus||98(558)|
|Thelephoraceae28||0||1||0||1||FJ196992||ITS||Tomentella cf. sublilacina||88(634)|
|Tomentellopsis sp. 1||0||1||0||2||FJ196898||ITS||Tomentellopsis submollis||95(653)|
|Tricholoma sp. 1||0||1||0||3||EU563477||ITS||Tricholoma fulvum||95(637)|
|Tricholoma sp. 2||2||11||45||113||EU563482||ITS||Tricholoma fulvum||98(659)|
|Tricholoma sp. 4||4||1||158||35||FJ197005||ITS||Tricholoma pessundatum‡||99(654)|
|Tricholoma sp. 5||1||0||3||0||FJ197006||ITS||Tricholoma sejunctum||96(663)|
|Tricholoma sp. 6||1||0||1||0||FJ197007||ITS and 28S||Tricholoma orirubens||92(1089)|
|Tricholoma sp. 7||2||0||60||0||FJ197008||ITS||Tricholoma japonicum||99(647)|
|Tuber sp. 1||11||7||76||57||EU563484||ITS||Tuber pacificum||89(630)|
|Xerocomus sp. MHM129||3||4||31||40||FJ197009||ITS and 28S||Xerocomus chrysenteron||93(1235)|
Species accumulation curves indicate that new species continued to be detected even after sampling 80 soil cores (Fig. 1). Mean ectomycorrhizal species richness was 6.2±2.6 (mean±SD) per soil core and 31.1±7.7 (mean±SD) per plot (five soil cores). Similar species richness was found on Q. crassifolia (92 taxa) and Q. laurina (102 taxa). Species richness was not significantly different between oak hosts based on overlapping confidence intervals of species accumulation curves (data not shown). Diversity indices, evenness and mean number of taxa per core were similar for both oaks (Supporting Information, Table S1). The first- and second-order jackknife estimates of species richness were 130 and 147 for Q. crassifolia and 146 and 172 for Q. laurina. The overall species richness of the ectomycorrhizal community was estimated to be 219 and 256 using the first- and second-order jackknife, respectively.
Many taxa occurred only in a single soil core (Q. crassifolia=39; Q. laurina=46) and almost two-thirds (61%) of the taxa were restricted to a single plot. Even the most abundant species were not particularly dominant. For example, Tuber sp. 1 was the most frequent species on Q. crassifolia, but this taxon accounted for only 11 of 233 total occurrences (5%). Tricholoma sp. 2 was the most frequent species on Q. laurina and accounted for 11 out of 264 total occurrences (4%). Twelve nonectomycorrhizal taxa from Ascomycota, Basidiomycota, Zygomycota, Chytridiomycota and Plasmodiophorida were detected in 12 soil cores (15%) but represented only one to four clones within a core (Table S2).
Influence of host and soil properties on ectomycorrhizal taxa distributions
Of the 154 ectomycorrhizal species detected, 52 (34%) were found only on Q. crassifolia, 62 (40%) were found only on Q. laurina and 40 (26%) were found on both oak hosts. CA resulted in distinct groupings of ectomycorrhizal samples from Q. crassifolia and Q. laurina although there was some overlap between samples from the two oak hosts (Fig. S1). The first and second CA axes explained 11.4% and 10.3% of the total variation in species data. Ordination of ectomycorrhizal communities using CCA demonstrated that the conditional effects of oak species (P=0.01) and available P (P=0.03) were significant in explaining the distribution of ectomycorrhizal species (Fig. 2). The first and second CCA axes explained 9.8% and 9.1% of the species variance, respectively. Variance partitioning revealed that oak species explained 16.8% of the variation in the species data and available P explained 16.3%. Together oak species and available P explained 32.6% of the variance, indicating that they had a shared variance of 0.5%. The conditional effect of total C was almost significant (P=0.052) and this variable explained an additional 13.4% of the variance. Results were consistent when ordination was conducted with and without singletons.
Ectomycorrhizal taxa in the Ascomycota were slightly more frequent on Q. crassifolia (relative frequency=17%) than on Q. laurina (relative frequency=11%). We detected 19 and 17 ectomycorrhizal families/orders on Q. crassifolia and Q. laurina, respectively. The families Atheliaceae, Corticiaceae, Entolomataceae, Hydnaceae and Hygrophoraceae were found only on Q. crassifolia whereas the families Cantharellaceae, Gomphaceae and Sclerodermataceae were detected only on Q. laurina. Cortinariaceae demonstrated significantly biased distribution on Q. laurina in June (Fisher's exact test: n=8, P=0.03) but not in August (n=8, P=0.49). The frequency of other families was not statistically different between the two oak host species. There were no significant differences in the frequency of individual ectomycorrhizal taxa, although several common species tended to be more frequent on a particular host (Fig. 3).
Temporal dynamics and spatial diversity of ectomycorrhizal fungi
Ectomycorrhizal species composition was similar across sampling dates and the majority of frequent ectomycorrhizal taxa were detected in both June and August (data not shown). Cluster analysis using several distance measures demonstrated that samples taken from the same plot in June and August grouped together for six out of eight plots (Fig. S2). CCA of species composition also showed that the composition of ectomycorrhizal taxa in any given plot was similar in June and August (Fig. 2). Furthermore, sampling date was not significant when it was included as an environmental variable in CCA. When sampling date was included in CCA as a covariable, only oak host species was significant (P=0.04) and no soil variables were significant. Although we did not detect statistically significant temporal differences, two ectomycorrhizal species appeared more frequently at a single sampling date. Sebacinales2 was detected in 10 cores in five plots, but only in August, whereas Boletellus russellii occurred in eight cores in June but only one core in August.
There was a significant effect of distance on Jaccard similarity of soil cores within plots in both June (P=0.0006) and August (P=0.0001) and no significant interaction between oak species and distance. Soil cores that were 25 cm apart tended to be more similar than soil cores separated by greater distances (50–125 cm).
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Ectomycorrhizal diversity and community structure
The paradigm that ectomycorrhizal associations are primarily restricted to temperate ecosystems has recently changed as many studies have documented ectomycorrhizal tree species in a wide variety of tropical habitats (Alexander & Högberg, 1986; Henkel et al., 2002; Alexander, 2006; Tedersoo et al., 2007). The diversity of ectomycorrhizal communities in tropical ecosystems, however, remains largely unknown. This study documents highly diverse ectomycorrhizal fungal communities in a tropical montane Quercus forest. We found similar species richness and diversity in this tropical ecosystem and in a Mediterranean woodland (Table 2). Surprisingly, the sampling curves in this Quercus-dominated tropical forest were almost identical to the sampling curves in a Quercus-dominated woodland studied with similar methods (Fig. 4). At the level of family/order, diversity was also similar with 20 ectomycorrhizal families/orders found in the Mediterranean oak-woodland study and 22 families/orders found in this cloud forest. This suggests that ectomycorrhizal diversity in oak forests in temperate and tropical ecosystems may be similar.
|This study||Morris et al. (2008b)|
|Mean annual precipitation (mm)||1350||750|
|Forest structure||Closed canopy cloud forest||Open woodland-savanna|
|Soil type||Hapludolls||Mollic Haploxeralfs|
|Host species†||Q. crassifolia and Q. laurina||Q. douglasii and Q. wislizeni|
|Oak lineages||Section Lobatae||Section Quercus and Lobatae|
|Area sampled (m2)||800||1216|
|Soil core volume (cm3)||942||900|
|No. of cores sampled‡||80||64|
|No. of root tips processed/core||100||100|
|Total no. of ectomycorrhizal species||154||140|
|No. of singletons||66||59|
|Mean no. of ectomycorrhizal species/core||6.2||6.5|
|No. of Basidiomycota/Ascomycota taxa||136/18||100/40|
The major taxonomic groups found in this tropical montane forest are similar to those found in temperate climates. Thelephoroid (38 taxa), Russuloid (21 taxa), and Sebacinoid (17 taxa) fungi were frequent and speciose groups in this study. These groups are well documented on roots in various temperate oak ecosystems (Avis et al., 2003; Dickie & Reich, 2005; de Roman & de Miguel, 2005; Richard et al., 2005; Walker et al., 2005). The ectomycorrhizal community in this tropical oak ecosystem is qualitatively similar to temperate oak ectomycorrhizal communities but different in some ways from ectomycorrhizal communities on Mediterranean oaks. Ectomycorrhizal communities on Fagaceae from Mediterranean climates appear to support a higher diversity and greater abundance of Ascomycota (Bergemann & Garbelotto, 2006; Smith et al., 2007; Morris et al., 2008b) whereas studies from mesic oak forests in the United States are dominated by Basidiomycota with less ascomycete diversity (Avis et al., 2003, 2008; Walker et al., 2005).
In this study, several ectomycorrhizal species detected on roots are also prevalent in oak-dominated ecosystems of the eastern United States and Central America. Two distinctive species, Boletus frostii and Lactarius chrysorrheus, are reported in Quercus forests from New England to Costa Rica (Halling & Mueller, 2005; Mueller et al., 2006) and L. chrysorrheus was a common belowground symbiont of Quercus rubra and Quercus prinus in North Carolina (Walker et al., 2005). The similarity of the ectomycorrhizal cloud forest community to the mycoflora of the eastern United States is further evidenced by Amanita flavoconia, Amanita pantherina, Amanita rubescens and Boletellus russellii; sporocarps of these taxa are all found in association with oaks in the eastern United States (Walker & Miller, 2002; Binion et al., 2008). This pattern has also been documented for the oak-associated Boletus rubropunctus in Massachusetts and Central Mexico; collections from these distant sites were almost identical based on five different DNA loci (Smith & Pfister, 2009). It is striking that some of the species found in this study are also found in different habitats thousands of miles away with a completely different climate. This suggests that ectomycorrhizal fungi may have migrated with their oak host trees and that oak host might be as important or more important in influencing the distribution of ectomycorrhizal fungi than either climate or habitat type (Halling et al., 2008).
Tuber is one taxonomic group that appears to be dominant on Quercus roots regardless of the ecosystem type. Tuber sp. 1 was the most frequently detected taxon in this tropical forest. Tuber species are also dominant root-inhabiting taxa in Mediterranean and mesic Quercus forests and woodlands (Murat et al., 2005; Walker et al., 2005; Smith et al., 2007; Morris et al., 2008b). Tuber species have a hypogeous fruiting habit and are often overlooked in routine sporocarp surveys, but are commonly detected during studies of hypogeous fungi with Quercus (Smith et al., 2007; M. Smith, pers. obs.).
The ectomycorrhizal community remained relatively stable between June and August, possibly because the sampling dates did not correspond to a significant change in environmental conditions or because of limited turnover of ectomycorrhizal roots tips during this time period. Of the 44 ectomycorrhizal species found on Q. crassifolia in October/November 2003 (Morris et al., 2008a), 30(68%) were detected again in this study (June/August 2004), further suggesting that ectomycorrhizal composition is not highly influenced by short-term temporal dynamics. Our results are similar to findings from a Quercus douglasii woodland where winter and spring ectomycorrhizal communities were not significantly different over a 2-year period (Smith et al., 2007), but are in contrast to other studies that found rapid ectomycorrhizal turnover at relatively short time scales (Izzo et al., 2005; Courty et al., 2008).
Influence of host and soil characteristics on ectomycorrhizal taxa distributions
Abiotic soil properties can influence sporocarp production, ectomycorrhizal formation on roots and ectomycorrhizal community structure (Peter et al., 2001; Erland & Taylor, 2002). Soil properties can also have indirect effects on ectomycorrhizal communities by influencing plant community composition. Thus, the interacting factors of host plant species and direct and indirect effects of soil properties may influence ectomycorrhizal community composition (Claridge et al., 2000; Wardle, 2002). Oak host species and available P were significant in explaining some variation in the distribution of ectomycorrhizal fungi in this study. However, available P was not significant when sampling date was used as a covariable, indicating that the effect of available P was strongly influenced by high phosphorus levels in a single plot in August. Furthermore, correlation between soil variables makes it difficult to separate effects of individual soil factors. Similarly, unmeasured soil factors could also influence ectomycorrhizal communities. Leaf litter chemistry varies between plant species (Hättenschwiler et al., 2008), which may have important consequences for ectomycorrhizal communities (Conn & Dighton, 2000). Litter quality may affect soil chemistry and fungi may respond differently to secondary metabolites in leaf litter (Jonsson et al., 2006). Differences in litter quality between the deciduous Q. crassifolia and evergreen Q. laurina could play a role in host preference of ectomycorrhizal fungi. In addition, tree phenology can influence ectomycorrhizal community composition and metabolic activity (Buee et al., 2005; Courty et al., 2006, 2007) and Talbot et al. (2008) hypothesize that ectomycorrhizal fungi may decompose soil C when photosynthate supplies are reduced, such as during plant dormancy.
Several common species (Sebacinales1, Russula sp. MHM097, Tricholoma sp. 2) were differentially distributed on the two oak hosts although this was not statistically significant. However, small sample size and the high diversity of ectomycorrhizal fungi limited our ability to detect significant differences of individual species on the two oaks. Cortinariaceae did exhibit significant preference for Q. laurina in June and Gomphaceae (five Ramaria species) was found exclusively on Q. laurina.
Tedersoo et al. (2008) found strong host preference of ectomycorrhizal fungi for three co-occurring trees from different families. Host preference was also demonstrated for trees from three families in a mixed conifer-broadleaf forest (Ishida et al., 2007). Although ectomycorrhizal host preference has not been extensively documented for different species within the same genus, two studies have reported distinct differences in ectomycorrhizal communities on co-occurring oak species (Morris et al., 2008b; Cavender-Bares et al., 2009). This study provides additional evidence that host preference may play an important role in structuring ectomycorrhizal communities on host trees that are phylogenetically similar. Conspicuous differences in ectomycorrhizal communities were found on two oak hosts that were more distantly related (e.g. one species was section Lobatae whereas the other was section Quercus) and were more scattered in distribution (Morris et al., 2008b). Further research is needed to better understand the role of taxonomic relatedness, spatial distribution and ecological differences (e.g. leaf phenology) in ectomycorrhizal host specificity.
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We thank Ken Oyama for his support and valuable contributions to this research. We gratefully acknowledge Mauricio Quesada and Kathy Stoner for use of laboratory space and equipment in Mexico, Maribel Nava-Mendoza and Dolores Lugo Aquino for conducting soil analyses, Susana Valencia Avalos and John Tucker for identification of oak specimens, Jenny Moreno Miranda for laboratory assistance and Marcel Rejmánek for statistical advice. This research was supported by a UC MEXUS Dissertation Research Grant, UC Davis Ecology Block Grant fellowships and a National Science Foundation Grant (#DEB-99-81711) to C.S.B. Participation by M.E.S. was made possible by the Harvard University Herbaria (HUH).
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Fig. S1. CA of the ectomycorrhizal communities on Quercus crassifolia and Quercus laurina.
Fig. S2. Cluster analysis using unweighted pair group method with arithmetic mean and Bray–Curtis distances showing similarity of ectomycorrhizal fungi in plots across sampling dates.
Table S1. Species richness and diversity indices of ectomycorrhizal fungi on the roots of Quercus crassifolia and Quercus laurina in a tropical montane cloud forest.
Table S2. Nonectomycorrhizal taxa on Quercus crassifolia (Q.c.) and Quercus laurina (Q.l.) in a tropical montane cloud forest.
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