Glomeromycota - Wiley Online Library

New Phytologist

Research

The online database MaarjAM reveals global and ecosystemic distribution patterns in arbuscular mycorrhizal fungi (Glomeromycota) ¨ pik1, A. Vanatoa2, E. Vanatoa1, M. Moora1, J. Davison1, J. M. Kalwij1, U ¨ . Reier1 and M. Zobel1 M. O 1

Department of Botany, Institute of Ecology and Earth Sciences, University of Tartu, 40 Lai St., 51005 Tartu, Estonia; 2Institute of Agricultural and

Environmental Sciences, Estonian University of Life Sciences, Fr. R. Kreutzwaldi 5, Tartu 51014, Estonia

Summary Author for correspondence: ¨ pik M. O Tel: +372 737 6224 Email: [email protected] Received: 22 February 2010 Accepted: 11 May 2010

New Phytologist (2010) 188: 223–241 doi: 10.1111/j.1469-8137.2010.03334.x

Key words: arbuscular mycorrhizal (AM) fungi, distribution, diversity, global, host range, metadata, sequence database, SSU rDNA.

• Here, we describe a new database, MaarjAM, that summarizes publicly available Glomeromycota DNA sequence data and associated metadata. The goal of the database is to facilitate the description of distribution and richness patterns in this group of fungi. • Small subunit (SSU) rRNA gene sequences and available metadata were collated from all suitable taxonomic and ecological publications. These data have been made accessible in an open-access database (http://maarjam.botany.ut.ee). • Two hundred and eighty-two SSU rRNA gene virtual taxa (VT) were described based on a comprehensive phylogenetic analysis of all collated Glomeromycota sequences. Two-thirds of VT showed limited distribution ranges, occurring in single current or historic continents or climatic zones. Those VT that associated with a taxonomically wide range of host plants also tended to have a wide geographical distribution, and vice versa. No relationships were detected between VT richness and latitude, elevation or vascular plant richness. • The collated Glomeromycota molecular diversity data suggest limited distribution ranges in most Glomeromycota taxa and a positive relationship between the width of a taxon’s geographical range and its host taxonomic range. Inconsistencies between molecular and traditional taxonomy of Glomeromycota, and shortage of data from major continents and ecosystems, are highlighted.

Introduction Arbuscular mycorrhizal (AM) fungi (phylum Glomeromycota; Schu¨ßler et al., 2001b) are among the world’s commonest soil microorganisms and associate with > 80% of all plant species (Smith & Read, 2008). To understand the role of Glomeromycota in ecosystems, information about their ecology and biogeography is of primary importance (Fitter, 2005; Chaudhary et al., 2008). During the past two decades, since the work by Simon et al. (1992), such information has increasingly been sought using molecular tools. However, despite the gradual accumulation of data indicating the molecular diversity and distribution of Glomeromycota, a broader ecological understanding remains elusive. Analysis of Glomeromycota molecular diversity is hampered by the lack of a universal system of nomenclature applicable to taxa that are identified only by their DNA

The Authors (2010) Journal compilation New Phytologist Trust (2010)

sequences. Thus, the same phylogroups (sequence groups, species, OTUs) are often referred to differently by individual case studies. Furthermore, there is no consensus as to which criteria are suitable for delimiting phylogroups. Therefore, sequence groups identified by different authors contain different degrees of within-group variability. Meanwhile, reference data describing intra- and interspecific genetic variability in described Glomeromycota species are contradictory and limited to relatively few taxa (Nilsson et al., 2008; Rosendahl, 2008; Gamper et al., 2009; Stockinger et al., 2009). Sequences of cultured reference species are not yet available for most of the phylogroups detected in natural ecosystems, meaning that relationships with known species are unclear for a large proportion of phylogroups (van der Heijden et al., 2008; Rosendahl, 2008). For these reasons, arbitrarily named phylogroups rather than species assignment have

New Phytologist (2010) 188: 223–241 223 www.newphytologist.com

New Phytologist

224 Research

typically been used when describing the natural diversity of Glomeromycota (Helgason et al., 1998; Vandenkoornhuyse et al., 2003). If original sequence data from case studies are made available in public databases, phylogenetic analysis can be performed on a metadataset comprising all such sequences in order to delimit standard phylogroups. Such phylogroups, ¨ pik et al., hereafter referred to as ‘virtual taxa’ (VT; cf. O 2009), can be named or coded to provide a standard taxonomy (see Horton et al., 2009). As well as allowing future studies to be comparable, a standardized taxonomy can be unequivocally associated with metadata, such as geographical location, host plant species and ecosystem, to provide an overview of Glomeromycota distribution, habitat preferences and other fundamental ecological characteristics. Currently, the quantity of comparable sequence data from Glomeromycota is reaching the level where ecologically meaningful questions can be answered. Indeed, metadata linked to sequence datasets of Glomeromycota has already provided insights into AM fungal community composition ¨ pik et al., 2006), and in relation to among ecosystems (O host range (Helgason et al., 2007) and dominance patterns (Dumbrell et al., 2010). DNA sequence data in public databases can be poorly and ⁄ or discontinuously annotated, misidentified or suffer from limited taxon sampling (Bridge et al., 2003; Bidartondo et al., 2008; Ryberg et al., 2008; Brock et al., 2009). In order to overcome these limitations, specialized curated databases are increasingly being compiled to provide high-quality sequences with complete and correct annotations, including a verified taxonomic identification (Ko˜ljalg et al., 2005; Abarenkov et al., 2010). The importance of fully annotated datasets is likely to increase further still as they can serve as reference data for en masse identification of sequences in the large datasets produced by nextgeneration sequencing technologies (Bueé et al., 2009; ¨ pik et al., 2009; Horton et al., 2009; Nilsson et al., 2009; O Ryberg et al., 2009; Martin & Martin, 2010). In this paper we describe an open-access database, called MaarjAM (http://maarjam.botany.ut.ee), and outline some of its potential applications. MaarjAM stores publicly available Glomeromycota sequence data and associated metadata such as location, host plant, biome, climatic zone etc. The information contained in MaarjAM is carefully checked by specialists and is presented in a format to facilitate downstream data analyses. Currently, the database primarily contains small subunit rRNA gene sequences, but the range of molecular markers will likely be increased in the future. Earlier versions of this database have already been used by our study group for en masse identification of large-sequence ¨ pik et al., 2009; M. datasets using the BLAST algorithm (O Moora et al., unpublished). MaarjAM additionally provides an overview of existing information about the ecology and biogeography of Glomeromycota. As an example, we

New Phytologist (2010) 188: 223–241 www.newphytologist.com

investigate several of the many potential questions that MaarjAM could help to answer: what is the global distribution of individual Glomeromycota VT and of VT richness; and which abiotic and biotic factors explain the observed VT distribution patterns?

Materials and Methods Data sources The MaarjAM database aims to provide a quality-controlled repository for published sequence data from Glomeromycota (the name of the database is an amalgamation of Maarja ¨ pik, the creator of the database) and arbus(from Maarja O cular mycorrhiza (AM)). Therefore, data from both ecological and taxonomic studies are included. For inclusion in MaarjAM, sequence data must be both submitted to public sequence databases and published in scientific papers. An overview of the principles and procedure guiding data input is provided in Supporting Information, Fig. S1. Particular care has been taken to include all publications using the small subunit ribosomal RNA gene between PCR primers NS31 and AM1 because the majority of natural Glomeromycota diversity data have been obtained using this marker region (Lee et al., 2008). However, the number of studies using other marker regions, including nuclear internal transcribed spacer (ITS), large subunit (LSU) rRNA gene, beta-tubulin, actin, elongation factor 1-alpha and mitochondrial LSU rRNA gene, is increasing rapidly. These data will be included in future versions of the database. DNA sequence data were obtained from the GenBank ⁄ EMBL ⁄ DDBJ nucleotide sequence databases (hereafter INSD, for International Nucleotide Sequence Databases). The origin of cultured fungi was taken from the Glomeromycota culture collections (BEG, INVAM, GINCO) if missing or insufficiently described in the original publication. Where necessary, authors were contacted for clarification. Glomeromycota nomenclature follows A. Schu¨ßler’s Glomeromycota phylogeny (http://www.lrz-muenchen.de/ ~schuessler/amphylo/; 29 April 2010). Host plant nomenclature follows APG III (Bremer et al., 2009; Chase & Reveal, 2009). Data structure The MaarjAM database contains individual records of phylogroup occurrences organized by location and host plant species. Several records per phylogroup with different DNA sequences were included if available in order to register within-group sequence variability in the database. When a specific location or host species was recorded in a publication, but no DNA sequences were made available, a dummy accession without sequence data was created in order to allow fungal distribution to be fully registered. Thus, the


New Phytologist

Research

following data are stored for each accession: DNA sequence (DNA sequence and INSD accession number if present, PCR primers, marker region), sample origin (four categories: plant roots, soil, cultured spores, other), host plant data (species, higher taxonomic classifications), location data (site name, geographical coordinates, administrative units, continent) and original publication reference. In particular, the trait ‘sample origin’ allows different kinds of data, such as ecological surveys based on plant roots and purely taxonomic surveys based on cultured fungi, to be separated in downstream analyses. The category ‘cultured spores’ is used for single-spore cultures (i.e. isolates) and single-species multispored cultures, but spores from natural soil, pot experiments and trap cultures are assigned to the category ‘other’. If possible, additional data were provided on the ecology and biogeography of the glomeromycotan taxa, either based on information available in the paper or inferred from the location of the study site. The ecological and biogeographical data are linked to individual accessions, not species names or other categories, in order to maintain independence of data for analyses. A brief description of these categories follows (for a full specification, see Supporting Information, Methods S1): Ecological categories The habitat classification implemented in the MaarjAM database uses three hierarchical levels (from general to specific): specific ecosystem features, biome, habitat (Table 1).

The category ‘specific ecosystem features’, which currently contains six levels, is a categorization that allows researchers to address particular ecological patterns of interest (Table 1). For the questions addressed in this paper, it is useful for distinguishing between structurally and functionally different ecosystems, such as forests, shrublands and grasslands (cf. McNaughton et al., 1989), and to characterize the dynamic status of the ecosystem by distinguishing early successional natural ecosystems and anthropogenic ecosystems, the latter containing cultivated and other disturbed ecosystems. The sixth level ‘culture’ is used for records originating from cultures of Glomeromycota if no information about the ecosystem of origin was available. Further specific categorizations may be created later to address future questions. The category ‘biome’ represents the highest ecological classification unit that is convenient to recognize globally. Habitats within a biome function in a broadly similar way. The WWF classification of terrestrial ecoregions within 14 biomes and eight biogeographical realms was used as a starting point (Olson et al., 2001). However, in order to interpret the distribution of Glomeromycota in a more precise ecological context, the original classification was further refined to include 27 biomes (Supporting Information, Methods S1). Currently, the MaarjAM database contains records from 17 biomes (Table 1). The category ‘habitat’ refers to the vegetation ⁄ ecosystem ⁄ ecoregion ⁄ habitat type where sampling was

Table 1 Hierarchical habitat classifications used in the MaarjAM database: specific ecosystem features, biome and habitat Specific ecosystem features

Biome

Examples of habitats

Anthropogenic

Anthropogenic ecosystem

Culturea Forest

Habitat not known Boreal forest Subtropical dry broadleaf forest Subtropical moist broadleaf forest Temperate broadleaf and mixed forest

Abandoned mine, arable field, agricultural ecosystem, contaminated land, glasshouse, park, olive plantation, vineyard Culturea Boreal forest Broadleaved forest Deciduous broadleaved second-growth forest Boreo-nemoral forest, broadleaved forest, mixed deciduous woodland Temperate forest Dry afromontane forest Rainforest, tropical montane cloud forest Savannah, serpentine soil, semi-arid grassland Agricultural grassland Ancient meadow, tallgrass prairie Temperate grassland Tropical tussock grassland, savannah Dolomitic shrubland, gypsophilous vegetation Garrigue Boreal forest border, coastal vegetation, lahar area, saltern, sand dune Salt marsh, wetland

Grassland

Shrubland Successional

Temperate coniferous forest Tropical dry broadleaf forest Tropical moist broadleaf forest Subtropical grasslands and savannahs Temperate cultivated grassland Temperate natural grassland Temperate semi-natural grassland Tropical grasslands and savannas Deserts and xeric shrublands Subtropical shrubland Azonal and successional Other wetlands

‘Habitat’ is a description provided by original publications, of which just a few examples are shown in this table. Please see the Materials and Methods section and Supporting Information, Methods S1, for further details. a Records from cultures from known biomes and ecosystems are classified into the respective categories.



225

New Phytologist

226 Research

conducted. If present, a description from the original publication was usually retained; however, if it was lacking or insufficient, wherever possible a specification was provided on the basis of other information available in the publication or elsewhere. Environmental categories A slightly modified version of Walter’s (1994) system with five broad climatic zones corresponding to those of Holdridge (1967) is used in the MaarjAM database: tropical s.l. (equatorial and tropical); subtropical s.l. (subtropical, Mediterranean and warm temperate); temperate s.l. (temperate, nemoral and continental); boreal; and polar. There are currently few records in MaarjAM from the boreal climatic zone and no records from the polar climatic zone. Geographical categories The continents are defined as: Africa, North America (with an artificial southern boundary in Panama), South America, Oceania (including biogeographical realms Australasia and Oceania; see the next paragraph), Europe and Asia (with a boundary formed by the Ural and Caucasus mountain ranges, and Caspian and Black seas). The ancient supercontinents Laurasia and Gondwana, which developed following the break-up of Pangaea, were interpreted as suggested by Scotese (2004); that is, Gondwana consisting of present-day Africa, South America, Oceania and India; and Laurasia consisting of present-day North America and Eurasia, but excluding India, Indonesia and the Philippines. Biogeographical realms are large geographical regions where ecosystems share broadly similar biota. We distinguished eight biogeographical realms following Olson et al. (2001): Palearctic, Nearctic, Afrotropic, Neotropic, IndoMalay, Australasia, Oceania and Antarctic. There are currently no data in MaarjAM from the Antarctic realm. Database design The MaarjAM database runs on a quad-core 64bit Linux server (CentOS 5.2, kernel 2.6.18.x, webserver Apache ver. 2.x). Data are stored in the relational tables of a MySQL ver. 5.x database. A graphical user interface (GUI) for accessing and editing data has been built using PHP 5.x scripting language and Ajax technology. The GUI is accessible through all class A browsers regardless of operating system, though it has been most intensively tested using Mozilla Firefox (ver. 2.x and 3.x) and Google Chrome. Phylogenetic analysis Glomeromycota sequence groups were identified following automatic alignment of all MaarjAM sequences using the MAFFT multiple sequence alignment web service implemented in JALVIEW 2.4 (Clamp et al., 2004) and


neighbor-joining analysis with TOPALi (Milne et al., 2004). Sequence groups (referred to as VT) were defined on the basis of bootstrap support and sequence similarity ‡ 97%. These criteria produced groupings with sequence variability (i.e. within-group variation) similar to those used ¨ pik et al., 2008). by some authors (Helgason et al., 1998; O Phylogenetic analysis was also conducted using a Bayesian approach in BEAST (version 1.5.3; Drummond & Rambaut, 2007). The GTR + I + G nucleotide substitution model was chosen on the basis of AIC (jModelTest; Posada, 2008). Posterior parameter estimates were drawn every 1000 steps from three separate 10 000 000 step Markov chain Monte Carlo (MCMC) runs, with the first 10–15% of steps discarded as burn-in. Posterior clade probabilities were summarized on a maximum clade credibility tree. Statistical data analysis Coleman rarefaction analysis using 50 randomizations without replacement was performed in EstimateS 8.0.0 (Colwell, 2006) to produce accumulation curves showing VT richness in relation to sampling intensity (number of accessions in MaarjAM). Two-way log-linear analysis and the Freeman–Tukey deviation test (Legendre & Legendre, 1998) were performed to determine whether the frequencies of VT belonging to the five most abundant Glomeromycota families are represented differently among the continents or among climatic zones; and whether the continental distribution pattern of VT (found in one, two, three or four continents) is related to their distribution pattern across host plant lineages (colonizing plant species from one, two or three of the plant superorders; different host plant groups are unevenly represented in MaarjAM; therefore this analysis only included data from plant superorders Asteranae, Lilianae and Rosanae). To determine whether there was a relationship between spatial or environmental variables and VT richness, we first tested whether the sample size (number of accessions) and geographical distribution of the accessions held in MaarjAM provided sufficient power. This was done using the global map of vascular plants from Kier et al. (2005), which shows that plant species richness is negatively correlated with latitude, as a proxy. Analysis was restricted to MaarjAM records from plant roots, excluding those from soil, cultured spores or other, in order to ensure methodological consistency. Furthermore, because of the low sample size from the southern hemisphere, we only used MaarjAM data from the northern hemisphere in this analysis. A subset of the Kier et al. (2005) vascular plant dataset was extracted by taking plant richness estimates only from the geographical positions corresponding to northern hemisphere VT observations in MaarjAM.


New Phytologist Correlation between latitude and vascular plant richness in 2 this reduced dataset was weak (radj = 0.305) but highly significant (F = 36.555, df = 80, P < 0.0001) indicating that our sample size and spatial distribution were sufficient to reveal a latitudinal effect of the magnitude exhibited among vascular plants. To determine whether elevation was a contributing environmental variable explaining VT richness, the elevation (m above sea level) at the geographical position of each VT observation was obtained from a digital elevation model (DEM) with a spatial resolution of c. 30 arcsec (http://www.ngdc.noaa.gov/mgg/topo/gltiles.html). All MaarjAM records with geographical position data (n = 1983 accessions) were imported into a geographical information system (GIS) using ArcMap 9.2 (ESRI, 2006). For analysing the distribution of global VT richness we only used MaarjAM accessions from plant roots (n = 1801; 99 locations). Richness values were interpolated using the inverse distance weighting function, which interpolates values within a circular range of 10–15 observations. To correct VT richness for sampling intensity, the number of observations (number of MaarjAM accessions) was determined for each location. Subsequently a linear regression model was fitted to determine the relationship between loge-transformed number of observations and loge-transformed VT richness, and the standardized residuals recorded. These residuals were interpolated using the same technique as described earlier to determine the global distribution of VT richness residuals. For ease of interpretation, interpolated richness data are only presented for terrestrial zones.

Results MaarjAM database size and phylogenetic delimitation of VT As of 20 April 2010 the MaarjAM database of glomeromycotan environmental and culture-originating sequences contained 2447 records of small subunit (SSU) rRNA gene sequence occurrences, derived from 105 publications. Sequences covering the NS31-AM1 amplicon of the SSU rRNA gene (1844 in total) were used in phylogenetic analysis in order to delimit VT. One hundred and two publications provided data that could be assigned to VT (2238 records; Methods S2). The remaining 209 accessions were not assigned to VT because they were dummy accessions with an original phylogroup identity that was linked to several VT or because the sequence covered a different SSU rRNA gene fragment. Based on clade support and sequence similarity ‡ 97%, 282 virtual taxa were delimited (Figs 1, S2). VT delimited on the basis of the neighborjoining phylogeny generally were supported by the Bayesian phylogenetic approach (Fig. S2). Two-thirds of


Research

the identified VT belonged to Glomeraceae (i.e. Glomus group A; 186 VT, Tables 2, S1). Sequences of cultured fungi ascribed to 71 species with Latin binomials were found in 53 VT (Tables 2, S1); some VT contained several named species, while some named species occurred in more than one VT. A list of VT showing the inclusion of previously named species and cultures not identified to species level is provided in Table S1. A total of 57 VT were represented by ‡ 10 records, while 54 VT were represented by only one record. VT richness Glomeromycota VT accumulation curves did not reach an asymptote, at either the global or the continental scale, indicating that there probably remain many unrecorded taxa. No marked differences in terms of taxon richness accumulation curves existed between the continents (Fig. 2). However, sampling effort has been extremely uneven (Table 3). The global distribution of VT richness, based on data from plant roots, is shown in Fig. 3(a). There was a significant linear relationship between VT richness per location 2 and sample size (radj = 0.818, df = 97, P < 0.001). When the effect of sample size (number of MaarjAM accessions from a location) was removed by using standardized residual VT richness per location, richness hotspots identified in the uncorrected analysis were no longer apparent (Fig. 3b). Distribution maps are shown in Fig. 4 for the 12 VT recorded from the greatest number of different locations. There were no significant relationships (P always > 0.05) between either loge-transformed VT richness or the standardized residual VT richness and any of the explanatory environmental variables (northern hemisphere latitude, loge-transformed elevation, loge-transformed vascular plant richness). Biogeographical and ecological patterns in VT distribution The distribution of VT across continents indicated a high prevalence of endemic VT (recorded from only one continent) and very few ubiquitous VT. Only one VT, Glomus VT166, has been recorded on all six continents (Table 3), while five VT have been recorded on five continents: Gigaspora VT39 (incl. G. albida, G. decipiens, G. gigantea, G. margarita, G. rosea), Scutellospora VT49 (incl. S. aurigloba, S. dipurpurescens), Glomus VT67 (incl. G. mosseae), Glomus VT191, Glomus VT219. By contrast, 168 VT have been recorded exclusively on one continent (Table 3) and 95 VT in one location. When the data from Europe and Asia, and North and South America were collapsed into two categories – Eurasia and America – the


227

228 Research

New Phytologist

(a)

(b)

distinctness of VT pools remained (Fig. 5a). These two well-studied continents shared only 69 VT out of their respective totals of 189 and 151 VT (Fig. 5a).


Fig. 1 Maximum clade credibility tree of glomeromycotan small subunit (SSU) rRNA gene virtual taxa (VT) in the MaarjAM database, inferred using Bayesian phylogenetic analysis. Posterior probabilities (when > 0.5) for nodes are shown for higher-order clades. The numbers of VT in each lineage are indicated on this outline phylogeny. Refer to Supporting Information Fig. S2 for detailed placement of VT and described species. (a) Glomeromycota; (b) subtree showing Archaeosporales and Paraglomerales. Note: no sequences from described species are available for the majority of Glomus group A lineages and for the putatively named Archaeosporaceae? and Paraglomeraceae? clades.

We compared the distribution of VT on land masses that historically belonged to the ancient supercontinents Laurasia and Gondwana (Fig. 5b). These historical


New Phytologist

Research

Table 2 Number of virtual taxa (VT) in each Glomeromycota family in the MaarjAM database Continent

Family

Climatic zone

Known species in North South MaarjAM ⁄ Total Africa Asia Europe America Oceania America Boreal Subtropical Temperate Tropical Total VT known species

Acaulosporaceae 2 Ambisporaceae 1 Archaeosporaceae 2 Diversisporaceae 2 Geosiphonaceae 0 Gigasporaceae 0 Glomeraceae 42 Glomus group B 1 Pacisporaceae 0 Paraglomeraceae 0 Total 50

4 2 0 5 0 4 50 5 0 2 72

28 1 6 7 1 6 95 7 1 3 155

8 1 2 3 0 5 76 3 1 2 101

3 0 0 1 0 3 7 0 0 0 14

12 0 0 1 0 7 53 2 0 2 77

0 1 0 0 0 0 1 1 0 0 3

9 2 2 7 0 5 71 3 2 2 103

29 2 6 6 1 7 127 10 1 5 194

15 1 1 4 0 8 86 3 0 2 120

46 2 8 11 1 10 186 10 2 6 282

7 ⁄ 36 4⁄8 1⁄2 8⁄7 1⁄1 23 ⁄ 47 20 ⁄ 102 5⁄7 1⁄7 3⁄3 71 ⁄ 220

Data are subdivided by continent and climatic zone. The final column provides the total number of known morphospecies following the nomenclature in A. Schu¨ßler’s Glomeromycota phylogeny (http://www.lrz-muenchen.de/~schuessler/amphylo/) and the number of known morphospecies represented in MaarjAM. Note that Glomeraceae includes Glomus group A; Glomus group B is treated as Fam. ined. (cf. Kru¨ger et al., 2009). Entrophosporaceae with two species is not yet represented in MaarjAM and therefore is not in the table.

Fig. 2 Global and continental taxon accumulation curves (Coleman rarefaction) showing glomeromycotan virtual taxon (VT) richness in relation to sampling intensity (the number of accessions in MaarjAM). Curves are presented up to a maximum of 500 accessions. See Table 2 for the total number of accessions in each category.

supercontinents shared 67 VT out of totals of 221 and 122 VT in Laurasia and Gondwana, respectively. Virtual taxa were also characterized by small distribution ranges when other biogeographical and ecological units were compared: 61, 61, 53 and 51% of VT occurred in only one biogeographical realm, climatic zone, ecosystem and biome, respectively (Table 3, Fig. 5); 70, 70, 80 and 85% of such VT are known from only one location. MaarjAM contains records from 168 host plant species from seven vascular plant superorders and six nonvascular plant subclasses (Table 3). Ninety-six VT have been recorded from the roots of single host species. We compared the occurrence of VT in the three plant superorders with the largest number of records: Asteranae, Lilianae and Rosanae (Table 3, Fig. 5d); 112 VT (49%) were associated with host plants from only one of these plant superorders,


including 53 VT that were represented by a single accession in the database. The distribution pattern of VT among host plant superorders contrasted with the pattern found in relation to geographical distribution, where relatively few records came from ubiquitous VT. VT detected in the roots of all three plant superorders were represented by large numbers of records and may thus represent abundant VT (average of 17.5, a maximum of 62 records per VT). By contrast, VT that were restricted to single plant superorders were represented by relatively few records and may represent less abundant VT (Table 3; average of 2.0, a maximum of 11 records per VT). However, as these include 53 VT with a single record among the three plant superorders, the effect of sample size cannot be excluded. For comparison, the global average across all VT in the database was 7.9 records per VT.


229

New Phytologist

230 Research

Table 3 Numbers of Glomeromycota SSU rRNA gene virtual taxa (VT), publications, and accessions in the MaarjAM database from different continents, biogeographical realms, climatic zones, ecosystems and biomes Accessions VT Continents Africa Asia Europe North America Oceaniaa South America Occurs on one continent out of six Occurs on two continents out of six Occurs on three continents out of six Occurs on four continents out of six Occurs on five continents out of six Occurs on six continents out of six Laurasia Gondwana Biogeographical realms Afrotropic Australasia Indo-Malay Nearctic Neotropic Oceaniaa Palearctic Occurs in one realm out of seven Occurs in two realms out of seven Occurs in three realms out of seven Occurs in four realms out of seven Occurs in five realms out of seven Occurs in six realms out of seven Occurs in seven realms out of seven Climatic zones Boreal Subtropical Temperate Tropical Occurs in one climatic zone out of four Occurs in two climatic zones out of four Occurs in three climatic zones out of four Occurs in four climatic zones out of four Ecosystems Anthropogenic Culture Forest Grassland Shrubland Successional Occurs in one ecosystem out of six (5)b Occurs in two ecosystems out of six (5) Occurs in three ecosystems out of six (5) Occurs in four ecosystems out of six (5) Occurs in five ecosystems out of six (5) Occurs in six ecosystems out of six Biomes Anthropogenic ecosystem Azonal and succesional Boreal forest Deserts and xeric shrublands Other wetlands Subtropical dry broadleaf forest Subtropical grasslands and savannas Subtropical moist broadleaf forest Subtropical shrubland Temperate broadleaf and mixed forest Temperate coniferous forest


Papers

Total

From roots

From soil

From cultures

Other

50 72 155 101 14 77 168 62 26 17 5 1 221 122

6 13 50 32 8 16

152 184 1255 364 23 225 540 487 303 571 197 105 1775 400

151 144 1130 294 11 208

0 0 0 36 0 0

1 15 82 34 11 15

0 25 43 0 1 2

50 13 12 95 83 2 176 165 69 24 11 2 0 0

6 7 3 30 18 2 52

165 47 35 226 245 2 1296 512 568 548 331 129 0 0

151 11 24 267 235 0 1144

0 0 0 36 0 0 0

1 11 2 33 15 1 86

0 0 2 0 2 1 66

3 103 194 120 171 75 29 3

3 37 58 24

6 410 1388 381 517 763 838 67

0 344 1220 362

0 2 34 0

6 50 80 16

0 14 54 3

81 44 166 147 27 62 151 (141)b 62 (65) 37 (39) 15 (10) 9 (11) 6

30 26 33 27 5 17

292 122 834 623 105 238 399 383 478 283 320 331

251 0 794 579 102 181

8 0 28 0 0 0

27 101 10 20 0 26

6 21 2 4 3 31

81 42 12 27 28 18 43 2 1 82 12

30 15 1 4 2 2 6 1 1 12 2

292 169 28 104 69 44 106 2 1 459 19

251 117 28 101 64 44 104 2 1 436 9

8 0 0 0 0 0 0 0 0 16 10

27 26 0 0 0 0 2 0 0 6 0

6 26 0 3 5 0 0 0 0 1 0


New Phytologist

Research

Table 3 (Continued) Accessions VT Temperate cultivated grassland 5 Temperate natural grassland 38 Temperate semi-natural grassland 90 Tropical dry broadleaf forest 18 Tropical grasslands and savannas 18 Tropical moist broadleaf forest 77 Occurs in one biome out of 17 134 Occurs in two biomes out of 17 59 Occurs in three biomes out of 17 26 Occurs in four biomes out of 17 16 Occurs in five biomes out of 17 6 Occurs in six biomes out of 17 12 Occurs in seven biomes out of 17 6 Occurs in eight biomes out of 17 3 Occurs in nine biomes out of 17 0 Occurs in 10 biomes out of 17 2 Occurs in 11 biomes out of 17 0 Occurs in 12 biomes out of 17 1 Occurs in 13–17 biomes out of 17 0 Host species Vascular plants (superorder level) Asteranae 115 Austrobaileyanae 3 Caryophyllanae 15 Lilianae 143 Magnolianae 6 Ranunculanae 57 Rosanae 146 Occurrence among Asteranae, Lilianae, Rosanae Occurs in one superorder 112 Occurs in two superorders 62 Occurs in three superorders 56 Nonvascular plants (subclass level) Lycopodiidae 2 Marchantiidae 13 Ophioglossidae 12 Pinidae 20 Polypodiidae 2 Psilotidae 6

Papers

Total

From roots

From soil

From cultures

Other

4 3 13 2 2 11

30 77 326 39 63 238 355 292 176 204 166 244 204 134 0 186 0 105 0

18 73 321 39 63 236

0 0 0 0 0 0

12 0 5 0 0 1

0 4 0 0 0 1

25 1 5 34 1 4 30

346 3 38 607 6 146 558 229 301 981

1 2 2 3 1 1

25 29 33 41 2 21

a

Oceania as a continent includes the biogeographical realms Australasia and Oceania (sensu Olson et al., 2001). Parentheses contain the value if accessions from cultures with no known ecosystem of origin are removed; accessions from roots, soil or other sources with no known ecosystem of origin are not counted here. The data originate from the following publications: Simon et al. (1992, 1993a,b), Gehrig et al. (1996), Simon (1996), Helgason et al. (1998), Sawaki et al. (1998), Vandenkoornhuyse & Leyval (1998), Helgason et al. (1999), Declerck et al. (2000), Kramadibrata et al. (2000), Redecker et al. (2000a,b), Daniell et al. (2001), Schu¨ßler et al. (2001a,b), Schwarzott et al. (2001), Bidartondo et al. (2002), Helgason et al. (2002), Husband et al. ¨ pik et al. (2003), Regvar et al. (2003), Calvente (2002a,b), Kowalchuk et al. (2002), Vandenkoornhuyse et al. (2002a,b), Helgason et al. (2003), O et al. (2004), Ferrol et al. (2004), Haug et al. (2004), Heinemeyer et al. (2004), Oba et al. (2004), Saito et al. (2004), Scheublin et al. (2004), Walker et al. (2004), Whitfield et al. (2004), Wirsel (2004), de Souza et al. (2005), Douhan et al. (2005), Jumpponen et al. (2005), Ma et al. (2005), O’Brien et al. (2005), Rowe & Pringle (2005), Russell & Bulman (2005), Sato et al. (2005), Yamato & Iwase (2005), de la Penã et al. (2006), DeBellis & Widden (2006), Franke et al. (2006), James et al. (2006), Martynova-Van Kley et al. (2006), Rodrı´guez-Echeverrıá & Freitas (2006), Santos et al. (2006), Vallino et al. (2006), Wubet et al. (2006a,b), Beck et al. (2007), Helgason et al. (2007), Kovaćs et al. (2007), Ligrone et al. (2007), Porras-Alfaro et al. (2007), Redecker et al. (2007), Renker et al. (2007), Santos-Gonza´lez et al. (2007), Walker et al. (2007), Vandenkoornhuyse et al. (2007), Winther & Friedman (2007), Alguacil et al. (2008), Appelhans et al. (2008), Błaszkowski et al. (2008), Burke (2008), Kottke et al. (2008), Lee et al. (2008), ¨ pik et al. (2008), Palenzuela et al. Lesaulnier et al. (2008), Liang et al. (2008), Likar et al. (2008), Maki et al. (2008), Merckx & Bidartondo (2008), O (2008), Schechter & Bruns (2008), Toljander et al. (2008), Turrini et al. (2008), Winther & Friedman (2008), Yamato et al. (2008), Alguacil et al. ¨ pik et al. (2009), (2009a,b,c), Błaszkowski et al. (2009), Gamper et al. (2009), Hausmann & Hawkes (2009), Ipsilantis et al. (2009), Liu et al. (2009), O Schreiner & Mihara (2009), Sonjak et al. (2009a,b), West et al. (2009), Wilde et al. (2009), Winther & Friedman (2009), Yamato et al. (2009), Dumbrell et al. (2010). b

Global geographical distribution patterns of VT in MaarjAM were related to their occurrence in host plant superorders (v2 = 106.7, df = 6, P < 0.001). VT detected


from a wider range of host plants (i.e. host plant species belonging to more than one of the three well-represented superorders) were also geographically more widespread (i.e.


231

232 Research

recorded in more than two continents) and vice versa: VT recorded from only one host plant superorder were overrepresented among VT recorded from only one continent (Freeman–Tukey test, P < 0.05). The occurrence of Glomeromycota families in continents and climatic zones is shown in Table 2. The distribution among continents of VT from the five most abundant Glomeromycota families was significantly different (v2 = 30.24, df = 16, P = 0.02). Acaulosporaceae were relatively overrepresented in Europe, while Gigasporaceae were underrepresented in Africa (Freeman–Tukey test, P < 0.05). The distribution of VT in the five most frequently recorded families of Glomeromycota did not differ between climatic zones (v2 = 6.6, df = 8, P = 0.58). The results of all log-linear analyses were unchanged when the 54 VT represented by a single accession were excluded.

Discussion One of the basic goals of taxonomy is to provide a means to identify organisms (Hibbett et al., 2009). The MaarjAM database introduced here is a repository of reference sequences for use in DNA sequence-based identification of AM fungi (Glomeromycota). It combines published DNA sequence information from taxonomic and ecological publications, and stores available metadata in an easily accessible format. The unique features of MaarjAM include a global taxonomy of Glomeromycota VT, pre-evaluation of data by specialists and organized storage of DNA sequence and metadata. Sequences deposited in the database are subjected to phylogenetic analyses, whereby phylogroups (VT) are defined anew, irrespective of original phylogroup or species identifications, on the basis of > 97% sequence identity and high branch support. This approach overcomes the problem of missing or erroneous identifications in public databases and ensures that data used for downstream analyses are delimited using the same principles. All VT are given numerical codes reflecting the chronological order in which they were identified. A ‘type’ sequence is assigned to each VT, around which the VT would evolve if the taxon splits or merges with others following the inclusion of additional sequences. The history of VT assignment will be included in a future version of MaarjAM in order to keep track of the changing nomenclature of accessions. If desired, the stored sequences and linked metadata in MaarjAM can be downloaded by end users and used to create alternative taxonomies. The principles of sequence-based taxonomy deserve further research in order to find the most suitable criteria and methods for molecular species delineation as well as optimal approach to the naming of sequence-based taxa or species (Hibbett et al., 2009; Horton et al., 2009). Evolutionary methods such as the generalized mixed Yule-coalescent model (GMYC), based on coalescence within independently evolving populations, have been


New Phytologist successfully used to delineate insect and bacterial molecular taxa (Pons et al., 2006; Barraclough et al., 2009) and have the potential to improve the sequence similarity-based VT taxonomy of MaarjAM in the future. Thorough attention is paid to the accuracy of data included in MaarjAM, which are all pre-evaluated by a specialist. Since one of the aims of the database is to allow an overview of glomeromycotan species (taxon) distribution, records of phylogroup occurrence associated with specific locations or host plants are included even if no representative DNA sequence is available. Such ‘dummy’ accessions are assigned to VT only if this can be done unambiguously. These records allow a more complete ecological interpretation of data in comparison with sequence databases, where identical DNA sequences from different geographical locations or host plants are frequently not submitted by authors. The metadata are all linked to accessions, not to VT or species identifications, in order to avoid making erroneous links between taxa and their biogeographical and ecological information. Particular care was taken to include all available data relating to morphotaxa in order to ensure that VT can be linked to fully taxonomically identified sequences wherever possible. However, when investigating ecological questions, data from purely taxonomic studies can be excluded by limiting the dataset by the origin of the sample (plant roots, cultured spores etc.). Other databases that aim to provide controlled reference sequences for fungal taxon identification include the UNITE database for identification of ectomycorrhizal fungi based on ITS sequences from voucher specimens (Ko˜ljalg et al., 2005; Abarenkov et al., 2010) and PHYMYCO, which collates available SSU rRNA gene sequences from all fungi (Le Calvez et al., 2009). It is clear that collaboration between these databases and software tools such as ARB (Ludwig et al., 2004) has the potential to improve certain of their shared features. These could result in future developments of MaarjAM, such as the inclusion of an automated sequence identification service. MaarjAM sequences (and linked metadata) are available for download as a reference dataset for identification of next-generation sequencing data (and have already been ¨ pik et al., 2009; M. Moora et al., used for this purpose in O unpublished). Moreover, next-generation sequences can be included in the MaarjAM database following the same principles as those obtained by Sanger sequencing: only representatives of each phylogroup for each location and host plant combination are included; assuming sequences are available in public databases and that a corresponding research paper has been published. Because of the higher error rate of next-generation sequencing compared with Sanger sequencing, the type of sequencing technology used will be recorded for each accession so that data obtained by different methods can be analysed separately, if required.


New Phytologist

Research

(a)

Richness 20–36 12–19 9–11 6–8 1–5

(b)

Residual s –3.87 to –0.39 –0.38 to –0.03

Fig. 3 The global distribution of glomeromycotan virtual taxon (VT) richness: (a) raw data; and (b) standardized residual richness with the effect of sample size removed.

–0.02 to 0.14 0.15 to 0.31 0.32 to 1.57

Phylogeny and VT delimitation The SSU rRNA gene region generally provides sufficient phylogenetic signal to allow the delimitation of sequence groupings that can be used to describe natural assemblages of Glomeromycota. These groupings correspond roughly to the species level (Lee et al., 2008) or slightly above (see the next paragraph). Clearly, the proposed taxonomy does not replace classical taxonomic identification and description. However, the delimitation of VT provides a means to capture the DNA sequence diversity of organisms as it occurs in nature. Ideally, if all morphospecies were sequenced in the target region, then all environmental sequences could be identified in relation to known species by sequence comparison. Currently, sequences attributed to 71 out of the total of 222 described morphospecies (A. Schu¨ßler’s Glomeromycota phylogeny, http://www.lrz-muenchen.de/ ~schuessler/amphylo/; 29 April 2010) fall into 53 VT (Tables 2, S1). Although the genus Glomus contains the highest number of described species, it is the genus with the smallest proportion of species sequenced for the SSU rRNA gene to date (Tables 2, S1). Thus, it appears that conditions are not yet favourable for successful integration of classical morphotaxonomy and sequence-based taxonomy. The data currently held in MaarjAM allow a total of 282 SSU rRNA gene VT of Glomeromycota to be distinguished. While this number exceeds the number of known Glomeromycota morphospecies, there are several reasons to


suppose that actual richness within this group of fungi is still underestimated. First, analysis of associated metadata indicates a degree of specificity exhibited by VT in relation to geographical distribution, climatic zone and ecosystem type. Therefore, new taxa can be expected from the wide geographical areas and major ecosystems that remain undersampled. Second, the SSU rRNA gene is considered to be incapable of resolving species in certain genera, for example Ambispora, Diversispora and Scutellospora (de Souza et al., 2004; Walker et al., 2007; Gamper et al., 2009). This view is supported by the data presented in this paper. Thus, VT classification based on the central region of the SSU rRNA gene may represent a taxonomic rank higher than that of species (Gamper et al., 2009), although rDNA sequence variability probably differs among phylogenetic lineages. More published information is certainly required about intra- and interspecific genetic variation in a phylogenetically wide range of Glomeromycota taxa. Data should originate from well identified isolates in order to provide guidelines for DNA-based species delimitation (Gamper et al., 2009). The coverage of described species and currently unidentified isolates in culture collections among published SSU rRNA gene sequences could be much improved and would also increase the proportion of taxonomically identifiable VT (cf. Brock et al., 2009). Taxon accumulation curves further supported the hypothesis that there remains Glomeromycota richness to be uncovered. Moreover, the MaarjAM database records


233

New Phytologist

234 Research

VT 00113 (N = 37)

n = 35 n=8 n=1 n=1

VT 00067 (N = 28)

VT 00166 (N = 24)

n = 46 n=1 n=1

VT 00115 (N = 21)

n = 45 n=3

VT 00145 (N = 19)

n = 15 n=5 n=4

VT 00193 (N = 17)

n = 16 n=9 n=2

VT 00065 (N = 17)

n = 55 n=4

VT 00219 (N = 16)

VT 00074 (N = 13)

n = 37 n=1

VT 00064 (N = 13)

VT 00105 (N = 13)

n = 22 n=1

VT 00062 (N = 12)

n = 124 n=7

n = 99 n=3

n = 59 n=2

n = 43 n=2



New Phytologist

Research

Fig. 4 The global distribution of the 12 glomeromycotan virtual taxa (VT) in the MaarjAM database recorded from the greatest number of different locations. Records were derived from plant root samples (circles), cultured spores (triangles, apex up), soil samples (squares) and other samples (triangles, apex down). Number of locations (N) and number of accessions (n) for each type of sample are indicated. Known species are included in the following VT: VT 113, Glomus fasciculatum; VT 67, Glomus mosseae; VT 115, Glomus intraradices, Glomus irregulare, Glomus vesiculiferum; VT 193, Glomus claroideum, Glomus etunicatum, Glomus lamellosum, Glomus luteum, Glomus viscosum; Glomus group B; VT 65, Glomus caledonium, Glomus clarum, Glomus fragilistratum, Glomus geosporum, Glomus verruculosum; VT 64, Glomus constrictum; VT 105, Glomus intraradices; VT 62, Glomus cf. etunicatum; Diversisporaceae.

(a)

(b) Laurasia

Gondwana

America

Eurasia 97

69

59

154

67

55

15 8 8 19 Africa

N (VT) = 275

Fig. 5 Venn diagrams showing the number of Glomeromycota virtual taxa (VT) in the MaarjAM database that are unique to and shared between different continents (a), ancient supercontinents (b), climatic zones (c) and host plant superorders (d). Numbers in the lower left-hand corner of each panel indicate the total number of VT for which the respective metadata have been recorded. The number of records in MaarjAM for each displayed category can be found in Table 3. Note: in the case of climatic zones, the boreal zone with three VT and six accessions is not shown here.

(c)

(d) Temperate

Tropical Rosanae

Lilianae 29

100

23

52

42

44

56

32 13

17

39

N (VT) = 278

Subtropical

16 26 Asteranae

19

occurrences of VT, resulting in species lists of VT per location, while VT abundances within locations are not recorded, as such data are rarely comprehensively provided in original papers. Therefore, it is likely that the abundance of rare taxa is overestimated and that of abundant taxa is underestimated, which can have the effect of producing asymptotic rarefaction estimates. The phylogenetic placement of some sequences into the families Archaeosporales and Paraglomerales (VT1, VT308) remained ambiguous. Archaeosporaceae as defined here remains unsupported, with only VT245 including a described species (Archaeospora trappei; Figs 1, S2), and a well supported subclade of seven VT showing unclear phylogenetic placement in relation to known families. Furthermore, the genera Kuklospora and Gigaspora render Acaulospora and Scutellospora paraphyletic, suggesting that further taxonomic investigation is required to resolve these groups. Glomeromycota species identifications as provided by sequence authors were not always consistent with VT assignment. Reasons for this could include misidentification, the presence of cryptic species within recognized morpho-


N (VT) = 276

N (VT) = 230

species, unresolved taxonomy or insufficient sequence variation to enable species distinction. Misidentification or the presence of cryptic species within apparent morphospecies may be the reason why some sequences obtained from spores derived from natural soils (e.g. VT265, incl. Glomus constrictum, Glomus coronatum, G. mosseae) appeared in clades unrelated to sequences from cultures of the same species (G. constrictum VT64 and G. mosseae VT67; Fig. S2). An even more striking example is the appearance of sequences named as Glomus viscosum in different families: Glomus A (VT63, incl. BEG126, EEZ34) and B clades (VT193, incl. BEG27). The unresolved taxonomy of the Glomus intraradices species group (Stockinger et al., 2009) is manifested here as sequences named as G. intraradices being present in three VT: VT105 (isolates IMA6, BEG123); VT114 (DAOM197198, the isolate for which the genome is being sequenced (Martin et al., 2008; Stockinger et al., 2009), EEZ1); and VT115 (GINCO 4695rac-11G2). Unresolved taxonomy may also be a reason for multiple species grouping in VT193 which currently includes Glomus claroideum, Glomus etunicatum, Glomus lamellosum, Glomus luteum and


235

New Phytologist

236 Research

G. viscosum. Some of these species have been suggested to be synonymous (Walker & Vestberg, 1998). Insufficient sequence variation to enable distinction of morphospecies is apparent within Ambisporaceae, Diversisporaceae and Gigasporaceae (Table S1, Fig. S2), including two of the geographically most widespread VT: Gigaspora VT39 (incl. G. albida, G. decipiens, G. gigantea, G. margarita and G. rosea) and Scutellospora VT49 (incl. S. aurigloba and S. dipurpurescens). Inconsistencies between species and VT identification mean that caution must be used when assigning environmental sequences to species or when using named sequences from databases to identify environmental sequences. We can only stress again the importance of single-spore cultures (isolates) of known origin and culture history for providing published reference sequences for Glomeromycota species identification purposes (Gamper et al., 2009). VT distribution patterns The MaarjAM database contains information from the majority of relevant publications (up to April 2010) and reveals a strong bias towards Europe and North America, with other continents severely underrepresented. There is also a shortage of data from particular ecosystems and climatic zones, including temperate forests (despite intensively studied locations in the UK and Estonia), subtropical and tropical grasslands and arid ecosystems. The uneven nature of existing distribution data is not specific to Glomeromycota. For instance, INSD accessions of fungal ITS sequences come mostly from Europe, North America, Japan and China (Ryberg et al., 2009). The world map of Glomeromycota VT richness reflects mostly the distribution of study areas, even when the effect of sample size is removed, as does a map of culture origins of a single species – G. mosseae (Avio et al., 2009). However, the degree of sampling effort means that more detail is apparent within the two best-studied regions, Europe and North America. In particular, areas with comparatively high VT richness are evident in the central Mediterranean region in Europe and the southwest of North America. Both of these areas remained uncovered by ice sheets during recent glaciations and may have acted as refugia for Glomeromycota and associated herbaceous vegetation (Willis, 1996; Adams, 1997; Kaltenrieder et al., 2009). We found VT to have restricted distribution ranges at biogeographical scales reflecting climatic zones and historical and current continental limits: approximately two-thirds of VT occurred in only one climatic zone or continent. This result cannot be attributed to the effect of a small or biased sample size, because in fact the number of continentor climatic zone-specific records is reasonably large (Table 3). The observed pattern gives support to the notion of Morton et al. (1995) that an important causal factor


underlying present-day Glomeromycota species distributions is dispersal over geological time and, correspondingly, that local diversity has a strong historical component. The MaarjAM data also indicate that the distribution of VT differs among ecosystems and habitats, confirming earlier findings that AM fungal communities vary according to ¨ pik et al., local environmental conditions (Fitter, 2005; O 2006; Chaudhary et al., 2008; Dumbrell et al., 2010). The species richness of macroorganisms generally decreases in regions closer to the poles (Hillebrand, 2004). While there is some evidence that taxon co-occurrence patterns in microorganisms may reflect those in macroorganisms (Horner-Devine et al., 2007), information about microorganism richness along the latitudinal gradient is scarce (Martiny et al., 2006; Chaudhary et al., 2008). Interestingly, Tedersoo & Nara (2010) recorded the opposite trend to that observed in macroorganisms – a decline in ectomycorrhizal fungal diversity towards the equator. However, the data in MaarjAM did not reveal a significant relationship between latitude and diversity among Glomeromycota, even though comparable sampling intensity would reveal a small but significant latitudinal effect in plants. Similarly, soil bacteria have been shown to exhibit no clear latitudinal richness gradient (Fuhrman, 2009). We also detected no trend in VT richness in relation to altitude. Seemingly, even more data may be required to reveal potentially subtle or complex relationships between environmental gradients and Glomeromycota richness. Host plant specificity Although AM fungi were not originally regarded as host-specific, recent studies have provided evidence of host specificity or preference (Fitter, 2005; Smith & Read, 2008). The MaarjAM data show VT to be unevenly distributed among angiosperm superorders: only a few VT occur in the roots of all three superorders with the largest number of records in MaarjAM, but these VT are represented by high numbers of records and predominantly have wide geographical ranges. At the same time, a considerable number of VT have been recorded in the roots of only one of the three plant superorders considered, and these taxa tend to have a narrow geographical range. This pattern further supports earlier findings that widely distributed AM fungi tend to associate with a wide range of host plants, including generalist plant species, while less common AM fungi associate with host plant species with narrower ecological (and correspondingly ¨ pik et al., 2009). also geographical) ranges (O Conclusions The MaarjAM sequence database provides a reference dataset for the identification of Glomeromycota (AM fungi) and stores available information about their geographical


New Phytologist distribution, occurrence in different habitats and climatic regions, and host plant association. Currently available data, although biased towards certain geographical areas and ecosystems, allow conclusions about the biogeography and ecology of these fungi to be drawn. Emerging patterns – including the uneven distribution of Glomeromycota among continents, climatic zones and ecosystems, or the tendency of fungi with a wide geographical distribution to associate with a wide taxonomic range of host plants – can serve as a basis to generate testable hypotheses for future study. The data in MaarjAM also indicate a wide gap between DNA sequence-based and traditional morphotaxonomy of Glomeromycota. In order to bridge this gap, which is a basic aspect inhibiting our understanding of biodiversity patterns in these fungi, more effort is needed in publishing sequences of selected marker regions of a phylogenetically wide range of Glomeromycota isolates of known origin and with a known culture history. Finally, the empty areas on the distribution maps (Figs 3, 4) indicate that there remains a need for more sequence data from South America, Africa, Asia and Australia, and Table 3 highlights the need for data from major biomes such as temperate forests, subtropical and tropical grasslands and arid ecosystems.

Acknowledgements The project was supported by Estonian Science Foundation grants 7371, 7366, 7738, SF0180098s08, EU FP6 Integrated Project EcoChange, a Marie Curie European Reintegration Grant within the 7th European Community Framework Programme (GLOBAM, PERG03-GA-2008¨ .) and by the European Regional Development 231034, to M.O Fund (Centre of Excellence FIBIR). We thank the editor and three anonymous referees for constructive criticism on the manuscript.

References Abarenkov K, Nilsson RH, Larsson KH, Alexander IJ, Eberhardt U, Erland S, Hoiland K, Kjøller R, Larsson E, Pennanen T et al. 2010. The UNITE database for molecular identification of fungi – recent updates and future perspectives. New Phytologist 186: 281–285. Adams JM. 1997. Global land environments since the last interglacial. TN, USA: Oak Ridge National Laboratory. http://www.esd.ornl.gov/ern/ qen/nerc.html Alguacil MM, Diaz-Pereira E, Caravaca F, Fernandez DA, Roldań A. 2009a. Increased diversity of arbuscular mycorrhizal fungi in a longterm field experiment via application of organic amendments to a semiarid degraded soil. Applied and Environmental Microbiology 75: 4254–4263. Alguacil MM, Lumini E, Roldań A, Salinas-Garcıá JR, Bonfante P, Bianciotto V. 2008. The impact of tillage practices on arbuscular mycorrhizal fungal diversity in subtropical crops. Ecological Applications 18: 527–536. Alguacil MM, Roldań A, Torres MP. 2009a. Assessing the diversity of AM fungi in arid gypsophilous plant communities. Environmental Microbiology 11: 2649–2659.


Research Alguacil MM, Roldań A, Torres MP. 2009b. Complexity of semiarid gypsophilous shrub communities mediates the AMF biodiversity at the plant species level. Microbial Ecology 57: 718–727. Appelhans M, Weber HC, Imhof S. 2008. Rutaceae sampled from Germany, Malta, and Mallorca (Spain) are associated with AMF clustering with Glomus hoi Berch & Trappe. Mycorrhiza 18: 263–268. Avio L, Cristani C, Strani P, Giovannetti M. 2009. Genetic and phenotypic diversity of geographically different isolates of Glomus mosseae. Canadian Journal of Microbiology 55: 242–253. Barraclough TG, Hughes M, Ashford-Hodges N, Fujisawa T. 2009. Inferring evolutionarily significant units of bacterial diversity from broad environmental surveys of single-locus data. Biology Letters 5: 425–428. Beck A, Haug I, Oberwinkler F, Kottke I. 2007. Structural characterization and molecular identification of arbuscular mycorrhiza morphotypes of Alzatea verticillata (Alzateaceae), a prominent tree in the tropical mountain rain forest of South Ecuador. Mycorrhiza 17: 607– 625. Bidartondo MI, Redecker D, Hijri I, Wiemken A, Bruns TD, Dominguez L, Se´rsic A, Leake JR, Read DJ. 2002. Epiparasitic plants specialized on arbuscular mycorrhizal fungi. Nature 419: 389–392. Bidartondo MI, Bruns TD, Blackwell M, Edwards I, Taylor AFS, Horton T, Zhang N, Ko˜ljalg U, May G, Kuyper TW et al. 2008. Preserving accuracy in GenBank. Science 319: 1616. Błaszkowski J, Czerniawska B, Wubet T, Schaefer T, Buscot F, Renker C. 2008. Glomus irregulare, a new arbuscular mycorrhizal fungus in the Glomeromycota. Mycotaxon 106: 247–267. Błaszkowski J, Kovaćs GM, Bala´zs T. 2009. Glomus perpusillum, a new arbuscular mycorrhizal fungus. Mycologia 101: 247–255. Bremer B, Bremer K, Chase MW, Fay MF, Reveal JL, Soltis DE, Soltis PS, Stevens PF, Anderberg AA, Moore MJ et al. 2009. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG III. Botanical Journal of the Linnean Society 161: 105–121. Bridge PD, Roberts PJ, Spooner BM, Panchal G. 2003. On the unreliability of published DNA sequences. New Phytologist 160: 43–48. Brock PM, Do¨ring H, Bidartondo MI. 2009. How to know unknown fungi: the role of a herbarium. New Phytologist 181: 719–724. Bueé M, Reich M, Murat C, Morin E, Nilsson RH, Uroz S, Martin F. 2009. 454 pyrosequencing analyses of forest soils reveal an unexpectedly high fungal diversity. New Phytologist 184: 449–456. Burke DJ. 2008. Effects of Alliaria petiolata (garlic mustard; Brassicaceae) on mycorrhizal colonization and community structure in three herbaceous plants in a mixed deciduous forest. American Journal of Botany 95: 1416–1425. Calvente R, Cano C, Ferrol N, Azcoń-Aguilar C, Barea JM. 2004. Analysing natural diversity of arbuscular mycorrhizal fungi in olive tree (Olea europaea L.) plantations and assessment of the effectiveness of native fungal isolates as inoculants for commercial cultivars of olive plantlets. Applied Soil Ecology 26: 11–19. Chase MW, Reveal JL. 2009. A phylogenetic classification of the land plants to accompany APG III. Botanical Journal of the Linnean Society 161: 122–127. Chaudhary VB, Lau MK, Johnson NC. 2008. Macroecology of microbes – biogeography of the Glomeromycota. In: Varma A, ed. Mycorrhiza. Berlin, Germany: Springer, 529–562. Clamp M, Cuff J, Searle SM, Barton GJ. 2004. The Jalview Java alignment editor. Bioinformatics 20: 426–427. Colwell RK. 2006. EstimateS: statistical estimation of species richness and shared species from samples. Version 8.0. User’s Guide and application. http://viceroy.eeb.uconn.edu/EstimateS. Daniell TJ, Husband R, Fitter AH, Young JPW. 2001. Molecular diversity of arbuscular mycorrhizal fungi colonising arable crops. FEMS Microbiology Ecology 36: 203–209.


237

238 Research de Souza FA, Kowalchuk GA, Leeflang P, van Veen JA, Smit E. 2004. PCR-denaturing gradient gel electrophoresis profiling of inter- and intraspecies 18S rRNA gene sequence heterogeneity is an accurate and sensitive method to assess species diversity of arbuscular mycorrhizal fungi of the genus Gigaspora. Applied and Environmental Microbiology 70: 1413–1424. DeBellis T, Widden P. 2006. Diversity of the small subunit ribosomal RNA gene of the arbuscular mycorrhizal fungi colonizing Clintonia borealis from a mixed-wood boreal forest. FEMS Microbiology Ecology 58: 225–235. Declerck S, Cranenbrouck S, Dalpe´ Y, Se´guin S, Grandmougin-Ferjani A, Fontaine J, Sancholle M. 2000. Glomus proliferum sp. nov.: a description based on morphological, biochemical, molecular and monoxenic cultivation data. Mycologia 92: 1178–1187. Douhan GW, Petersen C, Bledsoe CS, Rizzo DM. 2005. Contrasting root associated fungi of three common oak-woodland plant species based on molecular identification: host specificity or non-specific amplification? Mycorrhiza 15: 365–372. Drummond AJ, Rambaut A. 2007. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology 7: 214. Dumbrell AJ, Nelson M, Helgason T, Dytham C, Fitter AH. 2010. Idiosyncrasy and overdominance in the structure of natural communities of arbuscular mycorrhizal fungi: Is there a role for stochastic processes? Journal of Ecology 98: 419–428. ESRI. 2006. ArcGIS 9.2. Redlands, CA, USA: Environmental Research Institute. Ferrol N, Calvente R, Cano C, Barea JM, Azcoń-Aguilar C. 2004. Analysing arbuscular mycorrhizal fungal diversity in shrub-associated resource islands from a desertification-threatened semiarid Mediterranean ecosystem. Applied Soil Ecology 25: 123–133. Fitter AH. 2005. Darkness visible: reflections on underground ecology. Journal of Ecology 93: 231–243. Franke T, Beenken L, Doring M, Kocyan A, Agerer R. 2006. Arbuscular mycorrhizal fungi of the Glomus-group A lineage (Glomerales; Glomeromycota) detected in myco-heterotrophic plants from tropical Africa. Mycological Progress 5: 24–31. Fuhrman JA. 2009. Microbial community structure and its functional implications. Nature 459: 193–199. Gamper HA, Walker C, Schu¨ßler A. 2009. Diversispora celata sp. nov: molecular ecology and phylotaxonomy of an inconspicuous arbuscular mycorrhizal fungus. New Phytologist 182: 495–506. Gehrig H, Schu¨ßler A, Kluge M. 1996. Geosiphon pyriforme, a fungus forming endocytobiosis with Nostoc (Cyanobacteria), is an ancestral member of the Glomales: evidence by SSU rRNA analysis. Journal of Molecular Evolution 43: 71–81. Haug I, Lempe J, Homeier J, Weiß M, Setaro S, Oberwinkler F, Kottke I. 2004. Graffenrieda emarginata (Melastomataceae) forms mycorrhizas with Glomeromycota and with a member of the Hymenoscyphus ericae aggregate in the organic soil of a neotropical mountain rain forest. Canadian Journal of Botany 82: 340–356. Hausmann NT, Hawkes CV. 2009. Plant neighborhood control of arbuscular mycorrhizal community composition. New Phytologist 183: 1188–1200. van der Heijden MGA, Bardgett RD, van Straalen NM. 2008. The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecology Letters 11: 296–310. Heinemeyer A, Ridgway KP, Edwards EJ, Benham DG, Young JPW, Fitter AH. 2004. Impact of soil warming and shading on colonization and community structure of arbuscular mycorrhizal fungi in roots of a native grassland community. Global Change Biology 10: 52–64. Helgason T, Daniell TJ, Husband R, Fitter AH, Young JPW. 1998. Ploughing up the wood-wide web? Nature 394: 431.


New Phytologist Helgason T, Fitter AH, Young JPW. 1999. Molecular diversity of arbuscular mycorrhizal fungi colonising Hyacinthoides non-scripta (bluebell) in a seminatural woodland. Molecular Ecology 8: 659–666. Helgason T, Merryweather JW, Denison J, Wilson P, Young JPW, Fitter AH. 2002. Selectivity and functional diversity in arbuscular mycorrhizas of co-occurring fungi and plants from a temperate deciduous woodland. Journal of Ecology 90: 371–384. Helgason T, Merryweather JW, Young JP, Fitter AH. 2007. Specificity and resilience in the arbuscular mycorrhizal fungi of a natural woodland community. Journal of Ecology 95: 623–630. Helgason T, Watson IJ, Young JP. 2003. Phylogeny of the Glomerales and Diversisporales (Fungi: Glomeromycota) from actin and elongation factor 1-alpha sequences. FEMS Microbiology Letters 229: 127–132. Hibbett DS, Ohman A, Kirk PM. 2009. Fungal ecology catches fire. New Phytologist 184: 279–282. Hillebrand H. 2004. On the generality of the latitudinal diversity gradient. American Naturalist 163: 192–211. Holdridge L. 1967. Life zone ecology. San Jose, Costa Rica: Tropical Science Center. Horner-Devine MC, Silver JM, Leibold MA, Bohannan BJM, Colwell RK, Fuhrman JA, Green JL, Kuske CR, Martiny JBH, Muyzer G et al. 2007. A comparison of taxon co-occurrence patterns for macro- and microorganisms. Ecology 88: 1345–1353. Horton TR, Arnold AE, Bruns TD. 2009. FESIN workshops at ESA – the mycelial network grows. Mycorrhiza 19: 283–285. Husband R, Herre EA, Turner SL, Gallery R, Young JPW. 2002a. Molecular diversity of arbuscular mycorrhizal fungi and patterns of host association over time and space in a tropical forest. Molecular Ecology 11: 2669–2678. Husband R, Herre EA, Young JPW. 2002b. Temporal variation in the arbuscular mycorrhizal communities colonising seedlings in a tropical forest. FEMS Microbiology Ecology 42: 131–136. Ipsilantis I, Karpouzas DG, Papadopoulou KK, Ehaliotis C. 2009. Effects of soil application of olive mill wastewaters on the structure and function of the community of arbuscular mycorrhizal fungi. Soil Biology & Biochemistry 41: 2466–2476. James TY, Kauff F, Schoch CL, Matheny PB, Hofstetter V, Cox CJ, Celio G, Gueidan C, Fraker E, Miadlikowska J et al. 2006. Reconstructing the early evolution of Fungi using a six-gene phylogeny. Nature 443: 818–822. Jumpponen A, Townbridge J, Mandyam K, Johnson L. 2005. Nitrogen enrichment causes minimal changes in arbuscular mycorrhizal colonization but shifts community composition – evidence from rDNA data. Biology and Fertility of Soils 41: 217–224. Kaltenrieder P, Belis CA, Hofstetter S, Ammann B, Ravazzi C, Tinner W. 2009. Environmental and climatic conditions at a potential Glacial refugial site of tree species near the Southern Alpine glaciers. New insights from multiproxy sedimentary studies at Lago della Costa (Euganean Hills, Northeastern Italy). Quaternary Science Reviews 28: 2647–2662. Kier G, Mutke J, Dinerstein E, Ricketts TH, Kuper W, Kreft H, Barthlott W. 2005. Global patterns of plant diversity and floristic knowledge. Journal of Biogeography 32: 1107–1116. Ko˜ljalg U, Larsson KH, Abarenkov K, Nilsson RH, Alexander IJ, Eberhardt U, Erland S, Hoiland K, Kjøller R, Larsson E et al. 2005. UNITE: a database providing web-based methods for the molecular identification of ectomycorrhizal fungi. New Phytologist 166: 1063–1068. Kottke I, Haug I, Setaro S, Sua´rez JP, Weiß M, Preußing M, Nebel M, Oberwinkler F. 2008. Guilds of mycorrhizal fungi and their relation to trees, ericads, orchids and liverworts in a neotropical mountain rain forest. Basic and Applied Ecology 9: 13–23. Kovaćs GM, Bala´zs T, Peńzes Z. 2007. Molecular study of arbuscular mycorrhizal fungi colonizing the sporophyte of the eusporangiate


New Phytologist rattlesnake fern (Botrychium virginianum, Ophioglossaceae). Mycorrhiza 17: 597–605. Kowalchuk GA, de Souza FA, van Veen JA. 2002. Community analysis of arbuscular mycorrhizal fungi associated with Ammophila arenaria in Dutch coastal sand dunes. Molecular Ecology 11: 571–581. Kramadibrata K, Walker C, Schwarzott D, Schu¨ßler A. 2000. A new species of Scutellospora with a coiled germination shield. Annals of Botany 86: 21–27. Kru¨ger M, Stockinger H, Kru¨ger C, Schu¨ßler A. 2009. DNA-based species level detection of Glomeromycota: one PCR primer set for all arbuscular mycorrhizal fungi. New Phytologist 183: 212–223. Le Calvez T, Burgaud G, Mahe S, Barbier G, Vandenkoornhuyse P. 2009. Fungal diversity in deep-sea hydrothermal ecosystems. Applied and Environmental Microbiology 75: 6415–6421. Lee J, Lee S, Young JPW. 2008. Improved PCR primers for the detection and identification of arbuscular mycorrhizal fungi. FEMS Microbiology Ecology 65: 339–349. Legendre P, Legendre L. 1998. Numerical ecology. Amsterdam, the Netherlands: Elsevier. Lesaulnier C, Papamichail D, McCorkle S, Ollivier B, Skiena S, Taghavi S, Zak D, van der Lelie D. 2008. Elevated atmospheric CO2 affects soil microbial diversity associated with trembling aspen. Environmental Microbiology 10: 926–941. Liang ZB, Drijber RA, Lee DJ, Dwiekat IM, Harris SD, Wedin DA. 2008. A DGGE-cloning method to characterize arbuscular mycorrhizal community structure in soil. Soil Biology & Biochemistry 40: 956–966. Ligrone R, Carafa A, Lumini E, Bianciotto V, Bonfante P, Duckett JG. 2007. Glomeromycotean associations in liverworts: a molecular cellular and taxonomic analysis. American Journal of Botany 94: 1756–1777. Likar M, Bukovnik U, Kreft I, Chrungoo NK, Regvar M. 2008. Mycorrhizal status and diversity of fungal endophytes in roots of common buckwheat (Fagopyrum esculentum) and tartary buckwheat (F. tataricum). Mycorrhiza 18: 309–315. Liu Y, He L, An LZ, Helgason T, Feng HY. 2009. Arbuscular mycorrhizal dynamics in a chronosequence of Caragana korshinskii plantations. FEMS Microbiology Ecology 67: 81–92. Ludwig W, Strunk O, Westram R, Richter L, Meier H, Kumar Y, Buchner A, Lai T, Steppi S, Jobb G et al. 2004. ARB: a software environment for sequence data. Nucleic Acids Research 32: 1363–1371. Ma WK, Siciliano SD, Germida JJ. 2005. A PCR-DGGE method for detecting arbuscular mycorrhizal fungi in cultivated soils. Soil Biology and Biochemistry 37: 1589–1597. Maki T, Nomachi M, Yoshida S, Ezawa T. 2008. Plant symbiotic microorganisms in acid sulfate soil: significance in the growth of pioneer plants. Plant and Soil 310: 55–65. Martin F, Gianinazzi-Pearson V, Hijri M, Lammers P, Requena N, Sanders IR, Shachar-Hill Y, Shapiro H, Tuskan GA, Young JPW. 2008. The long hard road to a completed Glomus intraradices genome. New Phytologist 180: 747–750. Martin NF, Martin F. 2010. From Galactic archeology to soil metagenomics – surfing on massive data streams. New Phytologist 185: 343–348. Martiny JBH, Bohannan BJM, Brown JH, Colwell RK, Fuhrman JA, Green JL, Horner-Devine MC, Kane M, Krumins JA, Kuske CR et al. 2006. Microbial biogeography: putting microorganisms on the map. Nature Reviews Microbiology 4: 102–112. Martynova-Van Kley A, Wang HL, Nalian A, Van Kley J. 2006. Detection of arbuscular mycorrhizal fungi in an east Texas forest by analysis of SSU rRNA gene sequence. Texas Journal of Science 58: 231– 242. McNaughton SJ, Oesterheld M, Frank DA, Williams KJ. 1989. Ecosystem-level patterns of primary productivity and herbivory in terrestrial habitats. Nature 341: 142–144.


Research Merckx V, Bidartondo MI. 2008. Breakdown and delayed cospeciation in the arbuscular mycorrhizal mutualism. Proceedings of the Royal Society BBiological Sciences 275: 1029–1035. Milne I, Wright F, Rowe G, Marshal DF, Husmeier D, McGuire G. 2004. TOPALi: software for automatic identification of recombinant sequences within DNA multiple alignments. Bioinformatics 20: 1806–1807. Morton JB, Bentivenga SP, Bever JD. 1995. Discovery, measurement, and interpretation of diversity in arbuscular endomycorrhizal fungi (Glomales, Zygomycetes). Canadian Journal of Botany 73: S25–S32. Nilsson RH, Kristiansson E, Ryberg M, Hallenberg N, Larsson KH. 2008. Intraspecific ITS variability in the kingdom fungi as expressed in the international sequence databases and its implications for molecular species identification. Evolutionary Bioinformatics 4: 193–201. Nilsson RH, Ryberg M, Abarenkov K, Sjo¨kvist E, Kristiansson E. 2009. The ITS region as a target for characterization of fungal communities using emerging sequencing technologies. FEMS Microbiology Letters 296: 97–101. Oba H, Shinozaki N, Oyaizu H, Tawaraya K, Wagatsuma T, Barraquio WL, Saito M. 2004. Arbuscular mycorrhizal fungal communities associated with some pioneer plants in the Lahar area of Mt. Pinatubo, Philippines. Soil Science and Plant Nutrition 50: 1195– 1203. O’Brien HE, Parrent JL, Jackson JA, Moncalvo JM, Vilgalys R. 2005. Fungal community analysis by large-scale sequencing of environmental samples. Applied and Environmental Microbiology 71: 5544–5550. Olson DM, Dinerstein E, Wikramanayake ED, Burgess ND, Powell GVN, Underwood EC, D’Amico JA, Itoua I, Strand HE, Morrison JC et al. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. BioScience 51: 933–938. ¨ pik M, Metsis M, Daniell TJ, Zobel M, Moora M. 2009. Large-scale O parallel 454 sequencing reveals host ecological group specificity of arbuscular mycorrhizal fungi in a boreonemoral forest. New Phytologist 184: 424–437. ¨ pik M, Moora M, Liira J, Ko˜ljalg U, Zobel M, Sen R. 2003. Divergent O arbuscular mycorrhizal fungal communities colonize roots of Pulsatilla spp. in boreal Scots pine forest and grassland soils. New Phytologist 160: 581–593. ¨ pik M, Moora M, Liira J, Zobel M. 2006. Composition of rootO colonizing arbuscular mycorrhizal fungal communities in different ecosystems around the globe. Journal of Ecology 94: 778–790. ¨ pik M, Moora M, Zobel M, Saks U ¨ , Wheatley R, Wright F, Daniell T. O 2008. High diversity of arbuscular mycorrhizal fungi in a boreal herbrich coniferous forest. New Phytologist 179: 867–876. Palenzuela J, Ferrol N, Boller T, Azcoń-Aguilar C, Oehl F. 2008. Otospora bareai, a new fungal species in the Glomeromycetes from a dolomitic shrub land in Sierra de Baza National Park (Granada, Spain). Mycologia 100: 296–305. de la Penã E, Rodrı´guez-Echeverrıá S, van der Putten WH, Freitas H, Moens M. 2006. Mechanism of control of root-feeding nematodes by mycorrhizal fungi in the dune grass Ammophila arenaria. New Phytologist 169: 829–840. Pons J, Barraclough TG, Gomez-Zurita J, Cardoso A, Duran DP, Hazell S, Kamoun S, Sumlin WD, Vogler AP. 2006. Sequence-based species delimitation for the DNA taxonomy of undescribed insects. Systematic Biology 55: 595–609. Porras-Alfaro A, Herrera J, Natvig DO, Sinsabaugh R. 2007. Effect of long-term nitrogen fertilization on mycorrhizal fungi associated with a dominant grass in a semiarid grassland. Plant and Soil 296: 65–75. Posada D. 2008. jModelTest: phylogenetic model averaging. Molecular Biology and Evolution 25: 1253–1256. Redecker D, Morton JB, Bruns TD. 2000a. Ancestral lineages of arbuscular mycorrhizal fungi (Glomales). Molecular Phylogenetics and Evolution 14: 276–284.


239

240 Research Redecker D, Morton JB, Bruns TD. 2000b. Molecular phylogeny of the arbuscular mycorrhizal fungi Glomus sinuosum and Sclerocystis coremioides. Mycologia 92: 282–285. Redecker D, Raab P, Oehl F, Camacho F, Courtecuisse R. 2007. A novel clade of sporocarp-forming species of glomeromycotan fungi in the Diversisporales lineage. Mycological Progress 6: 35–44. Regvar M, Vogel K, Irgel N, Wraber T, Hildebrandt U, Wilde P, Bothe H. 2003. Colonization of pennycresses (Thlaspi spp.) of the Brassicaceae by arbuscular mycorrhizal fungi. Journal of Plant Physiology 160: 615–626. Renker C, Błaszkowski J, Buscot F. 2007. Paraglomus laccatum comb. nov. – a new member of Paraglomeraceae (Glomeromycota). Nova Hedwigia 84: 395–407. Rodrı´guez-Echeverrıá S, Freitas H. 2006. Diversity of AMF associated with Ammophila arenaria ssp. arundinacea in Portuguese sand dunes. Mycorrhiza 16: 543–552. Rosendahl S. 2008. Communities, populations and individuals of arbuscular mycorrhizal fungi. New Phytologist 178: 253–266. Rowe AR, Pringle A. 2005. Morphological and molecular evidence of arbuscular mycorrhizal fungal associations in Costa Rican epiphytic bromeliads. Biotropica 37: 245–250. Russell J, Bulman S. 2005. The liverwort Marchantia foliacea forms a specialized symbiosis with arbuscular mycorrhizal fungi in the genus Glomus. New Phytologist 165: 567–579. Ryberg M, Kristiansson E, Sjo¨kvist E, Nilsson RH. 2009. An outlook on the fungal internal transcribed spacer sequences in GenBank and the introduction of a web-based tool for the exploration of fungal diversity. New Phytologist 181: 471–477. Ryberg M, Nilsson RH, Kristiansson E, Topel M, Jacobsson S, Larsson E. 2008. Mining metadata from unidentified ITS sequences in GenBank: a case study in Inocybe (Basidiomycota). BMC Evolutionary Biology 8: 50. Saito K, Suyama Y, Sato S, Sugawara K. 2004. Defoliation effects on the community structure of arbuscular mycorrhizal fungi based on 18S rDNA sequences. Mycorrhiza 14: 363–373. Santos JC, Finlay RD, Tehler A. 2006. Molecular analysis of arbuscular mycorrhizal fungi colonising a semi-natural grassland along a fertilisation gradient. New Phytologist 172: 159–168. Santos-Gonza´lez JC, Finlay RD, Tehler A. 2007. Seasonal dynamics of arbuscular mycorrhizal fungal communities in roots in a seminatural grassland. Applied and Environmental Microbiology 73: 5613–5623. Sato K, Suyama Y, Saito M, Sugawara K. 2005. A new primer for discrimination of arbuscular mycorrhizal fungi with polymerase chain reaction-denature gradient gel electrophoresis. Grassland Science 51: 179–181. Sawaki H, Sugawara K, Saito M. 1998. Phylogenetic position of an arbuscular mycorrhizal fungus, Acaulospora gerdemannii, and its synanamorph Glomus leptotichum, based upon 18S rRNA gene sequence. Mycoscience 39: 477–480. Schechter SP, Bruns TD. 2008. Serpentine and non-serpentine ecotypes of Collinsia sparsiflora associate with distinct arbuscular mycorrhizal fungal assemblages. Molecular Ecology 13: 3198–3210. Scheublin TR, Ridgway KP, Young JPW, van der Heijden MGA. 2004. Nonlegumes, legumes, and root nodules harbor different arbuscular mycorrhizal fungal communities. Applied and Environmental Microbiology 70: 6240–6246. Schreiner RP, Mihara KL. 2009. The diversity of arbuscular mycorrhizal fungi amplified from grapevine roots (Vitis vinifera L.) in Oregon vineyards is seasonally stable and influenced by soil and vine age. Mycologia 101: 599–611. Schu¨ßler A, Gehrig H, Schwarzott D, Walker C. 2001a. Analysis of partial Glomales SSU rRNA gene sequences: implications for primer design and phylogeny. Mycological Research 105: 5–15.


New Phytologist Schu¨ßler A, Schwarzott D, Walker C. 2001b. A new fungal phylum, the Glomeromycota: phylogeny and evolution. Mycological Research 105: 1413–1421. Schwarzott D, Walker C, Schu¨ßler A. 2001. Glomus, the largest genus of the arbuscular mycorrhizal fungi (Glomales), is nonmonophyletic. Molecular Phylogenetics and Evolution 21: 190–197. Scotese CR. 2004. A continental drift flipbook. Journal of Geology 112: 729–741. Simon L. 1996. Phylogeny of the Glomales: deciphering the past to understand the present. New Phytologist 133: 95–101. Simon L, Bousquet J, Le´vesque CA, Lalonde M. 1993a. Origin and diversification of endomycorrhizal fungi and coincidence with vascular land plants. Nature 363: 67–69. Simon L, Lalonde M, Bruns TD. 1992. Specific amplification of 18S fungal ribosomal genes from VA endomycorrhizal fungi colonizing roots. Applied and Environmental Microbiology 58: 291–295. Simon L, Le´vesque RC, Lalonde M. 1993b. Identification of endomycorrhizal fungi colonizing roots by fluorescent single-strand conformation polymorphism-polymerase chain reaction. Applied and Environmental Microbiology 59: 4211–4215. Smith SE, Read DJ. 2008. Mycorrhizal symbiosis. Amsterdam, the Netherlands: Academic Press. Sonjak S, Beguiristain T, Leyval C, Regvar M. 2009a. Temporal temperature gradient gel electrophoresis (TTGE) analysis of arbuscular mycorrhizal fungi associated with selected plants from saline and metal polluted environments. Plant and Soil 314: 25–34. Sonjak S, Udovicˇ M, Wraber T, Likar M, Regvar M. 2009b. Diversity of halophytes and identification of arbuscular mycorrhizal fungi colonising their roots in an abandoned and sustained part of Secovlje salterns. Soil Biology & Biochemistry 41: 1847–1856. de Souza FA, Declerck S, Smit E, Kowalchuk GA. 2005. Morphological, ontogenetic and molecular characterization of Scutellospora reticulata (Glomeromycota). Mycological Research 109: 697–706. Stockinger H, Walker C, Schu¨ßler A. 2009. ‘Glomus intraradices DAOM197198’, a model fungus in arbuscular mycorrhiza research, is not Glomus intraradices. New Phytologist 183: 1176–1187. Tedersoo L, Nara K. 2010. General latitudinal gradient of biodiversity is reversed in ectomycorrhizal fungi. New Phytologist 185: 351–354. Toljander JF, Santos-Gonza´lez JC, Tehler A, Finlay RD. 2008. Community analysis of arbuscular mycorrhizal fungi and bacteria in the maize mycorrhizosphere in a long-term fertilization trial. FEMS Microbiology Ecology 65: 323–328. Turrini A, Avio L, Bedini S, Giovannetti M. 2008. In situ collection of endangered arbuscular mychorrhizal fungi in a Mediterranean UNESCO Biosphere Reserve. Biodiversity and Conservation 17: 643– 657. Vallino M, Massa N, Lumini E, Bianciotto V, Berta G, Bonfante P. 2006. Assessment of arbuscular mycorrhizal fungal diversity in roots of Solidago gigantea growing in a polluted soil in Northern Italy. Environmental Microbiology 8: 971–983. Vandenkoornhuyse P, Baldauf SL, Leyval C, Straczek J, Young JPW. 2002a. Extensive fungal diversity in plant roots. Science 295: 2051. Vandenkoornhuyse P, Husband R, Daniell TJ, Watson IJ, Duck JM, Fitter AH, Young JPW. 2002b. Arbuscular mycorrhizal community composition associated with two plant species in a grassland ecosystem. Molecular Ecology 11: 1555–1564. Vandenkoornhuyse P, Leyval C. 1998. SSU rDNA sequencing and PCRfingerprinting reveal genetic variation within Glomus mosseae. Mycologia 90: 791–797. Vandenkoornhuyse P, Mahe S, Ineson P, Staddon P, Ostle N, Cliquet JB, Francez AJ, Fitter AH, Young JP. 2007. Active root-inhabiting microbes identified by rapid incorporation of plant-derived carbon into RNA. Proceedings of the National Academy of Sciences, USA 104: 16970– 16975.


New Phytologist Vandenkoornhuyse P, Ridgway KP, Watson IJ, Fitter AH, Young JPW. 2003. Co-existing grass species have distinctive arbuscular mycorrhizal communities. Molecular Ecology 12: 3085–3095. Walker C, Błaszkowski J, Schwarzott D, Schu¨ßler A. 2004. Gerdemannia gen. nov., a genus separated from Glomus, and Gerdemanniaceae fam. nov., a new family in the Glomeromycota. Mycological Research 108: 707–718. Walker C, Vestberg M. 1998. Synonymy amongst the arbuscular mycorrhizal fungi: Glomus claroideum, G. maculosum, G. multisubstenum and G. fistulosum. Annals of Botany 82: 601–624. Walker C, Vestberg M, Demircik F, Stockinger H, Saito M, Sawaki H, Nishmura I, Schu¨ßler A. 2007. Molecular phylogeny and new taxa in the Archaeosporales (Glomeromycota): Ambispora fennica gen. sp. nov., Ambisporaceae fam. nov., and emendation of Archaeospora and Archaeosporaceae. Mycological Research 111: 137–153. Walter H. 1994. Vegetation of the earth. Berlin, Germany: Springer. West B, Brandt J, Holstien K, Hill A, Hill M. 2009. Fern-associated arbuscular mycorrhizal fungi are represented by multiple Glomus spp.: do environmental factors influence partner identity? Mycorrhiza 19: 295–304. Whitfield L, Richards AJ, Rimmer DL. 2004. Relationships between soil heavy metal concentration and mycorrhizal colonisation in Thymus polytrichus in northern England. Mycorrhiza 14: 55–62. Wilde P, Manal A, Stodden M, Sieverding E, Hildebrandt U, Bothe H. 2009. Biodiversity of arbuscular mycorrhizal fungi in roots and soils of two salt marshes. Environmental Microbiology 11: 1548– 1561. Willis KJ. 1996. Where did all the flowers go? The fate of temperate European flora during glacial periods. Endeavour 20: 110–114. Winther JL, Friedman WE. 2007. Arbuscular mycorrhizal symbionts in Botrychium (Ophioglossaceae). American Journal of Botany 94: 1248– 1255. Winther JL, Friedman WE. 2008. Arbuscular mycorrhizal associations in Lycopodiaceae. New Phytologist 177: 790–801. Winther JL, Friedman WE. 2009. Phylogenetic affinity of arbuscular mycorrhizal symbionts in Psilotum nudum. Journal of Plant Research 122: 485–496. Wirsel SGR. 2004. Homogenous stands of a wetland grass harbour diverse consortia of arbuscular mycorrhizal fungi. FEMS Microbiology Ecology 48: 129–138. Wubet T, Weiß M, Kottke I, Oberwinkler F. 2006a. Two threatened coexisting indigenous conifer species in the dry Afromontane forests of Ethiopia are associated with distinct arbuscular mycorrhizal fungal communities. Canadian Journal of Botany-Revue Canadienne de Botanique 84: 1617–1627. Wubet T, Weiß M, Kottke I, Teketay D, Oberwinkler F. 2006b. Phylogenetic analysis of nuclear small subunit rDNA sequences suggests that the endangered African Pencil Cedar, Juniperus procera, is associated


Research with distinct members of Glomeraceae. Mycological Research 110: 1059– 1069. Yamato M, Ikeda S, Iwase K. 2008. Community of arbuscular mycorrhizal fungi in a coastal vegetation on Okinawa island and effect of the isolated fungi on growth of sorghum under salt-treated conditions. Mycorrhiza 18: 1432–1890. Yamato M, Ikeda S, Iwase K. 2009. Community of arbuscular mycorrhizal fungi in drought-resistant plants, Moringa spp., in semiarid regions in Madagascar and Uganda. Mycoscience 50: 100–105. Yamato M, Iwase K. 2005. Community analysis of arbuscular mycorrhizal fungi in a warm-temperate deciduous broad-leaved forest and introduction of the fungal community into the seedlings of indigenous woody plants. Mycoscience 46: 334–342.

Supporting Information Additional supporting information may be found in the online version of this article. Fig. S1 MaarjAM data input principles and procedure. Fig. S2 Maximum clade credibility tree of glomeromycotan virtual taxa (VT) in the MaarjAM database, inferred using Bayesian phylogenetic analysis of small subunit rRNA gene. Methods S1 Categorizing biogeographical data in the MaarjAM database. Methods S2 List of publications that provided data for the MaarjAM database. Table S1 List of glomeromycotan virtual taxa (VT) in the MaarjAM database indicating taxonomic placement, included known species or unidentified cultures and respective culture codes. 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.


241