© iForest -Biogeosciences and Forestry IntroductionEctomycorrhizal (ECM) fungi are obligate plant mutualists and they are among the most functionally important soil organisms in forest ecosystems (Smith & Read 2008). However, as the delimitation and identification of many ECM species is problematic and their life cycles largely subterranean, the geographic ranges for species are unknown. There is a need to establish current distributions in the face of changing environmental conditions, because without them even large changes in mycorrhizal distributions may go undetected.Some ECM fungal species have conspicuous fruiting bodies that can thus be used to generate species distribution maps, e.g., Amanita phalloides (Wolfe et al. 2010). This is often not possible as many ECM species are cryptic and difficult to observe in this fashion, e.g., truffles and resupinate crusts.For these fungi an approach using their mycorrhizas for identification is more practical. DNA sequences of the internal transcribed spacer (ITS) region of the nuclear ribosomal DNA provide a universal genetic marker for fungi. This study makes use of their growing availability in online DNA databases to obtain spatial presence data for ECM species thus far unmapped. Ryberg et al. (2008) studied the strength of GenBank for meta-analysis and identification of ECM fungi with a focus on illustrating the gaps in identification for the genus Inocybe, but they also analysed the location of fungal species from GenBank providing a rough idea of their distribution on a wholecountry basis. This was an early example demonstrating the potential for a DNA sequence method for mycorrhizal mapping. Two recent studies have applied spatial data on fungal presence to generate Species Distribution Models (SDM). Wollan et al. (2008) used herbarium mushroom records to create a fungal SDM for Norway, and Wolfe et al. (2010) gathered mushroom data from Europe to create a powerful predictive SDM for North American Amanita phalloides. The application of MAXENT software shows promising results for niche modelling based on presence-only data (Wollan et al. 2008) which are often the only data available for fungi. Before applying niche modelling software this study sought to test the quality of DNA data and the available environmental layers.Studies by Cox et al. (2010aCox et al. ( , 2010b inferred ECM responses to nitrogen deposition at large geographic scales that differ from those at local scales. Here too the argument was made for using DNA to identify ECM in large-scale spatial analysis, but the problems and methodological incongruences of combining multiple studies were also noted. To enable this new facet of mycorrhizal ecology, Lilleskov & Parrent (2007) called for a unified approach to fungal root sampling. We envision that georeferenced fungal DNA sequence data will continue to accumulate rapidly to eventually reveal fungal species distributions. This study explores what signal indicating the environmental preferences of ECM might be already hidden in the growing onlin...