Explaining the large-scale diversity of soil organisms that drive biogeochemical processes—and their responses to environmental change—is critical. However, identifying consistent drivers of belowground diversity and abundance for some soil organisms at large spatial scales remains problematic. Here we investigate a major guild, the ectomycorrhizal fungi, across European forests at a spatial scale and resolution that is—to our knowledge—unprecedented, to explore key biotic and abiotic predictors of ectomycorrhizal diversity and to identify dominant responses and thresholds for change across complex environmental gradients. We show the effect of 38 host, environment, climate and geographical variables on ectomycorrhizal diversity, and define thresholds of community change for key variables. We quantify host specificity and reveal plasticity in functional traits involved in soil foraging across gradients. We conclude that environmental and host factors explain most of the variation in ectomycorrhizal diversity, that the environmental thresholds used as major ecosystem assessment tools need adjustment and that the importance of belowground specificity and plasticity has previously been underappreciated.

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We acknowledge funding from NERC grant NE/K006339/1 to M.I.B. and C.D.L.O. Analysis was partly based on the ICP Forests PCC Database (http://icp-forests.net). ICP Forests FSCC provided the first level II soil survey data. ICP Forests PCC and observers, technicians and scientists performed long-term sampling, analyses and environmental data handling largely funded by national institutions and ministries, supported by governmental bodies, services and landowners, and partially EU-funded under Regulation (EC) No. 2152/2003 (Forest Focus), project LIFE07ENV/D/000218 (FutMon), and through SWETHRO. Co-financing for D.Ž. and T.G. was provided by P4-0107 (RS Higher Education, Science and Technology Ministry). We thank D. Devey and L. Csiba for laboratory assistance; S. Boersma, F. van der Linde, H. van der Linde, J. van der Linde, C. Gonzales, A. Lenz, R. Lenz, S. Wipf, L. Garfoot, B. Spake, W. Rimington, J. Kowal, T. Solovieva, D. Gane, M. Terrington, J. Alden, A. Otway, V. Kemp, M. Edgar, Y. Lin, A. Drew, E. Booth, P. Cachera, R. De-Kayne, J. Downie, A. Tweedy, E. Moratto, E. Ek, P. Helminen, R. Lievonen, P. Närhi, A. Ryynänen, M. Rupel, J. Draing and F. Heun for field and laboratory work; R. Castilho for bioinformatics; K.-H. Larsson, P.-A. Moreau, J. Nuytinck and M. Ryberg for taxonomy; and N. Barsoum, E. Lilleskov, D. Read and T. Kuyper for discussions throughout.

Reviewer information

Nature thanks A. Dahlberg, P. Kennedy, F. Teste and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Author notes

    • Sietse van der Linde

    Present address: Forest Research, Alice Holt Lodge, Farnham, UK


  1. Life Sciences, Imperial College London, Ascot, UK

    • Sietse van der Linde
    • , C. David L. Orme
    • , Bonnie Atkinson
    • , Christopher Carroll
    • , Yuxin Zhang
    •  & Martin I. Bidartondo
  2. Comparative Plant and Fungal Biology, Royal Botanic Gardens, Kew, London, UK

    • Sietse van der Linde
    • , Laura M. Suz
    • , Bonnie Atkinson
    •  & Martin I. Bidartondo
  3. Earth & Environmental Sciences, University of Manchester, Manchester, UK

    • Filipa Cox
  4. Public Enterprise Sachsenforst, Kompetenzzentrum Wald und Forstwirtschaft, Pirna, Germany

    • Henning Andreae
  5. Estonian Environment Agency, Tallinn, Estonia

    • Endla Asi
  6. Forest Research, Alice Holt Lodge, Farnham, UK

    • Sue Benham
    •  & Elena Vanguelova
  7. Nature and Forest Research Institute, Environment and Climate, Geraardsbergen, Belgium

    • Nathalie Cools
    • , Bruno De Vos
    •  & Arne Verstraeten
  8. Bavarian State Forestry Institute, Freising, Germany

    • Hans-Peter Dietrich
  9. Northwest German Forest Research Institute, Göttingen, Germany

    • Johannes Eichhorn
    •  & Henning Meesenburg
  10. Landesamt für Natur Umwelt und Verbraucherschutz Nordrhein-Westfalen, Recklinghausen, Germany

    • Joachim Gehrmann
  11. Slovenian Forestry Institute, Ljubljana, Slovenia

    • Tine Grebenc
    •  & Daniel Žlindra
  12. Biological Sciences, University of Reading, Reading, UK

    • Hyun S. Gweon
  13. Centre for Ecology & Hydrology, Wallingford, UK

    • Hyun S. Gweon
  14. IVL Swedish Environmental Research Institute, Stockholm, Sweden

    • Karin Hansen
  15. Staatsbetrieb Sachsenforst, Pirna, Germany

    • Frank Jacob
  16. Federal Research and Training Centre for Forests, Natural Hazards and Landscape (BFW), Wien, Austria

    • Ferdinand Kristöfel
  17. Forest Research Institute, Sękocin Stary, Poland

    • Paweł Lech
  18. NARIC Forest Research Institute, Sárvár, Hungary

    • Miklós Manninger
  19. Landesforstanstalt M-V BT: FVI, Schwerin, Germany

    • Jan Martin
  20. Natural Resources Institute Finland, Oulu, Finland

    • Päivi Merilä
  21. Office National des Forêts, Recherche-Développement-Innovation, Fontainebleau, France

    • Manuel Nicolas
  22. National Forest Centre, Zvolen, Slovakia

    • Pavel Pavlenda
  23. Natural Resources Institute Finland, Rovaniemi, Finland

    • Pasi Rautio
  24. WSL Swiss Federal Institute for Forest, Snow and Landscape Research, Birmensdorf, Switzerland

    • Marcus Schaub
    • , Anne Thimonier
    •  & Peter Waldner
  25. Forschungsanstalt für Waldökologie und Forstwirtschaft, Trippstadt, Germany

    • Hans-Werner Schröck
  26. Thünen Institute of Forest Ecosystems, Eberswalde, Germany

    • Walter Seidling
  27. Forestry and Game Management Research Institute, Jíloviště, Czech Republic

    • Vít Šrámek
  28. Department of Geosciences and Natural Resource Management, University of Copenhagen, Frederiksberg, Denmark

    • Iben Margrete Thomsen
    •  & Lars Vesterdal
  29. University of Louvain, Earth and Life Institute, Louvain-la-Neuve, Belgium

    • Hugues Titeux
  30. Swedish Forest Agency, Jönköping, Sweden

    • Sture Wijk


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M.I.B. conceived the study. S.v.d.L., M.I.B., F.C., L.M.S. and B.A. led most sampling design and fieldwork. S.v.d.L., B.A., L.M.S., F.C., Y.Z. and M.I.B. processed and analysed samples. H.A., E.A., S.B., N.C., B.D.V., H.-P.D., J.E., J.G., T.G., K.H., F.J., F.K., P.L., M.M., J.M., H.M., P.M., M.N., P.P., P.R., M.S., H.-W.S., W.S., V.Š., A.T., I.M.T., H.T., E.V., A.V., L.V., P.W., S.W. and D.Ž. assisted with fieldwork and collected, collated and validated long-term environmental data. S.v.d.L., H.S.G. and C.D.L.O. performed bioinformatics. S.v.d.L., C.D.L.O. and L.M.S. performed data analysis. C.C. summarized literature. S.v.d.L. drafted the manuscript, M.I.B. provided chief contributions, and C.D.L.O. and L.M.S. contributed extensively. All authors wrote and reviewed the manuscript. S.v.d.L., L.M.S., C.D.L.O. and M.I.B. led revision of the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Sietse van der Linde.

Extended data figures and tables

  1. Extended Data Fig. 1 Global non-metric multidimensional scaling ordination of community composition.

    Plots shown with host trees: brown squares, beech; blue circles, oak; green triangles, pine; yellow diamonds, spruce. Isoclines depict the forest-floor pH and arrows show the direction and strength of correlation of the most-influential environmental variables according to their R2 values (>0.4). A, MAT; B, mean minimum annual air temperature; C, growing season length; D, NH4 throughfall deposition; E, NTFD.

  2. Extended Data Fig. 2 Threshold indicator taxa analyses.

    a, c, e, g, Analyses of individual OTU abundances in response to N:PF (a), forest-floor pH (c), KTFD (e) and MAT (g). Black symbols correspond to taxa declining with the increasing variable (z−) and open symbols depict increasing taxa (z+). Symbol size is proportional to magnitude of response (z-score). Horizontal lines represent 5th and 95th quantiles of values resulting in the largest change in taxon z-scores among 1,000 bootstrap replicates. Tree shapes indicate host generalist, conifer- or broad-leaf-specific. b, d, f, h, Community-level output of accumulated z-scores per plot is shown in response to N:PF (b), forest-floor pH (d), KTFD (f) and MAT (h).

  3. Extended Data Fig. 3 Threshold indicator taxa analysis at the genus level.

    a, c, e, g, i, Analyses in response to NTFD (a), N:PF (c), forest-floor pH (e), KTFD (g) and MAT (i). Black symbols correspond to taxa that declined with the increasing variable (z−) and open symbols depict increasing taxa (z+). Symbol size is proportional to magnitude of response (z-score). Horizontal lines represent 5th and 95th quantiles of values resulting in the largest change in taxon z-scores among 1,000 bootstrap replicates. b, d, f, h, j, The community-level output of the accumulated z-scores per plot is shown in response to NTFD (b), N:PF (d), forest-floor pH (f), KTFD (h) and MAT (j).

  4. Extended Data Table 1 Envfit results for the environmental variables used in the non-metric multi-dimensional scaling ordination
  5. Extended Data Table 2 Observed and expected frequencies of hyphae and rhizomorph presence
  6. Extended Data Table 3 Effects of key variables on hyphal plasticity
  7. Extended Data Table 4 Effects of key variables on rhizomorph plasticity
  8. Extended Data Table 5 Effects of key variables on hyphal and rhizomorph presence on the total ectomycorrhizal community

Supplementary information

  1. Supplementary Figure 1

    This file contains an html5 file with an interactive version of the Krona chart in Figure 2.

  2. Reporting Summary

  3. Supplementary Tables

    This file contains Supplementary Tables 1-2. Supplementary Table 1 contains a summary of recent large scale biogeograhical ectomycorrhiza publications and Supplementary Table 2 contains a summary of the variables measured on the ICP Forests Level II plots, that were used in this study.

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