Environment and host as large-scale controls of ectomycorrhizal fungi

An Author Correction to this article was published on 04 July 2018

This article has been updated (view changelog)

Abstract

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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Fig. 1: Map of Europe showing sampled level II plots from the United Nations Economic Commission for Europe International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (UNECE ICP Forests).
Fig. 2: Krona chart of taxonomic affiliation of ectomycorrhizas and their relative abundance.
Fig. 3: Variation-partitioning Venn diagram.
Fig. 4: Threshold indicator taxa analyses.

Change history

  • 04 July 2018

    In the HTML version of this Article, author ‘Filipa Cox’ had no affiliation in the author list, although she was correctly associated with affiliation 3 (Earth & Environmental Sciences, University of Manchester, Manchester, UK) in the PDF. In addition, the blue circles for ‘oak’ were missing from Extended Data Fig. 1. These errors have been corrected online.

References

  1. 1.

    Canadell, J. G. et al. Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proc. Natl Acad. Sci. USA 104, 18866–18870 (2007).

    ADS  Article  PubMed  Google Scholar 

  2. 2.

    Galloway, J. N. et al. Transformation of the nitrogen cycle: recent trends, questions, and potential solutions. Science 320, 889–892 (2008).

    ADS  Article  PubMed  CAS  Google Scholar 

  3. 3.

    Commission of the European Communities. Communication from the Commission to the Council, the European Parliament, the European Economic and Social Committee and the Committee of the Regions – Thematic Strategy for Soil Protection (COM(2006) 231) http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52006DC0231 (2006).

  4. 4.

    Janssens, I. A. et al. Reduction of forest soil respiration in response to nitrogen deposition. Nat. Geosci. 3, 315–322 (2010).

    ADS  Article  CAS  Google Scholar 

  5. 5.

    Johnson, N. C. & Jansa, J. in Mycorrhizal Mediation of Soil: Fertility, Structure, and Carbon Storage (eds Johnson, N. C. et al.) 1–6 (Elsevier, Amsterdam, 2017).

  6. 6.

    van der Heijden, M. G. A., Martin, F. M., Selosse, M.-A. & Sanders, I. R. Mycorrhizal ecology and evolution: the past, the present, and the future. New Phytol. 205, 1406–1423 (2015).

    Article  PubMed  CAS  Google Scholar 

  7. 7.

    Averill, C., Turner, B. L. & Finzi, A. C. Mycorrhiza-mediated competition between plants and decomposers drives soil carbon storage. Nature 505, 543–545 (2014).

    ADS  Article  PubMed  CAS  Google Scholar 

  8. 8.

    Clemmensen, K. E. et al. Roots and associated fungi drive long-term carbon sequestration in boreal forest. Science 339, 1615–1618 (2013).

    ADS  Article  PubMed  CAS  Google Scholar 

  9. 9.

    Bennett, J. A. et al. Plant-soil feedbacks and mycorrhizal type influence temperate forest population dynamics. Science 355, 181–184 (2017).

    ADS  Article  PubMed  CAS  Google Scholar 

  10. 10.

    Terrer, C., Vicca, S., Hungate, B. A., Phillips, R. P. & Prentice, I. C. Mycorrhizal association as a primary control of the CO2 fertilization effect. Science 353, 72–74 (2016).

    ADS  Article  PubMed  CAS  Google Scholar 

  11. 11.

    Smith, S. E. & Read, D. E. Mycorrhizal Symbiosis 3rd edn (Academic, London, 2008).

    Google Scholar 

  12. 12.

    Veresoglou, S. D. et al. Exploring continental-scale stand health – N:P ratio relationships for European forests. New Phytol. 202, 422–430 (2014).

    Article  PubMed  CAS  Google Scholar 

  13. 13.

    Jonard, M. et al. Tree mineral nutrition is deteriorating in Europe. Glob. Change Biol. 21, 418–430 (2015).

    ADS  Article  PubMed  Google Scholar 

  14. 14.

    Levin, S. A. Multiple scales and the maintenance of biodiversity. Ecosystems 3, 498–506 (2000).

    Article  Google Scholar 

  15. 15.

    Lilleskov, E. A. & Parrent, J. L. Can we develop general predictive models of mycorrhizal fungal community-environment relationships? New Phytol. 174, 250–256 (2007).

    Article  PubMed  CAS  Google Scholar 

  16. 16.

    Suz, L. M. et al. Environmental drivers of ectomycorrhizal communities in Europe’s temperate oak forests. Mol. Ecol. 23, 5628–5644 (2014).

    Article  PubMed  CAS  Google Scholar 

  17. 17.

    Peay, K. G. & Matheny, P. B. in Molecular Mycorrhizal Symbiosis (ed. Martin, F.) 341–361 (John Wiley & Sons, Hoboken, 2016).

  18. 18.

    Cox, F., Barsoum, N., Lilleskov, E. A. & Bidartondo, M. I. Nitrogen availability is a primary determinant of conifer mycorrhizas across complex environmental gradients. Ecol. Lett. 13, 1103–1113 (2010).

    Article  PubMed  Google Scholar 

  19. 19.

    Cudlin, P. et al. Fine roots and ectomycorrhizas as indicators of environmental change. Plant Biosyst. 141, 406–425 (2007).

    Article  Google Scholar 

  20. 20.

    Tedersoo, L. et al. Towards global patterns in the diversity and community structure of ectomycorrhizal fungi. Mol. Ecol. 21, 4160–4170 (2012).

    Article  PubMed  Google Scholar 

  21. 21.

    Ostonen, I. et al. Adaptive root foraging strategies along a boreal–temperate forest gradient. New Phytol. 215, 977–991 (2017).

    Article  PubMed  CAS  Google Scholar 

  22. 22.

    Kauserud, H. et al. Warming-induced shift in European mushroom fruiting phenology. Proc. Natl Acad. Sci. USA 109, 14488–14493 (2012).

    ADS  Article  PubMed  Google Scholar 

  23. 23.

    Peay, K. G., Bruns, T. D., Kennedy, P. G., Bergemann, S. E. & Garbelotto, M. A strong species–area relationship for eukaryotic soil microbes: island size matters for ectomycorrhizal fungi. Ecol. Lett. 10, 470–480 (2007).

    Article  PubMed  Google Scholar 

  24. 24.

    Peay, K. G., Bidartondo, M. I. & Arnold, A. E. Not every fungus is everywhere: scaling to the biogeography of fungal–plant interactions across roots, shoots and ecosystems. New Phytol. 185, 878–882 (2010).

    Article  PubMed  Google Scholar 

  25. 25.

    Suz, L. M. et al. Monitoring ectomycorrhizal fungi at large scales for science, forest management, fungal conservation and environmental policy. Ann. For. Sci. 72, 877–885 (2015).

    Article  Google Scholar 

  26. 26.

    Peay, K. G., Kennedy, P. G., Davies, S. J., Tan, S. & Bruns, T. D. Potential link between plant and fungal distributions in a dipterocarp rainforest: community and phylogenetic structure of tropical ectomycorrhizal fungi across a plant and soil ecotone. New Phytol. 185, 529–542 (2010).

    Article  PubMed  CAS  Google Scholar 

  27. 27.

    Taylor, D. L. et al. A first comprehensive census of fungi in soil reveals both hyperdiversity and fine-scale niche partitioning. Ecol. Monogr. 84, 3–20 (2014).

    Article  Google Scholar 

  28. 28.

    Bahram, M., Peay, K. G. & Tedersoo, L. Local-scale biogeography and spatiotemporal variability in communities of mycorrhizal fungi. New Phytol. 205, 1454–1463 (2015).

    Article  PubMed  CAS  Google Scholar 

  29. 29.

    Kennedy, P. G., Garibay-Orijel, R., Higgins, L. M. & Angeles-Arguiz, R. Ectomycorrhizal fungi in Mexican Alnus forests support the host co-migration hypothesis and continental-scale patterns in phylogeography. Mycorrhiza 21, 559–568 (2011).

    Article  PubMed  Google Scholar 

  30. 30.

    Kennedy, P. G. et al. Scaling up: examining the macroecology of ectomycorrhizal fungi. Mol. Ecol. 21, 4151–4154 (2012).

    Article  PubMed  Google Scholar 

  31. 31.

    Põlme, S. et al. Biogeography of ectomycorrhizal fungi associated with alders (Alnus spp.) in relation to biotic and abiotic variables at the global scale. New Phytol. 198, 1239–1249 (2013).

    Article  PubMed  CAS  Google Scholar 

  32. 32.

    Talbot, J. M. et al. Endemism and functional convergence across the North American soil mycobiome. Proc. Natl Acad. Sci. USA 111, 6341–6346 (2014).

    ADS  Article  PubMed  CAS  Google Scholar 

  33. 33.

    Tedersoo, L. et al. Global diversity and geography of soil fungi. Science 346, 1256688 (2014).

    Article  PubMed  CAS  Google Scholar 

  34. 34.

    Molina, R. & Horton, T. R. in Mycorrhizal Networks (ed. Horton, T. R.) 1–39 (Springer Science + Business Media Dordrecht, Dordrecht, 2015).

  35. 35.

    de Witte, L. C., Rosenstock, N. P., van der Linde, S. & Braun, S. Nitrogen deposition changes ectomycorrhizal communities in Swiss beech forests. Sci. Total Environ. 605–606, 1083–1096 (2017).

    Article  PubMed  CAS  Google Scholar 

  36. 36.

    Pardo, L. H. et al. Effects of nitrogen deposition and empirical nitrogen critical loads for ecoregions of the United States. Ecol. Appl. 21, 3049–3082 (2011).

    Article  Google Scholar 

  37. 37.

    Hettelingh, J.-P. et al. in Critical Loads and Dynamic Risk Assessments: Nitrogen, Acidity and Metals in Terrestrial and Aquatic Ecosystems (eds de Vries, W. et al.) 613–635 (Springer Science + Business Media Dordrecht, Dordrecht, 2015).

  38. 38.

    Reis, S. et al. From acid rain to climate change. Science 338, 1153–1154 (2012).

    ADS  Article  PubMed  CAS  Google Scholar 

  39. 39.

    Lilleskov, E. A., Hobbie, E. A. & Horton, T. R. Conservation of ectomycorrhizal fungi: exploring the linkages between functional and taxonomic responses to anthropogenic N deposition. Fung. Ecol. 4, 174–183 (2011).

    Article  Google Scholar 

  40. 40.

    Hendershot, J. N., Read, Q. D., Henning, J. A., Sanders, N. J. & Classen, A. T. Consistently inconsistent drivers of microbial diversity and abundance at macroecological scales. Ecology 98, 1757–1763 (2017).

    Article  PubMed  Google Scholar 

  41. 41.

    Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551, 457–463 (2017).

    ADS  Article  PubMed  CAS  PubMed Central  Google Scholar 

  42. 42.

    Glassman, S. I. et al. A continental view of pine-associated ectomycorrhizal fungal spore banks: a quiescent functional guild with a strong biogeographic pattern. New Phytol. 205, 1619–1631 (2015).

    Article  PubMed  CAS  Google Scholar 

  43. 43.

    Gardes, M. & Bruns, T. D. Community structure of ectomycorrhizal fungi in a Pinus muricata forest: above- and below-ground views. Can. J. Bot. 74, 1572–1583 (1996).

    Article  Google Scholar 

  44. 44.

    Anderson, I. C. & Cairney, J. W. G. Ectomycorrhizal fungi: exploring the mycelial frontier. FEMS Microbiol. Rev. 31, 388–406 (2007).

    Article  PubMed  CAS  Google Scholar 

  45. 45.

    Buée, M., Sentausa, E. & Murat, C. in Molecular Mycorrhizal Symbiosis (ed. Martin, F.) 323–406 (John Wiley & Sons, Hoboken, 2016).

  46. 46.

    Tedersoo, L. & Nilsson, R. H. in Molecular Mycorrhizal Symbiosis (ed. Martin, F.) 299–322 (John Wiley & Sons, Hoboken, 2016).

  47. 47.

    Newton, A. C. & Haigh, J. M. Diversity of ectomycorrhizal fungi in Britain: a test of the species–area relationship, and the role of host specificity. New Phytol. 138, 619–627 (1998).

    Article  Google Scholar 

  48. 48.

    Peay, K. G. The mutualistic niche: mycorrhizal symbiosis and community dynamics. Annu. Rev. Ecol. Evol. Syst. 47, 143–164 (2016).

    Article  Google Scholar 

  49. 49.

    Taylor, A. F. S., Fransson, P. M., Högberg, P., Högberg, M. N. & Plamboeck, A. H. Species level patterns in 13C and 15N abundance of ectomycorrhizal and saprotrophic fungal sporocarps. New Phytol. 159, 757–774 (2003).

    Article  CAS  Google Scholar 

  50. 50.

    Hortal, S. et al. Role of plant–fungal nutrient trading and host control in determining the competitive success of ectomycorrhizal fungi. ISME J. 11, 2666–2676 (2017).

    Article  PubMed  CAS  Google Scholar 

  51. 51.

    Tripler, C. E., Kaushal, S. S., Likens, G. E. & Walter, M. T. Patterns in potassium dynamics in forest ecosystems. Ecol. Lett. 9, 451–466 (2006).

    Article  PubMed  Google Scholar 

  52. 52.

    Agerer, R. Exploration types of ectomycorrhizae. Mycorrhiza 11, 107–114 (2001).

    Article  Google Scholar 

  53. 53.

    Boddy, L. et al. Climate variation effects on fungal fruiting. Fung. Ecol. 10, 20–33 (2014).

    Article  Google Scholar 

  54. 54.

    Wallander, H. A new hypothesis to explain allocation of dry matter between mycorrhizal fungi and pine seedlings in relation to nutrient supply. Plant Soil 168, 243–248 (1995).

    Article  Google Scholar 

  55. 55.

    van Strien, A. J., Boomsluiter, M., Noordeloos, M. E., Verweij, R. J. T. & Kuyper, T. W. Woodland ectomycorrhizal fungi benefit from large-scale reduction in nitrogen deposition in the Netherlands. J. Appl. Ecol. 55, 290–298 (2018).

    Article  CAS  Google Scholar 

  56. 56.

    Arnolds, E. Decline of ectomycorrhizal fungi in Europe. Agric. Ecosyst. Environ. 35, 209–244 (1991).

    Article  Google Scholar 

  57. 57.

    Lilleskov, E. A. in The Fungal Community (eds Dighton, J. et al.) 769–801 (CRC, Boca Raton, 2005).

  58. 58.

    Kiers, T. E., Palmer, T. M., Ives, A. R., Bruno, J. F. & Bronstein, J. L. Mutualisms in a changing world: an evolutionary perspective. Ecol. Lett. 13, 1459–1474 (2010).

    Article  Google Scholar 

  59. 59.

    Bobbink, R. & Hettelingh, J.-P. in Review and Revision of Empirical Critical Loads and Dose-Response Relationships (RIVM Report 680359002) (eds Bobbink, R. & Hettelingh, J.-P.) 135–171 (Coordination Centre for Effects, National Institute for Public Health and the Environment (RIVM), Bilthoven, 2011).

  60. 60.

    Giordani, P. et al. Detecting the nitrogen critical loads on European forests by means of epiphytic lichens. A signal-to-noise evaluation. For. Ecol. Manage. 311, 29–40 (2014).

    Article  Google Scholar 

  61. 61.

    Leppänen, S. M., Salemaa, M., Smolander, A., Mäkipää, R. & Tiirola, M. Nitrogen fixation and methanotrophy in forest mosses along a N deposition gradient. Environ. Exp. Bot. 90, 62–69 (2013).

    Article  CAS  Google Scholar 

  62. 62.

    Güsewell, S. N: Pratios in terrestrial plants: variation and functional significance. New Phytol. 164, 243–266 (2004).

    Article  Google Scholar 

  63. 63.

    Cools, N. & De Vos, B. Availability and evaluation of European forest soil monitoring data in the study on the effects of air pollution on forests. iForest 4, 205–211 (2011).

    Article  Google Scholar 

  64. 64.

    Hazard, C. & Johnson, D. Does genotypic and species diversity of mycorrhizal plants and fungi affect ecosystem function? New Pythol. https://doi.org/10.1111/nph.15010 (2018).

  65. 65.

    Chen, W. et al. Root morphology and mycorrhizal symbioses together shape nutrient foraging strategies of temperate trees. Proc. Natl Acad. Sci. USA 113, 8741–8746 (2016).

    Article  PubMed  CAS  Google Scholar 

  66. 66.

    Ferretti, M. & Fischer, R. (eds) Forest Monitoring: Methods for Terrestrial Investigations in Europe with an Overview of North America and Asia Forest Monitoring (Developments in Environmental Science Vol. 12) (Elsevier, Amsterdam, 2013).

    Google Scholar 

  67. 67.

    de Vries, W. et al. Intensive monitoring of forest ecosystems in Europe: 1. Objectives, set-up and evaluation strategy. For. Ecol. Manage. 174, 77–95 (2003).

    Article  Google Scholar 

  68. 68.

    Dirnböck, T. et al. Forest floor vegetation response to nitrogen deposition in Europe. Glob. Change Biol. 20, 429–440 (2014).

    Article  Google Scholar 

  69. 69.

    MCPFE Liaison Unit Warsaw, UNECE & FAO. State of Europe’s Forests: the MCPFE Report on Sustainable Forest Management in Europe (Ministerial Conference on the Protection of Forests in Europe, Warsaw, 2007).

    Google Scholar 

  70. 70.

    Gardes, M. & Bruns, T. D. ITS primers with enhanced specificity for basidiomycetes-application to the identification of mycorrhizae and rusts. Mol. Ecol. 2, 113–118 (1993).

    Article  PubMed  CAS  Google Scholar 

  71. 71.

    White, T. J., Bruns, T., Lee, S. & Taylor, J. in PCR Protocols: a Guide to Methods and Applications (eds Innis, M. A. et al.) 315–322 (Academic, New York, 1990).

  72. 72.

    UNECE ICP Forests Programme Co-ordinating Centre (ed.). Manual on Methods and Critera for Harmonized Sampling, Assessment, Monitoring and Analysis of the Effects of Air Pollution on Forests (Thünen Institute for Forest Ecosystems, Eberswalde, 2016).

    Google Scholar 

  73. 73.

    IUSS Working Group WRB. World Reference Base for Soil Resources 2014, Update 2015. International Soil Classification System for Naming Soils and Creating Legends for Soil Maps (World Soil Resources Reports 106) (FAO, Rome, 2015).

    Google Scholar 

  74. 74.

    Eichhorn, J. et al. in Manual on Methods and Critera for Harmonized Sampling, Assessment, Monitoring and Analysis of the Effects of Air Pollution on Forests (ed. UNECE ICP Forests Programme Co-ordinating Centre) 54 (Thünen Institute for Forest Ecosystems, Eberswalde, 2016).

  75. 75.

    Rautio, P., Fürst, A., Stefan, K. & Bartels, U. in Manual on Methods and Critera for Harmonized Sampling, Assessment, Monitoring and Analysis of the Effects of Air Pollution on Forests (ed. UNECE ICP Forests Programme Co-ordinating Centre) 19 (Thünen Institute for Forest Ecosystems, Eberswalde, 2016).

  76. 76.

    Waldner, P., et al. Detection of temporal trends in atmospheric deposition of inorganic nitrogen and sulphate to forests in Europe. Atmos. Environ. 95, 363–374 (2014).

    ADS  Article  CAS  Google Scholar 

  77. 77.

    Raspe, S., Beuker, E., Preuhsler, T. & Bastrup-Birk, A. in Manual on Methods and Critera for Harmonized Sampling, Assessment, Monitoring and Analysis of the Effects of Air Pollution on Forests (ed. UNECE ICP Forests Programme Co-ordinating Centre) 35 (Thünen Institute for Forest Ecosystems, Eberswalde, 2016).

  78. 78.

    Ewing, B. & Green, P. Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res. 8, 186–194 (1998).

    Article  PubMed  CAS  Google Scholar 

  79. 79.

    Kearse, M. et al. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28, 1647–1649 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  80. 80.

    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  81. 81.

    Rognes, T., Flouri, T., Nichols, B., Quince, C. & Mahé F. VSEARCH: a versatile open source tool for metagenomics. PeerJ 4, e2584 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  82. 82.

    Kõljalg, U. et al. Towards a unified paradigm for sequence-based identification of fungi. Mol. Ecol. 22, 5271–5277 (2013).

    Article  PubMed  CAS  Google Scholar 

  83. 83.

    Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    Article  PubMed  CAS  Google Scholar 

  84. 84.

    Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  85. 85.

    Rinaldi, A. C., Comandini, O. & Kuyper, T. W. Ectomycorrhizal fungal diversity: separating the wheat from the chaff. Fungal Divers. 33, 1–45 (2008).

    Google Scholar 

  86. 86.

    Tedersoo, L., May, T. W. & Smith, M. E. Ectomycorrhizal lifestyle in fungi: global diversity, distribution, and evolution of phylogenetic lineages. Mycorrhiza 20, 217–263 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  87. 87.

    Legendre, P. & Gallagher, E. D. Ecologically meaningful transformations for ordination of species data. Oecologia 129, 271–280 (2001).

    ADS  Article  PubMed  Google Scholar 

  88. 88.

    R Core Team. R: A language and environment for statistical computing. http://www.R-project.org/ (R Foundation for Statistical Computing, Vienna, 2016).

  89. 89.

    Borcard, D., Legendre, P. & Drapeau, P. Partialling out the spatial component of ecological variation. Ecology 73, 1045–1055 (1992).

    Article  Google Scholar 

  90. 90.

    Legendre, P. & Legendre, L. Numerical Ecology 2nd edn (Springer, Amsterdam, 1998).

    Google Scholar 

  91. 91.

    Blanchet, F. G., Legendre, P. & Borcard, D. Forward selection of explanatory variables. Ecology 89, 2623–2632 (2008).

    Article  PubMed  Google Scholar 

  92. 92.

    Nychka, D., Furrer, R., Paige, J. & Sain, S. fields: tools for spatial data. http://www.image.ucar.edu/fields (2015).

  93. 93.

    Lee, C.-R. et al. On the post-glacial spread of human commensal Arabidopsis thaliana. Nat. Commun. 8, 14458 (2017).

    ADS  Article  PubMed  PubMed Central  CAS  Google Scholar 

  94. 94.

    Lamb, A. M. et al. Climate-driven mitochondrial selection: a test in Australian songbirds. Mol. Ecol. 27, 898–918 (2018).

    Article  PubMed  CAS  Google Scholar 

  95. 95.

    Kalogirou, S. lctools: local correlation, spatial inequalities, geographically weighted regression and other tools. https://CRAN.R-project.org/package=lctools (2016).

  96. 96.

    Baker, M. E. & King, R. S. A new method for detecting and interpreting biodiversity and ecological community thresholds. Methods Ecol. Evol. 1, 25–37 (2010).

    Article  Google Scholar 

  97. 97.

    Dore, A. J. et al. Evaluation of the performance of different atmospheric chemical transport models and inter-comparison of nitrogen and sulphur deposition estimates for the UK. Atmos. Environ. 119, 131–143 (2015).

    ADS  Article  CAS  Google Scholar 

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Acknowledgements

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.

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

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Contributions

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.

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Correspondence to Sietse van der Linde.

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Extended data figures and tables

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.

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).

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).

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

Supplementary information

Supplementary Figure 1

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

Reporting Summary

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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van der Linde, S., Suz, L.M., Orme, C.D.L. et al. Environment and host as large-scale controls of ectomycorrhizal fungi. Nature 558, 243–248 (2018). https://doi.org/10.1038/s41586-018-0189-9

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