Mycology & Microbiology Center [Estonia]
Published June 7, 2023 | Version 1.0.0
Dataset Open

Connecting the multiple dimensions of global soil fungal diversity

Creators

  • 1. Institute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia
  • 2. Department of Biology, Philipps-University, Marburg, Germany
  • 3. Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden
  • 4. Department of Mycology and Plant Resistance, School of Biology, V.N. Karazin Kharkiv National University, Kharkiv, Ukraine
  • 5. Laboratorio de Biodiversidad y Funcionamiento Ecosistemico. Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), CSIC, Sevilla, Spain
  • 6. Instituto Multidisciplinar para el Estudio del Medio 'Ramón Margalef' and Departamento de Ecología, Universidad de Alicante; 03690, Alicante, Spain
  • 7. Gothenburg Global Biodiversity Centre, University of Gothenburg, Gothenburg, Sweden
  • 8. Institute of Botany, University of the Punjab, Lahore, Pakistan
  • 9. Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Universidad del Rosario, Bogotá, Colombia
  • 10. Institute of Forestry and Engineering, Estonian University of Life Sciences, Tartu, Estonia
  • 11. Grupo de BioMicro y Microbiología Ambiental, Escuela de Microbiologia, Universidad de Antioquia UdeA, Medellin, Antioquia, Colombia
  • 12. Department of Agricultural, Food and Forest Sciences, University of Palermo, Palermo, Italy.
  • 13. Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
  • 14. Department Biology, Ghent University, Ghent, Belgium
  • 15. Department of Crop Science, University of Dschang, Dschang, Cameroon
  • 16. Department of Ecology and Genetics, Uppsala University, Uppsala, Sweden
  • 17. Instituto Juruá, Manaus, AM, Brazil
  • 18. Department of Biological Sciences and Biotechnology, Botswana International University of Science and Technology, Palapye, Botswana
  • 19. Natural History Museum of Zimbabwe, Bulawayo, Zimbabwe
  • 20. Centro de Investigación e Innovación para el Cambio Climático (CiiCC), Universidad SantoTomás, Av. Ramón Picarte 1130, Valdivia, Chile
  • 21. Center of Mycology and Microbiology, University of Tartu, Tartu, Estonia
  • 22. Latvian State Forest Research Insitute Silava, Salaspils, Latvia
  • 23. Department of Botany, Jawaharlal Nehru Rajkeeya Mahavidyalaya, Pondicherry University, Port Blair, India
  • 24. College of Biological Resource and Food Engineering, Qujing Normal University, Qujing,Yunnan, China
  • 25. Instituto Multidisciplinario de Biología Vegetal (CONICET), Universidad Nacional de Córdoba, Cordoba, Argentina
  • 26. Natural History Museum of Denmark, Copenhagen, Denmark
  • 27. Department of Environmental Science, Saint Mary's University, Halifax, Nova Scotia, Canada
  • 28. Altai State University, Barnaul, Russia
  • 29. CSIRO Environment, Wembley, WA, Australia
  • 30. Department of Natural Sciences, Manchester Metropolitan University, Manchester, UK
  • 31. Helmholtz Zentrum München, Neuherberg, Germany
  • 32. Utah Valley University, Orem UT, USA
  • 33. Plant, Soil and Microbial Sciences, Michigan State University, East Lansing MI, USA
  • 34. Faculty of Natural and Environmental Sciences, Agricultural University of Iceland, Hvanneyri, Iceland
  • 35. Center for Macroecology, Evolution and Climate, University of Copenhagen, Copenhagen, Denmark
  • 36. Vokė branch, Institute of Agriculture, Lithuanian Research Centre for Agriculture and Forestry (LAMMC). Vilnius, Lithuania.
  • 37. Czech Academy of Sciences, Institute of Botany, Czech Republic, and Department of Botany, Faculty of Science, University of South Bohemia, České Budějovice, Czech Republic
  • 38. Plant Ecology and Nature Conservation, Wageningen University & Research, Wageningen, The Netherlands
  • 39. ELKH-EKKE Lendület Environmental Microbiome Research Group, Eszterházy Károly Catholic University, Eger, Hungary
  • 40. Environmental Science Center, Qatar University, Doha, Qatar
  • 41. Instituto de Biología, Universidad Nacional Autónoma de México, Ciudad de México, México
  • 42. Department of Arctic and Marine Biology, The Arctic University of Norway, Tromsø, Norway
  • 43. Research Unit Tropical Mycology and Plants-Soil Fungi Interactions, University of Parakou, Parakou, Benin
  • 44. Department of Silviculture and Ecology, Institute of Forestry, Lithuanian Research Centre for Agriculture and Forestry (LAMMC), Girionys, Lithuania.
  • 45. Center of Excellence in Fungal Research, Mae Fah Luang University, Chiang Rai, Thailand
  • 46. NERC British Antarctic Survey, High Cross, Cambridge, UK
  • 47. Chair of Hydrobiology and Fishery, Estonian University of Life Sciences, Tartu, Estonia
  • 48. Department of Plant Biology, University of Ilorin, Ilorin, Nigeria
  • 49. Gothenburg Centre for Sustainable Development, Gothenburg, Sweden
  • 50. Department of Biology, Syracuse University, Syracuse, NY, USA
  • 51. Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan
  • 52. Department of Genetics, University of the Free State, Bloemfontein, South Africa
  • 53. Department of Environment, Ghent University, Ghent, Belgium
  • 54. Mycology Working Group, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
  • 55. College of Biological Resource and Food Engineering, Qujing Normal University, Qujing, Yunnan, China
  • 56. Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Tartu, Estonia
  • 57. Center For Mountain Futures, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
  • 58. Freie Universität Berlin, Institut für Biologie, Berlin, Germany
  • 59. Institute of Microbiology, Czech Academy of Sciences, Prague, Czech Republic
  • 60. Instituto Ciencias Ambientales y Evolutivas, Universidad Austral de Chile, Valdivia, Chile
  • 61. College of Science, King Saud University, Riyadh, Saudi Arabia
  • 62. Department of Ecology and Plant Geography, Moscow Lomonosov State University, Moscow, Russia
  • 63. Department of Biology, College of Science, United Arab Emirates University, Al Ain, Abu Dhabi, UAE
  • 64. Department of Biological Sciences, California State Polytechnic University, Arcata CA, USA
  • 65. Department of Food Science and Technology, University of Burundi, Bujumbura, Burundi
  • 66. School of Biological Sciences and Institute of Microbiology, Seoul National University, Seoul, Korea
  • 67. Society for the Protection of Underground Networks, Dover, DE, USA
  • 68. Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
  • 69. Royal Botanic Gardens, Kew, Richmond, United Kingdom
  • 70. University of Tartu Natural History Museum, Tartu, Estonia

Description

How the multiple facets of soil fungal diversity vary worldwide remains virtually unknown, hindering the management of this essential species-rich group. By sequencing high-resolution DNA markers in over 4000 topsoil samples from natural and human-altered ecosystems across all continents, we illustrate the distributions and drivers of different levels of taxonomic and phylogenetic diversity of fungi and their ecological groups. We show the impact of precipitation and temperature interactions on fungal local species richness (alpha diversity) across different climates. Our findings reveal how temperature drives fungal compositional turnover (beta diversity) and phylogenetic diversity, linking them with regional species richness (gamma diversity). Our work integrates fungi into the principles of global biodiversity distribution and presents detailed maps for biodiversity conservation and modeling of global ecological processes.

### Data overview

These datasets contain comprehensive estimates of alpha, beta, and gamma diversity. The data are provided in two formats: TIFF (Tagged Image File Format) and GeoPackage formats, which are commonly used to store geospatially-referenced data.

Alpha Diversity:

  • `Alpha_S_*` files: These files contain estimates of alpha diversity (local species diversity) for each grid cell of a raster file.
  • `Alpha_AOA_*` files: These files outline the 'Area of Applicability' for the alpha diversity estimates.
  • `Alpha_Uncertainty_*` files: These files contain data related to the uncertainty of the alpha diversity predictions. Uncertainty here represents the range or degree of error associated with the diversity estimates.
  •  `Alpha_Hotspots_and_ProtectedAreas` contains information on fungal diversity hotspots and their area under protection (based on IUCN classification). 'Hotspots' are areas with exceptionally high alpha diversity.

Beta Diversity:

  • `Beta_*` files: These files include results of beta diversity analyses: maps of global compositional dissimilarity among soil fungal communities and maps of compositional turnover rate.

Other files:

  • `EcM_and_AM_GlobalDistribution`: the global distribution of areas with high richness of ectomycorrhizal and arbuscular mycorrhizal fungi.
  • `Ecoregions_Alpha,Beta,Gamma_Diversities`: estimates of alpha, beta, and gamma diversity at the level of ecoregion cf. Tedersoo et al., 2022 (DOI:10.1111/gcb.16398).

 

### Data description

Alpha diversity, which is a measure of local species richness (number of Operational Taxonomic Unit (OTU) representing distinct taxa, roughly corresponding to species level). Alpha diversity is represented by the residuals from a model adjusting for sequencing depth, with zero equating to the average OTU richness in the training data set.


`Alpha_S_AllFungi_Consensus.tif`: This file provides consensus estimates for total fungal alpha diversity.
Within the file, there are two types of consensus estimates:

  •     AvgW - weighted consensus estimates for alpha diversity. The weighting takes into account both the area of applicability and the goodness-of-fit for the model used to generate the estimates.
  •     Avg - non-weighted consensus estimates for alpha diversity. Unlike AvgW, these estimates give equal weight to all models regardless of their goodness-of-fit or area of applicability.


`Alpha_AOA_*`: Files containing Area of Applicability information:

  •     A raster value of '1' represents areas that are outside the Area of Applicability
  •     A raster value of '2' denotes areas that are inside the Area of Applicability


In the files containing prediction uncertainties (`Alpha_Uncertainty_*`), two types of data are presented to quantify the amount of uncertainty in model predictions, each represented by a different band:

  • The SD band represents the standard deviation of predictions based on different folds of cross-validation. A larger standard deviation indicates greater variability in the predictions.
  • The IQR band represents the interquartile range (the difference between the upper and lower quartiles) of predictions. The wider the IQR, the greater variability in the predictions.


`Alpha_Hotspots_and_ProtectedAreas.tif`: This file provides information on regions of exceptionally high species richness, referred to as 'hotspots', along with information about protected areas. Hotspots are identified as the top 2.5% quantiles of the richest grid cells on the map in terms of OTU richness.

  • IUCN_1_4 - terrestrial protected areas that fall into categories I-IV, as classified by the International Union for Conservation of Nature (IUCN). These categories typically represent areas with high levels of protection, often prohibiting extractive and destructive activities to preserve biodiversity.
  • IUCN_all - all terrestrial protected areas as recorded in the World Database on Protected Areas (WDPA) database v.1.6. It includes a wider range of protected areas beyond the categories I-IV.
  • All_Avg - Hotspots of total fungal alpha diversity, based on the consensus map
  • GSM_All - Hotspots of total fungal alpha diversity, based on the GSMc dataset
  • GSM_EcM - Hotspots of ectomycorrhizal alpha diversity
  • GSM_AM - Hotspots of arbuscular mycorrhizal alpha diversity
  • GSM_AgarNM - Hotspots of non-EcM Agaricomycetes alpha diversity
  • GSM_Mold - Hotspots of mold alpha diversity
  • GSM_Pathog - Hotspots of opportunistic human parasitic fungal alpha diversity
  • GSM_OHP - Hotspots of putative pathogenic fungal alpha diversity
  • GSM_Unicel - Hotspots of unicellular, non-yeast fungal alpha diversity
  • GSM_Yeast - Hotspots of yeast alpha diversity
  • GSMc_PD - Hotspots of phylogenetic alpha diversity
  • GSM_PDst - Hotspots of phylogenetic dispersion


`EcM_and_AM_GlobalDistribution.tif`: To illustrate the worldwide distribution of ectomycorrhizal (EcM) and arbuscular mycorrhizal (AM) fungi, we have categorized their richness into three distinct groups with low (1), medium (2), and high (3) alpha diversity. These categories have been encoded in the raster file using a bitcode system. Specifically, a value of '9' indicates that both EcM and AM fungal communities  have low alpha diversity, while a value of '27' signifies that both groups of fungi are OTU-rich To assist with interpretation, a color legend has been provided in a separate QML style file (`EcM_and_AM_GlobalDistribution.qml`). This should be automatically recognized by geographic information system software, such as QGIS, to aid in visual analysis.


`Beta_Taxonomic_AllFungi.tif` and `Beta_Phylogenetic_AllFungi.tif`: These files quantify the degree of difference in OTU composition of fungal communities. The measurements are based on the Generalized Dissimilarity Modelling (GDM) framework, as described by Mokany et al., 2022 (DOI:10.1111/geb.13459). Each file provides a different perspective on beta diversity: taxonomic (which is the change in species composition between different locations), and phylogenetic (the change in phylogenetic lineage composition between different locations). Each of these raster files contains three bands, with each band representing a scaled axis from a Principal Component Analysis (PCA) of the GDM-transformed environmental predictors.


`Beta_LocalTurnover.tif`: This file contains estimates of local turnover in fungal communities composition estimated as the median expected compositional dissimilarity (taxonomic or phylogenetic) between each location and its closest neighbors within a 150 km radius. In addition, interquartile range (IQR) of dissimilarities is also provided.

 

`Ecoregions_Alpha,Beta,Gamma_Diversities.gpkg`: Median alpha, beta, and gamma diversity estimates within ecoregions.

  • Ecoregion - Ecoregion name (cf. Tedersoo et al., 2022, DOI:10.1111/gcb.16398)
  • area - Ecoregion area, m2
  • Alpha_S_AllFungi_Consensus - Richness of all fungi (S'tot), consensus map
  • Alpha_S_AllFungi_GSMc - Richness of all fungi (S'GSMc), based on GSMc dataset
  • Alpha_S_EcM_GSMc - Richness of ectomycorrhizal fungi (S'ecm)
  • Alpha_S_AM_GSMc - Richness of arbuscular mycorrhizal fungi (S'am)
  • Alpha_S_NMA_GSMc - Richness of non-EcM Agaricomycetes (S'nma)
  • Alpha_S_Mold_GSMc - Richness of molds (S'mold)
  • Alpha_S_OHP_GSMc - Richness of opportunistic human parasitic fungi (S'ohp)
  • Alpha_S_Path_GSMc - Richness of putative pathogenic fungi (S'path)
  • Alpha_S_Ucel_GSMc - Richness of  unicellular, non-yeast fungi (S'ucel)
  • Alpha_S_Yeast_GSMc - Richness of yeasts (S'yeast)
  • Alpha_SESPD_GSMc - Phylogenetic dispersion of fungal communities (SESPD)
  • Beta_Taxonomic_Median - Median taxonomic dissimilarity of fungal communities (Simpson's index)
  • Beta_Taxonomic_IQR - Interquartile range of taxonomic dissimilarities of fungal communities
  • Beta_Phylogenetic_Median - Median phylogenetic dissimilarity of fungal communities
  • Beta_Phylogenetic_IQR - Interquartile range of phylogenetic dissimilarities of fungal communities
  • Gamma_AllFungi - Gamma diversity (regional species richness) for all fungi (Gtot)
  • Gamma_EcM - Gamma diversity of ectomycorrhizal fungi (Gecm)
  • Gamma_AM - Gamma diversity of arbuscular mycorrhizal fungi (Gam)
  • Gamma_NMA - Gamma diversity of non-EcM Agaricomycetes (Gnma)
  • Gamma_Mold - Gamma diversity of molds (Gmold)
  • Gamma_Path - Gamma diversity of opportunistic human parasitic fungi (Gohp)
  • Gamma_OHP - Gamma diversity of putative pathogenic fungi (Gpath)
  • Gamma_Ucel - Gamma diversity of  unicellular, non-yeast fungi (Gucel)
  • Gamma_Yeast - Gamma diversity of yeasts (Gyeast)

 

### Source code

The code used for data analysis and visualization of the main results of the study are available at GitHub:

https://github.com/Mycology-Microbiology-Center/Global_fungal_diversity

 

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Alpha_AOA_All_GSMc.tif

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Additional details

Related works

Is published in
Journal article: 10.1126/sciadv.adj8016 (DOI)