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Title: | Connecting the multiple dimensions of global soil fungal diversity | Data Creator - person: | Mikryukov, Vladimir Dulya, Olesya Zizka, Alexander Bahram, Mohammad Hagh-Doust, Niloufar Anslan, Sten Prylutskyi, Oleh Delgado-Baquerizo, Manuel Maestre, Fernando T. Nilsson, R. Henrik Pärn, Jaan Van Nuland, Michael E. Antonelli, Alexandre SOUDZILOVSKAIA, Nadia Kõljalg, Urmas Abarenkov, Kessy Tedersoo, Leho Öpik, Maarja Moora, Mari Zobel, Martin Espenberg, Mikk Mander, Ülo Khalid, Abdul Nasir Corrales, Adriana Agan, Ahto Vasco-Palacios, Aída M. Saitta, Alessandro Rinaldi, Andrea C. Verbeken, Annemieke Sulistyo, Bobby P. Tamgnoue, Boris Furneaux, Brendan Ritter, Camila Duarte Nyamukondiwa, Casper Sharp, Cathy Marín, César Gohar, Daniyal Klavina, Darta Sharmah, Dipon Dai, Dong Qin Nouhra, Eduardo Biersma, Elisabeth Machteld Rähn, Elisabeth Cameron, Erin K. De Crop, Eske Otsing, Eveli Davydov, Evgeny A. Albornoz, Felipe E. Brearley, Francis Q. Buegger, Franz Zahn, Geoffrey Bonito, Gregory Hiiesalu, Inga Barrio, Isabel C. Heilmann-Clausen, Jacob Ankuda, Jelena Doležal, Jiri Kupagme, John Y. Maciá-Vicente, Jose G. Fovo, Joseph Djeugap Geml, József Alatalo, Juha M. Alvarez-Manjarrez, Julieta Põldmaa, Kadri Runnel, Kadri Adamson, Kalev Bråthen, Kari Anne Pritsch, Karin Tchan, Kassim I. Armolaitis, Kęstutis Hyde, Kevin D. Newsham, Kevin K. Panksep, Kristel Lateef, Adebola A. Hansson, Linda Lamit, Louis J. Saba, Malka Tuomi, Maria Gryzenhout, Marieka Bauters, Marijn Piepenbring, Meike Wijayawardene, Nalin Yorou, Nourou S. Kurina, Olavi Mortimer, Peter E. Meidl, Peter Kohout, Petr Puusepp, Rasmus Drenkhan, Rein Garibay-Orijel, Roberto Godoy, Roberto Alkahtani, Saad Rahimlou, Saleh Dudov, Sergey V. Põlme, Sergei Ghosh, Soumya Mundra, Sunil Ahmed, Talaat Netherway, Tarquin Henkel, Terry W. Roslin, Tomas Nteziryayo, Vincent Fedosov, Vladimir E. Onipchenko, Vladimir G. Yasanthika, W. A. Erandi Lim, Young Woon |
Data Creator - organization: | University of Tartu Philipps-University Swedish University of Agricultural Sciences V.N. Karazin Kharkiv National University Instituto de Recursos Naturales y Agrobiologia de Sevilla Universidad de Alicante University of Gothenburg University of the Punjab Universidad del Rosario Universidad de Antioquia University of Palermo University of Cagliari Ghent University University of Dschang Uppsala University Instituto Juruà Botswana International University of Science and Technology Natural History Museum of Zimbabwe Universidad SantoTomàs Latvian State Forest Resarch Institute Silava Pondicherry University Quijing Normal University Universidad Nacional de Cordoba National History Museum of Denmark Estonian University of Life Sciences Saint Mary's University Altai State University CSIRO Environment Manchester Metropolitan University Helmholz Zentrum München Utah Valley University Michigan State University Agricultural University of Iceland University of Copenhagen Lithuanian Research Centre for Agriculture and Forestry (LAMMC) University of South Bohemia Wageningen University Karoly Catholic University Qatar University Universidad Nacional Autonoma de México The Arctic University of Norway University of Parakou Mae Fah Luang University NERC British Antarctic Survey University of Ilorin Gothenburg Centre for Sustainable Development Syracuse University Quaid-i-Azam University University of the Free State Goethe University Frankfurt am Main Chinese Academy of Sciences Freie Universität Berlin Czech Academy of Sciences United Arab Emirates University California State Polytechnice University University of Burundi Moscow Lomonosov State University Seoul National University Society for the Protection of Underground Networks Hasselt University Royal Botanic Gardens, Kew |
Data Curator - person: | Mikryukov, Vladimir | Data Curator - organization: | University of Tartu | Rights Holder - person: | Mikryukov, Vladimir | Rights Holder - organization: | University of Tartu | Publisher: | Zenodo | Issue Date: | 2023 | Abstract: | 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 | Research Discipline: | Natural sciences > Biological sciences > Microbiology > Mycology (01060804) | Keywords: | Fungi;Richness;Phylogenetic diversity;Diversity;Metabarcoding;Biogeography;Global maps;Conservation;Mycorrhizal fungi;Pathogens;Saprotrophs;Internal transcribed spacer;ITS;PacBio;Diversity hotspots;Species turnover | DOI: | 10.5281/zenodo.8013448 | Link to publication/dataset: | https://zenodo.org/record/8013448 | Source: | Zenodo. 10.5281/zenodo.8013448 https://zenodo.org/record/8013448 | Publications related to the dataset: | https://github.com/Mycology-Microbiology-Center/Global_fungal_diversity | License: | Creative Commons Attribution 4.0 International (CC-BY-4.0) | Access Rights: | Open Access | Version: | 1.0.0 | Category: | DS | Type: | Dataset |
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