Automated Author Profile

Kalev Adamson

Institute of Forestry and Engineering, Estonian University of Life Sciences, Tartu, Estonia

Current S-Index

2.4

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.2

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

75.0%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

3

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Connecting the multiple dimensions of global soil fungal diversity (Version: 1.0.0)

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 overviewThese 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 descriptionAlpha 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 ApplicabilityIn 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 mapGSM_All - Hotspots of total fungal alpha diversity, based on the GSMc datasetGSM_EcM - Hotspots of ectomycorrhizal alpha diversityGSM_AM - Hotspots of arbuscular mycorrhizal alpha diversityGSM_AgarNM - Hotspots of non-EcM Agaricomycetes alpha diversityGSM_Mold - Hotspots of mold alpha diversityGSM_Pathog - Hotspots of opportunistic human parasitic fungal alpha diversityGSM_OHP - Hotspots of putative pathogenic fungal alpha diversityGSM_Unicel - Hotspots of unicellular, non-yeast fungal alpha diversityGSM_Yeast - Hotspots of yeast alpha diversityGSMc_PD - Hotspots of phylogenetic alpha diversityGSM_PDst - Hotspots of phylogenetic dispersionEcM_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, m2Alpha_S_AllFungi_Consensus - Richness of all fungi (S'tot), consensus mapAlpha_S_AllFungi_GSMc - Richness of all fungi (S'GSMc), based on GSMc datasetAlpha_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 communitiesBeta_Phylogenetic_Median - Median phylogenetic dissimilarity of fungal communitiesBeta_Phylogenetic_IQR - Interquartile range of phylogenetic dissimilarities of fungal communitiesGamma_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 codeThe 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

Authors

  • Vladimir Mikryukov ;
  • Olesya Dulya ;
  • Alexander Zizka ;
  • Mohammad Bahram ;
  • Niloufar Hagh-Doust ;
  • Sten Anslan ;
  • Oleh Prylutskyi ;
  • Manuel Delgado-Baquerizo ;
  • Fernando T. Maestre ;
  • R. Henrik Nilsson ;
  • Jaan Pärn ;
  • Maarja Öpik ;
  • Mari Moora ;
  • Martin Zobel ;
  • Mikk Espenberg ;
  • Ülo Mander ;
  • Abdul Nasir Khalid ;
  • Adriana Corrales ;
  • Ahto Agan ;
  • Aída M. Vasco-Palacios ;
  • Alessandro Saitta ;
  • Andrea C. Rinaldi ;
  • Annemieke Verbeken ;
  • Bobby P. Sulistyo ;
  • Boris Tamgnoue ;
  • Brendan Furneaux ;
  • Camila Duarte Ritter ;
  • Casper Nyamukondiwa ;
  • Cathy Sharp ;
  • César Marín ;
  • Daniyal Gohar ;
  • Darta Klavina ;
  • Dipon Sharmah ;
  • Dong Qin Dai ;
  • Eduardo Nouhra ;
  • Elisabeth Machteld Biersma ;
  • Elisabeth Rähn ;
  • Erin K. Cameron ;
  • Eske De Crop ;
  • Eveli Otsing ;
  • Evgeny A. Davydov ;
  • Felipe E. Albornoz ;
  • Francis Q. Brearley ;
  • Franz Buegger ;
  • Geoffrey Zahn ;
  • Gregory Bonito ;
  • Inga Hiiesalu ;
  • Isabel C. Barrio ;
  • Jacob Heilmann-Clausen ;
  • Jelena Ankuda ;
  • Jiri Doležal ;
  • John Y. Kupagme ;
  • Jose G. Maciá-Vicente ;
  • Joseph Djeugap Fovo ;
  • József Geml ;
  • Juha M. Alatalo ;
  • Julieta Alvarez-Manjarrez ;
  • Kadri Põldmaa ;
  • Kadri Runnel ;
  • Kalev Adamson ;
  • Kari Anne Bråthen ;
  • Karin Pritsch ;
  • Kassim I. Tchan ;
  • Kęstutis Armolaitis ;
  • Kevin D. Hyde ;
  • Kevin K. Newsham ;
  • Kristel Panksep ;
  • Adebola A. Lateef ;
  • Linda Hansson ;
  • Louis J. Lamit ;
  • Malka Saba ;
  • Maria Tuomi ;
  • Marieka Gryzenhout ;
  • Marijn Bauters ;
  • Meike Piepenbring ;
  • Nalin Wijayawardene ;
  • Nourou S. Yorou ;
  • Olavi Kurina ;
  • Peter E. Mortimer ;
  • Peter Meidl ;
  • Petr Kohout ;
  • Rasmus Puusepp ;
  • Rein Drenkhan ;
  • Roberto Garibay-Orijel ;
  • Roberto Godoy ;
  • Saad Alkahtani ;
  • Saleh Rahimlou ;
  • Sergey V. Dudov ;
  • Sergei Põlme ;
  • Soumya Ghosh ;
  • Sunil Mundra ;
  • Talaat Ahmed ;
  • Tarquin Netherway ;
  • Terry W. Henkel ;
  • Tomas Roslin ;
  • Vincent Nteziryayo ;
  • Vladimir E. Fedosov ;
  • Vladimir G. Onipchenko ;
  • W. A. Erandi Yasanthika ;
  • Young Woon Lim ;
  • Michael E. Van Nuland ;
  • Nadejda Soudzilovskaia ;
  • Alexandre Antonelli ;
  • Urmas Kõljalg ;
  • Kessy Abarenkov ;
  • Leho Tedersoo
0 Citations3 Mentions73% FAIR1.9 Dataset Index
10.5281/zenodo.80134482023

Connecting the multiple dimensions of global soil fungal diversity (Version: 1.0.0)

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 overviewThese 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 descriptionAlpha 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 ApplicabilityIn 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 mapGSM_All - Hotspots of total fungal alpha diversity, based on the GSMc datasetGSM_EcM - Hotspots of ectomycorrhizal alpha diversityGSM_AM - Hotspots of arbuscular mycorrhizal alpha diversityGSM_AgarNM - Hotspots of non-EcM Agaricomycetes alpha diversityGSM_Mold - Hotspots of mold alpha diversityGSM_Pathog - Hotspots of opportunistic human parasitic fungal alpha diversityGSM_OHP - Hotspots of putative pathogenic fungal alpha diversityGSM_Unicel - Hotspots of unicellular, non-yeast fungal alpha diversityGSM_Yeast - Hotspots of yeast alpha diversityGSMc_PD - Hotspots of phylogenetic alpha diversityGSM_PDst - Hotspots of phylogenetic dispersionEcM_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, m2Alpha_S_AllFungi_Consensus - Richness of all fungi (S'tot), consensus mapAlpha_S_AllFungi_GSMc - Richness of all fungi (S'GSMc), based on GSMc datasetAlpha_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 communitiesBeta_Phylogenetic_Median - Median phylogenetic dissimilarity of fungal communitiesBeta_Phylogenetic_IQR - Interquartile range of phylogenetic dissimilarities of fungal communitiesGamma_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 codeThe 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

Authors

  • Vladimir Mikryukov ;
  • Olesya Dulya ;
  • Alexander Zizka ;
  • Mohammad Bahram ;
  • Niloufar Hagh-Doust ;
  • Sten Anslan ;
  • Oleh Prylutskyi ;
  • Manuel Delgado-Baquerizo ;
  • Fernando T. Maestre ;
  • R. Henrik Nilsson ;
  • Jaan Pärn ;
  • Maarja Öpik ;
  • Mari Moora ;
  • Martin Zobel ;
  • Mikk Espenberg ;
  • Ülo Mander ;
  • Abdul Nasir Khalid ;
  • Adriana Corrales ;
  • Ahto Agan ;
  • Aída M. Vasco-Palacios ;
  • Alessandro Saitta ;
  • Andrea C. Rinaldi ;
  • Annemieke Verbeken ;
  • Bobby P. Sulistyo ;
  • Boris Tamgnoue ;
  • Brendan Furneaux ;
  • Camila Duarte Ritter ;
  • Casper Nyamukondiwa ;
  • Cathy Sharp ;
  • César Marín ;
  • Daniyal Gohar ;
  • Darta Klavina ;
  • Dipon Sharmah ;
  • Dong Qin Dai ;
  • Eduardo Nouhra ;
  • Elisabeth Machteld Biersma ;
  • Elisabeth Rähn ;
  • Erin K. Cameron ;
  • Eske De Crop ;
  • Eveli Otsing ;
  • Evgeny A. Davydov ;
  • Felipe E. Albornoz ;
  • Francis Q. Brearley ;
  • Franz Buegger ;
  • Geoffrey Zahn ;
  • Gregory Bonito ;
  • Inga Hiiesalu ;
  • Isabel C. Barrio ;
  • Jacob Heilmann-Clausen ;
  • Jelena Ankuda ;
  • Jiri Doležal ;
  • John Y. Kupagme ;
  • Jose G. Maciá-Vicente ;
  • Joseph Djeugap Fovo ;
  • József Geml ;
  • Juha M. Alatalo ;
  • Julieta Alvarez-Manjarrez ;
  • Kadri Põldmaa ;
  • Kadri Runnel ;
  • Kalev Adamson ;
  • Kari Anne Bråthen ;
  • Karin Pritsch ;
  • Kassim I. Tchan ;
  • Kęstutis Armolaitis ;
  • Kevin D. Hyde ;
  • Kevin K. Newsham ;
  • Kristel Panksep ;
  • Adebola A. Lateef ;
  • Linda Hansson ;
  • Louis J. Lamit ;
  • Malka Saba ;
  • Maria Tuomi ;
  • Marieka Gryzenhout ;
  • Marijn Bauters ;
  • Meike Piepenbring ;
  • Nalin Wijayawardene ;
  • Nourou S. Yorou ;
  • Olavi Kurina ;
  • Peter E. Mortimer ;
  • Peter Meidl ;
  • Petr Kohout ;
  • Rasmus Puusepp ;
  • Rein Drenkhan ;
  • Roberto Garibay-Orijel ;
  • Roberto Godoy ;
  • Saad Alkahtani ;
  • Saleh Rahimlou ;
  • Sergey V. Dudov ;
  • Sergei Põlme ;
  • Soumya Ghosh ;
  • Sunil Mundra ;
  • Talaat Ahmed ;
  • Tarquin Netherway ;
  • Terry W. Henkel ;
  • Tomas Roslin ;
  • Vincent Nteziryayo ;
  • Vladimir E. Fedosov ;
  • Vladimir G. Onipchenko ;
  • W. A. Erandi Yasanthika ;
  • Young Woon Lim ;
  • Michael E. Van Nuland ;
  • Nadejda Soudzilovskaia ;
  • Alexandre Antonelli ;
  • Urmas Kõljalg ;
  • Kessy Abarenkov ;
  • Leho Tedersoo
0 Citations0 Mentions77% FAIR0.5 Dataset Index
10.5281/zenodo.80134472023