DOI: 10.5061/dryad.zpc866tcv
title: Data from: The spatial patterns of community composition, their environmental drivers and their spatial scale dependence vary markedly between fungal ecological guilds

description: Aim How community composition varies in space and what governs the
 variation has been extensively investigated in macroorganisms. However, we
 have only limited knowledge for microorganisms, especially fungi, despite
 their ecological and economic significance. Based on previous research, we
 define and test a series of hypotheses regarding the composition of fungal
 communities, its most influential drivers and their spatial scale
 dependence. Location Czech Republic. Time period Present. Taxa studied
 Fungi. Methods We analyzed the distance decay relationships, community
 composition and its drivers (physical distance, litter and soil chemistry,
 tree composition, climate) in fungi, using multivariate analyses. We
 compared the results across three fungal ecological guilds
 (ectomycorrhizal fungi, saprotrophs and yeasts), two forest microhabitats
 (litter and bulk soil) and six spatial scales (from 5 m to 80 km) that
 comprehensively cover the Czech Republic. Results We found that, similar
 to macroorganisms, the ectomycorrhizal fungi and saprotrophs showed marked
 distance-decay relationships, and their community composition was driven
 mainly by vegetation and dispersal at local scales, but at regional
 scales, by environmental effects. In contrast, the third fungal guild, the
 unicellular yeasts, showed little distance decay, suggesting extraordinary
 spatial homogeneity, as often seen in microorganisms, such as bacteria.
 Main conclusions Our results underscore the remarkable variation in the
 community ecology of fungi, which seems to range well-known patterns both
 from the macro- and the microworld. Knowledge of these patterns advances
 our understanding of the ecology of fungi, rather understudied organisms
 of significant ecological and economic importance, which our findings
 identify as a potentially suitable model for bridging the gaps between the
 biogeography of micro- and macroorganisms. 
description: # Data from: The spatial patterns of community composition, their
 environmental drivers and their spatial scale dependence vary markedly
 between fungal ecological guilds ## Description of the Data and file
 structure The zipped file in Dryad contains the data necessary to
 reproduce the statistical analyses published in the manuscript "The
 spatial patterns of community composition, their environmental drivers and
 their spatial scale dependence vary markedly between fungal ecological
 guilds" in Global Ecology and Biogeography by Odriozola et al. To run
 the R code in Zenodo, the zip containing the dataset should be unzipped to
 a folder and set that folder as working directory in the beginning of the
 script. The four datasets in the folder
 "Odriozola\_etal\_2023\_data": **OTU\_table.csv**: Sequence
 counts of Operational Taxonomic Units of fungi collected in six datasets
 representing different spatial scales across the Czech Republic.
 **Environment.csv**: Environmental variables measured in six datasets
 representing different spatial scales across the Czech Republic. * Sample
 Unique identifier of each sampling unit. * Horizon Classification of
 samples into litter and soil. * lat Latitude of the sample location. *
 long Longitude of the sample location. * Ntot Total N content of litter
 and soil samples (%). * Cox Organic C content of litter and soil samples
 (%). * C/N C to N ratio of litter and soil samples. * pH pH measured at
 litter and soil samples. * Herb layer % cover of the herb layer. * Stand
 age Years since the last disturbance of the stand. * BIO01 Mean annual
 daily mean air temperatures averaged over 1 year (C). * BIO02 Mean diurnal
 range of temperatures averaged over 1 year (C). * BIO03 Ratio of diurnal
 variation to annual variation in temperatures (C). * BIO04 Standard
 deviation of the monthly mean temperatures (C/100). * BIO05 The highest
 temperature of any monthly daily mean maximum temperature (C). * BIO06 The
 lowest temperature of any monthly daily mean maximum temperature (C). *
 BIO07 The difference between the Maximum Temperature of Warmest month and
 the Minimum Temperature of Coldest month (C). * BIO08 The wettest quarter
 of the year is determined (to the nearest month) (C). * BIO09 The driest
 quarter of the year is determined (to the nearest month) (C). * BIO10 The
 warmest quarter of the year is determined (to the nearest month) (C). *
 BIO11 The coldest quarter of the year is determined (to the nearest month)
 (C). * BIO12 Accumulated precipitation amount over 1 year (kg m-2). *
 BIO13 The precipitation of the wettest month (kg m-2). * BIO14 The
 precipitation of the driest month (kg m-2). * BIO15 The Coefficient of
 Variation is the standard deviation of the monthly precipitation estimates
 expressed as a percentage of the mean of those estimates (i.e. the annual
 mean) (kg m-2). * BIO16 The wettest quarter of the year is determined (to
 the nearest month) (kg m-2). * BIO17 The driest quarter of the year is
 determined (to the nearest month) (kg m-2). * BIO18 The warmest quarter of
 the year is determined (to the nearest month) (kg m-2). * BIO19 The
 coldest quarter of the year is determined (to the nearest month) (kg m-2).
 **Vegetation.csv**: Vegetation survey of the sampled locations with %
 cover of each species. Sample Unique identifier of each sampling unit.
 **Taxonomy\_Ecology.csv**: Taxonomic and ecological guild assignments of
 Operational Taxonomic Units of fungi.