Data of "Conditional love? Co-occurrence patterns of drought-sensitive species in European grasslands are consistent with the stress gradient hypothesis"

DOI

This dataset was developed for our study on the spatial associations between plant species along a drought gradient in European grasslands. We obtained species occurrences for 161 species from the European Vegetation Archives for 20,722 georeferenced vegetation plots located in dry grasslands across Europe. We also extracted a set of environmental variables from various sources for each vegetation plot. This data was used in a context-dependent Joint Species Distribution Model (JSDMs) to determine how the residual spatial associations (i.e. spatial associations that can’t be explained from the included environmental predictors) shift along a drought gradient. We compared the observed shifts in spatial associations with expectations from the stress-gradient hypothesis while accounting for differences in species’ drought tolerance.The results of this research are published in:de Jonge, M. M., Benítez‐López, A., Hennekens, S., Santini, L., Huijbregts, M. A., & Schipper, A. M. (2021). Conditional love? Co‐occurrence patterns of drought‐sensitive species in European grasslands are consistent with the stress‐gradient hypothesis. Global Ecology and Biogeography, 30(8), 1609-1620.The data and associated code used in this study are publicly available in an archived GitHub repository: https://github.com/MelindadeJonge/ConditionalLoveIn this repository we provide only the processed data from this study because the original data was gathered from existing open access and semi-open access databases.Original data from this project was gathered from the following databases:●European Vegetation Archives (project no. 44)●CHELSA Climatologies dataset v.1.4●SoilGrids1km●Species’ Ellenberg values for soil moistureData filesThe processed data is stored in 4 files●2021_deJonge_PlotInfo.csv: This file contains spatial and plot-level information for all 20,722 vegetation plots used in this study. Vegetation plots are identified by their unique plotID numbers.●2021_deJonge_Occurrences.csv: This file contains the presences/absence matrix of all 161 species (columns) in the vegetation plots (rows) included in this analysis. The first column contains the plotID.●2021_deJonge_Predictors.csv: This file contains the corresponding bioclimatic (minimum temperature of the coldest month, climatic water deficit, precipitation seasonality) and soil variables (organic carbon content, cation exchange capacity, pH) for each vegetation plot.●2021_deJonge_SpeciesList.csv: This file contains the latin name, Ellenberg value for soil moisture and taxonomic information associated with all 161 species included in the study.Additional informationAn overview of the definitions and units of the variables in each file is given in the codebook: “2021_deJonge_Codebook.pdf”A description of the methodology used to obtain the processed data is given in ‘2021_deJonge_Methodology.pdf”A list of the original datasets obtained from the European Vegetation Archives together with their respective data custodians and the number of plots included in this analyses is given in “2021_deJonge_Custodians.pdf”

Identifier
DOI https://doi.org/10.17026/dans-zvw-gpbn
Metadata Access https://lifesciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-zvw-gpbn
Provenance
Creator M.M.J. de Jonge; A. Benítez‐López; S.M. Hennekens; L. Santini; M.A.J. Huijbregts; A.M. Schipper
Publisher DANS Data Station Life Sciences
Contributor RU Radboud University
Publication Year 2022
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact RU Radboud University
Representation
Resource Type Dataset
Format application/pdf; text/csv; application/zip
Size 148030; 21919; 66071; 86960; 6829474; 1132704; 1799048; 9346; 25262
Version 2.0
Discipline Biospheric Sciences; Earth and Environmental Science; Ecology; Environmental Research; Geosciences; Life Sciences; Medicine; Natural Sciences