DOI: 10.6084/m9.figshare.27730890.v1
title: Soil microbial Volatile Organic Compounds (mVOCs) as biomarkers for grasslands across a land use gradient

description: Soil microbial Volatile Organic Compounds (mVOCs) as biomarkers for grasslands across a land use gradientDescription of the data and file structureSoil and microbial volatile organic compound (mVOC) data were collected from 18 permanent grasslands in the Ooijpolder region, The Netherlands, varying in land-use intensity (conventional, extensive, and semi-natural). Sampling took place in October and November 2022, with three plots per grassland, to study mVOC soil profiles in relation to their microbial community. Soil VOCs were extracted with VOC probes at 0-25 cm depth (Markes, UK) and captured in thermal desorption tubes to be analyzed via gas chromatography-mass spectrometry. Soil chemical, physical, and microbial data, including soil moisture, temperature, pH, nutrients, microbial DNA sequencing (16S and ITS2), and plant diversity, were gathered to correlate with mVOC profiles and microbial community composition. Statistical analyses examined differences in mVOC profiles and microbial communities across land-use types and explored their associations with soil properties.Files and variablesFile: Data_SBB24537.zip<b>Description:</b>Metadata forMicrobial scents: Soil microbial Volatile Organic Compounds (mVOCs) as biomarkers for grasslands across a land use gradientRosa W.C. Boone1,*, Joris Meurs2, Riikka Rinnan3, Hannie de Caluwe1, Anouk A. Wakely1, Jan-Willem Takke1 Simona M. Cristescu2, Wim H. van der Putten4,5, Hans de Kroon1 and Bjorn J.M. Robroek1,61 Department of Ecology, Radboud Institute for Biological and Environmental Sciences, Faculty of Science, Radboud University, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands2 Life Science Trace Detection Laboratory, Department of Analytical Chemistry & Chemometrics, Faculty of Science Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands.3 Center for Volatile Interactions (VOLT), Department of Biology, University of Copenhagen, Universitetsparken 15, DK, 2100 Copenhagen, Denmark4 Department of Terrestrial Ecology, NIOO-KNAW, Wageningen, The Netherlands5 Department of Nematology, Wageningen University & Research, Wageningen, The Netherlands6 School of Biological Sciences, University of Southampton, Life Sciences Building, Highfield Campus, Southampton SO17 1BJ,United Kingdom* Corresponding author. rosa.boone@ru.nl (R.W.C. Boone)Metadata belonging to the files:Folder: VOCENV_VOC_management.csv; containing data on management practices from questionnaires, environmental parameters from soil analysis and field observations.Column names- Name: [character] Sample ID’s from sampling locations (three replicates per field).- Type: [character] Land use intensity type from grasslands- Age_grassland: [numeric] age (in years) of grasslands, time since conversion to grassland- Age_management: [numeric] age (in years) of management, time since management has been implemented- Grasscutting_year: [numeric] number of mowing events per year- Grazing_months: [numeric] number of months per year that grassland is been used for grazing- GVE_ha: [numeric] unit of livestock per hectare of grassland- Extra_feeding: [binary] Yes = 1, No = 0 to question whether cows have received extra feeding (roughage)- Manure: [factor w/ 3 levels]- Pesticide_use: [binary] Yes = 1, No = 0 to question whether farmers have used pesticides in last 10 years of management- Chem_fert_use: [binary] Yes = 1, No = 0 to question whether farmers have used chemical fertiliser in last 10 years of management- Amount_manure_solid_m3: [numeric] amount of solid manure that fields receive per year in cubic meters.- Moisture_content_perc: [numeric] percentage moisture content from soil sample, dried at 105 °C.- BD_0_10: [numeric] dry soil bulk density from 0-10 cm soil layer- OM_perc: [numeric] organic matter content percentage from soil sample, dried at 550 °C- Nitrogen_perc: [numeric] percentage nitrogen from soil sample, measured with Elemental Analyser- SOC_perc: [numeric] percentage soil organic carbon from soil sample, measured with Elemental Analyser- pH: [numeric] value of pH, extracted with NaCl2 soil extraction- Al_NaCl_kg_ha: [numeric] amount of aluminium (kg per hectare) in grassland, extracted with NaCl2 soil extraction and measured on Auto Analyser- Ca_NaCl_kg_ha: [numeric] amount of calcium (kg per hectare) in grassland, extracted with NaCl2 soil extraction and measured on Auto Analyser- Fe_NaCl_kg_ha: [numeric] amount of iron (kg per hectare) in grassland, extracted with NaCl2 soil extraction and measured on Auto Analyser- K_NaCl_kg_ha: [numeric] amount of potassium (kg per hectare) in grassland, extracted with NaCl2 soil extraction and measured on Auto Analyser- Mg_NaCl_kg_ha: [numeric] amount of magnesium (kg per hectare) in grassland, extracted with NaCl2 soil extraction and measured on Auto Analyser- Mn_NaCl_kg_ha: [numeric] amount of manganese (kg per hectare) in grassland, extracted with NaCl2 soil extraction and measured on Auto Analyser- P_NaCl_kg_ha: [numeric] amount of phosphate (kg per hectare) in grassland, extracted with NaCl2 soil extraction and measured on Auto Analyser- S_NaCl_kg_ha: [numeric] amount of sulfate (kg per hectare) in grassland, extracted with NaCl2 soil extraction and measured on Auto Analyser- Olsen_P_kg_ha: [numeric] amount of plant-available phosphate (kg per hectare) in grassland, extracted with P Olsen soil extraction and measured on Auto Analyser- NaCl_NO3_kg_ha: [numeric] amount of nitrate (kg per hectare) in grassland, extracted with NaCl2 soil extraction and measured on Auto Analyser- NaCl_NH4_kg_ha: [numeric] amount of ammonium (kg per hectare) in grassland, extracted with NaCl2 soil extraction and measured on Auto Analyser- Average_fieldsoiltemp: [numeric] average field soil temperature °C- Average_fieldsoilmois: [numeric] average field soil moisture in percentage- Plant_richness: [numeric] number of individual species recorded with Braun-Blanquet within 2 x 2 m plot in grasslandPeak_area_for_analysis_filtered_TIC_norm.csv; containing peak surface areas per compound as analysed with PARADISe, normalized for total ion current (TIC)Column names- CompoundName: [character] name of sample ID- Type: [Factor w/ 3 levels] land use intensity type per sample- Field: [character] code name of field- Plot: [character] code name of plot (three per field)- Columns E-DT: [numeric] peak surface area per compound as analysesd with PARADISe, normalized for total ion current (TIC).IDs_checked_and_classes_BVOCS.csv; containing information on chemical classes and microbial origin from PARADISe derived compoundsColumn names- Nr: [numeric] number of compound ID’s- VOC_dataset: [character] name of compound in VOC dataset, as used in analysis.- Original: [character] name of compound as annotated in PARADISe with NIST library, adapted to R coding language- Ids_corrected: [character] name of compound, after correction for cross-referencing and validation with standard mixtures- Paradise Report Name: [character] original name of compound as annotated in PARADISe with NIST library- Est. Retention Time (min): [numeric] estimated retention time of compound as identified with PARADISe software- Hit 1: CAS: [numeric] CAS code for identification of compound- Microbial origin: [character] result of mVOC library search per compound.- Based on: [character] references for mVOC library search- Removed?: [binary] based on “Microbial origin”, a decision was made whether or not to remove the compound from further analysis- Titan?: [binary] whether or not the compound is identified with the Titan2 analysis in R- Classes: [character] chemical classes belonging to compounds, as identified with PubchemIDvoc_classes_transposed.csv; containing summed peak areas of transposed VOC classes from vocs_classes that was made in VOC.R script. Decision was made to manually edit the file in excel.Cells contain normalised peak areas per class for each field plot.Genus_abund_16S.csv; containing relative abundance per individual taxa for 16S dataset that was created in 16S.R script. Original file can be found in Data_SBB24537/16S/Output/taxa_abund/Genus_abundGenus_abund_ITS2.csv; containing relative abundance per individual taxa for ITS2 dataset that was created in ITS2.R script. Original file can be found in Data_SBB24537/ITS2/Output/taxa_abund/Genus_abundpc1_axis_16S.csv; containing values of PC1 axis per field plot, derived from Principle Coordinate Analysis (PCoA) from 16S community composition, as created with 16S.R script. Original file can be found in Data_SBB24537/16S/Output/pc1_axis_16S.csvpc1_axis_ITS2.csv; containing values of PC1 axis per field plot, derived from Principle Coordinate Analysis (PCoA) from ITS2 community composition, as created with ITS2.R script. Original file can be found in Data_SBB24537/ITS2/Output/pc1_axis_ITS2.csv16S_TITAN_20240508.RData; R dataset containing the saved output of the 16S threshold indicator taxa analysis (TITAN2) in R. Results were saved due to slight variations in output from random permutations.ITS2_TITAN_20240508.RData; R dataset containing the saved output of the ITS2 threshold indicator taxa analysis (TITAN2) in R. Results were saved due to slight variations in output from random permutations.vocs_TITAN_20240612; R dataset containing the saved output of the VOC threshold indicator taxa analysis (TITAN2) in R. Results were saved due to slight variations in output from random permutations.VOC.R; R script for analysis of LUE gradient, VOC data and TITAN analysis.Output (file folder); containing all outputs from VOC.R scriptFolder: 16SSeptokt_16S_seqtab_nochim.RData; R dataset containing sequence table after removing chimeric sequences, analysis done in Dada2Septokt2022_16S_taxa.RData: R dataset containing taxonomic classifications of the amplicon sequence variants (ASVs) present in sequence table, analysis done in Dada2Sampledatafile_septokt_2022.csv: containing type of land use intensity per sampleColumn names- Group: [character] land use intensity type- Field: [character] code name of field16S.R; R script for analysis of 16S sequencing table and taxa table derived from DADA2 (Callahan et al. 2016) processing with the microeco package (Liu et al., 2021).Output (file folder); containing all outputs from 16S.R scriptFolder: ITS2Septokt_ITS2_seqtab_nochim.RData; R dataset containing sequence table after removing chimeric sequences, analysis done in Dada2Septokt2022_ITS2_taxa.RData: R dataset containing taxonomic classifications of the amplicon sequence variants (ASVs) present in sequence table, analysis done in Dada2Sampledatafile_septokt_2022.csv: containing type of land use intensity per sampleColumn names- Group: [character] land use intensity type- Field: [character] code name of fieldITS2.R; R script for analysis of ITS2 sequencing table and taxa table derived from DADA2 (Callahan et al. 2016) processing with the microeco package (Liu et al., 2021).Output (file folder); containing all outputs from ITS2.R scriptCode/softwareR studio was used to run the scripts.Scripts can be found in the zip.fileVOC.R; R script for analysis of LUE gradient, VOC data and TITAN analysis.16S.R; R script for analysis of 16S sequencing table and taxa table derived from DADA2 (Callahan et al. 2016) processing with the microeco package (Liu et al., 2021).ITS2.R; R script for analysis of ITS2 sequencing table and taxa table derived from DADA2 (Callahan et al. 2016) processing with the microeco package (Liu et al., 2021).