DOI: 10.5061/dryad.h44j0zps5
title: Data from: Uniqueness of tree stand composition and soil microbial communities are related across urban spruce-dominated forests

description: The dataset contains data obtained from urban spruce-dominated forests in
 southern Finland where we have measured tree stand composition, forest
 management history, soil chemical properties, and soil microbial
 communities. Data files include (1) microbial OTU tables describing
 microbial community composition (sequence read counts of Operational
 Taxonomic Units) across the study plots, (2) taxonomic assignments and
 other metadata related to OTUs, and (3) measured and calculated variables
 describing the characteristics of sites and their microbial assemblages
 (site metadata).
description: Method description below are summarized from the original
 publication. Study
 area and sample plots We collected data from 73 forest plots
 distributed in three urban centers in southern Finland: Helsinki region
 (45 sites in cities of Helsinki, Espoo and Vantaa), Lahti (8
 sites), and Tampere (20 sites). Sample plots consisted of four
 interconnected 20 m × 20 m squares that were placed inside forest
 stands. Measurement
 of forest stand characteristics All living trees ≥ 5 cm at breast height (1.3 m)
 and all cut tree stumps with diameter ≥ 10 cm at cut surface were measured
 within the study plots. We assessed the degree of urbanization around
 sample plots by calculating the proportion of built land surface within
 200 m radius around sample plot center based on Corine Land Cover 2018
 GIS-dataset. Soil sampling
 Soil sampling was done between
 May 19th and July 19th 2022. Samples were collected from 16 regularly
 spaced grid points across each 0.16 ha study plot. Minimum distance
 between two sampling points was 10 m. At each point, we collected ca. 0.5
 dl of material from the humus layer between the undecomposed litter layer
 and mineral soil. After removing the undecomposed surface litter and
 roots, material was extracted with a DNA-sterilized hand shovel down to
 the boundary between humus layer and mineral soil to a maximum depth of 15
 cm. Samples were sieved through 2 mm mesh and stored in -20°C until
 further processing. Soil chemical analyses
 We measured the carbon (C) and
 nitrogen (N) content of the soil samples from combustion products with an
 elemental analyzer. We measured ergosterol as biomarker of fungal biomass.
 Ergosterol was extracted from 0.25 g soil samples and quantified
 with liquid chromatography. DNA extraction and
 sequencing DNA was extracted from two ca. 200 mg portions
 of material from each sample. For bacterial metabarcoding, V4 region of
 the 16S ribosomal RNA gene was amplified with primers 515F
 (GTGCCAGCMGCCGCGGTAA) and 806R (GGACTACHVGGGTWTCTAAT). For fungal
 metabarcoding, the Internal Transcribed Spacer 2 (ITS2) of the nuclear
 ribosomal RNA coding region was amplified with primers ITS3-2024F
 (GCATCGATGAAGAACGCAGC) and ITS4-2409R (TCCTCCGCTTATTGATATGC). Indexed
 amplicons were sequenced with Illumina NovaSeq 6000 (paired-end 250
 bp). Bioinformatics
 Sequence reads were demultiplexed, and index
 and primer sequences were
 removed from paired-end reads (data available under BioProject ID
 PRJNA1012880 in NCBI sequence read archive). Individual R1 and R2 reads
 were first quality filtered, and then assembled. Assembled reads were
 chimera filtered de novo. Remaining reads were clustered into OTUs with
 98% similarity threshold. OTUs were taxonomically assigned with 80%
 confidence cutoff using Naïve Bayesian Classifier trained with bacterial
 SILVA (v138) and fungal UNITE (v9, dynamic, all eucaryotes) databases
 in <em>mothur</em> v.1.36.1. Fungal OTUs were further assigned
 to functional groups according to FungalTraits database based on
 genus-level taxonomical assignments. OTU tables were finally filtered by
 discarding bacterial OTUs that had less than 1‰ relative abundance and
 fungal OTUs that had less 0.1‰ relative abundance in all samples and OTUs
 that had maximum read counts in negative controls.
 Data
 Preparation We calculated diversity
 indices for all bacteria, ectomycorrhizal (ECM) fungi and saprotrophic
 (SAP) fungi. We considered SAP fungi to include soil, litter, wood and
 unspecified saprotrophs. We estimated Shannon diversity with sample read
 depth of 30k for bacteria, 60k for ECM fungi, and 55k for SAP fungi using
 the <em>estimate</em>D function in the R
 package <em>iNEXT</em> (v3.0.9). To quantify the relative
 contributions of sites to taxonomic turnover of bacteria, ECM fungi and
 SAP fungi, we calculated local contributions to species replacement
 (LCBD<sub>repl</sub>) based on distance matrices representing
 the replacement component of beta diversity using
 the<em> beta.div.comp</em>
 and<em> LCBD.comp</em> functions in the R
 package <em>adespatial </em>(v0.3-21). We calculated
 LCBD<sub>repl</sub> for bacteria based on the quantitative
 indices of replacement (Sørensen, Podani family) and
 LCBD<sub>repl</sub> for fungi based on presence-absence
 (Jaccard, Podani family). We counted OTUs with relative abundance
 &gt;0.1‰ as present. To avoid conflating fungal taxa with (potentially
 artefactual) intraspecific sequence variants and other sequence reads with
 uncertain taxonomic affinity, we restricted the analysis to fungal OTUs
 that were identified to species-level and pooled together OTUs that were
 assigned to the same species before determining presence-absence. To
 quantify management intensity in forest sites, we reduced the logging
 history data (basal areas of cut stumps in five different decay classes)
 into two main gradients by running a principal component analysis on
 square root transformed basal areas of cut stumps and extracting site
 scores for the two first principal components. To quantify forest tree
 diversity at each site, we calculated the number of ECM tree species (ECM
 tree richness), Shannon diversity of tree species (TreeDiv) based on
 relative basal areas, and an index of relative uniqueness of tree stand
 composition (LCBD-Trees). LCBD Trees was calculated from a distance matrix
 (Sørensen, Podani family) derived from tree composition data (square root
 transformed basal areas of tree species).
description: # Data from: Uniqueness of tree stand composition and soil microbial
 communities are related across urban spruce-dominated forests
 [https://doi.org/10.5061/dryad.h44j0zps5](https://doi.org/10.5061/dryad.h44j0zps5) Data originate from urban spruce-dominated forests in southern Finland where we have measured tree stand composition, forest management history, soil chemical properties and soil microbial communities. Data files include (1) microbial OTU tables describing microbial community composition (sequence read counts of Operational Taxonomic Units) across the study plots, (2) taxonomic assignments and other metadata related to OTUs, and (3) measured and calculated variables describing the characteristics of sites and their microbial assemblages (site metadata). ## Description of the data and file structure DATA & FILE OVERVIEW DATA-SPECIFIC INFORMATION FOR: 'Korhonen et al 2023 OTU_table_Bacteria.csv' 1\. Number of variables/columns: 491 data columns + 1 header column (site names) 2\. Number of cases/rows: 73 data rows + 1 header row (OTU names) 3\. Column separator: ; DATA-SPECIFIC INFORMATION FOR: 'Korhonen et al 2023 OTU_table_Fungi.csv' 1\. Number of variables/columns: 4157 data columns + 1 header column (site names) 2\. Number of cases/rows: 73 data rows + 1 header row (site names) 3\. Column separator: ; DATA-SPECIFIC INFORMATION FOR: 'Korhonen et al 2023 OTU_metadata_Bacteria.csv' 1\. Number of variables/columns: 17 2\. Number of cases/rows: 491 data rows + 1 header row 3\. Column separator: ; 4\. Column explanations Col 1: OTU_ID Unique identifiers of bacterial OTUs Col 2: OTU_ID_original Unique identifiers of bacterial OTUs generated by the bioinformatic pipeline Col 3: RepSeq Representative sequences of bacterial OTUs Col 4: D Taxonomic assignment to Domain Col 5: D% Support for taxonomic assignment to Domain (values 80-100, NA when &lt;80) Col 6: P Taxonomic assignment to Phylum Col 7: P% Support for taxonomic assignment to Phylum (values 80-100, NA when &lt;80) Col 8: C Taxonomic assignment to Class Col 9: C% Support for taxonomic assignment to Class (values 80-100, NA when &lt;80) Col 10: O Taxonomic assignment to Order Col 11: O% Support for taxonomic assignment to Order (values 80-100, NA when &lt;80) Col 12: F Taxonomic assignment to Family Col 13: F% Support for taxonomic assignment to Family (values 80-100, NA when &lt;80) Col 14: G Taxonomic assignment to Genus Col 15: G% Support for taxonomic assignment to Genus (values 80-100, NA when &lt;80) Col 16: S Taxonomic assignment to Species Col 17: S% Support for taxonomic assignment to Species (values 80-100, NA when &lt;80) DATA-SPECIFIC INFORMATION FOR: 'Korhonen et al 2023 OTU_metadata_Fungi.csv' 1\. Number of variables/columns: 20 2\. Number of cases/rows: 4157 data rows + 1 header row 3\. Column separator: ; 4\. Column explanations Col 1: OTU_ID Unique identifiers of fungal OTUs Col 2: OTU_ID_original Unique identifiers of fungal OTUs generated by the bioinformatic pipeline Col 3: RepSeq Representative sequences of fungal OTUs Col 4: k Taxonomic assignment to Domain Col 5: k% Support for taxonomic assignment to Kingdom (values 80-100, NA when &lt;80) Col 6: p Taxonomic assignment to Phylum Col 7: p% Support for taxonomic assignment to Phylum (values 80-100, NA when &lt;80) Col 8: c Taxonomic assignment to Class Col 9: c% Support for taxonomic assignment to Class (values 80-100, NA when &lt;80) Col 10: o Taxonomic assignment to Order Col 11: o% Support for taxonomic assignment to Order (values 80-100, NA when &lt;80) Col 12: f Taxonomic assignment to Family Col 13: f% Support for taxonomic assignment to Family (values 80-100, NA when &lt;80) Col 14: g Taxonomic assignment to Genus Col 15: g% Support for taxonomic assignment to Genus (values 80-100, NA when &lt;80) Col 16: s Taxonomic assignment to Species Col 17: s% Support for taxonomic assignment to Species (values 80-100, NA when &lt;80) Col 18: Comment Lead author's personal comments on taxonomic assignment Col 19: LifeStyle Primary lifestyle based on genus-level taxonomic assignment from FungalTraits database Col 20: FinnishRedList2019 Species' Red List category (NT, DD, NE) according to the 2019 Red List of Finnish species. Value is NA if category is LC or undefined. DATA-SPECIFIC INFORMATION FOR: 'Korhonen et al 2023 Site_metadata.txt' 1\. Number of variables/columns: 63 2\. Number of cases/rows: 73 + 1 header row 3\. Column separator: ; 4\. Decimal separator for numeric variables: , 5\. Column explanations Col 1: Site Unique identifier of the sampling site, same as site names in OTU tables Col 2: City City of the sampling site (Helsinki, Espoo, Lahti, Tampere or Vantaa) Col 3: Region Region of the sapling site (Helsinki region, Lahti or Tampere) Col 4: Latitude Y coordinate (WGS 84) Col 5: Longitude X coordinate (WGS 84) Col 6: Local_dbMEM1 Distance-based Moran’s eigenvector calculated from geographic coordinates of study plots accounting for spatial autocorrelations within regions (&lt; 50 km distances) Col 7: Date Day when soil sample was collected Col 8: BasA_CutStumps_DecayClass_1 Basal area of decay class 1 cut stumps with diameter &gt;= 10 cm within the study plot (m²/ha) Col 9: BasA_CutStumps_DecayClass_2 Basal area of decay class 2 cut stumps with diameter &gt;= 10 cm within the study plot (m²/ha) Col 10: BasA_CutStumps_DecayClass_3 Basal area of decay class 3 cut stumps with diameter &gt;= 10 cm within the study plot (m²/ha) Col 11: BasA_CutStumps_DecayClass_4 Basal area of decay class 4 cut stumps with diameter &gt;= 10 cm within the study plot (m²/ha) Col 12: BasA_CutStumps_DecayClass_5 Basal area of decay class 5 cut stumps with diameter &gt;= 10 cm within the study plot (m²/ha) Col 13: Logging_recent Principal component corresponding to recent logging intensity (least decayed cut stumps) Col 14: Logging_old Principal component corresponding to old logging intensity (most decayed cut stumps) Col 15: Stem_density Number of tree stems with DBH &gt;= 5 cm within the study plot (number/ha) Col 16: Vascular_plant_cover Estimated proportion of the sample plot field layer that was covered by dwarf shrubs or herbaceous vascular plants Col 17: BasA_Picea Basal area of Picea trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 18: BasA_Pinus Basal area of Pinus trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 19: BasA_Betula Basal area of Betula trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 20: BasA_Populus Basal area of Populus trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 21: BasA_Sorbus Basal area of Sorbus trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 22: BasA_Alnus Basal area of Alnus trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 23: BasA_Salix Basal area of Salix trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 24: BasA_Quercus Basal area of Quercus trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 25: BasA_Acer Basal area of Acer trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 26: BasA_Corylus Basal area of Corylus stems with DBH &gt;= 5 cm within the study plot (m²/ha) Col 27: BasA_Tilia Basal area of Tilia trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 28: BasA_Prunus Basal area of Prunus trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 29: BasA_Abies Basal area of Abies trees with DBH &gt;= 5 cm within the study plot (m²/ha) Col 30: ECM_tree_richness Number of ectomycorrhizal tree genera present in the sample plot (Abies, Alnus, Betula, Corylus, Picea, Pinus, Populus, Quercus, Salix, Tilia) Col 31: TreeDiv Shannon diversity of tree species calculated from relative abundances in terms of basal area Col 32: LCBD_Trees Relative uniqueness of a site in terms of tree species composition Col 33: BuiltLand_200m Proportion of built land surface within 200 m radius around sample plot Col 34: CN_ratio Mass ratio of carbon and nitrogen in soil sample Col 35: pH Soil acidity Col 36: Al Aluminum content in soil samples (mg/kg dry weight) Col 37: B Boron content in soil samples (mg/kg dry weight) Col 38: C Carbon content in soil samples (proportion [0-1] of dry weight) Col 39: Ca Calcium content in soil samples (mg/kg dry weight) Col 40: Cr Chromium content in soil samples (mg/kg dry weight) Col 41: Cu Copper content in soil samples (mg/kg dry weight) Col 42: Fe Iron content in soil samples (mg/kg dry weight) Col 43: K Potassium content in soil samples (mg/kg dry weight) Col 44: Mg Magnesium content in soil samples (mg/kg dry weight) Col 45: Mn Manganese content in soil samples (mg/kg dry weight) Col 46: Na Sodium content in soil samples (mg/kg dry weight) Col 47: Ni Nickel content in soil samples (mg/kg dry weight) Col 48: P Phosphorus content in soil samples (mg/kg dry weight) Col 49: Pb Lead content in soil samples (mg/kg dry weight) Col 50: S Sulphur content in soil samples (mg/kg dry weight) Col 51: Zn Zinc content in soil samples (mg/kg dry weight) Col 52: Ergosterol Indicator of fungal biomass in soil samples (µg / g organic content) Col 53: Proteobacteria:Acidobacteria Ratio of relative read abundance of bacterial phyla Proteobacteria (i.e., Pseudomonadota) and Acidobacteriota Col 54: ECM_biomass Relative read abundance of ectomycorrhizal fungi * ergosterol (µg / g organic content) Col 55: SAP_biomass Relative read abundance of saprotrophic fungi * ergosterol (µg / g organic content) Col 56: Bacterial_diversity Rarefied estimate of bacterial Shannon Diversity Col 57: ECM_diversity Rarefied estimate of ectomycorrhizal fungal Shannon Diversity Col 58: SAP_diversity Rarefied estimate of saprotrophic fungal Shannon Diversity Col 59: LCBDrepl_BAC Local Contribution to the replacement component of Beta Diversity for bacterial, i.e., a measure of a site’s relative importance in bacterial OTU turnover across sites Col 60: LCBDrepl_ECM Local Contribution to the replacement component of Beta Diversity for ectomycorrhizal fungi, i.e., a measure of a site’s relative importance in ectomycorrhizal fungal species turnover across sites Col 61: LCBDrepl_SAP Local Contribution to the replacement component of Beta Diversity for saprotrophic fungi, i.e., a measure of a site’s relative importance in saprotrophic fungal species turnover across sites Col 62: RareECM Numer of rare (present in less than 10% of sites with at least 1 promille relative abundance) ectomycorrhizal fungal species Col 63: RareSAP Numer of rare (present in less than 10% of sites with at least 1 promille relative abundance) saprotrophic fungal species