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Data from: Landscape context and substrate characteristics shape fungal communities of dead spruce in urban and semi-natural forests

Citation

Korhonen, Aku; Miettinen, Otto; Kotze, Johan; Hamberg, Leena (2022), Data from: Landscape context and substrate characteristics shape fungal communities of dead spruce in urban and semi-natural forests, Dryad, Dataset, https://doi.org/10.5061/dryad.9w0vt4bfr

Abstract

Data from:

Korhonen, A., Miettinen, O., Kotze, D.J., & Hamberg, L. (2022). Landscape context and substrate characteristics shape fungal communities of dead spruce in urban and semi-natural forests. Environmental Microbiology. DOI: 10.1111/1462-2920.15903

This dataset contains occurrence data of 475 fungal ITS2 sequence clusters (OTUs) across 360 sequenced samples originating from dead wood of Norway spruce (Picea abies). Wood samples were collected from 90 downed spruce trunks, at four points from each trunk. Trunks were at intermediate stages of decay and located in spruce-dominated stands in 24 urban forests (66 trunks) and in 8 rural semi-natural forests (24 trunks) in southern Finland. The data consists of an OTU table (sequence read counts in each sample) and sample metadata (locality information, trunk characteristics and environmental variables).

Methods

All study sites represented forest stands with natural herb-rich to mesic heathland forest vegetation, Norway spruce (Picea abies) as the dominant tree species, and the age of dominant trees at least 60 years. Urban study sites (24 sites, 66 trunks) were distributed across the Helsinki metropolitan area (combined population of ca. 1.2 million) in southern Finland, and semi-natural study sites (8 sites, 24 trunks) in the surrounding rural areas. Urban sites represented deadwood hotspots within the urban landscape where deadwood had accumulated in large volumes locally. Semi-natural sites represented unmanaged stands with large volumes of deadwood and minimal signs of logging history and other human disturbances, including recreational use.

At each site, we searched for fallen Norway spruce trunks that were at intermediate stages of decay (predominantly decay class 3 according to Renvall’s (1995) five-stage classification) and had a diameter of 20–40 cm at 4–6 m from the base. Decay class 3 is defined as the stage in which the decaying trunk has already partly rotten (knife penetrates ca. 3–5 cm into the wood easily) but still retains its shape. At this decay stage, spruce trunks are mostly decorticated, and the wood surface is being colonized by epixylic lichens and bryophytes. In the urban area, 1–4 trunks were chosen per site depending on the availability of suitable tree trunks. In semi-natural areas, we chose three suitable trunks per site randomly.

All trunks were situated inside a closed forest with mean canopy openness of 23% (SD = 5). Distance between the trunk and the nearest forest edge varied from 7 to 589 m (Supplementary Table C1). Trunks in urban forests were generally closer to forest edges (median 53 m) than trunks in semi-natural forests (median 216 m). However, neither canopy openness nor distance to the forest edge had any significant associations with properties of the tree trunks.

Wood samples were collected from spruce trunks in October 2018. Four wood samples were taken from each tree trunk at 2, 4, 6, and 8 m distance from the base. Samples were extracted from the shadier side of the trunk. Epiphytes, bark and loose rotten wood were removed with a flame-sterilized knife to expose a clean surface of solid wood on the side of the trunk. Wood shavings were extracted with a flame-sterilized 6 mm diameter drill and collected into paper bags and stored at -20°C until DNA extraction.

DNA was extracted with a NucleoSpin Soil (Macherey-Nagel, Düren, DE) extraction kit from 112 ± 52 mg of sample material. Extraction was done according to the manufacturer’s instructions with lysis buffer SL2 and final elution in 30 µl volume. The ITS2 region was amplified using PCR with primers gITS7 (Ihrmark et al., 2012) and ITS4 (White et al., 1990) with 6 bp dual index for 28 cycles. The resulting PCR fragments were sequenced with the MiSeq v3 (Illumina, San Diego, US-CA) 2 × 300 bp paired-end system yielding 20–25 M raw sequence reads.

Quality filtering and the removal of artefacts, primer‐dimers and primers from raw sequence reads (NCBI BioSample accessions SAMN19307225-SAMN19307584 under BioProject PRJNA732060) were conducted with the PipeCraft 1.0 pipeline. Raw ITS sequence reads were processed according to the manual with the following specifications. Assembly of paired-end reads and initial quality filtering was conducted with vsearch v1.11.1 with the following parameters: minimum overlap 20, max differences 99, minimum length 150 bp, e_max 1, max ambiguous 0, and trunc qual 20. Chimera filtering was performed for the reoriented reads using reference-based filtering with Unite ITS2 ref. v7.1 as the database, also removing primers and primer artifacts from sequences at this step. In addition, the fungal ITS2 region was extracted from reads with ITSx.

The remaining 7.876 M sequences were then clustered with Swarm v2 algorithm (d = 1, fastidious = TRUE). These raw operational taxonomic units (OTUs) were identified to taxonomic groups with the Naïve Bayesian classifier using UNITE database v8.2 as the reference database and matched to the closest representative species hypothesis in the database using BLASTn. Raw OTUs that were assigned to the same named species with at least 90% confidence were then aggregated to combined OTUs. Raw OTUs that were not assigned to any named species-level taxon were compared to others that had the same UNITE species hypothesis as their closest match; if the representative sequence of an OTU had at least 97.5% sequence similarity to any other OTU in the same group, they were merged. Raw OTUs with < 97.5% similarity to any other OTU were retained as separate OTUs.

The diversity of fungal communities was measured with the Simpson diversity index. Before calculating the index, relative species (or OTU) abundances (read count divided by sample sequencing depth) were averaged between the two middlemost samples for each trunk (segments 2 and 3) to aggregate the data to trunk-level and to focus on the data that were most closely connected to the temperature measurement point within the tree trunk. Averaged species (or OTU) abundances were then used for calculating the index with R package iNEXT v.2.0.20.

To assess the value of tree trunks as habitat for WIF species of conservation concern, we recorded the number of red-listed species present in each individual trunk. We considered species included in the national or regional IUCN Red List assessments across the hemi- and southern boreal northeastern Europe, i.e., Estonia (see Runnel, Miettinen, and Lõhmus, 2021), Finland (Kotiranta et al., 2019), Norway (NBIC, 2019), Sweden (SLU Artdatabanken, 2020) and the Leningrad Region of Russian Federation (Geltman et al., 2018). A species was recorded as present if it accounted for at least 5‰ of the total sequence reads in at least one sample.

Characteristics of the downed spruce trunks were measured in June 2019. Measurements were taken from four 2 m segments between 1 and 9 m from the base of the tree trunk. Trunk diameter and distance between the bottom of the trunk and the soil surface directly below it was measured at the midpoint of each segment. Decay class (1–5) was determined for each segment based on knife penetration into the wood. Epiphyte cover (%) was measured for the top surface of each segment. Epiphyte cover consisted primarily of bryophyte mats. Wood moisture content (%), based on electric resistance, was measured (Moisture Meter ET-928, Clas Ohlson, Insjön, SE) from the shadier vertical side of the tree trunk at the midpoint of each segment. Measurements were made on an intact wood surface exposed by removing epiphytes, remains of bark and the most decayed layer of wood from the surface. The month of June, when all measurements were made, is at the end of the driest period of the year when wood moisture was expected to be close to the annual minimum.

Temperature inside each tree trunk was monitored between the spring and fall of 2019 with a datalogger (iButton Thermochron DS1921G-F5, Maxim Integrated, San Jose, US-CA) embedded in the middle of the trunk. Dataloggers were inserted into drilled holes that were sealed tightly with wooden plugs. Temperature measurements were recorded synchronously with 4 h intervals from 1 AM to 9 PM. To get an indication of how sensitive temperature inside the tree trunk was to external temperature changes, we extracted the maximum 4 h temperature change for each day of the measurement period between 1 May and 29 September. These values were then averaged across the days to yield one value for each trunk, the mean of daily maximum 4 h temperature changes.

Usage Notes

OTU sequence read counts in each sample are presented in an OTU table 'Korhonen et al OTU_table_Tab_Delimited.txt'). This file also contains information about OTUs: e.g. representative sequences, taxonomic assignments, and BLAST search match results against UNITE database.

Metadata is provided separately for individual samples ('Korhonen et al OTU_table_sample_metadata_Tab_Delimited.txt') and tree trunks ('Korhonen et al OTU_table_trunk_metadata_Tab_Delimited.txt').

Variable explanations are provided in separate files ('Korhonen et al OTU_table_explanations_Tab_Delimited.txt' and 'Korhonen et al OTU_table_metadata_explanations_Tab_Delimited.txt').

 

DATA-SPECIFIC INFORMATION FOR: 'Korhonen et al OTU_table_Tab_Delimited.txt'

1. Number of variables/columns: 387 (See file 'Korhonen et al OTU_table_explanations_Tab_Delimited.txt' for variable explanations.)

2. Number of cases/rows: 475 data rows + 1 total sequencing depth row + 1 header row

3. Abbreviations used: N/A; not applicable

4. Column separator: Tab Delimited

 

DATA-SPECIFIC INFORMATION FOR: 'Korhonen et al OTU_table_sample_metadata_Tab_Delimited.txt'

1. Number of variables/columns: 18 (See file 'Korhonen et al OTU_table_metadata_explanations_Tab_Delimited.txt' for variable explanations.)

2. Number of cases/rows: 360 data rows + 1 header row

3. Decimal separator for numeric data: ,

4. Column separator: Tab Delimited

 

DATA-SPECIFIC INFORMATION FOR: 'Korhonen et al OTU_table_trunk_metadata_Tab_Delimited.txt'

1. Number of variables/columns: 18 (See file 'Korhonen et al OTU_table_metadata_explanations_Tab_Delimited.txt' for variable explanations.)

2. Number of cases/rows: 90 data rows + 1 header row

3. Decimal separator for numeric data: ,

4. Column separator: Tab Delimited

 

DATA-SPECIFIC INFORMATION FOR: 'Korhonen et al OTU_table_explanations_Tab_Delimited.txt'

1. Number of variables/columns: 2

2. Number of cases/rows: 28 + 1 header row

3. Abbreviations used: N/A; not applicable

4. Column separator: Tab Delimited

 

DATA-SPECIFIC INFORMATION FOR: 'Korhonen et al OTU_table_metadata_explanations_Tab_Delimited.txt'

1. Number of variables/columns: 2

2. Number of cases/rows: 26 + 1 header row

3. Column separator: Tab Delimited

Funding

Maj ja Tor Nesslingin Säätiö, Award: 201800093

Suomen Metsätieteellinen Seura, Award: 201810053