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Data and code from: Traits and phylogenies modulate the environmental responses of wood-inhabiting fungal communities across spatial scales

Citation

Abrego, Nerea; Bässler, Claus; Christensen, Morten; Heilmann-Clausen, Jacob (2022), Data and code from: Traits and phylogenies modulate the environmental responses of wood-inhabiting fungal communities across spatial scales, Dryad, Dataset, https://doi.org/10.5061/dryad.t76hdr82r

Abstract

Identifying the spatial scales at which community assembly processes operate is fundamental for gaining a mechanistic understanding of the drivers shaping ecological communities. In this study, we examined whether and how traits and phylogenetic relationships structure fungal community assembly across spatial scales.

We applied joint species distribution modelling to a European-scale dataset on 215 wood-inhabiting fungal species, which includes data on traits, phylogeny and environmental variables measured at the local (log-level) and regional (site-level) scales.

At the local scale, wood-inhabiting fungal communities were mostly structured by deadwood decay stage, and the trait and phylogenetic patterns along this environmental gradient suggested the lack of diversifying selection.

At regional scales, fungal communities and their trait distributions were influenced by climatic and connectivity-related variables. The fungal climatic niches were not phylogenetically structured, suggesting that diversifying selection or stabilizing selection for climatic niches has played a strong role in wood-inhabiting communities. In contrast, we found a strong phylogenetic signal in the responses to connectivity-related variables, revealing phylogenetic homogenization in small and isolated forests.

Altogether, our results show that species-level traits and phylogenies modulate the responses of wood-inhabiting fungi to environmental processes acting at different scales. This result suggests that the evolutionary histories of fungal traits diverge along different environmental axes.

Methods

Study area and field data inventories

The data used in the present study was collected from 52 European beech forest reserves as used in Abrego et al. (2017). The criteria for site (i.e., reserve) selection and survey design was the same as described in Abrego et al. (2017). Briefly, the main criteria was that sites should represent the best reference for natural beech (Fagus sylvatica) forests in each country, and that altogether, the locations of the sites should represent the European beech forest distribution. As the spatial distribution of the visited forest sites was clustered in space, the sites were grouped into eight regions according to their geographical location.

The fungal fruitbody surveys were carried out between the years 2001-2014. Most samplings were carried out visiting each site once during the main fruiting season (from late August to early November, depending on the visited geographical area) except in 2001, when each resource unit was surveyed three times (data used in Ódor et al. 2006). Within each site, individual fallen beech logs of at least 10 cm in diameter, inclusive of their corresponding snag (if it was still present at the time of the survey), were considered individual deadwood units. The selection of the deadwood units was done to secure a balanced combination of the main five decay stages within each site (see Christensen et al. 2005 for more details in decay stage classification and log selection procedure). The surveys included all polyporoids and agaricoids, and a subset of corticoids, larger discomycetes and stromatic pyrenomycetes. Most species were identified in the field, but when microscopic identification was necessary, the specimens were collected for further identification in the laboratory.

Trait data

We compiled information about all traits that we considered ecologically relevant and for which data were available in the literature. The considered traits were classified into three groups: traits related to the reproductive strategy, traits related to the dispersal capability and traits related to the resource use.

Environmental variables

We selected the environmental variables which have been detected to significantly influence fungal species communities, based on results of our previous studies analyzing the partially the same data. The environmental covariates considered in this study include the diameter at breast height (called henceforth diameter; unit cm) and decay stage of each deadwood unit (scale 1-5), and the 10 km-scale connectivity (unitless index), area (ha), annual temperature range (ºC) and annual precipitation (mm) of each site. Diameter for trees with a standing snag diameter in breast height was measured at 1.3 meter above the forest floor, while for uprooted trees (and broken trees with a low breakpoint) the point was found along the lying log, 1.3 meter from the original anchoring of the tree. The connectivity at 10 km spatial scale was based on the beech distribution map in Europe produced by EFI-Alterra (Brus et al. 2012), and we computed it using the Zonation Conservation Planning Software (Lehtomäki & Moilanen 2013). For characterizing the annual temperature range and the annual precipitation in the reserves, we used the climatic GIS layers BIO7 and BIO 12 by Hijmans et al. (2005).

Phylogenetic data

The fungal phylogeny was constructed as described in detail in Bässler et al (2014; 2016). Briefly, available nuclear and mitochondrial sequences were mined from the GenBank sequence data repository. For those species that sequences were not available in the database, the species were manually added to the tree, which led to polytomies in some cases. We used a literature-based guide tree (Hibbett et al. 2007), to successively align the sequences. After removing ambiguously aligned nucleotide position, alignment blocks of all markers were concatenated into a single matrix. Tree topology and branch lengths were modelled in a maximum-likelihood framework using RAxML (Stamatakis 2014). Sequence evolution was modelled with the GTRCAT approximation for each marker separately on a common topology. The confidence in the tree topology was assessed by 1000 non-parametric bootstrap replicates.

References

Abrego, N., Christensen, M., Bässler, C., Ainsworth, A.M. & Heilmann-Clausen, J. (2017). Understanding the distribution of wood-inhabiting fungi in European beech reserves from species-specific habitat models. Fungal Ecology, 27, 168-174.

Bässler, C., Ernst, R., Cadotte, M., Heibl, C. & Müller, J. (2014). Near-to-nature logging influences fungal community assembly processes in a temperate forest. Journal of Applied Ecology, 51, 939-948.

Bässler, C., Müller, J., Cadotte, M.W., Heibl, C., Bradtka, J.H., Thorn, S. et al. (2016). Functional response of lignicolous fungal guilds to bark beetle deforestation. Ecological Indicators, 65, 149-160.

Brus, D.J., Hengeveld, G.M., Walvoort, D.J.J., Goedhart, P.W., Heidema, A.H., Nabuurs, G.J. et al. (2012). Statistical mapping of tree species over Europe. European Journal of Forest Research, 131, 145-157.

Christensen, M., Hahn, K., Mountford, E.P., Ódor, P., Standovár, T., Rozenbergar, D. et al. (2005). Dead wood in European beech (Fagus sylvatica) forest reserves. Forest Ecology and Management, 210, 267-282.

Hibbett, D.S., Binder, M., Bischoff, J.F., Blackwell, M., Cannon, P.F., Eriksson, O.E. et al. (2007). A higher-level phylogenetic classification of the Fungi. Mycological Research, 111, 509-547.

Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978.

Lehtomäki, J. & Moilanen, A. (2013). Methods and workflow for spatial conservation prioritization using Zonation. Environmental Modelling and Software, 47, 128-137.

Ódor, P., Heilmann-Clausen, J., Christensen, M., Aude, E., Dort, K., Piltaver, A. et al. (2006). Diversity of dead wood inhabiting fungi and bryophytes in semi-natural beech forest in Europe. Biological Conservation, 131, 58-71.

Stamatakis, A. (2014). RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics, 30, 1312-1313.

Funding

Academy of Finland, Award: 308651