DOI: 10.5061/dryad.t76hdr82r
title: Data and code from: Traits and phylogenies modulate the environmental responses of wood-inhabiting fungal communities across spatial scales

description: 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.
description: <b>Study area and
 field data inventories</b> 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 (<i>Fagus sylvatica</i>) 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<i> et al.</i> 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<i> et al.</i> 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. <b>Trait
 data</b> 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. <b>Environmental
 variables</b> 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<i> et al.</i>
 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). <b>Phylogenetic data
 </b> 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<i> et al.</i> 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. <b>References</b> 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. <i>Fungal Ecology, </i><b>27</b>, 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. <i>Journal of Applied Ecology, </i><b>51</b>, 939-948. Bässler, C., Müller, J., Cadotte, M.W., Heibl, C., Bradtka, J.H., Thorn, S.<i> et al.</i> (2016). Functional response of lignicolous fungal guilds to bark beetle deforestation. <i>Ecological Indicators, </i><b>65</b>, 149-160. Brus, D.J., Hengeveld, G.M., Walvoort, D.J.J., Goedhart, P.W., Heidema, A.H., Nabuurs, G.J.<i> et al.</i> (2012). Statistical mapping of tree species over Europe. <i>European Journal of Forest Research, </i><b>131</b>, 145-157. Christensen, M., Hahn, K., Mountford, E.P., Ódor, P., Standovár, T., Rozenbergar, D.<i> et al.</i> (2005). Dead wood in European beech (Fagus sylvatica) forest reserves. <i>Forest Ecology and Management, </i><b>210</b>, 267-282. Hibbett, D.S., Binder, M., Bischoff, J.F., Blackwell, M., Cannon, P.F., Eriksson, O.E.<i> et al.</i> (2007). A higher-level phylogenetic classification of the Fungi. <i>Mycological Research, </i><b>111</b>, 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. <i>International Journal of Climatology, </i><b>25</b>, 1965-1978. Lehtomäki, J. & Moilanen, A. (2013). Methods and workflow for spatial conservation prioritization using Zonation. <i>Environmental Modelling and Software, </i><b>47</b>, 128-137. Ódor, P., Heilmann-Clausen, J., Christensen, M., Aude, E., Dort, K., Piltaver, A.<i> et al.</i> (2006). Diversity of dead wood inhabiting fungi and bryophytes in semi-natural beech forest in Europe. <i>Biological Conservation, </i><b>131</b>, 58-71. Stamatakis, A. (2014). RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. <i>Bioinformatics, </i><b>30</b>, 1312-1313.