DOI: 10.5061/dryad.cjsxksn28
title: Raster and original working data for the paper Holocene matters: landscape history accounts for current species richness of vascular plants in forests and grasslands of eastern Central Europe

description: Aim: Current species-richness patterns are sometimes interpreted as a
 legacy of landscape history, but historical processes shaping the
 distribution of species during the Holocene are frequently omitted in
 biodiversity models. Here, we test their importance in modelling current
 species richness of vascular plants in forest and grassland vegetation.
 Location: Western Carpathians and adjacent regions. Taxon: Vascular
 plants. Methods: Numbers of all species and of habitat specialists were
 extracted from plot records of forest and grassland vegetation. For each
 plot, environmental and historical data were derived from thematic maps.
 Historical data related to the persistence of (i) temperate taxa during
 the Late Glacial and Early Holocene, (ii) open-landscape taxa during the
 Middle Holocene, and (iii) taiga species during the Late Holocene were
 based on 112 fossil pollen profiles. Boosted regression trees were used to
 model spatial patterns in species richness. Results: Historical variables
 always appeared among the best predictors of current species richness. In
 light forests, species richness highly mirrored both the Late Glacial
 (12.5% contribution) and Middle-Holocene (8.6%) landscape history. The
 latter factor became an important predictor also for species richness of
 steppe grasslands (8.3%) along with temperature seasonality (11.9%).
 Species richness of dark coniferous forests was best predicted by the
 Late-Holocene occurrence of taiga forests (14.8%), which had an even
 stronger effect on the richness of habitat specialists (20.5%). 
 Main conclusions: Landscape changes since the Last Glacial Maximum are
 important predictors of current plant species richness. The historical
 effects were found to be habitat-specific and, because they may interact
 with recent environmental conditions and anthropogenic pressures, they
 often show a non-linear relationship with species richness. We provide one
 possible direction of incorporating past landscape changes into the models
 of species richness.
description: Numbers of all species and of habitat specialists were extracted
 from plot records of forest and grassland vegetation (the EVA database).
 Environmental data were derived from GIS-based thematic maps. As
 historical data we used the pollen site scores on the first axis of
 principal coordinate analysis (PCoA) performed by Jamrichová et al. (2017
 J Biog) and interpolated them using ordinary kriging with an exponential
 semi-variogram model. We also weighted each spatial interpolation by the
 regional relationship between PCoA scores and elevation. In the regions
 where this relationship was relatively stronger (as measured by the
 <i>R</i><sup>2</sup> of linear regression model),
 the interpolated PCoA scores depend more on elevation, whereas in regions
 where this relationship was weak, the interpolated PCoA scores depend more
 on spatial similarity among sites with pollen profiles.
description: We present data for the manuscript Holocene Matters: landscape
 history accounts for current species richness of vascular plants in
 forests and grasslands of eastern Central Europe. We tested the importance
 of historical processes shaping the distribution of species during the
 Holocene in modelling current species richness of vascular plants in
 forest and grassland vegetation in the Western Carpathians and adjacent
 regions. Numbers of all species and of habitat specialists were extracted
 from plot records of forest and grassland vegetation. For each plot,
 environmental and historical data were derived from thematic maps.
 Historical data related to the persistence of (i) temperate taxa during
 the Late Glacial and Early Holocene, (ii) open-landscape taxa during the
 Middle Holocene, and (iii) taiga species during the Late Holocene were
 based on 112 fossil pollen profiles. Boosted regression trees were used to
 model spatial patterns in species richness. Here we present the working
 data sheets and final raster data. There are no missing
 values. We are providing the working data sheets (richness data, GIS based
 environmental data, historical data as described above) and final raster
 data.