DOI: 10.5061/dryad.0ff6b04
title: Data from: Mountain building, climate cooling and the richness of cold-adapted plants in the northern hemisphere

description: Aim The summits of mountain ranges at mid-latitude in the Northern
 Hemisphere and the Arctic share many ecological properties including
 comparable climate and similar floras. We hypothesise that the orogeny
 during the Oligocene-Miocene combined with global cooling allowed the
 origin and early diversification of cold-adapted plant lineages in these
 regions. Before establishment of the Arctic cryosphere, adaptation and
 speciation in high elevation areas of these mountains ranges may have led
 to higher species richness when compared to the Arctic. Subsequent
 colonisation from mid-latitude mountain ranges to the Arctic may explain
 similar but poorer flora. Location Arctic-Alpine regions of the Northern
 Hemisphere. Methods We mapped the cold climate in the Northern Hemisphere
 for most of the Cenozoic (60 Ma until present) based on paleoclimate
 proxies coupled with paleoelevations. We generated species distribution
 maps from occurrences and regional atlases for 5464 cold-adapted plant
 species from 756 genera occupying cold climates. We fitted a generalised
 linear model to evaluate the association between cold-adapted plant
 species richness and environmental as well as geographic variables. We
 performed a meta-analysis of studies, which inferred and dated the
 ancestral geographic origin of cold-adapted lineages using phylogenies.
 Results We found that the subalpine-alpine areas of the mid-latitude
 mountain ranges comprise higher cold-adapted plant species richness than
 the Palearctic and Nearctic polar regions. The topo-climatic
 reconstructions indicated that the cold climatic niche occurred first in
 mid-latitude mountain ranges (42-38 Ma), specifically in the Himalayan
 region, and only later in the Arctic (22-18 Ma). The meta-analysis of the
 dating of the origin of cold-adapted lineages indicated that most clades
 originated in central Asia between 39 and 7 Ma. Main conclusions Our
 results support the hypothesis that the orogeny and the progressive
 cooling in the Oligocene-Miocene generated cold climates in mid-latitude
 mountain ranges, before the appearance of cold climates in most of the
 Arctic. Early, cold mountainous regions likely allowed for the evolution
 and diversification of cold-adapted plant lineages followed by the
 subsequent colonisation of the Arctic. Our results are in line with
 Humboldt’s vision of integrating biological and geological context in
 order to better understand the processes underlying the origin of
 arctic-alpine plant assemblages.
description: Paleoclimate
 ReconstructionsCenozoic estimated air
 surface temperature (EAST) in the Northern Hemisphere at one degree
 resolution with coordinate reference system (CRS) "+proj=longlat
 +ellps=WGS84 +datum=WGS84 +no_defs +towgs84=0,0,0". The file
 ‘EAST_60to0Ma_Hagen_etal_2019.csv’ contains the x and y coordinates
 followed by the EAST at the given coordinate and time, starting at 60 Ma
 and ending at 0 Ma (i.e. present) as indicated by the column names. The
 file ‘read_paleoclimate.R’ contains code on how to load and convert
 ‘EAST_60to0Ma_Hagen_etal_2019.csv’ into a raster with the correct
 coordinate reference system and an example on plotting the Northern
 Hemisphere estimated air surface temperature at 60Ma.Richness
 PatternsData of species and
 genus richness for the Northern Hemisphere for the present, masked for
 cold regions criteria and aggregated at two degree resolution with CRS
 “+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0” The
 raster ‘cold-adapted_species.tif’ and ‘cold-adapted_genera.tif’ contains
 the richness of cold-adapted species and genera respectively, and is the
 data set used to produce Figure 3. The six files
 ‘cold-adapted_family_[family name].tif’ contain the richness for the
 Compositae, Poaceae, Leguminosae, Brassicaceae, Cyperaceae, and Rosaceae
 families. These are the six most common cold-adapted families for the
 Northern Hemisphere and is the data used to produce Figure 4. The script
 ‘read_plor_richness.patterns.R’ loads and plots one simple example of
 richness patterns in a Artic Polar Stereographic projection (EPSG:3995).
 The folder ‘ocean_layer’ contains an ocean layer shapefile used to
 facilitate data visualization.Species Range
 MappingIn a simplified way, the
 four main process from data to species ranges are: 1. Extract occurrence
 data from GBIF species that are pre-selected as cold-adapted or that
 complement Hulten’s ranges maps and the Panarctic Flora checklist. For
 that, data manipulation and a pre-resolution of species taxonomic names is
 necessary (see ‘1.extract_pre-select_cold_plants_gbif.R’). 2. After
 resolving taxonomic names and synonyms within datasets, merge distribution
 data (see ‘2.merge_dataset.R’). 3. From all merged points, create range
 maps using ecoregions and climatic layers information (see
 ‘3.create_range.R’). 4. After having clean datasets, merge all datasets
 (see ‘4.merge_datasets.R’). Additional steps as the removal of plants not
 belonging to the Angiosperms clade, masking of the cold areas and the
 manual check of species names are not provided here, given their
 simplicity, specificity to a cluster computer and large quantity of
 intermediate individual files. Inside the folder ‘support_functions’,
 there are four functions called by the scripts mentioned above. All
 functions have a short description and parameters are shortly described.
 The file (i) ‘range_from_points.R’ contains the function used to create
 range maps from occurrence data. The file (ii) ‘resolve_taxonomic_names.R’
 contains the function used to automatically resolve taxonomic names and
 look for synonyms while deleting clear mistakes. The taxonomic name
 resolution procedure involved a manual check of all species. The file
 (iii) ‘merge_occurance_data.R’ merges occurrence data from a same dataset
 considering duplicates and corrected species names. This function requires
 a species names resolution matrix and a specific structure for datasets
 (i.e. occurrences inside a folder named ‘points’ with a txt file for each
 species name containing x and y coordinates). The final occurrence data is
 stored in a folder named ‘merged_point’. The file (iv)
 ‘compress_housekeeping.R’ contains a function conveniently called after
 generating the merged points. It compresses all occurrence data inside
 ‘point’ folder and deletes the folder while keeping a compressed zip file
 for reference.