DOI: 10.5061/dryad.f4qrfj6w6
title: Projected climatic changes lead to biome changes in areas of previously constant biome

description: Aim: Recent studies in southern Africa identified past biome
 stability as an important predictor of biodiversity. We aimed to assess
 the extent to which past biome stability predicts present global
 biodiversity patterns, and the extent to which projected climatic changes
 may lead to eventual biome changes in areas with constant past biome.
 Location: Global. Taxon: Spermatophyta; terrestrial vertebrates.
 Methods: Biome constancy was assessed and mapped using results
 from 89 dynamic global vegetation model simulations, driven by outputs of
 palaeoclimate experiments spanning the past 140 ka. We tested the
 hypothesis that terrestrial vertebrate diversity is predicted by biome
 constancy. We also simulated potential future vegetation, and hence
 potential future biome patterns, and quantified and mapped the extent of
 projected eventual future biome change in areas of past constant biome.
 Results: Approximately 11% of global ice-free land had a constant
 biome since 140 ka. Aside from areas of constant Desert, many areas with
 constant biome support high species diversity. All terrestrial vertebrate
 groups show a strong positive relationship between biome constancy and
 vertebrate diversity in areas of greater diversity, but no relationship in
 less diverse areas. Climatic change projected by 2100 commits 46–66% of
 global ice-free land, and 34–52% of areas of past constant biome
 (excluding areas of constant Desert) to eventual biome change. Main
 conclusions: Past biome stability strongly predicts vertebrate
 diversity in areas of higher diversity. Future climatic changes will lead
 to biome changes in many areas of past constant biome, with profound
 implications for biodiversity conservation. Some projected biome changes
 will result in substantial reductions in biospheric carbon sequestration
 and other ecosystem services.
description: The CMass and LAI files are derived from outputs produced by
 LPJ-GUESS simulations.  These simulations were driven using climates
 derived from a GCM run for pre-industrial conditions (000kDV_...) and four
 GCM runs driven by the changing greenhouse gas concentrations for 2050
 (rcp4.55_... & rcp8.55_...) and 2100 (rcp4.57_... &
 rcp8.57_...) as defined by the RCP 4.5 and RCP 8.5 projections.  Full
 details of the GCM and relevant citations are given in Huntley et al.
 (2021) and Allen et al. (2020).  The LPJ-GUESS output files were opened
 (by JRMA) using Microsoft Excel, a header line added and, in the case of
 the CMass files, columns added giving the grid cell areas and ice-free
 land fractions, these being copied from the relevant columns of
 the Ice-free_land_fraction_89_time-slices file (see
 https://doi.org/10.5061/dryad.2fqz612mk for this file).  A second
 worksheet was then added to the CMass files and values for grid cell CMass
 calculated from the LPJ-GUESS CMass per unit area values output and the
 product of the grid cell area and ice-free land fraction values. The
 second worksheet was then saved in comma-delimited (.csv)
 format. The Biome_assignments_V1.1_present_and_RCPs.csv
 file is derived from the primary output file generated by the FORTRAN
 program BiomiseLPJ_V1.1.  This program was written by BH and the source
 code is provided in the Supplementary Information to Allen et al. (2020). 
 The program output file was opened (by BH) using Microsoft Excel, a header
 line added, and the resulting worksheet saved in comma-delimited (.csv)
 format. The Biome_extents_V1.1_present_and_RCPs
 and PFT_CMass_by_biome_V1.1_present_and_RCPs are also derived from output
 files generated by BiomiseLPJ_V1.1.  Minor editing was performed (by BH)
 using WordPad in order consistently to separate the blocks of data in the
 files and to ensure that all columns had labels in the header rows, thus
 rendering the files easier to open using software such as R.
 The Biome_constancies_89_time-slices_R1_with_0k_ice-free_areas.csv and Biome_counts_89_time-slices_R1_with_number_of_biomes.csv files were derived from the Biome_assignments_V1.1_89_time-slices.csv file (see https://doi.org/10.5061/dryad.2fqz612mk for this file) associated with the results reported by Allen et al. (2020).  The latter file was processed using a FORTRAN program written by BH that calculates the % constancy of each biome for each grid cell, including in particular the % constancy of the biome inferred for the 'present', and also counts the number of biomes inferred for that grid cell across the 89 time slices.  Output files generated by the program were processed using Excel (by BH) and saved in comma-delimited (.csv) format.
description: See Readme_first.pdf