This repository contains all scripts and data used for analysis and figures for the paper Pereira et al. (2024). Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050. Science. https://doi.org/10.1126/science.adn3441
This paper is the result of the BES SIM 1 project (Biodiversity and Ecosystem Services Scenario Inter-model Comparison).
This repository can also be downloaded from Zenodo at https://doi.org/10.5281/zenodo.10702963.
Henrique M. Pereira, Luise Quoß, Inês Martins, Isabel Rosa, HyeJin Kim
Version 1.2, 15.4.2024
Minor changes for cross-platform compatibility
https://doi.org/10.5281/zenodo.10973423
Version 1.1, 9.4.2024
Changed reference to downloading datasets from ID to DOI.
Corrected historical value of Insights delta_H_gamma.
Updated figured order and now uses color blind pallete for all figures.
https://doi.org/10.5281/zenodo.10971965
Version 1.0, 25.3.2024
https://doi.org/10.5281/zenodo.10703117
This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
Files to produce the different figures in the manuscript.
| Filename | Description |
|---|---|
| Figure1_and_S14.R | Create input data and plots for global biodiversity metrics |
| Figure2.R | Create BD maps (species richness) per scenario, averaged over several models |
| Figure3.R | Create input data and plots for global ecosystem service metrics |
| Figure4.R | Create Input data and Map with regional plots for ES and BD |
| FigureS1.R | Create global historical trends (1900-2015) in land-use and projected trends for each scenario (2015-2050) |
| FigureS2.R | Create distribution maps of primary land (forest & non-forest) in 1900, historical changes (1900-2015) and future changes (2015-2050) in each scenario |
| FigureS3.R | Create distribution maps of secondary land (forest & non-forest) in 1900, historical changes (1900-2015) and future changes (2015-2050) in each scenario |
| FigureS4.R | Create distribution maps of cropland (C3 & C4) in 1900, historical changes (1900-2015) and future changes (2015-2050) in each scenario |
| FigureS5.R | Create distribution maps of pasture and rangeland in 1900, historical changes (1900-2015) and future changes (2015-2050) in each scenario |
| FigureS6.R | Create S2a: Global historical trends (1990-2015) in mean annual temperature and for each scenario (2015-2050) and create S2b-e: Spatial distribution maps of absolute changes in mean annual temperature in each scenario (2015-2050) |
| FigureS7.R | Create BD maps (species richness) per model for the regional rivalry scenario |
| FigureS8.R | Create BD maps (intactness) per scenario, averaged over several models |
| FigureS9.R | Create BD maps per scenario for the AIM model |
| FigureS10-S13.R | Create ES maps per scenario, some per model, some averaged over several models |
The files are here for documentation as the spatial statistics from the maps are already stored in the files in Data_tables.
| Filename | Description |
|---|---|
| BES-SIM_statistics_global.R | Calculate global statistics per IPBES region for all netCDFs |
| BES-SIM_statistics_ipbes-regions.R | Calculate zonal statistics per IPBES region for all netCDFs |
All tabular data from the biodiversity and ecosystem service model outputs are available in this folder. These files also include the spatial statistics from the maps. See README files on that folder for the metadata.
A shapefile with the IPBES sub-regions is available. The sub-regions are: Central Africa, East Africa and adjacent islands, North Africa, Southern Africa, West Africa, Caribbean, Mesoamerica, North America, South America, North-East Asia, Oceania, South-East Asia, South Asia, Western Asia, Central and Western Europe, Central Asia, Eastern Europe.
The remaining data can be downloaded from the following repositories.
Download the datasets from the EBV Data Portal (this can also be automatically done by running Figure2.R and FigureS10-S13.R):
| ID | Title | DOI |
|---|---|---|
| 27 | Global trends in biodiversity (BES-SIM GLOBIO) | https://doi.org/10.25829/r7bt92 |
| 28 | Global trends in biodiversity (BES-SIM PREDICTS) | https://doi.org/10.25829/vt7qk9 |
| 29 | Global trends in biodiversity (BES-SIM cSAR-IIASA) | https://doi.org/10.25829/haq7d4 |
| 30 | Global trends in biodiversity (BES-SIM cSAR-iDiv) | https://doi.org/10.25829/5zmy41 |
| 31 | Global trends in biodiversity (BES-SIM AIM) | https://doi.org/10.25829/5wn357 |
| 68 | Global trends in biodiversity (BES-SIM INSIGHTS) | https://doi.org/10.25829/h2evr2 |
| 60 | Global trends in ecosystem services (BES-SIM LPJ-GUESS) | https://doi.org/10.25829/z5v9t2 |
| 61 | Global trends in ecosystem services (BES-SIM LPJ) | https://doi.org/10.25829/xq7a86 |
| 62 | Global trends in ecosystem services (BES-SIM CABLE POP) | https://doi.org/10.25829/ktnb68 |
| 63 | Global trends in ecosystem services (BES-SIM InVEST) | https://doi.org/10.25829/zr4d27 |
| 64 | Global trends in ecosystem services (BES-SIM GLOBIO-ES) | https://doi.org/10.25829/vqd4s4 |
Download the LandUseHarmonization2 from their website: https://luh.umd.edu/data.shtml.
Data used for the historical maps: LUH2 v2h Release (10/14/16), file:
- states.nc
Data used for the scenario maps: LUH2 v2f Release (12/21/17), files:
- multiple-states_input4MIPs_landState_ScenarioMIP_UofMD-AIM-ssp370-2-1-f_gn_2015-2100.nc (states.nc for RCP2.6 SSP1)
- multiple-states_input4MIPs_landState_ScenarioMIP_UofMD-IMAGE-ssp126-2-1-f_gn_2015-2100.nc (states.nc for RCP7.0 SSP3)
- multiple-states_input4MIPs_landState_ScenarioMIP_UofMD-MAGPIE-ssp585-2-1-f_gn_2015-2100.nc (states.nc for RCP8.5 SSP5)
Download the following files from Dryad: https://doi.org/10.5061/dryad.3n5tb2rr6:
- tas_bced_1960_1999_ipsl-cm5a-lr_hist_rcp2p6_1901-2099_noleap_monmean.nc
- tas_bced_1960_1999_ipsl-cm5a-lr_hist_rcp6p0_1901-2099_noleap_monmean.nc
- tas_bced_1960_1999_ipsl-cm5a-lr_hist_rcp8p5_1901-2099_noleap_monmean.nc
Download 'Land' from NaturalEarth: https://www.naturalearthdata.com/downloads/110m-physical-vectors/ (ne_110m_land) Version: 4.1.0 (The interface says Version 4.0.0 but the version information in the download files says 4.1.0 -> check both)
All paths in the codes are relative. Place all spatial data in 'Data_geo' and all code can be run. The folders need the following names (except your-folder-name which can be named for instance BES_SIM_1) and hierarchical structure:
*
├───Data_geo
│ ├───Climate_data
│ ├───ebv_cubes
│ ├───LUH2
│ ├───ne_110m_land
├───*your-folder-name, eg. "BES_SIM_1"*
│ ├───Code
│ ├───Data_tables
| ├───IPBES_Regions
│ ├───Figures
│ ├───Outputs
*
Session Info of the R- and package-version(s):
R version 4.3.2 (2023-10-31)
Platform: x86_64-apple-darwin20 (64-bit)
Running under: macOS Sonoma 14.2.1
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Europe/Berlin
tzcode source: internal
attached base packages:
[1] grid stats graphics grDevices utils datasets methods base
other attached packages:
[1] gridExtra_2.3 raster_3.6-26 sp_2.1-3 readr_2.1.5 igraph_2.0.1.1 purrr_1.0.2 sf_1.0-15 rlang_1.1.3
[9] ggpattern_1.0.1 readxl_1.4.3 ggpubr_0.6.0 Rmisc_1.5.1 plyr_1.8.9 lattice_0.22-5 dplyr_1.1.4 ggplot2_3.4.4
[17] classInt_0.4-10 terra_1.7-71 stringr_1.5.1 ebvcube_0.1.7
loaded via a namespace (and not attached):
[1] gtable_0.3.4 rstatix_0.7.2 rJava_1.0-11 rhdf5_2.46.1 tzdb_0.4.0 rhdf5filters_1.14.1
[7] vctrs_0.6.5 tools_4.3.2 generics_0.1.3 parallel_4.3.2 curl_5.2.0 tibble_3.2.1
[13] proxy_0.4-27 fansi_1.0.6 pkgconfig_2.0.3 KernSmooth_2.23-22 checkmate_2.3.1 lifecycle_1.0.4
[19] compiler_4.3.2 farver_2.1.1 munsell_0.5.0 codetools_0.2-19 carData_3.0-5 class_7.3-22
[25] crayon_1.5.2 pillar_1.9.0 car_3.1-2 tidyr_1.3.1 abind_1.4-5 tidyselect_1.2.0
[31] stringi_1.8.3 labeling_0.4.3 colorspace_2.1-0 cli_3.6.2 magrittr_2.0.3 xlsxjars_0.6.1
[37] utf8_1.2.4 broom_1.0.5 e1071_1.7-14 withr_3.0.0 scales_1.3.0 backports_1.4.1
[43] bit64_4.0.5 bit_4.0.5 ggsignif_0.6.4 cellranger_1.1.0 hms_1.1.3 memuse_4.2-3
[49] Rcpp_1.0.12 glue_1.7.0 DBI_1.2.1 xlsx_0.6.5 vroom_1.6.5 rstudioapi_0.15.0
[55] jsonlite_1.8.8 R6_2.5.1 Rhdf5lib_1.24.1 units_0.8-5