R scripts for spatial analyses of the Centinela flora.
The GBIF data used in the paper can be accessed at: https://drive.google.com/file/d/1DDdLYZOjQW4oCinXqJgYdWJM_PycdQ8w/view?usp=sharing
Or downloaded via rGBIF
d <- occ_download_get('0011588-231120084113126') %>% occ_download_import()
GBIF_download_species_notes.txt: Description of nomenclatural differences between 2024 Centinela flora list of 914 species and 873 species with GBIF data.
Centinela_rgbif_git.R: R scripts for downloading and cleaning GBIF data.
Centinela_getElevationRanges.R: scripts to generate elevation raster and define elevation ranges for a list of species.
elev_species_final.csv: elevational ranges per species !!! Note some of these species have less than 3 occurrence records and will produce errors in EOO computing script Centinela_range_size_git.R.
elevation_COECPAPE_0.5sec_maskedforestCover_30m_COECPAPE_x20_raster80.tif: elevation raster
Centinela_range_size_git.R: R scripts used to estimate species range sizes in the paper.
Users will need to download their own GBIF data, edit R script to reflect the user environment and filenames, and then run R script on the command line. The large sizes of the rasters and shapes in our analyses made this scripts run very slowly, about 30 minutes per species. I recommend splitting the elev_species_final.csv into several files that can be run in parallel on a server
The estimation of species ranges used in this paper depends on this great package. Please read the paper, docs, and cite it.
Dauby G, Stévart T, Droissart V, et al. ConR: An R package to assist large-scale multispecies preliminary conservation assessments using distribution data. Ecol Evol. 2017; 7: 11292–11303. https://doi.org/10.1002/ece3.3704 (2017).