giovannistrona/oil-palm-primates

Python code associated to the paper assessing the impact of oil palm expansion on African primate species # oil-palm-primates This repository includes the Python and R code associated to the following paper: **Strona G., S. D. Stringer, G. Vieilledent, Z. Szantoi, J. Garcia-Ulloa, S. Wich.** 2018. Small room for compromise between oil palm cultivation and primate conservation in Africa. _Proceedings of the National Academy of Sciences PNAS_. **115**(35): 8811-8816. \DOI:[10.1073/pnas.1804775115\]. / Supplementary materials ## Description The code permits the full replication of all the analyses in the paper, as well as the reproduction of all figures (including the supplementary one). Analyses and map plotting are performed by the Python script `script_oil_palm_primates.py`, while the R code in `make_plots.R` permits the reproduction of the other graphs. Note that the R code is called by the Python script, so the execution of the latter is enough for complete analysis replication. ## Input data All the raw input files necessary to run the analyses can be downloaded from Zenodo \DOI: [10.5281/zenodo.1200255\]. It is important that all the input files (which are provided in a single compressed zipped archive named INPUT_DATA.zip) are left in their relative position within their folder once this one is unzipped, and that both `script_oil_palm_primates.py` and `make_plots.R` are copied in that same folder. At that point, running (from within the folder) the `script_oil_palm_primates.py` will perform all the analyses and generate all the output files. ## Output data All the expected output can be downloaded from Zenodo \DOI: [10.5281/zenodo.1200265\]. ## Versioning and archiving on Zenodo The development version of this repository is available on GitHub at github.com. All versions of this repository, including the last release, are archived on Zenodo: \DOI: [10.5281/zenodo.1200339\]. ## Figure **Figure 2:** Spatial overlap between oil palm suitability and primate vulnerability, mapped at 100 km2 resolution. Numbers in …