The effect of post-conflict transition on deforestation of protected areas in Colombia

This repository contains analysis scripts and results that arose from replicating and extending upon a recent study on deforestation in Colombian protected areas. Our results strongly put in question the conclusions presented in the original study: Reporting an increase in deforestation after ending armed conflict, the authors of this study propose several drivers behind this trend that are supposed to specifically affect protected areas and render them particularly vulnerable to deforestation during post-conflict transition. In our reanalysis, it has become apparent that the original study merely picked up a national trend of increased deforestation and that forests in national protected areas are actually much less affected by the transition than other forests in Colombia -- it may even be argued that protected areas have become more effective at slowing down deforestation when compared to non-protected forests. The drivers and conservation lessons proposed in original study are therefore highly speculative. We are deeply concerned by the general increase in deforestation in Colombia. And we believe it is important to analyze potential drivers of deforestation more comprehensively, so that adequate measures to reduce forest loss can be identified.

Code overview

• R scripts for geospatial and statistical analyses are placed in the src folder.
• Statistical analyses are presented in src/3_analyses.R and can be run using the results (i.e. .csv files) that are generated by the geospatial analysis, and which are included in this repository.
• Data preparation and geospatial analysis (in this order) are performed using the scripts src/1_data_preperation.R, and src/2_forest_loss.R, respecitvely. To run the scripts, it is necessary to download the raw data first and place it in the data/ directory as described below.

Sources for raw data

Forest loss

We used version 1.6 of the global forest change data sets provided by Hansen et al. (2013), which can be downloaded from https://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.6.html. To cover all of Colombia, the granules needed are: 20N, 90W; 20N 80W; 10N 90W; 10N 80W; 10N 70W; 0N 90W; 0N 80W. The data sets needed are lossyear, datamask, and treecover2000. The granules for each data set should be placed into corresponding subfolders within the data/gfc/ directory, e.g. the file Hansen_GFC-2018-v1.6_lossyear_20N_090W is expected in data/gfc/lossyear/.

Protected areas

Shapes for Colombian protected areas were obtained from http://www.parquesnacionales.gov.co/portal/es/servicio-al-ciudadano/datos-abiertos/. The corresponding shapefile is expected in data/colombia/runap2. The pre-extension shape of the Serranía de Chiribiquete was obtained from a different data set. This data set is expected to reside in data/colombia/Parques_Nacionales_Naturales_de_Colombia-shp.

Administrative boundaries

The borders of Colombia are taken from version 3.6 of the Database of Global Administrative Boundaries (GADM), which can be downloaded at https://biogeo.ucdavis.edu/data/gadm3.6/gpkg/gadm36_COL_gpkg.zip. The GeoPackage is expected in data/colombia/.