Geopolitical inequalities in geographic biodiversity knowledge

Description This repository contains the data and scripts used to compare how geographic knowledge of terrestrial vertebrates has accumulated over time between the Global North and Global South. In addition, we test predictors that explain present-day variation in knowledge completeness across political administrative units. This repository contains only the analyses used to generate the results presented in the manuscript. For the complete data processing workflow, see: https://github.com/mmoroti/wallacean_time Contents data_analysis.R: Script containing all analyses used to generate the results presented in the manuscript. data_socioeconomic_aggregate.RData: Socioeconomic data aggregated at the administrative unit level. geographic_shape_data.RData: Spatial data (shapefiles) of administrative units, including classification into Global North and Global South. richness_completeness.RData & tetrapods_list_sensitivity.RData: Datasets containing observed and expected species richness per administrative unit. tetrapods_model.RData: Fitted recurrent event model. Data collection Occurrence data for terrestrial tetrapods were obtained from the following sources: Global Biodiversity Information Facility (GBIF) www.gbif.org speciesLink https://specieslink.net/ BioTime 2.0 (Dornelas et al., 2025) To ensure data quality and taxonomic consistency across different sources, we used the Darwin Core taxonomy framework available via the rgbif package API (Chamberlain et al., 2024). Taxonomic matching was validated with a confidence interval greater than 95%. Methodology The data were selected and standardized according to the following criteria: Species selection: We used TetrapodTraits (Moura et al., 2024) as the reference to select species, ensuring that they met the inclusion criteria: (1) included in global tetrapod phylogenies; (2) described at least 10 years ago; and (3) had functional traits available (e.g., body size, habitat, circadian activity). Taxonomic standardization: Species were homogenized using the rgbif package, specifically Darwin Core taxonomic backbone, to ensure name matching across different taxonomic sources, guaranteeing that occurrences were associated with the same taxonomic entity. Data Cleaning The data underwent a cleaning process to remove records with imprecise or missing coordinates, following these steps: Removal of records without coordinates or year. Removal of records dated prior to 1900 due to low coordinate accuracy. Application of the CoordinateCleaner pipeline (Zizka et al., 2019) to eliminate records with coordinates at country and/or capital centroids, located in research institutions, at sea, with equal absolute longitude and latitude, at GBIF headquarters Exclusion of records with coordinate precision lower than 100 km or without precision data. Duplicated coordinates Only occurrence records within the respective polygons were retained.