Code and Data for Integrating IUCN Threat Severity and Dark Diversity for Spatial Conservation Prioritization in Indonesia

This repository contains the R scripts, spatial datasets, and reproducible workflow associated with our study on the spatial dynamics of threatened species across the Indonesian archipelago. While Indonesia harbors an exceptional concentration of endemic flora and fauna, its biodiversity is severely threatened by escalating anthropogenic pressures. Effective conservation planning requires spatially explicit species occurrence data; however, global repositories are often biased toward accessible regions and charismatic taxa, perpetuating a critical Wallacean shortfall. To address this, the provided code integrates macroecological dark diversity modeling with IUCN Red List threat severity assessments to evaluate 1,047 threatened species. Using 33,029 spatially thinned occurrence records from the Global Biodiversity Information Facility (GBIF) included in this repository, the R scripts map observed threatened species richness onto a 1-degree hexagonal grid. The workflow applies the probabilistic RawBeals smoothing method to estimate site-specific dark diversity (locally absent but ecologically suitable species), community incompleteness, and total species pool size. Furthermore, the code provides the framework for a novel Conservation Priority Index (CPI) that combines normalized community incompleteness and cumulative IUCN threat severity. Users can execute these scripts to fully reproduce our spatial analyses, robustness tests, and core findings—including the stark spatial contrasts between well-documented strongholds (e.g., Java, Bali) and highly data-deficient regions with exceptional dark diversity (e.g., Maluku, Kalimantan). By providing this empirically grounded, operationally flexible framework, this repository serves as an open-source tool for directing conservation resources across data-rich and data-poor landscapes alike.