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Background & Summary
The Neotropical region comprises a wide range of biomes and habitats that place it as the richest biogeographic realm in the world for many groups of organisms, especially birds1, 2–3. Notably, this region is home to approximately 4,600 bird species, representing about 41% of the world’s bird diversity4. Despite this extraordinary diversity, the region is experiencing rapid and large-scale habitat conversion and degradation, resulting in an alarming loss of biodiversity5, 6–7. In fact, around 30% of bird species in the Neotropics are either declining or classified as at high risk of extinction, based on global and national assessments3,4,8,9. Therefore, establishing strategic conservation efforts to safeguard its bird diversity has become a critical priority.
Mapping species distributions is fundamental to supporting effective conservation strategies10, 11, 12–13, allowing the identification of priority areas and the assessment of likely threats. The most comprehensive and widely used global dataset on bird distributions comes from the range maps developed by BirdLife International and Handbook of the Birds of the World (BLI-HBW hereafter)14. These maps are constructed using a combination of occurrence data and polygon boundaries that capture historical, current, and potential species distributions14. Their accuracy is further validated through expert review, ensuring the maps represent as best as possible species ranges given the available data14.
Originally designed to delineate range margins for calculating Extent of Occurrence (EOO) in Red List assessments, BLI-HBW range maps are not intended to reflect actual occupancy. Consequently, while they are fit for their primary purpose, they may present limitations when applied to other uses such as conservation planning, where finer-scale, habitat-specific information is needed. These limitations stem from three main issues15, 16–17. First, by delineating species ranges based on marginal occurrences, these maps are susceptible to commission errors, as they often fail to account explicitly for altitude or habitat preferences18,19. Second, their intermittent updating process can result in significant omission errors, particularly in understudied areas where knowledge of species distributions is rapidly advancing15,20. Lastly, while the expert-based approach allows to detect and fix issues that require domain specific expertise21 (e.g. species misidentification, dispersal barriers), it lacks reproducibility and...