A data‐driven geospatial workflow to map species distributions for conservation assessments

Aim Species distribution maps are essential for assessing extinction risk and guiding conservation efforts. However, most come sourced as expert-drawn range with known issues of accuracy or developed overly complex modelling procedures. Thus, data-driven alternatives that accessible reliable a welcome addition to the spatial toolkit. Here, we geospatial workflow refine species from its extent occurrence (EOO) area habitat (AOH) within map. The produced an inverse distance weighted (IDW) interpolation procedure using presence absence points derived primary biodiversity data. Location Americas (North, South, Central America Caribbean). Methods As case study, mapped 723 resident forest birds in assessed their performance comparison maps. We evaluated differences accuracy, overlap, map size AOH. Results generated IDW higher overall (87% versus 62%) fewer errors omission (<1%) commission (14%) than expert (28% both errors). overlap between datasets was low (35%), but agreement increased areas high probability (68%). did not find significant size, AOH consistently smaller estimates Main Conclusions Our provides straightforward approach accurately ranges estimation planning decision-making. Conversely, procedures obtain producing biased local-scale applications.