Estimating Area of Occupancy From Incomplete Occurrence Records: Reproducible Workflow Illustrated on a Comprehensive...

Area of occupancy (AOO) is a widely used metric for assessing species' vulnerability. To standardize AOO estimation, the IUCN recommends using a fixed 2 × 2 km grid. However, for species represented by sparse and irregular records, this resolution can substantially underestimate AOO. Although spatial modeling offers a potential solution, model-based estimates may differ among taxa and studies depending on data structure, predictor choice, and modeling strategy. In this paper, we present a reproducible workflow that uses breakpoint analysis of record-accumulation curves to identify informative species-specific grid sizes and to estimate AOO from incomplete occurrence records. We applied this framework to 13 snake species found in Georgia, with diverse ecological characteristics within a topographically complex, irregularly sampled region. Repeated subsampling of the six best-represented species showed that accumulation-curve predictions were more accurate than raw occupied-cell counts in 96%-98% of comparisons. Nine of the 13 species showed significant breakpoint-derived scales between approximately 4 and 13 km rather than at the standard 2 km resolution. This workflow offers a practical way to explore scale dependence, sampling incompleteness, and sensitivity of AOO estimates derived from historical and citizen-science occurrence datasets. The workflow complements the standardized 2 × 2 km AOO used in formal IUCN Red List assessments.