Use of drone‐derived high‐resolution elevation data to improve species distribution models for a primate in mountainous areas

Accurate models of species distributions in mountainous ecosystems are essential for effective conservation, yet reliance on open‑access medium‑resolution elevation products often obscures fine-scale habitat heterogeneity critical for wildlife. We evaluated whether high-resolution digital surface models (DSMs) (≤1 m) based on data from an unmanned aerial vehicle (UAV) enhanced species distribution models (SDMs) relative to medium‑resolution satellite-based ALOS World 3D (AW3D) DSMs (≥30 m) for François' langur (Trachypithecus francoisi). This endangered primate represents an ideal focal species for evaluating SDM performance because its habitat consists of topographically complex karst mountains. Using a systematic comparative framework, we built 290 random forest SDMs across multiple spatial resolutions (3-150 m) and sample sizes (30-122 occurrence records). We assessed model accuracy with the area under the receiver operating characteristic curve (AUC-ROC) and the area under the precision-recall curve (AUC-PR). The UAV DSM improved model performance across all metrics, particularly identification of microhabitat. Performance improvements were scale dependent and most pronounced at fine spatial resolutions of 3-10 m. Improvement was less at coarser resolutions above 100 m, where topographic aggregation reduced fine-feature discrimination. The UAV-based models were more accurate than AW3D-based models even with fewer presence records, indicating greater robustness in data-limited mountainous surveys. Slope-related predictors derived from UAV DSM were more important than those derived from AW3D DSM, suggesting that high-resolution elevation data more effectively resolve terrain features relevant to species habitat selection. The UAV DSM showed wildlife corridors in steep terrain that did not appear in the AW3D DSM. Given that contemporary conservation planning in mountainous protected areas predominantly relies on medium-resolution elevation data, we recommend implementing UAV structure from motion photogrammetry as a cost-effective approach for generating detailed elevation data to enhance biodiversity management in topographically complex landscapes.