Species distribution models (SDMs) have been used across continents and taxonomic groups to guide field surveys and improve detection efficiency. In several studies, SDM-guided approaches achieved Area Under the Curve values between 0.90 and 0.976, with some reports documenting the discovery of new populations (e.g., 4 of 8 species or 5-16 additional sites) and time savings of up to 70% compared with unsystematic surveys. One study noted that Gaussian Process models operated 70 times faster than an alternative estimation method. Additional work indicates that SDMs narrow survey areas and enhance cost effectiveness, particularly when environmental layers and robust occurrence data support model development. These studies show that, when applied with methods such as Maxent and ensemble approaches, SDMs offer a viable alternative to direct field surveys for locating wild species over large areas. Limitations arise when data quality or model specification is insufficient, suggesting that careful design remains essential for reliable outcomes.
Taufiq et al. (Fri,) studied this question.