Integrating Multiple-Covariate Distance Sampling and Habitat Modeling to Inform Conservation of the Asian Houbara in Central Iran.

ABSTRACT: Reliable estimates of abundance and habitat associations are critical for conserving low-density species such as the Asian houbara (Chlamydotis macqueenii). Despite its vulnerable global status, robust estimates of houbara population size and habitat requirements remain scarce across much of its range. We combined multiple-covariate distance sampling (MCDS) with habitat modeling (Random Forest, GAMs, and GLMs) to estimate density and identify habitat relationships of houbaras in central Iran. In spring 2022, 223 line-transect surveys (1449 km) covering a 10,000 km² area yielded 205 individuals across 67 detections. The best-supported MCDS model included fine gravel cover (positive) and vegetation height (negative) as detectability covariates, though their effects were wea

SUBMITTER: Miranzadeh-Mahabadi R 

PROVIDER: S-EPMC12856516 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature