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Combining radio-telemetry and random observations to model the habitat of Near Threatened Caucasian grouse Tetrao mlokosiewiczi

  • Alexander Gavashelishvili (a1) and Zura Javakhishvili (a1)

The distribution of the Near Threatened Caucasian grouse Tetrao mlokosiewiczi, endemic to the Caucasus, was examined to model the species’ nesting habitat, and thus facilitate its conservation and the identification of Key Biodiversity Areas in the Caucasus. The species’ occurrence was defined by field surveys and radio-telemetry. Data were managed and analysed using a geographical information system and various modelling techniques. Grouse locations were divided into training and testing datasets. Habitat variables measured at training locations were used to develop models, and testing locations were used to validate the models. The final best-fit model suggested that Caucasian grouse prefer open habitat, and the most important independent variables accounting for the species' distribution were annual mean temperature, mean temperature of warmest quarter, precipitation seasonality and proximity to deciduous broad-leaf forest. The incorporation of human disturbance and ruggedness into the final model significantly increased its predictive power. This model provides a tool to improve search effectiveness for Caucasian grouse in the Caucasus and for the conservation and management of the species. The model can predict the probable distribution of Caucasian grouse and the corridors between known populations. Threatened and endemic species are often used as species for setting site-based conservation priorities, and this habitat model could help to identify new Key Biodiversity Areas for protection in the Caucasus. The Ministry of Environmental Protection and Natural Resources of Georgia is going to use the results of this study to reshape existing protected areas and identify new ones.

Corresponding author
*Center of Biodiversity Studies, Institute of Ecology, Ilia State University, Chavchavadze Avenue 32, 0179 Tbilisi, Georgia. E-mail
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  • ISSN: 0030-6053
  • EISSN: 1365-3008
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