Abstract

Summary Top predators are seen as keystone species of ecosystems. Knowledge of their habitat requirements is important for their conservation and the stability of the wildlife communities that depend on them. The goal of our study was to model the habitat of leopard Panthera pardus in west and central Asia, where it is endangered, and analyse the connectivity between different known populations in the Caucasus to enable more effective conservation management strategies to be implemented. Presence and absence data for the species were evaluated from the Caucasus, Middle East and central Asia. Habitat variables related to climate, terrain, land cover and human disturbance were used to construct a predictive model of leopard habitat selection by employing a geographic information system (GIS) and logistic regression. Our model suggested that leopards in west and central Asia avoid deserts, areas with long‐duration snow cover and areas that are near urban development. Our research also provides an algorithm for sample data management, which could be used in modelling habitats for similar species. Synthesis and applications. This model provides a tool to improve search effectiveness for leopard in the Caucasus, Middle East and central Asia as well as for the conservation and management of the species. The model can predict the probable distribution of leopards and the corridors between various known populations. Connectivity patterns can be used to facilitate corridor planning for leopard conservation, especially in the Caucasus, where the leopard is a top priority conservation species. Also, as top predators are often associated with high biodiversity, the leopard habitat model could help to identify biodiversity hotspots. The protection of biodiversity hotspots is seen as the most effective way to conserve biodiversity globally.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.