摘要
Predictive potential distribution modeling is crucial in outlining habitat usage and establishing conservation management priorities. In this paper we provide detailed data on the distribution of the Caucasian rock agama Para- laudakia caucasia, and use species distribution models (MAXENT) to evaluate environmental suitability and potential distribution at a broad spatial scale. Locality data on the distribution of P. caucasia have been gathered over nearly its entire range by various authors from field surveys. The distribution model ofP caucasia showed good performance (AUC = 0.887), and predicted high suitability in regions mainly located in Tajikistan, north Pakistan, Afghanistan, southeast Turkmenistan, northeast Iran along the Elburz mountains, Transcaueasus (Azerbajan, Armenia, Georgia), northeastern Turkey and northward along the Caspian Sea coast in Daghestan, Russia. The identification of suitable areas for this species will help to assess conservation status of the species, and to set up management programs.
Predictive potential distribution modeling is crucial in outlining habitat usage and establishing conservation management priorities. In this paper we provide detailed data on the distribution of the Caucasian rock agama Para- laudakia caucasia, and use species distribution models (MAXENT) to evaluate environmental suitability and potential distribution at a broad spatial scale. Locality data on the distribution of P. caucasia have been gathered over nearly its entire range by various authors from field surveys. The distribution model ofP caucasia showed good performance (AUC = 0.887), and predicted high suitability in regions mainly located in Tajikistan, north Pakistan, Afghanistan, southeast Turkmenistan, northeast Iran along the Elburz mountains, Transcaueasus (Azerbajan, Armenia, Georgia), northeastern Turkey and northward along the Caspian Sea coast in Daghestan, Russia. The identification of suitable areas for this species will help to assess conservation status of the species, and to set up management programs.
基金
funded by a scholarship at the University Milano-Bicocca,Italy
supported by grants from the Russian Foundation for Basic Research to NBA(Project 12-04-00057)
the Scientific School Support Program(NSh-6560.2012)