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Climate change created predominantly by burning fossil fuels leads to increased pressure on biodiversity. It may cause extinction in lizard species over the forthcoming years. Lizard species that are unable to adjust rapidly enough to the ecological alterations due to climate change are particularly under threat. Therefore, vulnerable lizard species should be monitored and adopt climate change scenarios. This study examines the changes in the habitats of Danford’s lizard (Anatololacerta danfordi) according to the RCP 4.5 and RCP 8.5 (HADGEM2-ES) climate scenarios. We modelled the current habitat preferences of A. danfordi using the MaxEnt method based on the bioclimatic features derived from Worldclim. Our results showed that A.danfordi prefers habitats with the bioclimate features including 12 mm for precipitation of driest month, 1-2ºC for mean temperature of wettest quarter, -4ºC for min temperature of coldest month, and 600 mm for annual precipitation. We determined the potential distributions of the A.danfordi using the model and GIS facilities for both RCP 4.5 and RCP 8.5 climate scenarios. In conclusion, the potential habitats of this lizard species may be dramatically influenced from two climate scenarios. We envisage that the suitable habitats may be mostly relocated from the south toward the north. A.danfordi may not adapt this rapid change and may not migrate to new suitable locations within this short period. Therefore, governments should make provisions against climate change without delay.
Turkey oak (Q. cerris) is an important species for rehabilitating soils, promoting conservation, and increasing biodiversity. It is also a fire-resistant plant. To predict the potential distribution of this species under climate change is crucial for better understanding the future of ecosystems – in particular Mediterranean ecosystems. The purpose of this study was to generate the potential distribution maps of Turkey oak under current and changing climate in the Sütçüler district located in the translation zone of the Mediterranean region. Classification and regression tree technique (CART) was applied to model the distribution of the species (response data) using current climatic data, parent material, landform types, and topographical position index (explanatory data). Geographic information system (GIS) was used for visualizing current potential distribution of the species. Next, the obtained distribution model was simulated to the digital data of climatic change scenario b2 of IPCC. In this way, changing the potential distribution of Turkey oak along the district was predicted under climate change.
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