MaxEnt Modeling for Predicting the Current and Future Potential Geographical Distribution of Quercus libani Olivier

Abstract

The purpose of the study was to model the current and potential future distribution of Quercus libani Olivier (Lebanon Oak), a tree species in Turkey, and to predict the changes in its geographical distribution under different climate change scenarios. In this study, 19 bioclimatic variables at a spatial resolution of 30 arc seconds (~1 km2) were used, collected from the WorldClim database. The bioclimatic data with high correlation according to 31 sets of presence data on the species were reduced with principal component analysis (PCA), and the current and potential distribution were identified using MaxEnt 3.4.1 software. In order to predict how the distribution of the species will be affected by climate change, its potential geographical distribution by 2050 and 2070 was modeled under the Representative Concentration Pathways (RCP) RCP 4.5 and RCP 8.5 scenarios of the species using the Community Climate System Model (CCSM, version 4), which is a climate change model based on the report of the fifth Intergovernmental Panel on Climate Change (IPCC). Change analysis was performed to determine the spatial differences between its current and future distribution areas. The study results showed that the suitable areas for the current distribution of Quercus libani Olivier cover 72,819 km2. Depending on the CCSM4 climate model, the suitable area will decline to 67,580 km2 by 2070, according to the RCP 4.5 scenario, or 63,390 km2 in the RCP 8.5 scenario. This may lead to a reduction in the future population of this species. The change analysis showed that suitable and highly suitable areas will decrease under global climate change scenarios (RCP 4.5 and RCP 8.5) for both current and future potential distribution areas. In this context, our study results indicate that for the management of this species, protective environmental measures should be taken, and climate change models need to be considered in land use and forest management planning.