Potential distribution pattern of the Quercus brantii Lindl. and Quercus frainetto Ten. under the future climate conditions.

This research aims to predict the potential distribution patterns of Brant's oak (Quercus brantii Lindl.) and Hungarian oak (Quercus frainetto Ten.) using three different climate models: HadGEM3-GC31-LL, MPI-ESM1-2-HR, and INM-CM5-0, all with a spatial resolution of 30 s (1 km2). These models were developed for CMIP 6 and utilize scenarios of SSP2-4.5 and SSP5-8.5 for various time periods spanning from 2041 to 2100. To compare the current potential distribution area with those of the periods for different climate models, a change analysis was conducted. The study area covers distribution areas extending from the coastline of Portugal to the southwest of Iran. When comparing the medium–low and high forcing climate models based on the climate sensitivity, we observed that the distribution patterns of both species vary depending on the scenario and time period. Compared to the current distribution, suitable areas of Quercus brantii Lindl. expected to decrease as 84% (109,854 km2) for HadGEM3-GC31-LL climate model and SSP5-8.5 scenario 2081–2100 time period. On the other hand, suitable areas of Quercus frainetto Ten. expected to increase as 59% (618,848 km2) for INM-CM5-0 climate model and SSP5-8.5 during the time period 2081–2100. When it comes to change analysis result, HadGEM3-GC31-LL climate model and SSP5-8.5 scenario project the most significant alterations in the distribution areas of Quercus frainetto Ten. and Quercus brantii Lindl. during the time period 2081–2100, resulting in a loss of 763,046 km2 and 220,759 km2, respectively. The results of the change analysis indicate that the areas marked as loss and gain for both species exhibit differences between the climate change scenarios and time periods. The findings of this research highlight that climate models offer a technological approach to adaptive forest management, enabling the development of strategies to mitigate issues related to climate change. [ABSTRACT FROM AUTHOR]