Research Information System
Ecological Informatics, vol.66, pp.1-28, 2021 (SCI-Expanded)
There is an urgent need to conduct scientific research in order to comprehend the impact of climate change on the geographical distribution of species that constitute an ecological niche. To meet this need, the current and future distribution areas of a species can be predicted by applying machine learning techniques. This study aims to model the current and future geographical distribution of common hornbeam under different climate scenarios. Furthermore, we focus on the differences between the predicted current and future potential distribution areas of the species in terms of area and location by means of change analysis. 15 bioclimatic variables obtained for presence data from sample points representing the natural distribution area of common hornbeam were reduced to six variables to prevent high correlation and multi-collinearity. Next, the CNRM-ESM-1 climate change model was used to determine how the distribution areas of the species will be affected by climate change and the potential distribution areas of the species under the SSP2 4.5 and SSP5 8.5 scenarios in the periods 2041–2060 and 2081–2100 were modelled by MaxEnt 3.4.4 software. The change analysis comparing the current and future potential distribution areas suggested that common hornbeam would be affected by climate change, expanding its range in the north. The findings can be used effectively to address biodiversity conversation planning and management as a whole and develop new strategies. In this way, future risks can be diminished.