Predicting the effect of climate change on the spatiotemporal distribution of two endangered plant species, Silene leucophylla Boiss. and Silene schimperiana Boiss., using machine learning, in Saint Catherine Protected Area, Egypt

Climate change is projected to significantly reduce or eliminate the suitable habitats for two endangered plant species, Silene leucophylla and Silene schimperiana, in Egypt's Saint Catherine Protected Area by 2080. The study used machine learning algorithms to model their current distributions and predict future changes under the worst-case climate scenario (RCP8.5). While S. leucophylla faces rapid range contraction by 2050-2070, S. schimperiana may experience both habitat loss and expansion in some areas before disappearing entirely. Key environmental factors like precipitation, temperature, altitude, and seasonality were critical predictors of their distribution. The findings underscore the urgent need for conservation strategies to protect these vulnerable species from climate-driven threats.

Refaat, A. M., Youssef, A. M., Mosallam, H. A.-A., & Farouk, H. (2024). Predicting the effect of climate change on the spatiotemporal distribution of two endangered plant species, Silene leucophylla Boiss. and Silene schimperiana Boiss., using machine learning, in Saint Catherine Protected Area, Egypt. Beni-Suef University Journal of Basic and Applied Sciences, 13(1). https://doi.org/10.1186/s43088-024-00553-2