Modelling climate change effects on Zagros forests in Iran using individual and ensemble forecasting approaches

Abstract

It is believed that climate change will cause the extinction of many species in the near future. In this study, we assessed the impact of climate change on the climatic suitability of the Persian oak in Zagros forests in southwest Iran, by simulating their conditions under four climate change scenarios in the 2030s, 2050s, 2070s, and 2080s. Additionally, we evaluated the predictive performance of different modelling algorithms by projecting the geographic distribution of Persian oak, using a block cross-validation technique. According to the results, the Persian oak shows a stronger response to temperature, particularly the maximum temperature of the warmest month, rather than precipitation variables. This indicates that temperature has a powerful control over the geographic distribution of the Persian oak. Based on a comparison of the Persian oak’s current climatic suitability and future projections, regardless of the chosen climatic scenarios, there will be an upward shift in its climatic suitability. However, an upward shift under the pessimistic scenarios was greater than the optimistic ones. The results also indicate that an ensemble of all models had a higher accuracy than single models. Despite the agreement between current climate condition predictions (mean correlation of 0.94), the projection of different algorithms for future periods is highly variable (mean correlation of 0.71). Thus, the ensemble approach was used to reduce the uncertainty of modelling, favouring the consensus of all models for future projection.