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The impact of climate change on ecosystems, especially at the species level, can be currently observed in many parts of the world. Species distribution models (SDMs) are widely used to predict the likely changes in the distribution of species in future climate change scenarios. The aim of the present study is to predict the effect of climate change on a valuable threatened tree species Dysoxylum binectariferum in the northeastern part of Bangladesh using the maximum entropy (MaxEnt) model on species’ occurrence data. The future distribution of D. binectariferum was predicted under two scenarios from the IPCC 5th assessment (RCP 4.5, and RCP 8.5) in 2050 and 2070. Model results showed that approximately 32% (2177 km2) of the studied area is currently suitable for this species to grow. However, future predictions obtained by the model projected a complete loss of suitable habitat for D. binectariferum in the studied area by both 2050 and 2070. Therefore, urgent measures are required for the conservation of D. binectariferum in northeastern Bangladesh. The application of species distribution models to simple inventory data (such as the occurrence of the species) may provide policymakers and conservationists with a useful tool for the prediction of future distribution (at both local and regional scales) of poorly known species with high preservation concerns.

iforest

Predicting impacts of climate change on forest tree species of Bangladesh: evidence from threatened Dysoxylum binectariferum (Roxb.) Hook.f. ex Bedd. (Meliaceae)