Habitat distribution modelling to identify areas of high conservation value under climate change for Mangifera sylvatica Roxb. of Bangladesh
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The impact of climate change on ecosystems, especially at the species level, is already being observed across the world. To assess potential future climate change effects on species, scientists often use species distribution modelling (SDM). The estimation of likely changes in the distribution of species under future climate conditions is a crucial first step towards the mitigation and management of future species losses or habitat shifts. Considering this, the aim of the present study is to predict the effect of climate change on a valuable threatened tree species, Mangifera sylvatica Roxb., of Bangladesh using Maximum Entropy. The current potential distribution as by the model suggests that around 5% of the study area is highly suitable wild mango habitat, with between 6% and 11% being moderately suitable. Under the RCP 4.5 scenario, the net decrease in suitable habitat is predicted to be 7% by 2070. Under the RCP 8.5 scenario, the model predicts that the total area suitable for mango will reduce by 12% by 2050, disappearing altogether by 2070. Therefore, urgent measures are required for the conservation of M. sylvatica in Bangladesh. The application of the species distribution model 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. The approach used in this study can provide a rapid assessment of the future conservation status of other important forest tree species in Bangladesh to improve our understanding of the vulnerability under changing climate.
Keywords
- Threatened species; MaxEnt; Geographic distribution; Habitat suitability; Conservation
Original language | English |
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Pages (from-to) | 223-232 |
Number of pages | 9 |
Journal | Land Use Policy |
Volume | 60 |
Early online date | 3 Nov 2016 |
DOIs | |
Publication status | Published - 7 Nov 2016 |
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