Habitat distribution modelling to identify areas of high conservation value under climate change for Mangifera sylvatica Roxb. of Bangladesh
Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid
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Yn: Land Use Policy, Cyfrol 60, 07.11.2016, t. 223-232.
Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid
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T1 - Habitat distribution modelling to identify areas of high conservation value under climate change for Mangifera sylvatica Roxb. of Bangladesh
AU - McDonald, Morag
AU - Marriott, Raymond
AU - Akhter, Sayma
AU - Van Breugel, Paulo
PY - 2016/11/7
Y1 - 2016/11/7
N2 - 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.
AB - 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.
KW - Threatened species; MaxEnt; Geographic distribution; Habitat suitability; Conservation
U2 - 10.1016/j.landusepol.2016.10.027
DO - 10.1016/j.landusepol.2016.10.027
M3 - Article
VL - 60
SP - 223
EP - 232
JO - Land Use Policy
JF - Land Use Policy
SN - 0264-8377
ER -