Abstract
AbstractTossa (Corchorus olitorius L.) is a significant cash crop, cultivated commercially in the lower flood plain of Bangladesh. The climatic regimes in Bangladesh are changing as well as the world does. However, this species is threatened by climate change. Occurrences of data on threatened and endangered species are frequently sparse which makes it difficult to analyse the species suitable habitat distribution using various modelling approaches. The current paper used maximum entropy (Maxent) and educational global climate model (EdGCM) modelling to predict and conserve the suitable habitat distributions for Tossa species in Bangladesh to the year 2100. Nine environmental variables, 239 occurrence data and two Representative Concentration Pathway scenarios (RCP4.5 and RCP8.5) were used for the Maxent modelling to project the impact of climate change on the Tossa distributions. Furthermore, the EdGCM was used to study the climatic space suitability for the Tossa species in the context of Bangladesh. Both of the climatic scenarios were used for the prediction to the year 2100. The Maxent model performed better than random for the Tossa species with a high AUC value of 0.86. Under the RCP scenarios, the Maxent model predicted habitat reduction for RCP4.5 is 2%, RCP8.5 is 9% and EdGCM is 10.2% from the current localities. The predictive modelling approach presented here is promising and can be applied to other important species for conservation planning, monitoring and management, especially those under the threat of extinction due to climate change.
Publisher
Cambridge University Press (CUP)
Subject
Genetics,Agronomy and Crop Science,Animal Science and Zoology