This study was conducted in the north-eastern part of Bangladesh, a region that is experiencing an increasing trend of temperature and rainfall over time. The area comprises two different districts (Moulvibazar and Habiganj), which are considered the major biodiversity hotspots of Bangladesh, and include three protected areas currently managed under an Integrated Protected Area Co-management (IPAC) system: the Lawachara National Park, the Rema-Kalenga Wildlife Sanctuary, and the Satchari National Park (SNP). Few scattered forest areas still exist adjacent to these protected areas. In the Lawachara National Park, 167 plant species, 26 mammalian species (including 5 non-human primates), 246 bird species, 4 amphibian, and 6 reptile species have been recorded so far. The forest is semi-evergreen with a canopy height varying from 10 m to 30 m. The top canopy mainly comprises Tectona grandis, Artocarpus chaplasha, Tetrameles nudiflora, Hopea odorata, and Toona ciliata. The second canopy comprises Syzygium grande, Syzygium jambos, Syzygium cumini, Gmelina arborea, Ficus benghalensis, Dillenia pentagyna, Grewia asiatica, Ficus infectoria, and many more plant species. The understory includes Bambusa tulda, Alstonia scholaris, Eupatorium odoratum etc. together with several ferns and epiphytes. The original indigenous mixed tropical evergreen vegetation was logged in the 1920s. The soil of Lawachara is alluvial brown sandy clay loam to clay loam. SNP has more than 200 plant species. Acidic soils (sandy loam to silt clay) dominate this area and the relief is characterized by a gently undulating plain changing to a hilly topography. The prominent vegetation type in SNP is mixed tropical evergreen forest. The relatively undisturbed forest is almost entirely restricted to the national park. At present, areas outside the reserved forest are being extensively converted into agricultural fields, fruit orchards, human settlements, sungrass (Saccharum spontaneum) fields including plantations of fast-growing timber species. Most plantations are dominated by exotic species such as Acacia spp., Eucalyptus camaldulensis, Tectona grandis, Albizia falcataria and Elaeis guineensis, forerunners of the palm oil industry in the country planted in this area during the mid-seventies. Rema-Kalenga wildlife sanctuary has 167 bird species, 37 species of mammals, and 638 plant species ([24]). The soil texture is sandy loam to silty clay and acidic. The terrain of the national park is undulating with slopes and hillocks, locally called tila, ranging from 10-50 m, scattered in the forest. The forest is drained by a number of small, sandy-bedded streams ([23]). Nineteen bioclimatic variables with 30-second (1 km) spatial resolution were obtained from the WorldClim dataset, and used to detect the most influential variables associated with the present and future distribution of D. binectariferum. Future climate scenario data for the years 2050 and 2070 (based on IPCC 5th assessment data) were downloaded from the WorldClim dataset, and used to project the potential distribution of the species under climate change. These data sets were down scaled and calibrated using WorldClim 1.4 as baseline “current” climate data. Two future greenhouse gas concentration trajectories, called as Representative Concentration Pathways (RCP) 4.5 and RCP 8.5 were selected for the periods 2050 and 2070, respectively. The RCP 4.5 is a relatively stable scenario where the total radiative forcing reaches 4.5 W m-2 by 2100 and further stabilises owing to the adoption of green technologies. Contrastingly, in RCP 8.5 emissions continue to increase throughout the 21st century. In this scenario, radiative forcing is predicted to reach up to 8.5 W m-2 by 2100 A Global Circulation Model (GCM), known as “Hadley Global Environment Model 2 Carbon Cycle” (HadGEM2-CC) and widely employed for simulating RCPs, was used in this study. To reduce the influence of highly correlated variables, a multi-collinearity test was conducted to check cross-correlation among variables. Variables showing pairwise Pearson’s correlation coefficient |r| ≥ 0.8 were excluded from the analysis. Based on such criterion, 14 bioclimatic variables were excluded and only 5 bioclimatic variables were used in the final model to predict the effect of climate change on the future distribution of D. binectariferum.