Freshwater Swamp Forest Trees of Bangladesh Face Extinction Risk from Climate Change

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• 作者：Jiban Chandra Deb ; H. M. Tuihedur Rahman ; Anindita Roy
• 关键词：Swamp trees ; Distribution ; Climate change ; MaxEnt ; Modelling ; Bangladesh
• 刊名：Wetlands
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：36
• 期：2
• 页码：323-334
• 全文大小：1,229 KB
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• 作者单位：Jiban Chandra Deb (1) (2)
  H. M. Tuihedur Rahman (3)
  Anindita Roy (4)
  
  1. Remote Sensing Research Centre, School of Geography, Planning and Environmental Management, The University of Queensland, St Lucia Campus, St Lucia, QLD, 4072, Australia
  2. Department of Forestry and Environmental Science, School of Agriculture and Mineral Science, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh
  3. Department of Natural Resource Sciences, Faculty of Agricultural and Environmental Sciences, McGill University, Macdonald Campus 21,111 Lakeshore Road, Ste-Anne-de-Bellevue, Québec, H9X 3V9, Canada
  4. Department of Biological Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, NSW, 2109, Australia
  
• 刊物主题：Freshwater & Marine Ecology; Environmental Management; Ecology; Hydrogeology; Coastal Sciences; Landscape Ecology;
• 出版者：Springer Netherlands
• ISSN：1943-6246

文摘

Global climate change is impacting the distribution and abundance of species acting as a major cause of species extinction. It is rapid in freshwater swamp forest ecosystems, since they support disproportionate levels of biodiversity compared to their spatial coverage. The natural swamp forests of Bangladesh have been especially susceptible to climate change as they are limited in range to a few scattered patches in the north-eastern region. We sought to understand how climate change may impact the swamp forests of Bangladesh by modelling distributional changes in Pongamia pinnata and Barringtonia acutangula species, which dominate or co-dominate most swamp forest ecosystems across Bangladesh. We used the maximum entropy (MaxEnt) modelling tool, combined presence-only data of species and bioclimatic variables for two climate scenarios (RCP6.0 and RCP8.5). We compared current, 2050 and 2070 distributions. Results suggest that plant extractable water holding capacity of soil, annual precipitation, precipitation of warmest quarter and mean annual actual evapotranspiration are the key bioclimatic variables for the distribution of both trees. The MaxEnt models indicate that Pongamia pinnata and Barringtonia acutangula trees of Bangladesh face increasing climate stress and may become extinction under both mid-range and extreme climate scenarios.