Abstract

Yongyut Trisurat Rob Alkemade and Eric Arets

Climate change is a global threat to biodiversity because it has the potential to cause significant impacts on the distribution of species and the composition of habitats. The objective of this research is to evaluate the consequence of climate change in distribution of forest tree species, both deciduous and evergreen species. We extracted the HadCM3 A2 climate change scenario (regionally-oriented economic development) for the year 2050 in northern Thailand. A machine learning algorithm based on maximum entropy theory (MAXENT) was employed to generate ecological niche models of forest plants. Six evergreen species and 16 deciduous species were selected using the criteria developed by the Asia Pacific Forest Genetic Resources Programme (APFORGEN) for genetic resources conservation and management. Species occurrences were obtained from the Department of National Park, Wildlife and Plant Conservation. The accuracy of each ecological niche model was assessed using the area under curve of a receiver operating characteristic (ROC) curve. The results show that the total extent of occurrence of all selected plant species is not substantially different between current and predicted climate change conditions. However, their spatial configuration and turnover rate are high, especially evergreen tree species. Ten plant species will loss their ecological niches (suitable locations) ranging from 2 - 13%, while the remaining 12 species will gain substantial suitable habitats. The assemblages of evergreen species or species richness are likely to shift toward the north where low temperature is anticipated for year 2050. In contrast, the deciduous species will expand their distribution ranges. Based on the IUCN Red List criteria, 10 plant species will be categorized as near threatened (NT) and 12 species will be listed as concerned status. An important point is that species distribution models were found to depend significantly on extreme climate variables such as minimum temperature of coldest months, and precipitation of driest and coldest quarters.