Environment factors control and climate change impact on forest type: Dong PraYa Yen-KhaoYai world heritage in Thailand

• Main Authors: Nathsuda Pumijumnong, Paramate Payomrat, Jessada Techamahasaranont, Surapol Panaadisai, นาฎสุดา ภูมิจำนงค์
• Other Authors: Mahidol University. Faculty of Environment and Resource Studies
• Format: Article
• Language: English
• Published: 2015
• Subjects: Carbon Content; Dong PraYa Yen- KhaoYai Forest Complex; Cluster Analysis; Climate Change; CCA
• Online Access: https://repository.li.mahidol.ac.th/handle/123456789/48336
• Institution: Mahidol University

Climate is a major determinant of global vegetation patterns and has a significant influence on the distribution and structure of forest ecosystems. Dong PraYa Yen-KhaoYai Forest Complex has been a UNESCO natural world heritage site since 2007, but little is known about its plant community. Our study aims to identify each plant community within the world heritage area and calculate its potential for carbon content. We determine both the relationship between forest type and both physio-chemical soil properties and climate change impact. We employed allometric equations to calculate aboveground biomass and both cluster analysis and canonical correspondence analysis (CCA) to examine the relationship between forest type and physiochemical soil properties. An equation for each physical parameter was used to predict the forest model. The climate scenario under A2 and B2 was applied to calculate future predominant forest types. Our results reveal that the forest ecosystems at Tab Lan (TL) have the highest species count (332 species) followed by Pang Srida (PD), KhaoYai (KY), Dong Yai (DY), and Tapraya (TY), with 293, 271, 169, and 99 species, respectively. We found KY to have the highest recorded carbon storage value at 2507.6 tC/ha followed by TL, PD, TY, and DY (1613.8, 1269.1, 844 and 810.7 tC/ha, respectively). Cluster analysis results indicated that the dominant species in each forest type is different. Moreover, CCA revealed that soil organic matter (SOM) and soil acid-base indicators are the best parameters to establish correlation for each forest type. Based on our results, future climate predictions show a negative impact on evergreen forests, but a positive one on deciduous ones.