The paper was presented at FORTROP, during November 2008, Kasetsart University BKK, Thailand. Climate Change Impact on Forest Area in Thailand

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1 The paper was presented at FORTROP, during November 2008, Kasetsart University BKK, Thailand Climate Change Impact on Forest Area in Thailand Nathsuda Pumijumnong 1 and Jassada Techamahasaranont 2 1 faculty of Environment and Resource Studies, Mahidol University; nathsuda@gmail.com; (corresponding author) 2 Kasetsart Universities, Sakhonnakhon Campus, Thailand. jediku@hotmail.com) Abstract Climate is probably the most important determinant of vegetation patterns globally and has significant influence on the distribution, structure and forest ecosystem. Global warming has been a serious environmental issue world wide. Natural resources such as forest ecosystem are both directly and indirectly most beneficial to human being and all living things. Therefore impact of climate change to natural resources would impact human being and other living things as well. This research aims to assess how climate change impacts the forest area at upper ChaoPhraya river basin, the most important watershed basin for Thai people. Forest type models (hill evergreen forest, dry evergreen forest, Mixed coniferous forest, mixed-deciduous forest, and dry dipterocarp forest) are established and verified using characteristics of each forest type and climate data set ( ). Climate data set in the future from , , , and from scenario double CO 2 (740 ppm) then is applied to predict the future forest types. The results are discussed and mitigation option is recommended. Key words: climate change, impact, forest, Thailand, upper ChaoPhraya river basin Introduction Tropical and subtropical forest are home of biodiversity and supply indirectly advantage to mankind such as controlling water runoff during heavy rain to prevent soil erosion or land slide, promoting human health by absorbing carbon dioxide and releasing oxygen through photosynthesis process and etc. Impacts on natural 1

2 resources due to climate change have been studied world wide but the degree of the impacts is different from region to region and from country to country. Tropical forest is vulnerable to climate impact. Projecting climate change could threaten the biodiversity of these forest areas and traditional people who depend upon the forest for their living. Forest ecosystem in Thailand has already been subjected to socio-economic pressures leading to forest degradation and loss, with adverse impacts on the livelihood of the forest-dependent communities. Climate change is another additional pressure on forest ecosystem. In this research we set conceptual framework shown in Fig. 1 to demonstrate how we can establish models of forest types. Then we employ application of GIS to modify environmental factors and compare the results of forest types to the actual forest types in the year 2002 using computer modeling. The Study Area We selected the forest area in northern Thailand as the study site with the reasons that this area has remained the largest forest area in Thailand and also consist of all forest types find in Thailand except tropical rain forest and mangrove forest. The main forest type in our study consists of 1) Every green forest which composes of dry evergreen forest, pine mixed dipterocorp forest and hill evergreen forest and 2) Dry deciduous forest which composes of dry dipterocarp forest and mixed deciduous forest. (Fig. 2). 2

3 Fig. 1 Conceptual framework 3

4 Fig. 2 study area Material and Methods According to any interaction software between regional climate model and vegetation model and world biome type classification which normally use only average temperature and total rainfall to distinguish all of biome in the world, forest type in Thailand will fall in the category of tropical rain forest. It is however rather coarse for Thai forest type classification. Therefore, to perceive our objective we set up the formula between forest type in Thailand and environment characteristic which influence forest types. We select elevation, soil depth, rainfall, wet and dry period, mean temperature and evapotranspiration rate as environmental characteristics in our study. We also use all literature in Thailand that state the characteristics of each forest 4

5 type in Thailand namely Chingchai (1992), Niwat (1996) and Uthid (1998) (table 1.) to formulate all of the forest types in our study area and change each parameter to computer codes. In fact all of physical factors that influence each forest type are overlapping such as we can find both dry dipterocarp forest and mixed deciduous forest at an elevation m. msl. The amount of rainfall in each forest type is approximately mm per year for dry dipterocarp and more than 1200 mm per year for mixed deciduous forest. The main distinction between both forest types perhaps is the soil depth. While dry dipterocarp forest mainly confines in laterite soil which it is rather shallow, mixed deciduous forest mainly confines in deeper soil. Therefore each environmental factor is being classified in the range to coincide with each forest type, and converted to a code for computer procedure (see Fig. 3). Table 1 environmental factor of forest types in northern Thailand Forest type Hill evergreen forest (HEF) Dry evergreen forest (DEF) Mixed coniferous forest ((MCF) Mixed-deciduous forest (MDF) Dry Dipterocarp Forest (DDF) Elevation: msl Soil Depth Precipitati on: mm Wet-Dry period Mean Temperature: mediumhigh lowmedium M month ( C ) >1,200 high 1,000- >8 - <4 <24 1, high 1, , ,800 medium 1, <20 1, ,000 <1, ,200 Source : Chingchai (1992), Niwat (1996) and Uthid (1998) <8 - >4 <8 - > Ration of evapotranspiration and rainfall (Et/P) low low medium high high 5

6 Fig. 3 Environmental factors that influence forest types being classified and coded for computer and identified for forest types. Rainfall Rainfall data that we use to classify forest types in northern Thailand come from Meteorological Department, Thailand. Most meteorological stations are located on plain land therefore there is some uncertainty about amount of rainfall in our study area. To reduce such an error we use an equation to calculate a new data set of rainfall at the high elevation; rain = elevation (Kringkrai, 2001) to get the amount of rainfall for forest type that grow at high elevation such as hill evergreen forest and mixed coniferous forest. After that we modify the value to our study area by using application of geography information system (GIS) (Fig. 4). Fig. 4 Modification of amount of rainfall to study area 6

7 Wet-Dry Period Forest types in Thailand are obviously distinguished by wet and dry periods. For instance, dry dipterocarp forest prefers real dry period at least four months in a year. On the other hand, evergreen forest prefers long wet months. We classify the range of wet and dry periods into three categories (see table 1) and use application of GIS to modify the value to our study area (Fig. 5). Fig. 5. Modification of wet and dry periods to study area Fig. 6. Modification of soil depth to study area 7

8 Soil Depth Generally soil types in Thailand classified by Land Development Department (LDD) in Bangkok are mainly for agriculture recommendation for appropriate crops. Therefore LDD does not classify soil properties in forest areas with an assumption that the areas are unsuitable for agriculture. We classify soil depth in our study into four classes: high, medium, high-medium and low-medium as shown on Table 1 according to its appropriateness to our forest types. Steps for soil modification to our study area are shown in Fig.6. Temperature This parameter data from Meteorological Department also has limitation since the data have been recorded at meteorological stations that located on plain land. Therefore in this study, we use a principle of adiabatic lapse rate; temperature will be decreased 1 C in every high 100 m., formula to calculate new temperature value at high elevation. The formulae is tem (adb) = (elevation-500)/100. Then we modify this new value to our study area by using GIS (see Fig. 5). Fig. 7. Modification of temperature to study area Ration of Evapotranspiration and Rainfall Evapotranspiration is a factor that being influenced by other factors such as the amount of rainfall, temperature and vegetation. We use a formula; AET = 0.7 8

9 (PET) (Agriculture Research Service, 1972) to calculate the ration of evapotranspiration for our study area (Fig. 8). Fig. 8. Modification of ration of evapotranspiration to study area Fig. 9. Environmental factors are overlaid and selected the appropriate forest types 9

10 Predicted Forest Types in Northern Thailand From Fig. 9 after we overlay all environmental factors that influence forest types, the computer simulates and gives results for predicted forest types. We then compare the predicted forest types with the actual forest types classified by Forestry Department. The results are shown in Table 2. Fig. 10 Predicted forest types by using environmental factors Table 2 Comparison between predicted forest types and actual forest types Forest type Evergreen Forest Hill Evergreen Forest (HEF) Dry Evergreen Forest (DEF) Mixed Coniferous Forest (MCF) Deciduous Forest Mixed Deciduous Forest (MDF) Dry Dipterocarp Forest (DDF) Actual forest type in 2002 Percentage of forest area Predicted of forest type in

11 Result and Discussion Fig. 11 Trend of forest change in Northern Thailand from , , , and by using climate scenario A2 Note: DDF = Dry Dipterocarp Forest, MDF = Mixed Deciduous Forest, DEF = Dry Evergreen Forest HEF = Hill Evergreen Forest MCF = Mixed Coniferous Forest 11

12 Table 3 Comparison trend of forest change in northern Thailand from Forest type Forest area (%) Evergreen Forest Hill Evergreen Forest (HEF) Dry Evergreen Forest (DEF) Mixed Coniferous Forest (MCF) Deciduous Forest Mixed Deciduous Forest ( MDF) Dry Dipterocarp Forest (DDF) Current and Future Climate Patterns The mean annual precipitation in northern Thailand as computed by the SEA START RC (2008) data is about mm ( ) and the mean annual temperature is about 27 C. The projected climate (average for , and ) for more extreme A2 (740 ppm CO 2 ) scenario is about , and mm and 31, 33 and 35 C respectively. There is considerable geographical variation in the magnitude of changes for both temperature and rainfall; north Thailand is likely to become drier. The area in northern Thailand is about 172, km 2 with forest cover at about 113,098 km 2 (65.68 %). After entering climate scenario for , and , we have results shown in Table 3 and Fig. 11. It could be explained that dry evergreen forest is probably the most vulnerable among forest types in northern Thailand. It would disappear in the year However it should be kept in mind that this forest type is not the majority of forest types in northern Thailand. Most of evergreen forest (dry evergreen forest, hill evergreen forest and Mixed coniferous forest) would loss cover area under climate scenario A2. Deciduous forest (mixed deciduous forest and dry dipterocarp forest) would gain cover area under climate scenario A2. However there is such a trend change under one scenario double CO 2 (A2; extremely climate scenario for 740 CO 2 and also without any adaptation process). This research results have given examples of possible changes of Thai forest in northern Thailand where it functions as watershed area for the main stream of ChaoPhraya River. Thus if green house gases have been 12

13 emitted at the level of double CO 2 (approximately 740 ppm) to global atmosphere, Thai forest will be suffered. This is also a signal for Thai government to setting adaptation activity to cope global warming impact on our forest area. Modeling potential change of forest area in Thailand under climate change was first done by Boonpragob and Santisirisomboon (1996). The research examined total forest areas in Thailand. The authors used Holdriridge Life Zone classification to divide forest areas in Thailand into seven classes namely subtropical dry forest, subtropical moist forest, subtropical wet forest, tropical very dry forest, tropical dry forest, tropical moist forest and tropical wet forest. Those forest names or forest types are not, however common in Thailand. The research used 3 climate scenario; UK 89, GISS and UKMO to predict forest change in the future. The results revealed that the subtropical life zone would decline from about 50% to 20-12% of total cover, whereas the tropical life zone would expand its cover from 45% to 80%. All three circulation model scenarios suggested that the tropical dry forest would have the greatest appropriate potential to extend into subtropical moist forest. The authors suggested that an appropriate strategy would be selecting drought adapted species for northeast and north and wet tolerant species for the south. These results are comparable to those of ours while deciduous forest would expand due to climate scenario in the future with general higher temperature and even with more rainfall. Dry dipterocarp forest prefers high temperature and is able to tolerate drought would compensate in future climate to extend its cover area. The climate change impact on forest area was also done in Indian forest (Ravindranath et al. 2006). The study was done based on climate projections on regional climate model of the Hadley Centre (HadRM3) using the A2 (740 ppm CO 2 ) and B2 (575 ppm CO 2 ) scenario and the BIOME4 vegetation response model. The main conclusion indicated that for the year 2085 the lost forest types would be tropical xerophytic shrub land, tropical deciduous forest/woodland, warm mixed forest, tropical semi-deciduous forest, temperate sclerophyll woodland, cool conifer forest, evergreen taiga/montane forest and cold mixed forest. The only three forest types that would benefit from future climate would be tropical savanna, tropical evergreen forest and temperate conifer forest. However the results of this particular study could not be compared to ours due to differences in methods and types of forest. The results from our study could be viewed as suggestion of possible changes in the forest area at upper ChaoPhraya river basin due to climate change. However, 13

14 magnitudes should be viewed with caution due to limitation of parameters used in this study and also other factors can very well contribute to the changes as well. For further research on climate change impact on forest in Thailand, better reliability of climate projection at regional level and use of dynamic vegetation model are needed. Also, data limitation is needed to be overcome by initiating studies to develop data base on forest vegetation characteristics and plant physiology. Acknowledgements This research was funded by Office of Natural Resources and Environmental Policy and Planning, Ministry of Natural Resources and Environment, Thailand. We would appreciate deeply thank SEA START RC (2008) provided us climate scenario A2, Miss Patcharin Pumchamnong for her kindness read through manuscript. References Agriculture Research Service A comparison of Lysimeter-Derived Potential Evapotranspiration with computed Values. Technical Bulletin No USDA, Washington. D.C. 71p. Boonpragob K. and Santisirisomboon J Modeling Potential Changes of Forest Area in Thailand under Climate Change. Water, Air and Soil Pollution 92: Chingchai Viriyabancha Analysis of Rainfall and forest distribution in Thailand, Master Thesis, Kasetsart University, Bangkok. Niwat Roungpanit Resources and Environment Conservation. Department of Conservation, Fac. of Forestry, Kasetsart University. Bangkok. Uthid Koodin Forest Ecology. Department of Forest Biology, Fac. of Forestry, Kasetsart University. Kringkrai Boontem Study on distribution of rain pattern in Mae Jam, Chiang Mai province by using application of Geographic Information System (GIS). Seminar on Watershed Management annual report. Department of Conservation, Kasetsart University, Bangkok. Ravindranath N.H., Joshi N.V., Sukumar R. and Saxena A Impact of climate change on forests in India. Current science, vol. 90, No Southeast Asia Regional Centre (SEA START RC) Climate Change scenario model for Thailand. Chulalongkorn University, Bangkok. 14

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