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    āļ›āļąāļˆāļˆāļąāļĒāļ—āļĩāđˆāļĄāļĩāļœāļĨāļ•āđˆāļ­āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļāļēāļĢāļ™āļģāļ™āđ‚āļĒāļšāļēāļĒāļ„āļ“āļ°āļ„āļēāļĢāđŒāļšāļ­āļ™āļ•āđˆāļģ (Low Carbon Faculty) āļŠāļđāđˆāļāļēāļĢāļ›āļāļīāļšāļąāļ•āļīāļ‚āļ­āļ‡āļšāļļāļ„āļĨāļēāļāļĢāđāļĨāļ°āļ™āļąāļāļĻāļķāļāļĐāļēāļ„āļ“āļ°āļŠāļīāđˆāļ‡āđāļ§āļ”āļĨāđ‰āļ­āļĄāđāļĨāļ°āļ—āļĢāļąāļžāļĒāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒ āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĄāļŦāļīāļ”āļĨ
    (2566) āļ­āļ āļīāļŠāļĢāļē āđ‚āļŠāļ•āļīāļ āļēāļ āļĢāļ“āđŒ; āļ§āļĢāļ™āļąāļ™āļ—āđŒ āļšāļļāļ•āļĢāļēāļŠ; Apisara Chotipaporn; Worranan Bootrach
    āļ‡āļēāļ™āļ§āļīāļˆāļąāļĒāļ™āļĩāđ‰āļĄāļĩāļ§āļąāļ•āļ–āļļāļ›āļĢāļ°āļŠāļ‡āļ„āđŒāđ€āļžāļ·āđˆāļ­āļĻāļķāļāļĐāļēāļĢāļ°āļ”āļąāļšāļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļ„āļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļ–āđƒāļ™āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāļžāļĪāļ•āļīāļāļĢāļĢāļĄ āļ—āļąāļĻāļ™āļ„āļ•āļīāļ•āđˆāļ­āļžāļĪāļ•āļīāļāļĢāļĢāļĄ āļāļēāļĢāļ„āļĨāđ‰āļ­āļĒāļ•āļēāļĄāļšāļļāļ„āļ„āļĨāļ­āđ‰āļēāļ‡āļ­āļīāļ‡āđ€āļāļĩāđˆāļĒāļ§āļāļąāļšāļžāļĪāļ•āļīāļāļĢāļĢāļĄ āļ„āļ§āļēāļĄāļ•āļąāđ‰āļ‡āđƒāļˆāđƒāļ™āļāļēāļĢāđāļŠāļ”āļ‡āļžāļĪāļ•āļīāļāļĢāļĢāļĄ āđāļĨāļ°āļ›āļąāļˆāļˆāļąāļĒāļ—āļĩāđˆāļĄāļĩāļœāļĨāļ•āđˆāļ­āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļāļēāļĢāļ™āļģāļ™āđ‚āļĒāļšāļēāļĒāļ„āļ“āļ°āļ„āļēāļĢāđŒāļšāļ­āļ™āļ•āđˆāļģ (Low Carbon Faculty) āđ„āļ›āļŠāļđāđˆāļāļēāļĢāļ›āļāļīāļšāļąāļ•āļī āđ‚āļ”āļĒāđ€āļāđ‡āļšāļ‚āđ‰āļ­āļĄāļđāļĨ āļˆāļēāļāļšāļļāļ„āļĨāļēāļāļĢ āļˆāļģāļ™āļ§āļ™ 90 āļ„āļ™ āđāļĨāļ°āļ™āļąāļāļĻāļķāļāļĐāļēāļˆāļģāļ™āļ§āļ™ 229 āļ„āļ™āļ‚āļ­āļ‡āļ„āļ“āļ°āļŠāļīāđˆāļ‡āđāļ§āļ”āļĨāđ‰āļ­āļĄāđāļĨāļ°āļ—āļĢāļąāļžāļĒāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒ āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĄāļŦāļīāļ”āļĨāđ‚āļ”āļĒāđƒāļŠāđ‰āđāļšāļšāļŠāļ­āļšāļ–āļēāļĄāđ€āļ›āđ‡āļ™āđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļĄāļ·āļ­āđƒāļ™āļāļēāļĢāđ€āļāđ‡āļšāļĢāļ§āļšāļĢāļ§āļĄāļ‚āđ‰āļ­āļĄāļđāļĨ āļŠāļ–āļīāļ•āļīāļ—āļĩāđˆāđƒāļŠāđ‰āđƒāļ™āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒ āđ„āļ”āđ‰āđāļāđˆ āļ„āļ§āļēāļĄāļ–āļĩāđˆ āļĢāđ‰āļ­āļĒāļĨāļ° āļ„āđˆāļēāđ€āļ‰āļĨāļĩāđˆāļĒ āļŠāđˆāļ§āļ™āđ€āļšāļĩāđˆāļĒāļ‡āđ€āļšāļ™āļĄāļēāļ•āļĢāļāļēāļ™ Independent Samples Test: T-Test One-way ANOVA āđāļĨāļ°āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļāļēāļĢāļ–āļ”āļ–āļ­āļĒ (Regression Analysis) āļ”āđ‰āļ§āļĒāđ‚āļ›āļĢāđāļāļĢāļĄ SPSS version 18 āļœāļĨāļāļēāļĢāļĻāļķāļāļĐāļē āļžāļšāļ§āđˆāļē āļšāļļāļ„āļĨāļēāļāļĢāļĄāļĩāļĢāļ°āļ”āļąāļšāļ—āļąāļĻāļ™āļ„āļ•āļīāļ•āđˆāļ­āļžāļĪāļ•āļīāļāļĢāļĢāļĄ āļ„āļ§āļēāļĄāļ•āļąāđ‰āļ‡āđƒāļˆāđƒāļ™āļāļēāļĢāđāļŠāļ”āļ‡āļžāļĪāļ•āļīāļāļĢāļĢāļĄ āđāļĨāļ°āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļĄāļēāļāļ—āļĩāđˆāļŠāļļāļ” āļĄāļĩāļĢāļ°āļ”āļąāļšāļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļ„āļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļ–āđƒāļ™āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāļžāļĪāļ•āļīāļāļĢāļĢāļĄ āđāļĨāļ°āļāļēāļĢāļ„āļĨāđ‰āļ­āļĒāļ•āļēāļĄāļšāļļāļ„āļ„āļĨāļ­āđ‰āļēāļ‡āļ­āļīāļ‡āđ€āļāļĩāđˆāļĒāļ§āļāļąāļšāļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļĄāļēāļ āļŠāļģāļŦāļĢāļąāļšāļ™āļąāļāļĻāļķāļāļĐāļē āļžāļšāļ§āđˆāļē āļĄāļĩāļĢāļ°āļ”āļąāļšāļ—āļąāļĻāļ™āļ„āļ•āļīāļ•āđˆāļ­āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļĄāļēāļāļ—āļĩāđˆāļŠāļļāļ” āļĄāļĩāļĢāļ°āļ”āļąāļšāļ„āļ§āļēāļĄāļ•āļąāđ‰āļ‡āđƒāļˆāđƒāļ™āļāļēāļĢāđāļŠāļ”āļ‡āļžāļĪāļ•āļīāļāļĢāļĢāļĄ āļžāļĪāļ•āļīāļāļĢāļĢāļĄ āļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļ„āļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļ–āđƒāļ™āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļĄāļēāļ āđāļĨāļ°āļĄāļĩāļĢāļ°āļ”āļąāļšāļāļēāļĢāļ„āļĨāđ‰āļ­āļĒāļ•āļēāļĄāļšāļļāļ„āļ„āļĨāļ­āđ‰āļēāļ‡āļ­āļīāļ‡āđ€āļāļĩāđˆāļĒāļ§āļāļąāļšāļžāļĪāļ•āļīāļāļĢāļĢāļĄāđƒāļ™āļĢāļ°āļ”āļąāļšāļ›āļēāļ™āļāļĨāļēāļ‡ āļ›āļąāļˆāļˆāļąāļĒāļ—āļĩāđˆāļĄāļĩāļœāļĨāļ•āđˆāļ­āļ„āļ§āļēāļĄāļ•āļąāđ‰āļ‡āđƒāļˆāđƒāļ™āļāļēāļĢāđāļŠāļ”āļ‡āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ‚āļ­āļ‡āļšāļļāļ„āļĨāļēāļāļĢāđāļĨāļ°āļ™āļąāļāļĻāļķāļāļĐāļēāđ„āļ”āđ‰āđāļāđˆ āļ—āļąāļĻāļ„āļ•āļīāļ—āļĩāđˆāļĄāļĩāļ•āđˆāļ­ (Îē = 0.63, p-value = 0.00 āđāļĨāļ° Îē = 0.41, p-value = 0.00 āļ•āļēāļĄāļĨāļēāļ”āļąāļš) āļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļ„āļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļ–āđƒāļ™āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄ (Îē = 0.28, p-value = 0.00 āđāļĨāļ° Îē = 0.31, p-value = 0.00 āļ•āļēāļĄāļĨāļēāļ”āļąāļš) āļāļēāļĢāļ„āļĨāđ‰āļ­āļĒāļ•āļēāļĄāļšāļļāļ„āļ„āļĨāļ­āđ‰āļēāļ‡āļ­āļīāļ‡āđ€āļāļĩāđˆāļĒāļ§āļāļąāļšāļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ‚āļ­āļ‡āļšāļļāļ„āļĨāļēāļāļĢ (Îē = 0.09, p-value = 0.02) āļĄāļĩāļœāļĨāļ•āđˆāļ­āļ„āļ§āļēāļĄāļ•āļąāđ‰āļ‡āđƒāļˆāđƒāļ™āļāļēāļĢāđāļŠāļ”āļ‡āļžāļĪāļ•āļīāļāļĢāļĢāļĄ āđƒāļ™āļ‚āļ“āļ°āļ—āļĩāđˆāļāļēāļĢāļ„āļĨāđ‰āļ­āļĒāļ•āļēāļĄāļšāļļāļ„āļ„āļĨāļ­āđ‰āļēāļ‡āļ­āļīāļ‡āđ€āļāļĩāđˆāļĒāļ§āļāļąāļšāļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ‚āļ­āļ‡āļ™āļąāļāļĻāļķāļāļĐāļē (Îē = 0.04, p-value = 0.21) āđ„āļĄāđˆāļĄāļĩāļœāļĨāļ•āđˆāļ­āļ„āļ§āļēāļĄāļ•āļąāđ‰āļ‡āđƒāļˆāđƒāļ™āļāļēāļĢāđāļŠāļ”āļ‡āļžāļĪāļ•āļīāļāļĢāļĢāļĄ āļŠāļģāļŦāļĢāļąāļšāļ„āļ§āļēāļĄāļ•āļąāđ‰āļ‡āđƒāļˆāļāļēāļĢāđāļŠāļ”āļ‡āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ‚āļ­āļ‡āļšāļļāļ„āļĨāļēāļāļĢ āļšāļļāļ„āļĨāļēāļāļĢ (Îē = 0.78, p-value = 0.00) āđāļĨāļ°āļ™āļąāļāļĻāļķāļāļĐāļē (Îē = 0.63, p-value = 0.00) āļĄāļĩāļœāļĨāļ•āđˆāļ­āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļāļēāļĢāļ™āļģāļ™āđ‚āļĒāļšāļēāļĒāļ„āļ“āļ°āļ„āļēāļĢāđŒāļšāļ­āļ™āļ•āđˆāļģ (Low Carbon Faculty) āļŠāļđāđˆāļāļēāļĢāļ›āļāļīāļšāļąāļ•āļīāļ­āļĒāđˆāļēāļ‡āļĄāļĩāļ™āļąāļĒāļŠāļģāļ„āļąāļ
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    Adaptiveness to Enhance the Sustainability of Freshwater-Aquaculture Farmers to the Environmental Changes
    (2022) Anawach Saithong; Suvaluck Satumanatpan; Kamalaporn Kanongdate; Thiyada Piyawongnarat; Poonyawee Srisantear; Mahidol University. Faculty of Environment and Resource Studies; Rajdamnern Nok Avenue. United Nations Building. United Nations Development Programme; King Mongkut's University of Technology Thonburi. Research, Innovation and Partnership Office; Foundation for Environmental Education for Sustainable Development (Thailand)
    Two alternative physical adaptations of freshwater-aquaculture farmers were observed along the upstream Bangpakong Watershed, Thailand. First was the modification of aquaculture types: (1) completely changing former species to others; (2) mixing freshwater prawn with current cultured species; (3) mixing fish with L. vannamei, and second was the direct reaction to environmental changes, including adding freshwater into cultured ponds to reduce temperature and dilute salt concentration; modifying pond-depth; aeration application; and reducing the amount of food or net covering on the water surface during flooding. Principal component analysis revealed that four key components (Options, Learning, Competitiveness, and Plan) reflected the perceived adaptive capacity of farmers to environmental changes. However, culture types have no significant effect on these four components. Farmers with an alternative source of income and practicing monoculture fish farming tend to have a greater ability to change occupation. Old age and more extended experience in aquaculture indicated a low ability to change occupation. The well-educated farmers and farmers who preferred to pass on aquaculture occupation to their children showed higher ability to learn and adapt, but this is not the case for older farmers. Thus, understanding the adaptations of the farmers may assist in promoting appropriate development programs based on their contexts as well as helping decision-makers to have a better plan for strengthening their adaptive capacities based on their perceptions.
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    āļāļēāļĢāļžāļąāļ’āļ™āļēāđāļĨāļ°āļ›āļĢāļ°āđ€āļĄāļīāļ™āļĢāļ°āļšāļšāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļšāļģāļĢāļļāļ‡āļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāļ­āļ­āļ™āđ„āļĨāļ™āđŒāļ„āļ“āļ°āļŠāļīāđˆāļ‡āđāļ§āļ”āļĨāđ‰āļ­āļĄāđāļĨāļ°āļ—āļĢāļąāļžāļĒāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒ
    (2564) āļ›āļĢāļ°āļ—āļĩāļ› āđ€āļ—āļžāļĒāļĻ; āļ­āļ āļīāļĢāļĄāļĒāđŒ āļ­āļąāļ‡āļŠāļļāļĢāļąāļ•āļ™āđŒ; Pratip Tepyot; Apirom Angsurat; āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĄāļŦāļīāļ”āļĨ. āļ„āļ“āļ°āļŠāļīāđˆāļ‡āđāļ§āļ”āļĨāđ‰āļ­āļĄāđāļĨāļ°āļ—āļĢāļąāļžāļĒāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒ. āļ‡āļēāļ™āļŠāļēāļĢāļŠāļ™āđ€āļ—āļĻ; āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĄāļŦāļīāļ”āļĨ. āļ„āļ“āļ°āļŠāļīāđˆāļ‡āđāļ§āļ”āļĨāđ‰āļ­āļĄāđāļĨāļ°āļ—āļĢāļąāļžāļĒāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒ. āļ‡āļēāļ™āļāļēāļĒāļ āļēāļžāđāļĨāļ°āļšāļĢāļīāļāļēāļĢāļžāļ·āđ‰āļ™āļāļēāļ™
    āļ‡āļēāļ™āļ§āļīāļˆāļąāļĒāļ™āļĩāđ‰ āļˆāļąāļ”āļ—āļģāļ‚āļķāđ‰āļ™āđ€āļžāļ·āđˆāļ­āļžāļąāļ’āļ™āļēāļĢāļ°āļšāļšāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļšāļģāļĢāļļāļ‡āļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāļ­āļ­āļ™āđ„āļĨāļ™āđŒāđƒāļŦāđ‰āļāļąāļšāļ‡āļēāļ™āļāļēāļĒāļ āļēāļžāđāļĨāļ°āļšāļĢāļīāļāļēāļĢāļžāļ·āđ‰āļ™āļāļēāļ™ āļ„āļ“āļ°āļŠāļīāđˆāļ‡āđāļ§āļ”āļĨāđ‰āļ­āļĄāđāļĨāļ°āļ—āļĢāļąāļžāļĒāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒ āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĄāļŦāļīāļ”āļĨ āļ™āļ­āļāļˆāļēāļāļ™āļĩāđ‰āļĒāļąāļ‡āļ›āļĢāļ°āđ€āļĄāļīāļ™āļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāļ‚āļ­āļ‡āļĢāļ°āļšāļšāđ‚āļ”āļĒāļ§āļąāļ”āļˆāļēāļāļ„āļ§āļēāļĄāļžāļķāļ‡āļžāļ­āđƒāļˆāļ‚āļ­āļ‡āļœāļđāđ‰āđƒāļŦāđ‰āđāļĨāļ°āļœāļđāđ‰āđƒāļŠāđ‰āļšāļĢāļīāļāļēāļĢ āļœāļđāđ‰āļ§āļīāļˆāļąāļĒāđ„āļ”āđ‰āļ—āļģāļāļēāļĢāļĻāļķāļāļĐāļēāļ›āļąāļāļŦāļē āļ‚āđ‰āļ­āļˆāļģāļāļąāļ” āđāļĨāļ°āļ‚āđ‰āļ­āđ€āļŠāļ™āļ­āđāļ™āļ°āļˆāļēāļāļœāļđāđ‰āđƒāļŠāđ‰āļšāļĢāļīāļāļēāļĢāļĢāļ°āļšāļšāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļšāļēāļĢāļļāļ‡āļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāđ€āļ”āļīāļĄ āļ‚āđ‰āļ­āļĄāļđāļĨāļ—āļĩāđˆāđ„āļ”āđ‰āļ–āļđāļāļ™āļģāļĄāļēāđƒāļŠāđ‰āđƒāļ™āļāļēāļĢāļžāļąāļ’āļ™āļēāļĢāļ°āļšāļšāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļšāļēāļĢāļļāļ‡āļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāļ­āļ­āļ™āđ„āļĨāļ™āđŒ āļĢāļ°āļšāļšāļ™āļĩāđ‰āđ„āļ”āđ‰āļ—āļģāļāļēāļĢāļžāļąāļ’āļ™āļēāļšāļ™āļĢāļ°āļšāļšāļ›āļāļīāļšāļąāļ•āļīāļāļēāļĢ Windows Server 2010 āļ āļēāļĒāđƒāļ•āđ‰ Internet Information Service (IIS) āļ”āđ‰āļ§āļĒāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩ .Net Framework āļšāļ™āļāļēāļ™āļ‚āđ‰āļ­āļĄāļđāļĨ Microsoft SQL Server 2000 āđāļĨāļ°āļ›āļĢāļ°āđ€āļĄāļīāļ™āļ„āļ§āļēāļĄāļžāļķāļ‡āļžāļ­āđƒāļˆāļŦāļĨāļąāļ‡āļ—āļ”āļĨāļ­āļ‡āđƒāļŠāđ‰āļĢāļ°āļšāļšāļˆāļēāļāļāļĨāļļāđˆāļĄāļ•āļąāļ§āļ­āļĒāđˆāļēāļ‡āļˆāļģāļ™āļ§āļ™ 24 āļ„āļ™ āļ‹āļķāđˆāļ‡āđ€āļ›āđ‡āļ™āļœāļđāđ‰āđƒāļŦāđ‰āđāļĨāļ°āļœāļđāđ‰āđƒāļŠāđ‰āļšāļĢāļīāļāļēāļĢāļĢāļ°āļšāļšāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļšāļēāļĢāļļāļ‡āļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāļ­āļ­āļ™āđ„āļĨāļ™āđŒ āļ—āļĩāđˆāđ€āļ„āļĒāđƒāļŦāđ‰āļšāļĢāļīāļāļēāļĢāđāļĨāļ°āļ—āļ”āļĨāļ­āļ‡āđƒāļŠāđ‰āļĢāļ°āļšāļšāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļšāļģāļĢāļļāļ‡āļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāļ­āļ­āļ™āđ„āļĨāļ™āđŒ āļœāļĨāļāļēāļĢāļĻāļķāļāļĐāļēāļžāļšāļ§āđˆāļē āļĢāļ°āļšāļšāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļšāļģāļĢāļļāļ‡āļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāļ­āļ­āļ™āđ„āļĨāļ™āđŒāļžāļąāļ’āļ™āļēāļ‚āļķāđ‰āļ™ āļĄāļĩāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāđāļĨāļ°āļŠāļēāļĄāļēāļĢāļ–āļ™āļģāđ„āļ›āđƒāļŠāđ‰āđ„āļ”āđ‰āļ”āļĩāđƒāļ™āļāļĢāļ°āļšāļ§āļ™āļāļēāļĢāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļšāļģāļĢāļļāļ‡āļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāļ­āļ­āļ™āđ„āļĨāļ™āđŒāļ‚āļ­āļ‡āļ„āļ“āļ°āļŊ āļœāļđāđ‰āđƒāļŦāđ‰āđāļĨāļ°āļœāļđāđ‰āđƒāļŠāđ‰āļšāļĢāļīāļāļēāļĢāļĄāļĩāļ„āļ§āļēāļĄāļžāļķāļ‡āļžāļ­āđƒāļˆāļ•āđˆāļ­āļĢāļ°āļšāļšāļ āļēāļžāļĢāļ§āļĄāļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļ”āļĩ (Mean Âą S.D. = 4.15Âą0.65) āđ‚āļ”āļĒāļžāļķāļ‡āļžāļ­āđƒāļˆāļ•āđˆāļ­āļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāđāļĨāļ°āļ›āļĢāļ°āđ‚āļĒāļŠāļ™āđŒāļ‚āļ­āļ‡āļĢāļ°āļšāļšāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļšāļģāļĢāļļāļ‡āļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāļ­āļ­āļ™āđ„āļĨāļ™āđŒ āļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļĄāļēāļāļ—āļĩāđˆāļŠāļļāļ” (Mean Âą S.D. = 4.21Âą0.69) āļ”āđ‰āļēāļ™āļāļēāļĢāļŠāļ™āļąāļšāļŠāļ™āļļāļ™āļāļēāļĢāđƒāļŦāđ‰āļšāļĢāļīāļāļēāļĢāļāļēāļĢāđƒāļŠāđ‰āļ‡āļēāļ™ āđāļĨāļ°āļ”āđ‰āļēāļ™āļāļēāļĢāļ­āļ­āļāđāļšāļšāđ‚āļ›āļĢāđāļāļĢāļĄ āļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļĄāļēāļ (Mean Âą S.D. = 4.15Âą0.59 āđāļĨāļ° 4.01Âą0.60 āļ•āļēāļĄāļĨāļēāļ”āļąāļš) āļ”āļąāļ‡āļ™āļąāđ‰āļ™ āļĢāļ°āļšāļšāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļšāļģāļĢāļļāļ‡āļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāļ­āļ­āļ™āđ„āļĨāļ™āđŒāļˆāļķāļ‡āļŠāļēāļĄāļēāļĢāļ–āļŠāļ™āļąāļšāļŠāļ™āļļāļ™āļāļĢāļ°āļšāļ§āļ™āļāļēāļĢāđāļˆāđ‰āļ‡āļ‹āđˆāļ­āļĄāļ„āļĢāļļāļ āļąāļ“āļ‘āđŒāļ‚āļ­āļ‡āļ„āļ“āļ°āļŊ āđƒāļŦāđ‰āļĄāļĩāļ„āļ§āļēāļĄāļŠāļ°āļ”āļ§āļ āļĢāļ§āļ”āđ€āļĢāđ‡āļ§ āđāļĨāļ°āļ–āļđāļāļ•āđ‰āļ­āļ‡āļĄāļēāļāļĒāļīāđˆāļ‡āļ‚āļķāđ‰āļ™
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    Maceral Association in Coal-bearing Formation of Mae Than Coal Mine in Lampang, Thailand - Implication for Depositional Environment
    (2022) Thunyapat Sattraburut; Benjavun Ratanasthien; Mahidol University. Faculty of Environment and Resource Studies; Chiang Mai University. Faculty of Science. Department of Geological Sciences
    The Mae Than Basin in Lampang Province contains low-ranked coal reserves of northern Thailand. Coal seams and ball clays were mined in the southern part of the basin. This study focuses on the coal petrography of coal samples collected from the upper coal seam in the Mae Than Coal Mine. Both the organic and inorganic constituents provide information on the nature and characteristics of the coal, reflecting the physical and chemical behaviors of coal. Petrological analysis reveals that the Mae Than coals contain more huminite than liptinite macerals, while inertinite is negligible. Huminite occurs mainly in the form of texto-ulminite, textinite, densinite, and gelinite. Liptinite consists of sporinite, cutinite, resinite, suberinite, liptodetrinite, and terpenite. The morphology of cutinite, sporinite, and the presence of terpenite indicate that the peat-forming vegetation may consist of conifers. In addition to the macerals, the coal samples contain a small to moderate amount of mineral matter. Silica and clay minerals are the main minerals found in the cavities and between the cracks of the coals. The assemblage of macerals and mineral matter indicates that the Mae Than coals were formed mainly from common peat-forming vegetation, possibly conifers, in a freshwater forest swamp or mire in a warm temperate climate. In addition, the high degree of preservation of the macerals indicates a high water table and suggests rheotrophic, anoxic, limnotelmatic to telmatic conditions during deposition.
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    Effect of Fungus-Growing Termite on Soil CO2 Emission at Termitaria Scale in Dry Evergreen Forest, Thailand
    (2021) Warin Boonriam; Pongthep Suwanwaree; Sasitorn Hasin; Phuvasa Chanonmuang; Taksin Archawakom; Akinori Yamada; Mahidol University. Faculty of Environment and Resource Studies; Suranaree University of Technology. Institute of Science. School of Biology; Valaya Alongkorn Rajabhat University under the Royal Patronage. College of Innovative Management. Innovation of Environmental Management; Thailand Institute of Scientific and Technological Research. Expert Centre of Innovation Clean Energy and Environment; Royal Forest Department. Sakaerat Environmental Research Station; Tokyo Institute of Technology. Department of Biological Sciences
    Termites are one of the major contributors to high spatial variability in soil respiration. Although epigeal termite mounds are considered as a point of high CO2 effluxes, the patterns of mound CO2 effluxes are different, especially the mound of fungus-growing termites in a tropical forest. This study quantified the effects of a fungus-growing termite (Macrotermes carbonarius) associated with soil CO2 emission by considering their nesting pattern in dry evergreen forest, Thailand. A total of six mounds of M. carbonarius were measured for CO2 efflux rates on their mounds and surrounding soils in dry and wet seasons. Also, measurement points were investigated for the active underground passages at the top 10% of among efflux rates. The mean rate of CO2 emission from termitaria of M. carbonarius was 7.66 Âĩmol CO2/m2/s, consisting of 2.94 and 9.11 Âĩmol CO2/m2/s from their above mound and underground passages (the rate reached up to 50.00 Âĩmol CO2/m2/s), respectively. While the CO2 emission rate from the surrounding soil alone was 6.86 Âĩmol CO2/m2/s. The results showed that the termitaria of M. carbonarius contributed 8.4% to soil respiration at the termitaria scale. The study suggests that fungus-growing termites cause a local and strong variation in soil respiration through underground passages radiating out from the mounds in dry evergreen forest.
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    Impact of Climate Change on Reservoir Reliability: A Case of Bhumibol Dam in Ping River Basin, Thailand
    (2561) Allan Sriratana Tabucanon; Areeya Rittima; Detchasit Raveephinit; Yutthana Phankamolsil; Wudhichart Sawangphol; Jidapa Kraisangka; Yutthana Talaluxmana; Varawoot Vudhivanich; Wenchao Xue; Mahidol University. Faculty of Environment and Resource Studies; Mahidol University. Faculty of Engineering; Mahidol University. Faculty of Information and Communication Technology; Kasetsart University. Faculty of Engineering; Kasetsart University. Faculty of Engineering at Kamphaeng; Asian Institute of Technology. Department of Energy Environment and Climate Change
    Bhumibol Dam is the largest dam in the central region of Thailand and it serves as an important water resource. The dam’s operation relies on reservoir operating rules that were developed on the basis of the relationships among rainfall-inflow, water balance, and downstream water demand. However, due to climate change, changing rainfall variability is expected to render the reliability of the rule curves insecure. Therefore, this study investigated the impact of climate change on the reliability of the current reservoir operation rules of Bhumibol Dam. The future scenarios from 2000 to 2099 are based on EC-EARTH under RCP4.5 and RCP8.5 scenarios downscaled by RegCM4. MIKE11 HD was developed for the inflow simulation. The model generates the inflow well (R2=0.70). Generally, the trend of increasing inflow amounts is expected to continue in the dry seasons from 2000-2099, while large fluctuations of inflow are expected to be found in the wet seasons, reflecting high uncertainties. In the case of standard deviations, a larger deviation is predicted under the RCP8.5 scenario. For the reservoir’s operation in a climate change study, standard operating procedures were applied using historical release records to estimate daily reservoir release needed to serve downstream water demand in the future. It can be concluded that there is high risk of current reservoir operating rules towards the operation reliability under RCP4.5 (80% reliability), but the risk is lower under RCP8.5 (87% reliability) due to increased inflow amounts. The unmanageability occurs in the wet season, cautioning the need to redesign the rules.
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    Organic Carbon in Wetland Soil: Seasonal Flooded Forest, Northeastern Thailand
    (2021) Piyakarn Teartisup; Prapeut Kerdsueb; Suwalee Worakhunpiset; āļ›āļīāļĒāļ°āļāļēāļāļˆāļ™āđŒ āđ€āļ—āļĩāđ‰āļĒāļ˜āļīāļ—āļĢāļąāļžāļĒāđŒ; āļ›āļĢāļ°āļžāļĪāļ•āļī āđ€āļāļīāļ”āļŠāļ·āļš; āļŠāļļāļ§āļĨāļĩāļĒāđŒ āļ§āļĢāļ„āļļāļ“āļžāļīāđ€āļĻāļĐ; Mahidol University. Faculty of Environment and Resource Studies; Mahidol University. Faculty of Tropical Medicine
    Seasonal flooded forest is one of the most important wetlands in northeastern Thailand, not only for its abundant biodiversity, but also as a source of carbon sequestration. Organic carbon plays an specially important role in the soil carbon cycle. To reinforce comprehension on soil organic carbon, five profiles in a northeast plateau were observed and determined. The most common trees were Albizzia Odoratissima, Combretum quadrangulare Kurz, and Streblus asper Lour. The contents of Soil Organic Carbon (SOC) varied from 3.52 g/kg to 5.90 g/kg in top soil and varied from 4.01 g/kg to 4.60 g/kg in sub soil. There was a close relationship between SOC content and basic soil properties, especially the bulk density of both top soil layer and sub soil layer. The distribution of SOC content was harmonized with distribution of plants. In comparative analysis, the flooded forest that composted with a high percentage of vegetation coverage (Khud Tew, Khud Chi Tao) had a significantly higher SOC content. The SOC storage varied from 2.65 kg/m2 to 4.18 kg/m2. Khud Chi Tao contained the maximum amount of SOC storage, whereas Kwo Chi Yai had the minimum. Limitation of flooded forest survival concerned over landscape change, particularly plant disappearance and waterlogged shortage. Therefore, vegetation and hydrology management have to be implemented practically to retain the existing organic carbon in wetlands and allow the soil to sequester additional carbon.
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    Factors Related to Coastal Communities’ Water-Related Natural Disaster Awareness, Preparedness, Resilience and Recovery in Three Cyclone Nargis Affected Areas in the Ayeyarwaddy Delta Region, Myanmar
    (2020) Zay Yar Min; Kampanad Bhaktikul; Sayam Aroonsrimorakot; Saranya Sucharitakul; Allan Sriratana Tabucanon; Budi Eko Siswoyo; āļāļąāļĄāļ›āļ™āļēāļ— āļ āļąāļāļ”āļĩāļāļļāļĨ; āļŠāļĒāļēāļĄ āļ­āļĢāļļāļ“āļĻāļĢāļĩāļĄāļĢāļāļ•; āļĻāļĢāļąāļ“āļĒāļē āļŠāļļāļˆāļĢāļīāļ•āļāļļāļĨ; āļ­āļĢāļąāļ™āļĒāđŒ āļĻāļĢāļĩāļĢāļąāļ•āļ™āļē āļ—āļēāļšāļđāļāļēāļ™āļ­āļ™; Mahidol University. Faculty of Environment and Resource Studies; Mahidol University. Faculty of Social Sciences and Humanities
    Natural disasters have a negative impact on the socio-economy of a country. This cross-sectional analytical study determined the factors that influence coastal communities’ water-related disaster awareness, preparedness, resilience and recovery in Cyclone Nargis affected areas in Myanmar. A total of 390 respondents from the three townships most affected by Cyclone Nargis in the Ayeyarwaddy Delta Region were purposively selected. Data were analyzed using SPSS Version 22.0. Associations between variables were analyzed by using binary logistic regression with p<0.05. Multivariate analysis was performed for the final model and interpreted with adjusted odds ratio and 95% confidence interval. Among respondents, more than 75% were not only aware and prepared before the disaster but had recovered and demonstrated resilience following the disaster. The respondents who had problems recovering on the “financial” index were 0.5 times less likely to exhibit recovery (OR=0.558, 95% CI=0.346-0.899, p=0.016) in binary analysis. The respondents who had problems recovering on the “health” index were 0.3 times less likely to demonstrate recovery (OR=0.387, 95% CI=0.194-0.772, p=0.007) in multivariate analysis. It is recommended that awareness and disaster management education programs that shape behavioral change are initiated which target both rural and urban areas in Myanmar.
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    Effects of Climate Variability on the Annual and Intra-annual Ring Formation of Pinus merkusii growing in Central Thailand
    (2020) Nathsuda Pumijumnong; Kritsadapan Palakit; Mahidol University. Faculty of Environment and Resource Studies; Kasetsart University. Faculty of Forestry. Department of Forest Management
    The research clarifies which climatic factors induce annual and intra-annual ring formation in merkus pine (Pinus merkusii) growing in the low lying plains of central Thailand and reconstructs the past climate by using climate modelling derived from climate-growth response. Not only are climate variations longer than a century in central Thailand explained, but the study also explores for the first time the variability in climate using the formation of intra-annual rings in Thai merkus pines. The tree-ring analysis of wood core samples indicated that the pine stand was more than 150 years old with the oldest tree being 191 years old. The annual variation in tree growth significantly correlated with local climate variables, the number of rainy days in each year (r=0.520, p<0.01) and the extreme maximum temperature in April (r=-0.377, p<0.01). The regional climate of the Equatorial Southern Oscillation in March (EQ_SOIMarch) also highly correlated with the pine growth (r=0.360, p<0.01). The climate reconstruction indicated a declining trend in the number of rainy days during the 20th century and a decline in the number of rainy days was observed during the first and second decades of the 21st century, respectively, while the past climate reconstruction of maximum temperature in April and EQ SOIMarch indicated a decline during the previous century and an increase in this century. A multiple regression analysis indicated that the extreme maximum temperature, which declined at the beginning of the wet season and increased around the transitional period of the late rainy and the cold seasons, influenced the formation of intra-annual rings (r2=40.5%, p<0.05). It can be summarized that the number of rainy days increasing in each year associated with the declining temperature at the beginning of the wet season indicated a rapid growth in P. merkusii, while the anomalous temperature declining at the beginning and increasing at the end of the wet season was the main factor inducing the intra-annual ring formation. Therefore the activity of forest and planation management, especially in the watering at the beginning of the wet season when anomalous increased temperature occurred, shall be specified in the forest management plan in order to increase annual pine growth and wood formation.
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    āļŠāļ āļēāļžāđāļ§āļ”āļĨāđ‰āļ­āļĄāđāļĨāļ°āļŦāļĄāļđāđˆāļšāđ‰āļēāļ™āđ€āļĢāļ·āļ­āļ™āđ„āļ—āļĒāđ€āļ­āļāļĨāļąāļāļĐāļ“āđŒāđ€āļ‰āļžāļēāļ°āļ–āļīāđˆāļ™ āļ­āļģāđ€āļ āļ­āļĄāđ‚āļ™āļĢāļĄāļĒāđŒ āļˆāļąāļ‡āļŦāļ§āļąāļ”āļŠāļąāļĒāļ™āļēāļ—
    (2546) āļŠāļļāļŠāļēāļ•āļī āļ™āļ§āļāļ§āļ‡āļĐāđŒ; āļžāļīāļˆāļąāļāļĢ āļŦāļīāļāļŠāļĩāļĢāļ°āļ™āļąāļ™āļ—āđŒ; Suchart Nawagawong; Phijak Hincheeranan; āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĄāļŦāļīāļ”āļĨ. āļ„āļ“āļ°āļŠāļīāđˆāļ‡āđāļ§āļ”āļĨāđ‰āļ­āļĄāđāļĨāļ°āļ—āļĢāļąāļžāļĒāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒ