-9 §«“¡ —¡æ—π∏Ï √ÿËßπ¿“ #2624C3 · 2017-11-09 · four sites including MJ1,...
Transcript of -9 §«“¡ —¡æ—π∏Ï √ÿËßπ¿“ #2624C3 · 2017-11-09 · four sites including MJ1,...
∫∑§«“¡«‘®—¬
§«“¡ —¡æ—π∏å√–À«à“ߧ«“¡À≈“°À≈“¬·≈–°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ” √à«¡°—∫§ÿ≥¿“æπÈ”„π≈”∏“√μâππÈ”·¡à·®à¡
Õ”‡¿Õ°—≈¬“≥‘«—≤π“ ®—ßÀ«—¥‡™’¬ß„À¡à
√ÿàßπ¿“ ∑“°—π* ·≈– ∑—μæ√ §ÿ≥ª√–¥‘…∞å
∫∑§—¥¬àÕ
°“√»÷°…“§√—Èßπ’ȉ¥â¡’«—μ∂ÿª√– ߧå‡æ◊ËÕ»÷°…“§«“¡ —¡æ—π∏姫“¡À≈“°À≈“¬·≈–°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ” §«∫§Ÿà°—∫§ÿ≥¿“æπÈ”„π≈”∏“√μâππÈ”·¡à·®à¡ Õ”‡¿Õ°—≈¬“≥‘«—≤π“ ®—ßÀ«—¥‡™’¬ß„À¡à ‰¥â∑”°“√°”Àπ¥®ÿ¥‡°Á∫μ—«Õ¬à“ß 4 ®ÿ¥ ‰¥â·°à MJ1 MJ2 MJ3 ·≈– MJ4 ‡°Á∫μ—«Õ¬à“ß 3 §√—Èß„π‡¥◊Õπ∏—𫓧¡ æ.».2557 情¿“§¡ æ.». 2558 ·≈– ‘ßÀ“§¡ æ.». 2558 ‚¥¬„™â«‘∏’‡°Á∫·¡≈ßπÈ”¥â«¬ D-frame net √«¡∂÷ß«—¥§à“§ÿ≥¿“æπÈ”∑“߇§¡’ ·≈–°“¬¿“æ∫“ߪ√–°“√ ®“°º≈°“√»÷°…“æ∫·¡≈ßπÈ”∑—ÈßÀ¡¥ 8,889 ®“° 9 Õ—π¥—∫84 «ß»å ‚¥¬æ∫·¡≈ßπÈ”„πÕ—π¥—∫ Diptera (54%) ¡“°∑’Ë ÿ¥ √Õß≈ß¡“§◊Õ Ephemeroptera (26%)Coleoptera (8%) Trichoptera (6%) Odonata (4%) Hemiptera (3%) ·≈–Õ◊ËπÊ (< 1%) μ“¡≈”¥—∫¥—™π’§«“¡À≈“°À≈“¬ Ÿß ÿ¥ 2.564 ∑’Ë MJ1 μË” ÿ¥∑’Ë MJ2 ¡’§à“ 0.921 §à“¥—™π’§«“¡ ¡Ë”‡ ¡Õ„π°“√°√–®“¬μ—« Ÿß ÿ¥∑’Ë MJ1 ¡’§à“ 0.638 μË” ÿ¥∑’Ë MJ2 ¡’§à“ 0.521 ®“°°“√ª√–‡¡‘𧫓¡™ÿ°™ÿ¡ —¡æ—π∏åæ∫«à“«ß»å Chironomindae ‡ªìπ ‘Ëß¡’™’«‘μ™π‘¥‡¥àπ ·≈–°“√ª√–‡¡‘π§ÿ≥¿“æπÈ”∑“ß™’«¿“æ¥â«¬ BMWPThai score·≈– ASPT ·≈–°“√ª√–‡¡‘π§ÿ≥¿“æπÈ”®◊¥º‘«¥‘π æ∫«à“§ÿ≥¿“æπÈ”„π·μà≈–®ÿ¥‡°Á∫μ—«Õ¬à“ßÕ¬Ÿà„π‡°≥±å§ÿ≥¿“æπÈ”ª“π°≈“ß∂÷ߧàÕπ¢â“ߥ’
§” ”§—≠: ·¡≈ßπÈ” §«“¡À≈“°À≈“¬∑“ß™’«¿“æ Õ”‡¿Õ°—≈¬“≥‘«—≤π“ ≈”πÈ”·¡à·®à¡
¿“§«‘™“™’««‘∑¬“ §≥–«‘∑¬“»“ μ√å·≈–‡∑§‚π‚≈¬’ ¡À“«‘∑¬“≈—¬√“™¿—Ƈ™’¬ß„À¡à*ºŸâπ‘æπ∏åª√– “πß“π, e-mail [email protected]
SWU Sci. J. Vol. 33 No. 1 (2017)118
Biology Department, Faculty of Science and Technology, Chiang Mai Rajabhat University*Corresponding author, e-mail: [email protected]
The Relationship between Diversity and Distributionof Aquatic Insect with Water Quality of Mae Chaem
Headwater streams, Kanlayaniwattana District,Chiang Mai Province
Rungnapa Tagun*, and Tatporn Kunpradid
ABSTRACT
The aim of this study is to assess the relationship between diversity and distributionof aquatic insect with water quality in Mae Chaem headwater stream, Kanlayanitwatta district,Chiang Mai. Aquatic macroinvertebrates were sampled at Mae Chaem wadeable-headstream atfour sites including MJ1, MJ2, MJ3 and MJ4 from December 2014 to August 2015 usingD-frame net and obtained some physico-chemical parameter of water quality. A total of 8,889individuals belonging to 84 families and nine orders were examined. The most aquatic insectabundance were Diptera (54%), Ephemeroptera (26%), Coleoptera (8%), Trichoptera (6%),Odonata (4%), Hempitera (3%) and others (< 1%) respectively. The highest diversity index wasrecorded at MJ1, 2.564 and lowest diversity index was recorded at MJ2, 0.921. The highestevenness index was found at MJ1, 0.638 and lowest evenness index was found 0.521. In termsof the relative abundance, the most abundant taxa recorded was Chironomidae. The use ofbiological indices as BMWPThai score and ASPT and physical and chemical parameters ofstandard fresh-water surface to evaluate water quality showed that the water quality was moderateto good quality in each sampling sites.
Keywords: Aquatic insect, Biodiversity, Kanlayaniwattana district, Mae Chaem headwater stream
«“√ “√«‘∑¬“»“ μ√å ¡»« ªï∑’Ë 33 ©∫—∫∑’Ë 1 (2560) 119
∫∑π”μâππÈ”≈”∏“√¡’§«“¡ ”§—≠μàÕ√–∫∫𑇫»·≈– ‘Ëß·«¥≈âÕ¡‡ªìπÕ¬à“ß¡“° ‚¥¬‡ªìπ·À≈àß°”‡π‘¥
¢ÕßπÈ”®◊¥∑’Ë¡’§«“¡ ”§—≠„™â„π°“√Õÿª‚¿§ ∫√‘‚¿§ ·≈–‡ªìπ·À≈àß∑’ËÕ¬ŸàÕ“»—¬¢Õß ‘Ëß¡’™’«‘μÀ≈“°À≈“¬π“π“™π‘¥·≈–Õ’°∑—È߬—ß “¡“√∂‡ªìπ¥—™π’∫àß™’ȧ«“¡Õÿ¥¡ ¡∫Ÿ√≥å¢Õßæ◊Èπ∑’ˉ¥â ¥—ßπ—Èπ·À≈àßμâππÈ”®÷ß¡’§«“¡À≈“°À≈“¬∑“ß™’«¿“æ Ÿß‚¥¬æ∫«à“„π‚≈°π’È¡’‡ªìπ·À≈àßμâππÈ”≈”∏“√·§à 1% ·μà¡’ ‘Ëß¡’™’«‘μ∑’ËÕ“»—¬„π·À≈àßπ’È∂÷ß 10% [1]·≈–„πªí®®ÿ∫—ππ’È¡’°“√√“¬ß“π«à“ ‘Ëß¡’™’«‘μ®”π«π∂÷ß 10,000-20,000 ™π‘¥ ∑’ËÕ“»—¬„π·À≈àßμâππÈ”°”≈—ß∂Ÿ°§ÿ°§“¡·≈–„°≈â Ÿ≠æ—π∏ÿå [1, 2] ‚¥¬ªí≠À“‡√◊ËÕߧ«“¡À≈“°À≈“¬∑“ß™’«¿“æ∂Ÿ°§ÿ°§“¡‡ªìπ‡√◊ËÕß∑’Ë ”§—≠Õ—π‡ªìπº≈ ◊∫‡π◊ËÕß¡“®“°º≈°√–∑∫®“°¿—¬∏√√¡™“μ‘·≈–°‘®°√√¡¢Õß¡πÿ…¬å Õ—π àߺ≈‚¥¬μ√ß·≈–∑“ßÕâÕ¡μàÕ ‘Ëß¡’™’«‘μ∑’ËÕ“»—¬„π·À≈àßπÈ” ‚¥¬·¡≈ßπÈ”‡ªìπ ‘Ëß¡’™’«‘μ∑’Ë¡’§«“¡ ”§—≠μàÕÀà«ß‚´àÕ“À“√ ‚¥¬ “¡“√∂∫àß∫Õ°∂÷ߧ«“¡Õÿ¥¡ ¡∫Ÿ√≥å¢Õß·À≈àßπÈ” ·≈–‡ªìπ°≈ÿà¡ ‘Ëß¡’™’«‘μ∑’Ë “¡“√∂„™â‡ªìπ¥—™π’∫àß™’ȧÿ≥¿“æπÈ”‰¥â‡π◊ËÕß®“°¡’§«“¡‰«μàÕ°“√‡ª≈’ˬπ·ª≈ß ¿“æ·«¥≈âÕ¡ ®÷ßπ‘¬¡„™â ‘Ëß¡’™’«‘μ°≈ÿà¡π’Èπ”¡“æ—≤𓇪ìπ¥—™π’∑“ß™’«¿“æ„π°“√∫àß™’ȧÿ≥¿“æπÈ” [3-5] Õ’°∑—È߬—߇ªìπ ‘Ëß¡’™’«‘μ°≈ÿà¡·√°∑’Ë¡’§«“¡‡ ’ˬߺ≈°√–∑∫®“° ‘Ëߪπ‡ªóôÕπ„π·À≈àßπÈ”‚¥¬°“√»÷°…“‡°’ˬ«°—∫§«“¡À≈“°À≈“¬¢Õß ‘Ëß¡’™’«‘μ„π·À≈àßμâππÈ”¢Õߪ√–‡∑»‰∑¬π—Èπ¬—ß¡’°“√»÷°…“∑’ËπâÕ¬¡“°À√◊Õ·¡â·μàμà“ߪ√–‡∑»‡Õß [6-9] Õ”‡¿Õ°—≈¬“≥‘«—≤𓇪ìπÕ”‡¿Õμ—Èß„À¡à∑’ˬ—߉¡à¡’°“√√∫°«π®“°°‘®°√√¡¢Õß¡πÿ…¬å¡“°π—° ·≈–¬—ß§ß ¿“槫“¡‡ªìπ∏√√¡™“μ‘ ‚¥¬æ◊Èπ∑’Ë à«π„À≠à‡ªìπªÉ“∑’ËÕÿ¥¡ ¡∫Ÿ√≥åπ’È∑”„Àâæ◊Èπ∑’ËÕ”‡¿Õ°—≈¬“≥‘«—≤𓇪ìπ·À≈àßμâπ°”‡π‘¥¢Õß·¡àπÈ”À≈“¬ “¬√«¡∑—È߬—߇ªìπ·À≈àßæ◊Èπ∑’ËμâππÈ”∑’Ë ”§—≠¢Õß¿“§‡Àπ◊Õ ‡™àπ ·¡àπÈ”·¡à·®à¡´÷Ë߇ªìπ·¡àπÈ” “¬ ”§—≠¢Õß·¡àπÈ”ªîß∑’ˇªìπ·¡àπÈ” “¬À≈—°¢Õß¿“§‡Àπ◊Õ
‚¥¬°“√»÷°…“§√—Èßπ’ȉ¥â¡’«—μ∂ÿª√– ߧå‡æ◊ËÕ 1) »÷°…“§«“¡À≈“°À≈“¬·≈–°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ”„πμâππÈ”·¡à·®à¡ Õ”‡¿Õ°—≈¬“≥‘«—≤π“ ®—ßÀ«—¥‡™’¬ß„À¡à 2) ‡æ◊ËÕ»÷°…“§«“¡ —¡æ—π∏å¢Õß°≈ÿà¡·¡≈ßπÈ” °—∫§ÿ≥¿“æπÈ”∑“ߥâ“𰓬 ·≈–‡§¡’
Õÿª°√≥å·≈–«‘∏’∑¥≈Õß√–¬–‡«≈“„π°“√»÷°…“
‡°Á∫μ—«Õ¬à“ß∑—ÈßÀ¡¥ 3 §√—Èß §√Õ∫§≈ÿ¡ƒ¥Ÿ°“≈ ‚¥¬„™â‡°≥±å≈—°…≥–Õ“°“»μ“¡ƒ¥Ÿ°“≈¢Õß¿“§μà“ßÊ „πª√–‡∑»‰∑¬ [10] ‰¥â·°à ‡¥◊Õπ∏—𫓧¡ æ.». 2557 (ƒ¥ŸÀπ“«) ‡¥◊Õπ情¿“§¡ æ.». 2558(ƒ¥Ÿ√âÕπ) ·≈–‡¥◊Õπ ‘ßÀ“§¡ æ.». 2558 (ƒ¥ŸΩπ)
æ◊Èπ∑’Ë»÷°…“·≈–®ÿ¥‡°Á∫μ—«Õ¬à“ßæ◊Èπ∑’Ë»÷°…“„π·À≈àßμâππȔՔ‡¿Õ°—≈¬“≥‘«—≤π“ ‚¥¬‰¥â·∫àß®ÿ¥‡°Á∫μ—«Õ¬à“ß 4 ®ÿ¥ ¥—ß· ¥ß„π¿“æ∑’Ë
1 ‰¥â·°à MJ1 À⫬§√° ∫â“πÀ⫬§√° (19°06.45 N, 98°17.10 E) MJ2 À⫬∫â“πÀπÕß·¥ß ∫â“πÀπÕß-·¥ß (19°06.35 N, 98°17.00 E) MJ3 (À⫬∫â“π®—π∑√å ∫â“π®—π∑√å 19°05.10 N, 98°16.50 E) ·≈– MJ4À⫬·®à¡À≈«ß ∫â“π·®à¡À≈«ß (19°01.12 N, 98°16.15 E)
SWU Sci. J. Vol. 33 No. 1 (2017)120
¿“æ∑’Ë 1 ®ÿ¥‡°Á∫μ—«Õ¬à“ß„πÕ”‡¿Õ°—≈¬“≥‘«—≤π“ [11]
‚¥¬®ÿ¥»÷°…“·μà≈–®ÿ¥¡’≈—°…≥–∑“ߥâ“𰓬¿“ææÕ —߇¢ª¥—ßπ’È®ÿ¥»÷°…“ MJ1 À⫬§√° ∫â“πÀ⫬§√° μ—ÈßÕ¬Ÿà„π‡¢μæ◊Èπ∑’˪ɓ §«“¡°«â“ß≈”πÈ”ª√–¡“≥ 1 ‡¡μ√
¡’æ◊™√‘¡Ωíòߪ°§≈ÿ¡·≈–¡’√“°‰¡âμâπ‰¡â√‘¡Ωíò߇ªìπ®”π«π¡“° ≈—°…≥–æ◊Èπ∑âÕßπÈ”‡ªìπ°âÕπÀ‘π¢π“¥„À≠à °√«¥·≈–∑√“¬
®ÿ¥»÷°…“ MJ2 À⫬∫â“πÀπÕß·¥ß ∫â“πÀπÕß·¥ß μ—ÈßÕ¬Ÿà„π‡¢μæ◊Èπ∑’˪ɓ·≈–‡°…μ√°√√¡ π“¢â“«·≈–‰√à∂—Ë«‡À≈◊Õß §«“¡°«â“ߢÕß≈”πÈ”ª√–¡“≥ 1-2 ‡¡μ√ ¡’æ◊™¬◊πμâπ·≈–√“°‰¡â√‘¡Ωíòß®”π«π¡“° ≈—°…≥–æ◊Èπ∑âÕßπÈ”‡ªìπ‚§≈π ∑√“¬ ·≈–‡»…´“°¢Õß„∫‰¡â∑’Ë∑—∫∂¡
®ÿ¥»÷°…“ MJ3 À⫬∫â“π®—π∑√å ∫â“π®—π∑√å ‡ªìπ·À≈àßπÈ”∑’ËÕ¬Ÿà„°≈â∫√‘‡«≥™ÿ¡™π ·≈–æ◊Èπ∑’ˇ°…μ√°√√¡¡’æ◊™√‘¡Ωíòß·≈–‰¡âæÿà¡ √«¡∂÷ß√“°‰¡â∑—Èß ÕßΩíòß ¡’μâπ‰¡â„À≠ર§≈ÿ¡æ◊Èπ∑’ˇªìπ∫“ß à«π ‡ªìπ∑’ˇªî¥‚≈àß à«π√‘¡ΩíòßπÈ”®–‡ªìπ«—™æ◊™®”æ«°À≠â“¢÷ÈπÕ¬ŸàÕ¬à“ßÀπ“·πàπ ≈—°…≥–æ◊Èπ∑âÕßπÈ”®–‡ªìπ‚§≈π °√«¥ ·≈–∑√“¬‡ªìπ à«π„À≠à §«“¡°«â“ߢÕß·À≈àßπÈ”ª√–¡“≥ 2 ‡¡μ√ ≈—°…≥–æ◊Èπ∑âÕßπÈ”‡ªìπ∑√“¬
«“√ “√«‘∑¬“»“ μ√å ¡»« ªï∑’Ë 33 ©∫—∫∑’Ë 1 (2560) 121
®ÿ¥»÷°…“ MJ4 À⫬·®à¡À≈«ß ∫â“π·®à¡À≈«ß ‡ªìπ®ÿ¥μâππÈ”∑’ËÕ¬Ÿà„°≈â·À≈àß™ÿ¡™π ¡’æ◊™√‘¡Ωíòß·≈–¡’μâπ‰¡â„À≠à∫√‘‡«≥ Õß√‘¡Ωíòß≈”πÈ” ≈—°…≥–æ◊Èπ∑âÕßπÈ”‡ªìπ∑√“¬·≈–‚§≈π à«π„À≠à §«“¡°«â“ߢÕß≈”πÈ”ª√–¡“≥ 2-3 ‡¡μ√
°“√»÷°…“§ÿ≥ ¡∫—μ‘∑“ß°“¬¿“æ ‡§¡’ ·≈–·¡≈ßπÈ”§ÿ≥ ¡∫—μ‘∑“ß°“¬¿“æ·≈–‡§¡’ „π·μà≈–®ÿ¥»÷°…“∑”°“√«—¥æ“√“¡‘‡μÕ√å 3 §√—Èß (3 ®ÿ¥) „π™à«ß
‡«≈“ 8.00-17.00 π“Ãî°“ ‚¥¬‡°Á∫®“°∫√‘‡«≥∑⓬πÈ”¢÷Èπ‰ª¬—ßμâππÈ” √«¡∂÷ßÕÿ≥À¿Ÿ¡‘πÈ”·≈–Õ“°“» ª√‘¡“≥ÕÕ°´‘‡®π∑’Ë≈–≈“¬„ππÈ” (Dissolved Oxygen; DO) ª√‘¡“≥ÕÕ°´‘‡®π∑’Ë®ÿ≈‘π∑√’¬å„™â„π°“√¬àÕ¬ ≈“¬(Biochemical Oxygen Demand; BOD) §«“¡‡ªìπ°√¥‡∫ ¢ÕßπÈ” (pH) §à“°“√π”‰øøÑ“ (Conductivity)ª√‘¡“≥¢Õß·¢Áß∑’Ë≈–≈“¬„ππÈ” (Total dissolved solid) ·≈–ª√‘¡“≥ “√Õ“À“√‰¥â·°à ·Õ¡‚¡‡π’¬¡-‰π‚μ√‡®π(Ammonium; NH4
+-N) ‚¥¬„™â«‘∏’ Salicylate „π°“√«‘‡§√“–Àå ‰π‡μ√μ-‰π‚μ√‡®π (Nitrate-Nitrogen;NO-
3-N) „™â«‘∏’ Cadmium reduction ·≈–ÕÕ√å‚∏øÕ ‡øμ (Orthophosphate) „™â«‘∏’ Ascorbic acid „π°“√«‘‡§√“–Àå ´÷Ëß«‘∏’°“√»÷°…“§ÿ≥¿“æπÈ”∑“ß°“¬¿“æ·≈–‡§¡’∑—ÈßÀ¡¥π’È„™â«‘∏’°“√μ“¡¡“μ√∞“π°“√«‘‡§√“–Àå§ÿ≥¿“æπÈ”·≈–πÈ”‡ ’¬ [12]
°“√‡°Á∫μ—«Õ¬à“ß·¡≈ßπÈ”„™â D-frame net §«“¡∂’Ëμ“¢à“¬ 500 ‰¡‚§√‡¡μ√ ‚¥¬‡°Á∫√‘¡ΩíòßπÈ”¥â“π ⓬·≈–¢«“ ·∫à߇ªìπ 3 ®ÿ¥¬àÕ¬„π·μà≈–¥â“π ®ÿ¥¬àÕ¬≈–ª√–¡“≥ 3 π“∑’ ‡æ◊ËÕ„Àâ§√Õ∫§≈ÿ¡∑ÿ°∂‘Ëπ∑’ËÕ¬Ÿà [13]®“°π—Èπ‡°Á∫≈ß Ÿà∂ÿßæ≈“ μ‘° ·≈–‡μ‘¡¥â«¬·Õ≈°ÕŒÕ≈å 70% π”μ—«Õ¬à“ß·¡≈ßπÈ”®”·π°„μâ°≈âÕß®ÿ≈∑√√»πå ‡μÕ√‘‚Õ Olympus SZ51 ‡æ◊ËÕ®”·π° —≥∞“π«‘∑¬“„Àâ∂÷ß√–¥—∫«ß»å (Family) ‚¥¬„™âÀπ—ß ◊ÕÕπÿ°√¡«‘∏“π[14, 15] ®“°π—Èππ—∫®”π«π ·≈–∫—π∑÷°º≈
°“√«‘‡§√“–Àå¢âÕ¡Ÿ≈‡ª√’¬∫‡∑’¬∫§à“ªí®®—¬∑“ß°“¬¿“æ·≈–‡§¡’¢ÕßπÈ”„π·μà≈–®ÿ¥‡°Á∫μ—«Õ¬à“ß„π·μà≈–‡¥◊Õπ¥â«¬°“√
«‘‡§√“–À姫“¡·ª√ª√«π®”·π°∑“߇¥’¬« (One-Way ANOVA) ¥â«¬«‘∏’ Tukey test [16] π”¢âÕ¡Ÿ≈·¡≈ßπÈ” ·≈–§ÿ≥¿“æπÈ”∑“ß°“¬¿“æ·≈–‡§¡’∑’ˉ¥âπ”¡“«‘‡§√“–Àå°“√®—¥°≈ÿࡧ«“¡‡À¡◊Õ𧫓¡·μ°μà“ß„π·μà≈–®ÿ¥»÷°…“¥â«¬°“√®—¥°≈ÿà¡·∫∫ Ward Linkage ¥â«¬«‘∏’ cluster analysis [17] √«¡∂÷ß»÷°…“¥—™π’§«“¡À≈“°À≈“¬∑“ß™’«¿“æ‚¥¬„™â«‘∏’ Shannon-Wiener Index ¥—™π’§«“¡ ¡Ë”‡ ¡Õ„π°“√°√–®“¬μ—«¥â«¬«‘∏’ Pielouûs Evenness Index ·≈–»÷°…“Õ‘∑∏‘æ≈¢Õßªí®®—¬∑“ߥâ“𰓬¿“æ ‡§¡’∑’Ë àߺ≈μàÕ°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ”¥â«¬«‘∏’ multivariate analysis ¥â«¬‡∑§π‘§ canonical corresponding analysis [18] °“√»÷°…“§«“¡™ÿ°™ÿ¡ —¡æ—∑∏å¢Õß·¡≈ßπÈ”‚¥¬°“√· ¥ß¿“æ¥â«¬ Heat map [19] ‚¥¬°“√«‘‡§√“–Àå∑—ÈßÀ¡¥„™â·æ§‡°® Vegan ‚ª√·°√¡ R studio (R core team version 3.3.1) [20] ¢âÕ¡Ÿ≈·¡≈ßπÈ”∑—ÈßÀ¡¥¡“‡ª√’¬∫‡∑’¬∫®”π«πμ—« ®”π«π«ß»å ·≈–Õ—π¥—∫∑’Ëæ∫„π·μà≈–®ÿ¥»÷°…“ ·≈–®ÿ¥‡°Á∫μ—«Õ¬à“ß ·≈â«π”‰ª‡∑’¬∫¡“μ√∞“π§ÿ≥¿“æπÈ”‚¥¬„™â BMWPThai score (Biological Monitoring Working Party) ·≈–𔉪À“§à“ASPT (Average Score Per Taxa) [3, 21] μ“¡≈”¥—∫
SWU Sci. J. Vol. 33 No. 1 (2017)122
º≈°“√∑¥≈Õߥâ“π™’«¿“æ°“√°√–®“¬μ—«·≈–§«“¡À≈“°À≈“¬¢Õß·¡≈ßπÈ”
°“√»÷°…“§√—Èßπ’Èæ∫·¡≈ßπÈ”∑—ÈßÀ¡¥ 8,889 μ—« „π 9 Õ—π¥—∫ 84 «ß»å ‚¥¬æ∫°≈ÿà¡ ‘Ëß¡’™’«‘μ„πÕ—π¥—∫ Diptera À√◊Õ°≈ÿà¡μ—«ÕàÕπ·¡≈ß Õߪﰡ“°∑’Ë ÿ¥§‘¥‡ªìπ 4,791 μ—« (54%) √Õß≈ß¡“§◊ÕÕ—π¥—∫Ephemeroptera À√◊Õ°≈ÿà¡μ—«ÕàÕπ·¡≈ß™’ª–¢“« 2,275 μ—« (25.7%) Õ—π¥—∫ Coleoptera À√◊Õ°≈ÿà¡μ—«ÕàÕπ¥â«ßªï°·¢Áß 689 μ—« (7.8%) Õ—π¥—∫ Trichoptera À√◊Õμ—«ÕàÕπ·¡≈ßÀπÕπª≈Õ°πÈ” 500 μ—« (5.6%)Õ—π¥—∫ Odonata À√◊Õ°≈ÿà¡·¡≈ßªÕ 342 μ—« (3.9%) Õ—π¥—∫ Hemiptera °≈ÿà¡¡«ππÈ” 253 μ—« (2.9%)Plecoptera °≈ÿà¡·¡≈߇°“–À‘π 17 μ—« (0.2%) °≈ÿà¡μ—«ÕàÕπº’‡ ◊ÈÕπÈ” 12 μ—« ·≈– Megaloptera °≈ÿà¡·¡≈ߙⓡ°√“¡‚μ 9 μ—« (< 0.1%) μ“¡≈”¥—∫ (¿“æ∑’Ë 2-1)
‡¡◊ËÕæ‘®“√≥“§«“¡À≈“°À≈“¬¢Õß®”π«π«ß»å„π·μà≈–Õ—π¥—∫¢Õß·¡≈ßπÈ”æ∫¡“°∑’Ë ÿ¥„π®ÿ¥‡°Á∫MJ4 æ∫ 58 «ß»å √Õß¡“§◊Õ MJ3 æ∫ 57 «ß»å MJ1 æ∫ 52 ·≈–®ÿ¥‡°Á∫ MJ2 æ∫πâÕ¬∑’Ë ÿ¥§◊Õ 37 «ß»åμ“¡≈”¥—∫ ®“°¿“æ∑’Ë 2-2 ®–‡ÀÁπ‰¥â«à“®ÿ¥‡°Á∫ MJ1 Õ—π¥—∫∑’Ë¡’®”π«π«ß»åÀ≈“°À≈“¬∑’Ë ÿ¥§◊Õ Trichopteraæ∫ 11 «ß»å ®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ2 §◊ÕÕ—π¥—∫¢Õß Diptera æ∫∑—ÈßÀ¡¥ 10 «ß»å MJ3 æ∫Õ—π¥—∫¢Õß OdonataÀ√◊Õ°≈ÿà¡·¡≈ߪÕ∑’Ë 15 «ß»å ·≈–®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ4 æ∫Õ—π¥—∫¢Õß Odonata ∑’Ë¡’§«“¡À≈“°À≈“¬¢Õß®”π«π«ß»å‡™àπ‡¥’¬«°—π§◊Õ 13 «ß»å ¥—ß· ¥ß„π¿“æ∑’Ë 2-2
¿“æ∑’Ë 2 2-1) —¥ à«π°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ”„πμâππÈ” Õ”‡¿Õ°—≈¬“≥‘«—≤π“ 2-2) ®”π«π«ß»å¢Õß·¡≈ßπÈ”„πμâππȔՔ‡¿Õ°—≈¬“≥‘«—≤π“μ“¡®ÿ¥‡°Á∫μ—«Õ¬à“ß„πμâππÈ”
(2-1) (2-2)
«“√ “√«‘∑¬“»“ μ√å ¡»« ªï∑’Ë 33 ©∫—∫∑’Ë 1 (2560) 123
§à“¥—™π’§«“¡À≈“°À≈“¬§à“¥—™π’§«“¡À≈“°À≈“¬¢Õß Shannon-Wiener · ¥ß„Àâ‡ÀÁπ∂÷ߧ«“¡ —¡æ—π∏å√–À«à“ß®”π«π
™π‘¥·≈–®”π«πμ—«¢Õß·¡≈ßπÈ”∑’Ëæ∫ [22, 23] ®“°º≈°“√«‘‡§√“–Àå∑’ˉ¥âæ∫«à“®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ1 ¡’§à“¥—™π’§«“¡À≈“°À≈“¬¡“°∑’Ë ÿ¥ 2.564 μË” ÿ¥∑’Ë®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ2 ¡’§à“ 0.921 ‡¡◊ËÕæ‘®“√≥“„π·μà≈–®ÿ¥‡°Á∫μ—«Õ¬à“ß„π·μà≈–‡¥◊Õπæ∫«à“ MJ2 „π‡¥◊Õπ情¿“§¡ §à“¥—™π’§«“¡À≈“°À≈“¬μË” ÿ¥§◊Õ 0.607 Ÿß ÿ¥∑’Ë®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ1 „π‡¥◊Õπ ‘ßÀ“§¡ ¡’§à“ 2.504 ¥—ß¿“æ∑’Ë 3-1 ·≈– 3-2
¿“æ∑’Ë 3 3-1) · ¥ß§à“¥—™π’§«“¡À≈“°À≈“¬„π®ÿ¥‡°Á∫μ—«Õ¬à“ß∑—Èß 4 ®ÿ¥‡°Á∫ ·≈– 3-2) ®ÿ¥‡°Á∫μ—«Õ¬à“ß„π·μà≈–‡¥◊Õπ
§«“¡ ¡Ë”‡ ¡Õ„π°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ” (Evenness)§«“¡ ¡Ë”‡ ¡Õ„π°“√°√–®“¬μ—«π—ÈπÀ¡“¬∂÷ß —¥ à«π¢Õß ‘Ëß¡’™’«‘μ™π‘¥μà“ßÊ ∑’Ë¡’Õ¬Ÿà ®“°°“√»÷°…“
æ∫«à“§à“§«“¡ ¡Ë”‡ ¡Õ„π°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ”æ∫«à“¡’§à“·μ°μà“ß°—π„π·μà≈–®ÿ¥‡°Á∫´÷Ëß§à“ Evennessπ’ÈÀ“°¡’§à“‡¢â“„°≈â 1 · ¥ß«à“¡’§«“¡ ¡Ë”‡ ¡Õ„π°“√°√–®“¬μ—« Ÿß ‚¥¬®ÿ¥‡°Á∫∑’Ë MJ1 ¡’§à“§«“¡ ¡Ë”‡ ¡Õ„π°“√°√–®“¬μ—«¡“°∑’Ë ÿ¥„π°“√»÷°…“§√—Èßπ’È¡’§à“‡∑à“°—∫ 0.638 √Õß¡“§◊Õ®ÿ¥‡°Á∫μ—«Õ¬à“ß∑’Ë MJ3 ¡’§à“ 0.612®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ4 ¡’§à“ 0.555 ·≈–§à“μË” ÿ¥æ∫∑’Ë®ÿ¥‡°Á∫μ—«Õ¬à“ß∑’Ë MJ2 ¡’§à“ 0.521 ¥—ß¿“æ∑’Ë 4
§«“¡™ÿ°™ÿ¡ —¡æ—∑∏å (Relative abundance)§«“¡™ÿ°™ÿ¡ —¡æ—∑∏å§◊ÕÕ—μ√“ à«π¢Õß·¡≈ßπÈ”·μà≈–«ß»åμàÕ®”π«πª√–™“°√∑—ÈßÀ¡¥„π®ÿ¥‡°Á∫
μ—«Õ¬à“ß„π·μà≈–‡¥◊Õπ„π°“√‡°Á∫μ—«Õ¬à“ß´÷Ë߇ªìπ°“√‡ª√’¬∫‡∑’¬∫§«“¡À≈“°À≈“¬¢Õß ‘Ëß¡’™’«‘μ°≈ÿà¡π—ÈπÊ ‰¥â‡ªìπÕ¬à“ߥ’ «à“¡’°“√‡ª≈’ˬπ·ª≈ß¡“°¢÷ÈπÀ√◊ÕπâÕ¬≈ßÕ¬à“߉√ ‚¥¬º≈°“√»÷°…“æ∫«à“·¡≈ßπÈ”∑’ˇªìπ™π‘¥‡¥àπæ∫∑ÿ°®ÿ¥»÷°…“ ·≈–¡’ª√‘¡“≥¡“°§◊Õ«ß»å Chironomidae æ∫«à“·¡≈ßπÈ”„π«ß»åπ’Èæ∫®”π«πμ—«¡“°∑’Ë®ÿ¥»÷°…“∑’ËMJ2 ‡™àπ‡¥’¬«°—π°—∫«ß»å Baetidae (¿“æ∑’Ë 5) ´÷Ëß·¡≈ßπÈ”°≈ÿà¡π’È∫àß∫Õ°∂÷ߧÿ≥¿“æπÈ”‰¡à¥’¡“°π—° [3]
(3-1) (3-2)
SWU Sci. J. Vol. 33 No. 1 (2017)124
°“√ª√–‡¡‘π§ÿ≥¿“æπÈ”∑“ß™’«¿“æ BMWP score (Biological Monitoring Working Party score)·≈– ASPT (Average Score Per Taxa)
μ“√“ß∑’Ë 1 §à“ BWMPTH score ·≈– ASPT „π·μà≈–®ÿ¥‡°Á∫μ—«Õ¬à“ßμâππÈ” 4 ®ÿ¥ Õ”‡¿Õ°—≈¬“≥‘«—≤π“®—ßÀ«—¥‡™’¬ß„À¡à √–À«à“߇¥◊Õπ∏—𫓧¡ æ.». 2557 ∂÷ß ‘ßÀ“§¡ æ.». 2558
Sites BMWPThai score ASPT §ÿ≥¿“æπÈ”*
MJ1 270 6.58 ª“π°≈“ß ∂÷ߧàÕπ¢â“ߥ’ (2)MJ2 152 5.84 ª“π°≈“ß (3)MJ3 270 6.27 ª“π°≈“ß∂÷ߧàÕπ¢â“ߥ’ (2-3)MJ4 237 6.41 ª“π°≈“ß ∂÷ߧàÕπ¢â“ߥ’(2-3)
®“°μ“√“ß∑’Ë 1 °“√ª√–‡¡‘π§ÿ≥¿“æπÈ”∑“ß™’«¿“æ¥â«¬ BMWPThai score ·≈– ASPT æ∫«à“§à“BMWPThai score Ÿß ÿ¥∑’Ë®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ1 ·≈– MJ3 ¡’§à“ 270 μË” ÿ¥∑’Ë®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ2 ¡’§à“270 ·≈–‡æ◊ËÕ«‘‡§√“–ÀåÀ“§à“ ASPT æ∫«à“¡’§à“ Ÿß ÿ¥∑’Ë®ÿ¥‡°Á∫μ—«Õ¬à“ß∑’Ë MJ1 ¡’§à“ 6.58 §ÿ≥¿“æπÈ”®—¥Õ¬Ÿà„π‡°≥±åª“π°≈“ß∂÷ߧàÕπ¢â“ߥ’ ·≈–μË”®ÿ¥∑’Ë®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ2 ¡’§à“ 5.84 §ÿ≥¿“æπÈ”®—¥Õ¬Ÿà„π‡°≥±åª“π°≈“ß
¿“æ∑’Ë 4 §à“ ¡Ë”‡ ¡Õ„π°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ”„π·μà≈–®ÿ¥‡°Á∫μ—«Õ¬à“ß
«“√ “√«‘∑¬“»“ μ√å ¡»« ªï∑’Ë 33 ©∫—∫∑’Ë 1 (2560) 125
¿“æ∑’Ë 5 · ¥ß§«“¡™ÿ°™ÿ¡ —¡æ—∑∏å¢Õß·¡≈ßπÈ”„π®ÿ¥»÷°…“·μà≈–‡¥◊Õπ‡ª√’¬∫‡∑’¬∫°—π Õ”‡¿Õ°—≈¬“≥‘«—≤π“®—ßÀ«—¥‡™’¬ß„À¡à √–À«à“߇¥◊Õπ∏—𫓧¡ æ.». 2557 ∂÷ß ‘ßÀ“§¡ æ.». 2558
À¡“¬‡Àμÿ MJ1.1; ®ÿ¥ 1 ‡¥◊Õπ∏—𫓧¡ æ.». 2557, MJ1.2; ®ÿ¥ 1 ‡¥◊Õπ情¿“§¡ æ.». 2558,MJ1.3; ®ÿ¥ 1 ‡¥◊Õπ ‘ßÀ“§¡ æ.». 2558
MJ2.1; ®ÿ¥ 2 ‡¥◊Õπ∏—𫓧¡ æ.». 2557, MJ2.2; ®ÿ¥ 2 ‡¥◊Õπ情¿“§¡ æ.». 2558,MJ2.3; ®ÿ¥ 2 ‡¥◊Õπ ‘ßÀ“§¡ æ.». 2558
MJ3.1; ®ÿ¥ 3 ‡¥◊Õπ∏—𫓧¡ æ.». 2557, MJ3.2; ®ÿ¥ 3 ‡¥◊Õπ情¿“§¡ æ.». 2558,MJ3.3; ®ÿ¥ 3 ‡¥◊Õπ ‘ßÀ“§¡ æ.». 2558
MJ4.1; ®ÿ¥ 4 ‡¥◊Õπ∏—𫓧¡ æ.». 2557, MJ4.2; ®ÿ¥ 4 ‡¥◊Õπ情¿“§¡ æ.». 2558,MJ4.3; ®ÿ¥ 4 ‡¥◊Õπ ‘ßÀ“§¡ æ.». 2558
SWU Sci. J. Vol. 33 No. 1 (2017)126
ªí®®—¬¥â“¬°“¬¿“æ·≈–‡§¡’§ÿ≥¿“æπÈ”∑“ß°“¬¿“æ·≈–‡§¡’„π∑—Èß ’Ë®ÿ¥‡°Á∫μ—«Õ¬à“ß„π·μà≈–‡¥◊Õππ—Èπæ∫«à“¡’§à“·μ°μà“ß°—π „π
·μà≈–®ÿ¥∑’ˇ°Á∫ ·≈–§√—Èß∑’ˇ°Á∫ à«π„À≠à¡’§«“¡ —¡æ—π∏å°—∫ ¿“æ·«¥≈âÕ¡∑’Ë·μ°μà“ß°—πμ“¡ƒ¥Ÿ°“≈¢Õßæ◊Èπ∑’Ë»÷°…“ ‚¥¬æ∫«à“ Õÿ≥À¿Ÿ¡‘Õ“°“» ·≈–Õÿ≥À¿Ÿ¡‘πÈ”¡’§à“ Ÿß ÿ¥∑’Ë MJ4 „π‡¥◊Õπ情¿“§¡ ´÷Ë߇ªìπƒ¥Ÿ√âÕπ ·≈–®ÿ¥‡°Á∫μ—«Õ¬à“ßπ’È¡’≈—°…≥–‡ªî¥‚≈àß°«â“ß ‰¡à¡’√ࡉ¡â„À≠ર§≈ÿ¡ pH ¡’§à“Õ¬Ÿà√–À«à“ß 5.6-8 §à“ DO ¡’§à“Õ¬Ÿà√–À«à“ß 4.6-7.7 mg.l-1 ‚¥¬§à“ DO μË” ÿ¥∑’ˇ°Á∫μ—«Õ¬à“ß MJ2.3 4.6 mg.l-1 §à“ BOD Õ¬Ÿà√–À«à“ß 0.2-1.7mg.l-1 §à“ Conductivity Õ¬Ÿà√–À«à“ß 53-196 μs.cm-1 §à“ Turbidity Õ¬Ÿà√–À«à“ß 7.3-64 mg.l-1 §à“NO3
--N Õ¬Ÿà√–À«à“ß ND-0.83 mg.l-1 §à“ Orthophosphate Õ¬Ÿà√–À«à“ß 0.09-0.38 mg.l-1 ·≈–§à“ NH4+-N
Õ¬Ÿà√–À«à“ß 0.16-0.63 mg.l-1 ¥—ß· ¥ß„πμ“√“ß∑’Ë 2®“°°“√»÷°…“§ÿ≥≈—°…≥–¢ÕßπÈ” æ∫«à“ „π∫“ß®ÿ¥»÷°…“¡’≈—°…≥–¢Õßªí®®—¬∑“ß°“¬¿“æ ‡§¡’
√«¡∂÷ߧÿ≥¿“æπÈ”·μ°μà“ß®“°®ÿ¥Õ◊ËπÊ ∑’Ë¡’§«“¡ —¡æ—π∏å°—∫≈—°…≥–¢Õß®ÿ¥‡°Á∫μ—«Õ¬à“ß·≈–ƒ¥Ÿ°“≈ ‚¥¬®–‡ÀÁπ‰¥â®“°°“√«‘‡§√“–À姫“¡ —¡æ—π∏å√–À«à“ß®ÿ¥»÷°…“·≈–§ÿ≥¿“æπÈ”∑“ß°“¬¿“æ·≈–‡§¡’ ¥â«¬«‘∏’ cluster analysisæ∫«à“®ÿ¥‡°Á∫μ—«Õ¬à“ß·≈–§ÿ≥¿“æπÈ”∑“ß°“¬¿“æ·≈–‡§¡’ “¡“√∂®—¥°≈ÿࡉ¥â 2 °≈ÿà¡„À≠à§◊Õ °≈ÿà¡∑’Ë 1 §◊ÕMJ2 ∑—Èß “¡‡¥◊Õπ ·≈– MJ4 „π‡¥◊Õπ ‘ßÀ“§¡ æ.». 2558 ‡¡◊ËÕæ‘®“√≥“¥Ÿ§à“§ÿ≥¿“æπÈ”°“¬¿“æ·≈–‡§¡’æ∫«à“¡’§à“∑’ËπâÕ¬°«à“®ÿ¥‡°Á∫μ—«Õ¬à“ßÕ◊ËπÊ ¥—ß· ¥ß„π¿“æ∑’Ë 6-1 Õ¬à“߉√°Áμ“¡ °“√°√–®“¬μ—«¢Õß·¡≈ßπÈ”æ∫«à“ƒ¥Ÿ°“≈¡’º≈μàÕ°“√®—¥°≈ÿà¡ ‚¥¬¡’°“√·∫àß°≈ÿࡇªìπ 2 °≈ÿà¡„À≠à‡™àπ‡¥’¬«°—π§◊Õ °≈ÿà¡∑’Ë 1 ®ÿ¥‡°Á∫μ—«Õ¬à“ß∑’ËMJ2 MJ3 ·≈– MJ4 „π‡¥◊Õπ情¿“§¡ ´÷Ëß¡’§«“¡·μ°μà“ߢÕß®”π«π·≈–™π‘¥°≈ÿà¡·¡≈ßπÈ”®“°®ÿ¥»÷°…“Õ◊ËπÊÕ¬à“ß™—¥‡®π (¿“æ∑’Ë 6-2)
¿“æ∑’Ë 6 6-1) °“√®—¥°≈ÿà¡√–À«à“ß®ÿ¥‡°Á∫μ—«Õ¬à“ßμ“¡§ÿ≥ ¡∫—μ‘∑“ß°“¬¿“æ·≈–‡§¡’¢ÕßπÈ” ·≈– 6-2)°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ”√–À«à“ß®ÿ¥‡°Á∫μ—«Õ¬à“ß
«“√ “√«‘∑¬“»“ μ√å ¡»« ªï∑’Ë 33 ©∫—∫∑’Ë 1 (2560) 127
μ“√“
ß∑’Ë 2
§à“º≈
§ÿ≥¿“
æπÈ”∑
“ß°“
¬¿“æ
·≈–‡
§¡’ (§
à“‡©≈
’ˬ ± à«
π‡∫’ˬ
߇∫π
¡“μ√
∞“π)
„π®ÿ¥
‡°Á∫μ
—«Õ¬à“
ßμâππ
È” 4 ®ÿ¥
Õ”‡¿
Õ°—≈¬
“≥‘«—≤
π“ ®—ßÀ
«—¥‡™
’¬ß„À
¡à √–
À«à“ß
‡¥◊Õπ
∏—π«“
§¡ æ
.». 2
557
∂÷ß
‘ßÀ“§
¡ æ.
». 2
558
Site
sAir
Wat
erpH
DO
BOD
Con
duct
ivity
Turb
idity
NO
3--N
Ort
hoph
osph
ate
NH
4+-N
tem
pera
ture
tem
pera
ture
(mg.
l-1)
(mg.
l-1)
(μs.c
m-1)
(mg.
l-1)
(mg.
l-1)
(mg.
l-1)
(mg.
l-1)
(O
C)
(O
C)
MJ1
.122
.2 ±
0.5f
19.0
± 0.
5d6.
7 ± 0.
5ab7.
6 ± 0.
5a0.
8 ± 0.
1c19
6±5.
3a7.
3±0.
5g0.
50± 0
.1b
0.09
±0.0
hi0.
16±0
.0g
MJ1
.231
.0 ±
0.5b
27.0
± 1.
0ab6.
7 ± 0.
5ab7.
0 ± 1.
1ab1.
6 ± 0.
2a11
9±1.
0d7.
6±0.
5fg0.
73± 0
.1a
0.38
±0.0
a0.
53±0
.0b
MJ1
.324
.3 ±
0.5e
26.0
± 0.
5bc7.
7 ± 0.
5ab5.
3 ± 0.
5ab0.
2 ± 0.
1e13
4±3.
2c10
.3± 0
.5e
0.53
± 0.1
b0.
18±0
.0de
f0.
18± 0
.0fg
MJ2
.125
.0 ±
0.5e
17.3
± 0.
5d6.
7 ± 0.
5ab7.
3 ± 0.
5ab1.
5 ± 0.
1ab68
± 1.0
g19
.6± 0
.5d
0.50
± 0.1
b0.
08±0
.0e
0.26
±0.0
e
MJ2
.232
.0 ±
0.5b
24.3
± 0.
5c5.
7 ± 0.
5b5.
6 ± 0.
5ab1.
7 ± 0.
1a90
± 0.6
f64
.0± 1
.0a
0.50
± 0.0
b0.
13±0
.0fg
h0.
27±0
.0e
MJ2
.327
.0 ±
0.5d
25.0
± 1.
1c7.
3 ± 0.
5ab4.
6 ± 0.
5b0.
7 ± 0.
1cd53
±1.0
h57
.0±1
.0b
ND
c0.
19±0
.0cd
e0.
63±0
.0a
MJ3
.120
.0 ±
0.5f
19.0
± 0.
5d7.
0 ± 1.
0ab7.
0 ± 1.
0ab1.
2 ± 0.
1b16
9 ±0.
5b27
.0±1
.5c
ND
c0.
21±0
.0bc
d0.
17±0
.0g
MJ3
.228
.0 ±
0.5c
27 ±
0.5ab
5.6 ±
0.5b
6.7 ±
1.1ab
1.6 ±
0.1a
118 ±
1.0d
17.6
±0.5
d0.
83±0
.1a
0.16
±0.0
efg
0.43
±0.0
c
MJ3
.325
.3 ±
0.5de
25 ±
0.5bc
7.3 ±
0.5ab
6.0 ±
1.0ab
0.5 ±
0.1de
110±
9.5de
30.0
±0.5
c0.
50±0
.0b
0.23
±0.0
bc0.
23±0
.0ef
MJ4
.129
.0 ±
0.5c
18.0
± 1.
0d6.
7 ± 0.
5ab7.
7 ± 0.
5a0.
4 ± 0.
1e14
1 ±1.
7c10
.0±1
.0ef
0.73
±0.1
a0.
11±0
.0gh
i0.
32±0
.0d
MJ4
.234
.0 ±
0.5a
28.0
± 0.
5a7.
0 ± 1.
0ab6.
7 ± 1.
1ab1.
5 ± 0.
1ab10
1 ±1.
3e18
.0±1
.0d
0.46
±0.0
b0.
24±0
.0b
0.24
±0.0
e
MJ4
.324
.0 ±
0.5e
24.0
± 0.
5c8.
0 ± 1.
0a6.
7 ± 1.
5ab0.
5 ± 0.
1de88
±1.5
f28
.0±1
.0c
0.50
±0.0
b0.
12±0
.0gh
i0.
25±0
.0e
À¡“¬
‡Àμÿ
ND
; Non
Det
ect
μ—«Õ—°
…√∑’Ëμ
à“ß°—π
„π·π
«μ—Èß
· ¥ß
«à“¡’§
«“¡·
μ°μà“
ß°—πÕ
¬à“ß¡
’π—¬ ”
§—≠∑“
ß ∂‘μ
‘ (P <
0.0
5)
MJ1
.1;
® ÿ¥ 1
‡¥◊Õπ
∏—π«“
§¡ æ
.». 2
557,
MJ1
.2; ®
ÿ¥ 1
‡¥◊Õπ
情¿
“§¡
æ.».
255
8, M
J1.3
; ®ÿ¥
1 ‡¥
◊Õπ ‘ß
À“§¡
æ.»
. 255
8
MJ2
.1;
® ÿ¥ 2
‡¥◊Õπ
∏—π«“
§¡ æ
.». 2
557,
MJ2
.2; ®
ÿ¥ 2
‡¥◊Õπ
情¿
“§¡
æ.».
255
8, M
J2.3
; ®ÿ¥
2 ‡¥
◊Õπ ‘ß
À“§¡
æ.»
. 255
8
MJ3
.1;
® ÿ¥ 3
‡¥◊Õπ
∏—π«“
§¡ æ
.». 2
557,
MJ3
.2; ®
ÿ¥ 3
‡¥◊Õπ
情¿
“§¡
æ.».
255
8, M
J3.3
; ®ÿ¥
3 ‡¥
◊Õπ ‘ß
À“§¡
æ.»
. 255
8
MJ4
.1;
® ÿ¥ 4
‡¥◊Õπ
∏—π«“
§¡ æ
.». 2
557,
MJ4
.2; ®
ÿ¥ 4
‡¥◊Õπ
情¿
“§¡
æ.».
255
8, M
J4.3
; ®ÿ¥
4 ‡¥
◊Õπ ‘ß
À“§¡
æ.»
. 255
8
SWU Sci. J. Vol. 33 No. 1 (2017)128
§«“¡ —¡æ—π∏å§ÿ≥¿“æπÈ”∑“ß°“¬¿“懧¡’ ·≈–·¡≈ßπÈ”°“√«‘‡§√“–À姫“¡ —¡æ—π∏å¢Õߧÿ≥¿“æπÈ”∑“ß°“¬¿“æ·≈–‡§¡’ °—∫·¡≈ßπÈ”¥â«¬‡∑§π‘§°“√
«‘‡§√“–Àå Canonical Correspondence analysis (CCA) ÷Ë߇ªìπ‡∑§π‘§°“√À“§«“¡ —¡æ—π∏å√–À«à“߇¡∑√‘°¢Õß°≈ÿà¡·¡≈ßπÈ” ·≈–‡¡∑√‘°∑“ߥâ“π ‘Ëß·«¥≈âÕ¡ æ∫«à“°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ” ‰¡à‰¥â¡’§«“¡ —¡æ—π∏å™—¥‡®π°—∫ƒ¥Ÿ°“≈ À√◊Õ§√—Èß∑’ˇ°Á∫ ´÷Ëßæ∫«à“·¡≈ßπÈ”¡’§«“¡ —¡æ—π∏å°—∫ªí®®—¬∑“ß°“¬¿“æ ·≈–‡§¡’∫“ߪ√–°“√ ‡™àπ Psephenidae ·≈– Hydreanidae ´÷Ëßæ∫‡ªìπ™π‘¥‡¥àπ„π®ÿ¥‡°Á∫μ—«Õ¬à“ß∑’Ë MJ2.2 ·≈–MJ2.3 ´÷Ëßæ∫«à“‡ªìπ®ÿ¥‡°Á∫μ—«Õ¬à“ß∑’Ë¡’≈—°…≥–§«“¡¢ÿàπ Ÿß πÕ°®“°π’Ȭ—ßæ∫°≈ÿà¡¢Õß·¡≈ßπÈ”„π°≈ÿà¡™’ª–¢“« ·≈–·¡≈ßÀπÕπª≈Õ°πÈ”∑’Ë∫àß∫Õ°∂÷ߧÿ≥¿“æπÈ”¥’ Õ“∑‘‡™àπ Lepidostomatidae LeptoceridaePotamanthidae ·≈– Perlidae „π®ÿ¥μâππÈ”≈”∏“√ MJ1 ∑’Ë¡’§à“ªí®®—¬∑“ß°“¬¿“æ·≈–‡§¡’μË” À√◊Õ®ÿ¥‡°Á∫μ—«Õ¬à“ß∑’Ë MJ3.2 æ∫°≈ÿà¡¢Õß¡«ππÈ”„π∫√‘‡«≥¥—ß°≈à“«·μ°μà“ß®“°®ÿ¥‡°Á∫μ—«Õ¬à“ßÕ◊Ëπ Õ“∑‘‡™àπ PleidaeVelidae ·≈– Helodidae ‡ªìπμâπ ¥—ß¿“æ∑’Ë 7
¿“æ∑’Ë 7 · ¥ß§«“¡ —¡æ—π∏å¢Õߧÿ≥¿“æπÈ”∑“ß°“¬¿“æ·≈–‡§¡’°—∫«ß»å¢Õß·¡≈ßπÈ”„π·μà≈–®ÿ¥‡°Á∫μ—«Õ¬à“ß
«“√ “√«‘∑¬“»“ μ√å ¡»« ªï∑’Ë 33 ©∫—∫∑’Ë 1 (2560) 129
√ÿª·≈–«‘®“√≥åº≈°“√∑¥≈Õß®“°°“√»÷°…“§ÿ≥¿“æπÈ”∑“ß°“¬¿“æ·≈–‡§¡’¢ÕßπÈ”æ∫«à“¡’§à“∑’Ë·μ°μà“ß°—πÕ—π‡π◊ËÕß¡“®“°
À≈“¬ªí®®—¬‰¡à«à“®–‡ªìπ≈—°…≥–‡©æ“–¢Õß®ÿ¥‡°Á∫μ—«Õ¬à“ß ·≈–‡«≈“„π°“√‡°Á∫μ—«Õ¬à“ß √«¡∂÷ßÕ‘∑∏‘æ≈¢Õ߃¥Ÿ°“≈≈â«π·μà¡’§«“¡‡°’ˬ«¢âÕß°—∫§ÿ≥¿“æπÈ”∑“ß°“¬¿“æ·≈–‡§¡’ [24, 25] ·≈–®“°§à“æ“√“¡‘‡μÕ√åμà“ßÊ∑’Ë∑”°“√»÷°…“„π§√—Èßπ’Èæ∫«à“Õ¬Ÿà„π‡°≥±åμ“¡¡“μ√∞“π§ÿ≥¿“æ·À≈àßπÈ”º‘«¥‘π∑’Ë 2 ·≈– 3 ‡ªìππÈ”∑’Ë “¡“√∂„™âÕÿª‚¿§∫√‘‚¿§‰¥â·μàμâÕß¡’°“√¶à“‡™◊ÈÕ‚√§μ“¡ª°μ‘ ·≈–ºà“π°√–∫«π°“√ª√—∫ª√ÿßπÈ”°àÕπ
°“√»÷°…“§«“¡ —¡æ—π∏å√–À«à“ߧ«“¡À≈“°À≈“¬·≈–°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ” √à«¡°—∫§ÿ≥¿“æπÈ”„π≈”∏“√μâππÈ”·¡à·®à¡ Õ”‡¿Õ°—≈¬“≥‘«—≤π“ ®—ßÀ«—¥‡™’¬ß„À¡à √–À«à“߇¥◊Õπ∏—𫓧¡ æ.». 2557情¿“§¡ æ.». 2558 ·≈– ‘ßÀ“§¡ æ.». 2558 æ∫·¡≈ßπÈ”∑—ÈßÀ¡¥ 8,889 ®“° 9 Õ—π¥—∫ 84 «ß»å‚¥¬æ∫·¡≈ßπÈ”„πÕ—π¥—∫ Diptera (54%) ¡“°∑’Ë ÿ¥ √Õß≈ß¡“§◊Õ Ephemeroptera (26%) Coleoptera(8%) Trichoptera (6%) Odonata (4%) Hemiptera (3%) ·≈–Õ◊ËπÊ (< 1%) μ“¡≈”¥—∫ ‚¥¬®”π«π«ß»å∑’Ëæ∫„π°“√»÷°…“§√—Èßπ’È¡’§«“¡À≈“°À≈“¬¢Õß«ß»å§àÕπ¢â“ß¡“°‚¥¬æ∫®”π«π«ß»å∂÷ß 84 «ß»å‡¡◊ËÕ‡∑’¬∫°—∫ß“πÕ◊ËπÊ∑’Ë¡’°“√»÷°…“„π≈”πÈ”„π¿“§‡Àπ◊Õ¢Õߪ√–‡∑»‰∑¬·≈–ª√–‡∑»„°≈⇧’¬ß [26, 27] ‚¥¬∑—Èßπ’ÈÕ“® ◊∫‡π◊ËÕß¡“®“°§«“¡‡À¡“– ¡¢Õßæ◊Èπ∑’Ë·≈–§«“¡À≈“°À≈“¬¢Õß∂‘Ëπ∑’ËÕ¬ŸàÕ“»—¬¢Õß·¡≈ßπÈ”∑’Ë¡’°“√∂Ÿ°√∫°«ππâÕ¬ ‚¥¬æ∫§à“¥—™π’§«“¡À≈“°À≈“¬ Ÿß ÿ¥∑’Ë®ÿ¥‡°Á∫μ—«Õ¬à“ß∑’Ë MJ1 ∑’Ëæ∫®”π«π«ß»å¢Õß ‘Ëß¡’™’«‘μ∑’ËÀ≈“°À≈“¬·≈–¡’®”π«πμ—« ¡Ë”‡ ¡Õ (Evenness) Ÿß°«à“®ÿ¥»÷°…“Õ◊ËπÊ ‚¥¬¡’§à“¥—™π’§«“¡À≈“°À≈“¬ Ÿß ÿ¥2.564 ‚¥¬‡©æ“–„π‡¥◊Õπ ‘ßÀ“§¡ (MJ1.3) ¡’§à“ 2.504 à«π§à“¥—™π’§«“¡À≈“°À≈“¬μË” ÿ¥æ∫∑’Ë®ÿ¥MJ2 ¡’§à“ 0.921 ‚¥¬‡©æ“–„π‡¥◊Õπ情¿“§¡ (MJ2.2) ¡’§à“‡æ’¬ß 0.607 ÷ËßÕ“®‡°’ˬ«¢âÕß°—∫ªí®®—¬∑“ߥâ“𰓬¿“æ ·≈–‡§¡’¢ÕßπÈ”∫“ߪ√–°“√∑’ˇª≈’ˬπ·ª≈ß·≈– àߺ≈μàÕ§«“¡À≈“°À≈“¬¢Õß·¡≈ßπÈ” ‚¥¬®ÿ¥MJ2 π’È∫√‘‡«≥√‘¡Ωíòß¡’°“√∑”°“√‡°…μ√ ·≈–π“¢â“« „π™à«ßƒ¥ŸΩπ¡’°“√™–≈â“ßÀπâ“¥‘π∑”„Àâ§à“æ“√“¡‘‡μÕ√å∫“ß§à“ Ÿß¢÷Èπ‡™àπ§à“§«“¡¢ÿàπ ·≈–ª√‘¡“≥ “√Õ“À“√ ®–‡ÀÁπ‰¥â«à“§à“·Õ¡‚¡‡π’¬-‰π‚μ√‡®π¡’§à“ Ÿß‡°‘π¡“μ√∞“π·À≈àßπÈ”º‘«¥‘π∑’Ë°”À𥉫â§◊Õ 0.5 mg.-1 Õ’°∑—Èßæ∫«à“§à“ DO μË”°«à“ª°μ‘ (MJ2.3) ‚¥¬¡’§à“4.6 mg.-1 ´÷Ëß·Õ¡‚¡‡π’¬-‰π‚μ√‡®π∑’ˇªìπ§à“∫àß∫Õ°∂÷ßπÈ”¡’°“√ªπ‡ªóôÕπ®“°´“°æ◊™´“° —μ«å ªÿܬ “√‡§¡’®“°‡°…μ√°√√¡·≈â«·∫§∑’‡√’¬¬àÕ¬ ≈“¬ “√Õ‘π∑√’¬å‰π‚μ√‡®π„À⇪ìπ·Õ¡‚¡‡π’¬ Õ’°∑—Èß§à“ª√‘¡“≥ “√Õ“À“√∑’Ë Ÿßπ’Ȭ—߇ªìπ·À≈àßÕ“À“√„Àâæ◊™πÈ”·≈– “À√à“¬„™â„π°“√‡®√‘≠‡μ‘∫‚μ·≈–¡’°“√„™âÕÕ°´‘‡®π¡“°¢÷Èπμ“¡‰ª¥â«¬ àߺ≈„Àâª√‘¡“≥ÕÕ° ‘‡®π„π·À≈àßπÈ”≈¥≈ߥ—ß°≈à“« √«¡‰ª∂÷ß®ÿ¥‡°Á∫μ—«Õ¬à“ßπ’È¡’æ◊™¬◊πμâπª°§≈ÿ¡√‘¡Ωíòß∑”„Àâ∫¥∫—ß· ß·¥¥ àߺ≈„Àâ°√–∫«π°“√ —߇§√“–Àå¥â«¬· ß∑’Ë„™â„π°“√º≈‘μÕÕ° ‘‡®π„Àâ°—∫·À≈àßπÈ”≈¥≈߉ª¥â«¬ [28]
‡¡◊ËÕæ‘®“√≥“§ÿ≥≈—°…≥–¢ÕßπÈ”·≈–°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ” æ∫«à“°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ”„π·μà≈–®ÿ¥‡°Á∫μ—«Õ¬à“ß¡’§«“¡·μ°μà“ß°—π ‚¥¬ªí®®—¬∑’Ë àߺ≈„À⇰‘¥§«“¡·μ°μà“ß°—π ª√–°Õ∫‰ª¥â«¬ 2 à«π§◊Õ ƒ¥Ÿ°“≈·≈–≈—°…≥–∑’ËÕ¬ŸàÕ“»—¬¢Õß·¡≈ßπÈ” ‚¥¬æ∫«à“„π®ÿ¥ MJ1 ‡ªìπ·À≈àßπÈ”∑’Ë¡’æ◊Èπ∑âÕßπÈ”‡ªìπÀ‘π·≈–∑√“¬ ·≈–æ◊™√‘¡Ωíòß ·≈–πÈ”‰À≈·√ß·≈–‡√Á« ∑”„Àâæ∫·¡≈ßπÈ”„πª√‘¡“≥∑’ËπâÕ¬ ·μà‡¡◊ËÕæ‘®“√≥“∂÷ß®”π«π«ß»å∑’Ëæ∫°≈—∫¡’¡“°‰¡à·μ°μà“ß°—∫®ÿ¥Õ◊ËπÊ „π¢≥–‡¥’¬«°—π°—∫®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ2 ÷Ëß¡’æ◊Èπ∑âÕßπÈ”‡ªìπ‚§≈π ·≈–¡’¢π“¥‡≈Á° ´÷Ëß∑”„Àâ·À≈àß∑’ËÕ¬ŸàÕ“»—¬¢Õß·¡≈ßπÈ”‰¡à¡’§«“¡À≈“°À≈“¬·≈–‡À¡“– ¡°—∫
SWU Sci. J. Vol. 33 No. 1 (2017)130
∫“ß°≈ÿࡇ∑à“π—Èπ ´÷Ëß„π®ÿ¥»÷°…“π’ȇÕßæ∫°≈ÿà¡·¡≈ßπÈ”«ß»å Chironominae À√◊ÕÀπÕπ√‘ÈππÈ”®◊¥‡ªìπ ‘Ëß¡’™’«‘μ™π‘¥‡¥àπ‚¥¬æ∫®”π«πμ—«§àÕπ¢â“ß¡“°°«à“®ÿ¥»÷°…“Õ◊ËπÊ Õ—π‡π◊ËÕß¡“®“°¡’∑’ËÕ¬ŸàÕ“»—¬∑’ˇÀ¡“– ¡§◊Õ‚§≈π [29] ‡™àπ‡¥’¬«°—π°—∫®ÿ¥‡°Á∫μ—«Õ¬à“ߥâ“π≈à“ß ‡™àπ MJ3 ·≈– MJ4 ¥—ßπ—Èπ¥â«¬®”π«πμ—«¢ÕßÀπÕπ√‘ÈππÈ”®◊¥∑’Ëæ∫®”π«πμ—«¡“°„π “¡®ÿ¥‡°Á∫μ—«Õ¬à“ߥ—ß°≈à“«®÷ß∑”„Àâ —¥ à«π¢Õß·¡≈ßπÈ”∑’Ëæ∫‡ªìπ°≈ÿà¡¢ÕßÕ—π¥—∫Diptera ¡’ª√‘¡“≥¡“°∑’Ë ÿ¥∂÷ß 54% ·≈– ‘Ëß¡’™’«‘μ„π°≈ÿà¡π’È “¡“√∂æ∫‰¥âμ“¡·À≈àßπÈ”∑—Ë«‰ª ‚¥¬„π·À≈àßπÈ”‰À≈¡—°¡’§«“¡À≈“°À≈“¬ Ÿß°«à“πÈ”π‘Ëß ‡ªìπ·¡≈ßπÈ”∑’Ë¡’Õ«—¬«–摇»…∑’˙૬„π°“√À“¬„® ·≈–¡’°“√ª√—∫μ—«„ÀâÕ¬Ÿà„π ¿“æ∑’Ë¡’ÕÕ°´‘‡®πμË”‰¥â¥—ßπ—Èπ®÷ß “¡“√∂Õ“»—¬„π·À≈àßπÈ”∑’Ë¡’ÕÕ°´‘‡®πμË” ·≈– “¡“√∂æ∫·¡≈ßπÈ”„π°≈ÿà¡π’ȉ¥âÕ¬à“ß°«â“ߢ«“ß [29]
à«π§«“¡ —¡æ—π∏å√–À«à“ßªí®®—¬∑“ß°“¬¿“æ ‡§¡’ ·≈–·¡≈ßπÈ”π—Èπæ∫«à“¬—߉¡à “¡“√∂√–∫ÿ‰¥â™—¥‡®π«à“‡ªìπº≈Õ—π‡π◊ËÕß¡“®“°ªí®®—¬„¥ ‡¡◊ËÕæ‘®“√≥“¥Ÿ°“√«‘‡§√“–Àå À —¡æ—π∏姓‚ππ‘§Õ≈ (CCA) ·≈â«æ∫«à“¬—߉¡àæ∫§«“¡ —¡æ—π∏åÕ¬à“߇¥àπ™—¥¢Õß°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ”°—∫§ÿ≥¿“æπÈ” ‡π◊ËÕß®“°®ÿ¥»÷°…“∑—ÈßÀ¡¥Õ¬Ÿà„π‡¢μμâππÈ”≈”∏“√ ´÷Ëß°“√‡ª≈’ˬπ·ª≈ߢÕ߃¥Ÿ°“≈ àߺ≈°√–∑∫§àÕπ¢â“ßπâÕ¬ ∑”„Àâ≈—°…≥–¢ÕßπÈ”„π·μà≈–®ÿ¥»÷°…“¡’§à“‰¡à·μ°μà“ß°—π¡“°π—° ‚¥¬ªí®®—¬Õ◊Ëπ∑’Ë àߺ≈°√–∑∫·≈–πà“®–∑”„Àâ°“√°√–®“¬¢Õß·¡≈ßπÈ”·μ°μà“ß°—π®–‡ªìπ≈—°…≥–¢Õß ¿“æ·«¥≈âÕ¡¢Õß·À≈àßπÈ”·≈–≈—°…≥–æ◊Èπ∑âÕßπÈ” ÷Ë߇°’ˬ«¢âÕß°—∫∑’ËÕ¬ŸàÕ“»—¬ (habitat) ¢Õß·¡≈ßπÈ” ·≈–‡¡◊ËÕæ‘®“√≥“¥Ÿ¿“æ∑’Ë 7 ®–‡ÀÁπ‰¥â«à“°≈ÿà¡·¡≈ßπÈ”∑’Ë°√–®“¬μ—«Õ¬Ÿà®ÿ¥»÷°…“ MJ1.3 ·≈– MJ1.2 ÷Ë߇ªìπ·À≈àßμâππÈ”¡’∂‘Ëπ∑’ËÕ¬ŸàÕ“»—¬§àÕπ¢â“ßÀ≈“°À≈“¬æ∫°≈ÿà¡·¡≈ßπÈ”∑’Ë∫àß∫Õ°∂÷ߧÿ≥¿“æπÈ”¥’ ‡™àπ Perlidae „πÕ—π¥—∫¢Õß·¡≈߇°“–À‘π∑’Ë∫àß∫Õ°∂÷ߧÿ≥¿“æπÈ”¥’ LeptoceridaeLepidostomatidae „πÕ—π¥—∫ Trichoptera ∑’Ë∫àß∫Õ°∂÷ߧÿ≥¿“æπÈ”¥’‡™àπ‡¥’¬«°—π Õ¥§≈âÕß°—∫§à“§ÿ≥¿“æπÈ”®“°°“√ª√–‡¡‘π∑“ߥâ“π™’«¿“æ¥â«¬ ASPT æ∫«à“§ÿ≥¿“æπÈ”‚¥¬√«¡Õ¬Ÿà„π‡°≥±åª“π°≈“ß∂÷ߧàÕπ¢â“ߥ’‚¥¬‡©æ“–®ÿ¥‡°Á∫μ—«Õ¬à“ß MJ1 ¡’§à“ ASPT Ÿß∑’Ë ÿ¥ ÷Ë߇ªìπ‰ª∑‘»∑“߇¥’¬«°—π°—∫§à“¥—™π’§«“¡À≈“°À≈“¬·≈–§à“§«“¡ ¡Ë”‡ ¡Õ„π°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ” à«π®ÿ¥‡°Á∫μ—«Õ¬à“ß∑’Ë MJ2 ¡’§à“ ASPT μË” ÿ¥´÷Ëß Õ¥§≈âÕß°—∫§à“¥—™π’§«“¡À≈“°À≈“¬·≈–§«“¡ ¡Ë”‡ ¡Õ„π°“√°√–®“¬μ—«∑’ËμË”‡™àπ°—π ·μàÕ¬à“߉√°Áμ“¡‡¡◊ËÕª√–‡¡‘π§ÿ≥¿“æπÈ”∑“ß™’«¿“æ¥â«¬ BMWPTh score ·≈– ASPT ·≈–°“√ª√–‡¡‘π§ÿ≥¿“æπÈ”®◊¥º‘«¥‘πæ∫«à“§ÿ≥¿“æπÈ”„π·μà≈–®ÿ¥‡°Á∫μ—«Õ¬à“ßÕ¬Ÿà„π‡°≥±å§ÿ≥¿“æπÈ”ª“π°≈“ß∂÷ߧàÕπ¢â“ߥ’
®“°º≈°“√»÷°…“®–‡ÀÁπ‰¥â«à“≈”∏“√μâππÈ”„πÕ”‡¿Õ°—≈¬“≥‘«—≤π“¡’§«“¡À≈“°À≈“¬¢Õß·¡≈ßπÈ”·≈–§ÿ≥¿“æπÈ”∑’ËÕ¬Ÿà„π‡°≥±å¥’ ‚¥¬æ∫«ß»å¢Õß·¡≈ßπÈ”∑’ËÀ≈“°À≈“¬ ·≈–§àÕπ¢â“ßÀ“¬“°‡ªìπμ—«∫àß™’È∂÷ߧ«“¡Õÿ¥¡ ¡∫Ÿ√≥å¢Õßæ◊Èπ∑’ˉ¥â‡ªìπÕ¬à“ߥ’ ¥—ßπ—Èπß“π«‘®—¬π’Èπà“®–‡ªìπ¢âÕ¡Ÿ≈æ◊Èπ∞“π∑’Ë ”§—≠¬‘Ëß„π°“√‡º¬·æ√à≈ß Ÿà™ÿ¡™π∫Õ°∂÷ß ∂“𖧫“¡À≈“°À≈“¬·≈–§«“¡Õÿ¥¡ ¡∫Ÿ√≥å„πæ◊Èπ∑’ˇæ◊ËÕ„Àâ™ÿ¡™π‰¥â‡ÀÁ𧫓¡ ”§—≠°àÕ„À⇰‘¥°“√Õπÿ√—°…å·≈–À«ß·Àπ À“°¡’°“√√∫°«πæ◊Èπ∑’Ë¥—Ë߇™àπ®ÿ¥ MJ2 ÷Ë߇ªìπæ◊Èπ∑’Ë∑’Ë¡’°“√∑”‡°…μ√°√√¡π“¢â“« ·≈–‰√à∂—Ë«‡À≈◊Õß ®÷߉ª√∫°«π àߺ≈μàÕ√–∫∫𑇫»‚¥¬‡©æ“–∂‘Ëπ∑’ËÕ¬ŸàÕ“»—¬¢Õß·¡≈ßπÈ”∑”„À⧫“¡À≈“°À≈“¬∑“ß™’«¿“æπâÕ¬«à“®ÿ¥»÷°…“Õ◊ËπÊ ¥—ßπ—ÈπºŸâ«‘®—¬®÷ß¡’§«“¡‡ÀÁπ«à“„π°“√‡°Á∫μ—«Õ¬à“ߧ«√®–¡’°“√»÷°…“Õ¬à“ßμàÕ‡π◊ËÕß ‚¥¬‡©æ“–°“√‡°Á∫μ—«Õ¬à“ß„Àâ§√Õ∫§≈ÿ¡°“√‡ª≈’ˬπ·ª≈ßμ“¡ƒ¥Ÿ°“≈ §«√®–μâÕß¡’°“√¢¬“¬æ◊Èπ∑’Ë„Àâ¡’≈—°…≥– ¿“æ·«¥≈âÕ¡∑’Ë¡’§«“¡·μ°μà“ß°—π¡“°¢÷Èπ‡æ◊ËÕ·¬°·¬– ·≈–«‘‡§√“–ÀåÀ“ªí®®—¬∑’Ë¡’º≈μàÕ°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ” ·≈–®–μâÕß¡’°“√‡°Á∫¢âÕ¡Ÿ≈´È”„π·μà≈–ªïÕ¬à“ßμàÕ‡π◊ËÕß ‡æ◊ËÕ‡æ‘Ë¡§«“¡·¡à𬔷≈–∂Ÿ°μâÕߢÕßªí®®—¬∑’Ë¡’º≈·≈–§«“¡ —¡æ—π∏åμàÕ°“√°√–®“¬μ—«¢Õß·¡≈ßπÈ”μàÕ‰ª ´÷Ëß “¡“√∂∑’Ë®–
«“√ “√«‘∑¬“»“ μ√å ¡»« ªï∑’Ë 33 ©∫—∫∑’Ë 1 (2560) 131
π”‡Õ“Õߧ姫“¡√Ÿâπ’ȉªª√–¬ÿ°μ儙Ⱇ∫ß“π¥â“πμà“ßÊ ‰¡à«à“®–‡ªìπß“π¥â“π°“√Õπÿ√—°…å °“√ª√–¬ÿ°μå„™âæ—≤𓇪ìπ¥—™π’∑“ß™’«¿“æ´÷Ëߪ√–‡∑»‰∑¬¬—߉¡à¡’°“√æ—≤π“¢âÕ¡Ÿ≈¥â“ππ’Èμ—Èß·μàªï 2002 [3] √«¡∂÷ßß“π¥â“π ‘Ëß·«¥≈âÕ¡ß“π¥â“π°“√ª√–‡¡‘𧫓¡Õÿ¥¡ ¡∫Ÿ√≥å¢Õßæ◊Èπ∑’Ë ·≈–∑’Ë ”§—≠®–‡ªìπ·π«∑“ß„π°“√¥”‡π‘π°‘®°√√¡¢Õß¡πÿ…¬å∑’Ë®– àߺ≈°√–∑∫∂÷ß∑√—欓°√∏√√¡™“μ‘„ÀâπâÕ¬∑’Ë ÿ¥ ÷Ë߇ªìπ‡ªÑ“À¡“¬¢Õß°“√Õπÿ√—°…åÕ¬à“߬—Ë߬◊π‰¥âμàÕ‰ª
°‘μμ‘°√√¡ª√–°“»ß“π«‘®—¬¥—ß°≈à“«‰¥â√—∫∑ÿπÕÿ¥Àπÿπ°“√«‘®—¬®“°§≥–°√√¡°“√«‘®—¬·Ààß™“μ‘ («™.) ªïß∫ª√–¡“≥ 2558
‡Õ° “√Õâ“ßÕ‘ß1. Gothe, E., Friberg, N., Kahlert, M., Temnerud, J., and Sandin, L. 2014. Headwater Biodiversity
among Different Levels of Stream Habitat Hierarchy. Biodiversity and Conservation.23(1): 63-80.
2. IUCN. 2007. IUCN Red List of Threatened Species. International Union for Conservationof Nature and Natural resources. Available from URL: http://www.iucnredlist.org. 5 May2016.
3. Mustow, S. E. 2002. Biological Monitoring of Rivers in Thailand: Use and Adaptation ofthe BMWP Score. Hydrobiologia. 479(1): 191-229.
4. Wongsanoon, J., Jatisatienr, A., Mungkornasawakul, P., and Phalaraksh, C. 2011. Aquatic-insect-based Biotic Indices to Assess Water Quality in Klong Pae, Rajjaprabha Dam, SuratThani Province 2008-2009. Chiang Mai Journal of Science. 38(3): 463-472.
5. Feeley, H. B., Davis, S., Bruen, M., Blacklocke, S., and Kelly-Quinn, M. 2012. The Impactof a Catastrophic Storm Event on Benthic Macroinvertebrate Communities in UplandHeadwater Streams and Potential Implications for Ecological Diversity and Assessment ofEcological Status. Journal of Limnology. 71(2): 299-308.
6. Staglino, D. M. and Whiles, M. R. 2002. Macroinvertebrate Production and Trophic Structurein a Tallgrass Prairie Headwater Stream. Journal of the North American BenthologicalSociety. 21: 97-113.
7. Heino, J. 2005. Functional Biodiversity of Macroinvertebrate Assemblages along MajorEcological Gradients of Boreal Headwater Streams. Freshwater Biology. 50: 1578-1587.
8. David, F. and Boonsoong, B. 2014. Colonisation of Leaf Litter by Lotic Macroinvertebratesin a Headwater Stream of the Phachi River (western Thailand). Fundamental and AppliedLimnology. 184: 109-124.
9. Docile, T. N., Figueiro, R., Portela, C. and Nessimian, J. L. 2016. MacroinvertebrateDiversity Loss in Urban Streams from Tropical Forests. Environmental Monitoring andAssessment. 188(4): 237.
SWU Sci. J. Vol. 33 No. 1 (2017)132
10. Manisarn, V. 2015. The Climate of Thailand. Available from URL:htttp://www.tmd.go.th/en/archive/thailand_climate.pdf. 16 December 2016.
11. GIS Chiang Mai. 2015. MAP. Available from URL: http://gis.chiangmai.go.th/index.php?name=document&District_ID=26&m=img. 10 May 2016.
12. Eaton, A. 2005. Standard Methods for the Examination Water and Wastewater. 21st Edi-tion. Washington, D.C. American Public Health Association (APHA), American WaterWorks Association (AWWA).
13. Al-Shami, S. A., Heino, J., Salmah, M. R. C., Abu Hassan, A., Suhaila, A. H., and Madrus,M. R. 2013. Drivers of Beta Diversity of Macroinvertebrate Communities in TropicalForest Streams. Freshwater Biology. 58(6): 1126-1137.
14. McCafferty, W. P. 1983. Aquatic Entomology. Boston: Jones and Bartlett. p. 448.15. Commission, M. R. 2006. Identification of Freshwater Invertebrates of the Mekong River
and Its Tributaries: Mekong River Commission. p. 274.16. Stubbington, R., Boulton, A. J., Little, S., and Wood, P. J. 2015. Changes in Invertebrate
Assemblage Composition in Benthic and Hyporheic Zones during a Severe SupraseasonalDrought. Freshwater Science. 34(1): 344-354.
17. Cao, Y., Bark, A. W., and Williams, W. P. 1997. A Comparison of Clustering Methods forRiver Benthic Community Analysis. Hydrobiologia. 347: 25-40.
18. Holmes, K. L., Goebel, P. C., Williams, L. R., and Schecengost, M. 2011. EnvironmentalInfluences on Macroinvertebrate Assemblages in Headwater Streams of Northeastern Ohio.Journal of Freshwater Ecology. 26(3): 409-422.
19. Giorgio, A., De Bonis, S., and Guida, M. 2016. Macroinvertebrate and Diatom Communitiesas Indicators for the Biological Assessment of River Picentino (Campania, Italy). EcologicalIndicators. 64: 85-91.
20. R Core Team. 2016. R: A Language and Environment for Statistical Computing. R Foundationfor Statistical Computing, Vienna, Austria. Available from URL: https://www.R-project.org/.4 January 2016.
21. Obolewski, K., Glinska-Lewczuk, K., and Strzelczak, A. 2014. The Use of BenthicMacroinvertebrate Metrics in the Assessment of Ecological Status of Floodplain Lakes.Journal of Freshwater Ecology. 29(2): 225-242.
22. Jost, L. 2006. Entropy and Diversity. Oikos. 113(2): 363-375.23. Buckup, L., Bueno, A. A. R., Bond-Buckup, G., Casagrande, M., and Majolo, F. 2007. The
Benthic Macroinvertebrate Fauna of Highland Streams in Southern Brazil: Composition,Diversity and Structure. Revista Brasileira De Zoologia. 24(2): 294-301.
«“√ “√«‘∑¬“»“ μ√å ¡»« ªï∑’Ë 33 ©∫—∫∑’Ë 1 (2560) 133
24. Wilson, C. O. 2015. Land Use/Land Cover Water Quality Nexus: Quantifying AnthropogenicInfluences on Surface Water Quality. Environmental Monitoring and Assessment. 187(7):425-428.
25. Yu, S. Y., Xu, Z. X., Wu, W., and Zuo, D. P. 2016. Effect of Land Use Types on StreamWater Quality under Seasonal Variation and Topographic Characteristics in the Wei RiverBasin, China. Ecological Indicators. 60: 202-212.
26. Jung, S. W., Nguyen, V. V., Nguyen, Q. H., and Bae, Y. J. 2008. Aquatic Insect Faunasand Communities of a Mountain Stream in Sapa Highland, Northern Vietnam. Limnology.9(3): 219-229.
27. Prommi, T., and Payakka, A. 2015. Aquatic Insect Biodiversity and Water Quality Parametersof Streams in Northern Thailand. Sains Malaysiana. 44(5): 707-717.
28. Greenwood, J. L., and Rosemond, A. D. 2005. Periphyton Response to Long-term NutrientEnrichment in a Shaded Headwater Stream. Canadian Journal of Fisheries and AquaticSciences. 62(9): 2033-2045.
29. Silver, P., Mc Call, C. B., and Wooster, D. 2004. Habitat Partitioning by ChironomidLarvae in Arrays of Leaf Patches in Streams. Journal of the North American BenthologicalSociety. 23(3): 467-479.
‰¥â√—∫∫∑§«“¡«—π∑’Ë 25 ‘ßÀ“§¡ 2559¬Õ¡√—∫μ’æ‘¡æå«—π∑’Ë 16 ∏—𫓧¡ 2559