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Proceedings of International Conference on Climate Change, Biodiversity and Ecosystem Services for the Sustainable Development Goals : Policy and Practice 27-29 June 2016 at the Sirindhorn International Environmental Park, Cha-am, Phetchaburi, Thailand

C.  Flux  calculation, WUE  and  data  processing The  fluxes  of  CO2,  ( (1) (1) (2) (3) were  (1) (1)   is  air  density,  (1)   is  the  instantaneous (1) (2) (3) (1) deviation  vertical  wind  velocity,  (1) instantaneous  deviation  of  CO2  concentration,  (2)   is  the  latent  heat  of  vaporization,  (2) instantaneous  deviation  of  water  vapor  density  from  the  mean,    is  gross  primary  (3) productivity  (3)   is  the  (2)   is  the  (3) (2) (3) (2) (3) (2) (3) 268 Proceedings  of  the  International  Conference  on  Climate  Change,  Biodiversity  and  Ecosystem  Services  for  the Sustainable  Development  Goals  (SDGs):  Policy  and  Practice  27-29  June  2016,  Cha-am,  Phetchaburi,  Thailand and  (1) (2)   is  evapotranspiratio(n3. )D ata  acquisition   for  flux measurements  was  done  with  EddyPro  express  software  (open  source  version  6.0.0,  LI-COR  Bioscience  2010).  Raw  data  were  processed  to  half-hourly  averages  with  the  EddyPro  software.  In  this  study,  fluxes  data  uses  a  double  rotation  with  30  min  block  averaging.  Spikes  were  removed  by  statistical  tests  embed  in  the  software  6,  7.  Corrections  for  density  fluctuations  8  were  applied  during post-processing  to  the  half-hourly  averaged  data.  Spectral  correction  was  followed  those  described  by  9.  Periods  with  low  turbulence  conditions  were  excluded  based  on  friction  velocity  (u*<0.05  m/s)  by  ejection  data  were  small  turbulence  (applying  appropriate  corrections  for  site-specific  parameter).  The  amounts  of  ET  half-hourly  dataset  were  applied  from  Eqs  (2)  using  specific  heat  of  vaporization  10  and  gaps  were  filled  using  the mean  diurnal  variation  (MDV)  and  nonlinear  regression  method,  respectively  11. III.  RESULTS  AND  DISCUSSIONS A.Climate  conditions The  seasonal  patterns  of  climatic  variables  and  soil  water  content  are  shown  in  Fig.1.  The  results  of  daily  air  and  soil  temperatures,  precipitation  and  soil  water  content  during  June  2013  to  December  2015  are  shown  in  Fig. 2 .   Dai ly  ai r   and  soil  temperatures  varied  between  9.04  to  36.45°C  and  14.15  to  34.62°C  respectively.  The  highest air  and  soil  temperatures  were  observed  in  March,  April  and  May,  while  the  lowest  air  and  soil  temperatures  were  observed  in  December  and  January.  Both  were  following  the  seasonal  changes  respectively.  The  average  of  air  temperature  (24.68±3.82°C)  and  soil  temperature  (24.47±2.58°C)  were  similar;  moreover  the  most  values  of  minimum  of  soil  temperature  was  higher  than  minimum  of  air  temperature  throughout  the  year.  However  the  fluctuation  of  air  temperature  was  higher  than  soil  temperature  was  of  around  5%  during  study  period.  As  a  general  pattern,  rainfall  in  this  upland  dipterocarp  forest  started  during  May  and  endured  until  October,  thus  characterizing  a  rainy  season.  During  this  season  the  rainfall  was>100  mm.  The  rest  of  the  year  was  a  dry  season.  The  total  precipitation  in  2013,  2014  and  2015  were  816,  968  and  927 mm  respectively. )  latent  heat  ( (1) (2) (3) )  and  ecosystem  water  use  efficiency  ( (1) (2) )  were   (3) determined  5  as: 


Proceedings of International Conference on Climate Change, Biodiversity and Ecosystem Services for the Sustainable Development Goals : Policy and Practice 27-29 June 2016 at the Sirindhorn International Environmental Park, Cha-am, Phetchaburi, Thailand
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