Evaluating Aboveground Terrestrial Carbon Flux as Ecosystem Planning Tool (Mt. Kenya Ecosystem)<br />Ochieng A. Adimo<br />
Outline of the presentation<br />Introduction<br />Objectives<br />Methods <br />Results and discussions<br />Acknowledgem...
Introduction<br />Presentation is  an evaluation of :<br />Terrestrial Carbon sink flux estimation using;<br />Net Primary...
Net Primary Production (NPP)<br />Carbon is removed from the atmosphere via photosynthesis by plants <br />           ecos...
Justification for using NPP – Demand and Supply<br />NPP is the “Common currency” for  <br />Climate Change, <br />Ecologi...
Conceptual framework<br />PEMs are based on the theory of light use efficiency (LUE)<br />Which states that :<br />“a rela...
Conceptual framework            Cont’d<br />PEMs usually require inputs of ;<br />Meteorological data : radiation, tempera...
Objectives<br />To assess Mt. Kenya vegetation carbon assimilation Potential by Net primary production Using CASA model<br...
Hypothesis<br /> CASA- can estimate Carbon flux variability in different vegetation using 30 M resolution Landsat 7 ETM <b...
Study Area<br />
Carnegie Ames Stanford Approach (CASA)  model<br /><ul><li>A numerical model of monthly fluxes of water, carbon and nitrog...
NPP = Sr* EVI *emax*T*W
Where Sr = 12 hrs surface solar irradiance
EVI = enhanced vegetation index
T = stress scalar temperature 30 years
W = stress scalar water deficit 30 years
emax = LUE term at 0.39gCMJ-1 PAR</li></li></ul><li>Where L is the canopy background adjustment that addresses non-linear,...
EVI modeling in ERDAS model maker<br />RED<br />BLUE<br />NIR<br />NIR<br />RED<br />
Thornewaite Monthly water balance model<br />Assume that air temperature is correlated with the integrated effects of net ...
Sample input data 30 years daily/monthly<br />
RESULTS THORNTHWAITE MODEL<br />
GIS MODELING<br />
CREAT RELATIONAL GEODATABASE<br />
Interpolate parameters to Raster-Spline<br />
Temperature scalar<br />
Land cover<br />Data Acquisition and processing<br />Landsat Thematic Mapper (TM) satellite (25/02/1987 & 14/02/2002)<br /...
Land use / land cover assessment based on Landscape metrics<br />The aim included;<br />To classify land use / land cover,...
Land cover/use<br />
Distribution of Mount Kenya vegetation cover<br />
Vegetation zonation<br />
Tree plantation spatial distributions of Mt. Kenya<br />
Mount Kenya Riverine networks of Mt. Kenya<br />
Human appropriation of net primary productivityHANPP<br />HANPP = NPP0-NPPt                             (1)<br />NPPo = NP...
HANPP<br />ΔNPPLC = NPP0 - NPPact                      ( 4)<br />HANPP = NPPh+ΔNPPLC                      (5)<br />Therefo...
Assumptions<br />Assumption 1: The imagery data taken in the dry season <br />when there are no crops in the field represe...
RIVER BASIN PLANNING <br />
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Evaluating aboveground terrestrial carbon flux as ecosystem planning

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Evaluating aboveground terrestrial carbon flux as ecosystem planning

  1. 1. Evaluating Aboveground Terrestrial Carbon Flux as Ecosystem Planning Tool (Mt. Kenya Ecosystem)<br />Ochieng A. Adimo<br />
  2. 2. Outline of the presentation<br />Introduction<br />Objectives<br />Methods <br />Results and discussions<br />Acknowledgement<br />
  3. 3. Introduction<br />Presentation is an evaluation of :<br />Terrestrial Carbon sink flux estimation using;<br />Net Primary production (NPP)<br /> Production Efficiency Models (PEMs) CASA , GLOPEM , TURC , C-Fix , MODIS, BEAMS (McCallum et al., 2009)<br />Vegetation remote sensing<br />General circulation model downscaling SDSM<br />GIS Interpolation of meteorological data<br />
  4. 4. Net Primary Production (NPP)<br />Carbon is removed from the atmosphere via photosynthesis by plants <br /> ecosystem<br />– Gross Primary Production GPP ( g C M2 )<br /> Autotrophic respiration (Ra) ( g C M2 )<br /> NPP ( g C M2 ) = GPP - Ra<br />Annual amount of vegetation produced on land in terms of elemental carbon.<br />
  5. 5. Justification for using NPP – Demand and Supply<br />NPP is the “Common currency” for <br />Climate Change, <br />Ecological, & <br />Economic Assessment. (Imhoff et al. 2010)<br />Demand for NPP strongly influences land use/land cover change and land management policy.<br />Agricultural versus ‘natural systems’ - Conflicting needs; energy production<br /> versus conservation of biodiversity<br />HUMAN APPROPRIATION OF NPP (HANPP)<br />
  6. 6. Conceptual framework<br />PEMs are based on the theory of light use efficiency (LUE)<br />Which states that :<br />“a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at canopy level.”<br />(McCallum et al., 2009)<br />At leaf level the relation is not linear<br />
  7. 7. Conceptual framework Cont’d<br />PEMs usually require inputs of ;<br />Meteorological data : radiation, temperature , moisture (VPD)<br />Satellite- derived fraction of absorbed photosynthetically available radiation (FAPAR). <br />
  8. 8. Objectives<br />To assess Mt. Kenya vegetation carbon assimilation Potential by Net primary production Using CASA model<br />To Quantify Human Appropriation of Net Primary Production in Mt. Kenya Ecosystem<br />
  9. 9. Hypothesis<br /> CASA- can estimate Carbon flux variability in different vegetation using 30 M resolution Landsat 7 ETM <br />
  10. 10. Study Area<br />
  11. 11. Carnegie Ames Stanford Approach (CASA) model<br /><ul><li>A numerical model of monthly fluxes of water, carbon and nitrogen in terrestrial ecosystems.
  12. 12. NPP = Sr* EVI *emax*T*W
  13. 13. Where Sr = 12 hrs surface solar irradiance
  14. 14. EVI = enhanced vegetation index
  15. 15. T = stress scalar temperature 30 years
  16. 16. W = stress scalar water deficit 30 years
  17. 17. emax = LUE term at 0.39gCMJ-1 PAR</li></li></ul><li>Where L is the canopy background adjustment that addresses non-linear, differential NIR and red radiant transfer through a canopy, and <br />C1, C2 are the coefficients of the aerosol resistance term, which uses the blue band to correct for aerosol influences in the red band. <br />The coefficients adopted in the <br />MODIS-EVI algorithm are; L=1, C1 = 6, C2 = 7.5, and G (gain factor) = 2.5.<br />EVI = 2.5*(B4-B3)/ (B4+6.0*B3-7.5B1+1)<br />
  18. 18. EVI modeling in ERDAS model maker<br />RED<br />BLUE<br />NIR<br />NIR<br />RED<br />
  19. 19. Thornewaite Monthly water balance model<br />Assume that air temperature is correlated with the integrated effects of net radiation and other controls of evapotranspiration, <br />Temperature<br />water<br />
  20. 20.
  21. 21. Sample input data 30 years daily/monthly<br />
  22. 22. RESULTS THORNTHWAITE MODEL<br />
  23. 23. GIS MODELING<br />
  24. 24. CREAT RELATIONAL GEODATABASE<br />
  25. 25. Interpolate parameters to Raster-Spline<br />
  26. 26. Temperature scalar<br />
  27. 27.
  28. 28. Land cover<br />Data Acquisition and processing<br />Landsat Thematic Mapper (TM) satellite (25/02/1987 & 14/02/2002)<br />Aster extracted land cover maps<br /> SRTM data<br />ERDAS<br />ARCGIS<br />FRAGSTAT<br />
  29. 29. Land use / land cover assessment based on Landscape metrics<br />The aim included;<br />To classify land use / land cover, and quantify function and spatial data that defines initial conditions of the landscape.<br />
  30. 30. Land cover/use<br />
  31. 31.
  32. 32. Distribution of Mount Kenya vegetation cover<br />
  33. 33. Vegetation zonation<br />
  34. 34. Tree plantation spatial distributions of Mt. Kenya<br />
  35. 35. Mount Kenya Riverine networks of Mt. Kenya<br />
  36. 36. Human appropriation of net primary productivityHANPP<br />HANPP = NPP0-NPPt (1)<br />NPPo = NPP before human <br />NPPt = current management<br />And, NPPt = NPPact – NPPh (2)<br />Thus NPPact = NPPt + NPPh (3)<br />
  37. 37. HANPP<br />ΔNPPLC = NPP0 - NPPact ( 4)<br />HANPP = NPPh+ΔNPPLC (5)<br />Therefore,<br /> HANPP = NPPh+ΔNPPLC = NPP0-NPPt (6)<br />and NPP = Sr EVI emaxTW <br />(Karl-Heinz Erb et al., 2009)<br />
  38. 38. Assumptions<br />Assumption 1: The imagery data taken in the dry season <br />when there are no crops in the field represents NPPt .<br />Assumption 2:Above ground NPP can estimate HANPP used for <br />approximating ecosystem energetic (energy flow).<br />
  39. 39.
  40. 40.
  41. 41.
  42. 42. RIVER BASIN PLANNING <br />
  43. 43. Aggregate HANPP of indigenous vegetation per river basin<br />
  44. 44. Land use /land cover in river basin 11 <br />
  45. 45. Key finding<br />Satellite observed canopy greenness EVI is useful as a variable to help account for CO2 sink in Mt. Kenya<br />Indigenous species are more resilient<br />Agricultural land have great potential for sequestration<br />CASA model captures landscape scale variability<br />Thornewaite water balance model show consistent water deficit maps.<br />CASA model can be used for annual Co2 fixation estimation in mount Kenya<br />
  46. 46. Acknowledgement<br />
  47. 47. THANK YOU<br />

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