2. Outline of the presentation Introduction Objectives Methods Results and discussions Acknowledgement
3. Introduction Presentation is an evaluation of : Terrestrial Carbon sink flux estimation using; Net Primary production (NPP) Production Efficiency Models (PEMs) CASA , GLOPEM , TURC , C-Fix , MODIS, BEAMS (McCallum et al., 2009) Vegetation remote sensing General circulation model downscaling SDSM GIS Interpolation of meteorological data
4. Net Primary Production (NPP) Carbon is removed from the atmosphere via photosynthesis by plants ecosystem â Gross Primary Production GPP ( g C M2 ) Autotrophic respiration (Ra) ( g C M2 ) NPP ( g C M2 ) = GPP - Ra Annual amount of vegetation produced on land in terms of elemental carbon.
5. Justification for using NPP â Demand and Supply NPP is the âCommon currencyâ for Climate Change, Ecological, & Economic Assessment. (Imhoff et al. 2010) Demand for NPP strongly influences land use/land cover change and land management policy. Agricultural versus ânatural systemsâ - Conflicting needs; energy production versus conservation of biodiversity HUMAN APPROPRIATION OF NPP (HANPP)
6. Conceptual framework PEMs are based on the theory of light use efficiency (LUE) Which states that : âa relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at canopy level.â (McCallum et al., 2009) At leaf level the relation is not linear
7. Conceptual framework Contâd PEMs usually require inputs of ; Meteorological data : radiation, temperature , moisture (VPD) Satellite- derived fraction of absorbed photosynthetically available radiation (FAPAR).
8. Objectives To assess Mt. Kenya vegetation carbon assimilation Potential by Net primary production Using CASA model To Quantify Human Appropriation of Net Primary Production in Mt. Kenya Ecosystem
9. Hypothesis CASA- can estimate Carbon flux variability in different vegetation using 30 M resolution Landsat 7 ETM
19. Thornewaite Monthly water balance model Assume that air temperature is correlated with the integrated effects of net radiation and other controls of evapotranspiration, Temperature water
28. Land cover Data Acquisition and processing Landsat Thematic Mapper (TM) satellite (25/02/1987 & 14/02/2002) Aster extracted land cover maps SRTM data ERDAS ARCGIS FRAGSTAT
29. Land use / land cover assessment based on Landscape metrics The aim included; To classify land use / land cover, and quantify function and spatial data that defines initial conditions of the landscape.
36. Human appropriation of net primary productivityHANPP HANPP = NPP0-NPPt (1) NPPo = NPP before human NPPt = current management And, NPPt = NPPact â NPPh (2) Thus NPPact = NPPt + NPPh (3)
37. HANPP ÎNPPLC = NPP0 - NPPact ( 4) HANPP = NPPh+ÎNPPLC (5) Therefore, HANPP = NPPh+ÎNPPLC = NPP0-NPPt (6) and NPP = Sr EVI emaxTW (Karl-Heinz Erb et al., 2009)
38. Assumptions Assumption 1: The imagery data taken in the dry season when there are no crops in the field represents NPPt . Assumption 2:Above ground NPP can estimate HANPP used for approximating ecosystem energetic (energy flow).
45. Key finding Satellite observed canopy greenness EVI is useful as a variable to help account for CO2 sink in Mt. Kenya Indigenous species are more resilient Agricultural land have great potential for sequestration CASA model captures landscape scale variability Thornewaite water balance model show consistent water deficit maps. CASA model can be used for annual Co2 fixation estimation in mount Kenya