Graduate Thesis Or Dissertation
 

Remote Sensing of Photosynthetic Light-use Efficiency of the Amazonian Rainforests

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  • When conditions for photosynthesis are unfavorable, excess solar radiation is dissipated as heat from leaves through a shift in xanthophyll pigments that result in reflecting rather than absorbing light at some wave lengths. The shift in xanthophyll pigments can be quantified as a photochemical reflectance index (PRI) by monitoring specific wavelengths in the visible part of the spectrum.In my research, I applied the photochemical reflectance index to assess changes in the degree of stress on tropical forests at two extremely different spatial resolutions: first, across the entire Amazon Basin using satellite-borne sensors, and secondly, above an individual stand of trees using a spectroradiometer mounted on a tower.The basin-wide analysis took advantage of NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) that sequentially monitored 1 x 1 km pixels at different viewing angles from two satellites. To correct for varying atmospheric conditions we used the most sophisticated algorithm available (Multi-angle Implementation of Atmospheric Correction Algorithm - MAIAC). With these combined data sets, I was able to discern large differences in photosynthetic efficiency occurred at monthly intervals between 2000 and 2012 across the entire Amazon Basin.The analysis of PRI from an individual stand was limited to a 17-day period at the end of the dry period and beginning of the wet in the year 2012. There was good agreement between average PRI reflectance patterns from three separate tree canopies with measured eddy-flux measurements of gross primary production over the selected period (r2 = 0.65, P <0.05). Moreover, the analysis demonstrated that the sunlit leaves were the ones most responsive to variation in climatic conditions whereas the reflectance patterns from more shaded parts of the canopy were relatively stable.The significance of my research is that it shows physiological responses to stress occur and can be monitored even if more conventional reflectance indices show no change. This indicates that we have much greater opportunities to explain and predict how forests are responding to climate change than previously thought.
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