Grant: Discovery Grants Program - Individual

Plant physiological processes are highly dynamic and can vary over space and time as plants respond to rapidly changing environmental conditions. As a result, modeling of carbon cycles requires parameterization of the land surface which is only possible using remote sensing because of its capacity to acquire data in synoptically and on a regular basis. Modelling gross primary production (GPP) using remote sensing is largely based on the relationship between plant physiological properties and foliage biochemical composition, which in turn influences the spectral response detected by remote sensors. My research program focuses on the development of functional relationships between vegetation reflectance (indicative of vegetation functioning), plant light use efficiency (LUE) and coincident measurements of carbon and water fluxes. The approach focuses on the determination and monitoring of LUE using the remote sensing derived photochemical reflectance index (PRI, (based on canopy reflectance at 531 and 570 nm) and other spectral indices. We will follow a number of critical lines of inquiry. We will undertake detailed spectral observations at a number of contrasting sites in Canada to develop a more complete understanding of the representativeness of these functional relationships across different vegetation types; Second we will investigate the role of vertical forest structure on the functional relationships, especially the impact of shadow fraction and internal crown shading, and finally we will fully integrate these functional relationships into models of GPP. Once developed these models will help quantity and monitor the carbon cycle at landscape and regional scales.