Leaf Chlorophyll Content as a Proxy for Photosynthetic Parameters for Estimating Carbon and Water Fluxes at a Forest Site

Chlorophyll is the main light-harvesting pigment in leaves to support photosynthesis and also reflects the seasonal variations in the supply of nitrogen for photosynthetic enzymes. In this study, we explore the feasibility of using leaf chlorophyll content (Chlleaf) as a proxy for the leaf maximum carbonxylation rate at 25 °C ( ) for the purpose of improving carbon and water cycle estimation. Measurements of Chlleaf and were made in a decidous forest stand near Borden in Northern Ontario, Canada, which was equiped with eddy covariance instruments for measuring carbon and water fluxes. Based on the measurements from four broadleaf deciduous species, a linear relationship is develoepd between Chlleaf and . Compared to the prescribed constant values, derived from Chlleaf shows pronounced seasonal variations and improves the simulations of GPP and ET by 5% and 3%, respectively. The most significant improvements are found in spring and fall, when the errors in modelled GPP are reduced from 4.71 to 0.69 g/m2/day and from 2.4 to 1.16 g/m2/day, respecively. Errors in ET estimation are correspondingly reduced from 0.85 to 0.61 mm/day and from 0.40 to 0.33 mm/day in spring and autumn, respectively. A two-leaf upscaling scheme was used to account for the uneven distribution of incoming solar irradiance inside canopies and the accompanied physiological differences between leaves. One μg/cm2 of Chlleaf corresponds to 1.3 and 0.77 μmol/m2/s of in sunlit leaves and shaded leaves, respectively. The seasonal average rate of photosynthesis, transpiration, water use efficiency and light use efficiency of sunlit leaves are 2.7, 15, 0.19 and 0.3 times those of shaded leaves. For the first time, this sutdy incorporates chlorophyll in terrestrial biosphere models at a forest stand. Since it is feasible to derive leaf chlorophyll information using remote sensing means, this study would have profound implications on large-scale carbon and water fluxes estimation.