Chen, B; Arain, MA; Chen, JM; Wang, SQ; Fang, HL; Liu, ZH; Mo, G; Liu, J (2020). Importance of Shaded Leaf Contribution to the Total GPP of Canadian Terrestrial Ecosystems: Evaluation of MODIS GPP. JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES, 125(10), e2020JG005917.

Terrestrial gross primary productivity (GPP) quantifies the photosynthetic uptake by vegetation and it is the largest component of the terrestrial carbon cycle. The separation of sunlit and shaded leaves has been shown to be an effective leaf-to-canopy upscaling method for modeling vegetation GPP. In this study, the performance of the Integrated Carbon-Canadian Land Surface Scheme (IC-CLASS) based on Farquhar's photosynthetic model and the two-leaf approach was compared against that of Moderate Resolution Imaging Spectroradiometer (MODIS) GPP algorithm using the light use efficiency (LUE) approach, validated with eddy covariance (EC) measured GPP over a variety of terrestrial ecosystems in Canada. There were systematic differences between the IC-CLASS simulated GPP and the MODIS GPP product in spatial distribution patterns. The differences were due to inherent shortcomings of the LUE modeling approach where a constant maximum LUE value is specified for each biome type, ignoring the variation of shaded leaf contribution to total GPP. The IC-CLASS model separates the sunlit and shaded leaves and the bias in simulating GPP was minimized. The IC-CLASS performed better than the MODIS GPP algorithm compared with monthly and annual GPP derived from EC flux data at 13 Canadian Carbon Program sites. The differences between the IC-CLASS and the MODIS GPP estimates were larger in more clumped canopies (i.e. forests), because of the increase in the shaded leaf fraction. Different LUEs in sunlit and shaded portions of the canopy should be considered for effective and reliable estimation of GPP at regional scale.