The importance of characterizing canopy architecture in estimating global terrestrial gross primary productivity

Sunlit and shaded leaf stratification is one of the most effective ways to upscale from leaf to canopy in modeling vegetation photosynthesis. Professor John Norman's seminal work (e.g. Norman, 1982) in canopy-level photosynthesis modeling has made profound impacts in micrometeorology and global ecology. The Boreal Ecosystem Productivity Simulator (BEPS), initially developed for regional carbon cycle modeling using remote sensing inputs, makes use of Norman's sunlit/shaded leaf separation methodology, and this methodology has been extensively validated using CO2 flux measurements in Canada and China for boreal, temperate and subtropical ecosystems. It is demonstrated that for clumped canopies such as boreal conifer forests, shaded leaves overall contribute more than sunlit leaves to the total canopy photosynthesis because of the relatively large shaded leaf fraction in clumped canopies. Our studies reinforced the importance of separating sunlit and shaded leaves in canopy-level photosynthesis modeling.

BEPS has now been used for global terrestrial productivity and carbon cycle simulations. In addition to the required input of leaf area index (LAI) to the model, we also used the first ever global map of the foliage clumping index derived from the multi-angle satellite sensor POLDER at 7 km resolution. The clumping index quantifies the degree of the deviation of leaf spatial distribution from the random case, and it determines the sunlit and shaded leaf area indices for a given LAI. Global simulations of the terrestrial gross primary productivity in 2003 at 1 degree resolution suggest that characterizing the three-dimensional vegetation structure using the clumping index within the sunlit/shaded leaf stratification framework made large differences (up to 25%) from the case when no clumping is assumed (clumping index=1). The largest differences are found in forest ecosystems where the canopies are most clumped.