Leaf age and canopy structure co-dominant canopy spectral signatures and photosynthesis: A case study in sub-tropical evergreen forests

Evergreen forests make up a large portion of forest ecosystem in the world, and play vital ecosystem goods and services that are essential for human well-being. Remote sensing (RS) surface reflectance data and eddy covariance (EC)-derived fluxes observations provide viable approaches to monitor the spatiotemporal dynamics of forests over large areas. Due to its unique feature of perpetual greenness, understanding the factors that contributes to the variation of evergreen forests canopy dynamics to remote sensing signals and canopy gross primary production (GPP) are critical to infer their ecosystem functions.

Leaf age is not only an important factor in controlling leaf optical properties, but also an important factor controlling leaf maximum carboxylation rate (V_cmax25) in evergreen forests. Leaf optical properties (including leaf reflectance and transmittance, LOP) shows leaf age dependence due to changes in leaf biochemistry properties (pigment content, leaf internal anatomy, and water content) and impacts canopy spectral signals. Leaf V_cmax25 which is a key biotic factor prescribed in terrestrial ecosystem models (TEMs) also shows leaf age dependence. Leaf V_cmax25 determines CO₂ assimilation rates and leaf stomata conductivity for water transport, but the paucity of its measurements has long plagued the simulation of fluxes.Beer's law is widely applied in most TEMs that employ the Farquhar leaf scale mechanistic model of CO₂ assimilation. Beer's law brings large error into GPP estimation without consideration of the impact of canopy gap on canopy radiative transfer modeling and sunlit/shaded leaf fraction estimation. Here, we provide an alternative option for the representation of canopy 3-D structure in TEMs which improves the GPP estimation significantly compared with Beer's law.

In this study, we use physically-based models to study the impacts of leaf age on canopy reflectance and canopy photosynthesis and proved that leaf age and canopy structure are both important factors that needed to be considered to improve the biophysical interpretation of the seasonal variation in canopy reflectance and GPP.