The Role of Spatial Averaging Scale in Leaf?To?Canopy Scaling of Non?Linear Processes in Homogeneous Canopies

In formulating canopy biophysical models of non-linear processes like photosynthesis and stomatal conductance, it is necessary to average inputs over some representative spatial scale (sub-leaf, leaf, sub-crown, crown, whole-canopy, etc.). The consequences the choice averaging often unclear due inability experiments robustly quantify fluxes across full range relevant length scales. This study quantified errors in canopy-level flux simulations input radiative using a detailed leaf-resolving model that represents three-dimensional geometry at sub-leaf level. Simulations were performed for an array homogeneous canopies differing leaf area index (LAI), height, inclination angle distribution, size, shape, size sub-sections relative total size. Canopy based on compared with derived from single leaves, sunlit shaded portions separately (i.e., two-leaf model), multiple vertical layers classes multi-layer model). Canopy-level found be influenced by chosen other variables tested, especially LAI. Averaging approaches inherent currently used most resulted low or moderate over-estimates under many conditions tested. Surprisingly, entire leaves model) had potential create largest errors. result underscored need sub-divide models.