Vertical attenuation of photosynthetically active radiation in closed forest canopies: average trends, patterns of variation and model implications

Abstract:

Vegetation structure affects the disposition of radiation, which controls the extent and location of light absorption and carbon assimilation. The pattern of vertical light attenuation both reflects and can be used to model these processes. However, the lack of direct observations of in-canopy light means that the vertical light profiles are commonly assumed.

We quantified the 3-D distribution in canopy transmittance of global (PAR, 400-700 nm) radiation in 23 forests varying by crown type, latitude and development stage. Measurements were acquired under clear conditions using quantum sensors deployed from tower cranes, in-canopy balloons or telescoping poles. We classified profile shapes, identified distinct vertical zones and quantified key profile parameters within and among stands.

Variation in vertical light profiles depends primarily on crown type and development stage. While the average patterns with height are generally smooth, individual profiles in conifer stands often show abrupt bright-dark transitions compared with those in broadleaved forests. Spatial variation is highest at canopy levels where the transmittance gradient is steepest and absorption is maximal. The frequency distribution of transmittance is never Gaussian and changes with height: there is marked skewness at all levels, changing from positive in the understory to negative in the overstory. The patterns of the mean attenuation and its variation can be used to define vertical light environment zones that are reliably dark (“dim”), reliably bright (“bright”) or variable in space and changing rapidly with height (“transition”). The vertical limits of these zones change as stands develop. We found models of assimilation based on mean transmittance profiles are significantly biased relative to those based on actual distributions.These results have implications for how canopy light environments are conceptualized, estimated and modelled. Spatial variability is enormous but has general patterns. Height-specific remote sensing measurements may aid to quantify this variation. Finally, the specifics of variation are important for accurate model representation.