Forest Canopy Structural Complexity and Light Absorption Relationships at the Subcontinental Scale

Understanding how the physical structure of forest canopies influences light absorption is a long‐standing area of inquiry fundamental to the physical sciences, including the modeling and interpretation of biogeochemical cycles. Conventional measures of forest canopy structure used to infer canopy light absorption are often limited to leaf or vegetation area indexes. However, LiDAR‐derived measures of canopy structural complexity (CSC) that describe the arrangement of vegetation may improve prediction of canopy light absorption by providing novel information on canopy‐light interactions not regulated by leaf area alone. We measured multiple indexes of CSC, vegetation area index (VAI), and the fraction of photosynthetically active radiation absorbed (fPAR) across the eastern United States using portable canopy LiDAR to evaluate how different canopy structural attributes relate to fPAR. Our survey included sites from the National Ecological Observation Network and university field stations. Measures of CSC were more strongly coupled with fPAR under high light (>1,000 μmol m−2 s−1 PAR). Under low light conditions, when diffuse light predominates, light scattering weakens the dependency of fPAR on CSC. A multivariate model including CSC parameters and VAI explains ~89% of the intersite variance in fPAR, an improvement of over a VAI only linear model (r2 = 0.73). The inclusion of CSC metrics in canopy light absorption models could increase confidence in predictions of biogeochemical cycles and energy balance. Plain Language Summary Our work shows that it is not only how many leaves there are in a forest that determines how much light the forest can absorb, but also how those leaves are arranged. More complex forests are able to more thoroughly absorb light. Key Points We use terrestrial LiDAR to quantify canopy structural complexity at eight National Ecological Network (NEON) and three university field sites Canopy structural complexity (CSC) metrics and vegetation area index (VAI) explained 89% of the variance in light absorption among sites Multidimensional descriptions of CSC, if scalable, may provide a basis for better representation of light absorption in ecosystem models