Ground-Based Lidar Measurements of Forest Canopy Structure as Predictors of Net Primary Production Across Successional Time

Abstract:

Forest canopy structure is a key predictor of gas exchange processes that control carbon (C) uptake, including the allocation of photosynthetically fixed C to new plant biomass growth, or net primary production (NPP). Prior work suggests forest canopy structural complexity (CSC), the arrangement of leaves within a volume of canopy, changes as forests develop and is a strong predictor of NPP. However, the expressions of CSC that best predict NPP over decadal to century timescales is unknown.

Our objectives were to use multiple remote sensing observations to characterize forest canopy structure in increasing dimensional complexity over a forest age gradient, and to identify which expressions of physical structure best served as proxies of NPP. The study at the University of Michigan Biological Station in Pellston, MI, USA uses two parallel forest chronosequences with different harvesting and fire disturbance histories and includes three old-growth ecosystems varying in canopy composition.

We have derived several expressions of 2-D and 3-D forest canopy structure from hemispherical images, a ground-based portable canopy lidar (PCL), and a 3-D terrestrial lidar scanner (TLS), and are relating these structural metrics with NPP and light and nitrogen allocation within the canopy. Preliminary analysis shows that old-growth stands converged on a common mean CSC, but with substantially higher within-stand variation in complexity as deciduous tree species increased in forest canopy dominance. Forest stands that were more intensely disturbed were slower to recover leaf area index (LAI) as they regrew, but 2-D measures of CSC increased similarly as forests aged, regardless of disturbance history. Ongoing work will relate long-term trends in forest CSC with NPP and resource allocation to determine which forest structure remote sensing products are most useful for modeling and scaling C cycling processes through different stages of forest development.