Impact of Forest Structure on Net Ecosystem Productivity Using Airborne Eddy Covariance and LiDAR Canopy Height

Accurate measurement and interpretation of the variation in net ecosystem productivity (NEP) is critical for studying the global carbon cycle and predicting the terrestrial carbon sink. Forest structure plays a significant role in governing NEP since it affects both plant physiology, through light availability within canopies and rainfall interception, as well as biogeochemical cycles through soil temperature and litter input. Current ecosystem models have shown that annual, net NEP is negatively correlated with canopy height, since heterotrophic respiration increases with canopy height and buffers net primary productivity. However, the relationship between NEP and canopy height has rarely been investigated with field measurements such as eddy-covariance (EC) techniques. One reason for this gap is that the widely-used tower-based EC only provides fluxes at a single point rather than across a canopy height gradient. In contrast, airborne EC is able to map gradients in surface exchange at relatively fine scales and across large spatial domains. In this study, we bridge three products funded by NASA Carbon Monitoring System (CMS) including LiDAR-based canopy height and forest cover maps, and CO2 exchange from NASA Carbon Airborne Flux Experiment (CARAFE), to investigate the relationship between NEP and canopy height. We use data from State of Maryland as a case study since the NASA CARAFE has successfully acquired fluxes across the eastern U.S., providing daily peak NEP across a diverse canopy height gradient. Our results demonstrate how spatial variability of daily peak NEP is related to canopy height and how this relationship compares with the results from current ecosystem models. This work may create the capability for estimating NEP across a larger spatial scale using incoming data from the Global Ecosystem Dynamics Investigation (GEDI).