Estimating daytime subcanopy respiration from conditional sampling methods applied to multi-scalar high frequency turbulence time series

This study presents a new method to estimate daytime respiration from the subcanopy of forests directly from conventional eddy covariance (EC) measurements. The method primarily considers the respiration signal from root, litter and microbial respiration, which are known to be the main components of ecosystem respiration, Re, as well as decomposition of coarse and fine woody detritus, and respiration from low understory vegetation (forbs, herbs and grasses). The conceptual framework is based on the premise that upward moving air parcels carry a specific and unambiguous signal in their CO2 and water vapour composition, which can be separated and distinguished into respiration and photosynthesis. The model employed a combination of conditional sampling methods, quadrant analysis and relaxed eddy accumulation with hyperbolic deadbands to identify respiration events and to quantify their flux contribution. Datasets from five sites, most of which had multiple sampling heights, were selected to test this technique among contrasting ecosystems and canopy structures.