B065-0003
A new approach for estimating and modeling tree methane emissions

Friday, 11 December 2020
Poster
Nicholas D Ward1, Matthew Norwood2, Wenzhi Wang3, Ben P Bond-Lamberty4 and Nathan McDowell3, (1)Pacific Northwest National Laboratory, Marine Sciences Laboratory, Richland, WA, United States, (2)Pacific Northwest National Laboratory, Marine Sciences Laboratory, Sequim, WA, United States, (3)Pacific Northwest National Laboratory, Richland, WA, United States, (4)Pacific Northwest National Laboratory, Joint Global Change Research Institute, College Park, MD, United States
Abstract:
Methane (CH4) emissions from trees have recently been identified as an important, but poorly understood source of atmospheric CH4. We lack an understanding of both the magnitude of these emissions on a global scale and the mechanisms driving them. The highly variable nature of CH4 emissions measured from tree stems is most often attributed to environmental heterogeneity. Researchers in this relatively new field also use a variety of chamber designs that may also contribute to variability across studies, or even within a given study. Reducing the methodological variability of stem CH4 flux measurements may help elucidate the mechanisms behind stem gas exchange such as gas diffusion barriers and CH4 cycling across the soil to stem continuum.

Recent measurements made across a variety of coastal forests and species revealed that high internal stem CH4 concentrations are inversely correlated to low internal stem O2 saturation levels, indicating that stem CH4 and oxygen levels are coupled. CH4 concentrations were also correlated with stem density, implying that CH4 accumulates to a higher degree when the stem’s barrier to diffusion is greater. Therefore, we hypothesize that the rate of stem CH4 emissions can be modeled as a function of stem wood density, internal CH4 concentration, and stem O2 saturation. If true, stem emissions could be modeled based on these fairly simple measurements, eliminating the need to make chamber-based measurements similar to the state of the art in other fields such as oceanography.

We tested this hypothesis in two Pacific Northwest coastal forests. We utilized permanently installed collars on each tree to minimize error in chamber volumes and sealing. We simultaneously monitored CH4 and O2 concentrations and measured stem density with a resistance drill. We found that stem CH4 concentrations, O2 saturation, and wood density are significant predictors for stem CH4 emissions. We used these relationships to develop and parameterize a simple model for tree stem gas exchange and estimate CH­4 emissions. The measurements involved are rapid, enabling high spatiotemporal resolution studies. This simple tree stem gas exchange model could ultimately be incorporated into ecosystem models to improve predictions of methane cycling in terrestrial environments.

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