2024 journal article

Reconciling Top‐Down and Bottom‐Up Estimates of Ecosystem Respiration in a Mature Eucalypt Forest

Journal of Geophysical Research: Biogeosciences.

By: N. Noh *, A. Renchon *, J. Knauer *, V. Haverd *, J. Li *, A. Griebel *, C. Barton *, J. Yang * ...

Source: ORCID
Added: October 15, 2024

Abstract Ecosystem respiration (R eco ) arises from interacting autotrophic and heterotrophic processes constrained by distinct drivers. Here, we evaluated up‐scaling of observed components of R eco in a mature eucalypt forest in southeast Australia and assessed whether a land surface model adequately represented all the fluxes and their seasonal temperature responses. We measured respiration from soil (R soil ), heterotrophic soil microbes (R h ), roots (R root ), and stems (R stem ) in 2018–2019. R eco and its components were simulated using the CABLE–POP (Community Atmosphere‐Biosphere Land Exchange–Population Orders Physiology) land surface model, constrained by eddy covariance and chamber measurements and enabled with a newly implemented Dual Arrhenius and Michaelis‐Menten (DAMM) module for soil organic matter decomposition. Eddy‐covariance based R eco (R eco.eddy , 1,439 g C m −2 y −1 ) was slightly higher than the sum of the respiration components (R eco.sum, 1,295 g C m −2 y −1 ) and simulated R eco (1,297 g C m −2 y −1 ). The largest mean contribution to R eco was from R soil (64%) across seasons. The measured contributions of R h (49%), R root (15%), and R stem (22%) to R eco.sum were very close to model outputs of 46%, 11%, and 22%, respectively. The modeled R h was highly correlated with measured R h (R 2 = 0.66, RMSE = 0.61), empirically validating the DAMM module. The apparent temperature sensitivities (Q 10 ) of R eco were 2.22 for R eco.sum , 2.15 for R eco.eddy , and 1.57 for CABLE‐POP. This research demonstrated that bottom‐up respiration component measurements can be successfully scaled to eddy covariance‐based R eco and help to better constrain the magnitude of individual respiration components as well as their temperature sensitivities in land surface models.