2024 Abstracts

Modeling Temperature Sensitivity of Soil Respiration from Two Field-Warming Experiments in Tropics


Debjani Sihi1* ([email protected]), Eric Davidson2, Andrew Nottingham3, Tana Wood4, Jianqiu Zheng5, Michael Weintraub6, Sasha Reed7, Jennifer Pett-Ridge8


1Emory University, Atlanta, GA; 2Center for Environmental Science, Appalachian Laboratory, University of Maryland–Frostburg, MD; 3University of Leeds, Woodhouse, United Kingdom; 4International Institute of Tropical Forestry, U.S. Forest Service; 5Pacific Northwest National Laboratory, Richland, WA; 6University of Toledo, Toledo, OH; 7Southwest Biological Science Center, U.S. Geological Survey, Moab, UT; 8Lawrence Livermore National Laboratory, Livermore, CA


Soil respiration is the second largest terrestrial carbon (C) flux. Understanding responses of soil respiration to warming is crucial for evaluating carbon-climate feedback. Warming response of soil respiration is typically modeled using a Q10 function. Generally, observations of the apparent Q10 of soil respiration are higher for cool vs. warm-climate ecosystems, reflecting expected biophysical controls of Arrhenius kinetics. However, results from two tropical field warming experiments contradict this expectation, both observing extraordinarily high soil respiration responses to in situ warming. Researchers systematically represent the potentially confounding effects of temperature sensitivity of enzymatic reactions, changes in the microbial enzymatic capacity, and substrate supply as they affect microbial decomposition of soil C in tropical forests under warming. Researchers are optimizing the Dual Arrhenius Michaelis-Menten (DAMM) model using data generated from the Soil Warming Experiment in lowland tropical forests in Panama and Tropical Responses to Altered Climate Experiment in Puerto Rico. By including simple representations of measured warming-induced changes in microbial biomass, which affects enzymatic capacity, and soil moisture, which affects substrate diffusion, researchers show that the observed increased soil respiration with warming does not necessarily reflect a change in activation energy (Ea), but rather can primarily be the consequence of increased microbial enzymatic capacity. In contrast, optimization of the model without representation of changing microbial biomass would require a higher Ea in the warmed plots, which is unlikely. The parsimonious modular approach allows researchers to attribute agreement or disagreement of model outputs with observations and specific model functions, as well as identify model structures necessary for skillfully representing temperature-sensitive processes from individual plots to Earth system scales.