New Theory Resolves the Non-Monotonic Temperature Response of Biogeochemical Reaction Rates
With increasing temperature, biogeochemical reaction rates are often observed to first increase, then plateau, and finally drop to zero. Various empirical functions and mechanistic models have been developed to represent this fundamental process. Based on first principles, we developed a chemical kinetics theory that not only succeeded at capturing this nonmonotonic relationship between temperature and biochemical reaction rates but also revealed that the apparent optimal temperature where biochemical reaction rates peak is a function of substrate type and availability.
Our theory predicts that (1) the reversible transition between active and inactive enzyme conformation states leads to the non-monotonic temperature response of biochemical rates; (2) the substrate affinity parameter has an Arrhenius-type temperature dependence; (3) for a given biochemical reaction, increasing substrate availability shifts the apparent optimal temperature to higher values; and (4) an organism’s optimal temperature shifts with changing substrate types. This study also developed a framework to upscale temperature sensitivity from a single biochemical reaction to a whole organism or population.
How biogeochemical reaction rates respond to temperature changes is critical for biogeochemical modeling. Many current empirical functions and mechanistical models have been proposed to represent these temperature sensitivities. By combining the law of mass action, von Smoluchowski's diffusion-limited chemical reaction theory, and Eyring’s transition state theory, we here developed a chemical kinetics theory to describe how the rates of an enzymatic reaction respond non-monotonically to temperature. The theory reveals that (1) the reversible transition between active and inactive enzyme conformation states leads to a non-monotonic temperature response of biochemical rates; (2) the substrate affinity parameter follows an Arrhenius-type temperature dependence; (3) high substrate availability will shift the apparent optimal temperature towards higher values; and (4) shifts of substrate type will also shift the apparent optimal temperature. We expect that wider application of this theory will lead to improved modeling of how biogeochemical rates respond to changes in temperature, including microbial adaptation and acclimation under climate warming.