A large fraction of plant litter comprises recalcitrant aromatic compounds (lignin and other phenolics). Quantifying the fate of aromatic compounds is difficult, because oxidative degradation of aromatic carbon (C) is a costly but necessary endeavor for microorganisms, and we do not know when gains from the decomposition of aromatic C outweigh energetic costs.
To evaluate these tradeoffs, we developed a litter decomposition model in which the aromatic C decomposition rate is optimized dynamically to maximize microbial growth for the given costs of maintaining ligninolytic activity. We tested model performance against >\uffe2\uff80\uff89200 litter decomposition datasets collected from published literature and assessed the effects of climate and litter chemistry on litter decomposition.
The model predicted a time\uffe2\uff80\uff90varying ligninolytic oxidation rate, which was used to calculate the lag time before the decomposition of aromatic C is initiated. Warmer conditions increased decomposition rates, shortened the lag time of aromatic C oxidation, and improved microbial C\uffe2\uff80\uff90use efficiency by decreasing the costs of oxidation. Moreover, a higher initial content of aromatic C promoted an earlier start of aromatic C decomposition under any climate.
With this contribution, we highlight the application of eco\uffe2\uff80\uff90evolutionary approaches based on optimized microbial life strategies as an alternative parametrization scheme for litter decomposition models.
A large fraction of plant litter comprises recalcitrant aromatic compounds (lignin and other phenolics). Quantifying the fate of aromatic compounds is difficult, because oxidative degradation of aromatic carbon (C) is a costly but necessary endeavor for microorganisms, and we do not know when gains from the decomposition of aromatic C outweigh energetic costs.
To evaluate these tradeoffs, we developed a litter decomposition model in which the aromatic C decomposition rate is optimized dynamically to maximize microbial growth for the given costs of maintaining ligninolytic activity. We tested model performance against >\uffe2\uff80\uff89200 litter decomposition datasets collected from published literature and assessed the effects of climate and litter chemistry on litter decomposition.
The model predicted a time\uffe2\uff80\uff90varying ligninolytic oxidation rate, which was used to calculate the lag time before the decomposition of aromatic C is initiated. Warmer conditions increased decomposition rates, shortened the lag time of aromatic C oxidation, and improved microbial C\uffe2\uff80\uff90use efficiency by decreasing the costs of oxidation. Moreover, a higher initial content of aromatic C promoted an earlier start of aromatic C decomposition under any climate.
With this contribution, we highlight the application of eco\uffe2\uff80\uff90evolutionary approaches based on optimized microbial life strategies as an alternative parametrization scheme for litter decomposition models.