Warming alters soil microbial traits through ecological and evolutionary processes, directly influencing the decomposition of organic matter, which significantly affects global soil carbon emissions. Yet, soil carbon models largely ignore these processes and their implications for global responses to warming. Here, we incorporate eco\uffe2\uff80\uff90evolutionary theory into a mechanistic model describing microbial soil carbon decomposition to address the question of whether such processes could have consequential effects on climate carbon feedbacks globally. We assume that a key trait of microbes, their resource allocation to production of exoenzymes (which facilitate decomposition of organic matter)\uffe2\uff80\uff94is optimized to environmental temperatures by natural selection. We find that eco\uffe2\uff80\uff90evolutionary optimization results in microbes allocating more resources to enzyme production under warming. When applied at the global scale, eco\uffe2\uff80\uff90evolutionary optimization enhances the biological realism of soil carbon models and significantly amplifies global soil carbon loss by 2100. Our results highlight the significant potential of microbial eco\uffe2\uff80\uff90evolutionary responses to influence carbon cycle feedbacks to climate change, and motivate an urgent need for more comprehensive data to accurately quantify the adaptive potential of microbiomes in response to climate change.
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.