Modelling optimal ligninolytic activity during plant litter decomposition

Area of Science:

• Ecology
• Microbial Ecology
• Biogeochemistry

Background:

• Plant litter decomposition is crucial for carbon cycling.
• Recalcitrant aromatic compounds, like lignin, pose challenges for microbial degradation due to high energetic costs.
• Understanding the dynamics of aromatic carbon decomposition is key to accurate ecosystem modeling.

Purpose of the Study:

• To develop and test a litter decomposition model that dynamically optimizes aromatic carbon decomposition rates.
• To evaluate the influence of climate and litter chemistry on the timing and rate of aromatic carbon decomposition.
• To explore the application of eco-evolutionary theory in parameterizing decomposition models.

Main Methods:

• Developed a dynamic litter decomposition model optimizing microbial growth based on ligninolytic activity costs.
• Validated the model against over 200 published litter decomposition datasets.
• Assessed the impact of temperature and litter aromatic carbon content on decomposition dynamics.

Main Results:

• The model accurately predicted a time-varying rate of aromatic carbon oxidation and associated lag times.
• Warmer temperatures accelerated decomposition, reduced lag times, and enhanced microbial carbon-use efficiency.
• Higher initial aromatic carbon content in litter led to earlier decomposition initiation across climates.

Conclusions:

• Eco-evolutionary optimization provides a novel framework for modeling microbial decomposition of recalcitrant compounds.
• Climate and litter chemistry significantly modulate the energetic trade-offs governing aromatic carbon breakdown.
• This approach offers a more mechanistic understanding of litter decomposition and its role in the carbon cycle.