Optimal lignin decomposition during litter decay

A better understanding of the litter decay process is critical for improved predictions of terrestrial carbon (C) exchange between above and below-ground C reservoirs. Furthermore, developing well-constrained decomposition models with explicit representation of microorganisms is becoming more crucial for improving our understanding of nutrient recycling between soils and plants, greenhouse gas emissions, and the contribution of litter to soil organic matter formation.

Litter is typically characterized by structural and non-structural pools—structural components representing the lignin like compounds and non-structural representing soluble and holocellulose organic compounds. Initial litter chemical composition has a strong control on its decomposition. In fact, empirical studies show that a higher initial lignin content in a litter is associated with slower decomposition of holocellulose and implies an increased cost of oxidative enzyme production to break the lignin cross-linked compounds, thereby decreasing microbial community carbon use efficiency. In mathematical models describing litter dynamics, the decomposition rates of these pools are given by the assumed kinetics, either first-order or Monod type, with time-invariant kinetic parameters. This approach neglects possible temporal changes in microbial traits that reflect how decomposer communities adapt to litter chemical properties.

Here, we have taken an optimal control approach that does not fix kinetic parameters, but instead finds the decomposition rate constant of the structural (lignin) pool by maximizing the microbial growth (i.e., maximum fitness as a result of natural selection) while taking into account the effect of litter chemistry on microbial metabolism. In this formulation, we combine the soluble and holocellulose C into a non-structural C pool and assume first-order kinetics of decomposition of both structural and non-structural pools. Our results predict a time-varying decomposition rate constant for the lignin pool. This means that optimally adapted microbes would start decomposing lignin at different times as a function of initial lignin content. Further, we provide a case study testing the performance of our model against observed litter decomposition data from a boreal forest. With this contribution, we aim to highlight the applications of eco-evolutionary approaches as an alternate parametrization scheme for litter decomposition models by utilizing microbial life strategy as the main driving factor.