A multi-scale eco-evolutionary model of cooperation reveals how microbial adaptation influences soil decomposition

Abstract

The decomposition of soil organic matter (SOM) is a critical process in global terrestrial ecosystems. SOM decomposition is driven by micro-organisms that cooperate by secreting costly extracellular (exo-)enzymes. This raises a fundamental puzzle: the stability of microbial decomposition in spite of its evolutionary vulnerability to “cheaters”—mutant strains that reap the benefits of cooperation while paying a lower cost. Resolving this puzzle requires a multi-scale eco-evolutionary model that captures the spatio-temporal dynamics of molecule-molecule, molecule-cell, and cell-cell interactions. The analysis of such a model reveals local extinctions, microbial dispersal, and limited soil diffusivity as key factors of the evolutionary stability of microbial decomposition. At the scale of whole-ecosystem function, soil diffusivity influences the evolution of exo-enzyme production, which feeds back to the average SOM decomposition rate and stock. Microbial adaptive evolution may thus be an important factor in the response of soil carbon fluxes to global environmental change.

Microbial eco-evolutionary responses amplify global soil carbon loss with climate warming

“…9, where c < 1 when φ mut < φ res and c > 1 when φ mut > φ res . This phenomenological approach is consistent with the mathematical construction and numerical analysis of a spatially explicit model of resident-mutant local interaction that accounts for soil diffusion (38).…”

Ecological modelling approaches for predicting emergent properties in microbial communities

“…While top-down models can simulate the fate of mutants, both mutants and their characteristics need to be predefined. Individual-based models can simulate the complete evolutionary process via inheritable mutations [ 133 – 136 ]. This allows capturing the emergence of community resilience and phenotypic complexity in a changing and/or heterogeneous environment.…”

“…In addition to capturing individual level heterogeneity, individual-based models are well suited for simulating stochastic processes such as genetic drift, horizontal gene transfer, and cell-cell interactions like type VI secretion stabbing [ 136 , 140 , 142 – 144 ]. While changes in and dispersal of biomass are modelled via discrete individual interactions, soluble substrates/chemical species typically need to be modelled as reaction-diffusion [ 77 ].…”

The Ecology Underground coalition: building a collaborative future of belowground ecology and ecologists

“…Romero‐Olivares et al ., 2019). Modelers also need empiricists to (1) pair measurements of interest with those that models require; for example, effort should be made to pair measurements of fine‐root morphology and chemistry with fine‐root function, and (2) provide them with microbial trait trade‐offs or range limits for a given trait (Abs et al ., 2020). Empirical data such as local carbon dioxide emissions or community‐level microbial biomass can be important to validate the emergent properties of individual‐based models while measurements such as ecosystem‐level net primary production or soil decomposition rates over time in long‐term warming experiments (Melillo et al ., 2017) or nitrogen addition experiments (Morrison et al ., 2018), can be needed to validate biogeochemical model outputs.…”

“…For example, individually based models can be used to test the outcome of interactions between microbial taxa (Allison et al ., 2010), the effect of evolving microbial strains on local decomposition (Fig. 3, Ex I; Abs et al ., 2020), or drought legacy in soil microbiomes (Steven Allison and Bin Wang, University of California, USA ). Biogeochemical models focus on highly‐resolved biogeochemical cycling within an ecosystem and are therefore useful to investigate processes related to changes in soil carbon in response to environmental changes, for example by integrating microbial functional groups (MIcrobial‐MIneral Carbon Stabilization (MIMICS) model; Wieder et al ., 2015) or the protection of soil organic matter (Sulman et al ., 2014).…”