Uniting the scales of microbial biogeochemistry with trait‐based modelling

Abstract

1. Below-ground microbial communities drive some of Earth's largest biogeochemical fluxes, yet they represent a major source of uncertainty in global biogeochemical models. This review synthesizes recent advances in trait-based soil carbon modelling in order to identify how empirical observations of microbial traits can inform the next generation of soil carbon models.2. We identify four key perspectives from which trait-based models have investigated the role of microbes in soil carbon fluxes, ranging from the largest to the smallest scales of biological organization: (i) Earth system models, which have recently begun to incorporate microbial traits at a global scale; (ii) ecosystem models, which relate microbial carbon cycling to other trophic levels and element cycles; (iii) models from community ecology, which link theories of species diversity to ecosystem cycles; and (iv) models of fine-scale physiology, which mechanistically represent traits at the individual level.3. Highlighting the contributions of diverse trait-based modelling approaches, we caution that this diversity makes it challenging to link perspectives at different scales. The meaning of a trait depends both on the structure of the model in which it occurs and on the scale treated by the model. Thus, reapplying a finescale trait at a broader scale may make incorrect predictions, an issue we illustrate quantitatively using model simulations.4. With these challenges in mind, we highlight several ways to synthesize the scales of microbial biogeochemical modelling: (i) quantitatively, using mathematical scaling techniques, (ii) empirically, by applying experiments to test relationships between scales and (iii) conceptually, by identifying key traits and processes across scales.5. Taking full advantage of trait-based modelling, ecologists will thus be able to incorporate multiple perspectives to better predict carbon cycling in a changing world.

Emerging relationships among soil microbes, carbon dynamics and climate change

“…We hope that the eight articles presented here will help to elucidate a path ahead for future research in this topic. For instance, the explicit representation of soil microbial communities using trait‐based modelling can reduce the disparities between field data and predictions, but also bring important challenges to the table that need to be solved before generalizing this modelling framework (Malik & Bouskill, 2022; Wan & Crowther, 2022). The sensitivity of soil microbial processes to changes in temperature and moisture is usually hypothesized to be constant across space and time, but this sensitivity has been demonstrated to vary across ecosystems (Carey et al., 2016; Hawkes et al., 2017) and from short‐ to long‐term periods (Chen et al., 2020; Dacal et al., 2020).…”

“…(2022), Notthingham et al (2022), Evans et al. (2022) and Wan & Crowther (2022) propose meaningful ways to do so. Lastly, emerging findings and ideas regarding the abiotic control of microbial processes such as the priming effect (Bernard et al., 2022), necromass formation and recycling (Buckeridge et al., 2022) and interactions with the soil mineral matrix (Sokol et al, 2022) should shape how we address soil C turnover and stabilization under climate change.…”

“…They use trait‐based soil C modelling to describe how microbial traits can be integrated in biogeochemical models ranging in spatial scale and biological organization, from global Earth system and ecosystem models to community level and physiology. Wan & Crowther (2022) is a troubleshooting reading for those interested in the potential and pitfalls of microbial trait‐based soil C modelling. First, they use model simulations to show the issues that may arise when upscaling local microbial mechanisms to large‐scale soil C cycle.…”

“…They use trait-based soil C modelling to describe how microbial traits can be integrated in biogeochemical models ranging in spatial scale and biological organization, from global Earth system and ecosystem models to community level and physiology. Wan & Crowther (2022)…”

“…Then, two reviews propose new frameworks to address the impacts of changing precipitation patterns on soil microbes and C using moisture response curves (Evans et al., 2022) and microbial traits (Malik & Bouskill, 2022). Lastly, Wan & Crowther (2022) bring us some recent advances merging trait‐based and soil C modelling.…”