Microbial dynamics and soil physicochemical properties explain large‐scale variations in soil organic carbon

Abstract

First‐order organic matter decomposition models are used within most Earth System Models (ESMs) to project future global carbon cycling; these models have been criticized for not accurately representing mechanisms of soil organic carbon (SOC) stabilization and SOC response to climate change. New soil biogeochemical models have been developed, but their evaluation is limited to observations from laboratory incubations or few field experiments. Given the global scope of ESMs, a comprehensive evaluation of such models is essential using in situ observations of a wide range of SOC stocks over large spatial scales before their introduction to ESMs. In this study, we collected a set of in situ observations of SOC, litterfall and soil properties from 206 sites covering different forest and soil types in Europe and China. These data were used to calibrate the model MIMICS (The MIcrobial‐MIneral Carbon Stabilization model), which we compared to the widely used first‐order model CENTURY. We show that, compared to CENTURY, MIMICS more accurately estimates forest SOC concentrations and the sensitivities of SOC to variation in soil temperature, clay content and litter input. The ratios of microbial biomass to total SOC predicted by MIMICS agree well with independent observations from globally distributed forest sites. By testing different hypotheses regarding (using alternative process representations) the physicochemical constraints on SOC deprotection and microbial turnover in MIMICS, the errors of simulated SOC concentrations across sites were further decreased. We show that MIMICS can resolve the dominant mechanisms of SOC decomposition and stabilization and that it can be a reliable tool for predictions of terrestrial SOC dynamics under future climate change. It also allows us to evaluate at large scale the rapidly evolving understanding of SOC formation and stabilization based on laboratory and limited filed observation.

Can N2O emissions offset the benefits from soil organic carbon storage?

“…A recent modelling study suggests that measure to increase SOC sequestration might be offset by increased N 2 O, depending on the crop rotation and on the duration of the land management practices (Lugato, et al, 2018). Recent progress in modelling SOC may help to better understand SOC dynamics and how we can enhance SOC storage (Abramoff et al., 2018; Cotrufo et al, 2013; Zhang et al., 2018, 2020), but so far the interaction between C and N cycles is still poorly represented in models. A better understanding of such interactions is necessary to evaluate the benefits of different management practices aimed at increasing SOC storage and to predict the full GHG balance of each practice.…”

Soil organic carbon is not just for soil scientists: measurement recommendations for diverse practitioners

“…For example, large‐scale SOC databases have advanced our understanding of environmental controls over SOC stabilization (Rasmussen et al 2018 a ), SOC responses to land management (Nave et al 2018), and the ecosystems in which uncertainty in SOC stocks is especially high (Jackson et al 2017). Abundant data on SOC stock sizes and timescales of SOC formation and loss can be found in the literature (Jobbagy and Jackson 2000, Cotrufo et al 2015, Hicks Pries et al 2017), helping investigators to parameterize and evaluate large‐scale representations of the global C cycle in models (Luo et al 2016, Collier et al 2018, Zhang et al 2020). In spite of these advances, two categories of problems limit our ability to gain a predictive understanding of SOC feedbacks to the global C cycle.…”

Modelling of land nutrient cycles: recent progress and future development

“…Nutrient mineralization rate is usually modelled to vary with the amount and quality of substrate and environmental conditions, whereas the role of soil microbes has been largely ignored, primarily because of their minor biomass (a few percent of total soil organic carbon) and short turnover time (days). However, recent studies suggest that microbial dynamics control spatial variation and residence time of soil carbon 11 , 12 . So far, only a few models have included soil microbial processes explicitly 13 , 14 , one of which resolves dynamics of different soil enzymes and functioning of different classes of decomposers (bacteria, fungi, and macrofauna) 15 .…”