Microbial Activity and Root Carbon Inputs Are More Important than Soil Carbon Diffusion in Simulating Soil Carbon Profiles

Abstract

Soils are the largest carbon (C) pool in the terrestrial biosphere, storing about 700 Pg C in the top 0.3 m (Batjes, 1996), or 2,300 Pg C in the top 3 m soil (Jobbágy & Jackson, 2000;Tifafi, Guenet et al. 2018). The amount of carbon below 0.3 m soil is about twice the amount, much older and stable than the carbon in the top 0.3 m soil (Fontaine et al., 2007). A recent soil warming study by Qin et al. (2019) found that the response of soil carbon to warming was dominated by soil microbial activities in the surface soil layer (0-0.3 m), but was codominated by low microbial abundance and strong aggregate protection in the deep (>0.3 m) soil layer. Therefore, deep soil carbon was less sensitive to warming and may function as a carbon sink despite global warming. This is also supported by the analysis of Baldesdent et al. (2018) who found that the soil at the depths between 0.3 and 1 m accounted for about 19% of the total soil carbon accumulated over the last five decades.There has been renewed interest within the global modeling community in representing the vertical variation of soil carbon for several reasons: (1) it enables direct comparisons of the simulations with observations of both soil carbon and carbon isotopes ( 13 C and 14 C) (see Elliott et al., 1996); (2) soil carbon in deeper layers is usually older and more stable than the soil carbon in surface layers (Fontaine et al., 2007;Rossel et al., 2019), and the sensitivity to warming is different between stable soil carbon and active soil carbon (Hicks Pries et al., 2017;Qin et al., 2019); and (3) most Earth system models (ESMs) significantly underestimated soil carbon age by a factor of more than 6, and overestimated the soil carbon sequestration potential by a factor of 2 (He et al., 2016;Shi et al., 2020).

Kinetic Properties of Microbial Exoenzymes Vary With Soil Depth but Have Similar Temperature Sensitivities Through the Soil Profile

“…Different soil models have been developed to represent exoenzyme kinetics, thermodynamics, ecological stoichiometry, enzyme diffusion, and interactions with environmental factors ( German et al, 2012 ; Sinsabaugh and Shah, 2012 ; Sulman et al, 2014 ; Wieder et al, 2014 ; Tang and Riley, 2015 , 2019 ; Wang et al, 2015 ; Wang and Allison, 2019 ). However, these processes have only recently started to be incorporated into depth-resolved soil biogeochemical models ( Dwivedi et al, 2019 ; Wang et al, 2021 ), are rarely considered in fully coupled ecosystem scale models ( Grant, 2013 ; Pasut et al, 2021 ), and are entirely unrepresented in current Earth system models. Moreover, exoenzyme kinetics, when included in depth-resolved models, are represented as a function of microbial biomass, and not as explicit properties that may vary independently due to differences in microbial life strategies or microbe-substrate interactions.…”

Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model

“…to include coupled C-N biogeochemistry (Kyker-Snowman et al, 2020) and vertical resolution (Y. Wang et al, 2021)), refinement (Zhang et al, 2020), and evaluation (Basile et al, 2020;Koven et al, 2017;Shi et al, 2018;Sulman et al, 2018). All of these activities rely on conducting simulations across multiple study sites and at global scales, which is a valuable precursor to considering incorporating MIMICS into an ESM.…”

Optimizing process-based models to predict current and future soil organic carbon stocks at high-resolution

“…Our analysis of the parametric uncertainty in the model projections shows the direct opportunities for additional observational data pertaining to microbial properties and SOC persistence to further refine MIMICS parameter estimates. Further potential also exists to generate more complex, fine scale estimates and projections of SOC dynamics by adapting the methods from this study to similarly enhance the spatial application scale and parameterization of the CN-coupled 70 and soil depth resolved 71 versions of the MIMICS model.…”