AggModel: A soil organic matter model with measurable pools for use in incubation studies

Segoli, Michal; Gryze, Steven De; Dou, Fugen; Lee, Juhwan; Post, Wilfred M.; Denef, Karolien; Six, Johan

doi:10.1016/j.ecolmodel.2013.04.010

Cited by 77 publications

(54 citation statements)

References 52 publications

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“…Conceptual models have been developed (Six & Paustian, 2014) and partially implemented in a numerical model (Segoli et al, 2013), indicating that the fraction of microaggregates within macroaggregates could be used as a measurable parameter related to C protected within aggregates. A model module of aggregate formation and breakdown could generate estimates of the fraction of C inputs not protected by aggregates and the rate of C exposure to enzymes from aggregate breakdown, which would be linked to [S x ] in DAMM in lieu of its current proportionality constant.…”

Section: Aggregation and Sorptionmentioning

confidence: 99%

A big‐microsite framework for soil carbon modeling

Davidson

Savage

Finzi

2014

Global Change Biology

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Soil carbon cycling processes potentially play a large role in biotic feedbacks to climate change, but little agreement exists at present on what the core of numerical soil C cycling models should look like. In contrast, most canopy models of photosynthesis and leaf gas exchange share a common 'Farquhaur-model' core structure. Here, we explore why a similar core model structure for heterotrophic soil respiration remains elusive and how a pathway to that goal might be envisioned. The spatial and temporal variation in soil microsite conditions greatly complicates modeling efforts, but we believe it is possible to develop a tractable number of parameterizable equations that are organized into a coherent, modular, numerical model structure. First, we show parallels in insights gleaned from linking Arrhenius and Michaelis-Menten kinetics for both photosynthesis and soil respiration. Additional equations and layers of complexity are then added to simulate substrate supply. For soils, model modules that simulate carbon stabilization processes will be key to estimating the fraction of soil C that is accessible to enzymes. Potential modules for dynamic photosynthate input, wetting-event inputs, freeze-thaw impacts on substrate diffusion, aggregate turnover, soluble-C sorption, gas transport, methane respiration, and microbial dynamics are described for conceptually and numerically linking our understanding of fast-response processes of soil gas exchange with longer-term dynamics of soil carbon and nitrogen stocks.

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Section: Aggregation and Sorptionmentioning

confidence: 99%

A big‐microsite framework for soil carbon modeling

Davidson

Savage

Finzi

2014

Global Change Biology

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“…Understanding the link between soil aggregation and C outputs from soils is also important for designing agricultural practices aiming at increasing OM stabilization. It is finally key for improving current soil C models, which are empirical in nature and mostly lacking to integrate the environmental controls of OM outputs from soils (von Lützow et al, 2008;Schmidt et al, 2011;Segoli et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Soil aggregate stability to predict organic carbon outputs from soils

Chaplot

Cooper²

2015

Geoderma

178

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“…While improvements in representing these processes are needed, for global change predictions it would also be valuable to integrate and test the importance of mechanistic representation of at least seven additional processes: (a) aggregation (Segoli et al, 2013;Six et al, 2001); (b) formation and transport of colloids (Flury and Qiu, 2008;Thompson et al, 2006); (c) surface interactions (Conant et al, 2011); (d) enzyme dynamics (Allison et al, 2010); (e) nutrient-microbe interactions; (f) microbe-plant interactions; and (g) representation of subgrid-scale heterogeneity in soil properties and climate.…”

Section: Observations Needed To Improve Som Modelsmentioning

confidence: 99%

Long residence times of rapidly decomposable soil organic matter: application of a multi-phase, multi-component, and vertically resolved model (BAMS1) to soil carbon dynamics

et al. 2014

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Abstract. Accurate representation of soil organic matter (SOM) dynamics in Earth system models is critical for future climate prediction, yet large uncertainties exist regarding how, and to what extent, the suite of proposed relevant mechanisms should be included. To investigate how various mechanisms interact to influence SOM storage and dynamics, we developed an SOM reaction network integrated in a one-dimensional, multi-phase, and multi-component reactive transport solver. The model includes representations of bacterial and fungal activity, multiple archetypal polymeric and monomeric carbon substrate groups, aqueous chemistry, aqueous advection and diffusion, gaseous diffusion, and adsorption (and protection) and desorption from the soil mineral phase. The model predictions reasonably matched observed depth-resolved SOM and dissolved organic matter (DOM) stocks and fluxes, lignin content, and fungi to aerobic bacteria ratios. We performed a suite of sensitivity analyses under equilibrium and dynamic conditions to examine the role of dynamic sorption, microbial assimilation rates, and carbon inputs. To our knowledge, observations do not exist to fully test such a complicated model structure or to test the hypotheses used to explain observations of substantial storage of very old SOM below the rooting depth. Nevertheless, we demonstrated that a reasonable combination of sorption parameters, microbial biomass and necromass dynamics, and advective transport can match observations without resorting to an arbitrary depth-dependent decline in SOM turnover rates, as is often done. We conclude that, contrary to assertions derived from existing turnover time based model formulations, observed carbon content and 14 C vertical profiles are consistent with a representation of SOM consisting of carbon compounds with relatively fast reaction rates, vertical aqueous transport, and dynamic protection on mineral surfaces.

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AggModel: A soil organic matter model with measurable pools for use in incubation studies

Cited by 77 publications

References 52 publications

A big‐microsite framework for soil carbon modeling

A big‐microsite framework for soil carbon modeling

Soil aggregate stability to predict organic carbon outputs from soils

Long residence times of rapidly decomposable soil organic matter: application of a multi-phase, multi-component, and vertically resolved model (BAMS1) to soil carbon dynamics

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