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Abstract. For decades, predominant soil biogeochemical models have used conceptual soil organic matter (SOM) pools and only simulated them to a shallow depthin soil. Efforts to overcome these limitations have prompted the development of the new generation SOM models, including MEMS 1.0, which representsmeasurable biophysical SOM fractions, over the entire root zone, and embodies recent understanding of the processes that govern SOM dynamics. Herewe present the result of continued development of the MEMS model, version 2.0. MEMS 2.0 is a full ecosystem model with modules simulating plantgrowth with above- and belowground inputs, soil water and temperature by layer, decomposition of plant inputs and SOM, and mineralization andimmobilization of nitrogen (N). The model simulates two commonly measured SOM pools – particulate and mineral-associated organic matter (POM andMAOM, respectively). We present results of calibration and validation of the model with several grassland sites in the US. MEMS 2.0 generallycaptured the soil carbon (C) stocks (R2 of 0.89 and 0.6 for calibration and validation, respectively) and their distributions between POM andMAOM throughout the entire soil profile. The simulated soil N matches measurements but with lower accuracy (R2 of 0.73 and 0.31 for calibrationand validation of total N in SOM, respectively) than for soil C. Simulated soil water and temperature were compared with measurements, and theaccuracy is comparable to the other commonly used models. The seasonal variation in gross primary production (GPP; R2 = 0.83), ecosystemrespiration (ER; R2 = 0.89), net ecosystem exchange (NEE; R2 = 0.67), and evapotranspiration (ET; R2 = 0.71) was wellcaptured by the model. We will further develop the model to represent forest and agricultural systems and improve it to incorporate newunderstanding of SOM decomposition. 

Abstract. Soil organic matter (SOM) dynamics in ecosystem-scale biogeochemical modelshave traditionally been simulated as immeasurable fluxes between conceptuallydefined pools. This greatly limits how empirical data can be used to improvemodel performance and reduce the uncertainty associated with theirpredictions of carbon (C) cycling. Recent advances in our understanding ofthe biogeochemical processes that govern SOM formation and persistence demanda new mathematical model with a structure built around key mechanisms andbiogeochemically relevant pools. Here, we present one approach that aims toaddress this need. Our new model (MEMS v1.0) is developed from the MicrobialEfficiency-Matrix Stabilization framework, which emphasizes the importance oflinking the chemistry of organic matter inputs with efficiency of microbialprocessing and ultimately with the soil mineral matrix, when studying SOMformation and stabilization. Building on this framework, MEMS v1.0 is alsocapable of simulating the concept of C saturation and representsdecomposition processes and mechanisms of physico-chemical stabilization todefine SOM formation into four primary fractions. After describing the modelin detail, we optimize four key parameters identified through avariance-based sensitivity analysis. Optimization employed soil fractionationdata from 154 sites with diverse environmental conditions, directly equatingmineral-associated organic matter and particulate organic matter fractionswith corresponding model pools. Finally, model performance was evaluatedusing total topsoil (0–20 cm) C data from 8192 forest and grassland sitesacross Europe. Despite the relative simplicity of the model, it was able toaccurately capture general trends in soil C stocks across extensive gradientsof temperature, precipitation, annual C inputs and soil texture. The novelapproach that MEMS v1.0 takes to simulate SOM dynamics has the potential toimprove our forecasts of how soils respond to management and environmentalperturbation. Ensuring these forecasts are accurate is key to effectivelyinforming policy that can address the sustainability of ecosystem servicesand help mitigate climate change.

 

When aboveground materials are harvested for fuel production, such as withSorghum bicolor, the sustainability of annual bioenergy feedstocks is influenced by the ability of root inputs to contribute to the formation and persistence of soil organic matter (SOM), and to soil fertility through nutrient recycling. Using¹³C and¹⁵N labeling, we traced sorghum root and leaf litter‐derived C and N for 19 months in the field as they were mineralized or formedSOM. Our in situ litter incubation experiment confirms that sorghum roots and leaves significantly differ in their inherent chemical recalcitrance. This resulted in different contributions to C and N storage and recycling. Overall root residues had higher biochemical recalcitrance which led to more C retention in soil (27%) than leaf residues (19%). However, sorghum root residues resulted in higher particulate organic matter (POM) and lower mineral associated organic matter (MAOM), deemed to be the most persistent fraction in soil, than leaf residues. Additionally, the overall higher root‐derived C retention in soil led to higher N retention, reducing the immediate recycling of fertility from root as compared to leaf decomposition. Our study, conducted in a highly aggregated clay‐loam soil, emphasized the important role of aggregates in newSOMformation, particularly the efficient formation ofMAOMin microaggregate structures occluded within macroaggregates. Given the known role of roots in promoting aggregation, efficient formation ofMAOMwithin aggregates can be a major mechanism to increase persistentSOMstorage belowground when aboveground residues are removed. We conclude that promoting root inputs inS. bicolorbioenergy production systems through plant breeding efforts may be an effective means to counterbalance the aboveground residue removal. However, management strategies need to consider the quantity of inputs involved and may need to supportSOMstorage and fertility with additional organic matter additions.

 

Managing soil organic matter (SOM) stocks to address global change challenges requires well‐substantiated knowledge of SOM behavior that can be clearly communicated between scientists, management practitioners, and policy makers. However, SOM is incredibly complex and requires separation into multiple components with contrasting behavior in order to study and predict its dynamics. Numerous diverse SOM separation schemes are currently used, making cross‐study comparisons difficult and hindering broad‐scale generalizations. Here, we recommend separating SOM into particulate (POM) and mineral‐associated (MAOM) forms, two SOM components that are fundamentally different in terms of their formation, persistence, and functioning. We provide evidence of their highly contrasting physical and chemical properties, mean residence times in soil, and responses to land use change, plant litter inputs, warming, CO₂enrichment, and N fertilization. Conceptualizing SOM into POM versus MAOM is a feasible, well‐supported, and useful framework that will allow scientists to move beyond studies of bulk SOM, but also use a consistent separation scheme across studies. Ultimately, we propose the POM versus MAOM framework as the best way forward to understand and predict broad‐scale SOM dynamics in the context of global change challenges and provide necessary recommendations to managers and policy makers.