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Abstract Identifying controls on soil organic carbon (SOC) storage, and where SOC is most vulnerable to loss, are essential to managing soils for both climate change mitigation and global food security. However, we currently lack a comprehensive understanding of the global drivers of SOC storage, especially with regards to particulate (POC) and mineral‐associated organic carbon (MAOC). To better understand hierarchical controls on POC and MAOC, we applied path analyses to SOC fractions, climate (i.e., mean annual temperature [MAT] and mean annual precipitation minus potential evapotranspiration [MAP‐PET]), carbon (C) input (i.e., net primary production [NPP]), and soil property data synthesized from 72 published studies, along with data we generated from the National Ecological Observatory Network soil pits (n = 901 total observations). To assess the utility of investigating POC and MAOC separately in understanding SOC storage controls, we then compared these results with another path analysis predicting bulk SOC storage. We found that POC storage is negatively related to MAT and soil pH, while MAOC storage is positively related to NPP and MAP‐PET, but negatively related to soil % sand. Our path analysis predicting bulk SOC revealed similar trends but explained less variation in C storage than our POC and MAOC analyses. Given that temperature and pH impose constraints on microbial decomposition, this indicates that POC is primarily controlled by SOC loss processes. In contrast, strong relationships with variables related to plant productivity constraints, moisture, and mineral surface availability for sorption indicate that MAOC is primarily controlled by climate‐driven variations in C inputs to the soil, as well as C stabilization mechanisms. Altogether, these results demonstrate that global POC and MAOC storage are controlled by separate environmental variables, further justifying the need to quantify and model these C fractions separately to assess and forecast the responses of SOC storage to global change. 

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 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.