Soil carbon dynamics of conventional tillage and no-till agroecosystems at Georgia Piedmont — HSB-C models

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This model was designed to simulate the dynamics of soil organic matter (SOM) and biomass change of detritus soil food webs after the application of crop residue in agroecosystems. Background data and literature parameters were used to initialize the model and a short-term field experiment was conducted to calibrate the model. Our model is a synthesis and integration of many others’ previous studies because many others’ ideas on food web or SOM modeling were incorporated into our model. In our model, soil microorganisms were considered to be the major decomposers of organic matter with soil animals playing an important role in decomposing organic matter by controlling the population of soil microorganisms through trophic interactions. Though we did not model the soil food web into species or functional groups, we attempted to represent the hierarchical structure and trophic interactions of soil food webs as complete as possible. The whole soil food web was conceptualized as a ‘super organism’ to process organic matter in the model diagram. State variables of our model were categorized into soil organic matter pools, inorganic carbon pool, and soil organism pools. Flows were modeled based on first order kinetics. A tillage effect was introduced in our model by assuming that soil microorganisms, microarthropods and earthworms decrease temporarily immediately after the tillage operation. We also introduced a ‘minimum population’ protection mechanism for each group of soil organisms by assuming that predation ceases when energy obtained can not offset the energy expended in prey-searching and feeding. We found that the simulation outputs fitted the measured data very well, the simulation outputs were in the range of field measurements in most cases. However, there was a significant discrepancy in respiration between simulation output and field measurement in both conventional tillage (CT) and no-till (NT), particularly in NT agroecosystems. We hypothesized that plant roots should be responsible for this discrepancy. The sensitivity analysis of our model showed that the population of soil microorganisms was controlled by resources rather than predators. However, the populations of soil protozoa, nematodes and microarthropods were controlled by both resources and predators.