Repeated application of exogenous organic matter (EOM) contributes to soil organic carbon (SOC) stocks in cropped soils. Simple and robust models such as the AMG model are useful tools for predicting the effects of various EOM practices on SOC. In AMG, EOM is characterized by a single parameter: the humification rate h, which represents the proportion of exogenous carbon that is incorporated into SOC. The AMG model has been validated for a range of pedo-climatic conditions and cropping systems, but has not yet been tested with data from long-term field experiments where EOM is regularly applied. The calibration of the EOM parameter h also remains an issue. In this study, AMG was used to simulate SOC stocks in seven long-term field experiments with EOM application. AMG predicted changes in SOC stocks with a mean RMSE of 3.0 t C ha⁻¹ when h values were optimized. The optimized h values were highly correlated (R²= 0.62) with the indicator of remaining organic carbon (I_ROC), measured by laboratory analysis. The present study demonstrates (1) the ability of the AMG model to accurately simulate SOC stocks evolution in long-term field experiments with regular EOM application and (2) the ability of calibrating the model using I_ROC, which is routinely measured by commercial laboratories. The parameter h was determined for 26 EOM types utilizing a database of more than 600 I_ROC. The AMG model can thus be used to predict the SOC increase following EOM addition with a very simple calibration.

中文翻译：

---

简单的AMG模型可以在重复应用外源有机物质后准确模拟土壤中的有机碳储存

反复施用外源有机物（EOM）有助于耕种土壤中的土壤有机碳（SOC）储备。简单而健壮的模型（例如AMG模型）是用于预测各种EOM实践对SOC的影响的有用工具。在AMG中，EOM的特征在于一个参数：腐殖化速率h，它表示掺入SOC中的外源碳的比例。AMG模型已针对多种古气候条件和耕作系统进行了验证，但尚未使用定期进行EOM的长期田间试验的数据进行测试。EOM参数h的校准仍然是一个问题。在这项研究中，在EOM应用的七个长期现场实验中，AMG被用来模拟SOC存量。当优化h值时，AMG预测SOC储量的变化为3.0 t C ha ^-1的平均RMSE。优化的h值与通过实验室分析测得的剩余有机碳指标（I _ROC）高度相关（R ² = 0.62）。本研究证明（1）在常规EOM应用的长期野外实验中，AMG模型能够准确模拟SOC存量的演变；（2）使用I _ROC校准模型的能力，通常由商业实验室进行测量。利用超过600 I _ROC的数据库确定了26种EOM类型的参数h。因此，可以使用AMG模型通过非常简单的校准来预测添加EOM之后的SOC增加。