Digital soil mapping (DSM) is an effective mapping technique that supports the increased need for quantitative soil data. In DSM, soil properties are correlated with environmental characteristics using statistical models such as regression. However, many of these relationships are explicitly described in mechanistic simulation models. Therefore, the mechanistic relationships can, in theory, replace the statistical relationships in DSM. This study aims to develop a mechanistic model to predict soil organic matter (SOM) stocks in Natura2000 areas of the Cantabria region (Spain). The mechanistic model is established in four steps: (a) identify major processes that influence SOM stocks, (b) review existing models describing the major processes and the respective environmental data that they require, (c) establish a database with the required input data, and (d) calibrate the model with field observations. The SOM stocks map resulting from the mechanistic model had a mean error (ME) of −2 t SOM ha−1 and a root mean square error (RMSE) of 66 t SOM ha−1. The Lin's concordance correlation coefficient was 0.47 and the amount of variance explained (AVE) was 0.21. The results of the mechanistic model were compared to the results of a statistical model. It turned out that the correlation coefficient between the two SOM stock maps was 0.8. This study illustrated that mechanistic soil models can be used for DSM, which brings new opportunities. Mechanistic models for DSM should be considered for mapping soil characteristics that are difficult to predict by statistical models, and for extrapolation purposes. Highlights: Theoretically, mechanistic models can replace the statistical relationships in digital soil mapping. Mechanistic soil models were used to develop a mechanistic model for digital soil mapping that predicted SOM stocks. The applicability of the mechanistic approach needs to be explored for different soil properties and regions.

中文翻译：

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在数字土壤绘图中引入机械模型来预测坎塔布连地区（西班牙）的土壤有机质库

数字土壤制图 (DSM) 是一种有效的制图技术，支持日益增长的定量土壤数据需求。在 DSM 中，使用回归等统计模型将土壤特性与环境特征相关联。然而，许多这些关系在机械仿真模型中得到了明确描述。因此，理论上，机械关系可以替代 DSM 中的统计关系。本研究旨在开发一种机制模型来预测坎塔布里亚地区（西班牙）的 Natura2000 地区的土壤有机质 (SOM) 库。机械模型分四个步骤建立：(a) 确定影响 SOM 库存的主要过程，(b) 审查描述主要过程的现有模型及其所需的相应环境数据，(c) 建立一个包含所需输入数据的数据库，以及 (d) 用实地观察校准模型。由机械模型得出的 SOM 库存图的平均误差 (ME) 为 -2 t SOM ha-1，均方根误差 (RMSE) 为 66 t SOM ha-1。Lin 的一致性相关系数为 0.47，解释的方差量 (AVE) 为 0.21。将机械模型的结果与统计模型的结果进行比较。结果表明，两个 SOM 股票图之间的相关系数为 0.8。这项研究表明机械土壤模型可用于 DSM，这带来了新的机会。在绘制统计模型难以预测的土壤特征以及用于外推目的时，应考虑 DSM 的机械模型。亮点：理论上，力学模型可以代替数字土壤绘图中的统计关系。机械土壤模型用于开发用于预测 SOM 储量的数字土壤测绘机械模型。需要探索机械方法对不同土壤特性和区域的适用性。