Abstract

Understanding spatial variations of soil properties is necessary for the management of rangelands vegetation ecosystem. The present study aimed to assess the spatial variations of soil properties in the hillslope of the Taftan semi-active volcanic mountain, Sistan and Baluchestan Province, south-eastern Iran. The locations of 30 sampling points were determined using random - systematic method and soil samples were taken from two depths: 0–30 and 30–60 cm. Spatial distribution of soil properties and relationships between soil properties and covariates were investigated using Random forest method. Model validation was done through 10-fold cross-validation approach. Based on results elevation, channel network base level and vertical distance to channel network, were the most importance environmental variables in predicting of the some soil characteristics such as soil clay, silt, sand, SOC, and EC in two studied depths. The maps produced indicated higher clay at 30–60 depth in the higher elevations. EC amounts were increased in the lower parts of the mountain because of leaching. Furthermore, the highest map accuracy was related to EC map at both depths and clay at 30–60 depth. The prediction maps of other properties of soil had low accuracy.

中文翻译：

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利用稀疏数据的随机森林预测半活火山山区的土壤性质

摘要

了解草地特性的空间变化对于管理牧场植被生态系统是必要的。本研究旨在评估伊朗东南部锡斯坦和Bal路支斯坦省塔夫坦半活火山山坡的土壤性质的空间变化。使用随机系统方法确定了30个采样点的位置，并从两个深度（0–30和30–60 cm）中获取了土壤样本。利用随机森林法研究了土壤特性的空间分布以及土壤特性与协变量之间的关系。通过10倍交叉验证方法进行模型验证。根据结果​​标高，渠道网络基本水平和与渠道网络的垂直距离，是在两个研究深度中预测某些土壤特性（例如粘土，淤泥，沙土，SOC和EC）的最重要的环境变量。绘制的地图表明，在较高海拔的30–60深度处，粘土含量较高。由于浸出，EC含量在山的下部增加。此外，最高的地图精度与深度和30-60度黏土的EC地图有关。土壤其他性质的预测图精度较低。