Developing scoring functions to assess soil quality at a regional scale in rangelands of SW Spain

ABSTRACT The drawing of maps of soil quality at a large scale is increasingly being more useful to land planners and stakeholders. Nevertheless, it involves different methodological steps from the description of soil profiles in the field until the regional mapping of integrative soil quality index (IQI) values. The development of proper scoring functions is a paramount task for the calculation of these IQI values since every parameter needs to be standardized accordingly and weighting factors are usually estimated by multivariate techniques. The main goal of this study was to map soil quality in the Spanish region of Extremadura (commonly known by its rangelands called dehesas). To do that, i) we gathered information from 194 soil profiles described throughout the region, ii) we calculated the weighting factors of ten meaningful parameters used as indicators by using multivariate techniques (Principal Component Analysis, PCA; and Analytic Hierarchy Process, AHP), and iii) we developed standard scoring functions (SSFs) that represent the singularity of every variable (less is better, more is better). We established upper and lower limits for standardizing the values of each indicator properly. Regarding weighting factors, soil texture was highlighted by the PCA and nutrients by the AHP. Once IQI values were calculated, two regional maps of soil quality were drawn by using interpolation methods (ordinary kriging). The IQI maps showed remarkable spatial differences in soil quality presumably induced by land management. We conclude this methodology could be useful and we encourage other colleagues to test its effectiveness in places where soil data are available.

摘要 大尺度土壤质量图绘制对土地规划者与利益相关方的应用价值日益凸显。然而，该流程涵盖从野外土壤剖面描述直至综合土壤质量指数（Integrative Soil Quality Index，IQI）值区域制图的一系列方法学步骤。构建合理的评分函数是计算该指数值的核心任务，因所有参数均需进行标准化处理，且权重因子通常通过多变量技术估算。本研究的核心目标是对西班牙埃斯特雷马杜拉地区（该地区以名为德赫萨（dehesas）的牧场闻名）的土壤质量进行制图。为此，本研究开展了三项工作：① 收集了整个区域内194个已描述的土壤剖面信息；② 借助多变量技术（主成分分析（Principal Component Analysis，PCA）与层次分析法（Analytic Hierarchy Process，AHP））计算了10个作为指标的有效参数的权重因子；③ 构建了能够反映各变量特性的标准评分函数（Standard Scoring Functions，SSFs），并明确了“越小越好”与“越大越好”两类变量的评分模式。我们为各指标的标准化设置了合理的上下限值。就权重因子而言，主成分分析凸显了土壤质地的重要性，而层次分析法则突出了养分的关键作用。在计算得到IQI值后，本研究通过普通克里金插值法（Ordinary Kriging）绘制了两幅区域土壤质量图。该指数图揭示了土壤质量存在显著的空间差异，推测该差异由土地管理方式所导致。本研究认为该方法具备应用价值，并呼吁其他研究者在具备土壤数据的地区验证其有效性。