Developing soil quality indices to investigate degradation impacts of different land use types in Northern Ethiopia.

Assessing soil quality is imperative to diagnose soil functioning and recognize inappropriate soil managements. However, the absence of defined indicators and their scoring methods and lack of universally accepted soil quality indexing frameworks complicate soil quality assessment, given soil systems complexity and diversity caused by variation in soil formation factors. This study was aimed to assess soil quality of three land use managements (CL, cropland; GR, grassland; SL, shrubland) in Northern Ethiopia, using two data sets (Total data set (TDS) and minimum data set (MDS)), linear and non-linear indicator transformation techniques and three indexing scenarios (Additive (SQI), nemoro (SQI) and weighted additive (SQI)). To screen MDS and TDS members, one-way analysis of variance and principal component analysis were applied. Twenty-two soil indicators responsible to changes in land use were screened as members of TDS. Four indicators (silt, mean weight diameter, visual evaluation of soil structure, and exchangeable calcium) were selected to establish MDS. The study results demonstrated a clear impact by land use managements to SQ in the study area. In all cases, CL soils scored significantly lower SQI values than those of GL and SL. Moderate (III) and low (IV) quality grade soils have the largest spatial share in the area. Soil organic carbon and structural stability were found to be the most important indicators explaining soil quality and its spatial variability. Overall, it was demonstrated by the study that soil quality deterioration is a serious issue particularly for soils in CL and GL, suggesting the essentiality to consider revisions and improvements in soil management. A positive and significant correlation was demonstrated among SQIs, revealing that all SQIs were sensitive to measure land use management impacts to soil quality. However, SQI was estimated and differentiated better when using non-linear indicator transformation and MDS indicator selection approach in the SQI (SQI) than other SQIs, and thus was suggested for future soil quality studies in areas of similar soil and climate environments.