Assessing and monitoring the soil quality of forested and agricultural areas using soil-quality indices and digital soil-mapping in a semi-arid environment

ABSTRACT

In recent decades, the conversion of forest to agricultural land has been a major worldwide concern and a cause of environmental and soil-quality degradation. In this study, soil-quality indices (SQIs) were applied using several soil properties to determine the effects of land use on soil quality in a 206.50 km² area in Kurdistan Province, Iran. The Weighted Additive Soil Quality Index (SQI_w) was calculated using two scoring methods and two soil indicator selection approaches. Nine soil-quality indicators/variables were measured for 124 soil samples (0–30 cm depth). Calculated SQIs were digitally mapped with a random forest (RF) model using auxiliary data. The RF model was the best predictor of the SQI computed using the total dataset (TDS) and linear score function (SQI_w-TDS-linear). Soil quality was better estimated using non-linear scoring (r² = 0.82) than with linear scoring (r² = 0.73). The mean values of all SQIs were significantly greater in forestland than cropland. It is clear that soil quality is considerably reduced by deforestation, and that best management practices that maintain soil quality and reduce erosion must be developed for the soils of this region if they are to remain productive.

KEYWORDS:

• Land use change
• random forest
• minimum data set
• scoring method
• Kurdistan

Disclosure statement

No potential conflict of interest was reported by the authors.