Abstract

ABSTRACT The conversion of forest to agricultural land has been a major worldwide concern and a cause of deterioration of soil quality. The study examined the influence of land uses on the soil quality index (SQI) using minimum datasets (MDS) constructed from soil profiles through two methods namely, additive (SQIa) and weighted (SQIw). In this study, 29 geo-referenced soil profiles (116 layers) up to a depth of 150 cm were collected in Northeastern India, representing forest, jhum, jhum fallow, and agricultural land uses. Principal component analysis (PCA) with multiple correlation analysis is found to be a suitable statistical method for selecting the key soil quality indicators. From PCA, organic carbon (OC), sand, clay, available P and available S were selected as soil quality indicators in MDS. Our results showed that these MDS significantly varied within the profiles depending on the land-uses. The estimated values of SQIs showed that SQIa was higher than SQIw across the soil depths and land-uses. For the surface soil, SQIa values were in the order of forest (2.97) > jhum fallow (2.82) > agriculture (2.68) > jhum land (1.97) and for profile soil jhum fallow (2.38) > forest (2.37) > agriculture (2.33) > jhum (1.88). Similarly, SQIw followed the trend of forest > jhum fallow > agriculture > jhum for all the three studied depths. The statistical analysis showed that the surface, subsurface, and profile soil had no significant impact on SQIw for agriculture, fallow jhum, and forest. The overall data indicated that jhum land had a significantly lower SQI than other land-uses for all soil depths. From this study, the information generated can be useful to assess the soil quality in different land-uses for managing soil health in similar areas of the Northeastern region of India. The findings are also useful in the ecosystems in which soils develop in an acid edaphic environment.

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