Comparative analysis of soil quality indexing techniques for various tree based land use systems in semi-arid India

Abstract

Inappropriate management of land use systems is one of the main factors that leads to soil quality degradation and its quantification is crucial to their sustainable utilization planning. The objective of the research is to evaluate how various land-use systems, viz., natural forest, tree plantations of Tectona grandis, Terminalia bellirica, Swietenia macrophylla, Artocarpus hirsutus, Melia dubia based agroforestry system, horticulture (Mangifera indica) and agriculture systems impact the soil physicochemical and biological characteristics in semi-arid climatic conditions of India. Principal component analysis followed by linear and non-linear scoring methods was employed to compute the soil quality index (SQI). The soil attributes viz., dehydrogenase activity, acid phosphatase activity, soil available nitrogen, potassium, calcium, porosity, and soil available iron emerged as significant indicators for assessing the soil quality. Among different SQIs, non-linear weighted SQI can efficiently assess soil quality. Based on the non-linear weighted SQI, the order of the systems studied was natural forest (0.973) > Swietenia macrophylla (0.756) > agroforestry (0.737) > agriculture (0.556) > Tectona grandis (0.416) > Terminalia bellirica (0.373) > Artocarpus hirsutus (0.343) > Mangifera indica (0.208). The study concludes that converting natural forests into different land-use systems deteriorated the soil quality. Identifying soil indicators will help rapidly diagnose soil degradation, assess soil-based ecosystem services, and design appropriate land management practices in the future.