Key research themes
1. How can soil quality have threshold interpretation schemes and multifunctional applicability validated for land management and policy?
This research theme addresses the challenge of soil quality (SQ) assessment in terms of defining relevant indicators, measurement interpretation, and aligning the assessments with soil multifunctionality considering ecosystem services and soil threats. It focuses on the development of assessment frameworks that are explicitly linked to soil functions, land uses, and ecosystem services to support actionable decisions for land managers and policymakers.
2. What are the most effective multivariate methods and minimum data sets for soil quality index (SQI) development and spatial mapping across diverse regions?
This theme centers on how multivariate statistical approaches such as principal component analysis (PCA) and factor analysis (FA) facilitate reduction of large soil property datasets into minimal but sensitive soil quality indicators (SQIs) for reliable SQI calculation and interpretation over regional to field scales. It highlights indicator selection (total data set vs minimum data set), different SQI scoring functions and integration models, and spatial predictive modeling using GIS and machine learning to localize and interpret soil quality variability, enhancing environmental monitoring and targeted management.
3. How do intensive agricultural practices influence soil quality as quantified by integrated soil quality index (SQI) frameworks combining physical, chemical, and biological indicators?
This research area investigates the effects of intensive agriculture, including fertilizer and manure management, land use changes, and management practices, on soil physicochemical and biological properties, evaluated through integrative soil quality indices. Emphasis is on synthesizing indicator-based assessments to monitor degradation risks, productivity declines, and ecosystem service loss, alongside guiding sustainable soil management via minimum data sets and scoring functions that capture the multi-dimensional impacts of conventional and alternative agricultural regimes.