Soil Erodibility and Degradation Risk Assessment in Irele and Okitipupa Local Government Areas, Southwest Nigeria: A Multi-Parametric Approach Integrating Erosion Indices with Advanced Multivariate Statistical Analysis Data set
Description
Soil erosion represents one of the most critical land degradation processes threatening agricultural productivity and ecosystem stability in the coastal environments of southwest Nigeria. This study evaluated soil erodibility and degradation risk at six contrasting sampling sites/landscape positions a coastal–inland transect, Upper Interfluve (UI); Lower Interfluve (LI); Shoulder (SH); Upper Linear (UL); Lower Linear (LL) and Foot of the slope (FS) within the Irele and Okitipupa Local Government Areas, Ondo State. A suite of physical, chemical, and erosion-specific parameters was measured, including the Coefficient of Friability Index (CFI), Dispersion Ratio (DR), Clay Dispersion Index (CDI), particle size distribution, bulk density, porosity, hydraulic conductivity, aggregate stability (MWD), organic carbon, and soil reaction. Advanced statistical analyses — including two-way ANOVA, principal component analysis (PCA), hierarchical cluster analysis, Pearson correlation, and variance-covariance modelling were applied. Two-way ANOVA revealed highly significant effects of location (F = 12.43; p < 0.0001), depth (F = 11.36; p = 0.0003), and their interaction (F = 3.11; p = 0.0213). PCA extracted four components explaining 94.1% of total variance, with PC1 (58.4%) dominated by clay content, organic carbon, MWD, CFI, and CDI. Cluster analysis partitioned the six sites into two groups: inland-forest soils (UI, LI, SH, UL) with higher clay (45–59%), greater aggregate stability (MWD: 0.73–0.93 mm), and lower CDI (17.73–21.70%); and coastal-transition soils (LL, FS) with elevated sand content (59–65%), lower CFI (64–67%), higher CDI (32–36%), and greater erodibility. Foreshore soils showed the highest erosion risk. The study underscores the importance of integrating multiple erosion indices with multivariate statistics and visualization tools for accurate land degradation assessment in coastal zones.