Spatial variation of soil physicochemical properties as influenced by land use systems in Southwest Nigeria

Soil physicochemical properties vary considerably across land use systems. Yet, as of 2025, spatially explicit quantitative assessment that integrate advanced multivariate statistical technique with GIS-based mapping remain limited in Okitipupa/Irele corridor of Ondo State, Southwest Nigeria. This study characterised twelve soil physicochemical properties pH, total organic carbon (TOC), total organic matter (TOM), total nitrogen (N), available phosphorus (P), exchangeable sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), exchangeable acidity (EA), cation exchange capacity (CEC), and base saturation (BS) as well as soil textural fractions (sand, clay, silt) at 0–30 cm and 30–60 cm depths across five contrasting land use types (farmland, oil palm plantation, forest land, watershed, and residential area) in both Okitipupa and Irele LGAs. A total of 30 composite soil samples per LGA were collected using a systematic strip-sampling approach. The statistical framework integrated descriptive statistics, Kolmogorov–Smirnov normality testing, coefficient of variation (CV) profiling, skewness–kurtosis analysis, one-way ANOVA with Duncan's Multiple Range Test, Pearson correlation matrices, principal component analysis (PCA; 3 PCs explaining 73.4% of variance), and Ward's method hierarchical cluster analysis (HCA). GIS-based spatial distribution maps for pH, TOC, N, P, K, Ca, Mg and CEC were generated using ArcGIS 10. Forest land consistently recorded the highest TOC (2.97–3.36 g kg⁻1), TOM (5.14–5.79 g kg⁻1), total N (0.15–0.27 g kg⁻1), and CEC (10.74–11.74 cmol kg⁻1), while farmland showed the lowest organic matter and most acidic conditions. PCA resolved a dominant organic matter–nutrient axis (PC1: 46.5%), a nitrogen–exchangeable cation axis (PC2: 15.5%), and a phosphorus/sodium mobility axis (PC3: 11.4%). HCA distinguished forest land and watershed as naturally enriched clusters, clearly separating them from anthropogenically disturbed farmland and the oil palm–residential cluster. These findings underscore the critical role of land use in regulating soil fertility gradients and provide spatially explicit evidence for precision soil management in the humid Nigerian tropics.

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Publication Details

Journal
Discover Soil.
Published
2026-09-28
DOI
https://doi.org/10.1007/s44378-026-00321-x
Primary Topic
Soil Geostatistics and Mapping
Type
article
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Spatial variation of soil physicochemical properties as influenced by land use systems in Southwest Nigeria

Olojugba Michael Rotimi, Wilson Yomi Brown, Ariyo Adetoyosi Catherine
Discover Soil.
Soil Geostatistics and Mapping
article

Spatial variation of soil physicochemical properties as influenced by land use systems in Southwest Nigeria

Olojugba Michael Rotimi, Wilson Yomi Brown, Ariyo Adetoyosi Catherine
article en

Abstract

Soil physicochemical properties vary considerably across land use systems. Yet, as of 2025, spatially explicit quantitative assessment that integrate advanced multivariate statistical technique with GIS-based mapping remain limited in Okitipupa/Irele corridor of Ondo State, Southwest Nigeria. This study characterised twelve soil physicochemical properties pH, total organic carbon (TOC), total organic matter (TOM), total nitrogen (N), available phosphorus (P), exchangeable sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), exchangeable acidity (EA), cation exchange capacity (CEC), and base saturation (BS) as well as soil textural fractions (sand, clay, silt) at 0–30 cm and 30–60 cm depths across five contrasting land use types (farmland, oil palm plantation, forest land, watershed, and residential area) in both Okitipupa and Irele LGAs. A total of 30 composite soil samples per LGA were collected using a systematic strip-sampling approach. The statistical framework integrated descriptive statistics, Kolmogorov–Smirnov normality testing, coefficient of variation (CV) profiling, skewness–kurtosis analysis, one-way ANOVA with Duncan's Multiple Range Test, Pearson correlation matrices, principal component analysis (PCA; 3 PCs explaining 73.4% of variance), and Ward's method hierarchical cluster analysis (HCA). GIS-based spatial distribution maps for pH, TOC, N, P, K, Ca, Mg and CEC were generated using ArcGIS 10. Forest land consistently recorded the highest TOC (2.97–3.36 g kg⁻1), TOM (5.14–5.79 g kg⁻1), total N (0.15–0.27 g kg⁻1), and CEC (10.74–11.74 cmol kg⁻1), while farmland showed the lowest organic matter and most acidic conditions. PCA resolved a dominant organic matter–nutrient axis (PC1: 46.5%), a nitrogen–exchangeable cation axis (PC2: 15.5%), and a phosphorus/sodium mobility axis (PC3: 11.4%). HCA distinguished forest land and watershed as naturally enriched clusters, clearly separating them from anthropogenically disturbed farmland and the oil palm–residential cluster. These findings underscore the critical role of land use in regulating soil fertility gradients and provide spatially explicit evidence for precision soil management in the humid Nigerian tropics.

Discover Soil.Vol. 3(1)
Life in Land
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Soil Geostatistics and Mapping
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Spatial variation of soil physicochemical properties as influenced by land use systems in Southwest Nigeria — Olojugba Michael Rotimi, Wilson Yomi Brown, et al. · Discover Soil. (2026) | TGRS Research Map | TGRS