A multivariate statistical framework for ecological assessment of Ikere Gorge Reservoir, south-western Nigeria

Abstract

Freshwater reservoirs provide critical water supply, fisheries and ecosystem services, yet increasing anthropogenic pressures threaten their ecological integrity. This study applies a multivariate statistical and data-driven analytical framework to assess the physicochemical conditions and biological structure in Ikere Gorge Reservoir, south-western Nigeria. During the dry season, four sampling sites (A–D) were surveyed for key physicochemical parameters, including temperature, pH, dissolved oxygen, nutrients, electrical conductivity and hardness, alongside biological assemblages comprising phytoplankton, zooplankton, macrophytes and fish. The integrated dataset was analysed using principal component analysis, hierarchical cluster analysis and Pearson correlation, supported by Shannon–Wiener diversity indices and a simplified water quality index. The first two principal components explained 84.9% of the total variance, with nutrient enrichment and trophic productivity dominating the first and water quality gradients related to oxygen availability influencing the second. Sites A and D exhibited higher dissolved oxygen and transparency, whereas Sites B and C showed elevated nutrients and conductivity. Phytoplankton diversity (H′ ≈ 3.9) exceeded that of other taxa, indicating moderate ecological balance. The water quality index values (61–66) classified the reservoir as mesotrophic with fair water quality. Despite limited spatial and temporal coverage, the study provides a robust baseline for reservoir monitoring and management.