Asian Journal of Fisheries and Aquatic Research

Aim: This study investigated common fish assemblages in four aquatic stations (Gbaji, Topo, Agboju and Ajegunle) in relation to physico-chemical parameters of its water and as well simulates numerical values of the physico-chemical parameters for year 2024.

Methodology: Data were collected and computed using standard methods and algorithm machine learning model respectively. Statistical tools employed include ANOVA and Pearson correlation (r) test. All the parameters (except turbidity, chemical oxygen demand and biochemical oxygen demand) were within standard permissible limits.

Results: The results of Pearson’s correlation analysis showed that increase in amount of fish species in the sampling stations was significantly and strongly linked to the decrease in value of biochemical oxygen demand (r = −0.571, P=.05), total dissolved solids (r= −0.696, P=.05) and conductivity (r=−0.882, P<0.01) while increase in number of fish species was significantly and strongly linked to the increase in value of dissolved oxygen(r= 0.991, P=.05).  However, salinity (r= 0.387), sulphate (r = 0.212) and turbidity (r= 0.282) had weak positive relationship with the number of fish species. The prediction by the machine learning algorithm modeling system revealed that at Agboju, total hardness would exceed permissible limit in February and September, carbondioxide (C0₂) in February, May and June, 2024.On the other hand, level of C0₂ at Ajegunle would exceed permissible limit in January, May, August and September, and total hardness in November, 2024. For both Agboju and Ajegunle, turbidity and chemical oxygen demand level would exceed limits throughout the months in year 2024.

Conclusion: Hence, effects of higher parameters could results in declination of distribution of demersal fish species which often shuttle between the water bottom and surface.