Numerical Simulations and Fish Diversity in Relation to Physico-chemical Parameters of Four Aquatic Stations in Badagry Division, Lagos, Nigeria
Mekuleyi Gabriel Olarinde *
Department of Fisheries, Lagos State University, Nigeria.
Joseph Olufemi Olabode
Department of Agric Education, Lagos State University of Education, Lagos, Nigeria.
Wusu Ashiribo Senapon
Department of Mathematics, Lagos State University, Nigeria.
Badmos Lateef Akorede
Department of Fisheries, Lagos State University, Nigeria.
Anetekhai Martins Agenuma
Department of Fisheries, Lagos State University, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
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.
Keywords: Fish diversity, numerical simulations, correlation, water quality
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References
Anwan HR, Anetekhai MA, Mekuleyi GO. Assessment of physico-chemical characteristics and heavy metal concentrations of stubbs Creek, Ibeno, Akwa Ibom, Nigeria. International Journal of Advanced Academic Research. 2021; 7(5):15-26.
Chindah AC. Response of periphyton community to salinity gradient in tropical estuary, Niger Delta. Pollution Journal of Ecology. 2004;52(1):83-89.
Ogbuagu DH, Ayoade AA, AC-Chukwuocha NB. Spatial dynamics in physicochemistry and bacterio- and myco-plankton assemblages of Imo River in a Niger-Delta community in Nigeria. African Journal of Microbiology Research. 2011; 5(8):872-887
Ogidiaka E, Esenowo IK, Ugwumba, AAA. Physio-chemical parameters and benthic macroinvertebrates of Ogunpa River at Bodija, Ibadan, Oyo State. European Journal of Scientific Research. 2012; 85(1):89-97.
Ayo-Olalusi CI, Ayoade AA. Biometric Characteristics of Sphyraena afra from the coastal waters of Lagos State. Journal of Biology, Agriculture and Healthcare. 2017; 7(8):1-9,3
Odulate DO, Samsons Y, Omoniyi IT. Multivariate analysis of fish species and environmental factors in marine coastal waters of the gulf of Guinea, Southwest Nigeria. Croatian Journal of Fisheries. 2014;72:55-62.
DOI: 10.14798/72.2.729
American Public Health Association (APHA).American Water Works Association and Water Pollution Control Federation, Washington, DC. Standard Methods for the Examination of Water and Wastewater. 2005;18th edition.
Mekuleyi GO, Anetekhai MA, Aderinola OJ, Adu AA. Environmental health status of some aquatic ecosystems in Badagry Division of Lagos State, Southwest, Nigeria. International Journal of Ecotoxicology and Ecobiology. 2019;4(4): 93-102.
United States Environmental Protection Agency (USEPA).Risk assessment, Regional Screening Levels (RSLs) for chemical contaminants at superfund sites-User’s guide and summary generic tables; 2018.
World Health Organization (WHO). Guidelines for drinking-water quality: Fourth edition incorporating the first addendum. Geneva: World Health Organization; 2017. Licence: CC BY-NC-SA 3.0IGO.T.
Ndimele PE, Kumolu-Johnson CA. Some aspects of the physicochemistry and heavy metal content of water, sediment and Cynothrissa mento (Regan, 1917) from Badagry Creek, Lagos, Nigeria. Trend in Applied Science Research. 2012;7:724-736.
Oladunjoye RY, Fafioye OO. Biochemical and physico-chemical characterization of Majidun River Water, South-West, Nigeria. International Journal of Environmental Chemistry and Ecotoxicology Research. 2016;1(1): 1-11.
Kuton MP, Ayanda IO, Uzoalu IA, Akhiromen DI, George A, Akinsanya B. Studies on heavy metals and fish health indicators in Malapterurus electricus from Lekki Lagoon, Lagos, Nigeria. Veterinary and Animal Science. 2021;12:1-7.
Clarke EO, Ndimele PE, Mekuleyi GO, Disu MO. Ecological impacts of sand mining on some aspects of fisheries of Lagos Lagoon Complex, Lagos State, Nigeria. Nigerian Journal of Fisheries and Aquaculture. 2019; 7(1):31-39.
Abdel-Baki A, Dkhil M, Al-Quraishy S. Bioaccumulation of some heavy metals in tilapia fish relevant to their concentration in water and sediment of Wadi Hanifah, Saudi Arabia. African Journal of Biotechnology. 2013;10(13):2541–2547.
Bolarinwa JB, Okeowo TO. The species composition and diversity of the coastal waters of Badagry, Lagos State, Nigeria. Global Journal of Agricultural Research. 2017;5(2):26-31.
Olawusi-Peters OO, Ayo-Olalusi CI. Finfish diversityin Agboyi Creek, Lagos State of Nigeria. Proceedings of the Conference of Fisheries Society of Nigeria. 2009;244-247.
Gawad SA, Abdo MH, Al-Afify AD.Variations in the macrobenthic invertebrates in relation to physico-chemical characteristics and WQI in Lake Qarun, Egypt. The Egyptian Journal of Aquatic Research. 2022;48(4):349-358.
Sohail M, Khattak MNK, Tauseef I, Korai AL, Shah A, Lashari KH. Ichthyodiversity in relation to physico-chemical parameters of River Swat. Sindh Univ Res J. 2014;46: 525-530.
Recknagel F. Applications of machine learning to ecological modeling. Ecological Modelling (Elsevier). 2001; 146:303-310.
Akita LG, Laudien J, Akrong M, Biney C, Nyarko E, Addo S. Physicochemical influence on the spatial distribution of faecal bacteria and polychaetes in the Densu Estuary, Ghana. African Journal of Environmental Science and Technology. 2020;14(6):139-158.
Niyoyitungiye L, Giri A, Mishra BP. Assessment of physico-chemical characteristics of water at selected stations of lake Tanganyika, Africa with Special emphasis on pisciculture purposes. International Journal of Basic and Applied Biology. 2019;6(3):211-217.