Assessment of Productivity Status Using Carlson’s TSI and Fish Diversity of Goronyo Dam, Sokoto State, Nigeria

Hassan Muhammad Maishanu, Muhammad Murtala Mainasara, Ibrahim Muhammad Magami


Goronyo Dam is the largest lentic waterbody in Sokoto, it was constructed to serve as flood control and used for irrigation activities. The study was conducted to evaluate productivity status and fish diversity of Goronyo Dam in 2016. Water samples were collected monthly from the Dam at two sampling sites (Upstream and Downstream). Water samples were collected using sterilized sampling bottles and analyzed in the Laboratory for physicochemical variables and the diversity of fish was evaluated through the use of a structured questionnaire. Depth and transparency were the only variables that did not show any statistically significant difference between the months. Productivity status of the dam was evaluated using Carlson’s Trophic State Index. The downstream has high TSI value of 16.54 compared to upstream with 13.00. A diversity of fishes from the shows that 3 species were more abundant in the dam, these were; Mormyrops species, Alestes species and Clupeid species. Factors contributed to the survival of fish species were an abundance of water and plankton in the dam. While factors affecting the distribution of fish species were pollution and predation.


downstream; fish; Goronyo; productivity; upstream

Full Text:



1. Adeyemo, O. K., Adedokun, O. A., Yusuf, R. K., & Adeleye, E. A. (2008). Seasonal changes in physicochemical parameters and Nutrient load of river sediments in Ibadan city, Nigeria. Global Nest Journal, 10(3), 326–336.

[Google Scholar]

2. American Public Health Association, American Water Works Association, Water Environment Federation. (1999). Standard methods for the examination of Water and Wastewater. Retrieved from

[Google Scholar]

3. Bootsma, H. A., & Hecky, R. E. (1993). Conservation of the African Great Lakes: A Limnological Perspective. Conservation Biology, 7(3), 644–656.

[Google Scholar] [CrossRef]

4. Carlson, R. E. (1977). A trophic state index for lakes. Limnology and Oceanography, 22(2), 361–369.

[Google Scholar] [CrossRef]

5. Devi Prasad, A. G., & Siddaraju, P. (2012). Carlson’s Trophic State Index for the assessment of trophic status of two Lakes in Mandya district. Advances in Applied Science Research, 5, 2992–2996.

[Google Scholar]

6. Downing, J. A., Plante, C., & Lalonde, S. (1990). Fish Production Correlated with Primary Productivity, not the Morphoedaphic Index. Canadian Journal of Fisheries and Aquatic Sciences, 47(10), 1929–1936.

[Google Scholar] [CrossRef]

7. Fee, E. J., Shearer, J. A., DeBruyn, E. R., & Schindler, E. U. (1992). Effects of Lake Size on Phytoplankton Photosynthesis. Canadian Journal of Fisheries and Aquatic Sciences, 49(12), 2445–2459.

[Google Scholar] [CrossRef]

8. Gelman, A. (2005). Analysis of variance? Why it is more important than ever. The Annals of Statistics, 33(1), 1–53. doi: 10.1214/009053604000001048

[Google Scholar] [CrossRef]

9. Henry, J. G., & Heinke, W. G. (2005). Environmental Science Engineering (2nd ed.). New Delhi: Prentice Hall Publishers.

[Google Scholar]

10. Kumar, A. (2005). Fundamentals of Limnology. New Delhi: APH.

11. Lake Country Wateratlas. (2017). Trophic State Index (TSI). Retrieved from

12. Ranta, E. and Lindstrom, K. (1998). Fish Yield Versus Variations in Water Quality in The Lakes of Kuusamo, Northern Finland. Annales Zoologici Fennici, 35(2), 95–106.

[Google Scholar]

13. Rothhaupt, K. O. (2000). Plankton population dynamics: food web interactions and abiotic constraints. Freshwater Biology, 45(2), 105–109.

[Google Scholar] [CrossRef]

14. Sarkar, B. C., Mahanta, B. N., Saikia, K., Paul, P. R., & Singh, G. (2006). Geo-environmental quality assessment in Jharia coalfield, India, using multivariate statistics and geographic information system. Environmental Geology, 51(7), 1177–1196.

[Google Scholar] [CrossRef]

15. Shuter, B. J., & Ing, K. K. (1997). Factors affecting the production of zooplankton in lakes. Canadian Journal of Fisheries and Aquatic Sciences, 54(2), 359–377.

[Google Scholar] [CrossRef]

16. Umar, A. S., & Parakoyi, D. B. (2005). The prevalence and intensity of urinary schistosomiasis among school children living along the Bakalori dam, Nigeria. The Nigerian postgraduate medical journal, 12(3), 168–172.

[Google Scholar]

17. Union of Concerned Scientists. (2003). Changes in Lake Productivity and Eutrophication. Retrieved from

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM


  • There are currently no refbacks.

Copyright (c) 2018 Hassan Muhammad Maishanu, Muhammad Murtala Mainasara, Ibrahim Muhammad Magami

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.