Stock Status of Brycinus Nurse (Ruppel 1832) in Oguta lake, Nigeria for Conservation and Management Strategies

Ogueri C, Adaka GS, Bunu AJ, Nwaka DE, Utah C, Wilfred PN, Ekeledo CB, Ogah J, Adebayo ET*


Abstract

The Fish stock status: growth rates, recruitment, Maximum Sustainable Yield (MSY), Mortality and Exploitation rate of B. nurse in Oguta lake, Nigeria, were investigated. The study was aimed at providing baseline information for the conservation and management strategies for the sustainability of its fishery. Standard lengths of 174,296 samples of B. nurse caught with assorted fishing gears were taken fortnightly from January to July, 2023. Data were analyzed by Electronic Length Frequency Analysis (ELEFAN II) fitted into the Von Bertalanffy Growth Model (VBGM). The VBGM for this study was L(t) = 35.70[1 – e-0.29(t – 3.05)]. Estimated Total Mortality (Z) was 1.98 yr-1, Fishing Mortality (F) = 0.26yr-1 and Exploitation rate (E) was 0.15yr-1. B. nurse was not over-exploited in Oguta Lake but the fishing is not operating at its MSY and the Reproductive load is low indicating that there should be restriction on the mesh sizes and closed fishing within the identified recruitment period of the Month of May, every year to avert the future collapse of B. nurse fishery in the lake.

Keywords: B. nurse, Oguta Lake, Stock status, MSY, Conservation, Exploitation, Management strategies

Introduction

The knowledge of fish stock status: growth rates, Age, recruitment (length/age of first capture), Mortality and Exploitation rates are necessary for the conservation and management of the fish. According to Fish Base1 Brycinus nurse also known as the Nurse tetra is presently listed as least concern by International Union for Conservation of Nature (IUCN). This classification indicates that the species is not considered threatened with extinction at the global level. However, Froese & Pauly2 opined that local population may still face threats and consistent monitoring is needed to ensure the species continues in good health.

Oguta Lake is the largest naturally-occurring lake in south-eastern Nigeria. Located at 5°42’33”N and 6°47’33”E, it is a source of water supply and Fisheries resources to neighboring settlements and beyond. The lake is imbued with abundant ichyo-fauna.3

Amongst the commercial fish species of Oguta Lake is B. nurse. Several studies have been carried out on B. nurse4-8but there are no published works on the stock status of the species in Oguta Lake.

Therefore, this study is aimed at investigating the stock assessment, viz; growth rates, recruitment, Maximum Sustainable Yield (MSY) Mortality and Exploitation rates of B. nurse in Oguta Lake in view of providing information for the conservation, sustainability and management policies for the fishery.

Materials and Methods

Four areas within the main basin of Oguta lake were designated as Sampling Stations Figure 1 Assorted Fishing gears; with mesh sizes > 2.5cm, hook and lines, basket and traps were used to catch fish fortnightly from January to July, 2023 by seasoned fisherfolks. Catches of local fish mongers were also examined. The catches were sorted into their different species using identification keys of Paugy9 and Adesulu and Sydenham.10 Standard Length (S.L) measurements of the samples were taken to the nearest centimeter (cm). The Data were grouped into 1-cm interval, monthly and analyzed using Electronic Length Frequency Analysis (ELEFAN II) of FiSAT (FAO – ICLARM Stock Assessment Tools) software explained in details by Gayanilo.11 then fitted into the Von Bertalanffy Growth Model (VBGM)
L(t) = L[1 – e-k(t – to)]
Where,
L(t) = Length of fish at age, t
L = Asymptotic Length (Maximum Length the fish will attain at that particular ecosystem)
K = the growth coefficient or the rate to which the fish grows to L
to = theoretical time when the fish length is zero

The total mortality (Z) was estimated by the length-converted catch curve12 and the natural Mortality (M) also estimated by using Pauly’s empirical formula. The Fishing Mortality (F) was Z – M, since Z = F + M.
The Exploitation rate (E) was calculated by the quotient E = F/Z.12

Relative Yield per recruit (Y’/R) was estimated by the model of Beverton and Holt13 as modified by Pauly and Soriano,13 incorporated in the FISAT software.  With reference to FAO14
Y’/R = 1 indicates that the fishery is operating at its Maximum Sustainable Yield (MSY).
Y’/R < 1 indicates that the fishery is not operating at its MSY and needs room for improvement.
Y’/R > 1 is not biologically possible as it would indicate that the fishery is producing more yield than is sustainable.

Probability of capture was estimated from the probability curve; L25 = capture of 25% of the stock, L50 = 50% fish capture and L75 = 75% of capture. Lc = Least Length/size of  first capture visible (Hoggarth 2006).
Length at first maturity (Lm) was derived from

(2 * L∞ )/3

Results

A total of 174,296 samples were examined ranging in size from 9 to 34cm with mean ± s.d (22.0 ± 1.47cm). In Figure 2 is shown the ELEFAN II plot while in Table 1 is presented the length-at-age and growth rates. The VBGM was:
L(t) = 35.70[1 – e -0.24(t – 3.05)]

The L  estimated was 35.70cm, Z = 1.98yr-1, M = 1.72 yr-1, F = 0.26yr-1 and E = 0.15yr-1. In Figure 3 is the length-converted catch curve. Recruitment per year is shown in Figure 4 indicating peak in the fifth month of May. Probability of capture plot is depicted on Figure 5 showing L25 = 9.00cm, L50 = 12.00cm and L75 = 29.00cm Lc = 9.00cm and Lm = 25.80cm.

The stock status of B nurse shown in Figure 6 indicates that Y//R < 1 meaning the fishery is not operating at its maximum sustainable Yield.

The analysis also indicated that the exploitation rate at which maximizes Yield per recruit produced Values of Emax = 0.421yr-1, E10 = 0.350yr-1 and E50 = 0.278yr-1. The Reproductive load Lc/L = 0.280 indicates over fishing.

Discussion

This study was for the provision of baseline information needed in the articulation of management strategies for sustainability in the Fishery of B. nurse and its conservation in Oguta Lake using ELEFAN II and VBGM predictions. The L estimated was S.L = 35.70cm and the K-value was 0.24yr-1. Komolafe and Arowomo asserts that K-value lower than one, indicates slow growth.

B. nurse could live up to 5years in Oguta Lake and the growth rate is fastest between 0 and 1 year (about 29.57cmYr-1) reducing at older ages with the slowest between age 4 and 5 years (about 0.04cmYr-1).

In the new Calabar River:15 L∞ was 24.46cm, K = 0.52yr-1, M = 1.05yr-1, F = 0.83yr-1 and E = 0.26yr-1. In comparison, M was higher than F in both ecosystems. Also in this present study, the Exploitation (E) was 0.15yr-1 indicating that B. nurse is not over-exploited in Oguta Lake, considering that theoretically16 optimal exploitation level is M = F = 0.5. Again, the Emax estimated in Oguta Lake was 0.421yr-1 while E (0.15yr-1) was lesser than the Emax of 0.421yr-1. This species was also not experiencing over-exploitation in the new Calabar River. This could be attributed to the fact that B. nurse is widespread and resilience in most ecosystems and therefore could withstand fishery pressure.17

However, the Yield per recruit (Y’/R) show values lesser than 1 in Figure 6 implying that the stock is not operating at its Maximum Sustainable Yield (MSY). This calls for serious management concerns.

In addition, the Reproductive load of quotient (Lc/L=0.28) is too low and indicates that the stock cannot carry much Fishery Pressure in the Future as the fishes are being caught before they reach half their maximum potential size going by Froese18 postulations.

With the Fishing in Oguta Lake being unregulated, there is need to place restriction on the use of small mesh sizes for capture of B. nurse as too many small-sized individuals are being caught, which could be seen in the values of the Reproductive Load. The management strategy should focus on the closing of the Fishing season in the Lake around the identified recruitment peak of the month of May every year to avert future collapse of the Fishery.19

Acknowledgments

None.

Funding

This Research Article received no external funding.

Conflicts of Interest

Regarding the publication of this article, the authors declare that they have no conflicts of interest.

References

  1. 1. Fishbase. Fishbase: www electronic Publication. 2024.
  2. 2. Froese R. Cube Law, condition factor and weight–length relationships, history, meta–analysis and recommendations. Journal of Applied Ichthyology. 2006;22(4):241-253.
  3. 3. Nwadiaro CS. Ichthyofauna of Lake Oguta, a shallow lake in southeastern, Nigeria. Archivur Hydrobiologie. 1989:pp.463-475.
  4. 4. Azeroual A, Moelants T. Brycinus nurse. The IUCN Red list of threatened species. 2010;3.
  5. 5. Odo EG, Nwani RD, Eyo EJ. The Fish fauna of Anambra River basin, Nigeria: species abundance and morphometry. Revista de biologia tropical. 2009;57(1-2):177-186.
  6. 6. Iyabo UB. Length–weight relationship, condition factor and diet composition of Brycinus nurse (Characiformes: Alestidae) in a tropical flood river basin. Continental Journal of Fisheries and Aquatic Science. 2014;8(1):25-34.
  7. 7. Murray AM, Stewart KM. Phylogenetic relationships of the African genera, Alestes and Brycinus (Teleostei Characiformes, Alestidae). Canadian Journal of zoology. 2002;80(II):1887-1899.
  8. 8. Mohammad ATM, Mahmoud ZN, Abushama HM. Morphometric measurements, Meristic counts and molecular identification of Alestes dentex, Alestes baremoze, Byrcinus nurse and Brycinus macrolepidotus from the River Nile at Kreima. The open Biology Journal. 2019;7(1):25-38.
  9. 9. Paugy D. Alestidae. In: Paugy D, Leveque C, Teugels GG. The Fresh and Brackish Water fishes of West Africa Vol. 1. Coll faune et. flore tropical 40. Institute de recherché de developpement Paris, France, Musuem national d’histoire naturelle, Paris France and Musee royal de l’Afrique Central, Tervuren, Belgium. 2003:pp.457.
  10. 10. Adesulu EA, Sydenham DHJ. The Freshwater and Fisheries of Nigeria. Macmillan Nigeria Publishers, Lagos, Nigeria. 2007:pp.347.
  11. 11. Gayanilo FC, Sparre P, Pauly D. FAO-ICLARM Stock Assessment Tools II (FISAT II) User’s guide FAO Computerized Information series (Fisheries). No 8, revised version, FAO, Rome. 2005.pp.168.
  12. 12. Pauly D. Fish population dynamics in tropical waters: a manual for use with programmable calculators. ICLARM stud Rev. 1984;8:325.
  13. 13. Pauly D, Soriano MC. Some practical extensions to Beverton and Holts’, (1966) relative yield per recruit mode. In: Maclean JC, Dizon LB, Hosillis LV, Editors. The first Asian Fisheries forum, Asian Fisheries society, Monila, Philippines. 1986;491-496.
  14. 14. FAO. Food and Agriculture Oganization. Review of the state of World Marine Fishery Resources which discusses MSY and its application in global fisheries. FAO Tech pap. 2011.pp.569.
  15. 15. Olopade A, Dienye, Nworgu UC. Estimation of Growth Mortality and Exploitation of Brycinus nurse and B. macrolepidotus (Family: Alestidae) from the new Calabar River, Nigeria. Indonesia Fisheries Research Journal. 2019;pp.2502-6569.
  16. 16. Hoggarth DD, Abeyasekera S, Arthur A, Beddington JR, Burn RW, et al. Stock assessment and Fishery management. A framework guide to the FMSP stock assessment tools. FAO Fisheries Technical Paper No. 487, Rome, Italy. 2006:pp.261.
  17. 17. Ahmad IM, Yola ID, Suleiman N. Mortality and Exploitation Rates of Challawa George Dam Fishes, Kano state, Nigeria. Journal of Fisheries and Livestock Production. 2018;6:262.
  18. 18. Froese R, Pauly. Fishbase. 2024.
  19. 19. Hilborn R, Walters CJ. Quantitative Fisheries stock Assessment. Published by Springer New York NY. 2013.

Article Type

Research Article

Publication history

Received date: 21 February, 2025
Published date: 10 March, 2025

Address for correspondence

Adebayo ET, Department of Biosciences and Biotechnology, Faculty of Science, University of Medical Sciences Ondo City, Ondo State, Nigeria

Copyright

© All rights are reserved by Adebayo ET

How to cite this article

Ogueri C, Adaka GS, Ajima MNO, Anyanwu CN, Utah C, Wilfred PN, Ekeledo CB, Ogah J, Adebayo ET. Stock Status of Brycinus nurse (Ruppel 1832) in Oguta lake, Nigeria for Conservation and Management Strategies: Research Article. Glob Scient Res Env Sci. 2025;5(1):1–5. DOI: 10.53902/GSRES.2025.05.000535

Author Info

Ogueri C,1 Adaka GS,1 Ajima MNO,1 Anyanwu CN,1 Utah C,1 Wilfred PN,1 Ekeledo CB,2 Ogah J,2 Adebayo ET3*

1Department of Fisheries and Aquaculture Technology (FAT), Federal University of Technology, Nigeria

2Department of Fisheries Technology, Federal Polytechnic, Nigeria

3Department of Biosciences and Biotechnology, University of Medical Sciences Ondo City, Nigeria

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