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International Journal of Fisheries and Aquatic Studies 2022; 10(4): 87-92
E-ISSN: 2347-5129
P-ISSN: 2394-0506
(ICV-Poland) Impact Value: 76.37
(GIF) Impact Factor: 0.549
IJFAS 2022; 10(4): 87-92
© 2022 IJFAS
www.fisheriesjournal.com
Received: 12-09-2022
Accepted: 17-10-2022
George Owiti Osure
1]
Department of Biological
Sciences, Pwani University, P.O.
Box 195-80108, Kilifi, Kenya
2]
Faculty of Agriculture and
Natural Resources Management,
Kisii University, P.O. Box 408 -
40200 Kisii, Kenya
Albert Getabu
Faculty of Agriculture and
Natural Resources Management,
Kisii University, P.O. Box 408 -
40200 Kisii, Kenya
Christopher Mulanda Aura
Kenya Marine and Fisheries
Research Institute (KMFRI),
P.O. Box 1881 - 40100, Kisumu,
Kenya
Reuben Omondi
Faculty of Agriculture and
Natural Resources Management,
Kisii University, P.O. Box 408 -
40200 Kisii, Kenya
Evans Basweti
Faculty of Agriculture and
Natural Resources Management,
Kisii University, P.O. Box 408 -
40200 Kisii, Kenya
Corresponding Author:
George Owiti Osure
1]
Department of Biological
Sciences, Pwani University, P.O.
Box 195-80108, Kilifi, Kenya
2]
Faculty of Agriculture and
Natural Resources Management,
Kisii University, P.O. Box 408 -
40200 Kisii, Kenya
Population parameters and exploitation rates of four
commercial fish species of Awach Kibuon River:
Towards sustainable management of riverine fisheries
of the Lake Victoria Basin
George Owiti Osure, Albert Getabu, Christopher Mulanda Aura, Reuben
Omondi and Evans Basweti
DOI: https://doi.org/10.22271/fish.2022.v10.i6b.2751
Abstract
The study estimated population parameters of four leading commercial fish species of Awach Kibuon
River in Lake Victoria Basin, Kenya to inform management interventions for sustainability. Length data
were collected monthly from January to December 2020 and length-frequency analysis conducted in
FiSAT II software utilizing ELEFAN I Routines. Exploitation rates (E = 0.63) for Protopterus
aethiopicus (Heckel, 1851) and (E = 0.56) for Clarias gariepinus (Burchell, 1822) indicate overfished
stocks (E > Eopt) whereas exploitation rates (E = 0.31) for Synodontis victoriae (Boulenger, 1906) and (E
= 0.32) for Oreochromis niloticus (Linnaeus, 1758) signify optimal exploitation (E = Eopt). There were
year-round recruitments with bi-modal annual pulses in the populations of O. niloticus, S. victoriae, and
P. aethiopicus. These results are crucial for sustainable management of riverine fisheries in the Lake
Victoria Basin. This study recommends reduction of fishing pressure on P. aethiopicus and C. gariepinus
to enhance their sustainability.
Keywords: Population parameters, recruitment patterns, growth rates, mortality rates, exploitation rates
1. Introduction
Estimation of fish population parameters is important in understanding fish stock status and
subsequent planning for their sustainable management
[1, 2]
. Natural fish populations are
dynamic owing to varying environmental conditions and changing fishing pressures
[3]
.
Recruitment-, growth-, and mortality rates are the main drivers of fish population dynamics
[4,
5]
. Fish populations increase in size if recruitment and growth rates exceed mortality losses and
decrease if mortality rates are higher. Fish population parameters are influenced by
environmental conditions and life-history strategies of the fish species
[6]
. Long-lived species
exhibit bigger asymptotic lengths (L∞), low natural mortality rates (M), and low growth
curvatures (K) while short-lived species exhibit smaller asymptotic lengths (L∞), high natural
mortality rates (M), and high growth curvatures (K)
[7]
.
Recruitment refers to the number of fish that survive the spawning and nursery grounds to
enter the fishing grounds in a year. It is highly variable in natural fish populations, varying
from year to year
[1]
. The causes of high variability are unclear but competition, cannibalism,
predation, diseases, and water temperature are known to influence eventual recruitment to
adult fish populations
[9, 10]
. Growth refers to increase in length or weight of fish in the
population over time. Growth of individual fish in fish populations is described by the von
Bertanlanffy growth model: L(t) = L∞ × {1- exp (-K×(t-t
0
)), where L∞ is the asymptotic
length, K is the rate at which fish grows towards this size, and t
0
is the hypothetical age of fish
at which the length of fish is zero
[9]
. In temperate fish species, growth is measured by use of
annual and seasonal growth rings on scales, otoliths, vertebrae, and fin rays but in tropical fish
growth is estimated by length-frequency analysis due to lack of distinct seasonal and annual
growth rings. Commonly estimated growth parameters include asymptotic length (L∞) and
growth curvature (K) which are unique to each species but may vary for different populations
of the same species
[9]
.