




































East


East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, Issue. 1, 28-41 
   

 

 

 

*Corresponding author: 

  Email:  buchale.shishitu@yahoo.com     https://dx.doi.org/10.4314/eajbcs.v4i1.3S 
 
 

 

 

Buchale Shishitu Shija*,  and Atnafu W/yohans Firew 

Fisheries and Aquaculture, Southern Agricultural Research Institute (SARI), Arba Minch Agricultural 

Research Center, P.O.Box 2228, Arba Minch, Ethiopia 

 

 

KEYWORDS:  

Ayalew reservoir;  

Cohort analysis; 

Condition factor; 

Cyprinus carpio;  

Length-weight 

relationship;  

Population dynamics 

parameters 

 

 

 

 

 

ABSTRACT 

Common carp (Cyprinus carpio) is an imported fish species in Ayalew 

reservoir. The study was intended at estimating important population 

dynamics parameters and production potential in the reservoir. Total length 

(TL) and total weight (TW) data were collected from a total of 276 fish 

samples (141 females and 135 males). The obtained data were analyzed 

using FiSAT II software. The population and production potential were 

assessed by using Jones length based cohort analysis model and length-based 

Thompson and Bell yield prediction models. The average total length was 

26 cm and the dominant length groups ranged from 17 to 33 cm were 87%. 

The length-weight relationship parameters were (TW = 0.0565TL2.53, R2 = 

0.95) and the condition factor K = 1.29. The parameters of von Vertalanffy 

growth curve were L∞ = 41 cm, k = 0.52, to = -0.29, θ = 2.9 and A0.95 = 5.5 

years. The assessed values of the total, natural and fishing mortalities were 

Z = 1.23, M = 0.55 and F = 0.68, respectively. The current exploitation rate, 

0.55, indicates slightly overexploitation. The estimated fish population and 

the annual fish yield were 59,304 and 1.5 tons, respectively. However, 

investigation on reproductive biology, limnolocal aspects and stock 

enhancements should be required for the sustainability of these resources.  

 

INTRODUCTION 

Common carp (Cyprinus carpio) is considered to 

be a very important aquaculture species in many 

Asian and some European countries. It is widely 

distributed and frequently considered a nuisance 

species outside its native range (Penne and 

Pierce, 2008; Mohammad, 2015). The Common 

carp is one of the most common freshwater fish 

invaders worldwide, creating adverse effects on 

water quality and impacting ecosystem structure 

and function (Letvin et al., 2017). It is highly 

adaptable to new environments and can alter the 

biotic and abiotic integrity of aquatic ecosystems 

(Bajer et al., 2012). 

East African Journal of Biophysical and Computational Sciences 

Journal homepage : https://journals.hu.edu.et/hu-journals/index.php/eajbcs 
  

Hawassa University

College of Natural & Computational Sciences

Year 2021

Volume xx No xx

Population Dynamics and Yield Estimation of Common Carp (Cyprinus carpio, Linnaeus, 1758) 

in Ayalew Reservoir, Gamo Zone, Southern Ethiopia 

 

 
Research article

mailto:buchale.shishitu@yahoo.com
https://dx.doi.org/10.4314/eajbcs.v4i1.3S


East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

29 
 

In Ethiopia, Cyprinus carpio was first introduced 

to Aba Samuel Dam (Awash River basin) in 1940 

from Italy (Getahun, 2017). Later, it has been 

introduced in Lake Ziway in the late 1980s 

(FAO, 1997; Abera et al., 2015). For food 

security purpose, C. carpio was introduced in 

highland lakes such as Ashengie, Ardibo, and 

Maybar and the introduction was successful 

(Golubtsov and Darkov, 2008). 

Ayalew reservoir is one of the highland water 

bodies in Gamo Zone Chencha woreda. 

According to gathered information from 

Chencha woreda, C. carpio was introduced in 

Ayalew reservoir in the late 1980s by National 

Fishery and Aquatic Life Research Center. After 

some years later, the fish was adapted and has 

been observed by the local community in the 

reservoir. Since then, there was no any 

documented information about the population 

dynamics of C. carpio in Ayalew reservoir. For 

sustainable management and utilization, 

information on the population dynamics and 

production potential is very important for this 

species. Therefore, the objective this study was 

to estimate the population dynamics and 

production potential of C. carpio in the reservoir.  

MATERIALS AND METHODS 

Description of the study area 

Ayalew reservoir is found in Chencha woreda in 

Gamo Zone. It is situated at the coordinates of 

06°25′068″N latitude and 037°57′368″E 

longitude with an elevation of 2861 meters above 

sea level. The area of the reservoir is about 4.37 

ha or 0.0437 km2 with a maximum depth of 5.3 

meters.  

.

 

Figure 1. Location of Ayalew reservoir in Chencha woreda, Gamo zone, Southern Ethiopia 



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

30 

Methods of sampling and data collection 

Ten youths were trained about fish catching and 

data recording systems. For the trained youths a 

boat and four monofilament gill nets with 3.5 

mesh sizes were delivered for the research 

activities. Two data collectors were selected 

based on their skill and involved in data 

collecting process. The gillnets were deployed 

with plastic bottles as floats across the reservoir 

at 5:00 PM and collected at 7:00 AM the next 

morning. Immediately following capture, the 

total length (TL) and weight (TW) of the fish 

were measured, using a measuring board and 

sensitive balance, to the nearest 0.1 cm and 1 g, 

respectively. Data were collected weekly for 

eight months, from October 2021 to May 2022. 

Length-weight relationship and condition 

factor 

Length-weight relationship was calculated using 

power function (Le Cren, 1951). 

TW = 𝑎𝑇𝐿𝑏------------------------------------------ [1] 

Where, 

TW = total weight (g), a = the intercept, TL = 

total length (cm), b = the slope of length-weight 

regression 

 

The Fulton’s condition factor (K) is often used to 

reflect the nutritional status or well-being of an 

individual fish. It was calculated by using the 

formula described by Fulton (1904) which 

indicated below. 

K = 
𝑇𝑊

𝑇𝐿3
∗ 100----------------------------------------- [2] 

Where, 

 K = Fulton’s condition factor 

 TW = total weight of fish in gram (g)  

 TL = total length of fish in centimeter 

(cm) 

Data summarization and analysis  

Catch data were compiled and summarized in a 

format suitable for the Jones length-based cohort 

analysis and the length-based Thompson and 

Bell yield prediction models. Microsoft Office 

Excel (2010) was employed for both data 

summarization and subsequent analysis. 

Estimating growth parameters 

The K-scan technique available in the ELEFAN 

I module of the FiSAT II software was utilized to 

estimate asymptotic length (L∞) and growth rate 

(k) from the length-frequency data. Pauly's 

empirical formula (1979) was then applied to 

calculate the theoretical age at length zero (t0)  

 

Log (–to) = –0.392 – 0.275*log L∞–1.038*log k ----

------------------------------------------------------------[3] 

 

Where, 

 to = is the theoretical age at which fish 

would have at zero length. 

 L∞ = asymptotic length, k = von 

Bertalanffy growth rate constant 

 

Growth performance indexes were calculated as 

Munro and Pauly (1983): 

 

θ = log(k) + 2 × log(L∞) ----------------------- [4] 

 

Where, θ = growth performance index 

The length at first maturity (L50) was computed 

as Froese and Binohlan’s (2000) equation: 

 

log(L50) = 0.8979 × log(L∞) – 0.0782 ------------- [5] 

 



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

31 

Estimating mortality parameters based on 

length composition data 

For the estimation of total mortality rates, 

linearized length converted catch curve method 

was applied and the mortality parameters were 

calculated based on the following formula 

(Pauly, 1984). 

∆t = 1/k*Ln[(L∞ - L1)/[(L∞ - L2)] -----------------[6] 

 

t (L1+L2)/2 = -1/k{Ln[(1-(L1+L2)/2/(L∞)] --------[7] 

 

Ln{[C(L1, L2)]/[∆t(L1, L2)]} = a- Z*t(L1+L2)/2 ---[8] 

 

Where: ∆t = is age interval between L1 and L2 or 

the time taken by fish of length L1 to reach length 

L2 

 t(L1+L2)/2 = age of the average 

consecutive length groups (X variable) 

 Ln{[C(L1,L2)]/[∆t(L1, L2)]} = Y 

variable  

The natural mortality coefficient (M) was 

estimated using Taylor’s method (1958) as 

follows: 

 

M = -ln(1-0.95)/A0.95------------------------------ [9] 

 

Where, A0.95 = longevity, the age at which 99% 

of the cohort would be dead as a result of natural 

means (Spare and Venema, 1997). 

 

A0.95 = to+2.996/k ------------------------------- [10] 

Where, to = is the theoretical age at which fish 

would have at zero length; 

k = von Bertalanffy growth rate constant 

To obtain total mortality, regression analysis was 

conducted between X and Y variables as 

described in formula 7 and 8, respectively. 

 

Total mortality (Z) = fishing mortality (F) + natural 

mortality (M) ---------------------------------------- [11] 

 

Then, the fishing mortality rate (F) was obtained 

by subtracting M from Z.  

 

Estimating population sizes and fishing 

mortalities by length group (Jones, 1984)  

Jones length-based cohort analysis model was 

used to estimate the population size and fishing 

mortality coefficient of C. carpio by length 

groups. This was done in the following three 

steps: 

i) Population number estimate of the largest 

length group in the catch. 

 

N(largest L) = C(Largest L)*(Z Largest L/F Largest 

L ) ----------------------------------------------------- [12] 

 

Where, N (largest L) = the population of the 

largest length group in the catch; 

C(largest L) = the catch of the largest length 

group; 

Z(largest L) = the total mortality rate of the 

largest length group in the catch; 

F(largest L) = the fishing mortality rate of the 

largest length group in the catch; 

C(L1, L2) = the catch of the length groups of 

N(L1) 

 

ii) Population numbers estimate of consecutively 

younger length groups in the catch. 

N(L1) = [N(L2) * H(L1, L2) + C(L1, L2)] * H(L1, L2) -

---------------------------------------------------------- [13] 

 

Where, N(L1) = The population number of L1 

(younger) fish 

 N(L2) = The population number of L2 

(older) fish 



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

32 

 H(L1, L2) = the fraction of N(L1) fish that 

survived natural death as it grows from length L1 

to L2 and computed as the following equation 

(Jones, 1984). 

 

H(L1, L2) = [(L∞ - L1)/ (L∞ - L2)] (M/2k) ------- [14] 

 

Where, L∞ = the asymptotic length (cm) of C. 

carpio attained at mature size; 

  

L1 and L2 = consecutive length groups of fish 

(cm) that contributed to the fishery; 

K = von Bertalanffy growth rate constant (yr-1);  

M = the rate of natural mortality coefficient  

 

iii) Fishing mortality rate estimate of the 

respective length groups. 

 

Fishing mortality values for each length group 

was estimated using the equation as follows: 

 

F(L1, L2) = (1/∆t) * ln[N(L1)/N(L2)] – M -------- [15] 

 

Where, F(L1, L2) = Fishing mortality coefficient 

pertaining to the respective length group;  

N(L1), N(L2) and M are as defined above.  

 

To know the status of the stock, the exploitation 

rate (E) was estimated from mortality parameters 

as: E = F/Z. The exploitation rate (E) equal to 0.5 

is considered as optimum level of exploitation; 

whereas less than 0.5 refers to under exploitation 

and greater than 0.5 refers to overexploitation 

(Gulland, 1971). 

 

Thompson and Bell (1934) yield prediction 

procedure 

Step 1) Estimating the total annual yield obtained 

under the current level of fishing 

i) Estimating the yield obtained per year 

from each length group 

Yield from each length group obtained per year 

(Y(L1, L2) - is catch in number per length group 

per year (C(L1, L2) multiplied by the average 

weight of each length group i.e., 

 

Y(L1, L2) = C(L1, L2) * W(L1, L2) --------------- [16] 

 

Where, Y(L1, L2) = the yield (weight) of fish 

obtained per year from respective length group;  

C(L1, L2) = total annual catch of fish obtained 

from respective length group;  

W(L1, L2) = the mean weight of each length 

group estimated using equation 

 

W(g) = a* Lb ---------------------------------------- [17] 

Where,  

W(g) = the average weight of each length group, 

L = the average length (cm) of each length group 

i.e., L = (L1+L2)/2 in which L1 and L2 are the 

length intervals of consecutive length groups. ‘a’ 

and ‘b’ are values of the regression coefficients.  

ii. Estimated yield was obtained from all length 

groups per year by adding up the 

contribution of each length group. 

RESULTS AND DISCUSSION  

Length-weight relationship and Fulton’s 

condition factor 

The values of the regression coefficient “b” for 

females (n =141), males (n =135) and combined 

sexes (n =276) obtained from the length-weight 

relationship by using the best-fit regression of 

power function gave 2.51, 2.47 and 2.53, 

respectively (Fig. 2). Analysis of variance (one-

way ANOVA) showed the significant differences 

between the regression coefficient “b” and the 

cubic value of “b” (3) (P < 0.05).  



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

33 

As indicated in Table 1, the t-test also revealed 

that the presence of significant difference 

between the regression coefficient “b” in female, 

male and combined sexes (P < 0.05).  

 

 

 

 

Females

TW = 0.0611TL2.51

R² = 0.9418

n = 141

0

100

200

300

400

500

600

700

0 10 20 30 40 50

T
o
ta

l 
w

ei
g
h

t 
(g

)

Males

TW = 0.0664TL2.47

R² = 0.9324

n = 135

0

100

200

300

400

500

600

0 10 20 30 40 50

T
o
ta

l 
w

ei
g
h

t 
(g

)



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

34 

 

Figure 2. Length-weight relationship of C. carpio from Ayalew reservoir  

In this study, the length-weight relationship 

showed that C. carpio showed a negative 

allometric growth. Values of b equal to 3 indicate 

that the fish grows isometrically; values other 

than 3 indicate allometric growth (Tesch, 1971). 

The b value is often 3.0 and generally between 

2.5 and 3.5 (Froese, 2006). The b values in fish 

is species specific and therefore varies with sex, 

age, seasons, physiological conditions, growth 

increment and nutritional status of fish (Ricker, 

1975; Bagenal and Tesch, 1978). Mert and Bulut 

(2014), Saylar and Semra (2014), Yilmaz et al. 

(2012),  Ünver and Yildirim (2011), and Richard 

et al. (2018) also reported negative allometric 

growth for C. carpio in different water bodies 

worldwide, and their b values were 2.9, 2.8, 2.83, 

2.89 and 2.75, respectively. 

However, positive allometric growth values for 

this species were documented by (Karataş et al., 

2007; Kirankaya and Ekmekçi, 2004), who 

reported b values of 3.21 and 3.022, respectively. 

The difference in the results of the current and 

previous publication might possibly be 

associated with reasons related to ecosystem and 

biological phenomena such as seasons, feeding 

behavior, cmpetition for fd, and maturity 

stages. 

 

Table 1. Regression static parameters of C. carpio. 

Parameters  Female Male Combined 

a value 0.0611 0.0664 0.0565 

b value 2.5135 2.4698 2.5303 

Std. Error (Sb) 28.61 30.05 29.58 

R2 0.9418 0.9324 0.9451 

t-calculated  48.62 42.55 69.26 

t-critical (5%) 1.97 1.97 1.97 

No of observation 141 135 276 

Significance  0.000 0.000 0.000 

Combined

TW = 0.0565TL2.53

R² = 0.9451

N = 276

0

100

200

300

400

500

600

700

0 10 20 30 40 50

T
o
ta

l 
w

ei
g
h

t 
(g

)

Total length (cm)



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

35 

 

Monthly mean Fulton’s condition factor (K) 

ranged from 1.15 to 1.39 for females, 1.16 to 1.44 

for males and 1.23 to 1.38 for combined sexes 

(Table 2). The average K value for females, 

males and combined sexes were 1.28, 1.30 and 

1.29, respectively. Females exhibited their 

lowest condition factor (1.15) in February and 

their highest (1.39) in May. In contrast, the 

lowest value for males (1.16) was recorded in 

November, and the peak value (1.44) occurred in 

April. For combined sexes, the minimum value 

(1.23) was recorded in November and the highest 

(1.38) in April and May. Fulton’s Condition 

factor indices have been widely used as 

indicators of relative health and depend on the 

environmental conditions and food availability. 

April and May are highly rainy season in the 

study area and might be the reason for the 

variation in monthly condition factor. The results 

indicated that there was no significant difference 

between sexes as well as month’s interaction in 

mean condition factor of C. carpio (P > 0.05).   

Table 2.The mean monthly Fulton’s condition factor of female, male and combined C. carpio in 

Ayalew reservoir. 

Moths  Female Male Combined 

October 1.28 1.21 1.25 

November 1.33 1.16 1.23 

December 1.23 1.30 1.26 

January 1.28 1.38 1.33 

February 1.15 1.32 1.25 

March 1.22 1.25 1.24 

April 1.32 1.44 1.38 

May 1.39 1.36 1.38 

Average 1.28 1.30 1.29 

 

Morton and Routledge (2006) divided the K 

values into five categories as very bad (0.8–1.0), 

bad (1.0–1.2), balance (1.2–1.4), good (1.4–1.6) 

and very good (> 1.6). On the other hand, Ayoade 

(2011) suggests that the Fulton’s condition factor 

higher than one is a good fish health condition. 

Based on the five categories above, the condition 

factor in the present study was not in the range of 

1.4-1.6 and C. carpio in the reservoir was not in 

a good health condition. This might be due to 

anthropogenic factor that affects the limnological 

aspects of the reservoir. 

The length cmpsition of sampled catch and 

estimated annual catch of C. carpio 

The mean total length catch composition and 

yield contribution of C. carpio are indicated in 

Fig. 3. The compositions were ranged from 13 to 

39 cm with an average length of 26cm. The mean 

length ranged from 17 cm to 33 cm were about 

87% of the total catch and had a high contribution 

in fish yield. 



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

36 

 
Figure 3. Size structure of C. carpio harvested from Ayalew reservoir 

Estimation of growth and mortality 

parameters  

The estimated asymptote length (L∞) and the 

length at first maturity (L50) were 41 cm and 

23.44 cm, respectively. The annual growth 

constant (k) and the growth performance index 

Phi (θ) were 0.52 yr-1 and 2.9, respectively (Fig. 

4). The theoretical age at which fish would have 

at zero length (to) was -0.29 and the Longevity 

(A0.95), the age at which 99% of the cohort 

would be dead as a result of natural means was 

5.5 years.  

The fish species with a growth constant (k) value 

greater than or equal to one (1) is a fast growing 

fish species (Gulland, 1983; Sparre and Venema, 

1998). Besides the genetic makeup which 

determines the growth potential of the fish 

species, food availability, environmental 

conditions and fishing effects could affect the 

growth performance index of a particular fish 

species (Getabu, 1992). According to Sambo and 

Haruna (2012), the growth performance index is 

a function of L∞ in which increase in L∞ leads to 

an increase in the growth performance index. The 

growth constant (k) value ranges from 0.06 to 

0.48, 0.12 to 0.75 and 0.11 to 0.69 for C. carpio 

species that live naturally in rivers, lakes and 

reservoirs, respectively (Fish Base, 2011). 

The growth constant (k) of C. carpio in Ayalew 

reservoir was 0.52 yr-1and laid into the range of 

0.11-0.69 for the C. carpio fish populations that 

live naturally in water of reservoirs. 

0

2

4

6

8

10

12

14

13 15 17 19 21 23 25 27 29 31 33 35 37 39

C
at

ch
 c

o
m

p
o

si
ti

o
n

 (
%

)

Mean total length (cm)



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

37 

 

Figure 4. ELEFAN I K- scan routine FiSAT II 

output for C. carpio from Ayalew reservoir. 

A length composition data prepared for a linear 

regression analysis was established between X 

and Y variables for estimation of total mortality 

(Table 3).  

Table 3. Parameters for length-based catch curve analysis  

Length 

group (cm) 

 

Annual 

Catch 

C(L1,L2) 

    X Y 

k L∞ 

(cm) 

∆t (L1,L2) (L1+L2)/2 t(L1+L2)/2 Ln(C(L1,L2)/∆t) 

16-18 859 0.52 41 0.16 17 1.03 8.59 

18-20 967 0.52 41 0.17 19 1.20 8.62 

20-22 859 0.52 41 0.19 21 1.38 8.40 

22-24 564 0.52 41 0.21 23 1.58 7.88 

24-26 591 0.52 41 0.24 25 1.81 7.81 

26-28 967 0.52 41 0.28 27 2.07 8.16 

28-30 644 0.52 41 0.32 29 2.36 7.60 

30-32 591 0.52 41 0.39 31 2.71 7.33 

32-34 483 0.52 41 0.48 33 3.14 6.91 

34-36 349 0.52 41 0.65 35 3.70 6.29 

36-38 107 0.52 41 0.98 37 4.48 4.69 

38-40 81 0.52 41 2.11 39 5.81 3.64 

 

Based on the linearized length-based catch curve 

analysis, the mortality parameters were 

estimated. As indicated in figure 5, the slope of 

the regression line (b) is -1.23 and hence, the 

estimated total mortality rate (Z) was 1.23 yr-1. 

Out of the total mortality, natural mortality rate 

(M) and fishing mortality rate (F) were 0.55 yr-1 

and 0.68 yr-1, respectively. Using these mortality 

estimates, the exploitation rate (E) was computed 

as 0.55 and indicates that the C. carpio is slightly 

overexploited. 



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

38 

Based on the computed exploitation rate (E), the 

C. carpio in Ayalew reservoir was overexploited 

and the fish population was not abundant enough 

to utilize the resource sustainably. The 

exploitation rate (E) of a fish stock is at its 

maximum level and sustainable if the value of F 

was equivalent with or same with the value of M 

or the rate of exploitation (E) had value of 0.5 

(Gulland, 1983). 

 

Figure 5. Linearized length-based catch curve of C. carpio from Ayalew reservoir 

Estimated population sizes and current yield 

by length group 

The estimated population number and annual 

yield of C. carpio in the study area were about 

59, 304 and 1.5 tons, respectively (Table 4). The 

recruitment pattern of the fish was year-round 

with two peak recruitment period in the year. The 

peak recruitment takes place twice a year, in 

April and July to August for this particular fish 

species (Figure 6). The projected annual 

recruitment of C. carpio in the reservoir was 

about 9,118 as indicated in Table 4 (column 8; 

row 3). Based on the estimated population, it is 

possible to obtain about 7.4 tons of fish biomass 

and 1.5 tons of fish yield per year.  

 

y = -1.2259x + 10.586

R² = 0.9805

0

1

2

3

4

5

6

7

8

9

0 1 2 3 4 5 6 7

L
n

(C
(L

1
,L

2
)/

∆
t)

Average age t(L1+L2)/2



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

39 

 

Figure 6. Recruitment pattern output from FiSAT II for C. carpio in Ayalew reservoir

  

Table 4. Estimated population, current yield and other parameters of C. carpio by length group 

Length 

group 

(cm) 

Annual 

catch 

  x y    

∆t 

(L1,L2) 

(L1+L2)/2 t(L1+L2)/2 Ln(C(L1,L2)/∆t) H N(L1,L2) Current 

yield 

(kg) 12-14 161 0.14 13 0.73 7.07 1.01 9118 6 

14-16 322 0.15 15 0.88 7.69 1.01 8774 18 

16-18 859 0.16 17 1.03 8.59 1.01 8264 64 

18-20 967 0.17 19 1.20 8.62 1.01 7220 95 

20-22 805 0.19 21 1.38 8.34 1.01 6081 102 

22-24 564 0.21 23 1.58 7.88 1.02 5115 89 

24-26 591 0.24 25 1.81 7.81 1.02 4400 115 

26-28 940 0.28 27 2.07 8.14 1.02 3665 222 

28-30 644 0.32 29 2.36 7.60 1.02 2597 182 

30-32 591 0.39 31 2.71 7.33 1.03 1847 197 

32-34 483 0.48 33 3.14 6.91 1.04 1170 189 

34-36 295 0.65 35 3.70 6.12 1.05 623 134 

36-38 107 0.98 37 4.48 4.69 1.08 284 56 

38-40 81 2.11 39 5.81 3.64 1.17 146 48 

Total 7,410      59,304 

 

1,517 

 

 

 

 

 



East Afr. J. Biophys. Comput. Sci. (2023), Vol. 4, No. 1, 28-41 
 

40 

CONCLUSIONS & RECOMMENDATIONS  

The growth pattern of C. carpio was negative 

allometric which implied that the fish became 

thinner as its body length increases. The 

wellbeing of the fish was not in a good health 

condition. The mean length groups ranged from 

17 cm to 33 cm was about 87% of the total catch 

and had a high contribution in fish yield. The C. 

carpio in Ayalew reservoir can grow up to the 

maximum length (L∞) 41 cm with growing speed 

(k) of 0.52 per year. The long lifespan (A0.95) of 

the cohort and the length at first maturity were 

5.5 years and 23.44 cm, respectively. The 

production potential of the fish was about 7.4 

tons of fish biomass and 1.5 tons of yields per 

year. However, investigation on reproductive 

biology, limnological aspects and stock 

enhancement are required in the reservoir.  

Acknowledgements 

The authors would like to highly acknowledge 

the Southern Agricultural Research Institute 

(SARI) for the financial support, Arba Minch 

Agricultural Research Center for allowing access 

to the necessary facilities and Arba Minch 

Agricultural Research Center staff members for 

their valuable assistance during the execution of 

the experiment.  

Conflicts of interest  

The authors declare that there is no conflict of 

interest in publishing the manuscript in this 

journal. 

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