Journal of animal-science-research

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RESEARCH ARTICLE
Maximum Sustainable Yield of Dolphinfish, Coryphaena hippurus (Linnaeus, 1758) Fishery in Pakistan

  Abdul Baset1*      Tariq Muhammad Haneef2      Abdul Waris3      Baochao Liao4      Aamir Mahmood Memon5      Ehsanul Karim6      Muhammad Ismail7   

1Department of Zoology, Bacha Khan University Charsadda, Pakistan
2College of Fisheries, Ocean University of China, Qingdao, China
3Department of Biotechnology, Quaid-i-Azam University, Islamabad, Pakistan
4Department of Probability and Statistics, Shandong University, Jinan, China
5Sindh Fisheries Department, Hyderabad, Sindh, Pakistan
6Bangladesh Fisheries Research Institute, Mymensingh, Bangladesh
7Department of Zoology, University of Karachi, Pakistan

*Corresponding author: Baset A, Department of Zoology, Bacha Khan University Charsadda, Pakistan, E-mail: drabdulbaset@bkuc.edu.pk


Abstract

The maximum sustainable yield (MSY) of Dolphinfish Coryphaena hippurus (Linnaeus, 1758) fishery in Pakistan was estimated from 20 (Twenty) years catch and effort data during 1990-2009. The average landing of dolphinfish fishery was 2418.55t. The highest catch was 4053t in the year 2002 and the lowest catch was 1297t in the year 1990. The CEDA (Catch and Effort Data Analysis) computer software package was used for the MSY estimation of dolphinfish fishery in Pakistan. In this study we used the initial proportion (IP) value of 0.3 because the starting catch was approximately 30% of the maximum catch. The estimated values of MSY from Fox model with two error assumptions normal and log-normal were 2792.125t (R2 =0.454) and 2920.592t (R2 =0.565) respectively. The MSY values from Schaefer and Pella Tomlinson models with two error assumptions normal and log-normal were 2781.02t (R2 =0.474) and 2863.3t (R2 =0.572) respectively. The values of Schaefer and Pella Tomlinson were the same. The gamma error assumption showed minimization failures for all three models. We may say the estimated MSY were lower than the current catch, therefore we suggest reducing the fishing effort for dolphinfish fishery.

Keywords

Stock assessment; Coryphaena hippurus; Maximum Sustainable Yield; CEDA; Pakistan


Introduction

The world’s fisheries sectors have more developed in the last 60 years. In 1950, the total world fish production was 19.3 million tones and reached 163 million tons in 2009 [1]. In 2009 marine fisheries produced 80 million tons of fishes and 34 million employers were operating the fishing in 2008 [2]. More than 3 billion people received fish in which at least 15% of their average animal protein produced [2].

Fishery resources have a big role in economics development of Pakistan [3,4]. In 1996 Pakistan received amount of Rs. 196 million from its export, in which 70% obtain from marine sector [5]. In 2007 total production of fishes was 750300 t including 60% from marine [6]. That’s why marine fisheries sector has a central role in Pakistan national economy and fish is a good source of protein for the public [7]. The Pakistanis provinces of Sindh and Baluchistan occupy coastal areas and about 90% of their population related to fishing and fishing related activities [8]. But the catch of fish is reducing day by day due to illegal, increased fishing efforts, unreported and unregulated fishing nets and the great problem of water pollution [9].

The dolphinfish Coryphaena hippurus (Linnaeus, 1758) belong to the family Coryphaenidae (Öktener, 2008) [10]. It is epipelagic and sophisticated fish, which found in tropical and subtropical waters mostly in warmer months [11]. Dolphinfish found in the depth from 0 to 85m. It is found in Western Mediterranean when the surface temperature reaches >16-18°C [12]. Mostly the adults of Coryphaena hippurus found in open sea but also found some time near the coast [13].

On economic point of view, the Coryphaena hippurus has great importance commercially as well as sport fisheries in all over the world [14-16]. Currently, there is no work presenting the estimation of Maximum Sustainable Yield (MSY) for dolphinfish from Pakistani waters. So, the present work has done on catch and effort data of Coryphaena hippurus from Pakistan, which have estimated maximum sustainable yield [17].

Materials and Methods
Data source

The catch and effort data of dolphinfish in the period from 1990 to 2009 were taken from the handbook of Fisheries Statistics of Pakistancompiled by Marine Fisheries Department (MFD), Karachi, Pakistan (Table 1). Fishing effort is represented by the number of powered fishing boats, and the annual total catch is presented in the form of weight in metric tons (mt).

Year Catch Effort CPUE
1990 1297 8522 0.152
1991 1300 8619 0.151
1992 1577 8831 0.179
1993 1875 9604 0.195
1994 2054 10296 0.199
1995 2570 11066 0.232
1996 1841 11061 0.166
1997 1658 10983 0.151
1998 1892 11444 0.165
1999 3109 11768 0.264
2000 1954 12114 0.161
2001 3850 12618 0.305
2002 4053 12695 0.319
2003 3742 12838 0.291
2004 2949 13002 0.227
2005 2705 13145 0.206
2006 2453 13308 0.184
2007 2536 13426 0.189
2008 2839 13522 0.21
2009 2072 13879 0.149

Table 1: The catch and effort data of dolphinfish fishery in Pakistani waters from 1990-2009.
Note: Catch is in the form of metric ton.

Surplus production models

The dolphinfish catch and effort data from 1990-2009 were analyzed by CEDA computer software package. There are three surplus production models (SPMs) used in CEDA package, Schaefer, Fox and Pella-Tomlinson. The most commonly used model is Schaefer MB, et al. [18] which is based on the logistic growth model:

After then the work of Fox (1970) put a Gompertz growth equation and a generalized production equation has reported by Pella and Tomlinson (1969).

Where: B is fish stock biomass; t is time (year); B∞ is carrying capacity; and r is intrinsic rate of population increase, n is the shape parameter.

Catch and Effort Data Analysis-CEDA

Catch and Effort Data Analysis (CEDA version 3.0.1) is a computer software package which is made of three non-equilibrium production models which are Schaefer (1954), Fox (1970) and Pella JJ, et al. [20] with three error assumption (normal, log-normal and gamma). By CEDA computer software package we calculate the following parameters MSY (maximum sustainable yield), q (catchability coefficient), K (carrying capacity), r (intrinsic growth rate), replacement yield and final biomass.

The initial proportion (IP, ratio of starting biomass over carrying capacity) is needed for CEDA from the user. When the IP is close to zero, it means that the data is from a virgin population and if the IP is close to 1 it indicates the data starts from a fully developed area. IP is an indicator that shows from which place the data has collected, starts from virgin population or from the serious exploitation population.

Results

The CEDA package results are showed with IP values 0.1 to 0.9 in table 2. There are mostly minimization failures for gamma error assumption. The estimated MSY is different from 0.1 to 0.9, sometime higher than the maximum catch and sometime lower than, but, the table 3 showed the CEDA results with initial proportions IP of 0.3 in which the estimated MSY is lower from the maximum catch from all of three models Fox, Schaefer and Pella-Tomlinson. The estimated values of MSY for Fox model were 2792.125t and 2920.592t for normal and log normal error assumptions respectively [21].

IP         MODELS        
    FOX     SCHAEFER     PELLATOMLINSON  
  Normal log-normal Gamma normal Log-normal Gamma Normal Log-normal Gamma
0.1 2.06E+07 3583.544 105258.6 MF 4648.458 4834.89 MF 4648.458 4834.89
0.2 252534.9 2875.534 MF 3139.889 3344.583 MF 3139.889 3344.583 MF
0.3 2792.125 2920.592 MF 2781.02 2896.3 MF 2781.02 2896.3 MF
0.4 3135.516 3361.771 MF 2775.479 2936.091 MF 2775.479 2936.091 MF
0.5 IPV 4788.347 57866.7 1.13E+09 3616.933 MF 1.13E+09 3616.933 MF
0.6 69622.14 68392.27 5.94E+07 1.30E+09 26443.56 MF 1.30E+09 26443.56 MF
0.7 2.45E+09 802399.6 MF 4.50E+08 370788.9 MF 4.50E+08 370788.9 MF
0.8 3.87E+09 485038.8 MF 1.09E+09 294272.9 MF 1.09E+09 294272.9 MF
0.9 1.49E+09 318078.2 MF IPV 439866.6 MF IPV 439866.6 MF

Table 2: Applying CEDA (Catch and Effort Data Analysis) Computer software package for Coryphaena hippururs in Pakistan for estimation of MSY with initial proportion ranging from 0.1 to 0.9.
IPV=Invalid property value, MF=Showing minimization failures

The estimated values of MSY for Schaefer and Pella Tomlinson with two error assumptions, normal and log normal were 2781.02 and 2896.3 metric tons respectively. The values of MSY were same for both Schaefer and Pella Tomlinson. Gamma error assumption showed minimization failure here from all models. There was a little difference among the estimated values of MSY for all of three models Fox, Schaefer and Pella Tomlinson. The figure 1 showed the estimated and observed catches, if using IP value 0.3, the observed catches by Fox and Schaefer were approximately near to the estimated catch.

Figure 1: Annual expected (lines) and observed (points) catch (mt) of Coryphaena hippurus fishery in Pakistan using CEDA. Gamma error assumption showed minimization failure for Fox, Schaefer and Pella-Tomlinson models.

Discussion and Conclusion

The average catch of Coryphaena hippurus from Pakistani waters was 2418.55t. For CEDA [22] computer software package needs catch and effort data which made of three surplus production models Fox, Schaefer and Pella Tomlinson. Each model has three error assumptions normal, log normal and gamma [23]. We can estimate MSY and some other related population parameters by surplus production models but do not contain age-structured models and related environmental factors.

Generally, when surplus production is greater than catch it means the population size increase when surplus production and catch are equal to one another its shows that population size remains constant, while when the catch is greater than the surplus production means the decline of population size. In surplus production models the MSY is measured as a biological indication point by which we can get sustainable exploitation [24-26]. The optimum fishing effort and MSY can be determined by surplus production model, which require the CPUE (catch per unit effort) and landed catch [27,28] without the need of age structure data [29].

CEDA is a helpful implement to estimate the MSY from different error assumptions. Table 3 showed initial proportion (IP) ranging from 0.1-0.9 in which the MSY values are different. From IP 0.1 and 0.2 from model Fox, the estimated SMY were higher than the maximum catch, Especially the values of Fox with assumption error normal is more high as compared to log normal and gamma error assumptions. But IP value 0.1 the estimated MSY from models Schaefer and Pella Tomlinson with all error assumptions normal, lognormal and gamma are nearly high than the maximum catch and IP value 0.2 the estimated values of MSY from Schaefer and Pella Tomlinson with all error assumptions are lower than the maximum catch. With IP values 0.3 and 0.4 the estimated values from all three models are lower than the maximum catch. When applying IP 0.5 from Fox with error assumption normal and IP 0.9 From Schaefer and Pella Tomlinson with error assumption normal showed Invalid Property Value (IPV). From IP value 0.5 to 0.9 the estimated values of MSY were high as compared with maximum catch (Table 3). The R2 from Fox model with error assumptions normal and log-normal were 0.454 and 0.565, respectively while from Schaefer and Pella Tomlinson with normal and log-normal were 0.474 and 0.572, respectively.

Models   IP K q r MSY Ryield R2
Fox Normal       0.3   62693.63 8.31E-06 1.21E-01 2792.125 2771.76 0.454
Fox Log normal   79866.97 6.36E-06 9.94E-02 2920.592 2890.824 0.565
Fox Gamma   MF MF MF MF MF MF
Schaefer Normal   44456.97 1.15E-05 0.250 2781.02 2681.629 0.474
Schaefer Log normal   58193.68 8.73E-06 0.199 2896.3 2805.809 0.572
Schaefer Gamma   MF MF MF MF MF MF
Pella-Tomlinson Normal   44456.97 1.16E-05 0.250 2781.02 2681.629 0.474
Pella-Tomlinson Log normal   58193.68 8.73E-06 0.199 2896.3 2805.809 0.572
Pella-Tomlinson Gamma   MF MF MF MF MF MF

Table 3: Applying CEDA (Catch and Effort Data Analysis) Computer software package for Coryphaena hippururs in Pakistan for estimation of MSY used initial proportion 0.3 because the initial catch was approximately 30% of the maximum catch.
Note: The sign of hyphen–showing minimization failure
The parameters are: K=carrying capacity, r=intrinsic population growth rate, MSY=Maximum Sustainable Yield, Ryield=Replacement Yield, q=catchability coefficient, R2=coefficient of determination

The estimated MSY results from CEDA were lower than the recent catch (Table 2). Therefore, we may say that the Coryphaena hippurus fishery in Pakistani waters over exploited. In Pakistan there is not any successful development to manage the dolphinfish stock. We may suggest that Pakistan fisheries managers will take some steps to reduce the catch to MSY level because by this way we can control fishing efforts trawl mesh size as way to protect the growth of the juvenile dolphinfish. We should to provide the time to bread once in their lifespan.


References

  1. FAO (2011) Review of the state of world marine fishery resources. Fisheries 334. [Ref.]
  2. FAO (2010) The state of world fisheries and aquaculture. Aquaculture Department 197. [Ref.]
  3. Nazir K, Yongtong M, Kalhoro MA, Memon KH, Mohsin M, et al. (2015) A preliminary study on fisheries economy of Pakistan: Plan of actions for fisheries management in Pakistan. Can J Basic Appl Sci 3: 7-17. [Ref.]
  4. Baset A, Liu Q, Hanif MT, Liao B, Memon AM, et al. (2017) Estimation of maximum sustainable yield using production modeling: A stock appraisal of Indian Oil Sardine (Sardinella longiceps) from Pakistani Waters. Pak J Zool 49: 521-528. [Ref.]
  5. Baset A, Liu Q, Liao B, Waris A, Ahmad I, et al. (2020) Population Dynamics of Saddle Grunt Fish, Pomadasys maculatus (Bloch, 1793) from Pakistani Waters. Bioprocess Engineering 4: 1-8. [Ref.]
  6. Baset A, Qun L, Pavase TR, Hameed A, Niaz Z (2017) Estimation of maximum sustainable yield of Scomberomorus species fish stocks in Pakistan using surplus production models. Indian J Mar Sci 46: 2372-2378. [Ref.]
  7. FAO (2009) Fishery and aquaculture country profiles. Food and Agriculture Organization of the United Nations.
  8. Mohsin M, Mu Y, Memon AM, Mehak A, Shah SBH, et al. (2017) Capture fisheries production and its economic role in Pakistan. IJMS 46: 1110-1115. [Ref.]
  9. Memon AM, Liu Q, Memon KH, Baloch WA, Memon A, et al. (2015) Evaluation of the fishery status for King Soldier Bream Argyrops spinifer in Pakistan using the software CEDA and ASPIC. Chin J Oceanol Limn 33: 966-973. [Ref.]
  10. Öktener A (2008) Peniculus fistula von Nordmann, 1832 (Copepoda: Pennelidae) parasitic on Coryphaena hippurus Linnaeus, 1758 (Teleostei: Coryphaenidae). Rev Fish Sci 16: 445-448. [Ref.]
  11. Martínez-Ortiz J, Aires-da-Silva AM, Lennert-Cody CE, Maunder MN (2015) The Ecuadorian Artisanal Fishery for Large Pelagics: Species Composition and Spatio-Temporal Dynamics. PLoS One 10. [Ref.]
  12. Claridge D, Dunn C, Ylitalo G, Herman D, Durban J, et al. (2015) Behavioral Ecology of Deep-diving Odontocetes in the Bahamas. [Ref.]
  13. Bignami S, Sponaugle S, Cowen RK (2014) Effects of ocean acidification on the larvae of a high-value pelagic fisheries species, mahi-mahi Coryphaena hippurus. Aquatic Biology 21: 249-260. [Ref.]
  14. Merten W, Appeldoorn R, Hammond D (2014) Spatial differentiation of dolphinfish (Coryphaena hippurus) movements relative to the Bahamian archipelago. Bull Mar Sci 90: 849-864. [Ref.]
  15. McBride RS, Snodgrass DJ, Adams DH, Rider SJ, Colvocoresses JA (2012) An indeterminate model to estimate egg production of the highly iteroparous and fecund fish, dolphinfish (Coryphaena hippurus). Bull Mar Sci 88: 283-303. [Ref.]
  16. Farrell ER (2009) The habitat, movements, and management of Dolphin, Coryphaena hippurus, in the western North Atlantic, Caribbean, and Gulf of Mexico. Duke University, USA. [Ref.]
  17. Karim E, Qun LIU, Mahmood MA, Baset A, Hoq ME, et al. (2017) Assessment of some demographic trends of Spadenose shark (Scoliodon laticaudus) of the Bay of Bengal, Bangladesh. IJMS 46: 1986-1995. [Ref.]
  18. Schaefer MB (1954) some aspects of the dynamics of populations important to the management of the commercial marine fisheries. Inter-American Tropical Tuna Commission Bulletin 1: 23- 56. [Ref.]
  19. Fox Jr WW (1970) An exponential surplus-yield model for optimizing exploited fish populations. Transactions of the American Fisheries Society 99: 80-88. [Ref.]
  20. Pella JJ, Tomlinson PK (1969) A generalized stock production model. Inter-American Tropical Tuna Commission Bulletin 13: 416- 497. [Ref.]
  21. Liao B, Liu Q, Zhang K, Baset A, Memon AM, et al. (2016) A continuous time delay-difference type model (CTDDM) applied to stock assessment of the southern Atlantic albacore Thunnus alalunga. Chin J Oceanol Limn 34: 977-984. [Ref.]
  22. Kalhoro MA, Liu Q, Memon KH, Chang MS, Jatt AN (2013) Estimation of maximum sustainable yield of Bombay duck, Harpodon nehereus fishery in Pakistan using the CEDA and ASPIC packages. Pakistan J Zool 45: 1757-1764. [Ref.]
  23. Hoggarth DD, Abeyasekera S, Arthur RI, Beddington JR, Burn RW, et al. (2006) Stock assessment for fishery management: a framework guide to the stock assessment tools of the fisheries management and science programme. Food & Agriculture Org 487. [Ref.]
  24. Hilborn R, Walters CJ (1992) Quantitative Fisheries Stock Assessment: Choice Dynamics and Uncertainty. Chapman and Hill, New York 570. [Ref.]
  25. Prager MH (2002) Comparison of logistic and generalized surplusproduction models applied to swordfish, Xiphias gladius, in the North Atlantic Ocean. Fish Res 58: 41-57. [Ref.]
  26. Musick JA, Bonfil R (2004) Elasmobranch fisheries management techniques (2004). Fisheries Working Group, Asia-Pacific Economic Cooperation (APEC), Singapore 133-164. [Ref.]
  27. Liao B, Zhang K, Shan X, Chen X, Baset A, et al. (2017) Application of Bayesian surplus production model and traditional surplus production model on stock assessment of the southern Atlantic albacore (Thunnus alalunga). IJMS 46: 922-928. [Ref.]
  28. Mehanna SF, El-Gammal FI (2007) Gulf of Suez fisheries: current status, assessment and management. JKAU Mar Sci 18: 3-18. [Ref.]
  29. Haddon M (2011) Modeling and quantitative methods in fisheries. Second edition, Chapman & Hall/CRC press, London 449. [Ref.]

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Article Information

Article Type: RESEARCH ARTICLE

Citation: Baset A, Haneef TM, Waris A, Liao B, Memon AM, et al. (2020) Maximum Sustainable Yield of Dolphinfish, Coryphaena hippurus (Linnaeus, 1758) Fishery in Pakistan. J Anim Sci Res 4(2): dx.doi.org/10.16966/2576-6457.138

Copyright: © 2020 Baset A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Publication history: 

  • Received date: 08 May, 2020

  • Accepted date: 26 May, 2020

  • Published date: 31 May, 2020
  •