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Fishery Appraisal of Portunus spp. (Family Portunidae) using Different Surplus Production Models from Pakistani Waters, Northern Arabian Sea

PJZ_50_1_135-141

 

 

Fishery Appraisal of Portunus spp. (Family Portunidae) using Different Surplus Production Models from Pakistani Waters, Northern Arabian Sea

Muhsan Ali Kalhoro1,2, Danling Tang1,*, Ye Hai Jun1, Morozov Evgeny1, Sufen Wang1 and Muhammad Aslam Buzdar2

1Research Center for Remote Sensing of Marine Ecology and Environment, State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, 510075, China

2Faculty of Marine Sciences, Lasbela University of Agriculture, Water and Marine Sciences, Uthal, Balochistan, Pakistan

ABSTRACT

Annual catch and effort data were used to estimate the maximum sustainable yield (MSY) of Portunus spp. to evaluate the population state of crab fishery from Pakistani waters. The catch and effort data of crab fishery from 1999-2009 were obtained from and handbook of Fisheries Statistics of Pakistan. Two computer software programs CEDA and ASPIC were used which were based on surplus production models. From CEDA Fox, Schaeder and Pella-Tomlinson were used with initial proportion (IP) 0.9 were used because the starting catch was 90% of the maximum catch the MSY estimated value from Fox with three error assumptions (normal, lognormal and gamma) were 3378 (R2=0.590), 3360 (R2=0.582), 3369 (R2 =0.586), respectively, whereas the obtained values from Schaefer and Pella-Tomlinson with three error assumptions were 2878 (R2=0.587), 3035 (R2=0.578) and gamma were minimization failure (MF) in both models. The MSY estimated value from ASPIC from Fox and logistic model were 3652 (R2=0.8) and from logistic model were 2962 (R2=0.799), respectively. The present estimated values from surplus production models is lower than annual catch it shows that the stock of crab fishery from Pakistani waters is in overexploitation state, we may suggest to reduce the fishing efforts to sustain the crab stock from Pakistani waters for future generation.


Article Information

Received 16 November 2016

Revised 03 March 2017

Accepted 24 April 2017

Available online 02 January 2018

Authors’ Contributions

DT supervised and designed the study. MAK executed the experimental work, analysed the data and wrote the article. YHJ, ME, SW and MAB helped in writing of the article.

Key words

Fisheries statistics of Pakistan, Crab fishery, Portunus spp., Maximum sustainable yield, overexploitation, CEDA, ASPIC.

DOI: http://dx.doi.org/10.17582/journal.pjz/2018.50.1.135.141

* Corresponding author: lingzistdl@126.com

0030-9923/2018/0001-0135 $ 9.00/0

Copyright 2018 Zoological Society of Pakistan



INTRODUCTION

 

Management of world’s marine fin and shellfish stock is sustained by scientific recommendation based on stock assessment using different research tools (Mace et al., 2001). Marine Fisheries sector of Pakistan has diversity of marine species from which marine crab species are also one of the valuable sources of economic value because most of the catch export to different countries of the world from which mainly export to China, Middle East and also South East Asian Countries. Pakistani waters are located at Northern part of the Arabian Sea coastline about 1120 km divided into Sindh and Balochistan coastline from Northwest Iranian border and Southwest Indian border from which Sindh coast have 348 km and Balochistan coast comprises about 772 km and about 290,000 km2 (Fig. 1) from which Pakistan can explore and exploit their marine resources. About 60% of total fish landing is primarily from marine sector and according to FAO (2009), there are about 250 demersal fish species, 20 and 50 are large and small pelagic fish species, respectively, 17 are different crab species and 15 are most commercially important shrimp species from Pakistani waters. FAO (2009) report shows that the major marine resources of the Pakistan are decreasing since 1999.

About 4500 crab species were found from the world from which more than 200 species have been reported from Pakistani water (Kazmi, 2003) out of 200 species five species are most commercial and edible fish species from Pakistani waters which are Portunus pelagicus (Linnaeus, 1785), Portunus sanguinolentus (Herbst, 1783) Scylla tranquebarica (Fabricius, 1798), S. olivacea (herbst, 1796) and Charybdis feriatus (Linnaeus, 1785). Portunidae crab family species are distributed throughout the Indo-west Pacific and plays important fishery role in different parts of the regions (Stephenson, 1962; Potter et al., 1983; Kailola et al., 1993; Afzaal et al., 2016). Pakistani crab fishery is mainly sustained by two species first the three spotted swimming crab, Portunus sanguinolentus (Herbst, 1783) and Portunus pelagicus (Linnaeus, 1758) from which P. sanguinolentus is dominant fish species from Pakistani waters and mostly caught from bottom gillnet or shrimp trawling fresh and frozen crabs were exported to different countries especially China and Middle East. Previous work is available on the biology of the Portunus spp. from Pakistani waters (Kazmi, 2003; Takween and Qureshi, 2001, 2005; Rasheed and Mustaquim, 2010; Afzaal et al., 2016). Portunus spp. were distributed in Indoa-Pacific region (Apel and Spiridonov, 1998) and mostly found at estuary areas where muddy or sandy bottom at about 50-65 m depth (Sumpton et al., 1989; Edgar, 1990). Present catch and effort data from 1999-2009 (Table I) shows that most of the catch were from Sindh coastline it maybe because of favorable habitat for the crab fishery, Sindh coastline have freshwater inflow from Indus River which may create best nursery and growing habitat for marine organisms (Snead, 1976; FAO, 2009).

The number of fishery stock assessment and maximum sustainable yield of different fish species have been studied from Pakistani waters like maximum sustainable fishery of Bombay duck and Saurida tumbil fishery, Saurida undosquamis and Nemipterus japonicus, N. randalli, hairtail and Decapterus russelli (Kalhoro et al., 2013, 2014a, b, 2015a, b, 2017a, b; Memon et al., 2015a) but the limited work has been done on the maximum sustainable yield of crab fishery from Pakistani waters, the present work will provide some crab fishery appraisal from Pakistani waters, which may help to sustain the stock level of crab fishery.

 

 

MATERIALS AND METHODS

Fishery statistical data

Fishery annual catch and effort data of Portunus spp. from 1999-2009 were obtained from FAO fisheries statistical data (http://www.fao.org/fishery/statistics/en) and handbook of Fisheries Statistics of Pakistan compiled by Marine Fisheries Department (MFD), Karachi (Table I) where fishing efforts was representing the number of fishing boats, and the annual catch were presented in the form of weight (metric ton).

 

Table I.- Yearly catch and effort data of Portunus spp. fishery from Pakistani waters, Northern Arabian Sea.

Year

Effort

Sindh

Baluchistan

EEZ

Total catch

1999

11768

5109

0

 

5109

2000

12114

5006

0

181

5187

2001

12618

4992

0

 

4992

2002

12695

4892

0

135

5027

2003

12838

4521

81

17

4619

2004

13002

4901

76

102

5079

2005

13145

4355

65

19

4439

2006

13308

4128

90

 

4218

2007

13426

3905

143

 

4048

2008

13522

3688

175

 

3863

2009

13897

4712

128

 

4840

Effort, number of fishing boats; EEZ, exclusive economic zone; Total catch in metric tons.

 

Annual catch and effort data were analyzed by different surplus production models which are Schaefer, Fox and Pella-Tomlinson which were available into two computer program CEDA (catch effort data analysis) (Hoggarth et al., 2006) and ASPIC (a surplus production models incorporating covariates) (Prager, 2005)

 

dB / dt = rB(B- B) (Schaefer, 1954)

 

Later work of Fox (1970) put forward a Gompertz growth equation, and another work from Pella and Tomlinson (1969) reported a generalized production equation:

 

dB / dt = rB(InB- InB) (Fox, 1970)

 

dB / dt = rB(Bn-1 - Bn-1) (Pella and Tomlinson, 1969)

 

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

 

Bt+1 = Bt + rBt (B- Bt) - Ct

 

Ct = qEtBt

 

Where, C is catch, q is catchability, E is the fishing efforts. Fishing mortality can then be calculated as:

F = qE

CEDA (catch and effort data analysis)

CEDA (Hoggarth et al., 2006) is computer base programming which is built on non-equilibrium surplus production models Schaefer, Fox and Pela and Tomlinson with three error assumptions (normal, lognormal and gamma) with output parameters were: MSY (maximum sustainable yield), K (carrying capacity), q (catchability coefficient), r (intrinsic growth rate), Ryield (replacement yield) and final biomass. The non-equilibrium surplus productions models were mostly used and it was assumed and fishery stock is not in equilibrium state because ecological, environmental and fishing efforts factors also affect the fishery stock and fishery stock will not in equilibrium state in that case non-equilibrium surplus production models were frequently used for stock assessment for better fishery management.

ASPIC (a surplus production models incorporating covariates)

ASPIC is non-equilibrium surplus production model and have two models; Logistic (Schaefer) and Fox model, ASPIC output parameters are: MSY, q, K, ration of the starting biomass over carrying capacity B1/K coefficient of determination (R2), coefficient of variation (CV), stock biomass in giving MSY (BMSY), and fishing mortality rate at MSY (FMSY). The initial proportion (IP) of B1/K (Starting biomass over carrying capacity) is input values by users, it was assumed that when IP is close to zero, this indicates that the data are from virgin population, and if IP is close to one it means the data starts from fully developed state (Prager, 2005).

 

RESULTS

CEDA

CEDA (catch and effort data analysis) computer software package shows sensitive with different IP values, different IP values and results are showing in Table II, gamma error assumptions of those three models mostly gives minimization failure (MF) it also shows that the values obtained from Schaefer (1954) and Pella and Tomlinson (1969) with all those error assumptions (normal, lognormal and gamma) were same. To estimate MSY value in present study IP value 0.9 were used because the starting catch was roughly 90% of the maximum catch which were calculate first year catch divided by maximum catch of those years, the estimated value from calculate IP (0.9) from Fox with three error assumptions (normal, lognormal and gamma) were 3378 R2 (R2 =0.590), 3360 (R2 =0.582), 3369 (R2 =0.586), respectively (Table III, Fig. 2), whereas, the obtained values from Schaefer (1954) and Pella and Tomlinson (1969) with two error assumptions (normal and lognormal) were 2878 (R2=0.587), 3035 (R2=0.578) and gamma were minimization failure (MF) in both models.

ASPIC

Output values from both Fox and logistic model are showing in Table IV using different IP values from 0.2-1, shows that ASPIC package is not sensitive with using different IP values. The MSY value from IP value 0.9 was obtained to set the level of fishery status because the initial yield was about 90% of the maximum catch. The estimated MSY value from Fox model were 3652 (R2 =0.8) with 0.183 coefficient of variation (CV) (Table V), overall values from 0.2-1 IP value estimated in fox models were range from 3650-3658 with R2 = 0.8, which shows the accuracy of data and best fit of the model showing the goodness of fit. Whereas, the MSY value from calculate IP (0.9) from logistic model were 2962 (R2 =0.799) with 0.199 CV (Table V), overall MSY values using

 

Table II.- MSY appraisal of Portunus spp. from CEDA package using different IP values from 0.2-0.9 from Pakistani waters, Northern Arabian Sea.

IP

Models FOX

Schaefer

Pella-Tomlinson

Normal

Log-normal

Gamma

Normal

Log-normal

Gamma

Normal

Log-normal

Gamma

0.2

5268

4605

MF

MF

5229

MF

MF

5229

MF

0.3

4228

3866

4217

MF

5914

5919

MF

5914

5919

0.4

3727

3580

3720

5103

5052

5061

5104

5052

5061

0.5

3460

3568

3455

4119

4215

4109

4119

4215

4109

0.6

3326

3547

3319

3595

3505

MF

3595

3505

MF

0.7

3278

3495

3267

3256

3442

3252

3256

3442

3252

0.8

3297

3551

MF

3028

3289

3026

3028

3289

3026

0.9

3378

3360

3369

2878

3035

MF

2878

3035

MF

CEDA, catch and effort data analysis; IP, initial proportion; MF, minimization failure; MSY, maximum sustainable yield.

 

Table III.- Outcomes value of Portunus spp. from CEDA package using IP value 0.9 because the initial catch were 90% of the maximum catch.

Model

K

r

MSY

Ryield

q

R2

Biomass

Fox (normal)

97129

0.094

3378

2812

5.19E-06

0.590

58330

Fox (Log normal

95855

0.095

3360

2814

5.26E-06

0.582

57199

Fox (Gamma)

95574

0.095

3368

2821

5.29E-06

0.586

57016

Schaefer (normal

92352

0.124

2878

2764

5.45E-06

0.587

55354

Schaefer (Log normal)

83687

0.145

3035

2938

6.08E-06

0.578

49304

Schaefer (Gamma)

MF

MF

MF

MF

MF

MF

MF

Pella Tomlinson (Normal)

92352

0.124

2878

2764

5.45E-06

0.587

55354

Pella Tomlinson (Log normal)

83687

0.145

3035

2938

6.08E-06

0.578

49304

Pella Tomlinson (Gamma)

MF

MF

MF

MF

MF

MF

MF

For abbreviations, see Table II.

 

Table IV.- ASPIC outcomes for the Portunus spp. fishery using IP values from 0.2-1 from Pakistani waters, Northern Arabian Sea.

Model

IP

MSY

B1/K

K

q

FMSY

R2

CV

BMSY

 

0.2

3658

1.00

95220

4.78E-06

0.104

0.8

0.127

35030

 

0.3

3655

1.00

95210

4.79E-06

0.104

0.8

0.133

35030

 

0.4

3658

1.00

95210

4.78E-06

0.104

0.8

0.135

35020

 

0.5

3655

1.00

95200

4.79E-06

0.104

0.8

0.151

35020

FOX

0.6

3653

1.00

95240

4.78E-06

0.104

0.8

0.167

35040

 

0.7

3650

1.00

95260

4.78E-06

0.104

0.8

0.131

35050

 

0.8

3660

1.00

95200

4.78E-06

0.104

0.8

0.125

35020

 

0.9

3652

1.00

95240

4.79E-06

0.104

0.8

0.183

35040

 

1.0

3657

1.00

95200

4.79E-06

0.104

0.8

0.157

35020

 

0.2

5270

0.367

24470

4.93E-05

0.430

0.794

0.968

12230

 

0.3

5147

0.429

8857

0.000121

1.162

0.741

0.059

4428

 

0.4

2958

1.00

92570

4.92E-06

0.063

0.799

0.153

46290

LOG

0.5

2959

1.00

92700

4.91E-06

0.063

0.799

0.124

46350

 

0.6

2972

1.00

92340

4.93E-06

0.064

0.799

0.172

46170

 

0.7

2960

1.00

92510

4.93E-06

0.064

0.799

0.148

46250

 

0.8

2951

1.00

92820

4.9E-06

0.063

0.799

0.170

46410

 

0.9

2962

1.00

92500

4.93E-06

0.064

0.799

0.199

46250

 

1.0

2954

1.00

92740

4.91E-06

0.063

0.799

0.166

46370

IP, initial proportion; MSY, maximum sustainable yield; B1/K, starting biomass; K, carrying capacity; q, catchability coefficient; FMSY, fishing mortality rate at MSY; R2, coefficient of determination; CV, coefficient of variation, BMSY, stock biomass in giving MSY.

 

Table V.- ASPIC results with 0.9 IP (initial proportion) value for the Portunus spp. fishery from Pakistani waters, Northern Arabian Sea.

Model

IP

MSY

B1/K

K

q

FMSY

R2

CV

BMSY

FOX

0.9

3652

1

95200

4.8E-06

0.1044

0.8

0.183

35020

LOGISTIC

0.9

2962

1

92500

4.9E-06

0.0641

0.799

0.199

46250

For abbreviations, see Table IV.

 

different IP values (0.2-1) from logistic model were 2151-5270 Table IV. The confidential interval is also easy to estimate using bootstrapping method which provides 95% confidential interval and overall values were lower than 0.2.

 

DISCUSSION

 

Catch and efforts data is mostly used to calculate MSY for better stock assessment for any fishery where catch should be yearly or monthly and efforts must be in number of fishing boats, number of fishermen engaged in that time period or number of fishing hours in that fishing time, in present study the yearly catch and number of fishing boats were used to estimate the MSY value for crab fishery from Pakistani waters, Northern Arabian Sea. The surplus production models are much more helpful to estimate the MSY and optimal level of efforts that produces the MSY and is always considered as target biological reference point (BRP) from which sustainable fishery management goals can be achieved (Hilborn and Walters, 1992). Earlier studies were based on equilibrium production models but stocks are seldom in equilibrium state due to some biological, environmental factors and unmanaged fishing mortality which effects the population in this case non-equilibrium surplus production models are frequently used to know the state of stock. The surplus production models can give idea about the stock because they do not require and environmental data (Quinn and Deriso, 1999) The surplus production models were frequently used for fishery management since last decades and recently were also used for Pakistani waters (Kalhoro et al., 2013, 2015; Soomro et al., 2015a, b; Memon et al., 2015a, b).

The overall results from CEDA and ASPIC surplus production models were almost equal or same using different IP values, the concept of the MSY is if MSY estimated value is greater than recent catch then it shows that the fish stock is in safe condition, but when the estimated MSY value equals to annual catch it may be assumed that fish population in in sustainable state, however, if the estimated MSY value from different surplus production models is smaller than annual catch it indicates that the stock of fishery is over-exploitation state. In the present study using different surplus production models results shows that the estimated MSY values (Tables II, III, IV, V) is smaller than annual catch. Table I shows that the stock of swimming crab fishery from Pakistani waters was in overexploitation state. In the light of present study, we may suggest that take some management steps to reduce the fishing efforts for crab fishery, protect the nursery grounds of the crab fishery to maintain the stock of crab fishery from Pakistani waters.

 

CONCLUSION

 

Maximum sustainable yield (MSY) estimated from both computer packages CEDA and ASPIC results were close and give value smaller than annual catch of the swimming crab fishery which indicates that the stock of crab fishery from Pakistani waters is in overexploitation state. We may suggest that fishery managers take some management steps like reduce the fishing efforts, declare Marine Protected Area at nursery grounds of fin and shellfish, generally due to freshwater inflow from Indus River creates rich mangrove ecosystem from Sindh area so it is considered to be best nursery grounds for fish and shellfish, monitoring the trawl mesh size, ban period during the breeding season of crab fishery to sustain the crab fishery stock from Pakistani waters, Northern Arabian Sea.

 

Acknowledgments

 

Present study is supported by research project awarded to Prof. Dr. DanLing Tang: 1) Key project, “Marine phytoplankton size classes and related ecological factors respond to typhoons - based on remote sensed and in situ data” awarded by National Natural Sciences Foundation of China (41430968); 2) Collaborative Innovation Center for 21st-Century Maritime Silk Road Studies, Guangzhou, China (2015HS05). First author also thankful to China Postdoctoral fellowship program by South China Sea Institute of Oceanology, Chinese Academy of Sciences (158563) and China Science and Technology Exchange Center, Ministry of Science and Technology for awarding Talented Young Scientist Award (PAK-16-021) recommended by Ministry of Science and Technology Pakistan.

 

Statement of conflict of interest

The authors have declared no conflict of interest.

 

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Pakistan Journal of Zoology

October

Vol. 50, Iss. 5, Pages 1601-1998

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