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

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Fishery Appraisal of Portunus Spp. (Family Portunidae) Using Different Surplus Production Models from Pakistani Waters, Northern Arabian Sea Pakistan J. Zool., vol. 50(1), pp 135-141, 2018. DOI: http://dx.doi.org/10.17582/journal.pjz/2018.50.1.135.141 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, Article Information Received 16 November 2016 Chinese Academy of Sciences, Guangzhou, 510075, China Revised 03 March 2017 2Faculty of Marine Sciences, Lasbela University of Agriculture, Water and Marine Accepted 24 April 2017 Sciences, Uthal, Balochistan, Pakistan Available online 02 January 2018 Authors’ Contributions ABSTRACT DT supervised and designed the study. MAK executed the Annual catch and effort data were used to estimate the maximum sustainable yield (MSY) of Portunus experimental work, analysed the spp. to evaluate the population state of crab fishery from Pakistani waters. The catch and effort data data and wrote the article. YHJ, ME, of crab fishery from 1999-2009 were obtained from and handbook of Fisheries Statistics of Pakistan. SW and MAB helped in writing of the article. 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 Key words used because the starting catch was 90% of the maximum catch the MSY estimated value from Fox with Fisheries statistics of Pakistan, Crab three error assumptions (normal, lognormal and gamma) were 3378 (R2=0.590), 3360 (R2=0.582), 3369 fishery, Portunus spp., Maximum (R2 =0.586), respectively, whereas the obtained values from Schaefer and Pella-Tomlinson with three error sustainable yield, overexploitation, assumptions were 2878 (R2=0.587), 3035 (R2=0.578) and gamma were minimization failure (MF) in both CEDA, ASPIC. 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. INTRODUCTION About 60% of total fish landing is primarily from marine sector and according to FAO (2009), there are about 250 anagement of world’s marine fin and shellfish stock demersal fish species, 20 and 50 are large and small pelagic Mis sustained by scientific recommendation based on fish species, respectively, 17 are different crab species and stock assessment using different research tools (Mace et 15 are most commercially important shrimp species from al., 2001). Marine Fisheries sector of Pakistan has diversity Pakistani waters. FAO (2009) report shows that the major of marine species from which marine crab species are also marine resources of the Pakistan are decreasing since 1999. one of the valuable sources of economic value because About 4500 crab species were found from the world most of the catch export to different countries of the world from which more than 200 species have been reported from which mainly export to China, Middle East and also from Pakistani water (Kazmi, 2003) out of 200 species five South East Asian Countries. Pakistani waters are located at species are most commercial and edible fish species from Northern part of the Arabian Sea coastline about 1120 km Pakistani waters which are Portunus pelagicus (Linnaeus, divided into Sindh and Balochistan coastline from Northwest 1785), Portunus sanguinolentus (Herbst, 1783) Scylla Iranian border and Southwest Indian border from which tranquebarica (Fabricius, 1798), S. olivacea (herbst, 1796) Sindh coast have 348 km and Balochistan coast comprises and Charybdis feriatus (Linnaeus, 1785). Portunidae crab about 772 km and about 290,000 km2 (Fig. 1) from which family species are distributed throughout the Indo-west Pakistan can explore and exploit their marine resources. Pacific and plays important fishery role in different parts of the regions (Stephenson, 1962; Potter et al., 1983; Kailola * Corresponding author: [email protected] et al., 1993; Afzaal et al., 2016). Pakistani crab fishery 0030-9923/2018/0001-0135 $ 9.00/0 is mainly sustained by two species first the three spotted Copyright 2018 Zoological Society of Pakistan swimming crab, Portunus sanguinolentus (Herbst, 1783) 1 3 6 M.A. Kalhoro et al. and Portunus pelagicus (Linnaeus, 1758) from which P. statistical data (http://www.fao.org/fishery/statistics/en) sanguinolentus is dominant fish species from Pakistani and handbook of Fisheries Statistics of Pakistan compiled waters and mostly caught from bottom gillnet or shrimp by Marine Fisheries Department (MFD), Karachi (Table trawling fresh and frozen crabs were exported to different I) where fishing efforts was representing the number of countries especially China and Middle East. Previous fishing boats, and the annual catch were presented in the work is available on the biology of the Portunus spp. from form of weight (metric ton). Pakistani waters (Kazmi, 2003; Takween and Qureshi, 2001, 2005; Rasheed and Mustaquim, 2010; Afzaal et al., Table I.- Yearly catch and effort data of Portunus spp. 2016). Portunus spp. were distributed in Indoa-Pacific fishery from Pakistani waters, Northern Arabian Sea. region (Apel and Spiridonov, 1998) and mostly found at estuary areas where muddy or sandy bottom at about 50- Year Effort Sindh Baluchistan EEZ Total catch 65 m depth (Sumpton et al., 1989; Edgar, 1990). Present 1999 11768 5109 0 5109 catch and effort data from 1999-2009 (Table I) shows that 2000 12114 5006 0 181 5187 most of the catch were from Sindh coastline it maybe 2001 12618 4992 0 4992 because of favorable habitat for the crab fishery, Sindh 2002 12695 4892 0 135 5027 coastline have freshwater inflow from Indus River which 2003 12838 4521 81 17 4619 may create best nursery and growing habitat for marine 2004 13002 4901 76 102 5079 organisms (Snead, 1976; FAO, 2009). 2005 13145 4355 65 19 4439 The number of fishery stock assessment and 2006 13308 4128 90 4218 maximum sustainable yield of different fish species 2007 13426 3905 143 4048 have been studied from Pakistani waters like maximum 2008 13522 3688 175 3863 sustainable fishery of Bombay duck and Saurida tumbil 2009 13897 4712 128 4840 fishery, Saurida undosquamis and Nemipterus japonicus, Effort, number of fishing boats; EEZ, exclusive economic zone; Total N. randalli, hairtail and Decapterus russelli (Kalhoro catch in metric tons. et al., 2013, 2014a, b, 2015a, b, 2017a, b; Memon et al., 2015a) but the limited work has been done on the Annual catch and effort data were analyzed by maximum sustainable yield of crab fishery from Pakistani different surplus production models which are Schaefer, waters, the present work will provide some crab fishery Fox and Pella-Tomlinson which were available into two appraisal from Pakistani waters, which may help to sustain computer program CEDA (catch effort data analysis) the stock level of crab fishery. (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) n-1 n-1 dB / dt = rB(B∞ - B ) (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 Fig. 1. Pakistan Coastline comprises Sindh and Balochistan and n is the shape parameter. coastline at different fish landing sites. Bt+1 = Bt + rBt (B∞ - Bt) - Ct MATERIALS AND METHODS Ct = qEtBt Fishery statistical data Where, C is catch, q is catchability, E is the fishing efforts. Fishery annual catch and effort data of Portunus Fishing mortality can then be calculated as: spp. from 1999-2009 were obtained from FAO fisheries F = qE 1 3 7 Fishery Appraisal of Portunus spp. 137 CEDA (catch and effort data analysis) software package shows sensitive with different IP CEDA (Hoggarth et al., 2006) is computer base values, different IP values and results are showing in programming which is built on non-equilibrium surplus Table II, gamma error assumptions of those three models production models Schaefer, Fox and Pela and Tomlinson mostly gives minimization failure (MF) it also shows with three error assumptions (normal, lognormal and that the values obtained from Schaefer (1954) and Pella gamma) with output parameters were: MSY (maximum and Tomlinson (1969) with all those error assumptions sustainable yield), K (carrying capacity), q (catchability (normal, lognormal and gamma) were same. To estimate coefficient), r (intrinsic growth rate), Ryield (replacement MSY value in present study IP value 0.9 were used because yield) and final biomass. The non-equilibrium surplus the starting catch was roughly 90% of the maximum catch productions models were mostly used and it was assumed which were calculate first year catch divided by maximum and fishery stock is not in equilibrium state because catch of those years, the estimated value from calculate ecological, environmental and fishing efforts factors IP (0.9) from Fox with three error assumptions (normal, also affect the fishery stock and fishery stock will not in lognormal and gamma) were 3378 R2 (R2 =0.590), 3360 equilibrium state in that case non-equilibrium surplus (R2 =0.582), 3369 (R2 =0.586), respectively (Table III, Fig. production models were frequently used for stock 2), whereas, the obtained values from Schaefer (1954) and assessment for better fishery management. Pella and Tomlinson (1969) with two error assumptions (normal and lognormal) were 2878 (R2=0.587), 3035 ASPIC (a surplus production models incorporating (R2=0.578) and gamma were minimization failure (MF) in covariates) both models.
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