Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/54067
Title: An assessment of overexploitation risk faced by cephalopod fisheries in China: A non-equilibrium surplus production model approach
Authors: Mohsin, Muhammad
Hengbin, Yin
Zhuo, Chen
Mehak, Ana
Keywords: Cephalopod fisheries;China;Economics;Management;Overexploitation;Risk
Issue Date: Feb-2020
Publisher: NISCAIR-CSIR, India
Abstract: This study analyses catch and effort(CE) data, 2006-2014, of cephalopod fisheriesto access its stock status for better management practices. Data analysis was performed by using two fisheries software, viz., catch and effort data analysis (CEDA) and a stock production model incorporating covariates (ASPIC). In CEDA, initial proportion (IP) = 0.8, Fox model estimated MSY, CV and R2 as 461687 t, 0.226 and 0.663 for log error assumption. The computed values of these parameters for log-normal and gamma error assumptions remained as 529612 t, 0.115, 0.671 and 503394 t, 0.176, 0.657, correspondingly. Estimated MSY values by using error assumptions, i.e., log and log-normal in Schaefer and Pella-Tomlinson models were same, i.e., 452106 t and 536284 t, in that order. However, gamma error assumption produced minimization failure. Fox model estimated the highest value of R2 (0.671). In ASPIC, Fox model assessed MSY, CV and R2 and FMSY as 545100 t, 0.090, 0.785 and 0.222 y-1, in that order. Whereas, Logistic model calculated similar parameters as 558700 t, 0.198 y-1, 0.111 and 0.78, respectively. The results of this preliminary study represent overexploitation of this fishery resource. Thus, effective management strategies with proper implementation are direly needed to conserve this commercially important marine fishery resource for its long-term economic gain. Moreover, supplement research on local fisheries resources by using single fish species data is strongly suggested in order to further strengthen this preliminary research.
Page(s): 318-325
URI: http://nopr.niscair.res.in/handle/123456789/54067
ISSN: 0975-1033 (Online); 0379-5136 (Print)
Appears in Collections:IJMS Vol.49(02) [February 2020]

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