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

2018 ◽  
Vol 50 (1) ◽  
Author(s):  
Muhsan Ali Kalhoro ◽  
Danling Tang ◽  
Ye Hai Jun ◽  
Morozov Evgeny ◽  
Sufen Wang ◽  
...  
2016 ◽  
Vol 35 (4) ◽  
pp. 936-946 ◽  
Author(s):  
Muhammad Mohsin ◽  
Yongtong Mu ◽  
Aamir Mahmood Memon ◽  
Muhammad Talib Kalhoro ◽  
Syed Baber Hussain Shah

2018 ◽  
Vol 51 (2) ◽  
Author(s):  
Imran Ahmed Khan ◽  
Lubna Ghazal ◽  
Mudassar Hassan Arsalan ◽  
Muhammad Faheem Siddiqui

1989 ◽  
Vol 46 (1) ◽  
pp. 137-144 ◽  
Author(s):  
D. Ludwig ◽  
C. J. Walters

The problem of robust estimation of optimal effort levels from surplus production models is considered. A variety of models are used to generate data, for the purpose of testing estimation schemes. The result of an estimation is an estimate of the optimal effort. These efforts are compared using the expected discounted value of a deterministic stock, which corresponds to the model used to generate the data. Such a criterion takes into account not only the loss due to bias in the estimated optimal effort, but also the loss due to the variance of the estimator. Estimation is difficult if there is a lack of informative variation in effort levels or stock sizes. In such cases, the estimation scheme which maximizes the criterion described above sacrifices realism in the representation of the stock-production relationship in order to reduce the variance of the estimate of optimal effort. We present a composite estimation scheme which performs acceptably in all the cases we have examined, and whose performance degrades slowly as the amount of information in the data decreases.


2006 ◽  
Vol 63 (1) ◽  
pp. 4-11 ◽  
Author(s):  
Jon T. Schnute ◽  
Rowan Haigh

Abstract Fisheries management often relies heavily on precautionary reference points estimated from complex statistical models. An alternative approach uses management strategies defined by mathematical algorithms that calculate controls, like catch quotas, directly from the observed data. We combine these two distinct paradigms into a common framework using arguments from the historical development of quantum mechanics. In fisheries, as in physics, the core of the argument lies in the technical details. We illustrate the process of designing a management algorithm similar to one actually used by the International Whaling Commission. Reference points and surplus production models play a conceptual role in defining management strategies, even if marine populations do not obey such simplistic rules. Physicists have encountered similar problems in formulating quantum theory, where mathematical objects with seemingly unrealistic properties generate results of great practical importance.


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