ISSN:0196-6324    

DOI:10.1080/01966324.1992.10737328

出版商:Taylor & Francis    

年代:1992

数据来源: Taylor

摘要:

Issues and problems in the control and management of fisheries systems have given rise to an extensive literature of applied management science models and methods. This paper surveys and classifies this literature into areas according to the major problems confronted in fisheries applications. Widely used management science methods are presented and key publications annotated. Finally, the bibliography presents an extended list of management science research in fisheries.

ISSN:0196-6324    

DOI:10.1080/01966324.1992.10737329

出版商:Taylor & Francis    

年代:1992

数据来源: Taylor

摘要:

This paper examines experience with operations research models that have been applied to enforcement issues in Canada's offshore fishery. A probabilistic model was successfully used in the late 1970's to predict the probability of sighting a vessel in a particular area given the level of air hours or vessel sea days expended. Allocations of air patrol hours and sea days to various areas were subsequently made in terms of the model's results.

ISSN:0196-6324    

DOI:10.1080/01966324.1992.10737330

出版商:Taylor & Francis    

年代:1992

数据来源: Taylor

摘要:

This paper presents a Bayesian updating algorithm which can be incorporated into fishery management simulation models in order to examine the effects of imperfect knowledge, parameter uncertainty and the role of learning processes in fishery systems. In particular, the algorithm is utilized here to explore the effects of uncertainty on the performance of fishery management and the dynamics of capacity planning. Monte Carlo results indicate that, on average, the algorithm produces parameter estimates which eventually approximate the true values. However, initial uncertainty can affect significantly the economic performance of the fishery, through excessive investment and suboptimal harvesting policies.

ISSN:0196-6324    

DOI:10.1080/01966324.1992.10737331

出版商:Taylor & Francis    

年代:1992

数据来源: Taylor

摘要:

Salinity exerts a major influence over the survival and distribution of many fish species. This has been demonstrated time and again with regard to the Chesapeake Bay. In this paper, we examine an enormous data set of nearly 37,000 observations gathered from 34 stations in the Chesapeake Bay from 1984 to 1989. We develop 10 regression models to take into account various factors such as diverse geographic regions of the Bay. Each model uses six (although not the same six) independent variables; R-squared values range from 56% to 81%. In addition, model validation is carried out successfully on a new data set.

ISSN:0196-6324    

DOI:10.1080/01966324.1992.10737332

出版商:Taylor & Francis    

年代:1992

数据来源: Taylor

ISSN:0196-6324    

DOI:10.1080/01966324.1992.10737327

出版商:Taylor & Francis    

年代:1992

数据来源: Taylor