EconPapers    
Economics at your fingertips  
 

Management of a Multiple Cohort Fishery: The Hard Clam in Great South Bay

Jon M. Conrad

No 183806, Staff Papers from Cornell University, Department of Applied Economics and Management

Abstract: Bioeconomics to date has focused almost exclusively on lumped parameter models where the resource is described by a single state variable defined as biomass. While such models are convenient mathematically they may be inappropriate in fisheries where recruitment and fecundity are dependent on the age structure of the resource. This paper develops a reasonably general multiple cohort model and derives conditions for optimal harvest and age structure based on a discrete time control problem which maximizes the present value of net revenues subject to recruitment and spawning constraints. The model is applied to the hard clam resource in Great south Bay which is located on Ling Island, New York The steady state optimum calls for exclusive harvesting of the younger, ( and more valuable), "littleneck" cohorts; leaving the older, (and less valuable), "cherrystone" and "chowder" cohorts to specialize in regeneration.

Keywords: Demand and Price Analysis; Environmental Economics and Policy; Livestock Production/Industries (search for similar items in EconPapers)
Pages: 27
Date: 1981-02
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/183806/files/Cornell-Dyson-sp8103.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:cudasp:183806

DOI: 10.22004/ag.econ.183806

Access Statistics for this paper

More papers in Staff Papers from Cornell University, Department of Applied Economics and Management Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().

 
Page updated 2025-03-19
Handle: RePEc:ags:cudasp:183806