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annotated bibliography of fisheries economics literature - Office of ...

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Ladner, Rosamund, Leah J. Smith, Susan Peterson, and James Wilson<br />

(1981). "Bibliography <strong>of</strong> Socio-Economic Studies: Fisheries <strong>of</strong> the<br />

Northeast U.S." Woods Hole Oceanographic Institution, Technical<br />

Report WHOI-81-99, Woods Hole, Massachusetts 02543.<br />

This <strong>bibliography</strong> <strong>of</strong> social and economic studies <strong>of</strong> the <strong>fisheries</strong> <strong>of</strong> the<br />

Northeast United States includes <strong>annotated</strong> listings for each entry and an<br />

index <strong>of</strong> key works for cross referencing. We have attempted to include all<br />

studies published since 1970, and a selected group <strong>of</strong> particularly significant<br />

studies done earlier. The major focus has been on commercial <strong>fisheries</strong>, but<br />

recreational fishing studies have also been included when possible. In<br />

addition to studies <strong>of</strong> the Northeast United States <strong>fisheries</strong>, studies <strong>of</strong><br />

Canadian fishing subsidies, European and other markets, have been included<br />

because <strong>of</strong> their relevance to the regional industry. All stages <strong>of</strong> the<br />

fishing industry's operation - harvesting, processing, distribution, marketing<br />

- are included, along with management and policy oriented material.<br />

Lallemand, Philippe, J.M. Gates, Joel Dirlam, and Jung Hee Cho (1998). The<br />

Costs <strong>of</strong> Small Trawlers. Final report, Department <strong>of</strong> Environmental &<br />

Natural Resource Economics, University <strong>of</strong> Rhode Island, Kingston, RI,<br />

March, 54 pp.<br />

The results <strong>of</strong> an economic survey <strong>of</strong> small northeast fishing vessels<br />

using otter trawl gear is described. The population consisted <strong>of</strong> 572 persons<br />

who were holders <strong>of</strong> groundfish permits, had fishing vessels <strong>of</strong> 65 feet or<br />

less, and who reported catches in New England using trawl gear in 1996. A 10<br />

percent response rate was achieved from a mail survey <strong>of</strong> a questionnaire that<br />

generated 35 usable responses from a probable population <strong>of</strong> 420 fishermen.<br />

The results <strong>of</strong> our mail survey <strong>of</strong> small trawlers are presented in eleven sets<br />

<strong>of</strong> tables and 4 sets <strong>of</strong> figures. Each table summarizes quantitative data<br />

responses by providing two or more measures <strong>of</strong> central tendency (the mean or<br />

average , the median, and the mode), and two measures <strong>of</strong> variability (the<br />

standard deviation, the standard error <strong>of</strong> the mean, the skewness, and the<br />

range). The Count on total respondents for each question is also provided as<br />

an indication <strong>of</strong> the reliability <strong>of</strong> the results.<br />

Lam, C.F., J.D. Whitaker, and F.S. Lee (1989). "Model for White Shrimp<br />

Landings for the Central Coast <strong>of</strong> South Carolina." North American<br />

Journal <strong>of</strong> Fisheries Management, 9:12-22.<br />

A stock recruitment relationship (SRR) was developed for white shrimp<br />

Penaeus setiferus in the central coastal area <strong>of</strong> South Carolina. The SRR is a<br />

Beverton-Holt type curve for which May and June commercial fishery landings<br />

represent stock and August-January landings represent recruitment. A<br />

variable, August salinity in Charleston Harbor, was selected by the stepwise<br />

regression process, and it was combined with the Beverton-Holt equation to<br />

produce a model that explained 86.8% <strong>of</strong> the variation in August-January<br />

landings. The final model was used to develop a family <strong>of</strong> SRR curves in which<br />

each curve corresponded to a different salinity. This model was sufficiently<br />

robust to forecast below average, average, and above average fall landings<br />

from readily obtainable data collected in spring and summer. These findings<br />

support South Carolina's existing management strategy <strong>of</strong> protecting spring<br />

spawners as much as possible after severe winter weather when the brood stock<br />

has suffered heavy mortality.<br />

Lambert, David K. and J.S. Shonkwiler (1995). Factor Bias Under Stochastic<br />

Technical Change. American Journal <strong>of</strong> Agricultural Economics,<br />

77(3):578-590.<br />

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