44
Views
9
CrossRef citations to date
0
Altmetric
Article

Comparing Historical Catch Rates of American Shad in Multifilament and Monofilament Nets: A Step toward Setting Restoration Targets for Virginia Stocks

, , &
Pages 282-288 | Received 20 Feb 2005, Accepted 28 Sep 2005, Published online: 09 Jan 2011
 

Abstract

Recreational and commercial harvest of American shad Alosa sapidissima in the Virginia waters of the Chesapeake Bay and its tributaries has been prohibited since 1994. The Atlantic States Marine Fisheries Commission Shad and River Herring Management Plan requires that Virginia develop restoration targets for its shad populations, but estimates of their sizes are not available and there is little information about historic population levels. Thus, establishing restoration targets based on population size is problematic. A current spawning stock monitoring program yields catch rate information that can be compared with historic catch rate information recorded in commercial fishery logbooks from the 1950s and the 1980s. However, multifilament gill nets were used in the 1950s and monofilament nets were used in the 1980s (as well as in the current monitoring program). A Latin square design was employed to test the differences in relative fishing power of the two gear types over 2 years of seasonal sampling on the York River, Virginia. Estimates are that the monofilament nets are roughly twice as efficient as the multifilament nets. Reported catch rates in the 1950s and 1980s are roughly equivalent. However, when adjustments are made for the differences in fishing gear, catch rates for the 1950s are twice as high as those during the 1980s. These results provide valuable information for setting restoration targets for Virginia stocks of American shad.

Log in via your institution

Log in to Taylor & Francis Online

There are no offers available at the current time.

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.