2022
DOI: 10.3389/fmars.2022.869560
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Learning From the Study Fleet: Maintenance of a Large-Scale Reference Fleet for Northeast U.S. Fisheries

Abstract: Logbook data from commercial fisheries are a vital component in the machinery of management, including tracking the volume of catches and allocating catch spatially. At the same time, logbooks can provide a unique window into the ecological and sociological conditions in marine fisheries, where fishermen interact with marine species and environments frequently and broadly. Traditional logbooks, however, often are not sufficiently standardized (when personal logs), or lack the detail (when regulatory documents)… Show more

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Cited by 11 publications
(24 citation statements)
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“…Models for doing so can be found in a variety of study fleets (Gawarkiewicz and Mercer 2019) that have been employed to collect fisheries, ecological, and oceanographic data on behalf of management and research agencies, such as the U.S. National Marine Fisheries Service's Northeast Cooperative Research Study Fleet (Jones et al. 2022) and the Woods Hole Oceanographic Institution's Shelf Research Fleet (see https://www.cfrfoundation.org/shelf-research-fleet). For the Pacific Halibut fishery, a carefully selected and properly compensated research fleet that spans vessel classes, gear types, and the geographic range of the species may provide an opportunity to collect full‐season data that are otherwise unavailable during the summer survey season and capture the unique dynamics of commercial fishing operations.…”
Section: Discussionmentioning
confidence: 99%
“…Models for doing so can be found in a variety of study fleets (Gawarkiewicz and Mercer 2019) that have been employed to collect fisheries, ecological, and oceanographic data on behalf of management and research agencies, such as the U.S. National Marine Fisheries Service's Northeast Cooperative Research Study Fleet (Jones et al. 2022) and the Woods Hole Oceanographic Institution's Shelf Research Fleet (see https://www.cfrfoundation.org/shelf-research-fleet). For the Pacific Halibut fishery, a carefully selected and properly compensated research fleet that spans vessel classes, gear types, and the geographic range of the species may provide an opportunity to collect full‐season data that are otherwise unavailable during the summer survey season and capture the unique dynamics of commercial fishing operations.…”
Section: Discussionmentioning
confidence: 99%
“…Sample collection.-Cusk samples (Table 1) were collected primarily during the spring (April-May) and fall (October-November) operations of the Northeast Fisheries Science Center (NEFSC) Gulf of Maine Bottom Longline Survey (BLLS; McElroy et al 2019) and the NEFSC Bottom Trawl Survey (BTS; Politis et al 2014). Additional samples in months outside the survey periods were obtained from commercial vessels participating in the NEFSC Study Fleet (Jones et al 2022). These samples came from vessels using both bottom trawl and rod-andreel gear.…”
Section: Methodsmentioning
confidence: 99%
“…Additional samples in months outside the survey periods were obtained from commercial vessels participating in the NEFSC Study Fleet (Jones et al. 2022). These samples came from vessels using both bottom trawl and rod‐and‐reel gear.…”
Section: Methodsmentioning
confidence: 99%
“…They may underestimate the extent of the commitment and continuity of resources required for sustained research (Starr, 2010), making it difficult to ensure that data provision persists (Lordan et al, 2011;Mangi et al, 2015;Mangi et al, 2018;Raicevich et al, 2020;Steins et al, 2020a;Van Helmond et al, 2020). Continuity may also be affected when committed fishers leave the fishery (Jones et al, 2022) or when there are trust issues, for instance, when participating fishers or their peers fear the information they provide will be used against them, serving only to punish efforts of collaboration (Carruthers and Neis, 2011;Kraan et al, 2013;Mangi et al, 2015;Röckmann et al,…”
Section: Issue 1: Quality Of Voluntary Industry Contributionsmentioning
confidence: 99%