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PLoS One. 2015 Apr 2;10(3):e0120929. doi: 10.1371/journal.pone.0120929. eCollection 2015.

Strategic assessment of fisheries independent monitoring programs in the gulf of Mexico.

Author information

1
University of South Florida-College of Marine Science, 140 7th Ave S, St. Petersburg, Florida, 33701, United States of America; Mote Marine Laboratory, 1600 Ken Thompson Parkway, Sarasota, Florida, 34236, United States of America.
2
University of South Florida-College of Marine Science, 140 7th Ave S, St. Petersburg, Florida, 33701, United States of America.

Abstract

This study evaluates information produced from 14 fisheries independent monitoring programs (FIM) in the Gulf of Mexico. We consider the uniqueness of information from each program and its usefulness in estimating fisheries management indices. Biomass values of 35 functional groups are extracted from an operating model (Ecospace) with a method that replicates the patterns of historic FIM samplings. Observation error is added to these data in order to create a set of pseudo data that replicate the type and quality of information obtained from FIM programs. The pseudo data were put into a separate fishery assessment model (Pella-Tomlinson) to determine management indices of each functional group (maximum sustainable yield (MSY), biomass at MSY, and fishing mortality at MSY). These indices are compared against values in Ecospace, and against previously published single-species stock assessments. We also evaluate the full suite of information derived from FIM within an ecosystem context, considering whether functional roles are over- or under-sampled, and whether sampling effort is proportional to the value of fish stocks. Results reveal that model derived fishery indices closely matched published indices for the majority of the functional groups, economic and ecological evaluation suggests that several piscivorous functional groups are under-sampled include forage base species that are likely to indirectly support fisheries for piscivores, and sampling efforts are not proportional to the value of some fish stocks. Following ecological modelling we performed statistical analyses on historic FIM catch data to identify optimal species-specific sampling months and gear-types that can be used to refine future FIM sampling efforts.

PMID:
25835742
PMCID:
PMC4383601
DOI:
10.1371/journal.pone.0120929
[Indexed for MEDLINE]
Free PMC Article

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