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

Suprenand PM, Drexler M, Jones DL, Ainsworth CH - PLoS ONE (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: 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.

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.

No MeSH data available.


Related in: MedlinePlus

Canonical analysis of principal coordinates (CAP) point (a) and vector (b) plots for SEAMAP abundance data organized by sampling months per year.Axes in a) are labelled according to the overall classification accuracy by sampling month (78%), whereas axes in b) depict the correlations to sampling month(s) by vector length along the first two canonical axes depicted in the CAP point-plot. Vector length is proportional to a month’s contribution in separating functional groups by abundance, where longer vector lengths indicate importance. In general this figure illustrates a predictable assemblage of species based on monthly captures, and indicates the similarity of different months in terms of the assemblage caught and therefore information content.
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pone.0120929.g006: Canonical analysis of principal coordinates (CAP) point (a) and vector (b) plots for SEAMAP abundance data organized by sampling months per year.Axes in a) are labelled according to the overall classification accuracy by sampling month (78%), whereas axes in b) depict the correlations to sampling month(s) by vector length along the first two canonical axes depicted in the CAP point-plot. Vector length is proportional to a month’s contribution in separating functional groups by abundance, where longer vector lengths indicate importance. In general this figure illustrates a predictable assemblage of species based on monthly captures, and indicates the similarity of different months in terms of the assemblage caught and therefore information content.

Mentions: The relative abundances of SEAMAP species comprising the 35 evaluated functional groups were found to be significantly different between sampling months (np-Manova; F = 4.10, P = 0.001, N = 162), suggesting that certain months may provide more comprehensive information by species than other months. CAP tests revealed that sampling months had an overall 78% classification accuracy rate when classifying data (Fig 6), which was significantly better than the 12% success rate predicted by PCC (P = 0.001). Therefore, sampling month has a strong effect in the quality of information produced by the SEAMAP program. When vector plots were examined, information overlap appeared most evident for Atlantic Croaker, Blue Crab, Pompano, Mackerel, and Sea Trout, and less evident for Bay Anchovy, Jacks, Red Drum, and Stone Crab. Species of Grouper, Red Snapper and two species of Jacks clearly showed that their abundance data was limited to specific sampling months, and no overlap with other sampling months was observed. The timing of sampling for these species is therefore inflexible and should be directed towards the most effective months.


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

Suprenand PM, Drexler M, Jones DL, Ainsworth CH - PLoS ONE (2015)

Canonical analysis of principal coordinates (CAP) point (a) and vector (b) plots for SEAMAP abundance data organized by sampling months per year.Axes in a) are labelled according to the overall classification accuracy by sampling month (78%), whereas axes in b) depict the correlations to sampling month(s) by vector length along the first two canonical axes depicted in the CAP point-plot. Vector length is proportional to a month’s contribution in separating functional groups by abundance, where longer vector lengths indicate importance. In general this figure illustrates a predictable assemblage of species based on monthly captures, and indicates the similarity of different months in terms of the assemblage caught and therefore information content.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4383601&req=5

pone.0120929.g006: Canonical analysis of principal coordinates (CAP) point (a) and vector (b) plots for SEAMAP abundance data organized by sampling months per year.Axes in a) are labelled according to the overall classification accuracy by sampling month (78%), whereas axes in b) depict the correlations to sampling month(s) by vector length along the first two canonical axes depicted in the CAP point-plot. Vector length is proportional to a month’s contribution in separating functional groups by abundance, where longer vector lengths indicate importance. In general this figure illustrates a predictable assemblage of species based on monthly captures, and indicates the similarity of different months in terms of the assemblage caught and therefore information content.
Mentions: The relative abundances of SEAMAP species comprising the 35 evaluated functional groups were found to be significantly different between sampling months (np-Manova; F = 4.10, P = 0.001, N = 162), suggesting that certain months may provide more comprehensive information by species than other months. CAP tests revealed that sampling months had an overall 78% classification accuracy rate when classifying data (Fig 6), which was significantly better than the 12% success rate predicted by PCC (P = 0.001). Therefore, sampling month has a strong effect in the quality of information produced by the SEAMAP program. When vector plots were examined, information overlap appeared most evident for Atlantic Croaker, Blue Crab, Pompano, Mackerel, and Sea Trout, and less evident for Bay Anchovy, Jacks, Red Drum, and Stone Crab. Species of Grouper, Red Snapper and two species of Jacks clearly showed that their abundance data was limited to specific sampling months, and no overlap with other sampling months was observed. The timing of sampling for these species is therefore inflexible and should be directed towards the most effective months.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: 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.

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.

No MeSH data available.


Related in: MedlinePlus