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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

Redundancy Analysis Plot of Year and CPUE per Functional Group.Redundancy analysis shows the functional groups (green text and vectors) most associated with the programmatic changes in the SEAMAP program according to the year-pattern (red text and vectors). The year-pattern refers to the geographical locations described as points in the operating model. Approximately 25% of the variability in functional group abundances is explained by the sampling year-pattern in two canonical axes. In general post-2009 changes have benefited only a few species, in particular Atlantic Croaker.
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pone.0120929.g005: Redundancy Analysis Plot of Year and CPUE per Functional Group.Redundancy analysis shows the functional groups (green text and vectors) most associated with the programmatic changes in the SEAMAP program according to the year-pattern (red text and vectors). The year-pattern refers to the geographical locations described as points in the operating model. Approximately 25% of the variability in functional group abundances is explained by the sampling year-pattern in two canonical axes. In general post-2009 changes have benefited only a few species, in particular Atlantic Croaker.

Mentions: The most representative SEAMAP sampling years between 2000 to 2012 that explained the most variability in CPUE for a few select species, and presented in order of variable selection and cumulative R2 values, are: 2012 (R2 = 0.05), 2010 (R2 = 0.11), 2009 (R2 = 0.19), and 2011 (R2 = 0.33). This is due to reduced discrepancies between the operating and assessment model for primarily the functional groups of Atlantic Croaker, Blue Crab, Catfish, Jacks, Menhaden, and Pigfish (Fig 5). Reduced discrepancies indicate that sampling strategies in the most recent years were more effective at providing representative stock information for the few functional groups listed above; however, sampling strategies might be less efficient for other functional groups (e.g. Red Snapper, Scaled Sardine or Silver Perch; Fig 2), and/or variability in CPUE could not be explained by sampling strategies used from 2000 to 2008 compared to those from 2009 to 2012. CAGES results by Gulf state showed that the most valuable sampling year(s) in Alabama were 2006 (R2 = 0.03) and 2007 (R2 = 0.07), Florida 2003 (R2 = 0.04), and Louisiana 2007 (R2 = 0.15) and 2001 (R2 = 0.19). Therefore, there has not been a noticeable increase or decrease in the quality of information emerging from CAGES; sampling years that provided the best results were scattered among the history of the CAGES program. Similarly, RDA tests for Mississippi and Texas revealed no differences in CAGES sampling variability from year-to-year.


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

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

Redundancy Analysis Plot of Year and CPUE per Functional Group.Redundancy analysis shows the functional groups (green text and vectors) most associated with the programmatic changes in the SEAMAP program according to the year-pattern (red text and vectors). The year-pattern refers to the geographical locations described as points in the operating model. Approximately 25% of the variability in functional group abundances is explained by the sampling year-pattern in two canonical axes. In general post-2009 changes have benefited only a few species, in particular Atlantic Croaker.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0120929.g005: Redundancy Analysis Plot of Year and CPUE per Functional Group.Redundancy analysis shows the functional groups (green text and vectors) most associated with the programmatic changes in the SEAMAP program according to the year-pattern (red text and vectors). The year-pattern refers to the geographical locations described as points in the operating model. Approximately 25% of the variability in functional group abundances is explained by the sampling year-pattern in two canonical axes. In general post-2009 changes have benefited only a few species, in particular Atlantic Croaker.
Mentions: The most representative SEAMAP sampling years between 2000 to 2012 that explained the most variability in CPUE for a few select species, and presented in order of variable selection and cumulative R2 values, are: 2012 (R2 = 0.05), 2010 (R2 = 0.11), 2009 (R2 = 0.19), and 2011 (R2 = 0.33). This is due to reduced discrepancies between the operating and assessment model for primarily the functional groups of Atlantic Croaker, Blue Crab, Catfish, Jacks, Menhaden, and Pigfish (Fig 5). Reduced discrepancies indicate that sampling strategies in the most recent years were more effective at providing representative stock information for the few functional groups listed above; however, sampling strategies might be less efficient for other functional groups (e.g. Red Snapper, Scaled Sardine or Silver Perch; Fig 2), and/or variability in CPUE could not be explained by sampling strategies used from 2000 to 2008 compared to those from 2009 to 2012. CAGES results by Gulf state showed that the most valuable sampling year(s) in Alabama were 2006 (R2 = 0.03) and 2007 (R2 = 0.07), Florida 2003 (R2 = 0.04), and Louisiana 2007 (R2 = 0.15) and 2001 (R2 = 0.19). Therefore, there has not been a noticeable increase or decrease in the quality of information emerging from CAGES; sampling years that provided the best results were scattered among the history of the CAGES program. Similarly, RDA tests for Mississippi and Texas revealed no differences in CAGES sampling variability from year-to-year.

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