Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch in the pelagic longline fishery
Estimating rare events from zero-heavy data (data withmany zero values) is a common challenge in fisheries science and ecology. For example, loggerhead sea turtles(Caretta caretta) and leatherback sea turtles (Dermochelys coriacea) account for less than 1% of total catch in theU.S. Atlantic pelagic longline fishery. Nevertheless, the Southeast Fisheries Science Center (SEFSC) of the National Marine Fisheries Service (NMFS) is charged with assessing the effect of this fishery on these federally protected species. Annual estimates of loggerhead and leatherbackbycatch in a fishery can affect fishery management and species conservation decisions. However, current estimateshave wide confidence intervals, and their accuracy is unknown. We evaluate 3 estimation methods, each at 2spatiotemporal scales, in simulations of 5 spatial scenarios representing incidental capture of sea turtles bythe U.S. Atlantic pelagic longline fishery. The delta-log normal method of estimating bycatch for calendar quarter and fishing area strata was the least biased estimation method in the spatial scenarios believed to be most realistic. This result supports the current estimation procedure used by the SEFSC.
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dig-aquadocs-1834-255792021-06-30T01:50:22Z Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch in the pelagic longline fishery Barlow, Paige F. Berkson, Jim Biology Ecology Fisheries Management Estimating rare events from zero-heavy data (data withmany zero values) is a common challenge in fisheries science and ecology. For example, loggerhead sea turtles(Caretta caretta) and leatherback sea turtles (Dermochelys coriacea) account for less than 1% of total catch in theU.S. Atlantic pelagic longline fishery. Nevertheless, the Southeast Fisheries Science Center (SEFSC) of the National Marine Fisheries Service (NMFS) is charged with assessing the effect of this fishery on these federally protected species. Annual estimates of loggerhead and leatherbackbycatch in a fishery can affect fishery management and species conservation decisions. However, current estimateshave wide confidence intervals, and their accuracy is unknown. We evaluate 3 estimation methods, each at 2spatiotemporal scales, in simulations of 5 spatial scenarios representing incidental capture of sea turtles bythe U.S. Atlantic pelagic longline fishery. The delta-log normal method of estimating bycatch for calendar quarter and fishing area strata was the least biased estimation method in the spatial scenarios believed to be most realistic. This result supports the current estimation procedure used by the SEFSC. 2021-06-24T16:21:05Z 2021-06-24T16:21:05Z 2012 article TRUE 0090-0656 http://hdl.handle.net/1834/25579 en http://fishbull.noaa.gov/1103/barlow.pdf application/pdf application/pdf 344-360 http://aquaticcommons.org/id/eprint/8967 403 2012-08-03 19:12:42 8967 United States National Marine Fisheries Service |
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Biology Ecology Fisheries Management Biology Ecology Fisheries Management Barlow, Paige F. Berkson, Jim Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch in the pelagic longline fishery |
| description |
Estimating rare events from zero-heavy data (data withmany zero values) is a common challenge in fisheries science and ecology. For example, loggerhead sea turtles(Caretta caretta) and leatherback sea turtles (Dermochelys coriacea) account for less than 1% of total catch in theU.S. Atlantic pelagic longline fishery. Nevertheless, the Southeast Fisheries Science Center (SEFSC) of the National Marine Fisheries Service (NMFS) is charged with assessing the effect of this fishery on these federally protected species. Annual estimates of loggerhead and leatherbackbycatch in a fishery can affect fishery management and species conservation decisions. However, current estimateshave wide confidence intervals, and their accuracy is unknown. We evaluate 3 estimation methods, each at 2spatiotemporal scales, in simulations of 5 spatial scenarios representing incidental capture of sea turtles bythe U.S. Atlantic pelagic longline fishery. The delta-log normal method of estimating bycatch for calendar quarter and fishing area strata was the least biased estimation method in the spatial scenarios believed to be most realistic. This result supports the current estimation procedure used by the SEFSC. |
| format |
article |
| topic_facet |
Biology Ecology Fisheries Management |
| author |
Barlow, Paige F. Berkson, Jim |
| author_facet |
Barlow, Paige F. Berkson, Jim |
| author_sort |
Barlow, Paige F. |
| title |
Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch
in the pelagic longline fishery |
| title_short |
Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch
in the pelagic longline fishery |
| title_full |
Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch
in the pelagic longline fishery |
| title_fullStr |
Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch
in the pelagic longline fishery |
| title_full_unstemmed |
Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch
in the pelagic longline fishery |
| title_sort |
evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch
in the pelagic longline fishery |
| publishDate |
2012 |
| url |
http://hdl.handle.net/1834/25579 |
| work_keys_str_mv |
AT barlowpaigef evaluatingmethodsforestimatingrareeventswithzeroheavydataasimulationmodelestimatingseaturtlebycatchinthepelagiclonglinefishery AT berksonjim evaluatingmethodsforestimatingrareeventswithzeroheavydataasimulationmodelestimatingseaturtlebycatchinthepelagiclonglinefishery |
| _version_ |
1756078048561594368 |