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.
| Main Authors: | , |
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| Format: | article biblioteca |
| Language: | English |
| Published: |
2012
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| Subjects: | Biology, Ecology, Fisheries, Management, |
| Online Access: | http://hdl.handle.net/1834/25579 |
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