Spatial and temporal statistical analysis of bycatch data: patterns of sea turtle bycatch in the North Atlantic

• Published in: Canadian Journal of Fisheries and Aquatic Sciences
• Main Authors: Gardner, Beth, Sullivan, Patrick J., Morreale, Stephen J., Epperly, Sheryan P.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Canadian Science Publishing 2008
• Subjects: North Atlantic
• Online Access: http://dx.doi.org/10.1139/f08-152; http://www.nrcresearchpress.com/doi/full-xml/10.1139/F08-152; http://www.nrcresearchpress.com/doi/pdf/10.1139/F08-152

Loggerhead ( Caretta caretta ) and leatherback ( Dermochelys coriacea ) sea turtle distributions and movements in offshore waters of the western North Atlantic are not well understood despite continued efforts to monitor, survey, and observe them. Loggerhead and leatherback sea turtles are listed as endangered by the World Conservation Union, and thus anthropogenic mortality of these species, including fishing, is of elevated interest. This study quantifies spatial and temporal patterns of sea turtle bycatch distributions to identify potential processes influencing their locations. A Ripley’s K function analysis was employed on the NOAA Fisheries Atlantic Pelagic Longline Observer Program data to determine spatial, temporal, and spatio-temporal patterns of sea turtle bycatch distributions within the pattern of the pelagic fishery distribution. Results indicate that loggerhead and leatherback sea turtle catch distributions change seasonally, with patterns of spatial clustering appearing from July through October. The results from the space–time analysis indicate that sea turtle catch distributions are related on a relatively fine scale (30–200 km and 1–5 days). The use of spatial and temporal point pattern analysis, particularly K function analysis, is a novel way to examine bycatch data and can be used to inform fishing practices such that fishing could still occur while minimizing sea turtle bycatch.