Koch, Volker, Peckham, Hoyt, Mancini, Agnese and Eguchi, Tomoharu (2013) Estimating At-Sea Mortality of Marine Turtles from Stranding Frequencies and Drifter Experiments. PLoS ONE, 8 (2). e56776. DOI https://doi.org/10.1371/journal.pone.0056776.

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Abstract

Strandings of marine megafauna can provide valuable information on cause of death at sea. However, as stranding probabilities are usually very low and highly variable in space and time, interpreting the results can be challenging. We evaluated the magnitude and distribution of at-sea mortality of marine turtles along the Pacific coast of Baja California Sur, México during 2010–11, using a combination of counting stranded animals and drifter experiments. A total of 594 carcasses were found during the study period, with loggerhead (62%) and green turtles (31%) being the most common species. 87% of the strandings occurred in the southern Gulf of Ulloa, a known hotspot of loggerhead distribution in the Eastern Pacific. While only 1.8% of the deaths could be definitively attributed to bycatch (net marks, hooks), seasonal variation in stranding frequencies closely corresponded to the main fishing seasons. Estimated stranding probabilities from drifter experiments varied among sites and trials (0.05–0.8), implying that only a fraction of dead sea turtles can be observed at beaches. Total mortality estimates for 15-day periods around the floater trials were highest for PSL, a beach in the southern Gulf of Ulloa, ranging between 11 sea turtles in October 2011 to 107 in August 2010. Loggerhead turtles were the most numerous, followed by green and olive ridley turtles. Our study showed that drifter trials combined with beach monitoring can provide estimates for death at sea to measure the impact of small-scale fisheries that are notoriously difficult to monitor for by-catch. We also provided recommendations to improve the precision of the mortality estimates for future studies and highlight the importance of estimating impacts of small–scale fisheries on marine megafauna.

Document Type:	Article
Programme Area:	UNSPECIFIED
Research affiliation:	Integrated Modelling > Resource Management
Refereed:	Yes
Open Access Journal?:	Yes
DOI:	https://doi.org/10.1371/journal.pone.0056776
ISSN:	1932-6203
Date Deposited:	16 Aug 2019 15:02
Last Modified:	01 Oct 2020 12:59
URI:	http://cris.leibniz-zmt.de/id/eprint/2665

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