Declining catch rates in Caribbean Nicaragua green turtle fishery may be result of overfishing
A 20-year assessment of Nicaragua’s legal, artisanal green sea turtle fishery has uncovered a stark reality: greatly reduced overall catch rates of turtles in what may have become an unsustainable take, according to conservation scientists from the Wildlife Conservation Society and University of Florida.
During the research period, conservation scientists estimated that more than 170,000 green turtles were killed between 1991 and 2011, with catch rates peaking in 1997 and 2002 and declining steeply after 2008, likely resulting from over-fishing. The trend in catch rates, the authors of the assessment results maintain, indicates the need for take limits on this legal fishery.
The study now appears in the online journal PLOS ONE. The authors are: Cynthia J. Lagueux and Cathi L. Campbell of the University of Florida (formerly of the Wildlife Conservation Society), and Samantha Strindberg of the Wildlife Conservation Society.
“The significant decrease in the catch rates of green turtles represents a concern for both conservationists and local, coastal communities who depend on this resource,” said Dr. Lagueux, lead author of the study. “We hope this study serves as a foundation for implementing scientifically based limits on future green turtle take.”
Caribbean coastal waters of Nicaragua contain extensive areas of sea grass, principal food source for green turtles, the only herbivorous sea turtle species. Green turtles in turn support a number of indigenous Miskitu and Afro-descendent communities that rely on the marine reptiles for income (by selling the meat) and as a source of protein.
The catch data used by the researchers to estimate trends was gathered by community members at 14 different sites located in two geographically political regions of the Nicaraguan coast. The research team analyzed the long-term data set to examine catch rates for the entire fishery, each region, and for individual turtle fishing communities using temporal trend models.
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