Not just another mixed stock analysis: green turtles of Espírito Santo, Brazil.

Abstract

In the Southwestern Atlantic Ocean, sea turtles are exposed to myriad threats including disease, fisheries bycatch, and industrial or coastal development, but protected by effective conservation organizations. In Espirito Santo, Brazil, green turtles (Chelonia mydas) with relatively high incidence of fibropapillomatosis tumors routinely strand in the vicinity of the state capital, Vitória, a highly urbanized area that encompasses the effluent discharge channel of a local steel plant. This is also a particularly interesting population because of its relative proximity to the regionally important Trindade Island rookery, whose feeding grounds have not been convincingly identified to date. To investigate the population distribution of the at-risk turtles, we sequenced a segment of the mitochondrial control region (862 bp; n = 132). Eight mtDNA haplotypes were revealed, of which the most common were CMA-08 and CMA-05. Haplotypes CMA-06 and CMA-09 were each found in six individuals, and rare haplotypes CMA-03, CMA-10, CMA-23, and CMA-32 were also detected. Two kinds of "many-to-many" mixed stock analyses were carried out, taking into account or alternately disregarding source nesting population size. The same approach was taken with traditional MSAS ("one-to-many"), and the main differences between the "one-to-many" and "many-to-many" results are reported. The analyses that included population size and all available data were most consistent with expectations. We recommend caution when employing different mixed stock analysis methods, and emphasize the importance of exploring alternate ways of investigating the origins of mixed stocks, including modeling approaches. These data will provide insight into population isolation and conservation priorities necessary to establish whether areas should be managed as independent units or as regional populations, and will clarify questions of scale in conservation and management, providing a scientific basis for conservation prioritization.