DNA and dispersal models highlight constrained connectivity in a migratory marine megavertebrate

Abstract

Population structure and spatial distribution are fundamentally important fields within ecology, evolution, and conservation biology. To investigate pan‐Atlantic connectivity of globally endangered green turtles Chelonia mydas from two National Parks in Florida, USA, we applied a multidisciplinary approach comparing genetic analysis and ocean circulation modeling. The Everglades (EP) is a juvenile feeding ground, whereas the Dry Tortugas (DT) is used for courtship, breeding, and feeding by adults and juveniles. We sequenced two mitochondrial segments from 138 turtles sampled there from 2006–2015, and simulated oceanic transport to estimate their origins. Genetic and ocean connectivity data revealed northwestern Atlantic rookeries as the major natal sources, while southern and eastern Atlantic contributions were negligible. However, specific rookery estimates differed between genetic and ocean transport models. The combined analyses suggest that post‐hatchling drift via ocean currents poorly explains the distribution of neritic juveniles and adults, but juvenile natal homing and population history likely play important roles. DT and EP were genetically similar to feeding grounds along the southern US coast, but highly differentiated from most other Atlantic groups. Despite expanded mitogenomic analysis and correspondingly increased ability to detect genetic variation, no significant differentiation between DT and EP, or among years, sexes or stages was observed. This first genetic analysis of a North Atlantic green turtle courtship area provides rare data supporting local movements and male philopatry. The study highlights the applications of multidisciplinary approaches for ecological research and conservation.

Predicted distributions and abundances of the sea turtle ‘lost years’ in the western North Atlantic Ocean

“…ICHTHYOP implemented a Runge-Kutta fourth-order time-stepping method whereby particle position was calculated each half-hour as they moved through the HYCOM velocity fields. Virtual particles were tracked for up to 3.5 yr (2.5 yr for Kemp's ridley) to account for the period of the oceanic stage when movement is most dominated by surface currents , Naro-Maciel et al 2017. These drift times are representative of the entire oceanic-stage for Kemp's ridley (~100% of the oceanic stage) and many green turtles (~70-100%).…”

Advances in the Application of Genetics in Marine Turtle Biology and Conservation

“…While these studies have expanded our understanding of connectivity between rookeries and foraging areas, they do not provide information on migration routes or the factors that influence the dispersal of turtles. In recent years, multidisciplinary approaches have combined MSA and high-resolution ocean circulation modeling to further our understanding of marine turtle movement (e.g., Putman and Naro-Maciel, 2013;Naro-Maciel et al, 2017). These studies have revealed that while ocean currents play a vital role in the spatial distribution of turtles they do not always correlate with MSA results, suggesting that other factors such as swimming behavior play important roles in the distribution of turtles (Putman and He, 2013;Hays et al, 2014a;Naro-Maciel et al, 2014bChristiansen et al, 2016).…”

Genetic composition and origin of juvenile green turtles foraging at Culebra, Puerto Rico, as revealed by mtDNA

“…There is however a lack of genetic differentiation at the mtDNA control region between some individual rookeries (e.g., Suriname and Aves Island, NaroMaciel et al, 2016), so we also ran a MSA pooling the individual rookeries into Regional Management Units (RMUs, Wallace et al, 2010), which group multiple nesting populations based on their genetic similarities, for conservation management. Following Naro-Maciel et al (2016), the RMUs were defined as: 1) Northwest Atlantic -EcFL, SFL, MEX, CUB, CR; 2) Central Atlantic -BUC, AV, SUR; and 3) South and East Atlantic -RC/FN, ASC, TRI, GB, BIO, STP. Four independent chains with different starting points were run for 30,000 iterations, with a burn-in of 15,000 steps.…”

“…Nesting populations: EcFL and SFL: Florida, USA (Shamblin et al, 2014); CUB: southwest Cuba (Ruiz-Urquiola et al, 2010); MEX: Quintana Roo, Mexico (Encalada et al, 1996); CR: Tortuguero, Costa Rica (Bjorndal et al, 2005b;Encalada et al, 1996); SUR: Matapica and Galibi, Suriname (Encalada et al, 1996;Shamblin et al, 2012); AV: Aves Island (Lahanas et al, 1998(Lahanas et al, , 1994Shamblin et al, 2012), Venezuela; BUC: Buck Island (Shamblin et al, 2012); RC/FN: Rocas Atoll and Fernando Noronha (Bjorndal et al, 2006;Encalada et al, 1996), Brazil; ASC: Ascension Island (Encalada et al, 1996;Formia et al, 2007); TRI: Trindade Island, Brazil (Bjorndal et al, 2006); GB: Poilão, Guinea-Bissau (Patrício et al, 2017); BIO: Bioko Island, Equatorial Guinea ; STP: Sao Tome and Principe . Foraging grounds: NC: North Carolina (Bass et al, 2006), HI: Hutchinson Island, Florida (Bass & Witzell, 2000), DT+EP: Dry Tortugas + Everglades Park, Florida (Naro-Maciel et al, 2016), SJ: St. Joseph Bay, Florida (Foley et al, 2007), TEX: Texas (Anderson et al, 2013), USA; BHM: Bahamas (Lahanas et al, 1998), CUL: Culebra, Puerto Rico (this study), BRB: Barbados (Luke et al, 2004), ALF: Almofala, Brazil (Naro-Maciel et al, 2007), RC: Rocas Atoll, Brazil ), FN: Fernando Noronha, Brazil (Naro-Maciel et al, 2012, BA: Bahia, Brazil , ES: Espirito Santo, Brazil , UB: Ubatuba, Brazil (Naro-Maciel et al, 2007), AI: Arvoredo Island, Brazil (Proietti et al, 2012), CB: Cassino Beach, Brazil (Proietti et al, 2012), BuA, Buenos Aires, Argentina (Prosdocimi et al, 2012), CV: Cape Verde (Monzón-Argüello et al, 2010).…”

“…Temporal variability in source contributions has been attributed to very low hatching success at a major source elsewhere (Jensen et al, 2016). Other studies with green turtles in Brazil (Naro-Maciel et al, 2007) and Florida (Naro-Maciel et al, 2016), and with hawksbill turtles in Puerto Rico (Velez-Zuazo et al, 2008), however, found no temporal variation on the genetic composition of juvenile aggregations.…”