Hybridization Analysis and Haplotypic Diversity in Eretmochelys Imbricata in Southeastern Brazil

Hybridization Analysis and Haplotypic Diversity in Eretmochelys Imbricata in Southeastern Brazil | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Hybridization Analysis and Haplotypic Diversity in Eretmochelys Imbricata in Southeastern Brazil Geovana Gonçalves, Bruno Henrique Mioto Stabile, José Henrique Becker, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7722562/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Marine Biology → Version 1 posted 5 You are reading this latest preprint version Abstract The hawksbill turtle ( Eretmochelys imbricata ), classified as critically endangered, has a global distribution in tropical and subtropical waters. The Brazilian colony is essential for the species' conservation, as it is the largest remaining nesting population in the South Atlantic. Furthermore, it exhibits the highest hybridization rate worldwide. This study investigated the foraging population in the state of São Paulo (Southeast Brazil), which previously lacked genetic data, using mitochondrial DNA (D-loop) analysis of immature individuals. Hybrids between E. imbricata and Caretta caretta were identified, along with hawksbill haplotypes previously recorded in southern South America and a novel haplotype for the region. The absence of Indo-Pacific haplotypes suggests the influence of the Benguela Current, which reduces genetic diversity compared to the Brazilian Northeast and the Caribbean. The results indicate that the foraging individuals in southern South America predominantly originate from the Brazilian Northeast, with some influence from the Caribbean, highlighting the role of the Brazil Current in the dispersal of hatchlings. These findings emphasize the importance of Southeast Brazil for hawksbill turtle conservation and its relevance to the species' life cycle across different regions. Biogeography Genetic diversity Genetic structure Migration Sea turtle Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION The hawksbill turtle, Eretmochelys imbricata (Linnaeus 1766), is a species with a circumglobal distribution in tropical and subtropical waters, including the Brazilian coast (IUCN 2014). Currently listed as critically endangered on the IUCN Red List (Mortimer and Donnelly 2008 ) and as endangered on Brazil’s List of Threatened Species (Brasil 2022), the hawksbill turtle was once on the verge of extinction in Brazil (Marcovaldi et al. 1999 ). The species continues to face numerous threats, including the collection and commercialization of eggs, meat, and carapaces, as well as habitat destruction from coastal development, pollution, and fisheries bycatch (Mortimer and Donnelly 2008 ; Simões et al. 2017 ; Barrios-Garrido et al. 2017 ; Miller et al. 2019 ; Bomfim et al. 2021 ; Balladares et al. 2023 ). Furthermore, it is vulnerable to the impacts of ongoing climate changes, such as the nesting sites loss due to rising sea levels, skewed sex ratios from temperature-dependent sex determination, and alterations in food availability (Fish et al. 2005 ; Montero et al. 2018 ; Maurer et al. 2021 ; Mau et al. 2024 ). The species is also affected by an exceptionally high rate of hybridization in Brazil, where the highest recorded global levels have been observed for sea turtles. Lara-Ruiz et al. ( 2006 ) identified that 42% of nesting hawksbill turtle females in Bahia were hybrids with the loggerhead turtle ( Caretta caretta (Linnaeus 1758)), while 1.6% were hybrids with the olive ridley turtle ( Lepidochelys olivacea (Eschscholtz 1829)). Although hybridization and genetic introgression can be natural evolutionary events, they may also be triggered by anthropogenic factors (Vilaça et al. 2012 ; Grabenstein and Taylor 2018 ). This phenomenon represents potential threats to the species involved, especially those at risk of extinction, such as sea turtles (Allendorf et al. 2001 ). The severity of this situation is further underscored by the fact that the Brazilian nesting colony is the largest remaining nesting population in the South Atlantic (Marcovaldi et al. 2007 ). Among sea turtles with a circumglobal distribution, natal homing behavior is common, in which females return to nest in the same region where they were born, while males exhibit this behavior to a lesser extent (Bowen and Karl 2007 ). This behavior leads to genetically structured nesting populations, where individuals are more genetically similar within populations, while foraging populations tend to be more genetically diverse, with individuals originating from multiple nesting populations (Bowen and Karl 2007 ; Arantes et al. 2020a ). Several factors influence a turtle’s foraging area, including hatchling swimming behavior and ocean currents (Blumenthal et al. 2009 ; Putman et al. 2014 ; Proietti et al. 2014 ; Cazabon-Mannette et al. 2016 ; Mansfield et al. 2017 ), resulting in individuals from different nesting areas sharing common foraging grounds (Bowen and Karl 2007 ; Arantes et al. 2020a ). Hawksbill turtles can travel hundreds to thousands of kilometers between their foraging and nesting areas (Marcovaldi and Filippini 1991 ; Bellini et al. 2000 ; Horrocks et al. 2001 ; Monzón-Argüello et al. 2011 ), with records of transoceanic migrations (Vilaça et al. 2013 ; Vargas et al. 2016 ; Arantes et al. 2020a ). In Brazil, the distinction between foraging and nesting areas is reflected in genetic diversity: foraging areas exhibit higher haplotypic diversity, including haplotypes from the Caribbean and Indo-Pacific, which aligns with the species’ extensive migratory ability (Vilaça et al. 2013 ; Arantes et al. 2020a ). Despite this potential for long-distance movement, Brazilian hawksbill turtles generally remain within feeding areas along the country’s coast (Vilaça et al. 2013 ; Proietti et al. 2014 ). Given this scenario, the present study aimed to investigate the origin and haplotypic composition of juvenile individuals of E. imbricata found along the north coast of São Paulo State, Southeastern Brazil — an understudied foraging area for the species and for other foraging regions in southern South America. The research investigated aspects of hybridization, haplotype diversity, potential nesting source populations, migratory patterns using mitochondrial DNA control region (D-loop) analysis. The findings contribute to a deeper understanding of hybridization and migration in hawksbill turtles, providing crucial information for more effective conservation strategies. MATERIALS AND METHODS Specimen collection Skin tissue samples from 25 juvenile Eretmochelys imbricata individuals were collected in the state of São Paulo, southeastern Brazil (18 specimens in Ubatuba, 6 in Ilhabela, and 1 in São Sebastião), a known foraging habitat for this species (Fig. 1 ), from 2011 to 2021 by the Projeto Tamar Foundation (Online Resource 1). The species identification of the specimens was conducted by specialists from the Tamar team, following the standards described by Pritchard and Mortimer ( 1999 ). Tissue samples were obtained using a disposable 6-mm biopsy punch. Samples collected prior 2013 were stored in absolute ethanol, while those collected afterward were stored in sodium chloride. DNA extraction A pre-treatment was performed with washing and hydration of the skin tissue samples using Tris-HCl pH 7.5, 1 M. Subsequently, total DNA extraction was carried out using the Wizard® Genomic DNA Purification Kit (Promega®) (Madison, WI, USA), following the manufacturer’s instructions. The quantification of the obtained genetic material was performed using a NanoDrop Lite spectrophotometer. D-loop sequencing The D-loop region was partially amplified using the primer pair LCM15382 (5'-GCTTAACCCTAAAGCATTGG-3') and H950 (5'-GTCTCGGATTTAGGGGTTTG-3') (Abreu-Grobois et al. 2006). The amplification reactions were performed in a ProFlex PCR System thermocycler, with a total volume of 25 µL, containing 10 ng of template DNA, Tris-KCl (20 mM Tris-HCl pH 8.4 and 50 mM KCl), MgCl₂ (1.5 mM), 2.5 µM of each primer, dNTP (0.1 mM each), and 1 U of Taq DNA polymerase. The reaction conditions were as follows: initial denaturation at 94°C for 5 min, followed by 36 cycles of 94°C for 30 s, 50°C for 30 s, 72°C for 1 min, and a final extension at 72°C for 10 min (Lara-Ruiz et al. 2006 ). The amplicons were purified using polyethyleneglycol (Rosenthal et al. 1993 ) and subsequently sequenced by a private company, using the Big Dye Terminator kit on the AB 3500 Genetic Analyzer. The sequencing reactions were prepared with the forward primer (LCM15382). Data analysis The nucleotide sequences obtained were edited using the BioEdit program (Hall, 1999 ) and aligned by ClustalW (Thompson et al. 1994 ) implemented in the MEGA X software (Kumar et al. 2018 ). The haplotype characterization was conducted using the DnaSP v6 software (Rozas et al. 2017 ). The haplotype nomenclature followed the standardizations of Arantes et al. ( 2020a ). Partial sequences of the mitochondrial DNA control region available in the literature were compiled, related to nesting E. imbricata in the Atlantic, as summarized by Arantes et al. ( 2020a ), with the addition of data from Arantes et al. ( 2020c ), Simões et al. ( 2021 ), and Almeida et al. ( 2023 ) (Online Resource 2). The selection included only sequences associated with hatchlings and nesting females. Furthermore, the sequences were grouped according to megaregions: the Caribbean and the Brazilian Northeast. The same procedure was applied to foraging areas of E. imbricata in the Atlantic, with additional data from Brito et al. ( 2020 ), Arantes et al. ( 2020c ), and Almeida et al. ( 2023 ), including only juvenile individuals (Online Resource 3). Populations with fewer than three individuals were grouped with the nearest population (within 300 km), forming what we refer to as aggregation. The parsimony relationship between nesting haplotypes and the haplotypes from the São Paulo area sampled in this study, as well as other foraging areas in southern South America (Rio de Janeiro (Brazil), Santa Catarina (Brazil), and Uruguay – see locations in Fig. 2 b), was represented in a network using the median-joining algorithm in the PopArt 1.7 software (Bandelt et al. 1999 ). For the hawksbill turtle foraging sequences related to southern South America, nucleotide diversity indices were calculated using the DnaSP v6 software (Rozas et al. 2017 ). Moreover, the level of differentiation between the foraging and nesting aggregations was estimated using the AMOVA and FST values of aggregations pairs based on haplotype frequencies in the Arlequin v3.5 software (Excoffier and Lischer 2010). Finally, a Bayesian mixed-stock analysis (MSA) was conducted using the mixstock package in R version 4.4.1 (Bolker et al. 2007 ; R Core Team 2024 ) to estimate the contribution probabilities of different nesting areas to foraging areas located in southern South America. This analysis used haplotype frequencies from potential nesting areas (Online Resource 2), excluding the areas of Rio de Janeiro and Ceará and Piauí due to the low number of samples, which could introduce noise into the analysis, and incorporated four specific foraging areas: São Paulo (Brazil), Santa Catarina (Brazil), Rio Grande do Sul (Brazil), and Uruguay (Online Resource 3). It also considered the distances between these areas and the nesting sites, following the modified model of Stahelin et al. ( 2022 ). All areas were kept at uniform sizes. The "many-to-many" holistic approach was employed in the model following Phillips et al. (2022), allowing the estimation of contributions from multiple origin sites to multiple mixed destinations. Each model run consisted of 300,000 iterations with a burn-in of 150,000. The Gelman and Rubin reduction factor diagnostic was also performed to test for convergence (< 1.2) (Pella and Masuda 2001 ). The occurrence areas of nesting and foraging haplotypes were mapped using QGIS 3.34 software (QGIS Development Team 2023). RESULTS A final alignment of 25 sequences from all analyzed specimens from São Paulo, with 891 bp. Among these sequences, five distinct haplotypes were identified. One of them corresponded to haplotype CC-A4, detected in two individuals. This haplotype has been previously described in the literature as characteristic of Caretta caretta (Reis et al. 2010 ). It is important to note, however, that the individuals sampled from São Paulo were morphologically identified as Eretmochelys imbricata . This finding suggests that these two individuals are hybrids, possessing mitochondrial DNA of C. caretta while exhibiting the external morphology of E. imbricata. The remaining four haplotypes (EiA01, EiA32, EiA61, and EiA62) were associated with Eretmochelys imbricata , as reported in previous studies (Simões et al. 2021 ; Vilaça et al. 2023 ). Among the haplotypes related to the hawksbill turtle, EiA01 was the most frequent, being found in 18 specimens. The haplotype EiA62 was identified in three samples, while the haplotypes EiA32 and EiA61 showed the lowest frequency, being detected in only one specimen each. The São Paulo region, along with Abrolhos, Fernando de Noronha, and Atol das Rocas (Brazil), were the only other areas where these four haplotypes were identified (Fig. 2 b), all of which were also used as foraging areas. The alignment used for the parsimony analysis among the Atlantic nesting haplotypes, as well as from this study (São Paulo) and haplotypes from other foraging areas in southern South America (São Paulo (Brazil), Santa Catarina (Brazil), Rio Grande do Sul (Brazil), and Uruguay), resulted in a final alignment of 748 bp. The haplotype EiA01 was the most frequent, occurring in both mega-regions (Caribbean and northeastern Brazil) and in foraging sites across southern South America, including our study area. In contrast, the remaining haplotypes identified in our samples and in southern South America (EiA32, EiA61, and EiA62) were exclusive to the Brazilian nesting regions (Figs. 3 and 2 a). The AMOVA for the Atlantic nesting colonies revealed significant genetic differentiation among aggregation, accounting for 30.8% of the total variation. Additionally, a marked differentiation was detected between the megaregions (Caribbean and South America), explaining 35.53% of the variation. However, a large portion of the genetic variation occurs within the aggregation themselves, representing 33.71% of the total variation. These results indicate that haplotype distribution is not random but follows a structured pattern, which is further supported by the high FST (66.3%) value, measuring differentiation among aggregation, and FCT (35.6%), reflecting differentiation between megaregions (Online Resource 4). For the FST test comparing the Atlantic nesting areas with the foraging areas in southern South America, the following results were obtained: genetic differentiation between the São Paulo foraging area and the Caribbean nesting colonies was observed through significant P-values, except with Cuba. For the Brazilian aggregation, the test identified differentiation only with the aggregation of Paraíba, while all other comparisons showed non-significant P-values (Online Resource 6). For the other foraging areas in southern South America, genetic differentiation was observed in relation to the Caribbean nesting areas, except for Barbados (Leeward Coast), Cuba, Sandy Point (U.S. Virgin Islands), and Tobago. Among the Brazilian aggregation, only Rio Grande do Sul showed significant differentiation from the aggregations of Bahia and Sergipe, while all other comparisons had non-significant P-values (Online Resource 6). The mixed-stock analysis indicated that the greatest contribution to the foraging area in São Paulo originated from Tobago, with a predominance of contributions from the southern region of the island, while the northern region showed smaller contributions (Fig. 4 ) (Online Resource 8). Analyzing the foraging areas, the haplotype distributions found in this study (EiA32, EiA61, and EiA62), which are also the only ones found in other foraging areas in southern South America, spanning from the Caribbean to Uruguay, including occurrences in some oceanic islands of the South Atlantic (Fig. 2 b). The alignment of haplotypes related to foraging areas in southern South America revealed three variable sites, a haplotype diversity (h) of 0.3285, and a nucleotide diversity (π) of 0.00047. The AMOVA analysis of the Atlantic foraging colonies revealed genetic differentiation among aggregations, which account for 12.58% of the total variation. In addition, there was marked differentiation between the mega-regions (Caribbean and South America), responsible for 32.5% of the variation. However, most of the genetic variation occurs within the aggregations, representing 54.9% of the total variation. These results indicate that the distribution of haplotypes follows a structured pattern and is not random, as observed in the nesting areas. This is supported by the high FST (45.1%) and FCT (32.5%) values (Online Resource 5). In the foraging colony data, the FST test indicated differentiation between São Paulo and the Caribbean nesting areas, except for Turks & Caicos. The test also showed differentiation between São Paulo and the areas of Cape Verde and Príncipe Island, both located on the African coast. However, no differentiation was observed with Ascension Island, an oceanic island in the middle of the South Atlantic. Regarding the Brazilian foraging aggregations, the test did not identify any differentiation with any of them (Online Resource 7). In relation to the other foraging areas in southern South America, significant genetic differentiation was observed in relation to the Caribbean, except for Mexico (Contoy Island, Cozumel, Banco Chinchorro, and Xcalak), the Cayman Islands, Turks & Caicos, Colombia, and Tobago (Windward Coast). Within the Brazilian aggregations, Rio Grande do Sul exhibited significant differentiation from the aggregations of Fernando de Noronha and Atol das Rocas. Additionally, the aggregation of Santa Catarina showed statistically significant differentiation from the aggregations of Espírito Santo, Rio de Janeiro, Bahia, and Sergipe. For all other comparisons, P-values were not significant. Concerning the aggregations of Cape Verde and Príncipe Island, all southern foraging aggregations showed significant differentiation. In contrast, the analyses did not indicate significant differentiation in relation to Ascension Island, an oceanic island located in the central South Atlantic (Online Resource 7). DISCUSSION This study represents the first genetic investigation of the foraging population of Eretmochelys imbricata from São Paulo (Brazil), contributing to a better understanding of the species' population structure and migratory patterns. The identification of hybrid individuals in the region offers new perspectives on the occurrence of this phenomenon along the Brazilian coast. Furthermore, new haplotypes were identified for the foraging areas in southern South America, expanding knowledge of the species' genetic diversity in the region. The results also suggest that the analyzed individuals likely originate from foraging populations in northeastern Brazil, providing new insights into migratory routes and connectivity between the species' different areas of occurrence. Hybridization The results for haplotype CC-A4 indicate that the mitochondrial DNA, or part of it, is derived from Caretta caretta . However, the external morphology of the individuals is consistent with E. imbricata , suggesting they are hybrids. This phenomenon has been widely reported in Brazil, with hybrids of E. imbricata more frequently associated with C. caretta (Lara-Ruiz et al. 2006 ; Proietti et al. 2014 ; Brito et al. 2020 ; Almeida et al. 2023 ). Notably, haplotype CC-A4, identified in the hybrids in this study, is the most prevalent in the Brazilian reproductive colonies (Reis et al. 2010 ). Additionally, this haplotype has been recorded in E. imbricata x C. caretta hybrids in foraging areas in southern Brazil and Uruguay (Brito et al. 2020 ). The results suggest that the analyzed individuals are hybrids of E. imbricata x C. caretta , indicating crossings between male E. imbricata and female C. caretta . Previous studies (Vilaça et al. 2012 ; Arantes et al. 2020b ) suggest that hybridization in Brazil shows a gender bias, favored by the larger population size of C. caretta and the temporal overlap of reproduction (Relvas et al. 2022 ), in addition to the morphological similarity between the species. Factors such as the absence of reproductive barriers (Seminoff et al. 2003 ), normal meiotic pairing (Seehausen 2004 ), low karyotypic evolution (Machado et al. 2020 ), and the population decline of Eretmochelys imbricata in the 20th century may have facilitated the occurrence of these crosses (Vilaça et al. 2012 ; Soares et al. 2017 ). Hybrids generally exhibit behaviors similar to C. caretta , migrating to temperate climate regions, but they may also show patterns different from the two parental species (Vilaça et al. 2023 ). This plasticity may explain their presence in the southern regions of Brazil, such as Rio Grande do Sul, and in Uruguay (Brito et al. 2020 ), a transition zone between the tropical preferences of E. imbricata and the temperate preferences of C. caretta . However, this does not explain the presence of these hybrids in São Paulo, given the occurrence of both species in this area (Gallo et al. 2006 ). The current and future implications of these hybridizations for species conservation remain unknown (Soares et al. 2017 , 2018 ; Arantes et al. 2020b ). However, the low incidence of hybrid generations beyond F1 is relevant, possibly indicating incompatibility for backcrossing or low fitness in the hybrids (Vilaça et al. 2012 , 2023 ). Therefore, it is crucial to investigate the consequences and prevalence of hybridization in populations with a high frequency of this phenomenon. Origins of the Foraging Aggregation in Southern South America The haplotypes of Eretmochelys imbricata identified in southern South America (São Paulo, Santa Catarina, Rio Grande do Sul, and Uruguay) (EiA01, EiA32, EiA61, and EiA62) are shared with various nesting areas, ranging from the Caribbean to Brazil (Figs. 3 and 4 a). Among them, haplotype EiA01 is the most prevalent in the Atlantic (Arantes et al. 2020a ). This broad distribution complicates the precise identification of the individuals' origin, although the closest nesting aggregation displaying haplotype EiA01 is located in northeastern Brazil. Despite the high dispersal capacity of the turtles, factors such as geographic distance and surface ocean currents often keep individuals near nesting areas, as observed in Brazilian colonies (Vilaça et al. 2013 ; Proietti et al. 2014 ). On the other hand, the other foraging haplotypes identified in southern South America (EiA32, EiA61, and EiA62) are restricted to Brazilian nesting areas, with records in the states of Bahia, Alagoas, and Rio Grande do Norte (Figs. 3 and 4 a). The AMOVA test revealed strong genetic structuring among nesting aggregations, both at the aggregation level and between megaregions (Caribbean and South America) (Online Resource 4). This genetic differentiation suggests that the aggregations maintain a distinct identity, possibly influenced by fidelity to nesting areas (natal homing) (Bowen and Karl 2007 ; Arantes et al. 2020a ). Furthermore, this genetic structuring becomes useful for inferring population origins, as the nesting populations are differentiated from each other. In line with this, the FST test revealed significant genetic differentiation between the Caribbean nesting colonies and the foraging aggregations in southern South America, while lower genetic differentiation was observed with aggregations from northeastern Brazil (Online Resource 6). The mixed-stock analysis, on the other hand, indicated a low contribution from Brazilian nesting areas, highlighting Tobago as the main contributing region, at least for the foraging area in São Paulo, despite only the EiA01 haplotype having been recorded in the country (Fig. 4 ). It is worth noting that Tobago is the closest non-Brazilian region to the São Paulo area, which may influence the results, as the mixed stock model takes geographic proximity into account, given that turtles tend to forage in areas close to their origins (Vilaça et al. 2013 ; Proietti et al. 2014 ). These results suggest a Caribbean influence on the foraging aggregations of southern South America, especially among individuals carrying haplotype EiA01. However, it is important to emphasize that most of the haplotypes identified in the foraging areas are exclusive to Brazilian regions. The results, along with the haplotype distribution (Fig. 2 ), indicate that turtles from the foraging areas of São Paulo and southern South America predominantly originate from Brazilian aggregations, with some influence from the Caribbean. This highlights the importance of the nesting colonies in northeastern Brazil for the species' conservation (Marcovaldi et al. 2007 ). Regarding the foraging areas of southern South America, three of the four haplotypes analyzed (EiA01, EiA32, and EiA62) had been previously identified for this region (Proietti et al. 2014 ; Brito et al. 2020 ). However, the detection of haplotype EiA61 in São Paulo represents a new record (Fig. 2 b). The only other foraging areas that presented the four haplotypes identified in São Paulo were the Abrolhos National Park, Fernando de Noronha, and Atol das Rocas, all located along the Brazilian coast (Fig. 2 b). The presence of these haplotypes in geographically distant regions suggests that similar nesting areas may contribute to the genetic composition of these foraging aggregations. Additionally, these areas, along with Ilha Bela and São Sebastião, sampled in the present study (Fig. 1 ), are located within conservation units (Brasil 1979, 1988; Bahia 1993; São Paulo 1977, 2008), reinforcing the role of these protected zones in maintaining the species' genetic diversity. Ubatuba, another area analyzed in this study, hosts a base of the Projeto Tamar Foundation, which plays a fundamental role in species conservation by providing protection through continuous monitoring, management activities and environmental education. The identification of these haplotypes in multiple protected areas highlights the importance of sea turtle conservation efforts carried out throughout the 21st century in Brazil (Casale et al. 2025 ). These findings suggest that effective conservation measures may play a crucial role in maintaining genetic diversity along the Brazilian coast. Another relevant aspect is the absence of Indo-Pacific haplotypes in the foraging areas of southern South America (Proietti et al. 2014 ; Brito et al. 2020 ; this study), which may be associated with the significant influence of the Benguela and South Equatorial currents (Fig. 2 ), which direct individuals to foraging areas along these currents, such as Cape Verde, Ascension Island, Príncipe Island, and oceanic islands in northeastern Brazil, where Indo-Pacific haplotypes have been recorded (Monzón-Argüello et al. 2010, 2011 ; Vilaça et al. 2012 , 2023 ; Putman et al. 2014 ; Arantes et al. 2020c ). Moreover, the foraging aggregations identified in southern South America exhibit lower haplotype diversity compared to those in northeastern Brazil (Vilaça et al. 2013 ; Proietti et al. 2014 ) and the Caribbean (Blumenthal et al. 2009 ; Proietti et al. 2014 ; Cazabon-Mannette et al. 2016 ; Pérez-Bermúdez et al. 2017 ; Labastida-Estrada et al. 2019 ). This pattern can be explained by the absence of oceanic confluences in the southern region, which limits the migration of individuals from different nesting areas. The AMOVA test revealed strong genetic structuring among the Atlantic foraging aggregations, as well as between the megaregions (Caribbean, South America, and East Atlantic), similar to the results observed for the nesting colonies (Online Resource 5). This indicates that the distribution of haplotypes in foraging areas is not random, as suggested in the literature (Vilaça et al. 2013 ; Proietti et al. 2014 ). However, genetic structuring in foraging areas is less pronounced than in nesting aggregations, as the majority of genetic variation occurs within groups. This pattern is also consistent with the literature, which points to greater genetic diversity in foraging areas compared to nesting areas (Arantes et al. 2020a ). In agreement, data from the foraging colonies, analyzed through the FST test, indicated some genetic differentiation between the foraging areas of southern South America and those in the Caribbean and oceanic islands, while largely showing no differentiation with Brazilian aggregations. These results suggest that the foraging aggregations of southern South America are more genetically connected to aggregations along the Brazilian coast, supporting the idea that nearby colonies share similar source populations (Vilaça et al. 2013 ; Proietti et al. 2014 ). Mansfield et al. ( 2017 ) demonstrated that for Caretta caretta , the migration of hatchlings to Santa Catarina is determined by currents as well as active swimming movements. Thus, it is possible that hatchlings originating from northeastern Brazil use the Brazil Current to reach the southern and southeastern regions of the country. Understanding the connections between populations and their mutual impacts is crucial for the conservation of endangered and highly migratory species, such as the hawksbill turtle. This study emphasizes the need to preserve both the nesting colonies in northeastern Brazil and their foraging areas. Protecting only the hatchlings within political boundaries is not enough if capture in foraging areas continues in other locations (Troëng et al. 2005 ). Furthermore, the data presented contribute to a better understanding of the hybridization and migration of these turtles, helping to develop more effective conservation strategies. Declarations Acknowledgments We thank the Projeto Tamar Foundation for providing the tissue samples used in this study. We also acknowledge the Núcleo de Pesquisas em Limnologia, Ictiologia e Aquicultura (Nupélia) for access to the Molecular Genetics Laboratory infrastructure. Additionally, we are grateful to Gustavo David Stahelin for his assistance with Mixstock analyses and for his valuable feedback on earlier versions of the manuscript. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author Contributions The study was conceptualized by Geovana Jeniffer Ortelã Gonçalves, José Henrique Becker, and Alessandra Valéria de Oliveira. Laboratory work was carried out by Geovana Jeniffer Ortelã Gonçalves. Data analyses were performed by Geovana Jeniffer Ortelã Gonçalves and Bruno Henrique Mioto Stabile. The first draft of the manuscript was written by Geovana Jeniffer Ortelã Gonçalves, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data Availability The datasets generated and/or analyzed during the current study are available within the main text and the supplementary materials. References Abreu-Grobois FA, Horrocks J, Formia A et al. New mtDNA Dloop primers which work for a variety of marine turtle species may increase the resolution of mixed stock analyses. In: Frick M, Panagopoulou A, Rees A, Williams K (eds) Book of Abstracts, Twenty-sixth Annual Symposium on Sea Turtle Biology and Conservation. International Sea Turtle Society, Athens, Greece. p. 179. https://internationalseaturtlesociety.org/wp-content/uploads/2021/02/26-turtle.pdf Allendorf FW, Leary RF, Spruell P, Wenburg JK (2001) The problems with hybrids: setting conservation guidelines. Trends Ecol Evol 16:613–622. https://www.cell.com/ajhg/abstract/S0169-5347(01)02290-X Almeida JP, Marques OK, Mott T, Santos R (2023) Hybridization and genetic characterization of sea turtles in Alagoas, northeastern Brazil. Mar Biol 170. https://doi.org/10.1007/s00227-022-04168-y Arantes LS, Ferreira LC, Driller M et al. (2020b) Genomic evidence of recent hybridization between sea turtles at Abrolhos Archipelago and its association to low reproductive output. Sci Rep 10. https://doi.org/10.1038/s41598-020-69613-8 Arantes LS, Vargas SM, Santos FR (2020a) Global phylogeography of the critically endangered hawksbill turtle (Eretmochelys imbricata). Genet Mol Biol 43. https://doi.org/10.1590/1678-4685-GMB-2019-0264 Arantes LS, Vilaça ST, Mazzoni CJ et al. (2020c) New Genetic Insights About Hybridization and Population Structure of Hawksbill and Loggerhead Turtles From Brazil. J Hered, 111(5): 444–456. https://doi.org/10.1093/jhered/esaa024 Bahia. Decreto nº 2.218, de 14 de junho de 1993. Dispõe sobre a criação da Área de Proteção Ambiental da Ponta da Baleia/Abrolhos, nos Municípios de Alcobaça e Caravelas, e dá outras providências. Palácio do Governo do Estado da Bahia, Bahia. Disponível em: https://www.jusbrasil.com.br/legislacao/83215/decreto-2218-93. Acesso em: 11 mar. 2025 Balladares C, Fermín I, García E, Amilibia JC, Rodríguez D (2023) Preliminary analysis of microplastics from the main continental nesting beach of the hawksbill sea turtle (Eretmochelys imbricata) in Venezuela. Lat Am J Aquat Res 51: 79–87. http://dx.doi.org/10.3856/vol51-issue1-fulltext-2789 Bandelt H, Forster P, Röhl A (1999) Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol 16: 37–48. https://doi.org/10.1093/oxfordjournals.molbev.a026036 Barrios-Garrido H, Espinoza-Rodríguez N, Rojas-Cañizales D et al (2017) Trade of marine turtles along the southwestern coast of Venezuela. Mar Biodivers Rec, 10: 15. https://doi.org/10.1186/s41200-017-0115-0 Bass AL, Good DA, Bjorndal KA, Richardson JI, Hillis Z-M, Horrocks JA e BW Bowen (1996) Testing models of female reproductive migratory behaviour and population structure in the Caribbean hawksbill turtle, Eretmochelys imbricata, with mtDNA sequences. Mol Ecol 5:321–328. https://doi.org/10.1046/j.1365-294X.1996.00073.x Bellini C, Sanches TM, Formia A (2000) Hawksbill turtle tagged in Brazil captured in Gabon, Africa. Marine Turtle Newsletter 87, 11–12. http://www.seaturtle.org/mtn/archives/mtn87/mtn87p11.shtml Blumenthal JM, Abreu-Grobois FA, Austin TJ et al. (2009) Turtle groups or turtle soup: dispersal patterns of hawksbill turtles in the Caribbean. Mol Ecol 18:4841–4853. https://doi.org/10.1111/j.1365-294X.2009.04403.x Bomfim AC, Farias DS, Silva FJ et al (2021). Long-term monitoring of marine turtle nests in northeastern Brazil. Biota Neotrop, 21(3). https://doi.org/10.1590/1676-0611-BN-2020-1159 Bolker BM, Okuyama T, Bjorndal KA, Bolten AB (2007). Incorporating multiple mixed stocks in mixed stock analysis: 'many-to-many' analyses. Mol Ecol 16: 685–695. https://doi.org/10.1111/j.1365-294X.2006.03161.x Bowen BW, Karl SA (2007) Population genetics and phylogeography of sea turtles. Mol Ecol 16:4886-4907. https://doi.org/10.1111/j.1365-294X.2007.03542.x Brasil. Decreto nº 83.549, de 5 de junho de 1979. Dispõe sobre a criação da Reserva Biológica do Atol das Rocas e dá outras providências. Diário Oficial da União, Brasília, DF. Disponível em: https://legis.senado.leg.br/norma/506189. Acesso em: 11 mar. 2025. Brasil. Decreto nº 96.693, de 14 de setembro de 1988. Dispõe sobre a criação do Parque Nacional Marinho de Fernando de Noronha e dá outras providências. Diário Oficial da União, Brasília, DF. Disponível em: https://www.planalto.gov.br/ccivil_03/decreto/1980-1989/d96693.htm. Acesso em: 11 mar. 2025. Brasil - Ministério Do Meio Ambiente. Lista Nacional de Espécies Ameaçadas de Extinção. Brasília, 2022. Disponível em: . Acesso em: 20 de outubro de 2024. Brito C, Vilaça ST, Lacerda AL et al. (2020) Combined use of mitochondrial and nuclear genetic markers further reveal immature marine turtle hybrids along the South Western Atlantic. Genet Mol Biol 43. https://doi.org/10.1590/1678-4685-GMB-2019-0098 Browne DC, Horrocks JÁ, Abreu-Grobois FA (2010) Population subdivision in hawksbill turtles nesting on Barbados, West Indies, determined from mitochondrial DNA control region sequences. Conserv Genet 11: 1541–1546. https://doi.org/10.1007/s10592-009-9883-3 Carreras C, Godley BJ, León YM et al. (2013) Contextualising the last survivors: Population structure of marine turtles in the Dominican Republic. PLoS One 8. https://doi.org/10.1371/journal.pone.0066037 Casale P, Arapis T, Ceriani SA. et al. (2025) Monitoring the conservation status of sea turtle nesting sites: expert knowledge and quantitative indicators. J Coast Conserv 29, 31. https://doi.org/10.1007/s11852-025-01117-x Cazabon-Mannette M, Browne D, Austin N, Hailey A and Horrocks J (2016) Genetic structure of the hawksbill turtle rookery and foraging aggregation in Tobago, West Indies. J Exp Mar Biol Ecol 485:94–101. https://doi.org/10.1016/j.jembe.2016.09.002 Excoffier L, Heidi ELL (2010) Arlequin Suite Ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour 10:564-567. https://doi.org/10.1111/j.1755-0998.2010.02847.x Fish MR, Coté IM, Gill JA, Jones AP, Renshoff S, Watkinson AR (2005) Predicting the impact of sea-level rise on Caribbean Sea turtle nesting habitat. Conserv Biol 19: 482–491. https://doi.org/10.1111/j.1523-1739.2005.00146.x Gallo BM, Macedo S, Giffoni BB, Becker JH, Barata PCR (2006) Sea Turtle Conservation in Ubatuba, Southeastern Brazil, a Feeding Area with Incidental Capture in Coastal Fisheries. Chelonian Conserv Biol 5 (1): 93–101. https://doi.org/10.2744/1071-8443(2006)5[93:STCIUS]2.0.CO;2 Gorham JC, Clark D, Bresette MJ et al. (2014) Characterization of a subtropical hawksbill sea turtle (Eretmochelys imbricata) assemblage utilizing shallow water natural and artificial habitats in the Florida Keys. PLoS One 9. https://doi.org/10.1371/journal.pone.0114171 Grabenstein KC, Taylor SA (2018) Breaking Barriers: Causes, Consequences, and Experimental Utility of Human-Mediated Hybridization. Trends Ecol Evol 33:198–212. https://doi.org/10.1016/j.tree.2017.12.008 1 Hall TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser, v. 41, p. 95-98. Hill JE, King CM, Stewart KR, Paladino FV, Dutton PH (2018) Genetic differentiation of Hawksbill Turtle rookeries on St. Croix, US Virgin Islands. Chelonian Conserv Biol 17:303–308. https://doi.org/10.2744/CCB-1293.1 Horrocks JA, Vermeer LA, Kreuger B, Coyne M, Schroeder B, Balazs G (2001) Migration routes and destination characteristics of post-nesting hawksbill turtles satellite-tracked from Barbados, West Indies. Chelonian Conserv Biol 4:107–114. Kumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) MEGA X: Molecular Evolutionary Genetics Analysis across computing platforms. Mol Biol Evol 35:1547–1549. https://doi.org/10.1093/molbev/msy096 Labastida-Estrada E, Machkour-M’Rabet S, Díaz-Jaimes P, Cedeño-Vázquez JR and Hénaut Y (2019) Genetic structure, origin, and connectivity between nesting and foraging areas of hawksbill turtles of the Yucatan Peninsula: A study for conservation and management. Aqua Conserv: Mar Freshw Ecosyst 29:211–222. https://doi.org/10.1002/aqc.2999 Lara-Ruiz P, Lopez GG, Santos FR, Soares LS (2006) Extensive hybridization in hawksbill turtles (Eretmochelys imbricata) nesting in Brazil revealed by mtDNA analyses. Conserv Genet 7: 773–781. https://doi.org/10.1007/s10592-005-9102-9 LeRoux RA, Dutton PH, Abreu-Grobois F et al. (2012) Re-examination of Population Structure and Phylogeography of Hawksbill Turtles in the Wider Caribbean Using Longer mtDNA Sequences. J Hered 103:806–820. https://doi.org/10.1093/jhered/ess055 Levasseur KE, Stapleton SP, Fuller MC, Quattro JM (2019) Exceptionally high natal homing precision in hawksbill sea turtles to insular rookeries of the Caribbean. Mar Ecol Prog Ser 620:155-171. https://doi.org/10.3354/meps12957 Machado CR, Domit C, Pucci MB et al. (2020) Heterochromatin and microsatellites detection in karyotypes of four sea turtle species: Interspecific chromosomal differences. Genet Mol Biol 43:1–9. https://doi.org/10.1590/1678-4685-GMB-2020-0213 Mansfield KL, Mendilaharsu ML, Putman NF et al. (2017) First satellite tracks of South Atlantic sea turtle ‘lost years’: seasonal variation in trans-equatorial movement. Proc. R. Soc. B 284. https://doi.org/10.1098/rspb.2017.1730 Marcovaldi MA, Filippini A (1991) Trans-Atlantic movement by a juvenile hawksbill turtle. Marine Turtle Newsletter 52:3. http://www.seaturtle.org/mtn/archives/mtn52/mtn52p3.shtml Marcovaldi MA, Lopez GG, Soares LS, Santos AJ, Bellini C, Barata PC (2007) Fifteen years of hawksbill (Eretmochelys imbricata) sea turtle nesting in northern Brazil. Chelonian Conserv Biol 6: 223–228. https://doi.org/10.2744/1071-8443(2007)6[223:FYOHST]2.0.CO;2 Marcovaldi MA, Vieitas CF, Godfrey MH (1999) Nesting and conservation of hawksbill turtles (Eretmochelys imbricata) in northern Bahia, Brazil. Chelonian Conserv Biol 3: 301–307. Mau A, Rodríguez PS, Picknell A et al. (2024) In-nest mortality and pathology of hawksbill sea turtle (Eretmochelys imbricata) embryos and hatchlings in St. Kitts and Nevis. J Comp Pathol, 209: 13-21. https://doi.org/10.1016/j.jcpa.2024.01.004 Maurer AS, Seminoff JA, Layman CA, Stapleton SP, Godfrey MH, Reiskind MO (2021) Population Viability of Sea Turtles in the Context of Global Warming. BioScience 71: 790–804. https://doi.org/10.1093/biosci/biab028 Miller EA, McClenachan L, Uni Y, Phocas G, Hagemann ME, Van Houtan KS (2019),The historical development of complex global trafficking networks for marine wildlife. Sci Adv, 5,eaav5948. https://doi.org/10.1126/sciadv.aav5948 Montero N, Marcovaldi MA, Lopez–Mendilaharsu M, Santos AS, Santos AJB, Fuentes MM (2018) Warmer and wetter conditions will reduce offspring production of hawksbill turtles in Brazil under climate change. PLOS ONE: 13. https://doi.org/10.1371/journal.pone.0204188 Monzón-Argüello C, Loureiro NS, Delgado C et al. (2011) Príncipe island hawksbills: genetic isolation of an eastern Atlantic stock. J Exp Mar Biol Ecol 407: 345–354. https://doi.org/10.1016/j.jembe.2011.07.017 Mortimer JA, Donnelly M (2008) IUCN SSC Marine Turtle Specialist Group. Eretmochelys imbricata. The IUCN Red List of Threatened Species 2008: e.T8005A12881238. https://dx.doi.org/10.2305/IUCN.UK.2008.RLTS.T8005A12881238.en. Pérez-Bermúdez E, Urquiola AR, Rebordinos-González L, Espinosa-López G, Lee-González I, Petric BLJ (2017) A new approach to mixed stock analysis that informs on the management and conservation of hawksbill in the wider Caribbean: the case of the legal fishery in Jardines del Rey, Cuba. Int J Mar Sci 7: 316–343. https://aquapublisher.com/index.php/ijms/article/view/3191 Pella J, Masuda M. (2001). Bayesian methods for analysis of stockmixtures from genetic characters. Fish bull, 99, 151–167. Pritchard PC, Mortimer JA (1999) Taxonomy, external morphology, and species identification. In: Eckert KL, Bjorndal KA, Abreu-Grobois FA, Donnelly M (eds) Research and Management Techniques for the Conservation of Sea Turtles. Washington: IUCN/SSC. https://widecast.org/Resources/Docs/Pritchard_and_Mortimer_1999_Sea_Turtle_Taxonomy.pdf Proietti MC, Reisser J, Marins LF et al. (2014) Genetic structure and natal origins of immature Hawksbill Turtles (Eretmochelys imbricata) in Brazilian waters. PLoS One 9. https://doi.org/10.1371/journal.pone.0088746 Putman NF, Abreu-Grobois F, Broderick A et al. (2014) Numerical dispersal simulations and genetics help explain the origin of hawksbill sea turtles in Ascension Island. J Exp Mar Biol Ecol 450:98–108. https://doi.org/10.1016/j.jembe.2013.10.026 QGIS Development Team. QGIS Geographic Information System. Versão 3.34.1 Prizren. 2023. Disponível em: https://download.qgis.org/downloads/. Acesso em: fevereiro de 2025. R Core Team (2024). R: A Language and Environment for Statistical Computing_. R Foundation for Statistical Computing, Vienna, Austria. . Reis EC, Soares LS, Vargas SM et al. (2010) Genetic composition, population structure and phylogeography of the loggerhead sea turtle: colonization hypothesis for the Brazilian rookeries. Conserv Genet 11: 1467–1477. https://doi.org/10.1007/s10592-009-9975-0 Relvas CI, Ribeiro MV, Ferreira ES, Miranda MR, Schiavetti A (2022) Reproductive and ecological similarity between Caretta caretta (Linnaeus, 1758) and Eretmochelys imbricata (Linnaeus, 1766) in southern Bahia (Brazil). Braz J Biol 82. https://doi.org/10.1590/1519-6984.261269 Richardson PB, Bruford M, Calosso M et al. (2009) Marine turtles in the Turks and Caicos Islands: Remnant rookeries, regionally significant foraging stocks, and a major turtle fishery. Chelonian Conserv Biol 8:192–207. https://doi.org/10.2744/CCB-0871.1 Rosenthal A, Coutelle O, Craxton M (1993) Large-scale production of DNA sequencing templates by microtire format PCR. Nucleic Acid Research 21:173–174. https://doi.org/10.1093/nar/21.1.173 Rozas J, Ferrer-Mata A, Sánchez-DelBarrio J et al. (2017) DnaSP 6: DNA Sequence Polymorphism Analysis of Large Data Sets. Mol Biol Evol 34: 3299–3302. https://doi.org/10.1093/molbev/msx248 São Paulo. Decreto nº 53.525, de 8 de novembro de 2008. Dispõe sobre a criação da Área de Proteção Ambiental Marinha do Litoral Norte e a Área de Relevante Interesse Ecológico de São Sebastião, e dá providências correlatas. Palácio dos Bandeirantes, São Paulo. Disponível em: https://www.al.sp.gov.br/repositorio/legislacao/decreto/2008/decreto-53525-08.10.2008.html. Acesso em: 11 mar. 2025 São Paulo. Decreto nº 9.414, de 20 de janeiro de 1977. Dispõe sobre a criação do Parque Estadual de Ilhabela e dá providências correlatas. Palácio dos Bandeirantes, São Paulo. Disponível em: https://www.al.sp.gov.br/norma/74329. Acesso em: 11 mar. 2025 Seehausen O (2004) Hybridization and adaptive radiation. Trends Ecol Evol 19: 198–207. https://doi.org/10.1016/j.tree.2004.01.003 Seminoff JA, Karl SA, Schwartz T, Resendiz A (2003) Hybridization of the green turtle (Chelonia mydas) and hawksbill turtle (Eretmochelys imbricata) in the Pacific ocean: indication of an absence of gender bias in the directionality of crosses. Bull Mar Sci 73: 643–652. https://www.ingentaconnect.com/content/umrsmas/bullmar/2003/00000073/00000003/art00008# Simões T, Santos E, Santos A et al. (2021) Low Diversity and Strong Genetic Structure Between Feeding and Nesting Areas in Brazil for the Critically Endangered Hawksbill Sea Turtle. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2021.704838 Simões TN, Silva AC, Moura CC (2017) Influence of artificial lights on the orientation of hatchlings of Eretmochelys imbricata in Pernambuco, Brazil. Zoologia (34). https://doi.org/10.3897/zoologia.34.e13727 Soares LS, Bjorndal K, Bolten A et al. (2018) Effects of hybridization on sea turtle fitness. Conserv Genet 19: 1311–1322. https://doi.org/10.1007/s10592-018-1101-8 Soares LS, Bolten AB, Wayne ML et al. (2017) Comparison of reproductive output of hybrid sea turtles and parental species. Mar Biol 164:9. https://doi.org/10.1007/s00227-016-3035-3 Stahelin GD, Hoffman EA, Quintana-Ascencio PF, Reusche M, Mansfield KL (2022) Incorporating distance metrics and temporal trends to refine mixed stock analysis. Sci Rep 12, 20569. https://doi.org/10.1038/s41598-022-24279-2 Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gappenalties and weight matrix choice. Nucleic Acids Res 22: 4673–4680. https://doi.org/10.1093/nar/22.22.4673 Troëng S, Dutton PH, Evans D (2005) Migration of hawksbill turtles Eretmochelys imbricata from Tortuguero, Costa Rica. Ecography 28:394–402. https://doi.org/10.1111/j.0906-7590.2005.04110.x Trujillo-Arias N, Amorocho DF, López-Álvarez D and Mejía-Ladino LM (2014) Phylogeographic relations of some feeding and nesting of hawksbill turtle rookeries (Eretmochelys imbricata) in the Caribbean and Pacific of Colombia. Bol Invest Mar Cost 43:59–182. http://www.scielo.org.co/scielo.php?pid=S0122-97612014000100008&script=sci_abstract&tlng=pt Vargas SM, Jensen M, Ho S et al. (2016) Phylogeography, Genetic Diversity, and Management Units of Hawksbill Turtles in the Indo-Pacific. J Hered 107: 199–213. https://doi.org/10.1093/jhered/esv091 Velez-Zuazo X, Ramos WD, Van Dam RP, Diez CE, Abreu-Grobois A, McMillan WO (2008) Dispersal, recruitment and migratory behaviour in a hawksbill sea turtle aggregation. Mol Ecol 17:839–853. https://doi.org/10.1111/j.1365-294X.2007.03635.x Vilaça ST, Lara-Ruiz P, Marcovaldi MA, Soares LS, Santos FR (2013) Population origin and historical demography in hawksbill (Eretmochelys imbricata) feeding and nesting aggregates from Brazil. J Exp Mar Biol Ecol 446:334–34. https://doi.org/10.1016/j.jembe.2013.06.004 Vilaça ST, Maroso F, Lara P et al. (2023) Evidence of backcross inviability and mitochondrial DNA paternal leakage in sea turtle hybrids. Mol Ecol 32: 628–643. https://doi.org/10.1111/mec.16773 Vilaça ST, Vargas S, Lara-Ruiz P et al. (2012) Nuclear markers reveal a complex introgression pattern among marine turtle species on the Brazilian coast. Mol Ecol 21: 4300–4312. https://doi.org/10.1111/j.1365-294X.2012.05685.x Wood LD, Hardy R, Meylan PA, Meylan AB (2013) Characterization of a hawksbill turtle (Eretmochelys imbricata) foraging aggregation in a high-latitude reef community in southeastern Florida, USA.Herpetol Conserv Biol 8:258–275. Supplementary Files SupplementaryMaterial.xlsx Cite Share Download PDF Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Marine Biology → Version 1 posted Editorial decision: Revise and Resubmit 21 Nov, 2025 Reviewers agreed at journal 01 Oct, 2025 Reviewers invited by journal 30 Sep, 2025 Editor assigned by journal 27 Sep, 2025 First submitted to journal 26 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7722562","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":522994851,"identity":"64633792-f4a0-42a4-8ce4-6455b7487ba6","order_by":0,"name":"Geovana Gonçalves","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYJADxgMMFUCKHchqIEoDGwPDAYYzDAw8zCRpYWwjQou8e/MxiZ877OTM5zcfOPBznk3ifmbmgw9nMNjJ6eLQZ3jmWJpk75lkY5ljbAkHe7elJfYwsyUbbmBINjY7gEPLjBxjA9425sQZbDwGB3i3HQZq4TGTfMBwIHEbLi3z3xgb/m2rB2rh/3Dw7xwitMhL8Bg+5m07DLKF4TBvA1TLBjxaDHjSEh/Lth03lmBLMzgscyzNuOcw0C8zDHD7Rb798IGDb9uq5SSYDz98+KbGRra9vfngw54KOzlcWgxwiWMXBtvSgFtuFIyCUTAKRgEEAACs71xx1VnSxAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-2236-4342","institution":"Universidade Estadual de Maringá","correspondingAuthor":true,"prefix":"","firstName":"Geovana","middleName":"","lastName":"Gonçalves","suffix":""},{"id":522994852,"identity":"462239f0-b83f-416e-a05e-2d7d1f69463d","order_by":1,"name":"Bruno Henrique Mioto Stabile","email":"","orcid":"","institution":"Programa de Pós-Graduação em Ecologia de Ambientes Aquáticos Continentais, Departamento de Biologia, Centro de Ciências Biológicas, Universidade Estadual de Maringá","correspondingAuthor":false,"prefix":"","firstName":"Bruno","middleName":"Henrique Mioto","lastName":"Stabile","suffix":""},{"id":522994853,"identity":"0111ed72-3b74-40cd-8c5e-00d83e62efab","order_by":2,"name":"José Henrique Becker","email":"","orcid":"","institution":"Fundação Projeto Tamar","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"Henrique","lastName":"Becker","suffix":""},{"id":522994854,"identity":"64cfb2d5-3633-4ff6-9111-6fccc5915f5a","order_by":3,"name":"Alessandra Valéria de Oliveira","email":"","orcid":"","institution":"Departamento de Biotecnologia, Genética e Biologia Molecular, Núcleo de Pesquisas em Limnologia, Ictiologia e Aquicultura (Nupélia), Centro de Ciências Biológicas, Universidade Estadual de Maringá","correspondingAuthor":false,"prefix":"","firstName":"Alessandra","middleName":"Valéria","lastName":"de Oliveira","suffix":""}],"badges":[],"createdAt":"2025-09-26 14:06:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7722562/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7722562/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00227-026-04825-6","type":"published","date":"2026-04-29T15:57:07+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":93441078,"identity":"e264ff4e-79fe-4e62-b95f-46f695eb5e3f","added_by":"auto","created_at":"2025-10-13 23:11:07","extension":"jpg","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3202549,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/244f34f709e81e61089ec626.jpg"},{"id":93440487,"identity":"011c9b4f-9dbe-4c39-ae72-4e55f2d7676d","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"tiff","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":848078,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.4.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/8dbc41272828c7c33c22d2a8.tiff"},{"id":93440493,"identity":"f32c6378-ea67-4a65-be20-77eecc722b75","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"tiff","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4118558,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/ce5b49928383e90391026e03.tiff"},{"id":93440496,"identity":"67821735-4dab-4568-9332-e0683b101148","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"tiff","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3485686,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2a.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/2226e0564afe9ab6ec721046.tiff"},{"id":93440574,"identity":"42a9891a-457d-4b29-b2ad-2e3e3a1b7ff6","added_by":"auto","created_at":"2025-10-13 23:03:07","extension":"tiff","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3485686,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2b.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/3a18a9600ee8e732400b2545.tiff"},{"id":93440490,"identity":"18270aad-8cc1-4bd5-af22-d175defb3c20","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":7638,"visible":true,"origin":"","legend":"","description":"","filename":"mabiMABID2500517.xml","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/553ea91c8b316de7e51c9eff.xml"},{"id":93440494,"identity":"503374fd-a38a-4388-baff-3712c9d3ee17","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"xml","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1175,"visible":true,"origin":"","legend":"","description":"","filename":"MABID250051714394.go.xml","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/ba7377842faaae89a92bcddb.xml"},{"id":93440573,"identity":"0a84b117-4f62-4548-814a-83f8afb65311","added_by":"auto","created_at":"2025-10-13 23:03:07","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":782,"visible":true,"origin":"","legend":"","description":"","filename":"MABID2500517Import.xml","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/e57be1703d994f1056f7aeef.xml"},{"id":93440509,"identity":"8b5c555b-b7a4-4eda-a891-4ad0eee5d817","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"xml","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":158692,"visible":true,"origin":"","legend":"","description":"","filename":"MABID25005170enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/a6b95b58d96e768e283b8b32.xml"},{"id":93440515,"identity":"6c7eafcd-a397-40da-873f-df69bfb05b48","added_by":"auto","created_at":"2025-10-13 22:55:08","extension":"jpg","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3202549,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/2d3a75fa3e2d316518a322f8.jpg"},{"id":93441383,"identity":"c18c432b-5d3f-427b-9606-5a04eb9bc4b3","added_by":"auto","created_at":"2025-10-13 23:27:07","extension":"tiff","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":848078,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.4.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/8862c5e6a2c1b9032bb95a59.tiff"},{"id":93441140,"identity":"8bbc002b-3cf5-45c8-942b-272753e85e7c","added_by":"auto","created_at":"2025-10-13 23:19:07","extension":"tiff","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4118558,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/8558c15cab333dddd59ab6b4.tiff"},{"id":93441087,"identity":"0b8e60c9-eb17-42ed-951c-3e24c5b0e068","added_by":"auto","created_at":"2025-10-13 23:11:08","extension":"tiff","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3485686,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2a.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/5d6fc46fac7a55690237e956.tiff"},{"id":93440575,"identity":"a051604f-8b1b-4911-ab28-ac5d412136d7","added_by":"auto","created_at":"2025-10-13 23:03:07","extension":"tiff","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3485686,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2b.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/f60a0e9347731bcd8773d1bc.tiff"},{"id":93597490,"identity":"82763deb-370d-43b5-a6ec-0c5aa15f968a","added_by":"auto","created_at":"2025-10-15 14:15:08","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":111045,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/2ce8188d72456cc357980c9a.png"},{"id":93597464,"identity":"65b6dc45-74cd-45e6-948a-163d5c3c4800","added_by":"auto","created_at":"2025-10-15 14:07:59","extension":"jpeg","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1000283,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/4e4d012be13d80b857c85d66.jpeg"},{"id":93441381,"identity":"39c60b86-f728-4f1a-86e3-99b861adea3d","added_by":"auto","created_at":"2025-10-13 23:27:07","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":162827,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/44ee74e5f70316528a8766ae.png"},{"id":93440506,"identity":"71e74011-4b44-4e34-8ad6-3076d0839e55","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"jpeg","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":110584,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/30505acb8b812112a86d8c31.jpeg"},{"id":93440499,"identity":"2f68f55c-5595-4769-b594-820d90e09664","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":472393,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/43e60524cd5f28f4407fe080.png"},{"id":93440581,"identity":"e89dd2ee-aa2f-42ed-b6bd-10d6e21ac9a2","added_by":"auto","created_at":"2025-10-13 23:03:07","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":203920,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/678a903c198cfa878d0a4514.png"},{"id":93440495,"identity":"cb8c54ee-058d-4d89-b4c9-3c70949bf284","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":32872,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/c54eaaeee5e581f0d546c69a.png"},{"id":93441079,"identity":"7e83a9ab-9972-4b4d-a508-5de542df790a","added_by":"auto","created_at":"2025-10-13 23:11:07","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":58012,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2a.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/df9751db75acc0f140422e0a.png"},{"id":93440517,"identity":"36891e19-20cd-499d-a14e-034fa91720b3","added_by":"auto","created_at":"2025-10-13 22:55:08","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":60464,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2b.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/51c1529eb5e0975c3d0ac223.png"},{"id":93440511,"identity":"7aeba30e-aa73-4885-a555-2f92d78c8503","added_by":"auto","created_at":"2025-10-13 22:55:08","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":28931,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/f9a26b709d44931f0e7d77ea.png"},{"id":93440510,"identity":"bd632d00-9535-4acd-a5ce-7bf0c353364e","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":251358,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/ec6c6173c589edf274ff330f.png"},{"id":93440576,"identity":"d93b0407-9692-42b7-b246-30864672c48e","added_by":"auto","created_at":"2025-10-13 23:03:07","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":41772,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/caf40819d338b1a9a692f19e.png"},{"id":93440586,"identity":"24af243b-3b5c-4701-af5f-a5d7b51695b2","added_by":"auto","created_at":"2025-10-13 23:03:08","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":64327,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/8be2d1f19cb71e37b183d021.png"},{"id":93441084,"identity":"dd6a7904-1619-4522-a18f-fcb8ac0af94a","added_by":"auto","created_at":"2025-10-13 23:11:07","extension":"xml","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":156036,"visible":true,"origin":"","legend":"","description":"","filename":"MABID25005170structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/dad6d869daec427f20fe1e4b.xml"},{"id":93440516,"identity":"dcc435e5-b14d-4341-add9-7926e54f103c","added_by":"auto","created_at":"2025-10-13 22:55:08","extension":"html","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":166506,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/83739e2dcbe8620cf7e54384.html"},{"id":93440484,"identity":"c1a33df3-0652-4181-ad4b-7b1605d6df06","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":260148,"visible":true,"origin":"","legend":"\u003cp\u003eSampling areas for \u003cem\u003eE. imbricata\u003c/em\u003e individuals used in this study\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/5ffba7cef17ae61616f4566a.png"},{"id":93440485,"identity":"44641123-3975-47e3-9aee-05a7543fc541","added_by":"auto","created_at":"2025-10-13 22:55:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1360044,"visible":true,"origin":"","legend":"\u003cp\u003eOccurrence regions for nesting areas (a) and foraging areas (b) for haplotypes EiA01, EiA32, EiA61, and EiA62. The regions are identified as: Caribbean: AN = Antigua and Barbuda, BI = United States Virgin Islands (Buck Island and Sandy Point), BW = Barbados (Windward and Leeward coast), CA = Cayman Islands, CO = Colombia, CU = Cuba, GU = Guadeloupe, MX = Mexico, PB = United States (Palm Beach County and Florida Key West), PR = Puerto Rico, SI = Dominican Republic (Saona Island and Jaragua National Park), TC = Turks \u0026amp; Caicos, TS = Tobago (South-West North-East coast); TL = Tobago (Leeward and Windward coast); South America: AB = Abrolhos Park, AL = Alagoas, BS = Bahia and Sergipe, CE = Ceará, CP = Ceará and Piauí, ER = Espírito Santo and Rio de Janeiro, NA = Fernando de Noronha and Atol das Rocas, PA = Paraíba, PE = Pernambuco, RJ = Rio de Janeiro, RN = Rio Grande do Norte, RS = Rio Grande do Sul, SC = Santa Catarina, SP = São Paulo, UR = Uruguai; Others: AS = Ascension Island, SA = São Pedro and São Paulo Archipelago. The black arrows indicate the flow of the main currents in the Atlantic Ocean: SE = South Equatorial Current, BR = Brazil Current, SA = South Atlantic Current (displaced to the North for illustrative purposes), BG = Benguela Current, NB = North Brazil Current, GU = Guiana Current, CB = Caribbean Current, EC = Equatorial Counter Current, NE = North Equatorial Current, GS = Gulf Stream, NA = North Atlantic Current, CN = Canary Current.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/362a9f3b4b8adebfba8406fe.png"},{"id":93440570,"identity":"a36dd4c1-7541-44a7-b17f-038b65f161ac","added_by":"auto","created_at":"2025-10-13 23:03:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":9272779,"visible":true,"origin":"","legend":"\u003cp\u003eMedian-joining haplotype network constructed based on the control region of the mtDNA of \u003cem\u003eE. imbricata\u003c/em\u003e, from Atlantic nesting colonies and individuals sampled in this study in São Paulo (foraging individuals), as well as for other foraging regions in southern South America (Santa Catarina, Rio Grande do Sul, and Uruguai). Small black circles represent median vectors.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/ea8d4772d43ad44b90044e83.png"},{"id":93440571,"identity":"f208445f-64b6-4fe3-b2f8-8478e6b96aca","added_by":"auto","created_at":"2025-10-13 23:03:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4483205,"visible":true,"origin":"","legend":"\u003cp\u003eMixed-stock analysis for the foraging areas located in Rio Grande do Sul, Santa Catarina, São Paulo, and Uruguay, considering contributions from Atlantic nesting areas. Points are mean estimates and whiskers indicate 95% credibility intervals. The abbreviations used correspond to those defined in Fig. 2.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/1c8a3ad011b85034af45a0b0.png"},{"id":108437567,"identity":"4282bcff-f364-4be1-b83f-32053f3fa6ce","added_by":"auto","created_at":"2026-05-04 15:59:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":16640050,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/6dcf11a3-8c9d-43d8-b3a8-6ea38c84051c.pdf"},{"id":93441136,"identity":"a7bc1384-e732-4900-bff3-b02f2c779cce","added_by":"auto","created_at":"2025-10-13 23:19:07","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":617873,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7722562/v1/a7167f10383a7a4a56fdf1e1.xlsx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eHybridization Analysis and Haplotypic Diversity in Eretmochelys Imbricata in Southeastern Brazil\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe hawksbill turtle, \u003cem\u003eEretmochelys imbricata\u003c/em\u003e (Linnaeus 1766), is a species with a circumglobal distribution in tropical and subtropical waters, including the Brazilian coast (IUCN 2014). Currently listed as critically endangered on the IUCN Red List (Mortimer and Donnelly \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and as endangered on Brazil’s List of Threatened Species (Brasil 2022), the hawksbill turtle was once on the verge of extinction in Brazil (Marcovaldi et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). The species continues to face numerous threats, including the collection and commercialization of eggs, meat, and carapaces, as well as habitat destruction from coastal development, pollution, and fisheries bycatch (Mortimer and Donnelly \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Simões et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Barrios-Garrido et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Miller et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bomfim et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Balladares et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, it is vulnerable to the impacts of ongoing climate changes, such as the nesting sites loss due to rising sea levels, skewed sex ratios from temperature-dependent sex determination, and alterations in food availability (Fish et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Montero et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Maurer et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mau et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe species is also affected by an exceptionally high rate of hybridization in Brazil, where the highest recorded global levels have been observed for sea turtles. Lara-Ruiz et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) identified that 42% of nesting hawksbill turtle females in Bahia were hybrids with the loggerhead turtle (\u003cem\u003eCaretta caretta\u003c/em\u003e (Linnaeus 1758)), while 1.6% were hybrids with the olive ridley turtle (\u003cem\u003eLepidochelys olivacea\u003c/em\u003e (Eschscholtz 1829)). Although hybridization and genetic introgression can be natural evolutionary events, they may also be triggered by anthropogenic factors (Vilaça et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Grabenstein and Taylor \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This phenomenon represents potential threats to the species involved, especially those at risk of extinction, such as sea turtles (Allendorf et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The severity of this situation is further underscored by the fact that the Brazilian nesting colony is the largest remaining nesting population in the South Atlantic (Marcovaldi et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmong sea turtles with a circumglobal distribution, natal homing behavior is common, in which females return to nest in the same region where they were born, while males exhibit this behavior to a lesser extent (Bowen and Karl \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This behavior leads to genetically structured nesting populations, where individuals are more genetically similar within populations, while foraging populations tend to be more genetically diverse, with individuals originating from multiple nesting populations (Bowen and Karl \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Arantes et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Several factors influence a turtle’s foraging area, including hatchling swimming behavior and ocean currents (Blumenthal et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Putman et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Proietti et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Cazabon-Mannette et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Mansfield et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), resulting in individuals from different nesting areas sharing common foraging grounds (Bowen and Karl \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Arantes et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHawksbill turtles can travel hundreds to thousands of kilometers between their foraging and nesting areas (Marcovaldi and Filippini \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Bellini et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Horrocks et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Monzón-Argüello et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), with records of transoceanic migrations (Vilaça et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Vargas et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Arantes et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). In Brazil, the distinction between foraging and nesting areas is reflected in genetic diversity: foraging areas exhibit higher haplotypic diversity, including haplotypes from the Caribbean and Indo-Pacific, which aligns with the species’ extensive migratory ability (Vilaça et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Arantes et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Despite this potential for long-distance movement, Brazilian hawksbill turtles generally remain within feeding areas along the country’s coast (Vilaça et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Proietti et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGiven this scenario, the present study aimed to investigate the origin and haplotypic composition of juvenile individuals of \u003cem\u003eE. imbricata\u003c/em\u003e found along the north coast of São Paulo State, Southeastern Brazil — an understudied foraging area for the species and for other foraging regions in southern South America. The research investigated aspects of hybridization, haplotype diversity, potential nesting source populations, migratory patterns using mitochondrial DNA control region (D-loop) analysis. The findings contribute to a deeper understanding of hybridization and migration in hawksbill turtles, providing crucial information for more effective conservation strategies.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eSpecimen collection\u003c/span\u003e\u003c/p\u003e\u003cp\u003eSkin tissue samples from 25 juvenile \u003cem\u003eEretmochelys imbricata\u003c/em\u003e individuals were collected in the state of São Paulo, southeastern Brazil (18 specimens in Ubatuba, 6 in Ilhabela, and 1 in São Sebastião), a known foraging habitat for this species (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), from 2011 to 2021 by the Projeto Tamar Foundation (Online Resource 1). The species identification of the specimens was conducted by specialists from the Tamar team, following the standards described by Pritchard and Mortimer (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Tissue samples were obtained using a disposable 6-mm biopsy punch. Samples collected prior 2013 were stored in absolute ethanol, while those collected afterward were stored in sodium chloride.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eDNA extraction\u003c/span\u003e\u003c/p\u003e\u003cp\u003eA pre-treatment was performed with washing and hydration of the skin tissue samples using Tris-HCl pH 7.5, 1 M. Subsequently, total DNA extraction was carried out using the Wizard® Genomic DNA Purification Kit (Promega®) (Madison, WI, USA), following the manufacturer’s instructions. The quantification of the obtained genetic material was performed using a NanoDrop Lite spectrophotometer.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eD-loop sequencing\u003c/span\u003e\u003c/p\u003e\u003cp\u003eThe D-loop region was partially amplified using the primer pair LCM15382 (5'-GCTTAACCCTAAAGCATTGG-3') and H950 (5'-GTCTCGGATTTAGGGGTTTG-3') (Abreu-Grobois et al. 2006). The amplification reactions were performed in a ProFlex PCR System thermocycler, with a total volume of 25 µL, containing 10 ng of template DNA, Tris-KCl (20 mM Tris-HCl pH 8.4 and 50 mM KCl), MgCl₂ (1.5 mM), 2.5 µM of each primer, dNTP (0.1 mM each), and 1 U of Taq DNA polymerase. The reaction conditions were as follows: initial denaturation at 94°C for 5 min, followed by 36 cycles of 94°C for 30 s, 50°C for 30 s, 72°C for 1 min, and a final extension at 72°C for 10 min (Lara-Ruiz et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The amplicons were purified using polyethyleneglycol (Rosenthal et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) and subsequently sequenced by a private company, using the Big Dye Terminator kit on the AB 3500 Genetic Analyzer. The sequencing reactions were prepared with the forward primer (LCM15382).\u003c/p\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eData analysis\u003c/span\u003e\u003c/p\u003e\u003cp\u003eThe nucleotide sequences obtained were edited using the BioEdit program (Hall, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) and aligned by ClustalW (Thompson et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) implemented in the MEGA X software (Kumar et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The haplotype characterization was conducted using the DnaSP v6 software (Rozas et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe haplotype nomenclature followed the standardizations of Arantes et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Partial sequences of the mitochondrial DNA control region available in the literature were compiled, related to nesting \u003cem\u003eE. imbricata\u003c/em\u003e in the Atlantic, as summarized by Arantes et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e), with the addition of data from Arantes et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020c\u003c/span\u003e), Simões et al. (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and Almeida et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) (Online Resource 2). The selection included only sequences associated with hatchlings and nesting females. Furthermore, the sequences were grouped according to megaregions: the Caribbean and the Brazilian Northeast.\u003c/p\u003e\u003cp\u003eThe same procedure was applied to foraging areas of \u003cem\u003eE. imbricata\u003c/em\u003e in the Atlantic, with additional data from Brito et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Arantes et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020c\u003c/span\u003e), and Almeida et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), including only juvenile individuals (Online Resource 3). Populations with fewer than three individuals were grouped with the nearest population (within 300 km), forming what we refer to as aggregation.\u003c/p\u003e\u003cp\u003eThe parsimony relationship between nesting haplotypes and the haplotypes from the São Paulo area sampled in this study, as well as other foraging areas in southern South America (Rio de Janeiro (Brazil), Santa Catarina (Brazil), and Uruguay – see locations in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), was represented in a network using the median-joining algorithm in the PopArt 1.7 software (Bandelt et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). For the hawksbill turtle foraging sequences related to southern South America, nucleotide diversity indices were calculated using the DnaSP v6 software (Rozas et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMoreover, the level of differentiation between the foraging and nesting aggregations was estimated using the AMOVA and FST values of aggregations pairs based on haplotype frequencies in the Arlequin v3.5 software (Excoffier and Lischer 2010).\u003c/p\u003e\u003cp\u003eFinally, a Bayesian mixed-stock analysis (MSA) was conducted using the mixstock package in R version 4.4.1 (Bolker et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; R Core Team \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) to estimate the contribution probabilities of different nesting areas to foraging areas located in southern South America. This analysis used haplotype frequencies from potential nesting areas (Online Resource 2), excluding the areas of Rio de Janeiro and Ceará and Piauí due to the low number of samples, which could introduce noise into the analysis, and incorporated four specific foraging areas: São Paulo (Brazil), Santa Catarina (Brazil), Rio Grande do Sul (Brazil), and Uruguay (Online Resource 3). It also considered the distances between these areas and the nesting sites, following the modified model of Stahelin et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). All areas were kept at uniform sizes.\u003c/p\u003e\u003cp\u003eThe \"many-to-many\" holistic approach was employed in the model following Phillips et al. (2022), allowing the estimation of contributions from multiple origin sites to multiple mixed destinations. Each model run consisted of 300,000 iterations with a burn-in of 150,000. The Gelman and Rubin reduction factor diagnostic was also performed to test for convergence (\u0026lt; 1.2) (Pella and Masuda \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe occurrence areas of nesting and foraging haplotypes were mapped using QGIS 3.34 software (QGIS Development Team 2023).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA final alignment of 25 sequences from all analyzed specimens from São Paulo, with 891 bp. Among these sequences, five distinct haplotypes were identified. One of them corresponded to haplotype CC-A4, detected in two individuals. This haplotype has been previously described in the literature as characteristic of \u003cem\u003eCaretta caretta\u003c/em\u003e (Reis et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). It is important to note, however, that the individuals sampled from São Paulo were morphologically identified as \u003cem\u003eEretmochelys imbricata\u003c/em\u003e. This finding suggests that these two individuals are hybrids, possessing mitochondrial DNA of \u003cem\u003eC. caretta\u003c/em\u003e while exhibiting the external morphology of \u003cem\u003eE. imbricata.\u003c/em\u003e The remaining four haplotypes (EiA01, EiA32, EiA61, and EiA62) were associated with \u003cem\u003eEretmochelys imbricata\u003c/em\u003e, as reported in previous studies (Simões et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Vilaça et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmong the haplotypes related to the hawksbill turtle, EiA01 was the most frequent, being found in 18 specimens. The haplotype EiA62 was identified in three samples, while the haplotypes EiA32 and EiA61 showed the lowest frequency, being detected in only one specimen each. The São Paulo region, along with Abrolhos, Fernando de Noronha, and Atol das Rocas (Brazil), were the only other areas where these four haplotypes were identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), all of which were also used as foraging areas.\u003c/p\u003e\u003cp\u003eThe alignment used for the parsimony analysis among the Atlantic nesting haplotypes, as well as from this study (São Paulo) and haplotypes from other foraging areas in southern South America (São Paulo (Brazil), Santa Catarina (Brazil), Rio Grande do Sul (Brazil), and Uruguay), resulted in a final alignment of 748 bp. The haplotype EiA01 was the most frequent, occurring in both mega-regions (Caribbean and northeastern Brazil) and in foraging sites across southern South America, including our study area. In contrast, the remaining haplotypes identified in our samples and in southern South America (EiA32, EiA61, and EiA62) were exclusive to the Brazilian nesting regions (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003eThe AMOVA for the Atlantic nesting colonies revealed significant genetic differentiation among aggregation, accounting for 30.8% of the total variation. Additionally, a marked differentiation was detected between the megaregions (Caribbean and South America), explaining 35.53% of the variation. However, a large portion of the genetic variation occurs within the aggregation themselves, representing 33.71% of the total variation. These results indicate that haplotype distribution is not random but follows a structured pattern, which is further supported by the high FST (66.3%) value, measuring differentiation among aggregation, and FCT (35.6%), reflecting differentiation between megaregions (Online Resource 4).\u003c/p\u003e\u003cp\u003eFor the FST test comparing the Atlantic nesting areas with the foraging areas in southern South America, the following results were obtained: genetic differentiation between the São Paulo foraging area and the Caribbean nesting colonies was observed through significant P-values, except with Cuba. For the Brazilian aggregation, the test identified differentiation only with the aggregation of Paraíba, while all other comparisons showed non-significant P-values (Online Resource 6).\u003c/p\u003e\u003cp\u003eFor the other foraging areas in southern South America, genetic differentiation was observed in relation to the Caribbean nesting areas, except for Barbados (Leeward Coast), Cuba, Sandy Point (U.S. Virgin Islands), and Tobago. Among the Brazilian aggregation, only Rio Grande do Sul showed significant differentiation from the aggregations of Bahia and Sergipe, while all other comparisons had non-significant P-values (Online Resource 6).\u003c/p\u003e\u003cp\u003eThe mixed-stock analysis indicated that the greatest contribution to the foraging area in São Paulo originated from Tobago, with a predominance of contributions from the southern region of the island, while the northern region showed smaller contributions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) (Online Resource 8).\u003c/p\u003e\u003cp\u003eAnalyzing the foraging areas, the haplotype distributions found in this study (EiA32, EiA61, and EiA62), which are also the only ones found in other foraging areas in southern South America, spanning from the Caribbean to Uruguay, including occurrences in some oceanic islands of the South Atlantic (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). The alignment of haplotypes related to foraging areas in southern South America revealed three variable sites, a haplotype diversity (h) of 0.3285, and a nucleotide diversity (π) of 0.00047.\u003c/p\u003e\u003cp\u003eThe AMOVA analysis of the Atlantic foraging colonies revealed genetic differentiation among aggregations, which account for 12.58% of the total variation. In addition, there was marked differentiation between the mega-regions (Caribbean and South America), responsible for 32.5% of the variation. However, most of the genetic variation occurs within the aggregations, representing 54.9% of the total variation. These results indicate that the distribution of haplotypes follows a structured pattern and is not random, as observed in the nesting areas. This is supported by the high FST (45.1%) and FCT (32.5%) values (Online Resource 5).\u003c/p\u003e\n\u003cp\u003eIn the foraging colony data, the FST test indicated differentiation between São Paulo and the Caribbean nesting areas, except for Turks \u0026amp; Caicos. The test also showed differentiation between São Paulo and the areas of Cape Verde and Príncipe Island, both located on the African coast. However, no differentiation was observed with Ascension Island, an oceanic island in the middle of the South Atlantic. Regarding the Brazilian foraging aggregations, the test did not identify any differentiation with any of them (Online Resource 7).\u003c/p\u003e\n\u003cp\u003eIn relation to the other foraging areas in southern South America, significant genetic differentiation was observed in relation to the Caribbean, except for Mexico (Contoy Island, Cozumel, Banco Chinchorro, and Xcalak), the Cayman Islands, Turks \u0026amp; Caicos, Colombia, and Tobago (Windward Coast). Within the Brazilian aggregations, Rio Grande do Sul exhibited significant differentiation from the aggregations of Fernando de Noronha and Atol das Rocas. Additionally, the aggregation of Santa Catarina showed statistically significant differentiation from the aggregations of Espírito Santo, Rio de Janeiro, Bahia, and Sergipe. For all other comparisons, P-values were not significant. Concerning the aggregations of Cape Verde and Príncipe Island, all southern foraging aggregations showed significant differentiation. In contrast, the analyses did not indicate significant differentiation in relation to Ascension Island, an oceanic island located in the central South Atlantic (Online Resource 7).\u003c/p\u003e\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study represents the first genetic investigation of the foraging population of \u003cem\u003eEretmochelys imbricata\u003c/em\u003e from São Paulo (Brazil), contributing to a better understanding of the species' population structure and migratory patterns. The identification of hybrid individuals in the region offers new perspectives on the occurrence of this phenomenon along the Brazilian coast. Furthermore, new haplotypes were identified for the foraging areas in southern South America, expanding knowledge of the species' genetic diversity in the region. The results also suggest that the analyzed individuals likely originate from foraging populations in northeastern Brazil, providing new insights into migratory routes and connectivity between the species' different areas of occurrence.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eHybridization\u003c/span\u003e\u003c/p\u003e\u003cp\u003eThe results for haplotype CC-A4 indicate that the mitochondrial DNA, or part of it, is derived from \u003cem\u003eCaretta caretta\u003c/em\u003e. However, the external morphology of the individuals is consistent with \u003cem\u003eE. imbricata\u003c/em\u003e, suggesting they are hybrids. This phenomenon has been widely reported in Brazil, with hybrids of \u003cem\u003eE. imbricata\u003c/em\u003e more frequently associated with \u003cem\u003eC. caretta\u003c/em\u003e (Lara-Ruiz et al. \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e; Proietti et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Brito et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Almeida et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNotably, haplotype CC-A4, identified in the hybrids in this study, is the most prevalent in the Brazilian reproductive colonies (Reis et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e). Additionally, this haplotype has been recorded in \u003cem\u003eE. imbricata\u003c/em\u003e x \u003cem\u003eC. caretta\u003c/em\u003e hybrids in foraging areas in southern Brazil and Uruguay (Brito et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results suggest that the analyzed individuals are hybrids of \u003cem\u003eE. imbricata\u003c/em\u003e x \u003cem\u003eC. caretta\u003c/em\u003e, indicating crossings between male \u003cem\u003eE. imbricata\u003c/em\u003e and female \u003cem\u003eC. caretta\u003c/em\u003e. Previous studies (Vilaça et al. \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e; Arantes et al. \u003cspan class=\"CitationRef\"\u003e2020b\u003c/span\u003e) suggest that hybridization in Brazil shows a gender bias, favored by the larger population size of \u003cem\u003eC. caretta\u003c/em\u003e and the temporal overlap of reproduction (Relvas et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), in addition to the morphological similarity between the species.\u003c/p\u003e\u003cp\u003eFactors such as the absence of reproductive barriers (Seminoff et al. \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e), normal meiotic pairing (Seehausen \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e), low karyotypic evolution (Machado et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), and the population decline of \u003cem\u003eEretmochelys imbricata\u003c/em\u003e in the 20th century may have facilitated the occurrence of these crosses (Vilaça et al. \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e; Soares et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHybrids generally exhibit behaviors similar to \u003cem\u003eC. caretta\u003c/em\u003e, migrating to temperate climate regions, but they may also show patterns different from the two parental species (Vilaça et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). This plasticity may explain their presence in the southern regions of Brazil, such as Rio Grande do Sul, and in Uruguay (Brito et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), a transition zone between the tropical preferences of \u003cem\u003eE. imbricata\u003c/em\u003e and the temperate preferences of \u003cem\u003eC. caretta\u003c/em\u003e. However, this does not explain the presence of these hybrids in São Paulo, given the occurrence of both species in this area (Gallo et al. \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe current and future implications of these hybridizations for species conservation remain unknown (Soares et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Arantes et al. \u003cspan class=\"CitationRef\"\u003e2020b\u003c/span\u003e). However, the low incidence of hybrid generations beyond F1 is relevant, possibly indicating incompatibility for backcrossing or low fitness in the hybrids (Vilaça et al. \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, it is crucial to investigate the consequences and prevalence of hybridization in populations with a high frequency of this phenomenon.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eOrigins of the Foraging Aggregation in Southern South America\u003c/span\u003e\u003c/p\u003e\u003cp\u003eThe haplotypes of \u003cem\u003eEretmochelys imbricata\u003c/em\u003e identified in southern South America (São Paulo, Santa Catarina, Rio Grande do Sul, and Uruguay) (EiA01, EiA32, EiA61, and EiA62) are shared with various nesting areas, ranging from the Caribbean to Brazil (Figs. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea). Among them, haplotype EiA01 is the most prevalent in the Atlantic (Arantes et al. \u003cspan class=\"CitationRef\"\u003e2020a\u003c/span\u003e). This broad distribution complicates the precise identification of the individuals' origin, although the closest nesting aggregation displaying haplotype EiA01 is located in northeastern Brazil. Despite the high dispersal capacity of the turtles, factors such as geographic distance and surface ocean currents often keep individuals near nesting areas, as observed in Brazilian colonies (Vilaça et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Proietti et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). On the other hand, the other foraging haplotypes identified in southern South America (EiA32, EiA61, and EiA62) are restricted to Brazilian nesting areas, with records in the states of Bahia, Alagoas, and Rio Grande do Norte (Figs. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003eThe AMOVA test revealed strong genetic structuring among nesting aggregations, both at the aggregation level and between megaregions (Caribbean and South America) (Online Resource 4). This genetic differentiation suggests that the aggregations maintain a distinct identity, possibly influenced by fidelity to nesting areas (natal homing) (Bowen and Karl \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e; Arantes et al. \u003cspan class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Furthermore, this genetic structuring becomes useful for inferring population origins, as the nesting populations are differentiated from each other. In line with this, the FST test revealed significant genetic differentiation between the Caribbean nesting colonies and the foraging aggregations in southern South America, while lower genetic differentiation was observed with aggregations from northeastern Brazil (Online Resource 6).\u003c/p\u003e\u003cp\u003eThe mixed-stock analysis, on the other hand, indicated a low contribution from Brazilian nesting areas, highlighting Tobago as the main contributing region, at least for the foraging area in São Paulo, despite only the EiA01 haplotype having been recorded in the country (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). It is worth noting that Tobago is the closest non-Brazilian region to the São Paulo area, which may influence the results, as the mixed stock model takes geographic proximity into account, given that turtles tend to forage in areas close to their origins (Vilaça et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Proietti et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). These results suggest a Caribbean influence on the foraging aggregations of southern South America, especially among individuals carrying haplotype EiA01. However, it is important to emphasize that most of the haplotypes identified in the foraging areas are exclusive to Brazilian regions.\u003c/p\u003e\u003cp\u003eThe results, along with the haplotype distribution (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), indicate that turtles from the foraging areas of São Paulo and southern South America predominantly originate from Brazilian aggregations, with some influence from the Caribbean. This highlights the importance of the nesting colonies in northeastern Brazil for the species' conservation (Marcovaldi et al. \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e). Regarding the foraging areas of southern South America, three of the four haplotypes analyzed (EiA01, EiA32, and EiA62) had been previously identified for this region (Proietti et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Brito et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the detection of haplotype EiA61 in São Paulo represents a new record (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003eThe only other foraging areas that presented the four haplotypes identified in São Paulo were the Abrolhos National Park, Fernando de Noronha, and Atol das Rocas, all located along the Brazilian coast (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb). The presence of these haplotypes in geographically distant regions suggests that similar nesting areas may contribute to the genetic composition of these foraging aggregations. Additionally, these areas, along with Ilha Bela and São Sebastião, sampled in the present study (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e), are located within conservation units (Brasil 1979, 1988; Bahia 1993; São Paulo 1977, 2008), reinforcing the role of these protected zones in maintaining the species' genetic diversity. Ubatuba, another area analyzed in this study, hosts a base of the Projeto Tamar Foundation, which plays a fundamental role in species conservation by providing protection through continuous monitoring, management activities and environmental education. The identification of these haplotypes in multiple protected areas highlights the importance of sea turtle conservation efforts carried out throughout the 21st century in Brazil (Casale et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). These findings suggest that effective conservation measures may play a crucial role in maintaining genetic diversity along the Brazilian coast.\u003c/p\u003e\u003cp\u003eAnother relevant aspect is the absence of Indo-Pacific haplotypes in the foraging areas of southern South America (Proietti et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Brito et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; this study), which may be associated with the significant influence of the Benguela and South Equatorial currents (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), which direct individuals to foraging areas along these currents, such as Cape Verde, Ascension Island, Príncipe Island, and oceanic islands in northeastern Brazil, where Indo-Pacific haplotypes have been recorded (Monzón-Argüello et al. 2010, \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e; Vilaça et al. \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Putman et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Arantes et al. \u003cspan class=\"CitationRef\"\u003e2020c\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMoreover, the foraging aggregations identified in southern South America exhibit lower haplotype diversity compared to those in northeastern Brazil (Vilaça et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Proietti et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e) and the Caribbean (Blumenthal et al. \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e; Proietti et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Cazabon-Mannette et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e; Pérez-Bermúdez et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Labastida-Estrada et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). This pattern can be explained by the absence of oceanic confluences in the southern region, which limits the migration of individuals from different nesting areas.\u003c/p\u003e\u003cp\u003eThe AMOVA test revealed strong genetic structuring among the Atlantic foraging aggregations, as well as between the megaregions (Caribbean, South America, and East Atlantic), similar to the results observed for the nesting colonies (Online Resource 5). This indicates that the distribution of haplotypes in foraging areas is not random, as suggested in the literature (Vilaça et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Proietti et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, genetic structuring in foraging areas is less pronounced than in nesting aggregations, as the majority of genetic variation occurs within groups. This pattern is also consistent with the literature, which points to greater genetic diversity in foraging areas compared to nesting areas (Arantes et al. \u003cspan class=\"CitationRef\"\u003e2020a\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn agreement, data from the foraging colonies, analyzed through the FST test, indicated some genetic differentiation between the foraging areas of southern South America and those in the Caribbean and oceanic islands, while largely showing no differentiation with Brazilian aggregations. These results suggest that the foraging aggregations of southern South America are more genetically connected to aggregations along the Brazilian coast, supporting the idea that nearby colonies share similar source populations (Vilaça et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Proietti et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMansfield et al. (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) demonstrated that for \u003cem\u003eCaretta caretta\u003c/em\u003e, the migration of hatchlings to Santa Catarina is determined by currents as well as active swimming movements. Thus, it is possible that hatchlings originating from northeastern Brazil use the Brazil Current to reach the southern and southeastern regions of the country. Understanding the connections between populations and their mutual impacts is crucial for the conservation of endangered and highly migratory species, such as the hawksbill turtle. This study emphasizes the need to preserve both the nesting colonies in northeastern Brazil and their foraging areas. Protecting only the hatchlings within political boundaries is not enough if capture in foraging areas continues in other locations (Troëng et al. \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e). Furthermore, the data presented contribute to a better understanding of the hybridization and migration of these turtles, helping to develop more effective conservation strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Projeto Tamar Foundation for providing the tissue samples used in this study. We also acknowledge the N\u0026uacute;cleo de Pesquisas em Limnologia, Ictiologia e Aquicultura (Nup\u0026eacute;lia) for access to the Molecular Genetics Laboratory infrastructure. Additionally, we are grateful to Gustavo David Stahelin for his assistance with Mixstock analyses and for his valuable feedback on earlier versions of the manuscript.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003eCompeting Interests\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eThe study was conceptualized by Geovana Jeniffer Ortel\u0026atilde; Gon\u0026ccedil;alves, Jos\u0026eacute; Henrique Becker, and Alessandra Val\u0026eacute;ria de Oliveira. Laboratory work was carried out by Geovana Jeniffer Ortel\u0026atilde; Gon\u0026ccedil;alves. Data analyses were performed by Geovana Jeniffer Ortel\u0026atilde; Gon\u0026ccedil;alves and Bruno Henrique Mioto Stabile. The first draft of the manuscript was written by Geovana Jeniffer Ortel\u0026atilde; Gon\u0026ccedil;alves, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eData Availability\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available within the main text and the supplementary materials.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbreu-Grobois FA, Horrocks J, Formia A et al. New mtDNA Dloop primers which work for a variety of marine turtle species may increase the resolution of mixed stock analyses. In: Frick M, Panagopoulou A, Rees A, Williams K (eds) Book of Abstracts, Twenty-sixth Annual Symposium on Sea Turtle Biology and Conservation. International Sea Turtle Society, Athens, Greece. p. 179. https://internationalseaturtlesociety.org/wp-content/uploads/2021/02/26-turtle.pdf\u003c/li\u003e\n\u003cli\u003eAllendorf FW, Leary RF, Spruell P, Wenburg JK (2001) The problems with hybrids: setting conservation guidelines. Trends Ecol Evol 16:613\u0026ndash;622. https://www.cell.com/ajhg/abstract/S0169-5347(01)02290-X\u003c/li\u003e\n\u003cli\u003eAlmeida JP, Marques OK, Mott T, Santos R (2023) Hybridization and genetic characterization of sea turtles in Alagoas, northeastern Brazil. Mar Biol 170. https://doi.org/10.1007/s00227-022-04168-y\u003c/li\u003e\n\u003cli\u003eArantes LS, Ferreira LC, Driller M et al. (2020b) Genomic evidence of recent hybridization between sea turtles at Abrolhos Archipelago and its association to low reproductive output. Sci Rep 10. https://doi.org/10.1038/s41598-020-69613-8\u003c/li\u003e\n\u003cli\u003eArantes LS, Vargas SM, Santos FR (2020a) Global phylogeography of the critically endangered hawksbill turtle (Eretmochelys imbricata). Genet Mol Biol 43. https://doi.org/10.1590/1678-4685-GMB-2019-0264\u003c/li\u003e\n\u003cli\u003eArantes LS, Vila\u0026ccedil;a ST, Mazzoni CJ et al. (2020c) New Genetic Insights About Hybridization and Population Structure of Hawksbill and Loggerhead Turtles From Brazil. J Hered, 111(5): 444\u0026ndash;456. https://doi.org/10.1093/jhered/esaa024\u003c/li\u003e\n\u003cli\u003eBahia. Decreto n\u0026ordm; 2.218, de 14 de junho de 1993. Disp\u0026otilde;e sobre a cria\u0026ccedil;\u0026atilde;o da \u0026Aacute;rea de Prote\u0026ccedil;\u0026atilde;o Ambiental da Ponta da Baleia/Abrolhos, nos Munic\u0026iacute;pios de Alcoba\u0026ccedil;a e Caravelas, e d\u0026aacute; outras provid\u0026ecirc;ncias. Pal\u0026aacute;cio do Governo do Estado da Bahia, Bahia. Dispon\u0026iacute;vel em: https://www.jusbrasil.com.br/legislacao/83215/decreto-2218-93. Acesso em: 11 mar. 2025\u003c/li\u003e\n\u003cli\u003eBalladares C, Ferm\u0026iacute;n I, Garc\u0026iacute;a E, Amilibia JC, Rodr\u0026iacute;guez D (2023) Preliminary analysis of microplastics from the main continental nesting beach of the hawksbill sea turtle (Eretmochelys imbricata) in Venezuela. Lat Am J Aquat Res 51: 79\u0026ndash;87. http://dx.doi.org/10.3856/vol51-issue1-fulltext-2789\u003c/li\u003e\n\u003cli\u003eBandelt H, Forster P, R\u0026ouml;hl A (1999) Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol 16: 37\u0026ndash;48. https://doi.org/10.1093/oxfordjournals.molbev.a026036\u003c/li\u003e\n\u003cli\u003eBarrios-Garrido H, Espinoza-Rodr\u0026iacute;guez N, Rojas-Ca\u0026ntilde;izales D et al (2017) Trade of marine turtles along the southwestern coast of Venezuela. Mar Biodivers Rec, 10: 15. https://doi.org/10.1186/s41200-017-0115-0\u003c/li\u003e\n\u003cli\u003eBass AL, Good DA, Bjorndal KA, Richardson JI, Hillis Z-M, Horrocks JA e BW Bowen (1996) Testing models of female reproductive migratory behaviour and population structure in the Caribbean hawksbill turtle, Eretmochelys imbricata, with mtDNA sequences. Mol Ecol 5:321\u0026ndash;328. https://doi.org/10.1046/j.1365-294X.1996.00073.x\u003c/li\u003e\n\u003cli\u003eBellini C, Sanches TM, Formia A (2000) Hawksbill turtle tagged in Brazil captured in Gabon, Africa. Marine Turtle Newsletter 87, 11\u0026ndash;12. http://www.seaturtle.org/mtn/archives/mtn87/mtn87p11.shtml\u003c/li\u003e\n\u003cli\u003eBlumenthal JM, Abreu-Grobois FA, Austin TJ et al. (2009) Turtle groups or turtle soup: dispersal patterns of hawksbill turtles in the Caribbean. Mol Ecol 18:4841\u0026ndash;4853. https://doi.org/10.1111/j.1365-294X.2009.04403.x\u003c/li\u003e\n\u003cli\u003eBomfim AC, Farias DS, Silva FJ et al (2021). Long-term monitoring of marine turtle nests in northeastern Brazil. Biota Neotrop, 21(3). https://doi.org/10.1590/1676-0611-BN-2020-1159\u003c/li\u003e\n\u003cli\u003eBolker BM, Okuyama T, Bjorndal KA, Bolten AB (2007). Incorporating multiple mixed stocks in mixed stock analysis: \u0026apos;many-to-many\u0026apos; analyses. Mol Ecol 16: 685\u0026ndash;695. https://doi.org/10.1111/j.1365-294X.2006.03161.x\u003c/li\u003e\n\u003cli\u003eBowen BW, Karl SA (2007) Population genetics and phylogeography of sea turtles. Mol Ecol 16:4886-4907. https://doi.org/10.1111/j.1365-294X.2007.03542.x\u003c/li\u003e\n\u003cli\u003eBrasil. Decreto n\u0026ordm; 83.549, de 5 de junho de 1979. Disp\u0026otilde;e sobre a cria\u0026ccedil;\u0026atilde;o da Reserva Biol\u0026oacute;gica do Atol das Rocas e d\u0026aacute; outras provid\u0026ecirc;ncias. Di\u0026aacute;rio Oficial da Uni\u0026atilde;o, Bras\u0026iacute;lia, DF. Dispon\u0026iacute;vel em: https://legis.senado.leg.br/norma/506189. Acesso em: 11 mar. 2025.\u003c/li\u003e\n\u003cli\u003eBrasil. Decreto n\u0026ordm; 96.693, de 14 de setembro de 1988. Disp\u0026otilde;e sobre a cria\u0026ccedil;\u0026atilde;o do Parque Nacional Marinho de Fernando de Noronha e d\u0026aacute; outras provid\u0026ecirc;ncias. Di\u0026aacute;rio Oficial da Uni\u0026atilde;o, Bras\u0026iacute;lia, DF. Dispon\u0026iacute;vel em: https://www.planalto.gov.br/ccivil_03/decreto/1980-1989/d96693.htm. Acesso em: 11 mar. 2025.\u003c/li\u003e\n\u003cli\u003eBrasil - Minist\u0026eacute;rio Do Meio Ambiente. Lista Nacional de Esp\u0026eacute;cies Amea\u0026ccedil;adas de Extin\u0026ccedil;\u0026atilde;o. Bras\u0026iacute;lia, 2022. Dispon\u0026iacute;vel em: \u0026lt; https://www.icmbio.gov.br/\ncepsul/images/stories/legislacao/Portaria\n/2020/P_mma_148_2022_altera_anexos\n_P_mma_443_444_445_2014_at\nualiza_especies_ameacadas_extincao.pdf\u0026gt;. Acesso em: 20 de outubro de 2024.\u003c/li\u003e\n\u003cli\u003eBrito C, Vila\u0026ccedil;a ST, Lacerda AL et al. (2020) Combined use of mitochondrial and nuclear genetic markers further reveal immature marine turtle hybrids along the South Western Atlantic. Genet Mol Biol 43. https://doi.org/10.1590/1678-4685-GMB-2019-0098\u003c/li\u003e\n\u003cli\u003eBrowne DC, Horrocks J\u0026Aacute;, Abreu-Grobois FA (2010) Population subdivision in hawksbill turtles nesting on Barbados, West Indies, determined from mitochondrial DNA control region sequences. Conserv Genet 11: 1541\u0026ndash;1546. https://doi.org/10.1007/s10592-009-9883-3\u003c/li\u003e\n\u003cli\u003eCarreras C, Godley BJ, Le\u0026oacute;n YM et al. (2013) Contextualising the last survivors: Population structure of marine turtles in the Dominican Republic. PLoS One 8. https://doi.org/10.1371/journal.pone.0066037\u003c/li\u003e\n\u003cli\u003eCasale P, Arapis T, Ceriani SA. et al. (2025) Monitoring the conservation status of sea turtle nesting sites: expert knowledge and quantitative indicators. J Coast Conserv 29, 31. https://doi.org/10.1007/s11852-025-01117-x\u003c/li\u003e\n\u003cli\u003eCazabon-Mannette M, Browne D, Austin N, Hailey A and Horrocks J (2016) Genetic structure of the hawksbill turtle rookery and foraging aggregation in Tobago, West Indies. J Exp Mar Biol Ecol 485:94\u0026ndash;101. https://doi.org/10.1016/j.jembe.2016.09.002\u003c/li\u003e\n\u003cli\u003eExcoffier L, Heidi ELL (2010) Arlequin Suite Ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour 10:564-567. https://doi.org/10.1111/j.1755-0998.2010.02847.x\u003c/li\u003e\n\u003cli\u003eFish MR, Cot\u0026eacute; IM, Gill JA, Jones AP, Renshoff S, Watkinson AR (2005) Predicting the impact of sea-level rise on Caribbean Sea turtle nesting habitat. Conserv Biol 19: 482\u0026ndash;491. https://doi.org/10.1111/j.1523-1739.2005.00146.x\u003c/li\u003e\n\u003cli\u003eGallo BM, Macedo S, Giffoni BB, Becker JH, Barata PCR (2006) Sea Turtle Conservation in Ubatuba, Southeastern Brazil, a Feeding Area with Incidental Capture in Coastal Fisheries. Chelonian Conserv Biol 5 (1): 93\u0026ndash;101. https://doi.org/10.2744/1071-8443(2006)5[93:STCIUS]2.0.CO;2\u003c/li\u003e\n\u003cli\u003eGorham JC, Clark D, Bresette MJ et al. (2014) Characterization of a subtropical hawksbill sea turtle (Eretmochelys imbricata) assemblage utilizing shallow water natural and artificial habitats in the Florida Keys. PLoS One 9. https://doi.org/10.1371/journal.pone.0114171\u003c/li\u003e\n\u003cli\u003eGrabenstein KC, Taylor SA (2018) Breaking Barriers: Causes, Consequences, and Experimental Utility of Human-Mediated Hybridization. Trends Ecol Evol 33:198\u0026ndash;212. https://doi.org/10.1016/j.tree.2017.12.008 1\u003c/li\u003e\n\u003cli\u003eHall TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser, v. 41, p. 95-98. \u003c/li\u003e\n\u003cli\u003eHill JE, King CM, Stewart KR, Paladino FV, Dutton PH (2018) Genetic differentiation of Hawksbill Turtle rookeries on St. Croix, US Virgin Islands. Chelonian Conserv Biol 17:303\u0026ndash;308. https://doi.org/10.2744/CCB-1293.1\u003c/li\u003e\n\u003cli\u003eHorrocks JA, Vermeer LA, Kreuger B, Coyne M, Schroeder B, Balazs G (2001) Migration routes and destination characteristics of post-nesting hawksbill turtles satellite-tracked from Barbados, West Indies. Chelonian Conserv Biol 4:107\u0026ndash;114. \u003c/li\u003e\n\u003cli\u003eKumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) MEGA X: Molecular Evolutionary Genetics Analysis across computing platforms. Mol Biol Evol 35:1547\u0026ndash;1549. https://doi.org/10.1093/molbev/msy096\u003c/li\u003e\n\u003cli\u003eLabastida-Estrada E, Machkour-M\u0026rsquo;Rabet S, D\u0026iacute;az-Jaimes P, Cede\u0026ntilde;o-V\u0026aacute;zquez JR and H\u0026eacute;naut Y (2019) Genetic structure, origin, and connectivity between nesting and foraging areas of hawksbill turtles of the Yucatan Peninsula: A study for conservation and management. Aqua Conserv: Mar Freshw Ecosyst 29:211\u0026ndash;222. https://doi.org/10.1002/aqc.2999\u003c/li\u003e\n\u003cli\u003eLara-Ruiz P, Lopez GG, Santos FR, Soares LS (2006) Extensive hybridization in hawksbill turtles (Eretmochelys imbricata) nesting in Brazil revealed by mtDNA analyses. Conserv Genet 7: 773\u0026ndash;781. https://doi.org/10.1007/s10592-005-9102-9\u003c/li\u003e\n\u003cli\u003eLeRoux RA, Dutton PH, Abreu-Grobois F et al. (2012) Re-examination of Population Structure and Phylogeography of Hawksbill Turtles in the Wider Caribbean Using Longer mtDNA Sequences. J Hered 103:806\u0026ndash;820. https://doi.org/10.1093/jhered/ess055\u003c/li\u003e\n\u003cli\u003eLevasseur KE, Stapleton SP, Fuller MC, Quattro JM (2019) Exceptionally high natal homing precision in hawksbill sea turtles to insular rookeries of the Caribbean. Mar Ecol Prog Ser 620:155-171. https://doi.org/10.3354/meps12957\u003c/li\u003e\n\u003cli\u003eMachado CR, Domit C, Pucci MB et al. (2020) Heterochromatin and microsatellites detection in karyotypes of four sea turtle species: Interspecific chromosomal differences. Genet Mol Biol 43:1\u0026ndash;9. https://doi.org/10.1590/1678-4685-GMB-2020-0213\u003c/li\u003e\n\u003cli\u003eMansfield KL, Mendilaharsu ML, Putman NF et al. (2017) First satellite tracks of South Atlantic sea turtle \u0026lsquo;lost years\u0026rsquo;: seasonal variation in trans-equatorial movement. Proc. R. Soc. B 284. https://doi.org/10.1098/rspb.2017.1730\u003c/li\u003e\n\u003cli\u003eMarcovaldi MA, Filippini A (1991) Trans-Atlantic movement by a juvenile hawksbill turtle. Marine Turtle Newsletter 52:3. http://www.seaturtle.org/mtn/archives/mtn52/mtn52p3.shtml\u003c/li\u003e\n\u003cli\u003eMarcovaldi MA, Lopez GG, Soares LS, Santos AJ, Bellini C, Barata PC (2007) Fifteen years of hawksbill (Eretmochelys imbricata) sea turtle nesting in northern Brazil. Chelonian Conserv Biol 6: 223\u0026ndash;228. https://doi.org/10.2744/1071-8443(2007)6[223:FYOHST]2.0.CO;2\u003c/li\u003e\n\u003cli\u003eMarcovaldi MA, Vieitas CF, Godfrey MH (1999) Nesting and conservation of hawksbill turtles (Eretmochelys imbricata) in northern Bahia, Brazil. Chelonian Conserv Biol 3: 301\u0026ndash;307. \u003c/li\u003e\n\u003cli\u003eMau A, Rodr\u0026iacute;guez PS, Picknell A et al. (2024) In-nest mortality and pathology of hawksbill sea turtle (Eretmochelys imbricata) embryos and hatchlings in St. Kitts and Nevis. J Comp Pathol, 209: 13-21. https://doi.org/10.1016/j.jcpa.2024.01.004\u003c/li\u003e\n\u003cli\u003eMaurer AS, Seminoff JA, Layman CA, Stapleton SP, Godfrey MH, Reiskind MO (2021) Population Viability of Sea Turtles in the Context of Global Warming. BioScience 71: 790\u0026ndash;804. https://doi.org/10.1093/biosci/biab028\u003c/li\u003e\n\u003cli\u003eMiller EA, McClenachan L, Uni Y, Phocas G, Hagemann ME, Van Houtan KS (2019),The historical development of complex global trafficking networks for marine wildlife. Sci Adv, 5,eaav5948. https://doi.org/10.1126/sciadv.aav5948\u003c/li\u003e\n\u003cli\u003eMontero N, Marcovaldi MA, Lopez\u0026ndash;Mendilaharsu M, Santos AS, Santos AJB, Fuentes MM (2018) Warmer and wetter conditions will reduce offspring production of hawksbill turtles in Brazil under climate change. PLOS ONE: 13. https://doi.org/10.1371/journal.pone.0204188\u003c/li\u003e\n\u003cli\u003eMonz\u0026oacute;n-Arg\u0026uuml;ello C, Loureiro NS, Delgado C et al. (2011) Pr\u0026iacute;ncipe island hawksbills: genetic isolation of an eastern Atlantic stock. J Exp Mar Biol Ecol 407: 345\u0026ndash;354. https://doi.org/10.1016/j.jembe.2011.07.017\u003c/li\u003e\n\u003cli\u003eMortimer JA, Donnelly M (2008) IUCN SSC Marine Turtle Specialist Group. Eretmochelys imbricata. The IUCN Red List of Threatened Species 2008: e.T8005A12881238. https://dx.doi.org/10.2305/IUCN.UK.2008.RLTS.T8005A12881238.en. \u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez-Berm\u0026uacute;dez E, Urquiola AR, Rebordinos-Gonz\u0026aacute;lez L, Espinosa-L\u0026oacute;pez G, Lee-Gonz\u0026aacute;lez I, Petric BLJ (2017) A new approach to mixed stock analysis that informs on the management and conservation of hawksbill in the wider Caribbean: the case of the legal fishery in Jardines del Rey, Cuba. Int J Mar Sci 7: 316\u0026ndash;343. https://aquapublisher.com/index.php/ijms/article/view/3191\u003c/li\u003e\n\u003cli\u003ePella J, Masuda M. (2001). Bayesian methods for analysis of stockmixtures from genetic characters. Fish bull, 99, 151\u0026ndash;167.\u003c/li\u003e\n\u003cli\u003ePritchard PC, Mortimer JA (1999) Taxonomy, external morphology, and species identification. In: Eckert KL, Bjorndal KA, Abreu-Grobois FA, Donnelly M (eds) Research and Management Techniques for the Conservation of Sea Turtles. Washington: IUCN/SSC. https://widecast.org/Resources/Docs/Pritchard_and_Mortimer_1999_Sea_Turtle_Taxonomy.pdf\u003c/li\u003e\n\u003cli\u003eProietti MC, Reisser J, Marins LF et al. (2014) Genetic structure and natal origins of immature Hawksbill Turtles (Eretmochelys imbricata) in Brazilian waters. PLoS One 9. https://doi.org/10.1371/journal.pone.0088746\u003c/li\u003e\n\u003cli\u003ePutman NF, Abreu-Grobois F, Broderick A et al. (2014) Numerical dispersal simulations and genetics help explain the origin of hawksbill sea turtles in Ascension Island. J Exp Mar Biol Ecol 450:98\u0026ndash;108. https://doi.org/10.1016/j.jembe.2013.10.026\u003c/li\u003e\n\u003cli\u003eQGIS Development Team. QGIS Geographic Information System. Vers\u0026atilde;o 3.34.1 Prizren. 2023. Dispon\u0026iacute;vel em: https://download.qgis.org/downloads/. Acesso em: fevereiro de 2025.\u003c/li\u003e\n\u003cli\u003eR Core Team (2024). R: A Language and Environment for Statistical Computing_. R Foundation for Statistical Computing, Vienna, Austria. \u0026lt;https://www.R-project.org/\u0026gt;.\u003c/li\u003e\n\u003cli\u003eReis EC, Soares LS, Vargas SM et al. (2010) Genetic composition, population structure and phylogeography of the loggerhead sea turtle: colonization hypothesis for the Brazilian rookeries. Conserv Genet 11: 1467\u0026ndash;1477. https://doi.org/10.1007/s10592-009-9975-0\u003c/li\u003e\n\u003cli\u003eRelvas CI, Ribeiro MV, Ferreira ES, Miranda MR, Schiavetti A (2022) Reproductive and ecological similarity between Caretta caretta (Linnaeus, 1758) and Eretmochelys imbricata (Linnaeus, 1766) in southern Bahia (Brazil). Braz J Biol 82. https://doi.org/10.1590/1519-6984.261269\u003c/li\u003e\n\u003cli\u003eRichardson PB, Bruford M, Calosso M et al. (2009) Marine turtles in the Turks and Caicos Islands: Remnant rookeries, regionally significant foraging stocks, and a major turtle fishery. Chelonian Conserv Biol 8:192\u0026ndash;207. https://doi.org/10.2744/CCB-0871.1\u003c/li\u003e\n\u003cli\u003eRosenthal A, Coutelle O, Craxton M (1993) Large-scale production of DNA sequencing templates by microtire format PCR. Nucleic Acid Research 21:173\u0026ndash;174. https://doi.org/10.1093/nar/21.1.173\u003c/li\u003e\n\u003cli\u003eRozas J, Ferrer-Mata A, S\u0026aacute;nchez-DelBarrio J et al. (2017) DnaSP 6: DNA Sequence Polymorphism Analysis of Large Data Sets. Mol Biol Evol 34: 3299\u0026ndash;3302. https://doi.org/10.1093/molbev/msx248\u003c/li\u003e\n\u003cli\u003eS\u0026atilde;o Paulo. Decreto n\u0026ordm; 53.525, de 8 de novembro de 2008. Disp\u0026otilde;e sobre a cria\u0026ccedil;\u0026atilde;o da \u0026Aacute;rea de Prote\u0026ccedil;\u0026atilde;o Ambiental Marinha do Litoral Norte e a \u0026Aacute;rea de Relevante Interesse Ecol\u0026oacute;gico de S\u0026atilde;o Sebasti\u0026atilde;o, e d\u0026aacute; provid\u0026ecirc;ncias correlatas. Pal\u0026aacute;cio dos Bandeirantes, S\u0026atilde;o Paulo. Dispon\u0026iacute;vel em: https://www.al.sp.gov.br/repositorio/legislacao/decreto/2008/decreto-53525-08.10.2008.html. Acesso em: 11 mar. 2025\u003c/li\u003e\n\u003cli\u003eS\u0026atilde;o Paulo. Decreto n\u0026ordm; 9.414, de 20 de janeiro de 1977. Disp\u0026otilde;e sobre a cria\u0026ccedil;\u0026atilde;o do Parque Estadual de Ilhabela e d\u0026aacute; provid\u0026ecirc;ncias correlatas. Pal\u0026aacute;cio dos Bandeirantes, S\u0026atilde;o Paulo. Dispon\u0026iacute;vel em: https://www.al.sp.gov.br/norma/74329. Acesso em: 11 mar. 2025\u003c/li\u003e\n\u003cli\u003eSeehausen O (2004) Hybridization and adaptive radiation. Trends Ecol Evol 19: 198\u0026ndash;207. https://doi.org/10.1016/j.tree.2004.01.003\u003c/li\u003e\n\u003cli\u003eSeminoff JA, Karl SA, Schwartz T, Resendiz A (2003) Hybridization of the green turtle (Chelonia mydas) and hawksbill turtle (Eretmochelys imbricata) in the Pacific ocean: indication of an absence of gender bias in the directionality of crosses. Bull Mar Sci 73: 643\u0026ndash;652. https://www.ingentaconnect.com/content/umrsmas/bullmar/2003/00000073/00000003/art00008#\u003c/li\u003e\n\u003cli\u003eSim\u0026otilde;es T, Santos E, Santos A et al. (2021) Low Diversity and Strong Genetic Structure Between Feeding and Nesting Areas in Brazil for the Critically Endangered Hawksbill Sea Turtle. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2021.704838\u003c/li\u003e\n\u003cli\u003eSim\u0026otilde;es TN, Silva AC, Moura CC (2017) Influence of artificial lights on the orientation of hatchlings of Eretmochelys imbricata in Pernambuco, Brazil. Zoologia (34). https://doi.org/10.3897/zoologia.34.e13727\u003c/li\u003e\n\u003cli\u003eSoares LS, Bjorndal K, Bolten A et al. (2018) Effects of hybridization on sea turtle fitness. Conserv Genet 19: 1311\u0026ndash;1322. https://doi.org/10.1007/s10592-018-1101-8\u003c/li\u003e\n\u003cli\u003eSoares LS, Bolten AB, Wayne ML et al. (2017) Comparison of reproductive output of hybrid sea turtles and parental species. Mar Biol 164:9. https://doi.org/10.1007/s00227-016-3035-3\u003c/li\u003e\n\u003cli\u003eStahelin GD, Hoffman EA, Quintana-Ascencio PF, Reusche M, Mansfield KL (2022) Incorporating distance metrics and temporal trends to refine mixed stock analysis. Sci Rep 12, 20569. https://doi.org/10.1038/s41598-022-24279-2\u003c/li\u003e\n\u003cli\u003eThompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gappenalties and weight matrix choice. Nucleic Acids Res 22: 4673\u0026ndash;4680. https://doi.org/10.1093/nar/22.22.4673\u003c/li\u003e\n\u003cli\u003eTro\u0026euml;ng S, Dutton PH, Evans D (2005) Migration of hawksbill turtles Eretmochelys imbricata from Tortuguero, Costa Rica. Ecography 28:394\u0026ndash;402. https://doi.org/10.1111/j.0906-7590.2005.04110.x\u003c/li\u003e\n\u003cli\u003eTrujillo-Arias N, Amorocho DF, L\u0026oacute;pez-\u0026Aacute;lvarez D and Mej\u0026iacute;a-Ladino LM (2014) Phylogeographic relations of some feeding and nesting of hawksbill turtle rookeries (Eretmochelys imbricata) in the Caribbean and Pacific of Colombia. Bol Invest Mar Cost 43:59\u0026ndash;182. http://www.scielo.org.co/scielo.php?pid=S0122-97612014000100008\u0026amp;script=sci_abstract\u0026amp;tlng=pt\u003c/li\u003e\n\u003cli\u003eVargas SM, Jensen M, Ho S et al. (2016) Phylogeography, Genetic Diversity, and Management Units of Hawksbill Turtles in the Indo-Pacific. J Hered 107: 199\u0026ndash;213. https://doi.org/10.1093/jhered/esv091\u003c/li\u003e\n\u003cli\u003eVelez-Zuazo X, Ramos WD, Van Dam RP, Diez CE, Abreu-Grobois A, McMillan WO (2008) Dispersal, recruitment and migratory behaviour in a hawksbill sea turtle aggregation. Mol Ecol 17:839\u0026ndash;853. https://doi.org/10.1111/j.1365-294X.2007.03635.x\u003c/li\u003e\n\u003cli\u003eVila\u0026ccedil;a ST, Lara-Ruiz P, Marcovaldi MA, Soares LS, Santos FR (2013) Population origin and historical demography in hawksbill (Eretmochelys imbricata) feeding and nesting aggregates from Brazil. J Exp Mar Biol Ecol 446:334\u0026ndash;34. https://doi.org/10.1016/j.jembe.2013.06.004\u003c/li\u003e\n\u003cli\u003eVila\u0026ccedil;a ST, Maroso F, Lara P et al. (2023) Evidence of backcross inviability and mitochondrial DNA paternal leakage in sea turtle hybrids. Mol Ecol 32: 628\u0026ndash;643. https://doi.org/10.1111/mec.16773\u003c/li\u003e\n\u003cli\u003eVila\u0026ccedil;a ST, Vargas S, Lara-Ruiz P et al. (2012) Nuclear markers reveal a complex introgression pattern among marine turtle species on the Brazilian coast. Mol Ecol 21: 4300\u0026ndash;4312. https://doi.org/10.1111/j.1365-294X.2012.05685.x\u003c/li\u003e\n\u003cli\u003eWood LD, Hardy R, Meylan PA, Meylan AB (2013) Characterization of a hawksbill turtle (Eretmochelys imbricata) foraging aggregation in a high-latitude reef community in southeastern Florida, USA.Herpetol Conserv Biol 8:258\u0026ndash;275. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"marine-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mabi","sideBox":"Learn more about [Marine Biology](https://www.springer.com/journal/227)","snPcode":"227","submissionUrl":"https://submission.nature.com/new-submission/227/3","title":"Marine Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Biogeography, Genetic diversity, Genetic structure, Migration, Sea turtle","lastPublishedDoi":"10.21203/rs.3.rs-7722562/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7722562/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe hawksbill turtle (\u003cem\u003eEretmochelys imbricata\u003c/em\u003e), classified as critically endangered, has a global distribution in tropical and subtropical waters. The Brazilian colony is essential for the species' conservation, as it is the largest remaining nesting population in the South Atlantic. Furthermore, it exhibits the highest hybridization rate worldwide. This study investigated the foraging population in the state of S\u0026atilde;o Paulo (Southeast Brazil), which previously lacked genetic data, using mitochondrial DNA (D-loop) analysis of immature individuals. Hybrids between \u003cem\u003eE. imbricata\u003c/em\u003e and \u003cem\u003eCaretta caretta\u003c/em\u003e were identified, along with hawksbill haplotypes previously recorded in southern South America and a novel haplotype for the region. The absence of Indo-Pacific haplotypes suggests the influence of the Benguela Current, which reduces genetic diversity compared to the Brazilian Northeast and the Caribbean. The results indicate that the foraging individuals in southern South America predominantly originate from the Brazilian Northeast, with some influence from the Caribbean, highlighting the role of the Brazil Current in the dispersal of hatchlings. These findings emphasize the importance of Southeast Brazil for hawksbill turtle conservation and its relevance to the species' life cycle across different regions.\u003c/p\u003e","manuscriptTitle":"Hybridization Analysis and Haplotypic Diversity in Eretmochelys Imbricata in Southeastern Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-13 22:55:02","doi":"10.21203/rs.3.rs-7722562/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revise and Resubmit","date":"2025-11-21T10:16:22+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-10-01T12:24:22+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-30T16:16:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-27T09:57:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Marine Biology","date":"2025-09-26T10:04:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"marine-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mabi","sideBox":"Learn more about [Marine Biology](https://www.springer.com/journal/227)","snPcode":"227","submissionUrl":"https://submission.nature.com/new-submission/227/3","title":"Marine Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2351396b-a547-426d-a83c-6d41627f7f74","owner":[],"postedDate":"October 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T15:58:57+00:00","versionOfRecord":{"articleIdentity":"rs-7722562","link":"https://doi.org/10.1007/s00227-026-04825-6","journal":{"identity":"marine-biology","isVorOnly":false,"title":"Marine Biology"},"publishedOn":"2026-04-29 15:57:07","publishedOnDateReadable":"April 29th, 2026"},"versionCreatedAt":"2025-10-13 22:55:02","video":"","vorDoi":"10.1007/s00227-026-04825-6","vorDoiUrl":"https://doi.org/10.1007/s00227-026-04825-6","workflowStages":[]},"version":"v1","identity":"rs-7722562","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7722562","identity":"rs-7722562","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}