João Paulo Felix Augusto de Almeida

Tese_Joao_UFAL_final.pdf
Documento PDF (3.2MB)

UNIVERSIDADE FEDERAL DE ALAGOAS
INSTITUTO DE CIÊNCIAS BIOLÓGICAS E DA SAÚDE
Programa de Pós-Graduação em Diversidade Biológica e Conservação nos
Trópicos

JOÃO PAULO FELIX AUGUSTO DE ALMEIDA

DIVERSIDADE GENÉTICA E CONSERVAÇÃO DE TARTARUGAS MARINHAS DO
OCEANO ATLÂNTICO SUDOESTE

MACEIÓ - ALAGOAS
Janeiro/2023

JOÃO PAULO FELIX AUGUSTO DE ALMEIDA

DIVERSIDADE GENÉTICA E CONSERVAÇÃO DE TARTARUGAS MARINHAS DO
OCEANO ATLÂNTICO SUDOESTE

Tese apresentada ao Programa de Pós-Graduação
em Diversidade Biológica e Conservação nos
Trópicos, Instituto de Ciências Biológicas e da
Saúde. Universidade Federal de Alagoas, como
requisito para obtenção do título de Doutor em
CIÊNCIAS BIOLÓGICAS, área de concentração em
Conservação da Biodiversidade Tropical.

Orientador(a): Prof(a). Dr.(a) Tamí Mott
Coorientador: Prof. Dr. Robson G. Santos

MACEIÓ - ALAGOAS
Janeiro/2023

Catalogação na fonte
Universidade Federal de Alagoas
Biblioteca Central
Divisão de Tratamento Técnico
Bibliotecária: Taciana Sousa dos Santos – CRB-4 – 2062
A447d

Almeida, João Paulo Felix Augusto de .
Diversidade genética e conservação de tartarugas marinhas do Oceano
Atlântico Sudoeste / João Paulo Felix Augusto de Almeida. – 2023.
132 f. : il. color.
Orientadora: Tamí Mott.
Coorientador: Robson G. Santos.
Tese (Doutorado em Ciências Biológicas) – Universidade Federal
de Alagoas. Instituto de Ciências Biológicas e da Saúde. Programa de PósGraduação em Diversidade Biológica e Conservação nos Trópicos. Maceió,
2023.
Bibliografia: f. 105-106.
Anexos: f. 108-132.
1. Tartarugas marinhas. 2. Variabilidade genética. 3. DNA mitocondrial.
4. Hibridização. I. Título.
CDU: 639.248 : 575

Folha de aprovação
João Paulo Felix Augusto de Almeida

DIVERSIDADE GENÉTICA E CONSERVAÇÃO DE TARTARUGAS MARINHAS DO
OCEANO ATLÂNTICO SUDOESTE

Tese apresentada ao Programa de Pós-Graduação
em Diversidade Biológica e Conservação nos
Trópicos, Instituto de Ciências Biológicas e da
Saúde. Universidade Federal de Alagoas, como
requisito para obtenção do título de Doutor(a) em
CIÊNCIAS
BIOLÓGICAS
na
área
da
Biodiversidade.

Tese aprovada em 16 de janeiro de 2023.
Dr.(a) Tamí Mott/UFAL
(orientadora)
Prof. Dr. Robson Guimarães dos Santos
(co-orientador)

Dr. (a) Taciana Kramer de Oliveira Pinto

Dr. (a) Liliana Poggio Colman

Dr. (a) Kim Ribeiro Barão

Dr. (a) Ricardo Jessouroun de Miranda

Dr. (a) Sibelle Torres Vilaça

MACEIÓ - AL
Janeiro/2023

AGRADECIMENTOS

A toda minha família, minha mãe, meu pai e todas as pessoas que me apoiaram
durante essa jornada. A meus avós, que se foram durante esse período, e que, de perto
ou de longe, sempre contribuíram para meu crescimento pessoal desde a infância. A
meus amigos, que me ouviram e incentivaram e que muitas vezes tiveram que ouvir
que eu não podia sair porque estava ocupado demais com coisas do doutorado.
A todos os amigos do laboratório de biologia integrativa; Grazi, André, Luana,
Isaelly, Aline, Letícia e Matheus. Bruna, pelas conversas descontraídas sobre a vida
acadêmica, animes e outras coisas aleatórias. Um agradecimento especial para
Jessika, pelas conversas, incentivos, conselhos, ajuda no laboratório e com tantas
outras coisas! E também por me permitir passar tempo com Jade, essa princesa
especial de quatro patas :).
A todos os amigos do laboratório de biologia marinha e conservação; Priscila,
Gabi, Nana, Laura, Adriano, Ingredy, Julia, Renata, Larissa, Kallyne, Jimena e
especialmente Thaila, pelas conversas e momentos compartilhados em campo e no
laboratório. Que venham mais campos como o de Maragogi 2020 haha.
A minha orientadora, Dra Tamí Mott, por ter me recebido em seu laboratório lá
em 2011. Por todos esses anos de parceria e aprendizado que me ajudaram a crescer
como pessoa e como pesquisador. A meu coorientador, Dr Robson Santos, por ter
aberto seu laboratório durante esse período de doutorado e por ter proporcionado essa
oportunidade de aprender mais sobre esse grupo fascinante que são as tartarugas
marinhas.
A todos os pesquisadores que fizeram parte das bancas avaliativas durante
esses mais de quatro anos de doutorado: Dra Maíra Proietti, Dr Kim Barão, Dr Franco
de Souza, Dra Tereza Thomé, Dra Camila Domit, Dr Ricardo Miranda, Dra Sibelle
Vilaça, Dra Liliana Colman e Dra Taciana Kramer. Da mesma forma, fica aqui meu
agradecimento a todos os professores e pesquisadores que fizeram parte da minha
formação acadêmica desde os tempos de escola até aqui. Igualmente, a todos os

funcionários que trabalharam para que essas instituições pudessem funcionar e
proporcionar educação e formação acadêmica para tantas pessoas.
Ao Dr Paolo Casale, por me receber em seu laboratório na Itália e a todos os
membros do departamento, que me receberam muito bem. Em especial Christina, que
foi minha guia assim que cheguei por lá e a quem perturbei fazendo as perguntas mais
absurdas e aleatórias que uma pessoa pode fazer quando vai morar em um novo país.
Em especial também a Giulia, pelas conversas nos intervalos do café e pelas aventuras
e conselhos na minha última semana por lá. A Sara e Chiara, por me oferecerem um
abrigo em sua casa nas minhas últimas semanas em Pisa. A Chiara, Salvatore e Giulia
pelas interações sempre amigáveis mesmo nos poucos momentos que compartilhamos.
A todas as pessoas que conheci por lá nos hostels e nas ruas e que proporcionaram
ótimas conversas e aprendizados.
A Universidade Federal de Alagoas, que tem sido minha segunda casa desde
2010, por oferecer um ensino público de qualidade e por ter se mantido forte mesmo
durante os momentos turbulentos. Que venham ainda muitos anos de formação de
profissionais, professores e pesquisadores de qualidade.
Ao Instituto Biota de Conservação, pela parceria na aquisição das amostras
utilizadas nessa tese. Aos órgãos de fomento, Fundação Boticário e Fundação PADI,
que foram fundamentais para que essa tese pudesse ser desenvolvida. Ao Projeto
Ecológico de Longa Duração Costa dos Corais Alagoas, por também ter contribuído
direta e indiretamente para o desenvolvimento dessa tese. A Fundação de Amparo à
Pesquisa do Estado de Alagoas por ter financiado minha bolsa durante a duração do
curso e também minha bolsa de doutorado sanduíche.
Por fim, ao Programa de Pós-graduação em Diversidade Biológica e
Conservação nos Trópicos e todos os seus professores, bem como a Julliene que
sempre resolve nossas angústias lá na secretaria.

Os sonhos vêm, os sonhos vão e o resto é imperfeito.
Legião Urbana

RESUMO
As tartarugas marinhas são répteis com ciclo de vida complexo, marcado por mudanças
ontogenéticas de hábitat. Ameaças às tartarugas marinhas são diversas e podem variar
de acordo com seu estágio de vida. Assim, a identificação e caracterização de suas
populações é fundamental para elucidar padrões de variabilidade e entender como
essas pressões podem estar afetando as tartarugas marinhas. Nesta tese foram
avaliadas a razão sexual de tartarugas verdes ao longo de áreas de alimentação do
Oceano Atlântico Sudoeste (OAS), a origem natal de fêmeas e machos dessa espécie,
a presença de hibridização entre tartarugas marinhas no nordeste do Brasil e se a
diversidade genética de tartarugas verdes tem variado ao longo do tempo no OAS e se
isso se relaciona com a recuperação de áreas de desova locais. Análises genéticas
foram realizadas utilizando-se principalmente a região controle do DNA mitocondrial
(mtDNA), porém também utilizamos marcadores nucleares e repetições curtas do DNA
mitocondrial (mtSTR) a fim de verificar a presença de estruturações populacionais não
reveladas apenas com mtDNA. Foi observada uma razão sexual de tartarugas verdes
em favor das fêmeas ao longo do OAS e que fêmeas e machos que se alimentam no
nordeste do Brasil possuem origem natal levemente diferente. A variação genética
temporal na espécie ao longo do OAS não é perceptível quando se avalia a região
como um todo. Porém, foi possível observar que a frequência dos haplótipos variou ao
longo do tempo tanto no nordeste quanto no sul do Brasil. Também foi detectada a
presença de hibridização entre quatro espécies de tartarugas marinhas ao longo do
litoral de Alagoas, nordeste do Brasil, além da presença de um espécime de tartaruga
de pente com um haplótipo típico de áreas de desova do Indo-Pacífico. Esses
resultados contribuem para a caracterização genética das tartarugas marinhas no OAS,
além de discutir questões ecológicas importantes como a presença de hibridização e a
diferença na produção de fêmeas e machos por diferentes áreas de desova e como
esses processos podem ser acentuados frente às mudanças climáticas e outras
pressões atuais.
Palavras-chave: Variabilidade genética. DNA mitocondrial. Aumento de temperatura.
Brasil. Hibridização.

ABSTRACT

Sea turtles are reptiles with complex life cycles, marked by ontogenetic habitat shifts.
They are under a wide range of threats that vary according to their life stage. Thus, the
identification and characterization of sea turtle populations is fundamental to clarify
variability patterns and how these anthropic pressures can affect these species. The
main goals of this study were to evaluate green turtle sex ratios along feeding grounds in
the Southwest Atlantic Ocean (SWA), to investigate natal origins of female and male
green turtles, to assess the hybridization process among sea turtles from northeastern
Brazil and to evaluate temporal variation in green turtle genetic diversity along the SWA
and if this variation is related to the recovery of local nesting sites. The control region of
the mitochondrial DNA was employed for most genetic analyses, but nuclear loci and
mitochondrial short tandem repeats (mtSTR) were also used to assess population
structure. Green turtle sex ratios along the SWA were female-skewed and females and
males that feed along the coast of northeastern Brazil have slightly divergent natal
origins. Temporal variation on green turtle genetic diversity along the SWA was not
noticeable. However, it was possible to observe temporal variation in haplotype
frequency and natal origins when analysing data from northeastern and southern Brazil
independently. Hybridization was observed among four sea turtle species along the
coast of Alagoas, northeastern Brazil. Furthermore, a hawksbill specimen had a
haplotype typical from Indo-Pacific nesting sites. This study contributes to sea turtle
genetic characterization in the SWA and debates important subjects with ecological
implications such as the presence of hybridization in sea turtle populations and varying
female and male outputs in local nesting sites. Understanding and monitoring these
processes is essential to evaluate how sea turtle populations will respond to ongoing
environmental pressures, such as climate change and other anthropic threats.

Keywords: Genetic variability. Mitochondrial DNA. Rising temperatures. Brazil.
Hybridization

SUMÁRIO
1 APRESENTAÇÃO ....................................................................................................... 10
REFERÊNCIAS............................................................................................................... 12
2 REVISÃO DA LITERATURA ....................................................................................... 14
2.1 Aspectos biológicos básicos das tartarugas marinhas....................................... 14
2.2 Marcadores moleculares no estudo da estrutura populacional de tartarugas
marinhas ........................................................................................................................ 17
2.3 Ameaças às tartarugas marinhas .......................................................................... 19
2.4 Tartarugas marinhas no Oceano Atlântico Sudoeste .......................................... 23
REFERÊNCIAS............................................................................................................... 28
3 SEX RATIOS AND NATAL ORIGINS OF GREEN TURTLES FROM FEEDING
GROUNDS IN THE SOUTHWEST ATLANTIC OCEAN ................................................. 37
3.1 Introduction ............................................................................................................. 38
3.2 Materials and Methods ............................................................................................ 40
3.2.1 Feeding grounds sex ratios .................................................................................... 40
3.2.2 Genetic composition and natal origins of female and male green turtles ............... 42
3.3 Results ..................................................................................................................... 44
3.3.1 Feeding grounds sex ratios .................................................................................... 44
3.3.2 Genetic composition and natal origins of female and male green turtles ............... 46
3.4 Discussion ............................................................................................................... 49
3.4.1 Feeding grounds sex ratios .................................................................................... 49
3.4.2 Genetic composition and natal origins of female and male green turtles ............... 50
3.5 Concluding remarks ................................................................................................ 53
3.6 Supplementary material .......................................................................................... 53
3.7 Acknowledgments ................................................................................................... 54
3.8 Data availability ....................................................................................................... 54
References ..................................................................................................................... 54
4 HYBRIDIZATION AND GENETIC CHARACTERIZATION OF SEA TURTLES IN
ALAGOAS, NORTHEASTERN BRAZIL ........................................................................ 61

4.1 Introduction ............................................................................................................. 62
4.2 Methods.................................................................................................................... 64
4.3 Results ..................................................................................................................... 67
4.3.1 Hybridization ........................................................................................................... 68
4.3.2 Genetic characterization ......................................................................................... 71
4.4 Discussion ............................................................................................................... 71
4.4.1 Hybridization ........................................................................................................... 72
4.4.2 Genetic characterization ......................................................................................... 75
4.5 Concluding remarks ................................................................................................ 78
4.6 Acknowledgments ................................................................................................... 79
4.7 Author contributions ............................................................................................... 79
4.8 Funding .................................................................................................................... 80
4.9 Data availability ....................................................................................................... 80
References ..................................................................................................................... 80
5 TEMPORAL VARIATION ON THE GENETIC DIVERSITY OF GREEN TURTLES
FROM THE SOUTHWEST ATLANTIC OCEAN ............................................................. 87
5.1 Introduction ............................................................................................................. 87
5.2 Methods.................................................................................................................... 89
5.3 Results ..................................................................................................................... 92
5.4 Discussion ............................................................................................................... 93
References ..................................................................................................................... 97
6 Discussão geral e conclusões ................................................................................ 101
Referências .................................................................................................................. 105
ANEXO A – CAPÍTULO 1 ............................................................................................. 107
ANEXO B – CAPÍTULO 2 ............................................................................................. 113
ANEXO C – CAPÍTULO 3 ............................................................................................. 120

1 APRESENTAÇÃO
As tartarugas marinhas fazem parte de um grupo de répteis com um complexo
ciclo de vida, caracterizado por um crescimento lento e mudanças ontogenéticas de
hábitat (BOLTEN, 2003). Cinco das setes espécies de tartarugas marinhas; Caretta
caretta (tartaruga cabeçuda), Chelonia mydas (tartaruga verde), Dermochelys coriacea
(tartaruga de couro), Eretmochelys imbricata (tartaruga de pente) e Lepidochelys
olivacea (tartaruga oliva); possuem ampla distribuição, podendo ser encontradas em
todo o globo, principalmente em regiões tropicais e subtropicais (BOLTEN, 2003). As
duas espécies remanescentes, Lepidochelys kempii e Natator depressus, em geral
possuem distribuição mais restrita, sendo encontradas principalmente no golfo do
México e no litoral Australiano, respectivamente (LIMPUS, 2007; MÁRQUEZ, 2001).
Atualmente, todas as espécies se encontram sob algum grau de ameaça de
acordo com União Internacional para a Conservação da Natureza (IUCN), exceto por N.
depressus, que se encontra sob a classificação de deficiência de dados (IUCN, 2022).
Apesar de serem historicamente exploradas em diversas fases da vida, desde a coleta
de ovos até a caça de tartarugas adultas; várias ações de proteção ao redor do mundo
têm contribuído para a recuperação e manutenção das populações remanescentes (e.g.
MARCOVALDI; MARCOVALDI, 1999; WEBER et al., 2014). Algumas áreas de desova
têm permanecido estáveis (ALMEIDA et al., 2011), enquanto outras têm apresentado
um crescimento significativo, apesar de ainda representarem apenas uma parte do seu
tamanho populacional original (CATRY et al., 2009; WEBER et al., 2014).
Ainda assim, mudanças no ambiente natural decorrentes de atividades humanas
têm ameaçado as populações de tartarugas marinhas ao redor do mundo. Mudanças
climáticas, pesca incidental, ocupação desordenada do ambiente costeiro, poluição dos
ambientes costeiro e marinho, são apenas algumas das ameaças às tartarugas
marinhas atualmente (FUENTES et al., 2010; FUENTES; LIMPUS; HAMANN, 2011;
SANTOS; MACHOVSKY-CAPUSKA; ANDRADES, 2021). Como consequência desse
cenário, a identificação e caracterização das populações remanescentes dessas

espécies se faz cada vez mais necessária, principalmente em áreas que apresentam
risco potencial para essas populações, como é o caso do Oceano Atlântico Sudoeste
(OAS) (WALLACE et al., 2010). Com exceção de L. kempii e N. depressus, todas as
outras espécies de tartarugas marinhas ocorrem no OAS. É possível encontrar áreas de
nidificação e alimentação dessas espécies na região e vários estudos apontam a
conexão do OAS com outras regiões do Atlântico (LUSCHI et al., 1998; NARO-MACIEL
et al., 2012; PROIETTI et al., 2014). Além disso, a frequência de hibridização entre
tartarugas marinhas em algumas áreas do OAS, particularmente no litoral do Brasil, é
maior do que em outras regiões do mundo (BRITO et al., 2020; LARA-RUIZ et al., 2006;
REIS; SOARES; LÔBO-HAJDU, 2010). Dessa maneira, o contínuo monitoramento
dessas áreas e da dinâmica populacional de tartarugas marinhas na região é essencial
para guiar futuros estudos e medidas de conservação adequadas para essas espécies.
Esta tese discute um pouco das temáticas expostas acima com um foco nas
tartarugas marinhas do OAS. Primeiramente, esses temas são discutidos com mais
detalhes na seção de revisão de literatura. Após, seguem-se três capítulos que
abordam a diversidade genética e conservação de tartarugas marinhas no OAS. No
primeiro capítulo discute-se a razão sexual de tartarugas verdes em áreas de
alimentação no OAS bem como a origem natal de fêmeas e machos da espécie em
uma área de alimentação no estado de Alagoas, nordeste do Brasil. No segundo
capítulo, discute-se a hibridização entre espécies de tartarugas marinhas em áreas de
nidificação e alimentação também em Alagoas. No terceiro capítulo é abordada a
diferenciação genética entre tartarugas verdes provenientes de áreas de alimentação
de Alagoas e do estado do Paraná, sul do Brasil, bem como a variação temporal na
diversidade genética da espécie no OAS e como ela se relaciona com a recuperação de
áreas de desova da região.
O primeiro capítulo encontra-se publicado no periódico ICES Journal of Marine
Science (https://doi.org/10.1093/icesjms/fsab093). O segundo capítulo está publicado
no periódico Marine Biology (https://doi.org/10.1007/s00227-022-04168-y) e o terceiro
está sendo preparado para submissão no mesmo periódico. Por fim, após os três

capítulos principais da tese, segue-se uma seção de discussão geral e conclusões. Os
três capítulos principais estão formatados segundo as normas das revistas citadas
acima, enquanto o restante da tese está formatado de acordo com as normas do
Programa de Pós-graduação em Diversidade Biológica e Conservação nos Trópicos
(PPG-DIBICT) e da Universidade Federal de Alagoas (UFAL).
REFERÊNCIAS
ALMEIDA, A. P. et al. Green turtle nesting on trindade island, Brazil: Abundance, trends,
and biometrics. Endangered Species Research, v. 14, n. 3, p. 193–201, 2011.
BOLTEN, A. B. Variation in sea turtle life history patterns: neritic vs oceanic
developmental stages. In: LUTZ, P. L.; MUSICK, J. A.; WYNEKEN, J. (Eds.), The
Biology of Sea Turtles Volume II. CRC Press, Boca Raton, 2003, p. 243–257.
BRITO, C. et al. Combined use of mitochondrial and nuclear genetic markers further
reveal immature marine turtle hybrids along the south western Atlantic. Genetics and
Molecular Biology, v. 43, n. 2, p. 1–11, 2020.
CATRY, P. et al. Status, Ecology, and Conservation of Sea Turtles in Guinea-Bissau.
Chelonian Conservation and Biology, v. 8, n. 2, p. 150–160, 2009.
FUENTES, M. M. P. B. et al. Potential impacts of projected sea-level rise on sea turtle
rookeries. Aquatic Conservation: Marine and Freshwater Ecosystems, v. 20, n. 2, p.
132–139, 2010.
FUENTES, M. M. P. B.; LIMPUS, C. J.; HAMANN, M. Vulnerability of sea turtle nesting
grounds to climate change. Global Change Biology, v. 17, p. 140–153, 2011.
IUCN. The IUCN Red List of Threatened Species. Version 2022-1, 2022.
<https://www.iucnredlist.org>
LARA-RUIZ, P. et al. Extensive hybridization in hawksbill turtles (Eretmochelys
imbricata) nesting in Brazil revealed by mtDNA analyses. Conservation Genetics, v. 7, n.
5, p. 773–781, 2006.
LIMPUS, C. J. A Biological Review of Australian Marine Turtles. 5. Flatback turtle,
Natator depressus (Garman). Report for the Environmental Protection Agency
Queensland. p. 1–54, 2007.

LUSCHI, P. et al. The navigational feats of green sea turtles migrating from Ascension
Island investigated by satellite telemetry. Proceedings of the Royal Society of London B,
v. 265, p. 2279–2284, 1998.
MARCOVALDI, M. A.; Marcovaldi, G. G. Marine turtles of Brazil: The history and
structure of Projeto TAMAR-IBAMA. Biological Conservation, v. 91, p. 35–41, 1999.
MÁRQUEZ, R. M. Status and Distribution of the Kemp’s Ridley Turtle, Lepidochelys
kempii, in the Wider Caribbean Region. p. 46–51, 2001.
NARO-MACIEL, E. et al. The interplay of homing and dispersal in green turtles: A focus
on the southwestern atlantic. Journal of Heredity, v. 103, n. 6, p. 792–805, 2012.
PROIETTI, M. C. et al. Genetic structure and natal origins of immature hawksbill turtles
(Eretmochelys imbricata) in Brazilian waters. PLoS ONE, v. 9, n. 2, 2014.
REIS, E. C.; SOARES, L. S.; LÔBO-HAJDU, G. Evidence of olive ridley mitochondrial
genome introgression into loggerhead turtle rookeries of Sergipe, Brazil. Conservation
Genetics, v. 11, n. 4, p. 1587–1591, 2010.
SANTOS, R. G.; MACHOVSKY-CAPUSKA, G. E.; ANDRADES, R. Plastic ingestion as
an evolutionary trap: Toward a holistic understanding. Science, v. 373, p. 56–60, 2021.
WALLACE, B. P. et al. Regional Management Units for Marine Turtles : A Novel
Framework for Prioritizing Conservation and Research across Multiple Scales. PLoS
ONE, v. 5, n. 12, 2010.
WEBER, S. B. et al. Recovery of the South Atlantic’s largest green turtle nesting
population. Biodiversity and Conservation, v. 23, n. 12, p. 3005–3018, 2014.

2 REVISÃO DA LITERATURA

2.1 Aspectos biológicos básicos das tartarugas marinhas
Atualmente, existem sete espécies conhecidas de tartarugas marinhas: Caretta
caretta (Linnaeus, 1758); Chelonia mydas (Linnaeus, 1758), Dermochelys coriacea
(Vandelli, 1761); Eretmochelys imbricata (Linnaeus, 1766), Lepidochelys kempii
Garman, 1980; Lepidochelys olivacea (Eschscholtz, 1829) e Natator depressus
(Garman, 1980). Duas dessas espécies, L. kempii e N. depressus, possuem distribuição
geralmente mais restrita; sendo a primeira majoritariamente restrita ao golfo do México
e a costa leste dos Estados Unidos da América (MÁRQUEZ, 2001), enquanto a
segunda é majoritariamente restrita a águas Australianas (LIMPUS, 2007). As outras
espécies possuem distribuição cosmopolita, sendo encontradas em águas tropicais e
subtropicais de todo o globo (BOLTEN, 2003).
As tartarugas marinhas possuem um ciclo de vida complexo que frequentemente
envolve mudanças ontogenéticas de habitat (BOLTEN, 2003). Historicamente, pouco se
sabia sobre a fase inicial da vida das tartarugas marinhas, como Carr (1967) escreveu
“Where do little sea turtles go, and how do they live after they leave the nesting beach?”.
Muito se descobriu depois que Carr fez essas perguntas e o princípio da elucidação do
mistério dos “anos perdidos” se deu com o próprio Carr (1967). A hipótese sugerida por
ele foi a de que, durante essa fase de vida, as tartarugas marinhas permanecem na
superfície de zonas oceânicas, geralmente associadas a campos de sargaço. Vários
relatos de pescadores que encontraram pequenas tartarugas nessas áreas foram
registrados (e.g. CARR, 1967), o que ajudava a sustentar a hipótese de Carr. Estudos
posteriores, principalmente baseados em telemetria por satélite e isótopos estáveis,
vieram a confirmar essa hipótese e esclarecer ainda mais a dinâmica migratória dos
filhotes recém eclodidos (ARTHUR; BOYLE; LIMPUS, 2008; MANSFIELD et al., 2014;
REICH; BJORNDAL; BOLTEN, 2007).

Atualmente, aceita-se a existência de três padrões principais no ciclo de vida das
tartarugas marinhas (BOLTEN, 2003). No primeiro deles, a fase juvenil de
desenvolvimento e a fase adulta do ciclo de vida dos indivíduos é restrita às zonas
neríticas (zonas próximas a costa com profundidade em geral menor que 200m), esse
padrão é observado apenas em N. depressus. No segundo padrão, logo após a
emergência dos ovos, os juvenis migram para zonas oceânicas onde se desenvolvem
por alguns anos, posteriormente migrando para zonas neríticas para completar seu
desenvolvimento, esse padrão pode ser observado em C. caretta, C. mydas, E.
imbricata e L. kempii. No último padrão, observado em D. coriacea e L. olivacea, o
desenvolvimento dos indivíduos ocorre inteiramente nas zonas oceânicas (Fig. 1;
BOLTEN, 2003).
As áreas de desenvolvimento e alimentação podem se localizar próximas as
áreas de desova ou podem estar separadas por até milhares de quilômetros. Quando
alcançam a maturidade sexual, fêmeas e machos adultos migram periodicamente das
áreas de alimentação para os sítios reprodutivos, que geralmente se localizam em
regiões costeiras próximas a seus sítios de nidificação (PLOTKIN, 2003). Tartarugas
marinhas apresentam fidelidade tanto aos sítios reprodutivos quanto aos de nidificação
(filopatria), ou seja, machos e fêmeas geralmente se reproduzem nas mesmas áreas e
as fêmeas da espécie nidificam na mesma região em que nasceram (CARR, 1967;
LOHMANN ET AL., 2013). Após o período de acasalamento, os machos retornam aos
sítios de alimentação enquanto as fêmeas nadam até a praia para depositar os ovos
(HAMANN; LIMPUS; OWEN, 2003; MORTIMER; CARR, 1987). O intervalo entre cada
temporada acasalamento para fêmeas gira em torno de dois a quatro anos, enquanto
machos podem acasalar mais frequentemente (MORTIMER; CARR, 1987; PLOTKIN,
2003).

Figura 1 – Diferentes padrões de ciclo de vida encontrados em tartarugas marinhas, de
acordo com Bolten, 2003.

Fonte: Elaborado pelo autor (2023).

Devido as características filopátricas das tartarugas marinhas, as áreas de desova
dessas espécies tendem a ser geneticamente estruturadas, uma vez que elas tendem a se
reproduzir na mesma região onde nasceram (ENCALADA et al., 1996; NARO-MACIEL et
al., 2014). Entretanto, ao contrário do que acontece nas áreas de desova, as áreas de
alimentação podem receber indivíduos de diversas áreas de desova diferentes, compondo
o que é conhecido como estoque misto. Nessas áreas há ocorrência não só de indivíduos
de diversas origens natais, mas também de classes etárias distintas. Nesse sentido, dados
moleculares se tornaram uma ferramenta útil para investigar a conexão entre essas áreas e
as possíveis rotas de migração que as tartarugas marinhas utilizam, uma vez que é
possível estimar a origem natal de indivíduos em um estoque misto a partir da análise de
seu DNA mitocondrial devido às

características filopátricas das

fêmeas

dessas

espécies(e.g. BOWEN et al., 1995; NARO-MACIEL et al., 2014; SHAMBLIN et al., 2012).

2.2 Marcadores moleculares no estudo da estrutura populacional de tartarugas
marinhas
A estrutura genética das tartarugas marinhas tem sido estudada desde o final da
década de 1980 e começo da década de 1990 (BOWEN et al., 1992; BOWEN;
MEYLANT; AVISE, 1989; BOWEN; NELSON; AVISE, 1993). Em tartarugas verdes,
uma ampla amostragem das áreas de desova da espécie no mundo encontrou vários
agrupamentos genéticos utilizando dados de polimorfismos de comprimento de
fragmentos de restrição (RFLPs) e forneceu suporte molecular para a hipótese de
filopatria em tartarugas marinhas (BOWEN et al., 1992). Porém, por conta da baixa
resolução de dados de RFLPs, a estruturação genética não pode ser avaliada em uma
escala mais fina. A partir daí estudos subsequentes começaram a empregar dados de
sequências de nucleotídeos para estudar a genética de populações das tartarugas
marinhas, primeiramente com o gene mitocondrial citocromo b (BOWEN; NELSON;
AVISE, 1993), e posteriormente com a região controle do DNA mitocondrial (ALLARD et
al., 1994; ENCALADA et al., 1996; LAHANAS et al., 1994).
A região controle do DNA mitocondrial (inicialmente um fragmento de ~400 pares
de base) foi utilizada em diversos estudos e se tornou a principal fonte de comparação

para estudos subsequentes (BASS; LAGUEUX; BOWEN, 1998; BJORNDAL et al.,
2006; LAHANAS et al., 1998; LUKE et al., 2004; NARO-MACIEL et al., 2007). Com o
crescente número de estudos utilizando a região controle, o centro de pesquisa Archie
Carr Center for Sea Turtle Research, na Universidade da Flórida, organizou uma lista
para tartarugas verdes e tartarugas cabeçudas, as duas espécies mais estudadas, com
uma nomenclatura padrão para todos os haplótipos conhecidos para esse fragmento do
DNA mitocondrial a fim de evitar possíveis duplicações e confusões nas publicações
(https://accstr.ufl.edu/resources/mtdna-sequences/).

Novos

primers

(iniciadores)

também foram desenvolvidos visando amplificar uma região maior da região controle
(~800 pares de base, ABREU-GROBOIS et al., 2006). À medida que novos estudos
passaram a utilizar esse fragmento mais longo, novas estruturações genéticas
passaram a ser identificadas (e.g. JORDÃO et al., 2015; NARO-MACIEL et al., 2012;
SHAMBLIN et al., 2015).
Outros marcadores moleculares têm ganhado espaço nos últimos anos. Por
exemplo, repetições curtas em tandem (do inglês Short Tandem Repeats, STR) e
polimorfismos de nucleotídeo único (do inglês Single Nucleotide Polymorphisms, SNP)
têm conseguido detectar uma estrutura populacional não observada anteriormente
(SHAMBLIN et al., 2015, 2017; TIKOCHINSKI et al., 2012). Da mesma maneira,
microssatélites nucleares também em sido desenvolvidos (CARRERAS et al., 2007;
FITZSIMMONS; MORITZ; MOORE, 1995; SHAMBLIN et al., 2009). No entanto, alguns
estudos têm mostrado que, apesar de exibirem alta estruturação genética (BAGDA;
BARDAKCI; TURKOZAN, 2012; NARO-MACIEL et al., 2014), eles têm revelado menos
estruturação do que marcadores mitocondriais (e.g. FITZSIMMONS et al., 1997; NAROMACIEL et al., 2014). Mais recentemente, técnicas de sequenciamento de nova
geração, como ddRAD, também têm ajudado a elucidar a estruturação populacional
nessas espécies (ARANTES et al., 2020). Ainda assim, a região controle do DNA
mitocondrial continua sendo o marcador molecular mais utilizado em genética de
populações de tartarugas marinhas.

2.3 Ameaças às tartarugas marinhas
Os desafios para as tartarugas marinhas começam cedo no seu ciclo de vida.
Ainda no seu estágio embrionário, estão suscetíveis à predadores naturais que utilizam
ovos de tartarugas marinhas como fonte de alimento; aves marinhas, crustáceos,
pequenos mamíferos e algumas vezes até plantas fazem parte desse grupo
(HEITHAUS, 2013). Seu pequeno tamanho corporal após a emergência dos ovos
também as deixa vulneráveis durante todo o seu percurso até o oceano (SANTOS et
al., 2016; STEWART; WYNEKEN, 2004). Consequentemente, apenas uma pequena
parte dos indivíduos que emergem dos ovos consegue atingir a fase adulta (FRAZER,
1986).
Além dos desafios naturais, elas também têm que lidar com os desafios impostos
pela presença humana. O avanço da urbanização em ambientes costeiros promove a
diminuição da faixa de areia disponível para desovas das tartarugas marinhas e
pisoteamento dos ninhos, além da poluição luminosa que desnorteia os filhotes recém
emergidos (COLMAN et al., 2020; SALMON, 2003; TRUSCOTT; BOOTH; LIMPUS,
2017). A eclosão dos filhotes geralmente ocorre no período noturno, e um dos principais
guias para os filhotes é a luz da lua que reflete sobre o oceano, que os direciona
diretamente para as águas marinhas (SALMON, 2003). Porém, com a iluminação
artificial presente nas áreas litorâneas, muitas vezes é possível encontrar filhotes de
tartarugas marinhas migrando em direção a essas luzes, em direção oposta ao oceano
(TRUSCOTT; BOOTH; LIMPUS, 2017).
Ao chegar ao oceano, as tartarugas marinhas passam a enfrentar uma gama
diferente de desafios. Entre eles, a pesca incidental é frequentemente apontada como
um dos principais fatores de mortalidade de tartarugas marinhas, e tanto a pesca
industrial quanto a artesanal desempenham um papel nesse cenário (LEWISON et al.,
2004). Porém, ainda é difícil traçar qual a real amplitude do impacto da pesca incidental
nas populações de tartarugas marinhas por conta da dificuldade em realizar medições
precisas da quantidade e da causa da mortalidade dos animais (LEWISON et al., 2004).

Devido a isso, embora o número de estudos na área tenha aumentado nas últimas
décadas (LEWISON et al., 2014; WALLACE et al., 2013), esse impacto ainda é
subestimado (para uma revisão sobre o assunto ver WALLACE et al., 2010b). Uma
melhor compreensão sobre a distribuição, hábitos alimentares e rotas migratórias das
populações de tartarugas marinhas é essencial para redução da mortalidade desses
animais, uma vez que as taxas de pesca incidental geralmente são mais altas em áreas
onde há sobreposição de atividades pesqueiras e alta concentração de tartarugas
marinhas (WALLACE et al., 2010b)
Apesar da pesca incidental ser considerada como a principal ameaça às
tartarugas marinhas (WALLACE et al., 2010b), outras ameaças emergentes começaram
a surgir juntamente com o avanço da industrialização. Atualmente, os efeitos das
mudanças climáticas, derivadas principalmente de ações antrópicas, têm sido
amplamente debatidos e estudados levando ao desenvolvimento de estimativas de
como essas mudanças irão afetar o planeta (IPCC, 2021). A constante emissão de
gases causadores de um efeito estufa no planeta tem causado grande preocupação e é
responsável por um iminente aumento da temperatura global (IPCC, 2021). O aumento
da temperatura pode afetar as tartarugas marinhas de diversas maneiras, desde a
mudança de hábitats ótimos para alimentação e migração devido a mudanças na
temperatura nos oceanos, até alterações na razão sexual de determinadas populações
(DAVENPORT, 1997). Todas as espécies de tartarugas marinhas têm o sexo
determinado por temperatura, onde cada espécie apresenta uma temperatura pivotal,
isto é, uma temperatura ótima onde a geração de fêmeas e machos tem probabilidade
igual (DAVENPORT, 1997). Temperaturas de incubação acima dessa temperatura
ótima geram mais fêmeas e temperaturas mais baixas, mais machos. Atualmente,
várias populações já exibem uma razão sexual em favor de fêmeas (HAYS; MAZARIS;
SCHOFIELD, 2014). Esse cenário tende a se intensificar ainda mais com o aumento da
temperatura nas praias de nidificação (FUENTES; LIMPUS; HAMANN, 2011).
Apesar de ser o foco de vários estudos recentes, os efeitos desse processo de
feminização na dinâmica populacional das espécies ainda não é totalmente claro

(MITCHELL; JANZEN, 2010). Além do aumento da temperatura nas praias, outros
fatores abióticos e bióticos também devem ser levados em consideração e podem
ajudar a mitigar os efeitos negativos dessa elevação da temperatura. Por exemplo, a
presença de vegetação nas praias bem como a coloração da areia podem amenizar a
temperatura de incubação dos ovos, afetando assim a razão sexual de determinadas
áreas de desova (PATRÍCIO et al., 2019). Da mesma forma, a maior frequência de
acasalamento dos machos de tartarugas marinhas, que podem acasalar com várias
fêmeas em uma mesma temporada reprodutiva e em temporadas sucessivas, pode
compensar a maior abundância de fêmeas na população (HAYS et al., 2017; HAYS;
MAZARIS; SCHOFIELD, 2014). Ainda assim, o aumento exacerbado da temperatura
em determinadas regiões pode causar um aumento na mortalidade dos filhotes
daquelas áreas de desova (DAVENPORT, 1997; HOWARD; BELL; PIKE, 2014). Dessa
maneira, áreas de desova que produzem machos são cada vez mais importantes para
dinâmica populacional da espécie, uma vez que a tendência atual aponta para um
aumento na produção de fêmeas e na mortalidade de filhotes nas áreas de desova.
Outra consequência das mudanças climáticas é o aumento do nível do mar, que
juntamente com o avanço da urbanização nas zonas costeiras, ameaça ecossistemas
litorâneos nas próximas décadas (IPCC, 2021). Uma consequência direta desse
processo para tartarugas marinhas é a inundação cada vez mais frequente de ninhos,
além da diminuição da área disponível para nidificação (FUENTES et al., 2010). Isso
pode gerar uma maior concentração de fêmeas nas áreas de praia remanescentes, o
que pode aumentar as chances de pisoteamento dos ninhos bem como a destruição de
ninhos por outras fêmeas durante as temporadas reprodutivas (FUENTES et al., 2010).
A diminuição das áreas disponíveis para nidificação também pode gerar maior
sobreposição das atividades de reprodução e nidificação entre espécies distintas, o que
pode aumentar as chances de eventos de hibridização, que já são comuns em áreas
com alta sobreposição em atividades reprodutivas no Brasil (LARA-RUIZ et al., 2006;
REIS; SOARES; LÔBO-HAJDU, 2010).

Ainda é incerto, no entanto, como as tartarugas marinhas irão se adaptar a essas
alterações ambientais. Mudanças na disponibilidade de hábitats para nidificação irão
possivelmente demandar uma adaptação comportamental em um período de tempo
relativamente curto (HAWKES et al., 2009). Os efeitos da mudança de temperatura de
superfície dos oceanos também podem alterar suas áreas de alimentação devido a
ocupação preferencial do hábitat de acordo com a temperatura (WITT et al., 2010).
Além disso, a mudança nas temperaturas dos oceanos também pode afetar outras
espécies animais e vegetais que fazem parte da sua cadeia alimentar, afetando, por
consequência, sua distribuição devido a mudanças na disponibilidade de alimento
(HAWKES et al., 2009).
Concomitantemente com as mudanças climáticas, outras ameaças de origem
antrópica se fazem cada vez mais presentes com o avanço da urbanização e ocupação
dos ambientes costeiros. Duas das principais ameaças decorrentes desses fatores
incluem a poluição por plástico e a fibropapilomatose, ambas relacionadas à poluição
dos ambientes marinhos (AGUIRRE; LUTZ, 2004; NELMS et al., 2016). A poluição por
plástico já afeta milhares de espécies no mundo nos mais variados grupos animais
(SANTOS; MACHOVSKY-CAPUSKA; ANDRADES, 2021). O grande aporte de plásticos
nos oceanos gera uma grande disponibilidade desse material no ambiente (GEYER;
JAMBECK; LAW, 2017), o que se traduz em uma maior probabilidade de interação das
tartarugas com itens plásticos. Casos de emaranhamento e ingestão são comuns e
representam um grande problema, uma vez que podem interferir no desenvolvimento
adequado dos indivíduos (RIZZI et al., 2019; RODRÍGUEZ et al., 2022). Por exemplo,
itens plásticos podem apresentar características físico-químicas que se assemelham
àquelas de presas das tartarugas, o que as faz consumir esses materiais já que há uma
grande abundância deles no ambiente e os mesmos não apresentam resistência
(SANTOS; MACHOVSKY-CAPUSKA; ANDRADES, 2021). Esse comportamento pode
ser nocivo para saúde das tartarugas uma vez que os itens plásticos não apresentam
nenhum valor nutricional e podem gerar complicações como obstrução do trato
gastrointestinal, desnutrição e eventualmente a morte (NELMS et al., 2016).

A fibropapilomatose por sua vez, se trata de uma doença viral caracterizada pela
presença de tumores externos e/ou internos. A presença e localização desses tumores
pode variar de indivíduo para indivíduo e pode ter associação com fatores ecológicos e
genéticos (AGUIRRE; LUTZ, 2004; ROSSI et al., 2016). Dependendo da localização
desses tumores no corpo dos indivíduos, eles podem interferir na movimentação, visão,
alimentação, ou mesmo no funcionamento de órgãos internos, o que pode afetar a
habilidade dos indivíduos de interagir com o ambiente (ROSSI et al., 2016). Embora, as
causas da fibropapilomatose não sejam totalmente claras, estudos recentes têm
ajudado a elucidar os mecanismos de infecção e transmissão da doença (e.g. FARREL
et al., 2021; YETSKO et al., 2021), que pode também estar associada à poluição de
ambientes marinhos (JONES et al., 2016; SANTOS et al., 2010).
Apesar da grande amplitude das ameaças às tartarugas marinhas, o
desenvolvimento de medidas de conservação adequadas é dificultado pelo seu
complexo ciclo de vida e recorrentes migrações entre diferentes hábitats, que podem
muitas vezes estar separados por milhares de quilômetros (LUSCHI et al., 2003). Zonas
de monitoramento mais restritas chamadas Unidades Regionais de Manejo (do inglês
Regional Management Units, RMUs) foram então sugeridas a fim de prover uma melhor
avaliação do status populacional bem como das ameaças a um nível regional, o que
poderia ajudar a melhorar a efetividade das ações de manejo (WALLACE et al., 2010a).
Entre as RMUs no Oceano Atlântico, a RMU do Oceano Atlântico Sudoeste (OAS) foi
considerada de alto risco para tartarugas marinhas (WALLACE et al., 2011), o que a
destaca como uma área prioritária para conservação nessa região.
2.4 Tartarugas marinhas no Oceano Atlântico Sudoeste
Atualmente, cinco espécies de tartarugas marinhas podem ser encontradas no
OAS: tartaruga cabeçuda, tartaruga verde, tartaruga de couro, tartaruga de pente e
tartaruga oliva. Áreas de desova dessas espécies na região se espalham pelo litoral
continental e ilhas oceânicas (MARCOVALDI; MARCOVALDI, 1999). A tartaruga verde
possui áreas de desova principalmente nas ilhas oceânicas de Trindade, Fernando de

Noronha e Atol das Rocas, porém as desovas também podem acontecer no litoral
continental em menor proporção (ALMEIDA et al., 2011; BJORNDAL et al., 2006).
Áreas de desova das outras espécies estão localizadas principalmente no continente. A
tartaruga cabeçuda desova entre os estados do Rio de Janeiro e Espírito Santo, no
sudeste do Brasil, e entre Bahia e Sergipe no nordeste do Brasil, tendo o litoral norte da
Bahia como sua principal área de desova (MARCOVALDI; CHALOUPKA, 2007; REIS;
SOARES; LÔBO-HAJDU, 2010). As principais áreas de desova da tartaruga de pente
são no litoral norte da Bahia e no litoral sul do Rio Grande do Norte (MARCOVALDI et
al., 2007), enquanto áreas de desova da tartaruga oliva se concentram principalmente
entre o litoral norte da Bahia e sul de Alagoas (SILVA et al., 2007). Por fim, áreas de
desova da tartaruga de couro podem ser encontradas principalmente no litoral norte do
estado do Espírito Santo (COLMAN et al., 2019; THOMÉ et al., 2007).
Áreas de desova de tartarugas verdes apresentam uma clara estruturação entre
as regiões norte e sul do oceano Atlântico (ENCALADA et al., 1996; NARO-MACIEL et
al., 2014), tendo uma composição mista na região da América Central (NARO-MACIEL
et al., 2014). No OAS, as áreas de desova também apresentam certo grau de
estruturação, embora o haplótipo CM-A8 (considerando o fragmento curto da região
controle do DNA mitocondrial), mais comum na região, esteja presente em maior
frequência em todas as áreas (BJORNDAL et al., 2006). Considerando o fragmento
longo da região controle, o haplótipo CM-A8 pode ser subdividido em cinco haplótipos
(subvariantes CM-A8.1–CM-A8.5) distintos. As tartarugas cabeçudas das áreas de
desova no litoral norte da Bahia, Sergipe, Rio de Janeiro e Espírito Santo; apresentaram
até o momento apenas três haplótipos distintos (CC-A4, CC-A24 e CC-A25), dos quais
o haplótipo mais frequente é o CC-A4, representando mais de 86% dos indivíduos
analisados até o momento (REIS et al., 2010). Este haplótipo, pode ser subdividido em
outros quatro considerando o fragmento longo da região controle (subvariantes CCA4.1–CC-A4.4). Da mesma forma, apenas três haplótipos (Dc1.1, Dc3.1 e Dc13.1) são
encontrados em áreas de desova da tartaruga de couro na região, mesmo
considerando o fragmento longo (VARGAS et al., 2019). Três haplótipos já foram

registrados nas áreas de desova da tartaruga oliva, Lo67, LoX3 e LoX4 (BOWEN et al.,
1998; Vilaça et al., 2022). Nas áreas de desova da tartaruga de pente, quatro haplótipos
podem ser encontrados (Ei-A01, Ei-A32, Ei-A61 e Ei-A62), sendo o haplótipo Ei-A01 o
mais frequente (ARANTES; VARGAS; SANTOS, 2020).
Áreas de alimentação dessas espécies no OAS ocorrem ao longo de todo o
litoral da América do Sul e recebem indivíduos de diversas áreas de desova de todo o
Atlântico (e.g. NARO-MACIEL et al., 2012; PROIETTI et al., 2014a; PROSDOCIMI et
al., 2012). Áreas de alimentação de tartarugas verdes recebem indivíduos
principalmente da Ilha de Ascensão, uma das maiores áreas de desova do Atlântico
Sul, e também de áreas de desova no caribe (NARO-MACIEL et al., 2012; PROIETTI et
al., 2012). A Ilha de Trindade abriga a maior área de desova da espécie no OAS, porém
o número de ninhos por temporada chega a ser até quatro vezes menor do que em
Ascensão (ALMEIDA et al., 2011; MEDEIROS et al., 2022). Como consequência, sua
influência na composição de indivíduos nas áreas de alimentação da região é mais
perceptível apenas em regiões geograficamente mais próximas, no sul do Brasil
(PROIETTI et al., 2012). Contribuições da área de desova de Guiné Bissau também são
notáveis (JORDÃO et al., 2015; NARO-MACIEL et al., 2012), embora em menor
proporção (mas veja capítulo 1). Contudo, áreas de desova no litoral Africano do
Oceano Atlântico ainda são pouco conhecidas, portanto a contribuição dessas áreas
para a composição de indivíduos nas áreas de alimentação do OAS pode vir a mudar a
medida em que essas áreas sejam mais bem estudadas.
A diversidade genética de tartarugas cabeçudas em suas áreas de alimentação
indica que a maior parte dos indivíduos têm origem em áreas de desova locais, o que é
indicado principalmente pela alta frequência do haplótipo CC-A4, que é exclusivo de
áreas de desova Brasileiras (REIS et al., 2010). Devidos a seus hábitos oceânicos,
estudos em áreas de alimentação das tartarugas de couro e oliva são escassos. As
áreas de alimentação da tartaruga de pente no OAS em geral recebem indivíduos
principalmente de áreas de desova locais (Bahia e Rio Grande do Norte), embora

haplótipos encontrados em áreas de desova Africanas também já tenham sido
observados (PROIETTI et al., 2014a).
O avanço de estudos sobre a diversidade genética das espécies de tartarugas
marinhas no OAS também revelou uma alta taxa de hibridização na região (e.g. LARARUIZ et al., 2006; REIS; SOARES; LÔBO-HAJDU, 2010), ao contrário do que se
encontra em outras regiões do mundo (BRITO et al., 2020). No OAS é possível
observar uma alta taxa de hibridização entre a tartaruga cabeçuda e a tartaruga de
pente e entre tartaruga cabeçuda e tartaruga oliva (LARA-RUIZ et al., 2006; REIS et al.,
2010). Híbridos entre a tartaruga cabeçuda e a tartaruga de pente podem ser
encontrados principalmente no litoral norte do estado da Bahia, nordeste do Brasil,
região que representa a principal área de desova para as duas espécies e onde as
taxas de hibridização chegam até 42% da população já analisada (LARA-RUIZ et al.,
2006; SOARES et al., 2018). Onde, a maior parte dos híbridos possui características
morfológicas da tartaruga de pente e DNA mitocondrial da tartaruga cabeçuda (LARARUIZ et al., 2006). Já híbridos de tartaruga cabeçuda e tartaruga oliva são mais
frequentes no litoral do estado de Sergipe, também no nordeste Brasileiro, onde a taxa
de hibridização registrada entre as duas espécies chega a 27% da população
analisada, onde os indivíduos apresentaram morfologia de tartaruga cabeçuda e DNA
mitocondrial de tartaruga oliva (REIS; SOARES; LÔBO-HAJDU, 2010). Essas duas
regiões apresentam ampla sobreposição espacial e temporal entre atividades
reprodutivas dessas espécies, o que propicia uma maior interação entre elas,
favorecendo a hibridização (LARA-RUIZ et al., 2006).

Figura 2 – Áreas de desova e alimentação no Oceano Atlântico Sudoeste com registros de
indivíduos híbridos. Cc – Caretta caretta, Cm – Chelonia mydas, Ei – Eretmochelys imbricata,
Lo – Lepidochelys olivacea. ABR – Arquipélago de Abrolhos, ARG – Argentina, BA – Bahia, CE
– Ceará, ES – Espírito Santo, RS – Rio Grande do Sul, SE – Sergipe, URU – Uruguai.

Fonte: Elaborado pelo autor (2023).

Como consequência da alta taxa de hibridização nessas áreas de desova, vários
híbridos também já foram registrados em áreas de alimentação dessas espécies, desde
o litoral do estado do Ceará até a Argentina (BRITO et al., 2020). Consequências
dessas altas taxas de hibridização no OAS ainda não são totalmente claras, porém o
perfil genético dos híbridos indica que eles se mantêm férteis e podem se reproduzir
também com as espécies parentais (PROIETTI et al., 2014b; VILAÇA et al., 2021). A
taxa de emergência de filhotes é levemente menor entre híbridos, mas não difere
significativamente das espécies parentais (SOARES et al., 2017). Da mesma maneira, a

viabilidade de híbridos e indivíduos puros parece não diferir significativamente
(SOARES et al., 2018). Por outro lado, alguns híbridos morfologicamente identificados
como uma espécie parental parecem adotar padrões migratórios da outra espécie
(PROIETTI et al., 2014b).
Com o avanço da urbanização em áreas litorâneas e os efeitos das mudanças
climáticas na distribuição das tartarugas marinhas (FUENTES et al., 2010), o
monitoramento constante das áreas de nidificação e alimentação é fundamental para
entender como essas espécies estão sendo afetadas por esses fatores. De fato, no
Brasil a identificação e caracterização dessas áreas quanto a sua distribuição espacial e
diversidade genética são diretrizes do plano de ação para a conservação das tartarugas
marinhas (ICMBIO, 2017). Identificar e caracterizar a diversidade genética dessas áreas
é essencial para entender as conexões entre elas, padrões de migração e a dinâmica
populacional dessas espécies. Isso é de particular importância no litoral do OAS,
especialmente no Brasil, tendo em vista a alta frequência de hibridização na região
(BRITO et al., 2020). Assim, estudos nessas temáticas são importantes para elaboração
de estratégias de conservação adequadas, especialmente em espécies com hábitos
altamente migratórios, como é o caso das tartarugas marinhas, que podem estar sob
uma ampla gama de ameaças (HAWKES et al., 2009; NELMS et al., 2016; WALLACE
et al., 2013).
REFERÊNCIAS
ABREU-GROBOIS, F. A.; HORROCKS, J.; FORMIA, A.; LEROUX, R.; VELEZ-ZUAZO,
X.; DUTTON, P.; SOARES, L.; MEYLAN, P.; BROWNE, D. New mtDNA D-loop primers
which work for a variety of marine turtle species may increase the resolution of mixed
stock analysis. In: Annual Symposium on Sea Turtle Biology and Conservation, 26.,
2006, Island of Crete. Book of abstracts of the 26th Annual Symposium on Sea Turtle
Biology and Conservation. Athens: International Sea Turtle Society, 2006; p. 179.
AGUIRRE, A. A.; LUTZ, PETERL. Marine Turtles as Sentinels of Ecosystem Health: Is
Fibropapillomatosis an Indicator? EcoHealth, v. 1, n. 3, p. 275–283, set. 2004.
ALLARD, M. W. et al. Support for Natal Homing in Green Turtles from Mitochondrial
DNA Sequences. Copeia, v. 1994, n. 1, p. 34–41, 1994.

ALMEIDA, A. DE P. et al. Green turtle nesting on trindade island, Brazil: Abundance,
trends, and biometrics. Endangered Species Research, v. 14, n. 3, p. 193–201, 2011.
ARANTES, L. S. et al. New genetic insights about hybridization and population structure
of hawksbill and loggerhead turtles from Brazil. Journal of Heredity, v. 111, n. 5, p. 444–
456, 2020.
ARANTES, L. S.; VARGAS, S. M.; SANTOS, F. R. Global phylogeography of the
critically endangered hawksbill turtle (Eretmochelys imbricata). Genetics and Molecular
Biology, v. 43, n. 2, p. 1–12, 2020.
ARTHUR, K. E.; BOYLE, M. C.; LIMPUS, C. J. Ontogenetic changes in diet and habitat
use in green sea turtle (Chelonia mydas) life history. Marine Ecology Progress Series, v.
362, p. 303–311, 30 jun. 2008.
BAGDA, E.; BARDAKCI, F.; TURKOZAN, O. Lower genetic structuring in mitochondrial
DNA than nuclear DNA among the nesting colonies of green turtles (Chelonia mydas) in
the Mediterranean. Biochemical Systematics and Ecology, v. 43, p. 192–199, ago. 2012.
BASS, A. L.; LAGUEUX, C. J.; BOWEN, B. W. Origin of Green Turtles, Chelonia mydas,
at “Sleeping Rocks” off the Northeast Coast of NicaraguaSource: Copeia. [s.l: s.n.].
Disponível em:
<http://www.jstor.orgURL:http://www.jstor.org/stable/1447360Accessed:28/08/200811:0
8>.
BJORNDAL, K. A. et al. Population structure and diversity of brazilian green turtle
rookeries based on mitochondrial DNA sequences. Chelonian Conservation and
Biology, v. 5, n. 2, p. 262–268, dez. 2006.
BOLTEN, A. B. Variation in sea turtle life history patterns: neritic vs oceanic
developmental stages. In: LUTZ, P. L.; MUSICK, J. A.; WYNEKEN, J. (Eds.), The
Biology of Sea Turtles Volume II. CRC Press, Boca Raton, 2003, p. 243–257.
BOWEN, B. W. et al. Global population structure and natural history of the green turtle
(Chelonia mydas) in terms of matriarchal phylogeny. Evolution, v. 46, n. 4, p. 865–881,
1992.
BOWEN, B. W. et al. Trans-Pacific migrations of the loggerhead turtle (Caretta caretta)
demonstrated with mitochondrial DNA markers. Population Biology, v. 92, p. 3731–3734,
1995.
BOWEN, B. W. et al. Global phylogeography of the ridley sea turtles (Lepidochelys spp.)
as inferred from mitochondrial DNA sequences. Genetica, v. 101, p. 179–189, 1998.

BOWEN, B. W.; MEYLANT, A. B.; AVISE, J. C. An odyssey of the green sea turtle:
Ascension Island revisited (mitochondrial DNA/intraspecific phylogeny/gene flow/genetic
distance). Proceedings of the Natiotal Academy of Sciences, v. 86, p. 573–576, 1989.
BOWEN, B. W.; NELSON, W. S.; AVISE, J. C. A molecular phylogeny for marine turtles:
Trait mapping, rate assessment, and conservation relevance. Proceedings of the
National Academy of Sciences, v. 90, p. 5574–5577, 1993.
BRITO, C. et al. Combined use of mitochondrial and nuclear genetic markers further
reveal immature marine turtle hybrids along the south western Atlantic. Genetics and
Molecular Biology, v. 43, n. 2, p. 1–11, 2020.
CARR, A. F. So Excellent a Fishe: A Natural History of Sea Turtles. New York: Scribner,
1967.
CARRERAS, C. et al. The genetic structure of the loggerhead sea turtle (Caretta
caretta) in the Mediterranean as revealed by nuclear and mitochondrial DNA and its
conservation implications. Conservation Genetics, v. 8, n. 4, p. 761–775, 2007.
COLMAN L. P. et al. Thirty years of leatherback turtle Dermochelys coriacea nesting in
Espírito Santo, Brazil, 1988−2017: reproductive biology and conservation. Endangered
Species Research, v. 39, p. 147–158, 2019.
COLMAN, L. P. et al. Assessing coastal artificial light and potential exposure of wildlife
at a national scale: the case of marine turtles in Brazil. Biodiversity and Conservation, v.
29, p. 1135–1152, 2020.
DAVENPORT, J. Temperature and the life-history strategies of sea turtles. Journal of
Thermal Biology, v. 22, n. 6, p. 479–488, 1997.
ENCALADA, S. E. et al. Phylogeography and population structure of the Atlantic and
Mediterranean green turtle Chelonia mydas: A mitochondrial DNA control region
sequence assessment. Molecular Ecology, v. 5, n. 4, p. 473–483, 1996.
FARREL, J. A. et al. Environmental DNA monitoring of oncogenic viral shedding and
genomic profiling of sea turtle fibropapillomatosis reveals unusual viral dynamics.
Communications Biology, v. 4, p. 565, 2021.
FITZSIMMONS, N. N. et al. Geographic Structure of Mitochondrial and Nuclear Gene
Polymorphisms in Australian Green Turtle Populations and Male-Biased Gene Flow.
Genetics, v. 147, p. 1843–1854, 1997.
FITZSIMMONS, N. N.; MORITZ, C.; MOORE, S. S. Conservation and Dynamics of
Microsatellite Loci over 300 Million Years of Marine Turtle Evolution. Molecular Biology
and Evolution, v. 12, n. 3, p. 432–440, 1995.

FRAZER, N. B. Survival from egg to adulthood in a declining population of loggerhead
turtles, Caretta caretta. Herpetologica, v. 42, n. 1, p. 47–55, 1986.
FUENTES, M. M. P. B. et al. Potential impacts of projected sea-level rise on sea turtle
rookeries. Aquatic Conservation: Marine and Freshwater Ecosystems, v. 20, n. 2, p.
132–139, 2010.
FUENTES, M. M. P. B.; LIMPUS, C. J.; HAMANN, M. Vulnerability of sea turtle nesting
grounds to climate change. Global Change Biology, v. 17, p. 140–153, 2011.
GEYER, R.; JAMBECK, J. R.; LAW, K. L. Production, use, and fate of all plastics ever
made. Science Advances, v. 3, p. e1700782, 2017.
HAMMAN, M.; LIMPUS, C. J.; OWENS, D. W. Reproductive cycles of males and
females. In: LUTZ, P. L.; MUSICK, J. A.; WYNEKEN, J. (Eds.), The Biology of Sea
Turtles Volume II. CRC Press, Boca Raton, 2003, p. 135–161.
HAWKES, L. A. et al. Climate change and marine turtles. Endangered Species
Research, v. 7, p. 137–154, 2009.
HAYS, G. C. et al. Population viability at extreme sex-ratio skews produced by
temperature dependent sex determination. Proceedings of the Royal Society B:
Biological Sciences, v. 284, n. 1848, p. 1–7, 2017.
HAYS, G. C.; MAZARIS, A. D.; SCHOFIELD, G. Different male vs. female breeding
periodicity helps mitigate offspring sex ratio skews in sea turtles. Frontiers in Marine
Science, v. 1, p. 1–9, 2014.
HOWARD, R.; BELL, I.; PIKE, D. A. Thermal tolerances of sea turtle embryos: Current
understanding and future directions. Endangered Species Research, v. 26, p. 75–86,
2014.
ICMBio (2017) Plano de Ação Nacional para Conservação das Tartarugas Marinhas.
https://www.icmbio.gov.br/portal/faunabrasileira/plano-de-acao-nacional-lista/841-planode-acao-nacional-para-a-conservacao-das-tartarugas-marinhas.
Intergovernmental Panel on Climate Change (2021). Climate Change 2021: Synthesis
Report. Contribution of Working Group III to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change [Core Writing Team]. Ed. by Jager-Waldau
A and Sapkota T. IPCC, Geneva, Switzerland.
JONES, K. et al. A review of fibropapillomatosis in Green turtles (Chelonia mydas). The
Veterinary Journal, v. 212, p. 48–57, 2016.

JORDÃO, J. C. et al. Green turtle (Chelonia mydas) genetic diversity at Paranaguá
Estuarine complex feeding grounds in Brazil. Genetics and Molecular Biology, v. 38, n.
3, p. 346–352, 2015.
LAHANAS, P. N. et al. Molecular evolution and population genetics of Greater
Caribbean green turtles (Chelonia mydas) as inferred from mitochondrial DNA control
region sequences. Genetica, v. 94, p. 57, 1994.
LAHANAS, P. N. et al. Genetic composition of a green turtle (Chelonia mydas) feeding
ground population: evidence for multiple origins. Marine Biology, v. 130, p. 345–352,
1998.
LARA-RUIZ, P. et al. Extensive hybridization in hawksbill turtles (Eretmochelys
imbricata) nesting in Brazil revealed by mtDNA analyses. Conservation Genetics, v. 7, n.
5, p. 773–781, 2006.
LEWISON, R. L. et al. Understanding impacts of fisheries bycatch on marine
megafauna. Trends in Ecology and Evolution, v. 19, n. 11, p. 598–604, 2004.
LEWISON, R. L. et al. Global patterns of marine mammal, seabird, and sea turtle
bycatch reveal taxa-specific and cumulative megafauna hotspots. Proceedings of the
National Academy of Sciences of the United States of America, v. 111, n. 14, p. 5271–
5276, 2014.
LIMPUS, C. J. A Biological Review of Australian Marine Turtles. 5. Flatback turtle,
Natator depressus (Garman). Report for the Environmental Protection Agency
Queensland. p. 1–54, 2007.
LOHMANN, K. J.; LOHMANN, C. M. F.; BROTHERS, J. R.; PUTMAN, N. F., 2013. Natal
homing and imprinting in sea turtles. In: WYNEKEN, J.; LOHMANN, K. J.; MUSIK, J. A.
The Biology of Sea Turtles, Volume III. Florida: CRC Press, 2013, p. 59–77.
LUKE, K. et al. Origins of green turtle (Chelonia mydas) feeding aggregations around
Barbados, West Indies. Marine Biology, v. 144, n. 4, p. 799–805, 2004.
LUSCHI, P. et al. A review of long-distance movements by marine turtles, and the
possible role of ocean currents. OIKOS, v. 103, p. 293–302, 2003.
MANSFIELD, K. L. et al. First satellite tracks of neonate sea turtles redefine the “lost
years” oceanic niche. Proceedings of the Royal Society B: Biological Sciences, v. 281,
n. 1781, 2014.
MARCOVALDI, M. A. et al. Fifteen years of Hawksbill Sea Turtle (Eretmochelys
imbricata) nesting in Northern Brazil. Chelonian Conservation and Biology, v. 6, n. 2, p.
223–228, 2007.

MARCOVALDI, M. Â.; MARCOVALDI, G. G. Marine turtles of Brazil: The history and
structure of Projeto TAMAR-IBAMA. Biological Conservation, v. 91, n. 1, p. 35–41, 1999.
MARCOVALDI, M.; CHALOUPKA, M. Conservation status of the loggerhead sea turtle
in Brazil: an encouraging outlook. Endangered Species Research, v. 3, p. 133–143,
2007.
MÁRQUEZ, R. M. Status and Distribution of the Kemp’s Ridley Turtle, Lepidochelys
kempii, in the Wider Caribbean Region. In: ECKERT, K.L. AND ABREU GROBOIS, F.A.
(Eds.). Proceedings, Marine Turtle Conservation in the Wider Caribbean Region: A
Dialogue for Effective Regional Management. Santo Domingo: WIDECAST, IUCNMTSG, WWF, and UNEP-CEP, 2001, p. 46–51.
MEDEIROS, L. et al. Tracking green turtle nesting trends at a remote oceanic rookery.
Marine Biology, n. 69, p. 68, 2022.
MITCHELL, N. J.; JANZEN, F. J. Temperature-Dependent sex determination and
contemporary climate change. Sexual Development, v. 4, n. 1–2, p. 129–140, 2010.
MORTIMER, J. A.; CARR, A. Reproduction and migration of the Ascension Island green
turtle (Chelonia mydas). Copeia, v. 1, p. 103-113, 1987.
NARO-MACIEL, E. et al. Testing dispersal hypotheses in foraging green sea turtles
(Chelonia mydas) of Brazil. Journal of Heredity, v. 98, n. 1, p. 29–39, 2007.
NARO-MACIEL, E. et al. The interplay of homing and dispersal in green turtles: A focus
on the southwestern atlantic. Journal of Heredity, v. 103, n. 6, p. 792–805, 2012.
NARO-MACIEL, E. et al. From refugia to rookeries: Phylogeography of Atlantic green
turtles. Journal of Experimental Marine Biology and Ecology, v. 461, p. 306–316, 2014.
NELMS, S. E. et al. Plastic and marine turtles: A review and call for research. ICES
Journal of Marine Science, v. 73, n. 2, p. 165–181, 2016.
PATRÍCIO, A. R., VARELA, M. R., BARBOSA, C., BRODERICK, A. C., CATRY, P.,
HAWKES, L. A., REGALLA, A., et al. 2019. Climate change resilience of a globally
important sea turtle nesting population. Global Change Biology, v. 25, p. 522–535.
PLOTKIN, P. Adult Migrations and Habitat Use. In: LUTZ, P. L.; MUSICK, J. A.;
WYNEKEN, J. (Eds.). The Biology of Sea Turtles, Volume II. Florida: CRC Press, 2003,
p. 225–241.
PROIETTI, M. C. et al. Green turtle Chelonia mydas mixed stocks in the western South
Atlantic, as revealed by mtDNA haplotypes and drifter trajectories. Marine Ecology
Progress Series, v. 447, n. 1, p. 195–209, 2012.

PROIETTI, M. C. et al. Genetic structure and natal origins of immature hawksbill turtles
(Eretmochelys imbricata) in Brazilian waters. PLoS ONE, v. 9, n. 2, 2014a.
PROIETTI, M. C. et al. Hawksbill × loggerhead sea turtle hybrids at Bahia, Brazil: Where
do their offspring go? PeerJ, v. 2014, n. 1, p. 1–14, 2014b.
PROSDOCIMI, L. et al. Genetic composition of green turtle feeding grounds in coastal
waters of Argentina based on mitochondrial DNA. Journal of Experimental Marine
Biology and Ecology, v. 412, p. 37–45, 2012.
REICH, K. J.; BJORNDAL, K. A.; BOLTEN, A. B. The “lost years” of green turtles: Using
stable isotopes to study cryptic lifestages. Biology Letters, v. 3, n. 6, p. 712–714, 2007.
REIS, E. C. et al. Genetic composition, population structure and phylogeography of the
loggerhead sea turtle: Colonization hypothesis for the Brazilian rookeries. Conservation
Genetics, v. 11, n. 4, p. 1467–1477, 2010.
REIS, E. C.; SOARES, L. S.; LÔBO-HAJDU, G. Evidence of olive ridley mitochondrial
genome introgression into loggerhead turtle rookeries of Sergipe, Brazil. Conservation
Genetics, v. 11, n. 4, p. 1587–1591, 2010.
RIZZI, M. et al. Ingestion of plastic marine litter by sea turtles in southern Brazil:
abundance, characteristics and potential selectivity. Marine Pollution Bulletin, v. 140, p.
536–548, 2019.
RODRÍGUEZ, Y. et al. Litter ingestion and entanglement in green turtles: An analysis of
two decades of stranding events in the NE Atlantic. Environmental Pollution, v. 298,
2022.
ROSSI, S. et al. Challenges in evaluating the severity of fibropapillomatosis: A proposal
for objective index and score system for green sea turtles (Chelonia mydas) in Brazil.
PLoS ONE, v. 11, n. 12, 2016.
SALMON, M. Artificial night lighting and sea turtles. Biologist, v. 50, n. 4, p. 163–168,
2003.
SANTOS, R. G. et al. Relationship between fibropapillomatosis and environmental
quality: A case study with Chelonia mydas off Brazil. Diseases of Aquatic Organisms, v.
89, n. 1, p. 87–95, 2010.
SANTOS, R. G. et al. The anti-predator role of within-nest emergence synchrony in sea
turtle hatchlings. Proceedings of the Royal Society B: Biological Sciences, v. 283, n.
1834, 2016.

SANTOS, R. G.; MACHOVSKY-CAPUSKA, G. E.; ANDRADES, R. Plastic ingestion as
an evolutionary trap: Toward a holistic understanding. Science, v. 373, p. 56–60, 2021.
SHAMBLIN, B. M. et al. Tetranucleotide markers from the loggerhead sea turtle (Caretta
caretta) and their cross-amplification in other marine turtle species. Conservation
Genetics, v. 10, n. 3, p. 577–580, 2009.
SHAMBLIN, B. M. et al. Mitogenomic sequences better resolve stock structure of
southern Greater Caribbean green turtle rookeries. Molecular Ecology, v. 21, n. 10, p.
2330–2340, 2012.
SHAMBLIN, B. M. et al. Deeper Mitochondrial Sequencing Reveals Cryptic Diversity and
Structure in Brazilian Green Turtle Rookeries. Chelonian Conservation and Biology, v.
14, n. 2, p. 167–172, 2015.
SHAMBLIN, B. M. et al. Mexican origins for the Texas green turtle foraging aggregation:
A cautionary tale of incomplete baselines and poor marker resolution. Journal of
Experimental Marine Biology and Ecology, v. 488, p. 111–120, 2017.
SILVA, A. C. C. D. et al. Nesting biology and conservation of the olive ridley sea turtle
(Lepidochelys olivacea) in Brazil, 1991/1992 to 2002/2003. Journal of the Marine
Biological Association of the United Kingdom, v. 87, n. 4, p. 1047–1056, 2007.
SOARES, L. S. et al. Comparison of reproductive output of hybrid sea turtles and
parental species. Marine Biology, v. 164, n. 1, 2017.
SOARES, L. S. et al. Effects of hybridization on sea turtle fitness. Conservation
Genetics, v. 19, n. 6, p. 1311–1322, 2018.
STEWART, K. R.; WYNEKEN, J. PREDATION RISK TO LOGGERHEAD HATCHLINGS
AT A HIGH-DENSITY NESTING BEACH IN SOUTHEAST FLORIDA. Bulletin of Marine
Science, v. 74, n. 2, p. 325–335, 2004.
THOMÉ, J. C. A. et al. Nesting biology and conservation of the leatherback sea turtle
(Dermochelys coriacea) in the State of Espírito Santo, Brazil, 1988-1989 to 2003-2004.
Chelonian Conservation and Biology, v. 6, n. 1, p. 15–27, 2007.
TIKOCHINSKI, Y. et al. Mitochondrial DNA STR analysis as a tool for studying the green
sea turtle (Chelonia mydas) populations: The Mediterranean Sea case study. Marine
Genomics, v. 6, p. 17–24, 2012.
TRUSCOTT, Z.; BOOTH, D. T.; LIMPUS, C. J. The effect of on-shore light pollution on
sea-turtle hatchlings commencing their off-shore swim. Wildlife Research, v. 44, n. 2, p.
127–134, 2017.

VARGAS, S. M. et al. Revisiting the genetic diversity and population structure of the
critically endangered leatherback turtles in the South-west Atlantic Ocean: Insights for
species conservation. Journal of the Marine Biological Association of the United
Kingdom, v. 99, n. 1, p. 31–41, 2019.
VILAÇA, S. T. et al. Divergence and hybridization in sea turtles: Inferences from genome
data show evidence of ancient gene flow between species. Molecular Ecology, n. 30, p.
6178–6192, 2021.
VILAÇA, S. T. et al. Global phylogeography of ridley sea turtles (Lepidochelys spp.):
evolution, demography, connectivity, and conservation. Conservation Genetics, n. 23, p.
995–1010, 2022.
WALLACE, B. P. et al. Regional Management Units for Marine Turtles: A Novel
Framework for Prioritizing Conservation and Research across Multiple Scales. PLoS
ONE, v. 5, n. 12, p. 1–11, 2010a.
WALLACE, B. P. et al. Global patterns of marine turtle bycatch. Conservation Letters, n.
3, p. 131–142, 2010b.
WALLACE, B. P. et al. Global conservation priorities for Marine turtles. PLoS ONE, v. 6,
n. 9, 2011.
WALLACE, B. P. et al. Impacts of fisheries bycatch on marine turtle populations
worldwide: Toward conservation and research priorities. Ecosphere, v. 4, n. 3, p. 1–49,
2013.
WITT, M. J. et al. Predicting the impacts of climate change on a globally distributed
species: The case of the loggerhead turtle. Journal of Experimental Biology, v. 213, n. 6,
p. 901–911, 2010.
YETSKO, K. et al. Molecular characterization of a marine turtle tumor epizootic, profiling
external, internal and postsurgical regrowth tumors, v. 4, p. 152, 2021.

3 CAPÍTULO 1
SEX RATIOS AND NATAL ORIGINS OF GREEN TURTLES FROM FEEDING
GROUNDS IN THE SOUTHWEST ATLANTIC OCEAN1
João Paulo Felix Augusto de Almeida, Robson Guimarães dos Santos, Tamí Mott

Abstract
Potential effects of climate change on living species are a widely debated topic. Species
with temperature-dependent sex determination can be particularly impacted by warmer
temperatures because unbalanced sex ratios could threaten population viability. In sea
turtles, sex ratio estimates have highlighted the potential feminization of current
populations, which tends to increase since warmer temperatures would generate more
females. Here, we evaluated temporal variation in sex ratios of green turtles from
feeding grounds of the Southwest Atlantic Ocean (SWA) using data from a seven-year
time frame, from 2010 to 2016. We also evaluated natal origins of female and male
green turtles from SWA based on mitochondrial DNA. Sex ratios of juvenile and adult
green turtles were generally female-skewed across collection years. We identified 11
haplotypes in northeast SWA, and haplotype composition of females and males was
slightly different. Likewise, estimated natal origins of females and males were divergent.
Ascension Island was estimated to be the main source of females while Guinea Bissau
was estimated to be the main source of males. Studies evaluating natal origins of
females and males independently are rare, this study provides one of the first
assessments of the kind for green turtles in the SWA.
Keywords: Brazil, Chelonia mydas, population genetics, sea turtles, warming
temperatures

1. Artigo publicado no periódico ICES Journal of Marine Science, qualis A1, percentil 89% pelo Scopus.
Almeida, J.P.F.A.A.; Santos, R.G.; Mott, T (2021). Sex ratios and natal origins of green turtles from
feeding grounds in the Southwest Atlantic Ocean. ICES Journal of Marine Science, 78(5), 1840–1848. doi:
10.1093/icesjms/fsab093.

3.1 Introduction
Marine ecosystems have been historically transformed by human activities; no
area in the world is unaffected and many are strongly impacted by multiple threats
(Halpern et al., 2008). As a result, marine wildlife populations have been deeply affected
both at local and global scales (McCauley et al., 2015). In addition to a widespread
habitat degradation and overexploitation, climate change will likely accelerate population
declines in the next decades (Harnick et al., 2012). Although a pattern of historical
decline is shared among marine animals (Lotze et al., 2006), species susceptibility to
anthropogenic threats may vary.
The impact of this rapidly changing world on migratory species such as sea turtles
might be aggravated by aspects of their biology (Robinson et al., 2009). Sea turtles are
long-lived animals with a life cycle characterized by multiple habitats shifts, including
direct land use during nesting activities, which increases their vulnerability (McCauley et
al., 2015). Additionally, sea turtles tend to use the same reproduction sites across
mating seasons and females tend to nest on the same beaches they were born
(philopatry), which can make them bound to potentially threatened areas (Hamann et al.,
2013). They also have temperature-dependent sex determination (TSD), where warmer
incubation temperatures generate more females (Hamann et al., 2013). Thus, rising
temperatures at nesting beaches can potentially affect sex ratios, which could eventually
compromise population viability (Laloë et al., 2016).
Understanding sex ratio variations is key to comprehend sea turtle population
dynamics, especially in a world threatened by climate change. However, determining
sex of individuals is logistically difficult and cannot always be determined through
morphology (Wibbels, 2003). Because of these limitations, most of the information on
sex ratio available for sea turtles is based on indirect methods, such as measuring of
sand and nest temperatures (e.g. Godfrey et al., 1996; Laloë et al., 2016, 2020). So far,
sex ratios at nesting sites (NS) around the globe are usually female-skewed, especially
in warmer beaches where females can represent over 90% of new hatchlings (e.g.

Godley et al., 2002; Hays et al., 2014). Only a few NSs are reported to have unbiased or
male-biased sex ratios (e.g. Esteban et al., 2016; Patrício et al., 2017b; Laloë et al.,
2020).
Sex ratios in feeding grounds (FG) are more difficult to access, but they can also
provide important information about population dynamics of sea turtles (e.g. Casale et
al., 2006; Maffucci et al., 2013). While assessments of NSs provide sex ratios of
hatchlings on specific nesting seasons; FGs harbour individuals of different age classes,
which allows the investigation of sex ratios on a wider temporal spectrum (Maffucci et
al., 2013). Furthermore, because of the philopatric behaviour of females, a genetic
structure can usually be detected in the matrilineal inherited mitochondrial DNA
(mtDNA). This genetic structure can be used to trace natal origins of individuals found in
FGs. Hence, when the sex of individuals in FGs is known, it is possible to estimate natal
origins of females and males independently and thus help to investigate sex ratios in
local NSs.
Recently, Jensen et al. (2018) used genetic data of individuals with known sex to
investigate sex ratio of green turtles, Chelonia mydas (Linnaeus, 1758), using samples
from FGs in the Great Barrier Reef (GBR), Australia. They found that sex ratio of green
turtles from the northern GBR, one of the largest nesting areas for green turtles in the
world, was highly female-skewed (Jensen et al., 2018). This result raises concerns
about other green turtle nesting sites, but also demonstrates the usefulness of using
data from FGs to investigate local sex ratios.
The Southwest Atlantic Ocean (SWA) is an important region for green turtles,
harbouring two of the main NSs in the Atlantic (Ascension Island and Surinam) and it is
considered to have high levels of threat to sea turtles (Wallace et al., 2011). Until now,
genetic studies of green turtles in the SWA using individuals with known sex are scarce.
Studying population genetics of females and males independently can provide important
information on population dynamics and help to identify male-producing NSs in the
region, which are increasingly important due to the current trend of feminization of

populations (Hays et al., 2014). The identification of NSs that produce mainly or
exclusively females is also important to help understand local environmental conditions
surrounding extremely skewed sex ratios. This information can be valuable to planning
conservation strategies that take into consideration the effects of climate change on
green turtle populations (Laloë et al., 2020).
Here, we compile historical data of green turtles from FGs in the SWA and
discuss spatiotemporal variations in sex ratios. Additionally, we evaluate genetic data
and determine natal origins of sexed specimens of an FG in north-eastern SWA. Our
main goals were to evaluate temporal changes in female-male proportions as well as to
determine genetic composition of green turtles from north-eastern SWA in order to
answer the following questions: i) did sex ratios in the SWA change in the recent years?;
ii) is there geographic variation in sex ratios within the SWA? iii) are there differences in
natal origins of female and male green turtles feeding in north-eastern SWA? And if so,
could that be an indicative of biased sex ratios at source NSs?
3.2 Materials and Methods
3.2.1 Feeding grounds sex ratios
Data from stranded green turtles were obtained from beach monitoring projects
performed between 2010 and 2016 in FGs of two geographical regions in north-eastern
and one in south-eastern Brazil (Fig. 1). These projects were established by the Instituto
Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA) as a
measure to evaluate environmental impact during the implementation of activities that
might alter the surrounding natural environment. Feeding grounds in north-eastern coast
encompassed five states and are henceforth denominated Northeast 1 (along the coast
of Ceará and Rio Grande do Norte States) and Northeast 2 (along the coast of Alagoas,
Sergipe and Bahia States). Feeding grounds in south-eastern, henceforth Southeast,
encompassed the coast of Espírito Santo State (Fig. 1, Supplementary Table S1). In

total, we used 3465 records with information on location, date, sex (determined through
gonadal inspection) and curved carapace length (CCL) of each stranded specimen.

Figure 1. Green turtle sampling included in this study. Areas in gray represent feeding grounds included in
sex ratio analyses. Area in black denotes feeding ground included for genetic analyses. White polygons
indicate nesting sites used as possible sources in genetic analyses. Feeding grounds: AL – Alagoas, BA –
Bahia, CE – Ceará, ES – Espírito Santo, RN – Rio Grande do Norte, SE – Sergipe. Nesting sites: AI –
Ascension Island, AV – Aves Island, BK – Bioko, CB – Cuba, CR – Costa Rica, FL – Florida, FN –
Fernando de Noronha, GB – Guinea Bissau, MX – Mexico, RA – Rocas Atoll, STP – São Tomé and
Principe, SU – Surinam, TR – Trindade Island.

We evaluated sex ratio variations throughout collection years by estimating mean
sex ratio among all FGs within each year and applying a Pearson chi-squared test.
Subsequently, as we did not detect differences in sex ratios throughout the years (see
results), we combined the data from different collection years and grouped females and
males into three size classes: juveniles recently recruited to the neritic zone (CCL <40
cm), older juveniles (CCL 40.1–90 cm) and adults (CCL >90 cm). Sizes of recently

recruited juveniles were determined conservatively based on the approximate CCL of
the smallest individuals recorded in different FGs in the Atlantic (19–36 cm; Goshe et al.,
2010; Lenz et al., 2017; Reich et al., 2007). As estimated growth rates of South Atlantic
green turtles with CCL between 30–39.9 cm is around 3.89cm per year (Lenz et al.,
2017), we expect that individuals with CCL <40 cm had been recruited to the neritic
zone only over the past few years. Size of adults was determined based on information
of the smallest nesting females at Trindade NS (around 90 cm; Almeida et al., 2011).
Data from age estimation and growth rates indicate that green turtles in the
Atlantic are usually two to seven years old when they recruit to the neritic zone and over
30 years old when they reach sexual maturity (Goshe et al., 2010; Lenz et al., 2017).
Thus, by grouping our samples within these three size classes we should have sex ratio
estimates for recent years (specimens with CCL <40 cm), for around seven to 30 years
(specimens with CCL 40.1–90 cm) and for over 30 years (specimens with CCL >90 cm).
It is important to highlight that the size classes we used are not definitive and that the
size at which green turtles recruit to neritic zones or reach sexual maturity might vary in
different regions (Goshe et al., 2010).
We estimated mean sex ratio in the SWA for each size class using data from all
FGs. We then evaluated differences in sex ratios among size classes using a chi-square
goodness of fit test. Finally, we tested if sex ratio within each FG differed from the
estimated mean sex ratio for the SWA for each size class also using chi-squared
goodness of fit tests. All analyses were performed using the software R 3.5.1 and the
native package stats (R Core Team, 2018).
3.2.2 Genetic composition and natal origins of female and male green turtles
For molecular analyses, we used muscle samples from 146 specimens (CCL 23–
115 cm), of which 89 were from females and 57 were from males. Samples were
collected from stranded green turtles found along the coast of Alagoas State between
May 2018 and March 2020, covering approximately 230 km of coastline in north-eastern

Brazil (Fig. 1). All specimens were dead, which allowed sex determination through direct
inspection of the gonads. Samples were stored in ethanol 92% and kept at -18°C.
Total genomic DNA was extracted using phenol-chloroform method (Sambrook et
al., 1989), and a fragment of approximately 800 base pairs (bp) of the mitochondrial
control region was amplified through 25 µl polymerase chain reactions using the primers
LCM15382 and H950 (Abreu-Grobois et al., 2006). Reactions consisted of 20.8 µl of
1XMaster Mix PCR Buffer with 0.4 mM of each dNTP and 3 mM of MgCl2, 1.0 µl of each
primer (10pmol); 2 µl of DNA template (>20ng/µl) and 0.2 µl of Taq DNA polymerase
(5U/µl). Amplifications were performed as follows: initial denaturation at 94°C for 7 min
followed by 35–40 cycles of denaturation at 94°C for 30 sec, annealing at 57°C for 30
sec, extending at 72°C for 1 min and a final extending at 72°C for 5–7 min. Posteriorly,
samples were purified with sodium acetate and isopropanol to remove PCR residuals
and sequenced in both directions using Sanger sequencing.
DNA sequences were submitted to the BLAST tool at GenBank database to
check for contamination and subsequently edited using BioEdit 7.0.5.3 (Hall, 2011).
Sequences were aligned using MAFFT 7.310 (Katoh and Standley, 2013), and trimmed
to a 490bp fragment for better comparison with nesting sites. Haplotypes were identified
based on the Archie Carr Center for Sea Turtle Research haplotype database
(https://accstr.ufl.edu/). Haplotype (h) and nucleotide (θπ) diversities were estimated
using DnaSP 5.10 (Librado and Rozas, 2009), and haplotypes relationships were
evaluated with median-joining haplotype networks (Bandelt et al., 1999) reconstructed
with Network 10.1 (https://www.fluxus-engineering.com). Genetic differentiation between
females and males was evaluated using an Analysis of Molecular Variance (AMOVA)
with 10 000 permutations implemented in Arlequin 3.5.2.2 (Excoffier and Lischer, 2010).
Natal origins of female and male green turtles were estimated independently
based on many-to-one mixed stock analyses (MSA), which allows to determine the
relative contribution of multiple sources (NSs) to a single mixed population (FG) based
on frequency and relative proportions of haplotypes using Bayesian methods (Pella and

Masuda, 2001). Data from the following nesting sites were used: Florida and Mexico
(Encalada et al., 1996), Aves Island and Surinam (Bjorndal et al., 2006; Shamblin et al.,
2012); Ascension Island (Formia et al., 2007); Costa Rica (Bjorndal et al., 2005); Cuba
(Ruiz-Urquiola et al., 2010); Guinea Bissau (Patrício et al., 2017a); Rocas Atoll,
Fernando de Noronha and Trindade Island (Bjorndal et al., 2006); São Tomé and
Principe and Bioko (Formia et al., 2006). Data from Rocas Atoll and Fernando de
Noronha were pooled because of the small sample size and because these two NSs are
geographically close and genetically similar (Bjorndal et al., 2006).
We performed MSA analyses using females and males independently. First, we
used the size of each NS (MSA1), based on the number of nesting females, as a prior
for the analyses (see Supplementary Table S2; also Seminoff et al., 2015). Second, we
considered equal weights for all NSs (MSA2), i.e. without the effect of size of NS.
Analyses were performed using BAYES (Pella and Masuda, 2001), with 12 chains per
run (equal to the number of sources [NSs]) and 50 000 iterations per chain. As default,
half of these iterations were discarded as burn-in. Chains convergence was checked
using the Gelman-Rubin criterion, considering that convergence has been achieved if
values were below 1.2 (Gelman and Rubin, 1992).
3.3 Results
3.3.1 Feeding grounds sex ratios
From the 3465 records of stranded green turtles, 2630 were females and 835
were males (for a detailed description see Supplementary Table S1). Sex ratios in the
SWA across collection years were similar, with slightly lower proportions of females in
2015 and 2016 (Fig. 2). Variation observed among years was not significant (X2 =
10.318, p = 0.112). Comparison of sex ratios among size classes revealed that sex
ratios of recently recruited (mean 3.10F:1M) and older juveniles (mean 3.27F:1M) were
similar and did not differ significantly (X2 = 0.976, p = 0.323). Sex ratio of adults was

slightly less female-biased (mean 3.03F:1M), but also did not differ significantly from
recently recruited (X2 = 0.097, p = 0.7545) or older juveniles (X2 = 0.658, p = 0.417).
When we compared sex ratios within each FG to mean sex ratios estimated for
the SWA for each size class, we found that in recently recruited juveniles sex ratios were
not different from the average value for the SWA in Northeast 2 (X2 = 0.891, p = 0.345)
and Southeast (X2 = 1.958, p = 0.161), but in Northeast 1 there were fewer females than
average (X2 = 8.199, p = 0.004; Fig 3). The number of older juvenile females was
significantly higher than the expected in Northeast 1 (X2 = 6.036, p = 0.014),
significantly lower in Northeast 2 (X2 = 10.825, p = 0.001) and no different from the
average in Southeast (X2 = 1.566, p = 0.210). The number of adult females was no
different from the expected in Northeast 1 (X2 = 3.746, p = 0.053), but lower in
Northeast 2 (X2 = 13.531, p = 0.0002, Fig 3). We did not compare proportion of females
in the Southeast to the SWA because of the low number of adults in this region (five
females and five males).

Figure 2. Proportion of female green turtles in Southwest Atlantic Ocean feeding grounds between 2010
and 2016, based on 3,465 records.

Figure 3. Proportions of female green turtle in Southwestern Atlantic Ocean feeding grounds according to
size classes. Dashed light gray, dark gray and black lines indicates mean proportion of females in recently
recruited juveniles, older juveniles and adults in the SWA, respectively.

3.3.2 Genetic composition and natal origins of female and male green turtles
We identified eleven haplotypes, of which nine were found in females and seven
in males. Five haplotypes were shared between females and males (Fig. 4,
Supplementary Table S2). The most common haplotype was CM-A8, 76.4% of females
and 64.9% of males, followed by CM-A5, 10.1% of females and 24.5% of males.
Nucleotide and haplotype diversities were slightly larger in males (θπ = 0.00234
±0.00058, h = 0.502 ±0.062) than in females (θπ = 0.00127 ±0.00023, h = 0.389
±0.063). The AMOVA analysis indicated that most genetic variation was within females
and males (95.83%), but variation between them was still significant (FST = 0.0417, p =
0.017). We obtained the longer fragment of the control region (~800 bp) from 106 of 146
specimens and only found more than one variant haplotype among CM-A8 samples:
CM-A8.1 (48 females, 28 males), CM-A8.2 (two females) and CM-A8.3 (one male). A full
list of long haplotypes is provided in supplementary Table S3.

Figure 4. Haplotype networks of female and male green turtles from Alagoas feeding ground, based on
490bp of the control region of the mitochondrial DNA.

Mixed-stock analyses considering the number of nesting females (MSA1)
estimated slightly different natal origins for females and males (Table 1). Ascension
Island was the main contributor to the composition of females (62.28%), while Guinea
Bissau contributed the most to the composition of males (40.28%). Guinea Bissau was
the second highest contributor to the composition of females (25.44%), followed by
Surinam (8.83%). For males, Ascension Island (30.44%) and Surinam (23.26%) also
had large contributions. All other NSs contributed with less than 5% for both females and
males (Table 1). When considering equally weighted priors (MSA2), contributions of NSs
were similar to MSA1, Ascension Island and Guinea Bissau contributed the most to the
composition of females (53.83% and 25.93%, respectively) and males (20.90% and
37.33%, respectively).

Table 1. Mixed-stock analyses of female and male green turtles from Alagoas feeding ground. Analyses
were performed using size of nesting sites as prior (MSA1) and equal weights priors (MSA2).
Contributions of nesting sites are in % and 2.5% and 97.5% confidence intervals are in parenthesis.
Nesting sites with the highest contribution are in bold in each MSA.

Females

Males

Stock
MSA1

MSA2

MSA1

MSA2

Florida

0.05 (0–0.58)

0.11 (0–1.16)

0.11 (0–1.29)

0.29 (0–2.94)

Mexico

0.13 (0–1.28)

0.10 (0–1.07)

0.26 (0–2.51)

0.22 (0–2.31)

Costa Rica

0.70 (0–3.27)

0.10 (0–1.06)

2.19 (0.01–7.97)

0.38 (0–3.54)

Aves Island

1.38 (0–12.43)

4.38 (0–15.11)

2.88 (0–28.85)

10.97 (0–34.31)

Surinam

8.83 (0–17.17)

5.88 (0–16.20)

23.26 (0–38.43)

15.57 (0–37.30)

Rocas/Noronha

0.03 (0)

1.13 (0–11.68)

0.17 (0)

4.23 (0–26.04)

Trindade Island

1.06 (0–15.60)

6.22 (0–28.95)

0.19 (0–2.14)

1.36 (0–11.79)

Ascension
Island

62.28 (28.99–
88.07)

53.83 (17.27–
85.80)

30.44 (1.67–
66.65)

20.90 (0–63.33)

Guinea Bissau

25.44 (1.76–
55.47)

25.93 (1.27–
56.36)

40.28 (5.94–
68.31)

37.33 (3.28–
67.13)

Bioko

0.08 (0–0.02)

1.80 (0–18.38)

0.18 (0–0.07)

7.55 (0–77.74)

São Tomé and
Principe

0.01 (0)

0.43 (0–4.35)

0.02 (0)

0.95 (0–10)

Cuba

0.01 (0–0.05)

0.10 (0–0.98)

0.03 (0–0.15)

0.27 (0–2.73)

3.4 Discussion
3.4.1 Feeding grounds sex ratios
Sex ratios in SWA feeding grounds were generally female-skewed (Fig. 3), which
is in line with most reported sex ratios for green turtles worldwide (Hays et al., 2014).
There was no significant change in sex ratios throughout collection years, suggesting
that proportion of females and males have been somewhat constant in the SWA in
recent years. Sex ratios of green turtles in the SWA have been historically investigated
through the evaluation of nesting beach temperatures within or between nesting
seasons (e.g. Broderick et al., 2001; Godley et al., 2002). Studies are mainly focused on
two major NSs, Ascension and Surinam (Mrosovsky et al., 1984; Godfrey et al., 1996;
Godley et al., 2002). Sex ratios in Ascension have been repeatedly reported as femaleskewed (Godley et al., 2002, Pintus et al., 2009) and this NS is usually reported as the
main contributor to the composition of individuals in FGs in the SWA (e.g. Naro-Maciel et
al., 2012; Proietti et al., 2012). Thus, we would expect that this high prevalence of
females would be reflected in the composition of individuals in FGs. Our results support
this observation, as the proportion of females generally exceeded 70%. Nevertheless,
implementation of genetic analyses is still required to corroborate natal origins of these
individuals.
Sex ratio of adult green turtles in SWA FGs was slightly less female-biased
(2.97F:1M), but not significantly different from juveniles. However, FGs in Northeast 2,
exhibited a noticeable lower proportion of adult females (Fig. 3). As green turtles in the
Atlantic usually take 30-40 years to reach sexual maturity (Goshe et al., 2010), the
similarity between juveniles and adults sex ratios could indicate that female output in
local NSs have been constantly high in the recent decades. This result is in agreement
with some studies that indicate that female-biased sex ratios were predominant during
the last decades in the largest NS in SWA, Ascension Island (Godley et al., 2002; Pintus
et al., 2009). However, other extrinsic factors, such as different migration periodicity and
differential death rates in female and male adults, could also be playing a role in sex

ratio variation between juveniles and adults (Maffucci et al., 2013). Furthermore, the
cause of death in stranded turtles is not always possible to determine accurately, making
it difficult to determine if local factors such as fisheries and pollution could bias our
results by having distinct impacts in females and males or even juveniles and adults.
3.4.2 Genetic composition and natal origins of female and male green turtles
Haplotype composition of females and males was slightly divergent, but the most
common haplotypes were CM-A8 and CM-A5, similarly to what is found in other FGs in
the SWA (Naro-Maciel et al., 2012; Proietti et al., 2012; Prosdocimi et al., 2012). Nesting
sites in the South Atlantic also exhibit a high prevalence of CM-A8 (e.g. Naro-Maciel et
al., 2014; Patrício et al., 2017a), while CM-A5 is more frequently found in NS closer to
the Caribbean (Shamblin et al., 2012). The occurrence of two specimens with the
haplotype CM-A42 is also noteworthy, since Guinea Bissau is the only NS to which this
haplotype was reported so far (Patrício et al., 2017a), and the presence of this haplotype
might have influenced MSA results. Considering the longer fragments, the predominant
variant of the CM-A8 (N = 79) haplotype was CM-A8.1 (96.2%, N = 76, 48 females and
28 males), similar to what was found in Rocas Atoll, Fernando de Noronha and Trindade
Island NSs (Shamblin et al., 2015), all in the SWA, as well as Guinea Bissau (Patrício et
al., 2017a). Likewise, the predominant variant of the CM-A5 (N = 14) haplotype was CMA5.1 (100%, ten females and four males), which is also the primary variant of this
haplotype in Suriname, Aves Island and Costa Rica NSs (Shamblin et al., 2012).
Relative contributions of NSs to our study area were slightly divergent between
female and male green turtles (Table 1). Considering the size of NSs (MSA1), the major
contributors to female composition were Ascension Island and Guinea Bissau. The
situation was inverted for males, with Guinea Bissau as the highest contributor followed
by Ascension Island (Table 1). While Ascension is usually reported as the major
contributor to the composition of individuals in FGs in the SWA, contributions of Guinea
Bissau are usually considered unlikely. Data from satellite tracking, tag return and
particle dispersion suggest that green turtles from Guinea Bissau most likely feed on

coastal areas of west Africa (Godley et al., 2010). However, contributions of Guinea
Bissau can still be substantial in some cases (Naro-Maciel et al., 2007; Proietti et al.,
2012). A recent report estimated that foraging aggregations in north-eastern Brazil could
receive up to 25% contribution from Guinea Bissau in foraging-centric MSAs (Patrício et
al., 2017a). This finding reinforces that individuals from this NS could reach Alagoas FG
as well. Additionally, data from hawksbill turtles, Eretmochelys imbricata (Linnaeus,
1766), also support transatlantic migration from African NSs to FGs in north-eastern
Brazil (Proietti et al., 2014).
Our results using both weighted (MSA1) and equal priors (MSA2) support a high
contribution of Guinea Bissau to the composition of individuals, particularly males, in our
study area. These results are also in agreement with estimates of balanced sex ratios in
this NS (Rebelo et al., 2012; Patrício et al., 2017b), where environmental conditions
seem to contribute to cooler nest temperatures and consequently to a higher proportion
of male hatchlings when compared to other NSs (see Patrício et al., 2019 for a detailed
discussion). In contrast, sex ratios in Ascension Island have been reported to be femaleskewed, with estimations varying between 54.2% and 99.6% of females, depending on
the specific beach (Godley et al., 2002). This is reflected in the contributions of this NS
to the composition of females in our study area, which were high in both MSA1 and
MSA2 (Table 1).
Contributions from Surinam to the composition of females and males were also
large (9.26% and 23.26%, respectively), which is agreement with reports from other FGs
(Naro-Maciel et al., 2012; Proietti et al., 2012). Nevertheless, the noticeably greater
incidence of males from this NS is noteworthy and it may be a result of the large relative
proportion of CM-A5 haplotype in male samples (24.5%) since this haplotype is
predominant in Surinam (Bjorndal et al., 2006; Shamblin et al., 2012). Sex ratios in
Surinam have also been reported to be slightly more balanced (68.4%) in relation to
some of the largest female-biased beaches in Ascension Island, although it can vary
throughout the same nesting season (Godfrey et al., 1996). Our results are concordant
with a larger output of males from this NS and seem to reinforce the hypothesis that

Surinam could be an important source of males for green turtle FGs in the SWA,
although more studies are still needed.
Male-producing NSs are sparsely scattered around the globe and most NSs of
green and other sea turtles usually exhibit a prevalence of females (for a detailed
discussion see Hays et al., 2014). In fact, one of the largest green turtle NS in the world,
the northern Great Barrier Reef, was recently revealed to be producing over 86.8%
females for the past two decades due to increased sand temperatures (Jensen et al.,
2018). This raises concerns about population status and sea turtles’ response to climate
change (Laloë et al., 2020), particularly on beaches where eggs are already incubated
above the pivotal temperature, and where effects of a warming climate can be even
more accentuated. With the imminent rise of global temperatures which, under different
scenarios, can increase over 2.0°C above current temperatures until 2100 according to
data from the Intergovernmental Panel on Climate Change (IPCC, 2014), production of
females in sea turtle NSs is expected to rise as well, which may promote the
feminization of some populations (Hays et al., 2014; Jensen et al., 2018).
The extent to which this feminization process would affect sea turtle populations
is still not completely clear (Hays et al., 2017). Undoubtedly, factors like extremely high
incubation temperatures and changes in sea surface temperature will likely affect
population dynamics of sea turtles (Hamman et al., 2013). However, some studies
suggest that the higher reproduction frequency of males and higher availability of
nesting females could, to a certain degree, compensate for female-skewed primary sex
ratios, at least while complete feminization is not reached (Hays et al., 2017; Tomillo and
Spotila, 2020). Additionally, local environmental features such as the presence of
vegetation and sand colour seem to play a role on the regulation of nest temperatures
(Patrício et al., 2019) and can be valuable tools for management of populations.
Finally, besides the direct effect of rising temperatures on sex determination of
sea turtles, a warming climate also poses other challenges, such as: i) the sea level rise,
which can compromise nesting activities by reducing the total area available for nests; ii)

increased frequency of lethal incubation temperatures and iii) changes in sea surface
temperature and ocean pH that can also affect sea turtles and associated marine
communities, such as coral reefs (Fuentes et al., 2010; Hoegh-Guldberg et al., 2019).
Moreover, other anthropogenic pressures, such as pollution of marine and coastal
environments, must also be taken into account as they can act synergistically as threats
to sea turtle populations (Fuentes et al., 2011). Thus, conservation actions that include
identification and protection of male-producing rookeries, protection of coastal
environments and ultimately direct management of nests could help mitigate some of
these harmful effects.
3.5 Concluding remarks
Studies distinguishing female and male sea turtles are rare, because determining
the sex of individuals is not always possible. Yet, these studies provide insights on
current population dynamics and help developing efficient conservation plans (Jensen et
al., 2018). Here, we provided a spatiotemporal evaluation of green turtle sex ratios in
FGs in the SWA revealing that a general pattern of female-biased sex ratios has likely
been prevalent during the last decades.
We also provided the first independent evaluation of natal origins of female and
male green turtles from a feeding ground in the SWA. We were able to detect slightly
divergent natal origins in females and males and found a high influence of Guinea
Bissau supporting previously proposed transatlantic migrations from this NS in Africa to
FGs in the SWA. Furthermore, a prevalence of males from Guinea Bissau and Surinam
highlighted the importance of these sites from a conservation standpoint. Nevertheless,
more data are still needed to shed more light on the implications of climate change on
population dynamics of green turtles.
3.6 Supplementary material
The following supplementary material is available at ICESJMS online:
Supplementary file including tables S1–S3 with data regarding composition of female

and male green turtles in feeding grounds sampled in the study, haplotypes of Alagoas
feeding ground and nesting sites included in the analyses and long haplotypes from
samples of Alagoas feeding ground.
3.7 Acknowledgments
We thank everyone involved in the beach monitoring projects as well as IBAMA
for granting access to the database. We thank members of LAMARC and LABI
laboratories for help with laboratory work. We also thank the editor and two reviewers for
constructive comments on the manuscript. This study was partially funded by PADI
Foundation (#47777/2020), Fundação Grupo Boticário de Proteção da Natureza
(#1143/20182) and Fundação de Amparo à Pesquisa do Estado de Alagoas (FAPEAL
#60030.1564/2016). This study also had the collaboration of Instituto Biota de
Conservação.

JPFAA

(#23038.023347/2016-74).

thanks
TM

FAPEAL

thanks

for

providing

Conselho

Nacional

PhD
de

scholarship

Desenvolvimento

Científico e Tecnológico - CNPq (309904/2015-3 and 312291/2018-3).
3.8 Data availability
Raw data used in sex ratio analyses is detailed in supplementary material. All
haplotypes used in genetic analysis were previously described by other studies and are
available in GenBank.
References
Abreu-Grobois, F. A., Horrocks, J., Formia, A., LeRoux, R., Velez-Zuazo, X., Dutton, P.,
Soares, L., et al. 2006. New mtDNA D-loop primers which work for a variety of marine
turtle species may increase the resolution of mixed stock analysis. In: Book of abstracts
of the 26th Annual Symposium on Sea Turtle Biology and Conservation, p. 179.
Almeida, A. P., Moreira, L. M. P., Bruno, S. C., Thomé, J. C. A., Martins, A. S., Bolten,
A. B., and Bjorndal, K. A. 2011. Green turtle nesting on trindade island, Brazil:
Abundance, trends, and biometrics. Endangered Species Research, 14: 193–201.

Bandelt, H. J., Forster, P., and Röhl, A. 1999. Median-joining networks for inferring
intraspecific phylogenies. Molecular Biology and Evolution, 16: 37-48.
Bjorndal, K. A., Bolten, A. B., and Troëng, S. 2005. Population structure and genetic
diversity in green turtles nesting at Tortuguero, Costa Rica, based on mitochondrial DNA
control region sequences. Marine Biology, 147: 1449–1457.
Bjorndal, K. A., Bolten, A. B., Moreira, L., Bellini, C., and Marcovaldi, M. A. 2006.
Population structure and diversity of brazilian green turtle rookeries based on
mitochondrial DNA sequences. Chelonian Conservation and Biology, 5: 262–268.
Broderick, A. C., Godley, B. J., and Hays, G. C. 2001. Metabolic Heating and the
Prediction of Sex Ratios for Green Turtles (Chelonia mydas). Physiological and
Biochemical Zoology, 74: 161–170.
Casale, P., Lazar, B., Pont, S., Tomás, J., Zizzo, N., Alegre, F., Badillo, J., et al. 2006.
Sex ratios of juvenile loggerhead sea turtles Caretta caretta in the Mediterranean Sea.
Marine Ecology Progress Series, 324: 281–285.
Encalada, S. E., Lahanas, P. N., Bjorndal, K. A., Bolten, A. B., Miyamoto, M. M., and
Bowen, B. W. 1996. Phylogeography and population structure of the Atlantic and
Mediterranean green turtle Chelonia mydas: A mitochondrial DNA control region
sequence assessment. Molecular Ecology, 5: 473–483.
Esteban, N., Laloë, J. O., Mortimer, J. A., Guzman, A. N., & Hays, G. C. 2016. Male
hatchling production in sea turtles from one of the world’s largest marine protected
areas, the Chagos Archipelago. Scientific Reports, 6: 1–8.
Excoffier, L., and Lischer, H. E. L. 2010. Arlequin suite ver 3.5: a new series of programs
to perform population genetics analyses under Linux and Windows. Molecular Ecology
Resources, 10: 564–567.
Formia, A., Godley, B. J., Dontaine, J. F., and Bruford, M. W. 2006. Mitochondrial DNA
diversity and phylogeography of endangered green turtle (Chelonia mydas) populations
in Africa. Conservation Genetics, 7: 353–369.
Formia, A., Broderick, A., Glen, F., Godley, B., Hays, G., and Bruford, M. 2007. Genetic
composition of the Ascension Island green turtle rookery based on mitochondrial DNA:
implications for sampling and diversity. Endangered Species Research, 3: 145–158.
Fuentes, M. M. P. B., Limpus, C. J., Hamann, M., and Dawson, J. 2010. Potential
impacts of projected sea-level rise on sea turtle rookeries. Aquatic Conservation: Marine
and Freshwater Ecosystems, 20: 132–139.

Fuentes, M. M. P. B., Limpus, C. J., and Hamann, M. 2011. Vulnerability of sea turtle
nesting grounds to climate change. Global Change Biology, 17: 140–153.
Gelman, A., and Rubin, D. B. 1992. Inference from Iterative Simulation Using Multiple
Sequences. Statistical Science, 7: 457–511.
Godfrey, M. H., Barreto, R., and Mrosovsky, N. 1996. Estimating past and present sex
ratios of sea turtles in Suriname. Canadian Journal of Zoology, 74: 267–277.
Godley, B. J., Broderick, A. C., Glen, F., and Hays, G. C. 2002. Temperature-dependent
sex determination of Ascension Island green turtles. Marine Ecology Progress Series,
226: 115–124.
Godley, B. J., Barbosa, C., Bruford, M., Broderick, A. C., Catry, P., Coyne, M. S.,
Formia, A., et al. 2010. Unravelling migratory connectivity in marine turtles using multiple
methods. Journal of Applied Ecology, 47: 769–778.
Goshe, L. R., Avens, L., Scharf, F. S., and Southwood, A. L. 2010. Estimation of age at
maturation and growth of Atlantic green turtles (Chelonia mydas) using
skeletochronology. Marine Biology, 157: 1725–1740.
Hall, T. 2011. BioEdit: An important software for molecular biology. GERF Bulletin of
Biosciences, 2: 60–61.
Halpern, B. S., Walbridge, S., Selkoe, K. A., Kappel, C. V., Micheli, F., D’Agrosa, C.,
Bruno, J. F., et al. 2008. A Global Map of Human Impact on Marine Ecosystems.
Science, 319: 948–952.
Hamann, M., Fuentes, M. M. P. B., Ban, N. C., & Mocellin, V. J. L. (2013). Climate
change and marine turtles. In The Biology of Sea Turtles Volume III, pp. 353–378. Ed.
by J. Wyneken, K. J. Lohmann, and J. A. Musick. CRC Press, Boca Raton, FL. 446 pp.
Harnick, P. G., Lotze, H. K., Anderson, S. C., Finkel, Z. V., Finnegan, S., Lindberg, D.
R., Liow, L. H., et al. 2012. Extinctions in ancient and modern seas. Trends in Ecology &
Evolution, 27: 608–617.
Hays, G. C., Mazaris, A. D., and Schofield, G. 2014. Different male vs. female breeding
periodicity helps mitigate offspring sex ratio skews in sea turtles. Frontiers in Marine
Science, 1: 1–9.
Hays, G. C., Mazaris, A. D., Schofield, G., and Laloë, J. O. 2017. Population viability at
extreme sex-ratio skews produced by temperaturedependent sex determination.
Proceedings of the Royal Society B: Biological Sciences, 284: 1–7.

Hoegh-Guldberg, O., Jacob, D., Taylor, M., Guillén Bolaños, T., Bindi, M., Brown, S.,
Camilloni, I. A., et al. 2019. The human imperative of stabilizing global climate change at
1.5°C. Science, 365.
Intergovernmental Panel on Climate Change (2014). Climate Change 2014: Synthesis
Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and
L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland.
Jensen, M. P., Allen, C. D., Eguchi, T., Bell, I. P., LaCasella, E. L., Hilton, W. A., Hof, C.
A. M., et al. 2018. Environmental Warming and Feminization of One of the Largest Sea
Turtle Populations in the World. Current Biology, 28: 154–159.
Katoh, K., and Standley, D. M. 2013. MAFFT multiple sequence alignment software
version 7: Improvements in performance and usability. Molecular Biology and Evolution,
30: 772–780.
Laloë, J. O., Esteban, N., Berkel, J., and Hays, G. C. 2016. Sand temperatures for
nesting sea turtles in the Caribbean: Implications for hatchling sex ratios in the face of
climate change. Journal of Experimental Marine Biology and Ecology, 474: 92–99.
Laloë, J. O., Monsinjon, J., Gaspar, C., Touron, M., Genet, Q., Stubbs, J., Girondot, M.,
et al. 2020. Production of male hatchlings at a remote South Pacific green sea turtle
rookery: conservation implications in a female-dominated world. Marine Biology, 167: 1–
13.
Lenz, A. J., Avens, L., and Borges-Martins, M. 2017. Age and growth of juvenile green
turtles Chelonia mydas in the western South Atlantic Ocean. Marine Ecology Progress
Series, 568: 191–201.
Librado, P., and Rozas, J. 2009. DnaSP v5: A software for comprehensive analysis of
DNA polymorphism data. Bioinformatics, 25: 1451–1452.
Lotze, H. K., Lenihan, H. S., Bourque, B. J., Bradbury, R. H., Cooke, R. G., Kay, M. C.,
Kidwell, S. M., et al. 2006. Depletion, degradation and recovery potential of estuaries
and coastal seas. Science, 312: 1806–1809.
Maffucci, F., D’Angelo, I., Hochscheid, S., Ciampa, M., de Martino, G., Travaglini, A.,
Treglia, G., et al. 2013. Sex ratio of juvenile loggerhead turtles in the Mediterranean
Sea: Is it really 1:1? Marine Biology, 160: 1097–1107.
McCauley, D. J., Pinsky, M. L., Palumbi, S. R., Estes, J. A., Joyce, F. H., and Warner, R.
R. 2015. Marine defaunation: Animal loss in the global ocean. Science, 347.

Mrosovsky, N., Dutton, P. H., & Whitmore, C. P. 1984. Sex-Ratios of 2 Species of Sea
Turtle Nesting in Suriname. Canadian Journal of Zoology, 62: 2227–2239.
Naro-Maciel, E., Becker, J. H., Lima, E. H. S. M., Marcovaldi, M. Â., and DeSalle, R.
2007. Testing dispersal hypotheses in foraging green sea turtles (Chelonia mydas) of
Brazil. Journal of Heredity, 98: 29–39.
Naro-Maciel, E., Bondioli, A. C. V., Martin, M., De Pádua Almeida, A., Baptistotte, C.,
Bellini, C., Marcovaldi, M. Â., et al. 2012. The interplay of homing and dispersal in green
turtles: A focus on the southwestern atlantic. Journal of Heredity, 103: 792–805.
Patrício, A. R., Formia, A., Barbosa, C., Broderick, A. C., Bruford, M., Carreras, C.,
Catry, P., et al. 2017a. Dispersal of green turtles from Africa’s largest rookery assessed
through genetic markers. Marine Ecology Progress Series, 569: 215–225.
Patrício, A. R., Marques, A., Barbosa, C., Broderick, A. C., Godley, B. J., Hawkes, L. A.,
Rebelo, R., et al. 2017b. Balanced primary sex ratios and resilience to climate change
inmajor marine turtle population. Marine Ecology Progress Series, 577: 189–203.
Patrício, A. R., Varela, M. R., Barbosa, C., Broderick, A. C., Catry, P., Hawkes, L. A.,
Regalla, A., and Godley, B. J. 2019. Climate change resilience of a globally important
sea turtle nesting population. Global Change Biology, 25: 522–535.
Pella, J., and Masuda, M. 2001. Bayesian methods for analysis of stock mixtures from
genetic characters. Fishery Bulletin, 99: 151–167.
Pintus, K. J., Godley, B. J., McGowan, A., & Broderick, A. C. 2009. Impact of Clutch
Relocation on Green Turtle Offspring. Journal of Wildlife Management, 73: 1151–1157.
Proietti, M. C., Reisser, J. W., Kinas, P. G., Kerr, R., Monteiro, D. S., Marins, L. F., and
Secchi, E. R. 2012. Green turtle Chelonia mydas mixed stocks in the western South
Atlantic, as revealed by mtDNA haplotypes and drifter trajectories. Marine Ecology
Progress Series, 447: 195–209.
Proietti, M. C., Reisser, J., Marins, L. F., Rodriguez-Zarate, C., Marcovaldi, M. A.,
Monteiro, D. S., Pattiaratchi, C., et al. 2014. Genetic structure and natal origins of
immature hawksbill turtles (Eretmochelys imbricata) in Brazilian waters. PLoS ONE, 9.
Prosdocimi, L., González Carman, V., Albareda, D. A., and Remis, M. I. 2012. Genetic
composition of green turtle feeding grounds in coastal waters of Argentina based on
mitochondrial DNA. Journal of Experimental Marine Biology and Ecology, 412: 37–45.
R Core Team. (2018). R: A language and environment for statistical computing. R
Foundation for Statistical Computing.

Rebelo, R., Barbosa, C., Granadeiro, J. P., Indjai, B., Novais, B., Rosa, G. M., and
Catry, P. 2012. Can leftovers from predators be reliably used to monitor marine turtle
hatchling sex-ratios? The implications of prey selection by ghost crabs. Marine Biology,
159: 613–620.
Reich, K. J., Bjorndal, K. A., and Bolten, A. B. 2007. The ‘lost years’ of green turtles:
Using stable isotopes to study cryptic lifestages. Biology Letters, 3: 712–714.
Robinson, R. A., Crick, H. Q. P., Learmonth, J. A., Maclean, I. M. D., Thomas, C. D.,
Bairlein, F., Forchhammer, M. C., et al. 2009. Travelling through a warming world :
climate change and migratory species. Endangered Species Research, 7: 87–99.
Ruiz-Urquiola, A., Riverón-Giró, F. B. F., Pérez-Bermúdez, E., Abreu-Grobois, F. A.,
González-Pumariega, M., James-Petric, B., Díaz-Fernández, R., et al. 2010. Population
genetic structure of greater Caribbean green turtles (Chelonia mydas) based on
mitochondrial DNA sequences, with an emphasis on rookeries from southwestern Cuba.
Revista de Investigaciones Marinas, 31: 33–52.
Sambrook, J., Fritsch, E.F. & Maniatis, T. 1989. Molecular cloning: a laboratory manual,
2nd edn, Cold Spring Harbor Laboratory Press, New York.
Seminoff, J. A., Allen, C. D., Balazs, G. H., Dutton, P. H., Eguchi, T., Haas, H. L.,
Hargrove, S. A. et al. 2015. Status review of the green turtle (Chelonia mydas) under the
U.S. Endangered Species Act (NOAA Tech Memo NOAA-NMFS-SWFSC-539). La Jolla,
CA: Southwest Fisheries Science Center, NOAA.
Shamblin, B. M., Bjorndal, K. A., Bolten, A. B., Hillis-Starr, Z. M., Lundgren, I., NaroMaciel, E., and Nairn, C. J. 2012. Mitogenomic sequences better resolve stock structure
of southern Greater Caribbean green turtle rookeries. Molecular Ecology, 21: 2330–
2340.
Shamblin, B. M., Dutton, P. H., Bjorndal, K. A., Bolten, A. B., Naro-Maciel, E., Santos, A.
J. B., Bellini, C., et al. 2015. Deeper mithocondrial sequencing reveals cryptic diversity
and structure in Brazilian green turtle rookeries. Chelonian Conservation and Biology,
14: 167–172.
Tomillo, P. S., and Spotila, J. R. 2020. Temperature-Dependent Sex Determination in
Sea Turtles in the Context of Climate Change: Uncovering the Adaptive Significance.
BioEssays, 42.
Wallace, B. P., DiMatteo, A. D., Bolten, A. B., Chaloupka, M. Y., Hutchinson, B. J.,
Abreu-Grobois, F. A., Mortimer, J. A., et al. 2011. Global conservation priorities for
Marine turtles. PLoS ONE, 6.

Weber, S. B., Weber, N., Ellick, J., Avery, A., Frauenstein, R., Godley, B. J., Sim, J., et
al. 2014. Recovery of the South Atlantic’s largest green turtle nesting population.
Biodiversity and Conservation, 23: 3005–3018.
Wibbels, T. (2003). Critical approaches to sex determination in sea turtles. In The
Biology of Sea Turtles Volume II, pp. 103-134. Ed. by P. Lutz, J. A. Musick, and J.
Wyneken. CRC Press, Boca Raton, FL. 455 pp.

4 CAPÍTULO 2
HYBRIDIZATION AND GENETIC CHARACTERIZATION OF SEA TURTLES IN
ALAGOAS, NORTHEASTERN BRAZIL2
João P. F. A. Almeida, Oscar K. L. Marques, Tamí Mott, Robson G. Santos

Abstract
Sea turtles are migratory species with wide geographical distributions, usually spanning
multiple countries. This characteristic, along with their complex life cycle, makes sea
turtle conservation challenging. In Brazil, continued monitoring and recent studies have
advanced the knowledge of sea turtle genetic composition and population structure.
Some of these studies have shown that hybridization is highly frequent in certain regions
along the Brazilian coast, despite being relatively rare globally. Here we investigate the
hybridization and genetic diversity of sea turtles in nesting and feeding grounds in the
state of Alagoas, northeastern Brazil, using the control region of mitochondrial DNA and
three nuclear loci. We were able to identify hybrids between four sea turtle species, but
mainly between Caretta caretta and Eretmochelys imbricata and C. caretta and
Lepidochelys olivacea. Most hybrids were readily identified using morphology and
mitochondrial DNA, but some were only detected with nuclear DNA. Apart from hybrids,
the genetic profile of each species was congruent with previous studies in Brazil.
However, one stranded E. imbricata had a haplotype (Ei-IP17) and nuclear allele
typically found in the Indo-Pacific, suggesting long distance migration for this species.
Our results indicate that hybridization events might be even more geographically spread
along the coast of Brazil and provide evidence of the connection between E. imbricata
from the Atlantic and Indo-Pacific Ocean basins.
Keywords: Population genetics, hawksbills, loggerheads, olive ridleys, green turtles,
hybrids
2. Artigo publicado no periódico Marine Biology, qualis A2, percentil 76% pelo Scopus. Almeida,
J.P.F.A.A.; Marques, O.K.L.; Mott, T.; Santos, R.G. (2023). Hybridization and genetic characterization of
sea turtles in Alagoas, northeastern Brazil. Marine Biology, 170: 14. doi: 10.1007/s00227-022-04168-y

4.1 Introduction
Sea turtles are migratory species with complex life cycles. Five of the seven sea
turtle species have wide distributions across different regions of the globe with distinctive
habitat changes throughout their lifespan (Bolten, 2003). This migratory behavior can
make conservation planning challenging, particularly when sea turtle movement patterns
span different countries, thereby requiring collaborative conservation efforts (Wallace et
al. 2010). To address this challenge and guide conservation planning at smaller scales,
regional management units (RMUs) have been suggested for sea turtles based on
distributional and ecological data (Wallace et al. 2010). Among these RMUs, the
Southwest Atlantic Ocean (SWA) exhibited considerable threat levels for sea turtle
populations (Wallace et al. 2011). Nevertheless, recent studies have reported population
recovery at some nesting sites in the region, likely due to continuing conservation efforts
in recent decades (Marcovaldi et al. 2007; Colman et al. 2019).
In Brazil, efforts on sea turtle conservation have been historically conducted by
TAMAR institute (Marcovaldi and Marcovaldi 1999). Additionally, a National Action Plan
for Sea Turtle Conservation (PAN Tartarugas Marinhas) was established by the
Brazilian government in 2010 and it is currently in its second phase (ICMBio 2017).
Research priorities established by the PAN Tartatrugas Marinhas include the
identification and monitoring of nesting and feeding grounds of the five sea turtle species
known to occur along the Brazilian coast: Caretta caretta (loggerhead turtles), Chelonia
mydas (green turtles), Dermochelys coriacea (leatherback turtles), Eretmochelys
imbricata (hawksbill turtles) and Lepidochelys olivacea (olive ridley turtles) (Marcovaldi
et al. 2007), as well as the evaluation of genetic profiles, population dynamics and
hybridization between these species (ICMBio 2017). Research on sea turtle genetic
diversity in nesting and feeding grounds in Brazil has increased in recent years (Reis et
al. 2010b; Naro-Maciel et al. 2012; Proietti et al. 2014a; Jordão et al. 2015; Vargas et al.
2019). Some studies have reported a high hybridization frequency in a few nesting sites
in northeastern Brazil (Lara-Ruiz et al. 2006; Reis et al. 2010a) however, this seems to

be rare in sea turtle populations worldwide (Brito et al. 2020). In Brazil, hybridization
rates can reach up to 42% between hawksbills and loggerheads on the coast of the
state of Bahia (Lara-Ruiz et al. 2006), and 27% between loggerheads and olive ridleys
on the coast of the state of Sergipe (Reis et al. 2010a).
A high hybridization rate in wild populations may lead to several evolutionary
outcomes, including the enhancement of genetic diversity and adaptative divergence
(Abbott et al. 2013). However, it can also compromise small populations by limiting their
growth rate through the production of inviable offspring (Todesco et al. 2016). The
consequences of these processes in sea turtles are not yet completely understood, but a
few studies have observed some differences in behavior and reproductive success
between hybrids and parental species (Proietti et al. 2014b; Soares et al. 2017; Arantes
et al. 2020a). For instance, while the clutch size of loggerhead and hawksbill hybrids has
been reported as intermediate, emergence success was lower in hybrids (Soares et al.
2017; Arantes et al. 2020a). Likewise, post-emergence behavior can also be slightly
divergent. Some hybrids, morphologically identified as one parental species, may adopt
the migration patterns of the other (Proietti et al. 2014b). Furthermore, these hybrids are
not likely to be completely inviable since genetic studies using mitochondrial DNA
(mtDNA) and nuclear DNA (nDNA) have detected crosses between F1 hybrids and
parental species (e.g., Vilaça et al. 2012; Brito et al. 2020; Arantes et al. 2020c).
Factors promoting this high hybridization frequency in Brazil require further
investigation, but the broad spatial and temporal overlapping in sea turtle breeding
activities, particularly in northeastern Brazil, certainly favors hybridization (Vilaça et al.
2012). Loggerhead and hawksbill breeding activities overlap along the northern coast of
Bahia (Fig. 1), which is the largest nesting site for both species in the SWA (Lara-Ruiz et
al. 2006, Marcovaldi et al. 2007). Loggerhead nests extend north along the coast of
Sergipe State, where they now coincide with olive ridley nests and several hybrids
between the two species have been reported in this area (Reis et al. 2010a). Olive ridley
nests extend to the southern coast of Alagoas State, where loggerhead nests become
sparse, but still occur.

The coast of Alagoas is an important area for sea turtles, harboring extensive
coral reefs that act as feeding and development grounds. Currently, five sea turtle
species can be found in this region: loggerheads, green turtles, hawksbills, leatherbacks
and olive ridleys; although leatherback sightings are rare (Oliveira et al. 2016; Bonfim et
al., 2022). Olive ridley nests are frequent in the southernmost portion of Alagoas, while
nests of the other species are present throughout the coast of this state. Green turtle
nests are rare, but this species uses the coast of Alagoas as a feeding ground
extensively. Furthermore, satellite tracking studies have shown that hawksbills and
loggerheads from Bahia, as well as olive ridleys from Sergipe nesting sites, usually feed
in Alagoas or pass through the region while migrating to northern feeding grounds (Fig.
1A, Marcovaldi et al. 2012).
These conditions may enable interactions among sea turtle species in Alagoas,
facilitating hybridization, but so far only one stranded hybrid (between a hawksbill and
loggerhead) has been reported in the region (Brito et al. 2020). Based on the conditions
presented above, our hypothesis is that the presence of hybrids in the region is highly
possible. Therefore, our main goal was to assess hybridization among sea turtle species
occurring along the coast of Alagoas using morphology, mtDNA and nDNA data.
4.2 Methods
We used 53 muscle samples collected along the coast of Alagoas (Fig. 1B) by the
Instituto Biota de Conservação between May 2019 and April 2021. Samples were taken
from stranded turtles, as well as from hatchlings found dead after emergence events.
Our sampling focused mainly on hawksbills and loggerheads as more nest samples
were available for these species, but we also included olive ridley and green turtle
samples for comparative purposes. Twenty-four samples were taken from turtles that
were morphologically identified as hawksbills (15 hatchlings and nine stranded turtles),
23 from loggerheads (14 hatchlings and nine stranded turtles), three from olive ridleys
(one hatchling and two stranded turtles) and three from green turtles (all stranded
turtles). The morphology of stranded turtles and hatchlings was assessed in the field

upon sample collection by staff of Instituto Biota de Conservação and hatchling
morphology was also examined in the laboratory. Species were morphologically
identified through the examination of scutes on the carapace, inframarginal scutes on
the plastron and prefrontal scales on the head (Pritchard and Mortimer, 1999). Each
hatchling sample was collected from a different nest.

Figure 1. Approximate distribution of the main nesting sites and movement pathways of loggerhead,
hawksbill and olive ridley turtles on the coast of the SWA (A). Solid lines indicate nesting sites and dashed
lines indicate movement pathways based on satellite tracking studies (Marcovaldi et al. 2010, 2012;
Santos et al. 2019; Soares et al. 2021). Sea turtles sampling along the coast of Alagoas State, SWA (B).

Total genomic DNA was extracted using the phenol-chloroform method
(Sambrook et al. 1989), and a fragment of 621 base pairs (bp) of the mtDNA control
region was recovered through polymerase chain reaction (PCR) using the primers
LCM15382 and H950 (Abreu-Gobrois et al. 2006). To better evaluate putative hybrids
we also employed three nuclear loci: the oocyte maturation factor mos (CMOS) using
the primers LIZ-CMOS and HCMOS-III (Kearney and Stuart 2004) and two anonymous
loci, 3061 and 109472 using the primers described by Arantes et al. (2020c). We chose
these nuclear loci because they have been shown to present informative variability
between loggerhead, hawksbill and olive ridley sea turtles (Vilaça et al 2012; Arantes et
al. 2020c). In addition to the primers we used, for the CMOS fragment, we also ran tests
with primers developed for sea turtles. We ultimately chose these primers because they
provided higher amplification success. We then aligned our CMOS sequences with
sequences from GenBank, generated with primers developed for sea turtles, to make
sure the fragments overlapped. The CMOS fragment was approximately 550bp while
3061 and 109472 were approximately 320bp each. While mtDNA was sequenced for all
samples, nDNA was only amplified for a subset of samples. This subset included all
hybrids identified through morphology and mtDNA (see results) and a few
representatives of each species (confirmed by morphology and mtDNA) for comparative
purposes (Online Resource 1). PCR reactions consisted of 20.8 µl of 1XMaster Mix PCR
Buffer with 0.4mM of each dNTP and 3mM of MgCl2, 1.0 µl of each primer (10 pmol);
0.2 µl of Taq DNA polymerase (5 U/µl) and 2 ul of DNA template (10–100 ng/µl). Control
region fragments were amplified using the following conditions: initial denaturation at
94°C for 7 min followed by 40 cycles of denaturation at 94°C for 30 s, annealing at 50°C
for 30 s, extension at 72°C for 1 min and a final extension at 72°C for 5 min. Nuclear loci
fragments were amplified using the same protocol, except for 109472 annealing
temperature which was 58°C. Negative controls were included to check for
contamination. Successfully amplified samples were purified with isopropanol and
sequenced through Sanger sequencing using the forward primer.

All sequences were checked for contamination using the BLAST tool in GenBank
and for some samples we repeated DNA extraction, PCR and sequencing to double
check our results. We edited the sequences using Bioedit v7.1.3.0 (Hall 1999) and
aligned them with MAFFT v7 using the L-INS-i algorithm (Katoh and Standley 2013).
Mitochondrial haplotypes were identified using the Archie Carr Center for Sea Turtle
Research database (https://accstr.ufl.edu/resources/mtdna-sequences/) and nuclear
sequences

were

identified

using

the

GenBank

database

(https://www.ncbi.nlm.nih.gov/genbank/). Nuclear alleles were reconstructed using the
PHASE algorithm implemented in DNAsp v5 (Librado and Rozas 2009). For the
purposes of this study, we considered a specimen to be a hybrid when it had the
morphology of one species and mtDNA or nDNA of a different species. Additionally, we
used nDNA to perform an assignment analysis to determine the most likely association
and generation of hybrids. We performed this analysis using three different species
pairs: hawksbills and loggerheads, loggerheads and olive ridleys, and hawksbills and
olive ridleys. The remaining species were not considered because of their small sample
size (see results and Online Resource 1). The analysis was performed using snapclust
as implemented in the R package adegenet (Jombart 2008, R Core Team 2021). For
each analysis, we set the number of expected clusters to two (k=2), indicated the
presence of hybrids between each species pair (hybrids=TRUE) and specified the
hybridization coefficient for F1 and first-generation backcross (hybrid.coef = c(.5, .25)).
All other parameters were run as default.
4.3 Results
Overall, it was possible to identify all specimens based on the morphological
characteristics of each species. However, some specimens were degraded or exhibited
morphological characteristics of more than one species (see detailed results below).
Mitochondrial haplotypes of all 53 samples were successfully identified according to the
Archie Carr Center database, meaning that no new haplotypes were found (Online
resource 1). Amplification of nDNA was less effective than mtDNA, particularly for

stranded turtles, likely due to the lower abundance of nDNA coupled with sample
degradation caused by long environmental exposure. Consequently, we were only able
to recover one locus for most samples (Online Resource 1). In total, we identified nine
hybrids out of 53 samples, three (5.6%) with only one source of evidence (weakly
supported) and six (11.3%) with more than one source of evidence (strongly supported).
Five hybrids were hatchlings from local nests and four were stranded turtles (Table 1).
Details on hybridization and overall genetic characterization are given below.
4.3.1 Hybridization
We identified four hybrids from nest samples based solely on morphology and
mtDNA. One sample was a hatchling identified as a hawksbill (T6R40), which had the
CC-A4 haplotype, typical of loggerheads. The three remaining hybrids (T4R14, T9R12019 and MIR1) had loggerhead morphology and the haplotype-F, unique to olive
ridleys. Specimen T9R1-2019 was from an olive ridley nest but exhibited malformations
and asymmetry of lateral scute counts, five on the right side and seven on the left side
(Online resource 2). Regarding the nuclear dataset, we successfully recovered
sequences from the three analyzed loci for all four hybrids. The hawksbill x loggerhead
hybrid (T6R40) had alleles of both species at the 3061 and 109472 loci, but only
hawksbill alleles at CMOS. One of the three loggerhead x olive ridley hybrids (T9R12019) only had olive ridley alleles at the three nuclear loci. The second (T4R14) only had
loggerhead alleles at 3061, but alleles of both parental species at 109472 and CMOS.
The last sample (MIR1) only had loggerhead alleles at 3061 and CMOS, and alleles of
both species at 109472.
Using nDNA, we were also able to identify one more hybrid from nests (T9R12020), not detected with mtDNA or morphology. The new hybrid had hawksbill
morphology and mtDNA (Ei-BR16) but exhibited an olive ridley allele at the 109472
locus while having only hawksbill alleles at 3061 and CMOS (Table 1). This specimen
was classified as a hybrid with weak evidence because it had a single olive ridley allele,
while morphology and all other genetic evidence indicated that it was a hawksbill.

Nevertheless, this specimen also exhibited dorsal scute malformations (Online resource
2). Membership probabilities of nest hybrids indicated that T6R40 was likely an F1
hybrid (46.9%), T4R14 was likely a loggerhead (41.8%) or a backcross of a F1 hybrid
and a loggerhead (40.4%), MIR1 likely a loggerhead (58.1%) and that T9R1-19 was
likely an olive ridley (75.6%, Fig. 2). Membership probabilities of T9R1-2020 were higher
for hawksbills (55.8%) and for a backcross between an F1 hybrid and a hawksbill
(35.7%, Fig. 2).
Among stranded turtles, one of the four hybrids was identified as a hawksbill
(T4T363), but had the loggerhead CC-A4 haplotype. The second hybrid had loggerhead
morphology, and the CM-A8 haplotype (T5T279), typical of green turtles. The third
hybrid had green turtle morphology and the CC-A4 haplotype (T4T8) from loggerheads.
The last hybrid (T3T68) was only identified by nDNA. While this specimen had hawksbill
morphology and mtDNA, it presented a loggerhead allele at CMOS. Nuclear data from
the other hybrids revealed that the hawksbill x loggerhead hybrid (T4T363) only had
hawksbill alleles at 3061. One green turtle x loggerhead hybrid (T5T279) only had
loggerhead alleles at both 3061 and CMOS loci, while the other sample (T4T8) also only
had loggerhead alleles at CMOS (Online Resource 1).
Membership probabilities of T3T68 and T4T363 were higher for loggerheads
(42.5%) and hawksbills (52.9%), respectively (Fig. 2). Membership probabilities of green
turtle x loggerhead hybrids were not estimated due to the low recovery of green turtle
alleles.

Figure 2. Membership probabilities of hawksbill, loggerhead and olive ridley specimens and their hybrids
as recovered using nuclear loci 3061, 109472 and CMOS. Probabilities were estimated for three pairs of
species: hawksbills and loggerheads (A), olive ridleys and loggerheads (B) and hawksbills and olive
ridleys (C). Hybrids are indicated in bold.

4.3.2 Genetic characterization
Except for the five hybrids, all remaining nest samples (n=25) exhibited
haplotypes from their respective species. Eleven hatchlings, identified as hawksbills,
exhibited the EiA01 haplotype, one had the Ei-BR16 haplotype and one had the Ei-BR10
haplotype, all typical of the species. All 11 non-hybrid loggerhead hatchlings had the
CC-A4 haplotype, typical of the species. The single hatchling identified as olive ridley
had the haplotype-F, which is also unique to this species (Online Resource 1). All nonhybrid samples evaluated for 3061 (total N=16), 109472 (total N=11) and CMOS (total
N=6) had alleles compatible with their morphological identifications (Online Resource 1).
The eight stranded turtles with hawksbill morphology had haplotypes typical of the
species: Ei-A01 (4), Ei-BR10 (2), Ei-BR16 (1) and Ei-IP17 (1). The latter is commonly
found in hawksbills from Indo-Pacific nesting sites in the Seychelles Islands and Chagos
archipelago. To corroborate the identification of this sample, we performed DNA
extraction, PCR and sequencing a second time and the same haplotype was recovered.
All eight non-hybrid stranded turtles identified as loggerheads had the CC-A4 haplotype,
characteristic of this species. The two turtles identified as olive ridley had the haplotypeF and the two green turtles had the CM-A8 haplotype, both unique to each species
(Online Resource 1).
4.4 Discussion
In this study, we contribute to the current knowledge on sea turtle hybridization in
the SWA. Here, we found hybrids among four sea turtle species: loggerheads,
hawksbills, green turtles and olive ridleys. We also expanded sampling on loggerheads
and hawksbills in understudied nesting areas in Alagoas and observed that the genetic
profile of these species is very similar to what is found in other nesting sites in the SWA
(Lara-Ruiz et al. 2006; Reis et al. 2010b). Remarkably, we observed a hawksbill
haplotype typical of the Indo-Pacific in the Alagoas feeding ground. This is not the first
time an Indo-Pacific haplotype has been observed in the Atlantic, which reinforces the

connection between these regions (Arantes et al. 2020b). Below we discuss these topics
in detail.
4.4.1 Hybridization
Hybrids among sea turtle species have already been reported in the SWA (Fig.
3), where loggerhead x hawksbill and loggerhead x olive ridley hybrids are particularly
more frequent (Lara-Ruiz et al. 2006; Reis et al. 2010a; Proietti et al. 2014a; Brito et al.
2020). Although the causes for the high hybridization frequency between these species
are still not completely clear, the temporal and spatial overlapping of their breeding
activities likely facilitates this process (Reis et al. 2010a). While breeding activities of
these species are still understudied in Alagoas, it is possible to find nests of these three
species along the coast of this state (Oliveira et al. 2016), which may facilitate
hybridization between them. In fact, all hybrids between loggerheads and olive ridleys
(3) found here were from nests. All of these samples had loggerhead morphology and
olive ridley mtDNA, the same pattern observed in hybrids from Sergipe nesting site (Reis
et al. 2010a). The two remaining hybrids from Alagoas nests had hawksbill morphology.
One had loggerhead mtDNA (CC-A4, T6R40), the same pattern found in most hybrids
from Bahia (Lara-Ruiz et al. 2006), and the other had an olive ridley allele in the 109472
nuclear locus (T9R1-2020). Hybridization between hawksbills and olive ridleys have
been reported in the SWA before, but this appears to be much less frequent (Lara-Ruiz
et al. 2006; Brito et al. 2020). Nuclear data from nest samples also revealed that these
hybrids are likely F1 or backcrosses with parental species (Fig. 2), which indicates that
hybridization may be an ongoing process in the region.
Among the stranded turtle hybrids, two had hawksbill morphology. One specimen
had loggerhead mtDNA (T4T363) while the other (T3T68) had loggerhead nDNA that
matched an Indo-Pacific loggerhead allele (as did its hawksbill mtDNA). The only other
hybrid previously reported from Alagoas was a hybrid between these species, a
stranded turtle with hawksbill morphology and loggerhead mtDNA (CC-A4) (Brito et al.
2020). However, both species use the Alagoas coastline as both feeding and

reproductive grounds, thus it is difficult to determine how these stranded specimens
were using this area. It is plausible that the T4T363 specimen could have originated
from the Bahia nesting site, since a particularly high frequency of hawksbill x loggerhead
hybrids have been reported there (Lara-Ruiz et al. 2006) and individuals from this
nesting site are also reported to migrate through Alagoas (Marcovaldi et al. 2012). On
the other hand, the loggerhead Indo-Pacific allele we found in the T3T68 specimen,
seems to reinforce that this specimen was indeed from that region (see detailed
discussion below).

Figure 3. Known reports of sea turtle hybrids in the Southwest Atlantic Ocean. ARG – Argentina, URU –
Uruguay, Brazilian States: AL Alagoas, BA Bahia, ABR Abrolhos Archipelago, Bahia, CE Ceará, RS Rio
Grande do Sul, SE Sergipe. Source of hybrid records: Brito et al. (2020): AL, BA, CE, ES, RS, URU; Karl
et al. (1995): BA; Lara-Ruiz et al. (2006): BA; Proietti et al. (2014b): CE, RS; Prosdocimi et al. (2014):
ARG; Reis et al. (2010a): SE; This study: AL.

The remaining stranded hybrids (2) identified through mtDNA were crosses
between green and loggerhead turtles. Hybrids between these species are less common
in the SWA, probably due to the low overlapping in their nesting activities. While
loggerhead nests are mainly found on the Brazilian mainland coast, green turtle nests
are mostly concentrated on oceanic islands, such as Rocas Atoll and Trindade, and are
sparse on continental areas within the SWA (Marcovaldi and Marcovaldi 1999;
Marcovaldi and Chaloupka 2007). Nevertheless, some green turtle nests can be found
along the Brazilian coast, mainly in the northern region of Bahia, the main nesting site
for loggerheads in Brazil (Lara-Ruiz et al. 2006). So, it is plausible that this region is the
probable origin of these hybrids.
Understanding the role hybrids play in sea turtle population structure is
particularly important given their status as threatened species (IUCN 2022), especially
when we take climate change effects into consideration. Many sea turtle populations are
already reported to have strong female bias (Hays et al. 2014; Jensen et al. 2018),
which tends to be even more exacerbated with the predicted rise of global temperatures
(IPCC 2021). Higher nesting beach temperatures could not only promote higher female
output, and consequently higher female proportions in natural populations, but also
increase hatchling mortality (Hays et al. 2017). Furthermore, the decrease in beaches
available for nesting due to sea level rise and coastal urbanization can potentially cause
shifts in habitat use (Fuentes et al. 2010, 2011), which can promote further overlapping
of breeding and nesting activities of these species. If these environmental and
anthropogenic factors act synergistically, we may likely observe an increase in
hybridization frequency over time. Thus, the continuous monitoring of ecological and
genetic aspects of these populations is fundamental.
The use of a multilocus approach to investigate hybridization in these populations
has been shown to be essential for improving our understanding of the hybridization
process (Vilaça et al. 2012; Brito et al. 2020; Arantes et al. 2020c). Here, we were only
able to use three nDNA loci, which precludes us from reaching more conclusive results,
particularly on hybrid generation. The lower success rate in the amplification of these

loci in stranded specimens, likely due to sample deterioration, also limited our
interpretation of these data. The use of nonspecific primers for the CMOS gene also
warrants caution in the interpretation of these data. However, all but one allele observed
in this locus have been identified before using sea turtle primers. Only one hybrid was
defined by CMOS data, all other hybrids can be identified using mtDNA or the other two
nDNA loci (Table 1, Online Resource 1). Despite these limitations, the inclusion of nDNA
allowed us to identify hybrids that would otherwise not have been observed solely using
mtDNA and morphology. Nevertheless, as suggested by previous studies, a better
comprehension of hybrid ecology is required to understand how this high hybridization
frequency along the Brazilian coast can affect population dynamics (Vilaça et al. 2012;
Arantes et al. 2020c).
Studies on the spatial distribution of nesting and feeding grounds, as well as
genetic diversity are initial in Alagoas. Consequently, information on breeding periodicity,
sex ratios and comprehensive genetic characterizations are still unavailable.
Nevertheless, sex ratio studies on loggerhead and hawksbill turtles nesting on the
Brazilian coast indicate high female bias (Marcovaldi et al. 1997; Godfrey et al. 1999),
thus it is likely that future studies would reveal a similar pattern for Alagoas. Therefore,
constant monitoring of this population, regarding shifts in habitat use and population
parameters, is extremely important in order to better understand the consequences of
hybridization and thereby, improve conservation actions.
4.4.2 Genetic characterization
The genetic diversity of hawksbill and loggerhead nests in the study area was
similar to other reproductive areas in the SWA. The CC-A4 haplotype, observed in all
non-hybrid loggerhead nests (11), is widely found in loggerhead nesting sites in Brazil
(Reis et al. 2010b). Likewise, among the three haplotypes we identified in non-hybrid
hawksbill nests (14), the Ei-A01 is widely distributed throughout feeding grounds in the
SWA and in the two major hawksbill nesting sites in Brazil: Bahia and Rio Grande do
Norte (Proietti et al. 2014a; Simões et al. 2021). The two other haplotypes, Ei-BR16 and

Ei-BR10, are both exclusive to Brazilian nesting sites (Lara-Ruiz et al. 2006).
Additionally, the single olive ridley nest sample had the haplotype-F, which is the only
haplotype observed for olive ridleys in the SWA to date (Bowen et al. 1997).
We observed that all stranded loggerheads (9) had the same CC-A4 haplotype
found in the nests. As mentioned above, this haplotype is the most commonly observed
in loggerhead nesting and feeding sites in Brazil and is also exclusive to this region
(Reis et al. 2010b). This low haplotype diversity is also in accordance with previous
studies and the presence of this exclusive Brazilian haplotype reinforces that the
specimens analyzed here likely originated from Brazilian nesting sites (Reis et al.
2010b). We observed a similar genetic profile in stranded hawksbills with haplotypes
commonly found in Brazilian nesting sites: Ei-BR10 (2), Ei-BR16 (1) and Ei-A01 (1)
(Lara-Ruiz et al. 2006; Proietti et al. 2014a; Simões et al. 2021). Finally, the presence of
the Ei-IP17 haplotype was surprising since this haplotype is only found in Indo-Pacific
nesting sites (Vargas et al. 2016), implications of which are discussed below.
In general, the genetic profile we observed for both species suggests that feeding
grounds are mostly occupied by individuals from local nesting sites. Satellite tracking
studies also suggest that the study area is within a migratory corridor for loggerheads
and hawksbills migrating from their main nesting area in Bahia to feeding grounds
farther north, being also the final destination for some of these individuals (Marcovaldi et
al. 2010, 2012).
The occurrence of the Ei-IP17 haplotype among our stranded samples was
a surprising and novel result, since this haplotype is typical for Indo-Pacific nesting sites
in the Seychelles Islands and Chagos Archipelago (Vargas et al. 2016), suggesting a
connection between the Atlantic and Indo-Pacific Oceans. To our knowledge, this is the
first time the Ei-IP17 haplotype has been reported in an Atlantic feeding ground. Two
other Indo-Pacific haplotypes, Ei-IP16 and EI-IP33, have been previously reported in
feeding grounds in Fernando de Noronha and Ascension Island (Fig. 4, Arantes et al.
2020b). Additionally, three orphan haplotypes (Ei-A49, Ei-A70 and Ei-A75) observed in

the Atlantic feeding grounds of Ascension Island, Fernando de Noronha, Cape Verde
and Principe Island, group together with haplotypes from the Indo-Pacific (Arantes et al.
2020b). The same occurs with the EATL haplotype observed in the Principe Island
nesting site in Africa (Monzón-Argüello et al. 2011; Arantes et al. 2020b).
Haplotype sharing between Atlantic and Indo-Pacific Oceans can also be seen in
loggerhead, green and leatherback turtles (Dutton et al. 1999; Bourjea et al. 2007;
Shamblin et al. 2014), and migrations in both directions through southern Africa have
been suggested. For instance, the CM-A8 haplotype, widely found in green turtle nesting
sites in the Atlantic, can also be found in the Mozambique nesting site (Bourjea et al.
2007), a similar pattern to that of the loggerhead CC-A2 haplotype (Shamblin et al.
2014). Loggerhead haplotypes from the Indo-Pacific have also been observed in the
Atlantic, suggesting that westward migrations may also occur (Shamblin et al. 2014).
Colonization of the Atlantic by olive ridleys is suggested to have occurred through
southern Africa (Bowen et al. 1997). Likewise, haplotype sharing between hawksbill
nesting sites in Principe Island and in the Indo-Pacific led Monzón-Argüello et al. (2011)
to suggest the colonization of this east African nesting site by hawksbill migrants from
the Indo-Pacific. Thus, although it seems plausible that the Ei-IP17 haplotype found here
could have originated directly from the Indo-Pacific, we cannot disregard putative
unsampled nesting sites in east Africa as a possible origin, since hawksbill haplotypes
from such sites have already been found in SWA feeding grounds (Proietti et al. 2014a).
The hawksbill sample analyzed here was from a juvenile male (curved carapace
length of 42.1cm), which could indicate an occasional incursion. We also observed IndoPacific alleles in the CMOS locus of seven additional hawksbill, loggerhead and olive
ridley samples (Online Resource 1). Due to the generally slower evolutionary rates of
nuclear genes, these alleles may have persisted at low frequencies in Atlantic sea turtle
populations after their separation from Indo-Pacific lineages. On the other hand, this
may evidence that at least some gene flow between Atlantic and Indo-Pacific sea turtles
still exists. Nevertheless, wider sampling of feeding and nesting grounds in the Atlantic is

required to help elucidate hawksbill and other sea turtle population structure and
migration pathways.

Figure 4. Known occurrences of hawksbill Indo-Pacific haplotypes in south Atlantic feeding and nesting
sites. Star denotes the study site in the state of Alagoas, northeastern Brazil.

4.5 Concluding remarks
Although relatively rare in sea turtles, hybridization seem to be very common in
Brazilian nesting and feeding grounds (Lara-Ruiz et al. 2006; Brito et al. 2020, our
study). Although our total sample size was relatively small, we were still able to detect
hybrids in Alagoas nests, as well as in stranded animals (11.3% of our total sampling),
including putative crosses between hybrids and parental species. This suggests that
hybridization events may be common in the region, as seen in other sites in the SWA,
such as Sergipe and Bahia (Lara-Ruiz et al. 2006; Reis et al. 2010a). Most hybrids were
readily identified using only morphology and mtDNA, however the use of nuclear data
revealed new hybrids that would otherwise remain unidentified, which highlights the

importance of using an integrative approach when studying hybridization (Vilaça et al.
2012; Brito et al. 2020).
The use of mtDNA and nDNA also revealed a possible connection between
feeding grounds in the study area and nesting sites in the Indo-Pacific. Understanding
these connections and migratory pathways is essential to the development of
appropriate conservation strategies and is one of the main priorities in sea turtle
research (Hamann et al. 2010). Although a more comprehensive research effort is
required to clarify the connections between sea turtles in the Atlantic and Indo-Pacific,
our findings represent the fifth hawksbill locality in the South Atlantic with Indo-Pacific
haplotypes (Arantes et al. 2020b), reinforcing the connection between these regions.
4.6 Acknowledgments
JPFAA thanks FAPEAL for providing PhD scholarship (#23038.023347/2016-74).
TM thanks Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq
(309904/2015-3 and 312291/2018-3) for financial support. We thank Camila Domit,
Maíra Proietti and Kim Barão for kindly read and comment on an earlier version of the
manuscript. We also thank the editor and two anonymous reviewers for constructive
comments on the manuscript.
4.7 Author contributions
João P. F. A. Almeida, Tamí Mott and Robson G. Santos contributed to the study
conception and design. Oscar K. L. Marques participated in sample collection and
material preparation. Sample processing and data analysis were performed by João P.
F. A. Almeida. The first draft of the manuscript was written by João P. F. A. Almeida and
all authors commented on previous versions of the manuscript. All authors read and
approved the final manuscript.

4.8 Funding
This study was partially funded by Fundação Grupo Boticário de Proteção da
Natureza (#1143/20182) and PADI Foundation (#47777/2020). Beach monitoring and
sample collection was partially supported by Long Term Ecological Research – Brazil
site PELD-CCAL funded by the Brazilian National Council for Scientific Research and
Technological Development (CNPq – #441657/2016-8, #442237/2020-0) and the
Research Support Foundation of the State of Alagoas (FAPEAL – #60030.1564/2016,
#PLD2021010000001).
4.9 Data availability
All data generated in this study is provided in the article and online resources or
was described previously and is already available at the GenBank database.
References
Abbott R, Albach D, Ansell S et al (2013) Hybridization and speciation. J Evol Biol 26:
229–246. https://doi.org/10.1111/j.1420-9101.2012.02599.x
Abreu-Grobois FA, Horrocks J, Formia A, LeRoux R, Velez-Zuazo X, Dutton P, Soares
L, et al. (2006). New mtDNA D-loop primers which work for a variety of marine turtle
species may increase the resolution of mixed stock analysis. In: Book of Abstracts of the
26th Annual Symposium on Sea Turtle Biology and Conservation, pp 179.
Arantes LS, Ferreira LCL, Driller M, Repinaldo Filho FPM, Mazzoni CJ, Santos FR
(2020a) Genomic evidence of recent hybridization between sea turtles at Abrolhos
Archipelago and its association to low reproductive output. Sci Rep 10:1–13.
https://doi.org/10.1038/s41598-020-69613-8
Arantes LS, Vargas SM, Santos FR (2020b) Global phylogeography of the critically
endangered hawksbill turtle (Eretmochelys imbricata). Genet Mol Biol 43:1–12.
https://doi.org/10.1590/1678-4685-GMB-2019-0264
Arantes LS, Vilaça ST, Mazzoni CJ, Santos FR (2020c) New genetic insights about
hybridization and population structure of hawksbill and loggerhead turtles from Brazil. J
Hered 111:444–456. https://doi.org/10.1093/jhered/esaa024

Bonfim WAG, Oliveira BSSP, Santos CRM, Medeiros LS, La Fuente MF (2022) First live
stranding of a leatherback sea turtle Dermochelys coriacea in Alagoas, north-east Brazil.
Herpetol Bull 160: 35–37. https://doi.org/10.33256/hb160.3537
Bolten AB, Lutz PL, Musick JA, Wyneken J (2003) Variation in sea turtle life history
patterns: neritic vs. oceanic developmental stages. In: Lutz PL, Musick JA, Wyneken J
(Eds) The biology of sea turtles, 2nd edn. CRC Press, Boca Raton, pp 243-257
Bourjea J, Lapègue S, Gagnevin L, Broderick D, Mortimer JA, Ciccione S, Roos D,
Taquet C, Grizel H (2007) Phylogeography of the green turtle, Chelonia mydas, in the
Southwest Indian Ocean. Mol Ecol 16:175–186. https://doi.org/10.1111/j.1365294X.2006.03122.x
Bowen BW, Clark AM, Chaves A, Reichart HA, Ferl RJ, Rica UDC, Heredia SP, Rica C,
Service SF (1997) Global phylogeography of the ridley sea turtles (Lepidochelys spp.)
as inferred from mitochondrial DNA sequences. Genetica 101:179–189.
https://doi.org/10.1023/a:1018382415005
Brito C, Vilaça ST, Lacerda AL, Maggioni R, Marcovaldi MA, Vélez-Rubio G, Proietti MC
(2020) Combined use of mitochondrial and nuclear genetic markers further reveal
immature marine turtle hybrids along the south western Atlantic. Genet Mol Biol 43:1–
11. https://doi.org/10.1590/1678-4685-GMB-2019-0098
Colman LP, Thomé JCA, Almeida ADP, Baptistotte C, Barata PCR, Broderick AC,
Ribeiro FA, Vila-verde L, Godley BJ (2019) Thirty years of leatherback turtle
Dermochelys coriacea nesting in Espírito Santo, Brazil, 1988−2017: reproductive biology
and conservation. Endang Species Res 39:147–158.
Dutton PH, Bowen BW, Owens DW, Barragan A, Davis SK (1999) Global
phylogeography of the leatherback turtle (Dermochelys coriacea). J Zool 248:397–409.
https://doi.org/10.1017/S0952836999007116
Fuentes MMPB, Limpus CJ, Hamann M, Dawson J (2010) Potential impacts of projected
sea-level rise on sea turtle rookeries. Aquat Conserv Mar Freshw Ecosyst 20:132–139.
https://doi.org/10.1002/aqc.1088
Fuentes MMPB, Limpus CJ, Hamann M (2011) Vulnerability of sea turtle nesting
grounds to climate change. Glob Chang Biol 17:140–153. https://doi.org/10.1111/j.13652486.2010.02192.x
Godfrey MH, D'Amato AF, Marcovaldi MA, Mrosovsky N (1997) Pivotal temperature and
predicted sex ratios for hatchling hawksbill turtles from Brazil. Can J Zool 77:1465–1473
Hall, TA (1999) BioEdit: a user-friendly biological sequence alignment editor and
analysis program for Windows 95/98/NT. Nucleic Acids Symposium Series 41:95–98.

Hamann M, Godfrey MH, Seminoff JA, Arthur K, Barata PCR, Bjorndal KA, Bolten AB,
Broderick AC, Campbell LM, Carreras C, Casale P, Chaloupka M, Chan SKF, Coyne
MS, Crowder LB (2010) Global research priorities for sea turtles : informing
management and conservation in the 21st century. Endang Species Res, 11:245–269.
https://doi.org/10.3354/esr00279
Hays GC, Mazaris AD, Schofield G (2014) Different male vs. female breeding periodicity
helps mitigate offspring sex ratio skews in sea turtles. Front Mar Sci 1:1–9.
https://doi.org/10.3389/fmars.2014.00043
Hays GC, Mazaris AD, Schofield G, Laloë JO (2017) Population viability at extreme sexratio skews produced by temperaturedependent sex determination. Proc R Soc B Biol
Sci 284:1–7. https://doi.org/10.1098/rspb.2016.2576
ICMBio (2017) Plano de Ação Nacional para Conservação das Tartarugas Marinhas.
https://www.icmbio.gov.br/portal/faunabrasileira/plano-de-acao-nacional-lista/841-planode-acao-nacional-para-a-conservacao-das-tartarugas-marinhas. Accessed 26 March
2022
Intergovernmental Panel on Climate Change (2021). Climate Change 2021: Synthesis
Report. Contribution of Working Group III to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change [Core Writing Team]. Ed. by Jager-Waldau
A and Sapkota T. IPCC, Geneva, Switzerland.
Jensen MP, Allen CD, Eguchi T, Bell IP, LaCasella EL, Hilton WA, Hof CAM, Dutton PH
(2018) Environmental Warming and Feminization of One of the Largest Sea Turtle
Populations in the World. Curr Biol 28:154–159.
https://doi.org/10.1016/j.cub.2017.11.057
Jombart T (2008) Adegenet: A R package for the multivariate analysis of genetic
markers. Bioinformatics 24:1403–1405. https://doi.org/10.1093/bioinformatics/btn129
Jordão JC, Bondioli ACV, Guebert FM, de Thoisy B, de Toledo LFA (2015) Green turtle
(Chelonia mydas) genetic diversity at Paranaguá Estuarine complex feeding grounds in
Brazil. Genet Mol Biol 38:346–352. https://doi.org/10.1590/S1415-475738320140353
Katoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7:
Improvements in performance and usability. Mol Biol Evol 30:772–780.
https://doi.org/10.1093/molbev/mst010
Kearney M, Stuart BL (2004) Repeated evolution of limblessness and digging heads in
worm lizards revealed by DNA from old bones. Proc R Soc London B 271:1677–1683.

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
Librado P, Rozas J (2009) DnaSP v5: A software for comprehensive analysis of DNA
polymorphism data. Bioinformatics 25:1451–1452.
https://doi.org/10.1093/bioinformatics/btp187
Marcovaldi M, Chaloupka M (2007) Conservation status of the loggerhead sea turtle in
Brazil: an encouraging outlook. Endanger Species Res 3:133–143.
https://doi.org/10.3354/esr003133
Marcovaldi MA, Godfrey MH, Mrosovsky N (1997) Estimating sex ratios of loggerhead
turtles in Brazil from pivotal incubation durations. Can J Zool 75: 755–770
Marcovaldi M, Lopez G, Soares L, López-Mendilaharsu M (2012) Satellite tracking of
hawksbill turtles Eretmochelys imbricata nesting in northern Bahia, Brazil: turtle
movements and foraging destinations. Endanger Species Res 17:123–132.
https://doi.org/10.3354/esr00421
Marcovaldi MA, Lopez GG, Soares LS, Santos AJB, Bellini C, Barata PCR (2007)
Fifteen years of Hawksbill Sea Turtle (Eretmochelys imbricata) nesting in Northern
Brazil. Chelonian Conserv Biol 6:223–228. https://doi.org/10.2744/10718443(2007)6[223:FYOHST]2.0.CO;2
Marcovaldi MA, Dei Marcovaldi GG (1999) Marine turtles of Brazil: The history and
structure of Projeto TAMAR-IBAMA. Biol Conserv 91:35–41.
https://doi.org/10.1016/S0006-3207(99)00043-9
Marcovaldi MA, Lopez GG, Soares LS, Lima EHSM, Thomé JCA, Almeida AP (2010)
Satellite-tracking of female loggerhead turtles highlights fidelity behavior in northeastern
Brazil. Endanger Species Res 12:263–272. https://doi.org/10.3354/esr00308
Monzón-Argüello C, Loureiro NS, Delgado C, Marco A, Lopes JM, Gomes MG, AbreuGrobois FA (2011) Príncipe island hawksbills: Genetic isolation of an eastern Atlantic
stock. J Exp Mar Bio Ecol 407:345–354. https://doi.org/10.1016/j.jembe.2011.07.017
Naro-Maciel E, Bondioli ACV, Martin M, De Pádua Almeida A, Baptistotte C, Bellini C,
Marcovaldi MA, Santos AJB, Amato G (2012) The interplay of homing and dispersal in
green turtles: A focus on the southwestern atlantic. J Hered 103:792–805.
https://doi.org/10.1093/jhered/ess068
Oliveira BSSP, Bonfim WAG, Santos CRM, Santos SM, Silva EA, Medeiros LS,
Santiago MC, Marques OKL, Ferreira AA, Izidoro FB, Santos MEF, Melo LL, Silva FMO
(2016). Instituto Biota de Conservação: Pesquisa e Conservação de Tartarugas

Marinhas no Estado de Alagoas. In: Correia JMS, Santos EM, Moura GJB (eds)
Conservação de Tartarugas Marinhas no Nordeste do Brasil. Editora Universitária da
UFRPE, Recife, pp 169–190
Pritchard PCH, 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. IUCN/SSC Marine
Turtle Specialist Group Publication No. 4, Washington, D.C., pp 21–38
Proietti MC, Reisser J, Marins LF, Rodriguez-Zarate C, Marcovaldi MA, Monteiro DS,
Pattiaratchi C, Secchi ER (2014a) Genetic structure and natal origins of immature
hawksbill turtles (Eretmochelys imbricata) in Brazilian waters. PLoS One 9:e88746.
https://doi.org/10.1371/journal.pone.0088746
Proietti MC, Reisser J, Marins LF, Marcovaldi MA, Soares LS, Monteiro DS, Wijeratne S,
Pattiaratchi C, Secchi ER (2014b) Hawksbill × loggerhead sea turtle hybrids at Bahia,
Brazil: Where do their offspring go? PeerJ 2014:1–14. https://doi.org/10.7717/peerj.255
Prosdocimi L, Bruno I, Diaz L, Carman VG, Albareda DA, Remis MI (2014)
Southernmost report of the hawksbill sea turtle, Eretmochelys imbricata, in temperate
waters of Argentina and evidence of a hybrid origin supported by mitochondrial DNA
analysis. Herpetol Rev 45:1–5.
R Core Team (2021). R: A Language and Environment for Statistical Computing. R
Foundation for Statistical Computing
Reis EC, Soares LS, Lôbo-Hajdu G (2010a) Evidence of olive ridley mitochondrial
genome introgression into loggerhead turtle rookeries of Sergipe, Brazil. Conserv Genet
11:1587–1591. https://doi.org/10.1007/s10592-009-9973-2
Reis EC, Soares LS, Vargas SM, Santos FR, Young RJ, Bjorndal KA, Bolten AB, LôboHajdu G (2010b) 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
Sambrook J, Fritsch EF, Maniatis T (1989). Molecular Cloning: A Laboratory Manual,
2nd edn. Cold Spring Harbor Laboratory Press, New York.
Santos EAP, Silva ACCD, Sforza R, Oliveira FLC, Weber MI, Castilhos JC, LópezMendilaharsu M, Marcovaldi MAAG, Ramos RMA, DiMatteo A (2019) Olive ridley internesting and post-nesting movements along the Brazilian coast and Atlantic Ocean.
Endanger Species Res 40:149–162. https://doi.org/10.3354/ESR00985
Shamblin BM, Bolten AB, Abreu-Grobois FA, Bjorndal KA, Cardona L, Carreras C, Clusa
M, Monzón-Argüello C, Nairn CJ, Nielsen JT, Nel R, Soares LS, Stewart KR, Vilaça ST,

Türkozan O, Yilmaz C, Dutton PH (2014) Geographic patterns of genetic variation in a
broadly distributed marine vertebrate: New insights into loggerhead turtle stock structure
from expanded mitochondrial DNA sequences. PLoS One 9:e85956.
https://doi.org/10.1371/journal.pone.0085956
Simões TN, Maranhão E, Santos AS, Thaynara E, Menezes C De, Chimendes V (2021)
Low Diversity and Strong Genetic Structure Between Feeding and Nesting Areas in
Brazil for the Critically Endangered Hawksbill Sea Turtle. Front Ecol Evol 9:704838.
https://doi.org/10.3389/fevo.2021.704838
Soares LS, Bolten AB, Wayne ML, Vilaça ST, Santos FR, dei Marcovaldi MAG, Bjorndal
KA (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
Soares LS, Bjorndal KA, Bolten AB, Wayne ML, Castilhos JC, Weber MI, LópezMendilaharsu M, Marcovaldi MA, Vilaça ST, Naro-Maciel E (2021) Reproductive output,
foraging destinations, and isotopic niche of olive ridley and loggerhead sea turtles, and
their hybrids, in Brazil. Endanger Species Res 44:237–251.
https://doi.org/10.3354/ESR01095
Todesco M, Pascual MA, Owens GL, Ostevick KL, Moyers BT, Hubner S, Heredia SM,
Hahn MA, Caseys C, Bock DG, Rieseberg LH (2016) Hybridization and extinction. Evol
Appl 9: 892–908. https://doi.org/10.1111/eva.12367
Vargas SM, Jensen MP, Ho SYW, Mobaraki A, Broderick D, Mortimer JA, Whiting SD,
Miller J, Prince RIT, Bell IP, Hoenner X, Limpus CJ, Santos FR, Fitzsimmons NN (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
Vargas SM, Lins LSF, Molfetti E, Ho SYW, Monteiro D, Barreto J, Colman L, Vila-Verde
L, Baptistotte C, Thomé JCA, Santos FR (2019) Revisiting the genetic diversity and
population structure of the critically endangered leatherback turtles in the South-west
Atlantic Ocean: insights for species conservation. J. Mar. Biol. Assoc. U. K. 99:31–41.
https://doi:10.1017/S002531541700193X
Vilaça ST, Vargas SM, Lara-Ruiz P, Molfetti É, Reis EC, Lôbo-Hajdu G, Soares LS,
Santos FR (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
Wallace BP, Dimatteo AD, Hurley BJ, Finkbeiner EM, Alan B, Chaloupka MY,
Hutchinson BJ, Abreu-grobois FA, Marcovaldi MA, Mortimer JA, Musick JA, Pilcher NJ,
Seminoff JA, Troe S (2010) Regional Management Units for Marine Turtles : A Novel
Framework for Prioritizing Conservation and Research across Multiple Scales. PLoS
One 5:e15465. https://doi.org/10.1371/journal.pone.0015465

Wallace BP, DiMatteo AD, Bolten AB, Chaloupka MY, Hutchinson BJ, Abreu-Grobois
FA, Mortimer JA, Seminoff JA, Amorocho D, Bjorndal KA, Bourjea J, Bowen BW,
Dueñas R, Casale P, Choudhury BC, Costa A, Dutton PH, Fallabrino A, Finkbeiner EM,
Girard A, Girondot M, Hamann M, Hurley BJ, López-Mendilaharsu M, Marcovaldi MA,
Musick JA, Nel R, Pilcher NJ, Troëng S, Witherington B, Mast RB (2011) Global
conservation priorities for Marine turtles. PLoS One 6:e24510.
https://doi.org/10.1371/journal.pone.0024510

5 CAPÍTULO 3
TEMPORAL VARIATION ON THE GENETIC DIVERSITY OF GREEN TURTLES
FROM THE SOUTHWEST ATLANTIC OCEAN
Abstract
Green turtles are migratory animals with a complex life cycle, which makes them
vulnerable to a wide range of threats. Despite being historically exploited, continuous
conservation efforts are resulting in the recovery of some nesting populations. The
recovery, and consequent output increase, of different nesting populations can affect the
composition of individuals in feeding grounds since these areas harbour individuals from
different nesting sites. In this study we evaluate temporal variations in the genetic
composition of feeding grounds in the Southwestern Atlantic Ocean (SWA) to investigate
if the recovery of nesting sites in the Atlantic Ocean, particularly Ascension Island, is
influencing the composition of individuals in the region. We used the control region of the
mitochondrial DNA and mitochondrial short tandem repeats to perform spatial and
temporal analyses using samples collected along the SWA in two temporal periods ten
years apart. Spatial and temporal genetic variations in the region were not significant.
Likewise, estimated natal origins remained similar between the time periods analyzed,
with small variations. However, there was significant temporal variation in genetic
diversity when considering only the northermost feeding grounds in the SWA, likely
related to an increase in the frequency of the CM-A8 haplotype, common in Ascension
Island. These results suggest that the genetic diversity in SWA feeding grounds have
remained somewhat similar in recent years. However, the constant monitoring of these
sites as well as the characterization of new sites are essential to create a strong
baseline and understand genetic diversity trends of SWA green turtles.

Keywords: Green turtles, feeding grounds, nesting sites, population recovery

5.1 Introduction
Green turtles (Chelonia mydas) are slow growing, long-lived and migratory
animals, with a complex life cycle characterized by ontogenetic habitat shifts. Their life
history encompasses different ecosystems from terrestrial habitats (nesting sites) to
open ocean, as well as a diversity of coastal foraging habitats (Bolten 2003). Adults
migrate between foraging grounds and breeding areas, which can be thousands of
kilometers apart (Plotkin 2003), and exhibit natal philopatry to nesting beaches (Bowen
and Karl 2007). As a result, there is a considerable genetic structure among nesting
sites (Bjorndal et al. 2006; Naro-Maciel et al. 2014). In contrast, feeding grounds are
commonly mixed stocks, harbouring individuals from several different nesting sites
(Naro-Maciel et al. 2007, 2012; Proietti et al. 2012; Prosdocimi et al. 2012).
Because of this complex life cycle, green turtles are usually under multiple threats
according to the environments they go through (Wallace 2010). They have been
historically exploited, and currently anthropic threats such as climate change, pollution of
marine environments and habitat degradation still threaten green turtle populations
(Fuentes et al. 2011). Nevertheless, some nesting sites are recovering as a result of
continuous conservation efforts (e.g. Catry et al. 2009; Weber et al. 2014). Because of
the connection between nesting and feeding grounds, differential recovery of nesting
sites can likely alter the composition of individuals at feeding grounds. For instance, a
green turtle feeding ground in Lac Bay, Boinare, in the Caribbean have shown an
increase in the proportion of individuals from local recovering nesting sites over a tenyear time span as revealed by variations on local genetic diversity based on
mitochondrial DNA analyses (van der Zee et al. 2019).
Some nesting sites in the South Atlantic, such as Ascension Island and Guinea
Bissau have grown significantly during the last decades (Catry et al. 2009; Weber et al.
2014), while others such as Trindade Island are reported to be stable (Medeiros et al.
2022). Ascension Island has been historically reported as the highest contributor to the
composition of green turtles in feeding grounds along the coast of Southwest Atlantic

(SWA) (Naro-Maciel et al. 2012; Prosdocimi et al. 2012). With the rising number of
nesting females in this nesting site, contributions of Ascension to local foraging grounds
could become even greater. A likely consequence of Ascension Island green turtle
nesting growth is that the influence of smaller nesting sites such as Trindade Island
could become harder to detect since the number of individuals from this area would be
proportionally lower, which could result in variations on the genetic diversity over time.
Therefore, our main goal was to evaluate if the recovery of green turtles nesting sites in
the Atlantic has influenced the genetic diversity at foraging grounds in the Southwestern
Atlantic.
5.2 Methods
We used muscle and skin samples collected from green turtles found stranded
along the coast of Alagoas (between May 2018 and January 2021) and Paraná
(between January 2018 and November 2021) (Fig. 1). We used samples from these
localities because they represent northern and southern distribution of green turtles
feeding grounds in the SWA and might different responses to the differential recovery of
local nesting sites. Since most green turtles in southern foraging grounds are smaller
than 60cm (Barata et al. 2011), we chose this size class as a threshold in sample
selection in order to avoid bias caused by migrants from southern to northern foraging
grounds. In total, we used 213 samples, of which 140 were from Alagoas (CCL 2359.2cm) and 73 were from Paraná (CCL 31-57.3cm). Among samples from Alagoas,
100 were from Almeida et al. (2021), and 40 were newly sequenced for this study.
Total genomic DNA was extracted using phenol-chloroform (Sambrook et al.
1989). We amplified the short fragment of the control region of the mitochondrial DNA
(493pb) for all samples. For a subset of these samples (49 from Alagoas and 47 from
Paraná), we amplified a longer mtDNA fragment (840pb), including the longer fragment
of the control region as well as four mitochondrial short tandem repeats (mtSTR) as
described in Tikochinski et al. (2012). Control region fragments were amplified using the
primers LCM15382 and H950 (Abreu-Grobrois et al. 2006) and mtSTRs were amplified

using the primers CMD1 and CMD5 (Tikochinski et al. 2012). We conducted 25 µl
polymerase chain reactions, consisting in 20.8 µl of 1XMaster Mix PCR Buffer with 0.4
mM of each dNTP and 3 mM of MgCl2, 1.0 ml of each primer (10 pmol); 2 µl of DNA
template (>20 ng/ml); and 0.2 µl of Taq DNA polymerase (5 U/ml). We amplified the
control region fragments using the following protocol: initial denaturation at 94°C for 7
min followed by 35–40 cycles of denaturation at 94°C for 30 s, annealing at 57°C for 30
s, extending at 72°C for 1 min and a final extending at 72°C for 7 min. Mitochondrial
STRs were amplified with the same protocol but with a 56°C annealing temperature. We
checked for successful amplifications using a 1% agarose gel and samples successfully
amplified were purified with isopropanol to remove PCR residuals and sequenced with
the forward primer (short control region fragment and mtSTRs) or both primers (long
control region fragment) using Sanger sequencing at ACTGene Análises Moleculares.
Sequences were edited with Bioedit 7.2.5 (Hall 1999) and aligned with MAFFT
online service (Katoh et al. 2019). We identified haplotypes using the Archie Carr Center
for Sea Turtles Research (https://accstr.ufl.edu/resources/mtdna-sequences/) and
categorized mtSTRs by counting the “AT” repeats in each of the four loci we analyzed.
Thus, each individual sample was represented by a four-digit code as described in
Tikochinski et al. (2012). Haplotype and nucleotide diversities were assessed using
DNAsp v6.12 (Rozas et al. 2017). We tested for population divergence between Alagoas
and Paraná using an analysis of molecular variance (AMOVA) with 10,000 permutations
as implemented in Arlequin v3.5.2.2 (Excoffier and Lischer 2010). We performed this
analysis in two different ways. Firstly, we used the shorter fragment of the control region,
which allowed the inclusion of a larger number of samples. Secondly, we used the
longer fragment of the control region plus mtSTRs.

Figure 1. Southwest Atlantic Ocean feeding grounds sampled in this study. Literature data are from NaroMaciel et al. (2012), Proietti et al. (2012) and Almeida et al. (2021). Colours indicate marine ecoregions by
Spaldin et al. 2007, Tropical Southwestern Atlantic in orange and Warm Temperate Southwestern Atlantic
in purple.

We assessed temporal variation in genetic composition on the SWA also using
two approaches. First, we pooled together our data from Alagoas and Paraná as
representative of current genetic composition and compared these data to data collected
ten to 15 years ago along the Southwest Atlantic Ocean (total N=743), mainly the
Brazilian coast (Naro-Maciel et al. 2012; Proietti et al. 2012). Second, we considered
northern and southern feeding grounds independently, according to the marine
provinces of Tropical Southwestern Atlantic (TSA, N=341) and Warm Temperate
Southwestern Atlantic (WTSA, N=402) (Spalding et al. 2007). To test for genetic
differences between time periods, we used AMOVA analyses as mentioned above.

Natal origins of green turtles were estimated using the same groupings described
above, first the SWA as a whole and then TSA and WTSA independently. Analyses
were carried out through many-to-one mixed stock analysis (MSA; Pella and Masuda
2001). We used 12 nesting sites in the Atlantic Ocean as putative sources of individuals
(Table S1). We performed the analyses using BAYES (Pella and Masuda 2001), with 12
chains per run (equal to the number of sources) and 50,000 iterations per chain,
discarding half of these iterations as burn-in. Convergence of the runs was checked
using the Gelman-Rubin criterion, considering values below 1.2 as adequate, as
indicated in the software manual. We used the number of nesting females at each
nesting site as a prior in the analyses (Table S1).
5.3 Results
Considering the new samples from Alagoas and Paraná (short fragment), we
identified 12 different haplotypes in Alagoas, of which the most frequent were CM-A8
(68%), CM-A5 (20%) and CM-A9 (3%). We also identified a previously undescribed
haplotype, H1. Using the CM-A8 haplotype (GenBank accession number Z50130) as
reference, the new haplotype has a transition, G to A, at position 89. Among Paraná
samples, we identified ten haplotypes, of which CM-A8 (58%), CM-A5 (25%) and CM-A9
(6%) were also the most frequent. Haplotype and nucleotide diversities were higher in
Paraná (Hd = 0.611, π = 0.00253) compared to Alagoas (Hd = 0.491, π = 0.00193).
Considering the longer fragment of the control region plus mtSTRs, we identified a total
of 23 haplotypes in Alagoas and 21 in Paraná. AMOVA results using the shorter
fragment of the control region or the longer fragment plus mtSTRs revealed no genetic
structure between Alagoas and Paraná (Fst = -0.005, P = 0.645 and Fst = 0.001, P =
0.338; respectively).
Proportion of haplotypes in the SWA as a whole (N=213) was similar between the
two sampling periods. We identified 14 different haplotypes currently (2018-2021), of
which the most frequent were CM-A8 (64.8%), CM-A5 (21.6%) and CM-A9 (4.2%). The
haplotypes CM-A8 (61.5%), CM-A5 (22.6%) and CM-A9 (4.1%) were also the most

frequent in the 2003-2008 sampling period (N=530). Accordingly, AMOVA analysis
revealed no genetic differentiation between the two sampling periods (Fst = -0.00275, p
= 0.98624). When we considered only samples from the southernmost sampling areas
(WTSA), we also observed no genetic differentiation between the two sampling periods
(Fst = -0.00014, p = 0.36297). On the other hand, we observed significant genetic
differentiation when considering only samples from the northernmost sampling areas
(TSA) (Fst = 0.01486, p = 0.03069), even though most genetic variation was within each
group (98.51%).
Natal origins of green turtles were similar considering all data (SWA). Ascension
Island, Surinam, Guinea Bissau and Trindade Island were the nesting sites with highest
contributions to the composition of individuals in SWA foraging grounds both in 20032008 (53%, 19%, 12% and 10%, respectively) and 2018-2021 (58%, 16%, 19% and 4%,
respectively). Ascension Island was also the highest contributor when considering past
and current TSA data (60% and 56%, respectively). Surinam was the second highest
contributor using past data (29%), followed by Trindade Island (4%) and Aves Island
(3%). Guinea Bissau was the second highest contributor using current data (28%),
followed by Surinam (12%) and Aves Island (2%). Considering only data from the
WTSA, Ascension Island (62%), Guinea Bissau (16%), Surinam (11%) and Aves Island
(5%) were the highest contributors in the past, while Ascension Island (55%), Surinam
(21%), Trindad Island (15%) and Guinea Bissau (3%) are highest contributors currently
(Fig. 2).
5.4 Discussion
Haplotype frequencies of new samples (Alagoas and Paraná) were similar to
what has been reported for the region, with a high frequency of CM-A8 and CM-A5
haplotypes (Naro-Maciel et al. 2012; Proietti et al. 2012; Almeida et al. 2021). We
detected no genetic differentiation between the two regions, even though feeding
grounds in the Atlantic have been reported to be somewhat structured (Naro-Maciel et
al. 2012).

Figure 2. Mixed stock analysis and proportion of haplotypes of green turtles from Southwest Atlantic
Ocean (A) and two subsets restricted to the Tropical Southwestern Atlantic (B) and the Warm Temperate
Southwestern Atlantic (C), considering past (2003-2008) and current (2018-2021) sampling. Error bars
indicate standard deviation.

The use of additional markers, such as mtSTRs has been suggested as a tool to
detect deeper genetic variation (Tikochinski et al. 2012; Shamblin et al. 2015; Bradshaw
et al. 2018). We sequenced mtSTRs for a subset of our samples and observed a
considerable increase in the number of haplotypes, but failed to detect genetic structure,
either between Alagoas and Paraná or between subvariants of the most common
haplotypes CM-A5 and CM-A8 (Table S2). Although mtSTR data from Trindade Island,
Fernando de Noronha and Rocas Atoll nesting sites is available (Shamblin et al. 2015),
other major nesting sites such as Ascension Island and Guinea Bissau remain to be
sampled. Finer scale analysis of currently known haplotypes could be extremely helpful
to reveal deeper genetic structure between nesting sites and help enhance natal origins
analyses in the region.
This high frequency of CM-A8 and CM-A5 haplotypes was also observed in data
from 2003-2008 and haplotype proportions did not vary greatly between time periods.
The CM-A8 haplotype is extremely common across nesting sites in the South Atlantic,
including Ascension Island, the second biggest nesting site in the region (Formia et al.
2007). Thus, a high frequency of this haplotype in SWA feeding grounds is expected.
The CM-A5 haplotype, on the other hand, is more common in nesting sites near the
Caribbean, such as Surinam and Aves Island (Shamblin et al. 2012). A high frequency
of this haplotype can be observed on feeding grounds near that region, such as Ceará
and Fernando de Noronha (Naro-Maciel et al. 2012). It would make sense that Alagoas
also exhibited a similar pattern due to its proximity to the region. However, we observed
an even higher frequency of this haplotype in Paraná, which is more than seven
thousand kilometers away. Besides the genetic evidence (Naro-Maciel et al. 2012;
Jordão et al. 2015), telemetry also indicated that juveniles and subadults green turtles
from the Caribbean migrate to foraging grounds along the Brazilian coast, swimming
against the Guiana and North Brazil currents (Chambault et al. 2018). Once they reach
the northeastern coast of Brazil, they could reach southern foraging grounds with the aid
of the Brazilian current as genetic data from our and other studies indicate (Proietti et al.
2012, Jordão et al. 2015).

Natal origin analyses corroborated these observations, as Ascension Island and
Surinam had high contribution to the composition of individuals considering all three
sample groupings (Fig. 2). When using data from the whole SWA, contributions of
Ascension Island, Surinam, Guinea Bissau and Trindade Island were somewhat
constant between the two time periods analysed (Fig. 2A). However, there was
noticeable variation in TSA and WTSA. Contributions of Surinam to the composition of
individuals in the TSA were visibly lower in 2018-2021. Conversely, contributions of
Guinea Bissau were visibly higher (Fig. 2B). This might be a result of the decreased
proportion of the CM-A5 haplotype, common in the Surinam nesting site (Shamblin et al.
2012). Concomitantly, the increased proportion of the CM-A8 haplotype in the 20182021 sampling may have promoted the increased contributions from Guinea Bissau, as
the overwhelming majority of individuals from there exhibit the CM-A8 haplotype
(Patrício et al. 2017).
Natal origins of samples from the WTSA showed an evident increase in the
contributions from Surinam and Trindade Island in 2018-2021, while contributions from
Guinea Bissau decreased in the same period (Fig. 2C), likely due to the higher
proportion of CM-A5 and CM-A9 haplotypes in the same period. The CM-A9 haplotype
have been reported in the nesting sites of Rocas Atoll, Ascension Island and Trindade
Island, but with a higher frequency on the latter (Bjorndal et al. 2006). Previous studies
also show that contributions from Trindade Island are usually higher to closer feeding
grounds in south Brazil (Naro-Maciel et al. 2012; Proietti et al. 2012), which is in
agreement with our results.
Overall, our results show that there is no clear influence of the recovery of
Ascension Island on the genetic composition of green turtles from SWA feeding
grounds, at least not in the time frame analysed here. Contrary to what was expected,
contributions of Trindade Island to feeding grounds in the WTSA increased, even though
that nesting site have been stable while Ascension have been increasing the number of
nesting females (Medeiros et al. 2022). Thus, we would expect an increase in the
frequency of haplotypes from Ascension Island in foraging grounds in south Brazil while

haplotypes from Trindade could become less likely to be sampled because their relative
frequency would decline. We did not observe such variation in haplotype frequencies.
Nevertheless, it is worth noting that the CM-A8 haplotype is the most common haplotype
in both nesting sites, which could mask some of those effects since we cannot precisely
determine the natal origin of CM-A8 individuals.
Even though our study indicates no significant temporal variation in haplotypes
proportion in SWA feeding grounds, continuous monitoring is essential to detect
changes in the dynamics of local feeding and nesting grounds. The use of more variable
genetic markers can help to detect finer variations on genetic diversity and improve the
genetic characterization of known populations, which can be highly useful to improve
natal origins estimation. Studies describing the genetic diversity of new feeding grounds
or expanding the knowledge on known feeding and nesting grounds also help to create
a stronger baseline that allow future studies to detect genetic variability more precisely.
References
Abreu-Grobois FA, Horrocks J, Formia A, Leroux R, Velez-Zuazo X, Dutton P, Soares L,
Meylan P, Browne D (2006) New mtDNA D-loop primers which work for a variety of
marine turtle species may increase the resolution of mixed stock analysis. In: Annual
Symposium on Sea Turtle Biology and Conservation, Island of Crete. Book of abstracts
of the 26th Annual Symposium on Sea Turtle Biology and Conservation. Athens:
International Sea Turtle Society, p. 179.
Almeida JPFA, Santos RG, Mott T (2021) Sex ratios and natal origins of green turtles
from feeding grounds in the Southwest Atlantic Ocean. ICES Journal of Marine Science
78:1840–1848. doi: 10.1093/icesjms/fsa
Barata PCR, Carman VG, Santos AS, Bondioli ACV, Almeida AP, Santos AJB, Silva
ACCD, Gallo BMG, Giffoni BB, Domit C, Baptistotte, Bellini C, Batista CMP, Bezerra DP,
Monteiro DS, Albareda D, Lima EHSM, Lima EP, Guebert-Bartholo F, Sales G, Lopez
GG, Stahelin GD, Bruno I, Castilhos JC, Thomé JCA, Nunes JAA, Becker JH,
Wanderlinde J, Rosa L, Marcovaldi MA, Melo MTD, Mascarenhas R, Estima SC, NaroMaciel E (2011) Variação latitudinal na distribuição do tamanho de tartarugas-verdes
(Chelonia mydas) ao longo de parte da costa leste da América do Sul. In: V Jornada
sobre Tartarugas Marinhas do Atlântico Sul Ocidental. Florianópolis, Brasil. p. 18–22.

Bjorndal KA, Bolten AB, Moreira L, Bellini C, Marcovaldi MÂ (2006) Population structure
and diversity of brazilian green turtle rookeries based on mitochondrial DNA sequences.
Chelonian Conservation and Biology 5:262–268. doi: 10.2744/10718443(2006)5[262:PSADOB]2.0.CO;2
Bolten, AB (2003) Variation in sea turtle life history patterns: neritic vc oceanic
developmental stages. In: LUTZ, P. L.; MUSICK, J. A.; WYNEKEN, J. (Eds.), The
Biology of Sea Turtles Volume II. CRC Press, Boca Raton, p. 243–257.
Bowen BW, Karl SA (2007) Population genetics and phylogeography of sea turtles.
Molecular Ecology, 16: 4886–4907.
Bradshaw PJ, Broderick AC, Carreras C, Fuller W, Snape RTE, Wright LI, Godley BJ
(2018) Defining conservation units with enhanced molecular tools to reveal fine scale
structuring among Mediterranean green turtle rookeries. Biol Conserv 222:253–260. doi:
10.1016/j.biocon.2017.12.014
Catry P, Barbosa C, Paris B, Indjai B, Almeida A, Limoges B, Silva C, Hono´ H, Pereira
H (2009) Status, Ecology, and Conservation of Sea Turtles in Guinea-Bissau. Chelonian
Conservation and Biology 8:150–160.
Chambault P, de Thoisy B, Huguin M, Martin J, Bonola M, Etienne D, Gresser J, Hiélard
G, Mailles J, Védie F, Barnerias C, Sutter E, Guillemot B, Dumont-Dayot É, Régis S,
Lecerf N, Lefebvre F, Frouin C, Aubert N, Guimera C, Bordes R, Thieulle L, Duru M,
Bouaziz M, Pinson A, Flora F, Queneherve P, Woignier T, Allenou JP, Cimiterra N,
Benhalilou A, Murgale C, Maillet T, Rangon L, Chanteux N, Chanteur B, Béranger C, le
Maho Y, Petit O, Chevallier D (2018) Connecting paths between juvenile and adult
habitats in the Atlantic green turtle using genetics and satellite tracking. Ecol Evol
8:12790–12802. doi: 10.1002/ece3.4708
Excoffier L, Lischer HEL (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. doi: 10.1111/j.1755-0998.2010.02847.x
Formia A, Broderick A, Glen F, Godley B, Hays G, Bruford M (2007) Genetic
composition of the Ascension Island green turtle rookery based on mitochondrial DNA:
implications for sampling and diversity. Endanger Species Res 3:145–158. doi:
10.3354/esr003145
Fuentes MMPB, Limpus CJ, Hamann M (2011) Vulnerability of sea turtle nesting
grounds to climate change. Glob Chang Biol 17:140–153. doi: 10.1111/j.13652486.2010.02192.x
Hall TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis
program for windows 95/98/NT. Nucleic Acids Symp Ser 41:95–98.

Jordão JC, Bondioli ACV, Guebert FM, de Thoisy B, de Toledo LFA (2015) Green turtle
(Chelonia mydas) genetic diversity at Paranaguá Estuarine complex feeding grounds in
Brazil. Genet Mol Biol 38:346–352. doi: 10.1590/S1415-475738320140353
Katoh K, Rozewicki J, Yamada KD (2019) MAFFT online service: multiple sequence
alignment, interactive sequence choice and visualization. Briefings in Bioinformatics
20:1160–1166. doi: 10.1093/bib/bbx108
Medeiros L, Chaloupka M, Bolten AB, von Muhlen EM, Santos A, Marcondes ACJ,
Thomé JCA, Marcovaldi MÂ, Bjorndal KA (2022) Tracking green turtle nesting trends at
a remote oceanic rookery. Mar Biol. doi: 10.1007/s00227-022-04054-7
Naro-Maciel E, Becker JH, Lima EHSM, Marcovaldi MÂ, DeSalle R (2007) Testing
dispersal hypotheses in foraging green sea turtles (Chelonia mydas) of Brazil. Journal of
Heredity 98:29–39. doi: 10.1093/jhered/esl050
Naro-Maciel E, Bondioli ACV, Martin M, de Pádua Almeida A, Baptistotte C, Bellini C,
Marcovaldi MÂ, Santos AJB, Amato G (2012) The interplay of homing and dispersal in
green turtles: A focus on the southwestern atlantic. Journal of Heredity 103:792–805.
doi: 10.1093/jhered/ess068
Naro-Maciel E, Reid BN, Alter SE, Amato G, Bjorndal KA, Bolten AB, Martin M, Nairn
CJ, Shamblin B, Pineda-Catalan O (2014) From refugia to rookeries: Phylogeography of
Atlantic green turtles. J Exp Mar Biol Ecol 461:306–316. doi:
10.1016/j.jembe.2014.08.020
Patrício AR, Formia A, Barbosa C, Broderick AC, Bruford M, Carreras C, Catry P, Ciofi
C, Regalla A, Godley BJ (2017) Dispersal of green turtles from Africa’s largest rookery
assessed through genetic markers. Mar Ecol Prog Ser 569:215–225. doi:
10.3354/meps1207
Pella J, Masuda M (2001) Bayesian methods for analysis of stock mixtures from genetic
characters. Fishery Bulletin 99:151–167.
Plotkin P (2003) Adult Migrations and Habitat Use. In: Lutz PL, Musik JA, Wyneken J
(Eds.). The Biology of Sea Turtles, Volume II. Florida: CRC Press, p. 225–241.
Proietti MC, Reisser JW, Kinas PG, Kerr R, Monteiro DS, Marins LF, Secchi ER (2012)
Green turtle Chelonia mydas mixed stocks in the western South Atlantic, as revealed by
mtDNA haplotypes and drifter trajectories. Mar Ecol Prog Ser 447:195–209. doi:
10.3354/meps09477
Prosdocimi L, González Carman V, Albareda DA, Remis MI (2012) Genetic composition
of green turtle feeding grounds in coastal waters of Argentina based on mitochondrial
DNA. J Exp Mar Biol Ecol 412:37–45. doi: 10.1016/j.jembe.2011.10.015

100

Rozas J, Ferrer-Mata A, Sanchez-DelBarrio JC, Guirao-Rico S, Librado P, RamosOnsins SE, Sanchez-Gracia A (2017) DnaSP 6: DNA sequence polymorphism analysis
of large data sets. Mol Biol Evol 34:3299–3302. doi: 10.1093/molbev/msx248
Sambrook J, Fritsch EF, Maniatis T (1989) Molecular cloning: a laboratory manual, 2nd
edn. Cold Spring Harbor Laboratory Press, New York
Shamblin BM, Bjorndal KA, Bolten AB, Hillis-Starr ZM, Lundgren I, Naro-Maciel E, Nairn
CJ (2012) Mitogenomic sequences better resolve stock structure of southern Greater
Caribbean green turtle rookeries. Mol Ecol 21:2330–2340. doi: 10.1111/j.1365294X.2012.05530.x
Shamblin BM, Dutton PH, Bjorndal KA, Bolten AB, Naro-Maciel E, Santos AJB, Bellini C,
Baptistotte C, Marcovaldi MÂ, Nairn CJ (2015) Deeper Mitochondrial Sequencing
Reveals Cryptic Diversity and Structure in Brazilian Green Turtle Rookeries. Chelonian
Conservation and Biology 14:167–172. doi: 10.2744/CCB-1152.1
Spalding MD, Fox HE, Allen GR, Davidson N, Ferdaña ZA, Finlayson M, Halpern BS,
Jorge MA, Lombana A, Lourie SA, Martin KD, McManus E, Molnar J, Recchia CA,
Robertson J (2007) Marine ecoregions of the world: a bioregionalization of coastal and
shelf areas. Bioscience 57:573–583.
Tikochinski Y, Bendelac R, Barash A, Daya A, Levy Y, Friedmann A (2012)
Mitochondrial DNA STR analysis as a tool for studying the green sea turtle (Chelonia
mydas) populations: The Mediterranean Sea case study. Mar Genomics 6:17–24. doi:
10.1016/j.margen.2012.01.002
van der Zee JP, Christianen MJA, Nava M, Velez-Zuazo X, Hao W, Bérubé M, van
Lavieren H, Hiwat M, Berzins R, Chevalier J, Chevallier D, Lankester MC, Bjorndal KA,
Bolten AB, Becking LE, Palsbøll PJ (2019) Population recovery changes population
composition at a major southern Caribbean juvenile developmental habitat for the green
turtle, Chelonia mydas. Sci Rep. doi: 10.1038/s41598-019-50753-5
Weber SB, Weber N, Ellick J, Avery A, Frauenstein R, Godley BJ, Sim J, Williams N,
Broderick AC (2014) Recovery of the South Atlantic’s largest green turtle nesting
population. Biodivers Conserv 23:3005–3018. doi: 10.1007/s10531-014-0759-6

101

6 Discussão geral e conclusões
Cinco das sete espécies de tartarugas marinhas ocorrem no Oceano Atlântico
Sudoeste (OAS). Todas essas espécies encontram-se sob algum grau de ameaça,
segundo a União Internacional para a Conservação da Natureza (IUCN, 2022). Devido
a isso, a identificação e caracterização de áreas de desova e alimentação de tartarugas
marinhas na região é fundamental para melhorar cada vez mais a elucidação da
dinâmica populacional dessas espécies e entender como elas podem responder a
ameaças atuais e futuras (FUENTES; LIMPUS; HAMANN, 2011). Nos estudos
desenvolvidos nessa tese, procuramos entender alguns aspectos da diversidade
genética e conservação das tartarugas marinhas do OAS.
Observamos que a razão sexual de tartarugas verdes em áreas de alimentação
da região é enviesada em favor das fêmeas, onde há cerca de três fêmeas para cada
macho. Essa tendência já foi relatada em outras regiões do mundo (HAYS; MAZARIS;
SCHOFIELD, 2014), e levanta discussões sobre uma possível feminilização das
populações, tendo em vista as mudanças climáticas e um provável aumento na
produção de fêmeas em áreas de desova ao redor do mundo (JENSEN et al., 2018).
Ainda assim, essa razão sexual é menor do que o observado em várias áreas de
desova, onde a produção de fêmeas pode chegar a mais de 90% (HAYS; MAZARIS;
SCHOFIELD, 2014), o que sugere que algumas áreas de desova ainda mantém uma
produção mais equilibrada de fêmeas e machos (e.g. PATRÍCIO et al. 2017). Assim, a
avaliação de áreas de desova e alimentação com relação a sua razão sexual se faz
cada vez mais necessária, em todas as espécies de tartarugas marinhas, para o
direcionamento de medidas de conservação adequadas a fim de que a viabilidade
populacional dessas espécies possa ser mantida. Nesse sentido, a avaliação de dados
genéticos de fêmeas e machos em áreas de alimentação pode ajudar a identificar áreas
de desova que estejam potencialmente gerando mais fêmeas ou mais machos
(JENSEN et al., 2018).

102

A avaliação desses dados para a área de alimentação de Alagoas, nordeste do
Brasil, revelou uma variação entre a origem natal de fêmeas e machos. As análises
indicaram que a maior parte das fêmeas que se alimentam na região são provenientes
da área de desova da Ilha de Ascensão, enquanto a maior parte dos machos provém da
área de desova de Guiné Bissau, no litoral Africano. Esse resultado foi congruente com
as análises de razão sexual dessas áreas, que indicam que Ascensão tem uma
produção de fêmeas mais acentuada, enquanto Guiné Bissau tem uma produção mais
equilibrada entre os dois sexos (GODLEY et al., 2002; PATRÍCIO et al., 2019). A área
de desova de Suriname também apresentou alta contribuição para a composição de
machos na região. Apesar de ser necessário cautela na interpretação dos resultados
devido a limitação das análises, essa avaliação se mostra útil não só para corroborar as
análises locais de razão sexual como também para identificar a conectividade da área
de alimentação de Alagoas com as áreas de desova da região com relação às fêmeas e
machos da espécie.
A análise de outras espécies de tartarugas marinhas no litoral de Alagoas
também revelou a presença de hibridização entre quatro espécies: tartaruga de pente e
tartaruga cabeçuda, tartaruga de pente e tartaruga oliva, tartaruga cabeçuda e tartaruga
oliva e, por fim, tartaruga verde e tartaruga cabeçuda. Foram identificados espécimes
híbridos tanto em áreas de desova quanto de alimentação em Alagoas. Isso sugere que
esse processo está acontecendo não só entre tartarugas que se reproduzem na região,
mas também entre aquelas que se reproduzem em outras áreas e migram para se
alimentar no litoral do estado. A alta frequência de hibridização entre tartarugas
marinhas no litoral Brasileiro é marcante, principalmente ao longo do litoral dos estados
da Bahia e Sergipe (LARA-RUIZ et al., 2006; REIS; SOARES; LÔBO-HAJDU, 2010).
Nosso estudo amplia o número de áreas com registro de hibridização e ressalta a
importância da ampliação dessa avaliação para outras regiões. O monitoramento
dessas áreas com registro de hibridização também é importante para entendermos
melhor os efeitos desse processo na dinâmica populacional das espécies e como
pressões atuais, como ocupação desordenada do ambiente costeiro e mudanças

103

climáticas, podem afetar a frequência de hibridização nessas regiões. Isso é de extrema
relevância uma vez que estudos recentes têm demonstrado que híbridos e espécies
parentais parecem exibir sobreposição ecológica e parecem também se tornar inviáveis
a partir da segunda geração (SOARES et al., 2021; VILAÇA et al., 2022). Isso evidencia
a necessidade do monitoramento contínuo desse processo no litoral brasileiro, a fim de
avaliar com mais clareza a amplitude da ocorrência de híbridos na região e como a
frequência de híbridos pode mudar no futuro e se isso pode vir a afetar a viabilidade das
populações dessas espécies na região de maneira significativa.
Também foi possível detectar um espécime de tartaruga de pente com um
haplótipo típico do Indo-Pacífico na área de alimentação de Alagoas. É precipitado
afirmar que esse espécime migrou diretamente daquela região, porém não é a primeira
vez que um haplótipo do Indo-Pacífico é registrado em áreas de alimentação no
Atlântico (ARANTES; VARGAS; SANTOS, 2020), o que reforça a conexão entre essas
duas regiões. Esse padrão de migração e ocupação de habitats que transcendem os
limites geográficos de países e continentes é um desafio para a conservação não só da
tartaruga de pente, mas das tartarugas marinhas em geral. Isso demanda a
coordenação entre diferentes países, uma vez que a proteção do hábitat que essas
espécies ocupam em um país, não necessariamente garante a proteção daquela
população se os hábitats que os indivíduos daquela população ocupam em outras
regiões estiverem sob constante ameaça (WALLACE et al., 2011).
Por fim, foi avaliada a variação temporal na diversidade genética de tartarugas
verdes em áreas de alimentação do OAS. Não foi observada uma mudança significativa
na proporção de haplótipos quando consideramos o OAS como um todo. Porém, foram
encontradas variações genéticas nas áreas de alimentação quando os dados foram
analisados de maneira mais regionalizada. A alta frequência do haplótipo CM-A5 no sul
do Brasil é digna de nota, uma vez que esse haplótipo é mais comum em áreas de
desova do Caribe e os indivíduos têm que nadar ativamente contracorrente para
atingirem áreas de alimentação no litoral Brasileiro (CHAMBAULT et al., 2018). A
alteração na frequência de haplótipos nas populações de tartarugas marinhas pode ser

104

um indicador da depleção ou recuperação de áreas de desova locais (VAN DER ZEE et
al., 2019). O monitoramento das espécies é essencial para esclarecer esses processos
e avaliar possíveis perdas de diversidade genética e o status populacional das
espécies. Além disso, a implementação de marcadores moleculares variáveis e de uma
abordagem integrativa é crucial para a elucidação de padrões de estruturação
populacional, que muitas vezes podem ser mascarados por haplótipos que são
altamente difundidos nas populações. A utilização de dados nucleares e de repetições
curtas do DNA mitocondrial (mtSTR) ajudou a revelar uma maior variabilidade nos
dados analisados nessa tese, que não seria observada apenas com o uso da região
controle do DNA mitocondrial, o marcador molecular mais utilizado em estudos com
tartarugas marinhas. Assim, estudos futuros que foquem nessa abordagem certamente
poderão revelar padrões de estruturação ainda não observados e contribuir para a
conservação das espécies de tartarugas marinhas.

105

REFERÊNCIAS
ARANTES, L. S.; VARGAS, S. M.; SANTOS, F. R. Global phylogeography of the
critically endangered hawksbill turtle (Eretmochelys imbricata). Genetics and Molecular
Biology, v. 43, n. 2, p. 1–12, 2020.
CHAMBAULT, P. et al. Connecting paths between juvenile and adult habitats in the
Atlantic green turtle using genetics and satellite tracking. Ecology and Evolution, v. 8, n.
24, p. 12790–12802, 1 dez. 2018.
FUENTES, M. M. P. B.; LIMPUS, C. J.; HAMANN, M. Vulnerability of sea turtle nesting
grounds to climate change. Global Change Biology, v. 17, p. 140–153, 2011.
GODLEY, B. J. et al. Temperature-dependent sex determination of Ascension Island
green turtles. Marine Ecology Progress Series, v. 226, p. 115–124, 2002.
HAYS, G. C.; MAZARIS, A. D.; SCHOFIELD, G. Different male vs. female breeding
periodicity helps mitigate offspring sex ratio skews in sea turtles. Frontiers in Marine
Science, v. 1, p. 1–9, 2014.
IUCN 2022. The IUCN Red List of Threatened Species. Version 2022-1.
<https://www.iucnredlist.org>
JENSEN, M. P. et al. Environmental Warming and Feminization of One of the Largest
Sea Turtle Populations in the World. Current Biology, v. 28, n. 1, p. 154–159, 2018.
LARA-RUIZ, P. et al. Extensive hybridization in hawksbill turtles (Eretmochelys
imbricata) nesting in Brazil revealed by mtDNA analyses. Conservation Genetics, v. 7, n.
5, p. 773–781, 2006.
PATRÍCIO, A. R.; VARELA, M. R.; BARBOSA, C.; BRODERICK, A. C.; CATRY, P.;
HAWKES, L. A.; REGALLA, A.; GODLEY, B. J. Climate change resilience of a globally
important sea turtle nesting population, v. 25, n. 2, p. 522–535, 2019.
REIS, E. C.; SOARES, L. S.; LÔBO-HAJDU, G. Evidence of olive ridley mitochondrial
genome introgression into loggerhead turtle rookeries of Sergipe, Brazil. Conservation
Genetics, v. 11, n. 4, p. 1587–1591, 2010.
SOARES, L. S. et al. Reproductive output, foraging destinations, and isotopic niche of
olive ridley and loggerhead sea turtles, and their hybrids, in Brazil. Endangered Species
Research, v. 44, p. 237–251, 2021.
VAN DER ZEE, J. P. et al. Population recovery changes population composition at a
major southern Caribbean juvenile developmental habitat for the green turtle, Chelonia
mydas. Scientific Reports, v. 9, n. 1, 2019.

106

VILAÇA, S. T. et al. Evidence of backcross inviability and mitochondrial DNA paternal
leakage in sea turtle hybrids. Molecular Ecology, v. 32, p. 628–643, 2022.
Wallace, B. P. et al. Global conservation priorities for Marine turtles. PLoS One, v. 6, n.
9, p. e24510, 2011.

107

ANEXO A – CAPÍTULO 1

108

Table S1. Female and male green turtles recorded stranded in Brazilian feeding grounds between 2010 and 2016.
Northeast1

Northeast2

Southeast

Year
Females Males Females Males Females Males
2010

2011

122

204

2012

145

219

260

2013

186

167

2014

231

159

2015

176

2016

211

122

109

Table S2. Haplotypes of green turtles found in Alagoas foraging ground and Nesting sites used in this study. Number of
nesting females are from Seminoff et al., 2015. Full references can be found in the main text reference list. AI – Ascension
Island, AV – Aves Island, BK – Bioko, CB – Cuba, CR – Costa Rica, FL – Florida, FN – Fernando de Noronha, GB –
Guinea Bissau, MX – Mexico, RA – Rocas Atoll, STP – São Tomé and Principe, SU – Suriname, TR – Trindade Island. I –
Encalada et al., 1996; II – Bjorndal et al., 2005; III – Bjorndal et al., 2006; IV – Shamblin et al., 2012; V – Formia et al.,
2006; VI – Formia et al., 2007; VIII – Patrício et al., 2017.
Haplotype

Alagoas FG

Rookeries

Females

Males

RA/FN

STP

CMA1

CMA2

CMA3

395

CMA4

CMA5

CMA6

CMA7

CMA8

204

170

CMA9

CMA10

CMA11

CMA12

CMA15

CMA16

CMA17

CMA18

CMA20

110

CMA21

CMA23

CMA24

CMA25

CMA27

CMA28

CMA32

CMA33

CMA35

CMA36

CMA37

CMA38

CMA39

CMA42

CMA44

CMA45

CMA46

CMA48

CMA50

CMA56

CMA57

Total N
Nesting
females
Source haplotype
data

433

245

171

8,322

24,330

131,751

2,833

13,067

345

13,417

2,016

30,125

850

376

2,226

This
study

II, IV

III

VIII

VII

111

Table S3. Haplotypes of 106 specimens of Chelonia mydas from Alagoas feeding ground based on ~800bp of the mtDNA
control region.
Haplotype
CMA5.1
CMA6.1
CMA8.1
CMA8.2
CMA8.3
CMA9.1
CMA10.1
CMA23.1
CMA32.1
CMA42.1
Total

Females
4
1
48
2
4
1
1
1
62

Males
10
2
28
1
1
1
1
44

References
Bjorndal, K. A., Bolten, A. B., and Troëng, S. 2005. Population structure and genetic diversity in green turtles nesting at

112

Tortuguero, Costa Rica, based on mitochondrial DNA control region sequences. Marine Biology, 147: 1449–1457.
Bjorndal, K. A., Bolten, A. B., Moreira, L., Bellini, C., and Marcovaldi, M. Â. 2006. Population structure and diversity of
brazilian green turtle rookeries based on mitochondrial DNA sequences. Chelonian Conservation and Biology, 5:
262–268.
Encalada, S. E., Lahanas, P. N., Bjorndal, K. A., Bolten, A. B., Miyamoto, M. M., and Bowen, B. W. 1996. Phylogeography
and population structure of the Atlantic and Mediterranean green turtle Chelonia mydas: A mitochondrial DNA control
region sequence assessment. Molecular Ecology, 5: 473–483.
Formia, A., Godley, B. J., Dontaine, J. F., and Bruford, M. W. 2006. Mitochondrial DNA diversity and phylogeography of
endangered green turtle (Chelonia mydas) populations in Africa. Conservation Genetics, 7: 353–369.
Formia, A., Broderick, A., Glen, F., Godley, B., Hays, G., and Bruford, M. 2007. Genetic composition of the Ascension
Island green turtle rookery based on mitochondrial DNA: implications for sampling and diversity. Endangered Species
Research, 3: 145–158.
Shamblin, B. M., Bjorndal, K. A., Bolten, A. B., Hillis-Starr, Z. M., Lundgren, I., Naro-Maciel, E., and Nairn, C. J. 2012.
Mitogenomic sequences better resolve stock structure of southern Greater Caribbean green turtle rookeries.
Molecular Ecology, 21: 2330–2340.
Patrício, A. R., Formia, A., Barbosa, C., Broderick, A. C., Bruford, M., Carreras, C., Catry, P., et al. 2017. Dispersal of
green turtles from Africa’s largest rookery assessed through genetic markers. Marine Ecology Progress Series, 569:
215–225.

113

ANEXO B – CAPÍTULO 2

114

Table S1. Sea turtles sampled in Alagoas. Samples in bold indicate hybrids. nDNA haplotype names refer to Arantes et al. (2020c).
Field
number

Type

T7R13

nest

Eretmochelys
imbricata

Ei-A01

T7R14

nest

Caretta
caretta

CC-A4.2

T7R18

nest

Eretmochelys
imbricata

Ei-A01

T8R6

nest

Caretta
caretta

CC-A4.1

T8R7

nest

T8R14

nest

T8R20

nest

T8R33

nest

T8R37

nest

T9R6

nest

T9R8

nest

Morphology

Caretta
caretta
Caretta
caretta
Caretta
caretta
Eretmochelys
imbricata
Eretmochelys
imbricata
Caretta
caretta
Eretmochelys
imbricata

nDNA

mtDNA

CC-A4.2

3061
Eretmochelys
imbricata
haplotype 1
Caretta
caretta
haplotype 2
Eretmochelys
imbricata
haplotype 1
Caretta
caretta
haplotype 2
Caretta
caretta
haplotype 2

CC-A4.1
CC-A4.2

Ei-A01

Eretmochelys
imbricata
haplotype 1

Ei-BR16

CC-A4.1
Ei-A01

Caretta
caretta
haplotype 2
Eretmochelys
imbricata

109472
Eretmochelys imbricata
haplotype 5 / Eretmochelys
imbricata haplotype 6

CMOS
Eretmochelys imbricata haplotype 5
JF415101 / Eretmochelys imbricata
Pacific isolate FJ039966

Caretta caretta haplotype 1
Eretmochelys imbricata
haplotype 4 / Eretmochelys
imbricata haplotype 5

Eretmochelys imbricata haplotype 10
JF415106 / Eretmochelys imbricata
Pacific isolate FJ039966

Caretta caretta haplotype 1 /
Caretta caretta haplotype 2

Caretta caretta haplotype 1

115

haplotype 1

T8R38

nest

Eretmochelys
imbricata

T8R4

nest

Caretta
caretta

Ei-A01

CC-A4

Eretmochelys
imbricata
haplotype 1
Caretta
caretta
haplotype 2
Eretmochelys
imbricata
haplotype 1

T9R1/20

nest

T6R86

nest

T7R19

nest

Eretmochelys
imbricata
Eretmochelys
imbricata
Caretta
caretta

T7R10

nest

Caretta
caretta

T8R15

nest

T7R5

nest

T1R5/21

nest

Caretta
caretta
Caretta
caretta
Eretmochelys
imbricata

T4R47

nest

Lepidochelys
olivacea

haplotypeF

MIR1

nest

Caretta
caretta

haplotypeF

T4R56

nest

Eretmochelys
imbricata

Ei-A01

Lepidochelys
olivacea
haplotype 4
Caretta
caretta
haplotype 2
Eretmochelys
imbricata
haplotype 1

T9R1/19

nest

Caretta

haplotypeF

Lepidochelys

Ei-BR16

Eretmochelys imbricata
haplotype 5 / Lepidochelys
olivacea haplotype 3

Eretmochelys imbricata haplotype 3
JF415099

Ei-BR10
CC-A4.2

CC-A4.2

Caretta
caretta
haplotype 2
Caretta
caretta
haplotype 2

Caretta caretta haplotype 1

Caretta caretta haplotype 2

CC-A4
Ei-A01
Lepidochelys olivacea
haplotype 3
Caretta caretta haplotype 1 /
Lepidochelys olivacea
haplotype 3

Lepidochelys olivacea

Eretmochelys imbricata
haplotype 5

Caretta caretta Pacific isolate FJ009023
Eretmochelys imbricata haplotype 5
JF415101 / Eretmochelys imbricata
haplotype 3 JF415099

Lepidochelys olivacea

Lepidochelys olivacea Pacific isolate

116

caretta

T6R40

nest

T6R84

nest

T1R5/19

nest

T4R14

nest

T4R66

nest

T4R109

nest

T2T13/20

strand

T4T166

strand

T8T348

strand

T8T350

strand

T6T155

strand

T1T10

strand

T6T4

strand

T3T68

strand

Eretmochelys
imbricata
Eretmochelys
imbricata
Eretmochelys
imbricata
Caretta
caretta
Eretmochelys
imbricata
Eretmochelys
imbricata
Eretmochelys
imbricata
Eretmochelys
imbricata
Eretmochelys
imbricata
Eretmochelys
imbricata
Eretmochelys
imbricata
Eretmochelys
imbricata
Eretmochelys
imbricata
Eretmochelys
imbricata

CC-A4.2

olivacea
haplotype 4
Eretmochelys
imbricata
haplotype 1 /
Caretta
caretta
haplotype 2

haplotype 3

FJ039980

Eretmochelys imbricata
haplotype 4 OR 6 / Caretta
caretta haplotype 1

Eretmochelys imbricata haplotype 5
JF415101 / Eretmochelys imbricata
haplotype 3 JF415099

Caretta
caretta
haplotype 2

Caretta caretta haplotype 1 /
Lepidochelys olivacea
haplotype 3

Caretta caretta Atlantic isolate
FJ009030 / Lepidochelys olivacea
Pacific isolate FJ039980

Ei-A01
Ei-A01

haplotypeF
Ei-A01
Ei-A01
Ei-A01
Ei-A01
Ei-A01
Ei-A01
Ei-BR16
Ei-BR10
Ei-BR10
Ei-IP17

Eretmochelys imbricata haplotype 5
JF415101 / Caretta caretta Pacific

117

isolate FJ009023
T1T59

strand

T4T29

strand

T3T8/20

strand

T2T20/20

strand

T2T65

strand

T4T90

strand

T4T182

strand

T4T8

strand

T4T100

strand

T4T363

strand

T4T389

strand

T3T74/20

strand

T5T279

strand

T9T183/20

strand

T8T8/20

strand

Lepidochelys
olivacea
Lepidochelys
olivacea
Caretta
caretta
Caretta
caretta
Caretta
caretta
Caretta
caretta
Caretta
caretta
Chelonia
mydas
Caretta
caretta
Eretmochelys
imbricata
Caretta
caretta
Caretta
caretta
Caretta
caretta
Chelonia
mydas
Chelonia
mydas

haplotypeF
Lepidochelys olivacea
haplotype 3

haplotypeF
CC-A4
CC-A4
CC-A4
CC-A4
CC-A4

Caretta caretta Atlantic isolate
FJ009030 / Caretta caretta Pacific
isolate FJ009023

CC-A4
CC-A4

CC-A4

Eretmochelys
imbricata
haplotype 1

CC-A4
CC-A4

CM-A8
CM-A8
CM-A8

Caretta
caretta
haplotype 2

Caretta caretta Atlantic isolate
FJ009030 / Caretta caretta Pacific
isolate FJ009023
Chelonia mydas haplotype
12

118

Figure S1. Hatchlings from Alagoas identified as hybrids in this study. T4R14 (a, b),
T6R40 (c, d), T9R1-2019 (e, f), T9R1-2020 (g, h), MIR1 (i, j). Black bars indicate
10mm.

119

Figure S2. Stranded turtles from Alagoas identified as hybrids in this study. T5T279
(a, b), T4T363 (c, d), T4T8 (e, f), T3T68 (g, h). Black bars indicate 100mm. Photos
by Instituto Biota de Conservação.

120

ANEXO C – CAPÍTULO 3

121

Table S1. Haplotypes of green turtles found in Alagoas foraging ground and Nesting sites used in this study. Number of nesting
females are from Seminoff et al., 2015. Full references can be found in the main text reference list. AI – Ascension Island, AV –
Aves Island, BK – Bioko, CB – Cuba, CR – Costa Rica, FL – Florida, FN – Fernando de Noronha, GB – Guinea Bissau, MX –
Mexico, RA – Rocas Atoll, STP – São Tomé and Principe, SU – Suriname, TR – Trindade Island. I – Encalada et al., 1996; II –
Bjorndal et al., 2005; III – Bjorndal et al., 2006; IV – Shamblin et al., 2012; V – Formia et al., 2006; VI – Formia et al., 2007; VIII –
Patrício et al., 2017.
Haplotype

Feeding grounds
(2018-2021)
Alagoas
Paraná

Rookeries
FL

RA/FN

STP

CMA1

CMA2

CMA3

395

CMA4

CMA5

CMA6

CMA7

CMA8

204

170

CMA9

CMA10

CMA11

CMA12

CMA15

CMA16

CMA17

CMA18

CMA20

122

CMA21

CMA23

CMA24

CMA25

CMA27

CMA28

CMA32

CMA33

CMA35

CMA36

CMA37

CMA38

CMA39

CMA42

CMA44

CMA45

CMA46

CMA48

CMA50

CMA56

CMA57

Total N
Nesting
females
Source haplotype
data

139

433

245

171

8,322

24,330

131,751

2,833

13,067

345

13,417

2,016

30,125

850

376

2,226

This
study

II, IV

III

VIII

VII

123

Table S2. Haplotypes of green turtles from Alagoas and Paraná feeding grounds for the 2018-2021 sampling.
Source
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study

Sample ID
CEM246132
CEM179072
CEM231761
CEM234881
CEM237187
CEM166390
UFP3659
CEM178344
CEM221919
CEM174559
CEM111677
CEM178008
CEM230912
CEM234014
CEM228272
CEM230915
CEM084198
CEM216116
CEM180600
CEM183851
CEM159204
CEM125331
CEM178761

Locality
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná

Size CCL (cm)
37.6
36.4
35.4
33.4
30.9
46.6
36.3
50.3
30.9
38.1
49.5
36.7
35.8
37.7
36.1
35
31.8
57.3
31
48
38.4
39
39.8

mtDNA_short
CMA32
CMA8
CMA1
CMA5
CMA8
CMA8
CMA5
CMA8
CMA8
CMA5
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA5
CMA5
CMA8

mtDNA_long
CMA32.1
CMA8.1
CMA1.1
CMA5.1
CMA8.1
CMA8.1
CMA5.1
CMA8.1
CMA8.1
CMA5.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA5.1
CMA5.1
CMA8.1

mtSTR_combination
6-12-4-4
7-12-4-4
7-12-4-4
6-12-4-4
7-11-4-4
7-13-4-4
7-12-4-4
7-13-4-4
8-14-4-4
7-15-4-4
7-11-4-4
--8-14-4-4
7-16-4-4
8-11-4-4
7-12-4-4
8-13-4-4
--7-12-4-4
5-12-4-4
----7-11-4-4

124

This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study

CEM115031
CEM185391
CEM253387
CEM065774
CEM159202
CEM159259
CEM114847
CEM178778
CEM076436
CEM245371
UFP3432
CEM235226
CEM203772
CEM186275
CEM166112
CEM169615
CEM170079
CEM171526
CEM164604
CEM159081
CEM125337
CEM135360
CEM101264
CEM159121
CEM159066
CEM157970

Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná

36
37
45.2
47.8
49.7
37.7
47.3
32.8
35
31.2
33.5
35
32.8
36.1
32.2
31.4
34.5
38.5
38.7
35.5
40.2
35.6
39.8
33.2
36.1
39

CMA5
CMA8
CMA8
CMA9
CMA6
CMA8
CMA8
CMA8
CMA8
CMA5
CMA8
CMA8
CMA8
CMA5
CMA8
CMA5
CMA9
CMA8
CMA24
CMA10
CMA8
CMA10
CMA32
CMA8
CMA45
CMA5

CMA5.1
CMA8.1
CMA8.1
CMA9.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA5.1
CMA8.1
CMA5.1
CMA9.1
CMA8.1
CMA24.1
CMA10.1
CMA8.1
CMA10.1
CMA32.1
CMA8.1
CMA45.1
CMA5.1

--6-16-4-4
7-12-4-4
7-12-4-4
----7-12-4-4
--------7-12-4-4
7-12-4-4
7-12-4-4
7-12-4-4
6-12-4-4
7-12-4-4
8-13-4-4
7-12-4-4
7-12-4-4
8-10-4-4
7-12-4-4
7-12-4-4
--5-13-4-4
7-11-4-4

125

This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
Almeida et al., 2021
This study
This study
This study
This study
This study

CEM172168
CEM106437
CEM185945
CEM185390
CEM214604
CEM144799
CEM231013
CEM234341
CEM76660
CEM79414
CEM237331
CEM245254
CEM169267
CEM159063
CEM172034
CEM172061
CEM179075
T9T302
T2T48/20
T2T45/20
T4T99
T4T173
CEM125295
CEM102273
CEM125338
CEM159190

Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Paraná
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Paraná
Paraná
Paraná
Paraná

36.9
54.5
45
45
45
53.2
36
35.4
31.5
50
34
34.5
45.2
48
38.7
35
39
37
36.5
38.5
34.9
37.4
37.9
34.3
37.2
34.5

CMA5
CMA5
CMA8
CMA8
CMA23
CMA9
CMA8
CMA8
CMA5
CMA8
CMA8
CMA8
CMA8
CMA5
CMA5
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA5
CMA9

CMA5.1
CMA5.1
CMA8.1
CMA8.1
CMA9.1
CMA8.1
CMA8.1
CMA5.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA5.1
CMA5.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA9.1

7-12-4-4
7-11-4-4
7-12-4-4
8-12-4-4
--7-13-4-4
7-12-4-4
--7-12-4-4
7-11-4-4
6-13-4-4
7-11-4-4
7-12-4-4
7-12-4-4
6-12-4-4
7-12-4-4
7-12-4-4
----------7-15-4-4
-------

126

This study
This study
This study
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
This study
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
This study
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021

CEM166177
CEM166681
CEM101221
T1T110
T7T12
T7T124
T4T223
T2T121
T5T78
T7T85
T4T181
T3T37
T7T59
T4T228
T4T219
T7T34
T4T139
T3T5
T3T81
T7T9
T2T8
T9T111
T5T9
T5T179
T8T105
T8T195

Paraná
Paraná
Paraná
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas

32
39.3
33.2
37.2
45
43
27.5
52
40.3
37.3
43.5
36.5
42.3
44.5
38.1
47.3
46.4
39
44
43.4
48.6
38.5
48.5
40
47.8
34.3

CMA5
CMA8
CMA5
CMA8
CMA8
CMA5
CMA8
CMA8
CMA8
CMA8
CMA8
CMA5
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA5
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8

CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA5.1
CMA8.1
CMA8.1
CMA8.1
CMA8.3

------7-16-4-4
7-12-4-4
8-11-4-4
7-13-4-4
7-12-4-4
7-16-4-4
7-12-4-4
7-11-4-4
6-12-4-4
8-16-4-4
7-11-4-4
3-13-4-4
7-12-4-4
6-13-4-4
7-13-4-4
6-16-4-4
7-12-4-4
7-12-4-4
7-13-4-4
6-12-4-4
--7-15-4-4
7-11-4-4

127

Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021
Almeida et al., 2021

T4T98
T5T149
T8T84
T8T59
T3T124
T5T148
T8T70
T3T125
T3T101
T8T53
T9T284
T5T123
T8T48
T4T54
T1T39
T1T45
T1T15
T1T56
T1T76
T1T85
T1T122
T1T23
T2T123
T3T113

Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas

51.3
42.3
39.5
35.4
50
47.2
40
35.5
38
51.3
47
51.7
38.2
40
45.5
39.8
35.2
40.1
36.3
41.5
49.1
38.1
53.2
46

CMA8
CMA8
CMA5
CMA8
CMA8
CMA9
CMA8
CMA8
CMA9
CMA8
CMA8
CMA8
CMA8
CMA8
CMA5
CMA8
CMA8
CMA5
CMA9
CMA8
CMA10
CMA8
CMA8
CMA8

This study

T4T252

Alagoas

45.3

New haplotype

CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA9.1
CMA8.1
CMA9.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA5.1
CMA8.1
CMA8.1
CMA5.1
CMA9.1
CMA8.1
CMA10.1
CMA8.1
CMA8.1
CMA8.1
New
haplotype

7-11-4-4
7-13-4-4
7-12-4-4
7-12-4-4
7-12-4-4
7-12-4-4
6-12-4-4
7-11-4-4
7-12-4-4
7-12-4-4
7-15-4-4
8-11-5-5
7-12-4-4
7-12-4-4
6-12-4-4
7-12-4-4
7-12-4-4
6-12-4-4
7-13-4-4
6-17-4-4
7-13-4-4
7-12-4-4
7-12-4-4
7-13-4-4
7-12-4-4

128

T4T278
T1T81
T1T37
T1T107
T9T315
T2T103
T2T104
T5T158
T7T134
T9T318
T4T227
T8T126
T9T158
T3T134
T1T48 /2018
T1T78 /2018
T2T11 /2018
T2T91 /2018
T1T4 /2018
T1T46 /2018
T1T121 /2018
T2T6 /2018
T2T51 /2018
T2T85 /2018
T2T96 /2018
T3T66 /2018

Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas

52.2
36.1
31.4
49.8
55
46
53
41
52
36.5
39.8
41
25
50
38.1
43.5
47.5
42.2
38.4
52.5
39.4
51.6
49.1
57.5
43.2
58

CMA8
CMA8
CMA8
CMA5
CMA8
CMA8
CMA5
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA8
CMA6
CMA23
CMA5
CMA8
CMA5
CMA8
CMA8
CMA8
CMA5
CMA8
CMA8

CMA8.1
CMA8.1
CMA8.1
CMA5.1
CMA8.1
CMA8.1
CMA5.1
CMA8.1
CMA8.1
CMA8.2
CMA8.1
CMA8.1
CMA8.1
CMA6.1
CMA23.1
CMA8.1
-

----7-13-4-4
5-13-4-4
8-12-4-4
8-12-4-4
--7-12-4-4
5-15-4-4
7-11-4-4
7-12-4-4
7-12-4-4
8-11-4-4
-

129

T3T108 /2018
T3T116 /2018
T3T121 /2018
T4T244 /2018
T4T37 /2018
T4T175 /2018
T5T16 /2018
T6T36 /2018
T7T10 /2018
T7T61 /2018
T5T6 /2018
T5T67 /2018
T5T114 /2018
T5T115 /2018
T5T157 /2018
T6T26 /2018
T7T166 /2018
T8T190 /2018
T9T42 /2018
T9T48 /2018
T9T76 /2018
T3T47 /2018
T4T164 /2018
T4T169 /2018
T4T235 /2018
T3T65 /2018

46.4
38.5
54
56.7
50.8
53.7
37.2
23
57.3
52.3
54
44.6
59.2
59
59
42.3
44
52
52.2
38
37
55.5
50.3
35.7
58.5
49.5

CMA8
CMA8
CMA3
CMA8
CMA46
CMA8
CMA8
CMA6
CMA5
CMA8
CMA8
CMA8
CMA5
CMA8
CMA8
CMA9
CMA5
CMA39
CMA8
CMA8
CMA8
CMA5
CMA6
CMA8
CMA6
CMA8

CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA8.1
CMA5.1
CMA6.1
CMA8.1
CMA6.1
CMA8.1

130

Almeida et al., 2021
Almeida et al., 2021
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study
This study

T3T109 /2018
T3T123 /2018
T1T5/2021
T1T34/2020
T4T84
T4T285
T7T58
T8T14
T8T179
T1T18
T1T20
T1T30
T1T116
T1T201
T2T38
T2T50
T2T55
T2T81
T2T86
T2T211
T2T212
T3T71/2020
T3T72/2020
T1T45/2020
T3T7/2020
T4T137/2020

50.7
33
36
38.5
36.5
29.8
38.4
37
37
43.5
41.3
55.3
40.3
47.5
42.6
40.5
41.5
59.7
57.1
41
44
57.5
43
33.5
33.2
54.3

CMA8
CMA8
CMA5
CMA8
CMA5
CMA8
CMA8
CMA8
CMA8
CMA5
CMA5
CMA5
CMA8
CMA8
CMA5
CMA8
CMA5
CMA8
CMA8
CMA8
CMA5
CMA5
CMA8
CMA5
CMA5
CMA5

CMA8.1
CMA8.1
-

131

This study
This study
This study
This study
This study
This study
This study
This study
This study

T1T207
T2T185
T3T49/2020
T1T48/2020
T2T61/2020
T2T68/2020
T3T13/2020
T1T35/2020
T3T63/2020

Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas
Alagoas

44
56
56
56
60
58.5
45
45
58

CMA8
CMA5
CMA8
CMA9
CMA8
CMA8
CMA10
CMA8
CMA8

References
Almeida JPFA, Santos RG, Mott T (2021) Sex ratios and natal origins of green turtles from feeding grounds in the Southwest
Atlantic Ocean. ICES Journal of Marine Science 78:1840–1848. doi: 10.1093/icesjms/fsa.
Bjorndal, K. A., Bolten, A. B., and Troëng, S. 2005. Population structure and genetic diversity in green turtles nesting at Tortuguero,
Costa Rica, based on mitochondrial DNA control region sequences. Marine Biology, 147: 1449–1457.
Bjorndal, K. A., Bolten, A. B., Moreira, L., Bellini, C., and Marcovaldi, M. Â. 2006. Population structure and diversity of brazilian
green turtle rookeries based on mitochondrial DNA sequences. Chelonian Conservation and Biology, 5: 262–268.
Encalada, S. E., Lahanas, P. N., Bjorndal, K. A., Bolten, A. B., Miyamoto, M. M., and Bowen, B. W. 1996. Phylogeography and
population structure of the Atlantic and Mediterranean green turtle Chelonia mydas: A mitochondrial DNA control region
sequence assessment. Molecular Ecology, 5: 473–483.
Formia, A., Godley, B. J., Dontaine, J. F., and Bruford, M. W. 2006. Mitochondrial DNA diversity and phylogeography of

132

endangered green turtle (Chelonia mydas) populations in Africa. Conservation Genetics, 7: 353–369.
Formia, A., Broderick, A., Glen, F., Godley, B., Hays, G., and Bruford, M. 2007. Genetic composition of the Ascension Island green
turtle rookery based on mitochondrial DNA: implications for sampling and diversity. Endangered Species Research, 3: 145–
158.
Shamblin, B. M., Bjorndal, K. A., Bolten, A. B., Hillis-Starr, Z. M., Lundgren, I., Naro-Maciel, E., and Nairn, C. J. 2012. Mitogenomic
sequences better resolve stock structure of southern Greater Caribbean green turtle rookeries. Molecular Ecology, 21: 2330–
2340.
Patrício, A. R., Formia, A., Barbosa, C., Broderick, A. C., Bruford, M., Carreras, C., Catry, P., et al. 2017. Dispersal of green turtles
from Africa’s largest rookery assessed through genetic markers. Marine Ecology Progress Series, 569: 215–225.