ads:
UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL
INSTITUTO DE BIOCIÊNCIAS
PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA E BIOLOGIA MOLECULAR
ABORDAGENS FILOGENÉTICAS, FILOGEOGRÁFICAS E
POPULACIONAIS
EM CANÍDEOS SUL-AMERICANOS
Ligia Tchaicka
Tese submetida ao Programa de Pós-
Graduação em Genética e Biologia Molecular
da UFRGS como requisito parcial para a
obtenção do grau de Doutor em Ciências
Orientador: Dr. Thales Renato Ochotorena de Freitas
Co-orientador: Dr. Eduardo Eizirik
Porto Alegre
Outubro de 2006
ads:
Livros Grátis
http://www.livrosgratis.com.br
Milhares de livros grátis para download.
2
Instituições e Fontes Financiadoras
Laboratório de Citogenética e Evolução, Departamento de Genética, UFRGS
Centro de Biologia Genômica e Molecular, Faculdade de Biociências, PUCRS
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
ads:
4
AGRADECIMENTOS
_________________________________________________________________
Este trabalho é resultado de um esforço conjunto de diversas pessoas. Não existe
ordenamento (a lista abaixo não segue ordem de importância) ou quantificação
adequados para agradecê-las, são todas imprescindíveis...
Ao meu orientador Thales R. O. Freitas pela confiança que sempre depositou no
meu trabalho, pela paciência e pela amizade.
Ao meu orientador Eduardo Eizirik (Duda), também pela confiança e paciência,
pelos ensinamentos e discussões que tanto contribuiram a minha formação como
cientista, e principalmente pela amizade.
Aos professores do Programa de Pós-Graduação em Genética e Biologia
Molecular da UFRGS pela sua preciosa colaboração a minha formação.
Ao Elmo Cardoso e à Ellen Meseck sempre disponíveis para as soluções de
problemas.
À Lucia Andréa Oliveira pela convivência, pela simpatia, e especialmente pela
ajuda na fase final do trabalho.
Ao Luciano e à Rose pela ajuda nos procedimentos cotidianos e pelas divertidas
conversas.
A toda equipe do Laboratório de Genômica da PUCRS, especialmente a
Cladinara Sarturi, Felipe Grazziotin e Nelson Fagundes, pela acolhida e pelo
apoio com as técnicas e análises.
Aos colegas do Departamento de Genética pela agradável convivência.
Aos colegas do laboratório de Citogenética e Evolução (não citarei nomes para
não esquecer ninguém), que ao longo desses anos compuseram um ambiente
agradável, animado e produtivo... obrigado pelos cafés, risadas, incentivos (em
todas as áreas!)... por todas as pequenas-grandes coisas que tornam a vida
melhor.
Aos colegas ¨carnivorólogos¨, que comigo compartilham objetivos maiores,
especialmente a Cristine Trinca, Taiana Haag, Manuel Rodrigues, Tatiane
Campos Trigo, Paulo Prates, Paulo Chaves e Fernanda Pedone Valdez pelas
valiosas discussões (cientificas ou não), auxilio nos procedimentos e amizade.
6
Aos meus pais Arilda e Natalio Tchaicka, que mesmo quando distantes se fazem
presentes em todos os momentos de minha vida, pelo amor que forneceu os
alicerces para construir meus sonhos e que apoia cada fase de sua realização.
Minhas vitórias são suas.
Ao meu irmão Cleber Tchaicka, por todo apoio (especialmente o logístico), pelas
tele-consultas, e por todo o carinho e incentivo.
A toda minha família: tios, primos, avós (in memorian), pelo carinho, apoio e
incentivos que sempre me deram.
Aos diversos colaboradores que cederam amostras de tecido para realização
deste trabalho: Dênis Sana, Tadeu de Oliveira, José Flávio Cândido Junior,
Mariana Faria-Corrêa, Alex Bager, Jose Néri Bernardi, Euclécio Elger, Luís Carlos
Diniz, Tatiane C. Trigo, Ana Paula Brandt, Ronaldo G. Morato, Flávio H. G.
Rodrigues, Rodrigo Jorge, Julio Dalponte, Guillermo D´Elia, Sergio Althoff, José
Francisco Stolz, Cristiana Prada, Margarete Mattevi, Fernanda Michalski, Roberto
Portela, Fabrício Horta, Vanderson C.Vaz, Cláudio V. Lyra, Poly-Ana Celina,
Warren Johnson, Robert K. Wayne, Andrés Novaro, Mauro
SUMÁRIO
RESUMO......................................................................................................... 8
ABSTRACT...................................................................................................... 10
Capítulo I INTRODUÇÃO.................................................................................
12
1.1 Os Canídeos..............................................................................................
13
1.2 A família Canidae na América do Sul........................................................ 15
1.2.1 Taxonomia dos canídeos sul-americanos...............................................
17
1.2.2. O gênero Lycalopex............................................................................... 20
1.2.3 Cerdocyon thous..................................................................................... 22
1.3 Estudos genéticos em populações naturais...............................................
25
1.3.1 Os Marcadores Moleculares................................................................... 26
1.3.1.1 DNA Mitocondrial................................................................................. 26
1.3.1.2 Marcadores nucleares......................................................................... 27
1.3.2 Alguns Dados Genéticos em Canídeos.................................................. 28
Capítulo II OBJETIVOS................................................................................... 31
Capítulo III 1
o
ARTIGO: Phylogeography and population history of the crab-
eating fox (Cerdocyon thous)……………………………………………………..
33
Capítulo IV 2
o
ARTIGO: POPULATION GENETIC STRUCTURE OF THE
CRAB-EATING FOX (Cerdocyon thous) INFERRED FROM
MICROSATELLITE LOCI………………………………………………………….
88
Capítulo V 3
o
ARTIGO: Molecular phylogeny of a recently diversified
endemic group of South American canids (Mammalia: Carnivora: Canidae)..
117
Capítulo VI DISCUSSÃO................................................................................ 164
REFERÊNCIAS BIBLIOGRÁFICAS............................................................... 172
8
RESUMO
O presente estudo foi realizado para investigar os padrões filogeográficos
de sete espécies de canídeos sul-americanos. Um fragmento de 588pb da região
controladora do DNA mitocondrial foi obtido para seis espécies do gênero
Lycalopex, e usado para inferir as relações evolutivas entre estas espécies. A
análise indicou L. vetulus como espécie basal, L. fulvipes como taxa monofilético,
L. culpaeus e L. griseus como espécies muito próximas. Padrões intraespecificos
da variação genética foram também abordados para o gênero Lycalopex e
intensivamente investigados em Cerdocyon thous, neste através de um fragmento
de 512pb da região controladora do DNA mitocondrial, três íntrons nucleares e
dez loci de microssatélites.
L. fulvipes, L. gymnocercus e Cerdocyon thous mostraram partição
geográfica entre a distribuição de seus haplótipos, indicando que barreiras
históricas influenciaram a variabilidade genética atual. Os processos que geraram
estes padrões e causaram a especiação do gênero Lycalopex provavelmente
ocorreram no Pleistoceno, determinados pelas modificações na distribuição da
vegetação e pelas oscilações nos níveis do mar.
Os três diferentes marcadores utilizados para a abordagem de Cerdocyon
thous mostraram-se informativos e sua análise conjunta indicou que a maior parte
do fluxo gênico é determinado pelos machos nesta espécie. Os marcadores
nucleares inferiram alta variabilidade e ausência de isolamento entre as
populações do cachorro-do-mato.
10
ABSTRACT
The present study was performed to investigate phylogeographic patterns
of seven South American canid species. A 588bp fragment of mitochondrial DNA
control region was obtained for the six species of Lycalopex genera, and used to
infer evolutionary relationships between them. These analysis indicates L. vetulus
as a basal species, L. fulvipes as a monophyletic taxa, and that L. culpaeus and L.
griseus are closer species. Intraspecific patterns of genetic variation were also
investigated for Lycalopex genera and were intensively investigated on Cerdocyon
thous, in this latter by 512bp fragment of mitochondrial DNA control region, three
nuclear introns and ten microsatellite loci.
L. gymnocercus, L. fulvipes and Cerdocyon thous shown geographic
partition between haplotype distributions, inferring that historical barriers had
influenced the actual genetic variability. The processes that generate these
patterns and caused the Lycalopex speciation probably took place on Pleistocene,
caused by the modifications on vegetation distribution and variation on sea levels.
Three different markers used for Cerdocyon thous approach were
informative and their conjunct analysis indicates that gene flow can be male
biased in this species. Nuclear markers inferred high variability and no geographic
isolation between crab-eating fox populations.
12
Capítulo I
INTRODUÇÃO
1.1 Os Canídeos
A família Canidae, pertencente à Ordem Carnívora (subordem Caniformia,
superfamília Canoidea) (Flyn e Nedbal, 1998) compreende 16 gêneros e 36
espécies atuais (Nowak, 1999).
De distribuição ampla, os canídeos são habitantes nativos de quase todos
os continentes, com exceção de ilhas do Caribe, Madagascar, Taiwan, Filipinas,
Borneo, Nova Guiné e Antártica. Na Austrália e Nova Zelândia existem
populações selvagens destes animais, resultantes, porém, da introdução de
linhagens primitivas do cão doméstico pelo homem. Sua distribuição abrange,
assim, uma grande variedade de hábitats, desde os quentes desertos até os
gelados campos árticos (Eisenberg, 1981; Wayne, 1996; Sillero-Zubiri et al.,
2004).
Os representantes desta família são bem caracterizados por adaptações
relacionadas ao hábito cursorial: os membros alongados e semi-rígidos terminam
em patas digitígradas. As patas anteriores usualmente possuem cinco dígitos
(sendo um deles reduzido) e as posteriores quatro, acompanhados por garras
bem desenvolvidas, algo rombas e não retráteis.
A cabeça e o focinho são alongados e os músculos da bochecha são fortes,
características ligadas à captura e contenção da presa. A dentição apresenta
incisivos não especializados, longos e fortes caninos, pré-molares afiados e
molares preensores, num total de geralmente 42 dentes (Stains, 1975; Emmons e
Feer, 1990).
Nas espécies selvagens o tamanho está associado à disponibilidade de
alimento, e vai desde menos de 1 Kg e aproximadamente 400cm de comprimento
nas raposas dos gêneros Fenecus e Vulpes (nativas de zonas áridas do Oriente
Médio) até, cerca de 60Kg e 1600mm para alguns lobos (Canis lupus - os maiores
animais são encontrados no Alasca e Canadá) (Nowak, 1999; Sillero-Zubiri e
Macdonald, 2004).
Muitos canídeos vivem em grupos e são exclusivamente carnívoros,
capturando presas grandes em cooperação, apresentando uma organização
social bastante complexa. Outros são solitários ou formam pares, predando
14
principalmente pequenos animais, sendo em vários casos onívoros. Algumas
espécies mostram-se bastante oportunistas, variando sua dieta de acordo com a
disponibilidade de alimento (Stains, 1975; Ginsberg e Macdonald, 1990; Wayne,
1996).
Quanto à reprodução, as fêmeas têm, em geral, uma gestação por ano que
dura em média 63 dias, parindo grandes ninhadas que recebem cuidado dos pais
e muitas vezes de outros membros do grupo (Emmons e Feer, 1990; Nowak,
1999).
Considerados ótimos dispersores, os canídeos são pouco limitados por
barreiras topográficas ou de hábitat. Cada indivíduo ou grupo possui uma grande
área de vida, exclusiva ou compartilhada em parte. Tal fato confere às populações
a ocupação de grandes áreas geográficas, e assim, extensa distribuição a cada
espécie (Wayne, 1996). Algumas delas habitam praticamente todo um continente,
como a raposa vermelha (Vulpes vulpes), por exemplo, que está presente em
todo o hemisfério Norte (Sillero-Zubiri e Macdonald, 2004).
As características ecológicas, morfológicas e comportamentais podem,
entretanto, variar mesmo entre populações de uma mesma espécie de canídeo,
como acontece em Canis lupus (lobo cinza). Nesta espécie, cujo peso vai de 15-
60 Kg, as ninhadas podem ter de 1 a 11 filhotes, a área de vida difere em 50-100
vezes e os indivíduos podem viver solitários, em pares ou em matilhas (Bekoff et
al., 1984).
Carismáticos e fascinantes, os canídeos sempre despertaram o interesse do
homem, espécie com a qual tem sua história intimamente ligada. A origem do cão
atual a partir do lobo, um dos poucos animais não herbívoros domesticados, pode
não ter sido o único evento de domesticação na família (Clutton-Brock, 1977;
Ostrander e Wayne, 2006). A associação entre humanos e canídeos na América
pré-colombiana é documentada por registros fósseis de cães domésticos e pela
existência de estoques ancestrais da espécie associados aos primeiros grupos
humanos da região (Olsen, 1974). No antigo Egito, os chacais estavam entre os
animais considerados divindades (Anúbis, o Deus da morte) e eram respeitados e
mumificados (Souza, 1990).
A alta mobilidade e o oportunismo ecológico são características que, a
despeito de conferirem sucesso à muitas espécies, atualmente aproximam os
canídeos selvagens do homem e os colocam em conflito (Ginsberg e Macdonald,
1990). A modificação antrópica do ambiente tem alterado amplamente a
distribuição de várias espécies da família: pelo menos sete delas aumentaram e
nove diminuíram sua distribuição no último século (Sillero-Zubiri e Macdonald,
2004).
1.2 A família Canidae na América do Sul
De acordo com o registro fóssil, a origem dos canídeos se deu no Hemisfério
Norte durante o Eoceno (Stains, 1975). Sua chegada a América do Sul, a partir da
América do Norte, foi feita através do istmo do Panamá, formado durante o fim do
Plioceno e início do Pleistoceno. Tal dispersão foi provavelmente provocada por
mudanças ambientais nas áreas próximas ou adjacentes ao ponto de travessia e
deve ter provocado um ou mais eventos de invasão (Langguth, 1975; Berta, 1987;
Wayne et al., 1997).
Após este período o grupo sofreu uma radiação adaptativa que pode ter tido
como centro de ocorrência a Argentina (Berta, 1987) ou as terras altas brasileiras
(Langguth, 1975), dando origem à grande diversidade de espécies atuais.
Os canídeos sul-americanos, como os demais mamíferos da região, são
caracterizados por alto endemismo. Doze espécies são nativas deste continente,
sendo onze delas endêmicas: Cerdocyon thous (cachorro-do-mato); Chrysocyon
brachyurus (lobo-guará); Speothos venaticus (cachorro-vinagre); Atelocynus
microtis (cachorro-de-orelha-curta); Lycalopex vetulus (raposinha-do-cerrado);
Lycalopex gymnocercus (cachorro-do-campo); Lycalopex culpaeus (zorro culpeo);
Lycalopex griseus (chilla); Lycalopex fulvipes (raposa de Darwin); Lycalopex
sechurae (zorro sechura); e Dusicyon australis (raposa das Ilhas Falkland,
atualmente extinta). Apenas a raposa cinza (Urocyon cinereoargenteus) ocorre na
América do Norte e Central e estende sua distribuição até o Norte da América do
Sul (Fig.1).
16
Os representantes da família são encontrados em todos os hábitats do
continente, dos desertos da costa do Oceano Pacífico (L. sechurae) até os
campos abertos (L. gymnocercus, L. culpaeus e L. griseus). Enquanto na África e
Ásia os canídeos evitam as florestas úmidas, uma espécie de canídeo neotropical
é habitante da floresta Amazônica (Atelocynus microtis) e outro habita as florestas
da costa atlântica e matas de galeria (Cerdocyon thous) (Ginsberg e Macdonald,
1990).
Em várias regiões do continente duas ou mais espécies sobrepõe suas
áreas: para um total de 55 pares de espécies sul-americanas possíveis, 12
mostram algum grau de simpatria (Medel e Jaksic, 1988).
A viabilidade da existência em simpatria neste grupo está provavelmente
relacionada ao grande oportunismo alimentar. Os estudos conduzidos revelaram
que, a sobreposição de habitat é compensada pela diminuição na sobreposição
da dieta (para L. culpaeus e L. griseus: Fuentes e Jaksik, 1979; Jaksic et al.,
1983; para C. thous, C. brachyurus e L. vetulus: Juarez e Marinho-Filho, 2002).
Apesar da alta diversificação dos canídeos sul-americanos em relação aos
outros continentes, esta é ainda a região com maior carência de dados acerca de
suas espécies. Três delas (A. microtis; L. vetulus e L. sechurae) não tem seu
status de conservação determinado devido à insuficiência de dados, enquanto
Speothos venaticus é considerada vulnerável; Chrysocyon brachyurus ameaçada;
L. fulvipes criticamente ameaçada; e D. australis foi recentemente extinta (1880)
por ação humana (Ginsberg e Macdonald, 1990; Clutton-Brock 1977; IUCN, 2003;
Sillero-Zubiri e Macdonald 2004).
1.2.1 Taxonomia dos canídeos sul-americanos
Segundo Berta (1987), a primeira referência a um canídeo na América do
Sul foi feita por Kerr 1792, descrevendo Canis australis das ilhas Falkland (costa
leste da Argentina). Desde então seguiram-se várias descrições, e diferentes
esquemas taxonômicos foram propostos baseados em métodos diversos (ex.
Thomas, 1914; Kraglievich, 1930; Cabrera, 1931; Osgood, 1934; Hough, 1948;
Thenius, 1954; Langguth, 1969; 1975; Clutton-Brock et al., 1976; Van Gelder,
1978; Berta, 1987; Wayne, 1993; Zunino et al., 1995).
Entre estes, Langguth (1975), baseado em dados ecológicos e morfológicos,
arranjou os canídeos sul americanos em dois grupos: o grupo com estruturas
diferenciadas e o grupo com padrões gerais de canídeos. Do primeiro fazem parte
os gêneros Chrysocyon, Cerdocyon, Speothos, Atelocynus e Lycalopex. O
segundo grupo é considerado como pertencente a um único gênero: Canis,
composto por dois subgêneros, Dusicyon e Pseudalopex. O primeiro compreende
apenas o recentemente extinto C. (Dusicyon) australis e o segundo possui quatro
espécies C.(P.) culpaeus, C.(P.) gymnocercus, C.(P.) griseus e C.(P.) sechurae (a
espécie L. fulvipes não foi considerada válida neste e em vários outros esquemas
taxonômicos do grupo).
Através de características morfológicas e comportamentais, utilizando
taxonomia numérica, Clutton-Brock et al. (1976) indicaram como monotípicos
Chrysocyon e Speothos; e incluíram Pseudalopex, Atelocynus, Cerdocyon e
Lycalopex no gênero politípico Dusicyon. Este autor ainda considerou a raposa de
Darwin como subespécie de L. griseus, o que corrobora Langguth (1969).
Van Gelder (1978) propôs uma nova classificação utilizando o grau de
hibridação entre os taxa. Segundo este autor, Chrysocyon e Speothos
representariam gêneros monotípicos, ao passo que Canis possuiria oito
subgêneros, dos quais seis são sul americanos: Dusicyon, Pseudalopex,
Lycalopex, Cerdocyon, Atelocynus e Vulpes (Urocyon).
Berta (1987), baseada em análise cladística de dados morfológicos e no
registro fóssil, reconheceu quatro grupos principais para os canídeos sul
americanos: (1) Urocyon; (2) Cerdocyon - incluindo os gêneros atuais Speothos,
Atelocynus e Cerdocyon, bem como outros gêneros extintos; (3) Chrysocyon e (4)
Dusicyon – incluindo dois gêneros distintos, o atual Pseudalopex e o
recentemente extinto Dusicyon. O gênero Cerdocyon, segundo a autora, é
representado atualmente apenas por C. thous, já Pseudalopex possuiria cinco
espécies atuais: P. culpaeus, P. gymnocercus, P. griseus, P. sechurae e P.
vetulus.
18
Mais recentemente, Zunino (1995), analisando características da pelagem e
medidas de crânio para as espécies de raposa da Argentina, propôs a utilização
de Lycalopex como nome para o gênero que inclui L. vetulus, L. culpaeus, L.
sechurae, e a união de L. griseus e L. gymnocercus em uma única espécie:
Lycalopex gymnocercus.
Na mesma época, Yahnke et al. (1996), através de estudos moleculares,
confirmaram a monofilia da raposa de Darwin em relação a P. griseus, elevando-a
à categoria de espécie, utilizando a nomenclatura Pseudalopex fulvipes.
Dado o grande número de diferentes propostas, a classificação permanece
controversa, especialmente no que se refere ao grupo dos animais popularmente
chamados “zorros” (espanhol), do qual fazem parte Cerdocyon thous e o gênero
Lycalopex, espécies abordadas neste estudo.
A nomenclatura mais amplamente utilizada até pouco tempo era a proposta
por Wozencraft (1993). Esse autor, revisando diversos trabalhos, concordava com
Berta (1987), descrevendo Cerdocyon thous como única espécie atual de seu
gênero, e para o gênero Pseudalopex (nomenclatura genérica proposta por
Burmeister, 1856): P. vetulus, P. gymnocercus, P. griseus, P. culpaeus e P.
sechurae. Tal classificação foi também seguida no Capitulo III do presente estudo
(pelo qual se iniciaram os trabalhos), sendo depois modificada para a proposição
mais recente de Wozencraft (2005), que propõe Lycalopex (nomenclatura
genérica mais antiga proposta por Burmeister, 1854) como nomenclatura para o
gênero que inclui: L. vetulus, L. gymnocercus, L. griseus, L. culpaeus, L. sechurae
e L. fulvipes.
20
1.2.2. O gênero Lycalopex
As espécies atuais do gênero Lycalopex tiveram sua origem na América do
Sul, a partir da radiação adaptativa ocorrida durante o Pleistoceno (Berta, 1987) e
distribuem-se pela maior parte da região (Fig.1).
O maior canídeo do gênero é L. culpaeus, o zorro colorado ou zorro andino.
A espécie apresenta um considerável dimorfismo sexual, sendo os machos em
média 1.5 vezes maior que as fêmeas, os primeiros chegando a pesar 11 Kg.
Possui as extremidades das patas claras, assim como a área ventral, e o restante
do corpo castanho com as pontas da cauda e orelhas escuras (Crespo, 1975;
Parera, 2002; Jimenez e Novaro, 2004). Habita as terras altas do oeste da
América do Sul, ao longo dos Andes, desde a Colombia até a Terra do Fogo
(Argentina), passando pelo Peru, Chile, Equador e Bolívia, sendo encontrado em
ambientes de florestas até desertos (Langguth, 1975; Jiménez e Novaro, 2004).
Em algumas dessas áreas ocorre em simpatria com L. griseus, ou zorro
gris, cuja distribuição abrange as planícies e montanhas aos dois lados dos
Andes, desde os 17S no Chile ate 54S na Terra do Fogo, sendo encontrado a
oeste até a costa chilena e a leste até aproximadamente a região central da
Argentina. Esta raposa e bastante tolerante a variações de clima e apesar de
habitar diversos ambientes prefere áreas abertas (González del Solar e Rau,
2004).
Lycalopex griseus é uma das menores raposas sul-americanas
(aproximadamente 4Kg), possui orelhas grandes e coloração acinzentada, com
uma linha dorsal e a ponta da cauda escuras (Duran et al., 1985).
Lycalopex fulvipes, conhecida popularmente como raposa de Darwin (o
primeiro exemplar foi coletado por Charles Darwin em 1834) é uma espécie de
distribuição muito restrita. Apenas duas populações, disjuntas, limitadas a áreas
de floresta úmida, são registradas para estas raposas: uma na Ilha Chiloé e outra
nas montanhas do Parque Nacional de Nahuelbuta, ambos na costa chilena. Os
indivíduos dessa espécie são muito pequenos, apresentam corpo alongado e
pernas curtas, com tonalidade entre cinza e negro (Yahnke et al., 1996; Vilà et al.,
Lycalopex sechurae é um canídeo de coloração amarelo-acinzentada e
região ventral mais clara, cabeça pequena com orelhas longas e um anel
castanho ao redor dos olhos. É uma espécie de tamanho pequeno pesando em
media 3,5 Kg. Existem registros de sua distribuição apenas na costa noroeste do
Peru, chegando à fronteira com o Equador (Nowak, 1999; Eisenberg e Redford
1999; Asa e Cossíos; 2004).
Duas espécies do gênero Lycalopex habitam as terras brasileiras: L.
gymnocercus e L. vetulus (ver Fig. 1).
Lycalopex gymnocercus é o canídeo popularmente conhecido como
graxaim-de-campo, cachorro-do-campo ou zorro pampeano. Sua coloração cinza
amarelada tem tendência ao marrom ferrugineo no alto da cabeça. O peito é
claro, bem como as extremidades das orelhas e patas e a ponta da cauda
apresenta-se escura (Crespo 1971; Silva, 1994).
É bastante similar, em termos de morfologia externa, a Cerdocyon thous,
sendo na língua guarani denominado da mesma forma que o primeiro como
Aguará cha’i. No entanto distingui-se do cachorro do mato pelas orelhas maiores
e mais triangulares, o focinho mais anguloso, a cauda mais comprida e peluda.
Seu peso varia de 4-6,5Kg, sendo os machos 10% mais pesados do que as
fêmeas (Parera, 2002).
Habitante de áreas abertas, freqüentemente bordas de matas, campos e
capoeiras, L. gymnocercus é encontrado desde o leste da Bolívia, Paraguai,
sudeste e sul do Brasil até o Uruguai e a Argentina (até a Província de Rio Negro)
(Crespo, 1971, 1975; Medel e Jaksic 1988).
Lycalopex vetulus, a raposinha-do-cerrado, e uma espécie endêmica do
Brasil, associada ao Cerrado e áreas de transição como o Pantanal. Sua
ocorrência é registrada nos estados de Minas Gerais, São Paulo, Goiás,
Tocantins, Mato Grosso do Sul e Mato Grosso, Piauí e Bahia. De pequeno porte,
L. vetulus tem em média 3,5Kg, apresenta coloração cinza-amarelada, com as
patas e a região ventral mais claras (Courtenay et al., 2006).
Em geral, os representantes do gênero Lycalopex são considerados
solitários, podendo em algumas espécies ser encontrados em pares durante a
22
época reprodutiva, e apresentam hábitos noturnos e crepusculares (Silva, 1994;
Cimardi, 1996; Eisenberg e Redford, 1999; Parera, 2002; Courtenay et al., 2006).
Estudos acerca da dieta nestas espécies relatam que os indivíduos
alimentam-se tanto de pequenos animais como vegetais (Parera, 2002; Jaksic et
al., 1980). Apresentam-se também bastante oportunistas, variando a composição
de sua dieta de acordo com a época do ano e o tipo de ambiente. Entre os
animais consumidos encontram-se aves, répteis, insetos e mamíferos, a maioria
silvestres. Em áreas habitadas por humanos, apenas uma pequena parte dos
animais incluídos na dieta são domésticos, e estes muitas vezes são encontrados
já mortos (não predados), porém o estigma de ameaça aos rebanhos de ovinos
tem tornado estas raposas alvo de combate por parte de produtores rurais
(Crespo, 1971; Dotto, 1997; Nowak, 1999; Parera, 2002). Dentre as espécies
deste grupo, considera-se que L. culpaeus possui a dieta com maior porcentagem
de carne, e L. vetulus possui a dieta mais especializada, sendo composta
predominantemente de insetos, especialmente térmitas e besouros (Courtenay et
al., 2006; Jaksic et al., 1980; Pia et al., 2003).
Estes canídeos aproximam-se com facilidade do homem e habitam áreas
antropicamente modificadas como pastagens. Uma das principais ameaças às
espécies é o uso de sua pele na produção de casacos (Crespo, 1971; Cimardi,
1996; Nowak, 1999; Parera, 2002).
1.2.3 Cerdocyon thous
Cerdocyon thous é uma espécie de distribuição ampla, presente em todo o
Brasil (com exceção da planície amazônica); sua ocorrência estende-se pelas
Guianas, Venezuela, Colômbia, Leste da Bolívia, Norte da Argentina e Uruguai
(Langguth, 1975; Medel e Jaksic, 1988; Eisenberg, 1989; Redford e Eisenberg,
1992; Anderson, 1997; Eisenberg e Redford, 1999).
Por ser habitante característico de florestas abertas, recebe a denominação
popular de cachorro-do-mato, graxaim-do-mato ou zorro de monte (países de
língua espanhola), porém é também comumente encontrado em áreas de savana
e pradaria (Langguth, 1975; Berta, 1982; Medel e Jaksic, 1988; Ginsberg e
Macdonald, 1990; Nowak, 1999; Parera, 2002).
Apesar de haver variação na coloração em determinadas épocas, pode-se
definir sua pelagem como amarela-acinzentada. A linha dorsal do corpo é mais
escura, formando uma faixa negra característica que se estende da cabeça até a
cauda, sendo escuras também as extremidade dos membros e da cauda (Berta,
1982; Silva, 1994; Parera, 2002). É um canídeo de aproximadamente 80-120cm e
peso em torno de 5-8Kg (Nowak, 1999) com uma dentição caracterizada pelos
carniceiros pequenos em relação aos molares grandes (Berta, 1982).
A reprodução da espécie foi abordada apenas nos trabalhos de Brady
(1978), realizado com animais de cativeiro, e de Macdonald e Courtenay (1996),
com populações naturais da Ilha de Marajó (Pará/Brasil). O primeiro autor relata a
ocorrência de duas crias anuais, com intervalo de oito meses, já no segundo
trabalho é observada apenas uma cria anual. A época de maior número de
nascimentos fica entre os meses de janeiro e fevereiro para os animais cativos e
entre novembro e dezembro para as populações de Marajó. Brady (1978)
descreve o período de gestação como de 59 dias (dado corroborado por
Macdonald e Courtenay, 1996) com o nascimento de três a seis filhotes, que
recebem cuidados de ambos os pais.
A maior parte dos estudos realizados nesta espécie abordam sua dieta e o
consideram um generalista. Através de estudos em ambientes bastante
diversificados, em síntese, os trabalhos relatam o consumo de pequenos
mamíferos, répteis, anfíbios, insetos, crustáceos, aves, frutos diversos e ovos.
Embora prefira pequenos vertebrados, o graxaim do mato ajusta sua ingesta
consumindo mais vegetais ou insetos de acordo com a disponibilidade do
alimento em cada época. Como oportunista, pode contribuir com a regulação de
populações naturais (Montgomery e Lubin, 1978; Brady, 1979; Bisbal e Ojasti,
1980; Berta, 1982; Olmos, 1993; Motta-Junior et al., 1994; Macdonald e
Courtenay, 1996; Facure e Monteiro-Filho, 1996; Facure e Giaretta, 1996).
Geralmente atribui-se o hábito solitário a C. thous, porém, vários dados
sugerem que este canídeo viva em pares ou em grupos maiores compostos por
unidades familiares (Montgomery e Lubin, 1978; Brady, 1979; Macdonald e
Courtenay, 1996).
24
Os valores estimados para a área de vida de cada indivíduo da espécie vão
de 0,3 Km
2
a 15 Km
2
, considerando diversas regiões de estudo e diversas
estações anuais (Brady, 1979; Sunquist et al., 1989; Macdonald e Courtenay,
1996; Michalski, 2000). A extensão das áreas utilizadas parece variar de acordo
com o tipo de ambiente e com a estação do ano, da mesma forma como varia a
tolerância entre indivíduos na sobreposição de áreas. Tais diferenças podem
estar relacionadas à disponibilidade de alimento (Brady, 1979).
Quando em pares, os indivíduos usam áreas que se sobrepõem e ambos as
marcam com urina, embora não cacem em cooperação (Brady, 1979; Biben,
1982). Em relação à dispersão dos indivíduos, os novos casais formados passam
a habitar áreas adjacentes as de seu grupo familiar natal, retornando
posteriormente de forma intermitente ao antigo grupo (Macdonald e Courtenay,
1996).
Durante o dia o graxaim do mato permanece em repouso, geralmente em
moitas de vegetação, forrageando intensamente durante a noite (Berta, 1982).
Procuram com muita freqüência áreas habitadas por humanos em busca de
restos alimentares ou margens de estradas onde predam pequenos mamíferos.
Tais hábitos acabam por torná-os muito suscetíveis a ações humanas. Vistos
como predadores de animais domésticos, são perseguidos, e nas rodovias são
freqüentemente atropelados (Silva, 1994; Cimardi, 1996; Becker e Dalponte,
1999).
1.3 Estudos genéticos em populações naturais
As informações genéticas obtidas pela análise de marcadores moleculares
têm contribuído muito para o entendimento das relações evolutivas e ecológicas
entre indivíduos, populações e espécies.
É ampla a utilização de polimorfismos de DNA para estudos filogeográficos.
Estes investigam os princípios e processos que determinam as distribuições
geográficas das linhagens genealógicas, especialmente dentro e entre espécies
muito próximas (Riddle, 1996; Avise, 2000). O tempo e o espaço são
considerados os eixos principais nos quais são mapeadas as genealogias de
interesse, através da integração de informações provenientes da genética de
populações, etologia, demografia, biologia filogenética, paleontologia, geologia e
biogeografia histórica, num esforço em conciliar diversas disciplinas micro e
macroevolutivas (Avise, 2000).
Nestes estudos, os caracteres moleculares representam uma fonte rica de
informação para a reconstrução de filogenias e diversas análises baseadas em
coalescência, para as quais o campo teórico e analítico tem se desenvolvido
consideravelmente (ex. Huelsenbeck e Ronquist 2001; Beerli e Felsenstein, 2001;
Hey e Nielsen, 2004). As inferências obtidas através destes métodos podem,
dentro de seus limites, indicar o tempo aproximado e a seqüência de eventos que
deram origem a grupos de indivíduos e servir como diagnóstico final para definir o
status taxonômico destes (Templeton, 2001; Frankland et al., 2003; Zhang e
Hewitth, 2003).
Em escala populacional, o uso de dados genéticos têm crescido
significativamente em estudos de estruturação (ex. Dalén et al., 2002; Dalén et al.,
2005; Iyengar et al., 2005); paternidade e parentesco (ex. Vigilant et al., 2001,
Seddon et al., 2005; Cutrera et al., 2005), dispersão de indivíduos (ex. Sacks et
al., 2004; Geffen et al., 2004) entre outras características da dinâmica das
populações.
A reconstrução destes padrões evolutivos, especialmente a nível infra-
específico, tem sido de grande importância para a determinação de estratégias
adequadas para a conservação de espécies (Eizirik, 1996). As subdivisões
genéticas encontradas correspondem a uma fração significativa da
biodiversidade, e a diversidade genética é componente fundamental da
diversidade biológica existente em uma determinada região (Moritz, 1994; Moritz
e Faith, 1998; Avise, 2000).
1.3.1 Os Marcadores Moleculares
Diversos fatores como tipo de herança e processos mutacionais determinam
características próprias a cada marcador molecular, especialmente entre
26
segmentos de DNA nuclear e de organelas. Torna-se interessante, assim, a
incorporação de diferentes marcadores nos estudos em populações naturais.
1.3.1.1 DNA Mitocondrial
O DNA mitocondrial (mtDNA) de animais consiste de um genoma haplóide,
circular, de pequeno tamanho que está presente em centenas a milhares de
cópias por célula (Ferreira, 2001).
Nos vertebrados, está organizado em sua forma mais simples, onde um total
de 37 genes é contido em um segmento circular de 16 a 17 kb, tendo pouco ou
nenhum espaço entre eles (Snustad e Simmons, 1997). Sua seqüência única (não
repetitiva) conta com 13 genes codificadores de proteínas, 2 genes para rRNA, 22
genes para tRNA e uma região controladora que contém seqüências regulatórias
para duplicação e inicio de transcrição (Graur e Li, 2000). Esta última é rica em
bases A-T (Brown, 1985) e chamada, em vertebrados, de D-Loop (Displacement
Loop) devido à formação de uma estrutura em fita tripla no início de sua
replicação (Brown et al., 1986).
A região controladora é frequentemente usada em estudos de genética de
populações dada sua alta variabilidade em seqüência de nucleotídeos, resultado
de sua alta taxa de mutação, consideravelmente maior em todo o DNA
mitocondrial do que em segmentos nucleares. Já os genes codificadores de
proteínas, mais conservados, como o do citocromo-b, são utilizados para análise
de filogenia acima do nível específico (Pereira, 2000; Graur e Li, 2000).
As altas taxas de substituição de bases apresentadas pela região
controladora encontram-se acentuadas em duas de suas porções, chamadas
segmentos hipervariáveis (HVS1 e HVS2 [Hipervariable Segment]). Estas porções
têm extensões próximas a 350pb cada e estão separadas por uma região mais
conservada de aproximadamente 200pb (Brown, 1985).
Outro fator importante no uso do mtDNA é sua herança matrilinear que
permite a identificação de linhagens maternas que contribuíram para a formação
de diferentes populações de uma espécie. Tal característica, aliada as baixas
taxas de recombinação, rearranjos, transposições e inversões, possibilita a
obtenção de padrões filogenéticos sem a ambigüidade causada pela
recombinação em genes nucleares (Brown, 1985; Snustad e Simmons, 1997;
Avise, 2000; Ostrander e Wayne 2006).
Entretanto, apesar destas vantagens, pode haver certa limitação no emprego
deste marcador, dado que sua análise representa apenas a história evolutiva das
linhagens maternas das populações. Suas características estruturais, ainda,
caracterizam os segmentos de mtDNA como um único conjunto de genes ligados,
e sua análise diz respeito a apenas uma perspectiva na análise da variação
genética total (Wayne, 1996). Devido a isto, o seu emprego combinado a locos
nucleares nos estudos populacionais aumenta a confiabilidade dos resultados,
podendo verificar, estender e aprofundar as inferências obtidas.
1.3.1.2 Marcadores nucleares
Polimorfismos nucleares, que constituem uma oportunidade quase ilimitada
para estudos evolutivos, se encontram amplamente distribuídos pelo genoma de
eucariotos. Neste, regiões não codificantes ou intergênicas, como íntrons e
microssatélites, apresentam-se mais variáveis do que as regiões codificantes e
tem assim um amplo emprego como marcadores moleculares.
Seqüências de íntrons são ferramentas muito poderosas para obtenção de
dados de polimorfismos. Sua análise, no entanto, deve levar em conta fatores
como recombinação, seleção, heterozigosidade, inserções, deleções, baixa
divergência e politomias. Especialmente para estudos populacionais, sua
utilização é ainda incipiente (ex: Antunes et al., 2002).
Os microssatélites são parte do grupo de loci chamados VNTRs (Variable
Number of Tandem Repeats). São compostos de uma seqüência simples de não
mais que 6 pares de bases, repetidas em um número de 10 a 50 cópias, e sofrem
uma elevada taxa de mutação (10
–2
a 10
-6
mutações por loco por geração) devido
a eventos de slippage e recombinação desigual das moléculas de DNA (Scribner
e Pearce, 2000). Por apresentarem altos níveis de variabilidade (Avise, 1994;
Snustad e Simmons, 1997; Scribner e Pearce, 2000) e serem usualmente tidos
como seletivamente neutros, têm altas chances de serem afetados por curtos
28
períodos de isolamento ou endocruzamento (Tautz, 1993; Scribner e Pearce,
2000), sendo assim marcadores moleculares úteis para investigar estes
processos.
1.3.2 Alguns Dados Genéticos em Canídeos
Estudos moleculares e citogenéticos têm sido importantes ferramentas no
entendimento dos padrões evolutivos na família Canidae.
monofiléticos os canídeos sul americanos, ocorrendo dentro deste grupo a
30
Capítulo II
OBJETIVOS
O objetivo geral deste trabalho é fornecer subsídios ao conhecimento dos
canídeos sul-americanos, contribuindo com dados genéticos ao entendimento da
dinâmica das populações e história evolutiva das espécies. Para tal, tem como
objetivos específicos:
- utilizar marcadores moleculares (regiões de introns e de microssatelites
do DNA nuclear, fragmentos de DNA mitocondrial) para a análise filogeográfica e
da estruturação populacional de Cerdocyon thous.
- obter inferências a respeito das relações filogenéticas e padrões
intrapopulacionais de diversidade genética para as espécies de canídeos do
gênero Lycalopex.
32
Capítulo III
1
O
ARTIGO
aceito para publicação na revista Molecular Ecology
Phylogeography and population history of the crab-eating fox
(Cerdocyon thous)
Phylogeography and population history of the crab-eating fox
(Cerdocyon thous)
LIGIA TCHAICKA
1
, EDUARDO EIZIRIK
2,3,4
, TADEU G. de OLIVEIRA
3,5
, JOSÉ
FLÁVIO CÂNDIDO JR.
6
, THALES R.O. FREITAS
1
1
Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio
Grande do Sul, Campus do Vale – Bloco III, Av. Bento Gonçalves 9500 Porto
Alegre, RS 91501970. Brazil.
2
Centro de Biologia Genômica e Molecular, Faculdade de Biociências, PUCRS.
Av. Ipiranga 6681, prédio 12. Porto Alegre, RS 90619-900, Brazil.
3
Instituto Pró-Carnívoros, Brazil.
4
Laboratory of Genomic Diversity, NCI-Frederick, NIH; Frederick, MD 21702-
1201, USA.
5
Departamento de Biologia, UEMA. Campus I, Cidade Universitária Paulo VI,
Tirirical, Caixa Postal, 09. São Luis, MA, Brazil.
6
Centro de Ciências Biológicas e da Saúde, UNIOESTE. Rua Universitária 1.619,
Jardim Universitário Cascavel, PR 85819-110, Brazil.
Corresponding author:
Eduardo Eizirik
Faculdade de Biociências, PUCRS. Av. Ipiranga 6681, prédio 12. Porto Alegre,
RS 90619-900, Brazil. Fax: 55-51-3320-3568. Email: [email protected]
Running title: Phylogeography of Cerdocyon thous
Keywords: Cerdocyon thous – Mitochondrial DNA control region – Nuclear Introns
– demographic history – Canidae - Carnivora
34
ABSTRACT
The crab-eating fox is a medium-sized Neotropical canid with generalist
habits and a broad distribution in South America. We have investigated its genetic
diversity, population structure and demographic history across most of its
geographic range by analyzing 512 base pairs (bp) of the mitochondrial DNA
(mtDNA) control region, 615 bp of the mtDNA cytochrome b gene and 1,573 total
nucleotides from three different nuclear fragments. Mitochondrial DNA data
revealed a strong phylogeographic partition between Northeastern Brazil and other
portions of the species’ distribution, with complete separation between southern
and northern components of the Atlantic Forest. We estimated that the two groups
diverged from each other ca. 400,000 - 600,000 years ago, and have had
contrasting population histories. A recent demographic expansion was inferred for
the Southern group, while Northern populations seem to have had a longer history
of large population size. Nuclear sequence data did not support this north-south
pattern of subdivision, likely due at least in part to secondary male-mediated
historical gene flow, inferred from multi-locus coalescent-based analyses. We
compare the inferred phylogeographic patterns to those observed for other
Neotropical vertebrates, and find evidence for a major north-south demographic
discontinuity that seems to have marked the history of the Atlantic Forest biota.
INTRODUCTION
The study of comparative phylogeographic patterns often reveals important
past evolutionary processes affecting regional faunas (Avise 2000). Most studies
on phylogeography have employed mitochondrial DNA (mtDNA) sequences, which
are amenable to sophisticated genealogical analyses but reflect only a portion of
the total historical record of a sexual organismal pedigree. Thus, more complete
conclusions can be obtained by adding nuclear sequences to phylogeographic
studies (Hare 2001; Zhang & Hewitt 2003). Sequences of
36
throughout Brazil except for the Amazon basin lowlands (Courtenay & Maffei
2004). (Fig. 1). Throughout this range, this fox is subject to constant persecution
by ranchers over supposed depredation on sheep and other small livestock (Berta
1982; Ginsberg & Macdonald 1990), and are also heavily killed on roads, although
the demographic impact of these sources of mortality is currently unknown.
Several studies have addressed aspects of intra-specific phylogeography
and population history of various canids (Lehman & Wayne 1991; Wayne 1996;
Girman et al. 2001; Dalén et al. 2005); however no large-scale study has yet been
published on Neotropical members of the family. C. thous is the single living
species of its genus; its fossil record suggests that it has evolved in North America
in the late Miocene to early Pliocene, and later dispersed to South America in the
Pleistocene (Langguth 1975; Berta 1987). Five subspecies of C. thous have been
recognized on the basis of classical morphological studies (Cabrera 1931;
Langguth 1969; Berta 1982): (I) C. t. entrerianus (southern Brazil, Bolivia,
Uruguay, Paraguay, Argentina); (II) C. t. azarae (north-eastern and central Brazil);
(III) C. t. thous (south-eastern Venezuela, Guyana, Surinam, French Guiana,
northern Brazil; (IV) C. t. aquilus (northern Venezuela, Colombia); (V) C. t.
germanus (Bogotá region, Colombia) (see Fig. 1). As it has been observed for
other Neotropical carnivores that classical subspecies often do not reflect inferred
patterns of historical population subdivision (e.g. Eizirik et al. 1998), it would be
important to test such partitions in a molecular phylogeographic context.
In this study, we report patterns of genetic variation in Cerdocyon thous,
based on the analysis of DNA sequences from two mitochondrial segments and
three nuclear introns, obtained from wild-born individuals sampled throughout
most of the species’ geographic range. We draw inferences on the evolutionary
history of this species, and discuss it in comparison with patterns observed for
other Neotropical taxa. In particular, we use the combination of mitochondrial and
nuclear data sets to test the following hypotheses: (i) there is a north-south
phylogeographic break in the Atlantic Forest populations of this fox (as observed in
smaller-bodied species) in spite of its higher mobility; (ii) historical partitions
coincide with classically recognized subspecies; (iii) the observed partitions are
derived from events that occurred in the Early or Middle Pleistocene; and (iv)
male-biased gene flow leads to detection of demographic partitions with mtDNA
but not with nuclear markers.
MATERIALS AND METHODS
Sample Collection and Laboratory Techniques
Biological material was collected from 106 crab-eating fox individuals (Table
1, Fig.1) across a large area of the species’ range. Blood samples (preserved in a
salt saturated solution; 100mM Tris, 100mM EDTA, 2% SDS) were collected from
captive individuals (of known origin) and wild animals captured for ecological
studies. Other tissue samples (preserved in 95% ethanol) were obtained from
road-killed individuals. Three samples each from Pseudalopex gymnocercus and
P. vetulus were included in the protocol and used as outgroups in phylogenetic
and network-based analyses.
Genomic DNA was extracted from samples using a standard
phenol/chloroform protocol (Sambrook et al. 1989). Five different fragments were
amplified by the Polymerase Chain Reaction (PCR; Saiki et al. 1985): (I) the 5’
portion of the mtDNA control region, containing the first hypervariable segment
(HVS-I), was amplified using primers MTLPRO2 (5’-
CACTATCAGCACCCAAAGCTG) and CCR-DR1 (5’-
CTGTGACCATTGACTGAATAGC) (or H16498 [Ward et al. 1991] as an alternative
reverse primer); (II) the complete cytochrome b gene using primers CytB-DF1 (5’ -
TCTCACATGGAATTTAACCATGA - 3’) and CytB-DR1 (5’ –
GAATTTCAGCTTTGGGTGCT – 3’); (III) the second intron of the Proteolipid
Protein 1 (PLP1) gene using primers described by Murphy et al. (1999); (IV) intron
14 of the Feline Sarcoma Protooncogene (FES) using primers described by Venta
et al. (1996); and (V) intron 8 of the Precursor 1 of Cholinergic Receptor Nicotinic
Alpha Polypeptide (CHRNA1) using primers described by Lyons et al. (1997).
38
PCR was performed in 20-µl reactions containing 2µl 10X buffer, 1.5 mM
MgCl
2
, 0.2 µM dNTPs, 0.2 µM each primer, 0.75 unit Taq polymerase and
empirical template dilutions. Thermocycling conditions for control region,
cytochrome b and PLP1 DNA amplification began with 10 cycles (Touchdown)
each including a 45s denaturing step at 94ºC, 45s annealing at 60-51ºC, and a 1.5
min extension at 72 ºC; this was followed by 30 cycles of 45s denaturing at 94ºC,
30s annealing at 50ºC and 1.5 min extension at 72 ºC. The PCR amplification for
CHRNA1 and FES began with 10 cycles (Touchdown) of which each had a 30s
denaturing step at 94ºC, 30s annealing at 60-51ºC, and 1min extension at 72ºC,
followed by 30-34 cycles of 30s denaturing at 94ºC, 30s annealing at 50ºC and
1min extension at 72ºC. Products were examined on a 1% agarose gel stained
with ethidium bromide, purified with Shrimp Alkaline Phosphatase and
Exonuclease I, and sequenced using ABI chemistry and an ABI-PRISM 3100
automated sequencer. Sequences were deposited in GenBank under accession
numbers XXXX-XXXX.
Sequence analysis
Sequence electropherograms were visually inspected and edited using
CHROMAS 1.45 (http://www.thecnelysium.com.au/chromas.html), and aligned
using the CLUSTALW algorithm implemented in MEGA 3.0 (Kumar et al. 2004).
Alignments were checked and edited by hand, and segments that could not be
unambiguously aligned were excluded from all analyses. Initial sequence
comparisons and measures of variability were performed using MEGA. To
determine the appropriate model of nucleotide sequence evolution, we used the
Akaike Information Criterion as implemented in MODELTEST 3.6 (Posada &
Crandall 1998). Details of the sequence analyses will be described separately
below for each data set (control region, cytochrome b and nuclear introns). For the
two latter data sets only aspects that differ from the control region analyses will be
specified.
mtDNA control region data set
The Tamura-Nei model (Tamura & Nei 1993) with a proportion of invariable
sites and a gamma distribution of rate heterogeneity across sites (TN+G+I)
provided the best fit to this data set (I= 0.7456; alpha=1.158), and was applied in
all subsequent model-based analyses. Phylogenetic relationships among
haplotypes were inferred using PAUP*4.0b10 (Swofford 1998) for three of the
different optimality criteria: (i) maximum parsimony (MP) with heuristic searches
using 10 replicates of random taxon addition; (ii) maximum likelihood (ML)
incorporating the TN+G+I model; and (iii) minimum evolution (ME) with a heuristic
search starting from a neighbor-joining (NJ: Saitou & Nei 1987) tree, and
employing three different types of distance: ML distance, TN+G+I distance, and p-
distance. In each case 100 bootstrap replicates were used to evaluate nodal
support. A separate phylogenetic analysis using Bayesian Inference (BI) was
performed with MrBayes 3.0b4 (Huelsenbeck & Ronquist 2001), incorporating the
GTR+G+I model. Two separate runs of the Markov chain Monte Carlo search
were performed with 100,000 and 200,000 generations, respectively, sampling
trees every 100 generations, and discarding the first 200 trees as burn-in.
Haplotype networks were generated using two different methods: (i)
statistical parsimony as implemented in TCS 1.18 (Clement et al. 2000), with
connections constrained by 95% confidence intervals; and (ii) the median-joining
approach (Bandelt et al. 1999) implemented in Network4.1.0.8 (www.fluxus-
engineering.com). A Nested Clade Analysis (NCA: Templeton et al. 1995) was
performed on the basis of a TCS network, whose clades were nested by hand
following the approach suggested by Templeton et al. (1987; 1995). The nested
structure was analyzed with Geodis 2.0 (Posada et al. 2000), employing 10,000
permutations to test the significance of genealogy-geography associations, and
using the latest inference key
(http//:darwin.uvigo.es/download/geodisKeys_14jul04.pdf) to interpret the
processes underlying significant results.
To investigate patterns of historical population structure, an Analysis of
Molecular Variance (AMOVA; Excoffier et al. 1992) was performed with
ARLEQUIN 2.0 (Schneider et al. 2000) under several variants of three different
scenarios of hypothesized geographic subdivision: (i) each sampling locale treated
as a distinct population; (ii) considering broad regional units called ecoregions
40
(adapted from Dinerstein et al. 1995 and
www2.ibge.gov.br/downloads/mapa_murais/biomas_pdf.zip), representing major
vegetational domains, with the Atlantic Forest subdivided into Northern and
Southern portions (see Fig. 1); and (iii) using the major phylogeographic partition
identified here (see Results) to define the two principal groups as population units.
Significance of estimated Φ
ST
values was tested using 10,000 permutations. We
also applied the program SAMOVA (Dupanloup et al. 2002) to investigate the
possibility of alternative patterns of population subdivision. This approach starts
from individual sampling locales as populations and surveys all possible
combinations forming two or more broader groups, attempting to identify the most
likely position of inferred historical barriers. To test for the occurrence of isolation
by distance, we assessed the correlation between genetic and geographic
distances among the 32 sample-sites (mean genetic distance value for each unit),
using a Mantel test (1967) performed in ARLEQUIN with 100,000 permutations.
For each population defined in the various schemes outlined above, DnaSP
4.0 (Rozas et al. 2003) was used to estimate gene diversity (h, the probability that
two randomly chosen mtDNA lineages were different in the sample) and
nucleotide diversity (π per nucleotide site, the probability that two randomly chosen
homologous nucleotides are different in the sample). We used this value of π as
an estimator of the populational parameter θ (θ=2N
ef
µ, where N
ef
is the historical
effective number of females, and µ is the substitution rate per site per generation
[see below]), referred to here as θ
π
(Tajima 1996). We also estimated θ using
coalescent-based approaches with LAMARC 2.0.2 (Kuhner et al. 1995; Beerli &
Felsenstein 2001) and IM (Hey & Nielsen 2004). Details of these runs are
presented below, in the context of divergence dating (IM) and multi-locus
(LAMARC) analyses. Inferences regarding the occurrence of past events of
population expansion or decline were based on Mismatch Distribution analyses
(Rogers & Harpending 1992) and estimates of neutrality tests such as Tajima’s D
(Tajima 1989), Fu and Li’s F* and D*, and Fu’s F
S
(Fu 1997) computed in DnaSP
and ARLEQUIN. LAMARC was also used to infer historical changes in population
size, as described below.
To date the coalescence time of Cerdocyon mtDNA lineages (and also to
estimate the historical effective number of females, as outlined above), we
obtained the substitution rate (µ) for the control region using data fro tardoso e s bni leta sososo Td[(e)2.808y27(st)1.40a38(r)3.21279(i)-1.40.893(04.940562(t)11.40g2(i)-1.4092( )-126.25694.3409([28(su)2.80M9(i)-1.40Y)(a)2.2(r279( )-115.]1( )-381.;1( )-381.574(04.9405V79( )-115.381(t)1.403l8(e)2.808á38(r)3.212J/R25 11.28 Tf171.48 016171.0)2.80827(t)-9.23449(e)13.4425694.3409(92(l)-1.40381( )-381../R25 11.2 Tf6.36 0 25d4( )-126.254(04.9487168( )-126.99(t)1.40599(t)1.40599(t)1.4052792(a)2.2(r.)(i)-1.40114(04.948725694.3396(S79( )-115.59(t)1.405q68(u)]TJ319(e)-7.83068(a)2.807068(ce)13.4459( )-126.s114(04.9487f19(r)-7.4255(o)2.80762(l)-12.0.405(04.9487s59( )-126.v62(r)3.212791(a)2.80762(l)-1.4051( )-381.574(04.9487434(o)-7.8359( )-19.8d68(b)2.807511(n)-7.83v511(n)-7.8362(a)2.807u68(a)2.80762(s )-381l08(n)-7.83s616(l)-1.4019.762(t)1715(r)3.21225694.3396(t79( )-381.h5(m)-7.42e1( )-126.s808( )277.998]TJ-319.08 141( )TTd[96)1.405114(a)2.808w)(a)2.80892( )-126.25641(1494(sp38(e)2.80892( )-392.c381(t)1.40392( )-115.325641(1494(279(a)2.807G1(e)2.808928(e)2.80892( )-9.23B79( )-115.92(l)-1.4092( )-9.23k83(o)2.80725641(1494(a1( )-126.c459( )-126.ss434(o)-7.83068(n)13.4459( )-19.871541(14883068(g)13.4462(m)-7.42551(b)2.80762(e)-7.83068(a)2.80779(i)-1.40.89341(14883279( )-115.Y)(a)2.2(r268(a)2.80781( )-126.09(t)1.405998(a)2.80749(t)1.40509( )-19.871541(14883t15(r)3.21219.762(t)189341(14883279.7687.83Y)(a)2.2(r26(t)1.405898(a)2.80709(t)1.40599(t)1.405398(a)2.80709.08 04o)21.0)2.808;19( )-381.57441(14883279( )-115.Y)(a)2.2(r26.762(t)1898(a)2.807098( )-126.99.762(33r268(a)277.981( )-126.57441(1500251(o)-7.82808( )277.998]TJ-259.32 04o)21.Td[(e)2.808279( )-115.Y)(a)2.2(r574456)-7.r26(t)19.2386(t)19.23028(e)2.80896(t)19.2326(t)19.2366(t)19.23;1( )-381.574456)-7.r279.7687.83Y)d[02.8r268(a)2.80887(t)-9.23028(e)2.808968(e)2.80827(t)-9.2331( )-126.574456)-7.r81(o)-7.8293(t)1.4055742(to)-73279.7687.83Y)(a)2.2(r268(a)2.80781( )1.40509(t)1.40599(t)1.405168( )-126.26.762(t)1;19( )-381.5744(to)-73279( )-115.Y)(a)2.2(r898(a)2.807168( )-126.26.762(.42798(a)2.80749(t)1.40516.762(t)1;19( )-381.5744(to)-73279.7687.83Y)(a)2.2(r898(a)2.80716(t)1.40526(t)1.40579(t)1.405398(a)2.80799.08 031d4( )-126.254456)-70511(a)2.80793(t)1.4055742(to)-73279( )-115.Y)(a)2.2(r89(t)1.405168( )-126.26(t)1500579(t)-126.308( )277.906.762(.42;15(r)3.41998]TJ-259.32 031d4(Td[96)1.405279( )-115.Y)(a)2.2(r268(a)2.80887(t)19.2397(t)19.23978(e)2.80896(t)19.2356(t)19.23279( )-9.23319(t)-9.23w81(t)1.40392( )-115.79(e)-7.8306( )-126.256(04.9405628(l)-1.4038(e)13.44381(t)1.403g28(e)2.80892( )-9.2306( )-126.d08( )277.9986(04.9405w8(e)13.44381(t)1.40511(h)-7.83068(e)2.80725694.3396(o68(g)13.4462(m)-7.4279( )-381.574(04.9487d68(b)2.80762(t)1.40511(a)2.80762( )1.40511694.3396(s83(e)2.80762(n)-7.8311(a)2.807319( )-381.574(04.948762(n)2.807628(e)2.81459( )-381.574(l)-1.4019( )1.40562(t)1.405434( )1.405s)(o)2.807.08 .7Td(m)Tj/[511(h)-7.83068(e)2.80762( )-381.574(l)-1.4019( )1.405v62(r)3.21279( )-381.434( )1.40562(n)2.807p2(n)2.807p2(n)2.807434(o)-7.8359( )-19.8g68(e)2.807256(04.948779(e)-7.8306( )-.80762(e)2.807434(o)-7.8306( )1.40562(t)-126.257(04.98(27905880726.762(.42798(a)277.9408( )277.998]TJ-259.32 -7Td(mTd[(o)2.80827(t)-9.23p68(g)13038279( )-9.233192f63.40w81(t)1.40372(t)-9.23s3192f63.4006( )-126.551(b)2.807p2(l)-1.40381( )-381.938(r)3.212s)(o)2.807938(d)13.4472( )-9.234492f63.40381(n)2.808928(r)3.212JTd0( )4381(h)-7.8293(t)-126.381(st)1.4034492f63.4062(n)2.80762(d)-7.83068(b)2.807l08(n)-7.83s)(o)2.8070511(n)-7.83s.)(i)-1.40114d0( )3(T11(6.6587.h5(m)-7.83068(a)2.807J/R25 11.288 Tf152.16 2(m)24m)Tj/R9 11.28 Tf6.36 0 Td[( )-126.2542f63.07v62(s )-381l08(n)-7.83u68(e)2.80762( )1.4051142f63.07w1( )-381.62( )1.405.83(o)2.807256d0( )3(11(h)-7.83068(e)2.807628(n)13.4459( )-19.87152f63.0762(s )-136.11(i)-1.40511(m)-7.42551(e)13.4462(t)1.40511(a)2.807068(d)13.4459( )-381.5742f63.0762(m)-7.42s434(o)-7.8359( )-1.42g08( )277.9986d0( )5251(o)-7.82h08( )277.9808( )277.998]TJ-319.08 2(r) )TTd[6e)2.808f28(su)2.1219.762(66779(e)-7.83551(e)13.44u2(l)-1.40381( )-381.a2( )-9.23449264.554459/R9 11.28 T7.55 )46 0 49.9)TTdd4(j/Ra 11.28 Tf6.36 0 4.2 dd4(j/[(=81( 10640526/R9 11.2828 Tf152.16 02[96))Tj/R9 11.28 Tf6.36 0 Td[())3.21T116)-2.23449264.5544279(a)2.807N81(t)1.40392( )-115.381(st)1.40449264.554417(t)19.23978(e)2.80887(t)-9.23778(e)2.808279( )-9.23,)(i)-1.40114d75.1907w1( )-381.h2(e)-7.8306(r)3.212791(a)2.80762( )1.405114253.9141T116)-2040449264.554038(e)2381.s449264.5540t19( )-381.068(e)2.80762( )1.405114253.9141t19( )-381.38(e)2381.m91(a)2.80762( )1.405114264.5540t1(a)2.80793(t)1.405574264.5540t1(a)2.807068(e)2.80762( )-381.574264.5540m91(a)2.807o2(s )-136.11(i)-1.40574264.5540791(a)2.80762(cy)-10.6628(n)13.4459(t)1.40511(a)2.807574264.5540co9.08 008d(m)Tj/[5.4058807.405880721( )-126.n08( )277.998]TJ-319.08 -81.(m5(r)5o)2.808a7(t)-9.2306(t)-9.23383(e)2.80762(n)-1.40381(i)-1.4092( )-126.79( )-381.57422292(l)-1.40928(d)13.4472(a)2.8082f63.4059/R9 11.28 T7.55 )46 0 78.84 Tdd4(j/Ra 11.28 Tf6.36 0 4.32 dd4(j/[(4492f63.40381(n)2.80834492f63.4081(h)-7.82938(e)2.80892( )-9.234492220g2(i)-1.40928(e)2.80892( )-7.8306(cy)-10.t19( )-381.38(e)2381.c257222d2(i)-7.40381(n)27.83st19( )-381.62(n)2.80762(cy)-10.683(e)2.80762(n)-7.835742f63.07279(a)2.807T116)-2040511(A)-3.212542f63.07.405.807o2(s )-136d2(e)-7.8306(r)3.212511(i)-1.4011422292( )-126.s1142f63.07511(m)-7.42551(e)13.44p6(r)3.212511(i)-1.4006(r)3.212m91(a)2.807628( )277.9n6(cy)-10.t19( )-381.e2(s )-136d2(e)-7.831142f63.07511(o)-7.8359( )-19.8114222M9(i)-1.40E9.08 009d[())3.21G1(o)-7.82279( )-0.402792(a)2811998]TJ-259.32 093(Td[96)1.40527(t)-9.2327(st)1.40114(a)2.808w)1(t)1.40392( )-115.e2(l)-1.4092( )-126.256424.1.80883(e)2.807p2( )-9.2392( )-392.c83(e)2.807381(t)1.40392(t)-9.23s319424.1.80583(o)2.80762(n)2.808791(a)2.80779(e)-7.8306(t)-9.23c819(e)2.80892( )-115.d2(e)-7.83114424.1.73319(o)2.80762(r)3.21279( )1.405114424.1.7362(n)2.80762(d)-7.83c62(s )-136.119(r)-7.4255(o)2.80762(l)-1.4051( )-381.5747.8.7654p6(r)3.212o6(r)3.212511(i)-1.40s)(o)2409(.405.807o28(a)2.80779(i)-1.40p6(r)3.212h2(i)-7.40381(n)27.83s.405424.1.73279(a)2.80759/R9 11.28 T7.55 )46 0 3146.36Tdd4(j/Ra 11.28 Tf6.36 0 4.2 dd4(j/[(=81(1.7-9.759/R9 11.28 T7.55 )46 0 02[96)-dd4(j/[(x)(a75 )0s)5005 11.2 Tf6.36 0 7)5o)dd4(j/[(-9(a)2.807[19(r)-7.4259/R9 11.28 T7.55 )46 0 03.16 Tdd4(j/Rx 11.28 Tf33.36 66) )Tdd4(j/[(+81(1.7-9.759/R9 11.28 T7.55 )46 0 02[84 Tdd4(j/Ry 11.28 Tf33.36 66) )Tdd4(j/[(]19(r)-7.42/19(r)-7.4226(t)1.405;1(o)-7.82424.1.07N8( )-381.628( )277.9511(o)-77.998]TJ-319.08 -7Td36.Td[(e)2.80817(st)1.40998(a)2.03887(t)19.2376(t)19.23279( )-9.23.1( )-381.574(c)-10.66(o)2.808938(e)2.808381(n)2.8083449(t)-9.23su38(e)2.80892(st)1.40381(i)-1.40381(t)1.40381(u)2.80892(t)1.40381-(e)13.44381(t)1.40392(n)2.80892( )-9.23319(a)2.808551(a)13.4472(t)-9.23449(e)13.4459( )-19.8715(()3.2162(n)2.80762(d)-7.8306(e)-7.83114(l)-1.40t15(r)3.212h5(m)-7.83068(a)2.807J9(a)2.808s92( )-126.m91(a)2.80762( )1.405114(a)2.808319(o)2.80762(r)3.21279( )1.405m91(a)2291319(e)-7.83434( )1.40562(n)2.80759( )-19.8715(()3.21w9(e)2.807628(a)2.80779.08 .90d(m)Tj/[5e6(e)-7.83114(l)-1.40t15(r)3.212h5(m)-7.83068(a)2.807n2( )1.405114(a)2.80862(m)-7.42s83(e)2.80762(n)-7.8359( )-381.574(t)1.405119(o)2.80762(r)3.212574(t)1.40562(s )-136.11(i)-1.40511(m)-777.4058807a1( )-126.51(o)-7.82808( )277.998]TJ-319.08 290d(mTd[96)1.405114(a)2.808h9.762(66727(st)1.40114d75.192d2(i)-1.4038(e)2.808v)2938(3.21279(i)-1.40g38(e)2.80892(n)2.80892( )-9.23c06( )-126.256253.915381-(e)13.4438(e)13.44m91(a)2.80762( )1126.256275.192b2( )-9.2392( )-392.119(o)2.807w)1(t)1.40392( )-7.8306(r)3.21262(t)1.405574264.5540m91(a)2.80762(n)2.807j81(n)27.8362(r)3.21279( )1.405114264.5540381(n)2.80762(e)-7.8311(r)3.212791(a)2.80762(n)21.40-9(a)2.807883(e)2.807p2(n)2.80759( )-19.8c381(n)2.807f19( )-381.381(n)2.807c574264.5540cl1( )-381.628(d)13.4459(n)2.80759( )-19.8s114d75.1907i9.08 004d[(t)1.40559( )-19.811/R25 11.28 Tf171.48 02)24m)Tj/33191(n)2.807.1(a)2.807574264.5540t19( )-381.06(r)3.212o68(u)]TJ319(e)-7.83s)5005 11.2 Tf6.36 0 45( )-126.254264.5540a68(a)2.807n2( )1.405d2(t)-126.257264.555472(t)-9850251(so)2.81083(o)2.807628( )277.998]TJ-319.08 -61.84 Td[(e)2.80827(t)-9.2327(st)1.40114(a)2.808w)1(t)1.40392( )-115.e2(l)-1.4092( )-126.25/R25 11.28 Tf171.48 46.9)T)Tj/33191(n)2.40392( )-115.791(a)2.807d38(e)2.808o2(t)-9.23cy938(r)3.212J/R9 11.28 Tf54.48 0 Td6( )-126.254(04.9405628(l)-1.4092( )-126.72( )-9.2344/R25 11.28 Tf171.48 27d[())3.21P79( )-115.s83(e)2.80762(n)-7.83u2( )1.405d28(b)2.80762(t)1.405l1( )-381.o68(u)]TJ3p68(u)]TJ359( )-19.8x)5005 11.2 Tf6.36 0 d[(T)))3.21.19( )-381.57494.3396(I19( )-381.59( )-19.8715(l)-1.40628(d)13.4459( )-19.8d6(i)-7.40381(n)27.8311(a)2.807434(o)-7.8306( )1.40562(t)1.405574(04.9487t1(a)2.80793(t)1.405574(04.948779(e)-7.83068(u)]TJ3p68(u)]TJ319.762(t)179(e)-7.83t19( )-381.381(n)2.80762(t)1.405g3(t)1.40557494.3396(t79(r)3.212h5( )-7.8306(r)3.212574(04.9487p6(r)3.212o6(r)3.212511(o)-7.8359( )-19.8t19( )-381.57494.3396(62(s )-136.11(i)-1.40511(m)-2.81.4058807a1( )-126.51-( )-381.62(t)-126.25]TJ-319.08 194.(mTd[(o)2.808f28(su)2.1219.762(66779(e)-7.83J/R25 11.288 Tf152.16 (su21.0)2.8R9 11.28 Tf6.36 0 Td[())3.2131( )-381.574296.4607w)(su)2.80)2938(3.212574285u)]472(t)-9.23381( )-381.083(o)2.80762( )1126.256275.192583(o)2.80792(l)-1.40381( )-381.583(o)2.807u2(t)-9.23381(o)2.80892(t)1.40381(e)2.808928(d)13.4472( )-9.23449285u)]4728(a)2.807J9d75.1907c068(n)13.4459( )-19.8s83(e)2.80762(n)-7.8379(e)-7.83v62(t)1.40511(a)2.807434(n)-7.83v83(e)2.80762( )-19.8114296.4672791(a)2.80762(l)-1.4062(t)1.405g3(t)1.405e28(a)2.807J9d75.1907715(r)3.21219.762(t)179( )1.405114285u)263068(a)2.80762( )-19.8c068(e)2.807256285u)2)-19.762(t)1715(r)3.21225.08 .97[96))Tj/[0t19( )-381.06(m)-7.83068(a)2.807s62(n)-7.83574275.1907d68(b)2.807511(n)-7.83v62(n)-7.8379(e)-7.83g68(e)2328.62(t)-126.59( )-1.42683(e)2.807628( )277.998]TJ-319.08 -24m5(r)4e)2.80827(st)1.40v928(e)2.80892( )-9.2381(e)2.808331( )-381.57441(1494(b38(r)3.212s)(o)2.80757451.78740a38(r)3.212p2( )-9.23p2(l)-1.40381(o)2.808s)(o)2.807381(n)2.808928(r)3.212g2( )1126.25641(1494(81(h)-7.82938(e)2.80892( )-9.2344941(1494(928( )277.956(t)19.23%)6)-204044951.78647c06(l)-1.4062(t)1.405f19( )-381.381(n)2.807d2(e)-7.8306(r)3.21262(d)-7.83c83(e)2.80762( )-19.811451.78647381(n)2.80762(e)-7.8311(r)3.212068(a)2.80779(i)-1.40v62(l)-1.4051( )-381.57451.78647279(a)2.86(+89.08ETQ .954 3252 55-361 5-3609 ref333 0 0 8.33333 0 0 cm BT/R13 11.29Tf1 0 0 1 105.96 -61.2 (h)138Tj/[.57441(1488322(n)-7.8357441(14883s11(a)2.807628(a)2.807n2( )1.405d2(t)-7.83068(b)2.80779(d)-7.8306( )-19.811451.7864706(r)3.212791(a)2.80755(o)2.807628(b)2.80779(d)-7.83.89341(14883[1(a)2.807S79( )-115.E79( )-115.]1( )-.807279( )-9.2331941(14883t15( )-381.o6( )-1.4211451.789827(t)-126.o1( )-126.51-( )-381.h28( )277.998]TJ-319.08 2.8.24 Td[(e)2.808114(a)2.808h9.762(667278(a)2.038449285u)]472( )-9.23381(n)2.808v83(e)2.80762(n)-115.791(a)2.807g2(i)-1.4092(n)2.80892( )-9.23c83(e)2.80762( )-1.23449296.460762(n)-1.40381(i)-1.40381(m)-7.42551(a)2.80892(t)-9.23449(e)13.4438(e)13.44628( )277.992( )-9.23319285u)]40a68(a)2.807n2( )1.405d2(t)-7.83574285u)2)-791(a)2.80762(l)-1.4011(r)3.21206(n)-7.83574275.1907583(o)2.80792(l)-.212511(i)-1.40511(n)-7.83b2(r)31.40791(a)2.807628(a)2.80711(a)2.807434(n)-7.8319.762(t)1n28(a)2.807J9d75.1907st19( )-381.e2(s )-136p6(r)3.212s114296.4672279.08 .87[(T)))3.21E79( )-115.38( )-381.z434(n)-7.8379(i)-1.40381(ca)7.83k83(o)2.80725/R25 11.28 Tf171.48 3Td[())3.2162(n)-7.83119( )-381.574296.467292(l)-.212512225 11.2 Tf6.36 0 2Td6( )-126..19( )-381.574285u)2)-22(n)-7.83098( )-126.09(t)1.40516(t)1.405019(,)-9.23.1(o)-7.82285u)]40F116)-2040o1( )-126.r92(a)2811998]TJ-259.32 048.24 Td[96)1.40527(st)1.40f6(i)-1.40f28(su)2.1206(t)-9.23c819(e)2.80838(e)2.808v)2( )-9.23319(a)2.8670511(n)-7.42z)(o)2.807938(d)13.44319(a)2.86792(t)-9.23s81-(e)13.4438(e)13.44m91(a)2.80792(t)1.40381(e)2.808421(o)2.80892(n)2.80892(t)-9.23s,49(e)13.44256(a)2.86762( )1.405116(t)1.405g3(t)1.405e28(a)2.80792( )-7.8306(n)-7.8379(e)-7.8362(t)1.40511(a)2.807434(o)-7.8306( )1.40562(t)1.405574(t)1.40511(i)-1.40511(m)-7.42551(e)13.4459( )-136.893(t)1.40562(f)-9.23319( )-381.574(t)1.40526( )-1.42114(()3.21s)(o)2.807938(d)2.80762(t)1.40579(d)-7.83.89.08 .87[(T)))3.21w1( )-381.62( )1.405.715(()3.2162( )-126.ss83(o)2.807u2( )1.405m91(a)2.80762( )1.40506( )-19.8,19( )-381.574(t)1.405b2(l)-12.062( )1.405.83(o)2.80762( )15005d2(t)-126.257(l)-1.44628( )277.9928( )277.998]TJ-319.08 287[(T)Td[(e)2.808s114(a)2.808u9.762(667d2(i)-1.40381(o)2.80892( )-115.325651.7874092(n)2.808f49(e)13.4425/R25 11.28 Tf171.48 5(n))))3.21279( )-115.381( )-381.93(n)2.808p2( )-9.2392( )-392.x25662a)263381(o)2.80892( )-9.23g38(e)2.808o38(r)3.212p2( )-9.2392(t)1.403s)5005 11.2 Tf6.36 0 TJ64( )-126.25662a)263279(a)2.807D34( )1.40562(e)-7.83434( )1.405é6( )1.40562( )-19.811/R25 11.28 Tf171.48 40.9)T)Tj/3362(n)-7.8311(a)2.80725662a)247792(l)-.212511(i)-1.40./R25 11.2 Tf6.36 0 25d08( )-126.25662a)2477298( )-126.09( )-19.8098( )-126.598( )-126.279( )-9.2331962atatmimeth t a o t
42
In addition to phylogeny-based dating analyses, we estimated the timing of
divergence between the two major Cerdocyon population units using the isolation-
with-migration model developed by Nielsen & Wakeley (2001) and Hey & Nielsen
(2004), and implemented in the program IM. This allowed us to incorporate
population-level processes (e.g. lineage sorting, fluctuations in size) in the dating
inference, likely leading to more realistic estimates of when divergence events
took place. Multiple runs of IM were performed, aiming to promote and to verify
convergence of parameter estimates. The two final runs consisted of (i) four
Metropolis-coupled Markov chain Monte Carlo (MCMC) chains, each run for 10
million steps after a burn-in period of 300,000 steps; and (ii) 10 Metropolis-coupled
MCMC chains, each run for 3 million steps after 100,000 steps of burn-in. The
substitution rate and generation time were the same as in the analyses outlined
above. In addition to estimating the divergence time between the two major
mtDNA phylogroups (taking into consideration the observed geographic swap of
some haplotypes between them, i.e. using geography as a defining criterion), we
also used the IM results to directly infer the historical effective population size in
each of these population units.
Cytochrome b data set
Since we could not obtain samples of individuals collected north of the
Amazon river, we generated a smaller additional data set (representing major
geographic regions) of the mtDNA cytochrome b gene to allow a comparison with
a single Venezuelan sample available in GenBank (Accession number AF266472;
Farrel et al. 2000). We determined with MODELTEST that the HKY model of
sequence evolution provides the best fit to our cytochrome b gene data. ME (NJ
with HKY distance), MP (heuristic search, random addition of taxa), and ML (HKY
model) trees were computed with PAUP. Nodal support was assessed with 1,000
bootstrap replicates.
Nuclear intron data set
Heterozygote sites in nuclear segments were identified when two different
nucleotides were present at the same position in electropherograms of both
strands, with the weakest peak reaching at least 25% of the strongest signal.
When two or more heterozygote sites were identified in the same segment, the
gametic phase of the variants was determined computationally using PHASE 2.1
(Stephens et al. 2001; Stephens & Donnelly 2003). In the case of the X-linked
segment PLP1, the obtained haplotypes were also verified using male individuals
as known hemizygotes. Haplotypes were then used for multiple analyses, such as
generating median-joining networks with NETWORK, which were rooted using
sequences generated for P. gymnocercus and P. vetulus. For each locus, we
estimated population diversity parameters such as θ, using DnaSP (θ
π
) and
LAMARC (see below for search details). ARLEQUIN was used to perform Fu´s
and Tajima´s tests of neutrality, and to investigate population subdivision via
AMOVA (ecoregions and the major phylogenetic groups inferred from mtDNA
were used as units). Departure from a neutral model of evolution was also
assessed with Fu and Li’s test using DnaSP.
Multi-locus analyses
Our final set of analyses consisted of the coalescent-based estimation of
relevant demographic parameters (effective sizes, migration rates, and population
growth rates) including simultaneously the mtDNA control region and nuclear
intron data sets. These analyses were performed with LAMARC, allowing for
differing sample sizes for each segment, and normalizing the effective population
size of each genomic region (autosomal or X-linked) so as to match the mtDNA
value. This should allow for a direct comparison of inferred patterns between the
mtDNA and nuclear data sets, so that inferences such as male-biased gene flow
can be tested while minimizing the effect of the varying rates of drift occurring in
these genomic partitions. Also, more accurate estimates of demographic
parameters can be achieved by integrating the results obtained from multiple loci.
In the case of analyses incorporating nuclear loci, we did not directly calculate N
e
(as presented for the mtDNA control region data set) since no reliable estimates of
their substitution rates were available. Rather, indirect comparisons of N
e
were
performed by directly analyzing estimates of the parameter θ for different data sets
and geographic partitions.
44
Seven final LAMARC runs were performed, all of which included two
populations (north and south), allowing for growth in both of them, as well as for bi-
directional migration. LAMARC searches were initiated with a starting value of θ
based on Waterson’s (1975) formula, and applied the F84 model of sequence
evolution with empirical base frequencies and transition/transversion ratios. Four
runs used a Maximum-likelihood (ML) search approach with 10 initial chains
(10,000 steps each) and 2 final chains (200,000 steps each). Samples were taken
very 20 steps, and the initial 1000 genealogies were discarded as burn-in. Three
other runs used a Bayesian search strategy: two of them included three replicates,
each consisting of one initial chain (10,000 steps) and one final chain (200,000
steps), with samples taken every 20 steps and burn-in of 1,000 genealogies. The
third Bayesian run used a single replicate of one long chain (800,000 steps), with
samples taken every 40 steps and burn-in of 2,000 genealogies. Consistency of
estimated parameters across different ML and Bayesian runs was used to assess
convergence, and LAMARC profiles were used to calculate confidence (or
credibility) intervals around point estimates.
RESULTS
mtDNA control region
A 512 base-pair (bp) sequence of the mtDNA control region (CR) was
obtained for 106 crab-eating fox individuals. The segment contained 58 variable
sites (41 of which were parsimony-informative), defining 35 different haplotypes
(Table 2). All the observed polymorphisms were single base-pair substitutions and
consisted of 58 transitions and one transversion (see online Supplementary Data).
Between Cerdocyon and outgroups there were 88 variable sites of which 73 were
parsimony-informative. High levels of gene diversity and nucleotide diversity were
observed among individuals (Table 3). Both ecoregion-specific and shared
sequences were identified in the crab-eating fox, however the majority of
haplotypes (77%) was sample-site specific. The most common and widespread
haplotype was shared by 37 individuals; it was only absent in the Eastern
Amazonia and Northern Atlantic Forest ecoregions. In these two areas, all
haplotypes were ecoregion or sample site-specific (Table 2).
Parsimony, minimum evolution, maximum likelihood and Bayesian analyses
retrieved topologically equivalent trees that differed only at nodes with bootstrap
values below 50%. ME trees generated using different distance methods were
equivalent, and maximum likelihood distances were conservatively chosen, as
their bootstrap values were the lowest. Two monophyletic groups of Cerdocyon
mtDNA lineages were evident (Fig. 2). The first clade (bearing support values of
85,<50, 62 and 53% in MP, ME, ML and Bayesian analyses, respectively)
contained haplotypes from the Cerrado, Pantanal, Southern Atlantic Forest and
Eastern Amazonia ecoregions, encompassing most of the sampled area, and
including almost all samples from southern locales (Table 2, Fig. 1). The shape of
its internal phylogeny, with short branches and little robust structure, is suggestive
of a recent population expansion (Avise 2000). Only two Northern individuals
(bCth196 [haplotype C20] and bCth202 [C15], both from the Caatinga region)
were present in this cluster. The second clade (supported by values of 99, 94, 99
and 100% in MP, ME, ML and Bayesian analyses, respectively) included all the
sequences obtained from the Northern Atlantic Forest, almost all samples from the
Caatinga, and some samples from Eastern Amazonia, with overwhelming
presence in the northern portion of the surveyed area (Fig. 1). The only exceptions
were one individual from the Pantanal ecoregion (bCth51 [C30]) and one from the
Cerrado (bCth177 [C23]). We found no evidence for phylogeographic subdivision
within either clade (Fig. 2).
The haplotype networks produced with TCS and NETWORK were nearly
identical, and only the former is shown here (Fig. 3) in the context of a Nested
Clade Analysis (NCA). To minimize the ambiguities and facilitate the NCA we
removed from this data set one haplotype (C23; see Table 2), whose incomplete
sequence led to the creation of ambiguous links. The network corroborated the
existence of two main clusters, Northern and Southern, with the presence of
Eastern Amazonian haplotypes in both groups (often in basal positions). These
two clades were separated by over 12 mutational steps (which is the 95%
confidence threshold for the statistical parsimony approach with our data, thus
46
creating two discrete clusters in the TCS analysis). In the NETWORK analysis (not
shown) these clusters were connected by haplotypes C31 and C14, which is
identical to the TCS result using a 90% threshold.
The networks are indicative of a relatively recent population expansion in
the Southern Clade, in which several localized lineages are connected by short
branches to the most common, widespread haplotype (Fig. 3). The null hypothesis
of no association between haplotypes and geographic location was rejected for
some clades positioned at all levels of the nested diagram (Fig. 3). Inference of
historical processes based on the NCA interpretation key suggested several
plausible scenarios of factors affecting population history in this species (see
online Supplementary Data and Discussion).
The AMOVA results indicated that most of the genetic variability in C. thous
can be explained by a single north vs. south partition (Table 4). For these two
geographic groups, suggested by the phylogenetic and network analyses, the
estimated Φ
ST
values were > 0.68. High fixation indices were also observed in
some other scenarios comprising three to five major groups, especially when the
Caatinga samples were treated as a separate unit (see Table 4 and Fig. 1). When
we calculated the Φ
ST
considering each of the 32 sample-sites as a separate
population, the estimated Φ
ST
was 0.52. However, if the two major groups
(Southern and Northern) were analyzed separately (in each case including
Eastern Amazonia, as it does not bear specific affiliation with either one), the
AMOVA results indicated that most of the diversity (>83%) occurs within sample-
sites, and not among local populations. The same observation resulted from
ecoregion-based analyses, strongly indicating that in every case the fixation
indices had been due to the main partition between Southern and Northern groups
(Table 4). Moreover, AMOVA analyses at the regional level indicated that several
pairwise comparisons among sites yielded non-significant values. Results from
the Mantel test showed a significant correlation between genetic and geographic
distances among the 32 sample-sites (r=0.54; determination of Y by X=30%;
p=0.000; Fig. 4), indicating that isolation by distance also plays a role in the
genetic structure of this species.
Since a deep phylogeographic partition was identified between Southern
and Northern groups, all subsequent analyses of population history were
conducted separately for each group, as well as for the total sample. Pairwise
mismatch distribution analyses of mtDNA CR sequences revealed a shape that
was approximately unimodal for the Southern Clade (Fig. 5), compatible with a
recent expansion scenario (perhaps followed by a more complex population
history, such as some level of subdivision). All neutrality tests performed with
mtDNA CR sequences from the Southern clade corroborated this inference, by
rejecting the null model assuming constant size (Tajima’s D: -1.78; Fu’s F
s
: -9.16;
F*: -2.373; D*: -2.337; significance: F
s
: p<0.02; all others: p<0.05). Conversely,
mtDNA CR analyses of both the Northern clade and the total sample revealed a
multimodal pattern of mismatch distribution (not shown) and neutrality tests that
were non-significant except for Fu’s F
s
value in the Northern group (F
s
: -6.52;
p=0.003). Coalescent-based analyses performed with LAMARC supported the
inference of historical population growth in both major demographic units (g values
> 61 in all runs). However, confidence intervals were broad and overlapped zero in
some of the Bayesian runs, thus warranting cautious interpretation. Maximum
likelihood estimates, on the other hand, were highly positive (g > 383), with
confidence intervals that did not overlap zero.
The point estimate for the mtDNA CR substitution rate was µ=3.68 x 10
-8
substitutions/site/year (considering only the shared segment with wolf and coyote
sequences). Taking into account the 95% CI around the wolf-coyote divergence
(see Methods), we obtained low and high limits for µ (2.02x10
-8
and 5.34x10
-8
,
respectively), which were used for every divergence event in combination with the
variance observed for d
a
at each node. This approach allowed us to estimate a
conservative interval for the time of each divergence event, accounting for the
variance at both the calibration and divergence estimation procedures. The point
estimate for the divergence between the Southern and Northern clades of
Cerdocyon was 578,082 years before the present (ybp), and the overall CI ranged
48
from 1,640,000 ybp to 177,358 ybp. The age of the divergence between
Cerdocyon and Pseudalopex was estimated at 908,216 ybp (CI: 2,337,500 -
368,867 ybp). The linearized tree method produced congruent results: 623,237
ybp for the south-north split in Cerdocyon, and 1,231,320 ybp for Cerdocyon vs.
Pseudalopex divergence.
Using the coalescent-based approach implemented in the program IM and
the same input parameters as above, we obtained in the two final runs of the
program (see online Supplementary Data) mean divergence dates of 369,957 and
421,975 ybp for the two main Cerdocyon mtDNA clades (overall 95% area interval
across both runs: 57,856 – 1,029,193 ybp). The estimated surface of the posterior
distribution of this parameter was not smoothly unimodal in any of the IM runs,
suggesting that this result should be taken with caution. However, the inferred
values (and conservative intervals) are consistent with the phylogeny-based
results presented above (and younger than those, as would be expected after
taking population processes more realistically into account), corroborating the
conclusion that this population split took place in Middle Pleistocene.
The age of the demographic expansion inferred for the Southern clade was
calculated based on the estimate of π, which is expected to approximate the
coalescence time for the base of this group. Using only the 274 bp segment
applied for the dating analyses mentioned above, this expansion was dated at
123,641 ybp (CI = 247,524 - 70,888 ybp). Extrapolating the substitution rate to our
full segment (512 bp), the estimate for this node was 108,625 ybp (CI = 237,623 -
59,925 ybp).
We estimated the female effective population size (N
ef
) from the mtDNA CR
data set using the formula θ=2N
ef
µ, with the point estimate of the substitution rate
mentioned above, and θ calculated from the nucleotide diversity (θ
π
) or from the
coalescent-based approaches implemented in LAMARC and IM (see Methods for
details, and Tables 3 and 5 for several estimated values of θ). The estimates of
N
ef
generated from θ
π
were 54,421 and 142,857 individuals for the Southern and
Northern clades, respectively. The observed difference between these values is
statistically significant, since a conservative estimate of their 95% CI (i.e. + 2SE;
see Table 3) indicates that their boundaries are clearly non-overlapping (i.e. p <<
0.05). Estimates of N
ef
produced with IM (in this case considering geography and
not phylogeny as the criterion for group affiliation) were 133,105 (95% area
interval: 70,266 – 239,361) and 273,256 (143,007 – 374,179) individuals for the
Southern and Northern groups, respectively (results were concordant between the
two final runs, only one of which is reported here). LAMARC analyses of the CR
data set (also considering geography to define groups) led to estimates of N
ef
of
339,546 (196,875 – 595,146) and 1,708,174 (505,003 – 5,370,428) individuals for
the Southern and Northern groups, respectively (see Table 5 for more details).
Overall, there was a clear trend in all analyses for the female historical effective
size to be considerably higher in the Northern versus Southern group, even though
in some cases the confidence (or credibility) intervals were very broad and
overlapped.
Cytochrome b gene
A 615 bp segment of the cytochrome b gene was sequenced for six
Cerdocyon thous individuals representing most of the sampled geographic region
(Fig. 1). Each individual was found to have a different haplotype. They were
compared to a sequence from a Venezuelan C. thous available in GenBank,
consisting of a 101-bp subset of the same segment. Fifteen sites were variable, 10
of which showed parsimony-informative variation (Table 6).
The two-clade phylogenetic pattern inferred for the mtDNA control region
was corroborated by the cytochrome b data set (Fig. 6), with increased bootstrap
support values for this partition (>85% for all methods) when the Venezuelan
sample was excluded from the analysis. This observation stems from the fact that
the available Venezuelan sequence had been sequenced for a shorter segment
(see Methods) that spanned only three of the included polymorphic sites, none of
which was diagnostic for either the Northern or Southern clade (Table 6). Thus,
the position of this Venezuelan sample relative to the two clades could not be
established based on the available data: the NJ tree grouped it with the Southern
Clade (Fig. 6), while ML placed it in the Northern Clade (not shown) and MP
50
created a polytomy relative to the other Cerdocyon sequences (not shown). All
analyses showed low support for such connections, due to the absence of
informative shared sites.
Nuclear intron sequences
Nuclear introns were amplified in a sub-sample of C. thous individuals
representing all different ecoregions in the study area. Twenty-eight Cerdocyon
thous individuals (representing 56 sampled chromosomes) were sequenced for a
423 bp fragment of the FES gene and for a 333 bp segment of the CHRNA1 gene.
A 817-bp segment of the X-linked PLP1 locus was sequenced for 37 individuals
(representing a total of 45 sampled chromosomes). Several polymorphic sites
were identified in each of the introns: five in CHRNA1 (including two
transversions), three in FES, and four in PLP1. The inclusion of Pseudalopex
outgroups (P. vetulus only, in the case of FES) in these data sets increased the
number of variable sites to 10, 5 and 9 for CHRNA1, FES and PLP1, respectively.
In addition, two indels were identified when C. thous and outgroups were
compared: one in CHRNA1 (2 bp) and one in PLP1 (4 bp). No sequence sharing
was observed between different species.
For each intron, polymorphic sites were computationally assigned to
haplotypes (Table 7) with 95% to 100% phase probability estimation. Estimates of
gene and nucleotide diversity were moderate to high for each intron (Table 3).
Rejection of the assumption of neutrality was observed for Tajima´s D in PLP1 (D=
-1.56; p= 0.02) and FES (D=–1.47; p=0.02), and for Fu’s F test in FES (F=-3.25;
p=0.0017). Of the six haplotypes identified for CHRNA1, two were observed only
in the Northern Atlantic Forest ecoregion, while two others were Caatinga-specific
(Fig. 7). FES sequences comprised four different haplotypes of which one
exhibited high frequency and was present in all ecoregions. The others were found
only in the Southern Atlantic Forest. In the PLP1 locus, four different haplotypes
were identified, two of which were ecoregion-specific (Northern and Southern
Atlantic Forest, respectively) (see Fig. 7 and Table 7). In spite of the occurrence of
these private haplotypes in the sample, no indication of significant
phylogeographic partitioning was identified, as the AMOVA analysis resulted in
non-significant values of Φ
ST
among ecoregions, as well as between the two major
groups inferred from mtDNA.
Multi-locus analyses
Demographic parameters were estimated with LAMARC for the combined
nuclear introns, as well as for the complete data set including nuclear and mtDNA
(control region) segments (see Table 5). This allowed for the comparison of
nuclear versus mitochondrial patterns of diversity (normalizing for relative effective
population size and mutation rate), so that demographic processes could be
evaluated more directly. Results from multiple ML and Bayesian runs were mostly
consistent, exhibiting largely concordant confidence intervals. Means across
multiple runs were used to arrive at final estimates. The trend described above
indicating higher diversity (and thus larger historical N
e
) in the Northern group than
in the Southern one was supported by the nuclear data set and the combined
inference, even though confidence intervals (CIs) overlapped. Migration rates
(expressed in Table 5 as the number of migrants per generation) were consistently
higher from South to North than in the reverse direction, although broad CIs
precluded the rejection of equality. Interestingly, there was a consistent trend of
lower migration rates inferred from the mtDNA data set when compared to the
nuclear segments, even after correction for lower effective size and higher
mutation rates. Multi-locus estimates of population growth produced results that
were similar to those presented above for the mtDNA CR data set. There was
indication of historical growth for both the Southern and Northern populations
(using nuclear alone or nuclear+CR data sets), with positive estimates of
parameter “g”, although CIs did overlap zero in most runs. Several runs led to
higher estimates of “g” in the Southern versus Northern group, supporting stronger
growth in the former.
52
DISCUSSION
We observed high levels of genetic diversity in the crab-eating fox using
both mtDNA and nuclear sequences. Genetic diversity in the mtDNA control
region (CR) was similar to that observed in other widespread canids such as the
gray wolf (Canis lupus; π = 0.026; Vilà et al. 1999) and the African wild dog
(Lycaon pictus, π = 0.014; Girman et al. 2001), while higher than that reported for
the arctic fox (Alopex lagopus; π=0.009 - Dalén et al. 2005) and lower than the
values inferred for coyotes (Canis latrans; π= 0.046; Vilà et al. 1999). Nucleotide
diversity was also rather high in the nuclear introns (see Table 3), however these
values could not be compared to other canids due to lack of polymorphism data
from additional species. Nevertheless, the number of polymorphic sites
(CHRNA1= 5, FES=3 and PLP1=4) and different haplotypes (CHRNA1= 6, FES=4
and PLP1=4) found in C. thous is quite high if we consider sequence sizes and the
small number of individuals analyzed. This result and the primary observation of
no shared haplotypes between Cerdocyon and its close relatives indicate that
these three segments are likely useful tools for canid phylogeographic studies.
The most apparent pattern observed with the mtDNA CR data was the deep
partition between two phylogeographic groups, separated in a roughly south-north
direction (Figs. 1, 2 and 3). These two distinct phylogenetic clades were supported
by the AMOVA and SAMOVA results (Φ
CT
=0.70 and 0.74 respectively), the NCA-
based inference (allopatric fragmentation), and also corroborated by the
cytochrome b phylogeny. Interestingly, this partition was not observed in the
networks generated with the nuclear sequences, which also yielded non-significant
Φ
ST
values. Phylogeographic structure is expected to be less pronounced at
diploid nuclear loci compared with mtDNA for three possible reasons: (i)
autosomal segments have an effective population size four times larger than
mtDNA, thus undergoing four times less genetic drift; (ii) they have slower
mutation rates, thus accumulating fewer differences over time even in the absence
of gene flow; and (iii) they are inherited from both parents, so that male-biased
gene flow would erode the signature of a matrilineal partition (Hare 2001; Antunes
et al. 2002; Zhang & Hewitt 2003). All three factors may play a role in the pattern
observed in Cerdocyon, and none could be completely ruled out by our results.
However, an interesting inference from the comparison of coalescent-based
nuclear versus mtDNA estimates of migration rates (Table 5) is that there is
indeed a trend suggestive of male-biased gene flow detectable in our data. The
estimated number of migrants per generation remained considerably smaller in
mtDNA-based relative to the nuclear-based inference, even after correction for
uneven effective sizes and mutation rates in the two genomes. This result
supports the inference that persistent male-mediated gene flow is a relevant (or
perhaps the main) factor leading to lack of geographic structure in the nuclear
markers analyzed here (Table 8). Male-biased dispersal and female philopatry
have been reported in field studies of small or medium-bodied canids (e.g. Vulpes
macrotica mutica [Koopman et al. 2000]; Vulpes velox [Kamier et al. 2004]). The
only study performed so far with C. thous suggested that both sexes are
somewhat philopatric, but did not rule out the possibility that males disperse on
average farther than females (Macdonald & Courtenay 1996).
The θ values estimated from the mtDNA control region and nuclear
sequences (Tables 3 and 5) indicate that past diversity was quite large in this
species, leading to the inference of large historical (as well as current) effective
population sizes. Direct estimates of N
e
were performed only for the mtDNA CR
data set, due to feasibility of calculating a substitution rate for this segment. As a
whole, estimates of N
e
using multiple methods were broadly consistent and quite
high, ranging from ca. 400,000 individuals estimated from θ
π
([Northern N
ef
+
Southern N
ef
] X 2; considering that N
ef
is the effective number of females and
assuming a 1:1 sex ratio) to a few million individuals based on the LAMARC
results. Although these values are indeed high, they are not incompatible with
plausible estimates of census sizes for C. thous, even taking into account that the
54
exercise). These values of current census size are therefore compatible with the
large effective population sizes estimated from our genetic data, even
hypothesizing an N
e
/N ratio of 0.5 or less.
The inferred scenario of two main phylogeographic groups for C. thous is
somewhat different from the intra-specific subdivision compiled by Cabrera (1931),
which lists three subspecies for our study area. He proposed that one subspecies,
C. t. entrerianus occupies Argentina, Paraguay and the southern states of Brazil,
with its northern limit corresponding approximately to the geographical position of
our SP1, SP2 and MS sample sites (see Fig. 1). This area coincides in part with
our Southern mtDNA phylogeographic group; however our data suggest a more
northerly boundary for this assemblage (see Fig. 1). The second of Cabrera’s
subspecies, C. t. azarae, would occur in Central and Northeastern Brazil, from the
northern boundary of C. t. entrerianius to the southern edge of Eastern Amazonia
(with our PI and TO sample-sites as a northwestern limit). Our observed mtDNA
partition shows a more restricted group in the C. t. azarae area, identified here as
the Northern clade. The third subspecies listed by Cabrera was C. t. thous,
occurring from Southeastern Amazonia (our sample-sites in MA and PA) to the
Guyanas; our data do not identify a third group in this area, but rather an
admixture zone between the two major phylogeographic clades. In spite of these
discrepancies, it is possible to reconcile our phylogeographic results with two of
Cabrera’s subspecies (C. t. entrerianus and C. t. azarae), which might remain
applicable in some contexts given appropriate adjustments in their geographic
range, as long as affirmed by corroboratory nuclear data in future studies.
The two major clades inferred from mtDNA data appear to have different
ages and/or contrasting population histories (Table 8). The nucleotide diversity
estimated for the Northern Clade is significantly higher than that of the Southern
Clade (see Table 3), and thus a larger effective population size may be inferred for
the former. Likewise, all other estimates of N
e
and/or θ were higher for the
Northern group than the Southern one (see Table 5). A high estimate of the
effective population size may be a result of two distinct situations: (i) a large
population (i.e. census size), caused by a broad geographic range and/or by high
density; or (ii) a stable population persisting at moderate to large sizes for long
periods of time, since the calculated N
e
is determined by the harmonic mean of the
population size throughout its history. The Northern Clade is almost completely
restricted to Northeastern Brazil, occupying an area about three times smaller than
that inhabited by the Southern Clade. Although there is no solid data on crab-
eating fox density in the wild (see above for a range of possible values), there is
no reason to assume that densities are considerably higher in the Brazilian
Northeast than elsewhere in the species’ range. On the contrary, current densities
are likely lower in this region since most of it is occupied by the harsh semi-arid
Caatinga biome. Densities in the Brazilian Northeast would have to be 7-12 times
higher than in the remainder of the range to explain the observed pattern based on
current demography alone. Since this is extremely unlikely, we view the latter
hypothesis as more probable, since it is corroborated by the deeper and more
structured pattern of the Northern clade’s internal phylogeny (Fig. 2), the higher
levels of divergence observed in the haplotype network for this group (Fig. 3), and
the estimates of historical demographic parameters. This conclusion is also
supported by the NCA inference of isolation by distance and restricted gene flow in
the North, suggesting a more complex demographic history in this area, in contrast
to a pattern of recent population expansion inferred for the Southern clade (see
Fig. 3 and online Supplementary Data).
Reinforcing these results, the nuclear intron data revealed more private
haplotypes for Northern Clade ecoregions: three for the Northern Atlantic Forest
and two for the Caatinga (considering the three segments altogether – see Fig. 7).
The only other ecoregion exhibiting private haplotypes was the Southern Atlantic
Forest, which spans a much broader geographic area than the ones mentioned
above. The Cerrado and Pantanal regions did not bear private alleles, perhaps
reflecting their intermediate geographic position leading to poor isolation with
either edge of the sampled distribution. The genetic distinctiveness of the
Caatinga was also suggested by some of the SAMOVA results that supported a
separation of sample-site CE (see Fig. 1) from the remaining areas, producing a
three-group scenario that yielded a slightly higher Φ
ST
value (0.75) than that
observed for the two-group pattern indicated by most analyses (see Table 4). In
56
fact, the palynological record from the latest Pleistocene indicates that there was a
dense forest covering the Caatinga region (De Oliveira et al. 2005), whose
fluctuations may have caused the isolation of fragments in some periods. On the
other hand, the inferred forest or savanna vegetation that covered the region
seems to have been widespread and stable over broad regions, possibly
supporting a large population of C. thous and thus playing a role in the
maintenance of larger effective sizes in this region.
The Southern clade, on the other hand, consists of a group of closely
related haplotypes exhibiting low levels of divergence. The patterns observed in
the phylogenetic trees and haplotype networks are consistent with a recent
population expansion for C. thous in this broad region. This inference is supported
by the mtDNA control region mismatch distribution revealing a prominent (albeit
not completely smooth) peak, suggestive of a population expansion event (Fig. 5;
Rogers & Harpending 1992). The significantly negative neutrality tests also
support this expansion scenario.
Within each major clade, all analyses suggested the existence of very little
genetic structuring among populations. This observation, along with the low values
of molecular divergence among ecoregions (8.8% and 9.6%), are expected since
C. thous individuals are extremely flexible, and adaptable to a variety of natural or
even suburban habitats. On a regional scale, the results from the AMOVA using
sample-sites as populations (separate analysis for Northern and Southern areas –
see Table 4) indicate a significant but weak genetic differentiation among units.
This pattern seems to be at least in part due to isolation by distance, as can be
inferred from the significant correlation between genetic and geographical
distances (Fig. 4). The NCA corroborated these results by suggesting some
restriction to gene flow between populations of the Northern Clade (clade 4-2). In
the Southern group this NCA inference was achieved only for one 1-step clade
(clade 1-2), as few newly arisen haplotypes were present and C15 was frequent
and widespread. This scenario of high gene flow with some isolation by distance
would be predicted for habitat generalists with a continuous distribution such as
the crab-eating fox, and has been similarly observed for coyotes and wolves
(Sacks et al. 2004; Geffen et al. 2004). In this context, the dramatic genetic
partition identified between the two major C. thous clades becomes quite striking,
implying that a strong disruptive process must have produced intense historical
isolation between these areas.
The location of this genetic discontinuity agrees with patterns observed in
other species, suggesting the occurrence of a shared, large-scale historical
fragmentation event in that region. Our south-north partition coincides with
latitudinal breaks (distributional or phylogeographic) displayed by other Atlantic
Forest vertebrates such as reptiles, lowland birds and small mammals including
the bat species Carollia perspicillata (Vanzolini 1988; Bates et al. 1998; Costa et
al. 2000; Lara & Patton 2000, Ditchfield 2000). The study performed by Costa
(2003) on small non-volant mammals strongly indicated that the Atlantic Forest is
a composite area (with the breakpoint concordant with our results). Data obtained
from marsupials and rodents showed that haplotypes from the easternmost
Amazonian localities were often more closely related to those from the northern
Atlantic Forest than to other Amazonian localities. For some species, a similar
relationship was observed between the southern Atlantic Forest and western
Amazonia, with the Caatinga and Cerrado appearing as past and present
connection areas. Molecular dates for the inferred biogeographic divergences
varied considerably across species and were often very old, pre-dating the
Pleistocene (Costa 2003). It is plausible to postulate that cycles of vicariance
shaped by ecological or physical barriers fragmented forest habitats at various
times (affecting different taxa differently), so that their biotic elements might be of
different ages (Cracraft 1988). These observations suggest that the apparent unity
of present-day biomes may be misleading, and that a complex history may
underlie the formation and biogeographic interactions of these ecosystems.
These South American phylogeographic patterns had so far not been
investigated in larger terrestrial mammals possessing higher dispersal capabilities,
such as carnivores. The deep genetic discontinuity observed in the crab-eating fox
mtDNA data argues for the existence of a common process affecting multiple
species. The divergence time estimated between the two major C. thous clades
58
(ca. 400,000 - 600.000 years) agrees with a Middle Pleistocene age, and was
similar to that found for the bat C. perspicillata (1 mya) by Ditchfield (2000).
Despite the generalist ecology and behavior of the crab-eating fox, environmental
changes during the Pleistocene might have limited its range, perhaps due to
strong vegetational shifts (e.g. increased aridity in connecting areas). The Brazilian
Atlantic Forest was probably fragmented into distinct patches isolated by open
grassland, with one of these splits separating the Northeastern and Southeastern
areas of Brazil (Câmara 1988). Additional phylogeographic studies of diverse
species occurring in this region should help test the occurrence of such a
pervasive vicariant process in the Pleistocene.
An alternative historical scenario can be postulated for Cerdocyon thous.
Since its current range excludes the core Amazon River basin and there is no
record indicating occupation of this region in the past (Berta 1987), it is unlikely
that the Southern Clade originated from Western Amazonia (as inferred for other
species – Costa [2003]). However, this Southern group could represent a
separate, more recent invasion from eastern Amazonia, using the Cerrado and the
Paraná River basin habitats as dispersal corridors. This younger origin relative to
the Northern clade is supported by historical demography inferences presented
here. If the two major clades of C. thous indeed represent separate colonization
processes that crossed the Amazon river, the original (source) population of this
species might be present in northern South America (e.g. in Venezuela and the
Guyanas). In this study, the samples from the Southeastern Amazon region
exhibited the highest levels of mtDNA CR diversity, bearing haplotypes belonging
to both major clades. This observation could be interpreted as evidence for current
genetic interchange between formerly isolated areas, but is also compatible with
the possibility of this being a more ancient area of distribution for this species. In
any event, the observed patterns require the existence of a period of south-north
demographic isolation in C. thous, particularly affecting Atlantic Forest populations.
The finding of a major phylogeographic discontinuity in C. thous in the
Brazilian Atlantic Forest, which seems to agree with patterns observed in other
species, highlights the complex history of this critically threatened biodiversity
hotspot, and argues for the urgency to develop efficient conservation plans for its
biota. In particular, extreme present-day fragmentation of the Northeastern Brazil
coastal forest currently threatens the persistence of several populations, whose
uniqueness relative to other areas is still poorly assessed. Given the pattern
inferred here of a history of isolation and differents asse p dss ras irn Gns,fss fat ipzittose2.8076298]TJ-304.5p[(i)-1.40l -18.96 Tda -18.84 Td[(u)2.2344941.1494472(l)-1.403026(a)2.80892(n)2.8089230..801.192(r)3.212n6( )-19.8715(o)2.80847(f)-9.23449(o)2.80c892(r)3.2144941.1494472(l)-1.403892(n)2.80892(r)3.2127(i)-1.40446(q)-7.82829(p)2.80765(o)2.808892(r)3.2144941.1494481(i)-1.403264.96 0 Td[(o)13.4762(n)2.80762(s)-10.6383(e)2.8071(i)-1.40382(l)-12.0434(a)13.4459(t)-9.23319(i)9.23319(o)-7.8306841.1482938(l)-190.8t2( )-275.191(G)-9.23319( )-73.063(co)2.80762(n)2.80789230..0982829(p)2.80715(a)2.8076e 30..0982191(a)2.807622(n)278.162(t)ereono p e8(l)-190.8t2( )-275.1s4( 30..0982s62( )-285.72(r)-7.42c91(G)-9.23362(s )-73.019(a)2.8102ca28(r)3.211(zi)-1.40219(so)2.102y1(se)-7.82808(278.162998]TJ-300.t46(n)2.808a28(r)3.42039(u)2.80762(r)-2.80892(r)3.21892(r)3.21279(t)1.403n92(r)3.21g92(n)2.80892(o)2.808892(r)3.21h2(r)-2.80892(r)3.21762(n)2.80762(s)-2.8089e)-7.82938(f)-9.23442(r)3.21279(r)-7.42[(co)2.808449(a))3.08928088]TJ-3L05.9'333310 0 cm BT/8]TJ-LT*[(R -18.96 TdE2( )-12.80F)42.80TdE2( )-12.80R28(h)13.44E2( )-12.80N28(h)13.44C2(t)-9.23E2( )-12.80S2( )-12.808928086.72 Tm( )Tj(t)-3L05.9'3T*[(A2( )-12.80[(i)-1.40892(r)3.2146(q)-7.82892(e)2.80892(n)-7.82992(f)-9.234A2( )-12.80938(r)3.21279()-9.234T)-6.2.878892(r)3.21068(g)2.80746(s)-10.6892(t)1.403e8(l)-1.40381(a)13.44o6(q)-7.82892(e)2.80892(f)-9.234A2( )-12.80R28(h)13.44938(r)3.21279()-9.23419( )-275.192( )-83.738(l)-12.019( )-73.0068(g)2.80779( )-275.191(a)2.807304.56 0 TliGn30..0982A2( )-12.8062(u)-7.83192(r)3.212x62( )-19.8715(a)2.80762(n)2.80(ss )-275.6559(715(a)2.80o9(o)-7.83068li)9.233P2( )-12.80898liss ntooot liss isno a nu rpese275.4 0 1 err rnhptpose 71.162993.44d[(u)2.2344511(3.44892(r)3.21h22(e)2.80892(n)-7.8244511(3.44b8(f)-9.23442(r)3.212o6(q)-7.82w40511(3.44d[(u)2.2344511(3.44892(r)3.21(ss )-275.28(i)-1.40446(q)-7.82892(r)3.21449(a)2.808927828086.252 Tm( )Tj930762(r)]TJM6(t)8s )-11(i)-9.23449(a)2.80892(n)-7.82cu8(i)9.23319(s11(s )-432938(a)292(e)-7.8306s11(s )-B2( )-12.80762(t)1.40511(i)-12.0l11(s )-11(i)-12.062(r)-7.42362( )-275.162( )-19.8715(a)2.80762(n)2.807611(s )-E2( )-12.80v319(i)9.23362(u)-7.8392( )-83.7.84(a)13.4459(t)-9.23319(i)9.23319(o)-7.8368(n)2.8076227828086.310 0 cm BT/666132(e)]TJ119(i)9.2339)55628086.72 Tm( )Tj(t)49(ci)]TJ,84(a)13.4419(o)-7.83299(i)9.23379(o)-7.8329(o)-8.44–9(o)-7.83119(i)9.23329(o)-7.8389(o)-7.8379(o)-7.83449(a))3.0892808-28977.998t)-3d05.96 3T*[(A2( )-12.80v6 -18.96 Tds892(r)3.2127951.78778JC49(a)2.80892(51.78778(ss )-275.222(r)3.21022(r)3.2102(i)-1.404092(r)3.21)) )-12.808927828086.252 Tm( )Tj840511(i)]TJP2( )-12.80h2(r)-2.80y892(t)1.40311(i)-9.2362(r)-2.80892(r)3.212o92(r)3.21g9(l)-1.40381(a)-7.82319(r)3.21262( )-285.h2(r)-7.42362(51.7872459(t)-9.23T)42.8781279(t)-9.23319(h)-7.8351.7864H Gs ip anNpfrass2(n)2.80762epn51.7864S2( )-12.8062( )-285.72(l)-190.8i9(sn)2.807e9(o)-7.83s i
60
Costa LP, Leite YLR, Fonseca GAB, Fonseca MT (2000) Biogeography of South
American forest mammals: endemism and diversity in the Atlantic Forest.
Biotropica, 32, 872–881.
Courtenay O & Maffei L (2004) Cerdocyon thous (Linnaeus, 1766). In: Canid
Action Plan (eds Hoffmann M, Sillero-Zubiri C) IUCN Publications, Gland,
Switzerland.
Cracraft J (1988) Deep-history biogeography retrieving the historical pattern of
evolving continental biotas. Systematic Zoology, 37, 221–236.
Dalén L, Fuglei E, Hersteinsson P et al. (2005) Population history and genetic
structure of a circumpolar species: the artic fox. Biological Journal of the
Linnean Society, 84, 79-89.
De Oliveira PE, Behling H, Ledru MP et al. (2005) Paleovegetação e paleoclimas
do Quaternário do Brasil. In: Quaternário do Brasil (eds Souza CRG, Suguio K,
Oliveira MAS, Oliveira PE), pp. 52-73. Holos Editora, Ribeirão Preto, Brasil.
Dinerstein E, Molson D, Graham DJ et al. (1995) A Conservation assessment of
the terrestrial ecoregions of Latin Amarica and the Caribbean. The World Bank,
Washington D.C.
Ditchfield AD (2000) The comparative phylogeography of Neotropical mammals:
patterns of intraspecific mitochondrial DNA variation among bats contrasted to
nonvolant small mammals. Molecular Ecology, 9, 1307–1318.
Dupanloup I, Schneider S, Excoffier L (2002) A simulated annealing approach to
define the genetic structure of populations. Molecular Ecology, 11, 2571–2581.
Eizirik E, Bonatto SL, Johnson WE, Crawshaw Jr PG, Vié JC, Brousset DM,
O’Brien SJ, Salzano FM (1998) Phylogeographic patterns and evolution of the
mitochondrial DNA control region in two Neotropical cats (Mammalia, Felidae).
Journal of Molecular Evolution, 47, 613-624.
Eizirik E, Kim JH, Raymond MM, Crawshaw Jr PG, O’Brien SJ, Johnson WE
(2001) Phylogeography, population history and conservation genetics of
jaguars (Panthera onca, Mammalia, Felidae). Molecular Ecology, 10, 65-79.
Excoffier L, Smouse P, Quattro J (1992) Analysis of Molecular Variance inferred
from metric distances among DNA haplotypes: Application to human
mitochondrial DNA restriction data. Genetics, 131, 479-491.
Farrel LE, Roman J, Sunquist ME (2000) Dietary separation of sympatric
carnivores identified by analysis of scats. Molecular Ecology, 9, 1583-1590.
Fu YX (1997) Statistical tests of neutrality of mutations against population growth,
hitchhiking and background selection. Genetics, 147, 915-925.
Gay L, Defous du Rau P, Mondain-Monval JY, Crochet PA (2004) Phylogeography
of a game species: the red-crested pochard (Netta rufina) and consequences
of its management. Molecular Ecology, 13, 1035-1045.
Geffen E, Anderson MJ, Wayne RK (2004) Climate and habitat barriers to
dispersal in the highly mobile gray wolf. Molecular Ecology, 13, 2481-2490.
Ginsberg JR, MacDonald DW (1990) Foxes, Wolves, Jackals, and Dogs: An
Action Plan for the Conservation of Canids. IUCN Publications, Gland,
Switzerland.
Girman DJ, Vilà C, Geffen E et al. (2001) Patterns of population subdivision, gene
flow and genetic variability in the African Wild Dog (Lycaon pictus). Molecular
Ecology, 10, 1703-1723.
Hare MP (2001) Prospects for nuclear gene phylogeography. Trends in Ecology
and Evolution, 16, 700–706.
Hey J. & Nielsen R (2004) Multilocus methods for estimating population sizes,
migration rates and divergence time, with applications to the divergence of
Drosophila pseudoobscura and D. persimilis. Genetics, 167, 747-760.
Huelsenbeck JP & Ronquist F (2001) MrBayes: bayesian inference of phylogeny.
Bioinformatics, 17, 754-755.
Kamier JF, Ballard WB, Gese EM, Harrison RL, Karkis S, Mote K (2004) Adult
male emigration and a female-based organization in swift foxes, Vulpes velox.
Animal Behavior, 67, 699-702.
Koopman ME, Cypher BL, Scrivner FH (2000) Dispersal patterns of San Joaquin
kit foxes (Vulpes macrotis mutica). Journal of Mammalogy, 81, 213-222.
Kuhner MK, Yamato J, Felsenstein J (1995) Estimating effective population size
and mutation rate from sequence data using Metropolis-Hastings sampling.
Genetics, 140, 1421–1430.
Kumar S, Tamura K, and Nei M (2004) MEGA3: Integrated software for molecular
evolutionary genetics analysis and sequence alignment. Briefings in
Bioinformatics, 5, 2.
Lara MC & Patton JL (2000) Evolutionary diversification of spiny rats (genus
Trinomys, Rodentia: Echimyidae) in the Atlantic Forest of Brazil. Zoological
Journal of the Linnean Society , 130, 661–686.
Langguth A (1969) Die sudmerikanischen Canidae under besonderer
berucksichtigung des mahnenwolfes Chrysocyon brachyurus Illiger. Zeitschirift
fur wissenachaftliche Zoologie, 179, 1-88.
62
Langguth A (1975) Ecology and evolution in the South American canids. In: The
Wild Canids (ed Fox MW), pp.192-206. Litton Educational Publishing, New
York.
Lehman N, Wayne RK (1991) Analysis of coyote mitochondrial DNA genotype
frequencies: estimation of the effective number of alleles. Genetics, 128, 405-
416.
Lyons LA, Laughlin TF, Copeland NG, Jenkins NA, Womack JE, O'Brien SJ (1997)
Comparative anchor tagged sequences (CATS) for integrative mapping of
mammalian genomes. Nature Genetics, 15, 47-56.
MacDonald DW, Courtenay O (1996) Enduring social relationships in a population
of crab-eating zorros, Cerdocyon thous, in Amazonian Brazil (Carnivora,
Canidae). Journal of Zoology, London, 239, 329-355.
Mantel N (1967) The detection of disease clustering and a generalized regression
approach. Cancer Research 27, 209-220.
Murphy WJ, Sun S, Chen ZQ, Pecon-Slattery J, O'Brien SJ (1999) Extensive
conservation of sex chromosome organization between cat and human
revealed by parallel radiation hybrid mapping. Genome Research, 9, 1223-
1230.
Nei M (1987) Molecular evolutionary genetics. Columbia Univ. Press. New York.
Nielsen R & Wakeley J (2001) Distinguishing migration from isolation. A Markov
chain Monte Carlo approach. Genetics, 158, 885-96.
Posada D, Crandall KA (1998) Modeltest: testing the model of DNA substitution.
Bioinformatics, 14, 817-818.
Posada D, Crandall KA, Templeton AR (2000) GeoDis: a program for the cladistic
nested analysis of the geographical distribution of genetic haplotypes.
Molecular Ecology, 9, 487-488.
Rogers AR, Harpending H (1992) Population growth makes waves in the
distribution of pairwise genetic differences. Molecular Biology and Evolution, 9,
552-569.
Rozas J, Sánchez-DelBarrio JC, Messeguer X, Rozas R (2003) DnaSP, DNA
polymorphism analyses by the coalescent and other methods. Bioinformatics,
19, 2496-2497.
Sacks NB, Brown S, Ernest HB (2004) Population structure of California coyotes
corresponds to habitat-specific breaks and illuminates species history.
Molecular Ecology, 13, 1265-1275.
Saiki RK, Scharf S, Faloona F et al. (1985) Enzymatic amplification of beta-globyn
genomic sequences and restriction site analysis for diagnosis of sickle cell
anemia. Science, 230, 1350-1354.
Saitou N & Nei M (1987) The neighbor-joining method: A new method for
reconstructing phylogenetic trees. Molecular Biology and Evolution, 4,406-425.
Sambrook J, Fritsch EF, Maniatis T (1989) Molecular Cloning: a Laboratory
Manual 2nd edn. Cold Spring Harbor Laboratory Press, New York.
Schneider S, Roessli D, Excoffier L (2000) ARLEQUIN, version 2.000. A Software
for Population Genetics Data Analysis. Switzerland, Genetics and Biometry
Laboratory. University of Geneva, Geneva Switzerland.
Spinks PQ & Shaffer BH (2005) Range-wide molecular analysis of the western
pond turtle (Emys marmorata): cryptic variation, isolation by distance, and their
conservation implications. Molecular Ecology, 14, 2047-2064.
Stephens M & Donnelly P (2003) A comparison of Bayesian methods for
haplotype reconstruction from population genotype data. American Journal of
Human Genetics, 73, 1162-1169.
64
Templeton AR, Boerwinkle E, Sing CF (1987) A cladistic analysis of phenotypic
associations with haplotypes inferred from restriction endonuclease mapping
and DNA sequence data: Basic theory and an analysis of alcohol
dehydrogenase activity in Drosophila. Genetics, 117, 343–351.
Vanzolini PE (1988) Distributional patterns of South American lizards. In:
Proceedings of a workshop on Neotropical distribution patterns (eds Vanzolini
PE & Heyer WR), pp. 317–342. Academia Brasileira de Ciências, Rio de
Janeiro.
Venta PJ, Brouillette JA, Yuzbasiyan-Gurkan V, Brewer GJ (1996) Gene-specific
universal mammalian sequence-tagged sites: application to the canine
genome. Biochemical Genetics, 34, 321-341.
Vilà C, Amorim IR, Leonard JA et al. (1999) Mitochondrial DNA phylogeography
and population history of the grey wolf Canis lupus. Molecular Ecology, 8,
2089-2183.
Ward RH, Frazier BL, Dew-Jager K, Pääbo S (1991) Extensive mitochondrial
diversity within a single Amerindian tribe. Proceedings of the National Academy
of Sciences of the USA, 88, 8720-8724.
Watterson GA (1975) On the number of segregating sites in genetical models
without recombination. Theoretical Population Biology, 7, 256-276.
Wayne RK (1996) Conservation genetics in the Canidae. In: Conservation
Genetics (eds Avise JC, Hamrick JL), pp. 75-113, Chapman & Hall, New York.
Zhang DX & Hewitt GM (2003) Nuclear DNA analyses in genetic studies of
populations: practice, problems and prospects. Molecular Ecology, 12, 563–
584.
Acknowledgments
The authors wish to thank all the people and institutions listed in Table 1,
who provided biological samples used in this study. We are also grateful to Centro
Nacional de Pesquisas para a Conservação de Predadores Naturais - CENAP /
IBAMA, Instituto Pró-Carnívoros and CNPq for having supported this project. We
especially thank Dênis A. Sana, Luís Carlos Diniz, Tatiane C. Trigo, Ana Paula
Brandt, Ronaldo G. Morato, Flávio H. G. Rodrigues, Rodrigo Jorge, Julio
Dalponte, Felipe Grazziotin, Karla Yotoko, Nelson Fagundes, Fernanda P. Valdez,
Paulo Prates Jr., Cladinara Sarturi, Sandro L. Bonatto, Maurício R. Bogo and
Laura Utz for support at various stages of this research, and two anonymous
reviewers whose suggestions have significantly improved the quality of this paper.
Figure Legends
Figure 1. Map showing the current geographic distribution of Cerdocyon thous
(modified from Courtenay & Maffey 2004) and approximate sample collection sites
(polygons) identified by ecoregion (i.e. major vegetation domains; the Southern
Atlantic Forest region includes marginal portions of adjacent biomes [Chaco and
southern grasslands]). Polygons are colored to indicate th
66
Fig. 5. Graph depicting the result of the Mismatch Distribution Analysis performed
for the Southern Clade of Cerdocyon thous, based on mtDNA control region
sequences. The main observed peak is at 3.4 differences between sequences.
Fig. 6. Minimum evolution trees of Cerdocyon thous mtDNA cytochrome b
sequences (615 bp). Labels are individual identification numbers followed by
ecoregion symbols (coded as in Fig. 1). Values above or below branches indicate
nodal bootstrap support in maximum parsimony/minimum evolution/maximum
likelihood trees. Asterisks indicate bootstrap support <50%. (a) Analysis including
the Venezuelan sequence from GenBank (see text) (b) Analysis excluding the
Table 1. Samples analyzed in the present study.
ECOREGION GEOGRAPHIC ORIGIN
(SAMPLE SITE)
SAMPLES INSTITUTION / CONTACT
P.N. Iguaçu, Paraná State, S
Brazil (PR)
bCth08
1
, bCth59
1 2 3 4 5
, bCth60
1
,bCth61
1
, bCth63
1 3 4 5
, bCth64
1
, bCth65
1
, bCth66
1
,
bCth67
1
, bCth68
1
, bCth71
1
, bCth74
1
, bCth77
1
UNIOESTE/José Flávio Cândido Jr.
and Instituto Pró-Carnívoros
Mato do Grosso do Sul State, SW
Brazil (MS)
bCth11
1
, bCth164
1
, bCth166
1 3 4 5
, bCth172
1 3 4 5
,bCth174
1
Instituto Pró-Carnívoros/ Dênis Sana
Paraguay (PY1) bCth91
1 3 4 5
, Guillermo D`Elia
Paraguay (PY2) bCth155
1
L. Tchaicka
Santa Catarina State, S Brazil
(SC1)
bCth153
1 5
,bCth154
1 3 4 5
L. Tchaicka
Santa Catarina State, S Brazil
(SC2)
bCth178
1 3 4 5
, bCth180
1
, bCth182
1
, bCth212
1
, bCth213
1
Sérgio Althoff, José F. Stholz and
Zoológico de Pomerode
Santa Catarina State, S Brazil
(SC3)
bCth210
1
,bCth211
1
CENAP-IBAMA
Rio de Janeiro State, E Brazil
(RJ)
bCth214
1 3 4 5
Zoológico de Pomerode
São Paulo State, E Brazil (SP1) bCth218
1
, bCth219
1 3 4 5
, bCth220
1
, bCth301
1
Instituto Pró-Carnívoros / C. Prada
São Paulo State, E Brazil (SP2) bCth305
1 4 5
Eduardo Nakano
Rio Grande do Sul State, S Brazil
(RS1)
bCth15
1 3 4 5
Margareth Mattevi
Rio Grande do Sul State, S Brazil
(RS2)
bCth106
1 5
, bCth112
1 2 3 4 5
, bCth116
1
, bCth118
1
, bCth126
1 5
Alex Bager
Rio Grande do Sul State, S Brazil
(RS3)
bCth13
1
, bCth90
1
Instituto Pró-Carnívoros, Mariana
Faria-Corrêa
Rio Grande do Sul State, S Brazil
(RS4)
bCth01
1
, bCth02
1
, bCth12
1
, bCth41
1
, bCth83
1
, bCth98
1 3 4 5
, bCth100
1
, bCth142
15
Mariana Faria-Corrêa, Instituto Pró-
Carnívoros
Rio Grande do Sul State, S Brazil
(RS5)
bCth26
1
, bCth27
1
, bCth28
1
, bCth31
15
, bCth33
15
, bCth34
15
Instituto Pró-Carnívoros, T. C. Trigo,
A. P. Brandt and F. Michalski
Southern Atlantic
Forest
Rio Grande do Sul State, S Brazil
(RS6)
bCth20
1 5
, bCth21
1
bCth23
1
, bCth35
1
bCth39
1 3 4 5
, bCth40
1
T. C. Trigo, A. P. Brandt and F.
Michalski
Minas Gerais State, E Brazil
(MG1)
bCth198
1
, bCth199
1
, bCth200
1
Fabrício Horta
Minas Gerais State, E Brazil
(MG2)
bCth336
1 3 4 5
Instituto Pró-Carnívoros / F. Rodrigues
Goiás State, Central Brazil (GO1) bCth203
1
, bCth204
1
, bCth205
1 3 4 5
, bCth206
1
, bCth207
1
, bCth208
1 3 4 5
, bCth209
1
Zoológico de Goiânia/ Roberto
Portela; CENAP-IBAMA
Goiás State, Central Brazil (GO2) bCth05
1
Margarete Mattevi
Mato Grosso State, SW Brazil
(MT1)
bCth159
1
, bCth161
1 3 4 5
, bCth163
1
R. Jorge, J. Dalponte, Instituto Pró-
Carnívoros
Cerrado
Tocantins State, Central Brazil
(TO)
bCth177
1
L. Tchaicka
PN Serra da Capivara, Piaui
State, NE Brazil (PI)
bCth201
1 5
, bCth202
1
FUNDHAM/ Vanderson C.Vaz and
Paulo César D´Andrea
Caatinga
Ceará State, NE Brazil (CE) bCth192
1 2 3 4 5
, bCth193
1
, bCth194
1 3 4 5
, bCth195
1
, bCth196
1
, bCth197
1
Zoológico de Fortaleza/ Luiz C. Diniz
Table 1. (continued)
2
Pará State, N Brazil (PA) bCth221
1
, bCth223
1 3
Tadeu de Oliveira
Maranhão State, N Brazil (MA1) bCth222
1
Tadeu de Oliveira
Maranhão State, N Brazil (MA2) bCth230
1
Tadeu de Oliveira
Eastern
Amazonia
Maranhão State, N Brazil (MA3) bCth224
1 4
, bCth225
1
, bCth226
1
, bCth227
1 4
, bCth228
1 2 3 4 5
Tadeu de Oliveira
Pantanal Mato Grosso State, SW Brazil
(MT2)
bCth48
1
, bCth49
1
, bCth50
1
, bCth51
1 3 4 5
, bCth56
1 2 3 4 5
L. Tchaicka
Northern Atlantic
Paraíba State, NE Brazil (PB) bCth309
1 3 4
F. Rodrigues / Instituto Pró-Carnívoros
Forest Bahia State, NE Brazil (BA) bCth186
1 3 4 5
, bCth187
1 3 5
Zoológico de Salvador/Cláudio V. Lyra
Pernambuco State, NE Brazil
(PE)
bCth184
1 2 3 5
, bCth185
1 3 4 5
Zoológico do Recife/ Poly-Ana Celina
Outgroups
Pseudalopex gymnocercus bPgy18
1 2 3 5
bPgy19
1
, bPgy37
1
Instituto Pró-Carnívoros
Pseudalopex vetulus bPve02
1
, bPve03
1 5
, bPve08
1 2 3 4
L. Tchaicka, C. Prada
1
samples typed for the mtDNA control region
2
samples typed for the cytochrome b gene
3
samples typed for the CHRNA1 intron
4
samples
typed for the FES intron
5
samples typed for the PLP1 intron
Table 2. List of individuals that bear each mitochondrial DNA control region haplotype. Also indicated are the absolute frequency in the sample (Fr)
and geographic distribution of haplotypes.
a
Absolute frequency on the total sample.
Haplotype Individuals Fr
a
Ecoregion
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
C16
C17
C18
C19
C20
C21
C22
C23
C24
C25
C26
C27
C28
C29
C30
C31
C32
C33
C34
C35
bCth49
bCth12,20,21,39,67,83,98,100,142,210,211
bCth221,227,230
bCth226
bCth118
bCth209
bCth198,200
bCth08,27,174,199,219,336
bCth13,23,34,106,112,126,212,213,178
bCth02,61,63,172
bCth91,155
bCth48
bCth15
bCth01
bCth05,11,26,28,31,33,35,40,41,56,59,60,64,65,66,68,71,74,77,90,
116,153,154,159,161,164,166,180,182,202,203,204,207,214,218,220,
301
bCth206,208
bCth163
bCth50
bCth205,223
bCth196
bCth305
bCth184
bCth177
bCth195
bCth222
bCth224
bCth225
bCth309
bCth185
bCth51
bCth228
bCth197
bCth192,193,194
bCth201
bCth186,187
1
11
3
1
1
1
2
6
9
4
2
1
1
1
37
2
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
3
1
2
Pantanal
Southern Atlantic Forest
Eastern Amazonia
Eastern Amazonia
Southern Atlantic Forest
Cerrado
Cerrado
Southern Atlantic Forest,Cerrado
Southern Atlantic Forest
Southern Atlantic Forest
Southern Atlantic Forest
Pantanal
Southern Atlantic Forest
Southern Atlantic Forest
Southern Atlantic Forest,
Pantanal,Cerrado, Caatinga
Cerrado
Cerrado
Pantanal
Eastern Amazonia, Cerrado
Caatinga
Southern Atlantic Forest
Northern Atlantic Forest
Cerrado
Caatinga
Eastern Amazonia
Eastern Amazonia
Eastern Amazonia
Northern Atlantic Forest
Northern Atlantic Forest
Pantanal
Eastern Amazonia
Caatinga
Caatinga
Caatinga
Northern Atlantic Forest
Table 3. Nucleotide and gene diversity observed in the Cerdocyon thous mtDNA control region (specified separately for different ecoregions and
also for the two major phylogeographic clades) and three nuclear intron segments.
Locus
Group N
a
Nucleotide diversity (SE) Gene diversity (SE)
Southern Atlantic Forest 62 0.009 (±0.001) 0.73 (±0.046)
Northern Atlantic Forest 5 0.006 (±0.001) 0.90 (±0.160)
Caatinga 8 0.028 (±0.005) 0.89 (±0.110)
Eastern Amazonia 9 0.038 (±0.005) 0.91 (±0.092)
Pantanal 5 0.021 (±0.025) 1 (± 0.120)
Cerrado 16 0.012 (±0.005) 0.75 (±0.107)
Southern Clade 88 0.008 (±0.001) 0.76 (±0.041)
Northern Clade 17 0.021 (±0.001) 0.97 (±0.032)
mtDNA
control
region
Total sample 106 0.019 (±0.002) 0.83 (±0.032)
CHRNA1
Total sample 56 0.00061(±0.0002) 0.17 (±0.067)
FES
Total sample 56 0.00041(±0.0001) 0.13 (±0.061)
PLP1
Total sample 45 0.00090(±0.0003) 0.20 (±0.060)
a
Number of individuals indicated for the mtDNA control region; number of chromosomes indicated for nuclear introns.
2
Table 4. Support for population groupings estimated using Φ
ST
values
calculated for mtDNA control region haplotypes.
Scheme Included Groups
Φ
ST
*
Two groups suggested by the phylogenetic analysis
(PI sample-site grouped with the Southern region)
(Eastern Amazonia without MA2 + Northern Atlantic Forest + Caatinga without
PI +TO) (Cerrado without TO + Pantanal + Southern Atlantic Forest + MA2 +
PI)
0.70
Two groups suggested by the phylogenetic analysis
(PI sample-site grouped with the Northern region)
(Eastern Amazonia without MA2 + Northern Atlantic Forest + Caatinga +TO)
(Cerrado - without TO + Pantanal + Southern Atlantic Forest + MA2)
0.68
Two geographic groups: Eastern Amazonia grouped
with the Southern region
(Caatinga + Northern Atlantic Forest) (Eastern Amazonia + Southern Atlantic
Forest + Cerrado + Pantanal)
0.68
Two geographic groups: Eastern Amazonia grouped
with the Northern region
(Eastern Amazonia + Caatinga + Northern Atlantic Forest) (Southern Atlantic
Forest + Cerrado + Pantanal)
0.61
Two groups suggested by SAMOVA based on
ecoregions
(Northern Atlantic Forest) (Caatinga + Eastern Amazonia + Cerrado +
Pantanal + Southern Atlantic Forest)
0,66
Three groups suggested by SAMOVA based on
ecoregions
(Eastern Amazonia) (Northern Atlantic Forest + Caatinga) ( Southern Atlantic
Forest + Cerrado + Pantanal)
0.45
Four groups suggested by SAMOVA based on
ecoregions
(Northern Atlantic Forest) (Caatinga) (Eastern Amazonia) (Cerrado + Pantanal
+ Southern Atlantic Forest)
0.66
Five groups suggested by SAMOVA based on
ecoregions
(Northern Atlantic Forest) (Caatinga) (Eastern Amazonia) (Pantanal) (Cerrado
+ Southern Atlantic Forest)
0.63
Six ecoregions treated as individual units See Fig. 1 0.54
Ecoregions treated as units (Northern region only) (Caatinga) (Northern Atlantic Forest) (Eastern Amazonia) 0.10
Ecoregions treated as units (Southern region only) (Cerrado)(Southern Atlantic Forest)(Eastern Amazonia)(Pantanal) 0.09
Two groups suggested by SAMOVA based on
individual sample-sites
(CE + Northern Atlantic Forest + TO+ MA1) (PI + Eastern Amazonia without
MA1+ Cerrado without TO + Pantanal + Southern Atlantic Forest)
0.74
Three groups suggested by SAMOVA based on
individual sample-sites
(CE) (Northern Atlantic Forest + TO+ MA1) (PI + Eastern Amazonia without
MA1 + Cerrado without TO + Pantanal + Southern Atlantic Forest)
0.75
32 sample-sites as separate units See Fig. 1 0.52
Sample-sites treated as units (Southern region only)
(PR)(SC1)(SC2)(SC3)(MG1)(MG2)(MT1)(MT2)(PY1)(PY2)(RJ)
(SP1)(SP2)(GO1)(GO2)(MS)(PA)(MA1)(MA2)(MA3)(RS1)(RS2)
(RS3)(RS4)(RS5)(RS6)
0.16
Sample-sites treated as units (Northern region only) (BA)(PB)(PE)(PI)(TO)(CE)(MA1)(MA2)(MA3)(PA) 0.14
*
Φ
CT
are reported in SAMOVA results
Table 5. Demographic parameters inferred for the two main geographic groups of Cerdocyon thous using the coalescent-based approaches
implemented in LAMARC. Values are means calculated from multiple runs using maximum likelihood and Bayesian search strategies (see
Methods). 95% confidence intervals (also means from multiple runs) are shown in parentheses.
mtDNA-CR Nuclear mean
b
Overall
c
θ - South
0.025 (0.015 – 0.044) 0.008 (0.002 – 0.804) 0.014 (0.012 – 0.035)
θ - North
0.126 (0.037 – 0.395) 0.032 (0.037 – 1.115) 0.031 (0.020 – 0.128)
Nm (South-North)
a
1.544 (0.100 – 12.473) 6.383 (2.146 – 270.373) 1.556 (0.505 – 25.777)
Nm (North-South)
a
0.394 (0.055 – 1.670) 1.223 (0.046 – 212.685) 0.761 (0.248 – 2.521)
a
The number of migrants per generation (Nm) was calculated from the estimated migration rate parameter “M” in LAMARC (as suggested in the
program documentation), incorporating the mean θ of the recipient population to correct for variation in the mutation rate among segments.
b
The nuclear mean is the average estimate from the three nuclear intron segments (CHRNA1, FES and PLP1) analyzed here.
c
Joint inference from the mtDNA control region and nuclear intron data sets.
Table 6. Mitochondrial DNA cytochrome b haplotypes identified from crab-eating fox samples (ecoregion
representation indicated on the right), along with a Venezuelan sequence (VEN) available from GenBank. The
top three lines comprise samples from the Northern phylogeographic group identified here, while the bottom
three are samples from the Southern group (see text). Only variable sites are shown. Site numbers (vertical
notation) refer to the aligned position in our 615 bp data set.
Sample Variable Site
1 2 2 2 2 3 4 4 4 4 5 5 5 5
2 9 5 6 6 8 9 0 2 7 9 0 1 2 6
7 6 6 5 8 9 4 6 7 6 0 5 0 0 9
Ecoregion
bCth184
bCth192
bCth228
VEN
bCth112
bCth59
bCth56
TTCTCTCCACCCTAG
.C....T......G.
.C....T..T...G.
??????...??????
C.TCTC....TT..A
C.TCTC.TG..T...
C.TCTC..G..TG..
Northern Atlantic Forest
Caatinga
Eastern Amazonia
Venezuela (GenBank)
Southern Atlantic Forest
Southern Atlantic Forest
Pantanal
Table 7. Haplotypes identified in three nuclear introns (CHRNA1, FES and PLP1) sequenced for Cerdocyon thous individuals.
Haplotype
Variable
sites
a
Samples Fr
b
CHRNA1
CH1
AGGCG bCth15,39,51,59,56,63,91,98,112,336,154,172,178,184,185,186,
187, 205,208,214,219,223,228
40
CH2
...CC bCth63,154,161,166,184,187,194,208,305 11
CH3
...TC bCth305 1
CH4
..A.. bCth186 1
CH5
.C... bCth192 1
CH6
GC...
bCth192,194 2
FES
F1
CTC
bCth15,39,51,56,59,63,91,98,112,154,161,166,172,178,185,186,192,194,
205,208,214,219,224,227,228,305,309,336
51
F2
..T bCth178 1
F3
.C. bCth39,219,305 3
F4
T..
bCth98 1
PLP1
P1
GCCT bCth142 1
P2
.T.. bCth59,142,172,194 4
P3
...C bCth15,20,31,33,34,39,51,56,63,86,91,98,336,106,112,126,153,154,161,
166,172,178,184,185,186,192,201,205,208,214,219,228,305
39
P4
A.TC bCth187 1
a
Variable sites correspond to the following nucleotide positions for each gene: CHRNA1: 29,143,210,220,276; FES: 82,160,230; PLP1:
336,425,473,610.
b
Absolute frequency in the total sample of chromosomes (see Fig. 7).
2
Table 8. Summary of inferences on C. thous population history obtained from various analytical approaches performed in this study.
a
N.P.: Analysis not performed with the combined mtDNA+nDNA data set.
Analytical method mtDNA nDNA Combined mtDNA+nDNA
a
Phylogenetic and network-based analyses Two well defined clades,
population split of North vs.
South took place in the Middle
Pleistocene; population
expansion of Southern clade ca.
100,000 years ago.
No phylogeographic
partitioning.
N. P.
AMOVA, SAMOVA, Mantel test, NCA North vs. south partition,
isolation by distance.
No genetic structure. N. P.
Mismatch distribution / Neutrality tests Recent expansion in the South;
longer time of stable population
in the North.
No conclusive evidence of
expansion.
N. P.
Diversity indices /
Effective population size (N
e
)
High molecular diversity; higher
diversity in the Northern group,
implying larger historical female
N
e
in this region.
High molecular diversity. N. P.
Coalescent-based estimate of N
e
(LAMARC and IM)
High molecular diversity;
estimate of larger female
historical N
e
in the North than in
the South.
Higher diversity (implying
larger N
e
) in the Northern
region.
Higher diversity (implying
larger N
e
) in the Northern
region.
Coalescent-based dating of South-North
population divergence (IM)
Population split of North vs.
south took place in Middle
Pleistocene,
N. P. N. P.
Coalescent-based estimation of population
growth (g parameter - LAMARC)
Suggestive of population
expansion in both North and
South.
Suggestive of population
expansion in both North and
South.
Suggestive of population
expansion in both North and
South.
Estimate of migration rates (LAMARC) Higher migration from South to
North.
Higher migration from South to
North; higher migration than
estimated by the mtDNA data
set, supporting male-biased
gene flow.
Higher migration from South
to North.
♦
Species range
Eastern Amazonia
Cerrado
Pantanal
Southern Atla
ntic Forest
Caatinga
Northern Atlantic Forest
Venezuela
RS1
RS5
RS4
RS3
RS6
RS2
SC1
SC3
SC2
PR
PY1
PY2
SP1
SP2
MS
RJ
MG1
MG2
GO1
GO2
MT2
MT1
TO
BA
PI
PE
PB
CE
PA
MA3
MA1
MA2
VEN
5
4
3
2
1
2
NORTHERN CLADE
C14
C4
C3
C6
C2
C5
C15
C11
C9
C10
C17
C21
C16
C13
C12
C18
C8
C7
C19
C20
C1
C29
C25
C35
C22
C24
C26
C27
C28
C23
C30
C33
C34
C32
C31
P.vetulus
P.vetulus
P.vetulus
P.gymnocercus
P.gymnocercus
P.gymnocercus
0.005 substitutions/site
99/70/100/100
99/98/100/100
85/ */62/53
97/87/93/99
99/ */85/93
79/ */54/64
99/94/99/100
57/ */73/76
54/ */54/64
75/ */*/56
*/ */99/70
57//52/88
SOUTHERN CLADE
♦
♦
♦
♦
NORTHERN CLADE
C14
C4
C3
C6
C2
C5
C15
C11
C9
C10
C17
C21
C16
C13
C12
C18
C8
C7
C19
C20
C1
C29
C25
C35
C22
C24
C26
C27
C28
C23
C30
C33
C34
C32
C31
P.vetulus
P.vetulus
P.vetulus
P.gymnocercus
P.gymnocercus
P.gymnocercus
0.005 substitutions/site
99/70/100/100
99/98/100/100
85/ */62/53
97/87/93/99
99/ */85/93
79/ */54/64
99/94/99/100
57/ */73/76
54/ */54/64
75/ */*/56
*/ */99/70
57//52/88
SOUTHERN CLADE
♦
♦
♦
♦
57/59
52/88
C15
C
8
C9
C11
C20
C7
C1
C19
C10
C17
C16
C18
C12
C14
C13
C21
C3
C5
C2
C6
C4
SOUTHERN CLADE
2
-
1
3
-
2
3
-
3
2
-
4
1
-
2
4
-
1
NORTHERN CLADE
C22
C25
C35
C24
C29
C28
C27
C26
C30
C34
C3
3
C31
4
-
2
C32
4
0
0,01
0,02
0,03
0,04
0,05
0,06
0,07
0,08
0 1000 2000 3000 4000
Distance (Km)
Genetic Distance
0
0,1
0,2
0,3
0,4
Obs
Exp
6
100/100/100
70/59/66
*
90/83/83
58/ */40
90/83/83
100/100/100
97/98/98
69/64/70
86/90/88
93/96/93
b
a
bCth59
bCth56
bCth112
bCth184
♦
bCth59
bCth112
bCth56
bCth192
bCth228
P. gymnocercus
P. vetulus
bCth228
P. gymnocercus
P. vetulus
bCth184 ♦
bCth192
8
Author Information Box
This project is part of Ligia Tchaicka’s Ph.D. dissertation at the Graduate Program in Genetics and Molecular
Biology of Federal University of Rio Grande do Sul (UFRGS), Brazil, where she is co-advised by Drs. Thales R.O.
Freitas and Eduardo Eizirik. Her project addresses phylogeographic and population genetic aspects of South
American canids, with emphasis on the genera Cerdocyon and Pseudalopex. Dr. Freitas is an evolutionary geneticist
interested in diverse mammalian systems, with emphasis on Neotropical fossorial rodents. Dr. Eizirik is an
evolutionary and conservation biologist focusing most of his research on Neotropical carnivores. Dr. Candido is a
mammalogist interested in species occurring in Southern Brazil. Tadeu G. de Oliveira is a conservation biologist
working on various species of Neotropical carnivores throughout Brazil, especially in the North of the country.
Online Supplementary Data for “Phylogeography and population history of the crab-eating fox (Cerdocyon thous)”, by L. Tchaicka et al. (ME 06-034)
Contents:
1. Supplementary Table1. Mitochondrial DNA control region haplotypes identified from crab-eating fox samples.
2. Supplementary Table 2. Phylogeographic interpretations derived from the Nested Clade Distance analysis of the
Cerdocyon thous mtDNA control region.
3. Summary of output files from the coalescent-based analyses performed with the Isolation-with-migration model
implemented in the program IM.
1. Supplementary Table1. Mitochondrial DNA control region haplotypes identified from crab-eating fox samples (ecoregion representation indicated
on the right). Only variable sites are shown. Site numbers (vertical notation) refer to the aligned position in our 512 bp data set.
a
Absolute frequence on the total sample
Nucleotide position
11111111111111111111122222222222333333334444455
2222335568901111122222333333445612244446799000011345588800
4678343705541245734789123456184030145690615278927337834989
Fr
a
Ecoregion
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
C16
C17
C18
C19
C20
C21
C22
C23
C24
C25
C26
C27
C28
C29
C30
C31
C32
C33
C34
C35
CTCTCCACGATACTGTCTACCCAACTCAAATTTCTGTTCCCTCCACTACCGACCTTGT
...C.......G...........G.............C....................
...C.......G.C..................C....C....................
...C.......G.C..................C....C...CT???????????????
...C..?....G...........G........C....C....................
...C......CG.C............T..G..C....C...........T........
...C...............T............C...C.....................
...C............................C...C.....................
...C.......G.........T..........C...C.....................
.C.C.......G........T...........C...C.T...................
...C..G....G.........T..........C.........................
...C.....G.G....................C...........G.............
...C.......G....T.........TG....C.........................
...C.......G....................C??....T.?????????????????
...C.......G....................C.........................
T..C.......G....................C................T........
...C.......G........T...........C.........................
...C.......G....................C..A.......T..C...........
...C............................C.........................
...C....................TC......C.........................
...C....A..G....................C.........................
....TT.T..C...A.T.G.T.......G.C.CTCT....T..T.T?GT..GT..CAC
....TT.T......A.T.G.T.........C..TCT....TCT???????????????
??????GT..C...A.T.G.T.........C.CTCT....T..T.TCGT..GT..CAC
....TTGT..C...ACT.G.T.........C.CTCT....TCT???????????????
....TTGT........T.G.T....C....C.CTCT....T..T.TCGT..GT..CAC
....TTGT......A.T.G.T.G..C....C.CTCT....T..T.TCGT..GT..CAC
....TTGT......A.T.G.T.........C.CTCT....T..T.TCGT..GT..CAC
....TTGT....T.A.T.G.T.........C..TCT.C..T..T.TCGT..GT..???
....TTGT....T.A.T.G.TT........C.?TCT...?T.??.T??...GT?.CAC
....TT.T..C...A.T....T........C.CTCT...........G...GT..CAC
..T?TT.T..C...A.TC...T........C.CT.T.......T.T.G.T.GT..CAC
....TTGT......A.TC..TT........CC.TCT..T....T.TCG.T.GT..CAC
....TTGT......A.TC...T........C..TCT....T..T...G.TAGT..???
....TTGT..C...ACT.G.T.........C.CTCT....T..T.TCGT..GTTCCAC
1
11
3
1
1
1
2
6
9
4
2
1
1
1
37
2
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
3
1
2
PANTANAL
SOUTH ATLANTIC FOREST
AMAZON
AMAZON
SOUTH ATLANTIC FOREST
CERRADO
CERRADO
SOUTH ATLANTIC FOREST AND CERRADO
SOUTH ATLANTIC FOREST
SOUTH ATLANTIC FOREST
SOUTH ATLANTIC FOREST
PANTANAL
SOUTH ATLANTIC FOREST
SOUTH ATLANTIC FOREST
SOUTH ATLANTIC FOREST, PANTANAL, CERRADO AND CAATINGA
CERRADO
AMAZON
PANTANAL
AMAZON AND CERRADO
NORTHEAST ATLANTIC FOREST
SOUTH ATLANTIC FOREST
NORTHEAST ATLANTIC FOREST
CERRADO
CAATINGA
AMAZON
AMAZON
AMAZON
NORTHEAST ATLANTIC FOREST
NORTHEAST ATLANTIC FOREST
PANTANAL
AMAZON
CAATINGA
CAATINGA
CAATINGA
NORTHEAST ATLANTIC FOREST
2. Supplementary Table 2. Phylogeographic interpretations derived from the Nested Clade
Distance analysis of the Cerdocyon thous mtDNA control region (see Fig.3).
Clade Chain of inference Inference
Clade 1-2 1-2-3-4 Restricted gene flow with isolation by distance
Clade 2-1 1-2-3-4-9 Allopatric fragmentation
Clade 2-4 1-19-20-2-11-12 Range Expansion/Continuous range expansion
Clade 3-2 1-19-20-2-3-4-9-10 Allopatric fragmentation
Clade 3-3 1-2-3-4-9 Allopatric fragmentation
Clade 4-1 1-2-11 Range Expansion/Continuous range expansion
Clade 4-2 1-2-11-17-4 Restricted gene flow with isolation by distance
Total Cladogram 1-2-11-17-4-9 Allopatric fragmentation
2
3. Summary of output files from the coalescent-based analyses performed with the Isolation-with-
migration model implemented in the program IM.
Final Run 1:
Command line string : -i controlgeoim.u -o Cerd6.out -b300000 -l10000000 -k4 -n4
-m110 -m210 -t20 -q110 -u 2 -a 20 -p5
MARGINAL HISTOGRAMS
----------------------------------
Summaries
q1 q2 qA t m1 m2
Minbin 3.7598 8.0648 0.0287 0.3700 0.0050 0.0050
Maxbin 57.1999 57.3721 57.3721 19.9900 6.5750 6.4550
HiPt 18.7414 40.4389 14.6085 1.3700 0.1550 0.2850
HiSmth 18.6840 41.4721 15.8139 1.4100 0.1650 0.2550
Mean 20.0616 41.1851 25.5147 7.9500 0.2750 0.4050
95Lo 10.5905 21.5540 1.5211 1.0900 0.0250 0.0650
95Hi 36.0764 56.3963 55.5353 19.3900 1.1850 1.5250
Tail? Complete falling flat flat complete complete
MARGINAL HISTOGRAMS IN DEMOGRAPHIC UNITS
Calculations use mutation rates (in years) and generation time (in years) input at
runtime
Parameter Meaning Units
q1 Pop1 Ne Individuals
q2 Pop2 Ne Individuals
qa Ancest.Pop Ne Individuals
t Years Div. Years
Generation time in years specified at runtime: 2.000000
Geometric mean of mutation rates per year (based on rates specified in input file):
1.884000e-005
Geometric mean of ML estimates of relevant mutation rate scalars: 1.000000e+000
----------------------------------
Summaries
q1 q2 qA t
Minbin 24945.2855 53508.5896 190.4220 19639.0658
Maxbin 379511.1000 380653.6321 380653.6321 1061040.3397
HiPt 124345.5837 268304.6362 96924.8118 72717.6221
HiSmth 123964.7396 275159.8291 104922.5369 74840.7643
Mean 133104.9969 273255.6089 169285.1821 421974.5223
95Lo 70265.7280 143006.9423 10092.3674 57855.6263
95Hi 239360.4880 374179.2832 368466.6224 1029193.2059
Tail? complete falling flat flat
Final Run 2:
Command line string : -i controlgeoim.u -o Cerd7.out -b100000 -l3000000 -k10 -n10 -m110 -
m210 -t20 -q110 -u 2 -a 20 -p5
MARGINAL HISTOGRAMS
----------------------------------
Summaries
q1 q2 qA t m1
m2
Minbin 4.9652 7.0890 0.0287 0.5500 0.0050
0.0050
Maxbin 57.2573 57.3721 57.3721 19.9900 4.5350
4.3450
HiPt 19.6024 46.9826 13.9197 1.6700 0.1450
0.2250
HiSmth 18.8562 46.1790 14.7807 1.7500 0.1850
0.2550
Mean 19.8894 41.7591 25.2851 6.9700 0.3250
0.4050
95Lo 9.3276 21.8410 1.7507 1.2700 0.0250
0.0450
95Hi 36.1338 56.5111 55.4779 19.2900 1.6150
1.4050
Tail? complete falling rising flat complete
complete
3
MARGINAL HISTOGRAMS IN DEMOGRAPHIC UNITS
(settings are the same as above)
Summaries
q1 q2 qA t
Minbin 32943.0107 47034.2407 190.4220 29193.2059
Maxbin 379891.9440 380653.6321 380653.6321 1061040.3397
HiPt 130058.2445 311720.8583 92354.6831 88641.1890
HiSmth 125107.2718 306389.0416 98067.3439 92887.4735
Mean 131962.4648 277064.0494 167761.8059 369957.5372
95Lo 61887.1588 144911.1626 11615.7437 67409.7665
95Hi 239741.3321 374940.9713 368085.7783 1023885.3503
Tail? complete falling rising flat
Capítulo IV
2
O
ARTIGO
a ser submetido para publicação na revista Journal of Mammalogy
89
POPULATION GENETIC STRUCTURE OF THE CRAB-
EATING FOX (Cerdocyon thous) INFERRED FROM
MICROSATELLITE LOCI
POPULATION GENETIC STRUCTURE OF THE CRAB-EATING FOX
(Cerdocyon thous) INFERRED FROM MICROSATELLITE LOCI
LIGIA TCHAICKA
*
, FERNANDA P. VALDEZ, DENIS A. SANA, MARIANA FARIA-CORREA,
THALES R.O. FREITAS , EDUARDO EIZIRIK
Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio
Grande do Sul, Campus do Vale – Bloco III, Av Bento Gonçalves 9500 Porto
Alegre, RS 91501970, Brazil (LT/FPV/MFC/TROF)
Centro de Biologia Genômica e Molecular, Faculdade de Biociências, PUCRS. Av.
Ipiranga 6681, prédio 12. Porto Alegre, RS 90619-900, Brazil (EE)
Instituto Pró-Carnívoros, Atibaia, SP, Brazil (DAS/EE)
Laboratory of Genomic Diversity, National Cancer Institute-Frederick, National
Institutes of Health, Frederick, MD 21702-1201, USA (EE)
Key words: Cerdocyon, genetic structure, microsatellites
* Correspondent: ligia.t[email protected]
90
High levels of gene flow are expected in generalist species such as the crab-
eating fox, Cerdocyon thous. This canid ranges through nearly all of South
America, and is found in a variety of vegetation domains, including human-
impacted areas. A previous study using mitochondrial DNA segments indicated
strong phylogeographic partitioning between the northeastern and southern parts
of the species' distribution, which was not supported by nuclear intron sequence
data. In the present study, we investigated ten microsatellite loci, which showed
high levels of polymorphism in this species, and no indication of genetic structuring
throughout Brazil. This result corroborates the hypothesis that male-biased gene
flow has been a major factor leading to the erosion of a historical pattern of
geographic subdivision in this species.
91
Canids in general are excellent dispersers: individuals are not strongly
limited by topographic or habitat barriers, and may range over several hundred
kilometers during their lifetime (Wayne 1996). Species with this pattern of
movement tend to show relatively little genetic differentiation among populations,
and their genetic structure is observable only in fine-scale studies (Geffen et al.
2004; Lehman and Wayne 1991; Roy et al. 1994; Sacks et al. 2004). In contrast,
some species of small canids with more limited vagility may be composed of
different genetic units (e.g. Mercure et al. 1993).
High levels of gene flow would be predicted for habitat generalists with
continuous distributions, such as the crab-eating fox. This fox is among the most
versatile of canids, as evidenced by its ability to exploit a wide variety of habitat
types and food sources (Courtenay and Maffei 2004). Cerdocyon thous ranges
through almost all of South America (Fig. 1). It is found in tropical and subtropical
forests, forest edges, open woodlands, savannas, and human-impacted areas
(Berta 1982, 1987; Langguth 1975; Medel and Jaksic 1988). Individuals are
opportunistic hunters and dietary generalists, eating fruits, eggs, crabs, small
mammals and insects (Juarez and Marinho-Filho 2002; Macdonald and Courtenay
1996).
Social groups of the crab-eating fox are composed of a couple and
sometimes their juvenile or adult offspring, occupying territories that partially
overlap. Detailed field studies of dispersal patterns are still scarce. The little
available data suggest that both male and female juveniles disperse, while
maintaining long-term interactions with their neighboring parents (Macdonald and
Courtenay 1996).
Insights into numerous aspects of species biology can be provided by
assessing the pattern of distribution of genetic variation. Previous phylogeographic
research conducted for C. thous using mitochondrial DNA control region
sequences indicated a strong genetic differentiation between northern and
southern populations in Brazil: these groups were defined by two historical
lineages that diverged ca. 400,000 - 600,000 years ago. In contrast, sequences of
92
three nuclear introns suggested no structure among regions (Tchaicka et al. in
press; [ver Capítulo III]). Coalescent-based analyses performed in that study
suggested that male-biased gene flow was a relevant factor potentially explaining
the lack of structuring in the nuclear data set. Alternative hypotheses were the
longer coalescent times for these loci, and their slower mutation rates relative to
the mtDNA control region segment. Both of these factors might also have
prevented the nuclear intron sequence data from capturing the historical
subdivision process inferred from the mitochondrial segment. To further test these
hypotheses, it is important to investigate nuclear markers that exhibit different
evolutionary properties from the previously analyzed introns, such as faster
mutation rates.
In this study, we assessed the pattern of genetic variation in free-ranging
Cerdocyon thous populations using 10 microsatellite loci. These markers were
found to be highly variable in this species, and provided adequate information
levels for testing the hypothesis of no population structuring based on nuclear
DNA.
MATERIALS AND METHODS
Biological material was obtained from 82 individuals, sampled at 17 sites
across most of the species' range. To explore regional-level patterns of population
structure, we selected three sites in Southern Brazil (MS, PR and RS) to perform
more extensive sampling, including 16-19 individuals from each locale (Fig. 1 and
Table 1).
Genomic DNA was extracted using a standard phenol/chloroform protocol
(Sambrook et al. 1989) from blood samples collected from captive individuals and
wild animals captured for ecological studies (DNA preserved in a salt-saturated
solution; 100 mM Tris, 100 mM EDTA, 2% SDS), and muscle or skin tissue
collected from road-killed individuals. Ten tetranucleotide microsatellites loci
originally described by Francisco et al. (1996) for the domestic dog (Canis
familiaris), and subsequently selected for optimized applicability in Neotropical
canids (Rodrigues et al. in preparation), were employed in this study: 2100, 2006,
2054, 2004, 2001, 2010, 2132, 2137, 2140, 2088. Each primer pairs were linked to
93
a standardized M13 fluorescent-labeled tail added to its 5’ end (Boutin-Ganache et
al. 2001) and used in a flexible three-primer PCR reaction.
Polymerase chain reactions were performed in mixtures containing 2 µl of
10X buffer, 1.5 mM MgCl
2
, 0.2 µM dNTPs, 0.2 µM each of the reverse primer and
the fluorescent M13 primer, 0.013 µM of the forward primer, 0.75 unit Taq
polymerase and 1-3 µl of template DNA. Thermocycling conditions began with 10
“touchdown” cycles, which each had a 30s denaturing step at 94ºC, 30s annealing
at 60-51ºC, and 45s extension at 72 ºC. This was followed by 30 cycles of 30s
denaturing at 94 ºC, 30s annealing at 50ºC and 45s extension at 72ºC.
The genotyping of the PCR products was performed in a MegaBACE 1000
(GE Healthcare) automatic sequencer, using the GENETIC PROFILER 1.5
software (GE Healthcare) and an internal size standard (ET Rox-400, GE
Healthcare). Initial verification of possible genotype errors during data recording
was performed with MICROCHECKER 2.2.3 (Oosterhout et al. 2004).
FSTAT 2.9.3.2 (Goudet 2002) was used to test the occurrence of linkage
disequilibrium (153,000 permutations), and also to calculate allele frequencies,
gene diversity (the probability that two randomly chosen alleles are different in the
sample; Nei 1987), number of sampled alleles in each site, and observed
heterozygosity values. A Hardy-Weinberg Equilibrium (HWE) exact test
implemented by the Markov chain method was performed with GENEPOP web
version 3.1c (Raymond and Rousset 1995).
To investigate the population structure across the sampled region, we used
STRUCTURE 2.1 (Pritchard et al. 2000), a Bayesian model-based approach. The
analyses were implemented in the population admixture model without prior
geographic information. Probabilities of 1 to 5 and 17 clusters (K, i.e. groups of
individuals that probably belong to the same population) were tested in two
different sets of analyses: (i) a data set with equivalent number of individuals for all
sites (i.e. using only 6 individuals for RS, PR and MS, and all sampled individuals
for the other sites); and (ii) using all 82 individuals obtained in this study. Each run
was replicated 10 times, with 100,000 steps of sampling following 100,000
generations of burn-in. A third set of analyses was performed focusing only in the
RS, PR and MS sample-sites (using all sampled individuals from these locales;
n=16, n=19 and n=17, respectively). In this case, we tested the fit of the data to
94
models with 1 to 5 different clusters; for these runs the MCMC replicates after
burn-in were modified to 150,000.
An analysis of molecular variance (AMOVA, Excoffier et al. 1992) and
estimates of population subdivision through F
ST
indices (conventional F
ST
statistics) were obtained with ARLEQUIN 2.000 (Schneider et al. 2000) and the
statistical significance of these values was tested using 10,000 permutations in the
same software.
RESULTS
All loci were polymorphic, with allele counts ranging from 4 to 24, average
observed heterozygosity of 0.645, and high gene diversity, with a mean of 0.757
for all loci (Tables 2 and 3). Three of ten microsatellite loci, 2132, 2137 and 2140,
exhibited a dinucleotide repeat pattern; all others behaved as tetranucleotide loci,
as originally described in C. familiaris. Allele frequencies and allele distribution by
sample site are shown in Figs. 2a-j.
After applying a sequential Bonferroni correction (Rice 1989), no linkage
disequilibrium was observed between loci (global and intra-sample analysis;
corrected α = 0.000065). Under this same correction (α = 0.005), a heterozygote
deficit was detected in PR and MS sample sites, based on the Hardy-Weinberg
test conducted for each sample using all loci (p < 0.00001). Testing for HWE in
each single locus in these two sample sites, we detected a heterozygote deficit
only for locus 2137 (p< 0.00001), which also showed departure from HWE in the
global analysis of sample sites (p<0.00001). Exclusion of locus 2137 from the PR
and MS populations, however, maintained the heterozygote deficit (p=0.0008 and
p=0.004 respectively). Comparative subsequent analyses of the population
structure without locus 2137 were conducted, and it was eventually kept in the
data set because its exclusion did not affect the results.
The Bayesian approach implemented in STRUCTURE using equivalent
samples for all sites indicated as most probable the existence of a single
population cluster (Ln Prob -1490 to -1505 on 10 runs), suggesting that there is no
genetic structure among all 17 sample sites (in this analysis, the MS, PR and RS
sites were each represented by 6 individuals, similar to the sample size from the
95
other locales; see Materials and Methods). This same analysis, when performed
using all 82 individuals, resulted in the highest probability values for K=2 and K=3
(Ln Prob – 2575 to – 2591 and Ln Prob – 2542 to – 2590, respectively), indicating
that RS is a differentiated cluster for both K=2 and K=3. In the latter case, the
other two clusters did not correspond to identifiable geographic locations. The
search using only MS, PR and RS (all sampled individuals from these sites; see
Materials and Methods) resulted in very similar probabilities for K=2 and 3 (with
the upper and lower limits of Ln estimation overlapping; from Ln -1582 to Ln -
1629). The K=2 analysis indicated that PR and MS are a single cluster, with only
one individual in RS being inferred to be a migrant from this region. The K=3
exercise correctly assigned all RS individuals to this population, and suggested
some level of structuring between PR and MS, although several individuals were
inferred to be admixed between these two areas.
The estimated fixation index produced concordant results and confirmed the
STRUCTURE inference. When we analyzed all 17 sample sites as different
populations (all 82 individuals), low values of F
ST
=0.00041 (from AMOVA) among
units were obtained. In the pairwise comparisons of sample sites, genetic
differentiation was observed only between RS and the other 16 sites, with F
ST
=
0.001 (for all RS pairs) significant for almost all the site pairs (p<0.05), including
PR but not MS. This value of RS differentiation was lost (F
ST
=0) when we used an
equivalent number of individuals for RS, PR, MS and the other sites. Considering
only these three major samples, RS, PR and MS, the calculated index among
populations was F
ST
= 0.0005 (p=0.08; AMOVA).
Alternative population schemes were also tested, grouping samples by
ecoregions (major vegetation domains, the southern Atlantic Forest region
including marginal portions of adjacent biomes of Chaco and southern
grasslands), northeastern X southern group detected with mtDNA data (Tchaicka
et al. in press [ver Capítulo III]), with and without the Eastern Amazonia sample
(PA; which shows the highest genetic diversity, Tchaicka et al. in press). For all
these analyses, the estimated F
ST
values were zero.
In the AMOVA analysis, 99.96% of the genetic variation was found to be
within each local samples; comparing only RS, PR and MS, 99.94% of variation
was found within local samples. Values of the F
IS
index were high only for the BA
96
sample site (0.455), and low to negative for the other sample sites, as listed in
Table 4.
DISCUSSION
The microsatellite loci used here were found to be highly polymorphic
(average gene diversity of 0.757) in C. thous, and are thus informative markers for
populational studies in this species. Observed levels of variability, such as 4-24
alleles per locus and average heterozygosity of 0.64 across loci, are comparable
to those obtained for coyotes and American wolves by Roy et al. (1994), who
reported 4-20 alleles per locus and average heterozygosis of 0.65 for both species
(using different loci). These diversity levels are likely influenced by high mutation
rates at these loci, as well as characteristics of the species’ life history and
evolutionary past, including large effective population sizes that directly affect
genetic variability. Species with large effective population sizes, such as wolves,
coyotes and probably Cerdocyon, are less influenced by genetic drift and maintain
high diversity (Amos e Balmford 2001).
Genetic indications of effective population sizes can be compared to data
from field population censuses. For Cerdocyon, no precise nd
97
these regions. Data from the microsatellite loci indicated no considerable
differences in diversity between these regions (mean gene diversity estimates of
0.64 and 0.70 for the northern and southern groups, respectively) or between
sample-sites (Table 4).
A striking aspect observed in this previous study was that the mitochondrial
DNA data revealed a strong geographic partition between northeastern Brazil and
other parts of the species’ distribution. F
ST
values estimated between these areas
were > 0.68, and the phylogenetic analysis defined two monophyletic lineages
occurring in a mostly non-overlapping phylogeographic fashion.
Despite the occurrence of exclusive alleles within the northern and southern
regions (Figs. 2a-j) microsatellite data failed to support such a subdivision. The
Bayesian approach implemented in STRUCTURE, as well as the F
ST
–based
inferences did not indicate the existence of geographical partitions, old population
subdivision events, or barriers to gene flow across the species’ range.
Comparing characteristics of mtDNA and intron sequences, discordant
results can be attributed to slow accumulation of mutations and larger effective
size of introns that delay the effect of genetic drift (Hare 2001). Microsatellite loci,
however, show high mutation rates, which can promote more rapid differentiation
between populations. Since mitochondrial markers have certain limitations
because of their matrilineal inheritance (Avise 2000), the microsatellite - mtDNA
discrepancy could be explained by the hypothesis that, in Cerdocyon, males
disperse more often and/or farther than females.
No specific field study addressing this question has been performed so far,
but available data (Macdonald and Courtenay 1996) reports dispersal of four
juvenile males and one adult female. These juvenile males formed pairs with
similar-aged females, who the authors suggest are also probably dispersers.
Our present data supports the view that males disperse more than females,
which should now be tested in more detailed field studies addressing this issue.
To evaluate the effect of sampling on inferences of regional-level genetic
structuring in C. thous, we selected three of our sites (PR, RS and MS - see Fig. 1
and Methods) to perform a more detailed assessment. These areas are thought to
have been connected via continuous Atlantic Forest cover in the recent past,
perhaps up to the end of the XXth Century. The PR sample site is in a central
98
position relative to the other two locales: it is ca. 650 km away from RS, and ca.
450 Km away from MS (see Fig. 1). The PR and RS are part of a formerly
continuous Atlantic Forest biome spanning most of Southern Brazil, while the MS
site lay on the western edge of this ecoregion, at the interface with more open
habitats, but still fully connected to the other two locations in terms of suitable
habitats for C. thous. Presently, the three sites are nearly completely separated by
heavily impacted areas (e.g. urban environments, soy beans plantations and other
agricultural areas), although the effects of such anthropogenic disturbances on C.
thous demography have not yet been assessed. C. thous seems to adapt
reasonably well to disturbed habitats, and may therefore remain continuously
distributed across these regions. This has not been tested directly throughout the
landscapes separating our sample sites. The MS site currently consists of patches
of Atlantic Forest native vegetation interspersed with agricultural areas dominated
by cattle ranching. The RS and PR sites are conservation units where the native
Atlantic Forest biome still remains rather well preserved: RS is 5,000-ha Itapuã
State Park; and PR is 185,000-ha Iguaçu National Park, which is adjacent to a
large tract of additional conserved areas in Argentina.
Only a small degree of genetic structuring between RS and the other two
sites was inferred from the F
ST
pairwise analysis of these three sites, as also
observed in the analyses including all other sites (Fst=0.001). STRUCTURE
analysis failed to detect this partition in the global analysis, but clearly indicates
this pattern on MS/PR/RS search (see results). The genetic similarities between
MS and PR are probably due to the more recent fragmentation by agricultural
development between these sites than between PR and RS.
Some species for which initial, large-scale, studies indicated no structure,
when observed in detailed molecular investigations, with larger sample sizes, have
shown some degree of genetic differentiation among sites, as observed in
American wolves and coyotes (Geffen et al. 2004; Sacks et al. 2004; Vilà et al.
1999).
The departures from Hardy-Weinberg equilibrium inferred for PR and MS
could be caused by the hypothesis of null alleles presence (inferred from
heterozigosity deficits, see Results and Table 2) on 2137 locus. However, the
deviations were maintained when this locus was excluded from the analysis.
99
Adding the observation of higher F
IS
estimated from PR and RS than from RS
(negative F
IS
), we could explain this by either limited inbreeding within populations,
or by a nonrandom sample of individuals within populations, which may be
composed of family groups in PR and MS (Walhund Effect, Hartl e Clark 1997).
Intra-specific comparisons using molecular data for canid species have
demonstrated how differences in dispersal ability, ecological constraints, historical
demography and the nature extrinsic of barriers influence the degree of genetic
structure within this group. The inferences from microsatellite data presented
herein contribute to knowledge of the life history of Cerdocyon thous, and provide
a basis for more detailed population-level studies in this species.
LITERATURE CITED
Amos, W. and A. Balmford. 2001. When does conservation genetics matter?
Heredity 87:257-265.
Avise, J.C. 2000. Phylogeography - The History and Formation of Species.
Harvard University Press, London, England.
Berta, A. 1982. Cerdocyon thous. Mammalian Species 186: 1-4.
Berta, A. 1987. Origin, diversification and zoogeography of the South American
Canidae. Fieldiana Zoology 39: 455-471.
Boutin-Ganache, I., M. Raposo, M. Raymond, C.F. Deschepper. 2001. M13-Tailed
Primers Improve the Readability and Usability of Microsatellite Analyses
Performed with Two Different Allele-Sizing Methods. BioTechniques 31: 25-28.
Courtenay, O., and L. Maffei. 2004. Cerdocyon thous (Linnaeus, 1766). Pp 30-32
in Canid Action Plan (eds Hoffmann M, Sillero-Zubiri C). IUCN Publications,
Gland, Switzerland.
100
Excoffier, L., P. Smouse, J. Quattro. 1992. Analysis of Molecular Variance inferred
from metric distances among DNA haplotypes: Application to human mitochondrial
DNA restriction data. Genetics 131: 479-491.
Francisco, L.V., A.A. Langston, C.S. Mellersh, C.L. Neal, E.A. Ostrander. 1996. A
class of highly polymorphic tetranucleotide repeats for canine genetic mapping.
Mammalian Genome 7: 359–362.
Geffen, E., M.J. Anderson, R.K. Wayne. 2004. Climate and Habitat Barriers to
dispersal in the highly mobile gray wolf. Molecular Ecology 13:2481-2490.
Goudet, J. 2002. Fstat. version 2.9.3.2. Institute of Ecology, Biology Building,
Lausanne, Switzerland.
Hare, M.P. 2001. Prospects for nuclear gene phylogeography. Trends in Ecology
and Evolution 16: 700–706
Hartl, D.L., and J. Clark. 1997. Principles of Populations Genetics, 3º ed. Sinauer
Associates, Sunderland, MA, 448p.
Juarez, K.M., J. Marinho-Filho. 2002. Diet, habitat use, and home ranges of
sympatric canids in Central Brazil. Journal of Mammalogy 83: 925-933.
Langguth, A. 1975. Ecology and Evolution in the South American
Canids. Pp.192-206 in The Wild Canids (ed Fox MW). Litton
Educational Publishing, New York.
Lehman, N., and R.K., Wayne. 1991. Analysis of coyote mitochondrial DNA
genotype frequencies: estimation of the effective number of alelles. Genetics 128:
405-416.
101
MacDonald, D.W., and O. Courtenay. 1996. Enduring social relationships in a
population of crab-eating zorros, Cerdocyon thous, in Amazonian Brazil
(Carnivora, Canidae). Journal of Zoological Society of London 239:329-355.
Medel, R.G., and F.M. Jaksic. 1988. Ecología de los Cánidos Sudamericanos: una
revisión. Revista Chilena de Historia Natural 61: 67-79
Mercure, A., K. Ralls, K.P. Koepfli, R.K. Wayne. 1993. Genetic subdivisions
among small canids: mitochondrial DNA differentiation of Swift, Kit and Artic fox.
Evolution 47: 1313-1328.
Nei, M. 1987. Molecular Evolutionary Genetics. Columbia University Press,New
York, 278pp.
Oosterhout, C.V., W.F. Hutchinson, D.P.M. Wills, P. Shipley. 2004. Micro-checker:
software for identifying and correcting genotyping erros in microsatellite data.
Molecular Ecology Notes 4:535.
Pritchard, J.K., M. Stephens, P. Donnely. 2000. Inference of a Population
Structure Using Multilocus Genotype Data. Genetics 12: 945-959.
Raymond, M., and F. Rousset. 1995. GENEPOP (version 1.2): population genetics
software for exact test ecumenism. Journal of Heredity 86: 248-249.
Rice, W.R. 1989. Analysing Tables and of statistical tests. Evolution 43: 223 -
225.
Roy, S.M., E. Geffen, D. Smith, E.A. Ostrander, R.K. Wayne. 1994. Patterns of
differentiation and hybridization in north americam wolflike canids, revelead by
analysis of microsatellite loci. Molecular Biology and Evolution, 11: 553-574.
Sacks, N.B., S. Brown, H.B. Hernest. 2004. Population structure of California
coyotes corresponds to habitat-specific breaks and illuminates species history.
Molecular Ecology 13:1265-1275
102
Sambrook, J., E.F. Fritsch, T. Maniatis. 1989. Molecular Cloning: a Laboratory
Manual 2nd edn. Cold Spring Harbor Laboratory Press, New York.
Schneider, S., D. Roessli, L. Excoffier. 2000. ARLEQUIN (A software for
population genetics data analysis). version 2.000. Genetics and Biometry
Laboratory, University of Geneva Switzerland, Geneva, Switzerland.
Sunquist, M. E., F. Sunquist, D. E. Daneke. 1989. Ecology Separation in a
Venezoela LLanos Carnivores Community. Pp.614-617 in Advances in
Neotropical Mammalogy (K. H. E. Redford, and J.F., Eisenberg eds). The Sandhill
Crane Press, Gainesville, Florida.
Tchaicka, L., E. Eizirik, T.G. Oliveira, J.F. Cândido Jr, T.R.O. Freitas. In press.
Phylogeography and population history of the crab-eating fox (Cerdocyon thous).
Molecular Ecology.
Vilà, C., I.R. Amorim, J.A. Leonard, D. Posada, J. Castroviejo, F. Petrucci-
Fonseca, K.A. Crandall, H. Ellegren, R.K. Wayne. 1999. Mitochondrial DNA
phylogeography and population history of the grey wolf Canis lupus. Molecular
Ecology, 8: 2089-2183.
Wayne, R.K. 1996. Conservation Genetics in the Canidae. Pp. 75-113 in
Conservation Genetics (J.C., Avise, and J.L., Hamrick eds), Chapman & Hall, New
York.
103
Fig. 1. — Map showing the current geographic distribution of Cerdocyon thous
(modified from Sillero-Zubiri et al. 2004) and approximate sample collection sites,
as coded in Table1, with sample sizes between parentheses.
Fig. 2. — Allele frequency distribution for each microsatellite locus analyzed in this
study (a-j), for each of the 17 sampling sites (blue area comprises the three
locales with larger sample sizes [RS, PR and MS]), and total frequency of alleles
for each locus for the complete data set (“all” - green area on the right).
a) Locus 2100; b) Locus 2006; c) Locus 2054; d) Locus 2004; e) Locus 2001; f)
Locus 2010; g) Locus 2132; h) Locus 2088; i) Locus 2137; j) Locus 2140.
104
RS2 (3)
RS (16)
PR (19)
SC (3)
PY (1)
SP (3)
RJ (1)
MS (17)
MG (2)
GO (3)
MT (2)
BA (2)
PE (2)
PB (1)
CE (3)
PA (3)
PI (1)
105
a)
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
RS PR MS RS2 SC PY RJ GO MG SP MT PA PI PE BA CE PB ALL
SAMPLE SITES
frequenciesses
Allele 1
Allele 2
Allele3
Allele 4
Allele 5
Allele 6
b)
0
0,2
0,4
0,6
0,8
1
1,2
RS PR MS RS2 SC PY RJ GO MG SP MT PA PI PE BA CE PB ALL
SAMPLE SITES
frequenciesses
Allele 1
Allele 2
Allele3
Allele 4
106
c)
0
0,2
0,4
0,6
0,8
1
1,2
RS PR MS RS2 SC PY RJ GO MG SP MT PA PI PE BA CE PB ALL
SAMPLE SITES
frequencies es
Allele 1
Allele 2
Allele 3
Allele 4
Allele 5
Allele 6
Allele 7
.
0
0,2
0,4
0,6
0,8
1
1,2
RS PR MS RS2 SC PY RJ GO MG SP MT PA PI PE BA CE PB ALL
SAMPLE SITES
frequencies es
Allele 1
Allele 2
Allele 3
Allele 4
Allele 5
Allele 7
Allele 8
d)
107
0
0,2
0,4
0,6
0,8
1
1,2
RS PR MS RS2 SC PY RJ GO MG SP MT PA PI PE BA CE PB ALL
SAMPLE SITES
frequencies ess
Allele 1
Allele 2
Allele 3
Allele 4
.
0
0,2
0,4
0,6
0,8
1
1,2
R43.1928(S)-1399.64(P12.47952(R)-163.83(M)9.572228(S)-4802132(R)-1.97436(S)2.47952(2)-1496196(S)2.47952(C)-176964(P12.47952(Y)-184551[(R43.1928(J)-171.923(G)93.01057(O)-1434.4(M)9.572228(G)-1650606(S12.47952(P)-178.83(M)-141.4132(T)-172.64(P12.47952(A)-1939.31(P)2.47952(I)-191.515(P)2.47952(E)-380.28(BP12.47952(A)-1761606CR43.1928ES)-1399.64(P-8.63406(B)-1561642(A12.47952L1)7.06436(L)550.986]TJ/R11 5.60112 Tf9313741 -9.6 Td[(S12.47952(A416.163(M)-72.65485(P)2.47952Lf)-1293382EP)2.47952 G)-17.877[(S12.47952I,)3.55196(T)22.40742EP)2.47952(S)666.999]TJ0 1.01472 -1 0 254.52256148 Tm[(f)46.8446(r)8.95188(e)280.1(qf)-1293382uf)-1293382e1)7.06436n)196.8927(c)7.06436i,)3.55196e1
108
0
0,2
0,4
0,6
0,8
1
1,2
RS PR MS RS2 SC PY RJ GO MG SP MT PA PI PE BA CE PB ALL
SAMPLE SITES
frequencies es
Allele 1
Allele 2
Allele 3
Allele 4
Allele 5
Allele 6
Allele 7
.
0
0,2
0,4
0,6
0,8
1
1,2
RS PR MS RS2 SC PY RJ GO MG SP MT PA PI PE BA CE PB ALL
SAMPLE SITES
frequencies es
Allele 1
Allele 2
Allele 3
Allele 4
Allele 5
Allele 6
g
)
h
)
i
)
j)
Table 1. — Samples analyzed in the present study.
ECOREGION GEOGRAPHIC ORIGIN (SAMPLE SITE) SAMPLES INSTITUTION/CONTACT
P.N. Iguaçu, Paraná State, S Brazil (PR)
bCth8, bCth9, bCth59, bCth60,bCth61,
bCth62 bCth63, bCth64, bCth65, bCth67,
bCth68, bCth69, bCth70, bCth71, bCth72,
bCth74, bCTh75, bCth76, bCth77
UNIOESTE/José Flávio
Cândido Jr. and Instituto Pro-
Carnivoros
Mato do Grosso do Sul State, SW Brazil (MS)
bCth164, bCth165, bCth166, bCth172,
bCth173,bCth174,bCth175,
bCth11,bCth232, bCth233, bCth234,
bCth235, bCth236, bCth239, bCth240,
bCth243, bCth244
Instituto Pró-Carnívoros/ Denis
Sana
Paraguay (PY1) bCth91, Guillermo D`Elia
Santa Catarina State, S Brazil (SC1) bCth154, bCth178, bCth210 Ligia Tchaicka
Rio de Janeiro State, E Brazil (RJ) bCth214 Zoológico de Pomerode
São Paulo State, E Brazil (SP2) bCth301, bCth305, bCth219 Cristiana Prada
Rio Grande do Sul State, S Brazil (RS)
bCth80, bCth81, bCth82, bCth83, bCth84,
bCth85, bCth99, bCth100, bCth134,
bCth135, bCth136, bCth142, bCth143,
bCth144, bCth145, bCth146
Mariana Faria-Corrêa and
Instituto Pro-Carnivoros
Southern
Atlantic Forest
Rio Grande do Sul State, S Brazil (RS2) bCth15, bCth39, bCth112 Alex Bager
Minas Gerais State, E Brazil (MG1) bCth200, bCth336 Instituto Pro-Carnivoros Cerrado
Goiás State, Central Brazil (GO1) bCth205, bCth208, bCth209
Zoológico de Goiânia/ Roberto
Portela; Instituto Pro-Carnivoros
PN Serra da Capivara, Piaui State, NE Brazil
(PI)
bCth201
FUNDHAM/ Vanderson C.Vaz
and Paulo César D´Andrea
Caatinga
Ceará State, NE Brazil (CE) bCth192,bCth194, bCth197
Zoológico de Fortaleza/ Luiz C.
Diniz
Table 1. — Continued.
Eastern
Amazônia
Pará and Maranhão State, N Brazil (PA) bCth221, bCth223, bCth228 Tadeu de Oliveira
Pantanal Mato Grosso State, SW Brazil (MT2) bCth51, bCth56 Rodrigo Jorge e Julio Dalponte
Northern
Atlantic
Paraíba State, NE Brazil (PB) bCth309
Flavio Rodrigues
Forest Bahia State, NE Brazil (BA) bCth186, bCth187 Zoológico de Salvador/Cláudio
V. Lyra
Pernambuco State, NE Brazil (PE) bCth184, bCth185
Zoológico do Recife/ Poly- Ana
Celina
Table. 2. — Characteristics of ten microsatellite loci amplified from C. thous.
*Original locus identification by Francisco et al. (1996).
** Nei’s estimation of Heterozygosity (Ho = observed values, Hs = expected values)
Indicate departure from HWE (α <0.005) for loci 2137.
Identification*
Number of
Alleles
Allele Size
Range
Ho** Hs**
2100 6 176-196pb 0.774 0.784
2006 4 226-238pb 0.404 0.672
2054 9 158-194pb 0.824 0.817
2004 7 251-175pb 0.637 0.685
2001 4 145-161pb 0.443 0.443
2010 6 231-151pb 0.695 0.697
2132 11 156-196pb 0.683 0.726
2137 23 173-245pb 0.533 0.833
2140 24 121-171pb 0.850 0.840
2088 6 109-129pb 0.610 0.652
Table. 3. — Gene diversity (Nei 1987) from microsatellite data in Cerdocyon thous (site names are coded as Fig. 1).
* Locus identification follows the original locus description (Francisco et al. 1996);
n.a. samples not analyzed
Locus * Sample sites
PR RS MS PA MT RS2 SC PE BA CE GO MG SP ALL
2100 0.787 0.769 0.827 0.750 0.750 0.667 0.917 0.500 0.500 0.833 0.667 0.750 0.833 0.816
2006 0.674 0.721 0.721 1.000 0.500 n.a 0.917 0.500 1.000 1.000 0.667 0.000 0.833 0.690
2054 0.789 0.642 0.838 1.000 0.750 0.750 0.917 0.750 n.a 0.917 0.750 0.750 1.000 0.810
2004 0.773 0.644 0.804 0.500 0.750 0.667 0.917 0.000 1.000 0.500 0.833 0.500 0.917 0.764
2001 0.287 0.517 0.398 0.500 0.500 0.667 0.500 0.500 0.500 0.500 0.333 0.500 0.500 0.440
2010 0.545 0.621 0.746 0.667 1.000 0.500 0.750 1.000 0.500 0.500 0.500 1.000 0.917 0.677
2132 0.827 0.788 0.752 0.833 0.000 0.917 0.833 n.a 1.000 0.833 0.500 0.500 1.000 0.830
2137 0.896 0.752 0.942 0.750 1.000 0.917 1.000 1.000 1.000 0.833 0.833 1.000 0.000 0.930
2140 0.913 0.763 0.788 0.500 n.a 0.917 0.750 1.000 n.a 1.000 1.000 0.750 0.917 0.917
2088 0.742 0.588 0.667 n.a n.a 0.667 0.750 0.500 0.000 1.000 0.667 n.a 0.500 0.722
Table. 4.— Population comparison of diversity measures: total number of alleles, gene diversity (Nei, 1987) and F
is
(heterozygote deficit) across all ten microsatellites loci studied for C. thous (the top line samples sites are coded as Fig. 1)
n.a.samples not analyzed
Capítulo V
3
O
ARTIGO
a ser submetido para publicação na revista Journal of Heredity
Molecular phylogeny of a recently diversified endemic group of South
American canids (Mammalia: Carnivora: Canidae)
119
Molecular phylogeny of a recently diversified endemic group of South American canids
(Mammalia: Carnivora: Canidae)
LIGIA TCHAICKA
1
, THALES R. O. FREITAS
1
, ALEX BAGER
2
, WARREN E. JOHNSON
3
,
ROBERT K. WAYNE
4
, EDUARDO EIZIRIK
3,5,6
1
Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande
do Sul, Porto Alegre, RS, Brazil
2
Universidade Católica de Pelotas, Pelotas, RS
3
Laboratory of Genomic Diversity, NCI, NIH, USA.
4
Department of Ecology and Evolutionary Biology, University of California, Los Angeles,
90095, USA.
5
Centro de Biologia Genômica e Molecular, Pontifícia Universidade Católica do Rio Grande
do Sul, Porto Alegre, RS, Brazil
6
Instituto Pró-Carnívoros, Brazil.
Corresponding author:
Running title:
Keywords: Mitochondrial DNA control region – phylogeny – Canidae - Carnivora
120
ABSTRACT
In order to understand the phylogeny and phylogeography of an endemic group of South
American canids, we examined 588pb of the mitochondrial DNA control region from a total of
142 individuals from six species of the genus Lycalopex. Phylogenetic analyses indicated
monophyly of the genus, with L. vetulus as the most basal species (time of divergence from
other Lycalopex ca. 1,000,000 years), a recent origin of the other species (ca. 500,000 years)
and a very close relationship between L. griseus and L. culpaeus (having diverged ca.
350,000 years ago). Intra-specific analysis indicated that most of these species experienced
population expansions, and that L. gymnocercus and L. fulvipes show indications of
genetically differentiated geographic groups. The history of these events and their
biogeographic and taxonomic implications are discussed.
121
INTRODUCTION
The first representatives of the family Canidae entered South America in the late
Pliocene and early Pleistocene, coming from North America through the Panama Isthmus
(formed approximately 3 million years ago [MYA]) and then radiated to achieve their present
diversity (Berta 1987). Currently there are ten canid species endemic to South America, which
is the most diverse continent with respect to this family. This diversity is at least in part due to
a generalist and opportunistic feeding strategy that utilizes small prey as well as fruits and
grains, and the potential to inhabit all types of habitats in the continent (Berta 1987, Ginsberg
and Macdonald 1990, Wozencraft 2005).
Morphological and molecular evidence generally agree that living South American
foxes belong to a monophyletic group (Cerdocyon, Lycalopex, Atelocynus and Dusicyon; e.g
Wayne et al. [1997]; Zrzavy and Ricankova [2004]). These species have similar karyotypes,
suggesting recent divergence (2n=74; NF=76 - L. gymnocercus, P griseus, L. culpaeus, L.
sechurae, A. microtis, P gymnocercus and L. vetulus; 2n= 74; NF=110 - Cerdocyon thous
[Brum-Zorrila and Langguth 1980; Wayne et al. 1987; Wayne 1993]). Although several
previous studies have addressed the evolutionary relationships among these foxes (using
morphological and/or molecular data; e.g. Bardeleben et al. 2005, Lindblad-Toh et al., 2006,
Lyras and Van-Gelder 2003, Wayne et al. 1997, Zrzavy e Ricancova 2004), their relationships
are still incompletely understood, especially with respect to the species usually included in the
genera Pseudalopex and/or Lycalopex. These canids will be treated here as Lycalopex
vetulus (Hoary fox), L. gymnocercus (Pampas fox), L. culpaeus (Culpeo fox), L. fulvipes
(Darwin’s fox), L. griseus (Chilla fox) and L. sechurae (Sechuran fox), following Wozencraft
(2005).
122
These foxes exhibit variable body sizes, with L. culpaeus weighing up to 11Kg and L.
gymnocercus 4 to 6.5 kg, while the other species are smaller, with mean weights of ca. 3.5Kg
(Sillero-Zubiri et al. 2004). Patterns of coloration and morphology are so similar between
some of these species, and in some cases between them and the related crab-eating fox
(Cerdocyon thous), that it is often difficult to arrive at precise species identification based on
visual criteria alone (L. Tchaicka and E. Eizirik, personal observation). This is especially
problematic with respect to pelage colors, which can exhibit great geographic and/or seasonal
variation, leading to potential confusion among species.
The precise geographic range of these species is still not known in full detail, but some
major distributional patterns are clearly documented (Fig. 1). L. culpaeus is distributed along
the Andes and hilly regions of western South America, from Southern Colombia to Tierra del
Fuego. L. fulvipes is endemic to costal Chile. L. griseus is widespread in areas of plains and
mountains on both sides of the Andes, from Northern Chile south to Tierra del Fuego. L.
gymnocercus ranges from eastern Bolivia and western Paraguay to Northern provinces of
Argentina and to the Atlantic coast in Southern Brazil. L. sechurae occurs in habitats near the
Pacific coast of Peru. Finally, L. vetulus is endemic to the Cerrado biome in Central Brazil
(Sillero-Zubiri and Macdonald, 2004).
Several taxonomic schemes for these species have been suggested in the past based
on different methods. Langguth (1975), based on ecological and morphological data,
suggested two taxa for this group: the Lycalopex genus and Pseudalopex as a subgenus of
Canis. The former contained only Lycalopex vetulus, the type species for this genus, while the
latter contained Canis (Pseudalopex) culpaeus, C. (P.) gymnocercus, C. (P.) griseus and C.
(P.) sechurae. Subsequently, Clutton-Brock et al. (1976), using morphological and behavioral
data, included all these species in the genus Dusicyon, originally proposed for the now extinct
123
Falkland Island “wolf”, D. australis (Wozencraft 2005). Berta (1987), based on the fossil
record and cladistic analyses of morphological data, proposed that the genus Pseudalopex
should include P. griseus, P. gymnocercus, P. culpaeus, P. vetulus, P. sechurae and the
extinct species P. peruanus. More recently, Zunino et al. (1995) grouped P. gymnocercus and
P. griseus into a single species, Lycalopex gymnocercus, supporting the use of Lycalopex as
the generic name for L. culpaeus, L. vetulus and L. sechurae (L. fulvipes was also considered
to be a synonym of L. gymnocercus in this study).
L. fulvipes was first considered to be a subspecies of L. griseus, and thought to be
endemic of Chiloe Island, in Chile (Nowak 1999, Redford and Eisenberg 1992, Wilson and
Reeder 1993). Recently, a mainland population of L. fulvipes has been discovered, and
molecular genetic analyses indicated that this fox is a distinct species that probably had a
much broader distribution in the past (Yahnke et al. 1996).
Additional classifications of this group have been suggested by Thomas (1914);
Kraglievich (1930); Cabrera (1931); Osgood (1934); Hough (1948); Thenius (1954); Van
Gelder (1978), but classification remains unclear due to remaining uncertainties in the
phylogenetic relationships among these taxa.
Recent intra-specific studies on Neotropical canids have concentrated mostly on
ecological aspects such as diet and habitat use (e.g. Crespo 1971, Dotto 1997, Courtenay et
al. 2006, Jaksic et al. 1998, Pia et al. 2003), and few papers have used molecular data to
investigate these species (e.g. Vilà et al. 2004 [addressing species distribution]; Farrell et al.
2000 [addressing dietary separation among species]) A comparative phylogeographic
approach can permit interesting studies of evolution, including patterns of speciation and the
underlying processes, as well as the effects of habitat use and dispersal capabilities on the
genetic structure of related taxa. These investigations may shed light on the links between
124
population processes and regional patterns of diversity and biogeography (Bermingham and
Moritz 1998).
Mitochondrial segments are useful in evolutionary studies of recent divergence
processes in animals due to their relatively high substitution rate, maternal inheritance, and
absence of recombination (Schlotterer 2004). In spite of limitations derived from these same
features, mtDNA segments remain an important source of information in the case of
phylogenetic studies of closely related species or intra-specific phylogeography, since these
rapidly evolving sequences (with lower effective population size) are often quite informative in
attempts to capture recent episodes of population divergence.
In this study we have used mitochondrial DNA (mtDNA) control region sequences to
investigate the evolutionary history of an endemic clade of South American foxes. These
closely related species, whose classification has remained controversial for decades, pose an
interesting challenge to phylogenetic reconstruction, due to their rapid and recent divergence,
and unclear classification at specific and generic levels.
MATERIALS AND METHODS
Biological material was collected from a total of 142 Neotropical canids, including
Lycalopex culpaeus (n=53), L. gymnocercus (n=24), L. vetulus (n=26), L. fulvipes (n=6) and
L. griseus (n=32; nine individuals had been initially identified as L. gymnocercus; see Fig. 1
and Discussion). In addition, nine Cerdocyon thous individuals were included as an outgroup
(two of them were previously sequenced by Tchaicka et al. [in press]; Capítulo III).
Blood samples (preserved in a saturated salt solution: 100mM Tris, 100mM EDTA, 2%
SDS) were collected from captive individuals of known origin, as well as wild animals
captured for field ecology studies. Tissue samples were obtained from road-killed individuals
125
and preserved in 95% ethanol. Genomic DNA was extracted from samples using a standard
phenol/chloroform protocol (Sambrook et al. 1989).
The 5’ portion of the mtDNA control region, containing the first hypervariable segment
(HVS-I), was amplified by the Polymerase Chain Reaction (PCR; Saiki et al. 1985) using
specific primers MTLPRO2 (5’-CACTATCAGCACCCAAAGCTG) and CCR-DR1, (5’-
CTGTGACCATTGACTGAATAGC) (or H16498 [Ward et al. 1991] as an alternative reverse
primer). PCR reactions contained 2µl 10X buffer, 1.5 mM MgCl
2
, 0.2 µM dNTPs, 0.2 µM each
primer, 0.75 unit Taq polymerase and 1-3 µl of empirically-diluted template DNA.
Thermocycling conditions included 10 initial cycles of “touchdown”, with 45’’ denaturing at
94ºC, 45’’ annealing at 60-51ºC, and 1’30’’ extension at 72 ºC. This was followed by 30 cycles
of 45’’ denaturing at 94 ºC, 30’’ annealing at 50ºC and 1’30’’ extension at 72ºC. Products were
examined on a 1% agarose gel stained with ethidium bromide, purified using shrimp alkaline
phosphatase and exonuclease I and sequenced with ABI chemistry and analyzed with an
ABI-PRISM 3100 automated sequencer. Sequences generated for this study have been
deposited in GenBank (accession numbers XXXXX-XXXXX). In addition, one previously
published partial sequence of the mtDNA control region of Lycalopex sechurae (Yahnke et al.
1996) was included in the analyses.
Sequences were verified and corrected by eye using Chromas (available from www.
tchnelysium.com.au) or Sequencher (Gene Codes Inc.), aligned using the ClustalW algorithm
implemented in MEGA 3.0 (Kumar et al. 2004) and visually checked. Sites or segments that
could not be unambiguously aligned were excluded from all analyses. Initial sequence
comparisons and measures of variability, such as the number of variable sites and nucleotide
diversity (π per nucleotide site, the probability that two randomly chosen homologous
nucleotides are different in the sample) were performed in Mega 3.0 using Kimura 2-
126
parameter distances and 1000 bootstrap replicates. Estimates of gene diversity (h, the
probability that two randomly chosen mtDNA lineages were different in the sample) and tests
of neutrality such as Tajima’s D (Tajima 1989) and Fu’s F
S
(Fu 1997) were computed in
Arlequin 2.0 (Schneider et al. 2000) with 10,000 permutations.
Phylogenetic relationships among haplotypes were inferred with PAUP 4.0 (Swofford
1998), using three different approaches: (i) maximum parsimony (MP), (ii) maximum
likelihood (ML), and (iii) distance-based phylogeny with the Neighbor-Joining (NJ) algorithm
(Saitou and Nei 1987). MP trees were estimated with heuristic searches implementing a
random addition of taxa and TBR branch swapping. For the likelihood-based analyses, the
appropriate model of sequence evolution, along with its parameters, were estimated from the
data set with Modeltest 3.6 (Posada and Crandall 1998), using the Akaike Information
Criterion, or directly with PAUP. ML heuristic searches started from an NJ tree and used NNI
branch-swapping. Distance-based trees were inferred using the NJ algorithm, with distance
measures chosen based on the selected model of sequence evolution for each data set. For
each of the three methods, one hundred bootstrap replicates were used to evaluate nodal
support. Three different data sets were analyzed: (i) all haplotypes, including incomplete
sequences (this set was investigated with NJ alone, due to the existence of >>10,000 equally
parsimonious trees, and the computational burden to run ML analysis in this case); (ii)
complete sequences alone, leading to increased stability; and (iii) a mixture of the former two
sets, in which three short haplotypes (representing L. sechurae and L. fulvipes) were added
back to the more stable matrix, to test their phylogenetic placement.
Haplotype networks were generated with sequences from each species (except L.
sechurae [n=1]) using statistical parsimony and the program TCS 1.18 (Clement et al. 2000),
with a 95% threshold for parsimonious connections between haplotypes. To evaluate possible
127
events of population expansion and decline, mismatch distribution analyses were computed in
DnaSP 4.0 (Rozas et al. 2003) and Harpending's Raggedness Test of goodness-of-fit was
performed in Arlequin 2.0 (1000 replicates; species with smaller sample sizes [L. fulvipes and
L. sechurae] were excluded from this analysis).
To estimate the time of divergence among mitochondrial lineages, we used the
mutation rate µ estimated by Tchaicka et al. (in press [ver Capítulo III]) based on available
data from grey wolf and coyote. We then used this substitution rate to calculate (with Mega)
the time of divergence between species, based on the equation d
xy
=2µT (Nei 1987).
RESULTS
Seventy-eight different haplotypes were identified with the 588-base pair (bp) segment
sequenced for Lycalopex species (nine additional haplotypes were included from C. thous),
defining 220 variable sites and 193 parsimony-informative sites (Table 1). Base composition
was biased, with a deficiency of guanine (T=31.1%; C=24.6%; A=26.6%; G=17.6%). No
haplotypes were found to be shared between species.
Using all 87 haplotypes, the NJ analysis generated a tree topology that indicated L.
vetulus as the most basal species in the genus Lycalopex, L. fulvipes and L. gymnocercus as
distinct monophyletic groups, and a shallow internal cluster containing both L. culpaeus and
L. griseus haplotypes, whose reciprocal monophyly was unclear (Fig. 2). L. fulvipes was
placed as a sister-group to the (L. griseus + L. culpaeus) group, but with low support. Since
some of the inferred clades showed low bootstrap values, we performed a second round of
analyses excluding sequences with more than 10% missing data, generating a more robust
data set of 49 haplotypes (including those of C. thous). This second set of analyses retrieved
congruent topologies with all three of the approaches employed, which were also similar to
128
the findings with the full data set, albeit with higher support (Fig. 3). These analyses revealed
reciprocally monophyletic clades for L. culpaeus and L. griseus, which are the most internal
sister taxa in the genus. In these analyses, the single long L. fulvipes sequence was not
placed as sister to the (L. griseus + L. culpaeus) group, but rather at a deeper position
external to L. gymnocercus. However, support for this position was low, rendering the exact
placement L. fulvipes unclear. The basal position of L. vetulus was strongly supported, but the
relationships of L. sechurae could not be assessed, as it was represented by a single short
sequence that was removed from this analysis. To address the outstanding issues, a third set
of phylogenetic analyses was performed, keeping the 49 longer haplotypes from the second
set, and returning the L. sechurae and two short L. fulvipes sequences, to test their placement
given a more stable overall topological framework (Fig. 4). The position of L. fulvipes was the
same as in the second set (compare to Fig. 3), indicating consistency of the information from
the three sampled haplotypes, but support for this placement remained low. Likewise, no
conclusive support could be obtained for the placement of L. sechurae (Fig. 4), although the
results suggest that it is a rather basal species in this group, and not immediately related to L.
culpaeus as might be expected (see Fig. 1).
Intra-specific analyses of sequences indicated that L. culpaeus and L. fulvipes showed
less genetic variability than the remaining species (Table 2). Haplotype networks built for
each species (Figs. 5, 6 and 7) indicated a geographic pattern in the distribution of variability
in L. fulvipes and L. gymnocercus (Fig. 6 and 7). In the former species, continental
haplotypes are separated from island haplotypes by four mutational steps, while between the
latter there is only one step (the small sample sizes warrant cautious interpretation of this
inference). All L. fulvipes samples with unknown origin had the same haplotype F03, which
may suggest that these samples are from Chiloe Island, as no other copy of this haplotype
129
was found in mainland individuals. The Culpeo network was characterized by few mutational
steps, as expected for recently diversified species. The L. gymnocercus network suggests a
possible geographic partition between TA (Taim Ecological Station, in Southernmost Brazil)
and other samples, as inferred from the phylogenetic analyses (Figs. 2, 3 and 7).
Despite no clear indication on the network, population expansion was inferred for L.
culpaeus (r= 0.05; p=0.33), L. vetulus (r=0.033, p= 0.10), L. griseus (r=0.03, p=0.22) and L.
gymnocercus (r=0.02, p=0.59), based on mismatch distribution analyses and the fit to a
population growth model (Fig. 8). This was supported by Fu’s F
s
test only in the case of L.
griseus (F=-8.17, significant), while all neutrality tests were not significant for the other
species.
Divergence time among mtDNA lineages was calculated considering 95% confidence
interval (CI:±2SE) from all values of d
xy
. Using this interval we obtained low, medium and fast
mutation rate estimations (2.02x10
-8
, 3.68x10
-8
and 5.34x10
-8
respectively) that were
combined with the same interval to the d
xy
estimated for each node. By this procedure we
estimate that the divergence between Cerdocyon and Lycalopex took place ca. 1,100,000
years ago. L. vetulus and L. sechurae seem to have diverged from other Lycalopex species
ca. 1,000,000 years to 900,000 years ago, while the divergence among the latter is inferred to
have occurred more recently, ca. 500,000 years ago (Table 3).
130
DISCUSSION
The trees produced using the full data set of 82 haplotypes (Fig. 2) recovered the main
patterns of divergence in this group of canids, but contained some weakly supported nodes
that proved to be unstable when compared to the results of the second set of analyses (with
49 longer haplotypes). This is likely due to missing data present in the first data set, which
may have confused the search when very similar sequences were compared. The second
round of analyses, using only the longer sequences, resolv
131
members of the chilla fox clade (Figs. 2 and 3). There are no formal reports of L. griseus
occurring in these regions (González del Solar and Rau 2004), but this species is sympatric
with L. gymnocercus in several areas, and information on the precise distribution limits of both
species is still scarce. Our results suggest that the areas where these samples were collected
may be in fact inhabited by L. griseus instead of L. gymnocercus. Since color patterns of
pelage are very similar between these foxes (Zunino et al. 1995), identifying them can be
challenging, which suggests that recording errors may have confused historical reports on
these species’ natural history and the delimitation of their ranges. A non-exclusive alternative
hypothesis is that hybridization between these species in their areas of contact could account
for these observations, as well as for their morphological similarity. Zunino et al. (1995),
analyzing pelage characters and cranial measures of Argentinean L. griseus and L.
gymnocercus, observed a clinal variation in size and color, and concluded that these foxes
are conspecific (thus calling them L. gymnocercus, the senior name). In this context, the
samples initially labeled as L. gymnocercus that grouped with L. griseus might be hybrids
between male pampa’s foxes and female chillas.
Another supported clade is formed by the L. fulvipes samples. This fox lives in costal
temperate rainforests of Southern Chile, where it inhabits Chiloe island and also occurs in
sympatry with the chilla and culpeo in a small continental area (Medel et al. 1990, Vilà et al.
2004). Initially, it was described as an endemic insular canid and considered a subspecies of
continental L. griseus (Nowak 1999; Wilson and Reeder 1993; Redford and Eisenberg, 1992).
A molecular genetic analysis conducted by Yahnke et al. (1996) revealed that Darwin’s
fox is a distinct species, a monophyletic clade that was a sister taxon to a (L. griseus + L.
culpaeus) cluster, from which it diverged in the Pleistocene, ca. 275,000 to 667,000 years
ago. These conclusions are broadly corroborated by the present study, as we estimate (using
132
the longer sequences) a divergence time of ca. 500,000 between Darwin’s fox and the
(culpeo + chilla) clade. However, the exact position of L. fulvipes in this recent clade was not
completely consistent among our analyses: while the larger data set (including short
sequences – Fig. 2) agreed with the position obtained by Yahnke et al. (1996), the other two
data sets (relying on longer sequences and in general more stable – Figs. 3 and 4) suggested
that this species is even less closely related to the Andean cluster, as it is placed outside the
group that also includes L. gymnocercus. Since support values for either alternative are low,
further accumulation of data will be required to settle this issue.
Our results strongly support a basal position of L. vetulus in the genus, and we
estimate its origin to have been ca. 1,000.000 ybp. This is in agreement with a recent
phylogeny based on multiple nuclear segments (Lindblad-Toh et al. 2005). The conclusion is
that L. vetulus represents a unique lineage (>97% bootstrap support), distinct from the
griseus-gymnocercus-culpaeus-fulvipes group.
Debate about the proper usage of Lycalopex or Pseudalopex for this group has been
going on for many years (e.g., Cabrera 1931; Osgood 1934; Langguth 1975; Berta 1987,
1988; Tedford et al. 1995). The basal phylogenetic position of the hoary fox implies that it
could be kept in its own genus (Lycalopex), while the other species move back to
Pseudalopex, or that the whole cluster could be considered a single genus (Lycalopex), as in
Wozencraft (2005). Both schemes are compatible with the phylogeny, and this decision will
be arbitrary. We recommend that this decision be based on criteria such as clade age,
morphology, and present usage, which should be established in a broader comparison across
all lineages in the family Canidae.
Combined analysis of morphological and molecular data (Zrzavy and Ricankova 2004)
and fossil data (Berta 1987) reported that L. sechurae and L. vetulus share a common
133
lineage. If this is true, the estimated time of divergence between these species (Table 3)
indicates that they split at roughly the same time as the L. vetulus X griseus-fulvipes-
gymnocercus-culpaeus separation, and that L. sechurae is also rather basal in this clade.
However, the exact phylogenetic position of L. sechurae could not be completely defined by
this mtDNA data set (Figs. 2 and 4), likely due at least in part to the lack of longer sequences
available for this species.
Individual history from each species
The results obtained from the haplotype networks, along with the internal branch
structure of the generated trees, indicate the occurrence of two partitioned genetic groups of
L. gymnocercus in the sampled area (Figs. 3 and 7). Three pampa’s fox subspecies have
been proposed by Massoia (1982). Their geographic limits are not precise and there is no
data regarding the taxonomic position of Bolivian foxes (our samples from Bolivia [BO] were
ultimately considered to be L. griseus). All included L. gymnocercus samples (i.e. those
composing its monophyletic clade; AR animals coming from this area were also grouped with
griseus; see Fig.1) were collected from the L. gymnocercus gymnocercus range, that includes
Southern Brazil and Northeastern Argentina (Massoia, 1982). Since TA (Taim Ecological
Station, in Southernmost Brazil) appears to be a differentiated area, it appears that the
classical subspecies’ distribution does not reflect inferred patterns of historical population
subdivision, as reported for other Neotropical carnivores (e.g. Eizirik et al. 1998; Tchaicka et
al. in press).
The TA sample-site is located in a region of marshlands and lakes that has been
intensively changed between the Middle Pleistocene and the Holocene, when sea level
134
variation created geographic barriers, probably including the event that created the Patos and
Mirim Lagoons (Vilwock et al. 1986). These processes may have influenced the genetic
structure and demographic history of some native species. Due to the matrilineal inheritance
of mtDNA, this pattern may be influenced by the possible occurrence of female philopatry in
this species, which should be investigated by in-depth field studies targeting this issue.
Some inference of genetic structure related to geographic distribution can also be
observed in the L. fulvipes phylogenetic and network analyses, which indicate that mainland
haplotypes are more similar to each other than to the island haplotype (Fig. 6). As suggested
previously (Vilà et al. 2004; Yahnke et al. 1996) the island population appears to be isolated
from remnant continental populations, and may have experienced genetic loss during its
history (only one haplotype is present in Yahnke’s data). This possibility must be investigated
in more detail with expanded sampling in this region, and with the use of additional markers
(e.g. microsatellites). The L. griseus results (Figs. 3 and 6) show no evidence of geographic
structure among haplotypes (with only some support for BO branches), but the complex
pattern of the network suggests that these inferences can be changed in the future by more
detailed studies. The L. culpaeus haplotypes, are quite similar to each other, which is
suggestive of a young age of the species, and compatible with a population expansion
process inferred from the shape of its phylogeny (e.g. Fig. 2).
The clade formed by L. vetulus samples presents some well-supported intra-specific
groups, which showed no obvious geographic orientation, and nor did the haplotype network
for this species (Fig. 5). This pattern may derive from historical geographic structuring that
has been obliterated by subsequent gene flow. This is not expected from small canids that
generally disperse rather short distances, leading to some level of genetic isolation among
areas (Mercure et al. 1993). However, field observations of hoary foxes report that all
135
offspring disperse by the time they are ca. 10 months old (Courtenay et al. 2006), and the
current species’ range seems to be rather continuous, probably offering sufficient opportunity
for genetic admixture over time.
Inferences on the history of South American foxes
Three different canid invasions from North to South America in the Pliocene or Early
Pleistocene have been proposed on the basis of previous inferences of the phylogenetic
relationships among extant species. One of them would include the ancestor of fox group that
includes Lycalopex, Cerdocyon, Atelocynus and Dusicyon (Langguth 1975; Wang et al.
2004). Genetic divergence values obtained from cytocrome b, COI and COII segments
(Wayne et al. 1997) between Cerdocyon+Atelocynus and the other species suggest that this
divergence occurred before the opening of the Panama land bridge, requiring one more
invasion event.
Contrary to this view, our mtDNA control region data indicate that the divergence
between Cerdocyon and Lycalopex took place ca. 1.2 mybp, suggesting that this episode of
speciation may have occurred in South America, after immigration of a single ancestor
through the Isthmus of Panama. In fact, the oldest fossils assigned to Lycalopex (L.
gymnocercus) are reported from Argentinean deposits of the Uquian age (2.5 to 1.5 mybp),
while those of Cerdocyon thous are recorded only from the Lujanian (800,000-10,000 ybp).
Interestingly, there are North American canid fossils reported from the Miocene/Early
Pliocene boundary (6-3mypb - Berta 1987) that have been assigned to the genus Cerdocyon,
which would challenge this hypothesis. The present dating results, which are congruent with
136
our previous analyses (Tchaicka et al. [in press], ver Capítulo III), suggest that the
identification and phylogenetic affinities of these fossils should be reassessed.
It is generally assumed from the fossil record (Berta, 1987; Langguth 1975) and
supported by molecular data (Wayne et al. 1997) that, subsequently to divergence with
Cerdocyon, the diversification of Lycalopex occurred in South America in the in the
Pleistocene. Our results agree with a Pleistocene radiation of Lycalopex, indicating that: (i)
the oldest extant lineages gave rise to L. vetulus and possibly also to L. sechurae (or perhaps
both lineage are directly related; see Berta 1987; Zrzavy and Ricankova 2004), in the Early-
Middle Pleistocene; (ii) this was followed by the diversification of the griseus-culpaeus-
gymnocercus-fulvipes clade, in the Middle Pleistocene; and (iii) finally, by the griseus-
culpaeus recent split in the Middle-Late Pleistocene.
In the Neotropical region, extensive environmental changes took place in the
Pleistocene, which may have influenced this canid radiation. Climatic changes affected the
vegetation domains as well as the sea level, producing potential geographic barriers to
dispersal or confining species to habitat refuges (Marroig and Cerqueira 1997; Withmore and
Prance 1987; Eisenberg and Redford 1999). Canids that had crossed Panama bridge and
dispersed trough Andean savanna corridors, expanded their range to Patagonian and
Brazilian lands by the Early Pleistocene (Langguth 1975). At this time, the La Plata- Paraguay
depression suffered a marine invasion, and possibly became connected to the Amazon Basin,
isolating a large region of Brazil (Marroig and Cerqueira 1997). This may account for the
isolation of canid species in two groups: Brazilian and Argentinean, corresponding to L.
vetulus vs. the remaining lineages.
During the Pleistocene glacial phases, arid climates dominated the equatorial areas
and savanna corridors were broken. Some mammal species that became restricted to tropical
137
humid regions may have become savanna-adapted, and now occur in areas consisting of
Cerrado habitat (Eisenberg and Redford 1999; Whitmore and Prance 1987). This may be the
case of the Hoary fox: its small carnassials, wide crushing molars and the exceptionally large
auditory bullae (Clutton-Brock et al. 1976) suggest adaptations to a predominantly
insectivorous diet. Their preference for insects now allows them to partition food resources
and to coexist with other sympatric canids such as the maned wolf (Chrysocyon brachyurus)
and the crab-eating fox (Cerdocyon thous) (Juarez and Marinho-Filho 2002).
The center of the Lycalopex radiation has been proposed by Berta (1987) to have been
in central Argentina, whereas Langguth (1975) suggested central Brazil are the most likely
region. These two hypotheses are here reconciled, since the second episode of speciation in
this group probably did take place in Argentina (gymnocercus-fulvipes-[griseus+culpaeus]).
The origin of these species was followed by population expansion processes that in some
cases are still detectable (Fig. 8). As suggested by Yahnke et al. (1996), L. fulvipes may
represent a set of relict populations of a once more widely distributed species, whose
phylogenetic affinities within this group are still not completely settled. Future work should use
increased sampling of individuals and characters to attempt to clarify this issue, as well as the
exact phylogenetic position of L. sechurae, so that a more complete biogeographic inference
can be devised for this group. Overall, the prospect of understanding this recent radiation in
South America promises to shed light on some of the processes shaping the mammalian
biodiversity in this region during the Pleistocene.
138
References
Bardeleben C, Moore R L, Wayne R K, 2005. A molecular phylogeny of the Canidae on six
nuclear loci. Molecular Phylogenetics and Evolution, 37:815-831.
Berta A, 1987. Origin, diversification and zoogeography of the South AmericanCanidae.
Fieldiana Zoology, 39:455-471.
Berta A, 1988. Quaternary evolution and biogeography of the large South American Canidae
(Mammalia, Carnivora). University of California Publications, Geological Sciences 132:1–149.
Bermingham E and Moritz C, 1998. Comparative Phylogeography: concepts and application.
Molecular Ecology, 7: 367-369
Brum-Zorrila N and Langguth A, 1980. karyotype of South American Pampas fox
Pseudalopex gymnocercus (Carnivora, Canidae). Experientia, 36:1043-1044.
Cabrera A, 1931. On some South American canine genera. Journal of Mammalogy, 12: 54-
67.
Clement M, Posada D, Crandall K, 2000. TCS: a computer program to estimate gene
genealogies. Molecular Ecology, 9: 1657–1660.
139
Clutton-Brock J, Cobert GB, Hills MA, 1976. A review of the family Canidae with a
classification by numerical Methods. Bulletin of the British Museum (Natural History) Zoology,
2: 117-199.
Courtenay O, Macdonald DW, Gillingham S, Almeida GRD, 2006. First observations on South
America’s largely insectivorous canid: the hoary fox (Pseudalopex vetulus). Journal of
Zoology, 268: 45-54.
Courtenay O and Maffei L 2004. Cerdocyon thous (Linnaeus, 1766). In Hoffmann M and
Sillero-Zubiri C (eds) Canid Action Plan. IUCN Publications, Gland, Switzerland, 67p.
Crespo JA, 1971. Ecologia del zorro gris Dusycion gymnocercus antiquus (Ameghino) en la
província de La Pampa. Revista del Museo Argentino de Ciencias Naturales Bernardino
Rivadavia, I: 148-205.
Dotto JCP, 1997. Estudo da Dieta de Pseudalopex gymnocercus (Fischer, 1814) e de
Cerdocyon thous (Linnaeus, 1766) (Mammalia, Canidae) e sua relação com a mortalidade de
Cordeiros no Rio Grande do Sul. Porto Alegre, Rio Grande do Sul, Brasil: PUCRS. 87p.
Eisenberg JF and Redford KH, 1999. Mammals of the Neotropics: The Central Neotropics.
Chicago: The University of Chicago Press.
140
Eizirik E, Bonatto SL, Johnson WE, Crawshaw Jr PG, Vié JC, Brousset DM, O’Brien SJ,
Salzano FM, 1998. Phylogeographic patterns and evolution of the mitochondrial DNA control
region in two Neotropical cats (Mammalia, Felidae). Journal of Molecular Evolution, 47: 613-
624.
141
Jaksic FM, 1998. Vertebrate invaders and their ecological impacts in Chile. Biodiversity and
Conservation, 7:1427–1445.
Juarez KM and Marinho-Filho J, 2002. Diet, Habitat Use, and Home Ranges of Sympatric
Canids in Central Brazil. Journal of Mammalogy, 83: 925-933.
Kraglievich L, 1930. Craniometría y Classificacion de los Canidos Sudamericanos
especialmente los Argentinos actuales y fósiles. Physis, 10: 35-73.
Kumar S, Tamura K and Nei M, 2004. MEGA3: Integrated software for molecular evolutionary
genetics analysis and sequence alignment. Briefings in Bioinformatics, 5: 2.
Langguth A, 1975. Ecology and evolution in the South American canids. In: Fox MW. The
Wild Canids. New York: Litton Educational Publishing; p.192-206
Lindblad-Toh K, Wade CM, Mikkelsen TS, Karlsson EK, Jaffe DB, Kamal M, Clamp M, Chang
JL, Kulbokas III EJ, Zody MC, Mauceli E, Xie X, Breen M, Wayne RK, Ostrander EA, Ponting
CP, Galibert F, Smith DR, Jong PJ, Kirkness E, Alvarez P, Biagi T, Brockman W, Butler J,
Chin CW, Cook A, Cuff J, Daly MJ, DeCaprio D, Gnerre S, Grabherr M, Kellis M, Kleber M,
Bardeleben C, Goodstadt L, Heger A, Hitte C, Kim L, Koepfli KP, Parker HG, Pollinger JP,
Searle SMJ, Sutter NB, Thomas R, Webber C, Lander ES et al., 2005. Genome Sequence,
comparative analysis and haplotype structure of he domestic dog. Nature, 438: 803-819.
142
Lyras GA, Van Der Geer AAE, 2003. External brain anatomy in relation to the phylogeny of
Caninae (Carnivora: Canidae). Zoological Journal of the Linnean Society, 138: 505–522.
Marroig G and Cerqueira R, 1997. Plio-Pleistocene South American History and the Amazon
Lagoon Hypothesis: a piece in the puzzle of Amazonian diversification. Journal Comp.
Biology, 2: 103-119.
Massoia E, 1982. Dusicyon gymnocercus lordi. una nueva subespecie del “zorro gris grande”
(Mammalia Carnívora Canidae). Neotropica, 28:147–152.
Medel RG, Jiménez JE, Jaksic FM, Yáñez JL, Armesto JJ, 1990. Discovery of a continental
population of the rare Darwin’s fox, Dusicyon f tuat (Matn2(ca)-818-4(0)-647)-4( )-322(i)2(n)-4(0( )-2(h)6(p)-4()-3(l)2(e586(.)-2.0019]TJ-)12.B02(A)-2.99i10(l)2.00195(o)10(l)2.00195(o)-4(i10(l)2.00i)2(ca)--4(f)7.99805( )277.998]T14-353.88 -26.76 TC-2(i)2(o)-4(ns-4(ce)-4()-4(v)10(a)-4(t)-2(i)2(o)-556)278]TJ/R25 1270.53.88 0 T)10(,)-2( )278]TJ/R9 126333.6 0 T–51-4(8)-8471-4(7)-4(7-64)-4(7d[(.)-2( )]( )48.076.88 Td( )TjT*[(M)3(e)-4(r)3(cu-92(r)3(e.)8((G)-2(A)-3(,)-22 )-82(m)3(a)-4()-4(s)-22 )K-2(A)-3(,)-22 )K52(S)-2(n)6(ep02(o)6(f))-4(l)2()-22 SP-2(A)-3(,)-8(W-2(6)-82(a)-4.00g)6(y)-4(n)6(e)-42 K-2(A)-3(,)-22 903.-3(,)-22 nee2
143
Pia MV, López MS, Novaro AJ, 2003. Effects of livestock on the feeding ecology of endemic
culpeo foxes (Pseudalopex culpaeus smithersi) in central Argentina. Revista Chilena de
Historia Natural 76: 313-321.
Posada D, Crandall KA, 1998. Modeltest: testing the model of DNA substitution.
Bioinformatics, 14: 817-818.
Redford KH and Eisenberg JF, 1992. Mammals of the Neotropics:The Southern Cone.
Chicago: The University of Chicago Press.
Rozas J, Sánchez-DelBarrio JC, Messeguer X, Rozas R, 2003. DnaSP, DNA polymorphism
analyses by the coalescent and other methods. Bioinformatics, 19: 2496-2497.
Saiki RK, Scharf S, Faloona F et al., 1985. Enzymatic amplification of beta-globyn genomic
sequences and restriction site analysis for diagnosis of sickle cell anemia. Science, 230:
1350-1354.
Saitou N and Nei M, 1987. The neighbor-joining method: A new method for reconstructing
phylogenetic trees. Molecular Biology and Evolution, 4:406-425.
Sambrook J, Fritsch EF, Maniatis T, 1989. Molecular Cloning: a Laboratory Manual 2
nd
. New
York: Cold Spring Harbor Laboratory Press.
144
Schlotterer C, 2004. The evolution of Molecular Markers – just a matter of fashion? Nature
Rewiews Genetics, 5: 63-69.
Schneider S, Roessli D, Excoffier L, 2000. ARLEQUIN, version 2.000. A Software for
Population Genetics Data Analysis. Geneva, Switzerland: Genetics and Biometry Laboratory,
University of Geneva.
Sillero-Zubiri C, Hoffmann M, Macdonald DW, 2004. Canids: foxes, wolves, jackals and dogs:
status survey and conservation action plan, second edition. Gland, Switzerland and
Cambridge, UK: IUCN Canid Specialist Group.
Sillero-Zubiri C and Macdonald DW, 2004. Introduction. In Sillero-Zubiri C, Hoffmann M,
Macdonald DW (eds) Canids: foxes, wolves, jackals and dogs: status survey and
conservation action plan, second edition. Gland, Switzerland and Cambridge, UK, IUCN
Canid Specialist Group.
Swofford DL, 1998. PAUP* Phylogenetic analysis using parsimony (*and other methods)
Vers. 4. Sunderland: Sinauer.
Tajima F, 1989. Statistical methods to test for nucleotide mutation hypothesis by DNA
polymorphism. Genetics, 123: 585-595.
Tchaicka L, Eizirik E, Oliveira TG, Cândido-JR JF, Freitas TRO, in press. Phylogeography
and population history of the crab-eating fox (Cerdocyon thous). Molecular Ecology.
145
Tedford RH, Taylor BE and Wang X, 1995. Phylogeny of the Caninae (Carnivora: Canidae):
the living taxa. American Museum Novitates, 3146:1–37.
Thenius E, 1954. Zur Abstammung der rotwolfe (Gattung Cuon Hodgson). Osterreichische
Zoologische Zeitschrift, 5: 378-387.
Thomas O, 1914. The Generic and Subgeneric names of the South American Canidae.
Annals and Magazine of Natural History, 8: 350-352.
Van Gelder RG, 1978. A review of Canidae Classification. American Museum Novitates,
2646: 1-10.
Vila C, Leonard JA, Iriarte A, O’Brien SJ,Johnson WE, Wayne RK, 2004. Detecting the
vanishing populations of the highly endangered Darwin’s fox, Pseudalopex fulvipes. Animal
Conservation, 7: 147–153.
Villwock JA, Tomazelli LJ, Loss EL, Dehnhardt EA, Horn Filho NO, Bachi FA, Dehnhardt BA,
1986. Geology of the Rio Grande do Sul coastal province. In: Rabassa JAA (eds.) Quaternary of
South America and Antartic Peninsula.
Wang X, Tedford RH, Van Valkenburgh B, Wayne RK 2004. Phylogeny, Classification, and
Evolutionary Ecology of the Canidae. In Sillero-Zubiri C, Hoffmann M, Macdonald DW (eds)
146
Canids: foxes, wolves, jackals and dogs: status survey and conservation action plan, second
edition. Gland, Switzerland and Cambridge, UK, IUCN Canid Specialist Group.
Ward RH, Frazier BL, Dew-Jager K, Pääbo S, 1991. Extensive mitochondrial diversity within a
single Amerindian tribe. Proceedings of the National Academy of Sciences of the USA, 88:
8720-8724.
Wayne RK, Geffen E, Girman DJ, Koepfli KP, Lau LM, Marshall CR, 1997. Molecular
systematics of the Canidae. Systematic Biology, 46:622– 653.
Wayne RK, 1993. Molecular Evolution of the Dog Family. Trends in Genetic and Evolution, 6:
218-224.
Wayne RK, Nash WG, O´Brien SJ, 1987. Chromossome Evolution of the Canidae - II
Divergence from the Primitive Carnivore Karyotipe. Cytogenetics and Cell Genetics, 44:134-
141.
Wilson DE and Reeder DM, 1993. Mammal species of the world: a taxonomic and geographic
reference, 2
nd
. Washington DC: Smithsonian Institution Press.
Withmore TC, Prance GT, 1987. Biogegraphy and Quaternary History in Tropical America.
New York: Oxford University Press.
Wozencraft WC, 2005. Order Carnivora. In Wilson DE and Reeder DM (eds) Mammals
Species of the World. London Smithsonian Institution Press, London, 1100pp.
147
Yahnke CJ, Johnson WE, Geffen E, Smith D, Hertel F, Roy MS, Bonacic CF, Fuller TK, Van
Valkenburgh B and Wayne RK, 1996. Darwin’s fox: a distinct endangered species in a
vanishing habitat. Conservation Biology, 10:366–375.
Zrzávy J, Ricánková V, 2004. Phylogeny of Recent Canidae (Mammalia,Carnivora): relative
reliability and utility of morphological and molecular datasets. Zoologica Scripta, 33: 311-333.
Zunino G, Vaccaro O, Canevari M, Gardner A, 1995. Taxonomy of the Genus Lycalopex
(Carnivora, Canidae) in Argentina. Proceedings of Biological Society of Washington, 108:
729-747
148
Figure legends
Figure 1. Map showing the current geographic distribution of Lycalopex species (modified
from Courtenay and Maffey 2004) and approximate sample collection sites (polygons)
identified as ■ L. culpaeus; ○ L. fulvipes; ▼ L. griseus; ● L. gymnocercus; ▲ L. vetulus; □ L.
sechurae; and L. griseus initially labeled as L. gymnocercus. The number of samples per
site are indicated (individuals with unknown geographic origin are not included; see Methods).
Figure 2. Neighbor Joining tree (built with Kimura81 [3-Parameter] distances) of 78
Lycalopex spp. haplotypes based on 588 bp of the mitochondrial DNA control region. Nine
Cerdocyon thous
149
Figure 4. Maximum likelihood tree (reconstructed with the GTR+G+I model) of Lycalopex
species mitochondrial DNA haplotypes (52 haplotypes [complete sequence data + short L.
sechurae and L. fulvipes haplotypes]) identified in this study, based on 588 bp of the control
region. Cerdocyon thous haplotypes are used as outgroup (CE, see Table 1). Labels are
haplotype identification numbers (see Table 1). Values above branches indicate support for
each node obtained from MP, NJ and ML respectively; values under 50% are indicated as *.
Figure 5. Networks of Lycalopex vetulus (a) and Lycalopex culpaeus (b) mtDNA control
region (588bp and 626pb respectively) haplotypes generated with TCS using a 95% threshold
for parsimony-based connections. Squares indicate haplotypes likely to be ancestral in each
network (highest outgroup probability). The area of circles and squares is roughly proportional
to the frequency of each haplotype. Haplotypes are identified as in Table 1 and geographic
origin are indicated on right (see Fig. 1; haplotypes without indication have unknown
geographic origin).
Figure 6. Networks of Lycalopex fulvipes (a) and Lycalopex griseus (b) mtDNA control region
(627bp and 624pb respectively) haplotypes generated with TCS using a 95% threshold for
parsimony-based connections. Squares indicate haplotypes likely to be ancestral in each
network (highest outgroup probability). The area of circles and squares is roughly proportional
to the frequency of each haplotype. Haplotypes are identified as in Table 1 and geographic
origins are indicated on the right (see Fig. 1; haplotypes without indication or bearing an *
have unknown geographic origin).
150
Figure 7. Networks of Lycalopex gymnocercus mtDNA control region (588pb) haplotypes
generated with TCS using a 95% threshold for parsimony-based connections. Squares
indicate haplotypes likely to be ancestral in each network (highest outgroup probability). The
area of circles and squares is roughly proportional to the frequency of each haplotype.
Haplotypes are identified as in Table 1 and geographic origin are indicated on right (See Fig.
1; haplotypes without indication and those with an * have unknown geographic origin).
Figure 8. Graphics depicting the result of the Mismatch D
151
(16) MT
(4) GO
(1) BA
(1
) MG
(1) SP
L. culpaeus
L. griseus
L. gymnocercus
L. vetulus
L. fulvipes
L. sechurae
TA (9)
PO (4)
SE (5)
MI (2)
(1)
(5) BO
(4) AR
CH (1)
CH (1)
AR (48)
CO (2)
IS (1)
152
CE01
CE02
CE03
CE04
CE07
CE08
CE06
CE05
CE09
F01 (CO)
F0
2 (CO)
F03 (IS)
C01 (AR)
C03 (AR)
C05 (AR)
C04 (AR)
C08 (AR)
C06 (AR)
C02 (AR)
C14
C09 (AR)
C10 (AR)
C11 (AR)
C13 (AR)
C12 (CH)
C07 (AR)
GR01 (AR)
GR23 (CH)
GR03
GR02
GR21 (CH)
GR04
GR05 (AR)
GR06 (AR)
GR13
GR09 (BO)
GR10 (BO)
GR0
8 (BO)
GR11 (AR)
GR07 (BO)
GR12 (BO)
GR15 (CH)
GR14 (CH)
GR17
GR16
GR20
GR18
GR22
GR19
G01
G02 (TA)
G05 (TA)
G06 (SE)
G18 (PO)
G17
G16 (TA)
G09 (TA)
G12 (TA)
G20 (TA)
G03 (MI)
G10 (PO)
G11 (SE)
G07 (SE,PO)
G04 (TA)
G19 (PO)
G
08 (SE)
G13 (SE)
G15 (MI)
G14 (SE)
S0
1
V01 (MT)
V03 (MT)
V09 (MG)
V10 (SP)
V15
V02 (MT)
V06 (MT)
V16
V17(GO)
V12 (GO)
V04 (MT)
V05 (MT)
V07 (MT)
V13 (GO)
V11 (SP)
V08 (BA)
V14
0.005 substitutions/site
93
100
62
100
55
79
100
153
CE02
CE01
CE04
CE05
F03
C01 (AR)
C03 (AR)
C04 (AR)
C08 (AR)
C05 (AR)
C11 (AR)
C13 (AR)
C02 (AR)
C14
C09 (AR)
GR02
GR21 (CH)
GR04
GR08 (BO)
GR09 (BO)
GR10 (BO)
GR17
GR18
GR19
GR20
GR22
GR13
G01
G02 (TA)
G09 (TA)
G12 (TA)
G16 (TA)
G20 (TA)
G04 (TA )
G07 (PO, SE)
G14 (SE)
G19 (PO)
G08 (SE)
G13 (SE)
V01 (MT)
V03 (MT)
V02 (MT)
V06 (MT)
V09 (MG)
V08 (BA)
V04 (MT)
V07 (MT)
V12 (GO)
0.005
V13 (GO)
100/100/100
92/99/96
72/84/83
100/100/100
79/
*/*
80/83/75
100/100/97
89/84/9
100/100/100
96/100/90
57/68/*
88/*/61
79/96/83
100/100/100
98/95/95
88/95/9
96/97/88
80/92/7
89/*/74
76/*/80
99/95/96
*/73/61
*/86/58
70/97/57
*/56/*
154
CE02
CE03
CE04
CE05
F03
F01
F02
C01
C03
C04
C08
C05
C11
C13
C02
C14
C09
GR02
GR21
GR04
GR08
GR09
GR10
GR17
GR18
GR19
GR20
GR22
GR13
G01
G02
G09
G12
G16
G20
G04
G18
G14
G19
G08
G13
S01
V01
V03
V02
V06
V04
V07
V13
V08
V12
V09
0.005
substitutions/site
97/97/
94
77/80/76
54/82/66
83/96/81
97/97/99
75/56/81
97/90/9
4
87/76/99
100/100/100
*/91/64
99/89/94
100/99/100
155
V03(MT)
V01(MT)
V14
V17 (GO)
V16
V15
V05 (MT)
V13 (GO)
V04 (MT)
V07 (MT)
V12 (GO)
V08 (BA)
V09 (MG)
V10 (SP)
V06 (MT)
V02 (MT)
V11 (SP)
C08 (AR)
C01 (AR)
C14
C13 (AR)
C07 (AR)
C11 (AR)
C09 (AR)
C02 (AR)
C10 (AR)
C12(CH)
C04(AR)
C083 (AR)
C06 (AR)
C05 (AR
)
b
a
156
GR22
GR02
GR04
GR01 (AR)
GR23(CH)
GR03
GR21(CH)
GR05 (AR)
GR06(AR)
GR10(BO)
GR09(BO)
GR07(BO
)
GR12(BO)
GR08(BO)
GR13
GR15(CH)
GR11(AR)
GR14(CH)
GR20
GR16
GR17
GR18
GR19
F03 (IS * )
F01 (CO)
F02 (CO)
a
b
157
G09 (TA)
G19 (TA)
G02 (TA)
G05 (TA)
G12 (TA)
G17 (TA)
G20 (TA)
G06 (SE)
G13 (SE)
G07 (SE, PO, TA)
G19 (SE)
G03 (SE)
G01
G14
G11
G04
G13 (SE)
L. culpaeus
L. griseus
L. gymnocercus
L. vetulus
159
Table 1a. Mitochondrial DNA control region haplotypes identified from Lycalopex spp. and Cerdocyon thous samples. Only
first 110 variable sites are shown. Site numbers (vertical notation) refer to the aligned position in our 588 bp data set
Nucletide Position
Species
Haplotipe
(Fr)
44444444444444444444444444444444444444444444455555555555555555555555555555555555555555555555555555555555555555
45555555556666666666777777777888888889999999900000000011111111222222233333333444444444555555555666666677777788
91234567890123456789012456789123457890134678912345678903456789234567923456789012345689012345679013467834567878
C. thous
CE01 (1)
CE02 (1)
CE03 (1)
CE04 (1)
CE05 (1)
CE06 (1)
CE07 (1)
CE08 (1)
CE09 (1)
L.fulvipes
F01 (1)
F02 (1)
F03 (4)
L.culpaeus
C01 (1)
C02 (1)
C03 (2)
C04 (5)
C05 (2)
C06 (6)
C07 (1)
C08 (1
2)
C09 (2)
C10 (1)
C11 (4)
C12 (1)
C13 (20)
C14 (1)
L.vetulus
V01 (6)
V02 (2)
V03 (4)
V04 (1)
V05 (1)
V06 (1)
V07 (1)
V08 (1)
V09 (1)
V10 (1)
V11 (1)
V12 (1)
V13 (1)
V14 (1)
V15 (1)
V16 (1)
V17 (1)
AAACACTATACGCTCTTCTTCGGAAGCTTGATTTAGGAAATATACCCTAGCTCAGGAATAAATAAACCATTCTCGTCACGCCGCTCGCAACTATTCCCGAACCTGTATCT
..............................................................................................................
..............................................................................................................
....T............................................A....................C.....T.................................
..........T.........T.....T........A.....G...T...A............C.......CTC.T.T.T........T..TC..................
???????????????????????.......TG...A.............A....................C.....T.................................
?????????........................................A....................C.....T.................................
???????????.............G.....................T..A....................C.....T.................................
???????????.........T.....T......C.A.....G...T...A.......G....C.......CTC.T.T......T...T..T?G...T.............
.......GC.TA..G..T.CT..GG.T...T....A....A...GTT.TAT....A....T.....A...C.CT.???????????????????????????????????
.......GC.TA..G..T.CT..GG.T...T....?....A...GTT.TAT....A....T.........C.CT????????????????????????????????????
.......GC.T...G..T.CT...G.T...T....A....A...GTT.TAT.T..A....TG........C.CT.CT.T......T..G.TC...T.....AA.......
.......GC.TA..G..T.CT...G..C..T....A....A...G.T.TATCT..A.G..C...........CT.CT.T......T..G..C..................
.......GC.TA..G..T.CT...G.....C....A....A...A.T.TATCT..A.G..C.........C.CT.CT.T......T..G..C...T.....AAGTATCTG
.......GC.TA..G..T.CT...G..C..T....A....A...G.T.TATCT..A.G..C...........CT.CT.T......T..G..C..................
.......GC.TA..G..T.CT......C..T....A....A...A.T.TATCT..A.G..C....G......CT.CT.T......T..G..C..................
.......GC.TA..G..T.CT...G..C..T....A....A...A.T.TATCT..A.G..C...........CT.CT.T......T..G..C..................
.......GC.TA..G..T.CT......C..T....A....A...A.T.TATCT..A.G..C...........CT.CT.T.....A?????????????????????????
.......GC.TA..G..T.CT.........T....A....A...A.T.TATCT..A.G..C....G....C.CT.???????????????????????????????????
.......GC.TA..G..T.CT......C..T....A....A...A.T.TATCT..A.G..C...........CT.CT.T......T..G..C..................
.......GC.TA..G..T.CT...G.....T....A....A...ATT.TATCT..A.G..C....G....C.CT.CT.T......T..G..C...T..............
.......GC.TA..G..T.CT.A.G.....?....A....A...A.T.TATCT..ACG..C......G..C.CT.CT.T......T..G..C..................
.......GC.TA..G..T.CT...G.....C....A....A...A.T.TATCT..A.G..C.........C.CT.CT.T...A..T..G..C..................
.......GC.TA..G..T.CT.........T....A....A...G.T.TATCT..A.G..C.........C.CT.???????????????????????????????????
.......GC.TA..G..T.CT...G.....T....A....A...A.T.TATCT..A.G..C.........C.CT.CT.T......T..G..C..................
.......GC.TA..G..T.CT...G.....T....A....A...A.T.TATCC..A.G..C.........C.CT.CT.T......T..G..C..................
?.....-GC.T...AA.TC.T...G.T........A..T.GGC.TAT.CAT....A....TG.......CC.C.ACTCT.........G..C..CT.T............
?......GC.T...AA.TC.T...G.T......C.A..T.AGC.TAT.CAT....A....TG.......CC.CT.CTCT.........G..C..CT.T............
?......GC.T...AA.TC.T...G.T..A.....A..T.GGC.TAT.CATC........TG.......CC.C..CTCT.........G.TC..CT.T............
?....T.GC.T...AA.TC.T...G.T........AAGT.AGC.TATCCAT.T..A....C........CC..TACTCT............C..CT.T............
?????????????????????T..G.T........AAGT.AGC.TATCCAT.T..A....C........CC..TACTCT.A..........C..CT.T.....???????
?..A...GC.T...AA.TC.T...G.T......C.A..T.AGC.TAT.CAT....A....TG.......CC.CT.CTCT.........G..C..CT.T............
?....T.GC.T...AA.TC.T...G.T........AAGT.AGC.TATCCAT.T..A....C........CC..TACTCT............C..CT.T............
?....T.GC.T...AA.TC.T..G..T........A..T.GGC.TAT.CAT.T..A....T........CC..T.CTCT......T....TC..CT.T............
?....T.GC.T...AA.TC.T...G.T........A..T.GGC.TAT.CAT....A....TG.......CC..T.CTCT.........G.TC...T.TA...........
???????????...AA.TC.T...G.T........A..T.GGC.TAT.CAT...AA....TG.......CC..T.CTCT.........G.TC...T.TA...........
?????????.T...AA.TC.T.AG..T........A..T.AGC.TAT.CAT...AA....CG.......CC..T.CT.T...A.....G..C...TTT............
.....T?GC.T...AA.TCC?...G.T......C.A..T.GGC.TAT.CAT....A....C........CC.CT.CTCT.........G.TC..CT.T............
?....T.GC.T...AA.TC.T...G.T........AAGT.AGC.TATCCAT....A....C........CC..TACTCT............C..CT.T............
.....T.GC.T...A..TC.T.....T...T..C.A....GGC.TAT.CAT....A....C........CC..T????????????????????????????????????
.....T.GC.T...AA.TC.T.....T......C.A..T.GGC.TAT.CAT....A....T........CC..T.CTCT......?????????????????????????
????????????????.TC.T...G.T......C.A..T.AGC.TAT.CAT....A.G..T........CC.CTA.TCT......T..G.TC..CT.T...........?
????????CGTA..AA.TC.T...G.T......C.A..T.AGC.TAT.CAT....A.G..T........CC.CTA.TCT......T..G.TC..CT.T............
160
Table 1a. continued
L.griseus
GR01 (1)
GR02 (1)
GR03 (1)
GR04 (1)
GR05 (1)
GR06 (1)
GR07 (1)
GR08 (1)
GR09 (1)
GR10 (1)
GR11 (1)
GR12 (1)
GR13 (1)
GR14 (1)
GR15 (1)
GR16 (1)
GR17 (1)
GR18 (1)
GR19 (2)
GR20 (1)
GR21 (4)
GR22 (4)
GR23 (2)
L.gymnocercus
G01 (1)
G02 (1)
G03 (1)
G04 (1)
G05 (1)
G06 (1)
G07 (2)
G
08 (2)
G09 (1)
G10 (1)
G11 (1)
G12 (1)
G13 (1)
G14 (1)
G15
(2)
G16 (2)
G17 (1)
G18 (1)
G19 (1)
G20 (1)
L.sechurae
S01 (1)
.......GC.TA..G..T.CT.........T....A....AG..A.T.CAT..G.A....CG....????????????????????????????????????????????
.......GC.TA..G..T.CT...G.....T....A....A...A.T.TA.CTG.A....C......G.CC.CT..T.T......TA....C...T..............
.......GC.TA..G..T.CT........?T....A....A...A.T.TA.CTG.A....C........CC.CT.???????????????????????????????????
.......GC.TA..G..T.CT.........T....A....A...A.T.TA.CTG......C.........C.CT..T.T......TA....C...T..............
.......GC.TA..G..T.CT.........T....A....A...A.T.TA.CT..A....C.....????????????????????????????????????????????
.......GC.TA..G..T.CT...G.....T..C.A....AG..A.T.TATCT..A....CG...G????????????????????????????????????????????
???????????A.GG..TCCT...G.T...C....A....A...A.T.?ATCT..A...GC.........C.CT..T.T......TA...TC...T..............
??G....GC.TA..G..TCCT.........T....A....A...A.T.TATCT..A....C...?.....C..T.CT.T......TA...T....T..............
?......GC.TA..G.CTCCT.........T....A....AG..A.T.TATCTG.A....C.........C..T.CT.T......TA...TC...T..............
??....?GC.TA..G.CTCCT.........?....A....AG..A...TATCTG.A....CG..?.....C..T.CT.T......TA...TC...T..............
.......GC.TA..G..TCCT.........T....A....A...A.T.TATCT..A....C.....????????????????????????????????????????????
??????????????????????????????????.A....A...A.T.TATCT..A...GC.........C.CT..T.TT.....TA...TC...T..............
.......GC.TA..G..TCCT.........T....A....AG..A.T.TATCT..A....C.........C.CT.CT.T......T....TC...T...G........T.
.......GC.TA..G..TCCT.........T....A....A...A...TATCT..A....C.........C.CT.???????????????????????????????????
.......GC.TA..G..T.CT.........T....A....A...A...TATCT..A....C.........C.CT.???????????????????????????????????
.......GC.TA..G..TCCT...G.....T....A....A...A...TATCT..A....C.........C.CT.???????????????????????????????????
.......GC.TA..G..TCCT...G.....T....A....A...A...TATCT..A....C.........C.CT.CT.T......TA...TCG..T.....AA.......
.......GC.TA..G..TCCT...G.....T....A....A...A...TATCT..A....C.........C.CT.CT.T......TA...TCGG.T.....AA.......
.......GC.TA..G..TCCT...G.....T....A....A...A...TATCT..A....C.........C.CT.CT.T......TA...TCG..T.....AA.......
.......GC.TA..G..TCCT...G.....T....A....A...A...TATCT..A....C.........C.CT.CT.T......TA...TCG..T.....AA.......
.......GC.TA..G..T.CT...G.....T....A....A...A.T.TA.CTG.A....C........CC.CT..T.T......TA....C...T..............
.......GC.TA..G..TCCT...G.....T....A....A...A...TATCT..A....C.........C.CT.CT.T......TA...TCG..T.....AA.......
.......GC.TA..G..T.CT...G.....C....A....A...A.T.TATCT..A.G..C.........C.CT.CT.T......T..G..C...T.....AA.......
.......GC.T...G..T.CT...G.T...T....A....A...ATT.CATCTG....C.C..G......C.CT...TT......T..G.TC.......GG..GTATCTG
?G.....GC.T...G..T.CT.....T...T....A....A...ATT.CATCTG....C.C..G......C.CT...TT......T..G.TC.......GG..GTATCTG
?????????????????????.....T...T..C.A....A...A.TCTAT.T..A....C..G.....CC.CT...TT..T...T..GGTC.....T.....GTATCTG
.......GC.T.T.G..T-C?.....T...C.CC.A....A...A.TCTAT.T..A....C..G......C.CT...TT......T..GGTC...........GTATCTG
???????????????????????????????????????????????????????????.C..G?...?.C.CT?????......T..G.TC.?.....GG?.GTATCTG
?????????????????????????TT..?T....A....A...ATT.CATCTG....C.C..G......C.CT...TTT.....TC.G.TC.......G?..GTATCTG
G......GC.T.T.G..T.CT.....T...C.CC.A....A...A.TCTAT.T..A....C..G......C.CT...TT......T..GGTC...........GTATCTG
?......GC.T...G..T.CT...G.T...T.CC.A....AG..A.TCTA..TG.A....T..G......CTC....TT......T..G.TC.....T.....GTATCTG
.......GC.T...G..T.CT.....T...T....A....A...ATT.CATCTG....C.C..G......C.CT...TT......T..G.TC.......GG..GTATCTG
?????????????????????.....T.G.C.CC.A....A...A.TCTAT.T..A....C..G......C.CT...TT......T..GGTC...........GTATCTG
?????????????????????????????????????????????????????..A....C..G......C.CT...TT......TC.GGTC...........GTATCTG
.......-C.T...G..T.CT.....T...T....A....A...ATT.CATCTG....C.C..G......C.CT...TT......T..G.TC.......GG..GTATCTG
.......GC.T...G..T.CT...G.T...T.CC.A....AG..A.TCTA..TG.A....T..G......CTC....TT......T..G.TC.....T.....GTATCTG
......GGC.T.T.G..T.CT.....T...C.CC.A....A...A.TCTAT.T..A....C..G......C.CT...TT......T..GGTC...........GTATCTG
?????????.G.T.G..T.C?.....T...C.CC.A....A...A.TCTAT.T..A....C..G......C.CT...TT......T..GGTC...........GTATCTG
.......GC.T...G..T.C?.....T...T....A....A...ATT.CATCTG....C.C..G......C.CT...TT......T..G.TC.......GG..GTATCTG
??????-GCCT...G..T.C?.....T...T...TA....C..TATT.CATCTG....C.C..GC...C.C.CT...TT......T..G.TC.......GG..GTATCTG
?????????????????????.....T...TG..?A....A...ATT.CATCTG....C.C..G......C.CT...TT......T..G.TC.......GG..GTATCTG
......-GC.T.T.G..T.CT.....T...C.CC.A....A...A.TCTAT.T..A....C..G......C.CT...TT......T..GGTC...........GTATCTG
......GG?.T...G..T.C?.?...T...T....A....?...ATT.CATCTG....C.C..GC.....C.CT...TT......T..G.TC.......GG..GTATCTG
......GC.T..CG..T..T.....T...T..C.A...TG.CTT?TCTATC...A....C.........C..T.???????????????????????????????????
Fr frequency on the sample
161
Table 1b. Mitochondrial DNA control region haplotypes identified from Lycalopex spp. and Cerdocyon thous samples. Only
latter 110 variable sites are shown. Site numbers (vertical notation) refer to the aligned position in our 588 bp data set.
Nucletide Position Species
Haplotipe
44444444444444444444444444444444444444444444455555555555555555555555555555555555555555555555555555555555555555
45555555556666666666777777777888888889999999900000000011111111222222233333333444444444555555555666666677777788
91234567890123456789012456789123457890134678912345678903456789234567923456789012345689012345679013467834567878
C. thous
CE01 (1)
CE02 (1)
CE03 (1)
CE04 (1)
CE05 (1)
CE06 (
1)
CE07 (1)
CE08 (1)
CE09 (1)
L.fulvipes
F01 (1)
F02 (1)
F03 (4)
L.culpaeus
C01 (1)
C02 (1)
C03 (2)
C04 (5)
C05 (2)
C06 (6)
C07 (1)
C08 (12)
C09 (2)
C10 (1)
C11 (4)
C12 (1)
C13 (20)
C14 (1)
L.vetulus
V01 (6)
V02 (2)
V03 (4)
V04 (1)
V05 (1)
V06 (1)
V07 (1)
V08 (1)
V09 (1)
V10 (1)
V11 (1)
V12 (1)
V13 (1)
V14 (1)
V15 (1)
V16 (1)
V17 (1)
GATCTGCTATCACTCACCTATGACACGACGCACTACTCTACTATCCTTGCTTTCAGAATATGCGTCGTGCTAA?????????????????????????????????????
.........................................................................CGCAGTCAGATATATGTAGCTGACTATCACATTTAGC
...................................................................G.....CGCAGTCAGATATATGTAGCTGACTATCACATTTAGC
.........................................................................CGCAGTCAGATATATGTAGCTGACTATCACATTCGGC
................T.......GT.........................C....G.........AC.....TGCAGTCAGATATATGTAGCTGACTATCACATTTAGC
.........................................................................CGCAGTCAGATATATGTAGCTGACTAT??????????
................?????.................................................????????????????????????????????????????
.....................................................................?????????????????????????????????????????
................?.......GT.........................C..............AC.?????????????????????????????????????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
................A.......G...............T.G..TC....C...............C.....TGCAGTCAGATATATGTAGCTGACTATCACATATAGC
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATATAT???
-...............G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATATATAGC
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATATATAGC
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATATATAGC
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATATATAGC
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATATATAGC
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATATATAGC
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTG???????????????
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATGTATAGC
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATATATAGC
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATATATAGC
................T.......G....................TC....C...............C.....CGCAGTCAAATACATGTAGCTGAC?????????????
........................GT...................TC....................C.....CGCAGTCAAATACATGTAGCTGAC?????????????
............T...T.......G....................TC....C..............AC.....CGCAGTCAAATACATGTAGCTGAC?????????????
................T............................TC....C............G..C..????????????????????????????????????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
........................GT...................TC....................C.....CGCAGTCAAATACATGTAGCTGAC?????????????
................T............................TC....C...............C...G.CGCAGTCAA????????????????????????????
........................G....................TC....................C.....CGCAGTCAAATACATGTAGCTGAC?????????????
................T.......G....................TC....C...............C.....CGCAGTCAAATATATGTAGCTGAC?????????????
........................G....................TC....C...............C.?????????????????????????????????????????
...........................................C.TC....C...............C.....CGCAGTCAGATACATGTAGCTGAC?????????????
..A.....................G....................TC....C...............C.....CGCAGTCAAATACATGTAGCTGAC?????????????
................T............................TC....C...............C.-.G.CGCAGTCAAGTACATGTAGCTGAC?????????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
................T.......G....................TC....C...............C.-...CGCAGTCAAATACATGTAGCTGAC?????????????
................T.......G....................TC....C...............C.....?????????????????????????????????????
162
Table 1b. continued
L.griseus
GR01 (1)
GR02 (1)
GR03 (1)
GR04 (1)
GR05 (1)
GR06 (1)
GR07 (1)
GR08 (1)
GR09 (1)
GR10 (1)
GR11 (1)
GR12 (1)
GR13 (1)
GR14 (1)
GR15 (1)
GR16 (1)
GR17 (1)
GR18 (1)
GR19 (2)
GR20 (1)
GR21 (4)
GR22 (4)
GR2
3 (2)
L.gymnocercus
G01 (1)
G02 (1)
G03 (1)
G04 (1)
G05 (1)
G06 (1)
G07 (2)
G08 (2)
G09 (1)
G10 (1)
G11 (1)
G12 (1)
G13 (1)
G14 (1)
G15
(2)
G16 (2)
G17 (1)
G18 (1)
G19 (1)
G20 (1)
L.sechurae
S01 (1)
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
................A.......G.A..................TC....C...............C.....TGCAG-CAAGTACATGTAGCTGACTATCACATATAGT
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
................A.......G.A..................TC....C...............C.....CGCAG-TAAG-ATATGTAGCTGACTATCACATATAGC
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
................G.......G.A..................TC....................C.....CGCAGTCAAATATATGTAGCTGAC?????????????
................A.......G.A..................TC.........G..........C.....TGCAGTCAAATATATGTAGCT????????????????
................A.......G.A..................TC....................C.....TGCAGTCAAATACATGTAGCTGACTAT??????????
................A.......G.A..................TC....................C.....TGCAGTCAAATACATGTAGCTGACTAT??????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
................G.......G.A..................TC....................C.....CGCAGTCAAATATATGTA???????????????????
................A.......G.A..................TC....C...............C.....TGCAGTCAAATACATGTAGCTGACTATCACATATAGC
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
................A.......G.A..................TC....................C.....TGCAGTCAAATACATGTAGCTGACTATCACATATACG
................A.......G.A..................TC....................C.....TGCAGTCAAATACATGTAGCTGACTATCACATATAGC
................A.......G.A..................TC....................C.....TGCAGTCAAATACATGTAGCTGACTATCACACATAGC
..............A.A.......G.A..................TC....................C.....GGCAGTCAAATACATGTAGCTGACTATCACATATAGC
................A.......G.A..................TC....C...............C.....CGCAG-CAAGTACATGTAGCTGACTATCACATATAGT
................A.......G.A..................TC....................C.....TGCAGTCAAATACATGTAGCTGACTATCACATATAGC
................G.......G.A...............G..TC....C...............C.....CGCAGTCAGATATATGTAGCTGACTATCATATATAGC
ATCTGCTATCACTCA..TATGACGCAACGCACTACTCTACTGTCT..GCTC.CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTATCAT????????
ATCTGCTATCACTCA..TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTAT???????????
ATCTGCTATCACTCAG.TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTAT???????????
ATCTGCTATCACTCAG.TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTAT???????????
ATCTGCTATCACTCA..TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTAT???????????
ATCTGCTATCACTCA..TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTAT???????????
ATCTGCTATCACTCAG.TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTAT???????????
ATCTGCTATCACTCAG.TATGACGCAACGCACTACTCTACTGTCT..GCT..CAG..TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTAT???????????
ATCTGCTATCACTCA..TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTAT???????????
ATCTGCTATCACTCAG.TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTAT???????????
ATCTGCTATCACTCAG.TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTAT???????????
ATCTGCTATCACTCA..TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.T?CACTCCGAT?TATGTAGCTGACT?????????????
ATCTGCTATCACTCAG.TATGACGCAACGCACTACTCTACTGTCT..GCT..CAG..TATGCGTCGCGCTA.TGCAGTCCGATATATGTAGCTGACTATCAT????????
ATCTGCTATCACTCAG.TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGC???????????????????????????????????
ATCTGCTATCACTCAG.TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGC?????????????????????????????????????????
ATCTGCTATCACTCA..TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTATCAT????????
ATCTGCTATCACTCA..TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTATCAT????????
ATCTGCTATCACTCA..TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATATGTAGCTGACTATCAT????????
ATCTGCTATCACTCAG.TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCACTCCGAT?TATGTAGCTGACTA????????????
ATCTGCTATCACTCA..TATGACGCAACGCACTACTCTACTGTCT..GCT..CAGA.TATGCGTCGCGCTA.TGCAGTCAGATATA????????????????????????
??????????????????????????????????????????????????????????????????????????????????????????????????????????????
Fr frequency on the sample
163
Table 2. Diversity indices (nucleotide [π] and gene [h] diversity) observed in Lycalopex species control region
N h π Number of
haplotypes
Number of
Variable sites
Number of Parsimony
informative sites
L. culpaeus 53
0.8004 +/- 0.0407 0.005 +-0.002 13 16 10
L. vetulus 26
0.9323 +/- 0.0352 0.023 +-0.004 17 51 33
L.griseus 31
0.9398 +/- 0.0311 0.023 +-0.005 23 50 27
L. gymnocercus 26
0.9723 +/- 0.0209 0.022+-0.004 20 44 29
L. fulvipes 6 0.6000 +/- 0.2152 0.009+-0.004 3 5 4
164
Table 3. Nucleotide divergence between pairs of species (Dxy, with standard error [se] included) used to infer the intervals of
divergence time (reported in years [y]) in this clade of Neotropical canids.
Lineages compared Dxy (se)
Lower bound (y)
Mean time (y)
Upper bound (y)
Inferences
Cerdocyon X Lycalopex species
0.088 (0.013)
580,524
1,125,652
2,821,782
Genera divergence on Early-Middle
Pleistocene
L. gymnocercus X L. vetulus
0.080 (0.011)
543,071
1,086,956
2,524,752
L. griseus X L. vetulus
0.079 (0.013)
496,254
1,076,369
2,599,009
L. fulvipes X L. vetulus
0.078 (0.016)
430,711
1,059,782
2,722,772
L. sechurae X L. vetulus 0.078 (0.016)
430,711
1,059,782
2,722,772
L. culpaeus X L. vetulus
0.071 (0.011)
552,434
964,673
2,301,980
L. vetulus divergence from other
Lycalopex on Early-Middle Pleistocene
L. griseus X L. sechurae
0.066 (0.015)
337,078
896,739
2,376,237
L. sechurae X L. culpaeus
0.064 (0.014)
337,078
869,565
2,277,227
L. gymnocercus X L. sechurae
0.064 (0.014)
337,078
869,565
2,277,227
L. fulvipes X L. sechurae
0.061 (0.011)
365,168
828,804
2,054,455
L. sechurae divergence from other
Lycalopex (except L. vetulus) on Early-
Middle Pleistocene
L. fulvipes X L. gymnocercus
0.052 (0.013)
243,445
706,521
1,930,693
Early-Middle Pleistocene
L. griseus X L. gymnocercus
0.050 (0.008)
318,352
679,347
1,633,663
L. gymnocercus X L. culpaeus
0.041 (0.007)
243,445
557,065
1,361,386
L. gymnocercus divergence from L.
griseus-culpaeus on Middle Pleistocene
L. griseus X L. fulvipes
0.042 (0.010)
205,992
570,652
1,534,643
L. fulvipes X L. culpaeus
0.036 (0.009)
168,539
489,130
1,336,633
L. fulvipes divergence from L. griseus-
culpaeus on Middle Pleistocene
L. griseus
X
L. culpaeus
0.027 (0.006)
140,449
366,847
965,346
Middle- Late Pleistocene
Capítulo VI
DISCUSSÃO
166
O conjunto de dados obtidos no presente estudo descreve um panorama
inicial para a filogeografia das raposas sul americanas, contribuindo para o
preenchimento das lacunas de conhecimento existente neste grupo de canídeos.
É abordado o gênero Lycalopex, sua especiação e algumas características
genéticas intraespecificas, bem como, mais detalhadamente, a história evolutiva e
dinâmica populacional de Cerdocyon thous.
As análises filogenéticas de seqüências da região controladora do DNA
mitocondrial (mtDNA) indicaram que as espécies do gênero Lycalopex compõem
um grupo monofilético. Neste, L. vetulus é a espécie mais basal e fulvipes-
griseus-culpaeus-gymnocercus formam um ramo mais interno no qual se observa
menor distância entre L. culpaeus e L. griseus.
Alguns estudos prévios haviam analisado as relações dentro do grupo
utilizando dados genéticos, morfológicos ou ambos. A posição basal L. vetulus foi
apoiada pela análise de 15 Kb de seqüências nucleares (Lindblad-Toh et al.,
2006), em contradição as inferências de Wayne et al. (1997) com uso de dados
de regiões codificadoras do DNA mitocondrial, Zrzavy e Ricancova (2004) em
abordagem conjunta de dados moleculares, morfológicos e comportamentais, e
Lyras e Van-Gelder (2003) com morfologia do cérebro.
A monofilia de L. fulvipes e sua distinção em relação a L. griseus foi
anteriormente indicada por Yahnke et al. (1996), e também é confirmada pelo
trabalho de Lindblad-Toh et al. (2006).
A relação entre as demais espécies é bastante discordante entre os
diferentes estudos, no entanto, griseus-gymnocercus-culpaeus estão muito
proximamente relacionados nas análises filogenéticas de Wayne et al. (1997),
incluindo entre eles também L. vetulus; Lindbal-Toh (2006) incluindo L. sechurae;
e Zrzavy e Ricancova (2004).
As estimativas de tempos de divergência entre os ramos das
filogenias obtidas para Lycalopex spp. e Cerdocyon thous, indicam que para os
canídeos, como para a maior parte da biota, o Pleistoceno foi um período decisivo
para determinação dos padrões de distribuição de espécies que observamos. As
datas aproximadas de divergência entre as espécies do gênero Lycalopex
indicaram o Pleistoceno médio-inferior como período de origem de L. vetulus e L.
sechurae; um pouco mais recente mais ainda neste período a origem de L.
167
gymnocercus e L. fulvipes; e o Pleistoceno médio-inferior para a divergência entre
L. griseus e L. culpaeus (Tabela 3 Capítulo V; os intervalos para todas as análises
estão compreendidos no período do Pleistoceno). Estas inferências são
compatíveis com o registro fóssil que descreve neste período a radiação
adaptativa do gênero: o registro mais antigo é de L. gymnocercus – 2,5 a 1,5
milhões de anos A.P. (antes do presente); para as outras espécies os registros
estão relacionados ao Pleistoceno superior ou ao tempo recente (Berta, 1987).
Ainda neste período (ca. 400.000 anos A.P.), Cerdocyon thous, segundo
nossos resultados, teria passado por processos demográficos que deram origem
a uma estruturação genética muito forte entre o grupo das populações do
nordeste X sul de sua distribuição (Figs. 1, 2, 3 e Tabela 3, 4 e 5 Capítulo III; as
diferentes inferências obtidas através de marcadores nucleares são abaixo
discutidas).
O Pleistoceno foi considerado por muito tempo um período de
estabilidade para a América do Sul, Ásia e Africa (Marroig e Cerqueira, 1987).
Dados posteriores, inclusive para a distribuição das espécies na América do Sul,
indicaram que ao contrário, este foi um período de intensas variações climáticas
que produziram fortes modificações ambientais. As oscilações de temperatura
durante o período foram acompanhadas de mudanças no tipo e distribuição da
vegetação e por alterações do nível do mar, que por sua vez modificaram a
distribuição de águas continentais (Withmore e Prance, 1987; Marroig e
Cerqueira, 1997; Eisenberg and Redford 1992; Costa 2003).
Durante a fase de maior transgressão marinha (aproximadamente 2,5
milhões de anos A.P., no inicio do Pleistoceno) a bacia Amazônica transformou-se
em um grande lago e pode ter se ligado a Bacia do Prata-Paraguai e Paraná que
tiveram seus níveis elevados. Esse evento deve ter gerado uma forte barreira
entre as regiões de terras Argentinas, que se mantiveram conectadas aos Andes,
e as terras Brasileiras (conforme revisão de Marroig e Cerqueira, 1997).
As linhagens de canídeos então existentes na América da Sul
possivelmente sofreram um processo de vicariância, que pode ser sugerido como
um dos fatores que influenciaram sua especiação. Especialmente a distância
entre L. vetulus e os demais Lycalopex pode ser explicada por este evento, aliada
as modificações de vegetação ocorridas no período.
168
As florestas tropicais e o Cerrado constituem formações bastante antigas
que se originaram durante o Cretáceo e o Terciário, e tiveram sua extensão
diminuída durante os períodos mais frios e secos do Pleistoceno, formando
refúgios aos quais espécies tornaram-se adaptadas (Withmore e Prance, 1987;
Eisenberg e Redford, 1992; Oliveira et al., 2005). O alto endemismo dos biomas
Cerrado e Mata Atlântica são resultados desse processo que pode ter incluído L.
vetulus, endêmico do cerrado (Eisenberg, 1981). Outro canídeo influenciado por
estas modificações parece ser C. thous, que apresenta história discrepante para
os dois clados intraespecíficos (Fig. 1, 2 e 3 Capítulo III). As populações a
nordeste de sua distribuição apresentam-se como um grupo antigo (altos índices
de diversidade – Tabelas 3 e 5, haplótipos bastante diferenciados – Figs. 2 e 3,
Capítulo III), que manteve-se estável em tamanho efetivo (ausência de expansão
populacional – Fig. 4 Capítulo III) e foi influenciado por processos de restrição ao
fluxo gênico em algumas épocas (Fig. 3 Capítulo III). Já as populações do clado
sul são resultantes de um evento recente de invasão da área e expansão no
tamanho populacional (Figs. 2, 3 e 4; Capítulo III). Provavelmente o primeiro
grupo esteja relacionado ao isolamento de um fragmento da floresta tropical no
nordeste do Brasil durante períodos de glaciação, e o segundo aos padrões mais
recentes de vegetação gerados ao final do Pleistoceno (Withmore e Prance,
1987).
Corroborando nossas inferências, Langguth (1975) sugere que as terras
Brasileiras foram um importante centro para a evolução dos canídeos
neotropicais, e Vanzolini (1988), Bates et al. (1998); Costa et al. (2000); Lara &
Patton (2000), Ditchfield (2000), Costa (2003) descrevem padrões concordantes
de distribuição de espécies e estruturação genética para diversos taxa (répteis,
aves e pequenos mamíferos).
Outra região importante para a especiação dos Canidae, conforme
sugerido por Berta (1987), parece ter sido a Argentina, onde provavelmente se
diversificaram as espécies mais recentes de Lycalopex (o que é apoiado pelo
maior número de espécies presentes atualmente), processo que deve estar
relacionado com as modificações climáticas que perduraram até o último glacial
(13,000-18.000 anos A.P. segundo Withmore e Prance, 1987). Nossos dados
169
sugerem que, após este período, várias espécies do gênero sofreram uma
expansão populacional (Fig. 8, Capítulo V).
A divergência entre os gêneros Lycalopex e Cerdocyon foi estimada em
cerca de 1milhões de anos antes do presente, tempo posterior ao fechamento do
istmo do Panamá, que ocorreu há aproximadamente 3 milhões de anos A.P. Os
resultados obtidos, assim, levantam a possibilidade de que a divergência entre os
dois grupos tenha ocorrido já no continente sul-americano. Nossos dados não
corroboram as inferências obtidas pela análise de 2001pb de seqüências
codificadoras de proteínas do mtDNA, que indicaram idade mais antiga para o
evento (cerca de 3 milhões de anos A.P.), e sugeriram que as espécies atuais dos
dois gêneros provêm de diferentes eventos de invasão do continente (Wayne et
al.,1997). As diferenças observadas para as duas estimativas podem estar
relacionadas a diferentes taxas de mutação entre as duas regiões mitocondriais
utilizadas e, mais provavelmente, a diferenças nos métodos de análise e nas
calibrações fósseis utilizadas. Análises mais aprofundadas utilizando múltiplos
segmentos e diferentes calibrações fósseis são necessárias para testar de forma
mais conclusiva estes cenários.
Os resultados discutidos nos parágrafos acima podem ser aplicados às
questões referentes à taxonomia do grupo, sugerindo a classificação de L.
fulvipes como espécie distinta de L. griseus (ver Yahnke et al., 1996). A
classificação de L. vetulus em um gênero distinto, como proposto por Langguth
(1969,1975), mostra-se compatível com a filogenia obtida, suscitando um debate
sobre a alternativa mais adequada para o uso neste grupo.
Indica-se ainda que L. gymnocercus e L. griseus (que representam ramos
distintos bem definidos) devem ser mantidos na categoria de espécies distintas,
contrariando Zunino et al. (1995), que propuseram sua união.
O agrupamento de animais inicialmente identificados como L. gymnocercus
no ramo formado por L. griseus tem implicações importantes relacionadas à atual
distribuição geográfica destas espécies, e também aos caracteres usados para
sua identificação. Para as áreas onde estes animais foram coletados, não é
considerada a ocorrência de L. griseus (Gonzáles del Solar e Rau, 2004) e, dada
a similaridade de coloração das duas espécies (Zunino et al., 1995), estes
animais podem estar sendo erroneamente identificados.
170
Outra possibilidade é a de que os animais sejam híbridos do cruzamento
de fêmeas de L. griseus (tendo em vista a herança matrilinear do mtDNA) e
machos de L. gymnocercus. Tal sugestão vem da comparação destes dados
genéticos com a variação clinal descrita por Zunino et al.,1995 para a coloração e
a morfologia das duas espécies na área Argentina de sua distribuição.
Para C. thous e L. gymnocercus, a estruturação genética observada
questiona as propostas de distribuição de subespécies propostas por Cabrera
(1931) e por Massoia (1982), para uma e outra espécie, respectivamente. A
subespécie C. thous entrerianus deve ter sua distribuição aumentada para o norte
(até a região do bioma Cerrado) em detrimento das áreas de C. thous azarae; e a
região para onde era reconhecido C. thous thous é mais propriamente uma área
onde se misturam os dois grupos anteriormente comentados (Fig.1 Capítulo III).
Para a raposa dos pampas pode ser questionada a distribuição de L.
gymnocercus gymnocercus, dada a inferência a partir dos dados moleculares de
uma estruturação genética dentro da área de ocorrência desta subespécie (na
região do banhado do Taim, ao sul do Brasil; Fig. 2,3,4 e 7, Capítulo V). Este
resultado deve ser explorado em mais detalhe em estudos futuros, utilizando um
maior número de indivíduos e outros marcadores moleculares.
As inferências intraespecificas obtidas nos permitem comparar a história
evolutiva de algumas das diferentes espécies abordadas. Enquanto um padrão
de haplótipos intimamente relacionados, ligados a um haplótipo central mais
freqüente, indica a idade recente dos grupos de populações ao sul da distribuição
de Cerdocyon, a existência de vários passos mutacionais entre os haplótipos das
populações ao norte desta espécie e de L. vetulus e L. griseus inferem uma
história evolutiva mais antiga (Fig. 2 – Capítulo III; Fig. 5 e 6 – Capítulo V). A
diferenciação dos haplótipos mostra relação com sua distribuição geográfica para
L. gymnocercus, Cerdocyon e L. fulvipes indicando que barreiras históricas devem
ter sido determinantes desses padrões (modificações ambientais do Pleistoceno
para as duas primeiras; isolamento na Ilha Chiloé para L. fulvipes)
A inferência de partição genética norte-sul para C. thous, obtida através
dos dados de mtDNA, foi amplamente investigada neste trabalho aplicando
diferentes marcadores moleculares. Todos os marcadores utilizados mostraram-
se informativos em relação às questões levantadas, e indicaram que Cerdocyon
171
thous apresenta altos índices de diversidade genética (4-24 alelos/locus e
heterozigosidade média de 0.64, no caso dos microssatélites; π = 0.83 ± 0.032
para região controladora do mtDNA; e π=0.13 ± 0.061 a 0.20 ± 0.06 para os três
seguimentos de introns).
As regiões nucleares, porém, não indicam nenhuma estruturação genética
dentro da área de distribuição estudada para C. thous. Esta diferença em relação
aos resultados provenientes do mtDNA, poderia resultar (ver Capítulo III), do
maior tamanho efetivo e das taxas menores de mutação nas regiões de íntrons, o
que faria com que os resultados destas seqüências mostrassem um panorama
anterior, mais antigo, ao indicado pelo mtDNA, sem capturar este episódio
histórico de subdivisão (Zhang e Hewitt, 2003). Tal hipótese foi testada pela
utilização dos microssatélites (Capítulo IV), marcadores aplicáveis ao estudo de
eventos recentes devido a suas altas taxas de mutação (Schlotterer, 2004). A
ausência de estruturação mostrada também para os microssatélites indica então
que o fluxo gênico diferencial entre os dois sexos é um importante fator
determinante das diferenças observadas (Hare, 2001; Antunes et al., 2002; Zhang
e Hewitt, 2003).
O mtDNA, apresentando herança matrilinear e tamanho efetivo menor que
o dos marcadores nucleares, é mais suscetível à deriva genética, capturando
assim de forma mais sensível a diferenciação genética entre grupos em períodos
de isolamento (Hare, 2001; Antunes et al., 2002; Zhang e Hewitt, 2003), como
provavelmente tenha acontecido neste caso. A manutenção desses padrões no
mtDNA no tempo recente, após o desaparecimento da barreira de isolamento
entre os dois grupos, deve-se provavelmente à maior filopatria das fêmeas, que
impediram a dissolução da estruturação. A ausência desses padrões nos
marcadores nucleares parece ser produto da influência da transmissão desses
caracteres também por machos, que teriam maiores taxas de dispersão nesta
espécie, conforme indicado pelas análises comparativas baseadas em
coalescência (Tabela 5, capítulo III).
Não existem dados precisos, obtidos por observação direta, para as taxas
de dispersão de machos e fêmeas nesta espécie. O trabalho que reporta em mais
detalhes eventos dessa natureza é o de Macdonald e Courtenay (1996), que
monitoraram grupos familiares de C. thous na região da Ilha de Marajó, no norte
172
do Brasil. Os autores reportam que entre os doze nascimentos durante o estudo
(mais de uma estação de reprodução) apenas cinco dispersaram, sendo quatro
machos juvenis e uma fêmea já adulta, porém, os machos formaram casais com
fêmeas de idade semelhante à deles, o que sugere que estas também dispersem.
Ambos estabeleceram territórios próximos ou adjacentes aos de seus pais, para
onde continuaram voltando ocasionalmente.
Estas características de distribuição dos territórios parecem estar refletidas
nos padrões de isolamento pela distância observados para as análises de mtDNA
(Fig. 2 e 3, Capítulo III), porém são muito levemente indicadas pelos marcadores
nucleares na abordagem de estruturação populacional, apoiando mais uma vez
as inferências de fluxo gênico preferencial de machos. Apenas a população de RS
(especialmente na análise bayesiana implementada no programa STRUCTURE)
aparece com alguma diferenciação em relação as demais (Capítulo IV). A
investigação mais completa desta e de mais duas populações da espécie (MS e
PR), indicaram que, mesmo distando aproximadamente 500Km entre si, estas
últimas comportam-se como uma única unidade evolutiva.
173
REFERÊNCIAS BIBLIOGRÁFICAS
174
Amos W e Balmford A (2001) When does conservation genetics matter? Heredity
87:257-265.
Anderson S (1997) Mammals of Bolivia. Bulletin of the Americam Museum of
Natural History 231:54-59.
Antunes A, Templeton AR, Guyomard R, Alexandrino P (2002) The role of nuclear
genes in intraspecific evolutionary inference: genealogy of the transferrin gene in
the brown trout. Molecular Biology and Evolution 19:1272–1287.
Asa C e Cossíos ED (2004) Pseudalopex sechurae (Thomas, 1900). In Sillero-
Zubiri C, Hoffmann M, Macdonald DW (eds) Canids: foxes, wolves, jackals and
dogs: status survey and conservation action plan, second edition. Gland,
Switzerland and Cambridge, UK, IUCN Canid Specialist Group.
Avise JC (2000) Phylogeography -The History and Formation of Species. Harvard
University Press, London, England 343pp.
Avise JC (1994) Molecular Markers, Natural History and Evolution. Chapman &
Hall, New York, 364pp.
Bandelt HJ, Forster P, Rohl A (1999) Median-joining networks for inferring
intraspecific phylogenies. Molecular Biology and Evolution 16: 37-48.
Bardeleben C, Moore RL, Wayne RK (2005) A molecular phylogeny of the
Canidae on six nuclear loci. Molecular Phylogenetics and Evolution 37:815-831.
Bates JM, Hackett SJ, Cracraft J (1998) Area-relationships in the neotropical
lowlands: an hypothesis based on raw distributions of passerine birds. Journal of
Biogeography 25: 783–793.
Becker M e Dalponte JC (1999) Rastros de Mamíferos Silvestres Brasileiros,
Editora da UNB, Brasília, 98pp.
Beerli P e Felsenstein J (2001) Maximum likelihood estimation of a migration
matrix and effective population sizes in subpopulations by using a coalescent
approach. Proceedings of the National Academy of Sciences of the USA 98:
4563–4568.
Bekkof M, Daniels TJ e Gittleman JL (1984) Live History Patterns and the
Comparative Social Ecology of Carnivores. Annual Review of Ecology and
Systematics 15: 191-232.
Bermingham E e Moritz C (1998) Comparative Phylogeography: concepts and
application. Molecular Ecology 7: 367-369.
Berta A (1982) Cerdocyon thous. Mammalian Species 186: 1-4.
175
Berta A (1987) Origin, diversification and zoogeography of the South American
Canidae. Fieldiana Zoology 39: 455-471.
Berta A (1988) Quaternary evolution and biogeography of the large South
American Canidae Orer-3.21279(m)-1.40511(a-413.489(l)i413.489(l)-1.40511(a,2.80762(f)-9.79( )-3)-280762(f))3.21279(a)-7.82938(rn413.489(b)-7.83068(i-7.83068(v)10.6383(o))13.4459(r)3.21279(a))2.80892().2.80762(f)1.79( )-3)U413.489(l)n413.489(b)-7.83068(i-7.83068(v)10.6383(e)-7.83068(r)3.21279(si)-413.489(t)7 0 Td[(y)1079( )-3)o
176
Chiarelli AB (1975) The Chromossomes of the Canidae. In Fox W (ed) The Wild
Canids. Litton Educational Publishing Inc, 505pp.
Clement M, Posada D, Crandall K (2000) TCS: a computer program to estimate
gene genealogies. Molecular Ecology 9:1657–1660.
Clutton-Brock J, Cobert GB, Hills MA (1976) A review of the family Canidae with a
classification by numerical Methods. Bulletin of the British Museum (Natural
History) Zoology 2: 117-199.
Clutton-Brock J (1977) Man-Made Dogs. Science 197: 1340-1342.
Costa LP (2003) The historical bridge between the Amazon and the Atlantic Forest
of Brazil: a study of molecular phylogeography with small mammals. Journal of
Biogeography 30: 71–86.
Costa LP, Leite YLR, Fonseca GAB, Fonseca MT (2000) Biogeography of South
American forest mammals: endemism and diversity in the Atlantic Forest.
Biotropica 32: 872–881.
Courtenay O e Maffei L (2004) Cerdocyon thous (Linnaeus, 1766). In Hoffmann M
and Sillero-Zubiri C (eds) Canid Action Plan. IUCN Publications, Gland,
Switzerland, 67pp.
Courtenay O, Macdonald, DW, Gillingham S, Almeida GRD (2006) First
observations on South America’s largely insectivorous canid: the hoary fox
(Pseudalopex vetulus). Journal of Zoology 268: 45-54.
Cracraft J (1988) Deep-history biogeography retrieving the historical pattern of
evolving continental biotas. Systematic Zoology 37: 221–236.
Crespo JA (1971) Ecologia del zorro gris Dusycion gymnocercus antiquus
(Ameghino) en la província de La Pampa. Revista del Museo Argentino de
Ciencias Naturales Bernardino Rivadavia I: 148-205.
Crespo JA (1975) Ecology of the Pampa Gray fox and the Large fox (Culpeo).In
Fox MW (ed) The Wild Canidis. Litton Educational Publishing Inc, UK, 505pp.
Cutrera AP, Lacey E, Busch C (2005) Genetic structure in a solitary rodent
(Ctenomys talarum) implications for kinship and dispersal. Molecular Ecology
14:2511-2525.
Dalén L, Götherström A, Tannerfeldt M, Angerbjörn A (2002) Is the Endangered
Fennoscandian Artic fox (Alopex lagopus) population genetically isolated?
Biological Conservation 105: 171-178.
177
Dalén L, Fuglei E, Hersteinsson P, Kapel CM, Roth JD, Samelius JD, Tannerfeldt
178
Excoffier L, Smouse P, Quattro J (1992) Analysis of Molecular Variance inferred
from metric distances among DNA haplotypes: Application to human mitochondrial
DNA restriction data. Genetics 131: 479-491.
Excoffier L, Smouse P, Quattro J (1992) Analysis of Molecular Variance inferred
from metric distances among DNA haplotypes: Application to human mitochondrial
DNA restriction data. Genetics 131: 479-491.
Facure KG e Giaretta AA (1996) Food habits of Carnivores in a Coastal Atlantic
Forest of Southeastern Brazil. Mammalia, 60: 499-502.
Facure KG e Monteiro-Filho ELA (1996) Feeding Habits of the Crab-eating fox,
Cerdocyon thous (Carnivora, Canidae), in a Suburban area of Southeastern Brazil.
Mammalia 60: 147-149.
Farrel LE, Roman J, Sunquist ME (2000) Dietary separation of sympatric
carnivores identified by analysis of scats. Molecular Ecology 9: 1583-1590.
Ferreira ME (2001) Técnicas e Estratégias para a Caracterização Molecular e Uso
de Recursos Genéticos. In GARAY B.I. (ed) Conservação da Biodiversidade em
Ecossistemas Tropicais.Vozes, 430pp.
Flynn JJ e Nedbal MA (1998) Phylogeny of the Carnivora (Mammalia) Congruence
vs Incompatibility amog Multiple Data Sets. Molecular Phylogenetics and
Evolution, 9: 414-426.
Francisco LV, Langston AA, Mellersh CS, Neal CL, Ostrander EA (1996) A class
of highly polymorphic tetranucleotide repeats for canine genetic mapping.
Mammalian Genome 7: 359–362.
Frankhan R, Ballou JD, Briscoe DA (2003) Introduction to Conservation Genetics.
Cambridge University Press, Cambridge, UK, 543pp.
Fu YX (1997) Statistical tests of neutrality of mutations against population growth,
hitchhiking and background selection. Genetics 147: 915-925.
Fuentes ER e Jaksic FM (1979) Latitudinal Size Variation of Chilean Foxes : Tests
of Alternative Hypoteses. Ecology 60: 43-47.
Gay L, Defous du Rau P, Mondain-Monval JY, Crochet PA (2004) Phylogeography
of a game species: the red-crested pochard (Netta rufina) and consequences of its
management. Molecular Ecology 13: 1035-1045.
Geffen E, Anderson MJ, Wayne RK (2004) Climate and Habitat Barriers to
dispersal in the highly mobile gray wolf. Molecular Ecology 13: 2481-2490
179
Geffen E, Gompper ME, Gittleman JL, Luh H, Macdonald DW, Wayne RK (1996)
Size, Life- History Traits and Social organization in the Canidae: a reevaluation.
The American Naturalist 147: 141-178.
Ginsberg JR e MacDonald DW (1990) Foxes, Wolves, Jackals, and Dogs: An
Action Plan for the Conservation of Canids. IUCN Publications, Gland,
Switzerland, 196pp.
Girman DJ, Vilá C, Geffen E Creel S, Mills MGL, McNutt JW, Ginsberg J, Kat PW,
Mimiya KH, Wayne RK (2001) Patterns of population subdivision, gene flow and
genetic variability in the African Wild Dog (Lycaon pictus). Molecular Ecology 10:
1703-1723.
Gonzáles del Solar R and Rau J (2004) Pseudalopex griseus (Gray, 1937). In
Sillero-Zubiri C, Hoffmann M, Macdonald DW (eds) Canids: foxes, wolves, jackals
and dogs: status survey and conservation action plan, second edition. Gland,
Switzerland and Cambridge, UK, IUCN Canid Specialist Group, pp.56.
Goudet J (2002) FSTAT version 2.9.3.2. Institute of Ecology, Biology Building,
Lausanne, Switzerland.
Graur D e LI W (2000) Fundamental of Molecular Evolution, Sinauer Associations,
389pp.
Hare MP (2001) Prospects for nuclear gene phylogeography. Trends in Ecology
and Evolution, 16: 700–706.
Hartl DL e Clark J (1997) Principles of Populations Genetics, 3º ed. Sinauer
Associates, Sunderland, 448p.
Hey J e Nielsen R (2004) Multilocus methods for estimating population sizes,
migration rates and divergence time, with applications to the divergence of
Drosophila pseudoobscura and D. persimilis. Genetics 167: 747-760.
Hough JR (1948) The Auditory Region in Some Members of the Procyonidae,
Canidae e Ursidae. Its significance in the Phylogeny of the Carnivora. Bulletin of
the American Museum of Natural History 92: 70-118.
Huelsenbeck JP and Ronquist F (2001) MrBayes: bayesian inference of
phylogeny. Bioinformatics 17: 754-755.
IUCN, (2003) www.iucnredlist.org
Iyengar A, Babu VN, Hedges S, Venkataraman AB, Maclean N, Morin PA (2005)
Phylogeography, genetic structure, and diversity in the dhole (Cuon alpinus).
Molecular Ecology 14: 2281-2297.
Jaksic FM, Schlatter P, Yáñez JL (1980) Feeding ecology of central Chilean foxes
Dusicyon culpaeus and D. griseus. Journal of Mammalogy 61:254–260.
180
Jaksic FM, Yañez J, Rau JR (1983) Trophic Relations of Southernmost Population
of Dusycion in Chile. Journal of Mammalogy 4: 693-697.
Jaksic FM (1998) Vertebrate invaders and their ecological impacts in Chile.
Biodiversity and Conservation 7:1427–1445.
Jiménez JE e McMahon E (2004) Pseudalopex fulvipes (Martin, 1837). In Sillero-
Zubiri C, Hoffmann M, Macdonald DW (eds) Canids: foxes, wolves, jackals and
dogs: status survey and conservation action plan, second edition. Gland,
Switzerland and Cambridge, UK, IUCN Canid Specialist Group, pp.50.
Jiménez JE e Novaro AJ (2004) Pseudalopex culpaeus (Molina, 1782). In Sillero-
Zubiri C, Hoffmann M, Macdonald DW (eds) Canids: foxes, wolves, jackals and
dogs: status survey and conservation action plan, second edition. Gland,
Switzerland and Cambridge, UK, IUCN Canid Specialist Group, pp.44.
Juarez KM e Marinho-Filho J (2002) Diet, habitat use, and home ranges of
sympatric canids in Central Brazil. Journal of Mammalogy 83: 925-933.
Kamier JF, Ballard WB, Gese EM, Harrison RL, Karkis S,Mote K (2004) Adult
male emigration and a famela-based organization in swift foxes, Vulpes velox.
Animal Behavior 67: 699-702.
Koopman ME, Cypher BL, Scrivner FH (2000) Dispersal patterns of San Joaquin
kit foxes (Vulpes macrotis mutica). Journal of Mammalogy 81: 213-222.
Kraglievich L (1930) Craniometría y Classificacion de los Canidos Sudamericanos
especialmente los Argentinos actuales y fósiles. Physis 10: 35-73.
Kuhner MK, Yamato J, Felsenstein J (1995) Estimating effective population size
and mutation rate from sequence data using Metropolis-Hastings sampling.
Genetics 140: 1421–1430.
Kumar S, Tamura K and Nei M (2004) MEGA3: Integrated software for molecular
evolutionary genetics analysis and sequence alignment. Briefings in Bioinformatics
5: 2.
Langguth A (1969) Die sudmerikanischen Canidae under besonderer
berucksichtigung des mahnenwolfes Chrysocyon brachyurus Illiger. Zeitschirift fur
wissenachaftliche Zoologie 179: 1-88.
Langguth A (1975) Ecology and evolution in the South American canids. In Fox
MW (ed) The Wild Canids. Litton Educational Publishing, New York, pp.192-206.
Lara MC e Patton JL (2000) Evolutionary diversification of spiny rats (genus
Trinomys, Rodentia: Echimyidae) in the Atlantic Forest of Brazil. Zoological
Journal of the Linnean Society 130: 661–686.
Lehman N, Wayne RK (1991) Analysis of coyote mitochondrial DNA genotype
frequencies: estimation of the effective number of alleles. Genetics 128: 405-416.
181
Lindblad-Toh K, Wade CM, Mikkelsen TS, Karlsson EK, Jaffe DB, Kamal M,
Clamp M, Chang JL, Kulbokas III EJ, Zody MC, Mauceli E, Xie X, Breen M, Wayne
RK, Ostrander EA, Ponting CP, Galibert F, Smith DR, Jong PJ, Kirkness E,
Alvarez P, Biagi T, Brockman W, Butler J, Chin CW, Cook A, Cuff J, Daly MJ,
DeCaprio D, Gnerre S, Grabherr M, Kellis M, Kleber M, Bardeleben C, Goodstadt
L, Heger A, Hitte C, Kim L, Koepfli KP, Parker HG, Pollinger JP, Searle SMJ,
Sutter NB, Thomas R, Webber C, Lander ES et al. (2005) Genome Sequence,
comparative analysis and haplotype structure of he domestic dog. Nature 438:
803-819.
Lyons LA, Laughlin TF, Copeland NG, Jenkins NA, Womack JE, O'Brien SJ (1997)
Comparative anchor tagged sequences (CATS) for integrative mapping of
mammalian genomes. Nature Genetics 15: 47-56.
Lyras GA, Van Der Geer AAE (2003) External brain anatomy in relation to the
phylogeny of Caninae (Carnivora: Canidae). Zoological Journal of the Linnean
Society 138: 505–522.
MacDonald DW, Courtenay O (1996) Enduring social relationships in a population
of crab-eating zorros, Cerdocyon thous, in Amazonian Brazil (Carnivora, Canidae).
Journal of Zoological Society of London 239: 329-355.
Mantel N (1967) The detection of disease clustering and a generalized regression
approach. Cancer Research 27: 209-220.
Marroig G, Cerqueira R (1997) Plio-Pleistocene South American History and the
Amazon Lagoon Hypothesis: a piece in the puzzle of Amazonian diversification.
Journal Comp. Biology 2: 103-119.
Massoia E (1982) Dusicyon gymnocercus lordi. una nueva subespecie del “zorro
gris grande” (Mammalia Carnívora Canidae). Neotropica 28:147–152.
Medel RG, Jaksic FM (1988) Ecología de los Cánidos Sudamericanos: una
revisión. Revista Chilena de Historia Natural 61: 67-79
Medel RG, Jiménez JE, Jaksic FM, Yáñez JL, Armesto JJ (1990) Discovery of a
continental population of the rare Darwin’s fox, Dusicyon fulvipes (Martin,1837) in
Chile. Biological Conservation 51:71–77.
Mercure A, Ralls K, Koepfli KP, Wayne RK (1993) Genetic subdivisions among
small canids: mitochondrial DNA differentiation of Swift, Kit and Artic fox. Evolution
47: 1313-1328.
Michalski F (2000) Ecologia de Carnívoros em Área Alterada no Sudeste do
Brasil. Universidade Federal do Rio Grande do Sul, Porto Alegre, 103pp.
Montgomery GG e Lubin YD (1978) Social Structure and Food Habits of Crab-
eating fox (Cerdocyon thous) in Venezoela LLanos. Acta Cientifica Venezolana
20: 282-283.
182
Moritz C (1994) Defining Evolutionarily Significant Units for Conservation. Trends
in Ecology e Evolution 9: 373-375.
Moritz C e Faith DP (1998) Comparative Phylogeography and the identification of
genetically Divergent areas for Conservation. Molecular Ecology 7: 419-429.
Motta-Junior JC, Lombardi JA, Talamoni, SA (1994) Notes on crab eating fox
(Dusycion thous) seed dispersal and food habits in Southeastern Brazil. Mammalia
58: 156-159.
Murphy WJ, Sun S, Chen ZQ, Pecon-Slattery J, O'Brien SJ (1999) Extensive
conservation of sex chromosome organization between cat and human revealed
by parallel radiation hybrid mapping. Genome Research 9: 1223-1230.
Nei M (1987) Molecular Evolutionary Genetics. Columbia University Press,New
York, 278pp.
Nielsen R e Wakeley J (2001) Distinguishing migration from isolation. A Markov
chain Monte Carlo approach. Genetics 158: 885-96.
Nowak, R.M. 1999. Walker’s mammals of the world. 6
th
edn. John Hopkins
University Press, Baltimore,Maryland, USA, 4567pp.
Oliveira PE, Behling H, Ledru MP et al. (2005) Paleovegetação e paleoclimas do
Quaternário do Brasil. In Souza CRG, Suguio K, Oliveira MAS, Oliveira PE (eds)
Quaternário do Brasil. Holos Editora, Ribeirão Preto, Brasil, pp. 52-73.
Olmos F (1993). Notes on the Food Habits of Brazilian ¨Caatinga¨ Carnivores.
Mammalia 57: 126-130
Olsen JS (1974) Early Domestic Dogs in North America and their origins. Journal
of Field Archeology 1:343-345.
Oosterhout CV, Hutchinson WF, Wills DPM, SHIPLEY, P. (2004). Micro-checker:
software for identifying and correcting genotyping erros in microsatellite data.
Molecular Ecology Notes 4:535.
Osgood WH, 1934. The Genera and Subgenera of South American Canidae.
Journal of Mammalogy, 15: 45-50.
Ostrander e Wayne (2006) Genome Research. http://www.genome.org
Parera A (2002) Los Mamiferos de la Argentina y La Región Austral de
Sudamerica. El Ateneo, Buenos Aires, 589pp.
183
Pereira SL (2000) Mitochondrial Genome Organization and Vertebrate
Phylogenetics. Genetics and Molecular Biology, 23: 745-752.
Pia MV, López MS, Novaro AJ (2003) Effects of livestock on the feeding ecology
of endemic culpeo foxes (Pseudalopex culpaeus smithersi) in central Argentina.
Revista Chilena de Historia Natural 76: 313-321.
Posada D e Crandall KA (1998) Modeltest: testing the model of DNA substitution.
Bioinformatics 14: 817-818.
Posada D, Crandall KA, Templeton AR (2000) GeoDis: a program for the cladistic
nested analysis of the geographical distribution of genetic haplotypes. Molecular
Ecology 9: 487-488.
Pritchard JK, Stephens M, P Donnely (2000) Inference of a Population Structure
Using Multilocus Genotype Data. Genetics 12: 945-959.
Raymond M e Rousset F (1995) GENEPOP (version 1.2): population genetics
software for exact test ecumenism. Journal of Heredity 86: 248-249.
Redford KH e Eisenberg JF (1992) Mammals of the Neotropics:The Southern
Cone. The University of Chicago Press, Chicago, 467pp.
Reinolds J, Weir BS, Cockerham CC (1983) Estimation for the coanscestry
coefficient: basis for the short-term genetic distance. Genetics 105: 767-779.
Rice WR (1989) Analysing Tables and of statistical tests. Evolution 43: 223-225.
Riddle BR (1996) The Molecular Phylogeographic Bridge between deep and
Shallow History in Continental Biotas. Trends in Ecology and Evolution 11: 207-
211.
Rogers AR e Harpending H (1992) Population growth makes waves in the
distribution of pairwise genetic differences. Molecular Biology and Evolution 9:
552-569.
Roy SM, Geffen E, Smith D, Ostrander EA, Wayne RK (1994) Patterns of
Differentiation and Hybridization in North Americam Wolflike Canids, Revelead by
Analysis of Microsatellite Loci. Molecular Biology and Evolution 11: 553-574.
Rozas J, Sánchez-DelBarrio JC, Messeguer X, Rozas R (2003) DnaSP, DNA
polymorphism analyses by the coalescent and other methods. Bioinformatics 19:
2496-2497.
Sacks NB, Brown S, Hernest HB (2004) Population structure of California coyotes
corresponds to habitat-specific breaks and illuminates species history. Molecular
Ecology, 13, 1265-1275.
184
Saiki RK, Scharf S, Faloona F et al. (1985) Enzymatic amplification of beta-globyn
genomic sequences and restriction site analysis for diagnosis of sickle cell
anemia. Science 230: 1350-1354.
Saitou N e Nei M (1987) The neighbor-joining method: A new method for
reconstructing phylogenetic trees. Molecular Biology and Evolution 4:406-425.
Sambrook J, Fritsch EF, Maniatis T (1989) Molecular Cloning: a Laboratory
Manual 2nd. Cold Spring Harbor Laboratory Press, New York, 1090pp.
Schlotterer C (2004) The evolution of Molecular Markers – just a matter of
fashion? Nature Reviews Genetics 5: 63-69.
Schneider S, Roessli D, Excoffier L (2000) ARLEQUIN, version 2.000. A Software
for Population Genetics Data Analysis. Switzerland, Genetics and Biometry
Laboratory. University of Geneva, Geneva Switzerland.
Scribner KT and Pearce JM (2000) Microsatellites: Evolutionary and
Methodological Background and Empirical Aplications at Individual, Population
and Phylogenetic Levels. In Baker AJ (ed) Molecular Metods In Ecology. Ed
Methods In Ecology, 235pp.
Seddon LM, Parker HG, Ostrander EA, Ellegren H (2005) SNPs in ecological and
conservation studies: a test in the Scandinavian wolf population. Molecular
Ecology 14: 503-511.
Sillero-Zubiri C, Hoffmann M, Macdonald DW (2004) Canids: foxes, wolves,
jackals and dogs: status survey and conservation action plan, second edition.
Gland, Switzerland and Cambridge, UK, IUCN Canid Specialist Group, 308pp.
Sillero-Zubiri C and Macdonald DW (2004) Introduction. In Sillero-Zubiri C,
Hoffmann M, Macdonald DW (eds) Canids: foxes, wolves, jackals and dogs: status
survey and conservation action plan, second edition. Gland, Switzerland and
Cambridge, UK, IUCN Canid Specialist Group, pp. 2-7.
Silva F (1994) Mamíferos Silvestres do Rio Grande do Sul, Fundação Zoobotânica
do Rio Grande do Sul, Porto Alegre, 78pp.
Snustad P e Simmons J (1997). Principles of Genetics. Wiley & Sons, New York,
498pp.
Souza OR (1990) Historia Geral. Editora Atica, São Paulo, São Paulo, Brasil,
432pp.
Spinks PQ and Shaffer BH (2005) Range-wide molecular analysis of the western
pond turtle (Emys marmorata): cryptic variation, isolation by distance, and their
conservation implications. Molecular Ecology 14: 2047-2064.
185
Stains HJ (1975) Distribution and Taxonomy of the Canidae. In FOX MW (ed) The
Wild Canids. Litton Educational Publishing Inc., 505pp.
Stephens M e Donnelly P (2003) A comparison of Bayesian methods for haplotype
reconstruction from population genotype data. American Journal of Human
Genetics 73: 1162-1169.
Sunquist ME, Sunquist F, Daneke DE (1989) Ecology Separation in a Venezoela
LLanos Carnivores Community. In Redford K and Eisenberg JF (eds) Advances in
Neotropical Mammalogy. The Sandhill Crane Press, New York, 614pp.
Swofford DL (1998) PAUP* Phylogenetic analysis using parsimony (*and other
methods) Vers. 4. Sinauer, Sunderland, MA.
Tajima F (1989) Statistical methods to test for nucleotide mutation hypothesis by
DNA polymorphism. Genetics 123: 585-595.
Tajima F (1996) The amount of DNA polymorphism maintained in a finite
population when the neutral mutation rate varies among sites. Genetics 143: 1457-
1465.
Tamura K e Nei M (1993) Estimation of the number of nucleotide substitutions in
the control region of mitochondrial DNA in humans and chimpanzees. Molecular
Biology and Evolution 10: 512-526.
Tautz D (1993) Notes on the Definition and Nomenclature of Tandemly Repetitive
DNA Sequences. In Pena C, Pplen R, Jeffreys AJ (eds) DNA fingerprinting: state
of the science, 21-28p.
Tchaicka L, Eizirik E, Oliveira
TG, Cândido-JR JF, Freitas TRO, in press.
Phylogeography and population history of the crab-eating fox (Cerdocyon thous).
Molecular Ecology.
Tedford RH, Taylor BE and Wang X (1995) Phylogeny of the Caninae (Carnivora:
Canidae): the living taxa. American Museum Novitates 3146:1–37.
Templeton AR, Boerwinkle E, Sing CF (1987) A cladistic analysis of phenotypic
associations with haplotypes inferred from restriction endonuclease mapping and
DNA sequence data: Basic theory and an analysis of alcohol dehydrogenase
activity in Drosophila. Genetics 117: 343–351.
Templeton AR, Routman E, Phillips CA (1995) Separating population structure
from population history: a cladistic analysis of the geographical distribution of
186
mitochondrial DNA haplotypes in the tiger salamander, Ambystoma tigrinum.
Genetics 140: 767–782.
Templeton AR (2001) Using phylogeographic analysis of gene trees to test
species status and processes. Molecular Ecology 10:779-781.
Thenius E (1954) Zur Abstammung der rotwolfe (Gattung Cuon Hodgson).
Osterreichische Zoologische Zeitschrift 5: 378-387.
Thomas O (1914) The Generic and Subgeneric names of the South American
Canidae. Annals and Magazine of Natural History 8: 350-352.
Van Gelder RG (1978) A review of Canidae Classification. American Museum
Novitates 2646: 1-10.
Vanzolini PE (1988) Distributional patterns of South American lizards. In Vanzolini
PE and Heyer WR (eds) Proceedings of a workshop on Neotropical distribution
patterns. Academia Brasileira de Ciências, Rio de Janeiro, pp. 317–342.
Venta PJ, Brouillette JA, Yuzbasiyan-Gurkan V, Brewer GJ (1996) Gene-specific
universal mammalian sequence-tagged sites: application to the canine genome.
Biochemical Genetics 34: 321-341.
Vigilant L, Hofreiter M, Siedel H, Boesch C (2001) Paternity And Relatedness In
Wild Chimpanzee Communities. PNAS 6: 12890-12895.
Vilà C, Amorim IR, Leonard JA, Posada D, Castroviejo J, Petrucci-Fonseca F,
Crandall KA, Ellegren H, Wayne RK (1999) Mitochondrial DNA phylogeography
and population history of the grey wolf Canis lupus. Molecular Ecology 8: 2089-
2183
Vila C, Leonard JA, Iriarte A, O’Brien SJ, Johnson WE, Wayne RK (2004)
Detecting the vanishing populations of the highly endangered Darwin’s fox,
Pseudalopex fulvipes. Animal Conservation 7: 147–153.
Villwock JA, Tomazelli LJ, Loss EL, Dehnhardt EA, Horn Filho NO, Bachi FA,
Dehnhardt BA (1986). Geology of the Rio Grande do Sul coastal province. In
Rabassa JAA (ed) Quaternary of South America and Antarctic Peninsula, UFRGS,
456pp.
Wang X, Tedford RH, Van Valkenburgh B, Wayne RK (2004) Phylogeny,
Classification, and Evolutionary Ecology of the Canidae. In Sillero-Zubiri C,
Hoffmann M, Macdonald DW (eds) Canids: foxes, wolves, jackals and dogs: status
survey and conservation action plan, second edition. Gland, Switzerland and
Cambridge, UK, IUCN Canid Specialist Group, pp. 7-20.
Ward RH, Frazier BL, Dew-Jager K, Pääbo S (1991) Extensive mitochondrial
187
Watterson GA (1975) On the number of segregating sites in genetical models
without recombination. Theoretical Population Biology 7: 256-276.
Wayne RK, Nash WG, O´Brien SJ, 1987. Chromossome Evolution of the Canidae
- II Divergence from the Primitive Carnivore Karyotipe. Cytogenetics and Cell
Genetics, 44:134-141.
Wayne RK (1996) Conservation genetics in the Canidae. In Avise JC and Hamrick
JL (eds) Conservation Genetics., Chapman & Hall, New York, pp. 75-113.
Wayne RK (1993) Molecular Evolution of the Dog Family. Trends in Genetic and
Evolution 6: 218-224.
Wayne RK, Geffen E, Girman DJ, Koepfli KP, Lau LM, Marshall CR (1997)
Molecular Systematics of the Canidae. Systematic Biology 46:622– 653.
Wilson DE e Reeder DM (1993) Mammal species of the world: a taxonomic and
geographic reference, 2
nd
. Smithsonian Institution Press, Washington DC, 543pp.
Withmore TC e Prance GT (1987) Biogegraphy and Quaternary History in Tropical
America. Oxford University Press, New York, 150pp.
Wozencraft WC, 1993. Order Carnivora. In Wilson DE and Reeder DM (eds)
Mammals Species of the World. London Smithsonian Institution Press, London,
1207pp.
Wozencraft WC, 2005. Order Carnivora. In Wilson DE and Reeder DM (eds)
Mammals Species of the World. London Smithsonian Institution Press, London,
1100pp.
Yahnke CJ, Johnson WE, Geffen E, Smith D, Hertel F, Roy MS, Bonacic CF,
Fuller TK, Van Valkenburgh B and Wayne RK (1996) Darwin’s fox: a distinct
endangered species in a vanishing habitat. Conservation Biology 10:366–375.
Zhang DX e Hewitt GM (2003) Nuclear DNA analyses in genetic studies of
populations: practice, problems and prospects. Molecular Ecology 12: 563–584.
Zrzávy J e Ricánková V (2004) Phylogeny of Recent Canidae
(Mammalia,Carnivora): relative reliability and utility of morphological and molecular
datasets. Zoologica Scripta 33: 311-333.
Zunino G, Vaccaro O, Canevari M, Gardner A (1995) Taxonomy of the Genus
Lycalopex (Carnivora, Canidae) in Argentina. Proceedings of Biological Society of
Washington 108: 729-747.
Livros Grátis
( http://www.livrosgratis.com.br )
Milhares de Livros para Download:
Baixar livros de Administração
Baixar livros de Agronomia
Baixar livros de Arquitetura
Baixar livros de Artes
Baixar livros de Astronomia
Baixar livros de Biologia Geral
Baixar livros de Ciência da Computação
Baixar livros de Ciência da Informação
Baixar livros de Ciência Política
Baixar livros de Ciências da Saúde
Baixar livros de Comunicação
Baixar livros do Conselho Nacional de Educação - CNE
Baixar livros de Defesa civil
Baixar livros de Direito
Baixar livros de Direitos humanos
Baixar livros de Economia
Baixar livros de Economia Doméstica
Baixar livros de Educação
Baixar livros de Educação - Trânsito
Baixar livros de Educação Física
Baixar livros de Engenharia Aeroespacial
Baixar livros de Farmácia
Baixar livros de Filosofia
Baixar livros de Física
Baixar livros de Geociências
Baixar livros de Geografia
Baixar livros de História
Baixar livros de Línguas
Baixar livros de Literatura
Baixar livros de Literatura de Cordel
Baixar livros de Literatura Infantil
Baixar livros de Matemática
Baixar livros de Medicina
Baixar livros de Medicina Veterinária
Baixar livros de Meio Ambiente
Baixar livros de Meteorologia
Baixar Monografias e TCC
Baixar livros Multidisciplinar
Baixar livros de Música
Baixar livros de Psicologia
Baixar livros de Química
Baixar livros de Saúde Coletiva
Baixar livros de Serviço Social
Baixar livros de Sociologia
Baixar livros de Teologia
Baixar livros de Trabalho
Baixar livros de Turismo
