Programa de Pós-Graduação em Genética, Conservação e ... · allowed the Great American Biotic...
Transcript of Programa de Pós-Graduação em Genética, Conservação e ... · allowed the Great American Biotic...
Instituto Nacional de Pesquisas da Amazônia – INPA
Programa de Pós-Graduação em Genética, Conservação
e Biologia Evolutiva
Filogenia e biogeografia de três famílias de aves do
Neotrópico
Mateus Ferreira
Manaus, Amazonas
Março, 2018
Mateus Ferreira
Filogenia e biogeografia de três famílias de aves do
Neotrópico
Orientador: Dra. Camila Cherem Ribas
Tese apresentada ao Instituto Nacional de
Pesquisas da Amazônia como requisito para
obtenção do grau de doutor em Genética,
Conservação e Biologia Evolutiva.
Manaus, Amazonas
Março, 2018
3
ii
iii
F383 Ferreira, Mateus
Filogenia e biogeografia de três famílias de aves do
Neotrópico / Mateus Ferreira. --- Manaus: [sem editor],
2018.
121 f. : il. color.
Tese (Doutorado) --- INPA, Manaus, 2018. Orientadora : Camila Cherem Ribas. Programa : Genética, Conservação e Biologia
Evolutiva.
1. Biogeografia. 2. Genômica. 3. Aves neotropicais. I.
Título.
CDD 598.7
Sinopse:
Neste trabalho foram realizados estudos sobre a relação
filogenética entre todas as espécies de três famílias de aves do
Neotrópico. Abordamos aspectos sobre a distribuição geográfica
das linhagens genéticas encontradas, conflitos entre os diferentes
marcadores genéticos e a subestimação da diversidade
taxonômica dos táxons estudados.
Palavras-chave: Bucconidae, Galbulidae, Trogonidae, Pantropical,
genômica, filogeografia, UCE
iv
Agradecimentos
Agradeço primeiramente a minha orientadora Camila Ribas, pela paciência e confiança
que depositou em mim durante esses anos de orientação. Sem sombra de dúvidas, esse trabalho
não seria possível sem essa amizade e parceria.
Ao meu co-orientador, Joel Cracraft, com quem tive a sorte de trabalhar durante o meu
doutorado sanduíche. Pelas excelentes conversas e orientações sobre biogeografia e sobre os
padrões e processos que moldaram a diversidade de aves no mundo.
À Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) e ao
programa de Pós-Graduação em Genética, Conservação e Biologia Evolutiva, do Instituto
Nacional de Pesquisas da Amazônia, pela concessão da bolsa de doutorado no país e bolsa
sanduíche (# 88881.133440/2016-01), que tornaram este projeto possível.
Aos curadores e responsáveis pelas coleções científicas que gentilmente cederam
material para que este trabalho fosse desenvolvido: Alexandre Aleixo, Fátima Lima e Antonita
Santana (MPEG); Marlene Freitas (INPA); Nate Rice (ANSP), Cristina Miyaki (LGEMA),
Donna Dittman e Robb Brumfield (LSU), Paul Sweet e Tom Trombone (AMNH), Mark
Robbins (KU), John Bates e Ben Marks (FMNH), Brian K. Schmidt (USNM), Sharon Birks
(UWBM). E, a todas as pessoas envolvidas nas expedições de coleta dessas institutições.
Ao projeto “Dimensions US-Biota: Assembly and evolution of the Amazon biota and
its environment: an integrated approach”, um projeto financiado conjuntamente pela Fundação
de Amparo à Pesquisa de São Paulo (FAPESP #2012/50260-6) e pelo National Science
Fundation (NSF DEB 1241056). Cujo apoio e financiamento foram essenciais para a execução
das várias etapas desse doutorado.
A todos os colegas do EBBA, pela constante ajuda e pelas excelentes discussões e
incentivos, e pelo café, especialmente pelos cafés: Robs, Fernanda, Rafael, Claudinha, Érico,
Erik, Lídia, Renatinha, Jessica, Nelson, Carol, Waleskinha e todo mundo que passou por aqui.
Ao pessoal que me aguentou durante esse doutorado: Mariana Tolentino, Leandro, Marina
Maximiano, Ana, Marizita (Marina Carmona) Derek, Miquéias, Pedro, Cadu e Manu. Em
especial à Romina, pela caminhada lado a lado durante toda a execução desse projeto, pelos
puxões de orelha quando eu precisei e por ter me aguentado todo esse período.
Ao pessoal do LTBM, Giselle e Paula, pela excelente companhia, pelos cafés e ajudas
quando precisei.
v
To everyone who received me at the AMNH during my sandwich fellowship: Lydia,
Bill, Tom, Paul, Gabi, Brian, Luke, and Peter. A special thanks to Jessica and Laís for all the
support and friendship during my time in NY.
Também gostaria de agradecer ao Laboratório Nacional de Computação Científica
(LNCC/MCTI) por fornecer recursos de computação de alto desempenho através do
supercomputador SDumont, fundamentais para as análises realizadas neste estudo.
Por fim, um agradecimento especial para a minha família, que me apoiou
incondicionalmente em todo esse percurso, e cuja ajuda foi essencial para a finalização deste
doutorado.
vi
“Nothing in biology makes sense except in the light of evolution”
Theodosius Dobzhansky
“Life and Earth evolve together”
Leon Croizat
vii
Resumo
O Neotrópico é uma das regiões com os maiores índices de biodiversidade do planeta e muito
tem se questionado sobre a origem de tamanha diversidade. Acredita-se que os padrões de
diversidade atual dentro da região sejam um resultado da complexa história geomorfológica e
climática da região. Entre os eventos geomorfológicos mais discutidos estão o soerguimento
dos Andes e consequente reestruturação da drenagem continental, e o fechamento do Istmo do
Panamá, que permitiu a troca intercontinental de biotas. Neste trabalho foram selecionadas três
famílias de aves do Neotrópico. A família Trogonidae tem uma distribuição Pantropical,
ocorrendo também nas regiões subtropicais e tropicais da África e Ásia, no entanto, a maior
diversidade encontra-se justamente na região Neotropical. As famílias Bucconidae e Galbulidae
são duas famílias irmãs endêmicas do Neotrópico. Foram selecionadas amostras de todas as
espécies e quase todas as subespécies descritas para os três grupos. Para as espécies amplamente
distribuídas foram selecionadas amostras ao longo de toda a distribuição e uma análise prévia
para verificar a estrutura filogeográfica de cada grupo, com base nesses resultados, foram
selecionadas amostras para o sequenciamento de milhares de loci de regiões Ultra Conservadas
(Ultraconserved Elements, UCE). Dessa forma, compilamos três estudos nessa tese. No
primeiro capítulo, foi estudado um complexo de aves da família Galbulidae associada aos
ambientes de areia branca na região Amazônica. Através da comparação entre marcadores
moleculares com diferentes métodos de herança, DNA mitocondrial e nuclear (UCE), pudemos
observar um conflito entre esses dois marcadores. Através deste conflito foi possível propor um
modelo de diversificação para os ambientes de areia branca na região. No segundo capítulo
analisamos a diversificação global da família Trogonidae, com o auxílio dos UCEs
reconstruímos a relação filogenética entre todas as espécies da família e estimamos uma árvore
datada da diversificação de Trogonidae. No terceiro e último capítulo, analisamos os padrões
de diversificação das famílias Galbulidae e Bucconidae através de uma abordagem
filogeográfica e filogenética. Neste trabalho pudemos observar que a diversidade do grupo se
encontra claramente subestimada.
viii
Abstract
The Neotropical region has one of the highest biodiversity index in the planet and several
hypotheses have been proposed to explain the origin of such diversity. Currently, landscape
and climatic evolution are credited to be the two main processes responsible for shaping the
patterns. Landscape evolution includes, for example, the Andean uplift and consequent
continental drainage reconfiguration, and the closure of the Isthmus of Panama, which
allowed the Great American Biotic Interchange. In the present study we selected three
Neotropical families of birds. Trogonidae has a Pantropical distribution, members of this
family inhabit tropical and subtropical regions of Africa, Asia, however, the highest diversity
is currently found in the Americas. Galbulidae and Bucconidae are sister families and
endemics to the Neotropics. WE sampled all species and almost all subspecies currently
recognized for this three families, and for widespread species we thoroughly sampled
throughout their distributions to uncover hidden phylogeographic patterns. Based on these
results, we selected the samples to sequence thousands of Ultraconserved Elements (UCE).
Thus, we compiled three studies for this thesis. In the first chapter, we studied one Galbulidae
species complex associated with the Amazonian White-sand environments. We compared
between molecular markers that have different heritage systems, the mtDNA and nuDNA
(UCE), where we recovered contrasting histories between markers, and based on these results
we proposed a diversification model for the White-sand environments. In the second chapter,
we analyzed the global diversification of Trogonidae, employing thousands of UCE loci to
propose a phylogenetic hypothesis between all species currently recognized, and we also
estimated a fossil calibrated time tree for Trogonidae diversification. At last, in the third
chapter, we analyzed the diversification patterns for Galbulidae and Bucconidae using a
phylogeographic/phylogenetic approach. In this chapter it was clear how these groups
diversity in underestimated by currently taxonomic approach.
ix
Sumário
Agradecimentos ....................................................................................................................... iv
Resumo .................................................................................................................................... vii
Abstract .................................................................................................................................. viii
Introdução Geral ...................................................................................................................... 1
Objetivos .................................................................................................................................... 7
Capítulo 1 .................................................................................................................................. 8
Abstract ............................................................................................................................................................ 10
1. Introduction ............................................................................................................................................. 11
2. Methods ................................................................................................................................................... 13
2.1. Taxon sampling ................................................................................................................................ 13
2.2. DNA extraction, amplification and sequencing ............................................................................... 13
2.3. Phylogenetic analysis and haplotype networks ............................................................................... 14
3. Results ...................................................................................................................................................... 16
3.1. Sanger sequencing and haplotype networks ................................................................................... 16
3.2. mtDNA genome and time tree ......................................................................................................... 17
3.3. UCE sequencing, supermatrix analysis and Species trees ................................................................ 17
4. Discussion ................................................................................................................................................ 18
4.1. mtDNA and nuDNA incongruence ................................................................................................... 18
4.2. Biogeography of WSE avifauna ....................................................................................................... 21
4.3. Evolution in the White-sand ecosystems ......................................................................................... 22
5. Conclusion ................................................................................................................................................ 24
Acknowledgements .......................................................................................................................................... 24
Funding ............................................................................................................................................................. 25
References ........................................................................................................................................................ 25
Capítulo 2 ................................................................................................................................ 37
Abstract ............................................................................................................................................................ 39
Introduction ..................................................................................................................................................... 40
Results .............................................................................................................................................................. 42
UCE sequencing .......................................................................................................................................... 42
Phylogenetic inference ................................................................................................................................ 42
Time-calibrated tree ................................................................................................................................... 43
Discussion......................................................................................................................................................... 43
Phylogenomic contribution to the reconstruction of Trogonidae diversification .................................. 43
Diversification and biogeography of Trogons .......................................................................................... 44
Africa and Asia diversification .................................................................................................................. 46
Neotropical diversification ......................................................................................................................... 47
Conclusion ....................................................................................................................................................... 49
Materials and Methods ................................................................................................................................... 49
x
Taxon sampling and DNA extraction ........................................................................................................ 49
UCE and exons assembly ........................................................................................................................... 50
Phylogenetic relationships and species tree analysis................................................................................ 50
Dating analysis ............................................................................................................................................ 51
Acknowledgements.......................................................................................................................................... 51
References ........................................................................................................................................................ 52
Capítulo 3 ................................................................................................................................ 66
Abstract ............................................................................................................................................................ 67
Introduction ..................................................................................................................................................... 68
Material and Methods .................................................................................................................................... 70
Sampling and DNA isolation ........................................................................................................................ 70
Phylogeographic structure and UCE sampling ............................................................................................ 71
UCE assembly ............................................................................................................................................... 71
Phylogenetic relationship ............................................................................................................................. 72
Results .............................................................................................................................................................. 72
Phylogeographic results ............................................................................................................................... 72
UCE sequencing ........................................................................................................................................... 73
Phylogenetic results ...................................................................................................................................... 73
Discussion......................................................................................................................................................... 74
Phylogenetic results ...................................................................................................................................... 74
Galbulidae systematics ................................................................................................................................. 75
Conclusion ....................................................................................................................................................... 83
Acknowledgements.......................................................................................................................................... 83
References ........................................................................................................................................................ 84
Síntese Geral ......................................................................................................................... 102
Referências Bibliográficas ................................................................................................... 103
1
Introdução Geral
O Neotrópico é uma das regiões biogeográficas com uma das maiores biodiversidades
do mundo (Jetz et al., 2012; Holt et al., 2013), mesmo que uma grande parcela dessa diversidade
ainda seja desconhecida (Kier et al., 2005; Hopkins, 2007; Barrowclough et al., 2016). Na
região Neotropical, os biomas Mata Atlântica, Cerrado e Amazônia despontam como hotspots
de biodiversidade altamente ameaçados pela ação humana (Myers et al., 2000; Mittermeier et
al., 2003; Colombo e Joly, 2010). Em especial para a região Amazônica, que abrange mais de
40% da área total do Neotrópico, desde que Wallace (1852), fez suas primeiras observações
sobre a importância dos rios na delimitação da distribuição de diferentes espécies de primatas,
vários trabalhos foram realizados demonstrando a importância dos afluentes do rio Amazonas
na estruturação da diversidade alfa da região (Vanzolini e Willians, 1970; Cracraft, 1985;
Haffer, 1985; Ávila-Pires, 1995). A comparação e aparente congruência dos padrões de
distribuição geográfica permitiu a elaboração de algumas hipóteses sobre quais processos
poderiam ter dado origem a esses padrões (revisões em Haffer (1997) e Leite e Rogers (2013)),
incluindo as variações climáticas do Pleistoceno, em especial o Último Máximo Glacial (LGM
– Last Glacial Maximum, ca. 20.000 anos) (Haffer, 1969; Brown et al., 1974); a influência das
incursões marinhas (Nores, 1999; 2004); e a formação dos rios da bacia Amazônica (Bates et
al., 2004; Ribas et al., 2012). Com o advento da filogeografia (Avise et al., 1987; Avise, 2009)
e técnicas de datação molecular (Bromham e Penny, 2003; Bromham et al., 2017) novas teorias
foram propostas e além da congruência entra a distribuição geográfica o tempo de
diversificação também passou a fazer parte da comparações (Donoghue e Moore, 2003). Como
consequência, a teoria dos refúgios associados aos eventos climáticos do LGM foi parcialmente
rejeitada, já que as espécies se mostraram mais antigas que os ciclos glaciais mais recentes
(Colinvaux et al., 2000; Bush e Oliveira, 2006). As incursões marinhas, por outro lado, seriam
muito antigas para explicar a origem das espécies (Hoorn, 1993), favorecendo o modelo da
hipótese dos rios como barreira.
Atualmente, no entanto, o que sabemos sobre a complexidade da diversidade Amazônica
sugere que mais de um processo está por trás de sua origem (Bush, 1995; Bates et al., 2008;
Smith et al., 2014). Todos os eventos que moldaram a paisagem do Neotrópico ao longo do
tempo podem ter influenciado a diversificação da biota, por exemplo: A) o fim do “isolamento
2
esplêndido” (Simpson, 1980; Dacosta e Klicka, 2008) após o estabelecimento do Istmo do
Panamá (Haug e Tiedeman, 1998; Coates e Stallard, 2013; Lessios, 2015; Odea et al., 2016).
B) O soerguimento da cadeia de montanha dos Andes (Garzione et al., 2008; Hoorn et al., 2010;
Horton, 2018), que influenciou drasticamente não só a drenagem da bacia Amazônica (Hoorn
e Wesselingh, 2010; Latrubesse et al., 2010; Shephard et al., 2010; Nogueira et al., 2013; Hoorn
et al., 2017), como também o clima de todo o continente (Hartley, 2003; Ehlers e Poulsen,
2009; Insel et al., 2009). C) A influência das flutuações climáticas do Pleistoceno também
voltou a fazer parte das discussões, especialmente com relação ao estabelecimento de diferentes
regimes de precipitação dentro do continente (Cheng et al., 2013; Wang et al., 2017).
Dessa forma, faz-se necessário investigar não somente a evolução do modelo através das
variáveis biológicas, mas também quais processos físicos podem ter influenciado a sua
diversificação (Baker et al., 2014). Por exemplo, o estabelecimento do atual curso
transcontinental do rio Amazonas, ainda bastante discutido na literatura, varia entre o final do
Mioceno (10 – 7 Ma) (Hoorn e Wesselingh, 2010; Hoorn et al., 2017), início do Plioceno (~5
Ma) (Latrubesse et al., 2010), ou ainda, durante o Pleistoceno (2,5 Ma) (Nogueira et al., 2013;
Rossetti et al., 2015). Nesse sentido, estudando um gênero de aves (Psophiidae: Psophia) que
é restrita aos ambientes de terra-firme, e dessa forma suscetível às mudanças na configuração
drenagem, Ribas et al. (2012) propuseram um modelo de diversificação da fauna de terra firme
ao correlacionar os eventos de diversificação das espécies do gênero ao estabelecimento de
barreiras associadas aos principais afluentes da bacia, favorecendo o modelo do
estabelecimento do rio Amazonas durante o Pleistoceno. O modelo proposto por Ribas et al.
(2012) sugere que para compreender os fatores que influenciaram a evolução da paisagem,
como o efeito da formação de um determinado rio na diversificação de espécies de terra-firme,
deve-se buscar padrões congruentes, temporais e espaciais, de diversificação em grupos que
serão de fato afetados diretamente pela barreira (e.g. Polo, (2015)). Em contraponto, análises
que buscam explicar a diversificação na Amazônia através de um único processo, como por
exemplo, a importância dos rios como barreira utilizando uma ampla gama de táxons com
nichos variados (Oliveira et al., 2017; Santorelli et al., 2018; Smith et al., 2014) tendem a
refutar esta teoria, já que diferentes organismos respondem de diferentes maneiras aos
processos e eventos históricos. Dessa forma, aceitando que a diversificação na Amazônia é
inerentemente complexa, o teste de hipóteses deve ser feito de maneira dirigida, ou seja, deve-
se buscar grupos taxonômicos que tenham sido potencialmente influenciados pelas barreiras
em questão. Só assim será possível estabelecer a importância biológica de um determinado
3
evento e gerar dados importantes para o estabelecimento dos modelos de evolução
geomorfológica da região (Baker et al., 2014).
Essa iluminação recíproca entre os processos físicos e bióticos, no entanto, só é possível
levando em consideração o fato de que qualquer evento de diversificação só pode ser
correlacionado com um evento biogeográfico se duas condições forem respeitadas: 1) as
unidades biológicas utilizadas devem ser comparáveis entre si e devem representar linhagens
com uma história evolutiva única; 2) a relação filogenética entre essas linhagens deve
representar de fato a história de diversificação do grupo.
A primeira condição refere-se ao fato de que as unidades utilizadas no estudo devem
representar linhagens independentes. Geralmente, entende-se que espécies devem ser a unidade
básica para qualquer estudo de ecologia, evolução, ou biogeografia, no entanto, essa prática
pode ser particularmente problemática na Amazônia, uma vez que grande parte das espécies
amplamente distribuídas pela região na realidade representam um complexo de linhagens
evolutivas independentes (Ribas et al., 2012; D’horta et al., 2013; Fernandes et al., 2013;
Fernandes et al., 2014; Hrbek et al., 2014; Boubli et al., 2015; Thom e Aleixo, 2015; Byrne et
al., 2016; Carneiro et al., 2016; Boubli et al., 2017; Ferreira et al., 2017; Lima et al., 2017;
Ribas et al., 2018). Para aves, em particular, esse déficit entre a taxonomia atualmente
reconhecida e a real diversidade está diretamente relacionado ao fato de que a definição daquilo
que reconhecemos como espécie ainda é muito influenciado pelo tipo de conceito de espécie
utilizado, em especial o conceito biológico de espécie (Mayr, 1942), que implica no
reconhecimento de metapopulações isoladas reprodutivamente. No entanto, o reconhecimento
de isolamento reprodutivo em populações naturais é particularmente difícil, especialmente em
populações alopátricas, onde é impossível observar naturalmente esse contato. Mesmo em
populações parapátricas, o contato e estabelecimento de uma zona híbrida não necessariamente
ameaça o statu quo das espécies envolvidas (Weir et al., 2015). Especialmente, porque a
capacidade de hibridização entre espécies, mesmo distantes, parece ser uma característica
sinapomórfica para aves (Grant e Grant, 1992; Gill, 1998; Harrison e Larson, 2014).
O conceito de espécie, mesmo sendo um dos assunto centrais para os estudo de evolução
e ecologia, permanece ainda sem definição clara e é sem dúvida um dos pontos mais discutidos
dentro da biologia (Mayr, 1976; Donoghue, 1985; Isaac et al., 2004; De Queiroz, 2005; Aleixo,
2007; Joseph et al., 2008; Aleixo, 2009; De Queiroz, 2011; Cellinese et al., 2012; De Queiroz,
2012; Willis, 2017). Ressaltando o impacto dessa escolha entre um conceito ou outro e do nosso
atual conhecimento sobre a taxonomia de aves, um estudo recente demonstrou que a diversidade
4
das aves é, pelo menos, duas vezes maior do que a atualmente reconhecida (Barrowclough et
al., 2016). Por exemplo, dentro da Neotrópico, um dos padrões mais observados é a existência
de espécies amplamente distribuídas, compostas por diferentes subespécies morfologicamente
distintas e geograficamente estruturadas, as quais foram, no entanto, agrupadas dentro de uma
mesma espécie devido a existência da possibilidade dessas populações hibridizarem caso
entrem em contato.
A segunda condição está relacionada aos problemas de conflitos entre a história de um
único gene e a história da espécie (Degnan e Rosenberg, 2009; Knowles, 2009). Esse conflito
tem se tornado cada vez mais evidente em face do desenvolvimento de técnicas de
sequenciamento massivo em paralelo (Metzker, 2010). Apesar de estarem se tornando mais
acessíveis, o sequenciamento e análise do genoma completo para organismos não modelo ainda
é impraticável para trabalhos que requerem amostragem de muitos indivíduos. Dessa forma,
algumas técnicas de se utilizar representações reduzidas foram desenvolvidas. Duas abordagens
dominam o cenário atualmente, uma delas é a utilização de enzimas de restrição para sítios
específicos ao longo de todo o genoma, denominada RAD-seq (restriction-site-associated DNA
sequencing) (Davey et al., 2011); e a outra é a utilização de sondas de RNA desenvolvidas para
capturar regiões específicas do genoma (Grover et al., 2012; Lemmon et al., 2012; Lemmon e
Lemmon, 2013). Uma das abordagens de sequenciamento de captura é a técnica que utiliza
sondas específicas para regiões do genoma ultra conservadas (do inglês, Ultra Conserved
Elements, UCE) (Faircloth et al., 2012). Essas regiões ultra conservadas foram selecionadas
pois permitem a utilização de um mesmo conjunto de sondas para realizar estudos em diversos
níveis taxonômicos, pois apesar das regiões centrais serem altamente conservadas, as regiões
flanqueadoras possuem variação suficiente tanto para recuperar relações mais antigas
(Mccormack et al., 2012; Crawford et al., 2015; Faircloth et al., 2015), quanto mais recentes
(Bryson et al., 2016; Manthey et al., 2016), inclusive utilizadas em radiações adaptativas
(Meiklejohn et al., 2016), onde altos níveis de separação incompleta de linhagens (do inglês,
Incomplete Lineage Sorting, ILS) sejam esperados (Degnan e Rosenberg, 2006; Oliver, 2013).
De modo a tentar então lançar alguma luz sobre os possíveis eventos que moldaram a
diversificação da biota Neotropical, foram selecionadas três famílias de aves: Trogonidae,
Galbulidae e Bucconidae. As três famílias possuem representantes por toda a região
Neotropical, incluindo várias espécies, ou grupo de espécies, amplamente distribuídas. A
família Trogonidae tem distribuição Pantropical, estando ausente apenas da região Australiana.
Representantes dessa família, popularmente conhecidos como surucuás, são aves de médio
5
porte e sua dieta varia entre insetívora e onívora, apresentam plumagem com coloração bastante
chamativa, e são reconhecidas por serem más dispersoras, não sendo capazes de realizar voos
de longa distância (Collar, 2017). Apesar de apresentarem plumagem bastante distinta, a
morfologia interna da família é bastante conservada e a sua monofilia nunca foi questionada
(Livezey e Zusi, 2007; Collar, 2017). No entanto, a relação entre trogonídeos e outras aves não
passeriformes já foi bastante controversa (Cracraft, 1981; Maurer e Raikow, 1981; Monteros,
2000; Mayr, 2003; Livezey e Zusi, 2006). Atualmente, aceita-se que a família seja uma das
primeiras linhagens a diversificar dentro da radiação de Coracimorphae sendo grupo irmão de
todas as outras famílias do grupo Core Landbirds (Jarvis et al., 2015; Prum et al., 2015).
Atualmente são reconhecidas 45 espécies (Collar, 2017; Gill e Donsker, 2018; Ramsen et al.,
2018) distribuídas em sete gêneros. A região Neotropical contém a maior diversidade da
família, com quatro gêneros e cerca de 30 espécies. A região Asiática contém dois gêneros e 12
espécies, e por último, a região Africana, possui um gênero com três espécies. Apesar da maior
diversidade da família ser encontrada no Neotrópico, a existência de fósseis na Europa (Mayr,
1999; Kristoffersen, 2002; Mayr, 2005) sugere uma origem no Paleártico e posterior dispersão
e colonização da distribuição atual. Diversos trabalhos já tentaram abordar a relação
filogenética entre os representantes da família (Monteros, 1998; Johansson e Ericson, 2005;
Moyle, 2005; Dacosta e Klicka, 2008; Ornelas et al., 2009; Hosner et al., 2010), entretanto,
nenhum foi capaz de resolver a relação entre os gêneros. O último trabalho publicado (Hosner
et al., 2010), e o único a incluir representantes de todos os gêneros, recuperou uma parafilia
entre regiões geográficas, sugerindo um cenário biogeográfico bem mais complexo, em que a
região Neotropical, por exemplo, tenha sido ocupada por pelo menos três linhagens distintas.
As famílias Galbulidae e Bucconidae formam um clado já bem estabelecido, tanto com
caracteres morfológicos (Livezey e Zusi, 2007), quanto dados moleculares (Hackett et al., 2008;
Prum et al., 2015). Dentro da ordem Piciformes, são as únicas famílias com representantes com
distribuição exclusivamente neotropical, formando o grupo irmão das outras famílias de
Piciformes (Prum et al., 2015). A família Galbulidae é composta por aves de pequeno a médio
porte, asas arredondadas e um bico longo e afilado utilizado para capturar insetos durante o
voo. Possui 19 espécies distribuídas em cinco gêneros diferentes (Tobias, 2017; Gill e Donsker,
2018; Ramsen et al., 2018). As espécies da família são geralmente agrupadas em oito grupos
zoogeográficos, seis desses grupos representam complexos de espécies com distribuições
alopátricas ou parapátricas, e dois são espécies amplamente distribuídas (Collar, 2017). A
família Bucconidae também inclui aves de pequeno a médio porte, asas curtas e arredondadas,
6
tendo como característica uma cabeça relativamente grande, atualmente são reconhecidas 35
espécies para a família distribuídas em nove gêneros (Gill e Donsker, 2018; Ramsen et al.,
2018). Os trabalhos de filogeografia desenvolvidos com representantes da família Bucconidae
– Malacoptila (Ferreira et al., 2017), Monasa e Nonnula (Soares, 2016) e Nystalus (Duarte,
2015) – demonstraram que a diversidade reconhecida pela taxonomia tradicional para esses
grupos é subestimada, já que existem muito mais linhagens genéticas geograficamente isoladas
do que táxons reconhecidos, demonstrando a importância da condução dos estudos de
filogeografia para elucidar a delimitação taxônomica dessas espécies amplamente distribuídas.
Dessa forma, o presente trabalho tem por objetivo reconstruir a relação filogenética entre
todas as linhagens dessas três famílias de modo a reconstruir a história de diversificação desses
três grupos. Para tanto, foram amostrados indivíduos ao longo da distribuição de todas as
espécies amplamente distribuídas para uma análise prévia da estrutura genética de cada uma
dessas linhagens. Com base nos resultados obtidos previamente foram selecionadas amostras
representativas de cada um desses agrupamento, tentando incluir, sempre que possível, um
representante para cada um dos táxons reconhecidos. Para essas amostras foram sequenciados
mais de 2000 loci de UCE, e com base nessa representação reduzida do genoma foram
realizadas análises para a reconstrução filogenética dos grupos.
7
Objetivos
O objetivo geral foi investigar a história biogeográfica da região Neotropical com base
nas relações filogenéticas entre todos os táxons atualmente reconhecidos para as famílias
Trogonidae, Bucconidae e Galbulidae baseado em dados de sequenciamento genômico. Sendo
que para isso foi necessário:
Capítulo 1: revisar a taxonomia e compreender os processos de isolamento e fluxo
gênico em um contexto espacial;
Capítulo 2: compreender a origem de táxons Neotropicais em uma família amplamente
distribuída;
Capítulo 3: compreender a estrutura filogeográfica de espécies amplamente distribuídas
em duas famílias Neotropicais para com isso obter uma reconstrução filogenética representativa
da diversificação do grupo.
8
Capítulo 1
Ferreira, M.; Fernandes, A.M.; Aleixo, A.; Antonelli,
A.; Olsson, U.; Bates, J.M.; Cracraft, J.; Ribas, C.C.
Evidence for mtDNA capture in the jacamar Galbula
leucogastra / chalcothorax species-complex and
insights on the evolution of white-sand environments
in the Amazon basin. Molecular Phylogenetics and
Evolution (doi: 10.1016/j.ympev.2018.07.007)
9
Manuscript submission to Molecular Phylogenetics and Evolution Contribution type: Original article
Evidence for mtDNA capture in the jacamar Galbula leucogastra / chalcothorax species-complex and insights on the evolution of white-sand ecosystems in the Amazon basin. Ferreira, Mateus a*; Fernandes, Alexandre M. b; Aleixo, Alexandre c; Antonelli, Alexandre d,e,f,g; Olsson, Urban d,f; Bates, John M. h; Cracraft, Joel i; Ribas, Camila C. j a Programa de Pós-Graduação em Genética, Conservação e Biologia Evolutiva, INPA, Manaus, AM, Brazil b Unidade Acadêmica de Serra Talhada, UFRPE, Serra Talhada, PE, Brazil c Coordenação de Zoologia, Museu Paraense Emílio Goeldi, Belém, PA, Brazil d Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden e Gothenburg Botanical Garden, Gothenburg, Sweden f Gothenburg Global Biodiversity Centre, Gothenburg, Sweden g Harvard University, Department of Organismic and Evolutionary Biology, Cambridge, MA, USA. h Integrative Research Center, Field Museum of Natural History, Chicago, IL, USA i Department of Ornithology, American Museum of Natural History, New York, NY, USA j Coordenação de Biodiversidade, Instituto Nacional de Pesquisas da Amazônia, Manaus, AM, Brazil *Corresponding author Correspondence: Mateus Ferreira, Coordenação de Biodiversidade, Instituto Nacional de Pesquisas da Amazônia, CEP 69080-971, Manaus-AM, Brazil E-mail: [email protected]
10
Abstract
Jacamar species occur throughout Amazonia, with most species occupying forested habitats.
One species-complex, Galbula leucogastra / chalcothorax, is associated to white sand
ecosystems (WSE). Previous studies of WSE bird species recovered shallow genetic structure
in mtDNA coupled with signs of gene flow among WSE patches. Here, we characterize
diversification of the G. leucogastra/chalcothorax species-complex with dense sampling
across its distribution using mitochondrial and genomic (Ultraconserved Elements, UCEs)
DNA sequences. We performed concatenated likelihood and Bayesian analysis, as well as a
species-tree analysis using *BEAST, to establish the phylogenetic relationships among
populations. The mtDNA results recovered at least six geographically-structured lineages,
with G. chalcothorax embedded within lineages of G. leucogastra. In contrast, both
concatenated and species-tree analyses of UCE data recovered G. chalcothorax as sister to
all G. leucogastra lineages. We hypothesize that the mitochondrial genome of one of the G.
leucogastra lineage (Madeira) was captured into G. chalcothorax in the past. We discuss how
WSE evolution and the coevolution of mtDNA and nuclear genes might have played a role in
this apparently rare event.
Keywords: Amazonia, Galbulidae, jacamars, mtDNA capture, UCE, White-sand ecosystems
11
1. Introduction
White-sand ecosystems (WSE) represent a unique type of habitat within Amazonia,
covering an area of approximately 5% of the Amazon basin (Adeney et al., 2016). Contrasting
to the apparently continuous upland forest habitats found all over the basin, the WSE consist
of patches of differentiated habitats scattered across the landscape and isolated by the
forest matrix (Adeney et al., 2016). WSE comprise a continuum from open non-forested
habitats, such as campinas, with a predominance of grass and shrubland, to denser
vegetation, called campinaranas and varillales. In general, these communities grow on
nutrient poor and highly acidic soils, usually associated with quarzitic sand, even though
some clay and silt can also be found with varying amounts of organic matter (Adeney et al.,
2016). These complex environments, however, do not share a single history, since different
patches of WSE may have different geological origins (Prance and Schubart 1978; Frasier et
al., 2008). Podzolization, a natural process in which nutrients are leached away from the top
layers of soil, leaving only sand (Sauer et al., 2007), appears to be a principal cause of in loco
formation of the white-sand soils, especially in northeastern Amazonia (Nascimento et al.,
2004). In contrast, in central, northwestern, and southern Amazonia, white sand soils can be
found as fluvial deposits of ancient rivers (Roddaz et al., 2005), or abandoned ancient
paleochannels (Latrubesse, 2002; Cordeiro et al., 2016).
The insular characteristic of WSE intrigued researchers as to how the ecosystem and
its specialized biota evolved, how it responded to Pleistocene glacial cycles, and whether the
specialized biota is able to disperse through the surrounding forest matrix (Brown and
Benson, 1977; Anderson, 1981; Capurucho et al., 2013; Matos et al., 2016). Besides its
characteristic fragmentation, WSE are more physiologically stressful and challenging from an
ecological and evolutionary perspective, making them much more taxonomically selective,
with overall diversity being smaller when compared with adjacent forest areas (Borges,
2003; Fine et al., 2010; Laranjeiras et al., 2014; Adeney et al., 2016), although several new
species endemic to this habitat have recently been described (Whitney and Alonso, 1998,
2005; Alonso and Whitney, 2001; Cohn-Haft and Bravo, 2013; Cohn-Haft et al., 2013). Even
though the patches of WSE may have distinct geomorphological origins, the associated biota
presents varying degrees of association with WSE. While some plants have a loose
association with WSE (Fine and Baraloto, 2016), others are tighly associated with them, such
12
as species of Pagamea (Rubiaceae) (Vicentini, 2016). The same can be observed amongst
other organisms (Cohn-Haft, 2008; Vriesendorp et al., 2006), such as birds (Borges et al.,
2016a; Borges et al., 2016b). Therefore, considering the distinct geomorphological
characteristics of WSE and the association of the biota with these environments, recent
climatic and landscape changes must have had an important influence on the evolution and
distribution of WSE and their associated biota (Capurucho et al., 2013).
The few phylogeographic studies of WSE birds that have been undertaken, show
little genetic diversity with no geographic structure throughout Amazonia (Green-tailed
Goldthroat, Polytmus theresiae, Matos et al., 2016); or shallow but geographically structured
genetic diversity, with significant migration rates between some populations (Red-
shouldered Tanager, Tachyphonus phoenicius, Matos et al., 2016; Black Manakin, Xenopipo
atronitens, Capurucho et al., 2013). In general, results obtained so far for WSE birds suggest
that: (1) black-water flooded forest (igapó), due to similarities to WSE in vegetation
structure, may facilitate dispersal between isolated WSE patches; and, (2) Pleistocene glacial
periods, especially the Last Glacial Maximum, are temporally correlated with geographical
expansion of populations of species specialized in WSE.
These studies have been based on mtDNA markers (Capurucho et al., 2013), or on a
combination of mtDNA and a single nuclear marker (Matos et al., 2016). Until recently, most
phylogeographic studies have employed mtDNA. Its characteristic maternal inheritance,
comparatively small effective population size, rapid rate of mutation, and lack of
recombination, have long made mtDNA markers ideal for phylogeographic studies (Avise et
al., 1987; Avise, 2009), in contrast to single or few nuclear markers which usually provide
very little phylogenetic information. However, there are potential biases and limitations
associated with mtDNA (Zink and Barrowclough, 2008), including the potentital to overlook
hybridization and introgression (Carling and Brumfield, 2008). The use of large quantities of
nuclear markers has become the alternative to overcome these problems. One such strategy
has been the use of probes for Ultraconserved Elements (Faircloth et al., 2012; McCormack
et al., 2013) to sample homologous genomic regions across individuals (Faircloth et al.,
2012). These markers have so far been successfully used to study both very old radiations
(Moyle et al., 2016), and recent ones (Smith et al., 2014; Harvey et al., 2016; Manthey et al.,
2016).
13
Here, we investigate the diversification of a jacamar species-complex specialized in
WSE using genomic data. The jacamars (family Galbulidae) occur exclusively in the
Neotropics, with 19 species and 5 genera, mostly associated with wooded, lowland forest
habitats (Stotz et al., 1996; Tobias, 2017). In Amazonia, most species are restricted to upland
(terra firme) and flooded (varzea and igapó) forests, with only two species (Bronzy Jacamar,
Galbula leucogastra and Purplish Jacamar, G. chalcothorax) known to occur in WSE (Borges
et al., 2016a). Galbula leucogastra and G. chalcothorax were previously considered
subspecies of a single species (Peters, 1948; Haffer, 1974), but were split by Parker and
Remsen (1987), based on diagnostic plumage and size differences. A phylogeny of the family,
based on multiple gene regions, indicates that G. leucogastra and G. chalcothorax are sister-
species with high support (Witt, 2004). Here we first investigate the distribution of mtDNA
diversity within these two species by sampling individuals from throughout their
distributions. Then, based on these results, we gathered sequences of thousands of genomic
markers (UCE) for a subset of samples to reconstruct their history of diversification and
make inferences about the evolution of WSE.
2. Methods
2.1. Taxon sampling
We sampled 35 individuals covering almost the entire distribution of the Galbula
leucogastra / chalcothorax complex (Table S1). As outgroups, we used one sample of Yellow-
billed Jacamar G. albicollis (Witt, 2004). All tissues sequenced are represented by voucher
specimens deposited in ornithological collections (Table S1).
2.2. DNA extraction, amplification and sequencing
DNA was extracted using a modified phenol-chloroform protocol (Sambrook and
Russel, 2001). We used published DNA primers (Sorenson et al., 1999) to amplify and
sequence two mitochondrial genes (Cytochrome b [cytb], and NADH subunit 2 [ND2]) for all
individuals following standard PCR protocols. For a subset of individuals (see below) we
extracted DNA using the DNeasy kit (Qiagen Inc.) following the manufacturer’s protocol, and
sent the extracts to RapidGenomics® (Gainsville, FL) for sequencing, using a probe set
targeting 2321 loci of Ultra Conserved Elements (UCE) plus 98 conserved exons from genes
that were previously used in phylogenetic analysis (Harvey et al., 2017). Some of the exons
14
used were flanked by introns, which are more variable, and were the focus of this capture.
More information about the capture and sequencing of UCE loci can be found in Faircloth et
al. (2012).
2.3. Phylogenetic analysis and haplotype networks
Phylogenetic analysis of the mtDNA genes using the complete dataset (cytb and
ND2, N=35) was performed using Bayesian Inference (BI) implemented in MrBayes 3.2.6
(Ronquist et al., 2012). Both genes were concatenated and the best partition scheme and
substitution model were selected by PartitionFinder 2.1.1 using the Bayesian Information
Criteria (BIC) (Lanfear et al., 2016). We partitioned the genes by codon position, considering
possible saturation in the codon’s third position. Four parallel simultaneous runs were
performed, for a total of 4x107 generations, with trees sampled every 1000 generations. We
discarded the first 10% of trees as burn-in after checking the ESS values of each run in Tracer
1.6 (Rambaut et al., 2014). We used TCS v1.21 (Clement et al., 2000) to reconstruct
haplotype networks.
2.3.1. UCE and exons assembly and supermatrix approach
Based on the results of the mtDNA, we selected eight samples for UCE sequencing
(Table 1). The raw data received from Rapid Genomics were processed using the Phyluce
script pack (Faircloth 2016). Sequences with adapter contamination, and those of low-
quality, were trimmed using illumiprocessor (Faircloth, 2013) and Trimmomatic (Bolger et
al., 2014). After the sequences were ‘cleaned’ we employed Trinity RNASeq assembler
r201331110 (Grabherr et al., 2011) to assemble the contigs using a de novo method. The
contigs were then compared with the UCE database to identify which UCE loci were
sequenced. Since Trinity does not recover information on heterozygote loci we performed a
second round of assembly using the contigs that were identified as a reference to map the
clean reads back to it using the Bowtie2 (Langmead et al., 2009; Langmead and Salzberg
2012) plugin in Geneious R7.1 (Kearse et al., 2012). The consensus sequence of each
individual, derived from the reads, mapped back to each reference, was called using a
threshold of 75% with a depth of at least 5 reads. We then aligned each locus using MAFFT
(Katoh and Standley, 2013) with default options, and prepared the input matrix for the
subsequent analysis. To infer the phylogenetic relationship among all samples we
concatenated all the UCE loci and employed RAxML v8.2 (Stamatakis, 2014) under a
15
Maximum Likelihood analysis. Since we recovered almost all UCE loci for each sample, we
only used loci that were shared among all samples, with the final matrix having 2271 loci.
This matrix was analyzed by running RAxML to search for the optimal tree, under the fast hill
climbing algorithm, and bootstraping was performed with the autoMRE algorithm in the
program.
The 98 exons targeted were from 47 different genes. Because some of the
sequences included intronic regions, which are prone to indels, de novo assembly was not an
option. Therefore, we mapped all the probes to the Paradise Jacamar (Galbula dea) genome
(B10K Project), identified the genes that were targeted, and then used the whole gene-
sequences to map the reads back following the same approach that we used for UCE loci.
2.3.2. Mitochondrial genome assembly and time tree
As a byproduct of the UCE sequencing we also recovered the complete mtDNA
genome. We mapped all the contigs, assembled by Trinity, from each specimen to two
reference mtDNA genomes from representatives of close related families, the Downy
Woodpecker, Dryobates pubescens (Aves, Picidae; GenBank: NC_027936.1), and the Ivory-
billed Araçari, Pteroglossus azara (Aves, Ramphastidae; GenBank: DQ780882.1, Prum et al.,
2015). After we identified the contigs from each individual we used those contigs to map
back the reads of that same specimen, again using Bowtie2 to check for coverage depth.
Incongruences found between reads and contigs were checked manually. The complete
mtDNA genomes were then aligned using MAFFT (Katoh and Standley, 2013) under default
options. The mtDNA genomes downloaded from GenBank were used to import annotations.
Coding regions were manually checked for codon translations and translated protein
sequences were compared to check for frame shifts and stop codons. We employed the
concatenated coding regions in BEAST 1.8.2 (Drummond et al., 2012) to estimate a time tree
calibrated with the cytochrome b mutational rate of 0.0105 (normal distribution, SD=0.0034)
substitution.lineage-1.million years-1 (Weir and Schluter, 2008). The best partition scheme
and substitution model were selected by PartitionFinder 2.1.1 under the Bayesian
Information Criteria (BIC) (Lanfear et al., 2016). Two independent runs of 108 generations
were performed sampling trees every 1000 generations. Convergence, posterior
distributions, and ESS values were checked in Tracer 1.6 (Rambaut et al., 2014).
2.3.3. Species-tree analysis
16
Considering the possibility that concatenation might result in highly supported but
inaccurate results (Kubatko and Degnan 2007; Weisrock et al., 2012, but see Gatesy and
Springer 2014), we performed a species-tree analysis, which infers the most likely species-
tree based on individual gene trees, using the StarBEAST2 (Ogilvie et al., 2017) template in
the BEAST v.2.4.6 package (Bouckaert et al., 2014). Even though StarBEAST2 was developed
to deal with large amounts of data, we selected only the loci that had more than four
parsimony informative sites (PIS) among our samples. This latter step reduces the total time
of analysis and also avoids including loci lacking phylogenetic signal, which would create
noise in the analysis. We employed PartitionFinder2 (Lanfear et al., 2016) to check for the
best partition scheme and substitution model. Trees models were unlinked, except for exons
from the same gene, in which case we linked tree models across different partitions. Since
recombination is not expected to happen inside one gene, all exonic regions recovered
belonging to the same gene were considered to be connected in the species-tree (ST)
analysis. We used a Yule model of speciation, and ploidy was set to 2.0, unless genes were
from the Z chromosome (in which case, ploidy=1.5). We also included the complete mtDNA
as a single locus, with ploidy=1.0.
3. Results
3.1. Sanger sequencing and haplotype networks
We sequenced 996 bp and 1013 bp, respectively, of the cytb and ND2 dataset. The
best partitioning scheme consisted of four partitions (cytb_pos1 = K80+I;
ND2_pos2+cytb_pos2 = HKY; ND2_pos3+cytb_pos3 = GTR+G; ND2_pos1 = HKY+I). All
sequences were deposited in GenBank under the accession numbers MH484353-MH484422.
The BI analysis, and the haplotype network, recovered eight allopatric mtDNA lineages (six of
populations of G. leucogastra and two of G. chalcothorax), six represented by well-
supported clades, and two represented by single individuals (Fig. 1). Although all clades
corresponding to the allopatric lineages had strong support, basal relationships among them
were poorly supported, the only exceptions being the sister relationships between Guiana
and Negro clades of G. leucogastra and between G. chalcothorax and the Madeira lineage of
G. leucogastra.
17
Haplotypes networks were recovered for the different mtDNA clades using the
concatenated matrix of cytb and ND2 in which all missing data were discarded (final matrix =
1304 bp). The six haplotype networks recovered by TCS were separated from each other by
at least 19 connection steps. In almost all networks mutations were concentrated on
terminal branches (star-like networks) suggesting recent population expansion, with little to
no genetic diversity within lineages, except for the G. leucogastra Madeira lineage and for G.
chalcothorax, for which we recovered a different haplotype for each specimen. Samples
from different banks of the Tapajós River are separated by six mutational steps (Fig. 1: light
and dark green), and samples of G. chalcothorax (Fig.1: light and dark brown) exhibit almost
the same number of mutations among them as they do with respect to the haplotypes from
the Madeira lineage.
3.2. mtDNA genome and time tree
We recovered the complete mitochondrial genome from all samples sequenced for
UCEs. In contrast to our cytb+ND2 tree, the tree based on all the mtDNA coding genes was
highly supported (Fig. 2). Molecular dating indicates that diversification of the mtDNA
lineages started in the Middle Pleistocene, at about 1.5 million years ago (mya) (95%HPD =
2.4 - 0.75). Although all nodes were recovered with high support, the first three splits
occurred in a short period of time, with short internodes, suggesting a rapid radiation among
lineages from southern, northern and western Amazonia (Fig. 2). The earliest divergence is
suggested to have been between populations separated by the Amazon River (Fig. 2). In
both mtDNA analyses (cytb+ND2 and mtDNA genome), G. chalcothorax was recovered as the
sister-group to the G. leucogastra lineage from the west bank of Madeira River, with their
divergence dating to around 0.74 mya (95%HPD = 1.21 – 0.38), therefore rendering G.
leucogastra paraphyletic. The lineages from the north bank of the Amazon River were also
recovered as sister-groups, and diverged roughly around the same time, 0.61 mya (95%HPD
= 1 – 0.31). The most recent divergence occurred between lineages separated by the Tapajós
River at 0.28 mya (95%HPD = 0.47 – 0.13).
3.3. UCE sequencing, supermatrix analysis and Species trees
Raw reads resulted from the sequencing were deposited at the National Center for
Biotechnology Information (NCBI) Sequence Read Archive (PRJNA476145). The complete
UCE matrix, which included only those loci shared among all samples, contained 2271 UCE
18
loci, with mean locus length of 543.06 bp (see Table 1 for total number of reads, Trinity
contigs, UCE and exon loci recovered from each sample; for alignments, total number of loci,
and locus information, see Table 2). The concatenated RAxML tree recovered G.
chalcothorax as sister to all other samples of G. leucogastra with high bootstrap support
(p=100, Fig. 3). Thus, the earliest divergence is here suggested to have occurred between an
eastern and a western population, unlike the pattern suggested by the mitochondrial data.
The first split within G. leucogastra is between lineages north and south of the Amazon
River, followed by a split across the Madeira River (p=100), and then younger splits across
the Tapajós (p=96) and the Aripuanã (p=76).
For the StarBEAST species-tree we used 124 loci that had more than four parsimony
informative sites. The species-tree was identical in topology to the concatenated RAxML UCE
phylogeny, with some differences in statistical support, including two nodes without strong
support in the species-tree (p<0.95) (Fig. 3). In both the concatenated and the species-trees,
we found contrasting differences compared to the mtDNA genome tree. Besides the nature
of the earliest split in the complex, the most significant one is that the nuclear data recover
G. leucogastra as monophyletic and sister to G. chalcothorax with strong statistical support;
which contrasts with the mtDNA genomic tree where G. leucogastra was paraphyletic, and
G. chalcothorax was sister to the G. leucogastra Madeira lineage (Fig. 2). Furthermore, in the
UCE trees the G. leucogastra Aripuanã lineage (Fig. 3, dark pink) was strongly clustered with
samples distributed east of the Madeira River (Fig. 3).
4. Discussion
4.1. mtDNA and nuDNA incongruence
Historically, the Purplish Jacamar (G. chalcothorax) was considered a subspecies of
the Bronzy Jacamar (G. leucogastra) (Peters, 1948; Haffer, 1974). Parker and Remsen (1987)
proposed that the two taxa be recognized as separate species based on their distinct
phenotypes: G. leucogastra is bronzy-green, with some suffused metallic blue, and a white
belly, whereas G. chalcothorax is tinged reddish-purple, and has a black belly with only the
feathers tips being white. Although these color characters seem to fluctuate across
populations, G. chalcothorax is distinctly larger than G. leucogastra (Haffer, 1974). Parker
and Remsen (1987) also suggested that Haffer (1974) did not recognize G. chalcothorax as a
19
full species because of the supposition they would interbreed if the two taxa came together,
but they also noted (p. 98) that “… the absence of major river barriers between their ranges
suggests that no interbreeding occurs or would occur”.
The structure recovered by the mtDNA data within G. leucogastra, with five well
supported mtDNA clades, suggests that current taxonomic treatment under-represents the
diversity within this species, which currently includes only two subspecies: G. l. leucogastra
and G. l. viridissima, described based on few individuals from the Tapajós river (Griscom and
Greeway, 1941). Surprisingly, mtDNA data also revealed that G. leucogastra specimens
comprising the Madeira clade, the geographically closest to G. chalcothorax, are sister to G.
chalcothorax with high support, but with no shared haplotypes among species (Fig. 1, 2). In
contrast, the UCE concatenated RAxML tree as well as the UCE species-tree recovered G.
leucogastra and G. chalcothorax as reciprocally monophyletic sister species, with the
Madeira lineage of G. leucogastra sister to G. leucogastra lineages from SE Amazonia (i.e.
Aripuanã and Tapajós lineages, Fig. 3). Multiple explanations have been proposed to account
for conflicts in mitochondrial and nuclear genes histories (summarized in Table 3).
Incomplete lineage sorting (ILS), usually referred as one of the main cause for this
kind of discordance, is often evidenced by the paraphyly or polyphyly of single gene trees in
phylogeographic studies. The existence of ancient polymorphism is potentially observed in
recent events of diversification, where there has been insufficient time to sort all alleles for
the genes and populations studied (McKay and Zink, 2010). This is especially true in the
nuclear DNA (nuDNA), because of larger populations sizes (2Ne) and the tendency to take
twice as much time to coalesce (4Ne) when compared with mtDNA (Moore, 1995). Our
phylogeographic results seem consistent with the idea that ILS is not affecting the patterns
recovered, at least with respect to the mtDNA, since there were no shared haplotype among
the different lineages (Fig. 1). However, another effect of ILS is discordance among gene
trees histories in ancient diversification events (Oliver, 2013). At the base of our
mitochondrial genome time tree we observe three diversification events close in time, which
could have caused conflict among gene trees histories. However, when we compare the
results from the mtDNA (Fig. 2) with the UCE dataset (Fig. 3), the only difference found is the
position of Galbula chalcothorax (LSU2803). If ILS was the cause for the discordance
observed here, we would expect discordance in topology between the mtDNA and UCE data,
20
and greater discordance between the concatenated RAxML tree and the species tree
analysis. The differences found between the two UCE analyses were mainly in the support of
the relationships among G. leucogastra lineages, with the species tree analysis recovering
two nodes with low support (Fig. 3), these same nodes exhibit this pattern in the mtDNA
tree (Fig. 2). The position of G. chalcothorax, however, was recovered by both analyses with
high support, as sister to all G. leucogastra specimens. Therefore, ILS cannot be used to
explain the discordance between the mtDNA and nuDNA trees, especially regarding the
position of G. chalcothorax.
Another process that can cause similar results as ILS is gene flow. Our hypothesis for
this incongruence is that an ancient event of hybridization between G. chalcothorax and the
Madeira lineage of G. leucogastra caused the introgression of the Madeira lineage mtDNA
into the G. chalcothorax lineage, replacing its “original” mtDNA lineage. This mitochondrial
capture may have been influenced by the populational and ecological context of
differentiation within WSE. Even though the ranges of G. leucogastra and G. chalcothorax
appear to be currently allopatric (Tobias 2017), they approach each other between the Purus
and Juruá rivers (Fig. 1). Therefore, past gene flow may have been possible during drier
climatic periods in SW Amazonia (see below) (Mayle et al., 2004; Bush, 2017). MtDNA clades
found within G. leucogastra are more structured and differentiated than the clades found
within the other WSE birds, but all of them agree in recovering a well supported clade in
northern Amazonia, and with the Madeira River being an important barrier in the south
(Capurucho et al., 2013; Matos et al., 2016). The maintenance of such structured mtDNA
lineages may indicate that little or no gene flow is presently ongoing between the lineages,
suggesting that the forest matrix is a strong barrier for these birds.
Although mtDNA lineages may reflect species boundaries (Hill, 2017), recent studies
have shown a number of cases in which apparent mtDNA paraphyly is not just derived from
improper taxonomy (McKay and Zink, 2010) but also from mtDNA introgression among
adjacent populations (Drovetski et al., 2015; Shipham et al., 2015, 2017; Dias et al., 2018;
see also Toews and Brelsford, 2012). In most cases in which mitochondrial sweeps are
reported, they happened within known zones of hybridization (Dias et al., 2018; Drovetski et
al., 2015; Shipham et al., 2015, 2017). However, genetic and phenotypic data for the Galbula
leucogastra/chalcothorax suggest that there is no current hybrid zone corresponding to the
21
conflict between UCE and mtDNA signal reported here. Male-biased dispersal could explain
the mixing of nuDNA without disrupting mtDNA structure. Such sex-biased traits are
commonly used to explain discordances between mtDNA and nuDNA (Excoffier, 2009; Toews
and Brelsford, 2012). However, in a recent review of this process, Bonnet et al. (2017)
simulated several scenarios and observed that the only way to have massive discordance in
all simulations, such as the one observed in our results, without detectable nuclear
introgression, is when there is positive selection acting on mitochondrial lineages. In
addition, the mtDNA can accumulate deleterious mutations quickly, and in small
populations, drift could spread these deleterious mutations across the whole population in
short periods of time. Therefore, small populations may accumulate several deleterious
mutations and the “defective” mtDNA lineage can be supplanted by a foreign mtDNA lineage
(Hailer et al., 2012; Llopart et al., 2014; Hulsey et al., 2016; Sloan et al., 2017). This
hypothesis can be more plausible if effects of the mtDNA sweep are more beneficial than the
disadvantageous effects of mitonuclear incompatibilities (Sloan et al., 2017). Furthermore,
isolation could lead to coevolution of mitochondrial and the nuclear background genes
involved in cellular respiration, which could function as a post-zygotic barrier to gene flow,
due to Bateson-Dobzhansky-Muller Incompatibility (BDMI) (Orr, 1996). Given the
fragmented distribution of WSE in Amazonia, it is possible that the occupation of new
patches, or the fragmentation of previously continuous habitats into smaller patches of WSE
due to landscape evolution, followed by some time in allopatry, could lead to the mtDNA
structure we observe today and consequent coevolution of the nuclear background.
4.2. Biogeography of WSE avifauna
In phylogeographic studies of the Black Manakin (Xenopipo atronitens, Pipridae),
Capurucho et al. (2013) found the largest mtDNA divergences to correspond to populations
found across the Branco and Amazonas rivers. Similar results were observed for the Red-
shouldered Tanager (Tachyphonus phoenicius, Thraupidae, Matos et al., 2016), but with
greater isolation between opposite margins of the Amazon river. The divergence times
estimated between northern and southern lineages within X. atronitens and T. phoenicius
were 0.92 and 0.88 Ma, respectively, both slightly younger than the mean age estimate we
obtained for the first divergence on the mtDNA tree (~1.5 Ma, 95%HPD = 0.75 - 2.4) in G.
leucogastra, but with overlap of confidence intervals. Another WSE specialist studied, the
22
Green-tailed Goldenthroat (Polytmus theresiae, Trochilidae), showed no genetic structure,
but exhibited strong signs of recent population expansion (Matos et al., 2016). Evidence of
recent gene flow among otherwise isolated populations of the aforementioned species
contrast with the highly-structured lineages recovered here. The phylogeographic structure
found in the G. leucogastra/chalcothorax is, in fact, more similar to phylogeographic
patterns found in understory birds of terra-firme environments (Ribas et al., 2012;
Fernandes et al., 2013; Fernandes et al., 2014; Thom & Aleixo, 2015; Ferreira et al., 2017).
Although we found evidence for an ancient capture event of mtDNA lineages, there is no
evidence of current gene flow between G. leucogastra and G. chalcothorax. This may be
evidence that the current forest cover separating these two taxa differs from the forest
cover that existed when the mtDNA capture occurred (Cowling et al., 2001; Arruda et al.,
2018). Alternatively, it is possible that some intrinsic incompatibility has developed between
the two taxa. Xenopipo atronitens and G. leucogastra/chalcothorax are found in both WSE
and black-water flooded forest, T. phoenicius in WSE and savannas, and P. theresiae in WSE,
black-water flooded forest and savannas (Borges et al., 2016b). In both X. atronitens and T.
phoenicius, the authors suggest that the use of black-water flooded forests would facilitate
the connection between patches of WSE, consequently increasing the gene flow among
adjacent populations (Capurucho et al., 2013; Matos et al., 2016). Even though G.
leucogastra and G. chalcothorax are also found in black-water flooded forests (Borges et al.,
2016b), the presence of the congeneric species-complex specialized in flooded forests –
Galbula galbula, G. tombacea, G. cyanescens, and G. ruficauda – may be restraining the
dispersal of individuals of G. leucogastra/chalcothorax, due to ecological competitive
exclusion. In addition, when compared to the other WSE species, G. leucogastra and G.
chalcothorax are the only exclusive insectivores, meaning that they need not have as
extensive foraging areas as do frugivores or nectarivores (Levey and Stiles, 1992), and hence
they are potentially more prone to isolation and differentiation (Burney and Brumfield,
2009).
4.3. Evolution in the White-sand ecosystems
In western Amazonia, white sand formations predate Andean uplift, and are
probably a result of westward rivers flowing from the Guiana and Brazilian shields to the
Pacific Ocean, during the Early Miocene (Hoorn, 1993). These sandy sediments of western
23
Amazonia were reorganized and recycled multiple times within the basin during the Andean
uplift, and most of these sediments are now covered by more recent clay-rich sediments
derived from the Andes making them very scattered today. This mosaic of sediments is
reflected in soils with distinct edaphic conditions, which influence floristic composition that
ultimately influences local bird communities (Pomara et al., 2012). In the eastern Amazonia,
most WSE occurs on podzolic soils and abandoned paleochannels (Prance and Schubart
1978; Latrubesse, 2002; Nascimento et al., 2004; Sauer et al., 2007; Frasier et al., 2008;
Cordeiro et al., 2016).
Phylogeographic studies of WSE specialized birds suggest a history related to north
eastern Amazonia (Guiana region) and dispersal from there to other parts of the basin during
the Pleistocene (Whitney and Alonso, 1998; Capurucho et al., 2013; Matos et al., 2016). Also,
most of WSE birds have sister groups inhabiting other open vegetation habitats and not the
adjacent Amazonian humid forest formations, such as terra-firme or varzea (Rheindt et al.,
2008; Capurucho et al., 2013; McGuire et al., 2014; Matos et al., 2016). This suggests the
colonization of Amazonian WSE by lineages that had already evolved in open habitats,
instead of repeated adaptations in multiple lineages from neighboring humid forest. In this
sense, Galbula leucogastra and Galbula chalcothorax are unlike other WSE taxa since all
other Galbula species are found in forest habitats (Witt, 2004; Tobias, 2017).
The WSE were probably more widespread throughout the continent before Andean
uplift, thus extant WSE lineages of birds may be resilient species capable of enduring the
reconfiguration of the Amazon basin (Campbell et al., 2006; Hoorn et al., 2010; Nogueira et
al., 2013). The pattern of greater genetic diversity in the east we observe today should be
then related to the fact that during the Pleistocene climatic cycles, eastern Amazonia
experienced greater fluctuations in precipitation (Wang et al., 2017). Although these cyclical
oscillations were not enough to entirely replace forest with savannas (Bush, 2017; Wang et
al., 2017), they may have affected forest structure (Cowling et al., 2001; Barthe et al., 2017;
Arruda et al., 2018). This could have facilitated contact between different patches of WSE in
the east, especially for birds that can use black-water flooded forest, allowing them to
expand their distribution and colonize previously unoccupied patches of WSE.
In contrast, the paleoclimatic record suggests that western Amazonia remained as
humid as it is today throughout the Pleistocene (Cheng et al., 2013; Wang et al., 2017).
24
Nowadays, after the main phases of Andean uplift, the existence of WSE in western
Amazonia would occur only in scattered patches in recycled quartzite soils reminiscent of
ancient fluvial deposits (Hoorn, 1993; Latrubesse, 2002). This scenario, however, contrasts
with the postulated past gene flow between G. chalcothorax and G. leucogastra. An
explanation to this biological evidence of a different landscape in the past in southwestern
Amazonia, may be related to the subduction of the Nazca Ridge under the South American
plate. This event may have caused the uplift of the Fitzcarrald Arch (Espurt et al., 2010),
affecting the drainage system and causing the erosion of the clay-rich sediment layer and
exposure the nutrient poor sediment layer below. This change in the edaphic condition,
coupled with climate oscillations may have periodically expanded WSE distribution in
southwestern Amazonia, facilitating the contact between currently isolated lineages of G.
leucogastra and G. chalcothorax.
5. Conclusion
Here we showed an instance of clear discordance between phylogenetic relationships
recovered using mtDNA and nuclear data in our study taxa. Nuclear data agrees with current
taxonomy, which is based on phenotypic patterns, while the mtDNA relationships seem to
be related to an old event of mtDNA capture. The capture event relates to what is currently
known about the distinct biogeographical histories of WSE in Eastern and Western
Amazonia, especially regarding the past distribution of WSE in western Amazonia
throughout the Pleistocene. While these results raise important issues about apparent
discordances between mtDNA clades and current taxonomy, they also show that interesting
biogeographic histories can be uncovered when enough genetic data with different and
independent histories are available. Nonetheless, this study will be an important
contribution of NGS for studies for recent speciation and taxonomy.
Acknowledgements
We thank the curator and curatorial assistants of the Academy of Natural Science of Drexel
University, Philadelphia, USA (ANSP); Field Museum of Natural History, Chicago, USA
(FMNH); Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil (INPA); Lousiana State
University Museum of Natural Science, Baton Rouge, USA (LSUMZ); and Museu Paraense
25
Emílio Goeldi, Belém, Brazil (MPEG), for loaning tissue samples under their care. We thank S.
W. Cardiff and N. Rice for helping us with LSUMZ and ANSP specimens, respectively. We are
also grateful for all collectors involved in fieldwork throughout Amazonia who made this
paper possible. We also thank the Bird 10k Project Committee for allowing access to the
genome sequence of Galbula dea. We thank J. M. G. Capurucho and S. H. Borges for early
inputs on this paper and the two anonymous reviewers. The authors also acknowledge the
National Laboratory for Scientific Computing (LNCC/MCTI, Brazil) for providing HPC
resources of the SDumont supercomputer, which have contributed to the research results
reported within this paper.
Funding
Support to M.F.’s graduate research was provided by CAPES PhD and PDSE (#
88881.133440/2016-01) fellowships, and by AMNH Frank M. Chapman Memorial Fund. Post-
doctoral fellowship to A.M.F. was provided by CNPq (#500488/2012-6). A. Aleixo and C.C.R.
are supported by CNPq research productivity fellowships. Research was partly covered by
grants to C.C.R. (PEER/USAID program, cycle 5), A. Aleixo (CNPq # 471342/2011-4 and
FAPESPA # ICAAF 023/2011) and A.Antonelli from the European Research Council under the
European Union’s Seventh Framework Programme (FP/2007-2013, ERC Grant Agreement n.
331024), the Knut and Alice Wallenberg Foundation through a Wallenberg Academy
Fellowship, the Swedish Research Council (2015-04857), the Swedish Foundation for
Strategic research, the Faculty of Sciences at the University of Gothenburg, the Wenner-
Gren Foundations, and the David Rockefeller Center for Latin Amarican Studies at Harvard
University. A.Aleixo, C.C.R., J.M.B., J.C. and M.F. were supported by the grant Dimensions
US-Biota-São Paulo: Assembly and evolution of the Amazon biota and its environment: an
integrated approach, co-funded by the US National Science Fundation (NSF DEB 1241056) to
J.C. and the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP grant
#2012/50260-6) to Lucia Lohmann.
References
Adeney, J.M., Christensen, N.L., Vicentini, A., Cohn-Haft, M., 2016. White-sand Ecosystems in Amazonia. Biotropica 48, 7-23.
26
Alonso, J.A., Whitney, B.M., 2001. A new Zimmerius tyrannulet (Aves: Tyrannidae) from white sand forests of northern Amazonian Peru. Wilson Bulletin 113, 1-9.
Anderson, A.B., 1981. White-sand vegetation of Brazilian Amazonia. Biotropica 13, 199-210. Arruda, D.M., Schaefer, C.E.G.R., Fonseca, R.S., Solar, R.R.C., Fernandes-Filho, E.I., 2018.
Vegetation cover of Brazil in the last 21 ka: New insights into the Amazonian refugia and Pleistocenic arc hypotheses. Global Ecol Biogeogr 27, 47-56.
Avise, J.C., 2009. Phylogeography: retrospect and prospect. J Biogeogr 36, 3-15. Avise, J.C., Arnold, J., Ball, R.M., Bermingham, E., Lamb, T., Neigel, J.E., Reeb, C.A., Saunders,
N.C., 1987. Intraspecific phylogeography: The mitochondrial DNA bridge between population genetics and systematics. Ann Rev Ecol Syst 18, 489-522.
Barthe, S., Binelli, G., Hérault, B., Scotti-Saintagne, C., Sabatier, D., Scotti, I., 2017. Tropical rainforest that persisted: inferences from the Quaternary demographic history of eight tree species in the Guiana Shield. Mol Ecol 26, 1161-1174.
Bock, D.G., Andrew, R.L., Rieseberg, L.H., 2014. On the adaptive value of cytoplasmic genomes in plants. Mol Ecol 23, 4899-4911.
Bolger, A.M., Lohse, M., Usadel, B., 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114-2120.
Bonnet, T., Leblois, R., Rousset, F., Crochet, P.-A., 2017. A reassessment of explanations for discordant introgressions of mitochondrial and nuclear genomes. Evolution 71, 2140-2158.
Borges, S.H., 2003. Species poor but distinct: bird assemblages in white sand vegetation in Jaú National Park, Brazilian Amazon. Ibis 146, 114-124.
Borges, S.H., Cornelius, C., Moreira, M., Ribas, C.C., Cohn-Haft, M., Capurucho, J.M.G., Vargas, C., Almeida, R., 2016a. Bird communities in Amazonian white-sand vegetation patches: effects of landscape configuration and biogeographic context. Biotropica 48, 121-131.
Borges, S.H., Cornelius, C., Ribas, C., Almeida, R., Guilherme, E., Aleixo, A., Dantas, S., Santos, M.P.D., Moreira, M., 2016b. What is the avifauna of Amazonian white-sand vegetation. Bird Conserv Int 26, 192-204.
Bouckaert, R., Heled, J., Kuhnert, D., Vaughan, T., Wu, C.H., Xie, D., Suchard, M.A., Rambaut, A., Drummond, A.J., 2014. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS computational biology 10, e1003537.
Brown, K.S., Benson, W.W., 1977. Evolution in Modern Amazonian Non-Forest Islands: Heliconius hermathena. Biotropica 9, 95-117.
Burney, C.W., Brumfield, R.T., 2009. Ecology predicts levels of genetic differentiation in neotropical birds. Am Nat 174, 358-368.
Bush, M.B., 2017. Climate science: The resilience of Amazonian forests. Nature 541, 167-168. Campbell, K.E., Frailey, C.D., Romero-Pittman, L., 2006. The Pan-Amazonian Ucayali
Peneplain, late Neogene sedimentation in Amazonia, and the birth of the modern Amazon River system. Palaeogeogr Palaeoclimatol Palaeoecol 239, 166-219.
Capurucho, J.M.G., Cornelius, C., Borges, S.H., Cohn-Haft, M., Aleixo, A., Metzger, J.P., Ribas, C.C., 2013. Combining phylogeography and landscape genetics of Xenopipo atronitens (Aves: Pipridae), a white sand campina specialist, to understand Pleistocene landscape evolution in Amazonia. Biol J Linn Soc 110, 60-76.
Carling, M.D., Brumfield, R.T., 2008. Haldane's rule in an avian system: using cline theory and divergence population genetics to test for differential introgression of mitochondrial,
27
autosomal, and sex-linked loci across the Passerina bunting hybrid zone. Evolution 62, 2600-2615.
Cheng, H., Sinha, A., Cruz, F.W., Wang, X., Edwards, R.L., d'Horta, F.M., Ribas, C.C., Vuille, M., Stott, L.D., Auler, A.S., 2013. Climate change patterns in Amazonia and biodiversity. Nature Commun 4, 1411.
Clement, M., Posada, D., Crandall, K.A., 2000. TCS: a computer program to estimate gene genealogies. Mol Ecol 9, 1657-1659.
Cohn-Haft, M., 2008. Estudos temático de impacto da BR-319: Aves. Internal Report. INPA, Manaus, Brazil.
Cohn-Haft, M., Bravo, G.A., 2013. A new species of Herpsilochmus antwren from west of the Rio Madeira in Amazonian Brazil. In: del Hoyo, J., Elliot, A., Sargatal, J., Christie, D. (Eds.), Handbook of the birds of the world. Special volume. New species and global index. Lynx Ediciones, Barcelona, Spain, pp. 272-276.
Cohn-Haft, M., Santos, M.A., Fernandes, A.M., Ribas, C., 2013. A new species of Cyanocorax jay from savannas of the central Amazon. In: del Hoyo, J., Elliot, A., Sargatal, J., Christie, D. (Eds.), Handbook of the birds of the world. Special volume. New species and global index. Lynx Ediciones, Barcelona, Spain, pp. 306-310.
Cordeiro, C.L.O., Rossetti, D.F., Gribel, R., Tuomisto, H., Zani, H., Ferreira, C.A.C., Coelho, L., 2016. Impact of sedimentary processes on white-sand vegetation in an Amazonian megafan. J Trop Ecol 32, 498-509.
Cowling, S.A., Maslin, M.A., Sykes, M.T., 2001. Paleovegetation Simulations of Lowland Amazonia and Implications for Neotropical Allopatry and Speciation. Quat Res 55, 140-149.
Daly-Engel, T.S., Seraphin, K.D., Holland, K.N., Coffey, J.P., Nance, H.A., Toonen, R.J., Bowen, B.W., 2012. Global phylogeography with mixed-marker analysis reveals male-mediated dispersal in the endangered scalloped hammerhead shark (Sphyrna lewini). PloS one 7, e29986.
Dias, C., Lima, K.A., Araripe, J., Aleixo, A., Vallinoto, M., Sampaio, I., Schneider, A., Rêgo, P.S., 2018. Mitochondrial introgression obscures phylogenetic relationships among manakins of the genus Lepidothrix (Aves: Pipridae). Mol Phylogenet Evolut 126, 314-320.
Dobler, R., Rogell, B., Budar, F., Dowling, D.K., 2014. A meta-analysis of the strength and nature of cytoplasmic genetic effects. J Evol Biol 27, 2021-2034.
Drovetski, S.V., Semenov, G., Red'kin, Y.A., Sotnikov, V.N., Fadeev, I.V., Koblik, E.A., 2015. Effects of asymmetric nuclear introgression, introgressive mitochondrial sweep, and purifying selection on phylogenetic reconstruction and divergence estimates in the Pacific clade of Locustella warblers. PloS one 10, e0122590.
Drummond, A.J., Suchard, M.A., Xie, D., Rambaut, A., 2012. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol Biol Evol 29, 1969-1973.
Espurt, N., Baby, P., Brusset, S., Roddaz, M., Hermoza, W., Barbarand, J., 2010. The Nazca Ridge and uplift of the Fitzcarrald Arch: implication for regional geology in northern South America. In: Hoorn, C., Wesselingh, F.P. (Eds.), Amazonia: Landscape and species evolution. Black-Willey Publisher Ltd., Oxford, UK, pp. 89-100.
Excoffier, L., Foll, M., Petit, R.J., 2009. Genetic Consequences of Range Expansions. Ann Rev Ecol Evol Syst 40, 481-501.
Faircloth, B.C., 2013. illumiprocessor: a trimmomatic wrapper for parallel adapater and quality trimming. http://dx.doi.org/10.6079/J9ILL.
28
Faircloth, B.C., 2016. PHYLUCE is a software package for the analysis of conserved genomic loci. Bioinformatics 32, 786-788.
Faircloth, B.C., McCormack, J.E., Crawford, N.G., Harvey, M.G., Brumfield, R.T., Glenn, T.C., 2012. Ultraconserved elements anchor thousands of genetic markers spanning multiple evolutionary timescales. Syst Biol 61, 717-726.
Fernandes, A.M., 2013. Fine-scale endemism of Amazonian birds in a threatened landscape. Biodivers Conserv 22, 2683-2694.
Fernandes, A.M., Cohn-Haft, M., Hrbek, T., Farias, I.P., 2014. Rivers acting as barriers for bird dispersal in the Amazon. Rev Bras Ornitol 22, 363-373.
Ferreira, M., Aleixo, A., Ribas, C.C., Santos, M.P.D., 2017. Biogeography of the Neotropical genus Malacoptila (Aves: Bucconidae): the influence of the Andean orogeny, Amazonian drainage evolution and palaeoclimate. J Biogeogr 44, 748-759.
Fine, P.V.A., Baraloto, C., 2016. Habitat endemism in white-sand forests: Insights into the mechanisms of lineage diversification and community assembly of the Neotropical Flora. Biotropica 48, 24-33.
Fine, P.V.A., García-Villacorta, R., Pitman, N.C.A., Mesones, I., Kembel, S.W., 2010. A Floristic Study of the White-Sand Forests of Peru. Ann Missouri Bot Gard 97, 283-305.
Frasier, C.L., Albert, V.A., Struwe, L., 2008. Amazonian lowland, white sand areas as ancestral regions for South American biodiversity: Biogeographic and phylogenetic patterns in Potalia (Angiospermae: Gentianaceae). Org Divers Evol 8, 44-57.
Funk, D.J., Omland, K.E., 2003. Species-level paraphyly and polyphyly: Frequency, causes, and consequences, with insights from animal mitochondrial DNA. Ann Rev Ecol Evol Syst 34, 397-423.
Gatesy, J., Springer, M.S., 2014. Phylogenetic analysis at deep timescales: unreliable gene trees, bypassed hidden support, and the coalescence/concatalescence conundrum. Mol Phylogenet Evol 80, 231-266.
Grabherr, M.G., Haas, B.J., Yassour, M., Levin, J.Z., Thompson, D.A., Amit, I., Adiconis, X., Fan, L., Raychowdhury, R., Zeng, Q., Chen, Z., Mauceli, E., Hacohen, N., Gnirke, A., Rhind, N., di Palma, F., Birren, B.W., Nusbaum, C., Lindblad-Toh, K., Friedman, N., Regev, A., 2011. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature Biotechnol 29, 644-652.
Griscom, L., Greenway, J.C., 1941. Birds of Lower Amazonia. Bull Mus Comp Zool 88, 83-344. Haffer, J., 1974. Avian speciation in Tropical South America. Nuttall Ornithological Club,
Harvard University, Cambridge. Hailer, F., Kutschera, V.E., Hallstrom, B.M., Klassert, D., Fain, S.R., Leonard, J.A., Arnason, U.,
Janke, A., 2012. Nuclear genomic sequences reveal that polar bears are an old and distinct bear lineage. Science 336, 344-347.
Harvey, M.G., Smith, B.T., Glenn, T.C., Faircloth, B.C., Brumfield, R.T., 2016. Sequence Capture versus Restriction Site Associated DNA Sequencing for Shallow Systematics. Syst Biol 65, 910-924.
Harvey, M.G., Aleixo, A., Ribas, C., Brumfield, R.T., 2017. Habitat association predicts genetic diversity and population divergence in Amazonian birds. Am Nat 190, 631-648.
Hill, G.E., 2017. The mitonuclear compatibility species concept. Auk 134, 393-409. Hoorn, C., 1993. Marine incursions and the influence of Andean tectonics on the Miocene
depositional history of northwestern Amazonia: results of a palynostratigraphic study. Palaeogeogr Palaeoclimatol Palaeoecol 105, 267-309.
29
Hoorn, C., Wesselingh, F.P., ter Steege, H., Bermudez, M.A., Mora, A., Sevink, J., Sanmartin, I., Sanchez-Meseguer, A., Anderson, C.L., Figueiredo, J.P., Jaramillo, C., Riff, D., Negri, F.R., Hooghiemstra, H., Lundberg, J., Stadler, T., Sarkinen, T., Antonelli, A., 2010. Amazonia through time: Andean uplift, climate change, landscape evolution, and biodiversity. Science 330, 927-931.
Hulsey, C.D., Bell, K.L., García-de-León, F.J., Nice, C.C., Meyer, A., 2016. Do relaxed selection and habitat temperature facilitate biased mitogenomic introgression in a narrowly endemic fish? Ecol Evol 6, 3684-3698.
Katoh, K., Standley, D.M., 2013. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol Biol Evol 30, 772-780.
Kearse, M., Moir, R., Wilson, A., Stones-Havas, S., Cheung, M., Sturrock, S., Buxton, S., Cooper, A., Markowitz, S., Duran, C., Thierer, T., Ashton, B., Meintjes, P., Drummond, A., 2012. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28, 1647-1649.
Kubatko, L.S., Degnan, J.H., 2007. Inconsistency of phylogenetic estimates from concatenated data under coalescence. Syst Biol 56, 17-24.
Lanfear, R., Frandsen, P.B., Wright, A.M., Senfeld, T., Calcott, B., 2017. PartitionFinder 2: New methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses. Mol Biol Evol 34, 772-773.
Langmead, B., Salzberg, S.L., 2012. Fast gapped-read alignment with Bowtie 2. Nature Methods 9, 357-359.
Langmead, B., Trapnell, C., Pop, M., Salzberg, S.L., 2009. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10, R25.
Laranjeiras, T.O., Naka, L.N., Bechtold, C.L., Costa, T.V.V., Andretti, C.B., Cerqueira, M.C., Torres, M.d.F., Rodrigues, G.L., Santos, M.P.D., Vargas, C.F., Pacheco, A.M.F., Sardelli, C.H., Mazar-Barnett, J., Cohn-Haft, M., 2014. The avifauna of Viruá National Park, Roraima, reveals megadiversity in northern Amazonia. Rev Bras Ornitol 22, 138-171.
Latrubesse, E.M., 2002. Evidence of Quaternary palaeohydrological changes in middle Amazonia: The Aripuanã-Roosevelt and Jiparaná "fans". Z Geomorph N F 129, 61-72.
Levey, D.J., Stiles, F.G., 1992. Evolutionary precursors of long-distance migration: resource availability and movement patterns in Neotropical landbirds. Am Nat 140, 447-476.
Llopart, A., Herrig, D., Brud, E., Stecklein, Z., 2014. Sequential adaptive introgression of the mitochondrial genome in Drosophila yakuba and Drosophila santomea. Mol Ecol 23, 1124-1136.
Manthey, J.D., Campillo, L.C., Burns, K.J., Moyle, R.G., 2016. Comparison of Target-Capture and Restriction-Site Associated DNA Sequencing for Phylogenomics: A Test in Cardinalid Tanagers (Aves, Genus: Piranga). Syst Biol 65, 640-650.
Matos, M.V., Borges, S.H., d'Horta, F.M., Cornelius, C., Latrubesse, E., Cohn-Haft, M., Ribas, C.C., 2016. Comparative Phylogeography of two bird species, Tachyphonus phoenicius (Thraupidae) and Polytmus theresiae (Trochilidae), specialized in Amazonian White-sand vegetation. Biotropica 48, 110-120.
Mayle, F.E., Beerling, D.J., Gosling, W.D., Bush, M.B., 2004. Responses of Amazonian ecosystems to climatic and atmospheric carbon dioxide changes since the last glacial maximum. Philos Trans R Soc Lond B Biol Sci 359, 499-514.
McCormack, J.E., Hird, S.M., Zellmer, A.J., Carstens, B.C., Brumfield, R.T., 2013. Applications of next-generation sequencing to phylogeography and phylogenetics. Molecular phylogenetics and evolution 66, 526-538.
30
McGuire, J.A., Witt, C.C., Remsen, J.V., Jr., Corl, A., Rabosky, D.L., Altshuler, D.L., Dudley, R., 2014. Molecular phylogenetics and the diversification of hummingbirds. Curr Biol 24, 910-916.
McKay, B.D., Zink, R.M., 2010. The causes of mitochondrial DNA gene tree paraphyly in birds. Mol Phylogenet Evol 54, 647-650.
Moore, W.S., 1995. Inferring phylogenies from mtDNA variation: mitochondrial-gene trees versus nuclear-gene trees. Evolution 49, 718-726.
Moyle, R.G., Oliveros, C.H., Andersen, M.J., Hosner, P.A., Benz, B.W., Manthey, J.D., Travers, S.L., Brown, R.M., Faircloth, B.C., 2016. Tectonic collision and uplift of Wallacea triggered the global songbird radiation. Nature Commun 7, 12709.
Nascimento, N.R., Bueno, G.T., Fritsch, E., Herbillon, A.J., Allard, T., Melfi, A.J., Astolfo, R., Boucher, H., Li, Y., 2004. Podzolization as a deferralitization process: a study of an Acrisol-Podzol sequence derived from Palaeozoic sandstones in the northern upper Amazon Basin. Eur J Soil Sci 55, 523-538.
Nogueira, A.C.R., Silveira, R., Guimarães, J.T.F., 2013. Neogene–Quaternary sedimentary and paleovegetation history of the eastern Solimões Basin, central Amazon region. J South Am Earth Sci 46, 89-99.
Ogilvie, H.A., Bouckaert, R.R., Drummond, A.J., 2017. StarBEAST2 brings faster species tree inference and accurate estimates of substitution rates. Mol Biol Evol 34, 2101-2114.
Oliver, J., 2013. Microevolutionary processes generate phylogenomic discordance at ancient divergences. Evolution 67, 1823-1830.
Orr, H.A., 1996. Dobzhansky, Bateson, and the genetics of speciation. Genetics 144, 1331-1335.
Parker, T.A., Remsen, J.V., 1987. Fifty-two Amazonian bird species new to Bolivia. Bull Brit Orn Cl 107, 94-107.
Peters, J.L., 1948. Check-list of birds of the world. Harvard University Press, Cambridge, UK. Pomara, L.Y., Ruokolainen, K., Tuomisto, H., Young, K.R., 2012. Avian composition co-varies
with floristic composition and soil nutrient concentration in Amazonian upland forests. Biotropica 44, 545-553.
Prance, G.T., Schubart, H.O.R., 1978. Notes on the vegetation of Amazonia I. A preliminary note on the origin of the open white sand campinas of the lower Rio Negro. Brittonia 30, 60-63.
Prum, R.O., Berv, J.S., Dornburg, A., Field, D.J., Townsend, J.P., Lemmon, E.M., Lemmon, A.R., 2015. A comprehensive phylogeny of birds (Aves) using targeted next-generation DNA sequencing. Nature 526, 569-573.
Rambaut, A., Suchard, M.A., Xie, D., Drummond, A.J., 2014. Tracer v1.6. http://beast.bio.ed.ac.uk/Tracer
Rheindt, F.E., Christidis, L., Norman, J.A., 2008. Habitat shifts in the evolutionary history of a Neotropical flycatcher lineage from forest and open landscapes. BMC Evol Biol 8.
Rheindt, F.E., Edwards, S.V., 2011. Genetic Introgression: An Integral but neglected component of speciation in birds. Auk 128, 620-632.
Ribas, C.C., Aleixo, A., Nogueira, A.C., Miyaki, C.Y., Cracraft, J., 2012. A palaeobiogeographic model for biotic diversification within Amazonia over the past three million years. Proc Biol Sci 279, 681-689.
Roddaz, M., Baby, P., Brusset, S., Hermoza, W., Maria Darrozes, J., 2005. Forebulge dynamics and environmental control in Western Amazonia: The case study of the Arch of Iquitos (Peru). Tectonophysics 399, 87-108.
31
Ronquist, F., Teslenko, M., van der Mark, P., Ayres, D.L., Darling, A., Hohna, S., Larget, B., Liu, L., Suchard, M.A., Huelsenbeck, J.P., 2012. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol 61, 539-542.
Sambrook, J., Russel, D.W., 2001. Molecular Cloning: A laboratory manual. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York.
Sauer, D., Sponagel, H., Sommer, M., Giani, L., Jahn, R., Stahr, K., 2007. Podzol: Soil of the year 2007. A review on its genesis, occurrence, and functions. J Plant Nutr Soil Sci 170, 581-597.
Shipham, A., Schmidt, D.J., Joseph, L., Hughes, J.M., 2015. Phylogenetic analysis of the Australian rosella parrots (Platycercus) reveals discordance among molecules and plumage. Mol Phylogenet Evol 91, 150-159.
Shipham, A., Schmidt, D.J., Joseph, L., Hughes, J.M., 2017. A genomic approach reinforces a hypothesis of mitochondrial capture in eastern Australian rosellas. Auk 134, 181-192.
Sloan, D.B., Havird, J.C., Sharbrough, J., 2017. The on-again, off-again relationship between mitochondrial genomes and species boundaries. Mol Ecol 26, 2212-2236
Smith, B.T., Harvey, M.G., Faircloth, B.C., Glenn, T.C., Brumfield, R.T., 2014. Target capture and massively parallel sequencing of ultraconserved elements for comparative studies at shallow evolutionary time scales. Syst Biol 63, 83-95.
Sorenson, M.D., Ast, J.C., Dimcheff, D.E., Yuri, T., Mindell, D.P., 1999. Primers for a PCR-based approach to mitochondrial genome sequencing in birds and other vertebrates. Mol Phylogenet Evol 12, 105-114.
Stamatakis, A., 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312-1313.
Stotz, D.F., Fitzpatrick, J.W., Parker, T.A., Moskovitz, D.K., 1996. Neotropical birds: Ecology and conservation. University of Chicago Press, Chicago, IL.
Thom, G., Aleixo, A., 2015. Cryptic speciation in the white-shouldered antshrike (Thamnophilus aethiops, Aves - Thamnophilidae): the tale of a transcontinental radiation across rivers in lowland Amazonia and the northeastern Atlantic Forest. Mol Phylogenet Evol 82, 95-110.
Tobias, J.A., 2017. Jacamars (Galbulidae). In: del Hoyo, J., Elliot, A., Sargatal, J. (Eds.), Handbook of the birds of the world. Lynx Ediciones, Barcelona. (retrieved from http://www.hbw.com/node/52281 on 15 August 2017)
Toews, D.P., Brelsford, A., 2012. The biogeography of mitochondrial and nuclear discordance in animals. Mol Ecol 21, 3907-3930.
Vicentini, A., 2016. The Evolutionary History of Pagamea (Rubiaceae), a White-sand Specialist Lineage in Tropical South America. Biotropica 48, 58-69.
Vriesendorp, C., Pitman, N.C., Rojas Moscoso, J.I., Pawlak, B.A., Chavéz, L.R., Méndez, L.C., Collantes, M.V., Rimachi, E.P.F., 2006. Perú: Matsés. Rapid biological inventories report 16. The Field Museum, Chicago.
Wang, N., Kimball, R.T., Braun, E.L., Liang, B., Zhang, Z., 2017. Ancestral range reconstruction of Galliformes: the effects of topology and taxon sampling. J Biogeogr 44, 122-135.
Weir, J.T., Schluter, D., 2008. Calibrating the avian molecular clock. Mol Ecol 17, 2321-2328. Weisrock, D.W., Smith, S.D., Chan, L.M., Biebouw, K., Kappeler, P.M., Yoder, A.D., 2012.
Concatenation and concordance in the reconstruction of mouse lemur phylogeny: an empirical demonstration of the effect of allele sampling in phylogenetics. Mol Biol Evol 29, 1615-1630.
32
Whitney, B.M., Alonso, J.A., 1998. A new Herpsilochmus antwren (Aves: Thamnophilidae) from Northern Amazonian Peru and adjacent Ecuador: The role of edaphic heterogeneity of terra firme forest. Auk 115, 559-576.
Whitney, B.M., Alonso, J.A., 2005. A new species of Gnatcatcher from white-sand forests of northern Amazonian Peru with revision of the Polioptila guianensis complex. Wilson Bull 117, 113-127.
Witt, C.C., 2004. Rates of molecular evolution and their application to Neotropical Avian Biogeography. Department of Biological Sciences. Louisiana State University, p. 132 p.
Zink, R.M., Barrowclough, G.F., 2008. Mitochondrial DNA under siege in avian phylogeography. Mol Ecol 17, 2107-2121.
Author contibutions
M.F. and A.M.F. developed the sampling plan, extracted DNA and sequenced all samples. M.F.
performed all analysis. A.A.P., A.A., U.O., J.M.B., J.C. and C.C.R. were involved in intellectual merit,
funding, and writing. All authors participated in writing the manuscript.
Supporting information
Additional supporting information may be found in the online version of this article.
Table S1 Supplementary details of individuals.
33
Table 1 - Samples used for UCE sequencing, their voucher numbers, general locality, number of clean reads after Illumiprocessor, number of contigs assembled by Trinity, and total UCE loci recovered from Trinity.
Species Museum voucher Locality Clean reads Trinity contigs UCE loci
G. chalcothorax LSUMZ B2803 N of Napo River, Iquitos, Peru 1,524,126 6,537 2,230
G. leucogastra INPA A4182 145 Km WWS of Apuí, AM, Brazil 2,540,148 12,163 2,269
G. leucogastra INPA A4672 Right bank of Jatapú River, AM, Brazil 2,209,895 9,491 2,263
G. leucogastra LSUMZ B35619 Arapiuns River, PA, Brazil 4,394,658 10,853 2,246
G. leucogastra LSUMZ B9608 Nicolás Suarez, Pando, Bolívia 1,677,988 5,074 1,928
G. leucogastra MPEG 59360 Novo Airão, AM, Brazil 2,372,950 6,026 1,957
G. leucogastra MPEG 75618 Right bank of Tapajós River, PA, Brazil 1,346,149 6,117 2,263
G. leucogastra MPEG 73685 Novo Aripuanã, AM, Brazil 1,466,240 6,896 2,227
G. albirostris INPA A064 Amazonas, Brazil 2,809,416 16,718 2,256
Table 2 – Summary of each method, including number of loci, total length, mean length size of each loci, minimum and maximum length, number of Parsimony Informative sites.
Method Complete Exons Species Tree†
Number of loci 2271 47 124
Total length (bp) 1,233,287 47,580 80,085
Mean length size (bp) 543.06 849.64 645.85
Min - Max length (bp) 118 – 1,305 182 - 3093 347 – 3093
Number of PI sites (mean) 2003 (0.88) 190 (3.39) 744 (6)
†without the mtDNA
Table 3 – Possible causes of conflict in mitochondrial and nuclear DNA histories.
Inferred process Reference
Incomplete lineage sorting Funk and Omland, 2003; McKay and Zink, 2010;
Zink and Barrowclough, 2008
Incomplete sampling Shipham et al., 2015, 2017
Improper taxonomy McKay and Zink, 2010
Adaptive introgression Bock et al., 2014; Dobler et al., 2014
Demography or Sex-biased traits Bonnet et al., 2017; Daly-Engel et al., 2012;
Rheindt and Edwards, 2011; Sloan et al., 2017
34
Figure 1 - Map of sequenced individuals, phylogenetic Bayesian tree recovered, and haplotype networks. The colors in the tree, map and networks are correspondent, and the tree and networks are based on two mtDNA genes (2009 bp, cytb and ND2). Posterior probabilities obtained at each node are indicated on the tree, red circles represent pp=1. The brown labeled points are G. chalcothorax, all other lineages are G. leucogastra. Terminal names in red are samples used in the UCE analysis. Circles sizes in the haplotypes network correspond to number of individuals sharing the haplotype. Maximum number of connection steps for the haplotypes networks is 19.
35
Figure 2 – Chronogram recovered by BEAST using all mtDNA coding genes with a calibration derived from the mutational rate of the cytb gene (Weir and Schluter 2008). Posterior probabilities obtained at each node are indicated in the tree, red circles represent pp>98, associated confidence interval (95% HPD) for diversification time (blue bar), and the median time of divergence. Colors are correspondent with Figure 1.
36
Figure 3 - Comparison between the concatenated UCE RAxML tree (left) and the StarBEAST2 species tree (right). Bootstrap support for the RAxML tree, and the posterior probability for the StarBEAST species tree, is show near the nodes. Colors are correspondent with Figure 1.
37
Capítulo 2
Ferreira, M.; Aleixo, A.; Bates, J. M.; Cracraft, J.;
Ribas, C. C. Phylogenomics of trogons (Aves:
Trogonidae) shed light on the Quaternary
biogeography of tropical forests and the connections
between Asia, North and South America. Manuscrito
formatado para Molecular Biology and Evolution
38
Manuscript submission to Molecular Biology and Evolution
Contribution type: Article
Phylogenomics of trogons (Aves: Trogonidae) shed light on the Quaternary
biogeography of tropical forests and the connections between Asia, North
and South America
Ferreira, Mateus1*; Aleixo, Alexandre2; Bates, John M.3; Cracraft, Joel4; Ribas, Camila C.5
1 Programa de Pós-Graduação em Genética, Conservação e Biologia Evolutiva, INPA,
Manaus, AM, Brazil 2 Coordenação de Zoologia, MPEG, Belém, PA, Brazil 3 Department of Ornithology, FMNH, Chicago, IL, USA 4 Department of Ornithology, AMNH, New York, NY, USA 5 Coordenação de Biodiversidade, INPA, Manaus, AM, Brazil
*Corresponding author
Correspondence: Mateus Ferreira, Coordenação de Biodiversidade, Instituto Nacional de
Pesquisas da Amazônia, CEP 69080-971, Manaus-AM, Brazil
E-mail: [email protected]
39
Abstract
The pantropical distribution of trogons always drew attention of biogeographers, with
species distributed all over the forests regions of subtropical and tropical Africa, Asia and
America, several studies tried to reconstruct the phylogenetic relationships without, however,
being able to achieve conclusive results. For the first time, all genera and almost all currently
recognized species, 43 out of 45, were sampled and sequenced for thousands of ultraconserved
elements (UCE) to reconstruct the family phylogenetic hypothesis. We analysed the
concatenated dataset using different treatments for missing data with RAxML and ExaBayes,
we also estimated a species tree using SVDquartets. We also estimated a fossil calibrated time
tree for trogons diversification sampling 177 individuals of the Core Landbirds for RAG1 and
RAG2 genes. Our results were congruent among all methods with high nodal support,
disagreement between treatments (Species Tree x concatenated) were observed only at the basal
nodes. In general, our results support the monophyly of the different biogeographical regions,
with Apaloderma species being sister to the Asian (Harpactes and Apalharpactes) and the
Neotropical trogons (Euptilotis, Pharomachrus, Priotelus, and Trogon). Trogonidae initial
diversifications occurred around 20 Ma, and continued till the Pleistocene, where most of the
Neotropical species appeared. Based on these results, we proposed how the climate changes
since the Late Oligocene influenced forest distributions and how the establishment of land
bridges between continents helped shape the family diversification.
40
Introduction
The Trogonidae have some of the most colourful and exquisite plumages among birds.
Representatives of this family, usually known as trogons or quetzals, can be found in forested
tropical and subtropical regions of Africa, Asia and America (Collar 2017). The monophyly of
the family was never questioned due to the morphological homogeneity among species
(Livezey and Zusi 2007; Collar 2017), the most iconic feature that differentiate trogons and
quetzals from other birds is the heterodactyl foot, in which digits 1 and 2 are directed backwards
and the basal half of digits 3 and 4 are fused and directed forward (Maurer and Raikow 1981;
Mayr 2009). However, it is precisely this unique feature that makes trogons so difficult to relate
with extant birds. Despite several attempts to reconstruct the relationship between trogons and
other birds, most of the morphological (Cracraft 1981; Maurer and Raikow 1981; Mayr 2003;
Livezey and Zusi 2007) and the first molecular analyses (Monteros 2000; Hackett, et al. 2008;
McCormack, et al. 2013) were unable to recover conclusive results about their phylogenetic
relationships. Only recently, employing genomic representations, trogons were shown to be a
sister group to a clade containing mousebirds (Coliiformes), cuckoo rollers (Leptosomiformes)
and other Core Landbirds (Jarvis, et al. 2014; Prum, et al. 2015).
Although the relationship with other birds is partially resolved, the relationships within
the family are still pending conclusive results. Historically, the genera and species within each
biogeographic region were considered monophyletic. The highest diversity is found in the
Neotropical region, with four genera, Euptilotis, Pharomachrus, Priotelus and Trogon, and ~30
species ranging from southwestern USA to northern Argentina. The Indo-Malaysian region
comprises 2 genera, Apalharpactes and Harpactes, and 12 species, ranging from southern India,
Southeast Asia, Philippines, the Malay Peninsula, Borneo, Philippines, Sumatra and Java, while
the African region includes only one genus, Apaloderma and tree species. Although trogons are
currently found only in tropical and subtropical regions, fossil records indicate that they had a
wider distribution in the past. Two fossils from Europe, Primotrogon wintersteini (Mayr 1999)
from the Middle Oligocene, and ?P. pumilio (Mayr 2005), from the Middle Eocene, are credited
to be sister group to all other extant species (Mayr 2009). Whereas Septentrogon madseni
(Kristoffersen 2002), from the transitional Paleocene-Eocene Fur Formation in north-western
Denmark shares morphological characteristics that put him inside the Trogonidae. The presence
of these fossils in Europe suggests a widespread lineage occurring in regions that are currently
unsuitable for them. The similarity between fossils and extant trogons also indicates that this
lineage suffered little morphological changes through time. This apparent conservatism of
41
morphological characteristics also makes the inferences of phylogenetic relationships among
extant species difficult.
The first molecular phylogenetic hypothesis for trogons was based on two mitochondrial
genes and included 20 out of the ca. 45 species (Monteros 1998). This study supported the
hypothesis of monophyly of the biogeographic regions, recovering the Neotropical genera sister
to the Asian, with the African clade sister to these two (Monteros 1998). Following studies that
increased the number of genes and/or samples, however, couldn’t recover the monophyly of the
Neotropical genera, nor the relationship among the different regions (Johansson and Ericson
2005; Moyle 2005; DaCosta and Klicka 2008; Hosner, et al. 2010). The most recent paper
(Hosner, et al. 2010), and the first one to sample the genus Apalharpactes, recognized six clades
(Apaloderma, Apalharpactes, Harpactes, Pharomachrus/Euptilotis, Priotelus, and Trogon)
with uncertain relationships among them, but showing evidences of Apalharpactes being more
closely related with the African Apaloderma, than to the other Asian genus, Harpactes,
implying a very complex biogeographical pattern, with two independent colonizations of Asia.
A similar pattern suggested for the Neotropical genera, which group three distinct clades
(Hosner, et al. 2010).
This uncertainty regarding phylogenetic relationships so far was probably related to the
scarcity of signal due to a low number of loci employed in previous studies. Genomic analyses
using a reduced representation of the genome can increase phylogenetic information and avoid
confounding the histories of single genes with the species relationships (Degnan and Rosenberg
2009; Knowles 2009). Also, since the correct interpretation of biotic evolution can shed light
on the landscape evolution (Baker, et al. 2014), a robust and well supported phylogenetic
hypothesis is of extreme importance for defining hypothesis in biogeography (Donoghue and
Moore 2003; Lexer, et al. 2013). In this sense, a prominent approach to study systematics using
genomic markers is the use of probes for Ultraconserved Elements (UCE)(Faircloth, et al. 2012;
McCormack, et al. 2012; McCormack and Faircloth 2013; McCormack, et al. 2013; Faircloth,
et al. 2015). These probes, have been employed to reconstruct deep (Faircloth, et al. 2015;
Moyle, et al. 2016; Branstetter, et al. 2017; Esselstyn, et al. 2017) and shallow (Bryson, et al.
2016; Manthey, et al. 2016) phylogenetic relationships, even where high incomplete lineage
sorting is expected, such as in cases of rapid evolutionary radiation (Meiklejohn, et al. 2016).
Therefore, trogons represent a great study model on how genomic representation may
elucidate uncertain phylogenetic relationships, and to understand how the landscape evolution
shaped the family diversification, due to its pantropical geographic distribution and preference
42
for forested habitats. Here, we aim (1) to generate and unprecedent and robust analyses of
phylogenetic relationships within the Trogonidae family, using nearly complete sampling of all
recognized speces and a genomic representation of more than 2,000 UCE loci, (2) to investigate
the monophyly of main biogeographical regions, and (3) to reconstruct a calibrated tree to infer
the timing of diversification, and how it was influenced by the global events on geography and
climate.
Results
UCE sequencing
The reference sequences we extracted from the Apaloderma vittatum genome (Gilbert,
Jarvis, Li, Consortium, et al. 2014) included 2,228 loci. The mean number of sequences for
each individual was 2,080,592, and a mean number of UCE loci was 2,222, with only one toe
pad sample (AMNH 322898) recovering less than 2000 loci (Table 1). The complete matrix
contained 1421 loci, with mean locus length of 510.27 base pairs, and a total of 37,880
parsimony informative (PI) sites, mean of 26.6 per locus (Table 2). The incomplete matrices
with 95% and 75% completeness have 2,210 and 2,217 loci, with mean locus length of 499.77
and 495.95 base pairs, and 55,060 and 57,259 PI sites, with mean of 24.91 and 25.83 sites per
locus (Table 2).
Phylogenetic inference
The tree topologies were congruent among all methods and with high node support, apart
from the SVDq analyses, in which the basal nodes presented low support. The concatenated
RAxML and ExaBayes phylogenies recovered the Asian trogons sister to the Neotropical, and
these two sisters to the African clade with high support (Fig. 1). All the ExaBayes analyses,
including the complete and the two incomplete datasets, recovered the same topology with all
nodes with the maximum posterior probability (Fig. 1). Although the topologies recovered by
RAxML trees were congruent with ExaBayes, some of the basal nodes received low support.
The same was observed with SVDq.
Within the Asian group, Apalharpactes was sister to Harpactes, but with low support in
the RAxML (Table 3) analyses. Within Harpactes we recovered three groups: (1) the distinct
H. oreskios; (2) the two small-bodied species H. duvaucelli and H. orrhophaeus; and (3) the
large-bodied species, containing the other species, with clearly defined and high support
supported relationships (Fig. 1). The Neotropical clade was recovered with high nodal support
(Table 3), showing the quetzals, Euptilotis and Pharomachrus, as sister to Priotelus and Trogon
43
(Fig. 1). Pharomachrus moccino, the only Central America species, is sister to all other
Pharomachrus species. The two Andean species, P. antisianus and P. auriceps, are not closely
related (Fig. 1). Within Trogon, the most diverse genus in the family, we recovered 5 clades,
all of which include species at both sides of the Andes (Fig. 1).
Time-calibrated tree
The concatenated matrix of RAG1 and RAG2 sequences includes 4757 base pairs for 177
representatives of the Core Land birds (Claramunt and Cracraft 2015; Prum, et al. 2015)
(Supplementary Table 1). Phylogenetic analysis of this matrix recovered a well-supported tree.
Trogonidae diversification started in the Early Miocene, the first of four divergence events are
close to each other, around 20 Ma (Fig. 2). While the Asian species originated during the Late
Miocene/ Early Pliocene, most Neotropical species originated during the Late
Pliocene/Pleistocene (Fig. 2).
Discussion
Phylogenomic contribution to the reconstruction of Trogonidae diversification
Recovering basal relationships in the Trogonidae phylogeny has proven to be challenging,
and previous studies have failed to resolve the relationships among genera (Monteros 1998;
Mayr 2003; Johansson and Ericson 2005; Moyle 2005), either because of incomplete taxon
sampling or inadequate number of markers. Monteros (1998) using only two mtDNA genes
recovered a tree topology similar to the one we recovered, in which taxa from different
biogeographical regions were monophyletic. However, the relationships among genera were
not well supported, and Apalharpactes was not sampled. Johansson and Ericson (2005), and
then Moyle (2005), increased the sampling and added a few nuclear introns, yet there were few
improvements in phylogenetic resolution. Moyle (2005) recovered a paraphyletic Neotropical
group, with the quetzals being sister to all other genera, and the Asian and African group sister
to each other embedded within Trogon and Priotelus. Johansson and Ericson (2005) based on
a combined analysis of mtDNA and three nuclear introns recovered a topology similar to ours,
however, node support for the Neotropical group, and the node grouping Asia and the
Neotropics, received low to moderate support. Hosner, et al. (2010) were the first to include an
Apalharpactes sample, but their results were also inconclusive, as relationships among genera
were poorly supported and biogeographical groups, except for Africa, were not monophyletic.
Our phylogenetic results were the first to recover with moderate to high support the
relationship of almost all currently recognized species, as our analyses recovered most of the
44
nodes with high statistical support (Fig. 1). The nodes that did not receive full support at the
base of the tree (Table 3) are connected by short internodes, probably as a result of an ancient
rapid radiation (Whitfield and Lockhart 2007). Recurrent issues arising from rapid radiations
usually include incomplete lineage sorting (ILS), represented by conflict among gene trees due
to successive events of speciation in short periods of time, which can be accentuated by large
population sizes (Oliver 2013; Suh, et al. 2015). ILS probably was also the main cause of low
support in previous studies that employed few genetic markers, as they could have conflicting
histories (Knowles 2009; Oliver 2013) and probably lacked strong phylogenetic signal to
recover the deep phylogenetic relationships (Salichos and Rokas 2013). Evidence of gene tree
incongruence was strongly observed in the whole-genome analysis of bird diversification,
where there was no single gene tree that fully corroborated the combined topology (Jarvis, et
al. 2014). However, counterintuitive, increasing the number of markers does not necessarily
means an improvement in poorly supported nodes. Instead, expanding the number of markers
increases the probability of discordance among them (Oliver 2013), and thus, notably in events
of rapid radiation, some divergences are expected not to behave as a fully bifurcating tree, but
more like a network (Bapteste, et al. 2013; Suh, et al. 2015) because most genes will have
discordant histories due to ILS (Degnan and Rosenberg 2006). Therefore, concatenation may
be the best approach when the number of possible sites supporting a relationship is concentrated
in a few loci diluted in a high number of loci affected by ISL (Gatesy and Springer, 2014;
Springer and Gatesy, 2016). Nonetheless, based on our results, after the first events of
diversification, most of nodes were recovered with high statistical support for all analysis,
including the Neotropical node, which means that, even though we probably do not have enough
confidence to allege the correct order of events that trogons went through their initial
diversification, we may still infer some hypothesis based on current distribution and ecology.
Diversification and biogeography of Trogons
Trogons are still-hunting predators feeding on insects or small vertebrates, but most of
Asian and Neotropical species also feed on fruits, with quetzals being mostly frugivores. They
inhabit the midstory and canopy of tropical and subtropical forest, with some species occurring
in forested patches of open habitats (e.g. Trogon curucui). Most species are territorialists, with
small territories, and lack the capacity to fly over long distances, usually flying from perch to
perch in short sallies (Collar 2017). The morphological conservatism of fossils compared to
extant species suggests that trogons have not underwent large ecological shifts (Mayr 1999,
2003; Mayr 2005), hence their historical distribution probably was affected by the distribution
45
of suitable habitats through time. Although nowadays there is no continuous patch of suitable
habitats, i.e. forested habitat, between Africa, Asia and America, during the Early Miocene, due
to a warmer climate, most of the dry land was covered by forest habitats, such as the broad-leaf
deciduous (Mixed Mesophytic) forest that covered most of the Northern Hemisphere (Baskin
and Baskin 2016), and forests dominated by deciduous conifers that extended even over the
Article Circle (Jahren 2007; Jahren and Sternberg 2008).
The abundance of forests during the Tertiary is due to both warmer temperatures and
twice the current amount of CO2 concentrations (Zachos, et al. 2001). However, after the
Eocene Climatic Optimum (52 to 50 Ma), in which global mean temperatures were 8-10°C
higher, the world temperature started to cool down with two climatic aberrations, where the
amount of ice in polar regions increased drastically. The first one, known as Oi-1, happened
just above the limits between Eocene and Oligocene (34 Ma) (Zachos, et al. 2001), this
glaciation event caused rapid expansions of Antarctic continental ice-sheets and global
temperatures remained low until a warming trend at the end of Oligocene (Zachos, et al. 2001).
This warm phase that followed extended from the Late Oligocene until middle Miocene (~15
Ma) with the Mid-Miocene Climatic Optimum (17 to 15 Ma) and it was followed by a gradual
cooling, with the culmination in the Glacial cycles throughout the Plio/Pleistocene (Zachos, et
al. 2001). The second aberration, Mi-1, happened during this warm period at the end of the
Oligocene (~23 Ma), and was followed by a series of glaciation events (Zachos, et al. 2001),
period well within the confidence interval for the initial diversification events we recovered in
our time calibrated phylogeny. Both aberrations probably influenced the distribution and rates
of diversification in some groups that have similar distributions as trogons, such as ferns
(Bauret, et al. 2017; Hennequin, et al. 2017), and flowering plants (Li, et al. 2017). Interestingly,
other groups of birds that have similar distributions present different patterns of diversification
than trogons; woodpeckers (Aves: Picidae) and kingfishers (Aves: Alcedinidae) apparently
have dispersed to the New World from the Old World more than once, however these events
seem to be younger than those we recovered for trogons, around 15 to 5 Ma for woodpeckers
(Shakya, et al. 2017), and 10 to 5 Ma for kingfishers (Andersen, et al. 2017). This pattern
suggests that dispersal between Asia and America was possible during a long period of time,
probably experiencing cycles of connection and disconnection due to climatic variations
(Zachos, et al. 2001). Therefore, our temporal framework supports an ancestral lineage
distributed over the Palearctic region (Claramunt and Cracraft 2015), with dispersal to Asia,
46
Africa and America during a short period of time, causing the poorly supported nodes we
observed in our analysis.
Africa and Asia diversification
Even though African and Asian linages are as old as the Neotropical, only 6% and 31%
of species diversity are found in these areas, respectively. Although contentious, there are
probably many reason for the uneven diversity among areas. Monteros (1998) suggests that
competitive exclusion might play a role in this pattern, as African and Asian trogons need to
compete with other groups of frugivores birds, such as mousebirds (Colliformes), hornbills
(Bucerotidae), barbets (Megalaimidae and Lybiidae), turacos (Musophagidae), and several
families of passerines (Irenidae, Pycnonotidae, etc). While the Neotropical trogons are, along
cotingas (Cotingidae) and toucans (Ramphastidae), one of the most important family for seed
dispersal in this region (Collar, et al. 2017).
Inside Africa, except for Apaloderma narina which has six recognized subspecies, the
other two, A. vittatum and A. aequatoriale are monotypic (Collar 2017). However, no
phylogeographic study was conducted to evaluate genetic structure within these species, with
recent studies using other organism as models showing shallow genetic structure probably
originated by aridification of the continent as a response of Plio/Pleistocene climatic
fluctuations (Bowie, et al. 2004; Bowie, et al. 2006; Voelker, et al. 2010). The diversification
event we recovered between A. vittatum and A. narina happened around 7.4 Ma (Fig. 2) and
precedes the beginning of the most drastic climatic fluctuations of the Pliocene, making any
assumption of what may have caused this very hard, in particular considering that Africa has
been geomorphologically stable for the last 40 Ma (Potts and Behrensmeyer 1992). Also, A.
vittatum inhabits the montane forests, while A. narina and A. aequatoriale, inhabits the
lowlands, and although we could not sample A. aequatoriale, previous work recovered it as
sister species to A. narina (Hosner, et al. 2010). Suggesting that other mechanisms may be
responsible for Apaloderma species diversification (Moritz, et al. 2000).
In contrast with previous studies (Hosner, et al. 2010), our analyses recovered the
monophyly of Asian trogons. Although the bootstrap support was moderate for this node in the
likelihood analysis, it was recovered with high statistical support in the Bayesian analysis
(Table 3). This suggest that after the initial diversification of the family, at least two Paleartic
lineages (Claramunt and Cracraft 2015) colonized the Sundaland, the continental shelf that
extended from SE Asia and comprises the Malay Peninsula, and the islands of Borneo, Java,
and Sumatra. The time of diversification we found for Apalharpactes and Harpactes is
47
consistent with the Hymalayan uplift acceleration, derived from India-Asia continental collision
(Hall 2012; Hu, et al. 2017), and with the intermittent glaciations that followed the Mi-1
glaciation at the Oligocene-Miocene boundary (Zachos, et al. 2001). These two events
combined may have shaped Asian trogons diversification, however, making assumptions about
Haparctes diversification involves a very complex history, and it is difficult based on extant
species distribution to make any assumption about possible biogeographic barriers. Current
geography of SE Asia and the Sunda islands can be misleading, the Sunda shelf was once
exposed and covered by forest (Hall 2012; Bruyn, et al. 2014), and sea-level fluctuations were
responsible for islands “formation” and connectivity, especially during the climatic fluctuations
of the Pleistocene (Woodruff 2010). This mechanism is suggested as a possible explanation for
Southeast Asia bird diversification (Lim, Rahman, et al. 2010; Lim, Zou, et al. 2010; Lim, et
al. 2017). However, most of the Harpactes diversification events precede the Pleistocene, and
occurred between the Mid-Miocene Climatic Optimum (17-15 Ma) (Zachos, et al. 2001) and
the Early Pliocene, much older than the diversification events of the Neotropical clade, for
example. The only phylogeographic study conducted so far, with the Philippine Trogon
(Harpactes ardens), demonstrated geographical structure among different island matching
subspecies distribution (Hosner, et al. 2014), whereas H. kasumba, H. diardii and H.
erythrocephalus showed little to no genetic variation in the mtDNA for the few samples used
(Hosner, et al. 2010). Therefore, further studies, with broad sampling are necessary to
understand how the Pleistocene climate, and sea level fluctuation, influenced population
structure, which in turn may shed some light on the initial diversification of this genus.
Neotropical diversification
For the first time, Neotropical trogons were recovered as a monophyletic group with high
statistical support (Monteros 1998; Johansson and Ericson 2005; Moyle 2005; Hosner, et al.
2010). Although most of extant diversity is currently found in Central and South America,
trogons arrived first in the Americas through the Beringia Bridge, northwest North America,
and colonized the whole west coast, during a period when there were vast forests covering
North America (Baskin and Baskin 2016). Therefore, tracing back the events related with the
initial divergences would require extensive palaeontological investigation. The overall trend we
observe in this clade diversification is that Central American lineages occupied South America
through the Panamanian Isthmus, and most of divergence events postdate the Mid-Miocene
Climatic Optimum (17-15 Ma), which marks the beginning of the cooling trend that escalated
to the Plio-Pleistocene glaciations. Also during this period, there was extensive orogenic
48
activity in Mexico, including the uplift of Sierra Madre Occidental (34 – 15 Ma) (Ferrari, et al.
2007) and the formation of the Trans-Mexican Volcanic Belt (35 – 2.5 Ma) (Ferrari, et al. 2000).
Both events triggered climatic changes, which in turn influenced the establishment of major
biomes in Mexico (Ferrari, et al. 1999), that have been shown to have influenced diversification
in Amazillia hummingbirds (Ornelas, et al. 2014), and some plants (Lavin, et al. 2004; Becerra
2005; Arakaki, et al. 2011).
Another major event that shaped Neotropical trogons diversification was the
establishment of the connection between North and South America, through the uplift of the
Isthmus of Panama. The Great American Biotic Interchange allowed inter-continental exchange
of biotas that were previously isolated in both continents and is of great importance for shaping
bird assemblages and diversification (Weir, et al. 2009; Smith and Klicka 2010). Early studies
suggested that the connection was only fully established at 3 Ma (Haug and Tiedeman 1998;
Coates and Stallard 2013; Odea, et al. 2016), however, even though contentious in the literature
(Farris, et al. 2011; Montes, et al. 2012; Bacon, et al. 2013; Bacon, et al. 2015a, b; Hoorn and
Flantua 2015; Lessios 2015; Montes, et al. 2015; Odea, et al. 2016), this date was broadly used
as a calibration point in phylogenetic studies attempting to integrate and synthesize patterns of
dispersion across the Isthmus (review in Bacon, et al. (2015a)). Our results suggest that trogon
dispersion across the Isthmus started as early as 6.5 Ma, with the split of Pharomachrus
moccino from the other Pharomachrus species, and happened at least six additional times
within Trogon diversification, all of them after 4 Ma. These results are also supported by a
former study using only one mitochondrial marker for Trogon (DaCosta and Klicka 2008).
Finally, the most notorious accomplishment of Neotropical trogons was to colonize the
Greater Antilles. The genus Priotelus, which includes species endemic to the islands of Cuba,
P. temnurus, and Hispaniola, P. roseigaster, split from Trogon around 17 Ma (Fig. 2). Trogons
are well known for being weak fliers, so the chances of the ancestor of Priotelus to have
dispersed through the ocean to colonize not just one, but two Caribbean islands are low. One
possible explanation is the land bridge that once connected Central America to South America,
known as GAARlandia (Greater Antilles + Aves Ridge) land bridge (Iturralde-Vinent 1994,
2006). Although this land connection is credited to be much older (35 – 33 Ma) (Alonso, et al.
2011; Rícan, et al. 2013; Nieto-Blázquez, et al. 2017) than the split of Priotelus and Trogon,
during the Middle-Late Miocene, the emerged islands that were part of the land bridge were
still connected by shallow seas (Iturralde-Vinent 2006), and sea levels fluctuations may have
facilitated the dispersal to these islands. Fabre, et al. (2014) studying Caribbean rodents found
49
a similar age (16.5 Ma) for the subfamily of rodents that occupy the Greater Antilles. However,
the sister group is from South America, and the authors suggested that the ancestor of this group
colonized the Caribbean Islands via rafting. Our results imply in a more complex scenario for
the Greater Antilles colonization, and further studies are required to evaluate this late
connection.
Conclusion
In this study we recovered the phylogenetic relationships among almost Trogonidae taxa
using a genomic approach. Coupled with our fossil calibrated time tree, we were able to propose
a model of diversification that related not only how the climate change since the Late Oligocene,
but also the connections between continents, shaped the family diversification. The monophyly
of the different biogeographical regions was recovered, and even though some nodes at the base
of the tree received low support, the pattern of rapid radiation is clear at the initial stages of
trogons diversification. Also, even though trogons are currently restricted to subtropical and
tropical regions, they were widespread lineages in the past, and their diversification was
influenced by forest distribution through time. Our results also identified some interestingly
new questions to be pursued: Are Neotropical trogons species really younger than African and
Asian, or is it just a sampling artifact? What was the influence of past sea level fluctuations in
the diversification of Harpactes? Is competition preveting diversification in Apaloderma?
Materials and Methods
Taxon sampling and DNA extraction
We sampled 48 individuals comprising all genera and currently recognized species of the
Trogonidae family, except for the African Bare-cheeked Trogon (Apaloderma aequatoriale),
and the narrow endemic Javan Trogon (Apalharpactes reinwardtii) (Collar 2017; Gill, et al.
2018; Remsen, et al. 2018). All samples are represented by voucher specimens deposited in
ornithological collections at the American Museum of Natural History (AMNH), Academy of
Natural Sciences of Drexel University (ANSP), Field Museum of Natural History (FMNH),
Instituto Nacional de Pesquisas da Amazônia (INPA), Kansas University (KU), Laboratório de
Genética e Evolução Molecular de Aves - USP (LGEMA), Louisiana Museum of Natural
History (LSUMZ), Museu Paraense Emílio Goeldi (MPEG), Smithsonian Institution National
Museum of Natural History (USNM) and Burke Museum (UWBM) (Appendix S1).
50
DNA from fresh tissue was extracted with the DNeasy kit (Qiagen Inc.), following the
manufacture’s protocol. For taxa lacking fresh tissues we cut toepad clips from museum
specimens with a sterile surgical blade and processed in a dedicated room for ancient DNA
(aDNA Lab, AMNH). Toepads were rinsed with 100% ethanol, and ultra-pure water prior to
digestion to remove any inhibitor that could cause problems in downstream procedures. We
then extracted DNA with the DNeasy kit (Qiagen Inc.), replacing the regular silica columns
with the QIAquick columns, to ensure maximum DNA yield. All extracts were sent to Rapid
Genomics (Gainsville, FL) for library prep and target-capture sequence 2321 loci of
Ultraconserved Elements (UCE) plus 98 conserved exons from 46 genes that were previously
employed in phylogenetic analyses (Hackett, et al. 2008; Kimball, et al. 2009; Harvey, et al.
2017).
UCE and exons assembly
The raw sequence data were processed with the Phyluce script pack (Faircloth 2016). We
employed illumiprocessor (Faircloth 2013) and Trimmomatic (Bolger, et al. 2014) to remove
adapter contamination and low-quality reads. To assemble a reference genome, we mapped the
UCE and exons probes back to the Apaloderma vittatum genome (Gilbert, Jarvis, Li,
Consortium, et al. 2014) using the script phyluce_probe_run_multiple_lastzs_sqlite, and then,
phyluce_probe_slice_sequence_from_genomes to extract the probe region plus 500 base pairs
from each flanking region. Apaloderma exonic regions were identified based on the Gallus
gallus genes, and annotations of CDS and exons were copied to the reference sequences inside
Geneious version R10.2.3 (Kearse, et al. 2012). With these sequences as a reference we mapped
back the clean reads of each individual employing Bowtie2 (Langmead and Salzberg 2012)
plugin 7.2.1 inside Geneious. The consensus sequences were called with the highest quality
threshold and a depth of at least 4 reads. Each locus was aligned with MAFFT (Katoh and
Standley 2013) under default parameters.
Phylogenetic relationships and species tree analysis
Since the intergeneric relationship among trogons are still mostly unresolved (Monteros
1998; Johansson and Ericson 2005; Moyle 2005; Hosner, et al. 2010), we first performed a
maximum likelihood analyses in RAxML v8.2 (Stamatakis 2014), and a Bayesian Inference
analyses in ExaBayes v.1.4 (Aberer, et al. 2014), using the concatenated matrix with three
treatments for missing data: a complete matrix, where no missing data was allowed, and two
where the missing data was allowed, a 95% and 75% completeness matrix, in which each locus
should have at least 95% or 75%, respectively, of all individuals in the matrix. As outgroups
51
we selected one mousebird (Colius striatus, (Gilbert, Jarvis, et al. 2014b)), and a roller
(Leptosomus discolor, (Gilbert, Jarvis, et al. 2014a)), suggested by recent studies as the closest
relatives to the Trogonidae family (Jarvis, et al. 2014; Prum, et al. 2015). We also estimated a
species tree using the SVDquartets (Chifman and Kubatko 2014) implemented in PAUP*
v4a(build157) (Swofford 2002), that samples quartets of individuals for each gene tree and infer
an unrooted phylogeny, performing a species tree using a coalescent approach. We
exhaustively sampled all quartets and performed a 100 bootstrap to quantify the support for
each node.
Dating analysis
To date the Trogonidae phylogeny we employed the slow evolving recombination-
activating genes (RAG-1 and RAG-2) and a dense sampling for the Core Landbirds group
(Telluraves), with the same calibration points used by Claramunt and Cracraft (2015). The
concatenated matrix was partitioned by codon and the best partition and substitution model
schemes were selected by PartitionFinder2 (Lanfear, et al. 2017).
Acknowledgements
The authors thankfully acknowledge all the curators and curatorial assistants of the
American Museum of Natural History, New York, USA (AMNH), Academy Academy of
Natural Science of Drexel University, Philadelphia, USA (ANSP); Field Museum of Natural
History, Chicago, USA (FMNH); Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil
(INPA); Kansas University (KU), Laboratório de Genética e Evolução Molecular de Aves –
USP (LGEMA), Lousiana State University Museum of Natural Science, Baton Rouge, USA
(LSUMZ); and Museu Paraense Emílio Goeldi, Belém, Brazil (MPEG), Smithsonian Institution
National Museum of Natural History (USNM), for borrowing tissue samples under their care.
We are also grateful for all collectors involved in the fieldwork that make this paper possible.
We thank L. Moraes for early input on this paper. MF acknowledge CAPES for his PhD
fellowship, and CAPES PDSE fellowship (# 88881.133440/2016-01) and the support from the
AMNH Frank M. Chapman Memorial Fund. The authors also thanks the grant Dimensions US-
Biota-São Paulo: Assembly and evolution of the Amazon biota and its environment: an
integrated approach, co-funded by the US National Science Fundation (NSF DEB 1241056) to
J.C. and the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP grant
#2012/50260-6) to Lucia Lohmann. AA and CCR are supported by CNPq research productivity
fellowships. The authors acknowledge the National Laboratory for Scientific Computing
52
(LNCC/MCTI, Brazil) for providing HPC resources of the SDumont supercomputer, which
have contributed to the research results reported within this paper.
References
Aberer AJ, Kobert K, Stamatakis A. 2014. ExaBayes: massively parallel bayesian tree inference
for the whole-genome era. Mol Biol Evol 31:2553-2556.
Alonso R, Crawford AJ, Bermingham E. 2011. Molecular phylogeny of an endemic radiation
of Cuban toads (Bufonidae: Peltophryne) based on mitochondrial and nuclear genes. J
Biogeogr 39:434-451.
Andersen MJ, McCullough JM, Mauck WM, Smith BT, Moyle RG. 2017. A phylogeny of
kingfishers reveals an Indomalayan origin and elevated rates of diversificatio on oceanic
islands. J Biogeogr early view.
Arakaki M, Christin P-A, Nyffeler R, Lendel A, Eggli U, Ogbum RM, Spriggs E, Moore MJ,
Edwards EJ. 2011. Contemporaneous and recent radiations of the world's major succulent
plant lineages. PNAS 108:8379-8384.
Bacon CD, Mora A, Wagner WL, Jaramillo CA. 2013. Testing geological models of evolution
of the Isthmus of Panama in a phylogenetic framework. Botanical Journal of the Linnean
Society 171:287-300.
Bacon CD, Silvestro D, Jaramillo C, Smith BT, Chakrabarty P, Antonelli A. 2015a. Biological
evidence supports an early and complex emergence of the Isthmus of Panama. PNAS
112:6110-6115.
Bacon CD, Silvestro D, Jaramillo C, Smith BT, Chakrabarty P, Antonelli A. 2015b. Reply to
Lessios and Marko et al.: Early and progressive migration across the Isthmus of Panama
is robust to missing data and biases: Fig. 1. PNAS 112:E5767-E5768.
Baker PA, Fritz SC, Dick CW, Eckert AJ, Horton BK, Manzoni S, Ribas CC, Garzione CN,
Battisti DS. 2014. The emerging field of geogenomics: Constraining geological problems
with genetic data. Earth-Sci Rev 135:38-47.
Bapteste E, Iersel Lv, Janke A, Kelchner S, Kelk S, McInerney JO, Morrison DA, Nakhleh L,
Steel M, Stougie L, et al. 2013. Networks: expanding evolutionary thinking. Trends Genet
29:439-441.
Baskin JM, Baskin CC. 2016. Origins and relationships of the Mixed Mesophytic Forest of
Oregon–Idaho, China, and Kentucky: Review and Synthesis. Ann MO Bot Gard 101:525-
552.
Bauret L, Gaudeul M, Sundue MA, Parris BS, Ranker TA, Rakotondrainibe F, Hennequin S,
Ranaivo J, Selosse M-A, Rouhan G. 2017. Madagascar sheds new light on the molecular
systematics and biogeography of grammitid ferns: New unexpected lineages and
numerous long-distance dispersal events. Mol Phylogenet Evol 111:1-17.
Becerra JX. 2005. Timing the origin and expansion of the Mexican tropical dry forest. PNAS
102:10919-10923.
Bolger AM, Lohse M, Usadel B. 2014. Trimmomatic: a flexible trimmer for Illumina sequence
data. Bioinformatics 30:2114-2120.
Bouckaert R, Heled J, Kuhnert D, Vaughan T, Wu CH, Xie D, Suchard MA, Rambaut A,
Drummond AJ. 2014. BEAST 2: a software platform for Bayesian evolutionary analysis.
PLoS Comput Biol 10:e1003537.
53
Bowie RC, Fjeldså J, Hackett SJ, Crowe TM. 2004. Molecular evolution in space and through
time: mtDNA phylogeography of the Olive Sunbird (Nectarinia olivacea/obscura)
throughout continental Africa. Mol Phylogenet Evol 33:56-74.
Bowie RCK, Fjeldså J, Hackett SJ, Bates JM, Crowe TM. 2006. Coalescent mdels reveal the
relative roles of ancestral polymorphism, vicariance, and dispersal in shaping
phylogeographical structure of an African montane forest robin. Mol Phylogenet Evol
38:171-188.
Branstetter MG, Longino JT, Ward PS, Faircloth BC. 2017. Enriching the ant tree of life:
enhanced UCE bait set for genome-scale phylogenetics of ants and other Hymenoptera.
Methods in Ecology and Evolution.
Bruyn M, Stelbrink B, Morley RJ, Hall R, Carvalho GR, Cannon CH, Bergh Gvd, Meijaard E,
Metcalfe I, Boitani L, et al. 2014. Borneo and Indochina are major evolutionary hotspots
for Southeast Asian biodiversity. Syst Biol 63:879-901.
Bryson RW, Jr., Faircloth BC, Tsai WLE, McCormack J, Klicka J. 2016. Target enrichment of
thousands of ultraconserved elements sheds new light on early relationships within New
World sparrows (Aves: Passarelidae). Auk 133:451-458.
Chifman J, Kubatko LS. 2014. Quartet inference from SNP data under the coalescent model.
Bioinformatics 30:3317-3324.
Claramunt S, Cracraft J. 2015. A new time tree reveals Earth history's imprint on the evolution
of modern birds. Sci Adv 1:e1501005.
Coates AG, Stallard RF. 2013. How old is the Isthmus of Panama? Bull Mar Sci 89:801-813.
Collar N. 2017. Trogons (Trogonidae). Barcelona: Lynx Ediciones.
Cracraft J. 1981. Toward a phylogenetic classification of the recent birds of the world (Class
Aves). Auk 98:681-714.
DaCosta JM, Klicka J. 2008. The Great American Interchange in birds: a phylogenetic
perspective with the genus Trogon. Mol Ecol 17:1328-1343.
Degnan JH, Rosenberg NA. 2006. Discordance of species trees with their most likely gene
trees. PLoS Genet 2:e68.
Degnan JH, Rosenberg NA. 2009. Gene tree discordance, phylogenetic inference and the
multispecies coalescent. Trends Ecol Evol 24:332-340.
Handbook of the birds of the world [Internet]. Barcelona: Lynx Ediciones; 2017 [cited 2017
12/19]. Available from: http://www.hbw.com/
Donoghue PC, Moore BR. 2003. Toward an integrative historical biogeography. Integr Comp
Biol 43:261-270.
Esselstyn JA, Oliveros CH, Swanson MT, Faircloth BC. 2017. Investigating difficult nodes in
the placental mammal tree with expanded taxon sampling and thousands of
Ultraconserved Elements. Syst Biol early view.
Fabre P-H, Vilstrup JT, Raghavan M, Sarkissian CD, Willerslev E, Douzery EJP, Orlando L.
2014. Rodents of the Caribbean: origin and diversification of hutias unravelled by next-
generation museomics. Biol Lett 10:201440266.
Faircloth BC. 2013. illumiprocessor: a trimmomatic wrapper for parallel adapater and quality
trimming. doi: 10.6079/J9ILL
Faircloth BC. 2016. PHYLUCE is a software package for the analysis of conserved genomic
loci. Bioinformatics 32:786-788.
Faircloth BC, Branstetter MG, White ND, Brady SG. 2015. Target enrichment of
ultraconserved elements from arthropods provides a genomic perspective on relationships
among Hymenoptera. Mol Ecol Resour 15:489-501.
Faircloth BC, McCormack JE, Crawford NG, Harvey MG, Brumfield RT, Glenn TC. 2012.
Ultraconserved elements anchor thousands of genetic markers spanning multiple
evolutionary timescales. Syst Biol 61:717-726.
54
Farris DW, Jaramillo C, Bayona G, Restrepo-Moreno SA, Montes C, Cardona A, Mora A,
Speakman RJ, Glascock MD, Valencia V. 2011. Fracturing of the Panamanian Isthmus
during initial collision with South America. Geology 39:1007-1010.
Ferrari L, Conticelli S, Vaggelli G, Petrone CM, Manetti P. 2000. Late Miocene volcanism and
intra-arc tectonics during the early development of the Trans-Mexican Volcanic Belt.
Tectonophysics 318:161-185.
Ferrari L, Lopez-Martínez M, Aguirre-Díaz G, Carrasco-Núñez G. 1999. Space-time patterns
of Cenozoic arc volcanism in central Mexico: From the Sierra Madre Occidental to the
Mexican Volcanic Belt. Geology 27:303-306.
Ferrari L, Valencia-Moreno M, Bryan S. 2007. Magmatism and tectonics of the Sierra Madre
Occidental and its relation with the evolution of the western margin of North America.
Geol Soc Am Spec Pap 422:1-39.
Gatesy J, Springer MS. 2014. Phylogenetic analysis at deep timescales: unreliable gene trees,
bypassed hidden support, and the coalescence/concatalescence conundrum. Mol
Phylogenet Evol 80:231-266.
Gilbert M, Jarvis ED, Li B, Consortium TAG, Wang J, Zhang G. 2014. Genomic data of the
Bar-tailed trogon (Apaloderma vittatum) GigaScience Database.
Gilbert MP, Jarvis ED, Li B, Li C, Consortium TAG, Wang J, Zhang G. 2014a. Genomic data
of the Cucko roller (Leptosomus discolor). GigaScience Database.
Gilbert MP, Jarvis ED, Li B, Li C, Consortium TAG, Wang J, Zhang G. 2014b. Genomic data
of the Speckled mousebird (Colius striatus). GigaScience Database.
Gill F, Donsker D. 2018. IOC World Bird List (v8.1). doi: 10.14344/IOC.ML.8.1
Hackett SJ, Kimball RT, Reddy S, Bowie RC, Braun EL, Braun MJ, Chojnowski JL, Cox WA,
Han KL, Harshman J, et al. 2008. A phylogenomic study of birds reveals their
evolutionary history. Science 320:1763-1768.
Hall R. 2012. Late Jurassic-Cenozoic reconstructions of the Indonesian region and the Indian
Ocean. Tectonophysics 570-571:1-41.
Harvey MG, Aleixo A, Ribas C, Brumfield RT. 2017. Habitat association predicts genetic
diversity and population divergence in Amazonian birds. Am Nat Early View.
Haug GH, Tiedeman R. 1998. Effect of the formation of the Isthmus of Panama on Atlantic
Ocean thermohaline circulation. Nature 393:673-676.
Hennequin S, Rouhan G, Salino A, Duan Y-F, Lepeigneux M-C, Guillou M, Ansell S, Almeida
TE, Zhang L-B, Schneider H. 2017. Global phylogeny and biogeography of the fern genus
Ctenitis (Dryopteridaceae), with a focus on the Indian Ocean region. Mol Phylogenet
Evol 112:277-289.
Hoorn C, Flantua S. 2015. An early start for the Panama land bridge. Science 348:186-187.
Hosner PA, Sánchez-González LA, Peterson AT, Moyle RG. 2014. Climate-driven
diversification and Pleistocene Refugia in Philippine birds: Evidence from
phylogeographic structure and palaeoenvironmental niche modeling. Evolution 68:2658-
2674.
Hosner PA, Sheldon FH, Lim HC, Moyle RG. 2010. Phylogeny and biogeography of the Asian
trogons (Aves: Trogoniformes) inferred from nuclear and mitochondrial DNA sequences.
Mol Phylogenet Evol 57:1219-1225.
Hu X, Wang J, An W, Garzanti E, Li J. 2017. Constraining the timing of the India-Asia
continental collision by the sedimentary record. Sci China Earth Sci 60:603.
Iturralde-Vinent MA. 1994. Cuba geology: a new plate-tectonic synthesis. J Petrol Geol 17:39-
70.
Iturralde-Vinent MA. 2006. Meso-Cenozoic Caribbean paleogeography: implications for the
historical biogeography of the region. Int Geol Rev 48:791-827.
55
Jahren AH. 2007. The Artic Forest of the Middle Eocene. Annu Rev Earth Planet Sci 35:509-
540.
Jahren AH, Sternberg LSL. 2008. Annual patterns within tree rings of the Artict middle Eocene
(ca. 45 Ma): Isotopic signatures of precipitation, relative humidity, and deciduousness.
Geology 36:99-102.
Jarvis ED, Mirarab S, Aberer AJ, Li B, Houde P, Li C, Ho SY, Faircloth BC, Nabholz B,
Howard JT, et al. 2014. Whole-genome analyses resolve early branches in the tree of life
of modern birds. Science 346:1320-1331.
Johansson US, Ericson PGP. 2005. A re-evaluation of basal phylogenetic relationships within
trogons (Aves: Trogonidae) based on nuclear DNA sequences. J Zool Syst Evol Res
43:166-173.
Katoh K, Standley DM. 2013. MAFFT Multiple Sequence Alignment Software Version 7:
Improvements in Performance and Usability. Mol Biol Evol 30:772-780.
Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, Buxton S, Cooper A,
Markowitz S, Duran C, et al. 2012. Geneious Basic: An integrated and extendable desktop
software platform for the organization and analysis of sequence data. Bioinformatics
28:1647-1649.
Kimball RT, Braun EL, Barker FK, Bowie RC, Braun MJ, Chojnowski JL, Hackett SJ, Han
KL, Harshman J, Heimer-Torres V, et al. 2009. A well-tested set of primers to amplify
regions spread across the avian genome. Mol Phylogenet Evol 50:654-660.
Knowles LL. 2009. Statistical Phylogeography. Annu Rev Ecol Evol Syst 40:593-612.
Kristoffersen AV. 2002. An early Paleogene trogon (Aves: Trogoniformes) from the Fur
Formation, Denmark. J Vert Paleontol 22:661-666.
Lanfear R, Frandsen PB, Wright AM, Senfeld T, Calcott B. 2017. PartitionFinder 2: New
methods for selecting partitioned models of evolution for molecular and morphological
phylogenetic analyses. Mol Biol Evol 34:772-773.
Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. Nat Methods
9:357-359.
Lavin M, Schrire BP, Lewis GP, Pennington RT, Delgado-Salinas A, Thulin M, Hughes CE,
Matos AB, Wojciechowski MF. 2004. Metacommunity process rather than continental
tectonic history better explains geographically structured phylogenies in legumes. Phil
Trans R Soc B 359:1509-1522.
Lessios HA. 2015. Appearance of an early closure of the Isthmus of Panama is the product of
biased inclusion of data in the metaanalysis. PNAS 112:E5765.
Lexer C, Mangili S, Bossolini E, Forest F, Stölting KN, Pearman PB, Zimmermann NE,
Salamin N, Carine M. 2013. ‘Next generation’ biogeography: towards understanding the
drivers of species diversification and persistence. J Biogeogr 40:1013-1022.
Li M, Ohi-Toma T, Gao Y-D, Xu B, Zhu Z-M, Ju W-B, Gao X-F. 2017. Molecular
phylogenetics and historical biogeography of Sorbus senso stricto (Rosaceae). Mol
Phylogenet Evol 111:76-86.
Lim HC, Gawin DF, Shakya SB, Harvey MG, Rahman MA, Sheldon FH. 2017. Sundaland's
east-west rain forest population structure: variable manifestation in four polytypic bird
species examined using RAD-Seq and plumage analyses. J Biogeogr 44:2259-2271.
Lim HC, Rahman MA, Lim SLH, Moyle RG, Sheldon F. 2010. Revisiting Wallace's haunt:
Coalescent simulations and comparative niche modeling reveal historical mechanisms
that promoted avian population divergence in the Malay Archipelago. Evolution 65:321-
334.
Lim HC, Zou F, Taylor SS, Marks BD, Moyle RG, Voelker G, Sheldon F. 2010. Phylogeny of
magpie-robins and shamas (Aves: Turdidae: Copsychus and Trichixos): implications for
island biogeography in Southeast Asia. J Biogeogr 37:1894-1906.
56
Livezey BC, Zusi RL. 2007. Higher-order phylogeny of modern birds (Theropoda, Aves:
Neornithes) based on comparative anatomy. II. Analysis and discussion. Zoological
Journal of the Linnean Society 149:1-95.
Manthey JD, Campillo LC, Burns KJ, Moyle RG. 2016. Comparison of Target-Capture and
Restriction-Site Associated DNA Sequencing for Phylogenomics: A Test in Cardinalid
Tanagers (Aves, Genus: Piranga). Syst Biol 65:640-650.
Maurer DR, Raikow RJ. 1981. Appendicular myology, phylogeny and classificaiton of the
avian order Coraciiformes (inluding Trogoniformes). Ann Carnegie Mus 50:417-434.
Mayr G. 1999. A new trogon from the Middle Oligocene of Céreste, France. Auk 116:427-434.
Mayr G. 2005. New trogons from the early Tertiary of Germany. Ibis 147:512-518.
Mayr G. 2003. On the phylogenetic relationships of trogons (Aves, Trogonidae). Journal of
Avian Biology 34:81-88.
Mayr G. 2009. Paleogene Fossil Birds. Germany: Springer.
McCormack JE, Faircloth BC. 2013. Next-generation phylogenetics takes root. Mol Ecol
22:19-21.
McCormack JE, Faircloth BC, Crawford NG, Gowaty PA, Brumfield RT, Glenn TC. 2012.
Ultraconserved elements are novel phylogenomic markers that resolve placental mammal
phylogeny when combined with species-tree analysis. Genome Res 22:746-754.
McCormack JE, Harvey MG, Faircloth BC, Crawford NG, Glenn TC, Brumfield RT. 2013. A
phylogeny of birds based on over 1,500 loci collected by target enrichment and high-
throughput sequencing. PLoS One 8:e54848.
Meiklejohn KA, Faircloth BC, Glenn TC, Kimball RT, Braun EL. 2016. Analysis of a rapid
evolutionary radiation using Ultraconserved Elements: Evidence for a bias in some
multispecies coalescent methods. Syst Biol 65:612-627.
Metzker ML. 2010. Sequencing technologies - the next generation. Nature Reviews Genetics
11:31-46.
Monteros AE. 2000. Higher-level phylogeny of Trogoniformes. Mol Phylogenet Evol 14:20-
34.
Monteros AE. 1998. Phylogenetic relationships among the Trogons. Auk 115:937-954.
Montes C, Cardona A, Jaramillo C, Pardo A, Silva JC, Valencia V, Ayala C, Perez-Angel LC,
Rodriguez-Parra LA, Ramirez V, et al. 2015. Middle Miocene closure of the Central
American Seaway. Science 348:226-229.
Montes C, Cardona A, McFadden R, Moron SE, Silva CA, Restrepo-Moreno S, Ramirez DA,
Hoyos N, Wilson J, Farris D, et al. 2012. Evidence for middle Eocene and younger land
emergence in central Panama: Implications for Isthmus closure. Geol Soc Am Bull
124:780-799.
Moritz C, Patton JL, Schneider CJ, Smith TB. 2000. Diversification of rainforest fauna: An
integrated molecular approach. Annu Rev Ecol Syst 31:533-563.
Moyle RG. 2005. Phylogeny and biogeographical history of Trogoniformes, a pantropical bird
order. Biol J Linn Soc 84:725-738.
Moyle RG, Oliveros CH, Andersen MJ, Hosner PA, Benz BW, Manthey JD, Travers SL, Brown
RM, Faircloth BC. 2016. Tectonic collision and uplift of Wallacea triggered the global
songbird radiation. Nat Commun 7:12709.
Nieto-Blázquez M, Antonelli A, Roncal J. 2017. Historical biogeography of endemic seed plant
genera in the Caribbean: Did GAARlandia play a role? Ecol Evol Early View.
Odea A, Lessios HA, Coates AG, Eytan RI, Restrepo-Moreno SA, Cione AL, Collins LS, de
Queiroz A, Farris DW, Norris RD, et al. 2016. Formation of the Isthmus of Panama. Sci
Adv 2:e1600883-e1600883.
Oliver J. 2013. Microevolutionary processes generate phylogenomic discordance at ancient
divergences. Evolution 67:1823-1830.
57
Ornelas JF, González C, de los Monteros AE, Rodríguez-Gómez F, García-Feria LM, Riddle
B. 2014. In and out of Mesoamerica: temporal divergence of Amazilia hummingbirds pre-
dates the orthodox account of the completion of the Isthmus of Panama. Journal of
Biogeography 41:168-181.
Potts R, Behrensmeyer AK. 1992. Late Cenozoic terrestrial ecosystems. In: Beherensmeyer
AK, Damuth JD, DiMichele WA, Potts R, Sues HD, WIng SL, editors. Terrestrial
ecosystems through time. Evolutionary paleoecology of terrestrial plants and animals.
Chicago: University of Chicago Press.
Prum RO, Berv JS, Dornburg A, Field DJ, Townsend JP, Lemmon EM, Lemmon AR. 2015. A
comprehensive phylogeny of birds (Aves) using targeted next-generation DNA
sequencing. Nature 526:569-573.
Tracer v1.6 [Internet]. 2014. Available from: http://beast.bio.ed.ac.uk/Tracer
Remsen JV, Jr., Areta JI, Cadena CD, Claramunt S, Jaramillo C, Pacheco JF, Pérez-Emen J,
Robbins MB, Stiles FG, Stotz DF, et al. 2018. A classification of the bird species of South
America. American Ornithologists' Union.
http://www.museum.lsu.edu/~Remsen/SACCBaseline.htm
Rícan O, Piálek L, Zardoya R, Doadrio I, Zrzavý J. 2013. Biogeography of the Mesoamerican
Cichlidae (Teleostei: Heroini): colonization through the GAARlandia land bridge and
early diversification. J Biogeogr 40:579-593.
Salichos L, Rokas A. 2013. Inferring ancient divergences requires genes with strong
phylogenetic signals. Nature 497:327-331.
Shakya SB, Fuchs J, Pons JM, Sheldon F. 2017. Tapping the woodpecker tree for evolutionary
insight. Mol Phylogenet Evol in press.
Smith BT, Klicka J. 2010. The profound influence of the Late Pliocene Panamanian uplift on
the exchange, diversification, and distribution of New World birds. Ecography.
Springer MS, Gatesy J. 2015. The gene tree delusion. Mol Phylogenet Evol 94:1-33.
Stamatakis A. 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysis of
large phylogenies. Bioinformatics 30:1312-1313.
Suh A, Smeds L, Ellegren H. 2015. The Dynamics of Incomplete Lineage Sorting across the
Ancient Adaptive Radiation of Neoavian Birds. PLoS Biol 13:e1002224.
Swofford R. 2002. PAUP*. Phylogenetic analysis using parsimony (* and other methods).
Version 4. Version 4. Sunderland, Massachusetts: Sinauer Associates.
Voelker G, Outlaw RK, Bowie RCK. 2010. Pliocene forest dynamics as a primary driver of
African bird speciation. Global Ecol Biogeogr 19:111-121.
Weir JT, Bermingham E, Schluter D. 2009. The Great American Biotic Interchange in birds.
PNAS 106:21737-21742.
Weir JT, Schluter D. 2008. Calibrating the avian molecular clock. Mol Ecol 17:2321-2328.
Whitfield JB, Lockhart PJ. 2007. Deciphering ancient rapid radiations. Trends Ecol Evol
22:258-265.
Woodruff DS. 2010. Biogeography and conservation in Southeast Asia: how 2.7 million years
of repeated environmental fluctuations affect today's patterns and the future of the
remaining refugial-phase biodiversity. Biodivers Conserv 19:919-941.
Zachos J, Pagani M, Sloan L, Thomas E, Billups K. 2001. Trens, rhytms, and aberrations in
global climate 65 Ma to present. Science 27:686-693.
58
Table 1 – Samples used in this study, the museum voucher numbers, locality and geographical coordinates
(when available), number of UCE reads, and loci recovered for each sample.
Species Museum voucher Locality Clean
reads
UCE
loci
Apaloderma vittatum SRP028834 Tanzania: Udzungwa Mts. - 2,228*
Apaloderma narina AMNH DOT-12430 Liberia: Lofa, Ziggida (08°02'15.5"N 9°31'49.5"W) 3,607,056 2,228
Apalharpactes mackloti LSUMZ B-49104 Indonesia: Sumatra 1,664,511 2,220
Apalharpactes mackloti AMNH 633881 Indonesia: Sumatra, Bandar-Baroe (03°15'57.6''N 98°30'49.9''E) 2,758,684 2,080
Harpactes ardens USNM 607340 Philippines: Barrio Via, Sitio Hot Springs, Baggao Mun. (17°50'N,
122°01'E) 1,193,041 2,208
Harpactes diardii AMNH DOT-563 Malaysia: Sabah, Klias Forest Reserve (05°19’34’’N
115°40’25’’E) 3,601,173 2,226
Harpactes oreskios ANSP 16308 Malaysia: Sabah, Mendolong (04°54'27.6"N 115°47'04.5"E) 5,208,017 2,228
Harpactes orrhophaeus AMNH DOT-15159 Malaysia: Sabah, Mt. Lucia (04°27’37.8’’N 117°55’20.4’’E) 4,250,801 2,228
Harpactes duvaucelli LSUMZ B-38592 Malaysia: Sabah, Imbak Valley, ca 60 km S Telupid (5°06’N
117°01’51’’E) 887,312 2,222
Harpactes fasciatus AMNH 778649 India: Dangs, Bhawandagad 5,386,424 2,218
Harpactes erythrocephalus AMNH DOT-12240 Vietnam: Quang Nam, Ngoc Linh Range (15°11’00’’N
108°02’00’’E) 2,126,329 2,224
Harpactes wardii AMNH 307761 Myanmar: Laukkaing 5,151,969 2,198
Harpactes whiteheadi LSUMZ B-52627 Malaysia: Sabah, Tambuman, Mt. Trus Madi (05°35’09’’N
116°29’26’’E) 11,299,280 2,228
Harpactes kasumba AMNH DOT-15326 Malaysia: Sabah, Ulu Tungud Forest Reserve, Melian Range
(05°50’48’’N 117°10’57’’E) 4,264,359 2,228
Euptilotis neoxenus AMNH DOT-11080 USA: Arizona, Ramsey Canyon Preserve (31°26'50.2"N
110°18'25.8"W) 1,955,116 2,186
Pharomachrus pavoninus INPA A-1993 Brazil: Amazonas, Parque Nacional do Jaú (01°49’50’’S
61°35’45’’W) 2,080,592 2,215
Pharomachrus auriceps
hargitti AMNH 175988 Ecuador: Baeza, Arriba (0°27’54’’S 77°53’44.9’’W) 6,034,956 2,210
Pharomachrus auriceps
auriceps FMNH 473723 Peru: Rodriguez de Mendoza (06°S 77°W) 2,620,376 2,221
Pharomachrus fulgidus AMNH 322895 Venezuela: Near village of Junquito on Colonia Tovar Rd
(10°27’23’’N 67°04’31’’W) 4,665,318 1,864
Pharomachrus moccino AMNH 326512 Honduras: Mt Pucca, Gracias (14°34’43’’N 88°38’30’’W) 5,630,314 2,215
Pharomachrus antisianus ANSP 19429 Ecuador: Napo, 12 km NNE El Chaco; Mirador 5,651,764 2,228
Priotelus temnurus ANSP 20257 Cuba 1,644,934 2,220
Priotelus roseigaster KU 8098 Dominican Republic: Parque Nacional Sierra Baoruco, Pueblo
Viejo (18°12’N 71°32’W) 1,431,709 2,221
Trogon clathratus USNM 613996 Panama: Bocas del Toro, Los Planes (08°35’43’’N 82°14’16’’W) 3,200,785 2,158
Trogon mesurus ANSP 19305 Ecuador: Esmeraldas, 20 km ENE Muisne (0°38’51’’N
79°59’59’’W) 7,341,190 2,142
Trogon massena KU 2073 Mexico: Campeche, Silvituc (18°13’48’’N 90°12’W) 1,689,867 2,224
Trogon comptus LSUMZ B-11829 Ecuador: Esmeraldas, El Placer (0°52’N 78°33’W) 2,072,859 2,228
Trogon melanurus INPA A-1955 Brazil: Amazonas, Parque Nacional do Jaú (01°49’50’’S
61°35’45’’W) 2,451,461 2,225
Trogon viridis INPA A-5240 Brazil: Pará, Aveiro, left bank Tapajós River (03°42.3’S
55°35.5’W) 1,893,902 2,226
Trogon chionurus LSUMZ B-28571 Panama: Colón, Achiote Road (09°13’32’’N 80°0’56’’W) 1,879,103 2,225
Trogon melanocephalus USNM 646857 El Salvador: La Paz, Aeropuerto Internacional El Salvador
(13°25’57’’N 89°03’50’’W) 1,521,530 2,224
Trogon citreolus UWBM 101087 Mexico: Michoacán, Lazaro Cardenas, La Mira (18°05.71’N
102°23.71’W) 1,311,613 2,224
Trogon bardii LSUMZ B-71992 Costa Rica: Osa, Los Charces (08°40’19’’N 83°30’19’’W) 2,036,944 2,226
Trogon violaceus MPEG CN437 Brazil: Pará, Alenquer, ESEC Grão-Pará (0°09’S 55°11’W) 1,251,316 2,222
Trogon caligatus LSUMZ B-66270 Peru: Tumbes, El caucho Biological Station (3°49’25’’S
80°15’37’’W) 4,878,667 2,150
Trogon ramonianus INPA A-5449 Brazil: Pará, Santarém, Rio Arapiuns (3°19’S 55°20’W) 2,665,900 2,228
Trogon curucui INPA A-5286 Brazil: Pará, Aveiro, left bank Tapajós River (3°42.3’S
55°35.5’W) 1,157,694 2,221
Trogon aurantius LGEMA 15782 Brazil: Minas Gerais, RPPN Serra do Caraça (20°07’01’’S
43°29’16’’W) 1,162,924 2,213
Trogon surrucura MPEG SC015 Brazil: Santa Catarina, Blumenau, Vila Itoupava (26°39’59’’S
49°05’41’’W) 2,005,634 2,224
Trogon rufus tenellus LSUMZ B-26564 Panama: Colón, Gamboa (9°09’25’’N 79°45’36’’W) 4,118,529 2,228
Trogon rufus amazonicus INPA A-5284 Brazil: Pará, Aveiro, left bank Tapajós River (3°42.3’S
55°35.5’W) 3,892,857 2,228
Trogon rufus chrysochlorus LGEMA 9557 Brazil: São Paulo, Ubatuba (23°23’24’’S 45°05’24’’W) 1,161,086 2,225
59
Trogon elegans FMNH 434014 El Salvador: Sonsonate: Izalco, Canton Las Laja (13°45’35’’N
89°40’21’’W) 475,853 2,201
Trogon mexicanus FMNH 343220 Mexico: Jalisco, Puerto los Mazos, Sierra de Manantlan
(19°28’09’’N 103°56’51’’W) 1,322,925 2,222
Trogon aurantiiventris LSUMZ B-41625 Panama: Bocas del Toro, Chiriqui (8°47’29’’N 82°12’35’’W) 6,441,454 2,228
Trogon collaris puella FMNH 394272 Mexico: Oaxaca, San Gabriel Mixtepec, Sierra de Miahuatlan
(16°09’56’’N 97°01’29’’W) 292,340 2,114
Trogon collaris collaris MPEG CN450 Brazil: Pará, Alenquer, ESEC Grão-Pará (0°09’S 55°11’W) 1,361,638 2,221
Trogon personatus LSUMZ B-48503 Guyana: Potaro-Siparuni, Kopinang Mountain (4°57’54’’N
59°54’49’’W) 1,826,664 2,228
Table 2 – Summary information of each method, including number of loci, total length of the concatenated
alignment, mean length size per locus, minimum and maximum length, and the total number of the Parsimony
Informative (PI) sites. Complete 75% 95%
Number of loci 1421 2110 2217
Total lenght 725090 1054512 1099526
Mean length size 510.27 499.77 495.95
Min-max length 259-1145 162-1145 162-1145
Number of PI sites 37,880 55,060 57,259
Table 3 – Node support for recalcitrant nodes in the Trogonidae phylogeny. RAxML ExaBayes SVDq
75% 95% complete 75% 95% complete 95%
Asian + Neotropical 70 62 84 1.0 1.0 1.0 -
Apalharpactes + Harpactes 60 46 52 1.0 1.0 1.0 -
Neotropical 100 100 100 1.0 1.0 1.0 100
60
Figure 1 – Phylogeny of Trogonidae inferred with ExaBayes summarizing the results from other analyses. The
circle at each node represent the statistical support for the RAxML analyses and the species tree reconstruction
inferred by SVDq. Green lines represent distribution shifts from Central America to South America. Trogon
species were group in five species groups highlighted with grey boxes: “rufus”, “collaris”, “melanurus”, “viridis”,
and “violaceus”.
61
Figure 2 – Time-calibrated phylogeny of Trogonidae inferred from the concatenated dataset of RAG1 and RAG2
genes using BEAST. This tree represents part of the tree calibrated using (Claramunt and Cracraft 2015)
calibrations, complete taxon data in Supplementary Table 1. The basal nodes were constrained to match the UCE
topology, all other nodes have a red circle, if the posterior probability is 1.0, or the posterior is written next to the
node. Timings of major splits are shown next to each node. Blue bars represent the 95% HPD estimates of node
height. Green lines represent distribution shifts from Central America to South America. The top-right figure
represents the whole tree with calibration points as red circles.
62
Supplementary Table S1 – Table containing taxonomic information on all specimens employed in the RAG time
tree. The RAG1 and RAG2 column refers to GenBank accession numbers for these two genes. Taxonomy follows
del Hoyo, et al. (2017).
Order Family Species RAG1 RAG2
Passeriformes Thraupidae Thraupis cyanocephala AY057035 AY443236
Passeriformes Emberizidae Emberiza schoeniclus AY056992 AY443143
Passeriformes Passeridae Passer montanus AF143738 AY443198
Passeriformes Prunellidae Prunella collaris AY057024 AY443213
Passeriformes Dicaeidae Dicaeum aeneum AY443282 AY443139
Passeriformes Regulidae Regulus calendula AY057028 AY443220
Passeriformes Irenidae Irena cyanogaster AY056999 AY443158
Passeriformes Nectariniidae Nectarinia olivacea AY057009 AY443180
Passeriformes Turdidae Catharus ustulatus AY443265 AY443114
Passeriformes Cinclidae Cinclus cinclus AY056985 AY443119
Passeriformes Mimidae Mimus patagonicus AY057005 AY443173
Passeriformes Sturnidae Sturnus vulgaris AY057032 AY443232
Passeriformes Troglodytidae Troglodytes aedon AY057038 AY443241
Passeriformes Certhiidae Certhia familiaris AY056983 AY443115
Passeriformes Sittidae Sitta carolinensis AY443332 AY443227
Passeriformes Sylviidae Sylvia nanna AY057033 AY443233
Passeriformes Pycnonotidae Pycnonotus barbatus AY057027 AY443219
Passeriformes Hirundinidae Hirundo rustica AY443290 AY443154
Passeriformes Aegithalidae Aegithalos iouschensis AY056976 AY443103
Passeriformes Locustellidae Megalurus palustris AY319988 AY799840
Passeriformes Remizidae Remiz pendulinus AY443328 AY443222
Passeriformes Promeropidae Promerops cafer AY443323 AY443212
Passeriformes Monarchidae Monarcha axillaris AY057006 AY443176
Passeriformes Laniidae Lanius excubitor AY443293 AY443160
Passeriformes Artamidae Artamus leucorhynchus AY056980 AY443109
Passeriformes Artamidae Artamus cyanopterus AY443262 AY443108
Passeriformes Artamidae Cracticus quoyi AY443278 AY443135
Passeriformes Vangidae Vanga curvirostris AY057040 AY443244
Passeriformes Platysteiridae Batis mixta AY443263 AY443110
Passeriformes Vireonidae Vireo philadelphia AY057041 AY443245
Passeriformes Melanocharitidae Melanocharis nigra AY057002 AY443167
Passeriformes Melanocharitidae Melanocharis vesteri AY443299 AY443168
Passeriformes Orthonychidae Orthonyx teminckii AY057012 AY443309
Passeriformes Climacteridae Climacteris erythrops AY443268 AY443121
Passeriformes Menuridae Menura novaehollandiae AY057004 AY443171
Passeriformes Furnariidae Furnarius rufus AY056995 AY443149
Passeriformes Rhinocryptidae Scytalopus magellanicus AY443331 AY443226
Passeriformes Thamonophilidae Terenura sharpei JX213518 JX213481
Passeriformes Pipridae Piprites chloris FJ501717 FJ501897
Passeriformes Pipridae Piprites pileata JF970177 KC157559
Passeriformes Pipridae Lepidothrix coronata FJ501655 FJ501835
Passeriformes Pipridae Antilophia galeata FJ501600 FJ501780
Passeriformes Oxyrunchidae Oxyruncus cristatus FJ501689 FJ501878
Passeriformes Cotingidae Cotinga cayana FJ501623 FJ501803
63
Passeriformes Cotingidae Laniisoma elegans FJ501651 FJ501831
Passeriformes Cotingidae Phoenicircus nigricollis FJ501705 FJ501885
Passeriformes Tyrannidae Tyrannus tyrannus AF143739 AY443243
Passeriformes Sapayoidae Sapaoya aenigma DQ320606 DQ320573
Passeriformes Dendrocolaptidae Dendrocolaptes certhia FJ461166 FJ460982
Passeriformes Pittidae Pitta sordida AY443219 AY443206
Passeriformes Acanthisittidae Acanthisitta chloris AY056975 AY443102
Psittaciformes Psittacidae Psittacus erithacus EF517674 EF517687
Psittaciformes Psittacidae Alisterus scapularis KT954426 EF517677
Psittaciformes Psittacidae Melopsittacus undulatus XM_005150647.1 XM_005150646.1
Psittaciformes Psittacidae Micropsitta brujinii EF517673 EF517681
Psittaciformes Psittacidae Amazona aestiva LMAW01003202 LMAW01003202
Psittaciformes Psittacidae Myopsitta monachus DQ143328 -
Psittaciformes Psittacidae Agapornis personata EF517672 EF517679
Psittaciformes Cacatuidae Calyptorhynchus funereus KT954425 EF517680
Psittaciformes Strigopidae Nestor notabilis XM_010020228.1 XM_010020229.1
Falconiformes Falconidae Falco peregrinus AY461399 KT954538
Falconiformes Falconidae Falco cherrug XM_005441067.1 XM_005441068.2
Falconiformes Falconidae Daptrius ater AY461397 KT954537
Falconiformes Falconidae Micrastur gilvicollis AY461403 KT954536
Cariamiformes Cariamidae Cariama cristata XM_009699718.1 XM_009699720.1
Piciformes Ramphastidae Pteroglossus aracari KT954416 KT954525
Piciformes Capitonidae Capito niger KT954414 KT954523
Piciformes Semnornidae Semnornis frantzii KT954415 KT954524
Piciformes Lybiidae Trachyphonus erythrocephalus KT954413 KT954522
Piciformes Lybiidae Lybius hirsutus KT954412 KT954521
Piciformes Megalaimidae Megalaima oorti KT954411 KT954520
Piciformes Picidae Melanerpes carolinus KT954418 KT954527
Piciformes Picidae Picoides pubescens XM_009905561.1 XM_009905562.1
Piciformes Picidae Picumnus cirratus AF295195 -
Piciformes Indicatoridae Indicator variegatus KT954417 KT954526
Piciformes Bucconidae Bucco capensis MPEG_ARA018
Piciformes Bucconidae Nystalus maculatus MPEG_MARJ045
Piciformes Bucconidae Nonnula rubecula INPA_A4705
Piciformes Bucconidae Monasa atra INPA_A8299
Piciformes Bucconidae Chelidoptera tenebrosa MPEG_JTW1160
Piciformes Bucconidae Hapaloptila castanea LSU_12059
Piciformes Bucconidae Micromonacha lanceolata LSU_4489
Piciformes Bucconidae Cyphos macrodactylus MPEG_AMA354
Piciformes Bucconidae Notharchus tectus LSU_28765
Piciformes Bucconidae Hypnellus bicinctus FMNH_339641
Piciformes Bucconidae Nystactes tamatia MPEG_JRT134
Piciformes Bucconidae Notharchus ordii LSU_25460
Piciformes Bucconidae Notharchus hyperrhynchus MPEG_GAPTO296
Piciformes Bucconidae Malacoptila fulvogularis FMNH_321031
Piciformes Bucconidae Malacoptila rufa LSU_103572
Piciformes Galbulidae Jacamalcyon tridactyla MPEG_800
Piciformes Galbulidae Brachygalba lugubris MPEG_293
Piciformes Galbulidae Jacamerops aureus MPEG_JAP375
64
Piciformes Galbulidae Galbacyrhynchus purusianus INPA_A1429
Piciformes Galbulidae Galbula dea INPA_A2288
Piciformes Galbulidae Galbula leucogastra MPEG_AMZ190
Piciformes Galbulidae Galbula ruficauda MPEG_MARJ109
Piciformes Galbulidae Galbula cyanescens MPEG_PUC159
Piciformes Galbulidae Galbula albirostris MPEG_JAP616
Piciformes Galbulidae Galbula cyanicollis MPEG_FLJA056
Coraciformes Alcedinidae Chloroceryle americana KT954422 KT954533
Coraciformes Alcedinidae Halcyon malimbica DQ111819 KT954532
Coraciformes Alcedinidae Alcedo leucogaster DQ111794 KT954531
Coraciformes Momotidae Momotus momota KT954421 KT954530
Coraciformes Todidae Todus angustirostris KT954420 KT954529
Coraciformes Coraciidae Coracias caudata AF143737 AY443126
Coraciformes Brachypteracidae Brachypteracias leptosomus KT954423 KT954534
Coraciformes Meropidae Merops pusillus KT954419 KT954528
Coraciformes Meropidae Merops nubicus XM_008938323.1 XM_008938322.1
Bucerotiformes Upupidae Upupa epops KT954409 KT954517
Bucerotiformes Phoeniculidae Phoeniculus purpureus KT954408 KT954516
Bucerotiformes Bucerotidae Buceros rhinoceros XM_010145185.1 XM_010145184.1
Bucerotiformes Bucerotidae Buceros bicornis KT954407 KT954515
Bucerotiformes Bucerotidae Tockus camurus KT954406 KT954514
Leptosomatiformes Leptosomidae Leptosomus discolor XM_009958543.1 XM_009958545.1
Colliformes Coliidae Colius colius KT954404 KT954512
Colliformes Coliidae Colius striatus XM_010201405.1 XM_010209029.1
Strigiformes Strigidae Strix occidentalis DQ482641 KT954508
Strigiformes Strigidae Ninox novaeseelandiae KT954400 KT954507
Strigiformes Tytonidae Tyto alba XM_009975325.1 XM_009975324.1
Strigiformes Tytonidae Phodilus badius KT954402 KT954510
Accipitrifromes Accipitridae Buteo jamaicensis EF078718 KT954506
Accipitrifromes Accipitridae Elanus caeruleus EF078724 KT954505
Accipitrifromes Pandionidae Pandion haliaetus EF078706 KT954504
Accipitrifromes Sagittaridae Sagittarius serpentarius KT954399 KT954503
Accipitrifromes Cathartidae Cathartes aura EF078766 KT954502
Accipitrifromes Accipitridae Aquila chrysateos XM_011594630.1 XM_011594629.1
Accipitrifromes Accipitridae Haliaeetus albicilla XM_009928640.1 XM_009928639.1
Accipitrifromes Accipitridae Haliaeetus leucocephalus XM_010586008.1 XM_010586006.1
Trogoniformes Trogonidae Apaloderma vittatum XM_009874816.1 XM_009869619.1
Trogoniformes Trogonidae Apaloderma narina AMNH_DOT12430
Trogoniformes Trogonidae Apalharpactes mackloti LSU_49104
Trogoniformes Trogonidae Apalharpactes mackloti AMNH_633881
Trogoniformes Trogonidae Harpactes ardens AY625239 -
Trogoniformes Trogonidae Harpactes ardens USNM_607340
Trogoniformes Trogonidae Harpactes diardii AMNH_DOT563
Trogoniformes Trogonidae Harpactes oreskios AY625238 -
Trogoniformes Trogonidae Harpactes oreskios ANSP_16308
Trogoniformes Trogonidae Harpactes orrhopheus AY625241 -
Trogoniformes Trogonidae Harpactes orrhopheus AMNH_DOT15159
Trogoniformes Trogonidae Harpactes duvaucelli LSU_38592
Trogoniformes Trogonidae Harpactes fasciatus AMNH_778649
65
Trogoniformes Trogonidae Harpactes erythrocephalus AMNH_DOT12240
Trogoniformes Trogonidae Harpactes wardii AMNH_307761
Trogoniformes Trogonidae Harpactes whiteheadii LSU_52627
Trogoniformes Trogonidae Harpactes kasumba AMNH_DOT15326
Trogoniformes Trogonidae Euptilotis neoxenus AMNH_DOT11080
Trogoniformes Trogonidae Pharomachrus pavoninus LSU_4986
Trogoniformes Trogonidae Pharomachrus auriceps hargitti AMNH_175988
Trogoniformes Trogonidae Pharomachrus auriceps auriceps FMNH_473723
Trogoniformes Trogonidae Pharomachrus fulgidus AMNH_322895
Trogoniformes Trogonidae Pharomachrus moccino AMNH_326512
Trogoniformes Trogonidae Pharomachrus antisianus ANSP_19429
Trogoniformes Trogonidae Priotelus temnurus ANSP_20257
Trogoniformes Trogonidae Priotelus roseigaster KU_8098
Trogoniformes Trogonidae Trogon clathratus USNM_613996
Trogoniformes Trogonidae Trogon mesurus ANSP_19305
Trogoniformes Trogonidae Trogon massena KU_2073
Trogoniformes Trogonidae Trogon comptus LSU_11829
Trogoniformes Trogonidae Trogon melanurus INPA_A1995
Trogoniformes Trogonidae Trogon viridis INPA_A5240
Trogoniformes Trogonidae Trogon chionurus LSU_28571
Trogoniformes Trogonidae Trogon melanocephalus USNM_646857
Trogoniformes Trogonidae Trogon citreolus UWBM_101087
Trogoniformes Trogonidae Trogon bardii LSU_71992
Trogoniformes Trogonidae Trogon violaceus MPEG_CN437
Trogoniformes Trogonidae Trogon caligatus LSU_66270
Trogoniformes Trogonidae Trogon ramonianus INPA_A5449
Trogoniformes Trogonidae Trogon curucui INPA_A5286
Trogoniformes Trogonidae Trogon aurantius LGEMA_15782
Trogoniformes Trogonidae Trogon surrucura MPEG_SC015
Trogoniformes Trogonidae Trogon elegans FMNH_434014
Trogoniformes Trogonidae Trogon rufus amazonicus INPA_A5284
Trogoniformes Trogonidae Trogon rufus tenellus LSU_26564
Trogoniformes Trogonidae Trogon rufus chrysochlorus LGEMA_9557
Trogoniformes Trogonidae Trogon mexicanus FMNH_343220
Trogoniformes Trogonidae Trogon aurantiiventris LSU_41625
Trogoniformes Trogonidae Trogon collaris puella FMNH_394272
Trogoniformes Trogonidae Trogon collaris collaris MPEG_CN450
Trogoniformes Trogonidae Trogon personatus LSU_48503
66
Capítulo 3
Ferreira, M.; Aleixo, A.; Bates, J. M.; Cracraft, J.;
Ribas, C. C. Phylogeography and phylogenomics of
jacamars (Aves: Galbulidae) and puffbirds (Aves:
Bucconidae) reveal underestimation of species
diversity and recurrent biogeographic patterns in the
Neotropics. Manuscrito formatado para Zoological
Journal of Linnean Society
67
Manuscript submission to Zoological Journal of Linnean Society
Contribution type: Article
Phylogeography and phylogenomics of jacamars (Aves: Galbulidae) and
puffbirds (Aves: Bucconidae) reveal underestimation of species diversity
and recurrent biogeographic patterns in the Neotropics
Ferreira, Mateus1*; Aleixo, Alexandre2; Bates, John M.3; Cracraft, Joel4; Ribas, Camila C.5
1 Programa de Pós-Graduação em Genética, Conservação e Biologia Evolutiva, INPA,
Manaus, AM, Brazil 2 Coordenação de Zoologia, MPEG, Belém, PA, Brazil 3 Department of Ornithology, FMNH, Chicago, IL, USA 4 Department of Ornithology, AMNH, New York, NY, USA 5 Coordenação de Biodiversidade, INPA, Manaus, AM, Brazil
*Corresponding author
Correspondence: Mateus Ferreira, Coordenação de Biodiversidade, Instituto Nacional de
Pesquisas da Amazônia, CEP 69080-971, Manaus-AM, Brazil
E-mail: [email protected]
Short running title: Galbuliformes phylogenomic
Abstract
Galbulidae (jacamars) and Bucconidae (puffbirds) are sister families endemic to the
Neotropical region. Together they comprise 57 species and more than a 100 described
subspecies. Both families have their highest diversity in Amazonia. Within Galbulidae, most
species have restricted and parapatric / allopatric distributions in relation to other closely related
species, while within Buccondiae, species are widespread and polytypic. In this study, we
obtained DNA sequence data for over 400 samples, and used previous published results, of all
widespread species to uncover phylogeographic patterns. Then, based on these results, we
selected and sequenced thousands of Ultraconserved Elements to reconstruct the phylogenetic
relationships among these phylogeographic groups and propose the first phylogenetic
hypothesis for these two families with dense taxon sampling. Our phylogeographic results
recovered phylogeographic breaks in almost all studied groups, most of them associated with
the main tributaries of the Amazon River, and many corresponding to already described
subspecies. We then reconstructed phylogenetic relationships based on over 2,000 UCE loci
using a concatenated approach in a Bayesian Inference framework. Overall, most nodes had
68
high support, and the relationships among genera, species and instraspecific diversity were
discussed. We propose the recognition of all subspecies that received support from the
phylogeographic and phylogenomic approaches as distinct species. We found evidence of
paraphyly of several species and proposed taxonomic changes to deal with that.
Introduction
Species usually are the basic unit of any study in evolutionary biology. Considering they
should represent the lowest and only non-arbitrary rank above individuals, species are the basic
operational unit for comparing any intrinsic evolutionary aspect, such as physiology, behaviour,
morphology, etc. However, we still lack a broad and comprehensive concept for species
recognition (Cellinese, Baum & Mishler, 2012; de Queiroz, 2007; de Queiroz, 2012). In birds,
taxonomy has been historically influenced by the Biological Species Concept (Mayr, 1942;
Mayr, 1976), based on reproductive isolation as the main criterion for species delimitation.
Therefore, since this concept was adopted several distinct allopatric populations were lumped
as subspecies due to morphological similarities pending further investigation to prove the
absence of gene flow (Peters, 1945; Peters, 1948). This implies that allopatric and parapatric
populations, even if diagnosably distinct, should only be recognized as full species if there is
evidence of reproductive isolation (Gill, 2014).
In the Neotropical region, and especially in Amazonia, one of the main issues that
obscures the recognition of diversity patterns is the fact that most widespread species are in fact
complexes of taxa, usually diagnosable and geographically structured, that are lumped under
the same species name due to their morphological similarities and physical isolation. Many of
these polytypic species, when thoroughly sampled, prove to include distinct lineages,
sometimes not even closely related to each other (Bravo, Chesser & Brumfield, 2012; Bravo,
Remsen, Whitney & Brumfield, 2012; Fernandes, Wink, Sardelli & Aleixo, 2014; Isler, Bravo
& Brumfield, 2013; Lopes, Chaves, Aquino, Silveira & Santos, 2017; Lutz, Weckstein, Patane,
Bates & Aleixo, 2013; Ribas, Aleixo, Nogueira, Miyaki & Cracraft, 2012; Ribas, Aleixo,
Gubili, d'Horta, Brumfield & Cracraft, 2018; Tobias, Bates, Hackett & Seddon, 2008). The
recognition of these hidden lineages is critical for appropriate hypothesis formulation in
macroevolution and biogeography (Donoghue & Moore, 2003; Lexer, Mangili, Bossolini,
Forest, Stölting, Pearman, Zimmermann, Salamin & Carine, 2013). For example, Amazonian
areas of endemism were recognized based on congruent distribution patterns of bird species
69
(Borges & Da Silva, 2012; Cracraft, 1985), and have been used as a basis to formulate
hypothesis of biotic diversification in Amazonia (Haffer, 1969; Haffer, 1974; Haffer, 1997).
Considering that any biogeographic study should be based on a taxonomy that correctly
recognizes the evolutionary units included in the studied groups, for the present study we
densely sampled all recognized taxa within two sister families of birds restricted to the
Neotropical region. Galbulidae and Bucconidae form a clade, sometimes recognized in its own
order Galbuliformes, that diverged from all the other Piciformes during the early Eocene and
diverged from each other in the Late Eocene (Prum, Berv, Dornburg, Field, Townsend,
Lemmon & Lemmon, 2015). Although the ancestor was from the Afrotropical region the two
families’ entire diversification happened inside the Neotropical region (Claramunt & Cracraft,
2015). Hence, making these two families excellent models to understand how landscape
evolution of the Neotropical region influenced diversification. However, there are no
phylogenetic hypotheses about relationships within these two families, and the few
phylogeographic studies conducted so far with Bucconidae species showed that the diversity is
highly underestimated by current species limits (Almeida, 2013; Duarte, 2015; Ferreira, Aleixo,
Ribas & Santos, 2017; Soares, 2016). Although Galbulidae species were never subjected to
phylogeographic studies, with 19 species distributed in 5 genera, jacamar distributions were
used as models by Haffer (1974), together with other families, when he proposed his theory for
Amazonian diversification (Haffer, 1974). Haffer recognized eight zoogeographic groups, five
were composed of species complexes, and two were widespread polytypic species. Bucconidae,
in turn, are composed of 38 species distributed in 12 genera. However, half of those species
consist of polytypic groups lumped as subspecies due to morphological similarities. Groups
such as the White-fronted Nunbird, Monasa morphoeus, and the Rusty-breasted Nunlet,
Nonnnula rubecula, are composed of several subspecies, which in fact still underestimate the
phylogeographic structure recovered for them (Soares, 2016). On the other hand, Malacoptila
species are widespread species for which only a few subspecies were described, however,
phylogeographic patterns indicated a great underestimation of taxonomic diversity. For
example, for a single species, the Rufous-necked Puffbird (M. rufa), that only includes two
subspecies described, ten distinct genetic lineages were recovered (Ferreira et al., 2017). Due
to these first results, the present study focused on sampling all named taxa described for these
two families, and sampling all widespread species throughout their distribution to uncover
phylogeographic patterns. Based on these results, we selected samples representing all
phylogeographic groups and sequenced thousands of Ultraconserved Elements (UCE)
70
(Faircloth, McCormack, Crawford, Harvey, Brumfield & Glenn, 2012; McCormack &
Faircloth, 2013; McCormack, Harvey, Faircloth, Crawford, Glenn & Brumfield, 2013) to
recover their phylogenetic relationships. Our aims are (1) to characterize the phylogeographic
patterns and population structure within widespread species, recognizing the cryptic diversity
within them, when present; (2) propose a densely sampled phylogenetic hypothesis for these
two families; and (3) discuss patterns of diversification in the entire clade.
Material and Methods
Sampling and DNA isolation
We sampled 436 individuals from almost all named taxa currently recognized within
Galbuliformes (Gill & Donsker, 2018; Peters, 1948; Piacentini, Aleixo, Agne, Mauricio,
Pacheco, Bravo, Brito, Naka, Olmos, Posso, Silveira, Betini, Carrano, Franz, Lees, Lima, Pioli,
Schunck, do Amaral, Bencke, Cohn-Haft, Figueiredo, Straube & Cesari, 2015; Rassmussen &
Collar, 2002; Remsen, Areta, Cadena, Claramunt, Jaramillo, Pacheco, Pérez-Emen, Robbins,
Stiles, Stotz & Zimmer, 2018 Tobias, 2017), and when available, we used published sequences
to select samples for UCE sequencing. All samples are represented by voucher specimens
deposited at the ornithological collections of the American Museum of Natural History
(AMNH), Academy of Natural Sciences of Drexel University (ANSP), Field Museum of
Natural History (FMNH), Instituto Nacional de Pesquisas da Amazônia (INPA), Kansas
University (KU), Laboratório de Genética e Evolução Molecular de Aves - USP (LGEMA),
Louisiana Museum of Natural History (LSUMZ), Museu Paraense Emílio Goeldi (MPEG),
Smithsonian Institution National Museum of Natural History (USNM) and Burke Museum
(UWBM) (Table S1).
DNA from fresh tissue was extracted with the DNeasy kit (Qiagen Inc.), following the
manufacturer’s protocol. For taxa lacking fresh tissues we sampled toe pad clips from museum
specimens at the American Museum of Natural History (AMNH). Toe pads were cut from
specimens with a sterile surgical blade and processed in a dedicated room for ancient DNA
(aDNA Lab, AMNH). They were rinsed with 100% ethanol, and twice with ultra-pure water
prior to digestion to remove any inhibitor that could cause problems in downstream procedures.
We then extracted DNA with the DNeasy kit (Qiagen Inc.), replacing the regular silica columns
with the QIAquick (Qiagen Inc.) columns, to ensure maximum DNA yield.
71
Phylogeographic structure and UCE sampling
Widespread species that lacked previous studies were sampled throughout their
distributions to uncover phylogeographic structure. We amplified one mitochondrial gene
(NADH subunit 2 – ND2) following conventional PCR protocols and sequenced both strands
with BigDye® Terminator v3.1 in an ABI 3130/3130XL automated capillary sequencer
(Applied Biosystems®) following manufacturer’s protocols. The sequences were edited on
Geneious version 10.2.3 (Kearse, Moir, Wilson, Stones-Havas, Cheung, Sturrock, Buxton,
Cooper, Markowitz, Duran, Thierer, Ashton, Meintjes & Drummond, 2012) and aligned with
MAFFT (Katoh & Standley, 2013) under default parameters. We analysed each species
complex independently. Within Galbulidae we analysed five species complexes: 1)
Brachygalba and Jacamaralcyon; 2) Jacamerops; 3) Galbula dea; 4) Galbula cyanicollis, G.
chalcocephala, and G. albirostris; and 5) G. ruficauda, G. pastazae, G. cyanescens, G.
tombacea, and G. galbula. We used a previous study to select samples for G. leucogastra and
G. chalcothorax (Ferreira et al., submitted). For Bucconidae, we gathered data in this study for
five polytypic species or species complexes: 1) Bucco capensis; 2) Cyphos macrodatylus; 3)
Notharchus tectus; 4) Notharchus ordii, N. hyperrhynchus, N. macrorhynchus, N. swainsoni,
and N. pectorales; and 5) Chelidoptera tenebrosa. Sample selection for the genera Monasa,
Nonnula, Malacoptila, and Nystalus was based on previous studies (Almeida, 2013; Duarte,
2015; Ferreira et al., 2017; Soares, 2016). The best evolutionary model for each matrix was
selected by jModelTest 2.1.10 (Darriba, Taboada, Doallo & Posada, 2012). We performed a
Bayesian inference analysis (BI) implemented in MrBayes 3.2.6 (Ronquist, Teslenko, van der
Mark, Ayres, Darling, Hohna, Larget, Liu, Suchard & Huelsenbeck, 2012) with four parallel
simultaneous runs consisting of a total of 4x107 generations, sampling trees every 1000
generations. ESS values, stationarity, and convergence among runs were checked in Tracer 1.6
(Rambaut, Suchard, Xie & Drummond, 2014). Based on these results we selected our samples
for UCE sequencing. All extracts were sent to Rapid Genomics (Gainsville, FL) for library prep
and target-capture sequencing of 2321 loci of Ultraconserved Elements (UCE) (Faircloth et al.,
2012; McCormack et al., 2013).
UCE assembly
The raw sequence data were processed with the Phyluce script pack (Faircloth, 2016).
We employed illumiprocessor (Faircloth, 2013) and Trimmomatic (Bolger, Lohse & Usadel,
2014) to remove adapter contamination and low-quality reads. We assembled our targeted
regions using a reference genome for each family. For Bucconidae, we used the Collared
72
puffbird (Bucco capensis), and for Galbulidae, the Paradise jacamar (Galbula dea) genomes.
We mapped the UCE probes back to each genome using the script
phyluce_probe_run_multiple_lastzs_sqlite, and then, phyluce_probe_slice_sequence_from_g-
enomes to extract the probe region plus 500 base pairs from each flanking region (Faircloth,
2016). With these sequences as a reference we mapped back the clean reads of each individual
employing Bowtie2 (Langmead & Salzberg, 2012) plugin 7.2.1 inside Geneious version 10.2.3
(Kearse et al., 2012). The consensus sequences were called with the highest quality threshold
and a depth of at least 4 reads. Each locus was aligned with MAFFT (Katoh & Standley, 2013)
under default parameters.
Phylogenetic relationship
Even though the sister relationship between Galbulidae and Bucconidae is well
established (Hackett et al., 2008; Livezey & Zusi, 2007; Prum et al., 2015), we used the
Rhinoceros hornbill (Buceros rhinoceros, Bucerotidae)(Gilbert, Jarvis, Li, Li, Avian Genome
Consortium, Wang & Zhang, 2014b), the Northern Carmine bee-eater (Merops nubicus,
Meropidae)(Gilbert, Jarvis, Li, Li, Avian Genome Consortium, Wang & Zhang, 2014c), and
the Downy woodpecker (Picoides pubescens, Picidae)(Gilbert, Jarvis, Li, Li, Avian Genome
Consortium, Wang & Zhang, 2014a) as outgroups. To recover the phylogenetic relationships,
we performed a Bayesian Inference analysis in ExaBayes v1.4 (Aberer, Kobert & Stamatakis,
2014) employing the concatenated matrix of all UCE loci with 75% completeness, where only
loci that had at least 75% of all individuals were selected. Four parallel chains consisting of
4x107 generations were performed.
Results
Phylogeographic results
With a few exceptions, we obtained the whole ND2 sequence for all samples.
Phylogenetic trees and maps of samples and lineages’ distributions can be found in the
Supplementary Material (Figures S1-S10). Overall, most species complexes contained
phylogeographic structure in the mtDNA that matches known areas of endemism for birds. The
only two widespread species that apparently lacked phylogeographic structure were Cyphos
macrodactylus and Chelidoptera tenebrosa. The phylogeographic breaks were more
conspicuous in birds with stronger association with terra-firme forests [Fig. S2-S4, S6,
Malacoptila spp. (Ferreira et al., 2017), Monasa morphoeus and Nonnula rubecula (Soares,
2016)]. However, species associated with other habitats, such as várzeas, open habitats (i.e.
73
non-forested) or white-sand environments also showed structure [Fig. S1, S5, S8-S9, also
Galbula leucogastra/chalcothorax, Nystactes (Almeida, 2013), Nystalus spp. (Duarte, 2015),
and Nonnula ruficapilla (Soares, 2016)]. Nonetheless, some lineages are represented by a single
individual and additional samples should be collected and analysed to make further
assumptions. It is also worth to note that some species were paraphyletic in the mtDNA. The
most remarkable are the complex Brachygalba lugubris, B. albogularis (Fig. S1), G. albirostris,
G. cyanicolis, and G. chalcocephala (Fig. S4), G. ruficauda, G. cyanescens (Fig. S5);
Notharchus tectus, N. subtectus (Fig. S8); N. hypperhynchus, N. swainsoni, N. macrorhynchus
(Fig. S9).
UCE sequencing
The reference sequences we assembled from the Collared puffbird (Bucco capensis) and
the Paradise jacamar (Galbula dea) genomes included 2226 and 2279 sequences, respectively.
The mean number of sequences was 2,240,885 reads; and a mean number of 2191 UCE loci per
sample (Table S1). The matrix for Galbulidae contained 2165 loci, while for Bucconidae, the
matrix had 2158 loci.
Phylogenetic results
In general, the ExaBayes tree is well supported, with most of the nodes with lower support
found near the tips (Fig. 2, 3). Galbulidae consisted of two clades, the first comprises
Jacamaralcyon and Brachygalba, and the other, Jacamerops, Galbacyrhynchus, and Galbula
(Fig. 1). Within Bucconidae, some genera were paraphyletic. Bucco, that previously included
four species (Gill & Donsker, 2018; Peters, 1948; Piacentini et al., 2015; Remsen et al., 2018),
comprises three distinct genera as previously suggested by morphological characters
(Rassmussen & Collar, 2018): B. capensis Linneus, 1766 is the family and genus type and more
closely related to Nystalus; Cyphos macrodactylus von Spix, 1824, is sister to the clade that
comprises Notharchus, Hypnelus, and Nystactes; and finally, Nystactes tamatia (J. F. Gemelin,
1788), and N. noanamae (Hellmayer, 1909), more closely related with Hypnelus species (Fig.
3). Notharchus was also paraphyletic, with Hypnelus and Nystactes embedded within it. N.
tectus and N. subtectus were sister to Hypnelus, Nystactes, and the remaining Notharchus
species (Fig. 1, 3).
The relationships within genera in the UCE trees (Fig. 2, 3) mostly agreed with the
mtDNA phylogeographic structure. Most notably is the paraphyly of Brachygalba lugubris in
relation to B. albogularis (Fig. 2), and the polyphyletic status of Galbula ruficauda, in which
the lineages from Central America (G. melanogenia), and northern South America (G. pallens,
74
G. ruficauda), including G. pastazae, are sister group to the clade comprising the species group
of G. albicollis (albicollis, chalcocephala, cyanicollis) and G. galbula (galbula, pastazae,
cyanescens, rufoviridis). Also, in contrast with the mtDNA, the two samples of G. cyanescens
are sister to G. heterogyna and G. rufoviridis from the Brazilian Shield, instead of being
embedded between them (Fig. S5). For puffbirds, the UCE tree also recovered the paraphyly of
N. tectus subspecies (Fig. 3), and for the hyperrhynchus group (Fig. S9), we recovered N.
macrorhynchus sister to N. swainsoni and N. hyperrhynchus, rendering the Amazonian group
paraphyletic.
Discussion
Phylogenetic results
Our dense sampling coupled with the use of UCE loci provided good insights about
genera and species relationships. We sampled all species, and almost all subspecies, for the two
families, and characterized the spatial distribution of mtDNA lineages for all widespread
species. Predominantly, our results indicate a severe disparity between currently recognized
species and the potential number of independent evolutionary units within these clades.
Avian taxonomy has historically been greatly influenced by the Biological Species
Concept (BSC), which assumes that reproductive isolation is required for recognition of species
status (de Queiroz, 2005). This condition, can be easily detected in sympatric taxa, however,
for parapatric and allopatric populations, natural observations are very hard to detect.
Consequently, many morphologically distinct taxa have been lumped into species complexes,
pending further analysis to prove them different. Thus, the null hypothesis for species
recognition has been of peer-reviewed publications proving that essential reproductive isolation
is true among allopatric populations. It implies that we should be looking for reasons that
differentiate allopatric populations, either through genetic evidence or some other characteristic
that would lead to reproductive isolation, rather than assuming that they already are
reproductive isolated, because they are not in contact, and looking for evidence proving the
contrary (Gill, 2014). Albeit avian taxonomy and systematics is probably the best known among
vertebrates, there are still many taxa to be described (Barrowclough, Cracraft, Klicka & Zink,
2016), and although species concept, or criteria, are amid one of the most controversial topics
in biology (Aleixo, 2007; Dayrat, Cantino, Clarke & de Queiroz, 2008; de Queiroz, 2012), the
appropriate understanding of a lineage’s evolutionary history is essential to several fields,
including conservation and biogeography (Avendaño, Arbeláez-Cortés & Cadena, 2017; Ribas,
75
Gaban-Lima, Miyaki & Cracraft, 2005; Tobias, Bates, Hackett & Seddon, 2008), especially in
the emergent field of geogenomics (Baker, Fritz, Dick, Eckert, Horton, Manzoni, Ribas,
Garzione & Battisti, 2014). Therefore, we are confident our results provide great insight about
Galbulidae and Bucconidae systematics and will enable future biogeography studies to uncover
how the landscape evolution of South America shaped this group’s diversity.
Galbulidae systematics
Galbulidae currently recognized diversity includes 19 species distributed in 5 genera
(Tobias, 2017). Our results, however, show that this diversity is severely underestimated. In
addition to the fact that most widespread species have genetic lineages structured
geographically, we also found evidence that, at least four species are para- (Brachygalba spp.)
or polyphyletic (Galbula ruficauda complex). Conceding that we recognize all subspecies that
were monophyletic in our analyses and elevate them to species status, the species diversity of
Galbulidae practically doubles, from 19 to 37 species, including at least six new taxa that need
to be formally described. Biogeographically, there is also some noteworthy patterns that arouse
from the mtDNA data. All widespread species presented some degree of genetic structure in
the known areas of endemism in Amazonia (Borges & Da Silva, 2012; Cracraft, 1985). Most
of the larger Amazonian tributaries, including rivers such as the Negro, Madeira, Solimões, and
Amazonas delimit lineages in opposite margins, however, if they were responsible for causing
these divergences still need to be investigated.
According to our phylogenetic hypothesis for Galbulidae, there are now eight main
groups of species:
1. Brachygalba and Jacamaralcyon
Brachygalba and Jacamaralcyon species were recovered as sisters to all other jacamars.
The monotypic Jacamaralcyon species, Jacaramaralcyon trydactyla (Viellot, 1817), is
endemic to the Atlantic Forest, inhabiting semi-deciduous or gallery forest. This species was
recovered as sister to all other Brachygalba species (Fig. 1), which prefer forest edges and open
habitats throughout the Amazon basin and north South America. B. goeringii Sclatter, PL &
Salvin, 1869 and B. salmoni Sclatter, PL & Salvin, 1879 represent two distinct lineages within
Brachygalba radiation (Fig. 2), with very distinct plumages and restricted distributions in
northern South America. B. goeringii was recovered as sister to all other Brachygalba species,
and B. salmoni, as sister group to the species group of B. lugubris (naumburgae, obscuriceps,
lugubris, and melanosterna) and B. albogularis (von Spix, 1824), from the Amazon basin (Fig.
2). Because B. albogularis was embedded within B. lugubris lineages, we recommend that the
76
current subspecies of B. lugubris should now be elevated to species status. This way, we resolve
the paraphyly of B. lugubris, and fully recognize all its diversity. Further studies are necessary
to completely understand B. obscuriceps Zimmer, JT & Phelps, 1947 and B. naumburgae
Chapman, 1931 distributions, especially regarding the relationship between B. lugubris, and B.
l. fulviventris Sclater, PL, 1891 and B. l. caquetae Chapman, 1917.
2. Jacamerops
Jacamerops individuals are so distinct from the other jacamars that were once considered
to belong to a separate subfamily Jacameropinae. Although this treatment is no longer followed,
Jacamerops are by far the bulkiest jacamars, inhabiting the midstory and canopy of continuous
forest in the Amazon basin. Among the four subspecies recognized, J. a. ridgway Todd, 1943
formed a well supported clade in both analyses. (Fig. 2, S2), while J. a. aureus (Statius Müller,
PL, 1776) was monophyletic in the mtDNA analysis (Fig. S2) but paraphyletic in the UCE
analysis, with the two individuals from the Guiana Shield as sister to all other J. aureus
individuals (Fig. 2). Since the type from J. a. aureus is British Guiana (Peters, 1948), we
consider that only this group should be recognized as J. aureus, while the second lineage should
receive a new name (Fig. 2). An interesting biogeographic pattern that arouse from Jacamerops
data was the sister relationship between J. penardi Bangs & Barbour, 1922, from Central
America, and J. isidori Deville 1849, from the Madeira-Solimões interfluve. A similar pattern
was found in the Hylophylax species complex (Fernandes et al., 2014). Finally, J. ridgwayi
Todd, 1943 requires further study to fully evaluate all diversity present in this group, our results
suggest the presence of at least 4 mtDNA lineages, each separated by the main rivers of the
Brazilia Shield.
3. Galbalcyrhynchus
Galbacyrhynchus species are endemic to floodplain forests from Western Amazon.
Galbalcyrhynchus purusianus Goeldi, 1904 was considered conspecific with G. leucotis Des
Murs, 1845, and they were actually considered male and female forms of the same species.
Nonetheless, the parapatric distribution and the apparently lack of intermediate forms (Haffer,
1974) render these two taxa the status of distinct species (Fig. 2).
4. Galbula dea complex
Previously allocated in the genus Urogalba, Galbula dea individuals are the most
morphologically distinct among Galbula species. Our results recovered six distinct mtDNA
lineages (Fig. S3) that matches with the UCE results (Fig. 2), in which four already have
associated names. G. dea (Linnaeus, 1758) from the Guiana Shield; G. brunneiceps (Todd,
77
1943) from the Negro-Solimões interfluve; G. phainopepla (Todd, 1943) from the Solimões-
Madeira interfluve; and G. amazonum (Sclater, PL, 1855). The last lineage, from the Madeira-
Tapajós interfluve was considered to be part of G. d. brunneiceps (Peters, 1948), however, since
the type locality from G. brunneiceps is Manacapurú, Rio Solimões, Brazil, we suggest that a
new name should be given to this lineage.
5. G. leucogastra/chalcothorax
This complex includes the only jacamars that inhabit white-sand environments (Adeney,
Christensen, Vicentini & Cohn-Haft, 2016) in the Amazon basin. Although highly structured
throughout its distribution (Ferreira et al., submitted) this group lacks morphological
distinctiveness among genetic lineages, thus further systematic and taxonomic work is required
before the proposition of any change in nomenclature.
6. Galbula albirostris, G. chalcocephala, and G. cyanicollis
These tree species were formerly considered conspecifics in G. albirostris Latham, 1790
(Peters, 1948), later Haffer (1974) recognized G. cyanicollis Cassin, 1851, based on the lack of
interbreeding between these two forms. Our results support the recognition of all three species,
with G. albirostris restricted to the Guiana Shield, east of Negro River; G. chalcocephala
Deville, 1849 in between the west bank of lower Negro river, west of Branco River, and north
of Solimões all the way down to the west bank of the upper Ucayali River (Harvey, Seeholzer,
Cáceres A, Winger, Tello, Camacho, Aponte Justiniano, Judy, Ramírez, Terrill, Brown, León,
Bravo, Combe, Custodio, Zumaeta, Tello, Bravo, Savit, Ruiz, Mauck & Barden, 2014); and at
last, G. cyanicollis, along the south bank of Amazon River. This group of species, in contrast
with other jacamars, only inhabits the interior of forests, mainly in terra-firme habitats. Not
surprisingly, the mtDNA showed lineages separated by the main Amazonian tributaries (Fig.
S4). However, some lineages presented some interesting biogeographic patterns, such as the
distinct lineage at the lower portion of Madeira-Tapajós interfluve, that is also found in other
groups of birds, such as Rhegmatorhina berlespchi (Ribas et al., 2018), Malacoptila rufa
(Ferreira et al., 2017), and Glyphorhynchus spirurus (Fernandes, Gonzalez, Wink & Aleixo,
2013). Another pattern, that has not been reported before for birds, is the distinct lineage
between the Purus and Tapajós Rivers (Fig. S4). This is the first evidence of a lineage of and
understory terra-firme bird that has n structure related to the Madeira River.
7. G. melanogenia, G. pastazae, G. pallens, and G. ruficauda.
Although G. melanogenia Sclater, PL, 1852, was first described as a full species, it was
later lumped together with G. rufoviridis Cabanis, 1851 in G. ruficauda Cuvier, 1816 due to
78
morphological similarity (Peters, 1948). Our results, however, recovered this group as sister to
the clade containing G. cyanicolis and G. galbula complex (Fig. 2). Also, G. pastazae
Taczanowski and Berlepsch, 1885, probably the only jacamar to live in high altitudes, is
embedded between G. melanogenia and G. ruficauda (Fig. S5, 2). Therefore, our
recommendation is that G. melanogenia, from Central America and the Pacific coast of
Colombia and Ecuador, along with G. pallens Bangs, 1898 and G. ruficauda Cuvier, 1816
should be recognized as species. Further studies are required to check the validity of G. r.
brevirostris Cory, 1913.
8. Galbula galbula, G. tombacea, G. cyanescens and G. rufoviridis
This group is often regarded as G. galbula (Linnaeus, 1766) species group due to
morphological and ecology similarity. Usually associated with forest edges and floodplains
forest, while G. albirostris species group, its sister clade (Fig. 2), is usually associated with the
interior of terra-firme forests. Despite been associated with floodplain forests, and therefore,
not “bounded” by rivers, there are no previous reports of hybridization among these taxa. We
found, however, that the individual INPA A019 is phenotypically G. tombacea (checked by
M.F.), however, the mtDNA clustered with G. cyanescens Deville, 1849 (Fig. S5). This is the
only reported case of hybrids among this group, the other individual that could be a hybrid - G.
cyanescens, voucher MPEG MAD305 - is phenotypically G. cyanescens (checked by Fátima
Lima), even though the individual was collected in the right bank of Madeira River, supposedly
the limit between distributions of G. cyanescens and G. heterogyna Todd, 1932. Another
important pattern that we can observe in this group is the apparently discordance between the
mtDNA and UCE trees (Fig. S5, 3). Our mtDNA tree recovered G. cyanescens as one lineage
embedded within lineages of G. rufoviridis and G. heterogyna. It also recovered G. rufoviridis
as paraphyletic (Fig. S5). The UCE tree instead, recovered G. cyanescens as sister to G.
heterogyna and G. rufoviridis (Fig. 2). In addition, all samples we sequenced for G. rufoviridis
were recovered as monophyletic and sister to G. heterogyna. Thus, this might be an evidence
of mtDNA capture (Sloan, Havird & Sharbrough, 2017), in which probably G. cyanescens
captured the mtDNA lineage of G. heterogyna. However, further studies are required to
understand the direction and timing of this event.
Bucconidae systematics
Our results showed that, similar to the situation with Galbulidae, Bucconidae diversity is
underestimated. In addition, we found evidence of genera paraphyly. Phylogeographic patterns
recovered for widespread puffbird species varied from little to no genetic structure, as in
79
Chelidoptera and Cyphos, to highly structured, as in Malacoptila (Ferreira et al., 2017),
Nonnula rubecula and N. ruficapilla, and Monasa morphoeus (Soares, 2016). Historically,
apart from the morphologically explicit genera Hapaloptila, Chelidoptera, Malacoptila,
Micromonacha, Monasa, and Nonnula, all other species were lumped in Bucco Brisson, and
later split in Notharchus and Hypnelus. Currently, although some authors recognize different
genera for former Bucco species (i.e. Cyphos, and Nystactes) (Rassmussen & Collar, 2018),
many others still keep several species within the genus Bucco (Gill & Donsker, 2018; Piacentini
et al., 2015; Remsen et al., 2018). Our results however recovered Bucco as polyphyletic, and
thus, we favor the recognition of Cyphos Spix, 1824 (which has priority over Argicus Cabanis
& Heine, 1863) and Nystactes Gloger 1827. Also, we recovered Notharchus specie as
paraphyletic, with the species group of N. tectus (Boddaert, 1783) as sister to the clade
containing Hypnelus, Nystactes and the other species of Notharchus. One way to resolve this
paraphyly would be to include Hypnelus and Nystactes in the genus Notharchus, however, both
Nystactes and Hypnelus species are morphologically distinct from any of Notharchus species.
Therefore, we propose the revalidation of Nothriscus Cabanis & Heine, 1863 to accommodate
Nothriscus tectus, N. subtectus and N. picatus, resolving the paraphyletic relationships found
within Notharchus species.
1. Bucco capensis and Nystalus
Bucco capensis Linnaeus, 1766 and Nystalus species were recovered as sister to all other
puffbirds. The sister relationship we recovered between B. capensis and Nystalus is validated
by the bill-tip morphology that was previously used to separate former Bucco species in the
genera Cyphos and Nystactes (Rassmussen & Collar, 2018). Our results for B. capensis samples
recovered three clades in the UCE tree (Fig. 3) in contrast to the four clades found in the mtDNA
analysis (Fig. S7). Our UCE analysis also favor the recognition of B. dugandi Gilliard, 1949
and suggest the presence of a new taxon yet undescribed. Nystalus relationships found here
were similar to a previous study that used only one mtDNA marker (Duarte, 2015), which
recovered N. maculatus (Gmelin, JF, 1788) and N. striatipectus (Sclater, PL, 1854) as sister to
all remaining species, and N. chacuru (Vieillot, 1816) as sister to N. radiatus (Sclater, PL, 1854)
and the N. striolatus species complex: N. obamai Whitney et al., 2013; N. striolatus (Pelzeln,
1856), and N. torridus Bond & Meyer de Schauensee, 1940. Further studies are required to fully
understand the distribution and relationship of Nystalus striolatus species complex.
2. Chelidoptera
80
The Swallow-winged puffbird, Chelidoptera tenebrosa Pallas, 1782, is by far the most
distinct puffbird, aberrant both in morphology and in ecology. With swallow-like morphology,
they are highly specialized in aerial activity, and its flying proficiency is probably the cause for
the lack of genetic structure we found in the mtDNA (Fig. S10). However, we were unable to
sample UCE from the two toe pad samples, from the subspecies C. t. pallida Cory, 1913, from
Northwest Venezuela; and C. t. brasiliensis Sclater, PL, 1862, from the east coast in Brazil.
3. Monasa and Nonnula
Monasa and Nonnula were the focus of a recent phylogeographic study (Soares, 2016).
Species from both genera presented high levels of genetic structure in the mtDNA, and we
sampled one individual per mtDNA lineage that were uncovered previously. We recovered
Monasa as sister to Chelidoptera, and these two sisters to Nonnula (Fig. 1). Relationships inside
each genus (Fig. 3) were also congruent to Soares (2016). In addition to this previous study, we
were able to sample three toe pads representing three subspecies of M. morphoeus (Hahn &
Küster, 1823): M. m. morphoeus (Hahn & Küster, 1823) from the east coast of Brazil; M. m.
pallescens Cassin, 1860; and M. m. grandior Sclater, PL & Salvin, 1868, both from Central
America. However, their phylogenetic relationship with other subspecies of M. morphoeus was
uncertain (Fig. S11) and further studies are required to fully understand if the phylogeographic
structure found in the mtDNA matches the UCE. For Nonnula, our results support the paraphyly
of N. ruficapilla (Tschudi, 1844), with N. amaurocephala Chapman, 1921 embedded within it.
Both genera are being studied using broader sampling of individuals and molecular markers.
4. Malacoptila
Malacoptila UCE topology was congruent with the concatenated dataset topology from
Ferreira et al. (2017), placing M. fulvogularis Sclater, PL, 1854 as sister to all other species.
This result changes the previous biogeographic interpretations, and a more detailed study
focusing on this genus is necessary, to fully understand the relationship of Malacoptila species,
including the position of M. mystacalis (Lafresnaye, 1850), that in the concatenated UCE tree
was recovered as sister to all other species (Fig. 3). Since, M. mystacalis UCE contigs were
shorter due to DNA degradation common in toe pad samples (McCormack, Tsai & Faircloth,
2016), we assembled a small subset of Malacoptila samples to minimize the effects of missing
data, and yet, M. mystacalis was again, recovered as sister to all other species of Malacoptila
(Fig. S12). Further sampling of this narrow endemic species is required to confirm if this pattern
is true, or an artefact of toe pad sequencing error.
5. Hapaloptila
81
The monotypic Hapaloptila castanea (Verreaux, J, 1866) was recovered as sister group
to Micromonacha, Cyphos, Nothriscus, Hypnelus, Nystactes, and Notharchus (Fig. 1, 3). Very
distinct in morphology, this species is specialized in cloud forests, usually above 1,500 m, and
even though it can be found in both sides of the Andes, no subspecies was ever described. The
two specimens we samples are from opposite sides of Andes, however a more focused work on
this species is required to understand the relationships among these apparently disjunct
populations.
6. Micromonacha
Micromonacha lanceolata (Deville, 1849) occurs in the middle and upper stories of
forests in both sides of the Andes, usually below 1,500 m. With populations also found in
Panama and Costa Rica. Although no subspecies is currently recognized (Rassmussen & Collar,
2018), populations from Central America were historically recognized in a distinct subspecies
M. l. austinsmithi Dwight and Griscom, 1942. Our results recovered the sample from Panama
as sister to the other two samples from Peru and Brazil, however, we refrain from making any
nomenclatural change pending better sampling of this group to fully understand its diversity.
7.Cyphos
Cyphos macrodactylus Spix, 1824 can only be found east of the Andes, mostly near water
inside terra-firme and varzea forests in Western Amazon. Our phylogeographic sampling
showed almost no genetic structure, only the westernmost sample showed some difference. If
this is, in fact, a phylogeographic structure, or just an artifact in sampling, still needs to be
investigated. The described subspecies C. m. caurensis (Cherrie, 1916) from the Caura River
region, Venezuela, is currently considered undifferentiated from the nominal form (Rassmussen
& Collar, 2018), and probably does not correspond to this phylogeographic break, additional
sampling is required for further assumptions.
8. Nothriscus
The three species included in the genus Nothriscus Cabanne & Heine 1863, N. tectus, N.
subtectus and N. picatus, were first described as full species, and later lumped and considered
conspecific as Nothriscus tectus (Boddaert, 1783) (Peters, 1948). Recently, N. subtectus
regained its status as full species (Rassmussen & Collar, 2018), but N. tectus and N. picatus are
still considered subspecies (Gill & Donsker, 2018; Remsen et al., 2018). Our results recovered
N. picatus as sister to a clade containing N. tectus and N. subtectus, both in the mtDNA and the
UCE tree. Biogeographically, implying that the two forms found in the Amazon, N. picatus and
N. tectus, are not sister. Therefore, we propose the recognition of these taxa as full species and
82
a more extensive work should be carried out to understand the limits of distribution of both
Amazonian species, and if there is any contact, what are the implications of it.
9. Hypnelus and Nystactes
The sister relationship of Hypnelus and Nystactes is supported by the autapomorphic bifid
bill tip in both genera, that is also present in Notharchus, although less pronounced in the later
(Rassmussen & Collar, 2018). Hypnelus species are restricted to northern South America, with
H. ruficollis (Wagler, 1829) having three subspecies, and H. bicinctus (Gould, 1837), two. Their
specific status has been questioned based on hybridization in part of their distribution (Donegan,
Quevedo, Verhelst, Cortés-Herrera, Ellery & Salaman, 2015), however without a thorough
genetic and geographic sampling, this decision remains questionable. Nystactes noanamae
(Hellmayr, 1909) and the species group of N. tamatia (Gmelin, JF, 1788), form the sister group
of Hypnelus (Fig. 1, 3). Nystactes noanamae, is a restricted-range species, present only in a
small portion of northwest Colombia, and currently considered Near-threatened by IUCN
(Rassmussen & Collar, 2018). Its sister species, N. tamatia, is associated with the flooded
forests in Amazonia, rarely found far from the water, even when in terra firme. Previous
phylogeographic study found six genetic lineages for N. tamatia, one lineage was composed by
only one sample though (Almeida, 2013). Nevertheless, our results corroborate the
relationships previously found, and further studies are being conducted to understand the
relationships and distribution of each lineage (Almeida, 2013).
10. Notharchus
Notharchus species can be grouped into three distinct groups based on distribution and
morphology. Notharchus ordii (Cassin, 1851), as sister to all other species, is restricted to
Amazonia, and unusually uncommon in collections. Its habitat preference and current
distribution is virtually unknown. The sampling we gathered for the mtDNA sequencing
actually represents all tissue samples available, and the apparent phylogeographic structure we
found (Fig. S9) may only represent an artifact of sampling. Notharchus pectorales (Gray, GR,
1846) is restricted to Northwest Colombia and East Panama. The last groups of species, is the
group centered in N. macrorhynchus (Gmelin, JF, 1788). The ND2 analyses recovered a
polytomy between the N. swainsoni (Gray, GR, 1846) N. macrorhynchus, and several lineages
of N. hyperrhynchus, including one lineage from Central America (Fig. S9). Our UCE tree, in
contrast, recovered N. macrorhynchus sister to N. swainsoni and N. hyperrhynchus. This result
corroborates the recognition of N. hyperrhynchus and N. swainsoni as full species and renders
the two Amazonian groups as non-sister lineages. Although the two subspecies of N.
83
hyperrhynchus seem to be paraphyletic in the UCE topology, the geographical relationship
seem to be reasonable, and a reappraisal of this subspecies distribution is desirable in further
studies.
Conclusion
The results presented here corroborate most of the diversity historically described in these
two families, but also hidden patterns that need further investigation. With our thorough
sampling of practically all widespread species and species complexes we were able to recover
the phylogeographic patterns for the entire diversification of jacamars and puffbirds. This study
is the first one to present a phylogenetic hypothesis for this two families employing a genomic
dataset. Based on this tree we resolved some relationships that were obscured by morphological
similarities among taxa, such as the recognition of the different species previously lumped into
Galbula ruficauda, and even revalidating four genera of puffbirds to accommodate paraphyletic
relationships found. Overall, the results presented here are another instance reinforcing the fact
that Neotropical bird diversity still is underestimated, and that we still need exploratory research
to fully comprehend diversity patterns, especially in the super complex Amazonian Basin,
which will be of extreme importance for future biogeographical interpretations and better
conservation planning.
Acknowledgements
The authors thankfully acknowledge all the curators and curatorial assistants of the
American Museum of Natural History, New York, USA (AMNH), Academy Academy of
Natural Science of Drexel University, Philadelphia, USA (ANSP); Field Museum of Natural
History, Chicago, USA (FMNH); Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil
(INPA); Kansas University (KU), Laboratório de Genética e Evolução Molecular de Aves –
USP (LGEMA), Lousiana State University Museum of Natural Science, Baton Rouge, USA
(LSUMZ); and Museu Paraense Emílio Goeldi, Belém, Brazil (MPEG), Smithsonian Institution
National Museum of Natural History (USNM), for borrowing tissue samples under their care.
We are also grateful for all collectors involved in the fieldwork that make this paper possible.
To J. McKay for helping with some laboratory procedures at the AMNH. MF acknowledge
CAPES for his PhD fellowship, and CAPES PDSE fellowship (# 88881.133440/2016-01) and
the support from the AMNH Frank M. Chapman Memorial Fund. The authors also thank the
grant Dimensions US-Biota-São Paulo: Assembly and evolution of the Amazon biota and its
84
environment: an integrated approach, co-funded by the US National Science Fundation (NSF
DEB 1241056) to J.C. and the Fundação de Amparo à Pesquisa do Estado de São Paulo
(FAPESP grant #2012/50260-6) to Lucia Lohmann; PEER-USAID Cycle 5 to CCR. AA and
CCR are supported by CNPq research productivity fellowships (#310880/2012-2 and
#308927/2016-8, respectively). The authors acknowledge the National Laboratory for
Scientific Computing (LNCC/MCTI, Brazil) for providing HPC resources of the SDumont
supercomputer, which have contributed to the research results reported within this paper.
References
Aberer AJ, Kobert K, Stamatakis A. 2014. ExaBayes: massively parallel bayesian tree
inference for the whole-genome era. Mol Biol Evol 31: 2553-2556.
Adeney JM, Christensen NL, Vicentini A, Cohn-Haft M. 2016. White-sand Ecosystems in
Amazonia. Biotropica 48: 7-23.
Aleixo A. 2007. Conceitos de espécie e o eterno conflito entre continuidade e operacionalidade:
uma proposta de normatização de critérios para o reconhecimento de espécies pelo
Comite Brasileiro de Registros Ornitológicos. Rev Bras Ornitol 15: 297-310.
Almeida B. 2013. Filogeografia de Bucco tamatia (Aves: Bucconidae): uma linhagem
associada a florestas alagadas na Amazônia. Mestrado em Zoologia, UFPA.
Avendaño JE, Arbeláez-Cortés E, Cadena CD. 2017. On the importance of geographic and
taxonomic sampling in phylogeography: A reevaluation of diversification and species
limits in a Neotropical thrush (Aves, Turdidae). Mol Phylogenet Evol 87-97.
Baker PA, Fritz SC, Dick CW, Eckert AJ, Horton BK, Manzoni S, Ribas CC, Garzione
CN, Battisti DS. 2014. The emerging field of geogenomics: Constraining geological
problems with genetic data. Earth-Sci Rev 135: 38-47.
Barrowclough GF, Cracraft J, Klicka J, Zink RM. 2016. How Many Kinds of Birds Are
There and Why Does It Matter? PLoS One 11: e0166307.
Bolger AM, Lohse M, Usadel B. 2014. Trimmomatic: a flexible trimmer for Illumina sequence
data. Bioinformatics 30: 2114-2120.
Borges SH, Da Silva JMC. 2012. A New Area of Endemism for Amazonian Birds in the Rio
Negro Basin. The Wilson J Ornithol 124: 15-23.
Bravo GA, Chesser RT, Brumfield RT. 2012. Isleria, a new genus of antwren (Aves:
Passeriformes: Thamnophilidae). Zootaxa 3195: 61-67.
Bravo GA, Remsen JV, Jr., Whitney BM, Brumfield RT. 2012. DNA sequence data reveal
a subfamily-level divergence within Thamnophilidae (Aves: Passeriformes). Mol
Phylogenet Evol 65: 287-293.
Cellinese N, Baum DA, Mishler BD. 2012. Species and phylogenetic nomenclature. Syst Biol
61: 885-891.
Cherrie GK. 1916. Two new birds from Venezuela. Bull Am Mus Nat Hist 35: 389.
Claramunt S, Cracraft J. 2015. A new time tree reveals Earth history's imprint on the
evolution of modern birds. Sci Adv 1: e1501005.
Cracraft J. 1985. Historical biogeography and patterns of differentiation within the South
American Avifauna: Areas of Endemism. Ornithol Monogr 36: 49-84.
Darriba D, Taboada GL, Doallo R, Posada D. 2012. jModelTest 2: more models, new
heuristics and parallel computing. Nat Methods 9: 772.
85
Dayrat B, Cantino PD, Clarke JA, de Queiroz K. 2008. Species Names in the PhyloCode:
the approach adopted by the International Society for Phylogenetic Nomenclature. Syst
Biol 57: 507-514.
de Queiroz K. 2005. Ernst Mayr and the modern concept of species. Proc Natl Acad Sci U S A
102 Suppl 1: 6600-6607.
de Queiroz K. 2007. Species concepts and species delimitation. Syst Biol 56: 879-886.
de Queiroz K. 2012. Biological nomenclature from Linnaeus to the PhyloCode. In: Bell CJ,
ed. The herpetological legacy of Linnaeus: A celebration of the Linnaean Tercentenary:
Bibliotheca Herpetologica 9. 135-145.
Donegan T, Quevedo A, Verhelst JC, Cortés-Herrera O, Ellery T, Salaman P. 2015.
Revision of the status of bird species occurring or reported in Colombia 2015, with
discussion of BirdLife International's new taxonomy. Conservacion Colombiana 23.
Donoghue PC, Moore BR. 2003. Toward an integrative historical biogeography. Integr Comp
Biol 43: 261-270.
Duarte SR. 2015. Filogenia molecular do gênero Nystalus (Bucconidae, Aves): enfoque na
estruturação populacional em N. maculatus e N. chacuru. Mestrado em Biologia
Animal, UNB.
Faircloth BC. 2013. illumiprocessor: a trimmomatic wrapper for parallel adapater and quality
trimming. http://dx.doi.org/10.6079/J9ILL.
Faircloth BC. 2016. PHYLUCE is a software package for the analysis of conserved genomic
loci. Bioinformatics 32: 786-788.
Faircloth BC, McCormack JE, Crawford NG, Harvey MG, Brumfield RT, Glenn TC.
2012. Ultraconserved elements anchor thousands of genetic markers spanning multiple
evolutionary timescales. Syst Biol 61: 717-726.
Fernandes AM, Cohn-Haft M, Hrbek T, Farias IP. 2014. Rivers acting as barriers for bird
dispersal in the Amazon. Rev Bras Ornitol 22: 363-373.
Fernandes AM, Gonzalez J, Wink M, Aleixo A. 2013. Multilocus phylogeography of the
Wedge-billed Woodcreeper Glyphorynchus spirurus (Aves, Furnariidae) in lowland
Amazonia: widespread cryptic diversity and paraphyly reveal a complex diversification
pattern. Mol Phylogenet Evol 66: 270-282.
Fernandes AM, Wink M, Sardelli CH, Aleixo A. 2014. Multiple speciation across the Andes
and throughout Amazonia: the case of the spot-backed antbird species complex
(Hylophylax naevius/Hylophylax naevioides). J Biogeogr: 41: 1094-1104
Ferreira M, Aleixo A, Ribas CC, Santos MPD. 2017. Biogeography of the Neotropical genus
Malacoptila (Aves: Bucconidae): the influence of the Andean orogeny, Amazonian
drainage evolution and palaeoclimate. Journal of Biogeography 44: 748-759.
Gilbert MP, Jarvis ED, Li B, Li C, Avian Genome C, Wang J, Zhang G. 2014a. Genomic
data of the Downy Woodpecker (Picoides pubescens). GigaScience Database.
Gilbert MP, Jarvis ED, Li B, Li C, Avian Genome C, Wang J, Zhang G. 2014b. Genomic
data of the Javan rhinoceros hornbill (Buceros rhinoceros silvestris). GigaScience
Database.
Gilbert MP, Jarvis ED, Li B, Li C, Avian Genome C, wang J, Zhang J. 2014c. Genomic
data of the Northern Carmine bee-eater (Merops nubicus). GigaScience Database.
Gill F, Donsker D. 2018. IOC World Bird List (v8.1). doi: 10.14344/IOC.ML.8.1
Gill FB. 2014. Species taxonomy of birds: Which null hypothesis? Auk 131: 150-161.
Haffer J. 1969. Speciation in amazonian forest birds. Science 165: 131-137.
Haffer J. 1974. Avian speciation in Tropical South America. Nuttall Ornithological Club:
Harvard University, Cambridge.
Haffer J. 1997. Alternative models of vertebrate speciation in Amazonia: an overview.
Biodivers Conserv 6: 451-476.
86
Harvey MG, Seeholzer GF, Cáceres A D, Winger BM, Tello JG, Camacho FH, Aponte
Justiniano MA, Judy CD, Ramírez SF, Terrill RS, Brown CE, León LAA, Bravo
G, Combe M, Custodio O, Zumaeta AQ, Tello AU, Bravo WAG, Savit AZ, Ruiz
FWP, Mauck WM, Barden O. 2014. The avian biogeography of an Amazonian
headwater: the Upper Ucayali River, Peru. Wilson J Ornithol 126: 179-191.
Isler ML, Bravo GA, Brumfield RT. 2013. Taxonomic revision of Myrmeciza (Aves:
Passeriformes: Thamnophilidae) into 12 genera based on phylogenetic, morphological,
behavioral, and ecological data. Zootaxa 3717: 469.
Katoh K, Standley DM. 2013. MAFFT Multiple Sequence Alignment Software Version 7:
Improvements in Performance and Usability. Mol Biol Evol 30: 772-780.
Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, Buxton S, Cooper
A, Markowitz S, Duran C, Thierer T, Ashton B, Meintjes P, Drummond A. 2012.
Geneious Basic: An integrated and extendable desktop software platform for the
organization and analysis of sequence data. Bioinformatics 28: 1647-1649.
Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. Nat Methods 9:
357-359.
Lexer C, Mangili S, Bossolini E, Forest F, Stölting KN, Pearman PB, Zimmermann NE,
Salamin N, Carine M. 2013. ‘Next generation’ biogeography: towards understanding
the drivers of species diversification and persistence. J Biogeogr 40: 1013-1022.
Livezey BC, Zusi RL. 2007. Higher-order phylogeny of modern birds (Theropoda, Aves:
Neornithes) based on comparative anatomy. II. Analysis and discussion. Zool J Linn
Soc 149: 1-95.
Lopes LE, Chaves AV, Aquino MM, Silveira LF, Santos FR. 2017. The striking polyphyly
of Suiriri: Convergent evolution and social mimicry in two cryptic Neotropical birds. J
Zool Syst Evol Res Early view.
Lutz HL, Weckstein JD, Patane JS, Bates JM, Aleixo A. 2013. Biogeography and spatio-
temporal diversification of Selenidera and Andigena Toucans (Aves: Ramphastidae).
Mol Phylogenet Evol 69: 873-883.
Mayr E. 1942. Systematics and the Origin of Species. Columbia Univ. Press: New York.
Mayr E. 1976. Species concept and definitions Topics in the Phylosophy of Biology.
Netherlands: Springer. 353-371.
McCormack JE, Faircloth BC. 2013. Next-generation phylogenetics takes root. Mol Ecol 22:
19-21.
McCormack JE, Harvey MG, Faircloth BC, Crawford NG, Glenn TC, Brumfield RT.
2013. A phylogeny of birds based on over 1,500 loci collected by target enrichment and
high-throughput sequencing. PLoS One 8: e54848.
McCormack JE, Tsai WLE, Faircloth BC. 2016. Sequence capture of ultraconserved
elements from bird museum specimens. Mol Ecol Resour 16: 1189-1203.
Peters JL. 1945. Check-list of birds of the world. Harvard University Press: Cambrigde.
Peters JL. 1948. Check-list of birds of the world. Harvard University Press: Cambridge, UK.
Piacentini VD, Aleixo A, Agne CE, Mauricio GN, Pacheco JF, Bravo GA, Brito GRR,
Naka LN, Olmos F, Posso S, Silveira LF, Betini GS, Carrano E, Franz I, Lees AC,
Lima LM, Pioli D, Schunck F, do Amaral FR, Bencke GA, Cohn-Haft M,
Figueiredo LFA, Straube FC, Cesari E. 2015. Annotated checklist of the birds of
Brazil by the Brazilian Ornithological Records Committee. Revista Brasileira de
Ornitologia 23: 91-298.
Prum RO, Berv JS, Dornburg A, Field DJ, Townsend JP, Lemmon EM, Lemmon AR.
2015. A comprehensive phylogeny of birds (Aves) using targeted next-generation DNA
sequencing. Nature 526: 569-573.
87
Rambaut A, Suchard MA, Xie D, Drummond AJ. 2014. Tracer v1.6. Availabe at:
http://tree.bio.ed.ac.uk/software/tracer/
Rassmussen P, Collar N. 2002. Family Bucconidae (Puffbirds). In: del Hoyo J, Elliot A and
Sargatal J, eds. Handbook of the birds of the world: Lynx Edicions.
Rassmussen P, Collar N. 2018. Puffbirds (Bucconidae). In: del Hoyo J, Elliot A, Sargatal J,
Christie DA and Juana E, eds. Handbook of the birds of the world Alive. Barcelona:
Lynx Ediciones.
Remsen JV, Jr., Areta JI, Cadena CD, Claramunt S, Jaramillo C, Pacheco JF, Pérez-
Emen J, Robbins MB, Stiles FG, Stotz DF, Zimmer KJ. 2018. A classification of the
bird species of South America. American Ornithologists' Union.
http://www.museum.lsu.edu/~Remsen/SACCBaseline.htm
Ribas CC, Aleixo A, Gubili C, d'Horta FM, Brumfield RT, Cracraft J. 2018. Biogeography
and diversification of Rhegmatorhina (Aves: Thamnophilidae): Implications for the
evolution of Amazonian landscapes during the Quaternary. J Biogeogr Early View.
https://doi.org/10.1111/jbi.13169
Ribas CC, Aleixo A, Nogueira AC, Miyaki CY, Cracraft J. 2012. A palaeobiogeographic
model for biotic diversification within Amazonia over the past three million years. Proc
Biol Sci 279: 681-689.
Ribas CC, Gaban-Lima R, Miyaki CY, Cracraft J. 2005. Historical biogeography and
diversification within the Neotropical parrot genus Pionopsitta (Aves: Psittacidae). J
Biogeogr 32: 1409-1427.
Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Hohna S, Larget B, Liu
L, Suchard MA, Huelsenbeck JP. 2012. MrBayes 3.2: efficient Bayesian phylogenetic
inference and model choice across a large model space. Syst Biol 61: 539-542.
Sloan DB, Havird JC, Sharbrough J. 2017. The on-again, off-again relationship between
mitochondrial genomes and species boundaries. Mol Ecol 26: 2212-2236.
Soares LMS. 2016. Sistemática molecular e diversificação dos gêneros Nonnula e Monasa
(Aves: Bucconidae). Doutorado em Zoologia, UFPA.
Tobias JA. 2017. Jacamars (Galbulidae). In: del Hoyo J, Elliot A and Sargatal J, eds. Handbook
of the birds of the world. Barcelona: Lynx Ediciones.
Tobias JA, Bates JM, Hackett SJ, Seddon N. 2008. Comment on "The latitudinal gradient in
recent speciation and extinction rates of birds and mammals". Science 319: 901; author
reply 901.
88
Figure 1 – Phylogeny of the Galbulidae and Bucconidae families inferred with ExaBayes. All nodes in this tree
receive the maximum posterior probability. The two genomes used as reference sequence were included in this
analysis.
89
Figure 2 – Phylogeny of the Galbulidae inferred by ExaBayes with the 75% completeness matrix. Node support
is indicated near it, if no support is indicated posterior probability is 1.0.
90
Figure 3 – Phylogeny of the Bucconidae inferred by ExaBayes with the 75% completeness matrix. Node support
is indicated near it, if no support is indicated posterior probability is 1.0.
91
Figure S1 – Phylogenetic relationship and map with sample distribution of Brachygalba and Jacamaralcyon
species. Phylogenetic tree was recovered by MrBayes using the mtDNA gene ND2 (1041bp). Red circles mean
posterior probabilities of 1.0, values that differs are indicated near the node. Samples highlighted in red were the
samples selected for UCE analysis. The maps contain sample localities and approximate lineage distribution.
Colours are correspondent between the tree and the map.
92
Figure S2 – Phylogenetic relationship and map with sample distribution of Jacamerops aureus complex.
Phylogenetic tree was recovered by MrBayes using the mtDNA gene ND2 (1041bp). Red circles mean posterior
probabilities of 1.0, values that differs are indicated near the node. Samples highlighted in red were the samples
selected for UCE analysis. The maps contain sample localities and approximate lineage distribution. Colours are
correspondent between the tree and the map.
93
Figure S3 – Phylogenetic relationship and map with sample distribution of Galbula dea complex. Phylogenetic
tree was recovered by MrBayes using the mtDNA gene ND2 (1041bp). Red circles mean posterior probabilities
of 1.0, values that differs are indicated near the node. Samples highlighted in red were the samples selected for
UCE analysis. The maps contain sample localities and approximate lineage distribution. Colours are
correspondent between the tree and the map.
94
Figure S4 – Phylogenetic relationship and map with sample distribution of the species complex of G. albirostris,
G. chalcocephala and G. albirostris. Phylogenetic tree was recovered by MrBayes using the mtDNA gene ND2
(1041bp). Red circles mean posterior probabilities of 1.0, values that differs are indicated near the node. Samples
highlighted in red were the samples selected for UCE analysis. The maps contain sample localities and
approximate lineage distribution. Colours are correspondent between the tree and the map.
95
Figure S5 – Phylogenetic relationship and map with sample distribution of the species complex of G. galbula, G.
tombacea, G. cyanescens, G. pastazae, and G. ruficauda. Phylogenetic tree was recovered by MrBayes using the
mtDNA gene ND2 (1041bp). Red circles mean posterior probabilities of 1.0, values that differs are indicated
near the node. Samples highlighted in red were the samples selected for UCE analysis. The maps contain sample
localities and approximate lineage distribution. Colours are correspondent between the tree and the map.
96
Figure S6 – Phylogenetic relationship and map with sample distribution of the species Bucco capensis.
Phylogenetic tree was recovered by MrBayes using the mtDNA gene ND2 (1041bp). Red circles mean posterior
probabilities of 1.0, values that differs are indicated near the node. Samples highlighted in red were the samples
selected for UCE analysis. The maps contain sample localities and approximate lineage distribution. Colours are
correspondent between the tree and the map.
97
Figure S7 – Phylogenetic relationship and map with sample distribution of the species Cyphos macrodactylus.
Phylogenetic tree was recovered by MrBayes using the mtDNA gene ND2 (1041bp). Red circles mean posterior
probabilities of 1.0, values that differs are indicated near the node. Samples highlighted in red were the samples
selected for UCE analysis. The maps contain sample localities and approximate lineage distribution. Colours are
correspondent between the tree and the map.
98
Figure S8 – Phylogenetic relationship and map with sample distribution of the species complex of Notharchus
tectus, N. subtectus, and N. picatus. Phylogenetic tree was recovered by MrBayes using the mtDNA gene ND2
(1041bp). Red circles mean posterior probabilities of 1.0, values that differs are indicated near the node. Samples
highlighted in red were the samples selected for UCE analysis. The maps contain sample localities and
approximate lineage distribution. Colours are correspondent between the tree and the map.
99
Figure S9 – Phylogenetic relationship and map with sample distribution of the species complex of Notharchus
ordii, N. pectorales, N. swainsoni, N. macrorhynchus, and N. hyperrhynchus. Phylogenetic tree was recovered by
MrBayes using the mtDNA gene ND2 (1041bp). Red circles mean posterior probabilities of 1.0, values that
differs are indicated near the node. Samples highlighted in red were the samples selected for UCE analysis. The
maps contain sample localities and approximate lineage distribution. Colours are correspondent between the tree
and the map.
100
Figure S10 – Phylogenetic relationship and map with sample distribution of the species Chelidoptera tenebrosa.
Phylogenetic tree was recovered by MrBayes using the mtDNA gene ND2 (1041bp). Red circles mean posterior
probabilities of 1.0, values that differs are indicated near the node. Samples highlighted in red were the samples
selected for UCE analysis. The maps contain sample localities and approximate lineage distribution. Colours are
correspondent between the tree and the map.
101
Figure S11 – Phylogenetic tree recovered for Monasa using a subset of samples to check for M. mystacalis
phylogenetic affinity. The same tree topology was recovered by RAxML and ExaBayes, the RAxML bootstrap
support were low overall.
Figure S12 – Phylogenetic tree recovered for Malacoptila using a subset of samples to check for M. mystacalis
phylogenetic affinity. The same tree topology was recovered by RAxML and ExaBayes with high support, with
only node receiving bootstrap support different from 100.
102
Síntese Geral
Neste trabalho coletamos dados que nos ajudaram a compreender a relação filogenética
de três famílias de aves do Neotrópico. A utilização de dados de sequenciamento genômico e a
inclusão de amostras representando quase todas as linhagens basais em cada família permitiu
realizar inferências sobre a importância de uma amostragem ampla, tanto num sentido de
amostras, quanto marcadores. No primeiro capítulo pudemos observar o impacto do conflito
entre marcadores moleculares com diferentes padrões de herança, e quais as implicações
biológicas deste conflito. Além disso, através da análise combinada da história dos dois
marcadores foi possível propor um modelo de evolução das áreas de vegetação aberta
relacionadas aos solos de areia branca dentro da bacia Amazônia. No segundo capítulo,
recuperamos a relação filogenética da família Trogonidae utilizando quase todas as espécies
descritas com base em uma matriz com mais de 2.000 marcadores moleculares. Com base
nesses resultados traçamos um modelo de como a evolução do clima desde o final do Oligoceno
e as conexões entre os continentes influenciaram a história de diversificação do grupo. Por fim,
no terceiro capítulo, analisamos a diversidade intraespecífica de duas famílias endêmicas do
Neotrópico e reconstruímos a primeira hipótese de relação filogenética para Galbulidae e
Bucconidae utilizando dados genômicos. Neste capítulo pudemos observar como a percepção
da diversidade nesses grupos é subestimada e influenciada pela taxonomia vigente, e que a
amostragem densa ao longo da distribuição de espécies amplamente distribuídas pode revelar
táxons e padrões ainda desconhecidos.
De modo geral, este trabalho reforça a complexidade dos padrões de diversidade da biota
Neotropical, e que ainda se faz necessário estudos para desvendar esses padrões, em especial
na Amazônia. Além disso, fica claro que a diversidade real da região ainda está mascarada pela
taxonomia vigente e revisões sistemáticas e taxonômicas são necessárias. Só através do
reconhecimento dessa diversidade escondida é que será possível, não só traçar hipóteses sobre
os processos que deram origem a tamanha diversidade, mas também traçar planos de
conservação que reconheçam a história evolutiva de cada um desses grupos.
103
Referências Bibliográficas
ALEIXO, A. Conceitos de espécie e o eterno conflito entre continuidade e operacionalidade: uma
proposta de normatização de critérios para o reconhecimento de espécies pelo Comite Brasileiro
de Registros Ornitológicos. Revista Brasileira de Ornitologia, v. 15, n. 2, p. 297-310, 2007.
______. Conceitos de espécie e suas implicações para a conservação. Megadiversidade, v. 5, n. 1-2, p.
87-95, 2009.
ÁVILA-PIRES, T. C. S. Lizards of Brazilian Amazon (Reptilia: Squamata). Zool Verh Natuur Mus,
v. 299, p. 1-637, 1995.
AVISE, J. C. Phylogeography: retrospect and prospect. J Biogeogr, v. 36, n. 1, p. 3-15, 2009.
AVISE, J. C. et al. Intraspecific phylogeography: The mitochondrial DNA bridge between population
genetics and systematics. Annu Rev Ecol Syst, v. 18, p. 489-522, 1987.
BAKER, P. A. et al. The emerging field of geogenomics: Constraining geological problems with genetic
data. Earth-Sci Rev, v. 135, p. 38-47, 2014.
BARROWCLOUGH, G. F. et al. How Many Kinds of Birds Are There and Why Does It Matter? Plos
One, v. 11, n. 11, p. e0166307, 2016.
BATES, J. M. et al. Diversification in the Neotropics: Phylogenetic patterns and historical processes.
Ornitologia Neotropical, v. 19, n. (Suppl.), p. 427-432, 2008.
BATES, J. M.; HAFFER, J.; GRISMER, E. Avian mitochondrial DNA sequence divergence across a
headwater stream of the Rio Tapajós, a major Amazonian river. Journal of Ornithology, v.
145, n. 3, p. 199-205, 2004.
BOUBLI, J. P. et al. Spatial and temporal patterns of diversification on the Amazon: A test of the
riverine hypothesis for all diurnal primates of Rio Negro and Rio Branco in Brazil. Mol
Phylogenet Evol, v. 82 Pt B, p. 400-12, 2015.
BOUBLI, J. P. et al. How many Pygmy Marmoset (Cebuella Gray, 1870) species are there? A
taxonomic re-appraisal based on new molecular evidence. Mol Phylogenet Evol, v. 120, p. 170-
82, 2017.
BROMHAM, L. et al. Bayesian molecular dating: opening up the black box. Biol Rev v. Early view,
2017. doi: 10.1111/brv.12390
BROMHAM, L.; PENNY, D. The modern molecular clock. Nat Rev Genet, v. 4, n. 3, p. 216-24, Mar
2003.
BROWN, K. S.; SHEPPARD, P. M.; TURNER, J. R. G. Quaternary refugia in tropical America:
evidence from race formation in Heliconius butterflies. Proc R Soc Lond B, v. 187, p. 369-378,
1974.
BRYSON, R. W., JR. et al. Target enrichment of thousands of ultraconserved elements sheds new light
on early relationships within New World sparrows (Aves: Passarelidae). Auk, v. 133, n. 3, p.
451-458, 2016.
104
BUSH, M. B. Amazonian speciation: A necessarily complex model. Journal of Biogeography, v. 21,
p. 5-17, 1995.
BUSH, M. B.; OLIVEIRA, P. E. D. The rise and fall of the Refugial Hypothesis of Amazonian
speciation: a paleoecological perspective. Biota Neotrop, v. 6, n. 1, 2006.
BYRNE, H. et al. Phylogenetic relationships of the New World titi monkeys (Callicebus): first appraisal
of taxonomy based on molecular evidence. Front Zool, v. 13, n. 1, 2016.
CARNEIRO, J. C. et al. Phylogeny of the Titi monkeys of the Callicebus moloch group (Pitheciidae,
Primates). Am J Primatol, v. 78, p. 904-913, 2016.
CELLINESE, N.; BAUM, D. A.; MISHLER, B. D. Species and phylogenetic nomenclature. Syst Biol,
v. 61, n. 5, p. 885-891, 2012.
CHENG, H. et al. Climate change patterns in Amazonia and biodiversity. Nat Commun, v. 4, p. 1411,
2013.
COATES, A. G.; STALLARD, R. F. How old is the Isthmus of Panama? Bull Mar Sci, v. 89, n. 4, p.
801-813, 2013.
COLINVAUX, P. A.; DE OLIVEIRA, P. E.; BUSH, M. B. Amazonian and neotropical plant
communities on glacial time-scales: The failure of the aridity and refuge hypothesis.
Quaternary Science Reviews, v. 19, p. 141-169, 2000.
COLLAR, N. Trogons (Trogonidae). In: DEL HOYO, J.;ELLIOT, A., et al (Ed.). Handbook of the
birds of the world Alive. Barcelona: Lynx Ediciones, 2018.
COLOMBO, A. F.; JOLY, C. A. Brazilian Atlantic Forest lato sensu: the most ancient Brazilian forest,
and a biodiversity hotspot, is highly threatene by climate change. Braz J Biol, v. 70, p. 697-708,
2010.
CRACRAFT, J. Toward a phylogenetic classification of the recent birds of the world (Class Aves). Auk,
v. 98, n. 4, p. 681-714, 1981.
______. Historical biogeography and patterns of differentiation within the South American Avifauna:
Areas of Endemism. Ornitholigical Monographs, v. 36, p. 49-84, 1985.
CRAWFORD, N. G. et al. A phylogenomic analysis of turtles. Molecular Phylogenetics and
Evolution, v. 83, p. 250-257, 2015.
D’HORTA, F. M. et al. Phylogeny and comparative phylogeography of Sclerurus (Aves: Furnariidae)
reveal constant and cryptic diversification in an old radiation of rain forest understorey
specialists. Journal of Biogeography, v. 40, n. 1, p. 37-49, 2013.
DACOSTA, J. M.; KLICKA, J. The Great American Interchange in birds: a phylogenetic perspective
with the genus Trogon. Mol Ecol, v. 17, n. 5, p. 1328-43, Mar 2008.
DAVEY, J. W. et al. Genome-wide genetic marker discovery and genotyping using next-generation
sequencing. Nat Rev Genet, v. 12, n. 7, p. 499-510, 2011
DE QUEIROZ, K. Ernst Mayr and the modern concept of species. Proc Natl Acad Sci U S A, v. 102
Suppl 1, p. 6600-7, 3 2005.
105
______. Branches in the lines of descent: Charles Darwin and the evolution of the species concept. Biol
J Linn Soc, v. 103, p. 19-35, 2011.
______. Biological nomenclature from Linnaeus to the PhyloCode. In: BELL, C. J. (Ed.). The
herpetological legacy of Linnaeus: A celebration of the Linnaean Tercentenary: Bibliotheca
Herpetologica 9, 2012. p.135-145.
DEGNAN, J. H.; ROSENBERG, N. A. Discordance of species trees with their most likely gene trees.
PLoS Genet, v. 2, n. 5, p. e68, 2006.
DEGNAN, J. H.; ROSENBERG, N. A. Gene tree discordance, phylogenetic inference and the
multispecies coalescent. Trends Ecol Evol, v. 24, n. 6, p. 332-340, 2009.
DONOGHUE, M. J. A critique of the Biological Species Concept and recommendations for a
phylogenetic alternative. The Bryologist, v. 88, n. 3, p. 172-181, 1985.
DONOGHUE, P. C.; MOORE, B. R. Toward an integrative historical biogeography. Integr Comp Biol,
v. 43, p. 261-270, 2003.
DUARTE, S. R. Filogenia molecular do gênero Nystalus (Bucconidae, Aves): enfoque na
estruturação populacional em N. maculatus e N. chacuru. 2015. (Mestrado em Biologia
Animal). Instituto de Biologia, UNB, Brasília.
EHLERS, T. A.; POULSEN, C. J. Influence of Andean uplift on climate and paleoaltimetry estimates.
Earth Planet Sci Lett, v. 281, p. 238-248, 2009.
FAIRCLOTH, B. C. et al. Target enrichment of ultraconserved elements from arthropods provides a
genomic perspective on relationships among Hymenoptera. Mol Ecol Resour, v. 15, n. 3, p.
489-501, 2015.
FAIRCLOTH, B. C. et al. Ultraconserved elements anchor thousands of genetic markers spanning
multiple evolutionary timescales. Syst Biol, v. 61, n. 5, p. 717-26, Oct 2012.
FERNANDES, A. M. et al. Multilocus phylogeography of the Wedge-billed Woodcreeper
Glyphorynchus spirurus (Aves, Furnariidae) in lowland Amazonia: widespread cryptic diversity
and paraphyly reveal a complex diversification pattern. Mol Phylogenet Evol, v. 66, n. 1, p.
270-82, 2013.
FERNANDES, A. M. et al. Multiple speciation across the Andes and throughout Amazonia: the case
of the spot-backed antbird species complex (Hylophylax naevius/Hylophylax naevioides).
Journal of Biogeography, p. n/a-n/a, 2014. ISSN 03050270.
FERREIRA, M. et al. Biogeography of the Neotropical genus Malacoptila (Aves: Bucconidae): the
influence of the Andean orogeny, Amazonian drainage evolution and palaeoclimate. Journal of
Biogeography, v. 44, n. 4, p. 748-759, 2017.
GARZIONE, C. N. et al. Rise of the Andes. Science, v. 320, n. 5881, p. 1304-7, Jun 6 2008.
GILL, F.; DONSKER, D. IOC World Bird List (v8.1). 2018.
GILL, F. B. Hybrization in birds. Journal of Ornithology, v. 115, n. 2, p. 281-283, 1998.
GRANT, P. R.; GRANT, B. R. Hybridization of bird species. Science, v. 256, n. 5054, p. 193-197,
1992.
106
GROVER, C. E.; SALMON, A.; WENDEL, J. F. Targeted sequence capture as a powerful tool for
evolutionary analysis. Am J Bot, v. 99, n. 2, p. 312-319, 2012.
HACKETT, S. J. et al. A phylogenomic study of birds reveals their evolutionary history. Science, v.
320, n. 5884, p. 1763-8, 2008.
HAFFER, J. Speciation in amazonian forest birds. Science, v. 165, n. 3889, p. 131-7, 1969.
______. Avian zoogeography in the Neotropical lowlands. Ornitholigical Monographs, v. 36, p. 113-
146, 1985.
______. Alternative models of vertebrate speciation in Amazonia: an overview. Biodivers Conserv, v.
6, p. 451-476, 1997.
HARRISON, R. G.; LARSON, E. L. Hybridization, introgression, and the nature of species boundaries.
J Hered, v. 105 Suppl 1, p. 795-809, 2014.
HARTLEY, A. Andean uplift and climate change. Journal of the Geological Society, London, v. 160,
p. 7-10, 2003.
HAUG, G. H.; TIEDEMAN, R. Effect of the formation of the Isthmus of Panama on Atlantic Ocean
thermohaline circulation. Nature, v. 393, p. 673-676, 1998.
HOLT, B. G. et al. An update of Wallace's zoogeographic regions of the world. Science, v. 339, n.
6115, p. 74-8, 2013.
HOORN, C. Marine incursions and the influence of Andean tectonics on the Miocene depositional
history of northwestern Amazonia: results of a palynostratigraphic study. Palaeogeography,
Palaeoclimatology, Palaeoecology, v. 105, n. 3-4, p. 267-309, 1993.
HOORN, C. et al. The Amazon at sea: Onset and stages of the Amazon River from a marine record,
with special reference to Neogene plant turnover in the drainage basin. Global Plant Change,
2017.
HOORN, C.; WESSELINGH, F. P. Amazonia: Landscape and species evolution: A look into past.
Oxford: Wiley-Blackwell Publishing Ltd., 2010.
HOORN, C. et al. Amazonia through time: Andean uplift, climate change, landscape evolution, and
biodiversity. Science, v. 330, n. 6006, p. 927-31, 2010.
HOPKINS, M. J. G. Modelling the known and unkown plant biodiversity of the Amazon Basin. J
Biogeogr, v. 34, p. 1400-1411, 2007.
HORTON, B. K. Tectonic regimes of the Central and Southern Andes: Responses to variations in plate
coupling during subduction. Tectonics, v. Early View, 2018. doi: 10.1002/2017TC004624
HOSNER, P. A. et al. Phylogeny and biogeography of the Asian trogons (Aves: Trogoniformes)
inferred from nuclear and mitochondrial DNA sequences. Mol Phylogenet Evol, v. 57, n. 3, p.
1219-25, 2010.
HRBEK, T. et al. A new species of river dolphin from Brazil or: how little do we know our biodiversity.
PLoS One, v. 9, n. 1, p. e83623, 2014.
107
INSEL, N.; POULSEN, C. J.; EHLERS, T. A. Influence of the Andes Mountains on South American
moisture transport, convection, and precipitation. Clim Dyn, v. 35, n. 7-8, p. 1477-1492, 2009.
ISAAC, N. J. B.; MALLET, J.; MACE, G. M. Taxonomic inflation: its influence on macroecology and
conservation. Trends Ecol Evol, v. 19, n. 9, p. 464-469, 2004.
JARVIS, E. D. et al. Phylogenomic analyses data of the avian phylogenomics project. Gigascience, v.
4, p. 4, 2015.
JETZ, W. et al. The global diversity of birds in space and time. Nature, v. 491, n. 7424, p. 444-8, 2012.
JOHANSSON, U. S.; ERICSON, P. G. P. A re-evaluation of basal phylogenetic relationships within
trogons (Aves: Trogonidae) based on nuclear DNA sequences. J Zool Syst Evol Res, v. 43, n.
2, p. 166-173, 2005.
JOSEPH, L. et al. Where and when does a ring start and end? Testing the ring-species hypothesis in a
species complex of Australian parrots. Proc Biol Sci, v. 275, n. 1650, p. 2431-40, 2008.
KIER, G. et al. Global patterns of plant diversity and floristic knowledge. J Biogeogr, v. 32, p. 1107-
1116, 2005.
KNOWLES, L. L. Statistical Phylogeography. Annu Rev Ecol Evol Syst, v. 40, n. 1, p. 593-612, 2009.
KRISTOFFERSEN, A. V. An early Paleogene trogon (Aves: Trogoniformes) from the Fur Formation,
Denmark. J Vert Paleontol, v. 22, n. 3, p. 661-666, 2002.
LATRUBESSE, E. M. et al. The Late Miocene paleogeography of the Amazon Basin and the evolution
of the Amazon River system. Earth-Sci Rev, v. 99, n. 3-4, p. 99-124, 2010.
LEITE, R. N.; ROGERS, D. S. Revisiting Amazonian phylogeography: insights into diversification
hypotheses and novel perspectives. Organisms Diversity & Evolution, 2013.
LEMMON, A. R.; EMME, S. A.; LEMMON, E. M. Anchored hybrid enrichment for massively high-
throughput phylogenomics. Syst Biol, v. 61, n. 5, p. 727-44, Oct 2012.
LEMMON, E. M.; LEMMON, A. R. High-Throughput Genomic Data in Systematics and
Phylogenetics. Annu Rev Ecol Evol Syst, v. 44, n. 1, p. 99-121, 2013.
LESSIOS, H. A. Appearance of an early closure of the Isthmus of Panama is the product of biased
inclusion of data in the metaanalysis. PNAS, v. 112, n. 43, p. E5765, 2015.
LIMA, M. G. M. et al. Capuchin monkey biogeography: understanding Sapajus Pleistocene range
expansion and the current sympatry between Cebus and Sapajus. Journal of Biogeography, v.
44, n. 4, p. 810-820, 2017.
LIVEZEY, B. C.; ZUSI, R. L. Phylogeny of Neornithes. Bull Carnegie Mus Nat Hist, v. 37, p. 1-544,
2006.
______. Higher-order phylogeny of modern birds (Theropoda, Aves: Neornithes) based on comparative
anatomy. II. Analysis and discussion. Zoological Journal of the Linnean Society, v. 149, p. 1-
95, 2007.
108
MANTHEY, J. D. et al. Comparison of Target-Capture and Restriction-Site Associated DNA
Sequencing for Phylogenomics: A Test in Cardinalid Tanagers (Aves, Genus: Piranga). Syst
Biol, v. 65, n. 4, p. 640-50, 2016.
MAURER, D. R.; RAIKOW, R. J. Appendicular myology, phylogeny and classificaiton of the avian
order Coraciiformes (inluding Trogoniformes). Ann Carnegie Mus, v. 50, p. 417-434, 1981.
MAYR, E. Systematics and the Origin of Species. New York: Columbia Univ. Press, 1942.
______. Species concept and definitions. In: (Ed.). Topics in the Phylosophy of Biology. Netherlands:
Springer, 1976. p.353-371.
MAYR, G. A new trogon from the Middle Oligocene of Céreste, France. Auk, v. 116, n. 2, p. 427-434,
1999.
______. On the phylogenetic relationships of trogons (Aves, Trogonidae). Journal of Avian Biology,
v. 34, p. 81-88, 2003.
MAYR, G. New trogons from the early Tertiary of Germany. Ibis, v. 147, p. 512-518, 2005.
MCCORMACK, J. E. et al. Ultraconserved elements are novel phylogenomic markers that resolve
placental mammal phylogeny when combined with species-tree analysis. Genome Res, v. 22,
n. 4, p. 746-54, 2012.
MEIKLEJOHN, K. A. et al. Analysis of a rapid evolutionary radiation using Ultraconserved Elements:
Evidence for a bias in some multispecies coalescent methods. Systematic Biology, v. 65, n. 4,
p. 612-627, 2016.
METZKER, M. L. Sequencing technologies - the next generation. Nature Reviews Genetics, v. 11, p.
31-46, 2010.
MITTERMEIER, R. A. et al. Wilderness and biodiversity conservation. Proc Natl Acad Sci U S A, v.
100, n. 18, p. 10309-13, 2003.
MONTEROS, A. E. Phylogenetic relationships among the Trogons. Auk, v. 115, n. 4, p. 937-954, 1998.
MONTEROS, A. E. Higher-level phylogeny of Trogoniformes. Mol Phylogenet Evol, v. 14, n. 1, p.
20-34, 2000.
MOYLE, R. G. Phylogeny and biogeographical history of Trogoniformes, a pantropical bird order. Biol
J Linn Soc, v. 84, p. 725-738, 2005.
MYERS, N. et al. Biodiversity hotspots for conservation priorities. Nature, v. 403, n. 6772, p. 853-8,
2000.
NOGUEIRA, A. C. R.; SILVEIRA, R.; GUIMARÃES, J. T. F. Neogene–Quaternary sedimentary and
paleovegetation history of the eastern Solimões Basin, central Amazon region. Journal of South
American Earth Sciences, v. 46, p. 89-99, 2013.
NORES, M. An alternative hypothesis for the origin of Amazonian bird diversity. Journal of
Biogeography, v. 26, n. 3, p. 475-485, 1999.
______. The implications of Tertiary and Quaternary sea level rise events for avian distribution patterns
in the lowlands of northern South America. Global Ecol Biogeogr, v. 13, p. 149-161, 2004.
109
ODEA, A. et al. Formation of the Isthmus of Panama. Science Advances, v. 2, n. 8, p. e1600883, 2016.
OLIVEIRA, U.; VASCONCELOS, M. F.; SANTOS, A. J. Biogeography of Amazon birds: rivers limit
species composition, but not areas of endemism. Scientific Reports, v. 7, p. 2992, 2017.
OLIVER, J. Microevolutionary processes generate phylogenomic discordance at ancient divergences.
Evolution, v. 67, n. 6, p. 1823-1830, 2013.
ORNELAS, J. F.; GONZALEZ, C.; ESPINOSA DE LOS MONTEROS, A. Uncorrelated evolution
between vocal and plumage coloration traits in the trogons: a comparative study. J Evol Biol, v.
22, n. 3, p. 471-84
POLO, E. M. Influência da formação do curso atual do rio Negro na origem da diversificação
regional em alguns grupos de aves. 2015. (Mestrado em Genética). GCBEv, INPA, Manaus,
AM.
PRUM, R. O. et al. A comprehensive phylogeny of birds (Aves) using targeted next-generation DNA
sequencing. Nature, v. 526, n. 7574, p. 569-73, 2015.
RAMSEN, J. V., JR. et al. A classification of the bird species of South America. American
Ornithologists' Union. 2018.
RIBAS, C. C. et al. Biogeography and diversification of Rhegmatorhina (Aves: Thamnophilidae):
Implications for the evolution of Amazonian landscapes during the Quaternary. J Biogeogr, v.
Early View, 2018. doi: 10.1111/jbi.13169
RIBAS, C. C. et al. A palaeobiogeographic model for biotic diversification within Amazonia over the
past three million years. Proc Biol Sci, v. 279, n. 1729, p. 681-9, 2012.
ROSSETTI, D. F. et al. Mid-Late Pleistocene OSL chronology in western Amazonia and implications
for the transcontinental Amazon pathway. Sedimentary Geology, v. 330, p. 1-15, 2015.
SANTORELLI JR., S.; MAGNUSSON, W. E.; DEUS, C. P. Most species are not limited by an
Amazonian river postulated to be a border between endemism areas. Sci Rep, v. 8, p. 2294,
2018.
SHEPHARD, G. E. et al. Miocene drainage reversal of the Amazon River driven by plate–mantle
interaction. Nature Geoscience, v. 3, n. 12, p. 870-875, 2010.
SIMPSON, G. G. Splendid isolation: the curious history of South American Mammals. Yale
University Press, 1980.
SMITH, B. T. et al. The drivers of tropical speciation. Nature, v. 515, n. 7527, p. 406-9, 2014.
SOARES, L. M. S. Sistemática molecular e diversificação dos gêneros Nonnula e Monasa (Aves:
Bucconidae). 2016. (Doutorado em Zoologia). Museu Paraense Emílio Goeldi, UFPA, Belém,
PA.
THOM, G.; ALEIXO, A. Cryptic speciation in the white-shouldered antshrike (Thamnophilus aethiops,
Aves - Thamnophilidae): the tale of a transcontinental radiation across rivers in lowland
Amazonia and the northeastern Atlantic Forest. Mol Phylogenet Evol, v. 82 Pt A, p. 95-110,
2015
110
TOBIAS, J. A. Jacamars (Galbulidae). Handbook of the birds of the world, Barcelona, 2017. Acesso
em: 26 February 2018.
VANZOLINI, P. E.; WILLIANS, E. E. South american anoles: the geographic differentiation and
evolution of the anolis Chrysolepis species group (Sauria, Iguanidae). Arquivos de Zoologia,
v. 19, n. 3-4, p. 125-298, 1970.
WALLACE, A. R. On the monkeys of the Amazon. Alfred Russel Wallace Writings, v. 3, 1852.
Disponível em: < http://digitalcommons.wku.edu/dlps_fac_arw/3 >.
WANG, X. et al. Hydroclimate changes across the Amazon lowlands over the past 45,000 years.
Nature, v. 541, n. 7636, p. 204-207, 2017.
WEIR, J. T. et al. Hybridization in headwater regions, and the role of rivers as drivers of speciation in
Amazonian birds. Evolution, v. 69, n. 7, p. 1823-34, 2015
WILLIS, S. C. One species or four? Yes!...and, no. Or, arbitrary assignment of lineages to species
obscures the diversification processes of Neotropical fishes. Plos One, v. 12, n. 2, p. e0172349,
2017.