Historical biogeography of an Indo-Pacific passerine bird family (Pachycephalidae): different...

ORIGINALARTICLE

Historical biogeography of an Indo-Pacificpasserine bird family (Pachycephalidae):different colonization patterns in theIndonesian and Melanesian archipelagos

Knud A. Jønsson1,2*, Rauri C. K. Bowie2, Robert G. Moyle3, Les Christidis4,5,

Janette A. Norman5,6, Brett W. Benz3 and Jon Fjeldsa1

1Vertebrate Department, Zoological Museum,

University of Copenhagen, Universitetsparken

15, DK-2100 Copenhagen Ø, Denmark,2Museum of Vertebrate Zoology and

Department of Integrative Biology, 3101 Valley

Life Science Building, University of California,

Berkeley, CA 94720-3160, USA, 3Natural

History Museum and Biodiversity Research

Center and Department of Ecology and

Evolutionary Biology, University of Kansas, KS

66045-7561, USA, 4Division of Research and

Collections, Australian Museum, 6 College

Street, Sydney, NSW 2010, Australia,5Department of Genetics, University of

Melbourne, Parkville, Vic. 3052, Australia,6Sciences Department, Museum Victoria, GPO

Box 666, Melbourne, Vic. 3001, Australia

*Correspondence: Knud A. Jønsson, Vertebrate

Department, Zoological Museum, University of

Copenhagen, Universitetsparken 15, DK-2100

Copenhagen Ø, Denmark.

E-mail: [email protected]

ABSTRACT

Aim We use molecular-based phylogenetic methods and ancestral area

reconstructions to examine the systematic relationships and biogeographical

history of the Indo-Pacific passerine bird family Pachycephalidae (whistlers).

Analysed within an explicit spatiotemporal framework, we elucidate distinct

patterns of diversification across the Melanesian and Indonesian archipelagos and

explore whether these results may be explained by regional palaeogeological

events. We further assess the significance of upstream colonization and its role in

species accumulation within the region.

Location The Indo-Pacific region, with an emphasis on the archipelagos on

either side of the Australo-Papuan continent.

Methods We used three nuclear and two mitochondrial markers to construct a

molecular phylogenetic hypothesis of the Pachycephalidae by analysing 35 of the

49 species known to belong to the family. The programs diva and MrBayes were

used to reconstruct ancestral area relationships and to examine biogeographical

relationships across the family, and beast was implemented to assess the timing

of dispersal events.

Results We constructed a molecular phylogenetic hypothesis for the

Pachycephalidae and estimated divergence times and ancestral area relationships.

Different colonization patterns are apparent for the Pachycephalidae in the

Indonesian and the Melanesian archipelagos. The Indonesian archipelago was

colonized numerous times, whereas one or two colonizations of the Melanesian

archipelagos account for the entire diversity of that region. After initial

colonization of the Melanesian archipelagos some whistler species recolonized

Australia and may have commenced a second round of colonization into

Melanesia.

Main conclusions The contrasting dispersal patterns of whistlers in

archipelagos on either side of the Australo-Papuan continent are congruent

with the arrangement and history of islands in each of the regions and

demonstrate that knowledge of palaeogeography is important for an

understanding of evolutionary patterns in archipelagos. We also highlight that

recolonization of continents from islands may be more common than has

previously been assumed.

Keywords

Colonization, dispersal, divergence, Melanesia, Pachycephalidae, Pacific,

Passeriformes, Pleistocene, Pliocene, Wallacea.

Journal of Biogeography (J. Biogeogr.) (2010) 37, 245–257

ª 2009 Blackwell Publishing Ltd www.blackwellpublishing.com/jbi 245doi:10.1111/j.1365-2699.2009.02220.x

INTRODUCTION

Islands have traditionally been regarded as evolutionary dead

ends, where populations that are established through dispersal

from biologically diverse continental biotas rarely contribute

to broader regional species generation via secondary coloni-

zation events beyond the island system (Darwin, 1859;

Wallace, 1876; MacArthur & Wilson, 1963, 1967). Conse-

quently, island biodiversity has been viewed in the context of

dynamic interactions between colonization and extinction,

with the direction and rate of these phenomena influenced by

population size, productivity, vagility, relative species diversity

of source and sink communities, and habitat conditions

(MacArthur & Wilson, 1963, 1967; Diamond, 1977).

Recent advances in the understanding of biodiversity

dynamics in island systems have shed new light on the

interface of these mechanisms (colonization, speciation,

extinction) and the role they may play in shaping patterns of

biodiversity in island environments (reviewed in Whittaker &

Fernandez-Palacios, 2007; Emerson & Gillespie, 2008; Gillespie

et al., 2008). Combined with further novel insight from

detailed molecular-based phylogenies examined within a

geographical framework, evidence of numerous secondary

colonization events (from islands back to the mainland) is now

challenging island biogeography dogma, suggesting that island

systems may in fact be recognized as a potential source for the

build-up of continental biodiversity (Filardi & Moyle, 2005;

Bellemain & Ricklefs, 2008). As such, understanding the

evolutionary histories of island biotas will probably be integral

to interpreting broader regional biogeographical patterns and

processes, and is thus one of the major challenges in modern

macroecology and biogeography (Jetz et al., 2004; Storch et al.,

2006; Fjeldsa et al., 2007; Bellemain & Ricklefs, 2008).

The Indo-Pacific region represents a particularly rich model

system for such work, as knowledge and understanding of the

geological history in this complex region has recently seen

significant advances (Hall, 1998, 2002; Hall & Holloway, 1998)

and few molecular-based studies have investigated distribu-

tions across the entire Indo-Pacific region (except Moyle et al.,

2009). Using molecular, palaeogeological and biogeographical

evidence, we aim to investigate biogeographical patterns and

the timing of diversification in the avian family Pachycepha-

lidae (whistlers), which includes 49 species distributed across

the Indo-Pacific realm (Gill & Wright, 2006). Within this

region, major archipelagos are found on either side of the

Australo-Papuan continent, with mobile oceanic island arcs to

the east and a mosaic of microplates and young volcanics

compressed in Wallacea to the west. The geological history of

each subregion is complex with respect to their composite

origins, each requiring a synoptic timeline of their respective

orogeny to set the geographical stage for analysis of diversi-

fication in the Pachycephalidae.

The present-day centre of pachycephalid diversity lies in

New Guinea’s extensive hill forests (Fig. 1), with a secondary

centre of diversity on the Australian continent (Boles, 2007).

The shared geological history of these regions began in the late

Mesozoic with the collision of the Pacific and Australian plates;

however, initial formation of the New Guinea orogen via

mountain uplift and terrane accretion along the northern

margin of the Australian continental shelf is thought to have

begun more recently in the late Oligocene (Hamilton, 1979;

Audley-Charles, 1991; Pigram & Symonds, 1991). Consider-

able uncertainty surrounds the timing of accretion history as

well as the rates of subsequent uplift across the 32 distinct

terranes that comprise the New Guinea orogen; however, a

general consensus drawing on diverse lines of evidence suggests

that the salient topographic features of the extensive central

dividing ranges and the Papuan peninsula were in place by the

Pliocene. Accreted North Coast terranes of oceanic affinity as

well as the Australian continental fragments that form New

Guinea’s Birds Head region may have completed docking more

recently, in the late Pliocene (Audley-Charles, 1991; Pigram &

Symonds, 1991; Hall, 1998, 2002).

To the east of the Australo-Papuan continent, the Melane-

sian arcs comprising the Solomons, New Britain, New Ireland,

Tonga and Fiji are thought to have rifted from the eastern

Figure 1 Worldmap representation of the

present distribution of members of the

Pachycephalidae. Each 1� square represents

110 km · 110 km at the equator. The

maximum number of species in a square

(warmest colour) is 13.

K. A. Jønsson et al.

246 Journal of Biogeography 37, 245–257ª 2009 Blackwell Publishing Ltd

Australian margin in the mid-Palaeogene, migrating north-east

into the Pacific before progressing back towards the Australian

margin; however, an alternative hypothesis suggests that these

arcs may have originated within the Pacific and subsequently

migrated to their present position (Yan & Kroenke, 1993; Hall,

2002). Regardless, their present-day close proximity to New

Guinea appears to be a gradual development initiated in the

mid-Miocene.

By comparison, the geological history of the Indonesian

archipelago and surrounding island systems to the north and

west of New Guinea’s Birds Head region is considerably more

complex, with a mixture of old and young terranes juxtaposed

in close proximity (Hall, 1998, 2002). The Philippine–Izu–

Bonin archipelago extends south to the Molucca Sea, where

ophiolitic terranes of the Halmahera Arc meet Gondwanan

continental fragments from the Australian Craton along the

Seram Trough, collectively forming the Moluccas. The Sangihe

Arc lies to the west of the Molucca Sea, and although its

collision with the Halmahera Arc initiated in the late Pliocene,

the Sangihe volcanics probably date to the mid-Miocene given

their affinity with north Sulawesi (Hall, 2002). Reconstructing

the evolutionary history of the Banda Sea region is problematic

owing to the diversity of the terranes present and the

potentially large and recent displacements involved (Hall,

2002). The Lesser Sunda Islands were formed by the emergence

of the Banda arc, which consists of an inner volcanic arc

(Wetar west to Bali) that has been active since the Miocene,

and an outer non-volcanic arc (Sumba, Timor and Tanimbar)

that has formed more recently in the Quaternary (Hall, 1998,

2002). Although improved isotopic, palaeomagnetic and GPS

tectonic data have enabled more rigorous plate tectonic models

in recent years, thus providing a clearer understanding of the

geographical history across the Indo-Pacific region, the

spatiotemporal uncertainty inherent in these data warrants

caution in applying such information to explicitly dated

biogeographical analyses.

Herein, we investigate the phylogenetic relationships of the

Pachycephalidae, examining the patterns and timing of

whistler diversification across the Indo-Pacific to: (1) shed

light on the phylogenetic relationships and general biogeo-

graphical patterns within the Pachycephalidae, (2) test whether

branching patterns and timing of major radiations coincide

with regional palaeogeographical histories, and (3) examine

the role of dispersal in lineage accumulation between the

distinctive Indonesian and Melanesian archipelagos and the

Australo-Papuan continent, in order to highlight potential

colonization events and assess how this phenomenon may have

affected the evolutionary history of the Pachycephalidae.

MATERIALS AND METHODS

Taxon sampling

Recent molecular studies have revealed that several species

historically assigned to the Pachycephalidae represent inde-

pendent lineages outside of the family, or belong to other bird

families altogether. Aleadryas rufinucha, Oreoica gutturalis and

Pitohui cristatus form a small assemblage outside of, but still

somewhat close to, the Pachycephalidae (Jønsson et al., 2008b;

Norman et al., 2009). Hylocitrea bonensis was surprisingly

found to be within a different parvorder (Jønsson et al., 2008a)

and is now robustly placed within the Bombycillidae (Spellman

et al., 2008). Rhagologus leucostigma, Pachycare flavogrisea and

Eulacstoma nigropectus are also known to not be closely related

to the Pachycephalidae but rather form part of the broader

radiation of corvoids (Jønsson et al., 2008b; Norman et al.,

2009, in press). Thus, the circumscription of the Pachyceph-

alidae needs to be redefined in order to properly infer

biogeographical patterns.

Based on our current knowledge, the avian family Pachy-

cephalidae encompasses all taxa assigned to the genera

Pachycephala and Colluricincla as well as Pitohui ferrugineus,

Pitohui nigrescens and the monotypic Coracornis raveni. With

this circumscription in mind, our sampling includes 35 of the

49 species (Table 1) known to belong to the family (Gill &

Wright, 2006). The lack of complete sampling reflects the

absence of modern ornithological field expeditions for much of

this region. As such, DNA extraction from museum study

skins was performed for 15 key taxa to help remedy this

sampling deficiency.

Although lacking genetic samples from nearly 30% of the taxa

in the family may appear to severely limit the biogeographical

conclusions that can be drawn, our sampling includes represen-

tatives of all major species groups identified in previous

taxonomic studies from all major biogeographical regions within

the family’s range. Three species (Pachycephala fulvotincta,

Pachycephala mentalis and Pachycephala graeffii) have previously

been considered subspecies of the Pachycephala pectoralis com-

plex(Galbraith,1956),whichcomprises66namedtaxa.Although

this complex appears to represent a species group rather than a

single species, the uniformity in morphological characters and

ecology give reason to believe that they all are relatively closely

related. Six additional species that we lack have restricted

distributions in New Guinea (Pachycephala aurea, Pachycephala

monacha, Pachycephala meyeri and Colluricincla umbrina), the

Philippines (Pachycephala homeyeri, which is considered closely

related to other Philippine species) and Australia (Pachycephala

rufogularis, which is probably closely related to Pachycephala

inornata). Although we lack Pachycephala johni, several checklists

(e.g. Dickinson, 2003) consider this taxon to be a subspecies of

Pachycephala griseonota. The remaining three missing taxa are

Pachycephala flavifrons of Samoa, Pachycephala jacquinoti of

Tonga and Pachycephala implicata of the Solomon Islands, which

are often considered to be part of a superspecies complex that

includes other Pacific whistlers and these taxa are sometimes

treated as subspecies of Pachycephala pectoralis (Boles, 2007).

Laboratory procedures

Three nuclear gene regions – myoglobin intron-2 (Myo2),

ornithine decarboxylase (ODC) introns 6 to 7, and glyceral-

dehyde-3-phosphodehydrogenase (GAPDH) intron-11 – and

Phylogeny and biogeography of the Pachycephalidae

Journal of Biogeography 37, 245–257 247ª 2009 Blackwell Publishing Ltd

two mitochondrial markers – NADH dehydrogenase subunit

2 (ND2) and subunit 3 (ND3) – were sequenced to

estimate phylogenetic relationships among members of the

Pachycephalidae. For each gene and taxon, multiple sequence

fragments were obtained by sequencing with various primer

combinations (see below).

Table 1 Taxonomic sampling of the Pachycephalidae. AMNH, American Museum of Natural History, USA; AM, Australian Museum,

Sydney, Australia; ANWC, Australian National Wildlife Collection, Canberra, Australia; FMNH, Field Museum of Natural History, Chicago,

USA; MCSNC, Museo Civico di Storia Naturale di Carmagnola, Italy; MVZ, Museum of Vertebrate Zoology, UC-Berkeley, USA; MV,

Museum Victoria, Melbourne, Australia; NRM, Swedish Museum of Natural History, Stockholm, Sweden; KU, University of Kansas, USA;

WAM, Western Australian Museum, Perth, Australia; ZMUC, Zoological Museum of Copenhagen, Denmark. All samples are vouchered

except three species indicated with an asterisk.

Taxon name Voucher Origin GAPDH ODC Myo2 ND2 ND3

Colluricincla boweri MVZ181452 Australia GQ494042 GQ494056 GQ494075 GQ494103 GQ494137

Colluricincla ferrugineus MV E506 New Guinea EU273391 EU273372 EU273413 GQ494089 GQ494123

Colluricincla harmonica MV1422 Australia EU273376 EU273356 EU273396 GQ494091 GQ494125

Colluricincla megarhyncha ANWC39343 Australia EU273377 EU273357 EU273397 GQ494092 GQ494126

Colluricincla megarhyncha ANWC26500 New Guinea GQ494038 GQ494050 GQ494067 GQ494093 GQ494127

Colluricincla woodwardi MV D592 Australia GQ494039 GQ494051 GQ494068 GQ494094 GQ494128

Coracornis raveni NRM569472 Sulawesi EU380472 EU380434 EU380503 GQ494106 GQ494141

Coracornis sanghirensis* ZMUC123921 Sangihe Island EF441213 EF441235 EF441256 GQ494110 GQ494145

Melanorectes nigrescens ANWC26846 New Guinea EU273393 EU273373 EU273415 GQ494090 GQ494124

Pachycephala albiventris ZMUC117176 Philippines EF441223 EF441245 EF441259 GQ494108 GQ494143

Pachycephala arctitorquis WAM25087 Tanimbar GQ494045 GQ494059 GQ494078 GQ494111 GQ494147

Pachycephala caledonica FMNH268487 New Caledonia GQ494040 GQ494052 GQ494069 GQ494095 GQ494129

Pachycephala cinerea plateni WAM12751 Palawan GQ494046 GQ494060 GQ494079 GQ494112 GQ494148

Pachycephala citreogaster ZM95289 New Ireland EU599250 EU599264 EU600802 EU600819

Pachycephala griseiceps ZMUC26820 Kai Islands GQ494055 GQ494074 GQ494101

Pachycephala griseiceps ZMUC26822 Kai Islands GQ494135

Pachycephala griseonota ZMUC26823 Kai Islands GQ494102 GQ494136

Pachycephala hyperythra FMNH280631 New Guinea GQ494073 GQ494099 GQ494133

Pachycephala hypoxantha AMNH648529 Borneo GQ494044 GQ494058 GQ494077 GQ494105 GQ494139

Pachycephala inornata ANWC38742 Australia GQ494036 GQ494048 GQ494063 GQ494081 GQ494115

Pachycephala lanioides ANWC 29493 Australia GQ494035 GQ494062 GQ494114

Pachycephala lorentzi FMNH280615 New Guinea GQ494054 GQ494071 GQ494097 GQ494131

Pachycephala macrorhynca fuscoflava WAM25185 Tanimbar EU599256 EU599272 EU600828 EU600810

Pachycephala melanura MV1248 Australia EU273383 EU273364 EU273405 EU600811 EU600794

Pachycephala modesta FMNH280637 New Guinea GQ494041 GQ494053 GQ494070 GQ494096 GQ494130

Pachycephala nudigula WAM22678 Flores GQ494047 GQ494061 GQ494080 GQ494113 GQ494149

Pachycephala olivacea MV1826 Australia EU273384 EU273365 EU273406 GQ494082 GQ494116

Pachycephala orioloides ZM139478 Solomon Islands EU599246 EU599260 EU600815 EU600798

Pachycephala ornate EBU13394 Vanuatu GQ494043 GQ494057 GQ494076 GQ494104 GQ494138

Pachycephala pectoralis fuliginosa MV2658 Western Australia EU599244 EU599258 EU600812 EU600795

Pachycephala pectoralis youngi MV3477 Victoria, Australia EU273385 EU273366 EU273407 EU600813 EU600796

Pachycephala phaionota FMNH280634 Kai Islands GQ494072 GQ494098 GQ494132

Pachycephala philippinensis* ZMUC117169 Philippines EU380480 EU380444 EU380509 GQ494109 GQ494144

Pachycephala rufiventris MV4205 Australia GQ494049 GQ494064 GQ494083 GQ494117

Pachycephala rufiventris NRM543657 Australia EU380481

Pachycephala schlegelii ANWC24574 New Guinea EU273386 EU273367 EU273408 GQ494084 GQ494118

Pachycephala simplex ANWC27005 New Guinea EU273387 EU273368 EU273409 GQ494085 GQ494119

Pachycephala simplex MV1183 Australia EU599245 EU599259 GQ494065 EU600814 EU600797

Pachycephala soror ANWC26736 New Guinea GQ494037 GQ494066 GQ494086 GQ494120

Pachycephala soror* ZMUC135468 New Guinea EU380447

Pachycephala sulfuriventer NRM569473 Sulawesi EU380484 EU380448 EU380513 GQ494140

Pachycephala tenebrosa NRM569469 Palau EU380414 EU380490 GQ494107 GQ494142

Outgroup

Oriolus oriolus ZMUC138401 Denmark GQ494146

Oriolus oriolus MCSNC1415 Italy EF052755 EU273363 EF052766 EF052693

Ornorectes cristatus ANWC26733 New Guinea EU273389 EU273370 EU273411 GQ494087 GQ494121

Pitohui dichrous ANWC27042 New Guinea EU273390 EU273371 EU273412 GQ494088 GQ494122

Pitohui kirhocephalus FMNH280697 New Guinea EU273392 EU273414 GQ494100 GQ494134



Primer pairs used for amplification were: Lmet (Hackett,

1996)/H6312 (Cicero & Johnson, 2001) for ND2; ND3-

L10755/ND3-H11151 (Chesser, 1999) for ND3; Myo2 (Slade

et al., 1993)/Myo-cora2R (Jønsson et al., 2008a) and Myo-

coraF1 (Jønsson et al., 2008a)/Myo3F (Heslewood et al., 1998)

for Myo2; OD6/OD8 (Allen & Omland, 2003) for ODC; and

G3P13/G3P14b (Fjeldsa et al., 2003) for GAPDH.

Thermocycling conditions included a hot start at 95 �C, an

initial denaturation step at 95 �C for 5 min, followed by 32

cycles at 95 �C for 40 s, 54–63 �C for 40 s, and 72 �C for 60 s

and completion by a final extension at 72 �C for 8 min. One

microlitre of polymerase chain reaction (PCR) products was

electrophoresed on a 1.5% agarose gel and visualized under

UV light with ethidium bromide to check for correct fragment

size and to control for the specificity of the amplifications. The

PCR products were purified using ExoSap enzymes (exonu-

clease and shrimp alkaline phosphatase). Purified PCR prod-

ucts were cycle-sequenced using Big Dye terminator chemistry

(ABI; Applied Biosystems, Foster City, CA, USA) in both

directions with the same primers used for PCR amplifications,

with the exception of the primer G3P13 which was replaced by

G3PintL1 (Fjeldsa et al., 2003), and run on an automated ABI

3730 DNA sequencer. Corresponding laboratory procedures

for the sequencing of ancient DNA from study skins are

detailed in Irestedt et al. (2006). Additional internal primers

for tissues taken from museum skins are specified in Jønsson

et al. (2008a) (for Myo2 and GAPDH), Jønsson et al. (2008c)

(for ND2) and in Irestedt et al. (2006) (for ODC). Sequences

were assembled with SeqMan II (DNASTAR Inc., Madison,

WI, USA). Nucleotides that could not be determined with

certainty (mostly heterozygous sites in nuclear loci) were

coded with the appropriate IUPAC code. GenBank accession

numbers are provided in Table 1.

Sequence alignment and phylogenetic analyses

Sequences were aligned using MegAlign (DNASTAR Inc.)

followed by a few manual adjustments. Coding genes (ND2

and ND3) were checked for the presence of stop codons or

insertion/deletion events that would have disrupted the

reading frame. All alignments are available from the first

author upon request. We used Bayesian inference (BI) (e.g.

Holder & Lewis, 2003; Huelsenbeck & Ronquist, 2003), as

implemented in MrBayes 3.1.2 (Huelsenbeck et al., 2001;

Ronquist & Huelsenbeck, 2003), to estimate phylogenetic

relationships. Substitution models were determined with

MrModeltest 2.0 (Nylander, 2004), using the Akaike

information criterion (AIC) (Akaike, 1973; Posada & Buckley,

2004). Model parameters were permitted to vary between the

seven partitions [GAPDH, ODC, Myo2, first, second and

third mitochondrial DNA (mtDNA) codon positions and

transfer RNA (tRNA)] in the mixed-model Bayesian analyses

(Ronquist & Huelsenbeck, 2003; Nylander, 2004). In all

MrBayes analyses, four Metropolis-coupled Markov chain

Monte Carlo (MCMC) simulations, one cold and three

heated, were run for 5–15 million iterations with trees

sampled every 1000 iterations. The burn-in was graphically

estimated using awty (Wilgenbusch et al., 2004; Nylander

et al., 2008) and this program was also used to graphically

assess whether the MCMC analysis had run for long enough,

such that tree topologies were being sampled in proportion

to their true posterior probability distribution. Two inde-

pendent Bayesian runs initiated from random starting trees

were performed for each data set, and the log-likelihood

values and posterior probabilities of nodes from each run

were compared to aid in assessing stationarity.

Maximum likelihood (ML) analyses were performed using

garli 0.95 (Zwickl, 2006). Five independent analyses (15 mil-

lion generations for the combined analysis and 5 million

generations for the individual partitions) were performed and

nodal support was evaluated with 100 nonparametric boot-

strap pseudoreplications.

Dating analyses

Establishing a general timeframe for evolution of a group can

allow one to reject hypotheses about factors that influenced

the process of diversification. Unfortunately, the fossil record

provides no calibration points within or close to the

Pachycephalidae, so we used two alternative approaches to

estimate divergence times in the group. First, we assigned

island ages in the region to nodes on the phylogeny and then

used those calibrated nodes to estimate the ages of other

nodes. Second, we applied to our data an ND2 divergence

rate calculated for another group of island-dwelling passe-

rines. Each of these methods includes numerous caveats and

assumptions (see below), but our interest was in seeing if two

independent methods returned similar results, thus providing

some degree of support for the general timeframe of

diversification.

The following geological events are relevant as calibration

points for the dating analysis. Islands in the Sangihe Arc were

formed by volcanism beginning in the early Miocene (Hall,

2002). However, it is only at the southern end of the arc, in the

north arm of Sulawesi, and at the north end of the arc, in

Mindanao, that this has led to the formation of a substantial

subaerial landmass. The intervening section has remained

submerged or has been intermittently emergent for the last

20 million years (Myr). For Sangihe Island, an emergence age

of the order of 2–3 Myr is likely to be realistic (Jezek et al.,

1981; Morrice et al., 1983). Tanimbar has been subaerial for a

shorter time, as this low island (< 300 m) is covered with early

Pleistocene marine deposits, which indicate that it may have

risen above sea level only within the last 1 Myr. Furthermore,

Quaternary reefs occur up to 200 m a.s.l., also supporting a

recent period of rapid emergence (de Smet et al., 1989;

Charlton et al., 1991).

We used the age of Sangihe Island north of Sulawesi to date

the split between Coracornis raveni and Coracornis sanghirensis

at 2.5 ± 0.5 million years ago (Ma) and the age of Tanimbar

to date the split between Pachycephala macrorhynca and

Pachycephala pectoralis/melanura at 0.8 ± 0.2 Ma.



A concern when using island ages to infer ages of speciation

events is that one must have accounted for all taxa in the

region and all possible land areas in the region. If some taxa are

not sampled, the island age might be applied to the incorrect

node because the appropriate one does not exist in the

phylogeny. Likewise, the colonization source must be unam-

biguous, which is complicated by the possibility of recently

submerged islands in dynamic regions such as the Indonesian

archipelago. This is a problem of missing islands rather than

missing taxa, and is impossible to remedy. We did not satisfy

either of these conditions, and so to further corroborate the

island divergence dates we applied to our data a rate of 0.028

substitutions per site per lineage per Myr for ND2 (corrected

pairwise distances), which is derived from Galapagos mock-

ingbirds (Drovetski et al., 2004). This divergence rate yields

ages similar to the above-mentioned nodes: 2.9 Ma for the

Coracornis raveni/sanghirensis split and 0.8 Ma for the Pachy-

cephala macrorhynca/pectoralis split.

We used beast version 1.4.6 (Drummond et al., 2002, 2006;

Drummond & Rambaut, 2007) to estimate divergence times

within the Pachycephalidae. We assigned the best fitting

model, as estimated by MrModeltest 2.0 (Nylander, 2004) to

each of the partitions. We ran three separate analyses using one

or both calibration points and found that the main effect of

using only one calibration point is to enlarge the 95% highest

posterior density (HPD) interval either distally or basally. We

assumed a Yule speciation process for the tree prior and an

uncorrelated lognormal distribution for the molecular clock

model (Ho, 2007). We used default prior distributions for all

other parameters and ran MCMC chains for 50 million

generations.

Establishing ancestral areas

Ancestral areas of clades were estimated with dispersal–

vicariance analysis (Ronquist, 1997) using the computer

program diva version 1.1 (Ronquist, 1996). Five geographical

regions were recognized: A, Australia/New Guinea; B, Philip-

pines; C, Wallacea; D, the Pacific; E, Asia (the area west of

Huxley’s modification of Wallace’s Line); and F, Palau.

Maxarea values were set to 2 (assuming that the ancestral

members of the extant Pachycephalidae radiation had the same

ability to disperse), and the analysis was carried out several

times to explore the effect of changing the cost settings (co-

divergence = 0–5, duplication = 0–5, sorting = 0–5, switch-

ing = 0–5). None of these changes altered the outcome of the

analysis, suggesting a robust result.

In addition, ancestral distributions were reconstructed by

performing a series of separate constrained BI analyses

(Huelsenbeck & Bollback, 2001; Ronquist, 2004) for each

node on the 50% majority-rule consensus tree derived from

analysis of the full five gene dataset. To do this we included the

distribution data as a separate partition and assumed the

evolutionary rate to be proportional to that of the other data;

other models and settings were the same as for the phylo-

genetic analyses.

RESULTS

Alignment and phylogenetic analyses

The concatenated alignment consisted of 3069 bp (660 parsi-

mony-informative sites). Amplification of DNA extracted from

museum study skins was not successful for all loci. Thus partial

or whole sequence fragments are missing for some taxa. The

total GAPDH alignment was 317 bp (30 parsimony-informa-

tive sites). We sequenced between 266 and 300 bp from fresh

samples, and from skin samples managed to obtain 197 bp for

Pitohui kirhocephalus, 210 bp for Pachycephala modesta,

178 bp for Colluricincla boweri and 189 bp for Pachycephala

hypoxantha. The total alignment of ODC intron 6 and 7 was

609 bp (43 parsimony-informative sites). We obtained

between 540 and 607 bp from fresh samples and obtained

ODC intron-6 sequences (249 bp) from skin samples of

Pachycephala modesta, Pachycephala lorentzi and Pachycephala

griseiceps. The total alignment of Myo2 was 707 bp (31

parsimony-informative sites). We sequenced between 674 and

707 bp from fresh samples, and from the museum study skins

obtained 499 bp from Pachycephala phaionota and 379 bp from

Colluricincla boweri. The ND2 alignment was 1041 bp (411

parsimony-informative sites). We obtained between 844 and

1041 bp from fresh samples and from skin samples we obtained

549 bp for Pachycephala griseonota, 567 bp for Colluricincla

tenebrosa, 580 bp for Pachycephala phaionota, 790 bp for

Pachycephala hypoxantha and 796 bp for Pachycephala lorentzi.

For ND3 and flanking tRNAs we sequenced 395 bp (145

parsimony-informative sites). However, we only obtained

318 bp for Colluricincla tenebrosa, 367 bp for Pachycephala

schlegelii and 391 bp for Pachycephala sulfuriventer.

Analyses performed on the concatenated data set (seven

partitions: GAPDH, ODC, Myo2, first, second and third

mtDNA codon positions and tRNA ML: )ln = 19,835.74, BI

harmonic mean )ln = 18,829.30) (Fig. 2) and on the individ-

ual partitions (GAPDH: AIC: GTR+C, ML: )ln = )1049.00, BI

harmonic mean )ln = 1191.85; ODC: AIC: HKY+C, ML:

)ln = )1943.28, BI harmonic mean )ln = 2166.67; Myo2:

AIC: K80+I, ML: )ln = )1740.65, BI harmonic mean

)ln = 1941.36; ND2: AIC: GTR+I+C, ML: )ln = )10075.14,

BI harmonic mean )ln = 9808.10; ND3: AIC: GTR+I+C, ML:

)ln = –3519.44, BI harmonic mean )ln = )3466.35) (see

Appendices S1–S5 in Supporting Information) yielded 50%

majority-rule consensus trees that were topologically congru-

ent for well-supported nodes (posterior probability > 0.95 and

bootstrap values > 70). Although the nuclear gene trees

(GAPDH, ODC and Myo2) contained few well-supported

clades, they did provide support for the partition between the

two main genera, Pachycephala and Colluricincla. The mito-

chondrial gene trees were more resolved, and as expected for

linked markers were congruent for well-supported nodes. The

only difference was within the basal part of Pachycephala,

where some discrepancies occurred. The differences are

supported only by Bayesian posterior probabilities in the

ND3 topology; likelihood bootstrap resampling supported



none of the discrepancies. This is probably the result of the

small size of the ND3 gene (351 bp) and relatively few

informative sites relative to the ND2 gene (1041 bp). Scores of

the best likelihood trees were within 0.05 likelihood units of

the best tree recovered in each of the other four garli runs,

suggesting that the five runs had converged. With the

individual data sets combined, the ML tree topology was

almost completely congruent with the BI topology.

The 14 species not included in the study could potentially

come out anywhere in the phylogeny, but as discussed above

we have broad geographical and taxonomic sampling. As a

result it is unlikely to alter the main biogeographical patterns

recovered, i.e. many dispersal events into the Indonesian

archipelago and few into the Melanesian archipelago. To the

east, however, it is possible that we have underestimated the

complexity of the pattern, and it is conceivable that multiple

dispersal events took place from New Guinea into the Pacific.

Dating analyses

Results from the beast dating analyses (Fig. 3) place the origin

of the Pachycephalidae assemblage in the early Pliocene, and

the origin of the genus Pachycephala was estimated to date

back to the late Pliocene. Wide confidence intervals on all of

Figure 2 The 50% majority-rule consensus tree of the Pachycephalidae obtained from the Bayesian analysis of the combined dataset

(GAPDH, ODC, Myo2, ND2 and ND3). Above the branch is the posterior probability (only values above 0.90 are shown, asterisks indicate

1.00 posterior probabilities). Below the branch is the maximum likelihood bootstrap value (only values above 70% are shown) from 100

pseudoreplicates. Letters at nodes indicate putative ancestral areas: A, Australia/New Guinea; B, the Philippines; C, Wallacea; D, Pacific;

E, Asia (including Palawan); F, Palau. To the left of the nodes is first indicated the ancestral area, according to the Bayesian ancestral area

reconstruction (either indicated as a large letter, which indicates an ancestral area probability ‡ 0.99, or as a two or three small letters

indicating ancestral area probability fractions). Following the Bayesian ancestral areas are the ancestral areas recovered from the diva

analysis. Letters to the right of the taxon names indicate present distributions and thus coding for the ancestral area analyses. An asterisk

in front of a taxon name indicates a change of genus name according to the discussion. The inset map indicates the regions demarcated

for the ancestral area analyses.



the age estimates allow only general biogeographical conclu-

sions. However, it is fairly clear that much of the diversity in

the genus was generated recently, probably in the Pleistocene,

and coincided with multiple dispersal events out of the

Australo-Papuan region.

Ancestral areas

Both progams (diva and MrBayes) identified Australia/New

Guinea as the ancestral area of the Pachycephalidae (Fig. 2).

Ancestral areas of many distal nodes of the tree were more

equivocal. However, both methods identified the Pacific as the

origin of the ‘pectoralis complex’. This has implications for the

biogeographical interpretation because the most distal taxa

within this clade are found in mainland Australia, which

indicates a probable upstream colonization event, from the

Pacific archipelagos to the mainland, within this assemblage.

DISCUSSION

Taxonomy

The phylogenetic results presented herein are in accord with

other recent molecular systematic studies (Dumbacher et al.,

2008; Jønsson et al., 2008b; Norman et al., 2009), demonstrat-

ing that Pitohui, Colluricincla and Pachycephala, as currently

circumscribed (e.g. Dickinson, 2003), are not monophyletic

assemblages. Based on these studies we recommend the

following taxonomic changes: (1) Pitohui ferrugineus and

Pitohui incertus (based on Dumbacher et al., 2008) should be

Figure 3 Chronogram based on the beast analysis of the Pachycephalidae. We used the age of Sangihe Island north of Sulawesi to date

the split between Coracornis raveni and Coracornis sanghirensis at 2.5 ± 0.5 Ma and the age of Tanimbar to date the split between

Pachycephala macrorhynca and Pachycephala orioloides at 0.8 ± 0.2 Ma. These dates were further corroborated by using a rate for ND2

of 0.028 substitutions per site per lineage Myr)1. Error bars indicate 95% highest posterior density (HPD) intervals. Letters to the right of

the taxon names indicate present distributions: A, Australia/New Guinea; B, the Philippines; C, Wallacea; D, Pacific; E, Asia (including

Palawan).



included in Colluricincla; (2) Colluricincla sanghirensis and

Coracornis raveni are sister taxa and as C. sanghirensis is not

part of Colluricincla, but is instead more closely related to

Coracornis, we recommend its placement in this genus; (3) the

highly divergent Pitohui nigrescens should be separated gener-

ically, with the available name Melanorectes Sharpe, 1877

applied; (4) Pitohui cristatus has recently been separated into

Ornorectes Iredale, 1956 (Norman et al., 2009); as a conse-

quence, the only remaining members of Pitohui are P. kirho-

cephalus and Pitohui dichrous, for which the former is the type

species; and (5) Colluricincla tenebrosa from Palau should be

placed into Pachycephala (also suggested by Norman et al.,

2009).

Origins and biogeography

Although modern molecular-based biogeographical studies on

mammals (e.g. Steppan et al., 2003; Heaney et al., 2005; Jansa

et al., 2006), amphibians (e.g. Evans et al., 2003) and birds

(e.g. Filardi & Moyle, 2005; Cibois et al., 2007; Irestedt et al.,

2008; Outlaw & Voelker, 2008) have been carried out in

subregions within the Indo-Pacific, only one study (also a

family of passerine birds by Moyle et al., 2009) has investigated

biogeographical patterns of terrestrial vertebrates across the

entire Indo-Pacific region. As such, the present study provides

an important contribution towards a better understanding of

biogeographical patterns and processes that have shaped this

diverse region.

Based on the results of our ancestral area analyses and

patterns of present-day pachycephalid species richness, the

family clearly arose within the Australo-Papuan region

(Fig. 2). Although the presence of several New Guinea humid

forest species at the base of the phylogeny suggests a Papuan

origin of the family, it is important to note that much of

Australia’s humid forest diversity has been lost as a conse-

quence of aridification beginning in the mid-Miocene. The

distribution and branching patterns within Colluricincla are

equivocal with respect to clarifying the origins of the genus,

whereas the basal placement of Pachycephala inornata and

Pachycephala olivacea indicate a possible Australian origin of

Pachycephala, before the genus diversified within and from

New Guinea. Repeated Quaternary interchange between these

landmasses has been facilitated by the New Guinea–Australia

land bridge, present during periods of climate-mediated sea

fluctuations, which have differed by as much as 120 m

(Bintanja et al., 2005). This connectivity is reflected in the

broad shared distribution of several pachycephalid taxa as well

as close sister relationships between taxa in these regions.

Several processes have traditionally been proposed to

explain New Guinea’s high avian diversity. Striking patterns

of elevational replacement along the central cordillera and

outlying ranges involving abrupt elevational transitions

between species led Diamond (1972) to identify ‘montane

speciation’ as one of the most important mechanisms

promoting diversification in the New Guinean avifauna. At

lower elevations (< 1800 m a.s.l.), where habitat complexity is

at its greatest (Paijmans, 1976; Coates, 1985), high levels of

niche partitioning involving fine-scale differences in habitat

preference, vertical zonation within the forest stratum and/or

feeding ecology have also been identified in speciation

processes across the island (Diamond, 1972; Coates, 1985,

1990). New Guinea’s whistler diversity is principally composed

of lowland endemics and mid-elevation generalists, with

relatively few species present in the highlands (2000 m a.s.l.

and above). Given that the New Guinea highlands had largely

taken shape by the Pliocene, significantly pre-dating the

majority of Pachycephala diversification, more recent climatic

factors may have played a role in diversification of the genus.

Pleistocene glacial cycles have significantly impacted climate

and habitat change in New Guinea and adjacent regions. This

includes local aridification in southern lowland areas and

increased rainfall in montane areas, with significant cooling at

higher elevations (McAlpine et al., 1983). Pleistocene fluctu-

ations caused vegetational zones to be lowered and com-

pressed, with a corresponding increase in the area of montane

grasslands and lowland savanna (Hope et al., 2004). The

timing of these phenomena coincides with the major radiation

of the forest-associated Pachycephala species according to our

time estimates (Fig. 3). The genus Colluricincla, which is

adapted to drier, more open habitats, does not show the same

rapid radiation as observed for the forest-adapted taxa.

Timing and patterns of diversification

The distribution of the family provides a unique opportunity

to compare dispersal patterns in two archipelagos that display

distinctly different geological histories and distributions of

current land area west and east of the presumed area of origin

in New Guinea. Members of Pachycephalidae colonized the

Indonesian archipelago at least seven times (Fig. 4). All of

these species (with the exception of the widespread Pachycep-

hala cinerea) are restricted to one or a few adjacent islands and

several are restricted to highland primary forest. The close

proximity of islands throughout the Indonesian archipelago

(since the Miocene–Pliocene transition when the Lesser Sunda

Islands developed; Hall, 2002) seems to present easily acces-

sible stepping-stones for colonization throughout the Pliocene

and Pleistocene.

The phylogenetic results present a very different scenario for

dispersal into the Pacific (Fig. 4). Our study suggests one or two

independent dispersal events. One species colonized New

Caledonia in the late Pliocene and another lineage colonized

the entire Melanesian arc (including the Bismarcks, the

Solomons and Vanuatu) during the Pleistocene, before back-

colonizing mainland Australia. Island arcs are well known as

dispersal corridors (Polhemus, 1996; Irestedt et al., 2008) and

their importance for dispersal and diversification is supported

by these results. The Pacific ‘pectoralis’ complex probably

colonized the Melanesian arc as this chain of islands drifted

westwards towards New Guinea in the Pliocene. The colonizing

population then rapidly dispersed throughout the chain of

islands from New Guinea via the Bismarcks, and the Solomons



to Vanuatu. Sparse taxon sampling, short internodes and lack of

branch support limit inferences about the exact sequence of

colonization, but underscore the rapid diversification. Reverse,

or ‘upstream’, colonization events have recently received

renewed attention (Filardi & Moyle, 2005; Bellemain & Ricklefs,

2008) and here we document another case of this hitherto

largely overlooked phenomenon. Jønsson et al. (2008c) recently

showed that Pachycephala melanura has colonized small islands

in the immediate vicinity of larger islands that hold populations

of P. pectoralis. This pattern extends as far east as the eastern

Bismarck archipelago. At the time it was not possible to

determine the origin of the clade. The present data set raises the

possibility that the lineage that back-colonized Australia

commenced a new round of colonization into the Bismarck

archipelago, exemplified by P. melanura.

Our study demonstrates that the dispersal and diversifica-

tion of a lineage in an archipelago can vary significantly

according to the tectonic history of the area. The Indonesian

and Melanesian radiations discussed here are closely related

and are thus expected to have similar dispersal potentials. Yet

the diversification process proceeded differently in the two

areas. Thus, our study emphasizes the importance of integrat-

ing knowledge of palaeogeology and plate tectonics for a given

region with modern phylogenetic and molecular clock dating

methods in order to appropriately describe and interpret

biogeographical patterns. Our findings also underscore the fact

that islands may be very important in the speciation and

diversification process and in shaping continental biotas,

contrary to traditional biogeographical paradigms.

ACKNOWLEDGEMENTS

We thank the following institutions for kindly providing access

to fresh tissue and/or toe-pads: American Museum of Natural

History, USA; Australian Museum, Sydney, Australia; Austra-

lian National Wildlife Collection, Canberra, Australia; Field

Museum of Natural History, Chicago, USA; Museo Civico di

Storia Naturale di Carmagnola, Italy; Museum of Vertebrate

Zoology, UC-Berkeley, USA; Museum Victoria, Melbourne,

Australia; Swedish Museum of Natural History, Stockholm,

Sweden; University of Kansas, USA; Western Australian

Museum, Perth, Australia; and the Zoological Museum of

Figure 4 Map indicating the dispersal and colonization routes of members of the Pachycephalidae in the Indonesian/Philippine archi-

pelago to the west of New Guinea and the Melanesian Archipelago to the east. Solid red lines indicate dispersal into the Pacific (note,

however, that support values are low for these relationships). Solid green lines indicate dispersal into Wallacea and beyond. The solid blue

line indicates dispersal to the Philippines. Solid black lines indicate dispersal within the Australo-Papuan region. Dotted lines indicate

putative dispersal routes (purple, the colonization of Palau from either New Guinea or the Philippines; red, the colonization of New

Caledonia either by long-distance ocean dispersal or via the Melanesian arc). Each terminal arrow indicates one colonization event of one

species. Yellow dotted lines indicate the boundaries of Wallacea; Wallace’s Line to the west and Lydekker’s Line to the east.



Copenhagen, Denmark. K.A.J. would also like to acknowledge

the support from the Australian Museum Postgraduate Awards

2006–07. We would also like to thank Jim Patton and Craig

Moritz for valuable comments on earlier drafts. Finally, we

thank two anonymous referees and the editor, Lawrence

Heaney, for constructive criticism that helped improve the

manuscript markedly.

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SUPPORTING INFORMATION

Additional Supporting Information may be found in the

online version of this article:

Appendix S1 The 50% majority-rule consensus tree

obtained from the Bayesian analysis of GAPDH.


obtained from the Bayesian analysis of ODC.


obtained from the Bayesian analysis of Myo2.


obtained from the Bayesian analysis of ND2.


obtained from the Bayesian analysis of ND3.

As a service to our authors and readers, this journal provides

supporting information supplied by the authors. Such mate-

rials are peer-reviewed and may be re-organized for online

delivery, but are not copy-edited or typeset. Technical support

issues arising from supporting information (other than

missing files) should be addressed to the authors.

BIOSKETCHES

Knud A. Jønsson is a PhD student at the Zoological

Museum, University of Copenhagen, Denmark. His main

interests include systematics and historical biogeography of

passerine birds with a particular emphasis on the Indo-Pacific

region.

Jon Fjeldsa is a professor at the Zoological Museum,

University of Copenhagen, Denmark. He has broad interests

in phylogeny and systematics of birds as well as a general

interest in several other aspects of ornithology, ecology and

conservation.

Author contributions: K.A.J. and J.F. conceived the ideas;

K.A.J. collected and analysed the data. All authors took part in

the writing process.

Editor: Lawrence Heaney



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