The influence of gene flow and drift on genetic and phenotypic divergence in two species of...

Autho

Electron101098

One cofinches i

Phil Trans R Soc B (2010) 365 1077ndash1092

doi101098rstb20090281

The influence of gene flow and drift ongenetic and phenotypic divergence in two

species of Zosterops in VanuatuSonya M Clegg12 and Albert B Phillimore13

1Division of Biology Imperial College London Silwood Park Ascot Berkshire SL5 7PY UK2Biodiversity and Geosciences Program Queensland Museum PO Box 3300 South Brisbane

Queensland 4101 Australia3NERC Centre for Population Biology Imperial College London Silwood Park Ascot

Berkshire SL5 7PY UK

Colonization of an archipelago sets the stage for adaptive radiation However some archipelagos arehome to spectacular radiations while others have much lower levels of diversification The amountof gene flow among allopatric populations is one factor proposed to contribute to this variation Inisland colonizing birds selection for reduced dispersal ability is predicted to produce changing pat-terns of regional population genetic structure as gene flow-dominated systems give way to drift-mediated divergence If this transition is important in facilitating phenotypic divergence levels ofgenetic and phenotypic divergence should be associated We consider population genetic structureand phenotypic divergence among two co-distributed congeneric (Genus Zosterops) bird speciesinhabiting the Vanuatu archipelago The more recent colonist Z lateralis exhibits genetic patternsconsistent with a strong influence of distance-mediated gene flow However complex patterns ofasymmetrical gene flow indicate variation in dispersal ability or inclination among populationsThe endemic species Z flavifrons shows only a partial transition towards a drift-mediatedsystem despite a long evolutionary history on the archipelago We find no strong evidence thatgene flow constrains phenotypic divergence in either species suggesting that levels of inter-islandgene flow do not explain the absence of a radiation across this archipelago

Keywords Vanuatu regional population structure gene flow allopatric divergence island birds

1 INTRODUCTIONThe role of geographical separation and consequentelimination of gene flow in driving population diver-gence was a central tenet of the speciation modelsthat emerged from the modern synthesis (Dobzhansky1937 Mayr 1942 1954) While allopatric speciationwith zero or very low levels of gene flow is probablythe most common geographic mode for many taxa(Barraclough amp Vogler 2000 Coyne amp Orr 2004Phillimore et al 2008a Price 2008) some contempor-ary views place greater emphasis on ecologicaldivergence and diversifying selection pressures ratherthan the geographic context of divergence (Ogden ampThorpe 2002 Jordan et al 2005 Rundle amp Nosil2005 Bolnick amp Fitzpatrick 2007 Butlin et al 2008Nosil 2008) Nonetheless in birds only a few casesof potential sympatric or parapatric speciation havebeen identified (Sorenson et al 2003 Huber et al2007 Ryan et al 2007 Smith amp Friesen 2007) andthe majority of sister-species have contemporary rangedistributions that do not overlap (Barraclough amp

r for correspondence (sonyaclegggmailcom)

ic supplementary material is available at httpdxdoiorgrstb20090281 or via httprstbroyalsocietypublishingorg

ntribution of 13 to a Theme Issue lsquoDarwinrsquos Galapagosn modern evolutionary biologyrsquo

1077

Vogler 2000 Coyne amp Price 2000 Phillimore et al2008a)

Fragmented landscapes such as archipelagos pro-vide a tractable setting to assess the influence ofgeography on genetic and phenotypic divergence(eg Clegg et al 2002a Petren et al 2005 Jordan ampSnell 2008 Phillimore et al 2008b) For insular popu-lations at the beginning of the speciation continuum(sensu Mayr amp Diamond (2001) eg populationslacking (subspecific) geographic variation subspeciesor allospecies) the characterization of patterns ofgenetic connectivity among island populations cancontribute to an understanding of the influence ofgeographical isolation on gene flow patterns andphenotypic divergence

Correspondence between geographic and geneticisolation largely depends on an organismrsquos vagility(Burney amp Brumfield 2009) an attribute that canchange over time in island colonizing species Evi-dence from plants (Cody amp Overton 1996) and birds(McNab 1994 Adler et al 1995) suggests that islanddwelling can result in selection for reduced dispersalabilities (see also Grant 1998) The changing patternsof population connectivity among islands are expectedto produce distinct signatures of regional populationgenetic structure at neutral loci (Hutchison ampTempleton 1999) If the colonizing ability of a specieswere maintained over time then there would be weak

This journal is q 2010 The Royal Society

1078 S M Clegg amp A B Phillimore Gene flow and drift in island Zosterops

relationships expected between the level of geographicisolation and genetic variation within and amongpopulations

Even in highly vagile organisms ongoing within-archipelago dispersal and gene flow can be affectedby behavioural or morphological changes that reducethe inclination or ability to effectively disperseacross water barriers (Diamond et al 1976 Mayr ampDiamond 2001) Distance-limited dispersal isexpected to generate a gene flow-mediated populationstructure evidenced by a negative relationship betweenneutral genetic diversity and geographic isolation(Jordan amp Snell 2008) the establishment ofisolation-by-distance patterns of genetic differentiation(Slatkin 1993 Hutchison amp Templeton 1999) and lowprobabilities of alleles being identical by descentwithin populations (Ciofi et al 1999) If geographicallyseparated populations become progressively moregenetically isolated over time gene flow is expectedto yield to drift as the predominant mechanism shap-ing population structure producing a positiverelationship between neutral genetic diversity andpopulation size (approximated by island area) butnot isolation (Lande amp Barrowclough 1987 egHinten et al 2003 Jordan amp Snell 2008) a breakdownof isolation by distance patterns (Hutchison ampTempleton 1999) and a high probability that alleleswithin a population are identical by descent (Ciofiet al 1999) These represent extremes in a spectrumand intermediate patterns may also arise as regionalpopulation structure shifts eg partial isolation-by-distance patterns (Hutchison amp Templeton 1999)and generation of geographic patterns for types ofvariation most sensitive to demographic change (egallelic diversity rather than heterozygosity Nei et al1975)

The importance of gene flow as a process retardingphenotypic divergence is expected to vary consider-ably depending on whether new mutations areuniversally favoured (Price 2008 Rundell amp Price2009 Schluter 2009) and on the strength of divergentselection (Lenormand 2002 Rundle amp Nosil 2005) Ifphenotypic divergence is influenced by new mutationsthat are favoured in all populations then a trickle ofgene flow may be sufficient to prevent phenotypicdivergence (Price 2008 Rundell amp Price 2009) Ifdivergent selection pressures exist but are over-whelmed by gene flow then this will also preventphenotypic divergence Under these two scenarios wewould predict greater phenotypic divergence amongdrift-mediated rather than among migration-mediation populations (Lenormand 2002) It is onlyif divergent selection is strong relative to levels ofgene flow that we would predict substantial phenotypicdivergence regardless of whether a populations geneticstructure is drift- or migration-mediated (eg diver-gence with gene flow scenarios Jordan et al 2005Nosil 2008)

Members of the avian family Zosteropidae arerenowned for their colonizing ability (Mayr 1945Mees 1969 Lack 1971) and it has recently beenrevealed that a South Pacific clade speciated remark-ably quickly (Moyle et al 2009) Because of themorphological conservatism noted in the family

Phil Trans R Soc B (2010)

Moyle et al (2009) suggested that rapid evolutionaryshifts in dispersal ability rather than adaptive ecologi-cal explanations were important for high speciationrates in the family At a population level thereforewaning gene flow among Zosterops populations ondifferent islands may be an important catalyst of diver-gence Divergent natural selection on phenotype hasbeen demonstrated in a number of island white-eyepopulations (Clegg et al 2002a 2008) but the facili-tating effects of shifts in dispersal ability and geneflow are not clear

While the distribution and morphological variationof southwest Pacific avifauna provided the foundationfor many early ideas about island speciation (Mayr1954 Mayr amp Diamond 2001) phylogeographic andpopulation genetic studies of the avifauna of thisregion are only now beginning to accumulate(Kirchman amp Franklin 2007 Smith amp Filardi 2007Phillimore et al 2008b) lagging behind other well-studied island groups such as the Galapagos (Petrenet al 1999) the Caribbean (see Ricklefs ampBermingham (2007) and references therein) andHawaii (Fleischer amp McIntosh 2001) In the Vanuatuarchipelago two Zosterops species the endemicZ flavifrons and the later colonizer Z lateralis have lar-gely coincident distributions but are at different stagesof divergence (Mees 1969 Phillimore 2006 Black2010) This situation allows us to contrast geneticand phenotypic patterns across the same landscapein related ecologically similar species that differ inage across islands We compare regional populationstructure in the two species examining the relativeimportance of gene flow and drift across thearchipelago and within-individual island populationsAgainst the neutral framework describing populationconnectivity and the geographical factors associatedwith declining gene flow we examine patterns ofmorphological variation to determine whether greaterisolation coincides with greater phenotypic divergence

2 MATERIAL AND METHODS(a) Study system

The Vanuatu archipelago (figure 1) was formedthrough cycles of volcanic growth and tectonic upliftthat began approximately 20ndash22 Myr ago althoughthe bulk of current land area was formed in the past05 Myr (Mallick 1975) The islands formed alongthree volcanic belts with the oldest islands on thewestern (Espiritu Santo and Malekula) and easternbelts (Maewo Pentecost and Efate) and the remaininggenerally younger islands on the central belt (Mallick1975) Assuming a relaxed clock model for substi-tution at mitochondrial protein-coding genes itappears that the archipelago was colonized somewherein the region of 2ndash4 Myr ago by Z flavifrons and lessthan 05 Myr ago by Z lateralis (Phillimore 2006Black 2010) suggesting that the ancestors of the ende-mic Z flavifrons colonized before many of the currentislands existed Zosterops flavifrons has previously beendivided into seven morphological subspecies whichfall into darker and yellow plumage colour groups(Mayr 1945 Mees 1969) Mitochondrial DNA(mtDNA) evidence has cast doubt on the monophyly

Vanua Lava

Gaua

MaewoAmbae

Pentecost

Malekula

Efate

Ambrym

Espiritu Santo

Epi

Erromango

Tanna

Aneityum

12

1

2

Australia

North

Figure 1 The Vanuatu archipelago showing locations sampled Numbers refer to locations in table 1 Zosterops lateralis were notfound on Maewo and Aneityum Inset shows the position of Vanuatu (circled) in the southwest Pacific Scale bar 100 km

Gene flow and drift in island Zosterops S M Clegg amp A B Phillimore 1079

of Z flavifrons with a single peripheral populationpossibly representing a cryptic species (Phillimoreet al 2008b) and the two plumage colour groups poss-ibly resulting from separate invasions (Black 2010)There is also considerable mtDNA structure withineach plumage colour group that often does not con-form to subspecies designations (Phillimore et al2008b) The deep mtDNA phylogenetic splits withinZ flavifrons suggest that gene flow has probablyceased between allospecies of the two plumagegroups (Phillimore et al 2008b) and we therefore trea-ted them separately in statistical analyses except


where indicated Zosterops lateralis is a prolific islandcolonizer with multiple invasions of southwest Pacificislands occurring either directly from its Australianmainland source or via island-hopping (Mayr 1954Mees 1969 Lack 1971 Clegg et al 2002b) InVanuatu two to three morphological subspecies ofZ lateralis are recognized (Mayr 1945 Mees 1969)

(b) Sampling

Birds were caught in mistnets and traps from Februaryto May 2004 (ABP) and February to April 2006(SMC) (table 1) Morphological measurements

Table 1 Location and sample size information for genetic and morphological analyses Plumage colour groups for

Z flavifrons D dark Y yellow Sample size nflav Z flavifrons nlat Z lateralis

location (abbreviation)latitudelongitude

Z flavifronssubspecies

Z lateralissubspecies

sample size

yearsnflav nlat

Vanua Lava (Van) 1388 S 16755 E perplexa (D) tropica 51 4 2004 2006Gaua (Gau) 1483 S 16767 E gauensis (Y) tropica 24 19 (20a) 2004E Santo Kole1 (San-1) 1523 S 16716 E brevicauda (D) tropica 32 31 2006E Santo Luganville (San-2) 1553 S 16722 E brevicauda (D) tropica 17 33 2004

Maewo 1519 S 16811 E perplexa (D) mdash 18 mdash 2006Ambae (Amb) 1622 S 16791 E perplexa (D) tropica 37 3 2006Pentecost (Pen) 1547 S 16816 E perplexa (D) tropica 9 28 2006Malekula Wiawi (Mal-1) 1613 S 16720 E macgillivrayi (D) vatensis 8 3 2006Malekula Lakatoro (Mal-2) 1612 S 16742 E macgillivrayi (D) vatensis 13 19 2004

Ambrym (Aby) 1528 S 16799 E perplexa (D) vatensis 61 22 2006Epi (Epi) 1645 S 16833 E perplexa (D) vatensis 9 9 2004Efate Moso Is (Efa-1) 1756 S 16822 E efatensis (Y) vatensis 34 8 2006Efate Port Vila (Efa-2) 1773 S 16832 E efatensis (Y) vatensis 45 25 2004

Erromango (Err) 1870 S 16915 E efatensis (Y) vatensis 17 13 2004Tanna (Tan) 1953 S 16927 E flavifrons (Y) vatensis 40 12 2004Aneityum (Ane) 2033 S 16966 E majuscula (D) mdash 23 mdash 2004

aSample size for morphological analysis


were recorded from each individual (wing tarsusculmen length (posterior nostril opening) andculmen depth and width (anterior nostril opening))Approximately 20ndash40 ml of blood was collected viavenipuncture of the brachial wing vein and stored in500 ml of 90 per cent ethanol or absorbed onto apiece of Whatman filter paper (no 113) wetted witha drop of 05 M EDTA (Petren 1998) Samples wereindividually numbered and the paper samples driedand stored with a desiccant in a sealed container

(c) Molecular methods

DNA was extracted via an ammonium acetate extrac-tion precipitation method (Nicholls et al 2000)DNA concentrations were estimated on a fluorometerand working dilutions of approximately 20 ng ml21

were prepared Microsatellite loci isolated fromCapricorn silvereye (Zosterops lateralis chlorocephalus)(Degnan et al 1999 Frentiu et al 2003) andSeychelles warbler (Acrocephalus sechellensis)(Richardson et al 2000) along with the chromo-helicase-DNA-binding (CHD) genes for avian sexing(Griffiths et al 1998) were amplified using standardpolymerase chain reaction (PCR) protocols orQiagen Multiplex PCR kits Microsatellite amplifica-tion of Z flavifrons samples have been describedelsewhere (Phillimore et al 2008b) and similar proto-cols were followed for Z lateralis samples Primer-dependent conditions and loci used for each speciesare given in the electronic supplementary materialappendix A Allele size scoring was conducted usingthe software GENEMAPPER v 30 (ABI)

(d) Gene flowdrift models genetic diversity

and geographical associations

Assumptions of linkage disequilibrium and HardyndashWeinberg equilibrium (HWE) were tested inGENEPOP 32a (Raymond amp Rousset 1995) Observed


and expected heterozgyosity (HO and HE) for eachlocuspopulation combination was calculated inGENEPOP 32a (Raymond amp Rousset 1995) and aver-aged across loci for each population Allelic richnesswas estimated using the rarefaction method in FSTAT

v 293 (Goudet 1995 2001) to account for differ-ences in sample size (Leberg 2002) The minimumsample size for rarefaction was eight for Z flavifronsand nine for Z lateralis All sampled populationswere included for Z flavifrons but two populationswith less than five Z lateralis samples (Vanua Lavaand Ambae) were excluded

The correlation between ln-transformed variables ofisland area and the distance to the nearest island host-ing a member of the same group was low for Z lateralis(r frac14 2022) and the dark plumage group Z flavifrons(r frac14 012) We used a multiple regression approachto estimate the degree to which island area and iso-lation (distance to the nearest island inhabited by amember of the same group) predicted indices ofgenetic diversity Each genetic diversity measure(allelic richness expected heterozygosity and modalF table 2) was considered the dependent variable inturn Multiple regression was conducted only onZ lateralis and the dark plumage group of Z flavifronsas there was insufficient replication in the yellow plu-mage group (n frac14 4) For the yellow plumage groupwe instead ran regressions for each predictor in turn

To test for an effect of isolation by distance(IBD) within each species across the archipelago wecompared a matrix of pairwise genetic differences(FST(1 2 FST)) (Rousset 1997) with log-transformedgeographic distances A pairwise FST matrix was calcu-lated in FSTAT (Goudet 1995 2001) Geographicdistances were calculated as great circle distancesusing latitude and longitude co-ordinates in theR software (R Development Core Team 2008) Signifi-cance was assessed via a Mantel test with 10 000randomizations and plotted using reduced major

Table 2 Population level genetic variation (AR allelic richness HO observed heterozygosity HE expected heterozygosity)

and summary statistics from 2MOD analyses giving the modal values of the posterior distribution of F (the probability thattwo genes in a population are identical by descent and not immigration) and M (the number of migrantsgeneration) foreach population Diversity measures are calculated from 11 loci (Z lateralis) and eight loci (Z flavifrons) Ninety per centhighest posterior density (HPD) ranges are given for F and M distributions

location AR HO HE F mode 90 HPD range M mode 90 HPD range

Z lateralisVanua Lava mdash 0523 0503 mdash mdash mdash mdash mdash mdashGaua 282 0431 0457 01242 00751 01917 159 091 264

Espiritu Santo 225 0488 0505 01271 00845 01882 150 098 241Ambae mdash 0515 0570 mdash mdash mdash mdash mdash mdashPentecost 307 0497 0525 00507 00267 00938 344 187 712Malekula 316 0525 0538 00059 00001 00277 1627 292 11937

Ambrym 332 0512 0533 00096 00008 00315 1171 358 5954Epi 291 0455 0496 00608 00178 01375 243 095 776Efate 251 0342 0332 02810 01994 03635 061 040 094Erromango 265 0438 0428 02425 01574 03465 071 041 119Tanna 227 0250 0314 04302 03255 05609 029 018 049

Z flavifrons (dark plumage group)

Vanua Lava 374 0446 0565 03896 02973 03917 037 024 056Espiritu Santo 388 0513 0528 04617 03677 05632 028 018 041Malekula 383 0496 0557 03182 02441 04042 051 034 073Epi 356 0568 0603 03635 02706 04559 042 027 064

Ambae 315 0446 0473 03125 02357 03917 053 037 077Maewo 280 0444 0475 04570 03792 05592 028 019 039Pentecost 271 0403 0435 03906 02967 04897 037 024 056Ambrym 313 0469 0516 03652 02933 04527 041 029 058Aneityum 226 0255 0329 mdash mdash mdash mdash mdash mdash

Z flavifrons (yellow plumage group)

Gaua 226 0298 0299 03897 02851 05250 033 020 058Efate 203 0209 0231 03473 02481 04526 045 027 070Erromango 285 0392 0460 01446 00676 02514 114 053 259Tanna 258 0385 0396 02083 01296 03179 080 045 147


axis regression using web-based software IBDWS(Jensen et al 2005)

We determined the relative contributions of driftversus gene flow across the region for Z lateralis(excluding Ambae and Vanua Lava owing to samplesizes less than 5) and the dark and yellow plumagegroups of Z flavifrons considered separately usingthe likelihood approach implemented in the program2MOD (Ciofi et al 1999) Two models were com-pared the drift model relates to populations that aresubject to drift alone with no influence from geneflow and the gene flowdrift equilibrium model(referred to as the gene flow model) relates to a bal-ance between the two microevolutionary forces Thedrift model assumes that mutation has not stronglyinfluenced gene frequencies such that alleles are iden-tical by descent and the gene flow model assumes thatthe mutation rate is much smaller than the immigra-tion rate (Ciofi et al 1999) Mutational influences ongene frequencies need to be considered especially interms of the yellow and dark clades of Z flavifronswhere mtDNA indicates substantial divergencebetween island populations (05ndash4 Myr Black2010) We ran the program four times to ensureconvergence of the MCMC algorithm with 105 iter-ations and the first 104 discarded as burn-in Wereport the first run of each model after confirmingthat independent runs yielded similar results Theprobability of a model was calculated as the proportion


of times that model was supported and also expressedas a Bayes factor (probability model 1probabilitymodel 2) The number of migrants per generation(M) for each population was calculated from Fvalues according to Ciofi et al (1999) Conditionalposterior distributions of F (the probability that twogenes share a common ancestor) and M were deter-mined from the program Locfit (Loader 2007)within the R framework (R Development Core Team2008) using values from only the favoured modelThe mode and 90 per cent highest posterior density(HPD) limits were calculated in R using code modifiedfrom Lopez-Vaamonde et al (2006)

(e) Population genetic structure and connectivity

patterns within each species

To more fully explore the population genetic structureof Z lateralis we used Bayesian clustering methodsimplemented in STRUCTURE v 2 to assess geneticstructure without using prior geographical information(Pritchard et al 2000) The number of genetic clusters(k) suggested by the data without using prior popu-lation information was evaluated for values of kbetween 1 and 9 using five independent runs ateach value of k each with a burn-in length of 105

and run length of 106 iterations The default programsettings were used including correlated allele frequen-cies (Falush et al 2003) and an admixture model

(a)

(e)(d)

(c)(b)

Figure 2 Distribution of microsatellite genetic clusters from STRUCTURE and estimates of migration rates from BAYESASS

among islands for (a) Z lateralis five genetic clusters In text cluster 1 red 2 yellow 3 green 4 purple 5 blue (b) Zosteropslateralis migration rates (c) dark plumage group Z flavifrons clusters (d) dark plumage group Z flavifrons migration rates and(e) yellow plumage group Z flavifrons genetic clusters Note that STRUCTURE analysis was conducted for each group separatelyand pie colours do not relate to across-group comparisons STRUCTURE data for Z flavifrons taken from Phillimore et al(2008b) Solid lines show migration rates more than 01 dashed lines 003ndash01 and dotted lines 002ndash003


allowing individuals to have mixed ancestry The priorprobabilities of the best run for each value of k (ie therun with the smallest value of 22 log Pr(Xjk)) werecompared to identify the most likely number of geneticclusters Individual assignments to clusters were ident-ified from the output of the best run for the most likelyvalue of k STRUCTURE identifies groups of individualsat the uppermost hierarchical level and when there isuneven migration among populations such as thatevidenced by IBD relationships more subtle nestedsub-structuring may be overlooked (Evanno et al2005) Therefore following assignment of individualsto each of the clusters identified in the first STRUCTURE

analysis separate analysis was carried out on thoseclusters that were geographically widespread to deter-mine if there was sub-structuring within clusters

A STRUCTURE analysis of each Z flavifrons plumagegroup has previously been reported (see Phillimore


et al (2008b) for details of analysis) For comparisonwith Z lateralis a summary of cluster associationswithin each Z flavifrons plumage group is presentedin figure 2

Contemporary inter-island migration rates forZ lateralis populations and a subset of Z flavifronspopulations were estimated via the Bayesian methodimplemented in BAYESASS 13 (Wilson amp Rannala2003) This method simultaneously estimates recentmigration rates (ie the fraction of individuals withina population that are migrants per generation) alongwith a suite of other parameters including individualmigrant ancestries (Wilson amp Rannala 2003) The per-formance of the method as assessed by Faubet et al(2007) was found to be accurate under conditions ofmoderate genetic differentiation (FST 005) andsmall migration rates (no more than one-third of theindividuals in a population being migrant per


generation) For Z lateralis the two populations withlow sample size (Ambae and Vanua Lava) wereexcluded from the analysis The BAYESASS analysiswas inappropriate for most of the Z flavifrons popu-lations given that many of the islands were found tobe monophyletic and in some cases highly divergenton a mtDNA gene tree (Epi Santo Tanna VanuaLava Phillimore et al 2008b) which is consistentwith an absence of gene flow In the case of theGaua and Efate populations of the yellow Z flavifronsongoing gene flow seems improbable given the largedistance between these two islands Moreover pair-wise FST estimates for many of these islandpopulations were large (more than 03 Phillimoreet al 2008b) The one group of populations whereongoing gene flow does appear plausible on the basisof low FST values (Phillimore et al 2008b) is for darkgroup Z flavifrons members inhabiting AmbaeAmbrym Maewo and Pentecost in the eastern partof central Vanuatu Consequently we consideredthese four islands in a BAYESASS analysis We setdelta values for allele frequencies inbreeding coeffi-cients and migration rates such that acceptance ratesfor changes in these parameters fell between 40 and60 per cent (Wilson amp Rannala 2003) The programwas run for 21 106 iterations including a burn-inof 2 106 iterations Model convergence was assessedby comparison of posterior probability densities ofinbreeding coefficients and allele frequencies across10 replicate runs (five replicates for the Z flavifronsanalysis) with different starting seeds (Wilson ampRannala 2003) Distributions of log-likelihood valuesfor each converged run were compared to determinethe best run from which to obtain parameter estimates

(f) Morphological variation

Analysis of morphological data was conducted in the Rframework (R Development Core Team 2008)Between-measurer repeatability (between SMCand ABP) was assessed from measures of museumspecimens of Z flavifrons and Z lateralis (from theMuseum of Natural History Tring) for culmentraits and wild-caught blue tits (Cyanistes caeruleus)for wing tail and tarsus following the proceduredescribed in Phillimore et al (2008b) Measurementswere compared directly with the exception ofculmen length where a systematic difference inmeasurement was apparent Correction factors of0048 and 0064 were added to the ln-transformedculmen length measurements made by ABP forZ lateralis and Z flavifrons respectively prior tocalculating repeatability Traits with high between-measurer repeatability were included in the analysis(wing repeatability (r) frac14 084 sample size (n) frac14 25tarsus r frac14 09 nfrac1425 culmen length r frac14 086 n frac1446 culmen depth r frac14 087 n frac14 46 culmen widthr frac14 069 n frac14 46) Tail length was removed fromfurther analysis owing to lower between-measurerrepeatability (r frac14 058 n frac14 25)

Principal components analysis was conducted onlog-transformed wing tarsus culmen length culmendepth and culmen width measurements We also cal-culated relative wing length as the residual values


from a regression of log-transformed wing length onlog-transformed tarsus length Latitudinal effects onmorphology summarized as (i) principal componentsand (ii) relative wing length were tested using leastsquares regression on mean location values (note thatwe did not make any correction for phylogeneticsimilarity or levels of population connectivity)

Correlation between total (measured) phenotypicvariance and covariance measured as the sum ofvariances for each morphological trait in each popu-lation and island isolation and area were assessedusing multiple regression For Z flavifrons populationage estimates obtained from coalescence estimates ofmtDNA lineages assuming a mean substitution rateof 2 per cent per million years were available(Phillimore et al 2008b) Therefore median age(measured as the median age of the most recentcommon ancestor shared between a focal island popu-lation and its closest relative on the maximum cladecredibility tree) was included as a covariate in additionto island isolation and area for Z flavifrons Lack ofcoalescence of mtDNA lineages precluded a similaranalysis in Z lateralis (Phillimore et al 2008b)

Pairwise multivariate morphological differencesbetween populations for both species were quantifiedvia a MANOVA-based approach (described inPhillimore et al 2008b) as the proportion of the totalmeasured phenotypic variation between and withinthe two populations that was found at the betweenpopulation level Note that this is identical to calculat-ing multivariate PST (Leinonen et al 2006)mdashitself aphenotypic equivalent of QST (Spitze 1993)mdashunderthe assumption that all phenotypic differences betweenpopulations are due to additive genetic variance and awithin-population heritability of 05

Correlations between phenotypic and genetic (FST)matrices and phenotypic and geographical distancematrices were assessed using Mantel tests with10 000 permutations The pairwise FST matrixobtained from FSTAT (Goudet 1995 2001) was firststandardized to account for differences in within-population variability (Hedrick 2005) using methodsand programs described in Meirmans (2006)

3 RESULTS(a) HWE and linkage disequilibrium

Eleven microsatellite loci were screened for Z lateralisTwo populations had a deficit of heterozygotesAmbrym (p-value combined across loci p frac14 001)and Tanna (p frac14 0007) In both cases this wasbecause of a small subset of loci and therefore hetero-zygote deficiency was not a population-specificproblem Two loci had a deficit of heterozygotesZL45 (p-value combined across populations p frac14005) and ZL38 (p 0001) However this does notsuggest a locus-specific problem with null alleles asin both of these cases only one and three of the12 populations respectively were responsible forthe significance of the combined value Linkage dis-equilibrium was not detected for any locus pair (p

006 for all pairwise comparisons) Therefore all 11loci were retained for further analysis of variation inZ lateralis populations Eight loci were used to

20

25

30

35

alle

lic r

ichn

ess

03

04

05

06

HE

200 500 1000 2000

00

01

02

03

04

island area (km2)

mod

al F

10 20 50distance between islands (km)

Figure 3 Regression of three diversity measures (allelic richness expected heterozygosity (HE) and modal F values from2MOD analysis) with island area (square kilometres) and distance to nearest inhabited island (kilometres) (of the samecolour morph in the case of Z flavifrons) Zosterops lateralis open circles solid line dark plumage Z flavifrons black circlesdashed line yellow plumage Z flavifrons black triangles (no regression shown) Zosterops flavifrons from Aneityum (indicatedby an asterisk) was not included in regressions because of its paraphyletic status


quantify microsatellite variation in Z flavifrons Theuse of these eight loci conformed to assumptions ofHWE and linkage equilibrium and across loci andpopulations (see Phillimore et al (2008b) for detailsof assumption testing)

(b) Gene flowdrift models genetic diversity


In Z lateralis an increase in island isolation was signifi-cantly associated with a decrease in allelic richness andheterozygosity and an increase in the inbreeding coef-ficient (figure 3 and table 3) In the darker Z flavifronsgroup allelic richness increased significantly withisland area but correlations of area with other indicesof genetic diversity were not significant A counterin-tuitive trend in the dark Z flavifrons was thatdistance to the nearest island correlated positivelywith both allelic richness and expected heterozygosityNone of the single predictor models involving theyellow Z flavifrons returned a significant correlation

A significant IBD relationship was found for Zlateralis (Mantel test Z frac14 2501 r frac14 057 p frac14 0002figure 4a) This relationship was strongly influencedby the most isolated and differentiated southern popu-lation on Efate Erromango and Tanna (excludingthese populations Z frac14 344 r frac14 012 p frac14 0344figure 4a) In Z flavifrons an IBD pattern had border-line significance across the entire archipelago (Z frac146425 r frac14 033 p frac14 005 figure 4b) while significantrelationships were found for each plumage group


considered separately (dark plumage group Z frac14766 r frac14 044 p frac14 002 yellow plumage groupZ frac14 659 r frac14 093 p 00001 figure 4c)

Results from 2MOD analysis supported a geneflow-drift equilibrium model over a drift-alone modelin Z lateralis (p(gene flow) frac14 09998 Bayes factor frac144999) Lower modal F values were found for centralpopulations of Pentecost Malekula Ambrym andEpi translating into particularly high number ofmigrantsgeneration for Malekula and Ambrym Incontrast higher F values were characteristic of moreperipheral islands (Gaua Efate Erromango and par-ticularly Tanna) along with the largest island(Espiritu Santo table 2) A gene-flowdrift equilibriummodel was also favoured in both plumage groups ofZ flavifrons (p(gene flow) frac14 1 for each) however indi-vidual populations tended to have high modal Fvalues indicative of drift with correspondingly lowestimates of number of immigrants per generation(table 2)

(c) Population genetic structure and connectivity


The STRUCTURE analyses indicated that Z lateralis wascomposed of five genetic clusters (k probability of 5clusters frac14 1) All other tested values of k were not sup-ported and had probabilities approaching zero Theaverage assignment probabilities of individuals toeach cluster were reasonably high (average assignmentprobability for individuals in cluster 1 frac14 071 cluster

Table 3 Intercepts and slopes from multiple regression showing relationships between diversity and inbreeding indices with

island area and distance to the nearest island

Z lateralis dark Z flavifrons yellow Z flavifronsa

allelic richness (AR)

intercept 456+090 006+044 i frac14 382+175 ii frac14 155+336distance 2043+013 [063] 067+010 [056] 2038+022 [024]area 2006+011 [002] 026+006 [027] 0137+0523 [003]

heterozygosity (HE)intercept 096+020 025+010 i frac14075+049 ii frac14 013+096

distance 2012+003 [065] 009+002 [072] 2011+013 [026]area 2002+002 [002] 001+001 [001] 004+015 [002]

modal Fintercept 2059+041 041+019 i frac14017+064 ii frac14 108+094distance 018+006 [059] 2004+004 [012] 003+017 [001]

area 001+005 [0] 001+003 [003] 2013+015 [027]

Significance from zero indicated byp 005p 001p 0001aIntercepts and slopes reported for yellow plumage group Z flavifrons are from univariate regression The two intercepts (i and ii) are fordistance and area respectively Partial r2 and r2 (in the case of the yellow Z flavifrons) are reported in brackets


2 frac14 091 cluster 3 frac14 077 cluster 4 frac14 088 cluster5 frac14 064) The genetic clusters showed geographicaffinities with members of cluster 3 predominantlyfound on Espiritu Santo and represented in lower fre-quencies on neighbouring islands members of clusters1 and 5 being more widely distributed across islands atthe northern end of the archipelago members of clus-ter 4 found predominantly on Efate and Erromangoand members of cluster 2 on the southern island ofTanna (figure 2a) Separate STRUCTURE analysis ofeach of the three most widely distributed genetic clus-ters (1 3 and 5) did not reveal further structure atlower levels with each cluster comprising a single gen-etic group when treated separately (values tested k frac141ndash5 for each cluster with the same settings as theinitial STRUCTURE analysis)

The assignments of a similar STRUCTURE analysisapplied separately to the dark and yellow populationsare shown in figure 2ce (protocol described inPhillimore et al 2008b) Five clusters were identifiedfor the dark plumage group and four for the yellowgroup Based on the proportions of the populationsbelonging to each cluster it is clear that in the darkplumage group Epi Malekula and Santo have similarcompositions as do Ambae Ambrym Maewo andPentecost with Vanua Lava being quite distinct Inthe case of the yellow plumage group Erromangoand Tanna have similar compositions while Efateand particularly Gaua are quite distinct

Of the 10 independent BAYESASS runs conducted toquantify degree and direction of migration ratesamong Z lateralis populations eight converged on asimilar solution The best of the eight runs was identi-fied from the distribution of log-likelihood valuesFigure 2b displays all migration rate estimates above002 The predominant direction of migration wasnorth to south with generally low levels of upstreammigration (from south to north) Gaua EspirituSanto Pentecost Efate and Tanna each had a highproportion of non-migrants (electronic supplementarymaterial appendix B) The central islands of


Malekula Ambrym and Epi had high (more than015) immigration rates from Pentecost in particularas well as influences from Espiritu Santo and GauaEpi was additionally affected by northward gene flowfrom Efate Erromango had a high migration ratefrom neighbouring Efate (figure 2b electronic sup-plementary material appendix B) Migration ratesout of Espiritu Santo into Gaua Malekula AmbrymEpi and Erromango all exceeded 001 howevermigration rates into Espiritu Santo from other islandsnever exceed this value (electronic supplementarymaterial appendix B)

All five independent BAYESASS runs for the easternfour populations of the dark Z flavifrons group con-verged on a similar solution Ambrym had thehighest proportion of non-migrants and contributeda substantial proportion of migrants to the threeother populations Pentecost was a sink populationand both Ambae and Maewo were the source of asmall amount of migration to neighbouring islands(figure 2d electronic supplementary materialappendix C)

(d) Morphological variation

In Z lateralis three principal components (PCs) sum-marized 772 per cent of variation in fivemorphological traits High loading coefficients of simi-lar size and the same sign for each trait at PC1(explaining 446 of variance) indicated that this com-ponent represents overall size variation and ishenceforth referred to as body size Structure coeffi-cients at PC2 (184 of variance) contrasted culmenlength with culmen width and are referred to asculmen shape PC3 (141 of variance) contrastedtarsus length and culmen length and is referred to asbody shape In Z flavifrons three PCs summarized824 per cent of variation PC1 corresponded tobody size (548 of variance) PC2 (162 ofvariance) contrasted culmen depth and width withwing tarsus and culmen length measures and is

0

02

04

06

08F

ST(

1minusF

ST)

FST

(1minus

FST

)F

ST(

1minusF

ST)

(a)

(b)

(c)

0

02

04

06

08

15 20 25

0

02

04

06

08

log (distance)

Figure 4 Isolation by distance relationships for Zosterops(a) Zosterops lateralis pairwise comparisons among all islands(solid line shows the reduced major axis (RMA) regression

line when all points (open and closed circles) are included)and pairwise comparison among northern islands only(from Epi northwards to Vanua Lava open circles onlydashed RMA line regression line) (b) Zosterops flavifronspairwise comparisons among all island populations (c) Zflavifrons pairwise comparisons within yellow (open circlesdashed RMA regression line) and dark (closed circles solidRMA regression line) plumage groups

Table 4 Multiple regressions of total phenotypic variance

with island area distance to nearest island (isolation) andpopulation age For Z flavifrons plumage groups distancewas measured to nearest island of the same plumage group(excluding the population from Aneityum) Limited degreesof freedom for the yellow plumage Z flavifrons group

precluded the inclusion of three covariates simultaneouslytherefore the relationship between total phenotypic varianceand age was calculated separately

component estimate (+se) t-value p-value

total phenotypic varianceZ lateralisisland area 0001+0002 009 09

distance 20003+0002 2134 02

Z flavifrons (all populations)island area 0001+0001 103 03distance 20001+0001 2097 03age 0001+0002 040 07


island area 0001+0001 015 08distance 20002+0001 2164 01age 0004+0003 137 02

Z flavifrons (yellow plumage group)island area 0002+0002 095 05

distance 20001+0001 2174 08age 0002+0006 030 07


referred to as body shape and PC3 (114 of var-iance) contrasted culmen width with culmen depthand is referred to as bill shape

Some latitudinal trends in morphology were evidentin both species In Z lateralis relative wing lengthincreased with latitude for Z lateralis (r2 frac14 047 p

001) and there was also a marginally non-significanttrend for an increase in overall body size (r2 frac14 022p frac14 009) Bill shape and body shape in Z lateralisdid not display latitudinal patterns (bill shape r2 frac14

007 p 03 body shape r2 frac14 017 p frac14 01) In con-trast Z flavifrons populations did not show latitudinalpatterns in either relative wing length (r2 frac14 012 p

01) or body size (r2 frac14 008 p 02) Body shape(PC2) in Z flavifrons was associated with latitudemore southerly populations having longer wings tarsiand bills but narrower and shallower bills (PC2 andlatitude r2 frac14 036 p 005)

Total phenotypic variance in a population was notrelated to island area or level of isolation for eitherspecies or to population age for Z flavifrons(table 4) Average pairwise phenotypic divergenceamong populations were Z lateralis 069 (range021ndash096) Z flavifrons dark plumage group 070(0ndash098) Z flavifrons yellow plumage group 081(050ndash095) all Z flavifrons (excluding Aneityum)071 (0ndash098) Phenotypic divergence among


populations did not exhibit an IBD pattern in Z later-alis (Mantel test of phenotypic divergence versus log-transformed geographical distance r frac14 0239 p frac14015) however a marginally non-significant relation-ship was found for Z flavifrons (r frac14 024 p frac14 007)This relationship was not apparent when each plu-mage group was considered separately (dark plumagegroup r frac14 013 p 02 yellow plumage group r frac14022 p 02)

Pairwise phenotypic divergence and standardizedFST values were not correlated in Z lateralis (Mantelr frac14 04 p 01) A marginally non-significant correl-ation between phenotypic and genetic divergencematrices was found across all Z flavifrons populations(r frac14 029 p frac14 006) but when the dark and yellowplumage groups were considered separately no suchrelationship was evident (dark plumage groupr frac14 2007 p 06 yellow plumage group r frac14 007p 03)

4 DISCUSSIONBird species that colonize archipelagos are generallybelieved to be stronger dispersers (Diamond et al1976) However once on an archipelago selectionmay lead to reduced dispersal ability (eg McCallet al 1998) and as a consequence migration betweenpopulations on geographically separated islands isexpected to decline over time (Mayr amp Diamond2001) Changes in the rates of gene flow in turn havethe potential to influence rates of phenotypic diver-gence (Price 2008) In our examination of geneticand morphological diversity in two congenericco-distributed bird species at different stages of popu-lation divergence across the Vanuatu archipelago we


observed different regional population genetic struc-tures that possibly reflect the transition from a geneflow-mediated system towards a drift-mediatedsystem in an archipelago situation The developmentof complex and asymmetrical patterns of gene flowin the more recent colonizer gave way to a situationof genetically isolated drift-influenced populationswithin groups of the endemic species Patterns of phe-notypic variance and divergence were not stronglyrelated to levels of gene flow or geographic isolationin either species Phenotypic traits were weakly associ-ated with latitude consistent with climate-relatedinfluences on phenotype whether through selectionor phenotypic plasticity

(a) Constraints on gene flow and drift the

influence of island isolation and area

There were marked differences in regional populationgenetic structure between the Zosterops species Amongpopulations of the more recent colonizer Z lateralisgene flow maintained a strong influence on populationstructure at both the regional level and within many ofthe individual populations However frequent long-distance movements (resulting in gene flow) expectedif dispersal was maintained at the lsquocolonizingrsquo levelwere not apparent Gene flow was constrained byincreasing levels of island isolation producingdistinctive patterns of reduced genetic diversity andincreasing genetic isolation The importance ofisland isolation on genetic characteristics was furthershown by the relatively elevated inbreeding coefficients(F values) observed in peripheral populations (EfateErromango and Tanna in the south Vanua Lava andGaua in the north) compared with central Z lateralispopulations The higher likelihood that alleles wereidentical owing to descent in the peripheral islandpopulations demonstrated that they represent morelsquoclosedrsquo populations However the central and largestisland of Espiritu Santo also had a large F-value whichwe infer is the product of drift and thus geographicalisolation provides only a partial explanation of the levelof genetic isolation Results from the Bayesian analysisof migration show that Espiritu Santo was a sourcearea sending out migrants to surrounding islandsbut receiving them at a much lower rate which is theexpected pattern of migration between densely andmore sparsely populated areas (Lenormand 2002)Therefore despite its larger size and central locationasymmetrical migration may leave the Espiritu Santopopulation exposed to drift-mediated divergence

Despite having occupied the archipelago for amuch longer evolutionary time period (Phillimoreet al 2008b Black 2010) Z flavifrons populationsshowed only a partial shift to a drift-modulatedsystem with a general lack of significant relationshipsbetween island area and indices of diversityinbreedingin both the dark and yellow groups Only one relation-ship that of increasing allelic richness and area (usedas a proxy for population size) for dark forms of Z fla-vifrons was significant and in the direction predictedfor a drift-mediated system suggesting that increasedpopulation size buffers the largest populations fromallele loss via drift to some extent The corresponding


lack of any significant distancendashdiversity patterns(neither allelic richness nor heterozygosity were sig-nificantly negatively affected by increasing islandisolation and in fact the trend in the dark plumagegroup was one of increasing diversity with isolation) isconsistent with a shift away from a gene flow-mediatedsystem

Although a gene flowdrift model was highlyfavoured over a drift-alone model in Z flavifrons plu-mage groups the influence of drift on individualisland populations was pronounced (much more sothan for any Z lateralis population) and was equallyevident in both central and peripheral islands A simi-lar pattern in red deer populations was interpreted asevidence of a shift from a gene flowdrift equilibriumsystem towards a drift system that had not been com-pleted owing to the historical time frame of populationfragmentation (Kuehn et al 2003) The time frameavailable for population fragmentation in Z flavifronsmay be complicated by (i) the possibility that the cur-rent geography of the archipelago was not fullydeveloped when the ancestors of Z flavifrons colonized(Mallick 1975) (ii) that multiple independent coloni-zations seem probable (Black 2010) and (iii) thatbackground extinction of island populations may behigh (Ricklefs amp Bermingham 1999) Given that ageestimates for Z flavifrons populations are more than05 Myr in 10 of the 13 populations and most of thepopulations are unlikely to be connected via currentgene flow (Black 2010) we suggest that the incompletetransition to a signature of a drift-mediated system forZ flavifrons plumage groups possibly reflects low levelsof ancient gene flow among populations of the sameplumage group with some contemporary gene flowamong the eastern islands rather than a lack of time

Results from the two Zosterops species contrast withstudies of island taxa that were marooned on islandsformed by rising sea levels For example drift wasidentified as the main determinant of regionalpopulation structure in lava lizards Microlophusalbemarlensis complex on the islets in the Galapagos(Jordan amp Snell 2008) and Australian bush ratsRattus fuscipes greyii on South Australian islands(Hinten et al 2003) Even in species that must havebeen capable of over-water colonization a strongsignature of drift has been reported to develop rapidly(eg Galapagos hawk Buteo galapagosensis Bollmeret al 2005) The maintenance of dispersal capacity inZ lateralis and to a lesser extent within some popu-lations of Z flavifrons may not be unusual for birdsinhabiting the Vanuatu archipelago A phylogeographicstudy of mtDNA variation in three other widespreadbirds (buff-banded rail Gallirallus phillippensis emeralddove Chalcophaps indica and streaked fantail Rhipiduraspilodera) across Vanuatu revealed little evidence forgeographical structure suggesting a role for ongoinggene flow (Kirchman amp Franklin 2007)

(b) Population connectivity in Z lateralisand Z flavifrons populations

Population connectivity patterns in Z lateralis offerinsights into geographical influences during the earlystages of diversification in the archipelago and


highlight the complexities of movement patterns acrossa fragmented environment The highest levels of geneflow occurred among neighbouring central islandswith some indication that stepping-stone rather thandirect dispersal may operate in some cases (eg Espir-itu Santo to Ambrym via Malekula) Patterns of geneflow inferred from the BAYESASS analysis (proportionof migrants per generation) compared with estimatescalculated from F values in 2MOD (number ofmigrants per generation) were broadly congruentwith respect to identifying those islands subject tohigh levels of gene flow (some central islands) com-pared with peripheral islands that are isolated egTanna However the BAYESASS analysis has theadvantage of showing direction and asymmetries ingene-flow patterns

Asymmetrical gene flow among islands is a featureof the system even among the neighbouring centralislands There are a number of possible explanationsfor the development of the particular sourcendashsinkrelationships seen in Z lateralis First uneven patternsof gene flow could be because of differences in popu-lation productivity (Lenormand 2002) If we takeisland size as a proxy for population size and prod-uctivity the evidence for this explanation inZ lateralis is equivocal with representatives of bothlarger and smaller islands appearing to be source andsink populations Second dispersal ability or inclin-ation may vary among populations It is not obviouswhat combination of population ecological andormorphological differences could produce dispersalvariation patterns that would account for the observedsourcendashsink relationships among populations ofZ lateralis However the extreme variation noted inthe dispersal ability of different Z rendovae subspecieswithin the Solomon archipelago (Mayr amp Diamond2001) indicates that dispersal variation may be animportant feature of fragmented Zosterops populations

Taking an archipelago-wide view the direction ofgene flow was predominantly north to south This isconsistent with the dominant pattern noted fromspecies distributions in the broader southwest Pacificregion (ie New Guinea Bismarks SolomonsVanuatu Fiji)mdashthat of lsquodownstreamrsquo avian coloniza-tion routes from regions of higher to lowerbiodiversity (Diamond et al 1976 Mayr amp Diamond2001) Interestingly this general pattern is at oddswith the latitudinal trends in relative wing length asin both species southern populations possessedlonger relative wing lengths and presumably havegreater dispersal ability (Skjelseth et al 2007) Onepossible resolution of the discord between predomi-nant dispersal direction and latitudinal trends inwing length is the idea that colonization itself createsa selection filter (eg Berry 1998) thus only the stron-gest flyers would reach the most southerly islandsNo single explanation accounts for the observedsourcendashsink patterns however a combination of thedominant pattern (northndashsouth dispersal) overlaidwith population density influences and otherpopulation-level idiosyncrasies such as dispersalinclination may all contribute

In addition to the ongoing distance-limited geneflow the population genetic structure of Z lateralis


may be impacted by local extinctions and recoloniza-tions that would have the effect of weakening thedevelopment of geographical structure (Slatkin1987) Diamond amp Marshall (1977) discussed thechanging distributions of Vanuatu avifauna since thebeginning of ornithological expeditions in 1774 withboth expansions and retractions of previously recordeddistributions particularly among the central islandsfrom Epi to Espiritu Santo and Maewo Zosteropslateralis was previously recorded on Maewo (Bregulla1992) but appears to be currently absent or extremelyrare (S Totterman VanBirds 2005 personalcommunication SMC personal observation2006) In all likelihood Maewo will be recolonizedfrom a neighbouring island given its geographicalproximity (less then 6 km) to large populations ofZ lateralis However despite this example extinctionand recolonization events within Z lateralis do notappear to have been frequent enough to impede thedevelopment of structured variation as evidenced byIBD patterns the discernible geographical structureof neutral allelesmdasheven among groups of centralislandsmdashand the substantial divergence of particularpopulations eg Tanna Phylogenetic informationwill need to be used to determine if this remains trueover longer evolutionary time frames thus fulfillingthe lsquopopulation persistencersquo requirement for diver-gence and potential adaptive radiation (Diamond ampMarshall 1977 Ricklefs amp Bermingham 2007)

Among Z flavifrons highly structured genetic clustersreflect the long history of isolation that many of the popu-lations even within plumage groups appear to haveexperienced Among the perplexa subspecies inhabitingAmbae Maewo Pentecost and Ambrym some geneflow occurs Like the patterns in Z lateralis gene flowis asymmetrical with Ambrym in the south being theprimary source population Again explanations forasymmetrical gene flow across this small region cannotbe pinpointed to one factor but presumably are due toa combination of population density differences andlocal exctinctionndashrecolonization dynamics The esti-mates of gene flow from 2MOD serve to show thatconnectivity across Z flavifrons populations is very lowalthough actual estimates should be treated with cautionowing to the influence that mutation may have on genefrequencies (Ciofi et al 1999)

(c) Gene flow phenotypic divergence and factors

limiting avian divergence in Vanuatu

The rapid rate of lineage divergence found for Zosteropscombined with overall morphological conservatismwithin the family led Moyle et al (2009) to arguethat allopatry plays an important role in the generationof lineage diversity in this group At a population levelwe did not find evidence to suggest that waning geneflow was associated with increased phenotypic diver-gence among the Z lateralis populations Furtherphenotypic variation did not mirror the negativerelationship between genetic diversity and increasingisland isolation that would be expected if gene flowalso impacted levels of phenotypic diversity Petrenet al (2005) likewise found little evidence of a con-straining role of gene flow in Darwinrsquos finches If


phenotypic differences between the Zosterops popu-lations on different islands have a genetic basis (iethey are not the product of phenotypic plasticityalone) then the lack of relationship between neutralgenes and phenotype implies that selection is impor-tant in allopatric divergence Indeed morphologicalpatterns showed latitudinal trends with body sizeand relative wing length increasing at higher latitudewhich is consistent with local climate generating natu-ral selection either directly or indirectly via its effect onhabitat For this study it was not logistically feasible totest if variation between populations has a geneticbasis as translocation or common garden experimentsare required However a growing list of translocationexperiments in birds report that population differencesin morphology and life history have a genetic com-ponent (Price 2008) In addition numerous studiesreport significant additive genetic variation of pheno-typic traits within populations of passerines (Merila ampSheldon 2001) For Zosterops in particular significantheritable variation in morphology was detected withinthe Z lateralis on Heron Island Australia (Frentiuet al 2007) It is therefore plausible that morphologicaldifferences between populations have a large additivegenetic component

The Vanuatu archipelago is conspicuous for its lowlevel of avifaunal endemism compared with neigh-bouring archipelagos (Mayr amp Diamond 2001) andlack of adaptive radiations compared with spectacularexamples in honeycreepers from Hawaii (Fleischer ampMcIntosh 2001) and Darwinrsquos finches on theGalapagos (Grant amp Grant 2008) The ancestor ofDarwinrsquos finches is believed to have colonized theGalapagos approximately 23 Myr ago (Sato et al2001) thereafter radiating into some 13 speciesseveral of which can now coexist on any singleisland In comparison the ancestor or ancestors ofthe main Z flavifrons clade are estimated to have colo-nized Vanuatu sometime in the period 2ndash4 Myr ago(Phillimore et al 2008b Moyle et al 2009 Black2010) and has radiated into just two or perhapsthree allospecies The constraining effect of intra-archipelago gene flow is just one of the proposedreasons for the generally low levels of divergenceacross the archipelago (Diamond amp Marshall 1977)Lack of population persistence is also thought to beresponsible for limiting avian diversification (Mayr1965 Diamond amp Marshall 1977 Ricklefs ampBermingham 2007) and the higher numbers of ende-mic species on isolated islands have been attributed toless extinction and turnover (Diamond 1980 Price2008) In Zosterops the strong phylogenetic and popu-lation genetic structure among populations suggestthat variation in population persistence is not a keylimitation to divergence However the extent towhich this is true of the Vanuatu avifauna in generalremains an open question Other possible explanationsfor the low endemism and the absence of adaptiveradiations on Vanuatu include close proximity tohighly diverse source areas ensuring few nichesremain empty (Mayr amp Diamond 2001) and lack ofstrong ecological differences among islands (Mayr1954) For example Petren et al (2005) concludedthat adaptive divergence among the warbler finches


(Certhidea) in the Galapagos was limited by stabilizingselection across similar environments Adaptive radi-ations may be particularly restricted by the lack ofopportunity for sympatry owing to ecological or patho-gen incompatibility (Ricklefs amp Bermingham 2007)Discriminating which set of conditions place most con-straint on avian diversification in Vanuatu requires anaccumulation of genetic morphological and parasitedata from numerous species and a much greater under-standing of ecology differences among populations

5 CONCLUSIONSAn influence of migration on population genetic struc-ture appears to persist for very long time periods (up tohundreds or thousands of years) in an archipelagosetting The expected transition to a signature of adrift-mediated system as island populations becomeincreasingly isolated because of proposed reductionsin dispersal ability was found to occur only partiallyin an endemic species despite a long evolutionary his-tory on the archipelago (millions of years) Gene flowdynamics within the colonizing Zosterops species werecomplex and characterized by a high degree of asym-metrical migration between pairs of populations Nosingle explanation accounted for these asymmetrieshowever a combination of variation in populationsizes and population-level dispersal capabilities over-laid with the dominant pattern of north to southmigration in the archipelago may all contributeAmong the four populations of Z flavifrons that arelikely to exchange migrants sourcendashsink relationshipswere also evident Intra-archipelago phenotypic vari-ation was not obviously influenced by the degree ofgene flow or drift experienced by each populationSome weak latitudinal phenotypic patterns found inboth species suggested that climate-related variablescould partially influence phenotypic divergencevia selection however numerous other ecologicaldifferences among populations await quantification

We would like to thank E Bani D Kalfatak and T Tiwokfrom the Vanuatu Environment Unit and the people of theislands of Vanuatu for permission to conduct fieldwork inthis region We thank O Drew and members of WantocEnvironment Center Luganville particularly R Hillsand S Totterman for logistic support during fieldworkI Owens R Black O Boissier S Geigerand J Phillimore for assistance in the field D DawsonA Krupa and T Burke for laboratory advice andM Adams for access to bird skins at the Natural HistoryMuseum Tring We are grateful to I Owens R Black JWorthington Wilmer and M Ekins for discussions andorcomments on the manuscript This project was funded bya Natural Environment Research Council (NERC)postdoctoral fellowship to SMC with additional supportfrom the NERC-funded Sheffield Molecular GeneticsFacility ABP was funded by a NERC studentship theNERC Center for Population Biology and the NERC-funded Sheffield Molecular Genetics Facility

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speciation of skinks among archipelagos in the tropical

Pacific Ocean Evol Ecol 9 529ndash541 (doi101007BF01237834)


Barraclough T G amp Vogler A P 2000 Detecting thegeographical pattern of speciation from species-level phy-logenies Am Nat 155 419ndash434 (doi101086303332)

Berry R J 1998 Evolution of small mammals In Evolutionon islands (ed P R Grant) pp 35ndash50 Oxford UKOxford University Press

Black R A 2010 Phylogenetic and phenotypic divergenceof an insular radiation of birds PhD thesis Imperial Col-

lege LondonBollmer J L Whiteman N K Cannon M D Bednarz

J C De Vries T amp Parker P G 2005 Population gen-etics of the Galapagos hawk (Buteo galapagoensis) genetic

monomorphism within isolated populations Auk 1221210ndash1224 (doi1016420004-8038(2005)122[1210PGOTGH]20CO2)

Bolnick D I amp Fitzpatrick B M 2007 Sympatric speci-ation models and empirical evidence Ann Rev EcolEvol Syst 38 459ndash487 (doi101146annurevecolsys38091206095804)

Bregulla H 1992 Birds of Vanuatu Oswestry UK AnthonyNelson

Burney C W amp Brumfield R T 2009 Ecology predicts

levels of genetic differentiation in neotropical birds AmNat 174 358ndash368 (doi101086603613)

Butlin R K Galindo J amp Grahame J W 2008 Sympatricparapatric or allopatric the most important way to clas-sify speciation Phil Trans R Soc B 363 2997ndash3007

(doi101098rstb20080076)Ciofi C Beaumont M A Swingland I R amp Bruford

M W 1999 Genetic divergence and units for conserva-tion in the Komodo dragon Varanus komodoensisProc R Soc Lond B 266 2269ndash2274 (doi101098rspb19990918)

Clegg S M Degnan S M Moritz C Estoup AKikkawa J amp Owens I P F 2002a Microevolutionin island forms the roles of drift and directional

selection in morphological divergence of a passerinebird Evolution 56 2090ndash2099

Clegg S M Degnan S M Kikkawa J Moritz CEstoup A amp Owens I P F 2002b Genetic consequencesof sequential founding events by an island-colonizing

bird Proc Natl Acad Sci USA 99 8127ndash8132(doi101073pnas102583399)

Clegg S M Frentiu F D Kikkawa J Tavecchia G ampOwens I P F 2008 4000 years of phenotypic divergencein an island bird heterogeneity in strength of selection

over three microevolutionary timescales Evolution 622393ndash2410 (doi101111j1558-5646200800437x)

Cody M L amp Overton J McC 1996 Short-term evolutionof reduced dispersal in island plant populations J Ecol84 53ndash61

Coyne J A amp Orr H A 2004 Speciation MA USASinauer Associates

Coyne J A amp Price T D 2000 Little evidence for sympat-ric speciation in island birds Evolution 54 2166ndash2171

Degnan S M Robertson B C Clegg S M amp Moritz C1999 Microsatellite primers for the study of gene flow andmating systems in white-eyes (Zosterops) Mol Ecol 8157ndash158

Diamond J M 1980 Species turnover in island bird

communities Proc 17th Int Ornith Congress BerlinGermany 1978 Berlin Germany Deutsche Ornithologen-Gesellschaft

Diamond J M amp Marshall A G 1977 Distributionalecology of New Hebridean birds a species kaleidoscope

J Anim Ecol 46 703ndash727Diamond J M Gilpin M E amp Mayr E 1976 Speciesndash

distance relation for birds of the Solomon Archipelagoand the paradox of the great speciators Proc Natl AcadSci USA 73 2160ndash2164 (doi101073pnas7362160)


Dobzhansky T 1937 Genetics and the origin of speciesNew York NY Columbia University Press

Evanno G Regnaut S amp Goudet J 2005 Detecting the

number of clusters of individuals using the softwareSTRUCTURE a simulation study Mol Ecol 14 2611ndash2620 (doi101111j1365-294X200502553x)

Faubet P Waples R S amp Gaggiotti O E 2007 Evaluatingthe performance of a multilocus Bayesian method for the

estimation of migration rates Mol Ecol 16 1149ndash1166(doi101111j1365-294X200703218x)

Falush D Stephens M amp Pritchard J K 2003 Inferenceof population structure extensions to linked loci and

correlated allele frequencies Genetics 164 1567ndash1587Fleischer R C amp McIntosh C E 2001 Molecular systemat-

ics and biogeography of the Hawaiian avifauna StudAvian Biol-Ser 22 51ndash60

Frentiu F D Lange C L Burke T amp Owens I P F

2003 Isolation of microsatellite loci in the Capricornsilvereye Zosterops lateralis chlorocephalus (AvesZosteropidae) Mol Ecol Notes 3 462ndash464 (doi101046j1471-8286200300484x)

Frentiu F D Clegg S M Blows M W amp Owens I P F

2007 Large body size in an island dwelling bird a micro-evolutionary analysis J Evol Biol 20 639ndash649 (doi101111j1420-9101200601242x)

Goudet J 1995 FSTAT version 12 a computer program tocalculate F statistics J Hered 86 485ndash485

Goudet J 2001 FSTAT a program to estimate and test genediversities and fixation indices version 293 See wwwunilchizeasoftwaresfstathtml

Grant P R 1998 Patterns on islands and microevolution In

Evolution on islands (ed P R Grant) pp 1ndash17 OxfordUK Oxford University Press

Grant P R amp Grant B R 2008 How and why species multi-ply The radiation of Darwinrsquos finches Princeton NJPrinceton University Press

Griffiths R Double M C Orr K amp Dawson R J G1998 A DNA test to sex most birds Mol Ecol 71071ndash1075 (doi101046j1365-294x199800389x)

Hedrick P W 2005 A standardized genetic differentiationmeasure Evolution 59 1633ndash1638

Hinten G Harriss F Rossetto M amp Baverstock P R2003 Genetic variation and island biogeography micro-satellite and mitochondrial DNA variation in islandpopulations of the Australian bush rat Rattus fuscipesgreyii Conserv Gen 4 759ndash778 (doi101023

BCOGE000000611358749ac)Huber S K De Leon L F Hendry A P Bermingham

E amp Podos J 2007 Reproductive isolation of sympatricmorphs in a population of Darwinrsquos finches

Proc R Soc B 274 1709ndash1714 (doi101098rspb20070224)

Hutchison D W amp Templeton A R 1999 Correlation ofpairwise genetic and geographic distance measures infer-ring the relative influences of gene flow and drift on the

distribution of genetic variability Evolution 53 1898ndash1914 (doi1023072640449)

Jensen J L Bohonak A J amp Kelley S T 2005 Isolation bydistance web service BMC Genet 6 13 v 308 Seehttpibdwssdsuedu

Jordan M A amp Snell H L 2008 Historical fragmentationof islands and genetic drift in populations of Galapagoslava lizards (Microlophus albemarlensis complex) MolEcol 17 1224ndash1237 (doi101111j1365-294X200703658x)

Jordan M A Snell H L Snell H M amp Jordan W C2005 Phenotypic divergence despite high levels of geneflow in Galapagos lava lizards (Microlophus albemarlensis)Mol Ecol 14 859ndash867 (doi101111j1365-294X200502452x)


Kirchman J J amp Franklin J D 2007 Comparative phylo-geography and genetic structure of Vanuatu birdscontrol regions variation in a rail a dove and a passerine

Mol Phylogenet Evol 43 14ndash23 (doi101016jympev200612013)

Kuehn R Schroeder W Prichner F amp Rottmann O2003 Genetic diversity gene flow and drift in Bavarianred deer populations (Cervus elaphus) Conserv Gen 4

157ndash166 (doi101023A1023394707884)Lack D 1971 Ecological isolation in birds Cambridge MA

Harvard University PressLande R amp Barrowclough G F 1987 Effective population

size genetic variation and their use in population man-agement In Viable populations for conservation (ed M ESoule) pp 87ndash123 Cambridge UK CambridgeUniversity Press

Leberg P L 2002 Estimating allelic richness effects of

sample size and bottlenecks Mol Ecol 11 2445ndash2449(doi101046j1365-294X200201612x)

Leinonen T Cano J M Makinen H amp Merila J 2006Contrasting patterns of body shape and neutral geneticdivergence in marine and lake populations of threespine

sticklebacks J Evol Biol 19 1803ndash1812 (doi101111j1420-9101200601182x)

Lenormand T 2002 Gene flow and the limits to naturalselection Trends Ecol Evol 17 183ndash189

Loader C 2007 Locfit local regression likelihood and

density estimation R package version 15ndash4 See httpcranr-projectorgwebpackageslocfit

Lopez-Vaamonde C Wikstrom N Labandeira CGodfray H C J Goodman S J amp Cook J M 2006

Fossil-calibrated molecular phylogenies reveal that leaf-mining moths radiated millions of years after their hostplants J Evol Biol 19 1314ndash1326 (doi101111j1420-9101200501070x)

Mallick D I J 1975 Development of the New Hebrides

archipelago Phil Trans R Soc Lond B 275 277ndash285(doi101098rstb19750087)

Mayr E 1942 Systematics and the origin of species New YorkNY Columbia University Press

Mayr E 1945 Birds of the southwest Pacific New York NY

MacmillanMayr E 1954 Change of genetic environment and evo-

lution In Evolution as a process (ed E B Ford)pp 157ndash180 London UK Allen amp Unwin

Mayr E 1965 Avifauna turnover on islands Science 150

1587ndash1588 (doi101126science15037031587)Mayr E amp Diamond J 2001 The birds of northern Melanesia

speciation ecology and biogeography New York NYOxford University Press

McCall R A Nee S amp Harvey P H 1998 The role ofwing length in the evolution of avian flightlessness EvolEcol 12 569ndash580 (doi101023A1006508826501)

McNab B H 1994 Energy conservation and the evolutionof flightlessness in birds Am Nat 144 628ndash642

(doi101086285697)Mees G F 1969 A systematic review of the Indo-Australian

Zosteropidae Part III Zool Verh (Leiden) 102 1ndash390Meirmans P G 2006 Using the AMOVA framework to esti-

mate a standardized genetic differentiation measure

Evolution 60 2399ndash2402Merila J amp Sheldon B C 2001 Avian quantitative genetics

Curr Ornithol 16 179ndash255Moyle R G Filardi C E Smith C E amp Diamond J 2009

Explosive Pleistocene diversification and hemispheric

expansion of a lsquogreat speciatorrsquo Proc Natl Acad SciUSA 106 1863ndash1868 (doi101073pnas0809861105)

Nei M Maruyama T amp Chakraborty R 1975 The bottle-neck effect and genetic variability in populationsEvolution 29 1ndash10 (doi1023072407137)


Nicholls J A Double M C Rowell D M amp Magrath D2000 The evolution of cooperative and pair breeding inthornbills Acanthiza (Pardalotidae) J Avian Biol 31

165ndash176 (doi101034j1600-048X2000310208x)Nosil P 2008 Speciation with gene flow could be common

Mol Ecol 17 2103ndash2106 (doi101111j1365-294X200803715x)

Ogden R amp Thorpe R S 2002 Molecular evidence for

ecological speciation in tropical habitats Proc NatlAcad Sci USA 99 13 612ndash13 615 (doi101073pnas212248499)

Petren K 1998 Microsatellite primers from Geospiza fortisand cross-species amplification in Darwinrsquos finchesMol Ecol 7 1782ndash1784

Petren K Grant B R amp Grant P R 1999 A phylogeny ofDarwinrsquos finches based on microsatellite DNA lengthvariation Proc R Soc Lond B 266 321ndash329 (doi10

1098rspb19990641)Petren K Grant P R Grant B R amp Keller L F 2005

Comparative landscape genetics and the adaptive radi-ation of Darwinrsquos finches the role of peripheralisolation Mol Ecol 14 2843ndash2957

Phillimore A B 2006 The ecological basis of speciation anddivergence in birds PhD thesis Imperial CollegeLondon

Phillimore A B Orme C D L Thomas G HBlackburn T M Bennett P M Gaston K J amp

Owens I P F 2008a Sympatric speciation in birds israre insights from range data and simulations Am Nat171 646ndash657 (doi101086587074)

Phillimore A B Owens I P F Black R A Chittock J

Burke T amp Clegg S M 2008b Complex patterns of gen-etic and phenotypic divergence in an island bird and theconsequences for delimiting conservation units MolEcol 17 2839ndash2853 (doi101111j1365-294X200803794x)

Price T D 2008 Speciation in birds Greenwood Village CORoberts

Pritchard J K Stephens M amp Donnelly P 2000 Inferenceof population structure using multilocus genotype dataGenetics 155 945ndash959

R Development Core Team 2008 R a language and environ-ment for statistical computing Vienna Austria RFoundation for Statistical Computing

Raymond M amp Rousset F 1995 GENEPOP version 12population genetics software for exact tests and ecumeni-

cism J Hered 86 248ndash249Richardson D S Jury F L Dawson D A Salgueiro P

Komdeur J amp Burke T 2000 Fifty Seychelles warbler(Acrocephalus sechellensis) microsatellite loci polymorphic

in Sylviidae species and their cross-species amplificationin other passerine birds Mol Ecol 9 2226ndash2234

Ricklefs R E amp Bermingham E 1999 Taxon cycles in theLesser Antillean avifauna Ostrich 70 49ndash59

Ricklefs R E amp Bermingham E 2007 The causes of evo-

lutionary radiations in archipelagos passerine birds ofthe Lesser Antilles Am Nat 169 285ndash297 (doi101086510730)

Rousset F 1997 Genetic differentiation and estimation ofgene flow from F-statistics under isolation by distance

Genetics 145 1219ndash1228Rundell R J amp Price T D 2009 Adaptive radiation

nonadaptive radiation ecological speciation and non-ecological speciation Trends Ecol Evol 24 394ndash399(doi101016jtree200902007)

Rundle H D amp Nosil P 2005 Ecological speciation EcolLett 8 336ndash352 (doi101111j1461-0248200400715x)

Ryan P G Bloomer P Moloney C L Grant T J ampDelport W 2007 Ecological speciation in south Atlantic


island finches Science 315 1420ndash1423 (doi101126science1138829)

Sato A Tichy H OrsquohUigin C Grant P R Grant B R amp

Klein J 2001 On the origin of Darwinrsquos finches Mol BiolEvol 18 299ndash311

Schluter D 2009 Evidence for ecological speciation and itsalternative Science 323 737ndash741 (doi101126science1160006)

Skjelseth S Ringsby T H Tufto J Jensen H ampSaether B-E 2007 Dispersal of introduced house spar-rows Passer domesticus an experiment Proc R Soc B274 1763ndash1771 (doi101098rspb20070338)

Slatkin M 1987 Gene flow and the geographic structure ofnatural populations Science 236 787ndash792 (doi101126science3576198)

Slatkin M 1993 Isolation by distance in equilibrium andnon-equilibrium populations Evolution 47 264ndash279

(doi1023072410134)


Smith C E amp Filardi C E 2007 Patterns of molecular andmorphological variation in some Solomon Island landbirds Auk 124 479ndash493 (doi1016420004-

8038(2007)124[479POMAMV]20CO2)Smith A L amp Friesen V L 2007 Differentiation of sympat-

ric populations of the band-rumped storm-petrel in theGalapagos Islands an examination of genetics mor-phology and vocalizations Mol Ecol 16 1593ndash1603

(doi101111j1365-294X200603154x)Sorenson M D Sefc K M amp Payne R B 2003 Specia-

tion by host switch in brood parasitic indigobirdsNature 424 928ndash931 (doi101038nature01863)

Spitze K 1993 Population-structure in Daphnia obtusaquantitative genetic and allozymic variation Genetics135 367ndash374

Wilson G A amp Rannala B 2003 Bayesian inferenceof recent migration rates using multilocus genotypes

Genetics 163 1177ndash1191


relationships expected between the level of geographicisolation and genetic variation within and amongpopulations

Even in highly vagile organisms ongoing within-archipelago dispersal and gene flow can be affectedby behavioural or morphological changes that reducethe inclination or ability to effectively disperseacross water barriers (Diamond et al 1976 Mayr ampDiamond 2001) Distance-limited dispersal isexpected to generate a gene flow-mediated populationstructure evidenced by a negative relationship betweenneutral genetic diversity and geographic isolation(Jordan amp Snell 2008) the establishment ofisolation-by-distance patterns of genetic differentiation(Slatkin 1993 Hutchison amp Templeton 1999) and lowprobabilities of alleles being identical by descentwithin populations (Ciofi et al 1999) If geographicallyseparated populations become progressively moregenetically isolated over time gene flow is expectedto yield to drift as the predominant mechanism shap-ing population structure producing a positiverelationship between neutral genetic diversity andpopulation size (approximated by island area) butnot isolation (Lande amp Barrowclough 1987 egHinten et al 2003 Jordan amp Snell 2008) a breakdownof isolation by distance patterns (Hutchison ampTempleton 1999) and a high probability that alleleswithin a population are identical by descent (Ciofiet al 1999) These represent extremes in a spectrumand intermediate patterns may also arise as regionalpopulation structure shifts eg partial isolation-by-distance patterns (Hutchison amp Templeton 1999)and generation of geographic patterns for types ofvariation most sensitive to demographic change (egallelic diversity rather than heterozygosity Nei et al1975)

The importance of gene flow as a process retardingphenotypic divergence is expected to vary consider-ably depending on whether new mutations areuniversally favoured (Price 2008 Rundell amp Price2009 Schluter 2009) and on the strength of divergentselection (Lenormand 2002 Rundle amp Nosil 2005) Ifphenotypic divergence is influenced by new mutationsthat are favoured in all populations then a trickle ofgene flow may be sufficient to prevent phenotypicdivergence (Price 2008 Rundell amp Price 2009) Ifdivergent selection pressures exist but are over-whelmed by gene flow then this will also preventphenotypic divergence Under these two scenarios wewould predict greater phenotypic divergence amongdrift-mediated rather than among migration-mediation populations (Lenormand 2002) It is onlyif divergent selection is strong relative to levels ofgene flow that we would predict substantial phenotypicdivergence regardless of whether a populations geneticstructure is drift- or migration-mediated (eg diver-gence with gene flow scenarios Jordan et al 2005Nosil 2008)

Members of the avian family Zosteropidae arerenowned for their colonizing ability (Mayr 1945Mees 1969 Lack 1971) and it has recently beenrevealed that a South Pacific clade speciated remark-ably quickly (Moyle et al 2009) Because of themorphological conservatism noted in the family


Moyle et al (2009) suggested that rapid evolutionaryshifts in dispersal ability rather than adaptive ecologi-cal explanations were important for high speciationrates in the family At a population level thereforewaning gene flow among Zosterops populations ondifferent islands may be an important catalyst of diver-gence Divergent natural selection on phenotype hasbeen demonstrated in a number of island white-eyepopulations (Clegg et al 2002a 2008) but the facili-tating effects of shifts in dispersal ability and geneflow are not clear

While the distribution and morphological variationof southwest Pacific avifauna provided the foundationfor many early ideas about island speciation (Mayr1954 Mayr amp Diamond 2001) phylogeographic andpopulation genetic studies of the avifauna of thisregion are only now beginning to accumulate(Kirchman amp Franklin 2007 Smith amp Filardi 2007Phillimore et al 2008b) lagging behind other well-studied island groups such as the Galapagos (Petrenet al 1999) the Caribbean (see Ricklefs ampBermingham (2007) and references therein) andHawaii (Fleischer amp McIntosh 2001) In the Vanuatuarchipelago two Zosterops species the endemicZ flavifrons and the later colonizer Z lateralis have lar-gely coincident distributions but are at different stagesof divergence (Mees 1969 Phillimore 2006 Black2010) This situation allows us to contrast geneticand phenotypic patterns across the same landscapein related ecologically similar species that differ inage across islands We compare regional populationstructure in the two species examining the relativeimportance of gene flow and drift across thearchipelago and within-individual island populationsAgainst the neutral framework describing populationconnectivity and the geographical factors associatedwith declining gene flow we examine patterns ofmorphological variation to determine whether greaterisolation coincides with greater phenotypic divergence

2 MATERIAL AND METHODS(a) Study system

The Vanuatu archipelago (figure 1) was formedthrough cycles of volcanic growth and tectonic upliftthat began approximately 20ndash22 Myr ago althoughthe bulk of current land area was formed in the past05 Myr (Mallick 1975) The islands formed alongthree volcanic belts with the oldest islands on thewestern (Espiritu Santo and Malekula) and easternbelts (Maewo Pentecost and Efate) and the remaininggenerally younger islands on the central belt (Mallick1975) Assuming a relaxed clock model for substi-tution at mitochondrial protein-coding genes itappears that the archipelago was colonized somewherein the region of 2ndash4 Myr ago by Z flavifrons and lessthan 05 Myr ago by Z lateralis (Phillimore 2006Black 2010) suggesting that the ancestors of the ende-mic Z flavifrons colonized before many of the currentislands existed Zosterops flavifrons has previously beendivided into seven morphological subspecies whichfall into darker and yellow plumage colour groups(Mayr 1945 Mees 1969) Mitochondrial DNA(mtDNA) evidence has cast doubt on the monophyly

Vanua Lava

Gaua

MaewoAmbae

Pentecost

Malekula

Efate

Ambrym

Espiritu Santo

Epi

Erromango

Tanna

Aneityum

12

1

2

Australia

North






(b) Sampling







sample size

yearsnflav nlat







































(a)

(e)(d)

(c)(b)























20

25

30

35

alle

lic r

ichn

ess

03

04

05

06

HE

200 500 1000 2000

00

01

02

03

04

island area (km2)

mod

al F





















distance 2012+003 [065] 009+002 [072] 2011+013 [026]area 2002+002 [002] 001+001 [001] 004+015 [002]


area 001+005 [0] 001+003 [003] 2013+015 [027]











0

02

04

06

08F

ST(

1minusF

ST)

FST

(1minus

FST

)F

ST(

1minusF

ST)

(a)

(b)

(c)

0

02

04

06

08

15 20 25

0

02

04

06

08

log (distance)








distance 20003+0002 2134 02





distance 20001+0001 2174 08age 0002+0006 030 07
















































































































































































(doi1023072410134)










Vanua Lava

Gaua

MaewoAmbae

Pentecost

Malekula

Efate

Ambrym

Espiritu Santo

Epi

Erromango

Tanna

Aneityum

12

1

2

Australia

North






(b) Sampling







sample size

yearsnflav nlat







































(a)

(e)(d)

(c)(b)























20

25

30

35

alle

lic r

ichn

ess

03

04

05

06

HE

200 500 1000 2000

00

01

02

03

04

island area (km2)

mod

al F





















distance 2012+003 [065] 009+002 [072] 2011+013 [026]area 2002+002 [002] 001+001 [001] 004+015 [002]


area 001+005 [0] 001+003 [003] 2013+015 [027]











0

02

04

06

08F

ST(

1minusF

ST)

FST

(1minus

FST

)F

ST(

1minusF

ST)

(a)

(b)

(c)

0

02

04

06

08

15 20 25

0

02

04

06

08

log (distance)








distance 20003+0002 2134 02





distance 20001+0001 2174 08age 0002+0006 030 07
















































































































































































(doi1023072410134)















sample size

yearsnflav nlat







































(a)

(e)(d)

(c)(b)























20

25

30

35

alle

lic r

ichn

ess

03

04

05

06

HE

200 500 1000 2000

00

01

02

03

04

island area (km2)

mod

al F





















distance 2012+003 [065] 009+002 [072] 2011+013 [026]area 2002+002 [002] 001+001 [001] 004+015 [002]


area 001+005 [0] 001+003 [003] 2013+015 [027]











0

02

04

06

08F

ST(

1minusF

ST)

FST

(1minus

FST

)F

ST(

1minusF

ST)

(a)

(b)

(c)

0

02

04

06

08

15 20 25

0

02

04

06

08

log (distance)








distance 20003+0002 2134 02





distance 20001+0001 2174 08age 0002+0006 030 07
















































































































































































(doi1023072410134)






























(a)

(e)(d)

(c)(b)























20

25

30

35

alle

lic r

ichn

ess

03

04

05

06

HE

200 500 1000 2000

00

01

02

03

04

island area (km2)

mod

al F





















distance 2012+003 [065] 009+002 [072] 2011+013 [026]area 2002+002 [002] 001+001 [001] 004+015 [002]


area 001+005 [0] 001+003 [003] 2013+015 [027]











0

02

04

06

08F

ST(

1minusF

ST)

FST

(1minus

FST

)F

ST(

1minusF

ST)

(a)

(b)

(c)

0

02

04

06

08

15 20 25

0

02

04

06

08

log (distance)








distance 20003+0002 2134 02





distance 20001+0001 2174 08age 0002+0006 030 07
















































































































































































(doi1023072410134)























20

25

30

35

alle

lic r

ichn

ess

03

04

05

06

HE

200 500 1000 2000

00

01

02

03

04

island area (km2)

mod

al F





















distance 2012+003 [065] 009+002 [072] 2011+013 [026]area 2002+002 [002] 001+001 [001] 004+015 [002]


area 001+005 [0] 001+003 [003] 2013+015 [027]











0

02

04

06

08F

ST(

1minusF

ST)

FST

(1minus

FST

)F

ST(

1minusF

ST)

(a)

(b)

(c)

0

02

04

06

08

15 20 25

0

02

04

06

08

log (distance)








distance 20003+0002 2134 02





distance 20001+0001 2174 08age 0002+0006 030 07
















































































































































































(doi1023072410134)
















distance 2012+003 [065] 009+002 [072] 2011+013 [026]area 2002+002 [002] 001+001 [001] 004+015 [002]


area 001+005 [0] 001+003 [003] 2013+015 [027]











0

02

04

06

08F

ST(

1minusF

ST)

FST

(1minus

FST

)F

ST(

1minusF

ST)

(a)

(b)

(c)

0

02

04

06

08

15 20 25

0

02

04

06

08

log (distance)








distance 20003+0002 2134 02





distance 20001+0001 2174 08age 0002+0006 030 07
















































































































































































(doi1023072410134)










0

02

04

06

08F

ST(

1minusF

ST)

FST

(1minus

FST

)F

ST(

1minusF

ST)

(a)

(b)

(c)

0

02

04

06

08

15 20 25

0

02

04

06

08

log (distance)








distance 20003+0002 2134 02





distance 20001+0001 2174 08age 0002+0006 030 07
















































































































































































(doi1023072410134)














































































































































































(doi1023072410134)










The influence of gene flow and drift on genetic and phenotypic divergence in two species of...

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Transcript of The influence of gene flow and drift on genetic and phenotypic divergence in two species of...