Biological Journal of the Linnean Society (2001), 72: 333-343. With 6 figures doi: 10.1006/bij1.2000.0483, available online at httpj//www.idealibrary.com on ID a3 E b1c

Evidence for long-distance dispersal in a sedentary W , Gymnorhinu tibicen (Artamidae)

ANDREW M. BAKER1*, PETER B. MATHER' and JANE M. HUGHES'

'School of Natural Resource Sciences, Queensland University of Technology, Gardens Point Campus, Downloaded from https://academic.oup.com/biolinnean/article/72/2/333/2638759 by guest on 30 September 2021 GPO Box 2434, Brisbane, Queensland, 4001, 'Australian School of Environmental Studies, Griffth University, Nathan, Queensland, 4111, Australia

Received 18 February 2000; accepted for publication 9 August 2000

Australian (Gymnorhina tibicen) are group-living found across much of mainland Australia. Adults commonly remain in a breeding territory until death. Young of the year either remain on the natal (birth) site or are forced by their parents to disperse. Observational studies in south-eastern Australia suggest that most dispersing juveniles settle within 7km of their natal territory. Therefore, despite potential for considerable gene flow (via flight), social organization predisposes magpies towards local population structuring. In this study, we measured genetic variation at both nuclear (allozyme) and mitochondrial loci and found evidence of substantial gene flow over very large distances (up to 1599 km). Thus, some juvenile magpies may disperse much greater distances than was previously thought. For mtDNA, geographic and genetic distance were strongly correlated, consistent with a pattern of isolation by distance. Therefore, although female gene flow is substantial it is apparently geographically restricted over large distances, in approximately a stepping-stone fashion. We conclude that a strong relationship between gene flow and geographic distance can develop even over large distances if populations have experienced no major historical disturbances to gene flow. 0 2001 The Linnean Society of London

ADDITIONAL KEYWORDS: Australian - - natal site - mitochondrial DNA - control-region - allozymes - gene flow - isolation by distance - geographic distance.

INTRODUCTION on a single genetic marker (Moritz, 1994); since markers can evolve at different rates they may indicate Evolutionary biologists have been able to assess the different rates of dispersal. geographic scale of dispersal from both a genetic and When used together, observational and genetic data observational perspective for only a handful of avian have the potential to provide more accurate in- species (see Stangel, Lennartz & Smith, 1992; Ed- formation about a species' dispersal behaviour than wards, 1993; Bell, 1992 in Slatkin, 1993; Kidd & can either method in isolation (Moritz, 1994; Peacock, Friesen, 1998; da Silva & Granadeiro, 1999; McDonald 1997). In spite of this, interpretation of such combined et al., 1999). Such studies are rare, both because ob- data sets is made difficult for many species because servational data on dispersal typically take years to the observed patterns of dispersal are at odds with compile and because it often proves difficult to retrieve inferences about dispersal based on the genetic data. sufficient genetic samples of the species under study In birds, a commonly emerging scenario appears to be to examine even superficially the relationship between limited observed dispersal in parallel with genetic gene flow and geographic proximity. Moreover, just as evidence of large-scale gene flow (e.g. Edwards, 1993; observational studies of dispersal have been criticised Kvist et al., 1998; da Silva & Granadeiro, 1999). because they may not detect the settling location of Observational data suggests that gene flow is likely all dispersers due to a limited study area (Koenig, Van to be limited in the (Gymnorhina Vuren & Hooge, 1996), genetic studies may be criticised tibicen Latham 1802), however, the population genetic for making inferences about dispersal behaviour based structure of this species is unknown. Previous studies of G. tibicen populations in south-eastern Australia suggest that juveniles will either remain on the natal * Corresponding author. E-mail: kingoftrees8hotmail.com site (Carrick, 1972; J. Hughes, unpublished data) or 333 0024-4066/01/020333 + 11 $35.00/0 @ 2001 The Linnean Society of London 334 A. M. BAKER ET AL. disperse very short distances (e.g. <1 mile, Carrick, 1963b; 1972; <7 km, J. Hughes, unpublished data) and once individuals have sequestered a breeding territory they are site tenacious (Carrick, 1963a). In this paper, we test the hypothesis that for the Australian magpie, the sedentary nature of adults and low dispersal tendency of juveniles have combined to restrict gene flow across large geographic distances in eastern Australia. If dispersing magpies always only move small distances before settling, then we would

expect distant populations to show genetic divergence, Downloaded from https://academic.oup.com/biolinnean/article/72/2/333/2638759 by guest on 30 September 2021 because during isolation such populations would be prone to the effects of genetic drift and natural se- lection. On the other hand, if magpies disperse large distances (even occasionally) we may expect limited genetic divergence among distant populations, due to the diffusive flow of genes which would impede local adaptation and reduce stochastic (random) variation (Barton, 1992). Specifically, in this study we will ex- Figure 1. Location of study sites. Region 1. 1. Mary- amine the relationship between patterns of genetic borough (N= 54); 2. Toowoomba (N= 55); 3. Brisbane (N= variation and geographic proximity in an attempt to 50); 4. Grafton (N=51). Region 2. 5. Dubbo (N=51); 6. understand better the microevolutionary processes Orange (N=52); 7. Cessnock (N=50); 8. Goulburn (N= which have shaped present-day population genetic 50). Region 3. 9. Ouyen (N=51); 10. Horsham (N=50); structure in this species. The utilization of two genetic 11. Seymour (N=50); 12. Phillip Island (N=50). markers (allozymes and the mitochondrial control- region) will permit a comparison between estimates of gene flow and provide potentially greater resolution and territorial group size in different regions (Baker, of magpie dispersal patterns. Further, because the Mather & Hughes, 2000). Although Australian mag- mitochondrial control-region is non-coding, evolves pies exhibit a range of patterns (backcolour rapidly and is maternally inherited (Birky, Maruyama morphs) in different regions across their natural dis- & Fuerst, 1983), historic and geographic effects on tribution, backcolour variation was not considered here magpie population structure at both local and regional because it is not relevant to the specific questions being levels should be more easily recognized (Bermingham addressed. The relationship between gene flow and & Moritz, 1998). back colour variation in G. tibicen is being investigated To determine whether geographic patterns of dis- in a parallel study. persal in the genetic data are consistent with direct It is legitimate to combine all sampled populations observations of dispersal, we draw on eight years of in the analysis to determine the geographic scale of our own observational data from magpie populations gene flow, because the nearest neighbour straight-line in eastern Australia, in addition to observational data distances between population pairs in adjacent regions from other eastern populations already reported in the (populations 4 and 7379km and populations 8 and literature. 11 483 km) are the same order of magnitude as the nearest neighbour straight-line distances between METHODS population pairs within each region (populations 1-4, range 106-250 km; populations 5-8, range SAMPLING 124-216 km; populations 9-12, range 160-183 km). Twelve populations of magpies spanning ap- All populations were sampled within 500 km of the proximately 1599 km (straight-line distance) were coastline because populations farther inland have sampled from eastern Australia between March 1994 lower densities, and individuals are less accustomed and November 1996 (Fig. 1). Four populations were to humans, making them more difficult to trap. sampled in each of three geographic regions. Popu- We sampled approximately 50 magpies per popu- lations within regions were situated at least 100 km lation (see Fig. 1) and no more than two individuals apart, so that individuals were unlikely to be able per territory (where possible only adults were taken to disperse directly between localities. This sampling to avoid potentially biasing population allele fre- design enabled us to examine (1) the relationship quencies by over-representation of individual lineages). between gene flow and geographic proximity (the pres- Wild magpies were entrapped using a live decoy housed ent study) and (2)the relationship between gene flow in a cage within a wire trap. We took a blood sample DISPERSAL IN AUSTRALIAN MAGPIES 335

(approx. 200 pl) from each magpie by clipping a single for 5 min, (2) 94°C for 1 min, (3) 55°C for 1min, (4) toenail. After sampling, individuals were released at 72°C for 1min, with steps 24repeated 40 times, (5) the site of capture. 72°C for 10min. PCR products were stored at -80°C. We used the DIAGEN horizontal TGGE system (DI- &LoZYMES AGEN GmbH) to screen amplified PCR products for variation. A single magpie sample was electrophoresed 36 enzyme loci were screened initially to identify poly- across a perpendicular gradient of 20-60"C to deter- morphic loci, using cellulose acetate gel electrophoresis mine the melting temperature of the 590 bp control- (Titan I11 Zip Zone Cellulose Acetate Plates, Helena region fragment (42"C), the migration rate (1.73 cm/h) Laboratories). Six polymorphic enzyme loci (Aspartate and the optimum electrophoretic running time for aminotransferase (Aat;E.C. 2.6.1.1), (p esterase (PEst;

subsequent parallel TGGE (3h 55 min). Heteroduplex Downloaded from https://academic.oup.com/biolinnean/article/72/2/333/2638759 by guest on 30 September 2021 E.C. 3.1.1.1), Glucose-phosphateisomerase (Gpi;E.C. analysis (TGGE-HA) and subsequent parallel TGGE 5.1.3.9), Isocitrate dehydrogenase (Idh;E.C. 1.1.1.42), analysis were performed according to the specifications Mannose-phosphate isomerase (Mpi;E.C. 5.3.1.Q outlined in the TGGE handbook (1993). Individuals Phosphoglucomutase (Pgm; E.C. 2.7.5.1) and 6-phos- possessing a unique banding pattern were each as- phogluconate dehydrogenase (6pgd; E.C. 1.1.1.44)) signed a distinguishing haplotype. were identified in blood that could be scored with PCR products from individuals representing each confidence (a single locus coded for each enzyme). unique haplotype were sequenced using an Applied Electrophoresis and staining procedures were per- Biosystems 3738 automated DNA sequencer. Re- formed as outlined in Richardson, Baverstock & Adams sulting sequences were aligned using the ClustalW (1986). program in the Australian National Genomic In- formation Service (ANGIS) computer package. Rep- MIT~CHONDRIALDNA licate sequencing of each haplotype was performed to Total genomic DNA was extracted using 50 p1 of whole confirm that individuals scored by gel as the same blood from each sample. After 10 minutes cen- haplotype possessed identical DNA sequence. Each trifugation, the pellet was resuspended in 950 pl ex- sample was sequenced in both directions with over- traction buffer (200mM Tris pH8.0; 250mM NaC1; lapping sections to ensure DNA-strand homology. 25mM EDTA 0.5% SDS). 112 pl of 1@/0nonidet P-40 was added and samples were left undisturbed at room ANALYSES temperature for 30 min. Samples were then immersed We conducted chi-square tests (with Yates' correction) in a 70°C water bath for 5min and centrifuged for to test for conformation of allozyme data to Hardy- 15min. Proteins and lipids were removed by phenol Weinberg equilibrium. To obtain an error rate SI, Ury's extraction, then a series of pheno1:chloroform:isoamyl- (1976) Dunn-Sidak Bonferroni technique was adopted. alcohol (25:24:1) and ch1oroform:isoamyl-alcohol Each test was conducted at the critical probability of (24:l) extractions. DNA was precipitated with 100 p1 a' = 1- (1- a)vk where lz is the number of intended of 3 M sodium acetate and 400 p1 isopropanol, washed tests. Wright's (1951) FSTwas calculated for each locus. with 70% ethanol, resuspended in 40 p1 TE buffer and This statistic uses departures from levels of het- stored at - 80°C. erozygosity expected under panmixia to partition sub- We designed two specific primers to generate a 590 bp division among populations (Wright, 1978). In defining control-region fragment for use in Temperature Gra- this value, Wright reported that an FSTof 1 indicates dient Gel Electrophoresis (TGGE). Primer 1(sequence fixation of alternate alleles in subpopulations and an 5' GGA ACC AGA GGC GCA AAA GAG C 3') was FSTof 0 indicates that the same alleles occur in equal located in the D-Loop Domain I1 and primer 2 frequencies. A chi-square test was used to test for (sequence 5' CAA GAT CTG TGG ClT GAA AAG CC significance using the formula: x2 = 2NFs,(a - l),df= 3') was located in the tRNAGlu gene adjacent to the @- l)(a- 1) where: N= total number of individuals, D-Loop. The Polymerase Chain Reaction (PCR) was a =number of alleles, p = number of populations. For performed in a 50 p1 total volume. Reactions contained: pooled allozyme loci, population subdivision estimates 16.75p1 ddJ&O, 5 pl Perkin Elmer 1OX Buffer 11, 4 p1 were derived by analysis of molecular variance Perkin Elmer 25 mM MgC12, 16 pl Promega 1OmM (AMOVA) (Excoffier, Smouse & Quattro, 1992) using Deoxynucleoside triphosphates (2.5 mM each), 3 p1 an analogue of FST weighted over loci. The absolute 25 pM Primer 1,3p125 pMPrimer 2,1.25 Units Perkin number of individuals exchanged between populations Elmer Amplitaq@DNA Polymerase, 200 ng DNA tem- per generation was estimated by N,m,, where: Name= plate and 40pl light mineral oil. A negative control (1- FsT)/4Fs3 assuming neutral alleles under an island solution (without DNA template) was included with model (Wright, 1951). Under this model, a value of each set of reactions. Temperature cycling was con- N,m>l will theoretically prevent populations diverging ducted in a Hybaid Omnigene Thermal Cycler: (1)95°C due to random genetic drift alone (Slatkin, 1987). 336 A. M. BAKER ET AL.

Because most evolutionary analyses based on mo- significance of associations between gene flow and lecular data assume that variation is neutral to se- geographical distance was tested using Mantel’s (1967) lection, we conducted Tajima’s (1989) test on test with 1000 random iterations. mitochondrial data for pooled and individual popu- Neighbourhood size can be estimated in the case lations, prior to any analysis. The test compares two of isolation by distance. The concept of genetically estimators of the population parameter 8. One is the estimated neighbourhood size is based on the fact that mean number of pairwise differences between haplo- genetic differentiation can only accumulate beyond types and the other is based on the number of poly- the neighbourhood area, such that genetic differences morphic sites in the sample. Theoretically, under the within the neighbourhood should not be a function of infinite-site model (Slatkin, 1985) both estimators distance, but beyond the neighbourhood they should should be equal. However, differences can arise due to rise as a function of distance (Johnson & Black, 1995). Downloaded from https://academic.oup.com/biolinnean/article/72/2/333/2638759 by guest on 30 September 2021 the effects of selection, changes in population size, Following the method outline by Slatkin (1993), we or among-site mutation rate heterogeneity (Tajima, used the intercept of the regression of M on distance 1989). Population subdivision estimates were derived to provide a rough estimate of Wright’s (1946) neigh- from mtDNA data using @statistics assessed by bourhood size, or the number of individuals in an area AMOVA under permutational procedures (Excoffier et of panmixis. al., 1992). Estimates of Nemf (effective female gene flow) were calculated using the relationship: Nemf= l/2( l/QST- 1) (Hudson, Slatkin & Maddison, 1992). RESULTS According to Wright (1943), isolation by distance will occur within continuously distributed populations POPULATION GENETIC STRUCTURE when propagules move only between proximate popu- After Bonferroni correction, allele frequencies at the lations. Kimura 8z Weiss (1964) predicted that a similar six polymorphic allozyme loci in all populations con- pattern of spatial differentiation will arise between formed to Hardy-Weinberg equilibrium. Allelic vari- discrete populations when only immediately adjacent ation was largest at the Est-l locus, although none of populations exchange genes (the stepping stone model). the enzyme loci screened were highly polymorphic In this scenario, one would expect the frequency of (allele frequencies are available from the authors on alleles to change gradually across two-dimensional request). All estimates of population subdivision for space and any areas where there are rapid changes in individual loci as well as pooled loci were significantly allele frequency may be viewed as barriers to effective different from zero, however the estimate for pooled dispersal (F’iertney et al., 1998). To test for isolation loci (FsT=0.042) implied only low levels of genetic by distance we employed two different methods. First, structuring among the sampled populations (Table 1). populations were ordinated in a two-dimensionalspace No significant deviation from neutrality was evident by metric multidimensional scaling as described by in the mtDNA data (Table 2). This suggests that the Lessa (1990). The major strength of this procedure is mitochondrial segment analysed was not influenced that it can detect nonhierarchical aspects of geographic by selection or linked to other genes. Total nucleotide variation without precluding the uncovering of hier- diversity was similar to population nucleotide di- archies and without assuming linearity (a major draw- versities (Table 2). Haplotypes two and four were back of both principal component and principal shared among all sampled populations; haplotypes 2, coordinate analyses; Lessa, 1990). Second, we used the 3, 4 and 6 were found in 85.0% of sampled individuals regression approach advocated by Slatkin (1993) which (haplotype frequencies are available from the authors involves linear regression of log-transformed estimates on request). These data reflect the low degree of haplo- of gene flow (M,where M is an estimator of gene type endemism among sampled populations. From a flow between two subpopulations such that M=Nm total of 614 magpies assayed, 16 mitochondria1 haplo- [calculated as described above], N, is the effective types (Genbank accession numbers AF 222961-AF population size and m is the proportion of migrants in 222976) were identified from the 590bp control-region a local subpopulation; Slatkin & Maddison, 1990) and fragment. Sequences encompassed 54bp of the glu- straight-line geographic distance between all pairwise tamic acid tRNA, all of control-region Domain I combinations of populations. A negative relationship (375 bp), and 161bp of control-region Domain 11. 13 indicates isolation by distance and the steepness of mutational sites were evident (Table 3); one was located the slope indicates how rapidly gene flow declines with in the glutamic acid tRNA, 10 in control-regionDomain distance; in a one-dimensional array of stepping-stones I and two in control-region Domain 11. The ratio of (discrete adjacent populations) the expected slope of transitions (THC, GwA) to transversions (T-A, T-G, the regression is -1.0 and under a two-dimensional C-G, CetA) was 12:l and no insertions or deletions stepping-stone model the expected slope is ap- were observed. Compared to the reference haplotype proximately - 0.5 (Slatkin, 1993). Statistical (Hl), the most similar haplotype differed at a single DISPERSAL IN AUSTRALIAN MAGPIES 337

Table 1. Subdivision analyses across all populations for allozymes and mtDNA

Locus

~~ f3-esterase (Est-1) 0.054*** Phosphoglucomutase (Pgrn-1) 0.018** Glucose-phosphate isomerase (Gpi-1) 0.049*** 6-phosphogluconate dehydrogenase (6pgd-1) 0.061*** Mannose-phosphateisomerase (Mpi-1) 0.021*** Isocitrate dehydrogenase (Idh-1) 0.015* Mean

0.042*** 5.65 Downloaded from https://academic.oup.com/biolinnean/article/72/2/333/2638759 by guest on 30 September 2021 MtDNA 0.134*** 3.24#

#N,m estimate for mtDNA is the number of effective female migrants; *P<0.05, **P

Table 2. Diversity estimates and Neutrality tests

Populations analysed Sample Haplotype Haplotype Nucleotide diversity Tajima’s size number diversity (h) (4* SD D* All populations 614 16 0.8113 0.003434 +0.002139 0.1986 (NS) Brisbane 50 5 0.6587 0.003106 +0.002015 0.0712 (NS) Grafton 51 6 0.7424 0.005081 0.002993 1.8646 (NS) Maryborough 54 6 0.7448 0.003085 +0.002002 1.5720 (NS) Toowoomba 55 6 0.7403 0.002598 +0.001755 0.0047 (NS) Cessnock 50 4 0.7143 0.002283 +0.001597 1.1533 (NS) Dubbo 51 6 0.7113 0.003105 If: 0.002014 0.4681 (NS) Goulburn 50 6 0.8269 0.003489 0.002207 0.8397 (NS) Orange 52 7 0.7994 0.004518 f0.002715 0.9407 (NS) Horsham 50 6 0.7086 0.002297 +0.001604 -0.6584 (NS) Ouyen 51 7 0.7371 0.002449 +0.001681 -0.5097 (NS) Phillip Island 50 5 0.6473 0.001516 +0.001193 -0.4810 (NS) Seymour 50 5 0.7478 0.002384 0.001649 1.3047 WS)

* NS indicates that Tajima’s D value falls within 95% Confidence Limits. nucleotide site (0.17°/o) and the most divergent haplo- in the MDS to northern populations such as Mary- types differed at 6 nucleotide sites (1.02%) (Table 3). borough and Toowoomba, than they were to geo- The estimate of total population subdivision (FST = graphically less distant populations such as Cessnock 0.134) implied moderate levels of genetic structuring and Goulburn). In the regression (equation Log [&I = (Table 1). 1.47 -0.19*Log [distance]), the slope was shallow and For allozymes, only 44% of the estimates of painvise only approximately 2% of variation in M could be population subdivision were significantly different explained by geographical distance among populations from zero, compared to 88% for mtDNA data (Table (Table 6). 4). In contrast, for mtDNA the MDS (Fig. 4), regression of log(&) on log(distance) (Fig. 5) and Mantel test (Table 5) revealed a correlation between gene flow ISOLATION BY DlSTANCE and geographic distance, consistent with a pattern of For allozymes, the MDS (Fig. a), regression of log(^) isolation by distance (Slatkin, 1993). In the MDS plot, on log(distance) (Fig. 3) and Mantel test (Table 5) over large geographic distances the positioning of the revealed no correlation between gene flow and geo- sampled populations was generally consistent with graphic distance. In the MDS plot, the position of their geographical proximity (one notable exception populations was generally unrelated to their geo- was the Ouyen population which was positioned closer graphical location (e.g. southern populations such as to Cessnock and Toowoomba than it was to Phillip Phillip Island and Ouyen were more closely positioned Island and Horsham). Over smaller spatial scales, 338 A. M. BAKER ET AL.

Table 3. Polymorphic sites (numbered 1-13) in magpie control-region sequences. Relative sequence position is indicated in parentheses, beginning at 1,54 bases into the glumatic acid tRNA. A blank cell indicates conformity to the reference haplotype (ref')

1 2 3 4 5 6 7 8 9 10 11 12 13 Number of Haplotype (45) (237) (240) (249) (252) (253) (254) (283) (294) (338) (341) (443) (446) bases divergent

1 (ref) C ctct a C a ct C a a - 2 tg g g4 3 t t tg g g6 4 tg g 3

5 t tg g 4 Downloaded from https://academic.oup.com/biolinnean/article/72/2/333/2638759 by guest on 30 September 2021 6 tg a g 4 7 t g g3 8 t gt g g5 9 gtg a g 5 10 g 1 11 tc tg g g6 12 t tg g g5 13 t g g g4 14 g g 2 15 tc tg a g 6 16 tg C a g 5

Table 4. Painvise population subdivision significance tests for allozymes (above diagonal) and mtDNA (below diagonal)

Population 1 2 3 4 5 6 7 8 9 10 11 12 1. Maryborough - NS * * NS * * * NS NS NS NS 2. Toowoomba NS - * * NS * * * NS * * NS 3. Brisbane NS * - * * * * * * * * * 4. Grafton * * * - NS NS NS * * NS * NS 5. Dubbo * * * * - NS NS * NS NS NS NS 6. Orange * * * * NS - NS NS * NS NS NS 7. Cessnock * NS * * * * - NS * NS NS NS 8. Goulburn * * * * NS NS * - * NS NS * 9. Ouyen * * * * * * * * - NS NS NS 10. Horsham * * * * * * * * * - NS NS 11. Seymour * * * * * * * NS * NS - NS 12. Phillip Island * * * * * * * * * * * -

NS, not significant; *P<0.05.

populations were not always arranged in a pattern equilibrium (Slatkin, 1993; Hellberg, 1995). Mantel consistent with their geographical proximity to nearest and regression analyses were also performed on the neighbours (e.g. Grafton was closer to Maryborough eight northernmost populations and the eight south- than to Brisbane; Goulburn was much closer to Dubbo ernmost populations, to determine if patterns of isol- than to Cessnock; Ouyen was closer to Seymour than ation by distance could be detected over smaller to Horsham). In the regression (equation log[&]= geographic distances (approx. 1000 km). The equations 3.01 -0.85*log[distance]), the slope was steep (-0.85) of the regressions (log(fi) = 3.15 - 0.93*log(distance) and approximately 40% of variation in could be and log(M) = 2.22 - 0.51 *log(distance), respectively; explained by geographical distance among populations Table 6) and Mantel tests (Table 5) were consistent (Table 6). The 95% confidence interval around the with a pattern of isolation by distance among both sets regression coefficient ranged from -0.59 to -1.11, of populations. Although the stepping-stone pattern of less than -0.5, yet including -1.0 which is the the- gene flow appears stronger for the northern group than oretically expected slope of a linear stepping-stone at the southern group (see Tables 5 and 6), the slopes of DISPERSAL IN AUSTRALIAN MAGPIES 339

In each case (not shown), the pattern of isolation by 3(Brisbane) distance remained clear. The intercept of the regression for the whole mtDNA dataset (log(fi) = 3.01) equated to a neighbourhood size of 103.01= 1023 individuals, 1.0 2 (Toowoomba) which is consistant with the evidence of considerable gene flow in this species. 0.5 5 (Dubbo)g (OuYen) r lfhlaryborough) It should be noted that our estimates of gene flow 4 (Grafton) 0 12 (Phillip Island) assume both (1) an island model (Wright, 1969) for 0 10 (Horsham) which dispersal is theoretically equal between any pair -0.5 11 (Seymour) of populations and (2) genetic equilibrium between 7 (Cessnock) -1.0 06 (Orange) populations. Because our sampled populations more Downloaded from https://academic.oup.com/biolinnean/article/72/2/333/2638759 by guest on 30 September 2021 closely fit a stepping-stone model (Kimura & Weiss, -1.5 ~ 8 (Goulburn) 1964) the estimates of gene flow may be lower than I 1 I I I I I real values.

DISCUSSION

POPULATION GENETIC STRUCTURE AND SPATIAL PAmERNS OF GENE FLOW A number of aspects of magpie life history may strongly influence population genetic structure. First, magpie populations are continuous in eastern Australia (Car- rick, 1972; pers. observ.). Second, magpies are site- tenacious after sequestering a breeding territory (Car- rick, 1963a). Third, many juveniles disperse (before their parents' next breeding effort) into neighbouring flocks for variable periods of time before establishing their own territories (Carrick, 1972; J. Hughes, un- published data). Since all magpie flocks are non-breed- ing groups, dispersers are unable to contribute to the local gene pool until they later sequester a territory, which mark-recapture data suggests is likely to be -0.5 ' I I I close to the natal site (4mile, Carrick, 196313; 1972; 1.5 2.0 2.5 3.0 3.5 <7km, J. Hughes, unpublished data). Fourth, fierce log(distance1 competition for territories (Carrick, 1963a; pers. ob- Figure 3. Ordinary least-squaresregression of log,, gene serv.) may greatly minimize the chance of survival flow (&I,generated from allozyme FSTvalues) on log,, for prospective long-distance dispersers, making the distance (km). transition to a nearby flock (where food and roosting sites are accessible) a more viable option. We would therefore expect limited gene flow to result the regressions were not significantly different (Ana- in the development of genetic structuring among local lysis of Covariance, Fl,52= 1.59; P=0.213). We removed magpie populations, as genes are confined over time each population sequentially from the regression ana- to limited areas. However, we found that magpie popu- lysis to determine if the position of individual popu- lations separated by up to 1599km exhibited only low lations could explain the steep negative slope observed. to moderate genetic structuring, implying substantial

Table 5. Mantel test statistics

Populations analysed g Z r P

Allozymes-all populations -0.55 324.72 -0.064 0.299 mtDNA-all populations -5.17 223.51 -0.621 0.002 mtDNA-northern 8 populations -3.31 101.10 -0.665 0.001 mtDNA-southern 8 populations -2.27 127.40 -0.356 0.011

g, Standard normal variate; Z, Mantel statistic; r, Product-moment correlation. 340 A. M. BAKER ET AL.

Table 6. Linear Fkgression statistics

Populations analysed R square Slope 1SE P Allozymes-all populations 0.017 -0.193 10.189 0.311 mtDNA-all populations 0.402 -0.850+0.131 0.000 mtDNA-northern 8 populations 0.442 - 0.927 + 0.204 0.000 mtDNA-southern 8 populations 0.127 -0.51010.263 0.063

20' a study by Edwards (1993) on Australian grey-crowned 3 (Brisbane) Downloaded from https://academic.oup.com/biolinnean/article/72/2/333/2638759 by guest on 30 September 2021 babblers (Pomatostomis temporalis) revealed disparity between the scale of the observed limited dispersal 1oL4 1 (Maryborough) patterns and estimates of gene flow extrapolated from 0 4 (Grafton) I 2 (Toowoomba) mitochondrial control-region sequence variation. Sim- 05b 7 (Cessnock) ilarly, Kvist et al. (1998) examined control-region se- quences of willow tits (Parus montanus borealis) and 00' 9 (OuYen) 5 (Dubbo) - revealed high gene flow between two geographically A *6(0ran e) -051 8 (Godburn5 distant populations. The principle cause for such dif- 011 (Seymour) ferences between direct and indirect estimates of gene -101 12 (Phillip Island) flow is that dispersal is highly variable in time; direct studies probably miss rare dispersal events. Thus, -1.5 1 0 10 (Horsham) 1 genes may often move greater distances than observed I 1 I u individual dispersal distances suggest, and long-dis- -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 tance dispersers (even if rare in occurrence) can mark- I1 edly shape population genetic structure (see Figure 4. Multidimensional scaling plot of mtDNA QsT Barrowclough, 1978; Coyne et al., 1982; Slatkin, 1985; values plotted in two dimensions (stress = 0.054). Payne, 1990; Waser & Elliott, 1991; Ibrahim, Nichols & Hewitt, 1996). In the present study, population subdivision es- timates based on allozyme data revealed low levels of population structuring (FST= 0.042), whereas es- timates based on mtDNA control-region sequences in- dicated moderate levels of structuring (FST= 0.134). Also, in analyses of geographic spatial structuring, isolation by distance was detected at the mitochondrial locus, but not at allozyme loci. These discrepancies between the two markers may be accounted for by any or all of the following: (1) a higher rate of mutation in the mitochondrial control-region compared to nuclear DNA (allozymes) in birds (see also Zink, 1991; Merila, Bjorkland & Baker, 1997), (2) differences in effective

I I population size (higher rates of drift are expected for , mitochondrial variants because effective population -0.5 ' I 1.5 2.0 2.5 3.0 3.5 size is fourfold lower, Birky, Fuerst & Maruyama, log(distance) 1989), (3) stochasticity (genetic drift may not have acted as strongly at allozyme loci), and (4) male-biased Figure 5. Ordinary least-squares regression of log,, ma- dispersal (Veltman and Carrick [1990] observed that ternal gene flow @, generated from mtDNA QST values) male magpies in Canberra (south-eastern Australia) on log,, distance (km). dispersed at a significantly younger age than females. Thus, higher levels of differentiation in mtDNA com- pared to allozymes in the present study may be due to gene flow, over much larger distances than ob- preferential movement of males, which do not transmit servational data suggests. Such discrepancies between mtDNA to offspring). direct and indirect estimates of dispersal have been Mantel analyses, multidimensional scaling and re- reported in other sedentary avian species. For example, gression plots of mitochondrial data all revealed a clear DISPERSAL IN AUSTRALIAN MAGPIES 341 signature of isolation by distance. We also constructed 60 000 UPGMA (Sneath & Sokal, 1973) and Fitch-Margoliash 50000 p-9 (Fitch & Margoliash, 1967) population trees (not 3 40 000 - shown) from the mtDNA data and found concordant 8 primary clades (Clade 1: Brisbane, Maryborough, 5 30 000 - Toowoomba, Grafton, Cessnock, Ouyen and Clade 2: % g 20 000 - Dubbo, Orange, Goulburn, Horsham, Seymour, Phillip Island) which broadly matched the population clusters 10 000 - in the MDS plot (Fig. 4). Secondary clades in the n population trees were not concordant however, im- " o 123 4 5 6 7 8 8101112 Number of painvise differences plying that populations were not strongly geo- Downloaded from https://academic.oup.com/biolinnean/article/72/2/333/2638759 by guest on 30 September 2021 graphically structured. "he regression of mtDNA data Figure 6. Mismatch distribution of haplotype pairs (the (Fig. 5) revealed that gene flow among pairs of popu- expected curve was generated using Rogers' (1995) lations separated by more than 300km (log[distance]= Sudden expansion model). (m) observed (0)expected. 2.48) often exceeded the equivalent of three females per generation (log A?= 0.48). In fact, gene flow between most pairs of populations separated by more than lOOOkm exceeded the equivalent of 1 female per gen- 18 326.85, P

1999) suggests that historical disruptions to gene flow expectations, approach to equilibrium, effects of hetero- have confounded any simple isolation by distance effect plasmic cells, and comparison to nuclear genes. Genetics east to west, across southern Australia. Progressive 121: 613-627. aridity and the consequent spread of unsuitable habitat Birky CW Jr, Maruyama T, Fuerst P. 1983. An approach for magpies (adequate water and suitable nesting trees to population and evolutionary genetic theory for genes in are essential) throughout much of central and southern mitochondria and chloroplasts, and some results. Genetics Australia during the most recent glacial cycle, suggests 103 513-527. that vicariance has been a major evolutionary force in Carrick R. 1963a. Ecological significance of territory in the southern populations. If this is true, these populations Australian magpie, Gymnorhina tibicen. Proceedings of the XIII International Ornithological Congress 740-753. probably have not had sufficient time to attain genetic Carrick R. 196313. Social and ecological factors in population equilibrium. Thus, contrasting genetic structures may Downloaded from https://academic.oup.com/biolinnean/article/72/2/333/2638759 by guest on 30 September 2021 regulation of the Australian magpie, Gymnorhina tibicen. have arisen among magpie populations in different Proceedings of the XVI International Congress of Zoology regions of mainland Australia, as a result of historical 3 339-341. differences in habitat continuity. Carrick R. 1972. Population ecology of the black-backed We are currently obtaining more detailed demo- magpie, royal penguin and silver gull. US Dept. Interior graphic and genetic data from other magpie popu- Research Report 2: 41-99. lations in eastern and southern Australia to Coyne JA, Boussy IA, Prout T, Bryant SH, Jones JS, complement the present data set. 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