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Demographic history of the Magellanic Penguin (Spheniscus magellanicus) on the Pacific and Atlantic coasts of South America

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Abstract

Spatial subdivision, local extinction and recolonization influence the genetic variation of natural populations. Different levels of population structure can be identified in nature, from panmictic populations, in which high gene flow homogenizes diversity across localities, to metapopulations, where combinations of moderate to high levels of population differentiation and source-sink population dynamics are expected. Gene flow, dispersal and recolonization can be affected by changes in ecological conditions such as climate and resource distribution. Evaluating demographic history is crucial for understanding current population dynamics. We assessed a mitchondrial DNA (mtDNA) control region and microsatellite data for 210 Magellanic Penguins (Spheniscus magellanicus) from 13 breeding colonies on the coastlines of Chile and Argentina, covering a great portion of the species’ distribution. We found high levels of genetic diversity and detected two genetic-geographic regions, Pacific and Atlantic, probably due to interruption of the connection between the oceans during the Last Glacial Maximum (LGM), when several parts of the Magellanic Channel were connected to the continent. The Atlantic ocean colonies showed a slight differentiation between the northern and southern colonies, and the Falkand/Malvinas one seems to be a mix of northern, southern and Pacific colonies. Magellanic Penguins showed intense gene flown among colonies, and exhibited low levels of genetic differentiation in each region. Furthermore, our findings indicate that the Magellanic Penguin experienced a population expansion around 17,500 years ago, which is in agreement with the timing of a decreased sea level and the exposure of the continental shelf along the coast of Argentina and the Falkland/Malvinas Islands at the end of the LGM. Thus, our results suggest that climate changes that affect the sea level in South America can play important roles in the migration of Magellanic Penguins.

Zusammenfassung

Die demografische Geschichte des Magellanpinguins ( Spheniscus magellanicus ) an den pazifischen und atlantischen Küsten Südamerikas

Räumliche Trennung sowie lokale Aussterbe- und Wiederbesiedlungsereignisse beeinflussen die genetische Variation natürlicher Populationen. In der Natur lassen sich verschiedene Ebenen der Populationsstruktur unterscheiden—von panmiktischen Populationen, bei denen starker Genfluss die Diversität zwischen den Örtlichkeiten ausgleicht, bis hin zu Metapopulationen, bei denen eine Kombination aus mäßigen bis hohen Graden der Populationsdifferenzierung und einer Source-Sink-Populationsdynamik zu erwarten ist. Genfluss, Dismigration und Wiederbesiedlung können durch Veränderungen der ökologischen Bedingungen, wie zum Beispiel Klima und Ressourcenverteilung, beeinflusst werden. Eine Analyse der demografischen Geschichte ist für das Verständnis der aktuellen Populationsdynamik daher von fundamentaler Bedeutung. Wir untersuchten mtDNA aus der Kontrollregion und Mikrosatelliten-DNA-Daten von 210 Magellanpinguinen (Spheniscus magellanicus) aus 13 Brutkolonien entlang der Küsten von Chile und Argentinien, was einen Großteil des Verbreitungsgebietes der Art abdeckt. Wir stellten ein hohes Maß an genetischer Diversität fest und ermittelten zwei genetisch-geografische Regionen, eine pazifische und eine atlantische, vermutlich aufgrund einer Unterbrechung der Verbindung zwischen den Ozeanen während des letzteiszeitlichen Maximums (Last Glacial Maximum, LGM), als verschiedene Abschnitte der Magellanstraße mit dem Kontinent verbunden waren. Am Atlantik zeigten sich leichte Unterschiede zwischen nördlichen und südlichen Küstenkolonien; auf den Falklandinseln/Malwinen scheint es sich um eine Mischung aus nördlichen, südlichen und pazifischen Kolonien zu handeln. Die Magellanpinguine zeigten einen starken Genfluss zwischen den Kolonien, aber ein geringes Maß an genetischer Differenzierung in der jeweiligen Region. Des Weiteren deuten unsere Ergebnisse an, dass es bei den Magellanpinguinen vor etwa 17.500 Jahren zu einer Populationsausdehnung kam, was im Einklang mit einer Periode abgesenkten Meeresspiegels und freiliegender Kontinentalschelfe entlang der Küsten Argentiniens und der Falklandinseln/Malwinen am Ende des letzteiszeitlichen Maximums steht. Daher legen unsere Ergebnisse nahe, dass Klimaveränderungen in Südamerika, welche den Meeresspiegel beeinflussen, eine wichtige Rolle für die Ausbreitungsbewegungen der Magellanpinguine spielen können.

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References

  • Akst EP, Boersma PD, Fleischer RC (2002) A comparison of genetic diversity between the Galápagos Penguin and the Magellanic Penguin. Conserv Genet 3:375–383

    Article  CAS  Google Scholar 

  • Bandelt HJ, Forster P, Röhl A (1999) Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol 16:37–48

    Article  PubMed  CAS  Google Scholar 

  • Beebee T, Rowe G (2008) An introduction to molecular ecology. Oxford, New York

  • Bochy P, Theodorou K, Couve D (2005) Metapopulation viability: influence of migration. Conserv Genet 6:75–85

    Article  Google Scholar 

  • Boersma PD (2008) Penguins are marine sentinels. Bioscience 58:597–607

    Article  Google Scholar 

  • Boersma PD, Rebstock GA (2014) Climate change increases reproductive failure in Magellanic Penguins. PLoS ONE 9:e85602

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Boersma PD, Frere E, Kane O (2013) Magellanic Penguin. In: Garcia-Borboroglu P, Boersma PD (eds) Penguins: natural history and conservation. University of Washinghton Press, Washinghton, pp 233–263

    Google Scholar 

  • Bouzat JL, Walker BG, Boersma PD (2009) Regional genetic structure in the Magellanic Penguin (Spheniscus magellanicus) suggests metapopulation dynamic. Auk 126:326–334

    Article  Google Scholar 

  • Clucas GV et al (2014) A reversal of fortunes: climate change ‘winners’ and ‘losers’ in Antarctic Peninsula penguins. Sci Rep 4:e5024

    Article  CAS  Google Scholar 

  • Corander J, Marttinen P, Sirén J, Tang J (2008) Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinf 9:539

    Article  CAS  Google Scholar 

  • Dantas GPM et al (2013) Evidence of northward extension of the winter range of Magellanic Penguins along the Brazilian coast. Mar Ornithol 41:195–197

    Google Scholar 

  • De Vries TJ (1987) A review of geological evidence for ancient El Niño activity in Peru. J Geophys Res 92:14471–14479

    Article  Google Scholar 

  • Di Rienzo A et al (1994) Mutational processes of simple-sequence repeat loci in human populations. PNAS 91:3166–3170

    Article  PubMed  Google Scholar 

  • Drummond AJ, Rambaut A (2007) BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol 7:214

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14:2611–2620

    Article  PubMed  CAS  Google Scholar 

  • Excoffier L, Laval G, Schneider S (2005) Arlequin (version 3.0): an integrated software package for population genetics data analysis. J Evolution Bioinf 1:47–50

    CAS  Google Scholar 

  • Frankham R, Ballou JD, Briscoe DA (2002) Introduction to conservation genetics. Cambridge University Press, New York

    Book  Google Scholar 

  • Fraser DJ et al (2007) Comparative estimation of effective population sizes and temporal gene flow in two contrasting population systems. Mol Ecol 16:3866–3889

    Article  PubMed  Google Scholar 

  • Fu YX (1997) Statistical test of neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147:915–925

    PubMed  PubMed Central  CAS  Google Scholar 

  • Gaggiotti OE, Excoffier L (2000) A simple method to removed the effect of bottleneck and unequal population sizes on pairwise genetic distances. Proc R Soc B 267:81–87

    Article  PubMed  CAS  Google Scholar 

  • Gandini P, Frere E, Boersma PD (1996) Status and conservation of Magellanic Penguins, Spheniscus magellanicus, in Patagonia Argentina. Bird Conserv Int 6:307–316

    Article  Google Scholar 

  • Gilpin M (1991) The genetic effective size of a metapopulation. Biol J Linn Soc 42:165–175

    Article  Google Scholar 

  • Grimm A, Barros VR, Doyle ME (2000) Climate variability in southern South America associated with El Niño and La Niña Events. J Clim 13:35–58

    Article  Google Scholar 

  • Harrison S, Hastings A (1996) Genetic and evolutionary consequences of metapopulation structure. Trends Ecol Evol 11:180–183

    Article  PubMed  CAS  Google Scholar 

  • Heled J, Drummond AJ (2008) Bayesian inference of population size history from multiple loci. BMC Evol Biol 8:289

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Higgins K, Lynch M (2001) Metapopulation extinction caused by mutation accumulation. PNAS 98:2928–2933

    Article  PubMed  CAS  Google Scholar 

  • IPCC International Panel on Climate Change (IPCC) (2013) The physical science basis. In: Stocker T et al (eds) Contribution of Working Group I to the fifth assessment report of the International Panel on Climate Change. Cambridge University Press, New York, p 1535

    Google Scholar 

  • Keller LF, Waller DM (2002) Inbreeding effects in wild populations. Trends Ecol Evol 17:230–241

    Article  Google Scholar 

  • Kimura M, Ohta T (1978) Stepwise mutation model and distribution of allelic frequencies in a finite population. PNAS 75:2868–2872

    Article  PubMed  CAS  Google Scholar 

  • Kuparinen A et al (2010) Effective size of an Atlantic Salmon (Salmo salar L.) metapopulation in Northern Spain. Conserv Genet 11:1559–1569

    Article  Google Scholar 

  • LaRue MA et al (2013) Climate change winners: receding ice fields facilitate colony expansion and altered dynamics in an Adélie Penguin metapopulation. PLoS ONE 8:e60568

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Librado P, Rozas J (2009) DnaSP v. 5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25:1451–1452

    Article  PubMed  CAS  Google Scholar 

  • Liedloff AC (1999) Mantel Nonparametric Test Calculator. Version 2.0. School of Natural Resource Sciences, Queensland University of Technology, Australia

  • Millar CD et al (2008) Mutation and evolutionary rates in Adélie Penguins from the Antarctic. PLoS Genet 4:e1000209

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Mills LS, Allendorf FW (1996) The one-migrant-per-generation rule in conservation and management. Conserv Biol 10:1509–1518

    Article  Google Scholar 

  • Moreno PI, Denton GH, Moreno H, Lowell TV, Putnam AE, Kaplan MR (2015) Radiocarbon chronology of the Last Glacial Maximum and its termination in northwestern Patagonia. Q Sci Rev 122:233–249

    Article  Google Scholar 

  • Oliveira LR et al (2008) Morphological and genetic evidence for two evolutionarily significant units (ESUs) in the South American Fur Seal, Arctocephalus australis. Conserv Genet 9:1451–1466

    Article  Google Scholar 

  • Oliveira LR, Gehara MCM, Fraga L, Lopes F, Túnez JI, Cassini MH, Majluf P, Cardenas-Alayza S, Pavés HJ, Crespo EA, García N, Loizaga de Castro R, Hoelzel AR, Sepúlveda M, Olavarría C, Valiati VH, Quiñones R, Pérez-Alvarez MJ, Ott PH, Bonatto SL (2017) Ancient female philopatry, asymmetric male gene flow, and synchronous population expansion support the influence of climatic oscillations on the evolution of South American Sea Lion (Otaria flavescens). PLoS ONE 12:e0179442

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Orsini L, Corander J, Alasentie A, Hanski I (2008) Genetic spatial structure in a butterfly metapopulation correlates better with past than present demographic structure. Mol Ecol 17:2629–2642

    Article  PubMed  CAS  Google Scholar 

  • Paetkau D, Calvert W, Stirling I, Strobeck C (1995) Microsatellite analysis of population structure in Canadian Polar Bears. Mol Ecol 4:347–354

    Article  PubMed  CAS  Google Scholar 

  • Paetkau D, Slade R, Burden M, Estoup A (2004) Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power. Mol Ecol 13:55–65

    Article  PubMed  CAS  Google Scholar 

  • Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28:2537–2539

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Peña FM et al (2014) Have historical climate changes affected Gentoo Penguin (Pygoscelis papua) populations in Antarctica? PLoS ONE 9:e95375

    Article  CAS  Google Scholar 

  • Piry S, Luikart G, Cornuet JM (1999) BOTTLENECK: a computer program for detecting recent reductions in the effective population size using allele frequency data. J Heredity 90:502–503

    Article  Google Scholar 

  • Piry S et al (2004) GENECLASS2: a software for genetic assignment and first-generation migrant detection. J Hered 95:536–539

    Article  PubMed  CAS  Google Scholar 

  • Ponce JF, Rabassa J, Coronato A, Barrome AM (2011) Palaeogeographical evolution of the Atlantic coast of Pampa and Patagonia from the Last Glacial Maximum to the Middle Holocene. Biol J Linn Soc 103:363–379

    Article  Google Scholar 

  • Posada D, Cradall KA (1998) Modeltest: testing the model of DNA substitution. Bioinf Appl Note 14:817–818

    Article  CAS  Google Scholar 

  • Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    PubMed  PubMed Central  CAS  Google Scholar 

  • Putz K, Incham RJ, Smith J (2000) Satellite tracking of the winter migration of Magellanic Penguins Spheniscus magellanicus breeding in the Falkland Island. Ibis 142:614–622

    Article  Google Scholar 

  • Rabassa J (2008) Late Cenozoic glaciations of Patagonia and Tierra del Fuego. Dev Q Sci 11:151–204

    Google Scholar 

  • Ramos-Onsins SE, Rozas J (2002) Statistical properties of new neutrality tests against population growth. Mol Biol Evol 19:2092–2100

    Article  PubMed  CAS  Google Scholar 

  • Rannala B, Mountain JL (1997) Detecting immigration by using multilocus genotypes. PNAS 94:9197–9201

    Article  PubMed  CAS  Google Scholar 

  • Ritchie PA, Millar CD, Gibb GC, Baroni C, Lambert DM (2004) Ancient DNA enables timing of the Pleistocene origin and Holocene expansion of two Adélie Penguin lineages in Antarctica. Mol Biol Evol 21:240–248

    Article  PubMed  CAS  Google Scholar 

  • Roeder AD, Ritchie PA, Lambert DM (2002) New markers for penguins. Conserv Genet 3:341–344

    Article  CAS  Google Scholar 

  • Romero OE, Kim J-H, Hebbeln D (2002) Paleoproductivity evolution off central Chile from the Last Glacial Maximum to the early Holocene. Q Res 65:519–525

    Article  Google Scholar 

  • Ruoppolo V et al (2012) Survival and movements of Magellanic Penguins rehabilitated from oil fouling along coast of South America, 2000–2010. Mar Pollut Bull 64:1309–1317

    Article  PubMed  CAS  Google Scholar 

  • Sallaberry-Pincheira N et al (2016) Contrasting patterns of selection between MHC I and II across populations of Humboldt and Magellanic Penguins. Ecol Evol 6:7498–7510

    Article  PubMed  PubMed Central  Google Scholar 

  • Sambrook KJ, Russel DW, Sambrook J (2001) Molecular cloning: a laboratory mannual. CSHI, New York

    Google Scholar 

  • Sandweiss DH, Richardson JBIII, Reitz EJ, Rollins HB, Maasch KA (1996) Geoarchaeological evidence from Peru for a 5000 years BC onset of El Niño. Science 273:1531–1533

    Article  CAS  Google Scholar 

  • Schlosser JA, Garner TWJ, Dubach JM, McElligott AG (2003) Characterization of microsatellite loci in Humboldt Penguin (Spheniscus humboldti) and cross-amplification in other penguin species. Mol Ecol Notes 3:62–64

    Article  CAS  Google Scholar 

  • Schlosser JA et al (2009) Evidence for gene flow differs from observed dispersal patterns in the Humboldt Penguin, Spheniscus humboldti. Conserv Genet 10:839–849

    Article  CAS  Google Scholar 

  • Silva L et al (2014) Differences in diet composition and foraging patterns between sexes of the Magellanic Penguin (Spheniscus magellanicus) during the non-breeding period as revealed by δ13C and δ15N values in feathers and bones. Mar Biol 161:1–12

    Article  CAS  Google Scholar 

  • Smyser TJ, Duchamp JE, Johnson SA, Larkin JL, Rhodes OE Jr (2012) Consequences of metapopulation collapse: comparison of genetic attributes between two Allegheny Woodrat metapopulations. Conserv Genet 13:849–858

    Article  Google Scholar 

  • Tajima F (1989) Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123:585–595

    PubMed  PubMed Central  CAS  Google Scholar 

  • Van-Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) Micro-checker: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol 4:535–538

    Article  CAS  Google Scholar 

  • Vianna JA et al (2017) Marked phylogeographic structure of Gentoo Penguin reveals an ongoing diversification process along the Southern Ocean. Mol Phylogenet Evol 107:486–498

    Article  PubMed  Google Scholar 

  • Villagrán C, Armesto JJ, Leiva R (1986) Recolonización postglacial de Chiloe insular: evidencias basadas en la distribución geográfica y los modos de dispersión de la flora. Rev Chil Hist Nat 59:19–39

    Google Scholar 

  • Younger J, Emmerson L, Southwell C, Lelliott P, Miller K (2015) Proliferation of East Antarctic Adélie Penguins in response to historical deglaciation. BMC Evol Biol 15:236

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

This study was financed by the National Counsel of Technological and Scientific Development, Brazil (CNPq 490403/2008-5); the São Paulo Research Foundation (FAPESP 2009/08624-8); FAPESP-CONICET (the National Research Council of Argentina) (10/525908), the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior of Brazil (CAPES), the Fondo Nacional de Desarollo Cientifico y Tecnologico del Chile (FONDECYT 11110060; 1010250; 1100695; 1150517); Sea World and Busch Gardens Conservation Fund, PICT 2110. Samples were obtained under Subpesca CONAF, DGFFS-minag, IBAMA, and Secretaria de Ambiente y Desarrollo Sustentable of Argentina (permits 011187/2010). Permits were granted from the Dirección de Fauna y Flora Silvestre and the Secretaría de Turismo y Areas Protegidas de la Provincia de Chubut. We thank Sarah Crofts, Micky Reeves, and Jonathan Handley from Falklands Conservation for their contribution to the sampling. The study was approved by the Ethics Committee of Pontificia Universidad Catolica de Minas Gerais, Brazil. All samples were collected with the Subpesca permit no. 110, CITES permit (Brazil, 10BR005149/DF; Chile, 0524984; Argentina, 011187).

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Authors and Affiliations

  1. Pos-Graduação em Biologia de Vertebrados, Pontifícia Universidade Católica de Minas Gerais, Av. Dom José Gaspar 500, Coração Eucarístico, Belo Horizonte, MG, Brazil

    Gisele Pires Mendonça Dantas

  2. Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, Belo Horizonte, Brazil

    Gisele Pires Mendonça Dantas & Fabricio Rodrigues Santos

  3. Instituto de Biologia, Universidade de São Paulo (USP), Rua do Matao, 321, São Paulo, SP, Brazil

    Gabriella Cardoso Maria, Anna Carolina Milo Marasco, Larissa Tormena Castro, Vanessa Simão Almeida & João Stenghel Morgante

  4. Universidade do Vale do Rio dos Sinos, Av. Unisinos, 950, São Leopoldo, Rio Grande do Sul, Brazil

    Larissa Rosa Oliveira

  5. Centro Nacional Patagónico (CONICET), Boulevard Brown 2915, (9120), Puerto Madryn, Chubut, Argentina

    Enrique Crespo

  6. Centro de Investigaciones de Puerto Deseado, Universidad Nacional de la Patagonia Austral, Puerto Deseado, Argentina

    Esteban Frere & Anna Milliones

  7. Facultad de Ciencias Veterinarias, Universidad de Concepción, Av. Vicente Méndes, 595, Casilla 537, Chillán, Chile

    Daniel González-Acuña

  8. Departamento de Ecosistemas y Medio Ambiente, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, Santiago, Chile

    Juliana A. Vianna

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  1. Gisele Pires Mendonça Dantas
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  2. Gabriella Cardoso Maria
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  3. Anna Carolina Milo Marasco
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Contributions

G. P. M. D. is interested in phylogeography and population genetics as a background to conservation, and she contributed to the design of the study, the sampling, data analysis, and the text. F. R. S., L. R. .O and J. S. M. are interested in evolutionary biology, phylogeography and conservation biology and contributed to writing the draft of the manuscript. D. G. A., E. C., E. F. and A. M. are interested in ornithology including penguins and other Antarctic organisms, and contributed to the sampling. J. A. V. is interested in phylogeography and conservation genetics, and contributed to sampling, data analysis and writing the text. G. C. M., A. C. M. M., L. T. C. and V. S. A. were responsible for the laboratory procedures.

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Correspondence to Gisele Pires Mendonça Dantas.

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Communicated by C. Barbraud.

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10336_2018_1538_MOESM1_ESM.tif

S1 Haplotype network for the D-loop region of Magellanic Penguin sequences. Colors correspond to haplotype source: light grey Chiloé, dark grey Magdalena, black Cabo Virgines, light green San Julian, dark green Falklands/Malvinas, light blue San Lorenzo, blue Isla Moreno, dark blue Cabo Bahía, yellow Cabo Blanco, orange Quiroga/Chaffer, pink Pinguino, brown Cb Guardian, red median vectors or hypothetical states inferred by maximum parsimony. Node size corresponds to haplotype frequency. (TIFF 261 kb)

10336_2018_1538_MOESM2_ESM.jpg

S2 Bayesian analysis of population structure from Magellanic Penguin sequences (D-loop region), considering clustering of individuals with spatial models, with mixture and admixture analysis, considering K1–13 and 100,000 interactions. (JPEG 30 kb)

10336_2018_1538_MOESM3_ESM.tif

S3 Comparison of STRUCTURE classification of Magellanic Penguin based on ten microsatellite loci admixture model, with K = 3 for 13 colonies with a total of 210 individuals with LOCPRIOR, 13 colonies with a total of 210 individuals without LOCPRIOR. y-axis shows individual probabilities of assignment. (TIFF 350 kb)

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Dantas, G.P.M., Maria, G.C., Marasco, A.C.M. et al. Demographic history of the Magellanic Penguin (Spheniscus magellanicus) on the Pacific and Atlantic coasts of South America. J Ornithol 159, 643–655 (2018). https://doi.org/10.1007/s10336-018-1538-z

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