American Journal of Physical Anthropology

(1)

1

SURNAMES IN CHILE

A study of the population of Chile through isonymy

I. Barrai, A. Rodriguez-Larralde2, J. Dipierri1, E.Alfaro1, N. Acevedo3, E. Mamolini, M. Sandri, A.Carrieri and C. Scapoli.

Dipartimento di Biologia ed Evoluzione, Università di Ferrara, 44121- Ferrara, Italy

1_{Instituto de Biología de la Altura, Universidad Nacional de Jujuy, 4600 – San Salvador De Jujuy,}

Argentina.

2_{Centro de Medicina Experimental, Laboratorio de Genetica Humana, IVIC, 1020A -Caracas,}

Venezuela.

3_{Museo Nacional de Ciencias Naturales, Santiago, Chile}

Running title: Surnames in Chile

Correspondence to: Chiara Scapoli

Department of Biology and Evolution University of Ferrara,

Via L. Borsari 46, - I-44121 Ferrara, Italy.

Telephone: +39 0532 455744; FAX: : +39 0532 249761 Email: scc@unife.it

Number of text pages: 15 Literature pages: 4 Number of Tables : 2 Number of Figures: 7

KEYWORDS: Chile, Population Structure, Isonymy, Inbreeding, Isolation by distance

ACKNOWLEDGMENTS: The authors are grateful to the Director of the Servicio Electoral de la

Republica de Chile Sr. Juan Ignacio Garcia Rodríguez, who made the data available, and to Sr. Dr.Ginés Mario Gonzalez Garcia, Embajador de la Republica Argentina en Chile. The work was supported by grants of the Italian Ministry of Universities and Research (MIUR) to Chiara Scapoli. The authors take pleasure in dedicating this work to Dr. Juan Pinto Cisternas of Valparaiso, a pioneer of isonymy studies.

Page 1 of 31

John Wiley & Sons, Inc.

American Journal of Physical Anthropology

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(2)

-2 0 2 4 6 8 10 12 14 Log(occurrence) -2 0 2 4 6 8 10 Lo g(fr eq ue ncy )

Figure S1. Frequency of a given occurrence of a surname as a function of its occurrence. 8.1

million paternal surnames, Chile 2006. Bilogarithmic scale.

-2 0 2 4 6 8 10 12 14 Log(occurrence) -2 0 2 4 6 8 10 12 Log(f requency)

Figure S2. Frequency of a given occurrence of a surname as a function of its occurrence. 8.1

(3)

F_ST F_IS 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 0.020 0.022 0.024 0.026 0.028 0.030 FIT -0.002 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 0.020 0.022 0.024 0.026 0.028

Figure S3. The components of inbreeding levels in 54 provinces of Chile. Local inbreeding seems

to be the largest component, whereas random inbreeding tends to stay constant. Inbreeding from

isonymy, 16 million surnames, Chile 2006.

(4)

LAS LASP LASM -500 0 500 1000 1500 2000 2500 3000 3500 4000 CENTER 5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6

Figure S4. Variation of Lasker’s distance on kilometers, Chile 2006. The belts are one standard

deviation wide.

NEI NEIP NEIM -500 0 500 1000 1500 2000 2500 3000 3500 4000 CENTER -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

Figure S5. Variation of Nei’s distance on kilometers, Chile 2006. The belts are one standard

(5)

TARAPACA ANTOFAGASTA ATACAMA COQUIMBO VALPARAISO LIBERTADOR MAULE BIOBIO ARAUCANIA LOS LAGOS AISEN MAGALLANES METROPOLITANA LOS RIOS ARICA Y PARINACOTA -5 -4 -3 -2 -1 0 1 2 3 4 5 6 Fact. 1: 41.25% -4 -3 -2 -1 0 1 2 3 4 Fac t. 2 : 2 0. 35 %

Figure S6P. Projection of the Euclidean distance matrix between regions on the first two Factors of

(6)

Figure S6M. Projection of the Euclidean distance matrix between regions on the first two

(7)

UPGMA Euclidean Distance A IS E N M A GA L L A NE S L OS L A GOS L OS RI OS A RA UC A N IA B IOB IO M A UL E L IB E RTA D OR M E TROP OL ITA N A V A L P A RA IS O CO QUIM B O A TA C A MA A NTOF A GA S TA A RI C A Y P A R IN A COTA TA RA P A CA 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55

Figure S7. Dendrogram based on the matrix of Euclidean surname distances between regions. Note

(8)

(9)

Arica Parinacota Iquique Tocopilla_{El Loa} Antofagasta Chañaral Copiapó Huasco Elqui Limarí Choapa Petorca Los Andes San Felipe de AconcaguaQuillota

Valparaíso_{San Antonio}

Isla de Pascua Chacabuco Santiago CordilleraMaipo Melipilla TalaganteCachapoal Colchagua Cardenal Caro Curicó TalcaLinares Cauquenes Ñuble Concepcion Biobío Arauco MallecoCautin Valdivia Osorno Llanquihue Chiloé Palena Coihaique Aisén General Carrera Capitan Prat Ultima Esperanza Magallanes Tierra del Fuego Antartica Chilena Tamarugal Ranco Marga Marga -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 Fact. 1: 38.90% -8 -6 -4 -2 0 2 4 6 8 10 12 Fac t. 2 : 20.77%

Figure S9P. Projection of the Euclidean distance matrix between provinces on the first two Factors

of PCA. Note the counterclockwise arc ordering of the provinces in the second, third, fourth, and

first quadrant. Note the outlier position of Isla de Pascua (Easter Island) in the first quadrant.

(10)

Figure S9M. Projection of the Euclidean distance matrix between provinces on the first two

Dimensions of MDS. Note the counterclockwise arc ordering of the provinces in the third, second,

first and fourth quadrant.

(11)

UPGMA Euclidean Distance Is la d e P asc u a A n ta rti ca C hi le n a Ca p it an P rat Gen e ral Ca rr e ra P a le na Ti err a d e l Fu e g o A is é n Co ih ai q u e Ul ti m a E spera n z a Ch ilo é M ag a lla ne s L lan q u ihu e Os orno Ra n c o V a ld iv ia P a ri n acota A rau c o Ca u ti n M al le c o B io b ío Co n c e p c io n Ñu b le Ca u q ue n e s Ca rde na l Ca ro Co lc h a g ua L ina res Ta lca Cu ri c ó M el ip ill a Ca c h a p o al Ta la g a n te M ai p o Co rdi lle ra S a n ti ag o Ch a c a b u c o S a n A n ton io M arga M arga V a lp araí s o Qui llota S a n Fel ip e de A concag u a L o s A n d es P e to rc a Ch o a pa Hu a s co L ima rí Ch a ñ aral Co p iap ó E lq u i A n to fag a s ta E l L o a To c o p ill a Ta ma rug al Iq ui q u e A ri c a 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Figure S10. Dendrogram of the 54 provinces of Chile. Note the considerable North-South ordering

(12)

Municipalities Complete Linkage Euclidean Distance N N N N N N N N N N N N N N N N N N N N N N S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S N N N N N N N N N N N N N N N N N N N N N N N N N N N S S S S S S S S S S S S S S S S S S N N N N N N N N N N N N N N N N N N N N N N N N N N N N N S S S S S S S S S S S S S N S S S N N N N CHE N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N S N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S 0.0 0.5 1.0 1.5 2.0 2.5 3.0 D istan za Le ga m e

Figure S11. The dendrogram from the Euclidean distance matrix between the 346 communes of

(13)

Figure S12P. Projection of the Euclidean distance matrix between the 346 communes of Chile on

the first two Factors of PCA. Note that the North (N) and the South (S) clusters are inverted in the

Projection. Label CHE means Chepica municipality.

(14)

Figure S12M. Projection of the Euclidean distance matrix between the 346 communes of Chile on

(15)

Figure S13. Mapping of Euclidean’s matrix of surname distances between departments in Chile on

the first three components of Pca. The first component (a) green) represents 38.9% of the total

dispersion, the second (b) blue) 20.8%, and the third component (c) red) 8.5%.

(16)

Table S1. Isonymy in Chile. From: I. Barrai et al., to be submitted to: Am J Phys Anthropol, 2011.

Municipality, average coordinates (Lat and Lon). Prefix: NIND = number of individuals; NSUR =

number of different surnames; I = isonymy; ALFA = Fisher’α; NI = Karlin’s ν. Suffix: PA =

paternal surname; MA = maternal surname; PM = both paternal and maternal surname. FST =

random inbreeding FST; IOBS = total observed isonymy; FIS = local inbreeding FIS; FIT = total

inbreeding FIT.

(17)

(18)

(19)

(20)

Table S2. The first 50 surnames in Chile, paternal and maternal series.

Paternal

N

Maternal

N

GONZALEZ 171266 GONZALEZ 172755 MUÑOZ 133998 MUÑOZ 136343 ROJAS 96090 ROJAS 96793 DIAZ 94912 DIAZ 95589 PEREZ 76643 PEREZ 76053 SOTO 68560 SOTO 70602 CONTRERAS 64057 CONTRERAS 64716 SILVA 61416 SILVA 60162 SEPULVEDA 58638 SEPULVEDA 58613 MARTINEZ 58330 MARTINEZ 58146 MORALES 57962 MORALES 57747 RODRIGUEZ 56353 LOPEZ 55210 LOPEZ 55418 RODRIGUEZ 55086 FUENTES 53657 FUENTES 53675 ARAYA 52596 TORRES 52383 TORRES 52393 ARAYA 52313 HERNANDEZ 52350 HERNANDEZ 52070 ESPINOZA 51132 FLORES 51562 VALENZUELA 50590 ESPINOZA 51042 FLORES 50462 VALENZUELA 50610 CASTILLO 49786 CASTILLO 49584 RAMIREZ 49316 RAMIREZ 49174 REYES 48353 REYES 48475 GUTIERREZ 46829 GUTIERREZ 46959 CASTRO 46104 CASTRO 46642 VARGAS 45640 VARGAS 46536 ALVAREZ 44468 VASQUEZ 45231 VASQUEZ 43960 ALVAREZ 44866 FERNANDEZ 42641 TAPIA 41821 TAPIA 42268 CARRASCO 40950 SANCHEZ 40822 SANCHEZ 40582 CORTES 40347 FERNANDEZ 40167 HERRERA 39925 CORTES 40100 CARRASCO 39811 GOMEZ 39858 GOMEZ 39795 HERRERA 39422 NUÑEZ 38325 NUÑEZ 39142 JARA 37672 JARA 38334 VERGARA 36579 VERGARA 37338 RIVERA 34321 FIGUEROA 34522 FIGUEROA 34072 RIVERA 34337 GARCIA 33385 RIQUELME 33967 RIQUELME 33114 VERA 33209 BRAVO 32903 MIRANDA 32747 VERA 32071 BRAVO 31986 MIRANDA 31696 GARCIA 31800 MOLINA 30464 MOLINA 30652 VEGA 30309 VEGA 30273 SANDOVAL 29194 CAMPOS 29762 CAMPOS 29116 SANDOVAL 28667 OLIVARES 28660 ORELLANA 28618