Languages, history and human adaptation

Clare Holden

UCL

Why languages?

• Cultural or ethnic marker– 6000 languages (ethno-linguistic groups)– 20-200 families

• Population history– Language trees and networks

• Evolution of cultural diversity– Empirical yet formal approach

“Curiously parallel”

August Schleicher (Indo-European, 1862)

Charles Darwin (1859, 1871)

Evolutionary biology

Historical linguistics

Species

Genetic units of transmission

Languages

Linguistic elements, e.g. words

Reproduction Learning, often parent-offspring

Horizontal transmission

Borrowing

Hybridisation Creoles

Linguistic data(basic vocabulary)

Ashes Belly Bird

Xhosa 1 1 1

Zulu 1 1 2

Sotho 1 2 3

Ndau 1 3 3

v1 v2 v3

Xhosa 1 0 0

Zulu 1 0 0

Sotho 0 1 0

Ndau 0 0 1

Binary coding ‘Belly’Multistate coding

X Z S N

Bantu language trees– Bayesian MCMC sample

800802

A31 A43

A75 B25 C36 C61a C51 C57 D32 J15 J16

B11B73 C34 C75 D25 J62 J23 F21 E62E72

H12 H16iH31 C84H32H16hH31

A32 C41 C40

R11 K19 K14 S45 N21

R31

R22

K11

S34 P31

B31 C61b D37 J13 J22 E51 E71 J51 J53 J61 E55

B80 C71 D24 F23 E73 E74F22

L42 M54 P21

L33D10

M15 M31 K22 M42

S33 S42

S31 S53

S43

S41

S21

N31aM64 N44S44 S15

S10

M52 N42

N31

A24

G12 G31 G23 G11 G34 G43

G35

N31b

West Bantu

East Bantu

South West Bantu

Central Bantu

Non-Bantu

Shambala G23Zigula G31Ngulu G34Kaguru G12Gogo G11Luguru G35Nyakyusa M31 2Yao P21 2Digo E73 1Giryama E72a 1Hadimu G43cPokomo E71 1Sagala E74bNyamwezi F22Sukuma F21Sumbwa F23Mambwe M15Gikuyu E51Kamba E55Caga E62 1Hima J13Zinza J23Haya J22HGanda J15Soga J16Rundi J62Rwanda J61 1Hunde J51Shi J53Lega D25 3Ndebele S44Swati S43Ngoni S45Zulu S42Xhosa S41Tsonga S53Sotho S33Tswana S31Lozi S34Venda S21Ndau S15Shona S10Nyanja N31aNyasa N31Cewa N31bKunda N42Sena N44Tumbuka N21 2Makwa P31 1Lala M52Lamba M54Bemba M42Kaonde L42Luba L33Songe D10STonga M64 1Binja D24 1Lwena K14 1Ndembu K22 1Ciokwe K11Gangela K19Herero R31Ndonga R22Umbundu R11 1Sikongo H16hSundi H16i 4Yombe H12b 1Yaka H31 4Yaka Kasongo H31 2Suku H32Madzing B80Mp 1Teke B73 5Bakoko A43bFang A75 1Duala A24 2Puku A32 1Kota B25 1Mpongwe B11aTsogo B31Kela C75Mongo Nkundo C61 1Mongo C61 3Tetela C71 1Lele C84 1Sakata C34Doko C40DNgombe C41Lingala C36Bira D32 2Kumu D37 2Bubi A31Likile C57Mbesa C51Ejagham 800Tiv 802

West Bantu

South West Bantu

Central Bantu

East Bantu

73

45

19

23

44

95100

97

18

46

27

100

99

53

67

100

1006328

4865

45

100

100

100

Holden and Gray, in pressHolden, Pagel and Meade, 2005

Bantu network

Holden and Gray, in press

East Bantu

Central Bantu

SW Bantu

West Bantu

Ancestral states

Spread of cattle among Bantu-

speakers

Ejagham Tiv

Mpongwe Kota

Duala Fang

Likile Mbesa

Lingala Teke

Yombe Sikongo

Sundi Yaka Kasongo

Suku Yaka

Ngombe Bira Kumu

Gangela Ciokwe

Lwena Ndonga

Herero Umbundu

Lele Sakata

Nkundo Kela

Binja Lega Tonga

Bemba Lala

Lamba Kaonde

Luba Songe

Rundi Rwanda

Ganda Soga

Hima Zinza

Caga Gikuyu

Giryama Nyamwezi Sumbwa

Nyakyusa Yao

Mambwe Tumbuka

Sena Kunda

Cewa Nyanja

Shona

Venda Lozi

Sotho Tswana Tsonga

Ndebele Swati

Xhosa Ngoni

Zulu

Ancestral states (nodes)

= Cattle

= No cattle

= Ambiguou s state

Blue text = Cattle

Purple text = No cattle

Ethnographic populations (tips of tree)

Adoption of cattle (2)

Adoption of cattle (1)

Loss of cattle

Possible route for gain of cattle by Cewa

Mace and Holden 2005

Co-evolution

• Testing adaptive hypotheses– Do two traits co-evolve along branches of tree?– Cultural, genetic, environmental traits

• Bantu-speakers– Spread of cattle led to the loss of matrilineal descent

• Indo-Europeans– Marriage payments co-evolve with monogamy/

polygyny

MatrilinyCattle

MatrilinyCattle absent

Patriliny/ mixedCattle absent

Matri lostP=0.83

Matri gainedP=0.01

Cattle gainedP=0.19

Cattle lost

P=0.81

Matri lostP=0.22

Matri gainedP=0.35

Cattle gainedP=0.03

Cattlelost

P=0.18

Holden and Mace (2003, 2005)

Patriliny/mixedCattle

How fast is cultural change?– Gain/ loss of trait over time, e.g. 500 yrs– Calibrate tree using archaeological dates

Origin of dowry in Indo-Europeans

Laura Fortunato, UCL

Summary

• Language trees and networks– Phylogenetic methods– Population/cultural history

• Reconstructing other cultural traits on trees– Testing co-evolutionary hypotheses– Rate of cultural evolution

Acknowledgements

Laura Fortunato, UCL

Russell Gray, University of Auckland

Ruth Mace, UCL

Andrew Meade, University of Reading

Mark Pagel, University of Reading

AHRB Centre for the Evolutionary Analysis of Culture, UCL

The Wellcome Trust

The Marsden Trust, New Zealand