Modelling population dispersal and language origins during the last 120,000 years
Professor Harald Sverdrup Lund Universtity, Sweden Purpose l Model the dispersal of humans out of Africa l Model the divergence of language with time l Investigate the impact of agriculture on archaic language distribution patterns Method and basics l Demic diffusion l Substrate supported population growth l Environmental regulation of growth intensity l Distributed mathematical model l STELLA modelling environment Neolithic Mesolithic population Demic diffusion population 1 Population density Geographical distance When the nucear area reaches saturation density, then a wave 2 of advance starts to propagate Population density Outward from the core area. The Geographical distance rate is approximately 1,000 km per millennium on flat plains, but 3 the rate slows down significantly Population density under difficult environmental Geographical distance conditions and rough topography 4 Population density Geographical distance Basic population+ model Migration
+ Population density
+ - + + Birth rate Population Mortality - + + - - Water
Soil fertility The competition model
+ Agricultural land
R Farmer Mesolithic population population + + R
+ Hunting - areas for mesolithic - population Essential equations For each geographic element, we have: p/ t=increase + D(in) - D(out) + growth + migration
The general equation of continuity leads to:
p/ t=D * nabla2(p) + Q* nabla(p) + r
Population growth is modelled as a first order growth equation with balancing and rate modifying terms Global temperature
5
0
-5
-10 o Temperature deviation in C -15 250 225 200 175 150 125 100 75 50 25 0 kYr BP The great icesheets 30 20 40 50 50 Computer 20 15 30 simulation 40
40 60 for the time 50 50 from 60 50 70 120,000 BC 80 30 40 90 30 to 40 100 100 120 60 70 80 90 110 50 10,000 BC 120 40 30 110 140
90 100 110 120 Nostratic according to model
SEMITIC AFRO-ASIATIC NORTH AFRICAN CENTRAL AFRICAN
GERMANIC BALTO-SLAVIC INDO-ARYAN CELTO-ITALIC INDO-EUROPEAN GREEK ANATOLIAN ALTAIC URALIC ELAMITEª BRAHUI DRAVIDIAN Mbuti pygmy W. Africa Bantu Nilosaharan Genetic San Ethiopians Berber Levant Iranian data European Sardinian India Tamil Lapp
Uralic Cavalli-Sforza et al. 1994 Mongol Tibetan Korean Japanese Ainu Turkic Eskimo Chukchi Amerind Na-Dene
Southern Chinese Mohn-Khmer Thai Indonesian Malaysian Filipinese Polynesian Micronesian Melanesian Papuan Australian
0.030 0.024 0.018 0.012 0.006 0.000 Approximate genetic distance Austric according to the model
JOMON AINU
MIAO MIAO-YAO AUSTRIC 20 YAO
TAI 3 7 DAIC AUSTRO KADAI THAI 5 MALAY-PACIFIC AUSTRONESIAN 3 OCEANIC 6
MUNDA NICOBAR AUSTRO ASLIAN ASIATIC KHASI MON-KHMER Testing on time of initial arrival to an area 100
80
60
40
20 Calculated date, thousand years BC 0 0 20 40 60 80 100 Observed date, thousand years BC Testing against glottochronology
100000
10000
LANGUAGE model prediction 1000 1000 10000 100000 Standard glottochronological model MacroCaucasian in 40,000 BC MacroCaucasian in 30,000 BC MacroCaucasian in 25,000 BC Gravettian, the reindeer hunters of the ice- age
Gravettian figurines 28,000-22,000 BC
23 1 t o 2 8 2 t o 5 Calculated language divergence
LANGUAGE model 100
80
60
40 % retention Pictish retention of Proto-Eurasian 20 Basque retention of Proto-Eurasian Nostratic retention of Proto-Eurasian 0 75 80 85 90 95 100 Time Calculation of similarity drift
LANGUAGE model 100 Nostratic Austric, Sino-Tibetan Basque 10 Pictish
1
0.1 Isogloss loss rate, % per millennium 20 16 12 8 4 0 Thousand years BC Starting positions 10,000 BC
Anyang, 7000 BC
7 Jeriko, 9000 BC Tibesti-Hoggar, 7000 BC Fukien, 7000 BC 3 4
5 7 4 3 4 5 6 AUSTRIC 6 3 Enter 5 4 SINOTIBETAN 4 agriculture; 5 4 3 3 Simulation 3 4 Burushaski 2 from 4 3 5 ELAMO- 3 Pict 3 DRAVIDIAN 10,000 BC 4 Caucasian 6 INDOEUROPEAN3 7 4 Sumerian 4 5 7 to Basque 6 6 8 7 2 5 Tart. 1,500 BC 3 4 5 6 3 AFROASIATIC 2 5 4
3 4 3 Dravidian 4 The Burushaski 5 Finnougroaltaic3 spread 6 3 4 North PictishIndoeuropean of 5 Caucasian 4 4 Rätian6 agriculture Basque 7 Etruscan 7 6 in the west Afroasiatic5 color 6 4 5 4 3 Capsian 5 4 3 Initial positions in Far East Asia at onset of agriculture The spread of agriculture in Asia
Elamo-Dravidian languages 4
4 5 7 6 6 5 4 4 5 5 6 Sino-Tibetan languages7 4 4 5 3 4 4 3 Austric languages 4 3
2 3 Population in China according to model LANGUAGE model 1000 Mesolitic population Neolithic population 100 Total population Historic data
10
1 Chinese population, millions 0.1 14 12 10 8 6 4 2 0 -2 Thousands of years BC Calculated population numbers
80 Indoeuropean 70 Dravidian 60 Afro-asiatic 50 Sino-Tibetan 40 Austric 30 North Caucasian Data, Europe 20 Data, China 10
Neolithic population in millions 0 8 7 6 5 4 3 2 1 0 Thousand years BC Test against glottochronology
20000
16000
12000
8000
4000
LANGUAGE model prediction 0 0 4000 8000 12000 16000 20000 Standard glottochronological model The farmers outnumbered hunter-gatherers by 1:500 LANGUAGE model 1000
Hunter-gatherer 100 Neolithic World population 10
1
0.1
0.01 World population in million persons 1000 100 10 1 Thousand years BC Observed population densisties in agricultural societies
1000 Mesopotamian delta Egypt 100 Central america Mexico
10
1 2
Population 0.1 density, persons per km -8000 -7000 -6000 -5000 -4000 -3000 -2000 -1000 0 Years before present Indoeuropean homeland
Pokorny, Grimm, m.m.
Gimbutas 4 4 Gamkrelidze 5 6 6 9 Diakonov Renfrew
Cavalli-Sforza Elite dominance, the rise of nomadism and horse warfare
Pictish Basque Paleosibirian Etruscan Finno-Ugric Yukagir European
Yenesseian Caucasian Altaic Indo-Aryan Korean
Elamite Chinese Burushaski
Brahui Burman
Austroasiatic Austronesian
Elamo-Dravidian Events correlate with climate Present 10 Nostratic split 30 Amerindian 50 Nostratic and Dene-Caucasian North and South Eurasian 70 90 ?
110 African and Eurasian Thousand years B.C 130 150 ? 170 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 Temperature deviation, o C Conclusions l The model is capable of reconstructing first time of arrival within +/- 5,500 years in the period from 140,000 BC to 9,000 BC l The model is capable of reconstructing the observed genetic patter in Europe and Asia l The model is giving populations estimates consistent with estimates based or archaeological data Conclusions 2 l The model reconstructs the Nostratic language family as determined by linguists down to small detail
l The model reconstructs a Sino-Caucaso-Iberian language family, consistent with findings of long- range linguistist. The group diverged 25,000 BC and fractionated through isolation with the advent of agriculture Conclusions 3 l The model reconstructs Austric as a language family with depths of 25,000 BC for diversification and 7,000 years for rearrangement by agriculture Conclusion 4 l The LANGUAGE model is at present in awkward form and need reprogramming to FORTRAN90 in order to become generally useful for extensive scenarios l A fat, nice research grant is needed