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Systems dynamics applied to reconstruct the dispersal
of modern man on Earth and language patterns
during the last 120,000 years
Harald Sverdrup and Ramon Guardans
Chemical Engineering, Lund University, Sweden
CIEMAT, Madrid, Espania
Abstract
Movement of populations and languages in Eurasia has been mathematically
modeled. The movements are explained by primarily demographic expansion caused
by climatic change in the historic past, ecological factors and the introduction of
agriculture from the Near East and Southeast Asia into the neighboring territo-
ries. This study use model outputs for the time period 120,000 BC-1,500 BC to
investigate the relation between language families such as Nostratic, Austric and
Dene-Sino-Caucasian, the approximate date of splitting into member languages,
assuming that language follow etnicity. The model is capable of reproducing the
archaeological dates available for initial settlement during the paleolithic period
and the archaeological dates for the neolithic transition in Europe, Middle East,
India, Indochina and Far East simultaneously within approximately +/-20%. The
calculations supports the existence of Nostratic, Austric and Dene-Sino-C aucasian,
and the date of initial settlement of Eurasia and the spread of different types of agri-
culture economies provide important clues to the dating of the splitting of language
families. The calculations suggest that it is not probable that the forst humans
arrived in America earlier than 25,000 years ago. The integrated interpretation of
the modeling study that the origin of language is significantly earlier than 100,000
years ago, in Africa, and that language transfer and diversification has been driven
by ecological factors.
1 Introduction
This study arose as a by-product of models for population dynamics and models for forest
growth and soil carrying capacity developed by the Biogeochemistry and systems analysis
group at the Department of Chemical Engineering at Lund University in Sweden. When
doing mathematical modeling and systems analysis of environmental pollution impacts on
ecological systems across Asia, we discovered that past climate changes and fossil pollen
records could be used to test the predictive capability of mathematical ecological models
for the effects of global climate change. Being used to make population models, it was
only natural to experiment with modelling of human populations. Once we were able to
use ecological factors for population control, the next natural step was to give them a
language and study where the different languages would go. The idea of large language
families is considered by many linguists to be very controversial to this day. The major
argument forewarded is that all resemblance between languages become lost in the noise of
1
random change after approximately 10,000 years. The American linguist Merrit Ruehlen
has written several books on that subject and analysed the long discussions pro and
contra concerning larger language families. In contrast, several Russian and American
scientists have shown such an assumption to be thoroughly wrong and more based in
conservatism than scientific analysis. At the same time, the “out of Africa” theory for
modern human origins has gained more and more scientific support among anthropologists
and pre-historians.
2 Unifying languages
The idea that all humans must have had one language is not new. In fact it follows as a
consequence from the consept of an originally created human couple, as found in most cre-
ation myths of the world. Recent advances in comparative linguistics have started to de
velop a picture of relationships between language families and groups of language families.
Using the same methodology, but starting where researchers in comparative linguistics in
Indoeuropean, Sino-T ibetan etc. left off, large superfamilies were reconstructed. Several
such superfamilies of languages could be identified as a result of recent work (IIlich-Svitych
1964, 1967, 1989; Dolgopolsky, 1986, 1988; Greenberg, 1990; Shevoroshkin, 1990). Ac-
cording to the results of the above listed studies as well as our mathematical studies, a
majority of the worlds languages can be ordered into 9 major language families that come
in three larger language family groups;
* The North Eurasian language family group has three branches;
- Nostratic-Eurasiatic, Dene-Sino-Caucasian, Amerind
* The South Eurasian language family group has three branches;
- Austric, Indo-Pacific, Australian
* The African language family group had four branches;
- Nilo-Saharan, Niger-C ongo-C ordofanian, K hoisan, T he extinct M buti languages
Nostratic is more or less overlapping with what is sometimes also called Eurasiatic. As
we understands the entity Nostratic, it comprises the language groups of Indo-European,
Kartvelian, Afro-Asiatic, Finno-Ugric, Yukagir, Dravidian and Altaic including the Ko-
rean and J apanese languages, probably also Eskimo-A leut and C huckchi-K amchadal (P ed-
ersen 1933; Illich-Svitych 1964, 1967, 1989; Dolgopolsky, 1986, 1988; Greenberg, 1987;
Kaiser and Shevoroshkin, 1986). The language groups listed have different rankings in
the development hierarcy within the group.
Dene-Sino-C aucasian , comprises the following larger language groups; Sino-T ibetan
languages, the North-C aucasian languages, Burushaski, Y enesseian, the pre-|ndoeuropean
North Caucasian languages of paleolithic Europe, Basque, Iberian, Pictish, Etruscan, Ra-
tian, Lemnian, Sumerian (Trombetti, 1925; Bouda 1948) and the Na-Dene languages of
the American Northwest Coast and East Central Canada (Rhys, 1892; MacAlister 1940;
Ruehlen, 1988; Greenberg, 1990; Starostin, 1989, Orel and Starostin, 1990, Sverdrup
1995, 1999). Of these there is a major divide east-west, the eastern group comprising
Sino-T ibetan, possibly Yenesseian and Na-Dene.
Austric comprise the larger language groups Austro-Tai languages, the Miao-Y ao-
She languages and several related extict languages called Man that once covered large
tracts of Eastern and Southern China, the Austronesian languages and the A ustro-A siatic
languages of India and Indo-China (Bellwood 1991; Peiros 1990).
Amerind comprises all Indian languages of the American Continents, except the
Na-Dene languages, a Dene-Sino-Caucasian language group and the Eskimo-Aleutian,
distantly related to the Nostratic language group (Ruehlen 1988; Greenberg 1987; Green-
berg et al. 1988; Shevoroshkin 1990; Nikolaev and Mudrak 1989).
Niger-C ongo, Nilo-Saharan and K hoisan are the general African language fam-
ilies, Indo-Pacific is a language family comprising Andamanese, Papua-New Guinean
and Tasmanian.
The research in inter-language grouping comparisons has been brought to the atten-
tion of a wider audience after an International Conference on Language and Prehistory at
Ann Arbor in 1988, arranged by the Professor of Slavic languages, Vitaly Shevoroshkin,
Professor of Slavic languages and literatures at Ann Arbor, and edited a series of publica-
tions with material from that conference (Reconstructing Language and Cultures, 1989;
Explorations in language macrofamilies, 1989; Proto-languages and proto-cultures, 1990;
Dene-Sino-C aucasian languages 1991). T he professor of Archaeology at Cambridge, Colin
Renfrew, has written several books in European prehistory and initiated a total revision
of European prehistory. Renfrew has brought transdisiplinary scientific thinking to a very
traditional field of science, and presented inovative results. R enfrew’s articles have started
a vigorous debate on many aspects of archaeology, and initiated a complete rethinking of
what causes evolution of language and cultural change. The phyologenetic trees are used
to present the evolution and history of languages. This approach has been criticized in
the literature as being too simple and omitting many aspects. The phylogenetic tree is
of course nothing but the projection of a multi-dimensional figure onto two-dimensional
paper. It implies that several different phylogenetic trees may be all correct because they
represents different projections onto paper.
3 Objectives
The objective of this study is to mathematically model the language distribution patterns
in Eurasia as a result of major movements of paleolithic and mesolithic peoples in Eurasia
during the time period from 100,000 BC to 10,000 BC, and on this overlay the effect
of the neolithic transition 10,000 BC to 2,000 BC causing a demographic inflation of
the population sizes. The models is much based on ecological mechanisms for driving
the population transfer. The calculations are analyzed by using linguistic information,
genetic information and archaeological information, in order to obtain an overall view of
language and proto-culture origins and dispersal in Eurasia. The model will be used for
(1) establish linguistic classifications based on the model alone, and (2) synthesize the
results of the model with the earlier language classifications of Ruehlen (1988) to yield a
new picture. Several hypothesizes have been formulated, and which will be tested with
the model. These are
1. The pre-colonial genetic pattern of the world’s populations can not be explained
mainly by demographic processes starting in Africa more than 100,000 tears ago,
only if it is modified by the processes started by the invention of agriculture in the
Middle East and central China.
2. Language is not the primary identifier of ethnicity and language can not be modelled
by a linear dependence on genetic ethnicity.
3. The model results do not support the large language families (Nostratic, Dene-Sino-
Caucasian. Austric, Amerind) proposed by comparative linguists.
4. The main driving forces for demographic expansion from the beginning until 1,500
BC are not of ecological nature.
4 Theory
4.1 Principles of change
All processes of change requires per definition a driving force. This is also true for lan-
guage change. Renfrew (1987, 1989) states that "without a true mechanism and a driving
force, there can be no change”, pertaining to linguistic or cultural change, this is a ba-
sic principle very well known in basic natural sciences, indeed, it is the Second Law of
thermodynamics, and has universal validity. Language change can always be modeled, as
long as the kinetic rules and the boundary conditions can be properly defined. T he major
problems are finding numerical values for rate coefficients and field data for model verifi-
cation. The model must always fulfill two conditions in order to be justifiable; It must be
both calculable and it must be quantitatively verifiable. Models are especially important
in research, not because they produce results of their own right, but because they allow
complex and non-linear systems to be investigated and data from such systems to be inter-
preted. When forced to form laws of change, equations and set values to coefficients, then
the formal understanding of the system is tested. There are no "maybe’s” in modeling,
as all parameters are assigned quantitative values according to unique and precise rules.
It is also important to recognize that some prob-
lems are so complex, non-linear and involve So tanguage *.
many interconnected processes that no predic- change
tion with any certainty can be made without a +
model. Modeling language change with time
and simultaneously modeling ethnic dispersal D . +
; jemographic
geographically may be an example of such a change
complex problem where the use of models are
of great help. J ust stiffly claiming that two lan-
guages are not related, is also a model, even if Cultural
change
it is a simple one. Such a model does not live A
up to the criteria of calculability and verifia-
bility as defined above, and is therefore of no Figure 1: The connection between
scientific value. There are basically two ways fanguage, demography and cultural
of testing the validity mathematical models. It change.
can be done either by testing against hard data,
which means words from written records, or indications from archaeological and genetic
data. The model will have to predict that certain populations advance to geographical
points in space and time as indicated by archaeology and subsequently arrive at the correct
final distribution of populations. Simultaneously it should match the observed pattern of
language distribution before the onset of large scale political movements of peoples and fit
the observed historical and present genetic pattern. In order to discuss language grouping
inter-relations and explain how they can be derive from each other, we have to define
the mechanisms by which we hypothesize the dispersal occurred. We will not accept that
change just occur with no mechanism at all. When a language has spread to an area
or overlays the established language in a region, then this can only happen if there is a
valid ecological or political mechanism for the transition. This will also have consequences
for the relative relatedness of different languages, and will help us in deciding between
different hypothesizes and hierarchies of relatedness which have been forwarded. Renfrew
(1990) has stated that the earlier applied equation describing that states are related such
as culture to population to language should be abandoned in favor of a differential model
stating that the change in one system will induce change in connected systems; language
change is proportional to demographic change which is proportional to cultural change.
This view forwarded by Renfrew (1990), was utilized to explain the origin of the Indo-
Europeans in Europe, combining the modeling of agricultural dispersal by Ammerman
and Cavalli-Sforza (1984). This is identical to the statement of Levenspiel (1980), where
the first equation represents the descriptive approach to industrial engineering utilized
before 1950. Levenspiel illustrated the development of process modeling with time in
engineering as the development through three stages:
Qualitative Direct quantitative Differential rate based
description -+ description in terms — on underlying physics
of observables and processing conditions
The consequence for language change would be to write language change as a dif-
ferentuoal equation where the change is driven by those conditions influencing language
change in every moment (demography, social order, political order, subsistence conditions,
ecological conditions, outside pressure, cultural conditions and state...). Potentially the
quantitatively functional dependency on the actual conditions would be more difficult to
define in mathematical models for linguistics and archaeology, but the study of Ammer-
man and Cavalli-Sforza (1984) is an excellent example of the feasibility in this and the
large possibilities in such a approach. It is also important to realize that certain problems
are so complex, non-linear and multi-dimensional, that quantitative differential models
are required for the solution of the problem. In such cases, the solution would simply
be beyond the reach of empirical approaches, linear regressions, descriptive efforts and
paper-and-pencil-only approach.
4.2 Mechanisms of language change
There are principally three different mechanisms of language change:
1. Initial colonization
2. Replacement:
« Demography-subsistence mechanisms
* Political mechanisms
* System collapse mechanisms
3. Continuous development
Climate and vegetation for very strongly influencing boundary conditions to all mecha-
nisms.
Climate change may induce a
movement leading to initial colo-
nization, climate change may also
change the rate of colonization most _ Population
significantly. The first and last dena
mechanisms are obvious in their
manner of working, whereas the re-
placement mechanisms need some
further explanation. W ith the devel- wa. wl * Moral
opment of political states and more \
complex societies, new mechanisms
of language replacement and disper-
sal evolved such as colonization and
forced settlements, variants of the
elite dominance mechanism. T he in-
troduction of superior war technolo- Figure 2: CLD of the basic population model as it
gies and metal represents a possibil- was realized in the LANGUAGE model.
ity for conquest and political domi-
nance. A special case of the system collapse mechanism is ecological collapse, such as
desertification of agricultural land, salination problems from irrigation, rise in sea level,
glaciation advances, climate change or epidemic events which cause system collapses, or
even outright depopulation. This way ecological events can depopulate geographical ar-
eas by extermination or exodus, preparing it for repeated initial settlement. The other
possible cause for initiating a population migration, is overpopulation in a case where
child mortality is decreased simultaneously with an increase in fertility. Then a relative
shortage of land can occur and a migration be initiated.
“ie
Water
Soil fetility
4.3 Neolithic transition
Dr. A. Ammerman and the Professor of Genetics at Stanford University, Dr. Luigi
Lucca Cavalli-Sforza modeled the genetic pattern of Europe, using a demographic dif-
fusion model to simulate the effect of the neolithic transition in Europe as early as in
1984. The prehistoric transfer of people into Europe correlated well with the available
dates of first appearance of neolithic farmers. The model was based on a demographic
diffusion principle. The present study owes much of its basic principles to that study.
Their modeling patterns were used by Renfrew (1990) to draw conclusions on the origin
of the Indo-European language. Ammerman and Cavalli-Sforza (1984) found that any
type of ecological advantage permitting a higher population density than the aboriginal
population, will eventually evolve into wave-of-advance moving over the territory, where
the population change occur in the wave front (Fig. 6). Over flat landscapes such as
in central Europe, the wave of agriculture advanced on the average 800-1,000 km per
millennium. In ecologically less advantageous conditions the rate of advance will be less.
The demography-subsistence mechanism imply that the original inhabitants are either
outnumbered or assimilated, in principle no violence is necessary. There are no migrating
hordes, and no planned colonization as the greeks did much later, but rather the slow
diffusion forward by a modest random and local migration activity. This is equivalent
to the situation where the son will make his new farm next to his fathers farm in the
general direction of available new land. The mesolithic groups pre-occupying the land in
much smaller number will simply be massivly outnumbered or assimilated, unless they
adapt the more superior food production technology. The archaeological record will not
show any trace of catastrophic events or sharp breaks in culture, as the the agricultur-
alists are introduced into the system as a minority, and simply outgrow the others.
The record will accordingly show a
continuous change, and a significant
increase in population density. In
the demographic diffusion of agri-
culture, we must also consider the
potential for herding, implying that
the growth of a population coming
in, may push a part of the aborig-
inal population before it, thus in-
creasing the population density of
the aboriginal population and later
causing a counter-pressure to oc-
cur. The idea of agriculture may
also diffuse faster than the advance
of population increase, which also
will have a similar effect of creat-
agricultural
substrate
hunting *
substrate ~~ population ~
beat growth
a et
fishing er
substrate yes on
3 aN
acculturation : noe
predation _-/
Figure 3: CLD of the population and population
submodel as it was realized in the LANGUAGE
model.
ing a counter-pressure to the ad-
vance.
southern France and Scandinavia.
Apparently this was what could have happened in the Iberian Peninsula,
In southern Scandinavia there was possibly an
early adaption of partial agriculture by the semi-mesolithic Ertebdlle culture.
4.3.1 Demographic diffusion
The principle of partly assimilation and partly
herding of the aboriginal mesolithic population
is illustrated in Figure 6. The basic equation
for demographic diffusion into an area such as
the neolithic transition in Europe, is the general
equation for diffusion and simultaneous reaction
of the diffusing substance, called the equation
of continuity, derived from the principle of
mass conservation in a system (Bird et al., 1960;
Cranck, 1979; Sverdrup and Bjerle, 1982, Am-
merman and Cavalli-Sforza, 1984). It describes
the transfer of two substances through a volume
element fixed in space, in our case the transfer
of two types of population through a land sur-
face element fixed geographically. One basic as-
sumption is that the concentration within the
geographical element of infinitesial size is uni-
Temperature
Soil
ax +
+ Growth
eaettiai tae
JN Water
Accumulative
civilication
advances
Figure 4: CLD of the environmental
adjustment of the rate coefficient in the
population growth submodel.
form. For each element we have the basic mass balance equation:
production + in = ackumulation + out (1)
For population change this implies having human individuals as the substance. Or-
ganic growth in numbers occur when the humans convert resources within the geographical
element to energy and mass in order to give birth to new members, positive production,
and when individuals die, negative production. Numbers in the geographical element is
also changed when individuals enter the geographical element from another element or
when they leave it. Under conditions where a neolithic population is diffusing into the
area, the diffusion of mesolithic hunter-gatherers out of the area will be proportional to
the total number of peoplein the area. The diffusion of neolithics into the area will depend
on the gradient, that is the difference between the population density behind the wave
front and that before it. Mostly the density of mesolithics will be neglible as compared
to neolithics, but there are som important exceptions. In cold areas will the fertility of
the land decrease, and the saturation population density for neolithics will be lower. At
some point it will sink to the level of the local mesolithic population, at which point the
diffusion will come to a halt. This ocurred in Scandinavia. There are also locations in the
Bay of Bisquay, in Denmark or Scotland where fishing resources or local aboundances of
game allowed the density to become higher than normal. In such areas, the diffusion of
neolithics will be slower or even halted completely. This is what we believe happened to
the Basque speaking population between Spain and France. We assume that the farming
population, utilize the landscape for hunting just the way the mesolithic population would
do in addition to their farming activities. Thus within a cell, the mesolithic poulation
will be subject to both adsorption into the farming population, and a large urge to leave
for other hunting-grounds. For any population, this implies a basic transfer equation in
traditional algebraic notation:
SP = D.Vp+Q-Vptr (2)
where V is the Nabla differential operator (km~+), p is population density (persons km~?),
D is the diffusivity of population (persons km~ yr~+), Q is physical flow rate of popula-
tion unit (persons km~?) and r is the net population growth rate (persons km~ yr~}).
Diffusion of the mesolithic population is driven by the total population density during the
neolithic period. Values of agricultural diffusivity in Europe has been determined by Am-
merman and Cavalli-Sforza, (1971). Mesolithic population densities varied in the range
0.03-0.2 km~? in the past, under neolithic economies this the total population density can
rise to 10-15 km~? on fertile land.
4.3.2. Population growth kinetics
All populations exist in predator-prey relationships with the environment. This also
implies man, and this relation can be described with simplified equations for the growth
rate in a geographically fixed surface unit, for a population in general:
T = Pgrowth + Tacculturation — Tmortality — predation (3)
where r is the rate (persons km~* yr~+), Acculturation is the assimilation of one identifi-
able group into another group of the same species. Mesolithic populations are assimilated
into neolithic populations, but rarely the opposite. Vegetation cover was estimated using
the climate change models reported in the literature. Neolithic societies will tend to re-
duce the role of prey animals significantly as a source of nutrient, living off agricultural
products and farmed animals. For the agricultural population we need parameter val-
ues for growth rate coefficient for (a) agricultural subsistence, (b) hunting subsistence,
(c) fishing subsistence (persons kg~+ yr-1), animal hunting yield, agricultural yield and
fishing yield (kg km~?). The first term relates to substrate from agricultural produc-
tion, the second from hunting of large animals and the third from fishing and gathering.
Farmers are assumed to hunt and gather as effectively as a mesolithic population.
The growth coefficient Agricultural
is adjusted for soil fer- lands : £ Hinter-gatheret
tility as expressed by pepulation
the weathering rate and R
soil carbon content, soil B
wetness and tempera- + Farmer oa
ture. Total mortal- population cea
ity is assumed to be
proportional to popula- NO .
tion density saturation.
For population density
above the saturation den-
sity, the mortality is in-
finite. The saturation
coefficient would be re
lated to agricultural sus-
tainability depending on
such factors as water, temperature, soil fertility and agricultural technology efficiency.
The mortlity approach infinity when the population density approach the saturation den-
sity. The physical reality of the density saturation coefficient falling below the ambient
population density would be the initiation of a hunger catastophe, which would instantly
reduce the population density to below the sustainability limit. For low population densi-
ties, the mortality stays nearly constant. The civilization development factor is an empiri-
cal function derived from the idea that all humans have contributed to the advancement of
civilization, the collective accumulated cultural inheritage. The function thus integrates
the number of peoples over the whole area in each geographic cell and time to determine
the civilization advance in that cell at a particular point in time. The integral is integrated
from t=0 to the time after the initial staring point, and thus does not fit calendar years.
The mesolithic population is also absorbed and assimilated by the population with higher
material standard and higher population density. This is assumed to be proportional to
the product of the population density of the absorbing and the absorbed population. The
rate of acculturation in relation to the neolithic population is positive, since individuals
from the mesolithic population are absorbed. For the paleolithic/ mesolithic population
we have a similar set of rate expressions for growth, mortality and loss due to assimila-
tion in the agricultural population. The growth rate will depend on hunting gathering
and fishing only. The mesolithic population losses individuals due to assimilation in the
neolithic population. Kinetics of populations are often modeled using Michaelis-Menten
kinetics for growth minus a mortality rate (Chapra and Reckhow, 1983, Sverdrup et al.,
1991). For an agricultural population, growth depend on ecological factors and the abil-
ity of the population, making growth to a certain degree independent of the population
density, below the over-population threshold. Growth on a mesolithic level depend on the
density and absolute volume of the resource upon which the mesolithic population live.
The coefficients k,, represent acculturation, the shift to food production from hunting and
gathering by the mesolithic population. Warfare and spread of contagious dangerous dis-
eases upon contact, have been neglected as insignificant long term processes. T he growth
of social structure and rise of polity and central government may enhance trade and other
contacts between population groups and increase the value of k:4.
Figure 5: CLD of the competition between a farming popula-
tion and a hunter-gatherer population. It can be seen that the
hunter-gatherer population has no feedback on the farmers,
whereas the farmers have a limiting feedback on the hunter-
gatherer. The hunter-gatherer population will be the obvious
long term loosers in this game.
4.4 Paleolithic diffusion
In the paleolithic and mesolithic stage, mod-
eling of movements is more difficult. In this
study, we have modeled the initial settlement of
Europe as a function of temperature and sub-
strate (Game for hunting). This would tend to
take into account the effect of disappearance of
big game, as well as climatic variations affect-
ing the ecological conditions. Paleolithic and
mesolithic mans wanderings was governed by
temperature and availability of prey animals,
and limited by competing groups and scarcity of
prey. Accordingly, they would move along gra-
dients in population density, prey density and
temperature gradients in the absence of farm-
ing populations. T he net population production
depend on the amount of substrate and ecolog-
ical factors, but the acculturation term is zero.
The invasion of biomass is assumed to follow
clearance of land from ice by instant seeding of
grass. In large part of Eurasia, another species
of man lived, Homo erectus, and in Europe
also Homo neanderthaliensis. How the ad-
vancing modern man interacted with the pop-
ulations of these other species was in principle
ignored but for one exception. Modern man was
not allowed to advance into Europe neither from
Anatolia nor from North Africa, before 50,000
BC, and then from central Asia. This repre
sent a forcing of the model, and generate signif-
icant uncertainty in the calculations. Without
this restriction, the present genetic pattern can-
not be recreated from any initial starting posi-
tion. The wild vegetation invasion diffusivity
in previously unvegetated landscape is similar
or slightly larger than the diffusivity of agri-
cultural advance in Europe (Ammerman and
Cavalli-Sforza, 1984). The rate has been mea-
sured for post-glacial conditions at several lo-
cations (Ugolini, 1986). The ecological factors
Neolithic
3 Mesalithic population
§ | populahon\, 7) BS
| \ “as
3 \ f
Pai a
Geographical distance
z ;
3 /
g /e—-| 2
4 ;
Geographical distance
Fy ———————
4 —— 3
3 wt
a fa—\}
“= je
a
Geographical distance
>
§ Le
yn, A
s |)
3 | +]
a }
be {|
B
2 }\
Geographical distance
Figure 6: The evolution of demographic
diffusion over time. The wave of ad-
vance of the population density for
farmers move in a front at constant
speed. A part of the hunter-gatherer
population is assimilated, the rest is
displaced. Over time, the displaced pop-
ulation builds up a counterpressure to
the advancing wave, if they can main-
tain the population density with modi-
fied food supply methods.
enter the calculations by the growth rate coefficients and the mortality coefficients. The
factors are affected by temperature and annual rainfall, the transfer coefficient and dif-
fusivity, are also affected by the roughness of the landscape. For the establishment of
a functioning vegetation and fauna, the temperature dependence of growing trees and
shrubs was used, and accordingly the temperature dependence of the lowest trophic level
of the mesolithic ecological system. However, for the human population a stronger depen-
dence was used due to the fact that humans are more mobile and thus more adaptive in
terms of changing his environment. The temperature dependence of neolithic population
density was set at a value derived from data of population density gradient going from
southern Europe to middle Scandinavia, where the population saturation density for farm-
ers were assumed to go from saturation in Northern Italy to approach hunter-gatherer
population densities in the north. For the hunter-gatherer populations, the saturation
density is dependent on the production of prey, depending on the production of grazing.
Accordingly the temperature dependency observed for boreal forests were used.
Within a short time the gradient at the wave front will reach a pseudo-steady state, and
the wave propagation velocity will depend only on the difference between the population
density before the front and after it, however modulated regionally by landscape diffusivity
and ambient temperature. T he wave propagation velocity can be approximated when it is
assumed that the diffusivity is constant in time and space, or alternatively, changes in D
occur over timeperiods one order of magnitude faster than the adjustment of the gradient
from one steady state to another. The rate of transfer at steady state in the wave front
for the neolithic population can then be approximated with:
uy = kr: (pws — pas) (4)
where wy is the neolithic population density wave velocity (km yr-1), kr is the transfer
coefficient (km? yr-1), pyg is the neolithic population saturation density, 3-12 km~* and
pus is the mesolithic population saturation density, 0.02-0.05 km~*. For the time period
before agriculture, mesolithic transfer occur according to:
vm = kr: pas (5)
where vy, is the mesolithic population density wave velocity (km yr-1). The transfer
coefficient is adjusted for surface roughness:
kr = ko: f( ) (6)
where ko is the reference transfer coefficient (km? yr~4) and f( ) the landscape roughness
response function (0-1). Roughness affects transfer in the same way as surface diffusion
is affected on an adsorbing surface:
f()=(-)" (7)
where is landscape slope (m km~*) and n roughness order. The steady state population
density is adjusted for temperature and water availability changes over time:
p= po-V(w) - 9(T)- f(F) - C(civ) (8)
where po is the reference steady state population density (km~1), p the steady state pop-
ulation density (km~1), f(F) is a fertility index function, g(7) the temperature depen-
dence, V(w) the water availability dependence and C(civ) theumulative cultural inher-
itance. In general terms the water availability function is expressed with a function
analogous to water absorption to soil particles:
nici . 1.25- FO.
Viw)= FC18 + 42.6-wi8 (9)
where FC is the field capacity (m? m~3) and w the soil water content m3? m~3). Soil
fertility is a function of many factors such as nutrient availability, soil carbon content,
clay content, expressed as:
A(F)= 1: 2° 3 (10)
Transfer mechanism Transfer rate ky K,
Neolithic diffusion 0.8 km yr-? 0.3 km3yr-?_ 5 km-?
Mesolithic diffusion 0.3-1.5km yr-? 0.3 km3yr-? 0.02 km~?
Table 1: The transfer rates, transfer coefficients and intrisic saturation population densi-
ties used in the calculations with the LANGUAGE model. The values were derived from
archaeological data before the calculation were initiated.
where the fertility index dependent on nutrients like Ca, Mg, K, P is:
- min, (ue2an) 1a
WMax
the dependence on carbon substrate is given by the amount of carbon in the soil:
= LOI (12)
riot Kror
and the nutrient holding capacity is dependent on the amount of clay:
3= 1°@ctay:(l— 2° 2ctay) (13)
the symbols are w is flux of nutrient i, x,.; is the restiction ratio, i is the nutrients Ca,
Mg, K, P, C, xzo, is the soil clay content, %/ 100, x, is the soil organic matter content,
%/ 100, W is weathering, D is deposition, L is leaching and a coefficient. N content
in the soil and long term avaliability is a dependent variable with respect to soil fertility
and vegetation type. The temperature dependence is assumed to follow the Arrhenius
function: 1
g(T) = 929/57) (14)
where To is the reference temperature (degrees Kelvin), E, is the energy of activation
(kJ mol-}), R is the universal gas constant, 8.31 k) mol~?°K -? and T is the temperature
(degrees K elvin). The temperature and soil moisture saturation dependence is set at the
same as that for forest vegetation, as the temperature and moisture sensitivity is related
to the complete ecosystem as an entity and not the single species. We have used the
Arrhenius relationship here for its simplicity of use and the easy access to annual aver-
age temperatures for Eurasia. An alternative would have been to use the temperature
sum, summing up the effective temperature-growth-days during a year. The tempera-
ture dependencies used in the calculations are for demographic agricultural diffusion rate
£,=56 kj /mol, for the Paleolithic/ M esolithic diffusion rate, Z,=22 kJ/mol, for natural
vegetation growth, £,=56 kJ / mol, and for organic matter decomposition, £,,=48 kJ / mol.
5 Input data, boundary conditions, test data
Our model of language dispersal should from the chosen starting point, arrive at the
known genetic pattern observed, as compared with language dispersal in historical times.
There are a number of dated events that can be used to constrain the model. The
paleolithic expansion was prevented from entering Europe through Anatolia until 40,000
Event Date
African migration to Near East 105,000-95,000 BC
Migration from Central Asia to Northern East Asia 50,000 BC
Migration from Central Asia to Southern East Asia 60,000 BC
Modern man replace neandertals in Europe 45,000-35,000 BC
Migration into Australia 40,000-30,000 BC
Amerindian migration to America 25,000-15,000 BC
Eskimo-Aleut migration to America 15,000-12,000 BC
Na-Dene migration to America 11,000-9,000 BC
Table 2: Archaeological dates can be used to date some of the nodes in the genetic tree
derived by Cavalli-Sforza et al., (1988), Cavalli-Sforza, (1991) and possibly some of the
nodes in the language tree (Clark and Piggott 1985). Such data has also been used to
check the performance of the model.
BC. The calculations, rest partly upon soil data sampled throughout Far East Asia on
a 0.5° by 0.5° grid, in Russia on a 150 km by 150 km grid, in Europe on a 50 km by
50 km grid and in Africa and America on a polygon basis approximately comparable to
a 2° by 2° grid. The temperature is of large importance in the model, and temperature
distribution patterns over Asia were utilized to distribute the effects of global change on
the local climate in Eurasia. The global temperature variations over the last 170,000
years and since the last glaciation has been shown in Fig. 7, together with the average
summer temperature in Southern Scandinavia for the period 12,000 BC-present. Initial
settlement of Europe occurred approximately 50,000 BC from the East. In 32,000 BC, a
period of very cold climate started which lasted till 23,000 BC, the Wurm-Weichsel glacial
maximum. This maximum transformed the Central European fringe to the icesheet to
a very cold polar desert. The paleolithic resettlement of Europe after the retreat of
ice approximately started maybe as early as 23,000 BC, but gained momentum 15,000-
17,000 BC due to significant warming of the climate, when the polar desert disappeared.
It represents an ecological event which can have carried a new population into a virtually
empty region. The change from paleolithic to mesolithic also represents a large cultural
change with possibly ecological causes, capable of changing the population density and
hence population. The upper paleolithic had been based on reindeer and its hunting
grounds on the tundra relatively close to the continental icecap. T he period called Y ounger
Dryas, a cold period lasting from 8,800-8,300 BC, had a particularly profound effect on
the conditions. It caused the already established northern boreal forest zone in Europe
to revert to cold tundra and arctic desert. This reduced the population density to a very
low level. The end of the Younger Dryas period saw the settlement of culture bearers
throughout Europe from central Asia and the Near East speaking a North Caucasian
language, filling the empty ecological space left as the reindeer hunters of the glacial period
pulled north with the ice and prey. This changed during transition to the mesolithic,
about 10,200-8,800 BC or after 8,300 BC, when the climate improved over larger parts of
Europe (the Alleréd oscillation or more probably at the end of the Younger Dryas cold
period), and the reindeer economy only survived for a period in theA lleréd-Lyngby culture
in Denmark. The mesolithic culture involved a more sedentary lifestyle relative to the
reindeer cultures of the tundra. Research has established connections and relationships
between languages on pure linguistic data. T hese linguistic reconstructions are based on
°
TTT
Temperature deviation from 1990
by
100 10
kYr BP
Figure 7: Example of temperature data used. Average temperature in Greenland during
the last 250,000 years. The data was digitized from the published work of Dansgaard et
al., 1990 given as a diagram in Calvin (1994). A number of rapid changes can be seen.
The changes are especially large and rapid in the time periods of 145,000-115,000 BP,
13,000-12,000 BC and 11,000-9,900 BC. These time intervals are very important in the
history of man.
rules which are basically the same language change laws which have been brought to play
between languages within establishedlanguage families. Especially the Indo-European
languages and the languages of the P acific Ocean have been thoroughly studied, and many
of the proto-languages constructed. The same rules can also be applied when starting
from proto-languages in order to study the relationship between language families. The
fact that the rules must work both ways, constrain the model of language change over
time considerably more than just using the model for bilingual comparison or comparisons
from within a language family. The model is not correct unless the derived proto-language
from several languages and the derived proto-language from the proto-proto-language are
identical. This has changed some of the rules for language change (Greenberg, 1990;
Kaiser and Shevoroshkin, 1989). The strength of the outside-inside approach is of course
that the information inside the language group is independent of the information used
from the outside of the language group, i.e. the information from other languages in
the same supergroup. In this study the the diagrams over language family structure is
generally based on the model calculations, and not the structure of the group as it has
been derived from linguistic data. One aim has been to test the hypothesis that the
language phyle Nostratic, Austric, Dene-Sino-Caucasian etc., are valid genetic language
nodes that would be supported by the model calculations. We cannot prove this, but
we can show that it is possible, and maybe very plausible. Thus, our phylogenetic trees
should best be compared with language classifications such as that of Ruehlen (1988,
1994). The language relationships are presented as phylogenic trees.
Archaeology and history forms the ultimate data backdrop for checking the theories.
Archeological artifacts do not carry any indication of the language of their makers, unless
inscribed in written language, but still can give indications of when a certain type of cul-
tural change took place as well as indications about the relation of individual cultures to
other cultures. The first appearance of man in a region is valuable information. Recording
Event Dating Date Reference Model
method prediction
Proto-Dene-Sino-Caucasian G 8,000-7,000 BC Starostin 1989 20-50,000 BC
Proto-Dene-Sino-Caucasian G 8,000-7,000 BC Peiros 1990 20-50,000 BC
Proto-Sino-T ibetan G 6,000-5,000 BC Peiros 1990 7,000 BC
Proto-Sino-T ibetan G 7,000 BC Yakhonotov 1977 7,000 BC
Proto-Sino-T ibetan A 7,100 BC Chang 1990 7,000 BC
Proto-A ustric 7,000 BC
Proto-A ustro-T ai G 6,000 BC Reid 1989 6,000 BC
Proto-A ustro-T ai G 6,000-5,000 BC Peiros 1990
Proto-A ustronesian G 5,000-4,000 BC Peiros 1990
Proto-A ustronesian A 5,000 BC Tryon 1985 5,500 BC
Proto-Nostratic G 11,000-10,000 BC Starostin 1989 12,000 BC
Proto-A fro-A siatic G 11,000-9,000 BC Militarev 1989 12,000 BC
Proto-A fro-A siatic G 10,000-9,000 BC Starostin 1989 12,000 BC
Proto-A kkadian-Semitic G 2,300 BC Starostin 1989 5,000 BC
Proto-South Semitic G 2,000 BC Starostin 1989 4,000 BC
Proto-Altaic G 4,500 BC Starostin 1989 4,500 BC
Proto-Dravidian G 3,000 BC Peiros and 3,700 BC
Shnirelman 1989
Proto-PlE-K artvelian G 9,000 BC Diakonov 1985 9,000 BC
Proto-Indo-E uropean G 6,500 BC Diakonov 1989 7,000 BC
Proto-Indo-E uropean A 7,000 BC Renfrew 1989 7,000 BC
Proto-Indo-E uropean G 4,200 BC Swadesh 1972 7,000 BC
Proto-Italic-Celtic G 3,900 BC Swadesh 1972 6,000 BC
Proto-Italic-Slavic G 3,000 BC Swadesh 1972 6,500 BC
Proto-Germanic-Slavic G 2,500 BC Swadesh 1972 5,000 BC
Table 3: Approximate dates of separation of some language groups as estimated using
glottochronology (G) or archaeology (A). The dates were taken from the authors indicated.
the time for major cultural changes may also be helpful. A set of dates for the first arrival
of modern man throughout Eurasia are available. The model must be able to reproduce
calculated values reasonably close to these values. Archeological dates can be used to
date some of the nodes in the genetic tree derived by Cavalli-Sforza et al., (1988), Cavalli-
Sforza, (1991) and possibly some of the nodes in the language tree (Clark and Piggott
1985). Data on first date of arrival has been listed in Tab. 2. Agriculture arose inde
pendently certainly in two, maybe three locations in Eurasia, (1) in the fertile crescent,
(2) in South-Central China and (3) probably in Northern China. Approximately 12,000
BC, wheat was harvested systematically in the Natufian culture in southern Palestine.
The plants harvested, were wild and the full domestication process took perhaps a millen-
nium. At a single habitation site, domestication can take considerably shorter time (50-
100 years), but since the process has elements of randomness, it probably took longer for
a whole region to systematically adopt cultivation as the major source of food production.
W heat is cultivated on a larger systematical scale in the Levant and in the Northern part
of the Fertile Crescent around 8,000 BC. During the initial phase when the domestication
is taking place and cultivation technics are developed, the efficiency of cultivation steadily
increase. When a critical yield is reached, farming becomes the dominant source of food,
and the spread outward through demographic diffusion starts. Around 8,000-7,000 BC,
initializing agricultural nuclei was established around Catal Hiiyiik in the Conya plain in
present Turkey (Proto-Indoeuropean), the Natufian culture centered on J eriko and Wadi
Arabi (Proto-A froasiatic), maybe at Cayonu in eastern Turkey (Proto-North Caucasian,
Hatti), around Ali Kosh in the Southern Zagros M ountains (Proto-Elamo-Dravidian) and
maybe also at J eitun in Transoxania (Proto-Ugric-Altaic). We hypothesize that this ini-
tial phase concluded the division of the language group called Nostratic, a process that
must have started earlier with the retreat of the ice-sheets over central Europe. Agri-
culture based on millet and later wheat started as an independent invention in Northern
China occurred before 6,500 BC. At the same time, wet rice cultivation was initiated in
the central Yang Tze River region of China. This was perhaps a development initiated
from the Fukien-Tonkin area in Southern China around 8,000-7,500 BC, where horticul-
ture was the initial form of agriculture. The introduction of agriculture into the Indian
subcontinent probably occurred from Anatolia (Renfrew, 1989), entering India around
4,500 BC moving into central and east central india by 3,000 BC (Peiros 1990). Similarly,
rice agriculture penetrate from the east into central India around the same time. T he set-
tlement of America by Amerindians is hypothesized from Eastern Asia and the settlement
by Na-Dene Indians is hypothesized to have originated from the M ongolia-A mur region,
as indicated by fossil dental genetic data (Turner, 1989). The settlement of America by
Eskimos and Aleutians is also inferred to have occurred from the Amur region. The set-
tlement of J apan by J omon and Southern China occurred from the Sundaland region and
the much later migration of J apanese to J apan from K orea and Northeastern China. The
dates derive from archaeological dating at specific sites, possible languages affected by the
change have been suggested. The different dates were taken from M cE vedy, (1985); Ren-
frew (1987,1989); Renfrew (1989); Benedict, (1975); Bellwood, (1991); McAlpin, 1981;
Zvelebil and Zvelebil, 1990; Turner, (1989), Greenberg, Turner and Zegura (1988) and
Cavalli-Sforza (1992). Important corroborative data has come from different types of ge-
netic research on the populations of the world. One approach use present populations,
and analyses a different number of genetic markers. The relatedness of the investigated
populations can then be assessed and approximately dated. Assimilations and admixtures
are the major source of uncertainty, even if the most evident melting pots for populations
have been avoided in the investigations. The distribution of principal components of dif-
ferent genetic markers as revealed by a synthesis of different genetic markers not sensitive
to climatic adaption in Eurasia. It is interesting to study the genetic relations measured
by Cavalli-Sforza et al., (1988) and Cavalli-Sforza (1991) on different human populations.
The relative relatedness of different populations was quantified using a number of differ-
ent genetic markers, and avoiding such genetic traits which are believed to be affected
by climatic adaption (Menozzi et al., 1987). The genetic tree as revealed in two different
studies are shown in Fig. 15. Whereas political mechanisms and elite dominance can
change language, only quantitatively significant population migrations and demographic
expansions show up in the genetic information. To Fig. 15 some footnote remarks can
be made: The Ethiopian people is known to have acquired a Semitic language in historic
times. Tamil and Lapp peoples are closer related to the Altaic and the Ugrian peoples, but
both have been exposed to heavy admixture of Scandinavians and Indo-Aryans, respec-
tively. The Tibetan people was a M ongolic tribe which acquired Sino-T ibetan language in
historical times. The Ainu people is very heavily admixed with J] apanese, and the genetic
signature may be totally muddled. The Siberian Turkic peoples may have experienced
admixture from Paleo-Sibirian groups. A similar genetic tree was constructed based on
nuclear DNA, indicating an African branch, a West Eurasian branch and an East Asian
branch (Stringer, 1990). Cavalli-Sforza et al., (1988) had unfortunately not sufficient data
on the Basque, Caucasian and Northern Chinese populations to assess their proper place
in the phylogenetic tree, their mutual connection as indicated by linguistic comparison,
and the linguistically indicated affiliation with P roto-Nostratic. The Basque sample was
pooled with the European, but other studies show the Basque population group to be
genetically very different from the present European population. It is generally accepted
that the Basque are a remnant of the Pre-Indo-European population of Europe (Bodmer
and Cavalli-Sforza 1976, Nei and Roychoudhury 1982). In the study of Cavalli-Sforza
et al., (1988) Sino-T ibetan was by mistake assigned to the Southern Chinese population
group, but this is more correctly placed within Austric. Chinese linguists are well aware
of the fact that the population of southern China (Chang 1990) spoke an Austric language
distantly related to Miao-Yao. Miao and Yao are the relict languages of Southern China,
and was earlier spoken over most of the Southern Chinese territory (the Chinese called
it "Man”). Through political mechanisms and events, recorded in old texts, in the dis-
tant historic past (Han dynasty), Miao, Yao and similar languages of central China were
replaced with Old Chinese. This is supported by data from Turner (1985) which also
shows a genetic difference between the Northern Chinese population and the Southern
Chinese population, "sundadontry” of Southern China versus "sinodontry” of Northern
China. The Southern Chinese population tend to cluster with the] apanese and the Indo-
Chinese. The affiliation of J apanese with Southern China may come from the fact that
the Austric agricultural diaspora started here sometime during 8,000-7,000 BC. Turner
(1985) showed using fossil dentition that the origin of J omon may be in Southern China.
The connection of the Ainu with Southern China is also supported by fossil dental data.
Whereas different political mechanisms migrations, demographic diffusion and expansion
and elite dominance all can change language, only quantitatively significant population
migrations and demographic expansions show up in the genetic information. Some of the
nodes in the genetic tree can be dated on archaeological data, but models for genetic
change over time share some of the same uncertainties as the glottochronological model.
The rate of evolution is not necessarily constant, especially in the view of the the very
large climatic and ecological changes seen in the paleolithic. The calculations are carried
out in two steps. Phase 1 comprise the initial peopling of Eurasia by modern man and
spans the time period 100,000 BC to 8,000 BC. It is initialized with 10,000 individuals
in Northeast Africa in the location of present day Cairo, an equal number stand ready
at present day Djibouti on the coast of Ethiopia, on J anuary 1., 100,000 BC, all having
uniform language, new brains and full of initiative. The known initiation locations for
the introduction of agriculture in the old world can be summarized as follows. The main
loci for demographic expansion, initiated by the invention of agriculture are (1) in the fer-
tile cresent connected to the Nostratic languages A froasiatic, Indoeuropean, K artvelian,
North Caucasian and Elamo-Dravidian, (2) Anyang, Northern China connected to Sino-
Tibetan and (3) Fukien connected with the Austric languages. Additional secondary loci
of lesser importance for the final global result may be Southcentral Sahara (4), connected
to the Nilo-Saharan languages, and Transoxania for Altaic languages (5). Phase 2 com-
prise the neolithic transition in Eurasia during 8,000 BC to 1,500 BC. The demographic
diffusion due to neolithic transition is started in the Far East in the Chinese Central Yel-
low River Vally approximately 7,500 BC, at the same time in southern Chine in Fukien.
It is also started in the J erico 8,800 BC, creating secondary initiation centres by 6,800
BC in different parts of the Fertile Crescent and Anatolia.
6 Results
6.1 Units
The model is used to calculate the results in terms of:
* First date of arrival of wave of advance
* Geographical area covered as a function of time for
- huntergatherer population (km?)
- neolithic population (km?)
For the neolithic population, the area of expansion and number of speakers can be
integrated per language group as seen expanding from each initial nucleus.
* Population density in each grid
* Total integrated population number for
- huntergatherer population (persons km~)
- neolithic population (persons km~?)
* Fraction of original language remaining, using the calculated variable isogloss rate
over time
Soil fertility is calculated as a function of soil moisture and chemical weathering rate
(Hettelingh et al., 1995), climate is expressed in terms of temperature, annual rainfall
and annual precipitation surplus (K uylenstierna et al., 1995). Language isogloss retention
is calculated, assuming a simple linear glottochronological model, but applying different
loss coefficients for paleolithic, mesolithic and neolithic times.
6.2 Paleolithic Eurasia
The calculated situation in Eurasia during the paleolithic timeperiod from 100,000 BC
to 20,000 BC is shown in Figure 8. The map show the position of the front of the wave
of advance at different times. The lines are isochrons for the first appearance of modern
man throughout Eurasia. The black shaded areas indicate mountains, and due to a lower
sea level, much land in the Sunda region was dry in the paleolithic. The hatched areas
represents areas under ice. The glaciation situation has been simplified here in order to
allow to show the whole movement in the period from 100,000 BC to 10,000 BC. The map
indicate how modern man initially populated Eurasia. The dates are calculated dates.
The first divide between those moving southeast of Himalaya and the other moving north
and west create the divide between Austic-Indp-Pacific and Australian languages on one
side and Nostratic, Amerind and Dene-Sino-Caucasian languages. This divide ocurred
60-70,000 years ago according to the model. T he isoglosses found between these language
groups must be this old. Isoglosses that are also found in African languages must be older
than 100,000 years old. Such glosses have been found, and confirm that human language
is at least 100,000 years old. Nostratic and Dene-Sino-Caucasian divided as separate
languages from their common Eurasian ancestor in central Asia 40-50,000 years ago. The
period from 67,000 to 58,000 BC was among the coldes during the glacial period, and
at this time Central Europe south of the ice was probably a rather sterile polar desert.
This changed after 45,000
BC when a short pe
riod of somewhat warmer
weather followed. The
northern part will even-
tually develop into a
Dene-Sino-Caucasian group
in the West and North
and and Nostratic lan-
guages in the south and
northeast, the southern
movement contiues south
to become Austric, Indo-
Pacific and Australian
languages. The transit
through Siberia come in
the time period 50,000-
30,000 BC. After 40,000
BC this region was very
cold, and only a small
number of people may
have passed through. The
number indicated by the BPP: as cas cs
model for the population ; siest lt Glee OF
density in this area is “H 2 coe
small, and suggests that
this is a narrow section.
The implication is that
only a part of the genetic
signal may have passed
this constriction, mak-
ing the Far Norytheast
Asian population genet- Figure 8: The calculated situation in the timeperiod 100,000-
ically distinct from the 39 999 BC. The map show the calculated first appearance of
western far east Asian mesolithic cultures in Eurasia.
population. — Linguistic
and genetic data indicate that Amerind and Eskimo-Aleut must have taken separate
paths in North-Eastern Asia, and that they must have taken separate paths to Amer-
ica. The model does not have the required resolution in this area to explain any of that.
Eastern Eurasian languages splits in at two or three branches in Siberia in the time pe
riod 40,000-30,000 BC. One northern branch continues eastward to become divided into
Amerind, Eskimo and Chuckchi-K amchadal. One branch may move into the Amur-K orea
area and form Gilyak and maybe a part of what later was to make one of the elements
in Ainu. Dene-Sino-Caucasian is originally a language of the western Eurasian reindeer
hunters, which at the end of the glaciation after 30,000 BC spread eastward across Russia
and Siberia. The initial internal split in this group may have been as early as 50,000 BC
into an eastern and western branch. This is represented by the M acro-Caucasian group
(Bengtson 1991a,b,c; Sverdrup 1995, 1997), containing at least the ancestors of a western
group of Basque, Pictish, Iberian, a central group consisting of Ratian and Etruscan,
North Caucasian and another central group with Sumerian and Burushaski languages.
The eastern group, is what later became Sino-T ibetan, Y enesseian and Na Dene. During
the last cold period of the early post-glacial 25,000-19,000 BC, these populations were
shifted southward, thus establishing themselves in Northern China. This implies that the
model suggests that the ancestors of the Sino-Tibetan speaking Chinese came to China
from the very cold north approximately 12,000 BC. Any earlier Proto-Nostratic popula-
tion in the area would have disappeared. T he very cold period of the third Weichsel-Wurm
glacial maximum 26,000-15,000 BC moved the tundra border south, and possibly pressed
population groups in Europe and Central Asia farther south. Something similar but less
severe occurred during the more recent Older Dryas and Younger Dryas cold periods. In
Europe, this implied that the population density fell to very low level, and large regions
being polar desert would have been inhabitable. As the temperature rose after 21,000-
15,000 BC, there would have been a reflux of Caucasian languages northward into Europe.
There was a reflux from Iberia and Northern Africa along the Atlantic border towards the
north, and another reflux started from Anatolia going northwest. According to this sce
nario, the Eastern European branch of North Caucasian represented by Lemnian, R atian,
Elymian and Etruscan divided from P roto-North Caucasian in Northern Anatolia approx-
imately 12,000-15,000 BC. The western branches that originally split from Proto-North
Caucasian 30,000-40,000 years ago, divided internally into Proto-Basque, Proto-Iberian,
Proto-Pictish after 15,000 BC. This deduction is supported by the pattern of Gravettian
statues. Throughout Europe and Western Asia, small stone statuettes of similar shape
and basic design have been found (Renfrew 1994; Powell 1977). They all originate from
the time period 32,000-20,000 BC. The great consistency in form suggest some form of in-
formation exchange over the area covered by the finds. T he area covered by all these finds
represents an area with some type of cultural or maybe linguistic unity. T he information
exchange required to create such an uniformness, must have been occuring at a transfer
rate at least at a rate where the whole area involved could be traversed in one third to
one fourth of the span of the time period. T hus the information signal velocity must have
been at least 1,000 km per millenium. It is suggested that the language in this area was
Proto-western-Sino-C aucasian. It eventually split up into the Western branch which later
became Basque, Pict and may be Iberian, a central European branch later developing into
languages like Etruscan, Ratian, Elymian, Lemnian and the non-Indoeuropean substrate
language found in southern Italy, Balkan and Greece, and the Caucasian branch develop-
ing into Hatti, Urarti, Hurri, present day Northwest Caucasian, Northeastern Caucasian
and the rather distinct Sumerian. The cultures in this area have been called Capsien in
the Western part and Tardenosian in the central part, and the overlap with the Gravettian
statuettes is almost complete in the western and central parts. But the Capsien culture
may also be one with a different genetic heritage and language. It may be remnant of the
initial peopling of North Africa. In that case, Iberian or Tartessian may be remnants of
this language. Bone remains would tend to suggest that the population north and south of
the strait of Gibraltar was the same at this time, favoring an earliy Dene-Sino-C aucasian
population. For the period 30,000-16,000 BC, cave art occur throughout large the same
area. The cave art of northern Spain and southwestern France is famous, but very similar
cave art has also been found in Sicily and in the Ural mountains. No cave art is known
from central Europe, but animal figures in stone occur over the same area as the female fig-
urines for approximately the same timeperiod. It is suggested that all this art arose within
the same cultural area and mass of cultural inheritance. The uniformity seen in art and
sculpture suggests that the different groups communicated culturally enough for the lan-
guage with in the area to diverge at a lower rate and stay understadable between groups.
Thus branching to di-
alect level is assumed,
but not to single lan-
guage status. The model
calculations show that
Sino-C aucasian groups in
the fertile crescent, fore-
bearers of the Hurrians,
Urartians and Sumerians
are completely confined
by Nostratic languages
to the West, South and
Southeast, In the north,
the Caucasus mountains
form a slowly penetra-
ble barrier, after which
the steppe begins. Hence
an expansion of Cau-
casian has no outlet to
any significant amount of
territory fit for agricul-
ture. The implication
of this is that the west-
ern Caucasian languages
did not really start to
diverge until the cul-
tural changes that oc-
cured with the advent
of the mesolithic around
13,000-12,000 BC. Then
the population densities
rose somewhat, and there
was a change in economic
base and probably as a
result also in religion.
The calculated initial sit-
Figure 9: Calculated expansion due to demographic diffu-
sion driven by agriculture for Indo-European, Afro-Asiatic,
Ugrian-Altaic, Elamo-Dravidian, Austric and Sino-T ibetan
for the time period 7,000-2,000 BC.
uation in 12,000 BC, before the advent of agriculture is shown in Fig 8. The population
density in each grid depend on several ecological parameters, where water, soil fertility
and temperature play the major role. As climate change, diffusion population transfer
and saturation population densities will change.
6.3 Neolithic Europe and Africa
The known initiation locations for the introduction of agriculture are (1) in the fertile cre
sent connected to the Nostratic languages, Eastern A froasiatic, |ndoeuropean, K artvelian
and Elamo-Dravidian, and the non-Nostratic North Caucasian, (2) Northern China con-
nected to Sino-Tibetan and (3) Fukien connected with the Austric languages. W heat
is assumed to have been domesticated just after 9,000 BC, but the lag-phase when the
practice takes root and expands rather passively in the fertile crescent takes place 9,000-
7,000 BC. During this time the practice spreads as an idea faster than the population
increase, causing agricultural practices to cross several language borders at this stage.
This implies that groups
speaking Nostratic lan-
guages and North Cau-
casian get inoculated with
agricultural practices. By
7,000-6,500 all nucleus
sites reach saturation pop-
ulation density and start
expanding outward. The
neolithic revolution has
just started. Initial lan-
guage positions in Cen-
tral Asia at the incep-
tion of agriculture is
based partly on guesses
and partly on modeling
for the period 120,000
BC to 7,000 BC us-
ing the model. The
calculated situation for
the time period from
7,000 BC to 2,000 BC
is shown in in Fig. 9. Figure 10: Population movements 4,000-1,000 BC, driven by
Nostratic has completed political factors. The shown movements were not calculated
the process of crystal- with the LANGUAGE model, but inferred from published lit-
lizing into Afro-Asiatic, erature.
West-Nostratic compris-
ing Indo-European and K artvelian, and East Nostratic comprised of Elamo-Dravid, Ugric
and Altaic. The transition to agriculture creates a wave of advance traveling out radially
from the fertile crescent. In 3,000 BC, Nostratic has reached the Atlantic Ocean and the
Northern border of agriculture. Etruscan gets confined in the mountain valleys of the
Central and North Appeninne Mountains in Italy. Basque, Pict and Etruscan occupy
confined enclaves. Iberian may also be such an enclave, but the model cannot distinguish
between this alternative and Iberian being an Afro-Asiatic language. Fig. 16 show the
relation between the languages included in the Nostratic group. The northern branch of
eastern Nostratic (Altaic, Ugrian) adapted agriculture in Northern Persia/ Southern Turk-
menistan (J eitun) and moved north into central Asia. Ugric-Y ukagir-Altaic expanded
straight north confined by the Caspian Sea and the Hindu Kush, Finno-Ugrian expand
into the area between Volga and Ural rivers. Altaic languages occupy the territory east of
the Ural river towards the mountains. Further up Volga, this wave of Finno-Ugrian meets
Slavic languages. Finno-Ugrian can reach Finland and Northern Norway approximately
2,000-1,500 BC. Proto-Elamo-Dravidian diffuses out from the inner eastern shore of the
Persian Gulf together with agriculture starting at at the same time as the other Nostratic
languages. The languages that moved north and east will develop into Dravidian. It has
been acertained that Elamitic languages were once spoken over most of the Iranian plateau
in early historic times, 3,000 BC (Lamberg-K arlovsky, 1978). Approximately 3,500 BC,
the wave of agriculturalists speaking Proto-Dravidian language meets a comparable wave
of advance of peoples speaking P roto-A ustroasiatic in the middle of India. Fig. 12 and 13
show the development of population numbers in millions in the areas going through the
neolithic transition, and show the accumulated population number in millions in China
highlighted. It can be seen how the huntergatherer population is replaced by a neolithic
population, but that the hunter-gatherer population remain as not all land is suitable to
agriculture. The points represents the historical population counts available for China.
During Han times, the first population count was held in China and number of 52 million
was obtained. This did not comprise whole China as we understand it today, and the
population for the whole area may have been 65-75 million. Fig. 12 show the integrated
number of people of the world during the period 9,000 BC-2,500 BC as calculated by
the LANGUAGE model. It is evident that the hunter-gatherer population is relaced by
the neolithic population. The model estimate that the world had 400 million inhabitants
in 200 BC, excluding America. The standard deviation of the calculation from observed
archaeological data was calculated using:
(15)
The archaeological data was taken from Cavalli-Sforza (1988); Larichev et al., (1988);
Howells (1988); Chang (1988). The coefficient of correlation between observed and cal-
culated was r2=0.91 and the standard deviation =5,100 years, roughly equivalent to an
accuracy of +/-18% on the calculated value. Several inherent uncertainties of the model,
model geographical resolution and uncertainties in input data may theoretically be added
to the observed uncertainty in the test. The accuracy observed in the test is surprisingly
good. This is surprisng since large simplifications have been made in the model. It may be
asign that the model despite the simplificatiosn do incorporate the most important driving
factors.the present accuracy of the LANGUAGE model for the paleolithic period. There
is one anomaly that creates problems for the assumptions behind one of the languages.
Datings of first pottery, domesticated
animals and a semi-neolithic type of cul-
ture in central Sahara overthrow the sim-
ple assumption that all Afroasiatic lan-
guages expanded from J eriko with agri-
culture (K uper 1979). The archaeological
data suggests an expansion of a pottry cul-
ture straight east and west starting 9,000
BC from the Hoggar-T ibesti region. T his
may have been the original speakers of
Nilo-Saharan. The data also suggest that
the M ahgreb region was continuously pop-
ulated with the peoples that were bearers 60 80 100
of the Capsien culture, whereas south of Observed date, thousand years BC
the Atlas, the present desert, then steppe
was inhabited by peoples of African stock
(Nilo-Saharans). The Capsien cultural
bearers are with all probability thedecen- Figure 11: Date of first arrival in the inter-
dants of the original Cro-Magnon popula- val 100,000 BC to 20,000 BC plotted against
tion in this part of the world. The Basque archaeologically observed dates.
are believed also to be the decendants of
, thousand years BIC
Caleulated date
them as also studies on skelettal remains seem to suggest. The model can be reset and
run with this new set of initial conditions, and this yields a sligtly different internal rela-
tionship for Afroasiatic languages. It is probable that the initial split of Afroasiatic took
place in central Sahara, and expanded outward as Chadic, K ushitic, Beber and Semitic.
It must then have been Old Semitic that expanded north-, east- and southward from
J eriko, but the reflux back into North Africa moving over the semi-neolithic culture there
brought the K optic-Berber branch. By the time the expansion would have reached Libya
by approximately 4,500 BC, the severe drougt there would have effectively have limited
the impact of the demographic expansion to a small coastal band of North Africa. The
neolithic culture reached the Canary islands by this process by 4,000 BC. The earlier
language in North Africa was according to the model of the same origin as Basque and
probably Iberian (Capsien). The Model suggests that a small remnant of the Capsien
may have survived as an isolate in the central Atlas mountains. This would also seem
to explain what has been called an Euro-Africanian language group to which several
sub-Saharan languages, Berber and Basque has been assigned (Mukarowsky 1975; Scharf
1985). In reality, the resemblance with Berber must be from substrate influences, whereas
this substrate would have a true genetic affiliation with Basque. Studies on placenames
by Roman (1993) may suggest this is correct. The implications of this is that A froasiatic
should be more distantly related to the other Nostratic languages, and not belong to the
core group.
6.4 Neolithic East Asia
Fig. 9 show the calculated demographic diffusion initiated by the inception of agricul-
ture. For the calculation two primary focuses were used, and a third secondary was
allowed to form in the Central Yang Tze Valley. Austric has expanded with rice agri-
culture into Indo-China and Eastern India. The western wave of advance meets with
the eastern wave in Eastern Central India. The neolithic transition occur in north-
ern China through the cultivation of foxtail millet. North Chinese meets the Austric
expansion of rice cultivation coming from the south, north of the Yang-Tse Valley.
This leads to the conclusion
that Austric must have had
an ancestral home in Southern
China and that Chinese lan-
guage entered China from the
north or northwest. A later in-
trusion of Chinese into the to-
pographically very broken and
fragmented region by politi-
cal mechanisms would also ex-
plain why Austric languages
ae M ae and Teeiite Figure 12: The development of Eurasian neolithic pop-
alle Sy RIchleee one "rhe ulation numbers with time in the interval 10,000 BC to
region (Ruehlen ). © 1BC, as calculated with the LANGUAGE model. The
calculation can be interpreted ‘ cee) : ;
to suggests that Burushaski points represents historical population estimates.
gets isolated from other Dene-Sino-Caucasian languages in the Pamir Mountains, close
to where it is found today, by Dravidian and Ugrian-Altaic languages around 5,500 BC.
paula
~ + Hoots Cuneasian
O Omang
1 Dam chara
eeesazee
The model suggests that Burushaski is closer to the western Dene-Sino-Caucasian lan-
guage group, whereas Y enesseian is closer to Sino-Tibetan. Other interpretations of the
results are possible within the ranges of uncertainty, and linguistic data must be uti-
lized for choosing a certain interpretation. Bengtsson (1990, 1991) and Ruehlen (1994)
has pointed out several similarities between Basque, Sumerian, North Caucasian, Bu-
rushaski, Yenesseian and Sino-Tibetan in the core vocabulary. The domestication of
hoses in the Central Asian steppe around 4,000 BC lead to development of pastoralism
and military superiority by 2,800-2,300 BC. The formation of states starting 2,800 BC
and the rise of nomadic pastoralism changes conditions for language dispersal. From
now on political factors become more and more important in relation to ecological fac-
tors. The LANGUAGE model do not include such processes, and it cannot predict any
of the movements of nomadic peoples nor the effect of policies of the large empires.
Later movements as recorded in history and
as reconstructed from archaeological remains,
has been shown in Fig. 10. Nomads fill LANGUAGE social
the wast grass expanse from Eastern Europe
to the Altaic Mountains after the domestica-
tion of the horse that started around 4,000
BC. Peoples speaking Indo-Aryan languages ex-
pand their numbers due to greater mobility
and better economic success at herding animals,
and flood the Central Asian steppe, and con-
Ward poy stn
World populstion in wailion persons
tinue into Iran and India. Dravidian Brahui is 9 * ‘om mo n
isolated in Pakistan, Munda in Western Ben- Thoweand years BC
galia. The language of the Indus civiliza-
tion is in this study uniquely pointed out as Linch
speakers of Elamo-Dravidian languages. This
is in line with the Finnish results (Parpola
et al., 1977; Koskenkenni et al., 1973) Rus-
sian results (Knorozov, 1972) and the results
of Fairservis (1973), all pointing out Dravid-
ian as the language of the texts from the In-
dus valley civilization. The Indo-Iranian no- at I ie oe aD
madic movement breaks the language continum, “wiz 8 6 4 2 0 2
leaving only Elamite in the west, the pocket of Thousands of years BC
Brahui in Pakistan and the numerous Tamils
of Eastern India. Recent results (Lambert-
Karlovsky 1974) have shown that Elamite or Figure 13: The development of world
closely related languages were spoken in alarger and Chinese population numbers as cal-
part of the Iranian area during the neolithic cylated with the LANGUAGE model.
and bronze age. Peoples speaking Ural-Ugric yh, int ts historical .
languages may have been pushed North, and latis estimate = muerorea! Peps
groups speaking Altaic languages are pushed
east, into Korea and J apan. The Altaic speaking groups aquire the horse in this pro-
cess, where as the northern part of the Ural-Ugrians that occupy the wet forest zone do
not experience the superiority that came with the horse under their forest conditions.
The incipient Chinese state expands slowly south during 4,000-1,000 BC, and overlays
the Austric language group called Man in old Chinese sources, Miao-Y iao is a remnant
of the aboriginal population of southern China (Chang 1987). Within Austro-asiatic and
Austronesian languages supposed to belong to Austic similar words are used for tribal
name, language name, or word for male and man. The Tibeto-Burmans move into Burma
in a process of demographic expansion, and the very special topography in this region
creates several isolated pockets of Austric. The relation between the different language
groups are based on the model calculations, which agree with the linguistic data down to
very detailed levels.
7 Discussion
7.1 Mesolithic movements
The time around 111,000-105,000 BC experienced an interglacial warm period which could
have initiated a population diffusion out of Africa into Asia and Southern Europe. The
split between P roto-Nostratic and P roto-Sino-C aucasian must have occurred before 17,000
BC, since that is the latest date at which Eskimo-Aleut could have split off from P roto-
Nostratic and still made it to America in time.
The time around 45,000 BC and _ alterna-
tively 55,000-62,000 BC experienced global cli-
matic changes that pushed populations around
enough to have initiated such a division. Etr-
uscan and Basque, possibly also Iberian, A qui-
tanian, Ligurian and Pict (Caesar 44 BC; Barr-
aclough 1983) seem to originate in the from the
same roots as the East-Caucasian languages,
supporting the relatedness hypothesized from
linguistic data. It must have split from East
Caucasian before 12,000-15,000 BC. The move-
ments of Sino-Caucasian languages in central ;
Asia remain uncertain in terms of modeling un- 100 eee =
til 5,000-4,000 BC. Much of the critical move- | Sealed ieaaeecbeiad okt
ments occurred during mesolithic times 20,000- <
10,000 BC when the calculations with the model
are more sensitive to initial conditions and rate
coefficients.
[
10000 --—+—
LANGUAGE model prediction
Figure 14: Test of the model during
neolithic times using independent dates
from glottochronology.
7.2 Major phylze
The calculations correlate well with the super-
phylae Nostratic, Sino-Caucasian and Austric. The superphylum Eurasiatic as defined
by Greenberg (1987) is only partly supported, this may be explained by the fact that
his classification method reveals genetic relationship, but is rather indiscriminate in
terms of time depth. Greenberg excludes Dravidian from the Eurasiatic group, some
thing that is difficult to support with the model calculations. Greenberg's method is
a method that looks down through several superimposed layers of languages, proto-
languages and proto-proto-languages, it collects both recent relationships and distant
ones at once, but cannot really estimate the time-depth associated with a certain sim-
ilarity without help from reconstruction of the proto-layers. It is however, one of the
most powerful tools available for detecting distant genetic relationship between lan-
guages. The split between Proto-Nostratic and Proto-Sino-Caucasian must have oc-
curred before 17,000 BC, since that is the latest date at which Eskimo-Aleut could have
split off from Proto-Nostratic and still made it to America in time. The time around
45,000 BC and alternatively 55,000-62,000 BC experienced global climatic changes that
pushed populations around enough to have initiated such a division. The overall re
lations between the languages of Eurasia as they appear after our integrated interpre
tation of linguistic data, archaeological data and genetic data, is shown in Fig. 17.
The apparent good fit between language
groups and genetically defined populations in-
dicate that initial settlement, demographic dif-
fusion and quantitatively significant migrations
have been the major mechanisms of language
dispersal in Eurasia, and that the other mech-
anisms seen as possible have not been of any
significant importance, until the development
of technological warfare and organized states _|
3,000-4,000 BC. The results of the calculations
also indicate that glottochronology may sig-
nificantly underestimate the age of language
divergences for dates earlier than 5,000-6,000
BC. The principles of glottochronology for pre-
literate conditions should be reconsidered and
analyzed through more research and language
change mathematical modeling for factors that
would decrease the rate of isogloss losses with
time. The split of Nostratic into three ini-
tial entities; (1) Afro-Asiatic, (2) Western Nos-
tratic (Indoeuropean, K artvelian) and (3) East-
ern Nostratic languages (Uralic, Altaic, Paleosi-
\pprsemate genet: aotacee
birian, Eskimo), must have occurred before the
neolithic revolution, in order for the groupings
to develop separate linguistic identities. Cor-
relations between population reallocations and
diffusion into new territory with climate would
indicate a date either around 10,200 BC or
12,000-15,000 BC. The first date correlates well
withe glottochronological dates for the separa-
tion of Afro-asiatic languages and the splitup
of Nostratic into different groups. T he different
hypothesizes on Indo-European origins and the
postulated dates can be plotted in a map (Fig.
Figure 15: Genetic relation tree for
populations of the world according to
Cavalli-Sforza, Piazza, Menozzi and
Mountain (1988) and Cavalli-Sforza
(1991). The genetic relatedness be-
tween different populations as reported
by Nei and Roychoudhury (1982). The
genetic distances were calculated using
different method than those of Cavalli-
Sforza and collaborators, still the gen-
eral pattern of relations stay the same.
22?) to show the agreements of the different proposals for a homeland with the demo-
graphic diffusion theory. The whole notion of a “homeland” looses all meaning unless it
is fixed in time. Since the location has changed perpetually over time, there is not much
sense in fixing it in time. Therefore also the apparent confusion in all the available offers
for a homeland found in the literature. From the map in Figure ?? with the dates assigned
by different authors to the homeland and geographical location offered (Gimbutas 1985;
Diakonov 1990; Mallory 1987; Sherratt and Sherratt 1989; Renfrew 1990; Shevoroshkin
1990; Gamkredlize and Ivanov 1990), we tend to get a movement in time out of Anatolia,
with a subsequent spread up the Balkans and into Central Europe and the Ukrainian
steppe. As it appears, however, the "homeland” of Gimbutas and others postulated on
the steppe of Ukraina, was not the starting point, but rather a secondary center of ex-
pansion for a subset of the Indoeuropeans on the way. Any reflux into Europe would
have occurred into already Indo-European speaking areas. The modified wave-of-advance
model employed here seem to be able to describe the present distribution of languages in
Eurasia, also on a detailed level in the European and Indian subcontinents. T he isolated
positions of Basque, Etruscan, Iberian and Pict in Europe are all predicted. Basque could
be a relict of the language of the Cro-Magnon man around 35,000 BC, as suggested by
Cavalli-Sforza (1989), but there is also a possibility of it being a product of later language
migrations connected to the climatic changes at the end of the glaciation in the Gravettian
period of 27,000-15,000 BC. The model favor the earlier date for Basque, but the later
date for the general spread of Dene-Sino-Caucasian across Eurasia. Glottochronology in
its traditional form the later date. The language of the Cro-Magnon man may still have
been something related to the Dene-Sino-C aucasian phyla, even if Basque came in later.
The calculations seem also to give substantially earlier dates for separation between lan-
guages than indicated by glottochronology. Comparison of the calculated patterns using
the LANGUAGE model with the genetic tree show some very interesting features.
* The populations speaking the languages included in the Austric macro-family form
one complete branch of the genetic tree.
* The populations speaking the languages included in Western Nostratic and East
Nostratic form two distinct branches in the genetic tree.
* The Asian populations speaking the languages Chukchi-K amchadal, Eskimo-A leut
and the American Amerind cluster with the same group as the populations speaking
East Nostratic languages.
The exceptions are Lapp which cluster with the populations speaking languages of the
West Nostratic group, but show admixture of populations speaking East Nostratic lan-
guages. Lapp are known archaeologically to belong to the Finno-Ugrian ethnic grouping,
but to be heavily admixed with Scandinavians due to the long time of cohabitation. The
Afro-asiatic language group overlaps into the African branch in Ethiopia, but this is known
to bea later supposition. T he Tibetans are also known to bea Mongolic population group
which later adopted Sino-Tibetan language. The discovery of a frozen human body in
the high mountains above the Otz Valley on the Italian-Austrian border a few years ago
has opened up the possibility for a genetic test. The body has been C 14-dated to approx-
imately late neolithic-chalcheolithic, approximately 3,520 BC. Genetic tests have shown
the Otz Valley man to be of central European stock, similar to present central Europeans.
The current hypothesis is that he originated in some of the settlements in the Otz Valley
below the mountain on the southern side, in one of the vallies that go down to the Po
River plain. This implies that the Kurgan hypothesis prescribing a central Asian origin
of the Indoeuropean language, is very likely incorrect.
7.3 Uncertainties
The uncertainties in these calculations remain quite large at the present time. Especially
the rate coefficients for population growth and migratory diffusivity in mesolithic time
remain problematic to estimate. Further research is needed for this type of transfer. The
model use rather large grid cells for Asia at present, and a smaller grid cell would refine res-
olution as well as precision.
Several points in time are possible for the
split between Nostratic, Sino-Caucasian and
Amerind. Model calculations cannot be suf-
ficiently confined by independent archaeologi-
cal data and linguistic clues to decide the is-
sue at present. When modern man expanded
into the new world at a rate that implies that
there was no population counterpressure. Thus
the population density of Homo Erectus was
either to low to be of consequence, or his com-
petitiveness was so inferior that the actual pop-
ulation density was of no consequence. The
models yield the best results if we simply pre-
tend that nobody was there. Something pre
vented modern man from entering Europe untill
45,000 BC. This could have been the competi-
tiveness of the Neanderthals that was sufficient
to prevent modern humans to gain a decisive
advantage. Not untill 45,000 BC could such a
significant advantage be obtained. The actual
mechanism of language transfer of Dene-Sino-
Caucasian language into Chinese territory re
main unsatisfactory constrained in the model.
Independent invention of agriculture in China
better fits the absolute dates of arrival for Sino-
Tibetan and agriculture throughout Southeast
Asia, than agricultural initiation from Anato-
lia, which tend to have problem to get there
on time in the calculations. The model seem
to be well confined for several events, however,
provided the initial conditions were correctly es-
timated. As such the unity of Nostratic as con-
cerns the language phylee Afro-Asiatic, Indo-
European and Dravidian are well supported and
the only functioning intermediary initial con-
dition leading to their present location is the
northwestern part of the fertile crescent. The
serene
[aren aanaras —+ — jw armas
LL comes aman
woermaric |
ee
Figure 16: The relation between
the languages included in the Nos-
tratic group according to the LAN-
GUAGE model calculation.T he model
suggest three basic units; Afroasiatic,
Western Nostratic with Indoeuropean
and Kartvelian and Eastern Nostratic
with Finno-Ugrian, Altaic and Elamo-
Dravidian.
Figure 17: The calculated interrelation
between the major language phylze of
Asia, Europa and America using the
LANGUAGE model.
model is also well confined for the spread of agriculture in south east Asia, supporting
the unity of Austric with reasonable accuracy and leading to the present distribution of
Austro-asiatic, Austro-Tai, Austronesian and Miao-Y iao with good accuracy. The model
calculations within the uncertainty bounds, indicate that the case for Austric appear to
as well founded and confined as the case for Nostratic.
8 Conclusions
The LANGUAGE model calculations and the data available indicate a number of state-
ments that may be made:
* On Nostratic; Nostratic is strongly supported by the model calculations and the
available data for checking the calculations. The spread of the Indo-European,
Ugric-Yukagir, Altaic, Dravidian, Kartvelian and Afro-Asiatic languages can be
simulated based on ecological factors and the spread of agriculture 9,000-3,000 BC.
Nostratic split up into three branches in the area of the fertile crescent 15,000-12,000
BC or 10,200 BC because of ecological factors.
* On DeneSino-Caucasian; The Dene-Sino-Caucasian language family is supported
by model and data. The DeneSino-Caucasian language family was one of the
large language families of northern Eurasia before the inception of agriculture. The
split between Proto-Nostratic and Proto-Sino-Caucasian must have occurred before
35,000, 43,000 or 55,000 BC caused by ecological changes large enough to have
initiated a division. The substrate language underlying Indo-European in Europe
and Anatolia must have been of North Caucasian type. The original language from
which the European branches of Caucasian developed split in the time period 23,000-
17,000 BC, when Europe was repopulated after having been a polar desert in a very
cold period.
* On Austric; Austric as a group of genetically related languages is strongly sup-
ported by the model calculations. The present distribution of Austric languages
can be calculated based on demographic diffusion caused by the introduction of
rice agriculture. Proto-A ustric was once spoken throughout Southern China. Miao,
Yao and She are the only remnants of the Austric substrate language of the region.
Austronesian, Austro-Asiatic and Tai-K adai languages have sprung from the same
root as Miao-Y iao around 7,000 BC.
* On Amerindian; Amerindian split of from Proto-Eurasiatic in 22,000, 35,000 or
43,000 BC caused by ecological change. The division of Amerind into many lan-
guages cannot have occurred before 25,000 BC, more likely it happened after 15,000
BC.
The genetic distribution pattern observed by Piazza et al,(1978, 1981) was used to check
the model calculations. The correlation between model calculation and observed genetic
pattern is good, as can be seen from Figures 17 and 15-??. The Nostratic language
family is strongly supported by both model and the genetic data. Austric, deduced from
linguistic data (Bellwood, 1990, Peiros, 1989), seem to be supported by the synthetic map
of genetic markers as well as the genetic and archaeological data presented by Cavalli-
Sforza et al. (1989). The pre-colonial genetic pattern of the world’s populations can be
explained mainly by demographic processes starting in Africa more than 100,000 years
ago, including processes started by the invention of agriculture in the Middle East and
central China. The human dispersal history as reconstructed by the LANGUAGE model
may as a result of this also in broad outline explain the precolonial distribution of the
world’s languages. The worlds languages can be divide into branches, North Eurasian
including Dene-Sino-C aucasian, Amerind and Nostratic, South Eurasian including A ustric
and Indo-Pacific, West African languages including Nilo-Saharan and Niger-C ordofanian
and East African including the K hoisan languages. The compilation of data together
with the present calculations, indicate that the major language groupings Nostratic, Sino-
Caucasian, Austric and Amerind share a common ancestry lying at least 40,000 years back
in the past. Genetic data suggests that modern man emerged from Africa about 100,000
BC. The model requires this amount of time to get every man to his modern position
when the historical record opens up. This together with the close connection between
genetic properties and language actually observed, and the hypothesis that Eurasian and
African humans share a distant common genetic past, seem to indicate that the origin of
speech is older than 100,000 years.
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