Currie & Mace, The Evolution of Ethnolinguistc Diversity, 2012

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Advances in Complex SystemsVol. 15, Nos. 1 & 2 (2012) 1150006 (20pages)c World Scientific Publishing Company

DOI:10.1142/S0219525911003372

THE EVOLUTION OF ETHNOLINGUISTIC DIVERSITY

THOMAS E. CURRIE,,, and RUTH MACE,

Evolutionary Ecology Research Group,

Department of Anthropology,

University College London,

London, United Kingdom

Evolutionary Cognitive Science Research Centre,University of Tokyo, Japan

AHRC Centre for the Evolution of Cultural Diversity,

University College London,

London, United [email protected]

Received 7 January 2011Revised 24 February 2011Published 6 January 2012

Humans divide themselves up into groups based on a shared cultural identity and com-mon descent. Culturally inherited differences in dress, language, and institutions areoften used as symbolic markers of the boundaries of these ethnic groups. Relatively lit-tle is known about the function of such ethnic groups, and why ethnic diversity is highin some regions yet lower in others. In this paper, we demonstrate how investigating thespatial distribution of ethnolinguistic groups can reveal the factors that affect the originand maintenance of human ethnic group diversity. Here we describe the use of a Geo-graphic Information System to construct a large database that integrates informationabout languages with a number of environmental, ecological, and ethnographic variables.Using these data on the spatial distribution of ethnolinguistic groups, we employ a hier-

archical linear modeling approach to test a variety of hypotheses concerning the functionof such groups. Despite revealing intriguing spatial patterns such as the latitudinal gra-dient in ethnolinguistic diversity, previous analyses suggested that the direct effects ofenvironmental variables on the distribution of ethnolinguistic groups were in fact quitesmall. Here we show that the strength of the relationship between ethnolinguistic areaand environmental variables is stronger in societies whose primary mode of subsistenceis foraging. We then go on to demonstrate this same finding using the estimated native

distributions of ethnolinguistic group in the Americas and Australia. In particular, NetPrimary Productivity is shown to be a good predictor of the area covered by ethno-linguistic groups in foragers but not in agriculturalists. This provides support for theidea that the factors affecting ethnic diversity have changed in a systematic way withchanges in subsistence strategies and social organization. We highlight future avenuesfor spatially explicit investigations of the evolution of ethnic diversity, and suggest thatthe evolutionary ecological approach adopted here may provide important insights intoprocesses affecting ethnic diversity in the modern world.

Keywords: Ethnic diversity; ethnolinguistic groups; cultural evolution; Niche Construc-tion; political complexity.

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T. E. Currie and R. Mace

1. Introduction

Despite being a relatively homogenous species genetically, humans are extraordi-

narily adept at finding differences between themselves and dividing themselves up

into separate ethnic groups [48]. While this tendency has created a wonderful arrayof distinct cultures and ways of life, it has also led to some of the darker aspects of

human history as groups from one ethnic group have sought to subjugate or destroy

those from another. Understanding the function of ethnic groups, and what factors

cause ethnic diversity to be high in some regions yet lower in others is therefore

of vital importance. However, relatively little is known about these questions. Here

we demonstrate how examining the geographical distribution of ethnic groups can

help shed light on the factors that affect the origin and evolution of such groups

[39, 48, 17].

1.1. Identifying and classifying ethnic groups

While the terms ethnic and ethnicity are widely used today these concepts

only become widely used in the social sciences relatively recently (especially in

comparison with concepts such as race or class) [32, 21]. This rise is often

linked to the breakdown of colonialism in Africa and Asia in the 1960s, and gained

yet further prominence with the collapse of Communist regimes in the early 1990s

[29]. Despite the prominence of ethnicity, the term is often used in a variety of

contexts with different meanings, and is often not explicitly defined [12, 21]. Here

we define ethnic groups as groups of individuals that share a common, self-ascribed

identity based on the belief in common descent, and/or a shared culture, distinct

in some respect from those of other groups. This belief is culturally inherited from

one generation to the next. Symbolic markers of these groups such as differences in

dress, language, and institutions are themselves culturally inherited. It is important

to stress that what is important in terms of the ways individuals and groups interact

with one another is the belief in cultural uniqueness or common descent rather than

the objective reality of such beliefs. We can also define ethnogenesisa

as the processby which ethnic groups are formed, while ethnopathosis refers to the extinction of

ethnic groups, which may involve either the physical death of all members of the

group, or the incorporation of at least some of them into another group.

In practice, identifying ethnic groups is not an easy task. Ethnic groups often

define themselves in relation to other groups and different markers may be more or

less important in different contexts. However, this difficulty should not dissuade us

aIt should be noted that [40] employs a different definition of ethnogenesis, one that incorporates

the idea that the formation of human cultural groups always involves reticulate, or rhizotic processrather being a purely splitting or cladistic process. However, this definition is rather confusing asit privileges one particular mode of group formation. The terms ethnogenesis and ethnopathosisas we and others (e.g. [32, 58]) employ them are more directly analogous to the terms speciationand extinction which are used in the biological literature [15], and denote phenomena that couldpotentially come about via a variety of processes.

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The Evolution of Ethnolinguistic Diversity

from attempting to identify ethnic groups in a systematic manner using a consistent

criterion in order to understand what factors affect their formation and mainte-

nance. The relational nature of ethnic groups is something that is held in common

with concepts of biological species, and delimiting species boundaries is by no meansstraightforward [15]. However, it would be hard to argue that species thinking

has not been of enormous value to biologists in cataloguing and explaining the mas-

sive variation seen in living organisms. Perhaps the most widespread ethnic marker

is differences in spoken language, with the critical development period in which a

language can be learnt making it particularly suitable for this task [44, 53]. Here,

we examine the diversity of ethnic groups that are based on differences in language.

This focus on language has a number of advantages. Language has received more

attention over a greater portion of the world, and for a longer time, than probably

any other cultural group marker. Consistent criteria, such as mutual intelligibility,have been employed in order to identify and classify distinct varieties of speech,

and are open to testing and evaluation [20]. Importantly, the classificatory system

employed in this study, the Ethnologue [24], explicitly uses group identity in its

determination of distinct languages and does not rely solely on more narrow lin-

guistic criteria. Again this has parallels with the identification of biological species

where the degree of genetic similarity by itself is not necessarily the most perti-

nent factor in delimiting species boundaries [15]. It should also be emphasized that

although multilingualism is undoubtedly a common feature in many societies here

we are interested only in the primary languages of groups, i.e. those associatedwith group identity, and not secondary languages or widespread trade languages

such Tok Pisin. In this paper, we therefore use the term ethnolinguistic group.

It is also important to stress at what level we are discussing the diversity of such

groups, as ethnicity, and variation in general, is often a nested phenomenon [57], e.g.

a person born in London may describe themselves as a Londoner, English, British,

European, or Western depending on the situation. Figure 1 shows two dimensions

of ethnolinguistic diversity: (1) the level of individual ethnolinguistic groups, (2) the

higher taxonomic grouping of language family. In any particular region these twodimensions of diversity may overlap (e.g. the island of New Guinea is highly diverse

both in the number of languages and number of language families (Fig. 1(d)),

while eastern China has relatively few languages, and all come from a single fam-

ily (Fig. 1(a))), or they may be discordant (e.g. the Pacific Island of Vanuatu is

extraordinarily diverse in number of languages, yet all belong to the Austronesian

language family (Fig. 1(c)), while the middle east does not have many languages

yet the languages that are present belong to a variety of different language families

(Fig. 1(b)). It should also be pointed out that higher levels of language diversity

may or may not be relevant in terms of a groups own ethnic (or meta-ethnic)identity, and often the classifications are based on the work of linguists (e.g. Hindi

and German are both classified as Indo-European languages, yet few speakers of

either language would feel affinity with those of the other language based on this).

The factors affecting diversity at these different levels may also be very different.

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Fig. 1. (Color online) The diversity of cultural groups can be assessed on a number of differentlevels. The thick black lines delimit distinct ethnolinguistic groups, while separate colors withineach panel indicate the different, higher-level groupings of language families. Language familyclassifications are taken from the Ethnologue [24]. Note the scale bars (in km). In this paper, weexamine the diversity at the lower-level of distinct ethnolinguistic groups.

For example, researchers such as Jared Diamond, Peter Bellwood, and Colin Ren-frew have argued that the distribution of certain language families is related to

the expansion of populations fuelled by some competitive advantage (most com-

monly agriculture) [18, 52, 10]. Under this hypothesis, regions that have relatively

few language families are those that have undergone such an expansion during the

last 10,000 years or so, while those that have larger numbers of language families

indicate longer periods of settlement with relatively less population replacement.

In this paper, we address what factors explain the diversity at the lower level of

individual ethnolinguistic groups, defined as those speaking distinct languages.

1.2. The global distribution of ethnolinguistic groups

Examining how ethnic groups are distributed in space may provide clues as to what

factors have been important in shaping the diversity of different regions. Figure 2

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Fig.

2.

Ethnolinguisticdiversityandgenetic

diversityexhibitdifferentglobalpatterns.Thecurrentdistributionofethnolinguisticgrou

psdoesnot

reflecttimesincedispersalfromAfrica.KerneldensitymapofethnolinguisticgroupswascreatedinArcGIS(datasources:OldWorld[24],

Americas

andAustralia[42]).Geneticdiversitydata(a

utosomalshorttandemrepeats)weretakenfrom[61].

Keys

forGeneticDiversityandEth

nolinguistic

Densityreprese

ntupperboundofeachcategory,

withEthnolinguisticDensitybeinginunitsofln

languages

perkm

2

.DataonEthnolinguisticdiversity

forthescatterplotwascalculatedasthedens

ityoflanguages(numberoflanguagesdividedbylandarea)withinina500kmradiusofea

chofthe49

focalsocietiesforwhichgeneticdatawasavailable(onlyregionsoflandcon

tributedtothisdensitycalculation).Thedottedregressionlineindicates

thisrelationshipisnotstatisticallysignificant

.

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shows the global distribution of ethnolinguistic diversity. The red regions repre-

sent the areas of highest diversity (in terms of number of groups per unit area),

while the yellow regions are those of lowest diversity. It can be seen that broadly

speaking there is a latitudinal gradient in ethnolinguistic diversity, with diversityincreasing as one moves from the poles towards the equator [17]. Interestingly, this

parallels well-known patterns of biological species diversity and biologists have long

been interested in explaining these patterns [60]. This non-random distribution of

groups suggests some ecological factors may be important in shaping ethnic diver-

sity. Interestingly, this latitudinal pattern of ethnolinguistic diversity is very differ-

ent to the global pattern of genetic diversity. Generally speaking, genetic diversity

of populations decreases as with increasing distance from Africa (see Fig. 2), most

likely due to serial founder effects following the migration of modern human popula-

tions out from their place of origin [50]. This suggests that different processes haveshaped these two different aspects of human diversity, and that the distribution of

ethnolinguistic groups cannot simply put down to the length of human occupation

of these areas (e.g. Vanuatu has a huge number of languages on a few small islands,

yet was first inhabited only around 3,500 years ago).

The association between cultural group diversity and latitude or other environ-

mental factors has led to a number of hypotheses concerning how this diversity is

determined. The topography hypothesis [55, 11, 23] argues that physical barriers,

such as mountain ranges, divide populations with ethnic groups forming in a manner

analogous to allopatric speciation. This idea reflects quite a passive view of ethnicgroup formation, implying that regions would be less diverse if such impediments

were not in place. However, while some regions such as the Highlands of New Guinea

and the Himalayas are both mountainous and ethnically diverse other regions are

either mountainous but not particularly diverse (e.g. the Altai mountains of Central

Asia), or diverse without such obvious physical barriers (e.g. Aboriginal northern

Australia). The ethnographic record also shows that people often maintain ethnic

or other culturally defined boundaries despite prolonged contact with other groups,

and the movement of individuals across these boundaries [3]. The environmentalproductivity hypothesis can be traced back to Birdsells pioneering work on Aus-

tralian aboriginal groups [8], and argues that distributions of ethnic groups are

related to the productivity of a region [17]. This argument is based on the idea that

membership of a group, while providing certain benefits, such as more effective

defense or increased hunting capacity, also involves some costs, such as the poten-

tial for altruistic acts to go unreciprocated. Therefore the group should be no larger

than that needed to be meet subsistence and reproductive needs (ethnic groups are

usually endogamous and therefore need to be large enough to avoid the deleterious

effects of inbreeding). Birdsell argued that for Aboriginal tribal groups this numberwas around 500 individuals. More productive regions will be able to support higher

population densities and therefore will contain more ethnic groups. In support of

this idea Birdsell found a strong correlation between the area covered by Aboriginal

tribal groups and amount of rainfall. The environmental risk hypothesis [30, 43],

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on the other hand, argues that the risk of failing to meet subsistence requirements

is the most important factor in determining the area over which a group is spread.

In more variable environments social networks need to spread over larger areas to

provide a buffer against temporary shortfalls in production, making more environ-mentally risky regions lower in ethnic diversity. In an analysis using country-level

data, Nettle [43] found a negative relationship between the number of languages

and an estimate of environmental risk (mean growing season: the number of months

in a year in which the climate is conducive to growing crops).

While these spatial patterns and correlations might suggest that the direct

effects of environmental factors have had a strong influence in shaping ethnolin-

guistic diversity previous studies have suffered from a number of methodological

issues (see Methodological Considerations below). In a previous study [17], we

addressed these problems and found that in fact the direct effects of environmentalvariables on the present-day distribution of ethnolinguistic groups were relatively

weak, and that in particular the productivity and topography hypotheses received

no support in our analysis. Instead, we found that the mobility of groups affected

the area over which they were spread (more mobile subsistence strategies such

as Pastoralism were associated with more widespread ethnolinguistic groups), and

that the degree of political complexity exhibited by a society was the biggest single

predictor of the area covered by their ethnolinguistic group, suggesting that regions

which are lower in ethnolinguistic diversity are those in which more complex soci-

eties have arisen and expanded, with those regions being generally away from thetropics.

These results suggest that the factors affecting ethnogenesis and ethnopathosis

have altered over time. Currie and Mace [17] argued that the relationship between

the environment and ethnic group distributions may have been stronger prior to

the development of agriculture and increasingly complex forms of political organi-

zation over the last 12,000 years. While it is difficult to ascertain the distribution

of ethnic groups in the remote past [34, 59], this hypothesis can be tested by exam-

ining whether the relationship between environmental factors and ethnolinguisticdiversity vary systematically across societies with different subsistence strategies.

From a niche construction perspective [45], we would predict that societies that rely

primarily on foraging and pastoral (animal herding) subsistence strategies would be

more strongly affected by direct climatic and environmental factors than agricul-

turalists who can often modify their environments in ways that buffer themselves

from such direct effects. For example, the construction of large-scale irrigation sys-

tems means that farmers can control the supply of water to their crops, and raise

productivity without having to rely on direct rainfall. To test these predictions, we

first use the database of ethnolinguistic groups described in [17]. We then go on totake advantage of a kind of natural experiment in history [19] by examining the

distribution of ethnolinguistic groups in the Americas and Australia at the time of

first contact with European societies, a period when foraging societies were more

abundant.

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2. Methods and Results

2.1. Methodological considerations

In our previous paper [17], we argued that there were several problems with exist-

ing studies that attempted to explain large-scale patterns of cultural group diver-

sity. Firstly, many studies have only provided descriptions of patterns rather than

testing specific hypotheses [39, 13, 41], or have only assessed single environmental

predictors of a preferred hypothesis in isolation [43, 22, 55]. As many environmental

variables vary with latitude, many of these correlations are likely to be spurious.

Secondly, many studies were conducted at a coarse scale of analysis, usually at the

level of countries, which masks a lot of potentially informative variation. To illus-

trate, Nettle [43] used the relationship between mean growing season (MGS) and

number of languages per country to argue for the Ecological Risk hypotheses, whileFincher and Thornhill [22] use the correlation between number of pathogens and

number of languages per country to argue that it is transmissible disease that is

the most important factor affecting ethnic diversity. Neither study attempts to con-

trol for other potentially important environmental variables. In fact if both MGS

and number of pathogens are entered in to a regression model with number of lan-

guages as the dependent variable (controlling for country area) then the relationship

between pathogens and number of languages is no longer statistically significant.b

We include this here not as a conclusive test of either the ecological risk or the

pathogen hypothesis but merely to highlight the potential problems with existingstudies. In our previous paper [17] and here, we have addressed these issues by

taking ethnolinguistic groups themselves as the unit of analysis. We examine the

association between the area covered by these groups and a number of different

ecological or cultural variables in line with the predictions of different hypotheses,

such as those described above. Finally, the units of analysis (in our case individ-

ual ethnolinguistic groups) cannot be considered as independent for the purposes

of statistical analysis due their historical relatedness [38]. We therefore employ a

Hierarchical Linear Modeling (HLM) approach [51] that controls for this problem.

In these analyses, individual ethnolinguistic groups are nested within the language

family to which they belong, with language family included as a random effect.

2.2. Ethnolinguistic groups and subsistence strategy

in the old world

In this study, we use the global ethnolinguistic database described in [17], based

on a digital map showing the geographical distribution of entries in the Ethnologue

[24], a comprehensive catalogue of the worlds languages.c Figure 1 shows examples

bMultiple regression with number of languages as the dependent variable, MGS is a significant pre-dictor (= 0.41, p


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Table 1. HLM parameter estimates showing the relationship between ethnolinguistic area

(log10km2) and various environmental variables. (LAT: Absolute Latitude, NPP: Net Primary

Productivity, MGS: Mean Growing Season, PREC: Mean annual precipitation, TEMP: Meanannual temperature).

Environmental predictors

Subsistence strategy LAT NPP MGS PREC TEMP

Foraging 0.589 0.397 0.585 0.488 0.543Pastoralism 0.617 0.567 0.558 0.699 0.010 (ns)Agriculture 0.319 0.038 (ns) 0.173 0.249 0.157

of the language polygons that make up this map. Briefly, this database integrates

information about the geographical extent of ethnolinguistic groups, with environ-

mental, ecological, and ethnographic data. Here we test how the strength of therelationship between various environmental variables and the area covered by an

ethnolinguistic group varies across different subsistence strategies. Societies are clas-

sified according their primary mode of subsistence using the available ethnographic

data from the Ethnographic Atlas [25] (Foraging [Hunting, Gathering, and Fishing],

n= 28; Pastoralism, n= 55; Agriculture, n= 498).

Table 1 shows the parameter estimates of the correlation between the area cov-

ered by an ethnolinguistic group and several (mean-centered) environmental vari-

ables in a series of HLMs. There is a positive relationship between ethnolinguistic

area and absolute latitude across all subsistence strategies. However, as latitude isonly a proxy for some other variable, and to test the hypotheses discussed above, we

assess the climatic variables annual precipitation and temperature, and also exam-

ine a measure of environmental productivity (Net Primary Productivity: a measure

of the net amount of plant biomass converted from solar energy during photosyn-

thesis), and a measure of environmental risk (Mean Growing Season: the number

of months in a year in which the mean temperature is above 6C and the total

precipitation in millimeters is more than twice the mean temperature in centigrade

[43]). As predicted, the strongest correlations between the climatic variables and

group area are found in the foraging and pastoral societies while the correlations are

generally weaker for those societies that practise agriculture (see Fig. 3). An inter-

esting exception to this general pattern is the non-significant relationship between

area and temperature in pastoralists. This may reflect the fact that pastoralists

tend to inhabit quite arid environments, and therefore the most pertinent variable

affecting survival will be the amount of rainfall.

2.3. Ethnolinguistic groups and subsistence strategy in the

Americas and Australia

Although the results from the old world sample are in line with the predictions of

the niche construction hypothesis, we only have a relatively small sample of foraging

populations to consider, which prevents more rigorous multivariate analyses from

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NPP

0.100.080.060.040.020.00

ethnolinguistic

area

6

4

2

0

NPP

0.100.080.060.040.020.00

ethnolinguistic

area

6

5

4

3

2

(a) (b)

NPP

0.080.060.040.020.00

ethnolinguistic

area

7

6

5

4

3

2

(c)

Fig. 3. The relationship between the area covered by an ethnolinguistic group (log10km2) and

Net Primary Productivity varies according to the groups subsistence strategy. Agriculturalists(a) show no relationship, while the negative correlation between these variables for both Pastoral-ists (b) and Foragers (c) is reasonably strong.

being performed. We therefore examine the distribution of ethnolinguistic groups

in Australia and the Americas. At the time of first European contact with these

regions, Australia was populated solely by foragers, while large numbers of foragers

were also still present in the Americas. The Ethnologue and associated maps only

show the current distribution of native languages in this region, which are often

heavily circumscribed compared to their original distributions. We therefore had

to construct a new ethnolinguistic database using maps describing the estimated

geographical distribution of languages at the time of first contact with Europeansocieties [42]. These maps are undoubtedly only an approximation of the true distri-

bution of native groups, and were constructed from sources reflecting an extended

period (and therefore do not represent a single narrow time slice). However, such

sources of error are only likely to introduce noise into our data and it seems unlikely

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Fig. 4. Where only point data were shown on the maps ethnolinguistic polygons were createdusing the Thiessen algorithm, which works by placing a line perpendicular to the midpoint betweentwo points. In this example from North Queensland, Australia the curved lines indicate where themaps already indicated the boundaries of different linguistic groups in some places.

that they have introduced a systematic bias with respect to the hypotheses being

tested in this paper. These maps were scanned and geo-referenced in the Geographic

Information System ArcGIS v9.1 (using multiple reference points and a third-order

polynomial algorithm) in order to bring all maps into the same coordinate and

projection system. Polygons were then created by drawing around each individ-

ual language. In some regions, single languages were shown only as a number. In

this case, the language was represented as a point and the geographical extent of

that language was estimated using Thiessen polygons (see Fig. 4). The area of these

polygons was then calculated under a Robinson projection. Multiple languages were

sometimes indicated with only at a single point with a range of numbers, in such

cases the area for the entire polygon was calculated and divided by the number of

languages indicated (in such cases only one entry was used in the statistical anal-yses). The resulting language polygons were overlaid onto high resolution maps of

various environmental variables and a number of values were calculated for each

language (e.g. mean annual temperature) [17]. Although agriculture was invented

independently in the Americas, its range was still somewhat limited before Euro-

pean contact. In order to categorize the subsistence strategy of the ethnolinguistic

groups in the Americas, we took the estimated boundary of native agriculture in the

Americas as delimited by [5] (Fig. 5). We can assign the societies living outside this

region to a foraging mode of subsistence, the societies that fall inside this zone are

categorized as agricultural (although it should be noted that some societies withinthis zone may also have subsisted predominantly via foraging).

Table 2 shows the HLM parameter estimates of several environmental predic-

tors of the area covered by an ethnolinguistic group (again groups are modeled as

being nested within language families). The results support the findings of the first

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NPP

0.100.080.060.040.020.00

ethnolinguist

ic

area

6

5

4

3

2

1

AB

NPP

0.060.050.040.030.020.010.00

ethnolinguistic

area

6

5

4

3

2

NPP

0.080.060.040.020.00

ethnolinguistic

area

6

5

4

3

2

Fig. 5. The strength of the relationship between ethnolinguistic area and NPP varies accordingto the subsistence strategy employed by native societies of the Americas and Australia. The areacovered by agricultural ethnolinguistic groups in the Americas (A) which show no relationshipwith NPP, while the extent of ethnolinguistic groups of foraging societies of the Americas (B)and Australia (C) are negatively related to NPP. The strength of this relationship is increasedfurther in Australia if societies found in the eastern temperate forests of Australia (empty trian-

gles) are removed from the analysis (Regression lines: Solid: all societies; Long-dashed: Australiannon-eastern temperate forests; Short-dashed: Australian eastern temperate forests). Boundary ofprehistoric agriculture adapted from [5].

Table 2. HLM parameter estimates indicating the strength of relationship between ethnolin-guistic area and various environmental predictors. Ethnolinguistic group area is generally betterpredicted by the environmental variables in the foraging regions of the Americas and Australia,than in the agricultural region of the Americas.

Latitude NPP MGS PREC TEMP

Australia 0.298 0.238 0.165 0.390 0.259Americas

Foraging 0.352 0.531 0.358 0.392 0.409Agriculture 0.080 0.004 (ns) 0.045 (ns) 0.040 (ns) 0.011 (ns)

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Table 3. HLMs showing the relationship of NPP and MGS with ethnolinguistic area in the

same model. AIC scores show the fit of these models in relation to a null model containing onlythe grouping variable language family.

Americas

Australia# Foraging Agriculture

AIC Null model 506.053 504.957 981.132AIC Alternative model 343.592 398.640 981.274

Parameter p Parameter p Parameter pestimate estimate estimate

Intercept 4.150


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coordinate the actions of larger numbers of people. Such groups were also able to

out-compete less complex groups and as they expanded they displaced, replaced

or assimilated existing ethnic groups, leading to an overall reduction in diversity.

This process has further severed the link between the geographical extent of ethnicgroups and the direct effects of environmental variables.

There is some evidence that ecological risk might become a more important

factor shaping ethnolinguistic diversity for agriculturalists. This may reflect the fact

that while the societies practicing foraging and pastoralism can respond to shortfalls

in production through their greater mobility, the more sedentary agriculturalists

may have to rely to a greater extent on buffering such risks through their social

networks as envisaged by the ecological risk hypothesis. However, we note that

ethnolinguistic group area in the agricultural zone of the Americas showed only

a weak relationship with MGS at best, while MGS explains only small amountof variation in the extent of ethnolinguistic groups in the agricultural societies of

the Old World. For agriculturalists, productivity may still be an important factor

determining the distribution of ethnic groups, however, the productivity of any

particular region came to depend more on labour inputs into farming, the kinds of

crops grown and the process of artificial selection to create more desirable cultivars.

Furthermore, different crops require different climatic conditions for optimal growth

with some vegetative crops doing best in warm, wet environments such as taro while

others such as sweet potato do better in drier conditions [36]. Grain crops, such as

rice, need a seasonal climate with appropriate annual patterns of temperature andrain to allow the grain to dry once harvested [4].

While our results are consistent with the niche construction hypothesis it is

important to point out that a number of other factors tend co-vary with the presence

of agriculture, and may also decrease the link between the area of an ethnic group

and environmental variables. For example, the presence of large-scale, expansive

polities mentioned previously, or trade of products including staple crops. It should

also be noted that foragers also conduct important niche construction activities

(e.g. the use of controlled burning as a resource management strategy in AustralianAborigines [7], or have a resource bases that are less linked directly to terrestrial

environmental variables (e.g. Salmon in the Northwest Coast of America [1]). These

factors may also affect the relationship between the climatic variables considered

here and the area covered by ethnic groups. In order to test the relative importance

of these different processes, future work will attempt to integrate such pertinent

ethnographic information with information about the native distribution of ethnic

groups in the Americas and Australia in the manner that we have previously done

for the old world [17].

While environmental factors such as Net Primary Productivity were shownto be better predictors of the area covered by ethnolinguistic groups for foragers

than for foragers than for agriculturalists, productivity more broadly defined may

still be a key factor underlying the propensity for human to split themselves off

into distinct ethnic groups in the modern world. Interestingly, major metropolises

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such as New York, or London, which can be thought of as being very productive

economically, are well known for containing many different ethnic communities. For

example, it is estimated that more than 300 languages are spoken by schoolchil-

dren in London [2]. [46] found that economic productivity of US cities correlatespositively with the number of languages spoken. This suggests that the evolution-

ary ecological perspective we have employed in this paper to examine may also be

fruitfully applied in future work to explain the patterns and processes of ethnic

differentiation in contemporary, urban settings. It will also be important for such

an approach to incorporate the impact that national or regional policies on such

factors as trade, immigration, and the assimilation of different groups, in shaping

ethnic diversity in these settings.

Our results demonstrate that the distribution of human cultural groups varies

systematically with a number of social and environmental factors. As such, ourapproach may have important implications for archaeologists who wish to study

the ethnicity of past populations, and may provide an independent lens through

which to view this aspect of the past. Interpretations about the ethnic affiliations

of societies represented in the archaeological record have a long and controver-

sial history, and there is a vigorous debate about to what extent ethnicity can be

deduced from material remains [34, 54, 59, 32]. One possibility is that the expected

number of ethnic groups of any particular region could be estimated based on esti-

mates of productivity, and information about such things as population density and

social complexity. Such estimates could then be tallied with hypothesized archae-ological markers of ethnic groups. A similar idea about using ecological data as a

window into the past has been proposed by Binford [6], particularly with respect to

predicting the distribution of hunter-gatherer groups. His approach was explicitly

inductive and attempted to make predictions about the past based on statistical

associations within his particular dataset without reference to an underlying the-

ory as to why those associations existed. However, such a strategy runs the risk of

finding associations that cannot be generalized to other situations. We argue that is

better to make predictions about the possible past distribution of groups or culturaltraits using the kind of data we have analyzed in this paper on the basis of specific

hypotheses that postulate a link between these phenomena.

In this paper, we have used a Geographical Information System to integrate

data from a number of different sources in order to statistically test a number

of hypotheses about the evolution of ethnic diversity. The use of spatially explicit

mathematical models or computer simulations could provide further tests of these or

other hypotheses, and would represent an important complement to this approach.

Such techniques have previously been employed to address related questions about

biological species diversity [49], human genetic diversity [23], and other aspects ofcultural evolution (see other papers in this volume). Hypotheses involving the rela-

tionship between environmental variables and ethnic diversity, such as the produc-

tivity and ecological risk hypotheses, are based on equilibrium models [13, 23, 43].

However, if the sequence described above is correct then, on a global scale, such

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equilibria have been systematically disrupted at least twice. First, in the transition

from foraging to agricultural modes of subsistence [43], and secondly in the develop-

ment of more complex forms of political organization [17]. Estimates of high recent

rates of language loss [56] suggest that we have not yet settled down to a new sta-ble equilibrium level of ethnolinguistic diversty. Furthermore, the development and

spread of other cultural innovations may cause disruption to equilibrium that may

be witnessed on a more local or regional scale and over shorter time scales, with

some practices creating either positive or negative feedback that may have conse-

quences for the distribution of ethnic groups. The extent to which these dynamic,

non-equilibrium processes have shaped the evolution of human ethnic diversity will

be modeled and tested using a complex systems framework in future work. Sim-

ulations could look explicitly at changes in distributions over time, or could test

how well alternative evolutionary models explain the current distribution of ethno-linguistic groups as indicated in the kind of maps we have examined in this paper.

Kandler et al.[35] have recently used such spatially explicit models to examine the

replacement of Celtic languages by English in Scotland.

Another future direction in which a spatial information can be used to test

hypotheses about the formation of ethnic groups that we are currently persuing

involves the spatially explicit use of cultural phylogenetics [37, 27, 16]. This kind

of cultural phylogeographic thinking has been employed in previous studies that

have applied phylogenetic methods to culturally inherited data, particularly those

that have examined large-scale migrations of human populations (e.g. [31, 26, 14, 9].However, these studies have not considered explicitly how geographically associated

factors may affect cultural group diversification. One particular advantage of such

an approach is that it will allow us to explore how ethnic groups have diversified over

time and can be used to examine how rates of ethnogenesis and ethnopathosis vary

according to movements into new environments, or the adoption of new cultural

practices or social institutions (Fig. 6). This kind of cultural phylogenetic approach

will also be used to assess the relationship between ethnic diversification and other

aspects of cultural diversity. For example, Pagelet al.

[47] used language phylogeniesto infer that the rate of change of lexical items increases following the divergence

of two languages, a phenomenom they interpreted as evidence that language was

being used as a marker of group identity. This approach will be adapted to examine

whether other ethnic group markers also change in this punctuated manner.

In conclusion, we have shown that the strength of the relationship between eth-

nolinguistic area and environmental variables is stronger in societies whose primary

mode of subsistence is foraging. This finding was replicated using the estimated

native distributions of ethnolinguistic groups in the Americas and Australia. In

particular, Net Primary Productivity is shown to be a good predictor of the areacovered by ethnolinguistic groups in foragers but not in agriculturalists. This pro-

vides support for the idea that the factors affecting ethnic diversity have changed

in a systematic way with changes in subsistence strategies and social organization.

In this paper, we have demonstrated how examining geographic and environmental

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Fig. 6. (Color online) The use of spatially explicit cultural phylogenies can be used to testhypotheses about ethnic group formation and how the rates of ethnogenesis and ethnopathosismay be affected by ecological variables. This hypothetical example shows a phylogeny mapped onto a background representing an environment that exhibits a cline (red to white) in a particularvariable. A number of different ethnic groups (large circles) have formed after spreading out anddiverging from a common ancestor in the homeland A. The phylogeny shows that the net rate ofethnogenesis has been larger in the redder areas.

information can shed light on the processes that have shaped human ethnolinguistic

diversity. The use of such a spatially explicit framework to understand the evolu-

tion of biological diversity is common in the natural sciences, and it is hoped that

such an approach will prove fruitful in our attempts to understand the evolution of

human ethnic groups and other aspects of cultural diversity.

Acknowledgments

The authors are supported by a European Research Council grant. Currie was also

supported at various stages of this research by an ESRC/NERC interdisciplinary

studentship, a Japan Society for the Promotion of Science Post-doctoral fellowship,

and the AHRC Centre for the Evolution of Cultural Diversity. This paper reflects

only the authors views, the European Union is not liable for any use that may be

made of the information contained therein. We thank the editors James Steele and

Anne Kandler and two anonymous reviewers for their constructive comments on an

earlier draft of this paper.

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Documents

Currie & Mace, The Evolution of Ethnolinguistc Diversity, 2012