Evolution of the Ainu Language in Space and Time

Evolution of the Ainu Language in Space and Time
Sean Lee*, Toshikazu Hasegawa
Department of Cognitive and Behavioral Science, Graduate School of Arts and Sciences, University of Tokyo, Tokyo, Japan
calls for a refinement to the dual-structure model.
Citation: Lee S, Hasegawa T (2013) Evolution of the Ainu Language in Space and Time. PLoS ONE 8(4): e62243. doi:10.1371/journal.pone.0062243
Editor: Luı́sa Maria Sousa Mesquita Pereira, IPATIMUP (Institute of Molecular Pathology and Immunology of the University of Porto), Portugal
Received January 17, 2013; Accepted March 19, 2013; Published April 26, 2013
Copyright: ß 2013 Lee, Hasegawa. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
Funding: This work was supported by a Grant-in-Aid for Japan Society for the Promotion of Science (JSPS) Fellows (248973). The funders had no role in study
* E-mail: [email protected]
Considerable debate surrounds the apparent incompatibility
between the conventional model of human prehistory for the
Japanese islands and the emerging evidence from modern
archaeology, anthropology and genetics. For several decades, the
dual-structure model [12] has posited that similarities in dental
[13] and cranial features [14] between the Ainu people and
Southeast Asians meant that the Ainu ancestry originated in
Southeast Asia around 10700 years before present (BP) [15].
Similarly, reconstructed proto-Ainu lexicons have also been
suggested to share some similarities with proto-Austroasiatic
lexicons [16]. Therefore, the Ainu have long been thought to be
direct descendants of a single ancient Southeast Asian lineage, the
Jomon, and have remained isolated from neighboring populations
throughout the Holocene. However, recent evidence from genetic
[17,18], morphological [19,20], and cultural studies [21] are
beginning to suggest that the Okhotsk people, a hunter-gatherer
group from the Amur river basin, migrated into northern
Hokkaido around 900–1600 BP bringing significant genetic and
cultural contributions to the preexisting Jomon, and subsequently
gave rise to modern Ainu people as well as their culture. In
essence, this ‘Okhotsk expansion scenario’ suggests that, far from
being direct descendants of a single ancient human lineage that
had no contact with the rest of the world, the Ainu and their
culture are the outcome of a recent population expansion into
northern Hokkaido.
If we accept premises (i) population expansions often leave its
signature in the patterns of linguistic variation and (ii) the cultural
flow from the incoming Okhotsk people had a profound impact on
the language, then we can reason that spatiotemporal reconstruc-
Patterns of linguistic variation among individuals often carry the
signature of a speech community’s demographic past. Accumulating evidence indicates that languages evolve by a process of
descent with modification and they form into distinct families in
a manner similar to their speakers forming into different ethnic
groups through evolutionary history [1–3]. The intertwined
history between languages and their speakers appears most vividly
in the areas that experienced large-scale population expansions,
often driven by agricultural intensification and cultural innovation
since the end of the last Ice Age [4]. Recent empirical evidence
supporting this phenomenon includes a range of language
phylogenies reconstructed with computational methods [5–8].
While the computational phylogenetic methods have been
fruitful in shedding new light on language evolution and the
speakers’ prehistory, their application has been focused mainly on
inferring temporal and sequential aspects. As a result, inferences
about the homeland or geographic diffusion pattern often relied on
heuristic approaches such as locating a monophyletic outgroup
and formulating post-hoc diffusion scenarios from the branching
order. Recent progress in phylogenetic methods is, however,
producing innovative ways to embed phylogenetic inference in
a geographical context, and allow us to explicitly estimate both
temporal and spatial aspects of evolution while accounting for
phylogenetic uncertainty [9–11]. In this paper, we adopt these
methodological innovations and directly reconstruct spatiotemporal evolution of the Ainu language: a nearly extinct language
spoken by indigenous people of Japan whose origins remain
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Ainu Language Phylogeography
tion of the Ainu language evolution might allow us to test the
plausibility of the Okhotsk expansion scenario for the Ainu origin,
and examine whether or not the dual-structure model should be
modified to accommodate the Okhotsk expansion scenario.
Accordingly, we predicted that if the scenario were correct, then
the estimated root age of the Ainu varieties should coincide with
900–1600 BP, and their geographic distribution should be the end
result of expansion from northern Hokkaido, where the gene and
cultural flows from the Okhotsk to Jomon is likely to have taken
place (blue bar in Figure 1). It should be noted that even if the
patterns of Okhotsk expansion were correct, the specific processes
of language change could be interpreted in two ways (see
Discussion for more details). Following the line of reasoning
above, we also predicted that if the scenario were incorrect, then
the Ainu language diffusion should conform to the conventional
scenario and spread northward from southern Hokkaido with the
root age being at least several thousand years older than 1600 BP
but not beyond 10000 BP, which is the current methodological
limit for tracing language ancestry.
be robust against reasonable levels of noise (i.e., up to 20% of
horizontal transfer per 1000 years) [26], (ii) if we define languages
as groups of tongues that are mutually unintelligible in a manner
similar to biologists defining species as groups of animals that
cannot interbreed [27], then Swadesh’s criterion of mutual
intelligibility (i.e., any two languages being mutually unintelligible
if they share less than 90% of their basic vocabularies with each
other [28]) and a matrix of pair-wise cognate similarities of the
Ainu varieties [22] allow us to estimate that any one of the
varieties would be able to communicate with the rest only about
18% at a time, meaning that the majority of the 19 varieties can
actually be considered languages in their own right and (iii) we
used SPLITSTREE4 [29] to estimate tree-likeness of the Ainu
phylogeny [30,31] and obtained the average delta score = 0.25 and
Q-residual score = 0.01, both indicating that the evolution of Ainu
lexicons was reasonably tree-like, and hence suitable for phylogenetic analysis (to put this in perspective, the tree-likeness scores
calculated from a subset of 12 Indo-European languages have
similar scores as our 19 Ainu varieties with the average delta
score = 0.23 and Q-residual score = 0.03 [31]). These observations
provide us confidence that the data should carry robust
evolutionary signal and the 19 Ainu varieties are appropriate
units of analysis for the current purpose.
Cognate judgments, a process of revealing shared ancestry
among lexicons, are carried out by identifying systematic
correspondences in phonetic structure and meaning [25]. For
our analyses, we adopted the cognate judgments made by the two
linguists who compiled the data [22]. The cognate sets were
encoded into binary states indicating presence (’1’) or absence (’0’)
of a cognate, which resulted in 196350 matrix.
We used BEAST [32] for all analyses because it allows us to
reconstruct phylogenies without specifying an a priori outgroup.
Continuous random walk model we use in this paper [9,33] is
a Bayesian expansion of Brownian diffusion model developed in
a maximum-likelihood framework [34]. In general, a Brownian
diffusion model aims to estimate the vectors of latitudes and
longitudes of internal nodes (i.e., common ancestors of extant
languages) on a continuous surface, in which increments are
independent and normally distributed with a mean centered on
zero with variance that scales linearly in time, meaning that
diffusion processes are assumed to be homogeneous over time and
space. This can be unrealistic as many geographic features (e.g.,
mountains and rivers) can influence the rate of spread for each
branch. Bayesian continuous diffusion model we adopt here
effectively overcomes this limitation by relaxing the Brownian
process: borrowing ideas from uncorrelated relaxed clock models
[35], the method models branch-specific dispersal processes with
the diffusion rate scalar in each branch being drawn independently
and identically from a range of parametric distributions. Distributions used in our analyses are (i) Cauchy distribution that has fat
tails accommodating long distance dispersals [36], (ii) gamma
distribution that accommodates infinite variance in a manner
similar to Lévy flight models [37] but without enforcing power-law
tail behavior, and (iii) lognormal distribution that allows even
greater degree of rate variability [35]. In order to make our
geographic inference more realistic, we sampled the root and node
locations only from the land by assigning a prior probability of
zero to the water [11].
In addition, we compared the degree of model-fit between
relaxed and strict clocks [35]. Temporal scale of phylogenies was
calibrated using a probabilistic prior taken from well-attested
evidence that modern Ainu expanded into Sakhalin around 15th
century [38,39]: a normally-distributed prior with a mean of
500 BP with its 95% of the distribution incorporating 200 years of
Materials and Methods
The data consist of 19 geocoded lists of 200 basic vocabularies
(Figure 1; for a full list of sites, see Figure S1) compiled by Hattori
and Chiri during 1950s [22], when there was still a rich linguistic
diversity among the Ainu people. The basic vocabularies are a set
of words transmitted vertically from one generation to the next
[23], thereby preserving evolutionary signal required for reconstructing phylogenetic history [3,24]. Nevertheless, one could
argue that the 19 varieties that we analyze here are dialects of the
Ainu language and if one supposes that only languages, not
dialects, constitute representative units of analysis, then using these
varieties implies that the resulting tree may potentially depict
a confusing branching pattern with excessive detail, or even fail to
recover the actual subdivisions of the speech community [25].
We do not, however, consider this to be a major obstacle for
reconstructing Ainu language evolution for three reasons: (i)
a natural model of language evolution that we use here is known to
Figure 1. Map of the Ainu language varieties. Colored circles
represent two major subgroups (Green-Hokkaido; Yellow-Sakhalin).
Blue bar in the center indicates the main area of the Okhotsk
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Ainu Language Phylogeography
In order to examine the robustness of our phylogeographic
inferences, we carried out two additional tests. Firstly, we tested
the strength of support for northern Hokkaido origin (i.e., the
Okhotsk expansion scenario) over southern Hokkaido origin (i.e.,
the dual-structure model) by directly calculating BF: we divided
Hokkaido into two broad regions of north and south at the
centroid of Hokkaido, and estimated BF by comparing the
posterior to prior odds ratio of observing potential homeland in
either one of the two regions. In agreement with our results, we
obtained substantial support (BF = 7.5) for northern Hokkaido
being the homeland of the Ainu. Secondly, we investigated
whether or not our results are statistical artifacts of the diffusion
model falling into the center of language mass regardless of the
data: we randomly reassigned the locations of 19 Ainu varieties to
the data for fifty times, and then obtained 90% HPDs for all
possible root locations (Figure S2). From this exercise, we observed
that the absence of true signal could cause the estimated homeland
to be as south as mainland Japan or as north as Sakhalin. This
observation clearly demonstrates that our results are valid
estimations based on true phylogeographical signal. Conversely,
this also suggests that if the data contained signal indicating
northward diffusion, or any other direction, our methods would
have reconstructed it accordingly.
We acknowledge, however, that a well-established subgroup of
the Ainu language, namely the Kuril, is absent from our data. This
is because the Kuril had become extinct by the time the data were
collected, and the Kuril lexicons seem to be available only through
sketchy records scattered around the literature. For this reason, we
currently have little information about the Kuril. If the point in
uncertainty. For all analyses, we applied a stochastic Dollo model
with a correction for ascertainment bias [40] and a Bayesian
skyline tree prior [41]. We chose the best model by comparing
Bayes Factors (BF) [42].
Based on BF tests among diffusion models and evolutionary
clock models, we chose the relaxed clock with gamma-distributed
diffusion as the best model (Table S1). Figure 2 shows the
summary of time-dated maximum clade credibility trees for 19
Ainu language varieties. Assuming that the patterns of linguistic
diversity is shaped by the demographic dynamics of speakers, we
predicted that if the recent evidence supporting the Okhotsk
expansion scenario were correct, then the estimated root age
should overlap with 900–1600 BP. The estimated root age of the
Ainu language across post-burn-in trees has a median of 1288 BP
[mean: 1323 BP; 95% Highest Posterior Density (HPD): 820–
1862 BP], in strong agreement with the prediction. We also
predicted that if the hypothesized scenario were correct, then the
current distribution of 19 Ainu language varieties should be the
end result of diffusion from northern Hokkaido; otherwise, we
would observe northward expansion from southern Hokkaido,
conforming to the conventional dual-structure model. Figure 3
(also in Animation S1) shows that the estimated diffusion pattern in
natural time scale [43] is in clear agreement with the prediction,
with the estimated homeland being in northern Hokkaido. Both
the diffusion pattern and root time were consistent across all
models we excluded based on BF tests.
Figure 2. Maximum clade credibility tree of 19 Ainu language varieties. Colored branches represent two major subgroups (Green-Hokkaido;
Yellow-Sakhalin). All node heights are scaled to match the posterior median node heights with bars indicating 95% HPD intervals of the estimated
ages. The value on each branch is the posterior probability, showing the percentage support for the following node.
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Ainu Language Phylogeography
Figure 3. Inferred origin and diffusion of the Ainu language varieties in natural time scale. Color gradient of the polygons (80% HPD)
indicates relevant age of the diffusion [Blue-older (1288 BP); Red-more recent (50 BP)]. White lines represent the phylogeny projected onto the
surface. Image sources: ß 2012 Google Earth; ß 2012 Cnes/Spot Image; ß 2012 TerraMetrics.
islands must properly account for the recent northern Hokkaido
origin of the Ainu. With this respect, we suggest that the most
effective way of shedding light on the deeper history of the Jomon,
or historical processes of any other regions, is to synthesize
different lines of evidence from archaeology, biology and culture,
and triangulate them to obtain a rigorous analytic framework [48]
rather than relying on a single line of evidence.
If our inferences are correct, then the recent Okhotsk expansion
scenario for the Ainu origin leads us to a new question: what
historical factors drove the Okhotsk people to migrate from the
Amur river basin to Hokkaido and give rise to the Ainu? It is now
clear that early farming populations went through similar processes due to agricultural intensification and cultural innovation
[4] but the Okhotsk people were hunter-gatherers, not farmers.
While not resolving this question directly, Hudson [49] provides
a comprehensive model of the Okhotsk socio-environmental
conditions that allows us to sketch out a possible scenario: (i) the
diet of the Okhotsk people relied heavily on marine mammal
products and (ii) the time in which the Okhotsk expansion
occurred seems to be characterized by dramatic climate changes,
beginning with a cold sea-ice stage between 1300–1800 BP
followed by a warmer open-ocean stage. Based on these
observations, we speculate that the Okhotsk expansion may have
been opportunistic in nature: the sea-ice condition in the early
stage probably resulted in increased area for exploiting marine
mammals as well as convenient routes for exploring new territory,
thereby leading to the migration into Hokkaido. The drastic
climate change in the later stage, however, may have deteriorated
the hunting conditions for the Okhotsk with rapid break up of seaice, which may also have necessitated increased reliance on other
types of food source, and hence causing a greater degree of niche
overlap with the preexisting Jomon population. The end result was
time that the Kuril diverged from other varieties turns out to be
much deeper, then the resulting divergence time and diffusion
pattern may differ significantly from the current results. The
search for a more complete set of data is, therefore, a direction that
should be prioritized for further evaluation of our conclusion.
In this paper, we reconstructed spatiotemporal evolution of 19
Ainu language varieties, and the results are in strong agreement
with the hypothesis that a recent population expansion of the
Okhotsk people played a critical role in shaping the Ainu people
and their culture. Together with the recent archaeological,
biological and cultural evidence, our phylogeographic reconstruction of the Ainu language strongly suggests that the conventional
dual-structure model must be refined to explain these new bodies
of evidence. The case of the Ainu language origin we report here
also contributes additional detail to the global pattern of language
evolution, and our language phylogeny might also provide a basis
for making further inferences about the cultural dynamics of the
Ainu speakers [44,45].
We recognize that there are also some evidence that the Jomon
people, one of the two ancestral populations of the Ainu, may have
descended from Northeast Asia rather than Southeast [46,47],
thereby questioning the validity of dual-structure model on
a greater time scale. Unfortunately, the scope of our results
presented here have little bearing on the larger question of the
Jomon prehistory because the linguistic traces of this process may
have been wiped out by the recent rise of the Ainu as our results
indicate. Regardless of what further research reveals about the
Jomon ancestry, however, we argue that the evidence for the
Okhotsk expansion scenario should remain valid, and therefore
any future models of deeper historical process for the Japanese
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Ainu Language Phylogeography
probably the admixture of the two populations, followed by the
rise of a new ethnolinguistic group, namely the Ainu.
If we accept a view that transmission of language may be
gender-specific [50–52], then we are able to formulate at least two
hypotheses for the specific processes of the Ainu language origin.
Because Y-chromosome haplogroup D is thought to represent
Jomon male ancestry, the predominance of that particular
Ainu male ancestry is from the Jomon [53,54], whereas a heavy
mixture of mtDNA haplogroups indicates that a significant
proportion of the Ainu female ancestry is from the Okhotsk
(excluding 35.3% of mtDNA haplogroups that the Ainu share with
other neighboring populations, 39.4% of the remaining female
heritage is shared exclusively with the Okhotsk and the rest is
a mixture of both Jomon and Okhotsk [18,47,54]). If we thus
assume male-specific language transmission for the Ainu, the first
hypothesis for the processes behind the Ainu language origin could
who intermarried with Okhotsk females in northern Hokkaido,
assume that the transmission of Ainu language corresponds with
female ancestry, the second hypothesis could be that proto-Ainu
was spoken by the incoming Okhotsk females who merged with
the preexisting Jomon males. Based on these observations, we
propose that one potential way of understanding how language
change occurred for the Ainu is to estimate which gender was
more influential when early Ainu people established family
membership. This may be carried out indirectly by revealing the
signature of historical post-marital residence pattern via estimating
the degrees of genetic variation in their Y-chromosome and
mtDNA [55] as well as reconstructing ancestral post-marital
residence rules from regional cultural variation [56]. Investigating
a direction that deserves more attention, and acquiring an
accurate description of how language change occurred for the
Ainu would allow us to make further inferences about the deeper
history of the human lineage that once thrived in northern Japan.
Languages rise and fall, and so do the communities who speak
them. Although significant progress has been made in recent years,
we are still far from thoroughly understanding why languages are
so deeply related to the fates of their speakers or how the process
unfolds through evolutionary history. These are perhaps some of
the most challenging questions in human sciences, and a complete
understanding of this complex phenomenon might thus be
reached only with further methodological innovations as well as
more language data from around the world. But as we
demonstrate in this paper, a combination of spatiotemporal
reconstruction of language evolution and synthesis of several
different historical evidences is probably one of the most promising
methodologies that can further illuminate the process and
consequence of this fascinating phenomenon.
Supporting Information
Figure S1 Full list of the Ainu language varieties. Colored
circles represent subgrouping (Green-Hokkaido; Yellow-Sakhalin).
Figure S2 Ninety percent highest probability density
obtained from fifty random reassignments of location
coordinates to the tips of phylogeny. This demonstrates that
our results are not statistical artifacts of the diffusion model
returning to the center of language mass. For all analyses, we
applied an arbitrary root calibration consisting of a normal
distribution with the mean of 1500 BP and the standard deviation
of 400 years.
Table S1 Log-marginal likelihoods estimated from all
models fitted to data. The model with a relaxed clock and
gamma-distributed random walk model shows the best fit with the
highest log-marginal likelihood.
Animated origin and diffusion of the Ainu
language varieties in natural time scale. Color gradient of
the polygons (80% HPD) indicates relevant age of the diffusion
represent the phylogeny projected onto the surface. Image sources:
Animation S1
NEXUS and BEAST input files for full
details of the analysis.
Analysis S1
We thank Russell Gray, Simon Greenhill and Quentin Atkinson for their
insightful comments and help with technical issues. We also thank two
thoughtful reviewers for their constructive comments.
Author Contributions
Conceived and designed the experiments: SL TH. Analyzed the data: SL.
Wrote the paper: SL TH.
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