I recently gave one of the plenary talks at a workshop on phylogenetic algorithms at the Lorentz Center in Leiden (Netherlands). In the talk I gave an overview of a number of recent results from my research program, including the creation of a Pama-Nyungan phylogeny and some of the research results that come from that.
The slides are available from academia.edu, from this link.
One of the results that is worth highlighting is the distribution of innovative languages within subgroups. A standard theory argues that languages innovate in the center of their ranges. The innovations diffuse across the language area over times, and therefore areas around the periphery tend to show more archaisms than those in the center. This distribution should also apply to language subgroups, assuming that language split occurs through the gradual accretion of isoglosses so that dialects split into separate languages.
If this is true, subgroup areas should show the same distributions, if not in absolute terms, but in large measure. That is, more innovative languages should lie towards the center of subgroups, and more conservative ones should lie around that edges.
It turns out that it is straightforward to plot the most innovative languages in each subgroup, according to how much basic vocabulary they have replaced. In the Chirila database, there are basic vocabulary lists coded by cognacy. To get a sense of how innovative a language is, we can simply sum, for each word in the language, the number of languages that share that cognate and divide it by the total number of language-cognate items. That gives us a sense of the extent to which languages participate in the most archaic vocabulary in the famiy. Plotting the most innovative language in each subgroup gives us the following map.
What can explain the discrepency? It’s probably the result of migratory expansions. That is, the languages that are the most innovative are the ones as the ‘ends’ of their subgroup phylogenetic expansions. That is, the most innovative languages are the ones that have undergone the most branching; another way of thinking about this is that more innovation happens on lineages with more branching events. This echoes a result from other work by Atkinson, Pagel, and colleagues, who also found that lineage splitting speeds up change.
One might think that this result reflects language contact; that is, that languages on the periphery might be in contact with more different languages, which leads to an increase in unidentifiable vocabulary. But these languages are not the only ones which are in contact with languages from other subgroups. In fact, if we map the most conservative languages in each subgroup, they are also often to be found around the periphery.
It may still be the case that the center-periphery model still holds in areas where languages have stopped expanding, and that Pama-Nyungan subgroups were (on the whole) not formed by diversification in situ.
It’s also interesting to plot the most and least conservative subgroups:
This is a bit more dodgy. For example, I strongly suspect that Thura-Yura’s place in this list is inflated by Wirangu having (as loans) a number of items that are otherwise found only in Western Pama-Nyungan languages, and by Wirangu overall showing some Pama-Nyungan retentions that are otherwise replaced in the rest of Thura-Yura. The broad trend, however, is that the further east, the less conservative. The correlation between longitude and retention is -0.49. The correlation doesn’t hold for latitude (0.05) or number of languages in the subgroup (-0.02).