Evidence for Divergence in Populations of Bonobos (Pan paniscus) in the Lomami-Lualaba and Kasai-Sankuru Regions Based on Preliminary Analysis of Craniodental Variation
- First Online:
- Cite this article as:
- Pilbrow, V. & Groves, C. Int J Primatol (2013) 34: 1244. doi:10.1007/s10764-013-9737-1
- 286 Downloads
Historical climatic events and riverine barriers influence the distribution of primates. The River Congo exerts the most significant influence on primate distribution in equatorial Africa, but the extent to which the inner basin of the Congo provided a refuge against Plio-Pleistocene climatic fluctuation is poorly understood. In this study we use cranial and dental morphometrics to examine how riverine barriers affect population patterns in bonobos (Pan paniscus). Bonobos and chimpanzees (Pan troglodytes) are sister species and share the distinction of being the closest evolutionary relatives of humans, yet comparatively little is known about bonobo morphological diversity. We selected 55 adult bonobo crania with well-preserved postcanine dentitions and divided them into regions separated by the rivers Lukenie, Kasai, Lomami, and Lualaba. We found good discrimination among these regions in cranial and dental metrics, but whereas the discriminant functions from cranial metrics were statistically significant, the discriminant functions from dental metrics were not. Mean classification accuracy was 89% for craniometrics, and ranged between 72% and 93% for dental metrics. On average 84–97% of phenetic variation was encountered within regions. Our results mirror molecular studies in suggesting that bonobos are characterized by a long-term stable demographic history allowing strong gene flow between regions and precluding drift and population differentiation. There are some indications that the bonobos from the Lomami-Lualaba and the Kasai-Sankuru regions are divergent, but modest sample sizes do not allow us to be conclusive. We would welcome the opportunity to work with field researchers to augment our sample sizes and reanalyze our data.