Author(s): Gibbs S, Collard M, Wood B
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Abstract This paper reports the results of a literature search for information about the soft-tissue anatomy of the extant non-human hominoid genera, Pan, Gorilla, Pongo and Hylobates, together with the results of a phylogenetic analysis of these data plus comparable data for Homo. Information on the four extant non-human hominoid genera was located for 240 out of the 1783 soft-tissue structures listed in the Nomina Anatomica. Numerically these data are biased so that information about some systems (e.g. muscles) and some regions (e.g. the forelimb) are over-represented, whereas other systems and regions (e.g. the veins and the lymphatics of the vascular system, the head region) are either under-represented or not represented at all. Screening to ensure that the data were suitable for use in a phylogenetic analysis reduced the number of eligible soft-tissue structures to 171. These data, together with comparable data for modern humans, were converted into discontinuous character states suitable for phylogenetic analysis and then used to construct a taxon-by-character matrix. This matrix was used in two tests of the hypothesis that soft-tissue characters can be relied upon to reconstruct hominoid phylogenetic relationships. In the first, parsimony analysis was used to identify cladograms requiring the smallest number of character state changes. In the second, the phylogenetic bootstrap was used to determine the confidence intervals of the most parsimonious clades. The parsimony analysis yielded a single most parsimonious cladogram that matched the molecular cladogram. Similarly the bootstrap analysis yielded clades that were compatible with the molecular cladogram; a (Homo, Pan) clade was supported by 95\% of the replicates, and a (Gorilla, Pan, Homo) clade by 96\%. These are the first hominoid morphological data to provide statistically significant support for the clades favoured by the molecular evidence.
This article was published in J Anat
and referenced in Biological Systems: Open Access