Tooth Size Apportionment, Bayesian Inference, and the Phylogeny of Homo Naledi
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bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423087; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Tooth size apportionment, Bayesian inference, and the phylogeny of Homo naledi Joel D. Irish a,b,*, Mark Grabowskia,c aResearch Centre in Evolutionary Anthropology and Palaeoecology, School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool L3 3AF UK bEvolutionary Studies Institute and Centre for Excellence in PalaeoSciences, University of the Witwatersrand, Private Bag 3, WITS 2050, Johannesburg, South Africa c Centre for Ecology and Evolutionary Synthesis, Department of Biosciences, University of Oslo, Norway *Corresponding author. E-mail address: [email protected] Acknowledgements Thank you to the individuals currently or formerly affiliated with the institutions at which the odontometric measurements of North and sub-Saharan H. sapiens samples were recorded. These include: Charles Merbs and Donald Morris from Arizona State University (ASU); Elden Johnson from the University of Minnesota; Douglas Ubelaker, David Hunt, and Carol Butler from the National Museum of Natural History; Ian Tattersall, Jaymie Brauer, and Gary Sawyer from the American Museum of Natural History; Andre Langaney, Frances Roville-Sausse, and Miya Awazu Periera da Silva from the Musée de l’Homme; Romuald Schild, Michal Kobusiewicz, and Jacek Kabaciński from the Combined Prehistoric Expedition to Gebel Ramlah; and Renée Friedman from the Hierakonpolis Expedition. Thanks are also extended to Lee Berger, from the Evolutionary Studies Institute and Centre for Excellence in PalaeoSciences; Darryl de Ruiter, Texas A&M, for those measurements presented in our 2016 TSA publication that are incorporated here; and Lucas Delezene, University of Arkansas, who provided a list of publications containing Asian H. erectus MD and BL measurements, several of which were accessed for the present summary data. Funding for the data collection by the first author came from the National Science Foundation (BNS- 9013942), the ASU Research Development Program, American Museum of Natural History, Friends of Nekhen, and a National Science Foundation grant awarded to Jerome Rose (BCS- 0119754). 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423087; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract This study has three main objectives—two methodological and one summative, namely, further characterization of Homo naledi (~335–236 ka) to more firmly establish its evolutionary history. Using mathematically-corrected mesiodistal and buccolingual crown dimensions, the species was compared with samples of Pan troglodytes, Australopithecus africanus, A. afarensis, Paranthropus robustus, P. boisei, H. habilis, H. ergaster, H. erectus, H. heidelbergensis, H. neanderthalensis, and H. sapiens; the correction yields equivalently scaled samples unaffected by significant interspecific size differences. After initial cluster analysis, the data were used in tooth size apportionment analysis to determine how size is distributed relatively in each species’ dentition, while visualizing this variation in a sample scatterplot. The first main objective then, after quantitative coding, is evaluating the utility of these characters to estimate phylogenetic relationships, here using Bayesian inference with an Mkv model. The second objective, for the first time in paleoanthropological study, is estimating relationships using continuous characters, i.e., the scaled data, through Bayesian inference under a Brownian-motion model. This strategy facilitates maximum reception of potential phylogenetic signal. The final objective based on all analyses, though principally continuous Bayesian inference, is to elucidate the phylogeny of H. naledi. Relationships are largely congruent across methods and, with markedly higher node support, most of those inferred in prior systematic studies using qualitatively discretized traits. The present results place H. naledi as a sister taxon to H. habilis (node support ~70-99%), with a plesiomorphic pattern of relative tooth size. It is nested within a clade comprising australopiths and early Homo dating 3.3 Ma to ~800 ka, distinct from younger H. erectus through H. sapiens. This suggests that H. naledi originated well before the geological date range associated with the Dinaledi Chamber, from which the remains in this study were recovered, to represent a long-lived side branch in the genus. Keywords: Geometric means, phenetic analyses, probabilistic phylogenetics, quantitative coding, continuous data, fossil hominins 2 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423087; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1. Introduction In this study tooth size apportionment (TSA) analysis was used to characterize further the recently defined hominin, Homo naledi (Berger et al., 2015), ~335–236 ka (Dirks et al., 2017), relative to other Plio-Pleistocene and recent comparative species. It builds on work demonstrating the efficacy of this odontometric technique for gauging phenetic affinities among various African hominin samples, including Australopithecus sediba, along with recent humans and Pan troglodytes (Irish et al., 2016). In TSA, the unit of study is the entire permanent dentition, rather than individual mesiodistal (MD) and buccolingual (BL) crown dimensions. That is, these lengths and widths are corrected mathematically (below) to yield equivalently scaled samples, which are then submitted to principal components analysis to produce statistically uncorrelated factor scores; these scores are compared to determine how crown size is differentially distributed, or apportioned, along the tooth rows. Because TSA was found to be effective in comparing both modern human individuals and groups (Harris and Bailit, 1988; Harris and Rathbun, 1991; Hemphill et al., 1992; Lukacs and Hemphill, 1993; Harris, 1997, 1998; Irish and Hemphill, 2001; Irish and Kenyhercz, 2013), which on an intraspecific level exhibit minimal variation, the approach was projected to be particularly effective in comparing more discernible interspecific dental differences in our hominin ancestors. This prediction was proven correct, as the grouping of species (in Irish et al., 2016) that were also included in other, albeit, cladistic studies (Strait et al., 1997; Strait and Grine, 2004; Smith and Grine, 2008) is congruent, as are results pertaining to specific relationships of A. sediba (Berger et al., 2010; Irish et al., 2013, 2014; Dembo et al., 2015, 2016). As such, the initial intent here was to simply undertake equivalent TSA analyses to assess the interspecific relationships of H. naledi, as well as its taxonomic classification. Earlier studies using characters throughout the skeleton, including dental nonmetric traits, supported its inclusion in the genus Homo, but as a distinct member (Berger et al., 2015; Thackeray, 2015; Dembo et al., 2016; Irish et al., 2018; also Holloway et al., 2018; Davies et 3 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423087; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. al., 2020). A phenetic approach was deemed most appropriate because odontometric data, original or scaled, do not lend themselves well to cladistics. Of course, the same caveat applies to all continuous morphological data in traditional, non-probabilistic phylogenetic analyses (Pimentel and Riggins, 1987; Pogue and Mickevich, 1990; Thiele, 1993; Wiens, 1995; Poe and Wiens, 2000; Parins-Fukuchi, 2018a), when not excluded entirely (Poe and Wiens, 2000; Garcia-Cruz and Sosa; 2006). Defined, these are data that “. can take on any real number value, whether a measurement of a morphometric character in a specific individual, or the mean value of an intraspecifically variable, quantitative trait for a given species” (Wiens, 2001:690). Standard operating procedure to include such data in cladistic analyses necessitates subjective, qualitative coding (per Stevens, 1991; Thiele, 1993; Wiens, 2001; Felsenstein, 2004; Parins-Fukuchi, 2018a, 2018b) into two or a few discrete states, or by using one of several more objective, quantitative techniques. Some of the latter, to boost phylogenetic signal over qualitative discretizing, return upwards of 30+ character states (reviewed in Wiens, 2001; Felsenstein, 2004; Garcia-Cruz and Sosa; 2006; Jones and Butler, 2018), including oft-used gap-weighting (Thiele, 1993; Schols et al, 2004; Garcia-Cruz and Sosa; 2006; Goloboff et al., 2006). Yet, quantitative coding comes with other concerns, and still fails to detect all key information (Farris, 1990; Wiens, 2001; Felsenstein, 2004; Goloboff et al., 2006; Parins-Fukuchi, 2018b). So, while coded data remain standard for phylogenetic analyses of fossil hominins (e.g., Strait et al., 1997; Strait and Grine, 2001; 2004; Dembo et al., 2015, 2016; Mongle et al., 2019), a relatively rare yet promising alternative (Parins-Fukuchi, 2018a, 2018b) is to