A new approach to exploratory data analysis in hominin phylogenetic reconstruction

IF 3.1 1区 地球科学 Q1 ANTHROPOLOGY
Joanna R. Gautney
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Abstract

The phylogenetic relationships between fossil hominin taxa have been a contentious topic for decades. Recent discoveries of new taxa, rather than resolving the issue, have only further confused it. Compounding this problem are the limitations of some of the tools frequently used by paleoanthropologists to analyze these relationships. Most commonly, phylogenetic questions are investigated using analytical methods such as maximum parsimony and Bayesian analysis. While these are useful analytical tools, these tree-building methods can have limitations when investigating taxa that may have complex evolutionary histories. Exploratory data analysis can provide information about patterns in a dataset that are obscured by tree-based methods. These patterns include phylogenetic signal conflict, which is not depicted in tree-based methods. Signal conflict can have a number of sources, including methodological issues with character choice, taxonomic issues, homoplasy, and gene flow between taxa. In this study, an exploratory data analysis of fossil hominin morphological data is conducted using the tree-based analytical method neighbor-joining and the network-based analytical method neighbor-net with the goal of visualizing phylogenetic signal conflict within a hominin morphological data set. The data set is divided into cranial regions, and each cranial region is analyzed individually to investigate which regions of the skull contain the highest levels of signal conflict. Results of this analysis show that conflicting phylogenetic signals are present in the hominin fossil record during the relatively speciose period between 3 and 1 Ma, and they also indicate that levels of signal conflict vary by cranial region. Possible sources of these conflicting signals are then explored. Exploratory data analyses such as this can be a useful tool in generating phylogenetic hypotheses and in refining character choice. This study also highlights the value network-based approaches can bring to the hominin phylogenetic analysis toolkit.

古人类系统发育重建中探索性数据分析的新方法
几十年来,古人类化石类群之间的系统发育关系一直是一个有争议的话题。最近新分类群的发现不仅没有解决这个问题,反而使它更加混乱。古人类学家在分析这些关系时经常使用的一些工具的局限性使问题更加复杂。最常见的是,系统发育问题的研究使用分析方法,如最大简约和贝叶斯分析。虽然这些都是有用的分析工具,但在研究可能具有复杂进化历史的分类群时,这些树构建方法可能存在局限性。探索性数据分析可以提供关于数据集中被基于树的方法所掩盖的模式的信息。这些模式包括系统发育信号冲突,这在基于树的方法中没有描述。信号冲突可能有许多来源,包括特征选择的方法问题、分类问题、同质性和分类群之间的基因流动。本文采用基于树的邻域连接(neighbor-joining)分析方法和基于网络的邻域网络(neighbor-net)分析方法对古人类化石形态数据进行了探索性数据分析,目的是可视化古人类形态数据集中的系统发育信号冲突。数据集被划分为颅区,每个颅区被单独分析,以研究颅骨的哪些区域包含最高水平的信号冲突。分析结果表明,在3 ~ 1 Ma的相对物种时期,人类化石记录中存在相互冲突的系统发育信号,并表明信号冲突的程度因颅骨区域而异。然后探索这些相互冲突的信号的可能来源。像这样的探索性数据分析可以成为生成系统发育假设和改进字符选择的有用工具。这项研究还强调了基于网络的方法可以给人类系统发育分析工具包带来的价值。
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来源期刊
Journal of Human Evolution
Journal of Human Evolution 生物-进化生物学
CiteScore
6.30
自引率
15.60%
发文量
104
审稿时长
3 months
期刊介绍: The Journal of Human Evolution concentrates on publishing the highest quality papers covering all aspects of human evolution. The central focus is aimed jointly at paleoanthropological work, covering human and primate fossils, and at comparative studies of living species, including both morphological and molecular evidence. These include descriptions of new discoveries, interpretative analyses of new and previously described material, and assessments of the phylogeny and paleobiology of primate species. Submissions should address issues and questions of broad interest in paleoanthropology.
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