机器学习证实了英国中侏罗世微脊椎动物群中手盗龙兽脚亚目的新记录

IF 2.3 2区 地球科学 Q1 PALEONTOLOGY
S. Wills, C. Underwood, P. Barrett
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引用次数: 1

摘要

目前的研究表明,手盗龙兽脚亚目的初始辐射发生在中侏罗世,尽管它们的化石记录几乎完全来自白垩纪。然而,侏罗纪手盗龙的化石很少,通常只由孤立的牙齿组成,它们的鉴定经常有争议。在这里,我们应用不同的机器学习模型,结合形态学比较,对一套从英国Bathonian微脊椎动物遗址中分离出来的兽脚亚目牙齿进行了研究,以确定这些牙齿中是否有任何一个可以自信地归属于手盗龙。我们在具有广泛的兽脚亚目分类群和广泛的地理和时间覆盖的训练数据集上生成了三个独立的模型。我们将样本中的中侏罗世牙齿与这些模型进行了分类,并对其形态进行了比较,结果表明,这些组合中至少存在三种不同的驰龙形态类型,外加一种兽尖龙和一种troodontid。这些新发现显著地将兽齿兽总科和齿龙总科的范围扩大了约27myr。这些结果表明,手盗龙不仅像之前的系统发育分析所预测的那样出现在中侏罗世,而且在泛大陆分裂之前,它们已经辐射成一个多样化的动物群。该研究还证明了机器学习在为分离牙齿提供定量评估方面的能力,为分类鉴定提供了一个强大的、可测试的框架,并强调了在动物群和进化分析中评估和包括来自微脊椎动物位点的证据的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning confirms new records of maniraptoran theropods in Middle Jurassic UK microvertebrate faunas
Current research suggests that the initial radiation of maniraptoran theropods occurred in the Middle Jurassic, although their fossil record is known almost exclusively from the Cretaceous. However, fossils of Jurassic maniraptorans are scarce, usually consisting solely of isolated teeth, and their identifications are often disputed. Here, we apply different machine learning models, in conjunction with morphological comparisons, to a suite of isolated theropod teeth from Bathonian microvertebrate sites in the UK to determine whether any of these can be confidently assigned to Maniraptora. We generated three independent models developed on a training dataset with a wide range of theropod taxa and broad geographical and temporal coverage. Classification of the Middle Jurassic teeth in our sample against these models and comparison of the morphology indicates the presence of at least three distinct dromaeosaur morphotypes, plus a therizinosaur and troodontid in these assemblages. These new referrals significantly extend the ranges of Therizinosauroidea and Troodontidae by some 27 myr. These results indicate that not only were maniraptorans present in the Middle Jurassic, as predicted by previous phylogenetic analyses, but they had already radiated into a diverse fauna that pre‐dated the break‐up of Pangaea. This study also demonstrates the power of machine learning to provide quantitative assessments of isolated teeth in providing a robust, testable framework for taxonomic identifications, and highlights the importance of assessing and including evidence from microvertebrate sites in faunal and evolutionary analyses.
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来源期刊
Papers in Palaeontology
Papers in Palaeontology PALEONTOLOGY-
CiteScore
4.50
自引率
4.30%
发文量
55
期刊介绍: Papers in Palaeontology is the successor to Special Papers in Palaeontology and a journal of the Palaeontological Association (www.palass.org). The journal is devoted to the publication of papers that document the diversity of past life and its distribution in time and space. Papers in Palaeontology is devoted to the publication of papers that document the diversity of past life and its distribution in time and space. As a sister publication to Palaeontology its focus is on descriptive research, including the descriptions of new taxa, systematic revisions of higher taxa, detailed biostratigraphical and biogeographical documentation, and descriptions of floras and faunas from specific localities or regions. Most contributions are expected to be less than 30 pp long but longer contributions will be considered if the material merits it, including single topic parts. The journal publishes a wide variety of papers on palaeontological topics covering: palaeozoology, palaeobotany, systematic studies, palaeoecology, micropalaeontology, palaeobiogeography, functional morphology, stratigraphy, taxonomy, taphonomy, palaeoenvironmental reconstruction, palaeoclimate analysis, biomineralization studies.
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