石灰岩时代的石灰岩系统的骨质基因和地层学影响
Héctor Del Valle1,2, Alejandro B Rodríguez-Navarro3, Abel Moclán4,5
1Institut Català de Paleoecologia Humana i Evolució Social (IPHES-CERCA), Zona Educacional 4, Campus Sescelades URV (Edifici W3), 43007, Tarragona, Spain. hectorvalleblanco@gmail.com.
Scientific reports
|February 14, 2025
概括
骨基生殖在埋葬过程中改变了骨结构,为化石层学提供了洞察力. 机器学习模型分析了阿帕的化学成分,揭示了不同的埋葬环境,并有助于化石分类.
科学领域:
- 古生物学的古生物学
- 地质化学 地质化学
- 材料科学 材料科学 材料科学
背景情况:
- 骨基因突变在埋葬后显著改变骨的组成和结构.
- 了解这些基因变化对于准确的化石分类和沉积物形成分析至关重要.
- 层级图形背景是解读骨材料中的代遗传途径的关键.
研究的目的:
- 在Galería遗址,Sierra de Atapuerca的完整地层学序列中调查骨基因过程.
- 评估化学指数和机器学习算法的有效性,用于分类骨基因和层级学.
- 为了阐明与骨炎的不同代遗传途径相关的环境条件.
主要方法:
- 结合X射线衍射与瑞特维尔德精细化和红外光谱学.
- 分析了11个与骨部件 (酸盐,碳酸盐,有机相) 相关的化学指数.
- 应用九个机器学习算法用于使用apatite单元细胞参数和细胞体积进行分类.
主要成果:
- 观察到阿帕蒂特单元细胞体积的逐渐变化 (531.9至526.1 Å3),与地层学单位 (GII至GIV) 相对应.
- 确定了不同的代谢途径:GII显示出浸和碳酸盐损失 (酸性,潮湿的环境),而GIII-GIV显示F−和CO3的结合 (性,干燥的环境).
- 证明了阿帕结构化学的变化,包括F−和OH−变化,与溶解-沉过程有关.
结论:
- 该研究成功开发了使用地球化学和机器学习方法的骨质diagenesis和层级学分类模型.
- 根据已识别的基因遗传路径推断出不同的埋葬环境.
- 这些发现增强了对沉积物形成动态的理解,并促进了化石遗骸的重新构建.
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