Department of Physics, University of Dayton, OH, USA; School of Mathematics and Statistics, The Open University, Milton Keynes, UK.
Earth & Planetary Sciences, University of New Mexico, NM, USA.
Phys Life Rev. 2022 Jul;41:22-57. doi: 10.1016/j.plrev.2022.04.001. Epub 2022 Apr 15.
Extinction of species, and even clades, is a normal part of the macroevolutionary process. However, several times in Earth history the rate of species and clade extinctions increased dramatically compared to the observed "background" extinction rate. Such episodes are global, short-lived, and associated with substantial environmental changes, especially to the carbon cycle. Consequently, these events are dubbed "mass extinctions" (MEs). Investigations surrounding the circumstances causing and/or contributing to mass extinctions are on-going, but consensus has not yet been reached, particularly as to common ME triggers or periodicities. In part this reflects the incomplete nature of the fossil and geologic record, which - although providing significant information about the taxa and paleoenvironmental context of MEs - is spatiotemporally discontinuous and preserved at relatively low resolution. Mathematical models provide an important opportunity to potentially compensate for missing linkages in data availability and resolution. Mathematical models may provide a means to connect ecosystem scale processes (i.e., the extinction of individual organisms) to global scale processes (i.e., extinction of whole species and clades). Such a view would substantially improve our understanding not only of how MEs precipitate, but also how biological and paleobiological sciences may inform each other. Here we provide suggestions for how to integrate mathematical models into ME research, starting with a change of focus from ME triggers to organismal kill mechanisms since these are much more standard across time and spatial scales. We conclude that the advantage of integrating mathematical models with standard geological, geochemical, and ecological methods is great and researchers should work towards better utilization of these methods in ME investigations.
物种甚至进化枝的灭绝是宏观进化过程的正常组成部分。然而,在地球历史上的几次,物种和进化枝的灭绝速度与观察到的“背景”灭绝率相比急剧增加。这些事件是全球性的、短暂的,与环境的重大变化有关,特别是与碳循环有关。因此,这些事件被称为“大规模灭绝”(MEs)。导致和/或促成大规模灭绝的情况的调查仍在进行中,但尚未达成共识,特别是关于共同的大规模灭绝触发因素或周期性。部分原因是化石和地质记录的不完整性,尽管这些记录提供了关于大规模灭绝的分类群和古环境背景的重要信息,但它们在时空上是不连续的,且保存的分辨率相对较低。数学模型提供了一个重要的机会,可以潜在地弥补数据可用性和分辨率方面缺失的联系。数学模型可以提供一种将生态系统尺度的过程(即个体生物的灭绝)与全球尺度的过程(即整个物种和进化枝的灭绝)联系起来的方法。这种观点将极大地提高我们对大规模灭绝的发生方式的理解,不仅包括大规模灭绝的触发因素,还包括生物和古生物学科学如何相互启发。在这里,我们提出了如何将数学模型纳入大规模灭绝研究的建议,首先将研究重点从大规模灭绝的触发因素转变为生物体的杀伤机制,因为这些在时间和空间尺度上更为标准。我们得出的结论是,将数学模型与标准的地质、地球化学和生态方法相结合具有很大的优势,研究人员应该努力更好地利用这些方法来进行大规模灭绝的研究。