可预测性、奥里里和物种机器:探索物种繁衍的标准模型。

IF 6.9 2区 生物学 Q1 CELL BIOLOGY
Marius Roesti, Hannes Roesti, Ina Satokangas, Janette Boughman, Samridhi Chaturvedi, Jochen B W Wolf, R Brian Langerhans
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引用次数: 0

摘要

准确的预测通常被认为是科学认识强大的标志。然而,我们今天似乎还没有能力对生物物种的形成做出许多准确的预测。为什么?是什么限制了一般的可预测性,预测的功能和价值究竟是什么,我们又该如何预测新物种呢?受用于解释日食的方阵的启发,我们通过一个思想实验来解决这些问题,在这个实验中,我们设想了一个产生新物种的进化物种机器。该实验强调了复杂性、偶然性和物种多元化是预测物种演化的三大基本挑战。它还说明了预测在测试和改进概念模型方面的方法论价值。然后,我们概述了如何从假设的物种演化机器转变为物种演化的预测性标准模型。要操作、测试和完善这一模型,就需要在整个生命之树上协同转向大规模、综合性和跨学科的努力。这项工作与技术进步相结合,可能会揭示出表面上的随机过程其实是确定性的,并有望拓展我们对物种演化乃至进化的理解的广度和深度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictability, an Orrery, and a Speciation Machine: Quest for a Standard Model of Speciation.

Accurate predictions are commonly taken as a hallmark of strong scientific understanding. Yet, we do not seem capable today of making many accurate predictions about biological speciation. Why? What limits predictability in general, what exactly is the function and value of predictions, and how might we go about predicting new species? Inspired by an orrery used to explain solar eclipses, we address these questions with a thought experiment in which we conceive an evolutionary speciation machine generating new species. This experiment highlights complexity, chance, and speciation pluralism as the three fundamental challenges for predicting speciation. It also illustrates the methodological value of predictions in testing and improving conceptual models. We then outline how we might move from the hypothetical speciation machine to a predictive standard model of speciation. Operationalizing, testing, and refining this model will require a concerted shift to large-scale, integrative, and interdisciplinary efforts across the tree of life. This endeavor, paired with technological advances, may reveal apparently stochastic processes to be deterministic, and promises to expand the breadth and depth of our understanding of speciation and more generally, of evolution.

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来源期刊
CiteScore
15.00
自引率
1.40%
发文量
56
审稿时长
3-8 weeks
期刊介绍: Cold Spring Harbor Perspectives in Biology offers a comprehensive platform in the molecular life sciences, featuring reviews that span molecular, cell, and developmental biology, genetics, neuroscience, immunology, cancer biology, and molecular pathology. This online publication provides in-depth insights into various topics, making it a valuable resource for those engaged in diverse aspects of biological research.
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