Predictability, an Orrery, and a Speciation Machine: Quest for a Standard Model of Speciation.

IF 6.9 2区 生物学 Q1 CELL BIOLOGY Cold Spring Harbor perspectives in biology Pub Date : 2024-06-03 DOI:10.1101/cshperspect.a041456
Marius Roesti, Hannes Roesti, Ina Satokangas, Janette Boughman, Samridhi Chaturvedi, Jochen B W Wolf, R Brian Langerhans
{"title":"Predictability, an Orrery, and a Speciation Machine: Quest for a Standard Model of Speciation.","authors":"Marius Roesti, Hannes Roesti, Ina Satokangas, Janette Boughman, Samridhi Chaturvedi, Jochen B W Wolf, R Brian Langerhans","doi":"10.1101/cshperspect.a041456","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":6.9000,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11146309/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cold Spring Harbor perspectives in biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1101/cshperspect.a041456","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
可预测性、奥里里和物种机器:探索物种繁衍的标准模型。
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。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
Mechanisms of Alternative Lengthening of Telomeres. Rediscovering and Unrediscovering Gregor Mendel: His Life, Times, and Intellectual Context. Teaching School Genetics in the 2020s: Why "Naive" Mendelian Genetics Has to Go. The Role of Microhomology-Mediated End Joining (MMEJ) at Dysfunctional Telomeres. Modeling the Emergence of Circuit Organization and Function during Development.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1