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

Rösti, Marius; Roesti, Hannes; Satokangas, Ina; Boughman, Janette; Chaturvedi, Samridhi; Wolf, Jochen B W; Langerhans, R Brian (2024). Predictability, an Orrery, and a Speciation Machine: Quest for a Standard Model of Speciation. Cold Spring Harbor perspectives in biology, 16(6) Cold Spring Harbor Laboratory Press 10.1101/cshperspect.a041456

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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.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Biology > Institute of Ecology and Evolution (IEE)

UniBE Contributor:

Rösti, Marius Samuel

Subjects:

500 Science > 570 Life sciences; biology

ISSN:

1943-0264

Publisher:

Cold Spring Harbor Laboratory Press

Language:

English

Submitter:

Pubmed Import

Date Deposited:

13 Feb 2024 12:14

Last Modified:

05 Jun 2024 00:13

Publisher DOI:

10.1101/cshperspect.a041456

PubMed ID:

38346860

URI:

https://boris.unibe.ch/id/eprint/192848

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