Predictability, an Orrery, and a Speciation Machine: Quest for a Standard Model of Speciation.
Publisher DOI
PubMed ID
38346860
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.
Date Issued
2024-06-03
Publication Type
Article
Subject(s)
Language(s)
en
Author(s)
Roesti, Hannes | |
Satokangas, Ina | |
Boughman, Janette | |
Chaturvedi, Samridhi | |
Wolf, Jochen B W | |
Langerhans, R Brian |
Additional Credits
Journal
Cold Spring Harbor perspectives in biology
Publisher
Cold Spring Harbor Laboratory Press
ISSN
1943-0264
Access(Rights)
metadata.only