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Locating Uncertainty in Stochastic Evolutionary Models: Divergence Time Estimation

Pence, Charles H. (2019) Locating Uncertainty in Stochastic Evolutionary Models: Divergence Time Estimation. Biology & Philosophy, 34. p. 21. ISSN 1572-8404

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Abstract

Philosophers of biology have worked extensively on how we ought best to interpret the probabilities which arise throughout evolutionary theory. In spite of this substantial work, however, much of the debate has remained persistently intractable. I offer the example of Bayesian models of divergence time estimation (the determination of when two evolutionary lineages split) as a case study in how we might bring further resources from the biological literature to bear on these debates. These models offer us an example in which a number of different sources of uncertainty are combined to produce an estimate for a complex, unobservable quantity. These models have been carefully analyzed in recent biological work, which has determined the relationship between these sources of uncertainty (their relative importance and their disappearance in the limit of increasing data), both quantitatively and qualitatively. I suggest here that this case shows us the limitations of univocal analyses of probability in evolution, as well as the simple dichotomy between “subjective” and “objective” probabilities, and I conclude by gesturing toward ways in which we might introduce more sophisticated interpretive taxonomies of probability (modeled on some recent work in the philosophy of physics) as a path toward advancing debates on probability in the life sciences.


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Item Type: Published Article or Volume
Creators:
CreatorsEmailORCID
Pence, Charles H.charles@charlespence.net0000-0002-6836-6047
Keywords: Probability, Uncertainty, Evolutionary theory, Divergence time, Scientific modeling, Stochastic models, Bayesian models
Subjects: Specific Sciences > Biology > Evolutionary Theory
Specific Sciences > Biology > Systematics
General Issues > Models and Idealization
Specific Sciences > Probability/Statistics
Depositing User: Charles H. Pence
Date Deposited: 22 Mar 2019 15:34
Last Modified: 22 Mar 2019 15:34
Item ID: 15842
Journal or Publication Title: Biology & Philosophy
Publisher: Springer
Official URL: https://link.springer.com/article/10.1007%2Fs10539...
DOI or Unique Handle: https://doi.org/10.1007/s10539-019-9683-1
Subjects: Specific Sciences > Biology > Evolutionary Theory
Specific Sciences > Biology > Systematics
General Issues > Models and Idealization
Specific Sciences > Probability/Statistics
Date: 19 March 2019
Page Range: p. 21
Volume: 34
ISSN: 1572-8404
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/15842

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