Quantifying the tape of life: Ancestry-based metrics provide insights and intuition about evolutionary dynamics
- Published
- Accepted
- Subject Areas
- Computational Biology, Adaptive and Self-Organizing Systems, Scientific Computing and Simulation
- Keywords
- evolutionary computation, phylogeny, evolutionary dynamics, lineage metrics, artificial life, computational evolution, tournament selection
- Copyright
- © 2018 Dolson et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. Quantifying the tape of life: Ancestry-based metrics provide insights and intuition about evolutionary dynamics. PeerJ Preprints 6:e26883v1 https://doi.org/10.7287/peerj.preprints.26883v1
Abstract
Fine-scale evolutionary dynamics can be challenging to tease out when focused on broad brush strokes of whole populations over long time spans. We propose a suite of diagnostic metrics that operate on lineages and phylogenies in digital evolution experiments with the aim of improving our capacity to quantitatively explore the nuances of evolutionary histories in digital evolution experiments. We present three types of lineage measurements: lineage length, mutation accumulation, and phenotypic volatility. Additionally, we suggest the adoption of four phylogeny measurements from biology: depth of the most-recent common ancestor, phylogenetic richness, phylogenetic divergence, and phylogenetic regularity. We demonstrate the use of each metric on a set of two-dimensional, real-valued optimization problems under a range of mutation rates and selection strengths, confirming our intuitions about what they can tell us about evolutionary dynamics.
Author Comment
This paper describes a new suite of metrics for summarizing the long-term evolutionary dynamics of lineages. It also points out some useful metrics used by biologists that we suggest should be used in computational evolution as well. We have submitted this paper to a peer-reviewed conference: Artificial Life 2018.