Location
Havener Center, St. Pat's Ballroom C
Presentation Date
April 21, 2023, 11:30am-12:30pm
Session
Session 1
Description
In the face of an extinction-level event, under what conditions are populations more likely to recover? When recovery happens, how do populations diversify to fill empty ecological niches? These questions in evolutionary biology are especially important in the current age of humanity-driven mass extinction. Our study uses a computational model of evolutionary dynamics to examine these questions. Simulated organisms on a two-dimensional phenotype space reproduce through assortative mating and an extinction event is triggered for a set number of generations halfway through the simulation. This model has been shown to exhibit nonequilibrium phase transition behavior when mutability or death rate parameters are varied. We use coalescent theory to construct lineage trees for populations that survive a mass extinction event. This analysis allows us to calculate the time to most recent common ancestor (TMRCA), which provides a quantitative measure of how the lineage structure is affected by the extinction event.
Meeting Name
32nd Annual Spring Meeting of the NASA-Mo Space Grant Consortium
Document Type
Presentation
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2023 The Authors, all rights reserved.
Simulating Mass Extinctions in an Agent-Based Evolutionary Model
Havener Center, St. Pat's Ballroom C
In the face of an extinction-level event, under what conditions are populations more likely to recover? When recovery happens, how do populations diversify to fill empty ecological niches? These questions in evolutionary biology are especially important in the current age of humanity-driven mass extinction. Our study uses a computational model of evolutionary dynamics to examine these questions. Simulated organisms on a two-dimensional phenotype space reproduce through assortative mating and an extinction event is triggered for a set number of generations halfway through the simulation. This model has been shown to exhibit nonequilibrium phase transition behavior when mutability or death rate parameters are varied. We use coalescent theory to construct lineage trees for populations that survive a mass extinction event. This analysis allows us to calculate the time to most recent common ancestor (TMRCA), which provides a quantitative measure of how the lineage structure is affected by the extinction event.
