Spatio-temporal Moran dynamics in continuous media
Melika Gorgi, Kamran Kaveh, Navid Aliakbarian, Mohammad Reza Ejtehadi

TL;DR
This paper develops a mathematical framework linking stochastic Moran models and deterministic reaction-diffusion equations to describe how evolutionary dynamics propagate across space and time, revealing different wave speeds depending on fitness components and media heterogeneity.
Contribution
It derives PDEs for the spatiotemporal limit of Moran dynamics, incorporating fitness components and media heterogeneity, bridging stochastic and deterministic models in evolutionary biology.
Findings
Selective wave speeds differ among Moran processes and FKPP.
Fecundity-driven waves decelerate in Birth-death processes.
Viability-driven waves accelerate in Death-birth processes.
Abstract
Understanding how natural selection unfolds across space and time is a central problem in evolutionary biology. Classic models such as the Moran process capture stochastic birth-death dynamics in structured populations, while reaction-diffusion equations like the Fisher-Kolmogorov-Petrovsky-Piskunov (FKPP) equation describe deterministic wave-like spread. In this work, we bridge these perspectives by deriving partial differential equations for the spatiotemporal limit of Moran dynamics in continuous media. Our model incorporates two distinct fitness components: fecundity (birth rate) and viability (death rate). We demonstrate that the resulting selective wave speeds differ substantially in spatial Moran Birth-death (Bd), Moran Death-birth (Db), and FKPP dynamics. When fecundity drives the dynamics, we observe that the selective waves decelerate for the Bd process, whereas in the Db…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEvolutionary Game Theory and Cooperation · Evolution and Genetic Dynamics · Mathematical Biology Tumor Growth
