ArticleProceedings. Mathematical, physical, and engineering sciences2020
Predicting population extinction in lattice-based birth-death-movement models.
Article in Proceedings. Mathematical, physical, and engineering sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Agent-Based and Continuum Models for Spatial Dynamics of Infection by Oncolytic Viruses.Bulletin of mathematical biology · 2023Article
- Interpreting how nonlinear diffusion affects the fate of bistable populations using a discrete modelling framework.Proceedings. Mathematical, physical, and engineering sciences · 2022Article
- Understanding nano-engineered particle-cell interactions: biological insights from mathematical models.Nanoscale advances · 2021Review
- Population dynamics with spatial structure and an Allee effect.Proceedings. Mathematical, physical, and engineering sciences · 2020Article
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3 authors.
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Abstract
The question of whether a population will persist or go extinct is of key interest throughout ecology and biology. Various mathematical techniques allow us to generate knowledge regarding individual behaviour, which can be analysed to obtain predictions about the ultimate survival or extinction of the population. A common model employed to describe population dynamics is the lattice-based random walk model with crowding (exclusion). This model can incorporate behaviour such as birth, death and movement, while including natural phenomena such as finite size effects. Performing sufficiently many realizations of the random walk model to extract representative population behaviour is computationally intensive. Therefore, continuum approximations of random walk models are routinely employed. However, standard continuum approximations are notoriously incapable of making accurate predictions about population extinction. Here, we develop a new continuum approximation, the
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