Inferring birth versus death dynamics for ecological interactions in stochastic heterogeneous populations

Fuente: arXiv
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Autores principales: Beckman, Erin, Cho, Heyrim, Huynh, Linh
Formato: Preprint
Publicado: 2024
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author Beckman, Erin
Cho, Heyrim
Huynh, Linh
author_facet Beckman, Erin
Cho, Heyrim
Huynh, Linh
contents In this paper, we study the significance of ecological interactions and separation of birth and death dynamics in stochastic heterogeneous populations via general birth-death processes. Interactions can manifest through the birth dynamics, the death dynamics, or some combination of the two. The underlying microscopic mechanisms are important but often implicit in population-level data. We propose an inference method for disambiguating the types of interaction and the birth and death processes from population size time series data of a stochastic $n$-type heterogeneous population. The interspecies interactions considered can be competitive, antagonistic, or mutualistic. We show that different pairs of birth and death rates with the same net growth rate result in different time series statistics. Then, the inference method is validated in the example of a birth-death process inspired by the two-type Lotka-Volterra interaction dynamics. Utilizing stochastic fluctuations enables us to estimate additional parameters in this stochastic Lotka-Volterra model, which are not identifiable in a deterministic model.
format Preprint
id arxiv_https___arxiv_org_abs_2410_09041
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Inferring birth versus death dynamics for ecological interactions in stochastic heterogeneous populations
Beckman, Erin
Cho, Heyrim
Huynh, Linh
Populations and Evolution
Probability
60J27, 92D25, 62M10
In this paper, we study the significance of ecological interactions and separation of birth and death dynamics in stochastic heterogeneous populations via general birth-death processes. Interactions can manifest through the birth dynamics, the death dynamics, or some combination of the two. The underlying microscopic mechanisms are important but often implicit in population-level data. We propose an inference method for disambiguating the types of interaction and the birth and death processes from population size time series data of a stochastic $n$-type heterogeneous population. The interspecies interactions considered can be competitive, antagonistic, or mutualistic. We show that different pairs of birth and death rates with the same net growth rate result in different time series statistics. Then, the inference method is validated in the example of a birth-death process inspired by the two-type Lotka-Volterra interaction dynamics. Utilizing stochastic fluctuations enables us to estimate additional parameters in this stochastic Lotka-Volterra model, which are not identifiable in a deterministic model.
title Inferring birth versus death dynamics for ecological interactions in stochastic heterogeneous populations
topic Populations and Evolution
Probability
60J27, 92D25, 62M10
url https://arxiv.org/abs/2410.09041