A Laboratory And Simulation Platform To Integrate Individual Life History Traits And Population Dynamics
Abstract
Understanding populations is important as they are a fundamental level of biological organization. Individual traits such as aging and lifespan interact in complex ways to determine birth and death, and thereby influence population dynamics; however, we lack a deep understanding of the relationships between individual traits and population dynamics. To address this challenge, we established a laboratory population using the model organism Caenorhabditis elegans and an individual-based computational simulation informed by measurements of real worms. The simulation realistically models individual worms and the behavior of the laboratory population. To elucidate the role of aging in population dynamics, we analyzed old age as a cause of death and showed, using computer simulations, that it was influenced by maximum lifespan, rate of adult culling and progeny number/food stability. Notably, populations displayed a tipping point for aging as the primary cause of adult death. Our work establishes a conceptual framework that could be used for better understanding why certain animals die of old age in the wild.
Recommended Citation
A. Scharf and J. Mitteldorf and B. Armstead and D. Schneider and H. Jin and Z. Kocsisova and C. H. Tan and F. Sanchez and B. Brady and N. Ram and G. B. DiAntonio and A. M. Wilson and K. Kornfeld, "A Laboratory And Simulation Platform To Integrate Individual Life History Traits And Population Dynamics," Nature Computational Science, vol. 2, no. 2, pp. 90 - 101, Nature Research, Feb 2022.
The definitive version is available at https://doi.org/10.1038/s43588-022-00190-8
Department(s)
Biological Sciences
International Standard Serial Number (ISSN)
2662-8457
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023 Nature Research, All rights reserved.
Publication Date
01 Feb 2022
Comments
National Institutes of Health, Grant P40 OD010440