A laboratory and simulation platform to integrate individual life history traits and population dynamics

Andrea Scharf, Josh Mitteldorf, Brinda Armstead, Daniel Schneider, He Jin, Zuzana Kocsisova, Chieh Hsiang Tan, Francesca Sanchez, Brian Brady, Natasha Ram, Gabriel B. DiAntonio, Andrea M. Wilson, Kerry Kornfeld

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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.

Original languageEnglish
Pages (from-to)90-101
Number of pages12
JournalNature Computational Science
Volume2
Issue number2
DOIs
StatePublished - Feb 2022

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