CaltechAUTHORS
Published February 2022 | Version public
Journal Article Metadata-only

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

Creators

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.

Additional Information

We are grateful to J. Losos for evolutionary insight and eagle viewing; L. Taber for agent-based model insight; C. Huang, S. Hughes, K. Evason, J. Collins and C. Pickett for establishing experimental foundations; W. Tao, L. Chen, A. Sigala and A. Earnest for preliminary studies; and S. Kirchner for scientific advice, discussion and editing. We thank the Caenorhabditis Genetics Center (funded by NIH Office of Research Infrastructure Programs (P40 OD010440)) for providing strains. This work was supported by the NIH grant R01 AG02656106A1 to K.K. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Additional details

Identifiers

Eprint ID
118502
Resolver ID
CaltechAUTHORS:20221219-417430800.29

Funding

NIH
P40 OD010440
NIH
R01 AG02656106A1

Dates

Created
2023-01-19
Created from EPrint's datestamp field
Updated
2023-01-19
Created from EPrint's last_modified field