Dylan Childs
Dylan Childs
United Kingdom
Field of research: Animal and Plant Sciences Email : d.childs[at]sheffield.ac.uk
"What can comparative demography teach us about ecology and evolution?"
30th July : 14:00-14:20 (open to all)
Venue: The Norwegian Academy of Science and Letters
(Drammensveien 78, Oslo)
A central concept in life history theory is that organisms are fundamentally constrained by trade-offs among fitness components. Demographic data provide a valuable means to explore these relationships—reanalyses of published matrix population models (MPMs) have identified consistent life history variation that appears to fall onto to a fast-slow continuum and a reproductive strategy axis. These relationships are assumed to reflect fundamental trade-offs. However, demographic constraints may also impact on patterns of covariance between life history metrics in natural populations. We simulated sets of size-structured integral projection models (IPMs) under the simple constraint that the long-term growth rate is close to one, which is to be expected when populations are subject to density dependence.
The IPMs were then discretised to mimic the stage structures found in published MPMs. We find that a PCA of life history metrics derived from the simulated models produced patterns of life history trait covariance that are very similar to patterns seen in empirical data. Our results indicate that comparative analysis of MPM-derived life history traits may not identify meaningful life history trade-offs and that a significant component of the covariance among MPM-derived life history matrics is consistent with non-adaptive constraints arising from density dependence.
Dr. Dylan Childs is a Senior Lecturer in the Department of Animal and Plant Sciences at the University of Sheffield. Prior to his appointment as Senior Lecturer, Dr. Childs was an NERC postdoctoral fellow in the Department of Animal and Plant Sciences at the University of Sheffield. He received his PhD in Population Biology from Imperial College, London and his bachelor’s degree from Churchill College, Cambridge.
He is a population biologist who investigates the ecological drivers of population dynamics and selection in laboratory and free-living populations. He seeks to understand how demographic and environmental processes interact to drive variation in population growth and selection on life histories—he is particularly interested in the causes and consequence of environmental stochasticity within this context. Much of this research relies on the application of data-driven, structured population models. To facilitate this, he develops theory and statistical tools for modelling demographically-structured populations, most prominently, having recently co-authored a monograph describing the theory and application of Integral Projection Models.