Journal
JOURNAL OF THE ROYAL SOCIETY INTERFACE
Volume 16, Issue 151, Pages -Publisher
ROYAL SOC
DOI: 10.1098/rsif.2018.0733
Keywords
nutritional geometry; life histories; in silico evolution; appetite; GPU; agent-based modelling
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Funding
- Australian Postgraduate Award
- Coffey Lab scholarship from the Charles Perkins Centre, University of Sydney
- Australian Research Council [DE180101520]
- Australian Research Council [DE180101520] Funding Source: Australian Research Council
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Lifespan and fecundity, the main components in evolutionary fitness, are both strongly affected by nutritional state. Geometric framework of nutrition (GFN) experiments has shown that lifespan and fecundity are separated in nutrient space leading to a functional trade-off between the two traits. Here we develop a spatially explicit agent-based model (ABM) using the GFN to explore how ecological factors may cause selection on macronutrient appetites to optimally balance these life-history traits. We show that increasing the risk of extrinsic mortality favours intake of a mixture of nutrients that is associated with maximal fecundity at the expense of reduced longevity and that this result is robust across spatial and nutritional environments. These model behaviours are consistent with what has been observed in studies that quantify changes in life history in response to environmental manipulations. Previous GFN-derived ABMs have treated fitness as a single value. This is the first such model to instead decompose fitness into its primary component traits, longevity and fecundity, allowing evolutionary fitness to be an emergent property of the two. Our model demonstrates that selection on macronutrient appetites may affect life-history trade-offs and makes predictions that can be directly tested in artificial selection experiments.
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