Evolutionarily Stable Strategies for Fecundity and Swimming Speed of Fish

Type of content
Journal Article
Thesis discipline
Degree name
Publisher
University of Canterbury. Mathematics and Statistics
Journal Title
Journal ISSN
Volume Title
Language
Date
2016
Authors
Plank, M.J.
Pitchford, J.W.
James, A.
Abstract

Many pelagic fish species have a life history that involves producing a large number of small eggs. This is the result of a trade-off between fecundity and larval survival probability. There are also trade-offs involving other traits, such as larval swimming speed. Swimming faster increases the average food encounter rate but also increases the metabolic cost. Here we introduce an evolutionary model comprising fecundity and swimming speed as heritable traits. We show that there can be two evolutionary stable strategies. In environments where there is little noise in the food encounter rate, the stable strategy is a low-fecundity strategy with a swimming speed that minimises the mean time taken to reach reproductive maturity. However, in noisy environments, for example where the prey distribution is patchy or the water is turbulent, strategies that optimise mean outcomes are often outperformed by strategies that increase inter-individual variance. We show that, when larval growth rates are unpredictable, a high-fecundity strategy is evolutionarily stable. In a population following this strategy, the swimming speed is higher than would be anticipated by maximising the mean growth rate.

Description
Citation
Plank, M.J., Pitchford, J.W., James, A. (2016) Evolutionarily Stable Strategies for Fecundity and Swimming Speed of Fish. Bulletin of Mathematical Biology, 78(2), pp. 280-292.
Keywords
first passage time, fish egg size, fish growth rate, genetic algorithm, patchiness, stochastic growth
Ngā upoko tukutuku/Māori subject headings
ANZSRC fields of research
Fields of Research::49 - Mathematical sciences::4901 - Applied mathematics::490102 - Biological mathematics
Fields of Research::49 - Mathematical sciences::4905 - Statistics::490510 - Stochastic analysis and modelling
Field of Research::07 - Agricultural and Veterinary Sciences::0704 - Fisheries Sciences
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