Variability in the evolutionarily stable seasonal timing of germination and maturation of annuals and the mode of competition

Kazuhiro Bessho, Yoh Iwasa

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Here, we present a study examining the evolutionarily stable patterns of a seasonal schedule for an annual plant. We consider an evolutionary game in which the dates for germination and maturation are x and y, respectively. An individual increases its mass during the growing stage (from day x to y) and reproduces on y with a number of seeds proportional to its size. The seeds remain dormant from da. y y to day x in the following year. The daily mortality in the growing stage varies seasonally, whilst the mortality in the dormant stage is constant and small. Due to competition among individuals, the growth rate, mortality, and recruitment rate may depend on the total biomass of individuals in the growing stage. The evolutionarily stable population contains a mixture of phenotypes differing in germination date and maturation date if either the growth rate decreases or the mortality increases with the total biomass. If competition occurs through a lowered growth rate, the variance in the maturation date is greater than that in the germination date. However, these two variances are not very different if competition results mainly in enhanced mortality. If instead the competition results in lower recruitment success of the growing stage, the evolutionarily stable strategy (ESS) is composed of individuals with very early germination and maturation dates with small variability among individuals.

Original languageEnglish
Pages (from-to)66-80
Number of pages15
JournalJournal of Theoretical Biology
Volume304
DOIs
Publication statusPublished - Jul 7 2012

All Science Journal Classification (ASJC) codes

  • Agricultural and Biological Sciences(all)
  • Applied Mathematics
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Statistics and Probability
  • Modelling and Simulation

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