Revealing Evolutionarily Optimal Strategies in Self-Reproducing Systems via a New Computational Approach.

Revealing Evolutionarily Optimal Strategies in Self-Reproducing Systems via a New Computational Approach. Bull Math Biol. 2019 Sep 20;: Authors: Sandhu SK, Morozov A, Kuzenkov O Abstract Modelling the evolution of complex life history traits and behavioural patterns observed in the natural world is a challenging task. Here, we develop a novel computational method to obtain evolutionarily optimal life history traits/behavioural patterns in population models with a strong inheritance. The new method is based on the reconstruction of evolutionary fitness using underlying equations for population dynamics and it can be applied to self-reproducing systems (including complicated age-structured models), where fitness does not depend on initial conditions, however, it can be extended to some frequency-dependent cases. The technique provides us with a tool to efficiently explore both scalar-valued and function-valued traits with any required accuracy. Moreover, the method can be implemented even in the case where we ignore the underlying model equations and only have population dynamics time series. As a meaningful ecological case study, we explore optimal strategies of diel vertical migration (DVM) of herbivorous zooplankton in the vertical water column which is a widespread phenomenon in both oceans and lakes, generally considered to be the largest synchronised movement of biomass on Earth. We reveal optimal trajectories of daily vertical m...
Source: Bulletin of Mathematical Biology - Category: Bioinformatics Authors: Tags: Bull Math Biol Source Type: research