Phytoplankton adaptation in ecosystem models

• Published in: Journal of theoretical biology Vol. 468; pp. 60 - 71
• Main Authors: Beckmann, Aike, Schaum, C-Elisa, Hense, Inga
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 07.05.2019
• Subjects: Adaptive evolution; Individual based model (IBM); Multi-compartment model (MCM); NPZD-Type model; Thermal adaptation; Trait diffusion model; Adaptive evolution; Multi-compartment model (MCM); NPZD-Type model; Trait diffusion model; Thermal adaptation; Individual based model (IBM)
• DOI: 10.1016/j.jtbi.2019.01.041
• ISSN: 0022-5193; 1095-8541

•we compare two different approaches to model trait value changes in unicellular asexual planktonic organisms.•the individual based (MuSe-IBM) and the compartment based (MuSe-MCM) approach show essentially identical results for a suite of model experiments.•MuSe-IBM and MuSe-MCM reproduce a variety of well-known and plausible features of phytoplankton response to temperature changes.•MuSe-IBM and MuSe-MCM are useful for investigating the evolutionary path of populations and suitable to tackle a wide variety of questions in the field of planktonic evolutionary science. We compare two different approaches to model adaptation of phytoplankton through trait value changes. Both consider mutation and selection (MuSe) but differ with respect to the underlying conceptual framework. The first one (MuSe-IBM) explicitly considers a population of individuals that are subject to random mutation during cell division. The second is a deterministic multi-compartment model (MuSe-MCM) that considers numerous genotypes of the population and where mutations are treated as a transfer of biomass between neighboring genotypes (i.e., a diffusion of characteristics in trait space). Focusing on the adaptation of optimal temperature, we show model results for different scenarios: a sudden change in environmental temperature, a seasonal variation and high frequency fluctuations. In addition, we investigate the effect of different shapes of thermal reaction norms as well as the role of alternating growth and resting phases on the adaptation process. For all cases, the differences between MuSe-IBM and MuSe-MCM are found to be negligible. Both models produce a number of well-known and plausible features. While the IBM has the advantage of including more mechanistic (i.e., probabilistic) processes, the MCM is much less computationally demanding and therefore suitable for implementation in three-dimensional ecosystem models.