Exploring evolution of maximum growth rates in plankton

Flynn, KJ; Skibinski, DOF; Koski, M. 2020 Exploring evolution of maximum growth rates in plankton. Journal of Plankton Research, 42 (5). 497-513. https://doi.org/10.1093/plankt/fbaa038

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Official URL: http://dx.doi.org/10.1093/plankt/fbaa038

Abstract/Summary

Evolution has direct and indirect consequences on species–species interactions and the environment. However, Earth systems models describing planktonic activity invariably fail to explicitly consider organism evolution. Here we simulate the evolution of the single most important physiological characteristic of any organism as described in models— its maximum growth rate (μm). Using a low-computational-cost approach, we incorporate the evolution of μm for each of the plankton components in a simple Nutrient-Phytoplankton-Zooplankton -style model such that the fitness advantages and disadvantages in possessing a high μm evolve to become balanced. The model allows an exploration of parameter ranges leading to stresses, which drive the evolution of μm. In applications of the method we show that simulations of climate change give very different projections when the evolution of μm is considered. Thus, productionmaydeclineasevolutionreshapesgrowthandtrophicdynamics.Additionally,predictions of extinction of species may be overstated in simulations lacking evolution as the ability to evolve under changing environmental conditions supports evolutionary rescue. The model explains why organisms evolved for mature ecosystems (e.g. temperate summer, reliant on local nutrient recycling or mixotrophy), express lower maximum growth rates than do organisms evolved for immature ecosystems (e.g. temperate spring, high resource availability).

Item Type: Publication - Article
Additional Keywords: NPZ model; plankton evolution; extinction; climate change
Divisions: Plymouth Marine Laboratory > National Capability categories > Modelling
Plymouth Marine Laboratory > Science Areas > Marine Ecology and Biodiversity
Plymouth Marine Laboratory > Science Areas > Marine Ecosystem Models and Predictions
Depositing User: S Hawkins
Date made live: 17 Sep 2020 11:28
Last Modified: 17 Sep 2020 11:28
URI: http://plymsea.ac.uk/id/eprint/9047

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