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Exploring evolution of maximum growth rates in plankton.
Flynn, Kevin J; Skibinski, David O F.
Afiliación
  • Flynn KJ; Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth PL1 3DH, UK.
  • Skibinski DOF; Swansea University Medical School, Swansea University, Swansea, SA2 8PP, UK.
J Plankton Res ; 42(5): 497-513, 2020.
Article en En | MEDLINE | ID: mdl-32939154
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, production may decline as evolution reshapes growth and trophic dynamics. 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).
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Plankton Res Año: 2020 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Plankton Res Año: 2020 Tipo del documento: Article