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Exploring evolution of maximum growth rates in plankton

Kevin J Flynn, David Skibinski Orcid Logo

Journal of Plankton Research, Volume: 42, Issue: 5, Pages: 497 - 513

Swansea University Author: David Skibinski Orcid Logo

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DOI (Published version): 10.1093/plankt/fbaa038

Abstract

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 charac...

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Published in: Journal of Plankton Research
ISSN: 0142-7873 1464-3774
Published: Oxford University Press (OUP) 2020
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URI: https://cronfa.swan.ac.uk/Record/cronfa55147
first_indexed 2020-10-30T14:50:47Z
last_indexed 2025-03-22T05:29:14Z
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spelling 2025-03-21T13:42:29.0379315 v2 55147 2020-09-09 Exploring evolution of maximum growth rates in plankton 328d16903f98c2b03a1cc64a7530322a 0000-0003-4077-6236 David Skibinski David Skibinski true false 2020-09-09 MEDS 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). Journal Article Journal of Plankton Research 42 5 497 513 Oxford University Press (OUP) 0142-7873 1464-3774 11 9 2020 2020-09-11 10.1093/plankt/fbaa038 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Another institution paid the OA fee Natural Environment Research Council (NERC, UK) through its iMARNET programme (NE/K001345/1); EC MSCA-ITN (766327) to the project MixITiN; Institute of Life Science at Swansea University. 2025-03-21T13:42:29.0379315 2020-09-09T19:37:06.5585923 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Kevin J Flynn 1 David Skibinski 0000-0003-4077-6236 2 55147__18545__ae53936b35ee42908ed064967cbf5cd5.pdf 55147.VOR.pdf 2020-10-30T14:52:56.5417987 Output 1715744 application/pdf Version of Record true © 2020 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 (CC BY) License. true eng https://creativecommons.org/licenses/by/4.0/
title Exploring evolution of maximum growth rates in plankton
spellingShingle Exploring evolution of maximum growth rates in plankton
David Skibinski
title_short Exploring evolution of maximum growth rates in plankton
title_full Exploring evolution of maximum growth rates in plankton
title_fullStr Exploring evolution of maximum growth rates in plankton
title_full_unstemmed Exploring evolution of maximum growth rates in plankton
title_sort Exploring evolution of maximum growth rates in plankton
author_id_str_mv 328d16903f98c2b03a1cc64a7530322a
author_id_fullname_str_mv 328d16903f98c2b03a1cc64a7530322a_***_David Skibinski
author David Skibinski
author2 Kevin J Flynn
David Skibinski
format Journal article
container_title Journal of Plankton Research
container_volume 42
container_issue 5
container_start_page 497
publishDate 2020
institution Swansea University
issn 0142-7873
1464-3774
doi_str_mv 10.1093/plankt/fbaa038
publisher Oxford University Press (OUP)
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
description 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).
published_date 2020-09-11T04:49:20Z
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