When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems
|Author(s)||Sauterey Boris1, 2, Ward Ben A.1, 3, Follows Michael J.4, Bowler Chris1, Claessen David1, 2|
|Affiliation(s)||1 : Ecole Normale Super, INSERM, Environm & Evolutionary Genom Sect, IBENS,CNRS,U1024,UMR 8197, F-75005 Paris, France.
2 : Ecole Normale Super, Environm Res & Teaching Inst, CERES, ERTI, F-75005 Paris, France.
3 : Inst Univ Europeen Mer, Lab Sci Environm Marin, Plouzane, France.
4 : MIT, Dept Earth Atmospher & Planetary Sci, Cambridge, MA USA.
|Source||Journal Of Plankton Research (0142-7873) (Oxford Univ Press), 2015-01 , Vol. 37 , N. 1 , P. 28-47|
|WOS© Times Cited||14|
|Keyword(s)||phytoplankton, competition, trait-based adaptive strategies, adaptive dynamics, eco-evolutionary dynamics, trade-off, community, global circulation model|
The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that "Everything is everywhere, but the environment selects", we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean.