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When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems.

Sauterey B, Ward BA, Follows MJ, Bowler C, Claessen D - J. Plankton Res. (2014)

Bottom Line: Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle.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.

View Article: PubMed Central - PubMed

Affiliation: Environmental and Evolutionary Genomics Section , Institut De Biologie De L'Ecole Normale Supérieure (IBENS), CNRS UMR 8197, INSERM U1024, Ecole Normale Supérieure , 46 RUE D'ULM, 75005 Paris , France ; Environmental Research and Teaching Institute (CERES-ERTI) , Ecole Normale Supérieure , 24 RUE Lhomond, 75005 Paris , France.

ABSTRACT

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.

No MeSH data available.


(a) Average Canberra distance between the mean distribution and the individual simulations, for each attractor (light for t = 100 years, dark for the t = 350 years), and for each seeding condition (8, 20, 40 or 80 initial phytoplankton species). (b) The mean Shannon index for the same groups.
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FBU078F6: (a) Average Canberra distance between the mean distribution and the individual simulations, for each attractor (light for t = 100 years, dark for the t = 350 years), and for each seeding condition (8, 20, 40 or 80 initial phytoplankton species). (b) The mean Shannon index for the same groups.

Mentions: Looking at the whole set of runs (Fig. 5a), we can first note that the communities emerging from the species sorting during the first phase are highly diverse: the example (Fig. 4a, t = 100) is not representative of what we observe in the other runs (Fig. 5a). First, in terms of cell size composition of the community, a clear size pattern cannot be identified in Fig. 5a for low seeding resolution (8 and 20 phytoplankton species), and the corresponding intra-group mean square distances are particularly high (Fig. 6a). However, at higher seeding resolution (40 and 80 species), the average MSDs are lower (Fig. 6a) and the selected cell sizes appear to be centred around four values (Fig. 5a), corresponding to the emergence of four dominant species.Fig. 5.


When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems.

Sauterey B, Ward BA, Follows MJ, Bowler C, Claessen D - J. Plankton Res. (2014)

(a) Average Canberra distance between the mean distribution and the individual simulations, for each attractor (light for t = 100 years, dark for the t = 350 years), and for each seeding condition (8, 20, 40 or 80 initial phytoplankton species). (b) The mean Shannon index for the same groups.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4378374&req=5

FBU078F6: (a) Average Canberra distance between the mean distribution and the individual simulations, for each attractor (light for t = 100 years, dark for the t = 350 years), and for each seeding condition (8, 20, 40 or 80 initial phytoplankton species). (b) The mean Shannon index for the same groups.
Mentions: Looking at the whole set of runs (Fig. 5a), we can first note that the communities emerging from the species sorting during the first phase are highly diverse: the example (Fig. 4a, t = 100) is not representative of what we observe in the other runs (Fig. 5a). First, in terms of cell size composition of the community, a clear size pattern cannot be identified in Fig. 5a for low seeding resolution (8 and 20 phytoplankton species), and the corresponding intra-group mean square distances are particularly high (Fig. 6a). However, at higher seeding resolution (40 and 80 species), the average MSDs are lower (Fig. 6a) and the selected cell sizes appear to be centred around four values (Fig. 5a), corresponding to the emergence of four dominant species.Fig. 5.

Bottom Line: Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle.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.

View Article: PubMed Central - PubMed

Affiliation: Environmental and Evolutionary Genomics Section , Institut De Biologie De L'Ecole Normale Supérieure (IBENS), CNRS UMR 8197, INSERM U1024, Ecole Normale Supérieure , 46 RUE D'ULM, 75005 Paris , France ; Environmental Research and Teaching Institute (CERES-ERTI) , Ecole Normale Supérieure , 24 RUE Lhomond, 75005 Paris , France.

ABSTRACT

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.

No MeSH data available.