Levels and limits in artificial selection of communities |
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| Authors: | Manuel Blouin Battle Karimi Jérôme Mathieu Thomas Z. Lerch |
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| Affiliation: | 1. Institute of Ecology and Environmental Sciences of Paris (UMR 7618), Université Paris‐Est Créteil Val‐de‐Marne (UPEC, UPMC, CNRS, IRD, INRA, Paris Diderot), Créteil, France;2. Laboratoire Chrono‐environnement (UMR 6249), Université de Franche‐Comté, Besan?on, France;3. Institute of Ecology and Environmental Sciences of Paris (UMR 7618), Université Pierre et Marie Curie Paris06 ‐ Sorbonne (UPEC, UPMC, CNRS, IRD, INRA, Paris Diderot), 75005, Paris, France |
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| Abstract: | Artificial selection of individuals has been determinant in the elaboration of the Darwinian theory of natural selection. Nowadays, artificial selection of ecosystems has proven its efficiency and could contribute to a theory of natural selection at several organisation levels. Here, we were not interested in identifying mechanisms of adaptation to selection, but in establishing the proof of principle that a specific structure of interaction network emerges under ecosystem artificial selection. We also investigated the limits in ecosystem artificial selection to evaluate its potential in terms of managing ecosystem function. By artificially selecting microbial communities for low CO2 emissions over 21 generations (n = 7560), we found a very high heritability of community phenotype (52%). Artificial selection was responsible for simpler interaction networks with lower interaction richness. Phenotype variance and heritability both decreased across generations, suggesting that selection was more likely limited by sampling effects than by stochastic ecosystem dynamics. |
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| Keywords: | Artificial selection co‐occurrence network ecological interaction experimental evolution heritability |
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