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Artificial selection of simulated microbial ecosystems
Recent work with microbial communities has demonstrated an adaptive response to artificial selection at the level of the ecosystem. The reasons for this response and the level at which adaptation occurs are unclear: does selection act implicitly on traits of individual species, or are higher-level t...
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Published in: | Proceedings of the National Academy of Sciences - PNAS 2007-05, Vol.104 (21), p.8918-8923 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Recent work with microbial communities has demonstrated an adaptive response to artificial selection at the level of the ecosystem. The reasons for this response and the level at which adaptation occurs are unclear: does selection act implicitly on traits of individual species, or are higher-level traits genuinely being selected? If the ecosystem response is just the additive combination of the responses of the constituent species, then the ecosystem response could be predicted a priori, and the ecosystem-level selection process is superfluous. However, if the ecosystem response results from ecological interactions among species, then selection at a higher level is necessary. Here we perform artificial ecosystem selection experiments on an individual-based evolutionary simulation model of microbial ecology and observe a similar response to that seen with real ecosystems. We demonstrate that a significant fraction of artificially selected ecosystem responses cannot be accounted for by implicit lower-level selection of a single type of organism within the community, and that interactions among different types of organism contribute significantly to the response in the majority of cases. However, when the ecological problem posed by the artificial ecosystem selection process can be easily solved by a single dominant species, it often is. |
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ISSN: | 0027-8424 1091-6490 |
DOI: | 10.1073/pnas.0610038104 |