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Structural blueprint and ontogeny determine the adaptive value of the plastic response to competition in clonal plants: a modelling approach

Abstract : Local competitive interactions strongly influence plant community dynamics. To maintain their performance under competition, clonal plants may plastically modify their network architecture to grow in the direction of least interference. The adaptive value of this plastic avoidance response may depend, however, on traits linked with the plant's structural blueprint and ontogeny. We tested this hypothesis using virtual populations. We used an Individual Based Model to simulate competitive interactions among clones within a plant population. Clonal growth was studied under three competition intensities in plastic and non-plastic individuals. Plasticity buffered the negative impacts of competition at intermediate densities of competitors by promoting clone clumping. Success despite competition was promoted by traits linked with (1) the plant's structural blueprint (weak apical dominance and sympodial growth) and (2) ontogenetic processes, with an increasing or a decreasing dependence of the elongation process on the branch generation level or length along the competition intensity gradient respectively. The adaptive value of the plastic avoidance response depended on the same traits. This response only modulated their importance for clone success. Our results show that structural blueprint and ontogeny can be primary filters of plasticity and can have strong implications for evolutionary ecology, as they may explain why clonal plants have developed many species-specific plastic avoidance behaviours.
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Submitted on : Tuesday, May 13, 2014 - 4:32:23 PM
Last modification on : Tuesday, October 19, 2021 - 11:47:15 AM
Long-term archiving on: : Wednesday, August 13, 2014 - 10:45:52 AM

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Anne‐kristel Bittebière, M. Garbey, M. Smaoui-Feki, Bernard Clément, Cendrine Mony. Structural blueprint and ontogeny determine the adaptive value of the plastic response to competition in clonal plants: a modelling approach. Evolutionary Ecology, Springer Verlag, 2014, 28, pp.573-590. ⟨10.1007/s10682-013-9688-1⟩. ⟨halsde-00983586⟩

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