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Stabilizing selection on individual pattern elements of aposematic signals.

ABSTRACT: Warning signal variation is ubiquitous but paradoxical: low variability should aid recognition and learning by predators. However, spatial variability in the direction and strength of selection for individual elements of the warning signal may allow phenotypic variation for some components, but not others. Variation in selection may occur if predators only learn particular colour pattern components rather than the entire signal. Here, we used a nudibranch mollusc, Goniobranchus splendidus, which exhibits a conspicuous red spot/white body/yellow rim colour pattern, to test this hypothesis. We first demonstrated that secondary metabolites stored within the nudibranch were unpalatable to a marine organism. Using pattern analysis, we demonstrated that the yellow rim remained invariable within and between populations; however, red spots varied significantly in both colour and pattern. In behavioural experiments, a potential fish predator, Rhinecanthus aculeatus, used the presence of the yellow rims to recognize and avoid warning signals. Yellow rims remained stable in the presence of high genetic divergence among populations. We therefore suggest that how predators learn warning signals may cause stabilizing selection on individual colour pattern elements, and will thus have important implications on the evolution of warning signals.

SUBMITTER: Winters AE

PROVIDER: S-EPMC5577479 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Stabilizing selection on individual pattern elements of aposematic signals.

Winters Anne E AE Green Naomi F NF Wilson Nerida G NG How Martin J MJ Garson Mary J MJ Marshall N Justin NJ Cheney Karen L KL

Proceedings. Biological sciences 20170801 1861

Warning signal variation is ubiquitous but paradoxical: low variability should aid recognition and learning by predators. However, spatial variability in the direction and strength of selection for individual elements of the warning signal may allow phenotypic variation for some components, but not others. Variation in selection may occur if predators only learn particular colour pattern components rather than the entire signal. Here, we used a nudibranch mollusc, <i>Goniobranchus splendidus</i> ...[more]

PMID: 28835556

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Project description:The development of multicellular organisms involves cells to decide their fate upon the action of biochemical signals. This decision is often spatiotemporally coordinated such that a spatial pattern arises. The dynamics that drive pattern formation usually involve genetic nonlinear interactions and positive feedback loops. These complex dynamics may enable multiple stable patterns for the same conditions. Under these circumstances, pattern formation in a developing tissue involves a selection process: why is a certain pattern formed and not another stable one? Herein we computationally address this issue in the context of the Notch signaling pathway. We characterize a dynamical mechanism for developmental selection of a specific pattern through spatiotemporal changes of the control parameters of the dynamics, in contrast to commonly studied situations in which initial conditions and noise determine which pattern is selected among multiple stable ones. This mechanism can be understood as a path along the parameter space driven by a sequence of biochemical signals. We characterize the selection process for three different scenarios of this dynamical mechanism that can take place during development: the signal either 1) acts in all the cells at the same time, 2) acts only within a cluster of cells, or 3) propagates along the tissue. We found that key elements for pattern selection are the destabilization of the initial pattern, the subsequent exploration of other patterns determined by the spatiotemporal symmetry of the parameter changes, and the speeds of the path compared to the timescales of the pattern formation process itself. Each scenario enables the selection of different types of patterns and creates these elements in distinct ways, resulting in different features. Our approach extends the concept of selection involved in cellular decision-making, usually applied to cell-autonomous decisions, to systems that collectively make decisions through cell-to-cell interactions.

Dataset Information

Stabilizing selection on individual pattern elements of aposematic signals.

Publications

Stabilizing selection on individual pattern elements of aposematic signals.

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