Comment on "Evolutionary Trade-Offs, Pareto Optimality, and the Geometry of Phenotype Space"

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Response to comment on "Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space".

Edelaar raises concerns about the way we tested our theory. Our mathematical theorem predicts that despite the high dimensionality of trait space, trade-offs between tasks leads to phenotypes in low-dimensional regions in trait space, such as lines and triangles. We address Edelaar's questions with statistical tests that eliminate pseudoreplication concerns, finding that our predictions remain ...

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Comment on "Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space".

Shoval et al. (Reports, 1 June 2012, p. 1157) showed how configurations of phenotypes may identify tasks that trade off with each other, using randomizations assuming independence of data points. I argue that this assumption may not be correct for most and possibly all examples and led to pseudoreplication and inflated significance levels. Improved statistical testing is necessary to assess how...

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Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space.

Biological systems that perform multiple tasks face a fundamental trade-off: A given phenotype cannot be optimal at all tasks. Here we ask how trade-offs affect the range of phenotypes found in nature. Using the Pareto front concept from economics and engineering, we find that best-trade-off phenotypes are weighted averages of archetypes--phenotypes specialized for single tasks. For two tasks, ...

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The geometry of the Pareto front in biological phenotype space

When organisms perform a single task, selection leads to phenotypes that maximize performance at that task. When organisms need to perform multiple tasks, a trade-off arises because no phenotype can optimize all tasks. Recent work addressed this question, and assumed that the performance at each task decays with distance in trait space from the best phenotype at that task. Under this assumption...

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ژورنال

عنوان ژورنال: Science

سال: 2013

ISSN: 0036-8075,1095-9203

DOI: 10.1126/science.1228281