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The Mass-Longevity Triangle: Pareto Optimality and the Geometry of Life-History Trait Space

机译:质量长寿三角形:帕累托最优和生命历史特征空间的几何

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摘要

When organisms need to perform multiple tasks they face a fundamental tradeoff: no phenotype can be optimal at all tasks. This situation was recently analyzed using Pareto optimality, showing that tradeoffs between tasks lead to phenotypes distributed on low dimensional polygons in trait space. The vertices of these polygons are archetypes—phenotypes optimal at a single task. This theory was applied to examples from animal morphology and gene expression. Here we ask whether Pareto optimality theory can apply to life history traits, which include longevity, fecundity and mass. To comprehensively explore the geometry of life history trait space, we analyze a dataset of life history traits of 2105 endothermic species. We find that, to a first approximation, life history traits fall on a triangle in log-mass log-longevity space. The vertices of the triangle suggest three archetypal strategies, exemplified by bats, shrews and whales, with specialists near the vertices and generalists in the middle of the triangle. To a second approximation, the data lies in a tetrahedron, whose extra vertex above the mass-longevity triangle suggests a fourth strategy related to carnivory. Each animal species can thus be placed in a coordinate system according to its distance from the archetypes, which may be useful for genome-scale comparative studies of mammalian aging and other biological aspects. We further demonstrate that Pareto optimality can explain a range of previous studies which found animal and plant phenotypes which lie in triangles in trait space. This study demonstrates the applicability of multi-objective optimization principles to understand life history traits and to infer archetypal strategies that suggest why some mammalian species live much longer than others of similar mass.
机译:当有机体需要执行多个任务时,它们将面临基本的权衡:没有任何表型可以在所有任务中都达到最佳。最近使用帕累托最优对这种情况进行了分析,结果表明任务之间的折衷导致了特征空间中低维多边形上分布的表型。这些多边形的顶点是原型,即在单个任务上最佳的表型。该理论被应用于动物形态和基因表达的例子。在这里,我们询问帕累托最优理论是否可以适用于寿命历史特征,包括寿命,繁殖力和质量。为了全面探讨生活史特征空间的几何形状,我们分析了2105个吸热物种的生活史特征数据集。我们发现,作为一阶近似,生活史特征落在对数质量对数寿命空间中的一个三角形上。三角形的顶点表示三种原型策略,例如蝙蝠,sh和鲸鱼,顶点附近有专家,三角形的中间有通才。对于第二个近似值,数据位于四面体中,其四面体在质量寿命三角形上方的额外顶点表明了与食肉动物有关的第四种策略。因此,可以根据每种动物与原型的距离将它们放置在坐标系中,这可能对哺乳动物衰老和其他生物学方面的基因组规模比较研究有用。我们进一步证明帕累托最优可以解释一系列先前的研究,这些研究发现在特征空间的三角形中存在动物和植物的表型。这项研究证明了多目标优化原则在理解生命史特征和推断原型策略方面的适用性,这些策略说明了为什么某些哺乳动物比其他同类动物寿命更长的原因。

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