Optimal allocation in annual plants with density-dependent fitness.

IF 1.3 4区 生物学 Q3 BIOLOGY
Theory in Biosciences Pub Date : 2021-06-01 Epub Date: 2021-04-13 DOI:10.1007/s12064-021-00343-9
Sergiy Koshkin, Zachary Zalles, Michael F Tobin, Nicolas Toumbacaris, Cameron Spiess
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引用次数: 1

Abstract

We study optimal two-sector (vegetative and reproductive) allocation models of annual plants in temporally variable environments that incorporate effects of density-dependent lifetime variability and juvenile mortality in a fitness function whose expected value is maximized. Only special cases of arithmetic and geometric mean maximizers have previously been considered in the literature, and we also allow a wider range of production functions with diminishing returns. The model predicts that the time of maturity is pushed to an earlier date as the correlation between individual lifetimes increases, and while optimal schedules are bang-bang at the extremes, the transition is mediated by schedules where vegetative growth is mixed with reproduction for a wide intermediate range. The mixed growth lasts longer when the production function is less concave allowing for better leveraging of plant size when generating seeds. Analytic estimates are obtained for the power means that interpolate between arithmetic and geometric mean and correspond to partially correlated lifetime distributions.

具有密度依赖适应度的一年生植物的最优配置。
我们研究了时变环境下一年生植物的最优两部门(营养和生殖)分配模型,该模型将密度依赖的寿命变异性和幼虫死亡率的影响纳入一个期望值最大化的适应度函数中。以前的文献中只考虑了算术和几何均值最大化的特殊情况,并且我们还允许更广泛的具有递减收益的生产函数。该模型预测,随着个体寿命之间相关性的增加,成熟时间被推到更早的日期,而最佳时间表在极端情况下是砰砰的,过渡是由营养生长与繁殖混合在一起的时间表介导的,中间范围很广。当生产函数凹度较小时,混合生长持续时间更长,从而在产生种子时更好地利用植株大小。在算术均值和几何均值之间插值的幂均值对应于部分相关寿命分布,得到了解析估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Theory in Biosciences
Theory in Biosciences 生物-生物学
CiteScore
2.70
自引率
9.10%
发文量
21
审稿时长
3 months
期刊介绍: Theory in Biosciences focuses on new concepts in theoretical biology. It also includes analytical and modelling approaches as well as philosophical and historical issues. Central topics are: Artificial Life; Bioinformatics with a focus on novel methods, phenomena, and interpretations; Bioinspired Modeling; Complexity, Robustness, and Resilience; Embodied Cognition; Evolutionary Biology; Evo-Devo; Game Theoretic Modeling; Genetics; History of Biology; Language Evolution; Mathematical Biology; Origin of Life; Philosophy of Biology; Population Biology; Systems Biology; Theoretical Ecology; Theoretical Molecular Biology; Theoretical Neuroscience & Cognition.
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