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.

我们研究了时间可变环境中一年生植物的最佳两部门（营养和生殖）分配模型，该模型在预期值最大化的适应度函数中结合了密度依赖性寿命变异性和幼年死亡率的影响。之前的文献中只考虑了算术和几何平均最大化器的特殊情况，我们还允许更广泛的生产函数的收益递减。该模型预测，随着个体生命周期之间的相关性增加，成熟时间被推迟到更早的日期，虽然最佳时间表在极端情况下是爆炸性的，但过渡是由营养生长与繁殖混合的时间表介导的。中间范围。当生产函数的凹度较小时，混合生长会持续更长时间，从而在生成种子时可以更好地利用植物大小。获得了在算术平均值和几何平均值之间插值并对应于部分相关的寿命分布的幂平均值的分析估计。