A New Metric of Inclusive Fitness Predicts the Human Mortality Profile

Biological species have evolved characteristic patterns of age-specific mortality across their life spans. If these mortality profiles are shaped by natural selection they should reflect underlying variation in the fitness effect of mortality with age. Direct fitness models, however, do not accurately predict the mortality profiles of many species. For several species, including humans, mortality rates vary considerably before and after reproductive ages, during life-stages when no variation in direct fitness is possible. Variation in mortality rates at these ages may reflect indirect effects of natural selection acting through kin. To test this possibility we developed a new two-variable measure of inclusive fitness, which we term the extended genomic output or EGO. Using EGO, we estimate the inclusive fitness effect of mortality at different ages in a small hunter-gatherer population with a typical human mortality profile. EGO in this population predicts 90% of the variation in age-specific mortality. This result represents the first empirical measurement of inclusive fitness of a trait in any species. It shows that the pattern of human survival can largely be explained by variation in the inclusive fitness cost of mortality at different ages. More generally, our approach can be used to estimate the inclusive fitness of any trait or genotype from population data on birth dates and relatedness.

生物物种在其生命周期中演化出了特定年龄段的死亡特征模式。若这些死亡轮廓受自然选择塑造，则它们应反映死亡对生存能力影响的潜在变异。然而，直接生存能力模型并不能准确预测许多物种的死亡轮廓。对于包括人类在内的几种物种，在生殖年龄前后，死亡率有显著变化，在这些生命阶段，直接的生存能力不存在变异的可能。这些年龄段的死亡率变化可能反映了通过亲属关系间接作用于自然选择的效应。为了验证这一可能性，我们开发了一种新的双变量inclusive fitness度量方法，称之为扩展基因组输出（Extended Genomic Output，简称EGO）。利用EGO，我们估算了一个具有典型人类死亡轮廓的小型狩猎采集群体在不同年龄段的inclusive fitness对死亡率的影响。在这个群体中，EGO预测了90%的年龄段死亡率变异。这一结果代表了任何物种中任何性状inclusive fitness的首次实证测量。它表明，人类生存的模式在很大程度上可以由不同年龄段的死亡inclusive fitness成本的变异来解释。更普遍地说，我们的方法可以用于从出生日期和亲缘关系的相关数据中估算任何性状或基因型的inclusive fitness。