Research Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, United Kingdom;
Department of Anthropology, University College London, London WC1E 6BT, United Kingdom.
Proc Natl Acad Sci U S A. 2017 Aug 1;114(31):8205-8210. doi: 10.1073/pnas.1619583114. Epub 2017 Jul 10.
Precise estimation of age is essential in evolutionary anthropology, especially to infer population age structures and understand the evolution of human life history diversity. However, in small-scale societies, such as hunter-gatherer populations, time is often not referred to in calendar years, and accurate age estimation remains a challenge. We address this issue by proposing a Bayesian approach that accounts for age uncertainty inherent to fieldwork data. We developed a Gibbs sampling Markov chain Monte Carlo algorithm that produces posterior distributions of ages for each individual, based on a ranking order of individuals from youngest to oldest and age ranges for each individual. We first validate our method on 65 Agta foragers from the Philippines with known ages, and show that our method generates age estimations that are superior to previously published regression-based approaches. We then use data on 587 Agta collected during recent fieldwork to demonstrate how multiple partial age ranks coming from multiple camps of hunter-gatherers can be integrated. Finally, we exemplify how the distributions generated by our method can be used to estimate important demographic parameters in small-scale societies: here, age-specific fertility patterns. Our flexible Bayesian approach will be especially useful to improve cross-cultural life history datasets for small-scale societies for which reliable age records are difficult to acquire.
准确估计年龄在进化人类学中至关重要，特别是对于推断人口年龄结构和理解人类生活史多样性的演化。然而，在小规模社会中，如狩猎采集者群体，时间通常不以日历年来表示，因此准确估计年龄仍然是一个挑战。我们通过提出一种贝叶斯方法来解决这个问题，该方法考虑了实地数据中固有的年龄不确定性。我们开发了一种 Gibbs 抽样马尔可夫链蒙特卡罗算法，该算法基于个体从最年轻到最年长的排序以及每个个体的年龄范围，为每个个体生成年龄的后验分布。我们首先在菲律宾的 65 名阿格塔狩猎采集者身上验证了我们的方法，他们的年龄是已知的，结果表明我们的方法生成的年龄估计值优于以前发表的基于回归的方法。然后，我们使用最近的实地调查中收集的 587 名阿格塔的数据来说明如何整合来自多个狩猎采集者营地的多个部分年龄等级。最后，我们举例说明了我们的方法生成的分布如何用于估计小规模社会中的重要人口统计参数：这里是特定年龄的生育率模式。我们灵活的贝叶斯方法将特别有助于改进对于难以获得可靠年龄记录的小规模社会的跨文化生活史数据集。
