Data from: Quantifying individual heterogeneity and its influence on life-history trajectories: different methods for different questions and contexts

Heterogeneity among individuals influences the life-history trajectories we observe at the population level because viability selection, selective immigration and emigration processes, and ontogeny change the proportion of individuals with specific trait values with increasing age. Here, we review the two main approaches that have been proposed to account for these processes in life-history trajectories, contrasting how they quantify ontogeny and selection, and proposing ways to overcome some of their limitations. Nearly all existing approaches to model individual heterogeneity assume either a single normal distribution or a priori known groups of individuals. Ontogenetic processes, however, can vary across individuals through variation in life-history tactics. We show the usefulness of describing ontogenetic processes by modelling trajectories with a mixture model that focuses on heterogeneity in life-history tactics. Additionally, most methods examine individual heterogeneity in a single trait, ignoring potential correlations among multiple traits caused by latent common sources of individual heterogeneity. We illustrate the value of using a joint modelling approach to assess the presence of a shared latent correlation and its influence on life-history trajectories. We contrast the strengths and limitations of different methods for different research questions, and we exemplify the differences among methods using empirical data from long-term studies of ungulates.

个体异质性（Heterogeneity）会影响我们在种群水平上观测到的生活史轨迹（life-history trajectories），因为随着年龄增长，生存选择（viability selection）、选择性迁入与迁出过程以及个体发育（ontogeny）会改变携带特定性状值的个体比例。本文综述了目前已提出的两种用于在生活史轨迹中阐释这些过程的主流方法，对比了二者量化个体发育与选择的方式，并提出了克服其部分局限性的思路。当前几乎所有用于建模个体异质性的方法，要么假设单一正态分布，要么预先设定个体的分组类别。然而，个体发育过程会因生活史策略（life-history tactics）的差异而在个体间有所不同。我们通过聚焦于生活史策略异质性的混合模型（mixture model）对轨迹进行建模，以此展示描述个体发育过程的有效性。此外，大多数方法仅针对单一性状分析个体异质性，忽略了由个体异质性的潜在共同来源所引发的多性状间潜在相关性。我们通过联合建模（joint modelling）方法，演示了评估共享潜在相关性及其对生活史轨迹影响的价值。本文针对不同研究问题对比了不同方法的优势与局限，并结合有蹄类动物（ungulates）长期研究的实证数据，示例了不同方法间的差异。