Data from: Separating intrinsic and environmental contributions to growth and their population consequences

Among-individual heterogeneity in growth is a commonly observed phenomenon that has clear consequences for population and community dynamics yet has proved difficult to quantify in practice. In particular, observed among-individual variation in growth can be difficult to link to any given mechanism. Here, we develop a Bayesian state-space framework for modeling growth that bridges the complexity of bioenergetic models and the statistical simplicity of phenomenological growth models. The model allows for intrinsic individual variation in traits, a shared environment, process stochasticity, and measurement error. We apply the model to two populations of steelhead trout (Oncorhynchus mykiss) grown under common but temporally varying food conditions. Models allowing for individual variation match available data better than models that assume a single shared trait for all individuals. Estimated individual variation translated into a roughly twofold range in realized growth rates within populations. Comparisons between populations showed strong differences in trait means, trait variability, and responses to a shared environment. Together, individual- and population-level variation have substantial implications for variation in size and growth rates among and within populations. State-dependent life-history models predict that this variation can lead to differences in individual life-history expression, lifetime reproductive output, and population life-history diversity.

个体间生长异质性是一种被广泛观测到的现象，其对种群与群落动态具有明确影响，但在实际中却难以量化。具体而言，观测到的个体间生长差异往往难以与特定作用机制建立关联。为此，我们构建了用于生长建模的贝叶斯状态空间框架（Bayesian state-space framework），该框架兼顾了生物能量模型（bioenergetic models）的复杂性与现象学生长模型（phenomenological growth models）的统计简洁性。该模型允许存在性状的固有个体差异、共享环境效应、过程随机性与测量误差。我们将该模型应用于两个钢头鳟（Oncorhynchus mykiss）种群，这些种群在相同但随时间变化的食物条件下饲养。允许存在个体差异的模型，相较于假设所有个体共享单一性状的模型，更符合现有观测数据。估算得到的个体差异使得种群内实际生长速率存在约两倍的差异范围。种群间的对比显示，性状均值、性状变异程度以及对共享环境的响应均存在显著差异。综上，个体与种群水平的变异对种群间及种群内部的体型与生长速率差异具有重要影响。状态依赖生活史模型（state-dependent life-history models）预测，这类变异会导致个体生活史表达、终生繁殖产出以及种群生活史多样性出现差异。