标题： 用分层随机微分方程研究表型进化 显示英文标题

标题： Phenotypic evolution studied by layered stochastic differential equations

摘要： 研究了属于球石藻科（隶属颗石藻门）的单细胞海洋藻类细胞大小演变的时间序列，覆盖5700万年时间跨度，该时间序列通过一个具有层次结构的线性随机微分方程系统进行研究。数据由来自世界六大洋深海沉积岩心中的化石化碳酸钙小板（颗石）尺寸测量值组成，这些沉积物的时间点分布不规则。 为了适应种群跟踪适合度最优值的生物学理论，并允许潜在可解释的时间和空间相关性，模型框架允许存在一个部分可观测的特定地点种群均值的上层、特定地点理论适合度最优值的一层以及表示环境和生态过程的底层。 尽管建模过程包含许多成分，但它符合高斯分布且在分析上易于处理。在此框架内比较了总共710个模型规格，并就模型结构、进化速度以及全球温度的影响进行了推断。 显示英文摘要

摘要： Time series of cell size evolution in unicellular marine algae (division Haptophyta; Coccolithus lineage), covering 57 million years, are studied by a system of linear stochastic differential equations of hierarchical structure. The data consists of size measurements of fossilized calcite platelets (coccoliths) that cover the living cell, found in deep-sea sediment cores from six sites in the world oceans and dated to irregular points in time. To accommodate biological theory of populations tracking their fitness optima, and to allow potentially interpretable correlations in time and space, the model framework allows for an upper layer of partially observed site-specific population means, a layer of site-specific theoretical fitness optima and a bottom layer representing environmental and ecological processes. While the modeled process has many components, it is Gaussian and analytically tractable. A total of 710 model specifications within this framework are compared and inference is drawn with respect to model structure, evolutionary speed and the effect of global temperature.