Computer modeling of dynamically changing distributions of random variables

Physiological characteristics of populations are often described with two t ypes of data and with analyses that coexist in mutual independence; One typ e targets global measures like mean and standard deviation, prevalence, inc idence, or distributions of weights, sizes, of some physiological markers, while the other type describes physiological or metabolic processes in indi viduals, such as growth or the accumulation of a metabolite. The paper desc ribes a methodological framework for bridging the gap between the two aspec ts. It shows how a dynamic model that characterizes the accumulation proces s in individuals and is represented by a set of ordinary differential equat ions can be reformulated as a transformation function that changes the stat istical distribution of the physiological marker over time. The method and its limitations are illustrated with data describing growth and size distri butions of loblolly pine (Pinus taeda). (C) 2000 Elsevier Science Ltd. All rights reserved.