  A quantitative understanding of the dynamics of bee colonies is important to
support global efforts to improve bee health and enhance pollination services.
Traditional approaches focus either on theoretical models or data-centred
statistical analyses. Here we argue that the combination of these two
approaches is essential to obtain interpretable information on the state of bee
colonies and show how this can be achieved in the case of time series of
intra-day weight variation. We model how the foraging and food processing
activities of bees affect global hive weight through a set of ordinary
differential equations and show how to estimate reliable ranges for the ten
parameters of this model from measurements on a single day. Our analysis of 10
hives at different times shows that crucial indicators of the health of honey
bee colonies are estimated robustly and fall in ranges compatible with
previously reported results. The indicators include the amount of food
collected (foraging success) and the number of active foragers, which may be
used to develop early warning indicators of colony failure.
