Speaker
Description
Many ecological studies employ general models that can feature an arbitrary number of populations. A common requirement imposed on such models is what we call clone consistency: If the individuals from two populations are indistinguishable, joining these populations into one shall not affect the outcome of the model. Otherwise a model produces different outcomes for the same scenario. Using functional analysis, we comprehensively characterize all clone-consistent models: We prove that they are necessarily composed from basic building blocks, namely linear combinations of parameters and abundances. These strong constraints enable a straightforward validation of model consistency or reveal implicit assumptions required to achieve it. Moreover, our insights facilitate building new clone-consistent models, which we illustrate for a data-driven model of microbial communities.
