Abstract

Abstract Phytoplankton species interact through competition for light and nutrients; they also interact through grazers they hold in common. Both interactions are expected to be size-dependent: smaller phytoplankton species will be at an advantage when nutrients are scarce due to surface/volume considerations, while species that are similar in size are more likely to be consumed by grazers held in common than are species that differ greatly in size. While phytoplankton competition for nutrients and light has been extensively characterized, size-based interaction through shared grazers has not been represented systematically. The latter situation is particularly unfortunate because small changes in community structure can give rise to large changes in ecosystem dynamics and, in inverse modeling, to large changes in estimated parameter values. A simple, systematic way to represent phytoplankton interaction through shared grazers, one resistant to unintended idiosyncrasy of model construction yet capable of representing scientifically justifiable idiosyncrasy, would aid greatly in the modeling process. Here I develop a model structure that allows systematic representation of plankton interaction. In this model, the zooplankton community is represented as a continuous size spectrum, while phytoplankton species can be represented individually. The mechanistic basis of the model is a shift in the zooplankton community from carnivory to omnivory to herbivory as phytoplankton density increases. I discuss two limiting approximations in some detail, and fit both to data from the IronEx II experiment. The first limiting case represents a community with no grazer-based interaction among phytoplankton species; this approximation illuminates the general structure of the model. In particular, the zooplankton spectrum can be viewed as the analog of a control rod in a nuclear reactor, which prevents (or fails to prevent) an exponential bloom of phytoplankton. A second, more complex limiting case allows more general interaction of phytoplankton species along a size axis. This latter case would be suitable for describing competition among species with distinct biogeochemical roles, or between species that cause harmful algal blooms and those that do not. The model structure as a whole is therefore simple enough to guide thinking, yet detailed enough to allow quantitative prediction.

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