A mathematical model for Phaeocystis spp. dominated plankton community dynamics.

摘要

Phaeocystic spp. are unicellular algae (Prymnesiophyceae) found in polar, temperate and tropical seas. They occur in a least two different forms, solitary and colonial, and are characterized by a complex life cycle. Massive vernal blooms of Phaeocystis spp. occur in polar and temperate regions, and have a broad impact on the environment. The many factors involved in the control of the blooms, as well as the complexity of its life cycle, the intricacies of the timing and densities associated with its numerous grazers, and the role of processes of sedimentation, make it difficult to predict the development as well as the fate of a bloom.; We develop a mathematical model as a tool to better understand the dynamical behavior of a Phaeocystis-dominated planktonic ecosystem and evaluate the relative importance of different components of the system. The model consists of the two nutrient compartments (nitrogen and phosphorus), three Phaeocystis compartments (solitary cells, grazable colonies, and ungrazable colonies), and several grazers compartments (microzooplankton and copepods), and is constructed in modular form, with each module representing different relationships between compartments. In order to accurately represent size structure in the populations, we use an individual-based model approach.; Initially, we use a structure with a minimal set of components to evaluate the model's behavior compared to a collection of benchmarks and explore patterns produced by the relationships included. This rudimentary model reveals the underlying feedbacks in the system and points to the most significant parameters. We sequentially analyse the effects of the inclusion of additional components and links, bringing the sequence of scenarios closer to perceived reality. When simulations reach a stage where data or information on certain processes are not available, the model is used to investigate the impact of assumptions on community level phenomena, such as structure and dynamics, and evaluate whether they are plausible.