Seasonality of modelled planktonic food web structure in the Strait of Georgia, Canada.

When attempting to model an ecosystem, compromises must be made to retain the essence of the system and its functioning. Here, we explore the implications of these aggregations on a modelled ecosystem by using Ecopath to model the plankton food web in the Strait of Georgia (SoG), a temperate coastal system on the west coast of Canada, in three seasons. The food web is defined by fifteen functional groups representing autotrophic phytoplankton, the microbial loop, and mesozooplankton in three seasons, differentiated by node biomass, productivity, and diet. Variations in the community composition lead to shifts in trophic behaviour and food-web structure seasonally. In spring, autotrophic phytoplankton (i.e. diatoms) are the main source of carbon for the system. In summer and winter, the microbial loop becomes more important due to limited primary production. These structural changes within the plankton food web throughout a year have implications for higher trophic levels, including the seasonal availability and quality of food for planktivorous fish. Finally, we compared this detailed seasonal approach to plankton modelling with a more common simplified approach and examined its impacts on the entire ecosystem. The microbial loop is often excluded from coastal ecosystem models but is an important component, influencing trophic positions and transfer efficiencies. However, aggregating plankton groups appears to be an adequate approach to plankton modelling in the SoG, but modelling decisions should be driven by the research question. • Ecosystem models often highly simplify plankton at the base of the food web. • Plankton community and interactions vary seasonally in the Strait of Georgia. • Food web models representing seasonal trophic structure with plankton are built. • Models provide insights into ecosystem functioning and food availability for fish. • Simplistic models may be appropriate in some cases. [ABSTRACT FROM AUTHOR]