New study from the Centre for Ocean Life shows the succession of three key resource-harvesting traits: photosynthesis, phagotrophy and inorganic nutrient uptake predicting the trophic strategy of plankton throughout the seasonal succession.
Unicellular plankton make up the base of the ocean food web and exist as a continuum in trophic strategy from pure heterotrophy (phagotrophic zooplankton) to pure photoautotrophy (‘phytoplankton’), with a dominance of mixotrophic organisms combining both strategies. The traditional plankton models follow functional-group type approach, where organisms are pre-described as ‘phytoplankton’ and ‘zooplankton’. Representing mixotrophy in such models leads to increased complexity and computational costs. However, by disposing of functional groups and species altogether, and focusing on the distribution of continuous trait values, trait-based approaches have the potential to represent the full spectrum of trophic strategies and partly overcome this complexity problem. In this paper, we tried to understand which environmental conditions favor specific key resource-harvesting traits or trophic strategy of mixotrophic plankton.
Our trait-based model for mixotrophy consists of three key resource-harvesting traits: photosynthesis, phagotrophy and inorganic nutrient uptake, which predicts the trophic strategy of species throughout the seasonal cycle. Assuming that simple carbohydrates from photosynthesis fuel respiration, and feeding primarily provides building blocks for growth, the model reproduces the observed light-dependent ingestion rates and species-specific growth rates with and without prey from the laboratory. The combination of traits yielding the highest growth rate suggests high investments in photosynthesis, and inorganic nutrient uptake in the spring and increased phagotrophy during the summer, reflecting general seasonal succession patterns of temperate waters. Our trait-based model presents a simple and general approach for the inclusion of mixotrophy, succession and evolution in ecosystem models.
Read the paper online here.