Modeling succession of key resource-harvesting traits of mixotrophic plankton

Abstract

Unicellular eukaryotes 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. Here we formulate a trait-based model for mixotrophy with 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.

Bridging the Gap between Knowing and Modeling Viruses in Marine Systems—An Upcoming Frontier

“…Yet, they don't compromise the knowledge on bacterial population control exerted by viral-induced mortality. Other recent studies, however, are questioning the paradigm where bacteria are central in the mechanisms for nutrient recycling, by pointing instead to the importance of mixotrophic organisms (Berge et al, 2016;Caron, 2016;Ward and Follows, 2016), although the question on the importance mixotrophs has previously been raised (Hall et al, 1993;Arenovski et al, 1995;Fenchel, 2008). According to this new paradigm, communities of mixotrophic protist plankton support the bulk of the base of the microbial food webs, having some fundamental differences in the flow of energy and nutrients from the bacteria-dominated microbial food web paradigm (Mitra et al, 2014).…”

“…Mixotrophy is of particular interest given that mixotrophic organisms also have a significant impact on bacterial populations. Despite being known as important player in the microbial food webs, only recently mixotrophs have received attention in modeling studies (Ward et al, 2011;Mitra et al, 2014;Berge et al, 2016;Ward and Follows, 2016). The inclusion of these "perfect beats" combining several modes of nutrition requires additional inclusion of complexity into models, as shown by Flynn and Mitra (2009); stoichiometric implication must be considered by the model, by which the C-to-nutrient ratios must be explicitly expressed for the mixotrophs and food source, otherwise the model is doomed to fail to reflect the reality of the trophic interactions, both at the mixotrophs level as on the ecosystem level.…”

“…However, this method of inclusion of a full description of mixotrophy into models has its own problems, such as an increase in complexity and computational costs. To solve the complexity problems associated with the functional group approach, Berge et al (2016) have recently proposed an alternative way to model mixotrophs using a trait-based approach to represent the full spectrum of trophic strategies.…”

“…• The classification of DOM into a larger number of categories and the identification of different processes controlling different fractions of DOM (Keller and Hood, 2013;Hasumi and Nagata, 2014); • The inclusion of P, critically important for viral replication (Wilson et al, 1996;Monier et al, 2012), but also consider multiple nutrients (organic and inorganic), as they have a significant influence on the physiologic processes of phytoplankton cells and limit their growth; • A latent period between infection and lysis, proportions of lysogenic vs. lytic virus infection under different nutrient availability (Béchette et al, 2013), and going beyond the type-I interactions between viruses and hosts and the exponential decay of viruses; • Taking upon the ERSEM model-type approach with multielement cycles, variable stoichiometry of both living entities and OM, and several functional groups; • Move toward the new paradigm in food webs where mixotrophy has a central role (Mitra et al, 2014;Berge et al, 2016).…”

Modelling the plankton groups of the deep, peri-alpine Lake Bourget

“…Following many decades of dichotomous classi cation of planktonic organisms as`autotrophs' and`heterotrophs' (Flynn et al, 2012), importance of mixotrophy in ecosystem functioning has been increasingly recognized (Mitra et al, 2014, and references therein). Mixotrophy has been addressed mainly by theoretical work so far (e.g., Thingstad et al, 1997;Flynn and Mitra, 2009;Crane and Grover, 2010;Berge et al, 2017). The recent work of Ward and Follows (2016) constitutes the rst example where mixotrophy is resolved in a global ocean model.…”