Abstract
Dynamic Green Ocean Models (DGOMs) include different sets of Plankton Functional Types (PFTs) and equations, thus different interactions and food webs. Using four DGOMs (CCSM-BEC, PISCES, NEMURO and PlankTOM5) we explore how predator–prey interactions influence food web dynamics. Using each model's equations and biomass output, interaction strengths (direct and specific) were calculated and the role of zooplankton in modeled food webs examined. In CCSM-BEC the single size-class adaptive zooplankton preys on different phytoplankton groups according to prey availability and food preferences, resulting in a strong top-down control. In PISCES the micro- and meso-zooplankton groups compete for food resources, grazing phytoplankton depending on their availability in a mixture of bottom-up and top-down control. In NEMURO macrozooplankton controls the biomass of other zooplankton PFTs and defines the structure of the food web with a strong top-down control within the zooplankton. In PlankTOM5, competition and predation between micro- and meso-zooplankton along with strong preferences for nanophytoplankton and diatoms, respectively, leads to their mutual exclusion with a mixture of bottom-up and top-down control of the plankton community composition. In each model, the grazing pressure of the zooplankton PFTs and the way it is exerted on their preys may result in the food web dynamics and structure of the model to diverge from the one that was intended when designing the model. Our approach shows that the food web dynamics, in particular the strength of the predator–prey interactions, are driven by the choice of parameters and more specifically the food preferences. Consequently, our findings stress the importance of equation and parameter choice as they define interactions between PFTs and overall food web dynamics (competition, bottom-up or top-down effects). Also, the differences in the simulated food-webs between different models highlight the gap of knowledge for zooplankton rates and predator–prey interactions. In particular, concerted effort is needed to identify the key growth and loss parameters and interactions and quantify them with targeted laboratory experiments in order to bring our understanding of zooplankton at a similar level to phytoplankton.
Highlights
Changes in marine ecosystem structure and functioning, due to anthropogenic greenhouse gas emissions and climate change, S.F
The dominant zPFTs for each model grid cell are plotted as a function of annual average sea surface temperature (SST) and total phytoplankton biomass (PBMtot, Fig. 1) to visualize the ecological niche of each zPFTs
In CCSM-BEC, the generic zooplankton group is present in the full SST range from −2 to 30 ◦C, for total phytoplankton concentrations below 2 mmol C m−3; they are present for higher phytoplankton biomass levels between 5 and 15 ◦C and above 25 ◦C
Summary
Changes in marine ecosystem structure and functioning, due to anthropogenic greenhouse gas emissions and climate change, S.F. Sailley et al / Ecological Modelling 261–262 (2013) 43–57 plays in the biogeochemical cycle of specific elements (e.g., diatoms and the silica cycle), and in processes such as remineralization (e.g., bacteria), grazing and export mediated through size class (e.g. microzooplankton versus mesozooplankton PFTs, (Le Quéré et al, 2005)). Model output (e.g. PFT biomass, distribution, export) is often sensitive to small changes in model parameters (Woods and Thomas, 1999; Fussmann and Balsius, 2005) and the modeled functional forms (Anderson, 2005). Formulations for zooplankton are important in this regard due to their effect on several processes: phytoplankton mortality due to zooplankton grazing, export of carbon through feces production, food sources for higher trophic levels (e.g., larger zooplankton, fish, marine mammals, birds)
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