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Latitudinal Variation in Plankton Traits and Ecosystem Function
Author(s) -
Chakraborty Subhendu,
Cadier Mathilde,
Visser André W.,
Bruggeman Jorn,
Andersen Ken H.
Publication year - 2020
Publication title -
global biogeochemical cycles
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.512
H-Index - 187
eISSN - 1944-9224
pISSN - 0886-6236
DOI - 10.1029/2020gb006564
Subject(s) - trophic level , autotroph , plankton , mixotroph , ecosystem , ecology , environmental science , phototroph , range (aeronautics) , biology , biomass (ecology) , abiotic component , heterotroph , photosynthesis , botany , genetics , materials science , bacteria , composite material
Planktonic ecosystems are usually modeled in terms of autotrophic and heterotrophic compartments. However, the trophic strategy of unicellular organisms can take a range of mixotrophic strategies with both autotrophic and heterotrophic contributions. The dominant emerging strategy found in nature depends on the environment (both biotic and abiotic aspects) and the cell size and influences key ecosystem functions like trophic transfer and carbon export. Ecosystem models that faithfully represent this diversity of trophic strategies are lacking. Here we develop a trait‐based model of unicellular plankton with cell size as the master trait and three other traits that determine trophic strategies: investments in photosynthesis, nutrient uptake, and phagotrophy. This unicellular model spans the entire auto‐ mixo‐ hererotrophic strategy continuum and the entire size range of unicellular organisms. The model reproduces observed latitudinal patterns in biomass, primary productivity, vertical carbon export, and energy transfer efficiency; all increase with increasing latitude. The size range of mixotrophic cells is independent of the season at low latitudes. At high latitudes, the dominance of pure phototrophs during early spring restricts mixotrophic behavior to a narrower range of cell sizes and with the occurrence of relatively smaller mixotrophs during summer. The model's ability to adapt to different environmental conditions, combined with its simple conceptual structure and low number of parameters and state variables (10), makes it ideally suited for global simulation studies under changing environmental conditions.