Phytoplankton thermal trait parameterization alters community structure and biogeochemical processes in a modeled ocean

Abstract: Phytoplankton exhibit diverse physiological responses to temperature which influence their fitness in the environment and consequently alter their community structure. Here, we explored the sensitivity of phytoplankton community structure to thermal response parameterization in a modelled marine phytoplankton community. Using published empirical data, we evaluated the maximum thermal growth rates (μ_max) and temperature coefficients (Q₁₀; the rate at which growth scales with temperature) of six key Phytoplankton Functional Types (PFTs): coccolithophores, cyanobacteria, diatoms, diazotrophs, dinoflagellates, and green algae. Following three well-documented methods, PFTs were either assumed to have (1) the same μ_max and the same Q₁₀ (as in to Eppley, 1972), (2) a unique μ_max but the same Q₁₀ (similar to Kremer et al., 2017), or (3) a unique μ_max and a unique Q₁₀ (following Anderson et al., 2021). These trait values were then implemented within the Massachusetts Institute of Technology biogeochemistry and ecosystem model (called Darwin) for each PFT under a control and climate change scenario.

Our results suggest that applying a μ_max and Q₁₀ universally across PFTs (as in Eppley, 1972) leads to unrealistic phytoplankton communities, which lack diatoms globally. Additionally, we find that accounting for differences in the Q₁₀ between PFTs can significantly impact each PFT's competitive ability, especially at high latitudes, leading to altered modeled phytoplankton community structures in our control and climate change simulations. This then impacts estimates of biogeochemical processes, with, for example, estimates of export production varying by ~10% in the Southern Ocean depending on the parameterization.

Our results indicate that the diversity of thermal response traits in phytoplankton not only shape community composition in the historical and future, warmer ocean, but that these traits have significant feedbacks on global biogeochemical cycles.