Description: The major part of dissolved iron (DFe) in seawater is bound to organic matter, which prevents iron from adsorptive removal by sinking particles and essentially regulates the residence time of DFe and its availability for marine biota. Characteristics of iron‐binding ligands highly depend on their biological origin and physico‐chemical properties of seawater which may intensely alter under ongoing climate change. To understand environmental controls on the iron binding, we applied a function of pH and dissolved organic carbon (DOC) to describe changes in the binding strength of organic ligands in a global biogeochemical model (REcoM). This function was derived based on calculations using a thermodynamic chemical speciation model NICA. This parameterization considerably improved the modeled DFe distribution, particularly in the surface Pacific and the global mesopelagic and deep waters, compared to our previous model simulations with a constant ligand or one prognostic ligand. This indicates that the organic binding of iron is apparently controlled by seawater pH in addition to its link to organic matter. We tested further the response of this control to environmental changes in a simulation with future pH of a high emission scenario. The response of the binding potential shows a complex pattern in different regions and is regulated by factors that have opposite effects on the binding potential. The relative contributions of these factors can change over time by a continual change of environmental conditions. A dynamic feedback system therefore needs to be considered to predict the marine iron cycle under ongoing climate change.

Description: Among mechanisms accounting for atmospheric pCO2 drawdown during glacial periods, processes operating in the North Atlantic (NA) and Southern Ocean (SO) have been proposed to be critical. Their individual and synergic effects during a course of glaciation, however, remain enigmatic. We conducted simulations to examine these effects at idealized glacial stages. Under early-glacial-like conditions, cooling in the SO can trigger an initial pCO2 drawdown while the associated sea ice expansion has little impact on air-sea gas exchange. Under later glacial-like conditions, further cooling in the NA enhances ocean carbon uptake due to a stronger solubility pump, and the SO-induced stronger deep stratification prevents carbon exchange between the deep and upper ocean. Meanwhile, strengthened dust deposition increases the SO contribution to the global biological pump, and CO2 outgassing is suppressed by fully extended sea ice cover. More carbon is then stored in the deep Pacific, acting as a passive reservoir.

Description: Phytoplankton growth is controlled by multiple environmental drivers, which are all modified by climate change. While numerous experimental studies identify interactive effects between drivers, large-scale ocean biogeochemistry models mostly account for growth responses to each driver separately and leave the results of these experimental multiple-driver studies largely unused. Here, we amend phytoplankton growth functions in a biogeochemical model by dual-driver interactions (CO2 and temperature, CO2 and light), based on data of a published meta-analysis on multiple-driver laboratory experiments. The effect of this parametrization on phytoplankton biomass and community composition is tested using present-day and future high-emission (SSP5-8.5) climate forcing. While the projected decrease in future total global phytoplankton biomass in simulations with driver interactions is similar to that in control simulations without driver interactions (5%-6%), interactive driver effects are group-specific. Globally, diatom biomass decreases more with interactive effects compared with the control simulation (-8.1% with interactions vs. no change without interactions). Small-phytoplankton biomass, by contrast, decreases less with on-going climate change when the model accounts for driver interactions (-5.0% vs. -9.0%). The response of global coccolithophore biomass to future climate conditions is even reversed when interactions are considered (+33.2% instead of -10.8%). Regionally, the largest difference in the future phytoplankton community composition between the simulations with and without driver interactions is detected in the Southern Ocean, where diatom biomass decreases (-7.5%) instead of increases (+14.5%), raising the share of small phytoplankton and coccolithophores of total phytoplankton biomass. Hence, interactive effects impact the phytoplankton community structure and related biogeochemical fluxes in a future ocean. Our approach is a first step to integrate the mechanistic understanding of interacting driver effects on phytoplankton growth gained by numerous laboratory experiments into a global ocean biogeochemistry model, aiming toward more realistic future projections of phytoplankton biomass and community composition.