Nutrient and light conditions control phytoplankton division rates in the surface ocean and, it is commonly believed, dictate when and where high concentrations, or blooms, of plankton occur. Yet after a century of investigation, rates of phytoplankton biomass accumulation show no correlation with cell division rates. Consequently, factors controlling plankton blooms remain highly controversial. In this review, we endorse the view that blooms are not governed by abiotic factors controlling cell division, but rather reflect subtle ecosystem imbalances instigated by climate forcings or food-web shifts. The annual global procession of ocean plankton blooms thus represents a report on the recent history of predator-prey interactions modulated by physical processes that, almost coincidentally, also control surface nutrient inputs.

Phytoplankton photosynthesis links global ocean biology and climate-driven fluctuations in the physical environment. These interactions are largely expressed through changes in phytoplankton physiology, but physiological status has proven extremely challenging to characterize globally. Phytoplankton fluorescence does provide a rich source of physiological information long exploited in laboratory and field studies, and is now observed from space. Here we evaluate the physiological underpinnings of global variations in satellite-based phytoplankton chlorophyll fluorescence. The three dominant factors influencing fluorescence distributions are chlorophyll concentration, pigment packaging effects on light absorption, and light-dependent energy-quenching processes. After accounting for these three factors, resultant global distributions of quenching-corrected fluorescence quantum yields reveal a striking consistency with anticipated patterns of iron availability. High fluorescence quantum yields are typically found in low iron waters, while low quantum yields dominate regions where other environmental factors are most limiting to phytoplankton growth. Specific properties of photosynthetic membranes are discussed that provide a mechanistic view linking iron stress to satellite-detected fluorescence. Our results present satellite-based fluorescence as a valuable tool for evaluating nutrient stress predictions in ocean ecosystem models and give the first synoptic observational evidence that iron plays an important role in seasonal phytoplankton dynamics of the Indian Ocean. Satellite fluorescence may also provide a path for monitoring climate-phytoplankton physiology interactions and improving descriptions of phytoplankton light use efficiencies in ocean productivity models.

Iron is essential for all life, but it is particularly important to photoautotrophs because of the many iron-dependent electron transport components in photosynthetic membranes. Since the proliferation of oxygenic photosynthesis in the Archean ocean, iron has been a scarce commodity, and it is now recognized as a limiting resource for phytoplankton over broad expanses of the open ocean and even in some coastal/continental shelf waters. Iron stress does not impair photochemical or carbon fixation efficiencies, and in this respect it resembles the highly tuned photosynthetic systems of steady-state macronutrient-limited phytoplankton. However, iron stress does present unique photophysiological challenges, and phytoplankton have responded to these challenges through major architectural changes in photosynthetic membranes. These evolved responses include overexpression of photosynthetic pigments and iron-economic pathways for ATP synthesis, and they result in diagnostic fluorescence properties that allow a broad appraisal of iron stress in the field and even the detection of iron stress from space.

The Carbon, Absorption, and Fluorescence Euphotic‐resolving (CAFE) net primary production model is an adaptable framework for advancing global ocean productivity assessments by exploiting state‐of‐the‐art satellite ocean color analyses and addressing key physiological and ecological attributes of phytoplankton. Here we present the first implementation of the CAFE model that incorporates inherent optical properties derived from ocean color measurements into a mechanistic and accurate model of phytoplankton growth rates (μ) and net phytoplankton production (NPP). The CAFE model calculates NPP as the product of energy absorption (Q_PAR), and the efficiency (ϕ_μ) by which absorbed energy is converted into carbon biomass (C_Phyto), while μ is calculated as NPP normalized to C_Phyto. The CAFE model performance is evaluated alongside 21 other NPP models against a spatially robust and globally representative set of direct NPP measurements. This analysis demonstrates that the CAFE model explains the greatest amount of variance and has the lowest model bias relative to other NPP models analyzed with this data set. Global oceanic NPP from the CAFE model (52 Pg C m⁻² yr⁻¹) and mean division rates (0.34 day⁻¹) are derived from climatological satellite data (2002–2014). This manuscript discusses and validates individual CAFE model parameters (e.g., Q_PAR and ϕ_μ), provides detailed sensitivity analyses, and compares the CAFE model results and parameterization to other widely cited models.