Global patterns of phytoplankton nutrient and light colimitation inferred from an optimality-based model

• Published in: Global Biogeochemical Cycles
• Main Authors: Arteaga, Lionel, Pahlow, Markus, Oschlies, Andreas
• Format: Article in Journal/Newspaper
• Language: English
• Published: AGU (American Geophysical Union) 2014
• Subjects: Pacific; Southern Ocean
• Online Access: https://oceanrep.geomar.de/id/eprint/25427/; https://oceanrep.geomar.de/id/eprint/25427/1/gbc20173.pdf; https://doi.org/10.1002/2013GB004668

The widely used concept of constant ”Redfield” phytoplankton stoichiometry is often applied for estimating which nutrient limits phytoplankton growth in the surface ocean. Culture experiments, in contrast, show strong relations between growth conditions and cellular stoichiometry with often substantial deviations from Redfield stoichiometry. Here we investigate to what extent both views agree by analyzing remote sensing and in situ data with an optimality-based model of nondiazotrophic phytoplankton growth in order to infer seasonally varying patterns of colimitation by light, nitrogen (N), and phosphorus (P) in the global ocean. Our combined model-data analysis suggests strong N and N-P colimitation in the tropical ocean, seasonal light, and N-P colimitation in the Northern Hemisphere, and strong light limitation only during winter in the Southern Ocean. The eastern equatorial Pacific appears as the only ocean area that is essentially not limited by N, P, or light. Even though our optimality-based approach specifically accounts for flexible stoichiometry, inferred patterns of N and P limitation are to some extent consistent with those obtained from an analysis of surface inorganic nutrients with respect to the Redfield N:P ratio. Iron is not part of our analysis, implying that we cannot accurately predict N cell quotas in high-nutrient, low-chlorophyll regions. Elsewhere, we do not expect a major effect of iron on the relative distribution of N, P, and light colimitation areas. The relative importance of N, P, and light in limiting phytoplankton growth diagnosed here by combining observations and an optimal growth model provides a useful constraint for models used to predict future marine biological production under changing environmental conditions.