This research explores nutrient limitations in oceanic primary production. While traditional experiments identify the immediate limiting nutrient at specific locations, this study aims to identify the ultimate limiting nutrient (ULN), which governs long-term productivity. A mathematical model incorporating nitrogen, phosphorus, and iron nutrient cycles is used. The model's results are compared with ocean observational data to assess its effectiveness in investigating the ULN.

The Coupled Model Intercomparison Project (CMIP) is an international consortium of climate modeling groups that produce coordinated experiments in order to evaluate human influence on the climate and test knowledge of Earth systems. This paper describes the data requested for Earth systems research in CMIP7. We detail the request for model output of the carbon cycle, the flows of energy among the atmosphere, land and the oceans, and interactions between these and the global climate.

Marine ecosystem models (MEMs) are valuable for assessing the threats of global warming to biodiversity and ecosystem functioning, but their predictions vary widely. We argue that MEMs should consider evolutionary processes and undergo independent validation. Here, we present a novel framework for MEM development using validation data from sediment archives, which map long-term environmental and evolutionary change. Our approach is a crucial step towards improving the predictive power of MEMs.

As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.

Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.