4.7 Article

Modeling silicate-nitrate-ammonium co-limitation of algal growth and the importance of bacterial remineralization based on an experimental Arctic coastal spring bloom culture study

Journal

BIOGEOSCIENCES
Volume 18, Issue 5, Pages 1719-1747

Publisher

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/bg-18-1719-2021

Keywords

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Funding

  1. UiT - The Arctic university of Norway
  2. Tromso Research Foundation [01vm/h15]

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Arctic coastal ecosystems are experiencing rapid changes due to climate warming. Spring blooms, dominated by diatoms, are important for primary production, but eventually terminate due to nutrient limitation. Bacteria play a role in extending bloom duration through ammonium regeneration. Improved modeling of nutrient co-limitations and regeneration processes is crucial for better understanding and predicting future changes in these vulnerable ecosystems.
Arctic coastal ecosystems are rapidly changing due to climate warming. This makes modeling their productivity crucially important to better understand future changes. System primary production in these systems is highest during the pronounced spring bloom, typically dominated by diatoms. Eventually the spring blooms terminate due to silicon or nitrogen limitation. Bacteria can play an important role for extending bloom duration and total CO2 fixation through ammonium regeneration. Current ecosystem models often simplify the effects of nutrient co-limitations on algal physiology and cellular ratios and simplify nutrient regeneration. These simplifications may lead to underestimations of primary production. Detailed biochemistry- and cellbased models can represent these dynamics but are difficult to tune in the environment. We performed a cultivation experiment that showed typical spring bloom dynamics, such as extended algal growth via bacterial ammonium remineralization, reduced algal growth and inhibited chlorophyll synthesis under silicate limitation, and gradually reduced nitrogen assimilation and chlorophyll synthesis under nitrogen limitation. We developed a simplified dynamic model to represent these processes. Overall, model complexity in terms of the number of parameters is comparable to the phytoplankton growth and nutrient biogeochemistry formulations in com-mon ecosystem models used in the Arctic while improving the representation of nutrient-co-limitation-related processes. Such model enhancements that now incorporate increased nutrient inputs and higher mineralization rates in a warmer climate will improve future predictions in this vulnerable system.

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