Modelling approaches for capturing plankton diversity (MODIV), their societal applications and data needs

Ecosystem models need to capture biodiversity, because it is a fundamental determinant of food web dynamics and consequently of the cycling of energy and matter in ecosystems. In oceanic food webs, the plankton compartment encompasses by far most of the biomass and diversity. Therefore, capturing pl...

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Bibliographic Details
Published in:Frontiers in Marine Science
Main Authors: Acevedo-Trejos, Esteban, Cadier, Mathilde, Chakraborty, Subhendu, Chen, Bingzhang, Cheung, Shun Yan, Grigoratou, Maria, Guill, Christian, Hassenrück, Christiane, Kerimoglu, Onur, Klauschies, Toni, Lindemann, Christian, Palacz, Artur Piotr, Ryabov, Alexey, Scotti, Marco, Smith, S. Lan, Våge, Selina, Prowe, Friederike
Format: Article in Journal/Newspaper
Language:English
Published: 2022
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Online Access:https://zenodo.org/record/8131548
https://doi.org/10.3389/fmars.2022.975414
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Summary:Ecosystem models need to capture biodiversity, because it is a fundamental determinant of food web dynamics and consequently of the cycling of energy and matter in ecosystems. In oceanic food webs, the plankton compartment encompasses by far most of the biomass and diversity. Therefore, capturing plankton diversity is paramount for marine ecosystem modelling. In recent years, many models have been developed, each representing different aspects of plankton diversity, but a systematic comparison remains lacking. Here we present established modelling approaches to study plankton ecology and diversity, discussing the limitations and strengths of each approach. We emphasize their different spatial and temporal resolutions and consider the potential of these approaches as tools to address societal challenges. Finally, we make suggestions as to how better integration of field and experimental data with modelling could advance understanding of both plankton biodiversity specifically and more broadly the response of marine ecosystems to environmental change, including climate change.