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Published April 10, 2024 | Version v1
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Simulating Plankton - getting it right in the era of Digital Twins of The Ocean; data to support plankton model construction.

Creators

  • 1. ROR icon Plymouth Marine Laboratory
  • 2. Eugene, Oregon, USA
  • 3. Horn Point Laboratory, University of Maryland, Cambridge, Maryland, USA
  • 4. Alfred-Wegener-Institute – Helmholtz Centre for Polar and Marine Research, 27498 Helgoland, Germany
  • 5. Institut de Biologie de l'Ecole Normale Supérieure (IBENS), CNRS, 75005 Paris, France
  • 6. ROR icon Stazione Zoologica Anton Dohrn
  • 7. ROR icon Bigelow Laboratory for Ocean Sciences
  • 8. Department of Ecoscience, Aarhus University, Roskilde, Denmark
  • 9. ROR icon Virginia Institute of Marine Science
  • 10. University of East Anglia, Norwich Research Park, Norwich NR4 7TJ UK
  • 11. ROR icon GEOMAR Helmholtz Centre for Ocean Research Kiel
  • 12. Alfred-Wegener-Institute – Helmholtz Centre for Polar and Marine Research, 27570 Bremerhaven, Germany

Description

This work describes the outcomes from a subcomponent of a project funded by the NERC (UK) during 2023, with the overarching aim of facilitating the construction of the next generation of plankton simulation models by engaging with experts in real plankton physiology and ecology. Over 30 experts, covering plankton from viruses to krill, contributed to various facets of the project. They were selected specifically for their empirical interests; modellers per se were not included.  This component had 13 contributors.

This work includes information to assist contributors in identifying data of use to modellers, including considerations of the types of data that modellers need, and the challenges inherent in certain data types.

Contributors were requested to provide exemplar references that they considered supportive of plankton modelling targeted at developing digital twins. These data were deposited in a database held in an Excel spreadsheet file (https://doi.org/10.5281/zenodo.10948648). The database, containing over 120 entries, can be explored using multi-level sort functions. Although entries contain data dominated by primary producers, temperature, light and inorganic nutrients, there are also a good range of other data types. Data also come from a range of different systems (laboratory, field, batch, steady-state).

Additional contributions are welcome, and the published database will be re-published to make such additions available on open access.

Files

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Additional details

Funding

Natural Environment Research Council
Simulating Plankton - getting it right in the era of Digital Twins of The Ocean NE/X010783/1