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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; core features of plankton digital twins.

  • 1. ROR icon Plymouth Marine Laboratory
  • 2. ROR icon Monash University
  • 3. ROR icon University of Wisconsin–Milwaukee
  • 4. Alfred-Wegener-Institute – Helmholtz Centre for Polar and Marine Research, 27498 Helgoland, Germany
  • 5. ROR icon Stazione Zoologica Anton Dohrn
  • 6. Institute of Marine Sciences, CSIC. Pg. Marítim 37-49, 08003. BCN, Spain
  • 7. ROR icon University of Southern California
  • 8. Marine Sciences, University of Connecticut, CT 06340-6048, USA
  • 9. Horn Point Laboratory, University of Maryland, Cambridge, Maryland, USA
  • 10. University of Copenhagen, Helsingør, Denmark
  • 11. ROR icon Guangzhou University
  • 12. ROR icon Bigelow Laboratory for Ocean Sciences
  • 13. Department of Ecoscience, Aarhus University, Roskilde, Denmark
  • 14. ROR icon University of Exeter
  • 15. Alfred-Wegener-Institute – Helmholtz Centre for Polar and Marine Research, 27570 Bremerhaven, Germany
  • 16. ROR icon Virginia Institute of Marine Science
  • 17. University of East Anglia, Norwich Research Park, Norwich NR4 7TJ UK
  • 18. ROR icon Old Dominion University
  • 19. ROR icon Heriot-Watt University
  • 20. ROR icon University of Warwick
  • 21. Earth & Environmental Sciences, University of Plymouth, PL4 8AA, UK
  • 22. Eugene, Oregon, USA
  • 23. ROR icon UiT The Arctic University of Norway
  • 24. Microbial Ecology, University of Vienna, Djerassiplatz 1, A-1030 Vienna, Austria
  • 25. Biological Sciences, University of Bergen, Bergen 5020, Norway
  • 26. INTECH, Buenos Aires 7130, Argentina

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 32 contributors.

Contributors were asked to configuring aspirational plankton digital twins (PDT). To protect the intellectual property of the contributors, their PDT concepts are not presented. The PDT concepts were analysed with respect to the required abiotic and biotic components and input/output needs.

Most PDT concepts were for short duration (<1mo) laboratory or mesocosm scenarios, some with chemostat-like settings. Field scenarios were 1D (with depth). Most concepts required multiple plankton function types, with host-virus, prey-predator and competition (allelopath) interactions. There was also interest in single organism concepts for photophysiology studies. Concepts included scope for multiple stressor/resource descriptions, most commonly including temperature, light (irradiance, light:dark cycle, with some interests in spectra), and pH/pCO2. While dissolved inorganics were the most requested nutrient form, over a third expressed interest in detailed dissolved organics (i.e., multiple DOM forms and DOC). Two-way interactions were of interest not only for inorganics (with nutrient regeneration), but also for pH, CO2/O2, dissolved organics and the fate of debris (including mortality).

Details of the plankton themselves were invariably expected to include biomass with variable stoichiometry (some including fatty acids), and also numeric abundance (often with explicit allometry). Interests in photopigments were dominated by chlorophyll, with some interest in other pigments such as carotenoids. About a third expressed a requirement for inclusion of allelopaths or toxins.

Almost all expressed a requirement for detailed physiological and/or behavioural descriptions for the plankton, including variable prey or host selectivity. Explicit descriptions of ontogeny and of vertical migration or other depth-linked aspects were also of interest. A few required explicit inclusion of omics-linkages within the PDT.

Input and outputs expectations included an interest in a rewind function during the simulation to facilitate ‘what-if?’ testing, and multiple time and x,y scatter plot options.

In short, the general expectation for a PDT, or at least for first-generation PDTs, describes an in silico laboratory in which a range of plankton types would be described to high levels of detail with respect to physiology and behaviour, in a chemically detailed but dimensionally simple (0D or 1D) setting for short-period incubations.

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Funding

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