Simulating Plankton – getting it right in the era of Digital Twins of The Ocean; building and challenging perceptions
Creators
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Flynn, Kevin John
(Project leader)1
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Sherr, Evelyn
(Project member)
- Stoecker, Diane (Project member)2
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Thingstad, Frede
(Project member)3
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Atkinson, Angus
(Project member)1
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Beardall, John
(Project member)4
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Boersma, Maarten
(Project member)5
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Bowler, Christopher
(Project member)6
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Calbet, Albert
(Project member)7
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Dam, Hans
(Project member)8
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Glibert, Pat
(Project member)2
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Hansen, Per J
(Project member)9
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Jin, Peng
(Project member)10
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Lomas, Michael W
(Project member)11
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Lønborg, Christian
(Project member)12
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Menden-Deuer, Susanne
(Project member)13
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Mock, Thomas
(Project member)14
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Needham, David
(Project member)15
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Robinson, Carol
(Project member)14
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Rokitta, Sebastian
(Project member)16
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Rost, Björn
(Project member)16
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Saiz, Enric
(Project member)7
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Schmidt, Katrin
(Project member)17
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Thiele, Stefan
(Project member)18
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Våge, Selina
(Project member)19
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1.
Plymouth Marine Laboratory
- 2. Horn Point Laboratory, University of Maryland, Cambridge, Maryland, USA
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3.
University of Bergen
-
4.
Monash University
- 5. Alfred-Wegener-Institute – Helmholtz Centre for Polar and Marine Research, 27498 Helgoland, Germany
-
6.
Institut de Biologie de l'École Normale Supérieure
- 7. Institute of Marine Sciences, CSIC. Pg. Marítim 37-49, 08003. BCN, Spain
- 8. Marine Sciences, University of Connecticut, CT 06340-6048, USA
- 9. University of Copenhagen, Helsingør, Denmark
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10.
Guangzhou University
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11.
Bigelow Laboratory for Ocean Sciences
- 12. Department of Ecoscience, Aarhus University, Roskilde, Denmark
- 13. University of Rhode Island, Narragansett, RI, USA
- 14. University of East Anglia, Norwich Research Park, Norwich NR4 7TJ UK
-
15.
GEOMAR Helmholtz Centre for Ocean Research Kiel
- 16. Alfred-Wegener-Institute – Helmholtz Centre for Polar and Marine Research, 27570 Bremerhaven, Germany
- 17. Earth & Environmental Sciences, University of Plymouth, PL4 8AA, UK
- 18. Microbial Ecology, University of Vienna, Djerassiplatz 1, A-1030 Vienna, Austria
- 19. Biological Sciences, University of Bergen, Bergen 5020, Norway
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 24 contributors.
Contributors were requested to respond to a series of plankton-specific (33) and general (34) statements and questions relating to the description of plankton in models as might be required for building digital twins. Although not directly emphasised, many of these matters may also be interpreted in the context of traditional extant plankton models. The format of the statements and questions varied, including provocative styles akin to those in a media (TV, radio) interview. For the bulk of the responses, contributors were in agreement.
Complexity in depth is of greater interest than complexity in breadth. Accordingly, digital twins describing rather few plankton types with physiological/behavioural detail were of more interest than models in which many plankton types are described each with little detail. This interest also aligns with that for multi-stressor environments and factors that potentially affect changes in plankton biodiversity. The construction of aspirational plankton digital twins which push the boundaries of empirical understanding are encouraged; examples included interests in dissolved organic matter (DOM) production and exploitation, and the subject of stability in food web dynamics. To deliver to such interests will require significant effort to not only design the simulation engine for the plankton but also the functionality of the graphic user interface.
Failures of aspirational digital twin models due to insufficient detail (as distinct to errors in detail) are not unwelcome, as they flag where more science effort is required. Failures due to simplicity for the sake of simplicity (to minimise computational loads) are considered counterproductive, and arguably dangerous, especially if the user of such information is unaware of the problems because model functionality is described inadequately. The underlying functionality of plankton models needs to be clear. Appropriate use of infographics to explain model functionality to empiricists, rather than relying on mathematical or computer language, is highly desirable. Opportunities to educate empirical plankton scientists in simulation modelling is also required.
Responses to the questions/statements cast doubts upon the functionality of core parts of extant plankton models. By inference (although only raised explicitly in 1 of the 77 questions/statements), doubts are also cast upon the deployment of those plankton simulation models for applied use in, for example, fisheries and biogeochemical circulation models. Having simple plankton models with biodiversity-like descriptors (i.e., species or taxon names) for organisms that are not actually matched by the models functionality give an unjustified level of confidence in simulation projections.
The failure to adequately integrate plankton simulation modelling with empirical plankton research over the last 50 years has resulted in miss-communication and a loss of opportunity for further understanding of plankton communities. The availability of plankton digital twins, available in some form of in silico laboratory, would help promote bi-directional interactions between empiricists and modellers.
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BuildingChallengingPerceptionsV1.pdf
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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