Call for expert witnesses in empirical plankton science
12 December 2022
Plankton models are used from science-theory to global-scale climate change research. The vast bulk of such models, however, are based on concepts that date from the 1970’s, and most are run in ecosystem models that also do not reflect modern understanding of marine ecology.
Set against a drive to develop and implement digital twins in marine research, Plymouth Marine Laboratory are leading on a project that will provide the building blocks that are essential for any realistic attempt to construct digital twins of plankton, in our project named 'Simulating Plankton - getting it right in the era of Digital Twins of The Ocean'.
To compensate for the lack of suitable numeric data, the project will exploit the hitherto largely untapped wealth of phenomenological data, working with experts in empirical plankton science from viruses to mesozooplankton, to bring together phenomenological data in the form of consensus lists of the traits expected of digital twins set against different scales of deployment, response curves describing feedbacks in physiology and behaviour, parameter values and exemplar numeric data series. This information, for each plankton group, will be published as ‘Expert Witness Reference Guides for Plankton Digital Twins’ co-authored (i.e. ‘owned’) by the expert witnesses in updatable open access e-publications to provide references against which to build new models and consider the value of work conducted with previous models.
Professor Kevin Flynn, who is leading the project - which commences in January 2023 - commented:
“We are only as good as our data. This is a truly exciting opportunity for scientists to contribute to an up-to-date, holistic understanding of plankton, that will ultimately benefit many sectors of science. We invite the scientific community to join us in and welcome any questions or expressions of interest.”
The aim of this project is to generate, using help from expert witnesses (i.e., researchers with experience from laboratory or field measurements), the validation data that are essential for any realistic attempt to construct and deploy digital twins of plankton (Flynn et al. 2022; https://doi.org/10.1093/plankt/fbac042)