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  • September 26, 2025

From DNA to action: improving climate change predictions and ocean conservation with advanced modelling

A recent publication co-funded by BIOcean5D improves advanced modelling, sharpening predictions of climate change impacts and guiding stronger ocean conservation efforts.
Credit: Reproduced from Antoine Régimbeau et al., Science Advances, DOI: 10.1126/sciadv.adq3593 [2025], AAAS.

Understanding Earth System Models (ESMs)

Climate models simulate the physics of the atmosphere, oceans, land surface, and ice to help us understand and predict climate patterns and variability. Earth System Models (ESMs) aim to be more comprehensive, also integrating chemical, biological, and ecological processes that interact with – and feed back into – the physical climate system. This allows ESMs to capture how different components of the Earth system influence one another and respond to both natural and human-induced changes.

“ESMs are essential tools for understanding climate change and are used by the IPCC to predict the impacts of climate change and explore the consequences of different scenarios,” explains Damien Eveillard, Professor at Nantes Université, France.

The challenge: simplified biology

Despite their power, ESMs are limited by computational constraints. Biological processes are often highly simplified, contributing to significant uncertainty in predicting how climate change affects biology or, conversely, how global ecosystems respond to changes in ocean phytoplankton physiology.

“ESMs typically use equations representing broad groups of organisms, such as picophytoplankton, diatoms, or copepods,” explains Damien. “Thanks to a collaborative, interdisciplinary effort, we’ve managed to develop an approach that replaces these generic representations with detailed molecular descriptions of organisms derived directly from DNA sequencing.”

Credit: Pixabay | Gerd Altmann

Genome-Scale Models (GSMs): from DNA to physiology

Thanks to recent advances in DNA sequencing, complete genomic data – covering all genes, their sequences, and their expression – are now available, forming the foundation for genome-scale models (GSMs). “GSMs represent the latest modelling paradigm in systems biology, enabling quantitative simulation of an organism’s physiology,” explains Damien. These models incorporate the full set of metabolic reactions encoded by the genome, capturing how an organism produces energy, grows, and responds to its environment. By mapping the links between reactions – where the product of one reaction serves as the substrate for another – a comprehensive metabolic network is formed.

Integrating GSMs into ESMs: a collective effort

Embedding GSMs within ESMs represents a major step towards incorporating molecular biodiversity and biocomplexity into ESMs, thus addressing a current key limitation. “Our approach enables a more precise estimation of plankton behaviour across the oceans, the influence of nutrient gradients on phytoplankton physiology, and a better understanding of their role in ocean biogeochemistry,” explains Damien. “Thanks to the team’s diverse expertise, the predicted physiological responses were validated by biologists, while the predicted oceanographic patterns were critically reviewed by experts in oceanography and biogeochemistry.”

The method was tested using publicly available marine phytoplankton data from the GSM repository. “Only a few organisms have been modelled at their genome-scale, and we chose the most established – Prochlorococcus, along with a few other diatoms. Our method, however, is ready for all models, and I encourage the development of GSMs for every organism of interest. It would be a great achievement if all the data collected by BIOcean5D and TREC were transformed into GSMs!”

Credit: Kogia | Karim Iliya

Multidisciplinary collaboration rooted in the BIOcean5D initiative

Recently published in Science Advances and featured on the front cover of Volume 11, Issue 23, the article was co-authored by nine scientists from eight institutes and supported by eight funding sources. “Our work brings biological modelling into the realm of physics, breaking a conceptual bottleneck and demonstrating the value of multidisciplinary collaboration in marine science,” explains Damien. “BIOcean5D brought together inspiration from many disciplines – modelling, oceanography, biogeochemistry, biology, and computer science – to solve a shared problem.”

Implications for ocean conservation

This collective work contributes to BIOcean5D’s effort to develop new theories on the relationship between marine biodiversity and ecosystem function. The knowledge generated will be key to strengthening future ocean conservation policies. “Our approach provides a tool to connect plankton molecular diversity with carbon flux estimation from ESMs and could help identify ocean areas of particular interest – hot spots where plankton play a central role in the carbon cycle,” explains Damien.

Looking ahead

The researchers are already planning the next steps. “We’d like to extend this concept across the biological scale, starting at the holobiont or community level, to integrate even more organisms into ESMs. We also hope to use this approach to explore whether entropy could help explain the diversity of plankton function!”

Credit: Reproduced from Antoine Régimbeau et al., Science Advances, DOI: 10.1126/sciadv.adq3593 [2025], AAAS.
Read the full article here: Unveiling the link between phytoplankton molecular physiology and biogeochemical cycling via genome-scale modeling, Antoine Régimbeau et al, Science Advances, June 2025
Discover all publications relating to the work of BIOcean5D here

Notice with respect to the cover of Science Advances Volume 11, Issue 23: “Readers may view, browse, and/or download material for temporary copying purposes only, provided these uses are for noncommercial personal purposes. Except as provided by law, this material may not be further reproduced, distributed, transmitted, modified, adapted, performed, displayed, published, or sold in whole or in part, without prior written permission from the publisher.”

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From DNA to action: improving climate change predictions and ocean conservation with advanced modelling

This website is co-funded by the European Union (GA#101059915). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.

This work is supported by the UK government Horizon Europe Guarantee, UKRI Grant Reference Number 10039266.

This work has received funding from the Swiss State Secretariat for Education, Research and Innovation (SERl) under contract #22.00255.

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