An international research team led by Johannes Gutenberg University Mainz and the Max Planck Institute for Chemistry has found a new way to reconstruct daily seawater temperatures over a four-month period. The method relies on rhodoliths—nodule-like calcareous structures formed by red algae that occur worldwide in oceans, from shallow water to depths of about 200 meters.
Researchers typically reconstruct past ocean conditions using the skeletons of corals, bivalves, and microfossils such as foraminifera. However, these archives face constraints from shrinking habitats, while rhodoliths are widely available. The challenge has been their complex three-dimensional branching structure and asynchronous growth, which complicate reconstruction of a clear timeline within the layered calcareous skeleton.
The team addressed this by combining multiple techniques. Researchers stained algae with a dye that accumulates in calcium carbonate and allowed them to grow in the field for four months as a time marker. They then scanned the nodule using micro-computed tomography, an X-ray technique, to map its internal growth layers in three dimensions. A laser vaporized tiny bits of the algae's skeleton, and a mass spectrometer analyzed the bits to measure changes in the ratios of magnesium to strontium in each layer, allowing researchers to determine the seawater temperature when each layer formed. Finally, the team applied a data-alignment algorithm called dynamic time warping to merge data from multiple branches into a single continuous timeline.
The researchers tested their method on a single rhodolith from a central Red Sea reef flat, reconstructing 133 days of temperature data from March to July 2024. The reconstruction closely matched measurements from temperature loggers at the site, capturing both the seasonal warming trend and short-term variations. The findings were published in the journal Communications Earth & Environment.
The study represents a proof of concept that could be extended to rhodoliths worldwide, enabling the collection of high-resolution climate data across larger regions and longer time periods. The approach could help reconstruct paleoclimatic development and more accurately predict the impacts of global warming on threatened marine ecosystems.
