Articles | Volume 22, issue 10
https://doi.org/10.5194/bg-22-2363-2025
https://doi.org/10.5194/bg-22-2363-2025
Ideas and perspectives
 | 
19 May 2025
Ideas and perspectives |  | 19 May 2025

Ideas and perspectives: How sediment archives can improve model projections of marine ecosystem change

Isabell Hochfeld, Ben A. Ward, Anke Kremp, Juliane Romahn, Alexandra Schmidt, Miklós Bálint, Lutz Becks, Jérôme Kaiser, Helge W. Arz, Sarah Bolius, Laura S. Epp, Markus Pfenninger, Christopher A. Klausmeier, Elena Litchman, and Jana Hinners

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Cited articles

Abrantes, F., Lebreiro, S., Rodrigues, T., Gil, I., Bartels-Jónsdóttir, H., Oliveira, P., Kissel, C., and Grimalt, J. O.: Shallow-marine sediment cores record climate variability and earthquake activity off Lisbon (Portugal) for the last 2000 years, Quaternary Sci. Rev., 24, 2477–2494, https://doi.org/10.1016/j.quascirev.2004.04.009, 2005. 
Alsos, I. G., Boussange, V., Rijal, D. P., Beaulieu, M., Brown, A. G., Herzschuh, U., Svenning, J.-C., and Pellissier, L.: Using ancient sedimentary DNA to forecast ecosystem trajectories under climate change, Philos. T. R. Soc. B, 379, 20230017, https://doi.org/10.1098/rstb.2023.0017, 2024. 
Appleby, P. G.: Chronostratigraphic Techniques in Recent Sediments, in: Tracking Environmental Change Using Lake Sediments, Volume 1: Basin Analysis, Coring, and Chronological Techniques, edited by: Last, W. M. and Smol, J. P., Springer, Dordrecht, 171–203, https://doi.org/10.1007/0-306-47669-X_9, 2001. 
Aranguren-Gassis, M., Kremer, C. T., Klausmeier, C. A., and Litchman, E.: Nitrogen limitation inhibits marine diatom adaptation to high temperatures, Ecol. Lett., 22, 1860–1869, https://doi.org/10.1111/ele.13378, 2019. 
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Short summary
Marine ecosystem models (MEMs) are valuable for assessing the threats of global warming to biodiversity and ecosystem functioning, but their predictions vary widely. We argue that MEMs should consider evolutionary processes and undergo independent validation. Here, we present a novel framework for MEM development using validation data from sediment archives, which map long-term environmental and evolutionary change. Our approach is a crucial step towards improving the predictive power of MEMs.
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