Ying, Rui
ORCID: https://orcid.org/0000-0001-5811-2388, Monteiro, Fanny M., Wilson, Jamie D., Ödalen, Malin and Schmidt, Daniela N.
(2024)
Past foraminiferal acclimatization capacity is limited during future warming.
Nature, 636 (8042).
pp. 385-389.
ISSN 0028-0836
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Abstract
Climate change affects marine organisms, causing migrations, biomass reduction and extinctions1,2. However, the abilities of marine species to adapt to these changes remain poorly constrained on both geological and anthropogenic timescales. Here we combine the fossil record and a global trait-based plankton model to study optimal temperatures of marine calcifying zooplankton (foraminifera, Rhizaria) through time. The results show that spinose foraminifera with algal symbionts acclimatized to deglacial warming at the end of the Last Glacial Maximum (LGM, 19–21 thousand years ago, ka), whereas foraminifera without symbionts (non-spinose or spinose) kept the same thermal preference and migrated polewards. However, when forcing the trait-based plankton model with rapid transient warming over the coming century (1.5 °C, 2 °C, 3 °C and 4 °C relative to pre-industrial baseline), the model suggests that the acclimatization capacities of all ecogroups are limited and insufficient to track warming rates. Therefore, foraminifera are projected to migrate polewards and reduce their global carbon biomass by 5.7–15.1% (depending on the warming) by 2100 relative to 1900–1950. Our study highlights the different challenges posed by anthropogenic and geological warming for marine plankton and their ecosystem functions.
| Item Type: | Article |
|---|---|
| Additional Information: | Data availability: The MARGO and ForCenS fossil data, in addition to the previously described77 LGM temperature assimilation product, can be retrieved from https://www.pangaea.de. The HadISST data product is publicly available at https://www.metoffice.gov.uk/hadobs/hadisst/. All the CMIP6 data can be downloaded from https://esgf-node.llnl.gov/projects/cmip6/. The cleaned foraminifera fossil abundance and temperature data in this study are available at https://zenodo.org/doi/10.5281/zenodo.8189768 (ref. 82). The existing pre-industrial, LGM and future cGENIE model outputs are archived in https://zenodo.org/doi/10.5281/zenodo.8189647 (ref. 83). The reanalysed data from a previous study12 are available at https://zenodo.org/doi/10.5281/zenodo.8189772 (ref. 84). Source data are provided with this paper. Code availability: The cGENIE model code used in this study is available at https://github.com/ruiying-ocean/cgenie.muffin/tree/DEV_Foram/ (https://zenodo.org/doi/10.5281/zenodo.12658600). Instructions including commands to run the models can be found in the genie-userconfig/FORAMECOGEM/readme.txt. Model data analyses were performed using cgeniepy (v.0.7.5)85. All the scripts for analyses and visualizations are stored at https://github.com/ruiying-ocean/lgm_foram_niche. |
| Uncontrolled Keywords: | general,sdg 13 - climate action,sdg 14 - life below water ,/dk/atira/pure/subjectarea/asjc/1000 |
| Faculty \ School: | Faculty of Science > School of Environmental Sciences |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 14 Aug 2026 15:31 |
| Last Modified: | 16 Aug 2026 06:38 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/104158 |
| DOI: | 10.1038/s41586-024-08029-0 |
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