Cooley, S. et al. in Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Pörtner, H.-O. et al.) 379â550 (Cambridge Univ. Press, 2022).
Yasuhara, M. et al. Past and future decline of tropical pelagic biodiversity. Proc. Natl Acad. Sci. 117, 12891â12896 (2020).
Pinsky, M. L., Worm, B., Fogarty, M. J., Sarmiento, J. L. & Levin, S. A. Marine taxa track local climate velocities. Science 341, 1239â1242 (2013).
Chaudhary, C., Richardson, A. J., Schoeman, D. S. & Costello, M. J. Global warming is causing a more pronounced dip in marine species richness around the equator. Proc. Natl Acad. Sci. USA 118, e2015094118 (2021).
Padfield, D., Yvon-Durocher, G., Buckling, A., Jennings, S. & Yvon-Durocher, G. Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton. Ecol. Lett. 19, 133â142 (2016).
Irwin, A. J., Finkel, Z. V., Müller-Karger, F. E. & Troccoli Ghinaglia, L. Phytoplankton adapt to changing ocean environments. Proc. Natl Acad. Sci. USA 112, 5762â5766 (2015).
Lee, Y. H. et al. Epigenetic plasticity enables copepods to cope with ocean acidification. Nat. Clim. Change 12, 918â927 (2022).
Yasuhara, M., Hunt, G., Dowsett, H. J., Robinson, M. M. & Stoll, D. K. Latitudinal species diversity gradient of marine zooplankton for the last three million years. Ecol. Lett. 15, 1174â1179 (2012).
Chivers, W. J., Walne, A. W. & Hays, G. C. Mismatch between marine plankton range movements and the velocity of climate change. Nat. Commun. 8, 14434 (2017).
Lotze, H. K. et al. Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change. Proc. Natl Acad. Sci. USA 116, 12907â12912 (2019).
Neukermans, G. et al. Quantitative and mechanistic understanding of the open ocean carbonate pump – perspectives for remote sensing and autonomous in situ observation. Earth Sci. Rev. 239, 104359 (2023).
Antell, G. S., Fenton, I. S., Valdes, P. J. & Saupe, E. E. Thermal niches of planktonic foraminifera are static throughout glacialâinterglacial climate change. Proc. Natl Acad. Sci. USA 118, e2017105118 (2021).
Waterson, A. M., Edgar, K. M., Schmidt, D. N. & Valdes, P. J. Quantifying the stability of planktic foraminiferal physical niches between the Holocene and Last Glacial Maximum: niche stability of planktic foraminifera. Paleoceanography 32, 74â89 (2017).
Davis, C. V., Wishner, K., Renema, W. & Hull, P. M. Vertical distribution of planktic foraminifera through an oxygen minimum zone: how assemblages and test morphology reflect oxygen concentrations. Biogeosciences 18, 977â992 (2021).
Vanadzina, K. & Schmidt, D. N. Developmental change during a speciation event: evidence from planktic foraminifera. Paleobiology 48, 120â136 (2022).
Ward, B. A. et al. EcoGEnIE 1.0: plankton ecology in the cGEnIE Earth system model. Geosci. Model Dev. 11, 4241â4267 (2018).
Ying, R., Monteiro, F. M., Wilson, J. D. & Schmidt, D. N. ForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal model. Geosci. Model Dev. 16, 813â832 (2023).
Follows, M. J., Dutkiewicz, S., Grant, S. & Chisholm, S. W. Emergent biogeography of microbial communities in a model ocean. Science 315, 1843â1846 (2007).
Sinclair, B. J. et al. Can we predict ectotherm responses to climate change using thermal performance curves and body temperatures? Ecol. Lett. 19, 1372â1385 (2016).
Lombard, F., Labeyrie, L., Michel, E., Spero, H. J. & Lea, D. W. Modelling the temperature dependent growth rates of planktic foraminifera. Mar. Micropaleontol. 70, 1â7 (2009).
Schmidt, D. N., Renaud, S., Bollmann, J., Schiebel, R. & Thierstein, H. R. Size distribution of Holocene planktic foraminifer assemblages: biogeography, ecology and adaptation. Mar. Micropaleontol. 50, 319â338 (2004).
Darling, K. F. et al. Genetic diversity and ecology of the planktonic foraminifers Globigerina bulloides, Turborotalita quinqueloba and Neogloboquadrina pachyderma off the Oman margin during the late SW monsoon. Mar. Micropaleontol. 137, 64â77 (2017).
Steinke, S., Yu, P.-S., Kucera, M. & Chen, M.-T. No-analog planktonic foraminiferal faunas in the glacial southern South China Sea: implications for the magnitude of glacial cooling in the western Pacific warm pool. Mar. Micropaleontol. 66, 71â90 (2008).
Möller, V. et al. in Climate Change 2022: Impacts, Adaptation And Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Pörtner, H.-O. et al.) 2897â2930 (Cambridge Univ. Press, 2022).
Hattich, G. S. I. et al. Temperature optima of a natural diatom population increases as global warming proceeds. Nat. Clim. Change 14, 518â525 (2024).
Sexton, P. F. & Norris, R. D. Dispersal and biogeography of marine plankton: long-distance dispersal of the foraminifer Truncorotalia truncatulinoides. Geology 36, 899â902 (2008).
Kucera, M. & Schonfeld, J. in Deep-Time Perspectives on Climate Change: Marrying the Signal from Computer Models and Biological Proxies (eds Williams, M. et al.) 409â425 (Geological Society of London on behalf of The Micropalaeontological Society, 2007).
Vargas, C., de, Renaud, S., Hilbrecht, H. & Pawlowski, J. Pleistocene adaptive radiation in Globorotalia truncatulinoides: genetic, morphologic, and environmental evidence. Paleobiology 27, 104â125 (2001).
Morard, R. et al. The global genetic diversity of planktonic foraminifera reveals the structure of cryptic speciation in plankton. Biol. Rev. 99, 1218â1241 (2024).
Jonkers, L., Hillebrand, H. & Kucera, M. Global change drives modern plankton communities away from the pre-industrial state. Nature 570, 372â375 (2019).
Chaabane, S. et al. Modern planktonic Foraminifera: migrating is not enough. Preprint at https://doi.org/10.21203/rs.3.rs-3485983/v1 (2023).
Grigoratou, M., Monteiro, F. M., Wilson, J. D., Ridgwell, A. & Schmidt, D. N. Exploring the impact of climate change on the global distribution of nonâspinose planktonic foraminifera using a traitâbased ecosystem model. Glob. Change Biol. 28, 1063â1076 (2022).
Greco, M., Werner, K., Zamelczyk, K., Rasmussen, T. L. & Kucera, M. Decadal trend of plankton community change and habitat shoaling in the Arctic gateway recorded by planktonic foraminifera. Glob. Change Biol. 28, 1798â1808 (2022).
Pinkerton, M. H. et al. Zooplankton in the Southern Ocean from the continuous plankton recorder: distributions and long-term change. Deep Sea Res. Part I 162, 103303 (2020).
Edgar, K. M. et al. Symbiont âbleachingâ in planktic foraminifera during the Middle Eocene Climatic Optimum. Geology 41, 15â18 (2013).
Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359, 80â83 (2018).
Boyd, P. W. Physiology and iron modulate diverse responses of diatoms to a warming Southern Ocean. Nat. Clim. Change 9, 148â152 (2019).
Grigoratou, M. et al. A trait-based modelling approach to planktonic foraminifera ecology. Biogeosciences 16, 1469â1492 (2019).
Galbraith, E. D. & Martiny, A. C. A simple nutrient-dependence mechanism for predicting the stoichiometry of marine ecosystems. Proc. Natl Acad. Sci. USA 112, 8199â8204 (2015).
LeKieffre, C. et al. Assimilation, translocation, and utilization of carbon between photosynthetic symbiotic dinoflagellates and their planktic foraminifera host. Mar. Biol. 165, 104 (2018).
Meilland, J., Howa, H., Lo Monaco, C. & Schiebel, R. Individual planktic foraminifer protein-biomass affected by trophic conditions in the Southwest Indian Ocean, 30°Sâ60°S. Mar. Micropaleontol. 124, 63â74 (2016).
Anderson, R. F. et al. Wind-driven upwelling in the Southern Ocean and the deglacial rise in atmospheric CO2. Science 323, 1443â1448 (2009).
Gray, W. R. et al. Deglacial upwelling, productivity and CO2 outgassing in the North Pacific Ocean. Nature Geosci 11, 340â344 (2018).
Kawahata, H. et al. Perspective on the response of marine calcifiers to global warming and ocean acidificationâbehavior of corals and foraminifera in a high CO2 world âhot houseâ. Prog. Earth Planet. Sci. 6, 5 (2019).
Deutsch, C., Penn, J. L. & Seibel, B. Metabolic trait diversity shapes marine biogeography. Nature 585, 557â562 (2020).
Sauterey, B. et al. Phytoplankton adaptive resilience to climate change collapses in case of extreme eventsâa modeling study. Ecol. Model. 483, 110437 (2023).
Gunderson, A. R. & Stillman, J. H. Plasticity in thermal tolerance has limited potential to buffer ectotherms from global warming. Proc. R. Soc. B 282, 20150401 (2015).
Lan, X., Tans, P. & Thoning, K. W. Trends in globally-averaged CO2 determined from NOAA Global Monitoring Laboratory measurements. https://doi.org/10.15138/9N0H-ZH07 (2023).
Pohl, A. et al. Continental configuration controls ocean oxygenation during the Phanerozoic. Nature 608, 523â527 (2022).
Edwards, N. R. & Marsh, R. Uncertainties due to transport-parameter sensitivity in an efficient 3-D ocean-climate model. Clim. Dyn. 24, 415â433 (2005).
Marsh, R., Müller, S. A., Yool, A. & Edwards, N. R. Incorporation of the C-GOLDSTEIN efficient climate model into the GENIE framework: âeb_go_gsâ configurations of GENIE. Geosci. Model Dev. 4, 957â992 (2011).
Ridgwell, A. et al. Marine geochemical data assimilation in an efficient Earth System Model of global biogeochemical cycling. Biogeosciences 4, 87â104 (2007).
Davies-Barnard, T., Ridgwell, A., Singarayer, J. & Valdes, P. Quantifying the influence of the terrestrial biosphere on glacialâinterglacial climate dynamics. Clim. Past 13, 1381â1401 (2017).
Albani, S. et al. Paleodust variability since the Last Glacial Maximum and implications for iron inputs to the ocean. Geophys. Res. Lett. 43, 3944â3954 (2016).
Morée, A. L. & Schwinger, J. A Last Glacial Maximum forcing dataset for ocean modelling. Earth Syst. Sci. Data 12, 2971â2985 (2020).
Kageyama, M. et al. The PMIP4 contribution to CMIP6 â Part 4: Scientific objectives and experimental design of the PMIP4-CMIP6 Last Glacial Maximum experiments and PMIP4 sensitivity experiments. Geosci. Model Dev. 10, 4035â4055 (2017).
Ãdalen, M. Model Analysis of Ocean Carbon Storage and Transport Across Climate States. PhD thesis, Stockholm Univ. (2019).
Bouttes, N., Paillard, D. & Roche, D. M. Impact of brine-induced stratification on the glacial carbon cycle. Clim. Past 6, 575â589 (2010).
Peterson, C. D., Lisiecki, L. E. & Stern, J. V. Deglacial whole-ocean δ13C change estimated from 480 benthic foraminiferal records. Paleoceanography 29, 549â563 (2014).
Muglia, J., Skinner, L. C. & Schmittner, A. Weak overturning circulation and high Southern Ocean nutrient utilization maximized glacial ocean carbon. Earth Planet. Sci. Lett. 496, 47â56 (2018).
Kageyama, M. et al. The PMIP4 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3 simulations. Clim. Past 17, 1065â1089 (2021).
Annan, J. D., Hargreaves, J. C. & Mauritsen, T. A new global surface temperature reconstruction for the Last Glacial Maximum. Clim. Past 18, 1883â1896 (2022).
Jonkers, L. & KuÄera, M. Quantifying the effect of seasonal and vertical habitat tracking on planktonic foraminifera proxies. Clim. Past 13, 573â586 (2017).
Cao, L. et al. The role of ocean transport in the uptake of anthropogenic CO2. Biogeosciences 6, 375â390 (2009).
Mahowald, N. M. et al. Change in atmospheric mineral aerosols in response to climate: last glacial period, preindustrial, modern, and doubled carbon dioxide climates. J. Geophys. Res. 111, D10202 (2006).
Morice, C. P. et al. An updated assessment of nearâsurface temperature change from 1850: the HadCRUT5 data set. J. Geophys. Res. Atmos. 126, e2019JD032361 (2021).
Tittensor, D. P. et al. Next-generation ensemble projections reveal higher climate risks for marine ecosystems. Nat. Clim. Change 11, 973â981 (2021).
Michaels, A. F., Caron, D. A., Swanberg, N. R., Howse, F. A. & Michaels, C. M. Planktonic sarcodines (Acantharia, Radiolaria, Foraminifera) in surface waters near Bermuda: abundance, biomass and vertical flux. J. Plankton Res. 17, 131â163 (1995).
Fraile, I. et al. Modeling the seasonal distribution of planktonic foraminifera during the Last Glacial Maximum. Paleoceanography 24, PA2216 (2009).
Siccha, M. & Kucera, M. ForCenS, a curated database of planktonic foraminifera census counts in marine surface sediment samples. Sci. Data 4, 170109 (2017).
Kucera, M., Rosell-Melé, A., Schneider, R., Waelbroeck, C. & Weinelt, M. Multiproxy approach for the reconstruction of the glacial ocean surface (MARGO). Quat. Sci. Rev. 24, 813â819 (2005).
Brummer, G.-J. A. & KuÄera, M. Taxonomic review of living planktonic foraminifera. J. Micropalaeontol. 41, 29â74 (2022).
Takagi, H. et al. Characterizing photosymbiosis in modern planktonic foraminifera. Biogeosciences 16, 3377â3396 (2019).
Schiebel, R. & Hemleben, C. Planktic Foraminifers in the Modern Ocean (Springer Berlin, 2017).
Huber, B. T. et al. Pforams@microtax: A new online taxonomic database for planktonic foraminifera. Micropaleontology 62, 429â438 (2016).
Rayner, N. A. et al. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. 108, 4407 (2003).
Tierney, J. E. et al. Glacial cooling and climate sensitivity revisited. Nature 584, 569â573 (2020).
Rebotim, A. et al. Factors controlling the depth habitat of planktonic foraminifera in the subtropical eastern North Atlantic. Biogeosciences 14, 827â859 (2017).
Muggeo, V. M. R., Torretta, F., Eilers, P., Sciandra, M. & Attanasio, M. Multiple smoothing parameters selection in additive regression quantiles. Stat. Model. 21, 428â448 (2021).
Kremer, C. T., Thomas, M. K. & Litchman, E. Temperature- and size-scaling of phytoplankton population growth rates: reconciling the Eppley curve and the metabolic theory of ecology. Limnol. Oceanogr. 62, 1658â1670 (2017).
R Core Team. R: A Language and Environment for Statistical Computing. https://www.R-project.org/ (R Foundation for Statistical Computing, 2023).
Ying, R. ruiying-ocean/lgm_foram_census: Foraminifera abundance data in the LGM/PI. Zenodo https://zenodo.org/doi/10.5281/zenodo.8189768 (2024).
Ying, R., Monteiro, F. M., Wilson, J. D. & Schmidt, D. N. Modelled planktic formainifera from LGM to future (ForamEcoGENIE). Zenodo https://zenodo.org/doi/10.5281/zenodo.8189647 (2024).
Ying, R. ruiying-ocean/quanternary_foram_niche: Foraminifera optimal niche reanalysis based on Antell et al. (2021) data. Zenodo https://zenodo.org/doi/10.5281/zenodo.8189772 (2024).
Ying, R. cgeniepy: a Python package for analysing cGENIE Earth System Model output. Preprint at https://doi.org/10.21203/rs.3.rs-3967633/v1 (2024).
