Articles | Volume 21, issue 5
https://doi.org/10.5194/os-21-2397-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-21-2397-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Oct 2025
Research article |
| 10 Oct 2025
| 10 Oct 2025
A novel multispecies approach for the detection of regime shifts in a plankton community – a case study in the North Sea
Geophysical Institute, University of Bergen, Bergen, Norway
Bjerknes Center for Climate Research, Bergen, Norway
Friederike Fröb
Geophysical Institute, University of Bergen, Bergen, Norway
Bjerknes Center for Climate Research, Bergen, Norway
Beatriz Arellano-Nava
University of Exeter, Laver Building, North Park Road, Exeter EX4 4QE, UK
David G. Johns
Continuous Plankton Recorder Survey, Marine Biological Association, Citadel Hill, Plymouth PL1 2PB, UK
Christoph Heinze
Geophysical Institute, University of Bergen, Bergen, Norway
Bjerknes Center for Climate Research, Bergen, Norway
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Andreas Karpasitis, Manabu Abe, Isaline Bossert, Friederike Fröb, Thomas Frölicher, Panos Hadjinicolaou, Colin Jones, Roland Séférian, Tomas Torsvik, Jeremy Walton, Klaus Wyser, Tokuta Yokohata, and George Zittis
EGUsphere, https://doi.org/10.5194/egusphere-2026-5285, https://doi.org/10.5194/egusphere-2026-5285, 2026
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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The tropical atmosphere plays a key role in driving rainfall and influencing weather around the world. In this study, we used idealized simulations to examine how tropical rainfall and atmospheric circulation change as the planet warms. We found that the main tropical rain belt shifts closer to the Equator. Although vertical air motion becomes weaker, rainfall becomes more intense. These changes could affect regional rainfall patterns and climate regimes in other parts of the world.
Colin Jones, Isaline Bossert, Donovan P. Dennis, Hazel A. Jeffery, Chris D. Jones, Torben Koenigk, Sina Loriani, Benjamin Sanderson, Roland Séférian, Klaus Wyser, Shuting Yang, Manabu Abe, Sebastian Bathiany, Pascale Braconnot, Victor Brovkin, Friedrich A. Burger, Patrica Cadule, Frederic S. Castruccio, Gokhan Danabasoglu, Andrea Dittus, Jonathan F. Donges, Friederike Fröb, Thomas L. Frölicher, Goran Georgievski, Chuncheng Guo, Aixue Hu, Peter Lawrence, Paul Lerner, José Licón-Saláiz, Bette Otto-Bliesner, Anastasia Romanou, Elena Shevliakova, Yona Silvy, Didier Swingedouw, Jerry Tjiputra, Jeremy Walton, Andy Wiltshire, Ricarda Winkelmann, Richard Wood, Tokuta Yokohata, and Tilo Ziehn
Geosci. Model Dev., 19, 6941–6966, https://doi.org/10.5194/gmd-19-6941-2026, https://doi.org/10.5194/gmd-19-6941-2026, 2026
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We introduce a new Earth system model experiment protocol to help researchers understand how Earth might respond to positive, zero, and negative carbon emissions. This protocol enables different models to be compared following similar warming and cooling rates. Researchers use the models to explore how the Earth reacts to different climate futures, including the risk of tipping points being exceeded and whether changes can be reversed. The results will support improved long-term climate policy.
Didier Swingedouw, Laura Jackson, Aixue Hu, Anastasia Romanou, Nicole C. Laureanti, Wilbert Weijer, Sina Loriani, Bette Otto-Bliesner, Ayako Abe-Ouchi, Lucas Almeida, Alessio Bellucci, Reyk Börner, Gokhan Danabasoglu, Donovan P. Dennis, Marion Devilliers, Sybren Drijfhout, Jonathan Donges, Friederike Fröb, Thomas L. Frölicher, Guillaume Gastineau, Heiko Goelzer, Chuncheng Guo, Urs Hofmann, Anna Höse, Colin Jones, Torben Koenigk, Ann Kristin Klose, Valerio Lembo, Jose Licon-Salaiz, Ken Mankoff, Virna Meccia, Irina Melnikova, Oliver Mehling, Laurie Menviel, Juliette Mignot, Jon I. Robson, Gavin A. Schmidt, Robin Smith, Yuchen Sun, Irene Trombini, Matteo Willeit, Richard Wood, Fanghua Wu, Lin Zhaohui, and Ricarda Winkelmann
EGUsphere, https://doi.org/10.5194/egusphere-2026-1698, https://doi.org/10.5194/egusphere-2026-1698, 2026
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This study presents a plan for climate model experiments to better understand how changes in freshwater in the North Atlantic affect major ocean currents. We designed coordinated simulations to test their response to warming, added freshwater, and possible recovery after weakening. Comparing results across models and past climate evidence helps improve confidence in projections and assess risks of large ocean circulation changes.
Timothée Bourgeois, Giang T. Tran, Aurich Jeltsch-Thömmes, Jörg Schwinger, Friederike Fröb, Thomas L. Frölicher, Thorsten Blenckner, Olivier Torres, Jean Negrel, David P. Keller, Andreas Oschlies, Laurent Bopp, and Fortunat Joos
Biogeosciences, 22, 5435–5462, https://doi.org/10.5194/bg-22-5435-2025, https://doi.org/10.5194/bg-22-5435-2025, 2025
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Anthropogenic greenhouse gas emissions significantly impact ocean ecosystems through climate change and acidification, leading to either progressive or abrupt changes. This study maps the crossing of physical and ecological limits for various ocean impact metrics under three emission scenarios. Using Earth system models, we identify when these limits are exceeded, highlighting the urgent need for ambitious climate action to safeguard the world's oceans and ecosystems.
Vasilis Dakos, Chris A. Boulton, Joshua E. Buxton, Jesse F. Abrams, Beatriz Arellano-Nava, David I. Armstrong McKay, Sebastian Bathiany, Lana Blaschke, Niklas Boers, Daniel Dylewsky, Carlos López-Martínez, Isobel Parry, Paul Ritchie, Bregje van der Bolt, Larissa van der Laan, Els Weinans, and Sonia Kéfi
Earth Syst. Dynam., 15, 1117–1135, https://doi.org/10.5194/esd-15-1117-2024, https://doi.org/10.5194/esd-15-1117-2024, 2024
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Tipping points are abrupt, rapid, and sometimes irreversible changes, and numerous approaches have been proposed to detect them in advance. Such approaches have been termed early warning signals and represent a set of methods for identifying changes in the underlying behaviour of a system across time or space that might indicate an approaching tipping point. Here, we review the literature to explore where, how, and which early warnings have been used in real-world case studies so far.
Andrea J. McEvoy, Angus Atkinson, Ruth L. Airs, Rachel Brittain, Ian Brown, Elaine S. Fileman, Helen S. Findlay, Caroline L. McNeill, Clare Ostle, Tim J. Smyth, Paul J. Somerfield, Karen Tait, Glen A. Tarran, Simon Thomas, Claire E. Widdicombe, E. Malcolm S. Woodward, Amanda Beesley, David V. P. Conway, James Fishwick, Hannah Haines, Carolyn Harris, Roger Harris, Pierre Hélaouët, David Johns, Penelope K. Lindeque, Thomas Mesher, Abigail McQuatters-Gollop, Joana Nunes, Frances Perry, Ana M. Queiros, Andrew Rees, Saskia Rühl, David Sims, Ricardo Torres, and Stephen Widdicombe
Earth Syst. Sci. Data, 15, 5701–5737, https://doi.org/10.5194/essd-15-5701-2023, https://doi.org/10.5194/essd-15-5701-2023, 2023
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Western Channel Observatory is an oceanographic time series and biodiversity reference site within 40 km of Plymouth (UK), sampled since 1903. Differing levels of reporting and formatting hamper the use of the valuable individual datasets. We provide the first summary database as monthly averages where comparisons can be made of the physical, chemical and biological data. We describe the database, illustrate its utility to examine seasonality and longer-term trends, and summarize previous work.
Christoph Heinze, Thorsten Blenckner, Peter Brown, Friederike Fröb, Anne Morée, Adrian L. New, Cara Nissen, Stefanie Rynders, Isabel Seguro, Yevgeny Aksenov, Yuri Artioli, Timothée Bourgeois, Friedrich Burger, Jonathan Buzan, B. B. Cael, Veli Çağlar Yumruktepe, Melissa Chierici, Christopher Danek, Ulf Dieckmann, Agneta Fransson, Thomas Frölicher, Giovanni Galli, Marion Gehlen, Aridane G. González, Melchor Gonzalez-Davila, Nicolas Gruber, Örjan Gustafsson, Judith Hauck, Mikko Heino, Stephanie Henson, Jenny Hieronymus, I. Emma Huertas, Fatma Jebri, Aurich Jeltsch-Thömmes, Fortunat Joos, Jaideep Joshi, Stephen Kelly, Nandini Menon, Precious Mongwe, Laurent Oziel, Sólveig Ólafsdottir, Julien Palmieri, Fiz F. Pérez, Rajamohanan Pillai Ranith, Juliano Ramanantsoa, Tilla Roy, Dagmara Rusiecka, J. Magdalena Santana Casiano, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Miriam Seifert, Anna Shchiptsova, Bablu Sinha, Christopher Somes, Reiner Steinfeldt, Dandan Tao, Jerry Tjiputra, Adam Ulfsbo, Christoph Völker, Tsuyoshi Wakamatsu, and Ying Ye
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-182, https://doi.org/10.5194/bg-2023-182, 2023
Revised manuscript not accepted
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For assessing the consequences of human-induced climate change for the marine realm, it is necessary to not only look at gradual changes but also at abrupt changes of environmental conditions. We summarise abrupt changes in ocean warming, acidification, and oxygen concentration as the key environmental factors for ecosystems. Taking these abrupt changes into account requires greenhouse gas emissions to be reduced to a larger extent than previously thought to limit respective damage.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
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In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Shuang Gao, Jörg Schwinger, Jerry Tjiputra, Ingo Bethke, Jens Hartmann, Emilio Mayorga, and Christoph Heinze
Biogeosciences, 20, 93–119, https://doi.org/10.5194/bg-20-93-2023, https://doi.org/10.5194/bg-20-93-2023, 2023
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We assess the impact of riverine nutrients and carbon (C) on projected marine primary production (PP) and C uptake using a fully coupled Earth system model. Riverine inputs alleviate nutrient limitation and thus lessen the projected PP decline by up to 0.7 Pg C yr−1 globally. The effect of increased riverine C may be larger than the effect of nutrient inputs in the future on the projected ocean C uptake, while in the historical period increased nutrient inputs are considered the largest driver.
Filippa Fransner, Friederike Fröb, Jerry Tjiputra, Nadine Goris, Siv K. Lauvset, Ingunn Skjelvan, Emil Jeansson, Abdirahman Omar, Melissa Chierici, Elizabeth Jones, Agneta Fransson, Sólveig R. Ólafsdóttir, Truls Johannessen, and Are Olsen
Biogeosciences, 19, 979–1012, https://doi.org/10.5194/bg-19-979-2022, https://doi.org/10.5194/bg-19-979-2022, 2022
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Ocean acidification, a direct consequence of the CO2 release by human activities, is a serious threat to marine ecosystems. In this study, we conduct a detailed investigation of the acidification of the Nordic Seas, from 1850 to 2100, by using a large set of samples taken during research cruises together with numerical model simulations. We estimate the effects of changes in different environmental factors on the rate of acidification and its potential effects on cold-water corals.
Clare Ostle, Kevin Paxman, Carolyn A. Graves, Mathew Arnold, Luis Felipe Artigas, Angus Atkinson, Anaïs Aubert, Malcolm Baptie, Beth Bear, Jacob Bedford, Michael Best, Eileen Bresnan, Rachel Brittain, Derek Broughton, Alexandre Budria, Kathryn Cook, Michelle Devlin, George Graham, Nick Halliday, Pierre Hélaouët, Marie Johansen, David G. Johns, Dan Lear, Margarita Machairopoulou, April McKinney, Adam Mellor, Alex Milligan, Sophie Pitois, Isabelle Rombouts, Cordula Scherer, Paul Tett, Claire Widdicombe, and Abigail McQuatters-Gollop
Earth Syst. Sci. Data, 13, 5617–5642, https://doi.org/10.5194/essd-13-5617-2021, https://doi.org/10.5194/essd-13-5617-2021, 2021
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Plankton form the base of the marine food web and are sensitive indicators of environmental change. The Plankton Lifeform Extraction Tool brings together disparate plankton datasets into a central database from which it extracts abundance time series of plankton functional groups, called
lifeforms, according to shared biological traits. This tool has been designed to make complex plankton datasets accessible and meaningful for policy, public interest, and scientific discovery.
Paul R. Halloran, Jennifer K. McWhorter, Beatriz Arellano Nava, Robert Marsh, and William Skirving
Geosci. Model Dev., 14, 6177–6195, https://doi.org/10.5194/gmd-14-6177-2021, https://doi.org/10.5194/gmd-14-6177-2021, 2021
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This paper describes the latest version of a simple model for simulating coastal oceanography in response to changes in weather and climate. The latest revision of this model makes scientific improvements but focuses on improvements that allow the model to be run simply at large scales and for long periods of time to explore the implications of (for example) future climate change along large areas of coastline.
Cited articles
Bartsch, J., Brandert, K., Heath, M., Munk, P., Richardson, K., and Svendsen, E.: Modelling the advection of herring larvae in the North Sea, Nature, 340, 632–636, https://doi.org/10.1038/340632a0, 1989. a, b
Beaugrand, G.: The North Sea regime shift: evidence, causes, mechanisms and consequences, Proceedings of Oceanography, 60, 245–262, https://doi.org/10.1016/j.dsr2.2008.12.022, 2004a. a
Beaugrand, G., Edwards, M., and Legendre, L.: Marine biodiversity, ecosystem functioning and the carbon cycles, P. Natl. Acad. Sci. USA, 107, 10120–10124, https://doi.org/10.1073/pnas.0913855107, 2010. a
Beaulieu, C., Cole, H., Henson, S., Yool, A., Anderson, T. R., de Mora, L., Buitenhuis, E. T., Butenschön, M., Totterdell, I. J., and Allen, J. I.: Marine regime shifts in ocean biogeochemical models: a case study in the Gulf of Alaska, Biogeosciences, 13, 4533–4553, https://doi.org/10.5194/bg-13-4533-2016, 2016. a
Bedford, J., Ostle, C., Johns, D. G., Atkinson, A., Best, M., Bresnan, E., Machairopoulou, M., Graves, C. A., Devlin, M., Milligan, A., Pitois, S., Mellor, A., Tett, P., and McQuatters-Gollop, A.: Lifeform indicators reveal large-scale shifts in plankton across the North-West European shelf, Glob. Change Biol., 26, 3482–3497, https://doi.org/10.1111/gcb.15066, 2020a. a, b, c, d, e, f, g, h
Bedford, J., Ostle, C., Johns, D. G., Budria, A., and McQuatters-Gollop, A.: The influence of temporal scale selection on pelagic habitat biodiversity indicators, Ecol. Indic., 114, 106311, https://doi.org/10.1016/j.ecolind.2020.106311, 2020b. a
Bertani, I., Primicerio, R., and Rossetti, G.: Extreme Climatic Event Triggers a Lake Regime Shift that Propagates Across Multiple Trophic Levels, Ecosystems, 19, 16–31, https://doi.org/10.1007/s10021-015-9914-5, 2016. a
Biggs, R., Peterson, G. D., and Rocha, J. C.: The Regime Shifts Database: a framework for analyzing regime shifts in social-ecological systems, Ecol. Soc., 23, https://doi.org/10.5751/ES-10264-230309, 2018. a
Bowler, C., Vardi, A., and Allen, A. E.: Oceanographic and biogeochemical insights from diatom genomes, Annu. Rev. Mar. Sci., 2, 333–365, https://doi.org/10.1146/annurev-marine-120308-081051, 2010. a, b
Capuzzo, E., Lynam, C. P., Barry, J., Stephens, D., Forster, R. M., Greenwood, N., McQuatters-Gollop, A., Silva, T., van Leeuwen, S. M., and Engelhard, G. H.: A decline in primary production in the North Sea over 25 years, associated with reductions in zooplankton abundance and fish stock recruitment, Glob. Change Biol., 24, e352–e364, https://doi.org/10.1111/gcb.13916, 2018. a, b
Curry, R., Dickson, B., and Yashayaev, I.: A change in the freshwater balance of the Atlantic Ocean over the past four decades, Nature, 426, 826–829, https://doi.org/10.1038/nature02206, 2009. a
Dakos, V., Carpenter, S., van Nes, E., and Scheffer, M.: Resilience indicators: prospects and limitations for early warnings of regime shifts, Philos. T. R. Soc. B, 370, https://doi.org/10.1098/rstb.2013.0263, 2015. a
Dees, P.: Regime shift timeseries (RST), Zenodo [code], https://doi.org/10.5281/zenodo.16363866, 2025. a, b
Dees, P., Bresnan, E., Dale, A. C., Edwards, M., Johns, D., Mouat, B., Whyte, C., and Davidson, K.: Harmful algal blooms in the Eastern North Atlantic ocean, P. Natl. Acad. Sci., 114, E9763–E9764, https://doi.org/10.1073/pnas.1715499114, 2017. a, b
Dees, P., Dale, A., Whyte, C., Mouat, B., and Davidson, K.: Operational modelling to assess advective harmful algal bloom development and its potential to impact aquaculture, Harmful Algae, 129, 1568–9883, https://doi.org/10.1016/j.hal.2023.102517, 2023. a
Di Pane, J., Wiltshire, K. H., McLean, M., Boersma, M., and Meunier, C. L.: Environmentally induced functional shifts in phytoplankton and their potential consequences for ecosystem functioning, Glob. Change Biol., 28, 2804–2819, https://doi.org/10.1111/gcb.16098, 2022. a, b
Doney, S. C., Fabry, V. J., Feely, R. A., and Kleypas, J. A.: Ocean Acidification: The Other CO2 Problem, Annu. Rev. Mar. Sci., 1, 169–192, https://doi.org/10.1146/annurev.marine.010908.163834, 2009. a
Décima, M.: Zooplankton trophic structure and ecosystem productivity, Mar. Ecol.-Prog. Ser., 692, https://doi.org/10.3354/meps14077, 2022. a
Edwards, M., Reid, P., and Planque, B.: Long-term and regional variability of phytoplankton biomass in the Northeast Atlantic (1960–1995), ICES J. Mar. Sci., 58, 39–49, https://doi.org/10.1006/jmsc.2000.0987, 2001. a, b, c
Edwards, M., Beaugrand, G., Hayes, G., Koslow, J., and Richardson, A.: Multi-decadal oceanic ecological datasets and their application in marine policy and management, Trend. Ecol. Evol., 25, 602–610, https://doi.org/10.1016/j.tree.2010.07.007, 2010. a, b
Eklöf, J. S., Sundblad, G., Erlandsson, M., Donadi, S., Hansen, J. P., Eriksson, B. K., and Bergström, U.: A spatial regime shift from predator to prey dominance in a large coastal ecosystem, Communications Biolog, 3, https://doi.org/10.1038/s42003-020-01180-0, 2020. a
Elson, P., de Andrade, E. S., Lucas, G., May, R., Hattersley, R., Campbell, E., Comer, R., Dawson, A., Little, B., Raynaud, S., scmc72, Snow, A. D., lgolston, Blay, B., Killick, P., lbdreyer, Peglar, P., Wilson, N., Andrew, Szymaniak, J., Berchet, A., Bosley, C., Davis, L., Filipe, Krasting, J., Bradbury, M., stephenworsley, and Kirkham, D.: SciTools/cartopy: REL: v0.24.1 (v0.24.1), Zenodo [code], https://doi.org/10.5281/zenodo.13905945, 2024. a
Fauchald, P., Skov, H., Skern-Mauritzen, M., Johns, D., and Tveraa, T.: Wasp-Waist Interactions in the North Sea Ecosystem, PLoS ONE, 6, https://doi.org/10.1371/journal.pone.0022729, 2011. a, b, c
Fox-Kemper, B., Hewitt, H., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S., Edwards, T., Golledge, N., Hemer, M., Kopp, R., Krinner, G., Mix, A., Notz, D., Nowicki, S., Nurhati, I., Ruiz, L., Sallée, J.-B., Slangen, A., and Yu, Y.: Ocean, Cryosphere and Sea Level Change, In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, 1211–1362, https://doi.org/10.1017/9781009157896.011, 2021. a, b
Fransz, H. G., Colebrook, J. M., Gamble, J. C., and Krause, M.: The zooplankton of the North Sea, Neth. J. Sea Res., 28, 1–52, https://doi.org/10.1016/0077-7579(91)90003-J, 1991. a, b
Groesser, S. N. and Schwaninger, M.: Contributions to model validation: hierarchy, process, and cessation, Syst. Dynam. Rev., 28, 157–181, https://doi.org/10.1002/sdr.1466, 2012. a
Hallegraeff, G. M.: Ocean Climate Change, Phytoplankton Community Responses, And Harmful Algal Blooms: A Formidable Predictive Challenge, J. Phycol., 46, 220–235, https://doi.org/10.1111/j.1529-8817.2010.00815.x, 2010. a
Hare, S. R. and Mantua, N. J.: Empirical evidence for North Pacific regime shifts in 1977 and 1989, Prog. Oceanogr., 47, 103–145, https://doi.org/10.1016/S0079-6611(00)00033-1, 2000. a, b
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río, J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant, T. E.: Array programming with NumPy, Nature, 585, 357–362, https://doi.org/10.1038/s41586-020-2649-2, 2020. a
Heinze, C., Blenckner, T., Martins, H., Rusiecka, D., Döscher, R., Gehlen, M., Gruber, N., Holland, E., Øystein Hov, Joos, F., Matthews, J. B. R., Rødven, R., and Wilson, S.: The quiet crossing of ocean tipping points, P. Natl. Acad. Sci., 118, 1–9, https://doi.org/10.1073/pnas.2008478118, 2021. a, b
Hewamalage, H., Ackermann, K., and Bergmeir, C.: Forecast evaluation for data scientists: common pitfalls and best practices, Data Min. Knowl. Disc., 788––832, https://doi.org/10.1007/s10618-022-00894-5, 2023. a
Hinder, S. L., Hays, G., Edwards, M., Roberts, E. C., Walne, A. W., and Gravenor, M. B.: Changes in marine dinoflagellate and diatom abundance under climate change, Nat. Clim. Change, 2, 271–275, https://doi.org/10.1038/nclimate1388, 2012. a
Hinder, S. L., Gravenor, M. B., Edwards, M., Ostle, C., Bodger, O. G., Lee, P. L., Walne, A. W., and Hays, G. C.: Multi-decadal range changes vs. thermal adaptation for north east Atlantic oceanic copepods in the face of climate change, Glob. Change Biol., 20, 140–146, https://doi.org/10.1111/gcb.12387, 2014. a
Hjøllo, S. S., Skogen, M. D., and Svendsen, E.: Exploring currents and heat within the North Sea using a numerical model, J. Marine Syst., 78, 180–192, https://doi.org/10.1016/j.jmarsys.2009.06.001, 2009. a, b
Ibanez, F. and Dauvin, J.-C.: Shape analysis of temporal ecological processes: long-term changes in English Channel macrobenthic communities, Coenoses, 13, 115–129, https://www.jstor.org/stable/43461224 (last access: 2 October 2025), 1998. a
IPCC: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, Cambridge University Press, Cambridge, UK and New York, NY, USA, https://doi.org/10.1017/9781009157964, 2019. a, b
Johns, D.: SEAS research dataset. Marine Biological Association of the United Kingdom, Marine Biological Association [data set], https://doi.org/10.17031/1841, 2022. a
Johnson, C., Inall, M., Gary, S., and Cunningham, S.: Significance of Climate Indices to Benthic Conditions Across the Northern North Atlantic and Adjacent Shelf Seas, Frontiers in Marine Science, 7, https://doi.org/10.3389/fmars.2020.00002, 2020. a
Kwiatkowski, L., Torres, O., Bopp, L., Aumont, O., Chamberlain, M., Christian, J. R., Dunne, J. P., Gehlen, M., Ilyina, T., John, J. G., Lenton, A., Li, H., Lovenduski, N. S., Orr, J. C., Palmieri, J., Santana-Falcón, Y., Schwinger, J., Séférian, R., Stock, C. A., Tagliabue, A., Takano, Y., Tjiputra, J., Toyama, K., Tsujino, H., Watanabe, M., Yamamoto, A., Yool, A., and Ziehn, T.: Twenty-first century ocean warming, acidification, deoxygenation, and upper-ocean nutrient and primary production decline from CMIP6 model projections, Biogeosciences, 17, 3439–3470, https://doi.org/10.5194/bg-17-3439-2020, 2020. a
Kürten, B., Painting, S. J., Struck, U., Polunin, N. V. C., and Middelburg, J. J.: Tracking seasonal changes in North Sea zooplankton trophic dynamics using stable isotopes, Biogeochemistry, 113, https://doi.org/10.1007/s10533-011-9630-y, 2013. a
Lowery, C. M., Bown, P. R., Fraass, A. J., and Hull, P. M.: Ecological response of plankton to environmental change: thresholds for extinction, Annu. Rev. Earth Planet. Sc., 48, 403–429, https://doi.org/10.1146/annurev-earth-081619-052818, 2020. a
Marques, R., Otto, S., Di Pane, J., Boersma, M., Meunier, C., Wiltshire, K. H., Möllmann, C., and Renz, J.: Response of the meso-and macro-zooplankton community to long-term environmental changes in the southern North Sea, ICES J. Mar. Sci., 81, 526–539, https://doi.org/10.1093/icesjms/fsad121, 2024. a, b, c
Mateus, M., Fernandes, J., Revilla, M., Ferrer, L., Villarreal, M. R., Miller, P., Schmidt, W., Maguire, J., Silva, A., and Pinto, L.: Early Warning Systems for Shellfish Safety: The Pivotal Role of Computational Science, in: Computational Science – ICCS 2019, edited by: Rodrigues, J. M. F., Cardoso, P. J. S., Monteiro, J., Lam, R., Krzhizhanovskaya, V. V., Lees, M. H., Dongarra, J. J., and Sloot, P. M., 361–375, Springer International Publishing, Cham, ISBN 978-3-030-22747-0, https://doi.org/10.1007/978-3-030-22747-0_28, 2019. a
McQuatters-Gollop, A., Raitsos, D. E., Edwards, M., and Attrill, M. J.: Spatial patterns of diatom and dinoflagellate seasonal cycles in the NE Atlantic Ocean, Mar. Ecol.-Prog. Ser., 339, 301–306, https://doi.org/10.3354/meps339301, 2007. a, b
Mengs, G., Stern, R. F., Clarke, J. L., Faith, M., and Medlin, L. K.: Mapping Selected Emergent Marine Toxin-Producing Organisms Using Historical Samples with Two Methods (Biosensors and Real-Time PCR): A Comparison of Resolution, Appl. Microbiol., 4, 312–328, https://doi.org/10.3390/applmicrobiol4010021, 2024. a
Meyer-Gutbrod, E. L., Greene, C. H., Davies, K. T., and Johns, D. G.: Ocean Regime Shift is Driving Collapse of the North Atlantic Right Whale Population, Oceanography, 34, 22–31, https://doi.org/10.5670/oceanog.2021.308, 2021. a
Montero, J. T., Lima, M., Estay, S. A., and Rezende, E. L.: Spatial and temporal shift in the factors affecting the population dynamics of Calanus copepods in the North Sea, Glob. Change Biol., 27, 576–586, https://doi.org/10.1111/gcb.15394, 2021. a
Nguyen, C. T.: The Limits of Data, Issues Sci. Technol., 40, 94–101, https://doi.org/10.58875/LUXD6515, 2024. a
Oliver, E. C. J., Donat, M. G., Burrows, M. T., Moore, P. J., Smale, D. A., Alexander, L. V., Benthuysen, J. A., Feng, M., Gupta, A. S., Hobday, A. J., Holbrook, N. J., Perkins-Kirkpatrick, S. E., Scannell, H. A., Straub, S. C., and Wernberg, T.: Longer and more frequent marine heatwaves over the past century, Nat. Commun., 9, 1–12, https://doi.org/10.1038/s41467-018-03732-9, 2018. a
Oliver, E. C. J., Burrows, M. T., Donat, M. G., Sen Gupta,, A., Alexander, L. V., Perkins-Kirkpatrick, S. E., Benthuysen, J. A., Hobday, A. J., Holbrook, N. J., Moore, P. J., Thomsen, M. S., Wernberg, T., and Smale, D. A.: Projected marine heatwaves in the 21st century and the potential for ecological impact, Frontiers in Marine Science, 6, 1–12, https://doi.org/10.3389/fmars.2019.00734, 2019. a
Overland, J. E., Percival, D. B., and Mofjeld, H. O.: Regime shifts and red noise in the North Pacific, Deep-Sea Res. Pt. I, 53, 582–588, https://doi.org/10.1016/j.dsr.2005.12.011, 2006. a, b
Park, M. G., Kim, S., Kim, H. S., Myung, G., Kang, Y. G., and Yih, W.: First successful culture of the marine dinoflagellate Dinophysis acuminata, Aquat. Microb. Ecol., 45, https://doi.org/10.3354/ame045101, 2006. a
Pyper, B. and Peterman, R.: Comparison of methods toaccount for autocorrelation analyses of fish data, Can. J. Fish. Aquat. Sci., 55, 2127–2140, https://doi.org/10.1139/f98-201, 1998. a
Python Software Foundation: Python Language Reference, version 3.9.12, http://www.python.org (last access: 14 March 2025), 2022. a
Reid, P., Colebrook, J., Matthews, J., Aiken, J., and Continuous Plankton Recorder Team: The continuous plankton recorder: concepts and history, from plankton indicator to undulating recorders, Prog. Oceanogr., 58, 117–173, https://doi.org/10.1016/j.pocean.2003.08.002, 2003. a, b, c, d
Reid, P. C., Hari, R. E., Beaugrand, G., Livingstone, D. M., Marty, C., Straile, D., Barichivich, J., Goberville, E., Adrian, R., Aono, Y., Brown, R., Foster, J., Groisman, P., Hélaouët, P., Hsu, H.-H., Kirby, R., Knight, J., Kraberg, A., Li, J., Lo, T.-T., Myneni, R. B., North, R. P., Pounds, J. A., Sparks, T., Stübi, R., Tian, Y., Wiltshire, K. H., Xiao, D., and Zhu, Z.: Global impacts of the 1980s regime shift, Glob. Change Biol., 22, 682–703, https://doi.org/10.1111/gcb.13106, 2016. a, b, c, d
Richardson, A., Walne, A., John, A., Jonas, T., Lindley, J., Sims, D., Stevens, D., and Witt, M.: Using continuous plankton recorder data, Prog. Oceanogr., 68, 27–74, https://doi.org/10.1016/j.pocean.2005.09.011, 2006. a, b
Robson, J., Sutton, R., and Smith, D.: Decadal predictions of the cooling and freshening of the North Atlantic in the 1960s and the role of ocean circulation, Clim. Dynam., 42, 2353–2365, https://doi.org/10.1007/s00382-014-2115-7, 2014. a
Rocha, J. C.: Ecosystems are showing symptoms of resilience loss, Environ. Res. Lett., 17, https://doi.org/10.1088/1748-9326/ac73a8, 2022. a
Schmidt, A. F. and Finan, C.: Linear regression and the normality assumption, J. Clin. Epidemiol., 98, 146–151, https://doi.org/10.1016/j.jclinepi.2017.12.006, 2018. a
Schmidtko, S., Stramma, L., and Visbeck, M.: Decline in global oceanic oxygen content during the past five decades, Nature, 542, 335–339, https://doi.org/10.1038/nature21399, 2017. a
Sguotti, C., Blöcker, A. M., Färber, L., Blanz, B., Cormier, R., Diekmann, R., Letschert, J., Rambo, H., Stollberg, N., Stelzenmüller, V., Stier, A. C., and Möllmann, C.: Irreversibility of regime shifts in the North Sea, Frontiers in Marine Science, 9, https://doi.org/10.3389/fmars.2022.945204, 2022. a, b
Sharples, J., Ross, O. N., Scott, B. E., Greenstreet, S. P., and Fraser, H.: Inter-annual variability in the timing of stratification and the spring bloom in the North-western North Sea, Cont. Shelf Res., 26, 733–751, https://doi.org/10.1016/j.csr.2006.01.011, 2006. a
Sherr, E. and Sherr, B.: Heterotrophic dinoflagellates: a significant component of microzooplankton biomass and major grazers of diatoms in the sea, Mar. Ecol.-Prog. Ser., 352, 187–197, https://doi.org/10.3354/meps07161, 2007. a
Skliris, N., Marsh, R., Josey, S. A., Good, S. A., Liu, C., and Allan, R. P.: Salinity changes in the World Ocean since 1950 in relation to changing surface freshwater fluxes, Clim. Dynam., 43, 709–736, https://doi.org/10.1007/s00382-014-2131-7, 2014. a
Strack, T., Jonkers, L., C. Rillo, M., Hillebrand, H., and Kucera, M.: Plankton response to global warming is characterized by non-uniform shifts in assemblage composition since the last ice age, Nat. Ecol. Evol., 6, 1871–1880, https://doi.org/10.1038/s41559-022-01888-8, 2022. a
The Pandas Development Team: pandas-dev/pandas: Pandas, Zenodo [code], https://doi.org/10.5281/zenodo.3509134, 2024. a
van Leeuwen, S., Tett, P., Mills, D., and van der Molen, J.: Stratified and nonstratified areas in the North Sea: Long-term variability and biological and policy implications, J. Geophys. Res.-Oceans, 120, 4670–4686, https://doi.org/10.1002/2014JC010485, 2015. a, b
Vollset, K. W., Urdal, K., Utne, K., Thorstad, E. B., Sægrov, H., Raunsgard, A., Øystein Skagseth, Lennox, R. J., Østborg, G. M., Ugedal, O., Jensen, A. J., Bolstad, G. H., and Fiske, P.: Ecological regime shift in the Northeast Atlantic Ocean revealed from the unprecedented reduction in marine growth of Atlantic salmon, Sci. Adv., 8, 1–10, https://doi.org/10.1126/sciadv.abk2542, 2022. a, b, c, d
Wells, M. L., Karlson, B., Wulff, A., Kudela, R., Trick, C., Asnaghi, V., Berdalet, E., Cochlan, W., Davidson, K., Rijcke, M. D., Dutkiewicz, S., Hallegraeff, G., Flynn, K. J., Legrand, C., Paerl, H., Silke, J., Suikkanen, S., Thompson, P., and Trainer, V. L.: Future HAB science: Directions and challenges in a changing climate, Harmful Algae, 91, 101632, https://doi.org/10.1016/j.hal.2019.101632, 2020. a
Wouters, N., Dakos, V., Edwards, M., Serafim, M., Valayer, P., and Cabral, H.: Evidencing a regime shift in the North Sea using early-warning signals as indicators of critical transitions, Estuar. Coast. Shelf S., 152, 65–72, https://doi.org/10.1016/j.ecss.2014.10.017, 2015. a, b, c
Yletyinen, J., Örjan Bodin, Weigel, B., Nordström, M. C., Bonsdorff, E., and Blenckner, T.: Regime shifts in marine communities: a complex systems perspective on food web dynamics, P. R. Soc. B, 283, https://doi.org/10.1098/rspb.2015.2569, 2016. a
Short summary
In this paper we describe a novel methodology to automate the estimation of ecological regime shift probability in a single time series. We have applied this new methodology to the continuous plankton recorder dataset in the North Sea and have shown how the model is able to estimate the likelihood of a regime shift using abundance data of multiple phytoplankton and zooplankton species.
In this paper we describe a novel methodology to automate the estimation of ecological regime...
