Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Climate change impacts the vertical structure of marine ecosystem thermal ranges

Abstract

Temperature drives global ocean patterns of biodiversity, shaping thermal niches through thresholds of thermal tolerance. Global warming is predicted to change thermal range bounds, yet research has primarily focused on temperature at the sea surface, while knowledge of changes through the depths of the water column is lacking. Here, using daily observations from ocean sites and model simulations, we track shifts in ocean temperatures, focusing on the emergence of thermal ranges whose future lower bounds exceed current upper bounds. These emerge below 50 m depth as early as ~2040 with high anthropogenic emissions, yet are delayed several decades for reduced emission scenarios. By 2100, concomitant changes in both lower and upper boundaries can expose pelagic ecosystems to thermal environments never experienced before. These results suggest the redistribution of marine species might differ across depth, highlighting a much more complex picture of the impact of climate change on marine ecosystems.

This is a preview of subscription content, access via your institution

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Overview of the OS stations.
Fig. 2: Profiles of thermal ranges.
Fig. 3: Emergence of climate change signals in thermal ranges.
Fig. 4: End-of-the-century thermal ranges.

Data availability

Interpolated data presented in the paper can be accessed via Zenodo at https://doi.org/10.5281/zenodo.6940283.

Code availability

All code used in the current study is available from the corresponding author upon reasonable request.

References

  1. Barnett, T. P. et al. Penetration of human-induced warming into the world’s oceans. Science 309, 284–287 (2005).

    Article  CAS  Google Scholar 

  2. Levitus, S. et al. Global ocean heat content 1955–2008 in light of recently revealed instrumentation problems. Geophys. Res. Lett. 36, L07608 (2009).

    Article  Google Scholar 

  3. Poloczanska, E. S. et al. Global imprint of climate change on marine life. Nat. Clim. Change 3, 919–925 (2013).

    Article  Google Scholar 

  4. García Molinos, J. et al. Climate velocity and the future global redistribution of marine biodiversity. Nat. Clim. Change 6, 83–88 (2016).

    Article  Google Scholar 

  5. Free, C. M. et al. Impacts of historical warming on marine fisheries production. Science 363, 979–983 (2019).

    Article  CAS  Google Scholar 

  6. Hughes, N. F. & Grand, T. C. Physiological ecology meets the ideal-free distribution: predicting the distribution of size-structured fish populations across temperature gradients. Environ. Biol. Fishes 59, 285–298 (2000).

    Article  Google Scholar 

  7. Tittensor, D. P. et al. Global patterns and predictors of marine biodiversity across taxa. Nature 466, 1098–1101 (2010).

    Article  CAS  Google Scholar 

  8. Sunday, J. M., Bates, A. E. & Dulvy, N. K. Global analysis of thermal tolerance and latitude in ectotherms. Proc. R. Soc. B 278, 1823–1830 (2011).

    Article  Google Scholar 

  9. Waldock, C., Stuart‐Smith, R. D., Edgar, G. J., Bird, T. J. & Bates, A. E. The shape of abundance distributions across temperature gradients in reef fishes. Ecol. Lett. 22, 685–696 (2019).

    Article  Google Scholar 

  10. Stuart-Smith, R. D., Edgar, G. J. & Bates, A. E. Thermal limits to the geographic distributions of shallow-water marine species. Nat. Ecol. Evol. 1, 1846–1852 (2017).

    Article  Google Scholar 

  11. Pinsky, M. L., Worm, B., Fogarty, M. J., Sarmiento, J. L. & Levin, S. A. Marine taxa track local climate velocities. Science 341, 1239–1242 (2013).

    Article  CAS  Google Scholar 

  12. Beaugrand, G., Edwards, M., Raybaud, V., Goberville, E. & Kirby, R. R. Future vulnerability of marine biodiversity compared with contemporary and past changes. Nat. Clim. Change 5, 695–701 (2015).

    Article  Google Scholar 

  13. Trisos, C. H., Merow, C. & Pigot, A. L. The projected timing of abrupt ecological disruption from climate change. Nature 580, 496–501 (2020).

    Article  CAS  Google Scholar 

  14. Levin, L. A. & Le Bris, N. The deep ocean under climate change. Science 350, 766–768 (2015).

    Article  CAS  Google Scholar 

  15. Deutsch, C. A. et al. Impacts of climate warming on terrestrial ectotherms across latitude. Proc. Natl Acad. Sci. USA 105, 6668–6672 (2008).

    Article  CAS  Google Scholar 

  16. Sunday, J. M., Bates, A. E. & Dulvy, N. K. Thermal tolerance and the global redistribution of animals. Nat. Clim. Change 2, 686–690 (2012).

    Article  Google Scholar 

  17. Radeloff, V. C. et al. The rise of novelty in ecosystems. Ecol. Appl. 25, 2051–2068 (2015).

    Article  Google Scholar 

  18. Lotterhos, K. E., Láruson, Á. J. & Jiang, L.-Q. Novel and disappearing climates in the global surface ocean from 1800 to 2100. Sci. Rep. 11, 15535 (2021).

    Article  CAS  Google Scholar 

  19. Mora, C. et al. The projected timing of climate departure from recent variability. Nature 502, 183–187 (2013).

    Article  CAS  Google Scholar 

  20. Henson, S. A. et al. Rapid emergence of climate change in environmental drivers of marine ecosystems. Nat. Commun. 8, 14682 (2017).

    Article  Google Scholar 

  21. Séférian, R. et al. Evaluation of CNRM Earth System Model, CNRM‐ESM2‐1: role of Earth system processes in present‐day and future climate. J. Adv. Model. Earth Syst. 11, 4182–4227 (2019).

    Article  Google Scholar 

  22. Gidden, M. J. et al. Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century. Geosci. Model Dev. 12, 1443–1475 (2019).

    Article  CAS  Google Scholar 

  23. Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9, 1937–1958 (2016).

    Article  Google Scholar 

  24. Beszczynska-Möller, A., Fahrbach, E., Schauer, U. & Hansen, E. Variability in Atlantic water temperature and transport at the entrance to the Arctic Ocean, 1997–2010. ICES J. Mar. Sci. 69, 852–863 (2012).

    Article  Google Scholar 

  25. Sutton, T. T. Vertical ecology of the pelagic ocean: classical patterns and new perspectives. J. Fish. Biol. 83, 1508–1527 (2013).

    Article  CAS  Google Scholar 

  26. Richter, I. Climate model biases in the eastern tropical oceans: causes, impacts and ways forward. WIREs Clim. Change 6, 345–358 (2015).

    Article  Google Scholar 

  27. Pozo Buil, M. et al. A dynamically downscaled ensemble of future projections for the California Current System. Front. Mar. Sci. 8, 612874 (2021).

    Article  Google Scholar 

  28. Leonard, M. et al. A compound event framework for understanding extreme impacts. WIREs Clim. Change 5, 113–128 (2014).

    Article  Google Scholar 

  29. Kwiatkowski, L. et al. Twenty-first century ocean warming, acidification, deoxygenation, and upper-ocean nutrient and primary production decline from CMIP6 model projections. Biogeosciences 17, 3439–3470 (2020).

    Article  CAS  Google Scholar 

  30. Bopp, L. et al. Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models. Biogeosciences 10, 6225–6245 (2013).

    Article  Google Scholar 

  31. Cheng, L., Abraham, J., Hausfather, Z. & Trenberth, K. E. How fast are the oceans warming? Science 363, 128–129 (2019).

    Article  CAS  Google Scholar 

  32. Hawkins, E. & Sutton, R. Time of emergence of climate signals. Geophys. Res. Lett. 39, L01702 (2012).

    Article  Google Scholar 

  33. Stuart-Smith, R. D., Edgar, G. J., Barrett, N. S., Kininmonth, S. J. & Bates, A. E. Thermal biases and vulnerability to warming in the world’s marine fauna. Nature 528, 88–92 (2015).

    Article  CAS  Google Scholar 

  34. Filbee-Dexter, K. et al. Marine heatwaves and the collapse of marginal North Atlantic kelp forests. Sci. Rep. 10, 13388 (2020).

    Article  CAS  Google Scholar 

  35. Román-Palacios, C. & Wiens, J. J. Recent responses to climate change reveal the drivers of species extinction and survival. Proc. Natl Acad. Sci. USA 117, 4211–4217 (2020).

    Article  Google Scholar 

  36. Silvy, Y., Guilyardi, E., Sallée, J.-B. & Durack, P. J. Human-induced changes to the global ocean water masses and their time of emergence. Nat. Clim. Change 10, 1030–1036 (2020).

    Article  CAS  Google Scholar 

  37. Cheng, L., Zheng, F. & Zhu, J. Distinctive ocean interior changes during the recent warming slowdown. Sci. Rep. 5, 14346 (2015).

    Article  CAS  Google Scholar 

  38. Brito-Morales, I. et al. Climate velocity reveals increasing exposure of deep-ocean biodiversity to future warming. Nat. Clim. Change 10, 576–581 (2020).

    Article  CAS  Google Scholar 

  39. Frölicher, T. L. & Laufkötter, C. Emerging risks from marine heat waves. Nat. Commun. 9, 650 (2018).

    Article  Google Scholar 

  40. Oliver, E. C. J. et al. Marine Heatwaves. Ann. Rev. Mar. Sci. 13, 313–342 (2021).

    Article  Google Scholar 

  41. Perry, A. L., Low, P. J., Ellis, J. R. & Reynolds, J. D. Climate change and distribution shifts in marine fishes. Science 308, 1912–1915 (2005).

    Article  CAS  Google Scholar 

  42. 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).

    Article  CAS  Google Scholar 

  43. Burrows, M. T. et al. Ocean community warming responses explained by thermal affinities and temperature gradients. Nat. Clim. Change 9, 959–963 (2019).

    Article  Google Scholar 

  44. IPCC Climate Change 2022: Impacts, Adaptation, and Vulnerability (eds Pörtner, H.-O. et al.) (Cambridge Univ. Press, 2022).

  45. Cahill, A. E. et al. How does climate change cause extinction? Proc. R. Soc. B280, 20121890 (2013).

    Article  Google Scholar 

  46. Hastings, R. A. et al. Climate change drives poleward increases and equatorward declines in marine species. Curr. Biol. 30, 1572–1577.e2 (2020).

    Article  CAS  Google Scholar 

  47. Jorda, G. et al. Ocean warming compresses the three-dimensional habitat of marine life. Nat. Ecol. Evol. 4, 109–114 (2020).

    Article  Google Scholar 

  48. Dulvy, N. K. et al. Climate change and deepening of the North Sea fish assemblage: a biotic indicator of warming seas. J. Appl. Ecol. 45, 1029–1039 (2008).

    Article  Google Scholar 

  49. Thatje, S. Climate warming affects the depth distribution of marine ectotherms. Mar. Ecol. Prog. Ser. 660, 233–240 (2021).

    Article  Google Scholar 

  50. Manuel, S. A., Coates, K. A., Kenworthy, W. J. & Fourqurean, J. W. Tropical species at the northern limit of their range: composition and distribution in Bermuda’s benthic habitats in relation to depth and light availability. Mar. Environ. Res. 89, 63–75 (2013).

    Article  CAS  Google Scholar 

  51. Peck, L. S., Webb, K. E. & Bailey, D. M. Extreme sensitivity of biological function to temperature in Antarctic marine species. Funct. Ecol. 18, 625–630 (2004).

    Article  Google Scholar 

  52. Peck, L. S., Morley, S. A., Richard, J. & Clark, M. S. Acclimation and thermal tolerance in Antarctic marine ectotherms. J. Exp. Biol. 217, 16–22 (2014).

    Article  Google Scholar 

  53. Walsh, J. E. Climate of the Arctic marine environment. Ecol. Appl. 18, S3–S22 (2008).

    Article  Google Scholar 

  54. Storch, D., Menzel, L., Frickenhaus, S. & Pörtner, H.-O. Climate sensitivity across marine domains of life: limits to evolutionary adaptation shape species interactions. Glob. Change Biol. 20, 3059–3067 (2014).

    Article  Google Scholar 

  55. Araújo, M. B. et al. Heat freezes niche evolution. Ecol. Lett. 16, 1206–1219 (2013).

    Article  Google Scholar 

  56. Pörtner, H. O., Peck, L. & Somero, G. Thermal limits and adaptation in marine Antarctic ectotherms: an integrative view. Philos. Trans. R. Soc. B 362, 2233–2258 (2007).

    Article  Google Scholar 

  57. Qu, Y.-F. & Wiens, J. J. Higher temperatures lower rates of physiological and niche evolution. Proc. R. Soc. B 287, 20200823 (2020).

    Article  Google Scholar 

  58. Cohen, D.M., Inada, T., Iwamoto, T. and Scialabba, N. FAO Species Catalogue, Vol. 10. Gadiform Fishes of the World (Order Gadiformes) (FAO, 1990).

  59. Strand, E. & Huse, G. Vertical migration in adult Atlantic cod (Gadus morhua). Can. J. Fish. Aquat. Sci. 64, 1747–1760 (2007).

    Article  Google Scholar 

  60. Frölicher, T. L., Fischer, E. M. & Gruber, N. Marine heatwaves under global warming. Nature 560, 360–364 (2018).

    Article  Google Scholar 

  61. Wernberg, T. et al. Climate-driven regime shift of a temperate marine ecosystem. Science 353, 169–172 (2016).

    Article  CAS  Google Scholar 

  62. Smale, D. A. et al. Marine heatwaves threaten global biodiversity and the provision of ecosystem services. Nat. Clim. Change 9, 306–312 (2019).

    Article  Google Scholar 

  63. Cheung, W. W. L. & Frölicher, T. L. Marine heatwaves exacerbate climate change impacts for fisheries in the northeast Pacific. Sci. Rep. 10, 6678 (2020).

    Article  CAS  Google Scholar 

  64. Brierley, A. S. & Kingsford, M. J. Impacts of climate change on marine organisms and ecosystems. Curr. Biol. 19, R602–R614 (2009).

    Article  CAS  Google Scholar 

  65. Bijma, J., Pörtner, H.-O., Yesson, C. & Rogers, A. D. Climate change and the oceans—what does the future hold? Mar. Pollut. Bull. 74, 495–505 (2013).

    Article  CAS  Google Scholar 

  66. Jackson, J. B. C. et al. Historical overfishing and the recent collapse of coastal ecosystems. Science 293, 629–637 (2001).

    Article  CAS  Google Scholar 

  67. Duarte, C. M. et al. The soundscape of the Anthropocene ocean. Science 371, eaba4658 (2021).

    Article  CAS  Google Scholar 

  68. Rochman, C. M. & Hoellein, T. The global odyssey of plastic pollution. Science 368, 1184–1185 (2020).

    Article  CAS  Google Scholar 

  69. Gruber, N., Boyd, P. W., Frölicher, T. L. & Vogt, M. Biogeochemical extremes and compound events in the ocean. Nature 600, 395–407 (2021).

    Article  CAS  Google Scholar 

  70. Madec, G. et al. NEMO ocean engine. Zenodo https://www.earth-prints.org/handle/2122/13309 (2017).

  71. Mathiot, P., Jenkins, A., Harris, C. & Madec, G. Explicit representation and parametrised impacts of under ice shelf seas in the z- coordinate ocean model NEMO 3.6. Geosci. Model Dev. 10, 2849–2874 (2017).

    Article  Google Scholar 

  72. Dai, A. & Bloecker, C. E. Impacts of internal variability on temperature and precipitation trends in large ensemble simulations by two climate models. Clim. Dyn. 52, 289–306 (2019).

    Article  Google Scholar 

  73. Deser, C., Phillips, A., Bourdette, V. & Teng, H. Uncertainty in climate change projections: the role of internal variability. Clim. Dyn. 38, 527–546 (2012).

    Article  Google Scholar 

  74. Middag, R. et al. Intercomparison of dissolved trace elements at the Bermuda Atlantic Time Series station. Mar. Chem. 177, 476–489 (2015).

    Article  CAS  Google Scholar 

  75. Welch, B. L. The generalization of Student’s’ problem when several different population variances are involved. Biometrika 34, 28 (1947).

    CAS  Google Scholar 

  76. Lenoir, J. et al. Species better track climate warming in the oceans than on land. Nat. Ecol. Evol. 4, 1044–1059 (2020).

    Article  Google Scholar 

  77. Janzen, D. H. Why mountain passes are higher in the Tropics. Am. Nat. 101, 233–249 (1967).

    Article  Google Scholar 

  78. Seebacher, F., White, C. R. & Franklin, C. E. Physiological plasticity increases resilience of ectothermic animals to climate change. Nat. Clim. Change 5, 61–66 (2015).

    Article  Google Scholar 

  79. Hoffmann, A. A. & Sgrò, C. M. Climate change and evolutionary adaptation. Nature 470, 479–485 (2011).

    Article  CAS  Google Scholar 

  80. Sandblom, E. et al. Physiological constraints to climate warming in fish follow principles of plastic floors and concrete ceilings. Nat. Commun. 7, 11447 (2016).

    Article  CAS  Google Scholar 

  81. Tewksbury, J. J., Huey, R. B. & Deutsch, C. A. Putting the heat on tropical animals. Science 320, 1296–1297 (2008).

    Article  CAS  Google Scholar 

  82. Dahlke, F. T., Wohlrab, S., Butzin, M. & Pörtner, H.-O. Thermal bottlenecks in the life cycle define climate vulnerability of fish. Science 369, 65–70 (2020).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by the European Union’s Horizon 2020 research and innovation programme with the TRIATLAS project under the grant agreement number 817578 (Y.S.-F. and R.S.), the COMFORT project under the grant agreement number 820989 (Y.S.-F. and R.S.) and the ESM2025 project under the grant agreement number 101003536 (R.S.). The work reflects only the authors’ view; the European Commission and their executive agency are not responsible for any use that may be made of the information the work contains. We thank L. Kwiatkowski, S. Berthet and E. Sánchez for comments on pre-submission drafts of the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

Y.S.-F. and R.S. conceived the study, developed the datasets, performed the computations and wrote the manuscript.

Corresponding author

Correspondence to Yeray Santana-Falcón.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Climate Change thanks the anonymous, reviewers for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Observed and simulated daily temperature across the six stations.

Depth-time plots of daily ocean temperature anomalies from the surface to 1000 m. Anomalies are computed for the full observational records by removing the daily climatological temperature to daily temperature. They are indicated for both observations and CNRM-ESM2-1. The observational mask in space and time is applied to model data. Red/blue colours indicate warmer/cooler daily temperature variations with respect to the daily climatological temperature. Profiles of the full observational period are given for both observations (orange) and the model ensemble mean (black). Fifteen model ensemble members are also included (grey). Blank space indicates lack of observational data.

Extended Data Fig. 2 Thermal range developments in response to climate change.

Schematics of possible developments of thermal ranges as a consequence of concomitant changes in their lower (Tmin) and upper (Tmax) bounds in response to climate change. Both changes that reduce or increase the upper or lower limit, or changes in both, will perturb the thermal range. These changes can either expand, contract, or shift it toward cooling or warming, possibly leading to a redistribution or collapse of the original marine habitat. Colour code refers to those shown in Fig. 4.

Extended Data Fig. 3 Profiles of thermal range boundaries and detected trends at each station.

Profiles of lower and upper boundaries of the thermal range are presented with anomalies of Tmin (bluish colours) and Tmax (reddish colours) relative to temperature mean over the period of available observations as simulated by CNRM-ESM2-1, respectively. Dashed lines demarcate the upper epipelagic, lower epipelagic and mesopelagic layers. Within these layers, numbers indicate mean trends per decade as derived from observations (grey) and as simulated by the model (black). Only significant trends with respect to internal climate variability are shown. Positive (negative) values indicate warming (cooling) trends.

Extended Data Fig. 4 Probability density function (pdf) of trends for Tmin (a) and Tmax (b) over the observational period for each station.

Trends are estimated from a 100 randomly selected observational period-long time series of the piControl simulation. The pdf over upper epipelagic, lower epipelagic and mesopelagic layers are displayed in blue. Trends derived from observations (orange) and simulated by the model (black) during the observational period are given with vertical lines. Empirical p-value as derived from the comparison of the observed and modelled trends against the distribution of the piControl trends are presented in Supplementary Table 3.

Extended Data Fig. 5 Examples of Tmin- and Tmax-based ToE computations at the station HOT-01.

(a) Examples of the computation of the timing for which future Tmin will be warmer than the current Tmidpoint. At each depth level, ToE is considered as the year at which a spline for the simulation (1990 to 2100) time series of Tmin surpasses the mean of a spline ± climate variability for the current period (1990 to 2020) Tmidpoint. SSP5-8.5 is considered in this example. Climate variability is considered as the 5th and 95th percentiles of a 100 randomly selected 30 years period time series of Tmidpoint as simulated by fifteen samples of the piControl simulation. (b) Examples of the computation of the timing for which future Tmin will be warmer than the current Tmax. At each depth level, ToE is considered as the year at which a spline for the simulation (1990 to 2100) time series of Tmin surpasses the mean of a spline ± climate variability for the current period (1990 to 2020) Tmax. SSP5-8.5 is considered in this example. Climate variability is considered as the 5th and 95th percentiles of a 100 randomly selected 30 years period time series of Tmax as simulated by fifteen samples of the piControl simulation. (c) Examples of the computation of the timing for which future Tmax emerges from current natural variability. At each depth level, ToE is considered as the year at which a spline for the simulation (1990 to 2100) time series of Tmax surpasses the mean of a spline + climate variability for the current period (1990 to 2020) Tmax. SSP5-8.5 is considered in this example. Climate variability is considered as twice the standard deviation of a 100 randomly selected 30 years period time series of Tmax as simulated by fifteen samples of the piControl simulation.

Extended Data Fig. 6 End-of-the-century thermal ranges resulting from concomitant changes in their lower and upper bounds in response to climate change considering SSP5-8.5.

Profiles illustrate temperature anomalies for Tmin and Tmax with respect to the mean over last years of the historical simulation (1990 to 2014) for the historical (1990 to 2014) and end-of-the-century (2080 to 2100) periods. Reddish (bluish) shading areas indicate ocean layers where end-of-the-century Tmin and Tmax are warmer (cooler) than the historical counterparts. Numbers indicate their anomalies (in °C). Climate Novelty profiles are given in the right-hand sided boxes. Dashed lines demarcate the upper epipelagic, lower epipelagic and mesopelagic layers.

Extended Data Fig. 7 End-of-the-century number of days and intensity of marine heatwaves (MHWs) anomalies with respect to historical period.

MHWs anomalies are computed as the difference between the end-of-the-century (2080 to 2100) and the historical period (1990 to 2014) number of days (a) and maximum intensity (b). Differences are given for upper epipelagic, lower epipelagic and mesopelagic waters. High (SSP5-8.5), moderate (SSP2-4.5), and low (SSP1-2.6) emission scenarios are displayed.

Extended Data Fig. 8 End-of-the-century thermal ranges resulting from concomitant changes in their lower and upper bounds in response to climate change considering SSP2-4.5.

Profiles illustrate temperature anomalies for Tmin and Tmax with respect to the mean over last years of the historical simulation (1990 to 2014) for the historical (1990 to 2014) and end-of-the-century (2080 to 2100) periods. Reddish (bluish) shading areas indicate ocean layers where end-of-the-century Tmin and Tmax are warmer (cooler) than the historical counterparts. Numbers indicate their anomalies (in °C). Climate Novelty profiles are given in the right-hand sided boxes. Dashed lines demarcate the upper epipelagic, lower epipelagic and mesopelagic layers.

Extended Data Fig. 9 End-of-the-century thermal ranges resulting from concomitant changes in their lower and upper bounds in response to climate change considering SSP1-2.6.

Profiles illustrate temperature anomalies for Tmin and Tmax with respect to the mean over last years of the historical simulation (1990 to 2014) for the historical (1990 to 2014) and end-of-the-century (2080 to 2100) periods. Reddish (bluish) shading areas indicate ocean layers where end-of-the-century Tmin and Tmax are warmer (cooler) than the historical counterparts. Numbers indicate their anomalies (in °C). Climate Novelty profiles are given in the right-hand sided boxes. Dashed lines demarcate the upper epipelagic, lower epipelagic and mesopelagic layers.

Extended Data Fig. 10 Maps of the changes in thermal ranges at the end of the century resulting from concomitant changes in both lower and upper boundaries.

These maps provide a geographical representation of the right hand sided boxes as shown in Fig. 4 for the high (SSP5-8.5), moderate (SSP2-4.5), and low (SSP1-2.6) emission scenarios. Changes in thermal ranges are averaged for the upper epipelagic, lower epipelagic, and mesopelagic layers, consistently with Fig. 4.

Supplementary information

Supplementary Information

Supplementary Discussion, Figs. 1–7 and Tables 1–3.

Reporting Summary

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Santana-Falcón, Y., Séférian, R. Climate change impacts the vertical structure of marine ecosystem thermal ranges. Nat. Clim. Chang. 12, 935–942 (2022). https://doi.org/10.1038/s41558-022-01476-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41558-022-01476-5

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing