Circumpolar projections of Antarctic krill growth potential


Antarctic krill is a key species of important Southern Ocean food webs, yet how changes in ocean temperature and primary production may impact their habitat quality remains poorly understood. We provide a circumpolar assessment of the robustness of krill growth habitat to climate change by coupling an empirical krill growth model with projections from a weighted subset of IPCC Earth system models. We find that 85% of the study area experienced only a moderate change in relative gross growth potential (± 20%) by 2100. However, a temporal shift in seasonal timings of habitat quality may cause disjunctions between krill’s biological timings and the future environment. Regions likely to experience habitat quality decline or retreat are concentrated near the northern limits of krill distribution and in the Amundsen–Bellingshausen seas region during autumn, meaning habitat will likely shift to higher latitudes in these areas.

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Fig. 1: Taylor diagram assessing individual model performance in projecting growth potential against observation-based values for selection and weighting scheme.
Fig. 2: Changes in future environmental drivers projected by the weighted subset for RCP scenarios 4.5 and 8.5.
Fig. 3: Evaluating the performance of the weighted subset.
Fig. 4: The projected change in krill growth potential between each RCP scenario and the historical scenario.
Fig. 5: The projected RGGP in CCAMLR management areas.

Data availability

The data that support the findings of this study are publicly available at the Australian Antarctic Data Centre, (ref. 85). The CMIP5 output is available from the Earth System Grid Federation ( In addition to being retrievable using the raadtools package in R (, the satellite data can be found at for sea surface temperature, for SeaWiFS75 chlorophyll a and for the Johnson et al.76 chlorophyll a data.

Code availability

The code relating to this study is available from the corresponding author on request.


  1. 1.

    Murphy, E. J. et al. Climatically driven fluctuations in Southern Ocean ecosystems. Proc. R. Soc. Lond. B 274, 3057–3067 (2017).

  2. 2.

    Murphy, E. J. et al. Understanding the structure and functioning of polar pelagic ecosystems to predict the impacts of change. Proc. R. Soc. Lond. B 283, 20161646 (2016).

  3. 3.

    Schmidt, K. et al. Seabed foraging by Antarctic krill: implications for stock assessment, bentho‐pelagic coupling, and the vertical transfer of iron. Limnol. Oceanogr. 56, 1411–1428 (2011).

    CAS  Article  Google Scholar 

  4. 4.

    Trathan, P. N. & Hill, S. L. in Biology and Ecology of Antarctic Krill (ed. Volker, S.) 321–350 (Springer, 2016).

  5. 5.

    Nicol, S., Foster, J. & Kawaguchi, S. The fishery for Antarctic krill—recent developments. Fish Fish. 13, 30–40 (2011).

    Article  Google Scholar 

  6. 6.

    Nicol, S. & Foster, J. in Biology and Ecology of Antarctic Krill (ed. Volker, S.) 387–421 (Springer, 2016).

  7. 7.

    Flores, H. et al. Impact of climate change on Antarctic krill. Mar. Ecol. Prog. Ser. 458, 1–19 (2012).

    Article  Google Scholar 

  8. 8.

    McBride, M. M. et al. Krill, climate, and contrasting future scenarios for Arctic and Antarctic fisheries. ICES J. Mar. Sci. 71, 1934–1955 (2014).

    Article  Google Scholar 

  9. 9.

    Constable, A. J. et al. Climate change and Southern Ocean ecosystems I: how changes in physical habitats directly affect marine biota. Glob. Change Biol. 20, 3004–3025 (2014).

    Article  Google Scholar 

  10. 10.

    Hill, S. L., Phillips, T. & Atkinson, A. Potential climate change effects on the habitat of Antarctic krill in the Weddell quadrant of the Southern Ocean. PLoS ONE 8, e72246 (2013).

    CAS  Article  Google Scholar 

  11. 11.

    Murphy, E. J. et al. Restricted regions of enhanced growth of Antarctic krill in the circumpolar Southern Ocean. Sci. Rep. 7, 6963 (2017).

    Article  CAS  Google Scholar 

  12. 12.

    Vaughan, D. G. et al. Recent rapid regional climate warming on the Antarctic Peninsula. Climatic Change 60, 243–274 (2003).

    Article  Google Scholar 

  13. 13.

    Meredith, M. et al. in IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (eds Pörtner, H.-O. et al.) Ch. 3 (2019).

  14. 14.

    Atkinson, A., Siegel, V., Pakhomov, E. & Rothery, P. Long-term decline in krill stock and increase in salps within the Southern Ocean. Nature 432, 100–103 (2004).

    CAS  Article  Google Scholar 

  15. 15.

    Loeb, V. J. & Santora, J. A. Climate variability and spatiotemporal dynamics of five Southern Ocean krill species. Prog. Oceanogr. 134, 93–122 (2015).

    Article  Google Scholar 

  16. 16.

    Cox, M. J. et al. No evidence for a decline in the density of Antarctic krill Euphausia superba Dana, 1850, in the Southwest Atlantic sector between 1976 and 2016. J. Crust. Biol. 38, 656–661 (2018).

  17. 17.

    Atkinson, A. et al. Krill (Euphausia superba) distribution contracts southward during rapid regional warming. Nat. Clim. Change 9, 142–147 (2019).

  18. 18.

    Hill, S. L., Atkinson, A., Pakhomov, E. A. & Siegel, V. Evidence for a decline in the population density of Antarctic krill Euphausia superba Dana, 1850 still stands. A comment on Cox et al. J. Crust. Biol. 39, 316–322 (2019).

    Article  Google Scholar 

  19. 19.

    Ross, R. M., Quetin, L. B., Baker, K. S., Vernet, M. & Smith, R. C. Growth limitation in young Euphausia superba under field conditions. Limnol. Oceanogr. 45, 31–43 (2000).

    Article  Google Scholar 

  20. 20.

    Kawaguchi, S., Candy, S. G., King, R., Naganobu, M. & Nicol, S. Modelling growth of Antarctic krill. I. Growth trends with sex, length, season, and region. Mar. Ecol. Prog. Ser. 306, 1–15 (2006).

    Article  Google Scholar 

  21. 21.

    Atkinson, A. et al. Natural growth rates in Antarctic krill (Euphausia superba): II. Predictive models based on food, temperature, body length, sex, and maturity stage. Limnol. Oceanogr. 51, 973–987 (2006).

    Article  Google Scholar 

  22. 22.

    Flato, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 741–866 (Cambridge Univ. Press, 2013).

  23. 23.

    Stock, C. A. et al. On the use of IPCC-class models to assess the impact of climate on Living Marine Resources. Prog. Oceanogr. 88, 1–27 (2011).

  24. 24.

    Flato, G. M. Earth system models: an overview. WIREs Clim. Change 2, 783–800 (2011).

    Article  Google Scholar 

  25. 25.

    Piñones, A. & Fedorov, A. V. Projected changes of Antarctic krill habitat by the end of the 21st century. Geophys. Res. Lett. 43, 8580–8589 (2016).

    Article  Google Scholar 

  26. 26.

    Leung, S., Cabré, A. & Marinov, I. A latitudinally banded phytoplankton response to 21st century climate change in the Southern Ocean across the CMIP5 model suite. Biogeosciences 12, 5715–5734 (2015).

  27. 27.

    Groeneveld, J. et al. How biological clocks and changing environmental conditions determine local population growth and species distribution in Antarctic krill (Euphausia superba): a conceptual model. Ecol. Model. 303, 78–86 (2015).

    Article  Google Scholar 

  28. 28.

    Höring, F., Teschke, M., Suberg, L., Kawaguchi, S. & Meyer, B. Light regime affects the seasonal cycle of Antarctic krill (Euphausia superba): impacts on growth, feeding, lipid metabolism, and maturity. Can. J. Zool. 96, 1203–1213 (2018).

  29. 29.

    Piccolin, F. et al. The seasonal metabolic activity cycle of Antarctic krill (Euphausia superba): evidence for a role of photoperiod in the regulation of endogenous rhythmicity. Front. Physiol. 9, 1715 (2018).

  30. 30.

    Quetin, L. B., Ross, R. M., Fritsen, C. H. & Vernet, M. Ecological responses of Antarctic krill to environmental variability: can we predict the future? Antarct. Sci. 19, 253–266 (2007).

    Article  Google Scholar 

  31. 31.

    Atkinson, A. et al. Oceanic circumpolar habitats of Antarctic krill. Mar. Ecol. Prog. Ser. 362, 1–23 (2008).

    CAS  Article  Google Scholar 

  32. 32.

    Atkinson, A., Siegel, V., Pakhomov, E., Jessopp, M. & Loeb, V. A re-appraisal of the total biomass and annual production of Antarctic krill. Deep Sea Res. Part I 56, 727–740 (2009).

    Article  Google Scholar 

  33. 33.

    Cavanagh, R. D. et al. A synergistic approach for evaluating climate model output for ecological applications. Front. Mar. Sci. 4, 308 (2017).

    Article  Google Scholar 

  34. 34.

    Turner, J., Bracegirdle, T. J., Phillips, T., Marshall, G. J. & Hosking, J. S. An initial assessment of Antarctic sea ice extent in the CMIP5 models. J. Clim. 26, 1473–1484 (2013).

    Article  Google Scholar 

  35. 35.

    Siegel, V. & Watkins, J. L. in Biology and Ecology of Antarctic Krill (ed. Siegel, V.) 21–100 (Springer, 2016).

  36. 36.

    Meyer, B. & Teschke, M. in Biology and Ecology of Antarctic Krill (ed. Siegel, V.) 145–174 (Springer, 2016).

  37. 37.

    Perry, F. A. et al. Habitat partitioning in Antarctic krill: spawning hotspots and nursery areas. PLoS ONE 14, e0219325 (2019).

    CAS  Article  Google Scholar 

  38. 38.

    Kawaguchi, S. in Biology and Ecology of Antarctic Krill (ed. Siegel, V.) 225–246 (Springer, 2016).

  39. 39.

    Tarling, G. et al. Recruitment of Antarctic krill Euphausia superba in the South Georgia region: adult fecundity and the fate of larvae. Mar. Ecol. Prog. Ser. 331, 161–179 (2007).

    Article  Google Scholar 

  40. 40.

    Thompson, A. F., Stewart, A. L., Spence, P. & Heywood, K. J. The Antarctic Slope Current in a changing climate. Rev. Geophys. 56, 741–770 (2018).

    Article  Google Scholar 

  41. 41.

    Meijers, A. J. et al. Representation of the Antarctic Circumpolar Current in the CMIP5 climate models and future changes under warming scenarios. J. Geophys. Res. Oceans 117, C12008 (2012).

    Article  Google Scholar 

  42. 42.

    Heuzé, C., Heywood, K. J., Stevens, D. P. & Ridley, J. K. Southern Ocean bottom water characteristics in CMIP5 models. Geophys. Res. Lett. 40, 1409–1414 (2013).

  43. 43.

    Heywood, K. J. et al. Ocean processes at the Antarctic continental slope. Phil. Trans. A 372, 20130047 (2014).

  44. 44.

    Quetin, L. B. & Ross, R. M. Episodic recruitment in Antarctic krill Euphausia superba in the Palmer LTER study region. Mar. Ecol. Prog. Ser. 259, 185–200 (2003).

    Article  Google Scholar 

  45. 45.

    Saba, G. K. et al. Winter and spring controls on the summer food web of the coastal West Antarctic Peninsula. Nat. Commun. 5, 4318 (2014).

    CAS  Article  Google Scholar 

  46. 46.

    Turner, J. et al. Antarctic climate change and the environment: an update. Polar Rec. 50, 237–259 (2013).

    Article  Google Scholar 

  47. 47.

    Cai, W. et al. Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Clim. Change 4, 111–116 (2014).

    CAS  Article  Google Scholar 

  48. 48.

    Murphy, E. J., Clarke, A., Abram, N. J. & Turner, J. Variability of sea-ice in the northern Weddell Sea during the 20th century. J. Geophys. Res. Oceans 119, 4549–4572 (2014).

  49. 49.

    Report of the Thirty-seventh Meeting of the Scientific Committee (CCAMLR, 2018).

  50. 50.

    Krill Fishery Report 2018 (CCAMLR, 2018).

  51. 51.

    Reisinger, R. R. et al. Habitat modelling of tracking data from multiple marine predators identifies important areas in the Southern Indian Ocean. Divers. Distrib. 24, 535–550 (2018).

    Article  Google Scholar 

  52. 52.

    Hindell, M. A. et al. in The Kerguelen Plateau: Marine Ecosystem and Fisheries (eds Duhamel, G. & Welsford, D.) 203–215 (Societe Francaise d’Ichtyologie, 2011).

  53. 53.

    Croxall, J. P., Reid, K. & Prince, P. A. Diet, provisioning and productivity responses of marine predators to differences in availability of Antarctic krill. Mar. Ecol. Prog. Ser. 177, 115–131 (1999).

  54. 54.

    Goedegebuure, M. Improving Representations of Higher Trophic-Level Species in Models: Using Individual-Based Modelling and Dynamic Energy Budget Theory to Project Population Trajectories of Southern Elephant Seals. PhD thesis, University of Tasmania (2018).

  55. 55.

    Murphy, E. et al. Spatial and temporal operation of the Scotia Sea ecosystem: a review of large-scale links in a krill centred food web. Phil. Trans. R. Soc. Lond. B 362, 113–148 (2007).

    CAS  Article  Google Scholar 

  56. 56.

    Constable, A. J. & Kawaguchi, S. Modelling growth and reproduction of Antarctic krill, Euphausia superba, based on temperature, food and resource allocation amongst life history functions. ICES J. Mar. Sci. 75, 738–750 (2017).

    Article  Google Scholar 

  57. 57.

    Nicol, S. Krill, currents, and sea ice: Euphausia superba and its changing environment. Bioscience 56, 111–120 (2006).

    Article  Google Scholar 

  58. 58.

    Thorpe, S. E., Tarling, G. A. & Murphy, E. J. Circumpolar patterns in Antarctic krill larval recruitment: an environmentally driven model. Mar. Ecol. Prog. Ser. 613, 77–96 (2019).

  59. 59.

    Siegel, V. & Loeb, V. Recruitment of Antarctic krill Euphausia superba and possible causes for its variability. Mar. Ecol. Prog. Ser. 123, 45–56 (1995).

    Article  Google Scholar 

  60. 60.

    Lowe, A. T., Ross, R. M., Quetin, L. B., Vernet, M. & Fritsen, C. H. Simulating larval Antarctic krill growth and condition factor during fall and winter in response to environmental variability. Mar. Ecol. Prog. Ser. 452, 27–43 (2012).

    Article  Google Scholar 

  61. 61.

    Yoshida, T. et al. Structural changes in the digestive glands of larval Antarctic krill (Euphausia superba) during starvation. Polar Biol. 32, 503–507 (2009).

    Article  Google Scholar 

  62. 62.

    Meyer, B. et al. The winter pack-ice zone provides a sheltered but food-poor habitat for larval Antarctic krill. Nat. Ecol. Evol. 1, 1853–1861 (2017).

    Article  Google Scholar 

  63. 63.

    Meyer, B. et al. Physiology, growth, and development of larval krill Euphausia superba in autumn and winter in the Lazarev Sea, Antarctica. Limnol. Oceanogr. 54, 1595–1614 (2009).

    CAS  Article  Google Scholar 

  64. 64.

    Kohlbach, D. et al. Ice algae-produced carbon is critical for overwintering of Antarctic krill Euphausia superba. Front. Mar. Sci. 4, 310 (2017).

    Article  Google Scholar 

  65. 65.

    Meyer, B. The overwintering of Antarctic krill, Euphausia superba, from an ecophysiological perspective. Polar Biol. 35, 15–37 (2012).

    Article  Google Scholar 

  66. 66.

    Mackintosh, N. A. Life cycle of Antarctic krill in relation to ice and water conditions. Discovery Rep. 36, 1–94 (1972).

    Google Scholar 

  67. 67.

    Arzel, O., Fichefet, T. & Goosse, H. Sea ice evolution over the 20th and 21st centuries as simulated by current AOGCMs. Ocean Model. Online 12, 401–415 (2006).

    Article  Google Scholar 

  68. 68.

    Meiners, K. et al. Chlorophyll a in Antarctic sea ice from historical ice core data. Geophys. Res. Lett. 39, L21602 (2012).

    Article  CAS  Google Scholar 

  69. 69.

    Melbourne-Thomas, J. et al. Under ice habitats for Antarctic krill larvae: could less mean more under climate warming? Geophys. Res. Lett. 43, 10322–10327 (2016).

    Article  Google Scholar 

  70. 70.

    Kawaguchi, S. et al. Risk maps for Antarctic krill under projected Southern Ocean acidification. Nat. Clim. Change 3, 843–847 (2013).

  71. 71.

    Ericson, J. A. et al. Adult Antarctic krill proves resilient in a simulated high CO2 ocean. Commun. Biol. 1, 190 (2018).

    Article  CAS  Google Scholar 

  72. 72.

    Riebesell, U. et al. Enhanced biological carbon consumption in a high CO2 ocean. Nature 450, 545–548 (2007).

    CAS  Article  Google Scholar 

  73. 73.

    Cummings, V. J. et al. In situ response of Antarctic under-ice primary producers to experimentally altered pH. Sci. Rep. 9, 6069 (2019).

    Article  CAS  Google Scholar 

  74. 74.

    Renaud, P. E. et al. Pelagic food-webs in a changing Arctic: a trait-based perspective suggests a mode of resilience. ICES J. Mar. Sci. 75, 1871–1881 (2018).

  75. 75.

    SeaWiFS Level-3 Binned Chlorophyll Data version 2018 (NASA OB.DAAC, 2018); 10.5067/ORBVIEW-2/SEAWIFS/L3B/CHL/2018

  76. 76.

    Johnson, R., Strutton, P. G., Wright, S. W., McMinn, A. & Meiners, K. M. Three improved satellite chlorophyll algorithms for the Southern Ocean. J. Geophys. Res. Oceans 118, 3694–3703 (2013).

    CAS  Article  Google Scholar 

  77. 77.

    Orsi, A. H. Whitworth III, T. & Nowlin Jr, W. D. On the meridional extent and fronts of the Antarctic Circumpolar Current. Deep Sea Res. Part I 42, 641–673 (1995).

  78. 78.

    Sumner, M. D. raadtools: Tools for Synoptic Environmental Spatial Data. R package version (2020).

  79. 79.

    van Vuuren, D. P. et al. The representative concentration pathways: an overview. Climatic Change 109, 5–31 (2011).

    Article  Google Scholar 

  80. 80.

    R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2018).

  81. 81.

    Riekkola, L. et al. Application of a multi-disciplinary approach to reveal population structure and Southern Ocean feeding grounds of humpback whales. Ecol. Indic. 89, 455–465 (2018).

  82. 82.

    Tjiputra, J. F. et al. Evaluation of the carbon cycle components in the Norwegian Earth system model (NorESM). Geosci. Model Dev. 6, 301–325 (2013).

  83. 83.

    Dunne, J. P. et al. GFDL’s ESM2 global coupled climate–carbon Earth system models. Part I: physical formulation and baseline simulation characteristics. J. Clim. 25, 6646–6665 (2012).

  84. 84.

    Dunne, J. P. et al. GFDL’s ESM2 global coupled climate–carbon Earth system models. Part II: carbon system formulation and baseline simulation characteristics. J. Clim. 26, 2247–2267 (2013).

    Article  Google Scholar 

  85. 85.

    Veytia, D. et al. Circumpolar Projections of Antarctic Krill (Euphausia superba) Growth Potential version 1 (Australian Antarctic Data Centre, 2020).

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We thank A. Constable, R. Johnson and A. Lenton for their advice on the project, as well as M. Sumner and J. Berkhout for their technical support.

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups (listed in Supplementary Table 2) for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

This research was supported by the Australian Government through Antarctic Science Project 4408 and the Cooperative Research Centres Programme through the Antarctic Climate and Ecosystems Cooperative Research Centre (ACE CRC). D.V. is the recipient of a Tasmania Graduate Research Scholarship provided by the University of Tasmania. S.B. is the recipient of an Australian Research Council Australian Discovery Early Career Award (project DE180100828). E.M. was supported by the BAS ALI-Science Ecosystems project (developing krill life-cycle models and future projections) and acknowledges BAS colleagues for discussions on the development of analyses, models and projections of Antarctic krill population processes. The study is also a contribution to the international Integrating Climate and Ecosystems Dynamics Programme (ICED).

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The study was developed by all authors. All authors supervised D.V. in conducting the analyses, designing figures and preparing the manuscript, as well as provided feedback and ideas in the manuscript development.

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Correspondence to Devi Veytia.

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Peer review information Nature Climate Change thanks Jilda Caccavo, Bettina Fach and Elisa Ravagnan for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Map of study area.

Highlights commonly referenced locations throughout the text. White text with a large font size denotes ocean basins, white text with a small font size denotes seas, and yellow text denotes commonly-referenced topographic features.

Extended Data Fig. 2 Assessing model outputs of explanatory variables a. SST and b. chlorophyll with a Taylor diagram.

Statistics for the Taylor diagram were calculated from the area-weighted seasonal surface averages of SST and chlorophyll. Seasonal surface averages of observations were calculated from OISST v2 for SST, and the mean of the SeaWiFS75 and Johnson et al.76 datasets for chlorophyll.

Extended Data Fig. 3 Comparing chlorophyll observation datasets.

These values represent a climatology taken from Dec 1997-2010. a, is the difference of seasonal surface averages of the Johnson et al.76 dataset minus the SeaWiFS75 dataset. b, The climatologies of the two datasets using a monthly timeseries. c, Seasonal growth potential calculated using each chlorophyll dataset and OISST v2 SST. Black meridional lines on maps delineate ocean basin sectors9.

Extended Data Fig. 4 Different model weighting schemes trialled.

To compare the shapes of these weighting schemes together, weighting schemes #2-5 were multiplied by a constant of 30.

Extended Data Fig. 5 Observation-based seasonal growth potential compared to different model weighting schemes.

The five weighting schemes pictured correspond to the weighting schemes picture in Supplementary Fig. 3. Observation-based growth potential here represents the mean calculated from the Johnson et al.76 and SeaWiFS75 datasets pictured in Supplementary Fig. 2c. Growth potential for the model weighting schemes was calculated over the CMIP5 “historical” period of 1960-1989. Black meridional lines on maps delineate ocean basin sectors9.

Extended Data Fig. 6 Taylor diagram assessing modelled growth potential of different weighting schemes trialled.

The weighting schemes correspond to the weighting schemes picture in Supplementary Fig. 3, except that weighting schemes #2-5 were not multiplied by a constant of 30. Statistics for the Taylor diagram were calculated from the area-weighted seasonal modelled growth potential, averaged over 1960-1989. Observation-based growth potential was calculated using the average of the SeaWiFS75 and Johnson et al.76 chlorophyll datasets and the OISST v2 dataset, over the climatology of 1997-2010.

Extended Data Fig. 7 Comparing the density of growth potential values between chlorophyll datasets, the weighted subset and full ensemble.

The growth potential values represented were taken from surface averages, for a. spring, b. summer, c. autumn and d. winter. Averages were taken over the period of Dec 1997-2010 for the chlorophyll datasets and 1960-1989 for models. See reference for definitions of the sectors and zones used9. The distribution of growth potential values from the weighted subset falls largely within the range of observed variability obtained using the two different Southern Ocean chlorophyll-a algorithms, particularly during spring and summer, which are the seasons with the greatest observation coverage.

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Supplementary Appendices A–C, Figs. 1–5 and Tables 1–4.

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Veytia, D., Corney, S., Meiners, K.M. et al. Circumpolar projections of Antarctic krill growth potential. Nat. Clim. Chang. 10, 568–575 (2020).

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