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Arctic freshwater fish productivity and colonization increase with climate warming

Abstract

Climate warming at high latitudes has long been expected to exceed that predicted for tropical and temperate climes, but recent warming in the Arctic has exceeded even those expectations1. The geophysical consequences of this warming are reasonably well established2, but the impacts on freshwater fauna are poorly understood. Here we use a large-scale geospatial analysis of the population dynamics of one of the most abundant north temperate freshwater fish species to forecast increased demographic rates, productivity and colonization range in response to IPCC climate warming scenarios. Geospatial lake morphometry data were used to characterize 481,784 lakes in the Canadian Arctic capable of supporting lake trout (Salvelinus namaycush) populations. Lake trout productivity in existing habitat is projected to increase by 20% by 2050 due to climate change, but an expanded habitable zone may result in a 29% increase in harvestable biomass. Although many ecosystems are likely to be negatively impacted by climate warming, the phenotypic plasticity of fish will allow a rapid relaxation of the current environmental constraints on growth in the far north, as well as enhanced colonization of bodies of water in which there are few potential competitors.

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Fig. 1: Distribution and characteristics of 481,784 lakes with a surface area >10 ha in the Canadian Arctic.
Fig. 2: Length at age of lake trout.
Fig. 3: Lake trout population dynamics.
Fig. 4: Observed spatial patterns in lake trout growth, mortality and productivity, and those predicted under climate change model RCP8.5 to the year 2050.

Data availability

The geospatial data (Canadian Digital Surface Model and Canadian Digital Elevation Model) are available from http://maps.canada.ca/czs/index-en.html. Air temperature data from 881 weather stations across Canada are available from http://climate.weather.gc.ca/climate_normals/results_1981_2010_e.html.

Other data that support the findings of this study have been archived at Knowledge Network for Biocomplexity https://doi.org/10.5063/F1ZP44F1 and https://doi.org/10.5063/F1TX3CPV.

References

  1. 1.

    Huang, J. et al. Recently amplified arctic warming has contributed to a continual global warming trend. Nat. Clim. Change 7, 875–879 (2017).

    Article  Google Scholar 

  2. 2.

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

  3. 3.

    Thuiller, W. et al. Consequences of climate change on the tree of life in Europe. Nature 470, 531–534 (2011).

    CAS  Article  Google Scholar 

  4. 4.

    Beaugrand, G. A. et al. Prediction of unprecedented biological shifts in the global ocean. Nat. Clim. Change 9, 237–243 (2019).

    Article  Google Scholar 

  5. 5.

    Forcada, J., Trathan, P. N. & Murphy, E. J. Life history buffering in Antarctic mammals and birds against changing patterns of climate and environmental variation. Glob. Change Biol. 14, 2473–2488 (2008).

    Google Scholar 

  6. 6.

    Pacifici, M. et al. Assessing species vulnerability to climate change. Nat. Clim. Change 5, 215–225 (2015).

    Article  Google Scholar 

  7. 7.

    Frainer, A. et al. Climate-driven changes in functional biogeography of Arctic marine fish communities. Proc. Natl Acad. Sci. USA 114, 12202–12207 (2017).

    CAS  Article  Google Scholar 

  8. 8.

    Wessely, J. et al. Habitat-based conservation strategies cannot compensate for climate-change-induced range loss. Nat. Clim. Change 7, 823–827 (2017).

    Article  Google Scholar 

  9. 9.

    Ryder, R. A. The Morphoedaphic Index—use, abuse and fundamental concepts. Trans. Am. Fish. Soc. 111, 154–164 (1982).

    Article  Google Scholar 

  10. 10.

    Messager, M. L., Lehner, B., Grill, G., Nedeva, I. & Schmitt, O. Estimating the volume and age of water stored in global lakes using a geo-statistical approach. Nat. Comm. 7, 13603 (2016).

    CAS  Article  Google Scholar 

  11. 11.

    Campana, S. E., Casselman, J. M. & Jones, C. M. Bomb radiocarbon chronologies in the Arctic, with implications for the age validation of lake trout (Salvelinus namaycush) and other Arctic species. Can. J. Fish. Aquat. Sci. 65, 733–743 (2008).

    Article  Google Scholar 

  12. 12.

    Shuter, B. J., Jones, M. L., Korver, R. M. & Lester, N. P. A general, life history based model for regional management of fish stocks: the inland lake trout (Salvelinus namaycush) fisheries of Ontario. Can. J. Fish. Aquat. Sci. 55, 2161–2177 (1998).

    Article  Google Scholar 

  13. 13.

    Campana, S. E. Accuracy, precision and quality control in age determination, including a review of the use and abuse of age validation methods. J. Fish. Biol. 59, 197–242 (2001).

    Article  Google Scholar 

  14. 14.

    Casselman, J. M., Jones, C. M. & Campana, S. E. Bomb radiocarbon age validation for the long-lived, unexploited Arctic fish species Coregonus clupeaformis. Mar. Freshwat. Res. 70, 1–8 (2019).

    Article  Google Scholar 

  15. 15.

    Lester, N. P., Shuter, B. J. & Abrams, P. A. Interpreting the von Bertalanffy model of somatic growth in fish: the cost of reproduction. Proc. R. Soc. Ser. B 271, 1625–1631 (2004).

    CAS  Article  Google Scholar 

  16. 16.

    Minte-Vera, C. V., Maunder, M. N., Casselman, J. M. & Campana, S. E. Growth functions that incorporate the cost of reproduction. Fish. Res. 180, 31–44 (2016).

    Article  Google Scholar 

  17. 17.

    Collins, M. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 1029–1136 (IPCC, Cambridge Univ. Press, 2013)

  18. 18.

    Climate Change 2014: Synthesis Report (eds Pachauri, R. K. and Meyer, L. A.) (IPCC, Cambridge Univ. Press, 2014).

  19. 19.

    Islam, D. & Berkes, F. Indigenous peoples' fisheries and food security: a case from northern Canada. Food Secur. 8, 815–826 (2016).

    Article  Google Scholar 

  20. 20.

    Musick, J. A. Ecology and conservation of long-lived marine animals. Am. Fish. Soc. Symp. 23, 1–10 (1999).

    Google Scholar 

  21. 21.

    Schloss, C. A., Nunez, T. A. & Lawler, J. J. Dispersal will limit ability of mammals to track climate change in the Western Hemisphere. Proc. Natl Acad. Sci. USA 109, 8606–8611 (2012).

    CAS  Article  Google Scholar 

  22. 22.

    Hirsch, P. E., N’Guyen, A., Muller, R., Adrian‐Kalchhauser, I. & Burkhardt‐Holm, P. Colonizing Islands of water on dry land—on the passive dispersal of fish eggs by birds. Fish. Fish. 19, 502–510 (2018).

    Article  Google Scholar 

  23. 23.

    Spens, J., Englund, G. & Lundqvist, H. Network connectivity and dispersal barriers: using geographical information system (GIS) tools to predict landscape scale distribution of a key predator (Esox lucius) among lakes. J. Appl. Ecol. 44, 1127–1137 (2007).

    Article  Google Scholar 

  24. 24.

    Swanson, H. K. et al. Anadromy in Arctic populations of lake trout (Salvelinus namaycush): otolith microchemistry, stable isotopes, and comparisons with Arctic char (Salvelinus alpinus). Can. J. Fish. Aquat. Sci. 67, 842–853 (2010).

    CAS  Article  Google Scholar 

  25. 25.

    Ockendon, N. et al. Mechanisms underpinning climatic impacts on natural populations: altered species interactions are more important than direct effects. Glob. Change Biol. 20, 2221–2229 (2014).

    Article  Google Scholar 

  26. 26.

    Wilson, K. L., De Gisi, J., Cahill, C. L., Barker, O. E. & Post, J. R. Life‐history variation along environmental and harvest clines of a northern freshwater fish: plasticity and adaptation. J. Anim. Ecol. 88, 717–733 (2019).

    Article  Google Scholar 

  27. 27.

    Gauthier, G. et al. Long-term monitoring at multiple trophic levels suggests heterogeneity in responses to climate change in the Canadian Arctic tundra. Philos. Trans. R. Soc. B 368, 20120482 (2013).

    Article  Google Scholar 

  28. 28.

    Thomas, C. D. Climate, climate change and range boundaries. Diversity Distrib. 16, 488–495 (2010).

    Article  Google Scholar 

  29. 29.

    Healey, M. C. The dynamics of exploited lake trout populations and implications for management. J. Wildl. Manag. 42, 307–328 (1978).

    Article  Google Scholar 

  30. 30.

    Burr, J. M. Growth, density and biomass of lake trout in Arctic and Subarctic Alaska. Am. Fish. Soc. Symp. 19, 109–118 (1997).

    Google Scholar 

  31. 31.

    Mills, K. H., Dyck, M. & Harwood, L. A. Proceedings of the second lake trout symposium 2005, Yellowknife, Northwest territories. Can. Tech. Rep. Fish. Aquat. Sci. 2778, 247 (2008).

    Google Scholar 

  32. 32.

    Hollister, J. W., Milstead, W. B. & Urrutia, M. A. Predicting maximum lake depth from surrounding topography. PLoS ONE 6, e25764 (2011).

  33. 33.

    Livingstone, D. M., Lotter, A. F. & Walker, I. R. The decrease in summer surface water temperature with altitude in Swiss alpine lakes: a comparison with air temperature lapse rates. Arct. Antarct. Alp. Res. 31, 341–352 (1999).

    Article  Google Scholar 

  34. 34.

    Shuter, B. J., Schlesinger, D. A. & Zimmerman, A. P. Empirical predictors of annual surface water temperature cycles in North American lakes. Can. J. Fish. Aquat. Sci. 40, 1838–1845 (1983).

    Article  Google Scholar 

  35. 35.

    Da Fang, X. & Stefan, H. G. Long-term lake water temperature and ice cover simulations/measurements. Cold Reg. Sci. Technol. 24, 289–304 (1996).

    Article  Google Scholar 

  36. 36.

    Campana, S. E. Physical Characteristics of 55 Canadian Arctic Lake Trout Lakes (Knowledge Network for Biocomplexity archive, 2020); https://doi.org/10.5063/F1ZP44F1

  37. 37.

    Campana, S. E. Lake Trout Population Characteristics in 55 Canadian Arctic Reference Lakes (Knowledge Network for Biocomplexity, 2020); https://doi.org/10.5063/F1TX3CPV.

  38. 38.

    Samarasin, P., Minns, C. K., Shuter, B. J., Tonn, W. M. & Rennie, M. D. Fish diversity and biomass in northern Canadian lakes: northern lakes are more diverse and have greater biomass than expected based on species–energy theory. Can. J. Fish. Aquat. Sci. 72, 226–237 (2015).

    Article  Google Scholar 

  39. 39.

    Campana, S. E., Valentin, A. E., MacLellan, S. E. & Groot, J. B. Image-enhanced burnt otoliths, bomb radiocarbon and the growth dynamics of redfish (Sebastes mentella and S. fasciatus) off the eastern coast of Canada. Mar. Freshw. Res. 67, 925–936 (2016).

    Article  Google Scholar 

  40. 40.

    Francis, R. I. C. C. Growth in age-structured stock assessment models. Fish. Res. 180, 113–118 (2015).

    Article  Google Scholar 

  41. 41.

    Smith, M. W. et al. Recommendations for catch-curve analysis. North Am. J. Fish. Managem. 32, 956–967 (2012).

    Article  Google Scholar 

  42. 42.

    Ricker, W. E. Computation and Interpretation of Biological Statistics of Fish Populations (Bulletin of the Fisheries Research Board of Canada, 1975).

  43. 43.

    Deriso, R. B. Optimal F 0.1 criteria and their relationship to maximum sustainable yield. Can. J. Fish. Aquat. Sci. 44, 339–348 (1987).

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the Nunavut Wildlife Management Board, Fisheries and Oceans Canada, US National Science Foundation grant OCE-9985884 and the University of Iceland. We thank S. Armsworthy, P. Bentzen, J. Brazner, C. Campana, P. Campana, S. Campana, S. Casselman, M. Fowler, D. Houlihan, W. Joyce, P. Leblanc, A. MacDonnell and M. Showell for their exceptional assistance in the field and laboratory. B. Shuter and J. Morrongiello provided valuable comments on the MS.

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The study was conceived and designed by S.C., J.C. and C.J., and coordinated by S.C. All authors contributed to fieldwork, data collection and/or data interpretation. G.B. (now retired) prepared and analysed the geospatial data. S.C. drafted the paper with contributions from all authors.

Corresponding author

Correspondence to Steven E. Campana.

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The authors declare no competing interests.

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Peer review information Nature Climate Change thanks Arild Folkvord and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Figs. 1–3, Tables 1–4 and Notes 1–4.

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Campana, S.E., Casselman, J.M., Jones, C.M. et al. Arctic freshwater fish productivity and colonization increase with climate warming. Nat. Clim. Chang. 10, 428–433 (2020). https://doi.org/10.1038/s41558-020-0744-x

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