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Light and energetics at seasonal extremes limit poleward range shifts

Abstract

Seasonality in light becomes increasingly extreme at high latitudes, both in terms of the diel light–dark cycle and the duration of light summers and dark winters. In contrast to temperature, this latitudinal gradient in light seasonality is not affected by climate change. A key question is therefore whether light may act as a fixed constraint on warming-driven redistributions of organisms at high latitudes. One answer is provided by studying mechanistic models of visual foraging and temperature-driven physiology along latitudinal gradients to project where populations survive and acquire resources to reproduce, and where they demise. Here we contrast such models for two widespread planktivorous fish types. We identify two processes through which seasonality in light can act as a barrier to poleward range expansions at high latitudes: (1) longer dark winters lead to greater depletion of overwinter energy stores and (2) a longer duration of midnight sun entails higher foraging-related predation mortality.

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Fig. 1: The seasonal light regime becomes increasingly extreme towards the poles.
Fig. 2: Feeding behaviour of a diel-vertically migrating mesopelagic planktivore.
Fig. 3: Warmer temperatures lead to reduced starvation resistance in winter.
Fig. 4: Sensitivity of model projections to parameter variation.

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Data availability

The GIN Seas Regional Climatology with temperature and salinity is freely available online53. The zooplankton prey field was based on published literature values (see Supplementary Section M4 Zooplankton for references), generated in the mesopelagic fish model (code is available, see below), and used as input in the epipelagic fish model. The data used as input in the mesopelagic fish model are available in Supplementary Table 4 and the input data for the epipelagic fish model are available in Supplementary Tables 2 and 3.

Code availability

The source code for the epipelagic fish model is provided in Supplementary Code 1, and Supplementary Code 2 contains the source code for the mesopelagic fish model.

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Acknowledgements

The authors received funding through the MARmaED project from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement number 675997. The results of this publication reflect only the authors’ view and the Commission is not responsible for any use that may be made of the information it contains. All authors received funding from the Research Council of Norway, project 294819.

Author information

Authors and Affiliations

Authors

Contributions

G.L., T.J.L. and C.J. conceived and designed the research. G.L. and T.J.L. developed the models with guidance from C.J. All the authors contributed to the interpretation of the results. G.L. wrote the paper with input from T.J.L. and C.J. The figures were created by T.J.L. with input from G.L. and C.J.

Corresponding author

Correspondence to Gabriella Ljungström.

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The authors declare no competing interests.

Additional information

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

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

Extended data

Extended Data Fig. 1 Model flowchart of drivers, mechanisms, and agents.

There are several commonalities between the Epipelagic and Mesopelagic fish model: both models base energy acquisition on visual encounters, which depend on light and prey availability, and physiological processes, including digestion and loss of energy, are temperature-dependent. Predation pressure is only included in the mesopelagic fish model.

Extended Data Fig. 2 Data localities and seasonal latitude distributions of zooplankton and temperature.

All simulations were run with seasonal light, idealised zooplankton prey fields (B), and temperature (C) at 30 m depth derived from data of current observations along a high latitude gradient from 55 to 75°N (A).

Extended Data Fig. 3 Current and future overwintering costs for the epipelagic planktivore.

The left panel shows the overwintering costs (kJ·ind−1·year−1) for current temperatures, the middle panel shows the change associated with a 2 °C warming, and the right panel shows the sum of panel 1 and 2, that is the new situation in an ocean that is 2 °C warmer. Values in left and right panel are normalized to the highest overwintering loss projected in the current scenario and isoclines represent the projected combination of latitude and body size for different percentages of these values. Red lines show the latitude that after 2 °C warming has equal overwintering cost as currently experienced by populations at 60°N and 70°N (blue dashed lines). For the highest latitudes (beyond ca. 74°N), the colder temperatures towards the poles reduce metabolic rates sufficiently to compensate for longer winters, making the total overwintering cost lower even though wintertime lasts longer. At the lowest latitudes (below ca. 58°N), the dark season is relatively short, but the smaller prey in the North Sea constrains energy intake in the largest individuals and makes winters comparatively favourable only for small fish.

Extended Data Fig. 4 Data localities and latitude-depth distributions of zooplankton and temperature.

All simulations were run with seasonal light, idealised zooplankton prey fields (B), and temperature (C) derived from data of current observations along a high latitude gradient from 55 to 75°N (A).

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2, and methods M1–M4.

Reporting Summary

Supplementary Data 1

Source code for the epipelagic fish model.

Supplementary Data 2

Source code for the mesopelagic fish model.

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Ljungström, G., Langbehn, T.J. & Jørgensen, C. Light and energetics at seasonal extremes limit poleward range shifts. Nat. Clim. Chang. 11, 530–536 (2021). https://doi.org/10.1038/s41558-021-01045-2

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