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Fine-scale tundra vegetation patterns are strongly related to winter thermal conditions

Nature Climate Change volume 10, pages 1143–1148 (2020)Cite this article

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Abstract

Harsh winters are a characteristic element of Arctic ecosystems, yet the importance of winter conditions for Arctic plant communities is still underrepresented in climate change impact studies. Here, we use fine-scale microclimate data with plot-scale records of vascular plants, lichens and bryophytes from three Arctic areas, and show that topographically heterogeneous tundra holds marked spatial variation, especially in winter temperatures. Winter conditions are the strongest environmental variable related to the fine-scale patterns in tundra vegetation, whereas summer temperatures mainly explain the coarse-scale differences among the Arctic areas. Nonetheless, the three plant groups (and also individual species) show often contrasting and complex responses along the local environmental gradients. Our results highlight the importance of local conditions and heterogeneity for tundra plants, and knowing that the Arctic winters are warming faster than summers, a greater focus should be placed on winter conditions in simulations of climate change impacts in tundra ecosystems.

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Fig. 1: The study areas and their microclimates.
Fig. 2: Ordination analyses of species communities in relation to predictors.
Fig. 3: Variable importance values of species richness and species occurrence models.
Fig. 4: Relationships of four circum-Arctic species and species richness with winter and summer temperatures.

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Data availability

The data that support the findings of this study have been deposited in a Zenodo public data repository (https://doi.org/10.5281/zenodo.3946817).

Code availability

The main computer code that supports the findings of this study has been deposited in a Zenodo public data repository (https://doi.org/10.5281/zenodo.3946817).

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Acknowledgements

We acknowledge research support provided by the Academy of Finland (project nos 286950 and 312559), Maj and Tor Nessling Foundation, Kone Foundation, Societas pro Fauna et Flora Fennica, “The protected area network in the changing climate (SUMI)” project funded by the Ministry of Environment, and the Doctoral Programme in Geosciences at the University of Helsinki. We thank A. Niskanen for her language check; H. Rautakoski, A.-M. Virkkala and E. Puhjo for pH analyses in the lab; P. Eidesen for helping with the temperature loggers; H. Riihimäki for the UAV imagery used in Fig. 1; and all members of the BioGeoClimate Modelling Lab for assisting with the fieldwork. We also thank the laboratory personnel at the University of Helsinki and the staff at The University Centre in Svalbard, Kangerlussuaq International Science Support and Kilpisjärvi Biological research station.

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Authors and Affiliations

  1. Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland

    Pekka Niittynen, Juha Aalto, Julia Kemppinen & Miska Luoto

  2. Finnish Environment Institute, Helsinki, Finland

    Risto K. Heikkinen

  3. Finnish Meteorological Institute, Helsinki, Finland

    Juha Aalto

  4. DEE & IDYST, University of Lausanne, Lausanne, Switzerland

    Antoine Guisan

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  1. Pekka Niittynen
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Contributions

P.N., M.L., J.K. and J.A. designed the research and gathered the field data. P.N. performed the analysis and wrote the first draft of the paper. All the authors contributed markedly to writing the paper.

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Correspondence to Pekka Niittynen.

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

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Extended data

Extended Data Fig. 1 Variable importance values of species richness models.

Variable importance values from species richness analyses (HGAM and BRT) for all study areas a, and separately for the Sub-Arctic b, the Low-Arctic c, and the High-Arctic study areas d. Whiskers represent the standard errors (SE) of mean over 100 bootstrap runs. FDD = freezing degree days (°C); TDD = thawing degree day (°C).

Extended Data Fig. 2 Variable importance values of species occurrence models.

Variable importance values from species occurrence analyses (HGAM and BRT) for all study areas a, and separately for the Sub-Arctic b, the Low-Arctic c, and the High-Arctic study areas d. Whiskers represent the standard error of means over modelled species. FDD = freezing degree days (°C); TDD = thawing degree day (°C).

Extended Data Fig. 3 Simulated species richness in relation to FDD and TDD in the Sub-Arctic study area.

Species richness for all species included a, vascular plants b, bryophytes c, and lichens d. The models (GAM) were fitted with the true observations and then predicted across the ranges of observed FDD and TDD (see methods). FDD and TDD values far from the true measurements at the study area removed to avoid extrapolation. FDD = freezing degree days (°C); TDD = thawing degree day (°C).

Extended Data Fig. 4 Simulated species richness in relation to FDD and TDD in the Low-Arctic study area.

Species richness for all species included a, vascular plants b, bryophytes c, and lichens d. The models (GAM) were fitted with the true observations and then predicted across the ranges of observed FDD and TDD (see methods). FDD and TDD values far from the true measurements at the study area removed to avoid extrapolation. FDD = freezing degree days (°C); TDD = thawing degree day (°C).

Extended Data Fig. 5 Simulated species richness in relation to FDD and TDD in the High-Arctic study area.

Species richness for all species included a, vascular plants b, bryophytes c, and lichens d. The models (GAM) were fitted with the true observations and then predicted across the ranges of observed FDD and TDD (see methods). FDD and TDD values far from the true measurements at the study area removed to avoid extrapolation. FDD = freezing degree days (°C); TDD = thawing degree day (°C).

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Niittynen, P., Heikkinen, R.K., Aalto, J. et al. Fine-scale tundra vegetation patterns are strongly related to winter thermal conditions. Nat. Clim. Chang. 10, 1143–1148 (2020). https://doi.org/10.1038/s41558-020-00916-4

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