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Improving niche projections of plant species under climate change: Silene acaulis on the British Isles as a case study

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Abstract

Empirical works to assist in choosing climatically relevant variables in the attempt to predict climate change impacts on plant species are limited. Further uncertainties arise in choice of an appropriate niche model. In this study we devised and tested a sharp methodological framework, based on stringent variable ranking and filtering and flexible model selection, to minimize uncertainty in both niche modelling and successive projection of plant species distributions. We used our approach to develop an accurate, parsimonious model of Silene acaulis (L.) presence/absence on the British Isles and to project its presence/absence under climate change. The approach suggests the importance of (a) defining a reduced set of climate variables, actually relevant to species presence/absence, from an extensive list of climate predictors, and (b) considering climate extremes instead of, or together with, climate averages in projections of plant species presence/absence under future climate scenarios. Our methodological approach reduced the number of relevant climate predictors by 95.23% (from 84 to only 4), while simultaneously achieving high cross-validated accuracy (97.84%) confirming enhanced model performance. Projections produced under different climate scenarios suggest that S. acaulis will likely face climate-driven fast decline in suitable areas on the British Isles, and that upward and northward shifts to occupy new climatically suitable areas are improbable in the future. Our results also imply that conservation measures for S. acaulis based upon assisted colonization are unlikely to succeed on the British Isles due to the absence of climatically suitable habitat, so different conservation actions (seed banks and/or botanical gardens) are needed.

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Acknowledgements

We thank two anonymous reviewers for their helpful comments that improved this manuscript.

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Authors and Affiliations

  1. Via G. Saragat 4, I-43123, Parma, Italy

    Alessandro Ferrarini

  2. Department of Biological and Environmental Sciences, College of Arts and Sciences, Qatar University, P.O. Box 2713, Doha, Qatar

    Mohammed H. S. A. Alsafran & Juha M. Alatalo

  3. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Junhu Dai

Authors
  1. Alessandro Ferrarini
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  2. Mohammed H. S. A. Alsafran
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  3. Junhu Dai
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  4. Juha M. Alatalo
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Contributions

AF and JMA conceived the study. AF performed the GIS and modelling work. AF and JMA wrote the manuscript. MHSAA and JD commented on the paper.

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Correspondence to Juha M. Alatalo.

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Ferrarini, A., Alsafran, M.H.S.A., Dai, J. et al. Improving niche projections of plant species under climate change: Silene acaulis on the British Isles as a case study. Clim Dyn 52, 1413–1423 (2019). https://doi.org/10.1007/s00382-018-4200-9

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