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

  • Alessandro Ferrarini
  • Mohammed H. S. A. Alsafran
  • Junhu Dai
  • Juha M. Alatalo
Article

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.

Keywords

British Isles Climate-driven niche modelling Climate extremes Model selection Parsimonious modelling Silene acaulis Variable ranking Variable selection 

Notes

Acknowledgements

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

Author 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.

Compliance with ethical standards

Conflict of interest

The authors declare no competing financial interests.

Supplementary material

382_2018_4200_MOESM1_ESM.pdf (582 kb)
Supplementary material 1 (PDF 582 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.ParmaItaly
  2. 2.Department of Biological and Environmental Sciences, College of Arts and SciencesQatar UniversityDohaQatar
  3. 3.Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina

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