A dynamic eco-evolutionary model predicts slow response of alpine plants to climate warming

Olivier Cotto (), Johannes Wessely, Damien Georges, Günther Klonner, Max Schmid, Stefan Dullinger, Wilfried Thuiller and Frédéric Guillaume ()
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Olivier Cotto: University of Zurich
Johannes Wessely: Faculty of Life Sciences, University of Vienna
Damien Georges: Univesity Grenoble Alpes, CNRS, Laboratoire d’Écologie Alpine
Günther Klonner: Faculty of Life Sciences, University of Vienna
Max Schmid: University of Zurich
Stefan Dullinger: Faculty of Life Sciences, University of Vienna
Wilfried Thuiller: Univesity Grenoble Alpes, CNRS, Laboratoire d’Écologie Alpine
Frédéric Guillaume: University of Zurich

Nature Communications, 2017, vol. 8, issue 1, 1-9

Abstract: Abstract Withstanding extinction while facing rapid climate change depends on a species’ ability to track its ecological niche or to evolve a new one. Current methods that predict climate-driven species’ range shifts use ecological modelling without eco-evolutionary dynamics. Here we present an eco-evolutionary forecasting framework that combines niche modelling with individual-based demographic and genetic simulations. Applying our approach to four endemic perennial plant species of the Austrian Alps, we show that accounting for eco-evolutionary dynamics when predicting species’ responses to climate change is crucial. Perennial species persist in unsuitable habitats longer than predicted by niche modelling, causing delayed range losses; however, their evolutionary responses are constrained because long-lived adults produce increasingly maladapted offspring. Decreasing population size due to maladaptation occurs faster than the contraction of the species range, especially for the most abundant species. Monitoring of species’ local abundance rather than their range may likely better inform on species’ extinction risks under climate change.

Date: 2017
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DOI: 10.1038/ncomms15399

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