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.
Highlights
Withstanding extinction while facing rapid climate change depends on a species’ ability to track its ecological niche or to evolve a new one
Long adult lifespan limits the adaptive capacity of local populations, on the other hand it allows long-term persistence in unsuitable sites
The slow decline in occupancy hides a rapid loss of local adaptation and a rapid decrease in population density as the climate changes
Summary
Withstanding extinction while facing rapid climate change depends on a species’ ability to track its ecological niche or to evolve a new one. It remains unclear how local additive genetic variance, life history, landscape structure, and dispersal interactively constrain, or promote, rapid evolutionary adaptation of species to a changing environment[8,17,30] To add to this uncertainty, only a handful of studies have incorporated evolutionary processes into biodiversity models and most of them concern species with short generation times and fast growth (for example, dengue mosquitoes[31] or flies[16]). We use static ecological niche models (SENMs) based on SDMs (see Methods) to predict the current distribution of a species in a study area as a function of spatial variation in environmental conditions This predicted distribution pattern is used to initialize populations in DEEMs, which subsequently simulate changes in the distribution and adaptation of plant individuals as driven by scenarios of climatic (or other environmental) change. By explicitly incorporating species demography and evolutionary potential, highlights how local eco-evolutionary processes translate into changes in species range
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