Abstract

Learning has been postulated to ‘drive’ evolution, but its influence on adaptive evolution in heterogeneous environments has not been formally examined. We used a spatially explicit individual-based model to study the effect of learning on the expansion and adaptation of a species to a novel habitat. Fitness was mediated by a behavioural trait (resource preference), which in turn was determined by both the genotype and learning. Our findings indicate that learning substantially increases the range of parameters under which the species expands and adapts to the novel habitat, particularly if the two habitats are separated by a sharp ecotone (rather than a gradient). However, for a broad range of parameters, learning reduces the degree of genetically-based local adaptation following the expansion and facilitates maintenance of genetic variation within local populations. Thus, in heterogeneous environments learning may facilitate evolutionary range expansions and maintenance of the potential of local populations to respond to subsequent environmental changes.

Highlights

  • Learning allows an animal to modify its behaviour in an adaptive way in response to sensory feedback

  • For a range of parameters, for which the population expands into the novel habitat even without learning, learning slows down genetically-based adaptation following the expansion and reduces the degree of local adaptation at equilibrium

  • The ability to learn significantly extended the range of selection parameters under which the species was able to expand and adapt to a novel habitat if the two habitats were separated by a sharp transition (Fig. 2)

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Summary

Introduction

Learning allows an animal to modify its behaviour in an adaptive way in response to sensory feedback. Learning may facilitate expansion and adaptation to a novel, initially marginal habitat independently of its effects on the relationship between genotype and relative fitness.

Results
Conclusion
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