Rapid evolution of flower phenology and clonality in restored populations of multiple grassland species

Abstract

Abstract Restoration of terrestrial ecosystems often requires re‐introduction of plants. In restored sites, the plants often face environments that differ from those of natural populations. This can affect plant traits, reduce performance and impose novel selection pressures. As a response, restored populations might rapidly evolve and adapt to the novel conditions. This may enhance population survival and contribute to restoration success, but has been rarely tested so far. Here, we focused on populations of three grassland species restored 20 years ago (Galium wirtgenii, Inula salicina and Centaurea jacea) by the transfer of green hay, and compared them with donor populations that were the source of the hay. We measured plants both in situ, and in a common garden under control and three stress conditions. In situ, plants in restored sites flowered earlier than plants in donor sites in two out of the three species. In the common garden, plants from the restored populations flowered earlier (in Galium) or showed increased plasticity of clonal propagation in response to clipping (in Inula). Both these traits suggest rapid adaptation to the contrasting mowing regimes in restored in comparison with the donor sites. In Centaurea, we detected no differentiation, neither in situ, nor in the common garden. Synthesis and applications. Grassland plants introduced into degraded habitats within the framework of ecological restoration may quite commonly evolve in response to novel selection pressures at restored sites. This rapid evolution likely increases the plant's adaptation to the new conditions of the restored grassland and thus enhances the likelihood of survival of the population and ultimately restoration success. While most practitioners do not consider evolution to be part of restoration, our finding highlights that restored populations of grassland species can be systems with considerable eco‐evolutionary dynamics.