In this post Erin Espeland discusses the recent paper ‘Evolution of plant materials for ecological restoration: insights from the applied and basic literature‘ by herself and co-authors Nancy Emery, Kristin Mercer, Scott Woolbright, Karin Kettenring, Paul Gepts and Julie Etterson.

Native plant materials can evolve during seed collection, increase, and planting. We survey the evolutionary and agricultural literature and apply it to the problem of restoration, supporting the contention that intentional and unintentional selection could ultimately reduce the persistence and contribution to ecosystem function of ecological restorations.

During seed collection, increase, and planting, restoration populations are subject to genetic sampling as well as natural and artificial selection, potentially resulting in successful adaptation to the propagation or early restoration environment but maladaptation to natural or established restoration environments.

The existing literature is specific regarding traits susceptible to maladaptation and how their evolution could impact population function in the wild. They include seed dormancy, seed dispersal, competitive ability, phenology, pathogen susceptibility, and resource allocation. Not only do we expect shifts in trait means as a result of restoration and propagation practice, but we also expect reductions in variance, which in turn reduces the opportunity for selection and adaptive capacity of restored populations.

We show how to use neutral genetic markers and field observations (together or separately) to test for evolution as a result of propagation and/or restoration practices. The paper concludes with six tools for “evolutionarily enlightened management” of restoration: 1) conduct multiple collections from source and production populations, 2) use sources from several native populations that are in close proximity, 3) maintain large effective population size on the production farm, 4) track seed sources through propagation and restoration, 5) intentionally promote gene flow, and 6) reduce selection.

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