A Climate-Oriented Approach to Support Decision-Making for Seed Provenance in Ecological Restoration

• Main Authors: Cristina E. Ramalho, Margaret Byrne, Colin J. Yates
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2017-08-01
• Series: Frontiers in Ecology and Evolution
• Subjects: climate-adjusted provenancing; climate change adaptation; conservation planning; ecological restoration; seed provenance; seed sourcing
• Online Access: http://journal.frontiersin.org/article/10.3389/fevo.2017.00095/full

There is increasing awareness that the long-term success of ecological restoration efforts can be compromised if projected climate change is not effectively incorporated in restoration planning. We propose an approach that aims to support the decision-making process for seed provenance selection in ecological restoration when clear genetic-based guidelines for seed transfer are not available. The approach takes advantage of the increasing availability and refinement of user-friendly web-based GIS interfaces that allow non-experts to directly access biodiversity and environmental data, and build species distribution models. It offers an easily accessible desktop method that land managers and practitioners can use to gain insight: (1) on the overall spatial implications of projected climate change to their restoration project; (2) whether assisted gene flow through climate-adjusted provenance may be appropriate for a given species at a given restoration site; and (3) how far away and in which direction from the restoration site seeds should be collected from. This approach should be used in the early stages of the restoration project to help frame the decision-making process in a climate change context, and can also be used as a platform where other lines of evidence are integrated. We advocate that, in the context of rapid climate change, the climate-adjusted provenance is a promising approach to seed sourcing in ecological restoration, and we suggest its refinement in a way that hedges against uncertainty in climatic projections.