Restore and Renew: a genomics-era framework for species provenance delimitation

Maurizio Rossetto, Jason Bragg, Andrzej Kilian, Hannah McPherson, Marlien van der Merwe, Peter D. Wilson

    Research output: Contribution to journalArticlepeer-review

    47 Citations (Scopus)
    63 Downloads (Pure)


    Here we present “Restore and Renew,” a replicable framework for gathering and interpreting evolutionary, ecological, and genomic data in support of restoration practices. In an era of rapid climatic change and continuous widespread clearing, revegetation projects need to focus on producing resilient and long-term self-sustaining populations. Restore and Renew expands current knowledge of genetic provenance via genome-scan data, environmental niche modeling (ENM), and site-specific climate information. The sampling strategy is to obtain leaf tissue representing the distributions of over 100 species commonly used in restoration. We apply generalized dissimilarity modeling to genome-wide single nucleotide polymorphism datasets from hundreds of samples. Species-specific local provenances are obtained using a model that represents observed patterns of genetic variation across the landscape. Climate modeling is implemented to interpret genetic provenance boundaries in the context of current and future climatic conditions at the specified site. Results are presented in an easy-to-use webtool (, where the user simply selects their site of interest and a target species to obtain the size and distribution of local genetic provenance. Although Restore and Renew is not prescriptive, it allows restoration practitioners to make informed decisions on where to source material from, to fulfill their restoration scenario of choice. Two examples, Westringia fruticosa and Acacia suaveolens, are presented to demonstrate how the analytical pipeline responds to different ecological and evolutionary patterns. The webtool has multiple applications for biodiversity management and will continue to evolve with new species and analytical/interpretative outputs.

    Original languageEnglish
    Pages (from-to)538-548
    Number of pages11
    JournalRestoration Ecology
    Issue number3
    Publication statusPublished - 1 May 2019


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