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

Abstract

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 (www.restore-and-renew.org.au), 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.

The Potential for Rapid Evolution under Anthropogenic Climate Change

“…A second important question is how we might exploit geographic variation in conservation efforts to promote adaptation through targeted gene flow [29,104]. Central to this question is the problem of identifying how strongly a species is adapting to different aspects of climate: for example, a species might show strong local adaptation to temperature but only moderate adaptation to precipitation.…”

Restore or Redefine: Future Trajectories for Restoration

“…To ensure empirical genetic data is utilized to facilitate informed provenance decisions, data on genetic diversity and structure and their links to environmental conditions should be made publicly available to stakeholders and non-experts including community groups and governments who often implement restoration programs. For example, the restore and renew website for terrestrial plants 2 (Rossetto et al, 2019) allows users to define a site to be restored, choose appropriate provenance within defined genetic populations and even provides provenance options to improve resilience (see "Revive -Restoring Extant or Historic Genetic Baselines"). No such platforms exist for marine systems but development of new marine restoration methods that will increase accessibility of 2 restore-and-renew.org.au marine restoration to diverse user groups and over large scales, will necessitate similar initiatives to ensure scientifically informed provenance decisions are made within the decade of restoration.…”

Combining genotype, phenotype, and environmental data to delineate site-adjusted provenance strategies for ecological restoration

“…S12), which could be used to delineate seed sourcing strategies. In contrast to the commonly employed Generalized Dissimilarity Models (GDM) (Shryock et al, 2015;Gugger et al, 2018;Supple et al, 2018;Rossetto et al, 2019), our mapping approach based on sPCA allows incorporating GPA and predicting adaptive genetic variation from site-level data, which is particularly useful in areas lacking high-resolution environmental layers. Moreover, sPCA explicitly account for spatial autocorrelation in genetic composition, which is likely to play an important role explaining patterns of local adaptation (Lesica & Allendorf, 1999b;Richardson et al, 2014) (see Fig.…”

“…Although the use of neutral genetic markers to identify independent demographic units is now common practice (Coates et al, 2018), few restoration studies have delineated seed sourcing strategies based on population genetic structure (Durka et al, 2017) or the genetic neighborhood size (the distance at which genetic composition stops being spatially autocorrelated) (Krauss & Koch, 2004;Krauss et al, 2013;Rossetto et al, 2019). On the other hand, only three restoration genomic studies so far have identified putative adaptive loci and then mapped adaptive genetic variation (Steane et al, 2014;Shryock et al, 2015;Martins et al, 2018).…”