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Plant collections for conservation and restoration: can they be adapted and adaptable?


Bragg, Jason et al. (2022), Plant collections for conservation and restoration: can they be adapted and adaptable?, Dryad, Dataset,


Plant collections are important for the conservation of threatened species, and as a source of material for ecological restoration. Typically we want collections to have high genetic diversity so populations founded from it are adaptable to future challenges. Sometimes, we have additional objectives for collections, such as enrichment for desirable traits controlled by adaptive alleles. We used landscape genomic datasets for two plants, Westringia fruticosa and Wilkiea huegeliana, to design collections that are genetically diverse, and that are adapted to warming climates. We characterized temperature adaptation by: (i) using the mean annual temperature of the sites of origin of the plants, and (ii) using the representation of alleles that are associated with warm temperatures. In Westringia fruticosa, there was a negative correlation, or tradeoff between designing a collection that was both genetically diverse and adapted to warm temperatures. This tradeoff was weaker in Wilkiea huegeliana. We hypothesized this was because neutral genetic variation was strongly correlated with temperature in Westringia fruticosa, and not in Wilkiea huegeliana. Accordingly, when we shuffled the temperature data, breaking up the covariance between Westringia fruticosa genetic variation and temperature, there was a relaxation of the observed tradeoff. In sum, we explore tradeoffs between genetic diversity and environmental adaptation in plant collections, and highlight factors that influence the strength of these tradeoffs. This represents a useful step towards understanding when selection will have a large cost in genetic diversity, and when it will be possible to design a collection that is both adapted and adaptable.


Samples of two species, Westringia fruticosa and Wilkiea huegeliana, were collected across their respective ranges. Each sample was genotyped using DArTseq, a restriction based method. The resulting genotype data and sample meta-data are in this repository. These data were analysed using R code, which is archived in this repository.

Usage Notes

A README file accompanies this archive, and outlines the directory structure, and describes the data and code available in those directories.