Larcombe et al. 2014 Int J Forest Research Bayesian hybrids .pdf (5.35 MB)
Download fileAssessing a Bayesian approach for detecting exotic hybrids between plantation and native eucalypts
journal contribution
posted on 2023-05-18, 07:16 authored by Larcombe, MJ, Rene VaillancourtRene Vaillancourt, Rebecca JonesRebecca Jones, Bradley PottsBradley PottsEucalyptus globulus is grown extensively in plantations outside its native range in Australia. Concerns have been raised that the species may pose a genetic risk to native eucalypt species through hybridisation and introgression. Methods for identifying hybrids are needed to enable assessment and management of this genetic risk. This paper assesses the efficiency of a Bayesian approach for identifying hybrids between the plantation species E. globulus and E. nitens and four at-risk native eucalypts. Range-wide DNA samples of E. camaldulensis, E. cypellocarpa, E. globulus, E. nitens, E. ovata and E. viminalis, and pedigreed and putative hybrids (n = 606), were genotyped with 10 microsatellite loci. Using a two-way simulation analysis (two species in the model at a time), the accuracy of identification was 98% for first and 93% for second generation hybrids. However, the accuracy of identifying simulated backcross hybrids was lower (74%). A six-way analysis (all species in the model together) showed that as the number of species increases the accuracy of hybrid identification decreases. Despite some difficulties identifying backcrosses, the two-way Bayesian modelling approach was highly effective at identifying F1s, which, in the context of E. globulus plantations, are the primary management concern.
Funding
Forest & Wood Products Australia Limited
History
Publication title
International Journal of Forestry ResearchArticle number
650202Number
650202Pagination
1-13ISSN
1687-9368Department/School
School of Natural SciencesPublisher
Hindawi Publishing CorporationPlace of publication
United StatesRights statement
Copyright 2014 Matthew J. Larcombe et al. Licenced under Creative Commons Attribution 3.0 Unported (CC BY 3.0) http://creativecommons.org/licenses/by/3.0/Repository Status
- Open