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Assessing a Bayesian Approach for Detecting Exotic Hybrids between Plantation and Native Eucalypts

机译:评估检测人工林和本地桉树之间异源杂种的贝叶斯方法

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Eucalyptus 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 inthe 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) showedthat 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 FjS, which, in the context of E. globulus plantations, are the primary management concern.
机译:桉树在澳大利亚本土以外的人工林中广泛种植。有人担心该物种可能通过杂交和渗入对天然桉树物种造成遗传风险。需要用于鉴定杂种的方法以能够评估和管理这种遗传风险。本文评估了贝叶斯方法用于识别人工林物种globulus和E.nitens与四个有风险的天然桉树之间的杂种的效率。用10个微卫星基因座对n。,tenova,E。ovata和E. viminalis以及纯种和推定杂种(n = 606)进行基因分型。使用双向仿真分析(一次在模型中同时存在两个物种),第一代杂种的识别准确性为98%,第二代杂种的识别准确性为93%。但是,识别模拟回交杂种的准确性较低(74%)。六向分析(模型中的所有物种一起)表明,随着物种数量的增加,杂交鉴定的准确性降低。尽管在确定回交方面存在一些困难,但是双向贝叶斯建模方法在识别FjS方面非常有效,而FjS在小球藻人工林的情况下是主要的管理问题。

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