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Genetic thinning of clonal seed orchards using linear deployment may improve both gain and diversity

机译:使用线性部署对种子种子园进行遗传稀疏可以提高产量和多样性

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The linear deployment algorithm defines a straight line relationship between the number of ramets and the breeding value of a given clone. However, when used to determine thinning in clonal seed orchards, there is an upper limit, determined by the number of ramets in the seed orchard prior to thinning. Linear deployment thinning maximises genetic gain and effective clone number whilst minimising thinning intensity, thus both production and genetic diversity are optimised. Here two applications of linear deployment to Swedish Norway spruce seed orchards are described. The first example is a cutting seed orchard of Picea abies situated at Lagan, southern Sweden. The genetic values of the clones were determined from a series of 12-year old field trials. The remarkable result was that considerable improvements in both effective number and breeding value were achieved simultaneously. The second example is a grafted seed orchard of Picea abies at Maglehem, from which results of a progeny-test were available. It was thinned mainly on the basis of the algorithm. In the practical operations at Lagan and Maglehem, the linear deployment thinning algorithm was not applied exactly: silvicultural considerations and ease of management necessitated minor deviations. The actual outcomes of the thinning are reported, and the results were close to optimal. Linear deployment thinning is recommended where the effective number of clones is a concern and where breeding values are known. The algorithm has characteristics that justify its results being described as 'optimal' and the benefits of using it may be substantial. Although a slightly higher genetic gain can be obtained by conventional truncation thinning at the same thinning intensity, this is usually accompanied by a considerable loss in the effective and actual numbers of remaining clones. With linear deployment thinning the flexibility regarding the trees to remove, the opportunities for additional thinning based on later observations, the numbers of clones archived in the orchard and the opportunities for selective harvest are all increased.
机译:线性展开算法定义了分株数与给定克隆的育种值之间的直线关系。但是,当用于确定克隆种子果园的间伐时,存在上限,该上限由间苗前种子园中分株的分枝数决定。线性展开稀疏可最大化遗传增益和有效克隆数,同时最小化稀疏强度,因此可同时优化产量和遗传多样性。这里描述了线性部署在瑞典挪威云杉种子园中的两种应用。第一个例子是位于瑞典南部拉根(Lagan)的云杉切花果园。这些克隆的遗传价值是通过一系列12年的现场试验确定的。引人注目的结果是同时实现了有效数量和育种价值的显着提高。第二个例子是在马格里姆(Maglehem)嫁接的云杉云杉种子园,可以得到子代测试结果。它主要是根据算法进行细化的。在Lagan和Maglehem的实际操作中,线性部署稀疏算法未完全应用:造林和管理的便利性要求较小的偏差。报告了间伐的实际结果,结果接近最佳。如果需要考虑克隆的有效数量并且已知育种值,则建议进行线性部署稀化。该算法具有可证明其结果被描述为“最佳”的特征,并且使用它的好处可能是巨大的。尽管在相同的稀疏强度下通过常规截短稀化可以获得略高的遗传增益,但这通常伴随着剩余克隆的有效和实际数量的大量损失。随着线性部署的稀疏,树木去除的​​灵活性,基于后来观察的进一步稀疏的机会,在果园中存档的克隆数量以及选择性收获的机会都增加了。

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