4.5 Article

Conservation and Monitoring of Tree Genetic Resources in Temperate Forests

期刊

CURRENT FORESTRY REPORTS
卷 2, 期 2, 页码 119-129

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SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/s40725-016-0038-8

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Conservation genetics; Genetic monitoring; Conservation genomics; Genomic monitoring; Forest trees

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In the era of predicted significant environmental change, genetic conservation and monitoring of long-lived forest trees are of paramount importance for the survival of natural populations. Genetic conservation aims to protect and preserve genetic variation, vital for the maintenance of adaptive potential within populations and species. This paper discusses the advances made in gene conservation and genetic monitoring approaches in particular that aim to put into practise a concept that was developed more than 25 years ago, but rarely put into practise. Genetic monitoring, the quantification of temporal changes in population genetic variation and structure, elucidates processes that maintain genetic variation in natural populations, introduces prognosis and helps define tools for the management of forest genetic resources. Based on the geneecological approach, proposed indicators reflect the assessment of genetic variation, genetic drift, gene flow (mating system) and natural selection. Indicators are evaluated in contemporary monitoring schemes by 7-11 verifiers. Genomic data are expected to increase the precision of estimates of adaptive genetic potential and of population genetic parameters due to the significantly higher number of markers assayed. The transition from genetic to genomic monitoring should provide an enhanced potential for disentangling natural selection from demography, and deciphering the association of genetic variation to environmental gradients. In the future, genetic monitoring will be more limited by time-consuming procedures and funding constraints in the assessment of demographic parameters, as well as by conceptual and analytical weaknesses of biostatistical tools, than by genotyping needs and the amount of available sequence data. Its important contribution to applied forest management can be foreseen.

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