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Establishment of a genetic monitoring system for beech and spruce trees in Germany to assess the genetic adaptability of tree species against environmental changes (GenMon)


Project code: 28WC4092
Contract period: 13.06.2016 - 30.09.2019
Budget: 1,603,445 Euro
Purpose of research: Inventory & Assessment

Within the project “GenMon” a genetic monitoring network will be installed for beech (Fagus sylvatica) and spruce (Norway spruce) in Germany for the first time. The main goal is to assess the genetic variation and the status of the genetic system of different populations as well as its dynamics in time and space on the basis of criteria, indicators and verifiers. Therewith the effects of factors influencing the genetic system in the forests can be estimated and evaluated. Changes at the level of the genetic system have a delayed effect on tree composition and stability of forest stands. Therefore, genetic monitoring can serve as an early warning system for changes at higher levels (diversity of species and habitats), which is very important under climate change.
The genetic monitoring network will comprise 14 plots for beech and 10 plots for spruce in Germany. The meth-odology is based on the “Concept of a Genetic Monitoring of Forest Tree Species in the Federal Republic of Germany” but takes into account also experiences from already accomplished punctual pilot studies. On each monitoring plot both genetic and phenological observation will be conducted. Genetic investigations will mainly be based on neutral nuclear microsatellites, but new adaptive markers (SNP) related with phenotypical traits will be developed within the project too. After successful development, the extracted and long-term stored genetic material (DNA) can be examined with these markers. Based on the genotypes of the adult trees, the natural re-generation and the seeds indicators for genetic processes (e.g. genetic multiplicity, diversity and allele distribu-tion) will be calculated. Additionally simulation studies based on empirical monitoring data will help to identify any critical developments, which could for example be caused by human intervention of varying intensity.

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