Abstract

AbstractGenetic diversity is considered to be a prerequisite for adaptation and adaptability as it is a key element of biological diversity. However, the monitoring of genetic diversity has tended to be ignored in biodiversity monitoring. We report a comprehensive genetic monitoring effort in two dominant forest tree species, which was started with a baseline survey in 12 European beech populations and 10 Norway spruce populations in Germany. The standardized experimental design is based on collecting samples of at least 250 adult trees, and 400 natural regeneration and 400 seed samples and their genotyping with 15–16 high-resolution SSR markers. In addition to commonly used mean values across the markers to quantify genetic diversity, we placed special emphasis on various marker-based, pedigree-based and demographic models for estimating the contemporary effective population size Ne of the different generations. In both beech and spruce, no variation in genetic diversity with mean values across markers was detectable between the studied stands and between age cohorts. We detected that stable allelic diversity in progeny generations is ensured by sufficient gene flow from surrounding forests. However, estimates of effective population size show marked differentiation among populations and among age cohorts. Natural regeneration samples appear to converge on the parent generation, while seed samples show a clear bottleneck effect. The Ne parameter can be used to derive conclusions for sustainable natural regeneration management in forest stands and for seed stand approvals including adequate seed collections for appropriate artificial regenerations.The sibship frequency-based method for Ne estimates is presented as much more robust than the widely used LD estimates, which often fail for samples with too weak relatedness. Despite the distinct kinship structure in our monitoring plots, the contemporary effective population size proves to be an essential parameter for assessing the integrity of the reproductive system.

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