The study covers the development and calibration of a set of functions to estimate volume, dry matter, and nutrient contents for a regional database of Sessile oak (Quercus petraea [Matt.] Liebl.) in northeast Germany. We applied regression analyses to biomass samples from a total of 22 trees using methods of Randomized Branch Sampling and Importance Sampling. Coarse wood volume and dry matter content in coarse wood were available for all sample trees. A subsample of ten trees was used for separate estimations for the components foliage, twigs, branches, and coarse wood. Subsequent analyses focused on the respective contents of carbon, nitrogen, potassium, calcium, magnesium, phosphorus, and sulphur. The determined allometric functions use diameter and/or tree height to estimate individual volume, dry matter, and nutrient contents. Stand values for mean basal area diameter, mean height, and stem number per hectare were applied to calculate biomass data for whole stands. Analyses of the different components show that trees during growth accumulate coarse wood dry matter to an increasing degree. Dry matter of the other components is growing much slower. The amounts stay almost constant for twigs and foliage above a certain age. Nutrient contents over time follow an analogue course except for branches where – similarly to coarse wood – the share of nutrients in the respective totals per trees is continuously increasing. The established models are restricted to trees in the diameter range of 8–40 cm. Within this range tree height is statistically insignificant as explanatory variable in 81% of all cases. Further research is needed to extend the range of reliable model predictions especially for larger trees.

Keywords: Biomass functions, Nutrient contents, Quercus petraea, Randomized Branch Sampling.