This study investigated biomass allocation in young stands of European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) Karst.) across 31 forest sites in the Western Carpathians, Slovakia. A total of 541 trees aged 2–10 years, originating from natural regeneration and planting, were destructively sampled to quantify biomass in four components: foliage, branches, stems, and roots. Generalized non-linear least squares (GNLS) models with a weighing variance function outperformed log-transformed seemingly unrelated regression (SUR) models in terms of accuracy and robustness, especially for foliage and branch biomass. When using height as the predictor, SUR models tended to underestimate biomass in planted beech, leading to notable underprediction of aboveground and total biomass. Biomass allocation patterns varied significantly by species and regeneration origin. Using a non-linear system of equations and component ratio modelling, we found out that planted spruce displayed low variability and a consistent dominance of needle biomass, while naturally regenerated beech showed greater variability and a higher proportion of stem biomass, reflecting stronger competition-driven vertical growth. Interspecific differences in total biomass were more pronounced when using tree height, with spruce generally exhibiting greater biomass than beech at equivalent heights. Overall, stem base diameter marginally outperformed tree height as a predictor of biomass. However, tree height-based models showed strong performance and are particularly suitable for integration with remote sensing applications. These findings can directly support forest managers and modellers in comparing regeneration methods and biomass estimation approaches for early-stage stand development, carbon accounting, and remote sensing calibration.

While numerous allometric models exist for estimating biomass in trees with single stems, models for multi-stemmed species are scarce. This study presents models for predicting aboveground biomass (AGB) in European hazel (Corylus avellana L.), growing in multi-stemmed shrub form. We measured the size and harvested the biomass of 30 European hazel shrubs, drying and weighing their woody parts and leaves separately. AGB (dry mass) and leaf area models were established using a range of predictors, such as the upper height of the shrub, number of shoots per shrub, canopy projection area, stem base diameter of the thickest stem, and the sum of cross-sectional areas of all stems at the stem base. The latter was the best predictor of AGB, but the most practically useful variables, defined as relatively easy to measure by terrestrial or aerial approaches, were the upper height of the shrub and the canopy projection area. The leaf biomass to AGB ratio decreased with the shrub's height. Specific leaf area of shaded leaves increases with shrub height, but that of leaves at the top of the canopy does not change significantly. Given that the upper shrub height and crown projection of European hazel can be estimated using remote sensing approaches, especially UAV and LIDAR, these two variables appear the most promising for effective measurement of AGB in hazel.