Biomass, basic density and biomass expansion factor functions for European beech (Fagus sylvatica L.) in Denmark

The objective of this study was to analyse the within-tree allocation of biomass and to develop biomass functions for above- and below-ground components of European beech in Denmark. Separate functions were developed for stem, branches, below-ground stump and root system, total above-ground biomass and total tree biomass. For each of these components or aggregate components, models were also developed for the average basic density of wood and bark. To enhance the versatility of the models, a function for estimating the biomass expansion factor (BEF) was also developed. The functions were based on 66 trees measured for total biomass. Model performance was evaluated based on 74 trees measured only for above-ground biomass. The trees were sampled in 18 different forest stands covering a wide range of tree sizes and stand treatments. Models were estimated using a linear mixed-effects procedure to account for within-stand correlations. The functions for biomass and BEFs included only diameter at breast height and total tree height for individual trees as predictor variables. Inclusion of additional variables reflecting site quality or stand density did not improve model performance. The functions for basic density included individual tree diameter, tree height and quadratic mean diameter as predictor variables, indicating an effect of stand density on the basic density of wood and bark.     

Simulating conversion of even-aged Norway spruce into uneven-aged mixed forest: effects of different scenarios on production,economy and heterogeneity

European Journal of Forest Research - Despite a general lack of knowledge on the effects of different strategies, conversion of even-aged stands to uneven-aged forest is ongoing across Europe....     

A state-space approach to stand growth modelling of European beech

Static models of forest growth, such as yield tables or cumulative growth functions, generally fail to recognize that forest stands are dynamic systems, subject to changes in growth dynamics due to silvicultural interventions or natural dynamics. Based on experimental data, covering a wide range of initial spacings and thinning practises, we developed a dynamic stand growth model of European beech in Denmark. The model entailed three equations for predicting dominant height growth, basal area growth, and mortality. The signs of the parameter estimates generally corroborated the anticipated growth paths of dominant height and basal area. Although statistical tests indicated significant systematic deviations between observed and predicted values, the deviations were small and of little practical importance. Cross validation procedures indicated that the model may be applied across a wide range of growth conditions and thinning practises without significant loss of precision.     

Effects of nurse trees,spacing, and tree species on biomass production in mixed forest plantations

Growing concern about increasing concentrations of greenhouse gases in the atmosphere, and resulting global climate change, has spurred a growing demand for renewable energy. In this study, we hypothesized that a nurse tree crop may provide additional early yields of biomass for fuel, while in the longterm leading to deciduous stands that are believed to better meet the demands for other ecosystem services. Ten different species combinations were planted, with two different stocking densities, at three different sites in Denmark. Significant differences, with regard to biomass production, were observed among the different sites (P?P??1?yr^?1 more biomass. The additional biomass production was similar to what was obtained in stands with conifers only (Sitka spruce, Douglas-fir and Japanese larch), which produced 4.9–6.1?t ha^?1yr^?1 more biomass than the pure beech stands. No effects of initial planting density (P?=?.19), or of initial weeding (P?=?.81), on biomass production were observed. Biomass production of the broadleaved crop was in most cases reduced due to competition. However, provided timely thinning of nurse trees, the qualitative development of the trees will allow for long-term timber production.     

Forest inventory inference with spatial model strata

ABSTRACT

In design-based model assisted inference from data gathered in a large area forest inventory under a probability sampling design, one should anticipate spatial heterogeneity in the regression coefficients of an assisting model. The consequence of such heterogeneity is that a global estimate of a root mean squared error (RMSE) becomes unsuited for local predictions. With data from the Danish National Forest Inventory, we demonstrate how to: obtain an assisting model with the lasso method; test for spatial stationarity in regression coefficients of the assisting model; and identify spatial model strata for a post-stratification with either a finite mixture modeling or a lasso spatial clustered coefficients method. Spatial model strata apply to any domain and small area estimation problem without the need for complex modeling when domains or small area changes with shifting user needs. One should not à priori expect a spatial model stratification to improve design-based population and strata estimates of precision, but the reliability of domain and small area RMSEs will improve in presence of statistically significant spatial model strata.