Search

• Height growth of Norway spruce and Scots pine were assessed from 1986 to 2018. • Trees grew faster than before, especially after the millennium shift. • Increased growth correlated positively with temperature but not precipitation. • Growth increases may suggest higher forest value and shorter rotation periods. For boreal forests in colder climates, changes in environmental conditions are hypothesised to substantially affect ecosystem processes. In this study, trends of top height growth of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst) were analysed using permanent sample plot data from more than 300 long-term experimental sites distributed from temperate zones to the boreal forest conditions in Sweden. By regression analyses, the effects of temperature-sum and precipitation-sum on top height growth were assessed in the period 1986–2018. A significant upward temporal trend in height growth was observed for both species, with the trend more pronounced after the millennium shift. The magnitude of the annual relative height growth after the millennium was about 16.92% and 9.54% higher than expected, respectively for Scots pine and Norway spruce. A potential climate response on height growth was found for both species with temperature-sum positively correlated with top height growth. No significant effect of precipitation-sum on height growth was observed for either species. Our results suggest improved growing conditions and forest sites became more productive in response to increasing temperature in the northern temperate and boreal regions. The increasing growth trends may offer shorter rotation periods and increased forest value for Norway spruce and Scots pine, coupled with contributions of boreal forests to the emerging bio-economy and the regulation of global atmospheric carbon. [ABSTRACT FROM AUTHOR]

Fig. A.4. Three dimensional (3-D) relationship of canopy leaf area index (LAI), coefficient of tree diameter variation (CVD) and height-diameter (H-D) ratio in managed stands of Norway spruce and Scots pine. LAI decreases with increasing tree size heterogeneity. • Basal area and LAI relationship can be modelled using field and remote sensing data. • Tree size variation moderates basal area and LAI relationship. • Sentinel-2 has a potential to be used in growth models. • Structural complexity of managed forests can be described with indices of heterogeneity. The structure of contemporary managed forests is complex and deviates from experimental forests which are usually even-aged monocultures and single-storied. To apply theoretical growth and yield functions on managed forests, adjustments are required, especially for leaf area index (LAI) which is a key biophysical variable in process-based growth models. To asses this, the performance of canopy LAI in modelling the basal area (BA) of managed boreal forests dominated by Norway spruce (Picea abies (L). Karst) and Scots pine (Pinus sylvestris L.) was investigated by heterogeneity analysis. The study was based on the assumption that canopy LAI and BA are strongly related and are vital for estimating stand productivity and growth. Managed forests were represented by field data from the 2016 and 2017 Swedish National Forest Inventory (NFI) campaigns. Species-specific LAI conversion parameters were applied on the general plant area index (PAI) values from hemispheric fish-eye photos taken from the permanent and temporary NFI sample plots. The heterogeneity analysis was studied in two parts by: (a) ground-based stand structural heterogeneity (SSH) described by species composition, coefficient of tree diameter variation, tree social status and height-diameter ratio, and (b) spectral heterogeneity (SPH) by vegetation and textural indices developed from Sentinel-2. Species-specific final (with heterogeneity metrics) and base (without heterogeneity metrics) models were fitted for BA-LAI and BA-PAI relationships by nonlinear least squares and generalised additive regression functions, respectively. The performance of models was assessed by the root-mean-squared error (RMSE, m2 ha−1) and the relative root-mean-squared error (RelRMSE, %) metrics. For both species, BA-LAI final models (FMs) accounting for heterogeneity resulted in larger explained variance than the base models (BMs). Compared with the BMs, FMs with SSH reduced the variance by 55% in Norway spruce (RMSE = 3.33, RelRMSE = 15.39) and 43% in Scots pine (RMSE = 3.70, RelRMSE = 17.38). The fit between BA-LAI with SPH also showed an improvement for Norway spruce (RMSE = 5.56) and Scots pine (RMSE = 5.66) over the BMs, suggesting the potential use of Sentinel-2 in future growth models. The results of the study suggest that in growth models when extrapolating theoretical growth functions to managed forests, there is a need to calibrate the models with the forest structural heterogeneity. This is important for drawing realistic conclusions from growth and yield modelling of managed stands of Norway spruce and Scots pine. [ABSTRACT FROM AUTHOR]