An understanding of the relationship between volume increment and stand density (basal area, stand density index, etc.) is of utmost importance for properly managing stand density to achieve specific management objectives. There are two main approaches to analyse growth–density relationships. The first relates volume increment to stand density through a basic relationship, which can vary with site productivity, age, and potentially incorporates treatment effects. The second is to relate the volume increment and density of thinned experimental plots relative to that of an unthinned experimental plot on the same site. Using a dataset of 229 thinned and unthinned experimental plots of Norway spruce, a growth model is developed describing the relationship between gross or net volume increment and basal area. The models indicate that gross volume increases with increasing basal area up to 50 m² and thereafter becomes constant out to the maximum basal area. Alternatively, net volume increment was maximized at a basal area of 43 m² and decreased with further increases in basal area. However, the models indicated a wide range where net volume increment was essentially constant, varying by less than 1 m³ ha⁻¹ year⁻¹. An analysis of different thinning scenarios indicated that the relative relationship between volume increment and stand density was dynamic and changed over the course of a rotation.

New mortality models were developed for the purpose of improving long-term growth and yield simulations in Finland, Norway, and Sweden and were based on permanent national forest inventory plots from Sweden and Norway. Mortality was modelled in two steps. The first model predicts the probability of survival, while the second model predicts the proportion of basal area in surviving trees for plots where mortality has occurred. In both models, the logistic function was used. The models incorporate the variation in prediction period length and in plot size. Validation of both models indicated unbiased mortality rates with respect to various stand characteristics such as stand density, average tree diameter, stand age, and the proportion of different tree species, Scots pine ( L.), Norway spruce ( (L.) Karst.), and broadleaves. When testing against an independent dataset of unmanaged spruce-dominated stands in Finland, the models provided unbiased prediction with respect to stand age.Pinus sylvestris Picea abies

A new stand-level growth and yield model, consisting of component equations for stand volume, basal area, survival, and dominant stand height, was developed from a dataset of long-term trials for managed thinned and unthinned even-aged Norway spruce (Picea abies (L.) Karst.) forests in Norway. The developed models predict considerably faster growth rates than the existing Norwegian models. Further, it was found that the existing Norwegian stand-level models do not match the data from the thinning trails. The significance of thinning response functions indicated that thinning increases basal area growth while reducing competition related mortality. No significant effects of thinning were found in the dominant stand height growth. Model examination by means of cross-validation indicated that the models were unbiased and performed well within the data range. An application of the developed stand-level model highlights the potential use for these models in comparing different management scenarios.

An understanding of relationships between stand volume growth and stand density is important for making informed management decisions. Contradictions concerning these relationships have been attributed to differences in definitions of volume growth and stand density, among other pitfalls. Models were developed to test growth-density relationships using past-growth data from three thinning studies in 11- to 41-year-old loblolly pine (Pinus taeda L.) plantations. Relationships between gross growth and stand density measures of basal area per hectare, stand density index, volume per hectare, and relative spacing were compared. Relative growth-density relationships were also compared by relating the growth and density of thinned plots to unthinned plots. Analyses indicated that gross volume growth increases with increasing stand density when accounting for age, quadratic mean diameter, and site quality. Results from relative growth-density relationships suggested that thinned stands can exhibit increased growth at relatively lower densities compared to that of an unthinned stand on a similar site. The fitted models, across all four density measures, indicated ever-increasing gross volume growth with increasing stand density within the range of observed data for loblolly pine plantations.

As a carbon dioxide removal measure, the Norwegian government is currently considering a policy of large-scale planting of spruce (Picea abies (L) H. Karst) on non-forested lands (i.e., aff-/reforestation) and secondary forested lands dominated by early successional broadleaved tree species (i.e., improved forest management).  Given the need to achieve net zero emissions in the latter half of the 21st century in effort to limit the global mean temperature rise to “well below” 2 °C, the mitigation potential of such a policy is unclear given relatively slow tree growth rates in the region.  Further convoluting the picture is the magnitude and relevance of surface albedo changes linked to such projects, which typically counter the benefits of an enhanced forest CO2 sink in high latitude regions.  Here, we carry out a rigorous empirical assessment of the terrestrial carbon dioxide removal (tCDR) potential of large-scale aff-/reforestation (AR) and improved forest management (IFM) projects in Norway, taking into account transient developments in both terrestrial carbon sinks and surface albedo over the 21st century and beyond.  We find that surface albedo changes would likely play a negligible role in counteracting the carbon cycle benefit of tCDR, yet given slow forest growth rates in the region, meaningful tCDR benefits from AR and IFM projects would not be realized until the end of the 21st century, with maximum benefits occurring around 2150.  We estimate Norway’s total accumulated tCDR potential at 2100 and 2150 (including surface albedo changes) to be 447 (± 240) and 852 (± 295) Mt CO2-eq. at mean costs of US$ 29 (± 18) and US$ 26 (± 14) per ton CDR, respectively.  For perspective, the accumulated tCDR potential at 2100 represents around 8 years of Norway’s total current annual production-based (i.e., territorial) CO2-eq. emissions.