Even Bergseng

Production efficiency and size in Norwegian sawmilling

Production efficiency in the Norwegian sawmilling sector was investigated by means of data envelopment analysis, using individual mill observations from the period 1974-91. The resulting efficiency scores were evaluated with respect to size using censored regression analysis and non-parametric comparison tests. Average efficiency estimates indicated that the smallest mills ( h 5000 m 3 yr -1 ) were less efficient than large mills (lumber output > 25000 m 3 yr -1 ). During most of the period studied, average efficiency estimates for the smallest mills were significantly lower than for larger mills.

Applying simulated annealing using different methods for the neighborhood search in forest planning problems

Adjacency constraints along with even flow harvest constraints are important in long term forest planning. Simulated annealing (SA) is previously successfully applied when addressing such constraints. The objective of this paper was to assess the performance of SA under three new methods of introducing biased probabilities in the management unit (MU) selection and compare them to the conventional method that assumes uniform probabilities. The new methods were implemented as a search vector approach based on the number of treatment schedules describing sequences of silvicultural treatments over time and standard deviation of net present value within MUs (Methods 2 and 3, respectively), and by combining the two approaches (Method 4). We constructed three hundred hypothetical forests (datasets) for three different landscapes characterized by different initial age class distributions (young, normal and old). Each dataset encompassed 1600 management units. The evaluation of the methods was done by means of objective function values, first feasible iteration and time consumption. Introducing a bias in the MU selection improves solutions compared to the conventional method (Method 1). However, an increase of computational time is in general needed for the new methods. Method 4 is the best alternative because, for large parts of the datasets, produced the best average and maximum objective function values and had lower time consumption than Methods 2 and 3. Although Method 4 performed very well, Methods 2 and 3 should not be neglected because for a considerable number of datasets the maximum objective function values were obtained by these methods.

Harvest residue potential in Norway – A bio-economic model appraisal

Abstract Use of harvest residues for bioenergy is minimal in Norway, and the proposed increase of 14 TWh in annual bioenergy use by year 2020 may thus to a large part be based on residues from conventional timber harvesting. To judge the potential of harvest residues for bioenergy both in the short and long run, we present cost-supply curves for residue harvesting at national and regional levels. We produce different harvesting scenarios using the detailed forest model Gaya/J and a representative description of the Norwegian forest area from Norwegian national forest inventory (NFI) sample plots including environmental restrictions. Forest information is sufficiently detailed to estimate necessary biomass fractions and calculate costs of harvest residue extraction at plot level. We estimate a maximum annual energy production of 5.3 TWh from harvest residues with the present harvest level, which is far from the official target. In principle, there are two solutions for achieving this target; increase harvests and thus the corresponding residue supply, or increase the use of roundwood for energy purposes on the expense of pulpwood. Scenarios with long-run increase in timber production shows an annual energy potential from harvest residues in the range 6–9 TWh. Thus, to reach the political target roundwood must be used for energy production.

Assessing forest inventory information obtained from different inventory approaches and remote sensing data sources

ContextEvaluations of forest inventories usually end when accuracy and precision have been quantified.AimsWe aim to value the accuracy of information derived from different remote sensing sensors (airborne laser scanning, aerial multispectral and hyperspectral imagery) and four alternative forest inventory approaches.MethodsThe approaches were (1) mean values or (2) diameter distributions both obtained by the area-based approach (ABA), (3) individual tree crown (ITC) segmentation and (4) an approach called semi-individual tree crown (SITC) segmentation. The estimated tree information was assessed and used to evaluate how erroneous inventory data affect economic value and loss due to suboptimal harvesting decisions. Field measured data used as reference come from 23 field plots collected in a study area in south-eastern Norway typical of managed boreal forests in Norway.ResultsThe accuracy of the forest inventory was generally in line with previous studies. Our results show that using mean values from the area-based approach may yield large economic losses, while adding a diameter distribution to the area-based approach yielded less loss than the individual tree crown methods. Adding information from imagery had little effect on the results.ConclusionsTaking inventory costs into account, diameter distributions from the area-based approach without additional information seems favourable.

Combining ecological and economic modelling in analysing a pest invasion contingency plan – The case of pine wood nematode in Norway

Abstract Introductions of the pine wood nematode (PWN), which causes Pine Wilt Disease (PWD), have devastating effects on pine forests in regions with susceptible host trees under suitable climate conditions. Norwegian authorities have proposed a contingency plan if PWN is detected in Norway. We compare the costs of implementing this plan with the costs of further spread and damage of PWN under two climate change scenarios: present and the most likely future climate. With the present climate, PWD will not occur in Norway. Under climatic change, the cost of PWD damage is approximately 0.078–0.157 million NOK (0.01–0.02 million Euros) estimated as net present value with 2 and 4% p.a. discount rate. In contrast, the corresponding costs of implementing the suggested contingency plan will be 1.7–2.2 billion NOK (0.2–0.25 billion Euros). These costs are caused by reduced income from industrial timber production and the costs of the eradication measures. Costs related to reduced recreation or biodiversity are expected to be very high, but are not included in the above estimates. Many of the factors in the analysis are burdened with high uncertainty, but sensitivity analyses indicate that the results are rather robust even for drastic changes in assumptions. The results suggest that there is a need to revise the current PWN contingency plan in Norway.

Effects of site productivity on forest harvest scheduling subject to green-up and maximum area restrictions

ABSTRACT Green-up requirements are of great interest for forests near cities since these forests are commonly used for recreational activities by the local population as well as for commercial forestry activities. We present three formulations to establish green-up requirements, based on a dynamic green-up approach and constructed by means of: (i) a predefined fixed length for the green-up time, (ii) a predefined variable length for the green-up time and (iii) height information produced by the growth simulator. Additionally, restrictions on harvested volume and maximum open areas were applied. All the green-up formulations were applied to five datasets comprising different initial forest conditions regarding age and site index distribution. Results show that higher net present values are obtained by the formulation that allow a predefined variable length for the green-up time and by using the height information from the growth simulator compared to the formulations using a predefined fixed length for the green-up time. The increase in NPV was most pronounced for the old forest datasets and varied between 4.23% and 8.15%. The optimal solution was always found when modeling the green-up requirement using the height information. This formulation also tended to find optimal solutions faster than other formulations.