How much timber from Norway spruce (Picea abies L.) is left on the harvesting site as treetops? A study on scaling and grading yields of harvesters

Abstract Key message Timber losses during Norway spruce ( Picea abies L.) harvesting with the cut-to-length method were analyzed using data from 41,948 stems. The volume of timber left on the site after CTL harvesting reached 0.111% overall and 0.454% for stems larger than 34 cm DBH, compared to official production records. On the other hand, for small stems, a surplus of 2.50% of timber was extracted compared to official records. Optimizing measurement accuracy and harvester technology is essential to improve economic efficiency. Context Volume estimation during forest harvesting frequently involves losses due to production technologies and errors of measurement methods. Treetop losses, timber left unrecorded at the harvesting site, represent a significant source of inaccuracies without systematic study. Aims This article aims to assess the volume of treetop timber left on the harvesting site and to evaluate the size of these losses in operational records for Norway spruce ( Picea abies L.) processed using the cut-to-length (CTL) method. Methods We compared standard inventory methods with operational records on a raw sample of 41,948 Norway spruce stems with diameters at breast height (DBH) ranging from 10 to 34 cm, processed by harvesters. We quantified the unrecorded timber in terms of treetop losses and analysed their impact on forestry production records. Results The assessment revealed that for stems with a DBH up to 17 cm, there was between 0.153 and 2.50% of operational surplus timber compared to inventory. This surplus decreases with increasing DBH, turning into losses, which at the diameter class of 33.1 to 35 cm reached 0.454% of the volume of harvested timber. Conclusion The findings highlight that treetops timber losses were significant, suggesting that increased accuracy in recording treetop dimensions could improve yield calculations and economic outcomes for forest operations. Additionally, the results indicate that potential adjustments are needed for automated machine scaling methods to reduce these discrepancies.