iForest - Biogeosciences and Forestry (Aug 2023)

Evaluation of operating cost management models for selection cutting in Scandinavian continuous cover forestry

  • Bianchi S,
  • Ahtikoski A,
  • Muhonen T,
  • Holmström E,
  • Valkonen S,
  • Nuutinen Y

DOI
https://doi.org/10.3832/ifor4204-016
Journal volume & issue
Vol. 16, no. 1
pp. 218 – 225

Abstract

Read online

The importance of continuous cover forestry (CCF) is increasing, yet there is lack of data and understanding about many aspects of this management, including the operational costs. Our objectives were to retrieve available harvesting cost models from published studies on selection cutting in Norway-spruce-dominated stands in Scandinavian countries and to evaluate them against real case studies. First, we retrieved three recently published harvesting cost models which provided explicit cost functions. Models 1 and 2, based on rotation forestry (RF) data and adapted for CCF, had separate sub-models for cutting and hauling costs. Model 3 was based on CCF data and produced total harvesting costs, including the cutting and hauling costs combined. Second, we measured cutting costs for 29 harvesting operations on stands with different stages of CCF structure. We then compared the observations with the simulations of Models 1 and 2 cutting cost sub-models for those cases. Third, we expanded the dataset, including a further 34 harvesting operations in stands with more advanced CCF structures (without measured costs). We then simulated the total harvesting costs for all three models in this dataset to investigate their general behaviour. On average, Models 1 and 2 cutting cost sub-models had relatively good and consistent predictions compared with the observed values. However, they differed in total costs due to different estimates for the hauling cost sub-models. Model 3 had predictions comparable to Models 1 and 2 in the more advanced stages of CCF, but much higher in the less advanced. This study provides important data regarding cutting costs in CCF and demonstrates the feasibility of using existing harvesting cost models.

Keywords