Influence of timber harvesting costs on the layout of cuttings and economic return in forest planning based on dynamic treatment units

Abstract

Aim of study: To analyze the influence of harvesting costs on the distribution and type of cuttings when forest management planning is based on the dynamic treatment units (DTUs) approach.Area of study: A Mediterranean pine forest in Central Spain.Materials and methods: Airborne laser scanning data were used in area-based approach to predict stand attributes and delineate segments that were used as calculation units. Predicted stand attributes and existing models for diameter distribution and individual-tree growth were used to simulate alternative management schedules for each segment for a 60-year planning horizon divided into three 20-year periods. Three alternative forest planning problems were formulated. They aimed to maximize or minimize net income, or maximize timber production with a constant flow of harvested timber. Spatial goals were used in all cases to enhance the clustering of treatments.Main results: Maxizing timber production without considering harvesting costs can be costly, even close to the plan that minimized net incomes. Maximizing net incomes led to frequent use of final felling instead of thinnings, placing cuttings near forest roads and creating more compact DTUs than obtained in the plan that maximized timber production.Research highlights: Compared to previous studies on DTUs, this study integrated felling and forwarding costs, which depended on distance to road and stand attributes, in the process of creating DTUs by means of spatial optimization.

Trade-offs between economic profitability, erosion risk mitigation and biodiversity in the management of uneven-aged Abies alba Mill. stands

“…6) and transportation (Eq. 7) cost functions have been presented in earlier studies (Solano et al 2007;González-Olabarria and Pukkala 2011;Pascual et al 2018). In this study, distance to road was assumed to be 500 m in all cases to represent the average forwarding distance.…”

Improving dynamic treatment unit forest planning with cellular automata heuristics

“…Pukkala (2009) showed that heuristic methods can successfully handle large spatial problems. This was shown for DTU purposes by and was further highlighted by Pascual et al (2018). Noteworthy heuristics applied to DTU problems are threshold accepting , reduced cost (Heinonen et al 2018;Packalén et al 2011;Pukkala et al 2009), genetic algorithm (Lu and Eriksson 2000) and simulated annealing (de Miguel and Pukkala 2013; Öhman 2001).…”

“…Previous research has studied the concept and performance of DTUs and presented various models for conducting this type of forest planning (e.g., Pascual et al 2018;Heinonen et al 2018;Wilhelmsson et al 2021). The economic incentive to cluster treatments lies in the entry cost for forest operations.…”

“…Borges et al (2017) showed that the entry cost influences the optimal treatment unit size, which has been a concern for past studies concerned with DTU. However, instead of directly modeling the entry cost, most DTU studies have used proxy variables such as conditional common borders in combination with distance from the nearest road (Pascual et al 2018). Their model tracked the cut-to-cut and cut-touncut borders, and metrics were included in the utility function to drive the clustering of treatments.…”

“…CA was first presented by von Neumann (1966) and introduced in forest planning contexts by Strange et al (2002). It has been used to solve forest planning problems with a DTU approach in several studies Mathey et al 2007;Pascual et al 2018;Pukkala 2019). In the general form, a CA is constituted of a lattice of cells where each cell may take on a finite set of states.…”