Evaluation of the impact of forest information on regional harvest planning and land productivity based on mixed-integer programming

Keywords: clear-Cutting, forest management, harvest, labor requirements, land productivity, rotation periods

Abstract

Aim of study: To investigate the impact of site class information on forest operation and harvest planning using mixed-integer programming, silviculture regimes, and forest planning. Area of study: A privately owned Japanese cedar “sugi” (Cryptomeria japonica) plantation managed by a forestry association in a cool temperate mountain forest in Japan. Material and methods: Income and timber volume were estimated for each position, forest age, and stem diameter. Age-class distribution, harvest volume, required labor, profit, and other relevant metrics were compared over the forecast period using two optimized harvest plans incorporating status considerations, i.e., with or without site indices. Data were validated based on the premise and assumption that concentrating labor in well-positioned forest management units augments timber yield and improves profits by optimizing timber quality, reducing the proportion of biomass timber, and increasing the proportion of Grade-A timber. Main results: Accounting for status notably increased the total harvested volume by 5.7% over 24 quarters, with a significant 10.8% increase in revenue. Integrating site-class information facilitates efficient and sustainable forest management practices. Stand units with a favorable status may be prioritized for relatively shorter logging operations owing to declining labor availability. Thinning is less affected by a favorable status than clear-cutting, as thinning is financially subsidized, considerably reducing its economic impact. Conversely, logging in areas with poorer status poses risks because a slight decline in timber prices can negatively affect income and expenses. Research highlights: Incorporating site class information helps avoid unprofitable locations and improves harvest plans under constraints, such as labor requirements.

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Published
2026-07-17
How to Cite
Nakajima, T., Mukai, K., Kamei, H., & Tatsuhara, S. (2026). Evaluation of the impact of forest information on regional harvest planning and land productivity based on mixed-integer programming. Forest Systems, 35(1), 20920. https://doi.org/10.5424/fs/2026351-20920
Section
Research Articles