Predicting Effects of Logging Systems and Bucking Strategies forPrivately Owned Sugi (<i>Cryptomeria japonica</i>) Plantations in Atsumi District, Tsuruoka City, Yamagata Prefecture

Abstract

We simulate two forest management strategies applied to privately owned sugi (Cryptomeria japonica) plantations in Atsumi District, Tsuruoka City, Yamagata Prefecture, Japan, in order to assess potential improvements in profitability, labour requirements and harvests. The first strategy uses a traditional logging system with cable yarders yielding high-value logs; the second, 'efficient' strategy uses vehicle-based forestry machines to mass-produce regular logs. We create forest management units with areas greater than three hectares by merging stands and defining topographic conditions using a geographic information system. We consider sixteen variants of each strategy: 15 with candidate rotation ages ranging from 50 to 120 years and one with no clearcutting within the planning horizon. Harvests, labour requirements, and profits for these rotation ages are predicted for each forest management unit. We simulate harvest scheduling using 0-1 integer programming to show the proportions of chosen rotation ages and the changes in periodic harvests, labour requirements, and profits. The two strategies yield similar harvests, although the efficient strategy requires fewer person-days and generates greater profits than the traditional strategy. However, the efficient strategy is not suitable for some topographical conditions.

Estimating Potential Woody Biomass Supply under Sustainable Timber Production from Plantation Forests in a Snowy Mountainous Region of Japan

“…Both the length of a planning period and width of an age class were set at 10 years, and the length of the planning horizon was set at 150 years (15 planning periods). The predicted volumes, revenues and profits could only fluctuate by up to ±10% over the 150-year planning horizon, which reflects the threshold for deviation applied by Nelson et al (1991) and Suzuki et al (2018) in previous simulations of harvesting and net revenue.…”