Dynamic treatment units in forest planning improves economic performance over stand-based planning

Abstract High-resolution, wall-to-wall forest information enables precision-driven decision-making in forest management planning. In a case study we compare planning approaches using such information for solving long-term forest planning problems. The two first approaches are based on dynamic treatment unit (DTU) planning with high-resolution cells (12.5 × 12.5 m 2 ) or segments (0.27 ha on average), respectively, solved with a cellular automata heuristics. The third approach is a traditional stand-based approach using stands (5.2 ha on average) and linear programming to solve the planning problem. Fixed costs associated with cutting operations are quantified as each treatment unit is charged with an entry cost of 10 000 SEK. The entry costs are included in the DTU approach while in the stand approach entry costs are applied accordingly in a post-optimization routine. In large, the analyses are based on open-access tools and data provided by Swedish authorities. The traditional stand approach produced plans with 5.2–2.7% lower net present value compared to DTU planning. Most of the differences were caused by greater suboptimal losses in plans produced with the stand approach, but entry costs were also lower in DTU plans. While forestry was less profitable, treatment units were more spatially compact with stands, especially compared to cell-based plans. Therefore, we reason that a combination of modelling of direct costs and use of spatial proxy variables, such as common border length, may be advisable in DTU planning to achieve compact and realistic treatment units. Finally, the results indicate that high-resolution data and DTU planning may better utilize forests’ potential of economic production, compared to the traditional stand approach.