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Instructions for optimal any-aged forestry
- Pukkala, Timo
- Forestry 2018 v.91 no.5 pp. 563-574
- discount rate, forest thinning, heat sums, models, probability, profitability, stand basal area, stand management, tree and stand measurements, trees, uneven-aged management, Finland
- In this study, any-aged forestry (AAF) refers to forest management in which no explicit choice is made between even- and uneven-aged management, or between rotation forest management and continuous cover forestry. Optimal AAF is more profitable than optimal even- or uneven-aged management because AAF has fewer constraints. This study developed management instructions for optimal AAF. The instructions consist of four models, the first indicating the probability that an immediate cutting in the stand is the optimal decision. In case of cutting, the second model gives the probability that partial cutting (thinning) is optimal. If thinning is selected, the remaining two models indicate how many trees should be removed from different diameter classes. The models for optimal management were based on optimized cutting schedules of 2095 stands, located in different parts of Finland. The use of the model requires that discount rate is specified, and site fertility and temperature sum of the stand are known. The required growing stock characteristics are stand basal area, mean tree diameter and the basal area of pulpwood-sized trees (dbh 8–18 cm). High stand basal area and large mean tree size increase the probability that cutting is the optimal decision. High basal area of pulpwood-sized trees increases the probability that partial cutting is optimal. Thinning from above is the optimal type of cutting in most cases. The models were tested by comparing the model-driven stand management schedules with stand-level optimizations. Schedules based on the models resulted in equally good net present values as schedules based on optimizations. When the discount rate was 3 per cent or more, the models led to similar profitability as stand-level optimization.