Articles containing the keyword 'bucking'

This study examined a theoretical model for stand structures from the volumes of pulpwood and saw logs of clear-cut stands. The average stem size was used to estimate the number of cut trees. The distribution was solved using nonlinear derivative-free optimization. The truncated 2-parameter Weibull distribution was used to describe the stand structure of the commercial stems. This method was first tested with harvester data collected from seven clear-cut stands in southern Finland. Validation included reliability in the stand characteristics and goodness-of-fit of the species-specific distributions. The distributions provided unbiased estimates for the saw log volume, while the bias in the estimated pulpwood volume was 2%. The standard stand characteristics from the Weibull distributions corresponded notably well with the harvester data. A Kolmogorov-Smirnov (KS) test rejected two distributions out of 21 cases, when the accurate input variables were available for the theoretical model. The results of the study suggest that the presented method is a relevant option for predicting the stand structure. In practice, the reliability of the presented method was dependent on the quality of the information available from the stand prior to cutting. With a timber trade data set, the solution for the distribution for a clear-cut section was found. The goodness-of-fit was dependent on the accuracy of the visually assessed timber trade variables. Especially the average stem size proved difficult to assess due to high number of understorey pulpwood stems. Due to overestimated average stem sizes, the solved number of harvested trees was underestimated. Less than 50% of the distributions predicted for clear-cut sections passed the KS test.

• Siipilehto, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, P.O. Box 2, FI-00790 Helsinki, Finland E-mail: jouni.siipilehto@luke.fi
• Rajala, Metsä Group, Revontulenpuisto 2, P.O. Box 10, 02020 METSÄ, FI-02100 Espoo, Finland E-mail: miika.rajala@metsagroup.com

Detailed pre-harvest information about the volumes and properties of growing stocks is needed for increased precision in wood procurement planning for just-in-time wood deliveries by cut-to-length (CTL) harvesters. In the study, the non-parametric Most Similar Neighbour (MSN) methodology was evaluated for predicting external quality of Scots pine and Norway spruce, expressed as stem sections fulfilling the saw log dimension and quality requirements of Finnish forest industry, as they affect the recovery of timber assortments and the value of a pre-harvest stand. Effects of external tree quality were evaluated using saw log recovery and saw log reduction caused by stem defects, as well as total timber value (€) and average unit value (€ m^–3) in a stand. Root mean square error (RMSE) of saw log recovery and reduction were 9.12 percentile points (pp) for Scots pine and 6.38 pp for Norway spruce stands. In the unit value considerations, the predictions compared with measurements resulted in the RMSE of 3.50 € m^–3 and the bias of 0.58 € m^–3 in Scots pine stands and 2.60 € m^–3, and 0.35 € m^–3 in Norway spruce stands, respectively. The presented MSN based approach together with the utilization of the external stem quality database included in the ARVO software could provide dimension and external quality predictions usable for pre-harvest assessment of timber stock at a stand level. This prediction methodology is usable especially in analyses where timber assortment recoveries, values and unit prices are compared when different bucking objectives are used.

• Malinen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: jukka.malinen@uef.fi
• Kilpeläinen, Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: harri.kilpelainen@luke.fi
• Verkasalo, Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: erkki.verkasalo@luke.fi

The objective of the study was to ascertain the effects of tree selection (thinning from below, from above and according to stem quality) and timing of first commercial thinning (early and delayed) on the growth, yield and quality of trees in a Scots pine (Pinus sylvestris L.) stand. A long-term field experiment (25 years) was measured in 5-year periods and the further development was simulated with growth and yield models to final cuttings using alternative rotation periods of 55–85 years. The measurements included also the exact location and type of technical defects detected on all trees in the experimental plots. The measured volume increment per unit area during the study period, 25 years after the early thinning stage was the lowest in the plots thinned from below, and the highest in the plots thinned from above or in the delayed thinning plots. However, the largest volume of saw logs during the whole rotation of 80 years was yielded after early first thinning according to the quality. The largest volume of very high-quality butt logs was produced by pruning connected with early thinning from above, and a smaller volume after early thinning according to stem quality but no after thinning from below or delayed first thinning. Without pruning an early quality thinning with one intermediate thinning was the most profitable thinning treatment in the Scots pine stand regardless the rotation length or the interest rate used. By interest rates of 1% and 2%, the optimal rotations were 80–85 years and 70 years respectively. A late thinning at the age of 60 year with long rotation was profitable only for the pruned pine stands with a low interest rate.

• Niemistö, Natural Resources Institute Finland (Luke), Natural resources, Kampusranta 9 C, FI-60320 Seinäjoki, Finland E-mail: pentti.niemisto@luke.fi
• Kilpeläinen, Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: harri.kilpelainen@luke.fi
• Poutiainen, Oulu E-mail: eero1.poutiainen@dnainternet.net

• Kilpeläinen, Finnish Forest Research Institute, Eastern Finland Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: hk@nn.fi
• Lindblad, Finnish Forest Research Institute, Eastern Finland Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jl@nn.fi
• Heräjärvi, Finnish Forest Research Institute, Eastern Finland Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: henrik.herajarvi@metla.fi
• Verkasalo, Finnish Forest Research Institute, Eastern Finland Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: ev@nn.fi

• Nurminen, Metsätoimisto Tuomo Nurminen, Joensuuntie 5 B 8, FI-41800 Korpilahti, Finland E-mail: tn@nn.fi
• Korpunen, Finnish Forest Research Institute, Parkano Research Unit, Kaironiementie 54, FI-39700 Parkano, Finland E-mail: hk@nn.fi
• Uusitalo, Finnish Forest Research Institute, Parkano Research Unit, Kaironiementie 54, FI-39700 Parkano, Finland E-mail: ju@nn.fi

• Koskela, University of Tampere, Dept of Mathematics, Statistics and Philosophy, FI-33014 University of Tampere, Finland E-mail: laura.koskela@uta.fi
• Sinha, Indian Statistical Institute, Kolkata, India E-mail: bks@nn.in
• Nummi, University of Tampere, Dept of Mathematics, Statistics and Philosophy, FI-33014 University of Tampere, Finland E-mail: tn@nn.fi

• Marshall, Ensis Forests, Private Bag 3020, Rotorua, New Zealand E-mail: hamish.marshall@ensisjv.com
• Murphy, Forest Engineering Department, Oregon State University, Corvallis, Oregon 97331, USA E-mail: gm@nn.us
• Boston, Forest Engineering Department, Oregon State University, Corvallis, Oregon 97331, USA E-mail: kb@nn.us

• Uusitalo, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: jori.uusitalo@joensuu.fi
• Kokko, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: sk@nn.fi
• Kivinen, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: vpk@nn.fi