Articles containing the keyword 'decision support'

Many kinds of planning systems have been labelled decision support systems (DSS), but few meet the most important features of real DSSs in planning and control of wood procurement. It has been concluded that many reasons exist to develop DSSs for wood procurement. The purchasing of timber seems to be one of the most promising areas for DSS, because there is no formal structure for these operations and decisions deal with human behaviour. Relations between DSSs and different features of the new approaches in wood procurement are also discussed, and hypotheses for future studies suggested.

• Harstela, E-mail: ph@mm.unknown

The purpose of this study was to prepare a comprehensive, computerized teak (Tectona grandis L.f) plantation yield model system that can be used to describe the forest dynamics, predict growth and yield and support forest planning and decision-making. Extensive individual tree and permanent sample plot data were used to develop tree-level volume models, taper curve models and stand-level yield models for teak plantations in Panama. Tree volume models were satisfactorily validated against independent measurement data and other published models. Tree height as input parameter improved the stem volume model marginally. Stand level yield models produced comparable harvest volumes with models published in the literature. Stand level volume product outputs were found like actual harvests with an exception that the models marginally underestimate the share of logs in very large diameter classes. The kind of comprehensive model developed in this study and implemented in an easy to use software package provides a very powerful decision support tool. Optimal forest management regimes can be found by simulating different planting densities, thinning regimes and final harvest ages. Forest practitioners can apply growth and yield models in the appropriate stand level inventory data and perform long term harvest scheduling at property level or even at an entire timberland portfolio level. Harvest schedules can be optimized using the applicable financial parameters (silviculture costs, harvesting costs, wood prices and discount rates) and constraints (market size and operational capacity).

• Seppänen, Verdas Oy, Kihlinkuja 7, FI-50600 Mikkeli, Finland E-mail: petteri@verdas.fi
• Mäkinen,  Simosol Oy. Hämeenkatu 10, FI-11100 Riihimäki, Finland E-mail: antti.makinen@simosol.fi

Due to changes in forest management in various European countries, hardwood forest areas and amounts will increase. Sustainable and individual utilization concepts have to be developed for the upcoming available resource. Studies conclude that there is low potential for hardwoods in the traditional appearance market thus the application areas have to be extended to new structural innovative products. This paper examines the extension to a future laminated beech wood supply network which would be a combination of already existing and new production facilities. For a better future use of hardwood raw materials it is necessary to consider the entire supply chain. This also better shows a total hardwood value chain. Therefore, this paper provides data to the solid hardwood business and develops a mixed integer linear programming to design a laminated beech wood supply network. The model is applied to Austria as the sample region. It covers the important strategic decisions where to locate a downstream facility within the existing production network with the lowest supply network cost. Fourteen scenarios are developed to examine various future network configurations. Results about optimal material flows and used sawmills as well as downstream production facilities are presented in form of material and financial performances. Two optimal laminated beech production locations are determined by the calculated scenarios results, and the impact of a new sawmill is analyzed which is focused on beech.

• Kühle, BOKU - University of Natural Resources and Life Sciences, Vienna, Department of Material Science and Process Engineering, and Renewable Institute of Wood Technology Materials, Konrad-Lorenz-Straße 24, 3430 Tulln, Austria E-mail: skuehle@boku.ac.at
• Teischinger, BOKU - University of Natural Resources and Life Sciences, Vienna, Department of Material Science and Process Engineering, and Renewable Institute of Wood Technology Materials, Konrad-Lorenz-Straße 24, 3430 Tulln, Austria E-mail: alfred.teischinger@boku.ac.at
• Gronalt, BOKU - University of Natural Resources and Life Sciences, Vienna, Department of Economics and Social Sciences, Institute of Production and Logistics, Feistmantelstraße 4, 1180 Vienna, Austria E-mail: manfred.gronalt@boku.ac.at

Rut formation caused by logging operations has been recognised as a challenge for Swedish forestry. Frequent traffic with heavy machines on extraction roads, together with a warmer climate, is one of the factors that increases the risk of rut formation in forests. One possible way to control this impact of logging operations is to design and apply decision support tools that enable operators to take sensitive areas into account when planning extraction roads. In this study, 16 different logging sites in south-eastern Sweden were surveyed after clear-cut. Information was collected about extraction roads (i.e. traffic intensity, whether the roads had been reinforced with slash) and ruts. Digital maps such as cartographic depth-to-water (DTW) index and soil type were also examined for any connection to rut positions. Soil type and traffic intensity were found to be significant factors in rut formation, while DTW and slash reinforcement were not. However, the DTW map combined with other information, such as soil type, could contribute to decision support tools that improve planning of extraction roads.

• Mohtashami, The forestry research institute of Sweden, Skogforsk, Uppsala Science Park, SE-751 83 Uppsala, Sweden E-mail: sima.mohtashami@skogforsk.se
• Eliasson, The forestry research institute of Sweden, Skogforsk, Uppsala Science Park, SE-751 83 Uppsala, Sweden http://orcid.org/0000-0002-2038-9864 E-mail: lars.eliasson@skogforsk.se
• Jansson, The forestry research institute of Sweden, Skogforsk, Uppsala Science Park, SE-751 83 Uppsala, Sweden http://orcid.org/0000-0002-3018-9161 E-mail: gunnar.jansson@skogforsk.se
• Sonesson, The forestry research institute of Sweden, Skogforsk, Uppsala Science Park, SE-751 83 Uppsala, Sweden http://orcid.org/0000-0002-2018-7496 E-mail: johan.sonesson@skogforsk.se

Environmental planning for of the maintenance of different conservation objectives should take into account multiple contrasting criteria based on alternative uses of the landscape. We develop new concepts and approaches to describe and measure conflicts among conservation objectives and for resolving them via multiobjective optimization. To measure conflicts we introduce a compatibility index that quantifies how much targeting a certain conservation objective affects the capacity of the landscape for providing another objective. To resolve such conflicts we find compromise solutions defined in terms of minimax regret, i.e. minimizing the maximum percentage of deterioration among conservation objectives. Finally, we apply our approach for a case study of management for biodiversity conservation and development in a forest landscape. We study conflicts between six different forest species, and we identify management solutions for simultaneously maintaining multiple species’ habitat while obtaining timber harvest revenues. We employ the method for resolving conflicts at a large landscape level across a long 50-years forest planning horizon. Our multiobjective approach can be an instrument for guiding hard choices in the conservation-development nexus with a perspective of developing decision support tools for land use planning. In our case study multiple use management and careful landscape level planning using our approach can reduce conflicts among biodiversity objectives and offer room for synergies in forest ecosystems.

• Mazziotta, University of Jyväskylä, Department of Biological and Environmental Science, P.O. Box 35, FI-40014 University of Jyväskylä, Finland; Center for Macroecology Evolution and Climate, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen, Denmark; Stockholm Resilience Centre, Stockholm University, Kräftriket 2b, 11429 Stockholm, Sweden http://orcid.org/0000-0003-2088-3798 E-mail: a_mazziotta@hotmail.com
• Podkopaev, University of Jyväskylä, Department of Biological and Environmental Science, P.O. Box 35, FI-40014 University of Jyväskylä, Finland; Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland E-mail: dmitry.podkopaev@ibspan.waw.pl
• Triviño, University of Jyväskylä, Department of Biological and Environmental Science, P.O. Box 35, FI-40014 University of Jyväskylä, Finland E-mail: maria.trivino@jyu.fi
• Miettinen, University of Jyväskylä, Faculty of Information Technology, P.O. Box 35, FI-40014 University of Jyväskylä, Finland E-mail: kaisa.miettinen@jyu.fi
• Pohjanmies, University of Jyväskylä, Department of Biological and Environmental Science, P.O. Box 35, FI-40014 University of Jyväskylä, Finland E-mail: tahti.t.pohjanmies@jyu.fi
• Mönkkönen, University of Jyväskylä, Department of Biological and Environmental Science, P.O. Box 35, FI-40014 University of Jyväskylä, Finland E-mail: mikko.monkkonen@jyu.fi

A new sampling design, the local pivotal method (LPM), was combined with the micro stand approach and compared with the traditional systematic sampling design for estimation of forest stand variables. The LPM uses the distance between units in an auxiliary space – in this case airborne laser scanning (ALS) data – to obtain a well-spread sample. Two sets of reference plots were acquired by the two sampling designs and used for imputing data to evaluation plots. The first set of reference plots, acquired by LPM, made up four imputation alternatives (varying number of reference plots) and the second set of reference plots, acquired by systematic sampling design, made up two alternatives (varying plot radius). The forest variables in these alternatives were estimated using the nonparametric method of most similar neighbor imputation, with the ALS data used as auxiliary data. The relative root mean square error (RelRMSE), stem diameter distribution error index and suboptimal loss were calculated for each alternative, but the results showed that neither sampling design, i.e. LPM vs. systematic, offered clear advantages over the other. It is likely that the obtained results were a consequence of the small evaluation dataset used in the study (n = 30). Nevertheless, the LPM sampling design combined with the micro stand approach showed potential for improvement and might be a competitive method when considering the cost efficiency.

• Saad, Swedish University of Agricultural Sciences (SLU), Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden E-mail: rami.saad@slu.se
• Wallerman, Swedish University of Agricultural Sciences (SLU), Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden E-mail: jorgen.wallerman@slu.se
• Holmgren, Swedish University of Agricultural Sciences (SLU), Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden E-mail: johan.holmgren@slu.se
• Lämås, Swedish University of Agricultural Sciences (SLU), Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden E-mail: tomas.lamas@slu.se

• Nordström, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd 1, SE-901 83 Umeå, Sweden E-mail: eva-maria.nordstrom@slu.se
• Eriksson, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd 1, SE-901 83 Umeå, Sweden E-mail: loe@nn.se
• Öhman, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd 1, SE-901 83 Umeå, Sweden E-mail: ko@nn.se

• Kurttila, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: mikko.kurttila@joensuu.fi
• Leskinen, Finnish Environment Institute, Research Programme for Production and Consumption, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: pl@nn.fi
• Pykäläinen, Metsämonex Ltd., Joensuu, Finland E-mail: jp@nn.fi
• Ruuskanen, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: tr@nn.fi

• Coulter, College of Forestry and Conservation, University of Montana, 32 Campus Drive, Missoula, MT 59812, USA E-mail: elizabeth.coulter@cfc.umt.edu
• Sessions, Department of Forest Engineering, College of Forestry, Oregon State University, 204 Peavy Hall, Corvallis, OR 97331-5706, USA E-mail: js@nn.us
• Wing, Department of Forest Engineering, College of Forestry, Oregon State University, 204 Peavy Hall, Corvallis, OR 97331-5706, USA E-mail: mgw@nn.us

• Vestlund, Swedish University of Agricultural Sciences, Department of Silviculture, P.O. Box 7060, SE-750 07 Uppsala, Sweden E-mail: karin.vestlund@ssko.slu.se
• Nordfjell, Swedish University of Agricultural Sciences, Department of Silviculture, SE-901 83 Umeå, Sweden E-mail: tm@nn.se
• Eliasson, Swedish University of Agricultural Sciences, Department of Silviculture, SE-901 83 Umeå, Sweden E-mail: le@nn.se

• Laukkanen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: sanna.laukkanen@joensuu.fi
• Palander, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: tp@nn.fi
• Kangas, UPM-Kymmene Forest, P.O. Box 32, FI-37601 Valkeakoski, Finland E-mail: jk@nn.fi
• Kangas, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ak@nn.fi

• Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: annika.kangas@metla.fi
• Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: jk@nn.fi
• Pykäläinen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: jp@nn.fi

• Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: jyrki.kangas@metla.fi
• Leskinen, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: pl@nn.fi
• Pukkala, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: tp@nn.fi

• Kärhä, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: karha@forest.joensuu.fi
• Oinas, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: so@nn.fi

This review systematically analyses and classifies research and review papers focusing on discrete event simulation applied to wood transport, and therefore illustrates the development of the research area from 1997 until 2017. Discrete event simulation allows complex supply chain models to be mapped in a straightforward manner to study supply chain dynamics, test alternative strategies, communicate findings and facilitate understanding of various stakeholders. The presented analyses confirm that discrete event simulation is well-suited for analyzing interconnected wood supply chain transportation issues on an operational and tactical level. Transport is the connective link between interrelated system components of the forest products industry. Therefore, a survey on transport logistics allows to analyze the significance of entire supply chain management considerations to improve the overall performance and not only one part in isolation. Thus far, research focuses mainly on biomass, unimodal truck transport and terminal operations. Common shortcomings identified include rough explanations of simulation models and sparse details provided about the verification and validation processes. Research gaps exist concerning simulations of entire, resilient and multimodal wood supply chains as well as supply and demand risks. Further studies should expand upon the few initial attempts to combine various simulation methods with optimization.

• Kogler, Institute of Production and Logistics, Department of Economics and Social Sciences, University of Natural Resources and Life Sciences, Vienna, Feistmantelstrasse 4, A-1180 Vienna, Austria https://orcid.org/0000-0001-8811-152X E-mail: christoph.kogler@boku.ac.at
• Rauch, Institute of Production and Logistics, Department of Economics and Social Sciences, University of Natural Resources and Life Sciences, Vienna, Feistmantelstrasse 4, A-1180 Vienna, Austria http://orcid.org/0000-0002-5812-4415 E-mail: peter.rauch@boku.ac.at