Articles containing the keyword 'forest plan'

The impact of carbon sequestration on the financial profitability of four tree plantation cases in Finland and the Philippines were examined. On the basis of stem wood growth; the accumulation of carbon in forest biomass, the formation and decomposition of litter, and the carbon flow in wood-based products were assessed for each reforestation case representing boreal (Finland) and moist tropical conditions (the Philippines). Using different unit values for carbon sequestration the profitability of reforestation was estimated for a fixed 100-year period on a per hectare basis. The financial profitability of reforestation increased notably when the sequestered carbon had high positive values. For example, when the value of carbon sequestration was set to be Twenty-five United States Dollar per megagram of carbon (25 USO/Mg C), the internal rate of return (IRR) of a reforestation investment with Norway spruce (Picea abies (L.) H. Karst.) in Finland increased from 3.2% to 4.1 %. Equally, the IRR of reforestation with mahogany (Swietenia macrophylla King) in the Philippines increased from 12.8% to 15.5%. The present value of carbon sequestration ranged from 39–48% and from 77–101% of the present value of the reforestation cost in Finland and the Philippines, respectively when a 25 USO/Mg C shadow price and a 5% discount rate were applied. Sequestration of one mg of carbon in reforestation in Finland and the Philippines was estimated to cost from 10.5–20.0 and from 4.0–13.6 USO, respectively.

• Niskanen, E-mail: an@mm.unknown
• Rantala, E-mail: tr@mm.unknown
• Saastamoinen, E-mail: os@mm.unknown

Ten trails, one kilometre each, were evaluated by 15 persons for scenic beauty, recreational value and variety. All trails passed through commercially managed forests dominated by conifers. The trails were first evaluated by viewing computer simulations based on a series of graphical illustrations of forest landscapes, then from a slide show, and finally in the field. In the computer simulation and slide show, landscape pictures along the trail at an interval of 35–40 m were presented for 3–4 seconds. The ranks between slide show and field were slightly more similar than those between simulation and field. The mean correlation of 12 persons between the field ranking and assessment of either computer simulations or slide shows or graphics than scenic beauty or recreational value. Spearman’s rank correlations computed from median scores of a group of 12 peers were clearly better than the average of individual persons varying from 0.6 to 0.9.

The PDF includes an abstract in Finnish

• Nousiainen, E-mail: in@mm.unknown
• Pukkala, E-mail: tp@mm.unknown

An alternative approach to formulating a forestry goal programming problem is presented. First, single objective optima levels are solved. The Analytical Hierarchy Process is applied in the estimation of a priori weights of deviations from the goal target levels. The ratios of the weights can be interpreted as relative importance of the goals, respectively. The sum of the weighted deviations from all single optima levels associated with the management goals is minimized. Instead of absolute deviations, relative ones are used. A case study problem of forest management planning with several objectives, measured in different units, is analysed.

The PDF includes an abstract in Finnish.

• Kangas, E-mail: jk@mm.unknown
• Pukkala, E-mail: tp@mm.unknown

Length of the regeneration period is a criterion commonly used for comparing different reforestation methods. The time factor should be evaluated using a realistic system for long-term planning. In this paper the preliminary evaluation is made by simplified calculations based on the development series. The slow regeneration method is assumed to be otherwise equal to the rapid one but it has a 5- or 10-years delay at the beginning, and the rotation is thus the final cutting age plus 5- or 10-years delay. Cost of the time delay is taken to be the difference in reforestation costs that makes the rapid and the slow methods equivalent. Calculations are made using zero costs for the slow method; but if the cost of the slow method increases, the critical cost difference decreases very slowly. The final cutting age and the regeneration method must be decided simultaneously. Therefore, the cost of the time delay is presented as a function of final cutting age. By maximizing the average annual revenue, rotation can be even increased if more rapid but more expensive regeneration method is used.

The PDF includes a summary in English.

• Lappi, E-mail: jl@mm.unknown

The planning of timber production in a forestry unit is divisible into two phases. In the first phase, planning provides the decision-maker with a number of possible timber production policies; these policies define the production possibility boundary. After the decision-maker has chosen one of these policies, planning moves to the second phase, in which a detailed programme is prepared with a view to meeting the requirements of the timber production policy accepted. The paper indicates one possibility of solving these two tasks simultaneously. In the first phase, the solution of the primal linear programming problem is employed and in the second phase the respective dual or shadow price solution.

The PDF includes a summary in English.

• Kilkki, E-mail: pk@mm.unknown
• Pökälä, E-mail: rp@mm.unknown
• Siitonen, E-mail: ms@mm.unknown

This paper describes different methods of long-term forecasts in forest management planning with a special attention on intention forecasts for a total forest property or district. Methods for calculating the sustained yield on the basis of the actual increment or the yearly area cut are discussed. It is concluded that a better estimate of the sustained yield is obtainable by the application of a long-term forecast technique. Forecasts for 100 years should not be viewed as plans, but as a background for making short-term decisions. Some of the long-term-type programmes, such as the programme of maximum profit, sustained yield in volume and in money are discussed briefly.

It is pointed out that there is often present a conflict between the various elements of the policy formulated by a forest owner. This leads to the conclusion that the calculations of the profitability of single projects may be misleading.

The precision of a long-term forecast is discussed, and how under certain assumptions the error of the allowable cut is influenced by errors in area, volume, age etc. It is shown that the precision in area and volume is more important in this connection than, say, the precision in increment. In conclusion, existing knowledge, methods and equipment for calculations constitute a basis for long-term forecasts which make them an important instrument in forest management planning.

The PDF includes a summary in English.

• Seip, E-mail: hs@mm.unknown

Silva Fennica Issue 64 includes presentations held in 1947 in the third professional development courses, arranged for foresters working in the public administration. The presentations focus on practical issues in forest management and administration, especially in regional level. The education was arranged by Forest Service. Two of the presentations were published in other publications than Silva Fennica issue 64.

This presentation discusses different ways of organizing felling cycle, forest management practices used in the forests of Finnish forest research institute, and how good practices developed in the institue could be applied in state forests.

• Heikinheimo, E-mail: oh@mm.unknown

The aim of the study was to develop a method for calculating a cutting budget that is adapted to the present forest management practices. The cutting budget determines the volume of annual cuttings for a forest holding in a certain period of time. Effect of fellings on the cutting budget depends on the cutting methods used. The study aimed at proving that growth of the forest can be estimated based on growing stock and structure of the forests for a certain time period. Accordingly, adequate drain can be defined in advance. The cutting budget is based on age-class distribution of the forest holding, which is most applicable for even-aged forestry. Calculation is based on area of the forest land and estimated volume of the growing stock. Also, the quality of the forest soil can be taken into account when age-class distribution is used. A suitable period for estimating a cutting budget is suggested to be 20 years, which is divided in two 10-year periods. The cutting budget it is included in a forestry plan. An example of a cutting plan based on the method is presented.

The PDF includes a summary in German.

• Lihtonen, E-mail: vl@mm.unknown

The paper examines the needs, premises and criteria for effective public participation in tactical forest planning. A method for participatory forest planning utilizing the techniques of preference analysis, professional expertise and heuristic optimization is introduced. The techniques do not cover the whole process of participatory planning, but are applied as a tool constituting the numerical core for decision support. The complexity of multi-resource management is addressed by hierarchical decision analysis which assesses the public values, preferences and decision criteria toward the planning situation. An optimal management plan is sought using heuristic optimization. The plan can further be improved through mutual negotiations, if necessary. The use of the approach is demonstrated with an illustrative example. Its merits and challenges for participatory forest planning and decision making are discussed and a model for applying it in general forest planning context is depicted. By using the approach, valuable information can be obtained about public preferences and the effects of taking them into consideration on the choice of the combination of standwise treatment proposals for a forest area. Participatory forest planning calculations, carried out by the approach presented in the paper, can be utilized in conflict management and in developing compromises between competing interests.

• Kangas, E-mail: jk@mm.unknown
• Loikkanen, E-mail: tl@mm.unknown
• Pukkala, E-mail: tp@mm.unknown
• Pykäläinen, E-mail: jp@mm.unknown

The establishment of moose (Alces alces L.) winter feeding sites, their utilization and their effect on damage to young Scots pine (Pinus sylvestris L.) plantations was studied in Ruokolahti-Imatra area in Eastern Finland in 1987–89. During the period, the density in the area was about 3–5 moose/ 1,000 ha.

Six feeding sites were established by fertilization, offering mineral lics and the tops of aspen and Scot pine and by salting the tops of pine. The moose preferred the feeding site to control areas during both summer and winter. In winter browsing was very heavy, especially in those areas located in or close to traditional wintering areas. In winter no moose were seen in the summer habitats.

The extent of, and fluctuations in moose damage were studied in 47 Scots pine plantations in the immediate surroundings of the feeding sites (29 plantations), control areas (18 plantations) and also 68 randomly selected pine plantations. Before the experiment began in 1987 four plantations had been seriously damaged. During the study period only one plantation was seriously damaged. However, it could not be conclusively proved that damage to the pine plantations had been reduced as a result of the feeding sites. The results of the study can be put into practice elsewhere to create better living conditions for moose in their winter habitats. However, the food offered at the feeding site should be in the right proportion to the number of animals wintering in the area, so that the risk of damage to nearby plantations would be kept as small as possible.

The PDF includes a summary in Finnish.

• Lääperi, E-mail: al@mm.unknown

• Eyvindson, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Campus Ås, Norway; Natural Resource Institute Finland (Luke), Bioeconomy and Environment, Laatokartanonkaari 9, 00790 Helsinki, Finland https://orcid.org/0000-0003-0647-1594 E-mail: kyle.eyvindson@nmbu.no
• Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, Yliopistokatu 6, 80100 Joensuu, Finland https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi
• Nahorna, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Campus Ås, Norway https://orcid.org/0000-0002-5497-0315 E-mail: olha.nahorna@nmbu.no
• Hunault-Fontbonne, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Campus Ås, Norway https://orcid.org/0009-0004-1864-5162 E-mail: juliette.hunault@nmbu.no
• Potterf, Ecosystem Dynamics and Forest Management Group, Technical University of Munich, Hans Carl-von-Carlowitz-Platz 2, 85354 Freising, Germany https://orcid.org/0000-0001-6763-1948 E-mail: maria.potterf@tum.de

• Strîmbu, Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, NO-1432 Ås, Norway https://orcid.org/0000-0002-0588-2036 E-mail: victor.strimbu@nmbu.no
• Eid, Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, NO-1432 Ås, Norway E-mail: tron.eid@nmbu.no
• Gobakken, Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, NO-1432 Ås, Norway https://orcid.org/0000-0001-5534-049X E-mail: terje.gobakken@nmbu.no

We modelled the effect of habitat composition and roads on the number and occurrence of moose (Alces alces L.) damage in Ostrobothnia and Lapland using a zero-inflated count model. Models were developed for 1 km², 25 km² and 100 km² landscapes consisting of equilateral rectangular grid cells. Count models predict the number of damage, i.e. the number of plantations and zero models the probability of a landscape being without damage for a given habitat composition. The number of moose damage in neighboring grid cells was a significant predictor in all models. The proportion of mature forest was the most frequent significant variable, and an increasing admixture of mature forests among plantations increased the number and occurrence of damage. The amount of all types of plantations was the second most common significant variable predicting increasing damage along with increasing amount of plantations. An increase in thinning forests as an admixture also increased damage in 1 km² landscapes in both areas, whereas an increase in pine-dominated thinning forests in Lapland reduced the number of damage in 25 km² landscapes. An increasing amount of inhabited areas in Ostrobothnia and the length of connecting roads in Lapland reduced the number of damage in 1 and 25 km² landscapes. Differences in model variables between areas suggest that models of moose damage risk should be adjusted according to characteristics that are specific to the study area.

• Nikula, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, Ounasjoentie 6, FI-96200 Rovaniemi, Finland E-mail: ari.nikula@luke.fi
• Nivala, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, Ounasjoentie 6, FI-96200 Rovaniemi, Finland E-mail: vesa.nivala@luke.fi
• Matala, Natural Resources Institute Finland (Luke), Natural resources, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: juho.matala@luke.fi
• Heliövaara, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: kari.heliovaara@helsinki.fi

• Haataja, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: lauritapiohaataja@gmail.com
• Kankaanhuhta, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: ville.kankaanhuhta@luke.fi
• Saksa, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: timo.saksa@luke.fi

• Bettinger, School of Forestry and Natural Resources, 180 E. Green Street, University of Georgia, Athens, Georgia, USA 30602 E-mail: pbettinger@warnell.uga.edu
• Demirci, General Directorate of Forestry, Ministry of Forest and Water Affairs, Republic of Turkey E-mail: mehmetdemirci@yahoo.com
• Boston, Department of Forest Engineering, Resources and Management, College of Forestry, Oregon State University, USA E-mail: Kevin.Boston@oregonstate.edu

• Wallertz, Unit for Field-based Forest Research, Swedish University of Agricultural Sciences (SLU), Asa Research Station, SE-36030 Lammhult, Sweden E-mail: kristina.wallertz@slu.se
• Nordenhem, Department of Ecology, Swedish University of Agricultural Sciences (SLU), P.O. Box 7044, SE-75007 Uppsala, Sweden E-mail: henrik.nordenhem@slu.se
• Nordlander, Department of Ecology, Swedish University of Agricultural Sciences (SLU), P.O. Box 7044, SE-75007 Uppsala, Sweden E-mail: goran.nordlander@slu.se

• Zamora-Cristales, Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331, USA E-mail: rene.zamora@oregonstate.edu
• Boston, Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331, USA E-mail: kevin.boston@oregonstate.edu
• Sessions, Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331, USA E-mail: john.sessions@oregonstate.edu
• Murphy, Waiariki Institute of Technology, Rotorua, New Zealand E-mail: glen.murphy@waiariki.ac.nz

• Nordström, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden E-mail: eva-maria.nordstrom@slu.se
• Holmström, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden E-mail: hampus.holmstrom@slu.se
• Öhman, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden E-mail: karin.ohman@slu.se

• Nilsson, Swedish University of Agricultural Sciences, Department of Forest Resource Management, SE-901 83 Umeå, Sweden E-mail: malin.nilsson@slu.se
• Staal Westerlund, Swedish University of Agricultural Sciences, Department of Forest Resource Management, SE-901 83 Umeå, Sweden E-mail: dianne.wasterlund@slu.se
• Wahlberg, Swedish University of Agricultural Sciences, Department of Forest Resource Management, SE-901 83 Umeå, Sweden E-mail: ow@nn.se
• Eriksson, Swedish University of Agricultural Sciences, Department of Forest Resource Management, SE-901 83 Umeå, Sweden E-mail: ljusk.ola.eriksson@slu.se

• Hiltunen, Metsähallitus, Viestitie 2, FI-87700 Kajaani, Finland E-mail: veikko.hiltunen@metsa.fi
• Kurttila, Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: mikko.kurttila@metla.fi
• Pykäläinen, Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jouni.pykalainen@metla.fi

• Kangas, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: annika.kangas@helsinki.fi
• Mehtätalo, University of Eastern Finland, School of Forest Sciences, Joensuu, Finland E-mail: lm@nn.fi
• Mäkinen, Simosol Oy, Riihimäki, Finland E-mail: am@nn.fi
• Vanhatalo, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: kv@nn.fi

• Hokajärvi, Oulu University of Applied Sciences, School of Renewable Natural Resources, Metsäkouluntie 4–6, FI-90650 Oulu, Finland E-mail: raili.hokajarvi@oamk.fi
• Hujala, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: th@nn.fi
• Leskinen, University of Eastern Finland, Department of Geographical and Historical Studies, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: lal@nn.fi
• Tikkanen, Oulu University of Applied Sciences, School of Renewable Natural Resources, Metsäkouluntie 4–6, FI-90650 Oulu, Finland E-mail: jt@nn.fi

• Islam, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: nurul.islam@joensuu.fi
• Kurttila, Finnish Forest Research Institute, Joensuu Research Unit, FI-80101 Joensuu, Finland E-mail: mk@nn.fi
• Mehtätalo, University of Helsinki, Dept. of Forest Resource Management, FI-00014 University of Helsinki, Finland E-mail: lm@nn.fi
• Haara, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: ah@nn.fi

• 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

• Zhu, Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA E-mail: jz@nn.us
• Bettinger, Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA E-mail: pbettinger@warnell.uga.edu
• Li, Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA E-mail: rl@nn.us

• Eid, Agricultural University of Norway, Dept of Ecology and Natural Resource Management, P.O. Box 5003 NO-1432 Ås, Norway E-mail: tron.eid@ina.nlh.no

• Bettinger, Department of Forest Resources, Oregon State University, Corvallis, OR 97331 E-mail: pete.bettinger@orst.edu
• Graetz, Department of Forest Resources, Oregon State University, Corvallis, OR 97331 E-mail: dgw@nn.us
• Boston, Carter Holt Harvey Forest Fibre Solutions, Tokoroa, New Zealand E-mail: kb@nn.nz
• Sessions, Department of Forest Engineering, Oregon State University, Corvallis, OR 97331 E-mail: js@nn.us
• Chung, Department of Forest Engineering, Oregon State University, Corvallis, OR 97331 E-mail: wc@nn.us

• Boston, Forest Fibre Solutions, Carter Holt Harvey, Tokoroa, New Zealand E-mail: kevin.boston@chh.co.nz
• Bettinger, Department of Forest Resources, Oregon State University, Corvallis, OR 97331 E-mail: pb@nn.us

• Leskinen, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: pekka.leskinen@metla.fi
• Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: jk@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

• Leskinen, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: pekka.leskinen@metla.fi
• Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: jk@nn.fi

• Kangas, Finnish Forest Research Institute, Joensuu Research Centre, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: jyrki.kangas@metla.fi
• Store, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: rs@nn.fi