Articles containing the keyword 'stand management'

Within the European Community snow damage affects an estimated 4 million m³ of timber every year, causing significant economic losses to forest owners. In Northern Europe, for example, the occurrence of snow damage has increased over the last few decades mainly due to the increase in total growing stock. The most common form of damage is stem breakage, but trees can also be bent or uprooted. Trees suffering snow damage are also more prone to consequential damage through insect or fungal attacks.

Snow accumulation on trees is strongly dependent upon weather and climatological conditions. Temperature influences the moisture content of snow and therefore the degree to which it can accumulate on branches. Wind can cause snow to be shed, but can also lead to large accumulations of wet snow, rime or freezing rain. Wet snow is most likely in late autumn or early spring. Geographic location and topography influence the occurrence of damaging forms of snow, and coastal locations and moderate to high elevations experience large accumulations. Slope plays a less important role and the evidence on the role of aspect is contradictory. The occurrence of damaging events can vary from every winter to once every 10 years or so depending upon regional climatology. In the future, assuming global warming in northern latitudes, the risk of snow damage could increase, because the relative occurrence of snowfall near temperatures of zero could increase.

The severity of snow damage is related to tree characteristics. Stem taper and crown characteristics are the most important factors controlling the stability of trees. Slightly tapering stems, asymmetric crowns, and rigid horizontal branching are all associated with high risk. However, the evidence on species differences is less clear due to the interaction with location. Management of forests can alter risk through choice of regeneration, tending, thinning and rotation. However, quantification and comparison of the absolute effect of these measures is not yet possible. An integrated risk model is required to allow the various locational and silvicultural factors to be assessed. Plans are presented to construct such a model, and gaps in knowledge are highlighted.

• Nykänen, E-mail: mn@mm.unknown
• Broadgate, E-mail: mb@mm.unknown
• Kellomäki, E-mail: sk@mm.unknown
• Peltola, E-mail: hp@mm.unknown
• Quine, E-mail: cq@mm.unknown

Model-based information systems have proved valuable planning tools for analysing the production possibilities of forests as well as for understanding forest resources dynamics, stand management practices and forest economics. Computerized forest models implemented in the users’ information systems facilitate the transfer and application of research results in practical forestry.

Conclusions and visions concerning modelling are drawn from experiences in developing the MELA system and its application in solving timber production problems on both the national and forest holding level in Finland. The precondition for predicting forest resource dynamics and for planning the utilization of forests is to accept conditions, uncertainties and a restricted period of time.

The interactive process of forest resource, growth and drain monitoring, and forest management planning supported by forest research and modelling, are the means to enable an operational information base for a dynamic regulation and adaptation strategy for forest resource management under changing conditions and uncertainty.

The PDF includes an abstract in Finnish.

• Siitonen, E-mail: ms@mm.unknown

A nonlinear programming algorithm was combined with two individual-tree growth simulators consisting of distance-independent diameter and height growth models and mortality models. Management questions that can be addressed by the optimization model include the timing, intensity and type of thinning, rotation age, and initial density. The results were calculated for Norway spruce (Picea abies (L.) H. Karst.) stands on Oxalis-Myrtillus site in Southern Finland, where the stand density after clearing of a seedling stand is about 2,000 trees/ha.

The optimum thinning programs were characterized by late first thinnings (at dominant height of 15–17 m) and relatively high growing stock levels. It was optimal to thin from above, unless mean annual increment was maximized instead of an economic objective. In most cases, the optimum number of thinnings was two or three. Compared to a no-thinning alternative, thinnings increased revenues by 15 –45% depending on the objective of stand management. Optimum rotation was strongly dependent on the interest rate.

Hooke and Jeeves’ direct search method was used for determining optimum solutions. The performance of the optimization algorithm was examined in terms of the number of functional evaluations and the equivalence of the objective function values of repeated optimizations.

The PDF includes a summary in Finnish.

• Valsta, E-mail: lv@mm.unknown

• Saksa, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, 77600 Suonenjoki, Finland https://orcid.org/0000-0002-1776-2357 E-mail: ext.timo.saksa@luke.fi
• Miina, Natural Resources Institute Finland (Luke), Natural resources, Yliopistokatu 6 B, 80100 Joensuu, Finland https://orcid.org/0000-0002-8639-4383 E-mail: jari.miina@luke.fi
• Luukkonen, Metsäsydän Oy, Junninmäentie 53, 52200 Puumala, Finland E-mail: olli.p.j.luukkonen@gmail.com

This study’s aim was to identify how the application season and the method of early cleaning (EC), the first stage of multistage pre-commercial thinning (PCT), affected the time consumption in EC and in the subsequent second PCT operation. The worktime in EC was recorded in the spring, summer, and autumn in 22 sites, which were either totally cleaned or point cleaned. Later, these sites were measured at the time of the second PCT. Time consumption was estimated in PCT, based on the removal of the sites. The time consumption in EC was 5.3 productive work hours (pwh) ha^–1, 7.3 pwh ha^–1, and 6.2 pwh ha^–1 respectively in the spring, summer, and autumn. EC in the spring instead of the summer saved 27–30% of working time, depending on the cleaning method. Point cleaning was 0.8 pwh ha^–1 quicker than total cleaning, but the difference was statistically insignificant. The second stage, PCT, was 1 pwh ha^–1 slower to conduct in sites which had been early cleaned in the spring instead of the summer. However, at the entire management program level, EC applied in the spring or autumn instead of the summer saved 11% or 5% respectively of the total discounted costs (3% interest rate) of multistage pre-commercial thinning. Today, the commonest time to conduct EC is in the summer, which was the most expensive of the analyzed management alternatives here. We can expect savings in juvenile stand management in forestry throughout boreal conifer forests by rethinking the seasonal workforce allocation.

• Uotila, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: karri.uotila@luke.fi
• Saksa, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: timo.saksa@luke.fi

In Nordic forests, consistent evidence about better seedling survival rate and increased growth due to site preparation have been obtained in numerous studies. Proper site preparation method can reduce costs of the whole regeneration chain through its effects on survival of planted seedlings, abundance of natural regeneration and competition in early stand development. This study compared the natural regeneration of birches (silver birch (Betula pendula Roth) and downy birch (B. pubescens Ehrh.)), amount of exposed mineral soil, and growth of planted seedlings between spot mounding and inverting site preparation methods. Present study was conducted in eight forest stands established in 2012 or 2015. Even though difference was not statistically significant, inverting exposed less mineral soil than spot mounding and thus reduced the natural regeneration of birch seedlings by 6135 seedlings ha^–1 compared to spot mounding. However, the variation between regeneration areas was remarkable. There was no difference in seedling mortality or growth between the site preparation methods. In order to achieve high growth of conifers, moderate amount of exposed mineral soil and thus less naturally regenerated birch, inverting should be favored over spot mounding.

• Laine, Metsä Group, P.O. Box 208, FI-70101 Kuopio, Finland E-mail: tiina.laine@metsagroup.com
• Kankaanhuhta, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: ville.kankaanhuhta@luke.fi
• Rantala, Metsä Group, P.O. Box 10, FI-02020 METSÄ, Finland E-mail: juho.rantala@metsagroup.com
• Saksa, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: timo.saksa@luke.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

• Heikkilä, L&T Biowatti Oy, P.O. Box 738, FI-60101 Seinäjoki, Finland E-mail: jani.heikkila@biowatti.fi
• Sirén, Finnish Forest Research Institute, Vantaa Research Unit, P.O.Box 18, FI-01301 Vantaa, Finland E-mail: ms@nn.fi
• Ahtikoski, Finnish Forest Research Institute, Rovaniemi Research Unit, P.O.Box 16, FI-96301 Rovaniemi, Finland E-mail: aa@nn.fi
• Hynynen, Finnish Forest Research Institute, Vantaa Research Unit, P.O.Box 18, FI-01301 Vantaa, Finland E-mail: jh@nn.fi
• Sauvula, Seinäjoki University of Applied Sciences, School of Agriculture and Forestry, Tuomarniementie 55, FI-63700 Ähtäri, Finland E-mail: ts@nn.fi
• Lehtonen, Finnish Forest Research Institute, Vantaa Research Unit, P.O.Box 18, FI-01301 Vantaa, Finland E-mail: ml@nn.fi

• Huuskonen, University of Helsinki, Department of Forest Ecology, Helsinki, Finland E-mail: saija.huuskonen@helsinki.fi
• Hynynen, Finnish Forest Research Institute, Vantaa Research Unit, Vantaa, Finland E-mail: jh@nn.fi
• Ojansuu, Finnish Forest Research Institute, Vantaa Research Unit, Vantaa, Finland E-mail: ro@nn.fi