Articles by Karri Uotila

We developed tree level biomass (dry weight) models for Norway spruce (Picea abies [L.] H. Karst.), silver birch (Betula pendula Roth), rowan (Sorbus aucuparia L.) and aspen (Populus tremula L.) growing in young spruce dominated seedling stands with high mixture of broadleaves. The study material was collected from three planted Norway spruce seedling stands located on mineral soil in southern Finland. Biomass models were estimated by individual tree component (stem, living branches, foliage, stump, and roots with diameter of 2 mm) by using a multi-response approach (seemingly unrelated regression), which estimated the parameters of the sub-models (tree component) simultaneously. Even though the application and generalization of the developed models can be restricted by the limited material, they provide new information of seedling biomass allocation and more reliable biomass predictions for spruce and birch growing in young seedling stand compared with those of the commonly applied biomass models (Repola 2008, 2009) in Finland. Repola’s models (2008, 2009) tended to produce biased predictions for crown and below-ground biomasses of seedlings by allocating too much biomass to roots and too little to needle and branches. In addition, this study provides biomass models for aspen and rowan, which were not previously available.

• Repola, Natural Resources Institute Finland (Luke), Ounasjoentie 6, FI-96200 Rovaniemi, Finland https://orcid.org/0000-0001-7086-0549 E-mail: jaakko.repola@luke.fi
• Luoranen, Natural Resources Institute Finland (Luke), Juntintie 154, FI-77600 Suonenjoki, Finland https://orcid.org/0000-0002-6970-2030 E-mail: jaana.luoranen@luke.fi
• Huuskonen, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0001-8630-3982 E-mail: saija.huuskonen@luke.fi
• Peltoniemi, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0003-2028-6969 E-mail: mikko.peltoniemi@luke.fi
• Väänänen, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: paivi.vaananen@luke.fi
• Uotila, Natural Resources Institute Finland (Luke), Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: karri.uotila@luke.fi

Mechanical site preparation (MSP) is a common practice that precedes the planting of Norway spruce (Picea abies (L.) H. Karst.) in Nordic forests. Mounding has become the most used method in spruce planting in recent years. This study examined the effects of different mounding treatments (spot and ditch mounding, inversion, unprepared control with or without herbicide application) and a mechanical vegetation control (MVC) treatment done 3–4 years after planting on the post-planting growth of spruce container seedlings and their development to saplings during the first 11–13 years on two forest till soils in central Finland, one on flat terrain and other on a southwest slope. On these fine-textured soils the spot and ditch mounding methods favoured spruce saplings development. Inversion and unprepared plots showed weakest growth. On the site with flat terrain, 11 years post planting, spruce saplings were 78–144 cm (38–80%) taller and their breast height diameters were 11–13 mm (60–74%) thicker for ditch or spot mounding than for inversion or herbicide treatment. On the site with sloped terrain the differences were minor between the MSP treatments. MVC improved spruce height growth on sites which did not have intensive MSP, especially on control saplings planted on unprepared soil in herbicide and inversion treatments. On the flat terrain, MVC reduced the density of resprouts to be removed later in pre-commercial thinning. As a conclusion, spot or ditch mounding favoured the growth of spruce over inversion especially on flat terrain with fine-textured soil.

• Uotila, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: karri.uotila@luke.fi
• Luoranen, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland https://orcid.org/0000-0002-6970-2030 E-mail: jaana.luoranen@luke.fi
• Saksa, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland https://orcid.org/0000-0002-1776-2357 E-mail: timo.saksa@luke.fi
• Laine, Metsä Forest, Revontulenpuisto 2, FI-02100 Espoo, Finland https://orcid.org/0000-0002-6448-8274 E-mail: tiina.laine@metsagroup.com
• Heiskanen, Natural Resources Institute Finland (Luke), Natural resources, Juntintie 154, FI-77600 Suonenjoki, Finland https://orcid.org/0000-0002-0549-835X E-mail: juha.heiskanen@luke.fi

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

The time consumption (TC) of pre-commercial thinning (PCT) varies greatly among sites, stands and forest workers. The TC in PCT is usually estimated by field-assessed work difficulty factors. In this study, a linear mixed model for the TC in PCT was prepared by utilizing forest resources data (FRD). The modelling data included 11 848 and validation data included 3035 worksites with TC information recorded by forest workers within the period of 2008–2018. The worksites represented a range of site and stand conditions across a broad geographical area in Finland. Site and stand characteristics and previous management logically explained the TC in PCT. The more fertile the site, the more working time was needed in PCT. On sites of medium fertility, TC in the initial PCT increased with stand age by 0.5 h ha^–1 yr^–1. Site wetness increased the TC. PCT in summer was more time consuming than in spring. Small areas were more time consuming to PCT per hectare than larger ones. The between-forest worker variation involved in the TC was as high as 35% of the variation unexplained by the TC model. The coefficient of determination in validation data was 19.3%, RMSE 4.75 h ha^–1 and bias –1.6%. The TC model based on FRD was slightly less precise than the one based on field-assessed work difficulty factors (removal quantity and type and terrain difficulty): RMSE 4.9 h ha^–1 vs. 4.1 h ha^–1 (52% vs. 43%). The TC model could be connected to forest information systems where it would facilitate the predictions of the labour costs of PCT without field-assessing work difficulty factors.

• Uotila, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: karri.uotila@luke.fi
• Miina, Natural Resources Institute Finland (Luke), Natural resources, Yliopistokatu 6 B, FI-80100 Joensuu, Finland E-mail: jari.miina@luke.fi
• Saksa, Natural Resources Institute Finland (Luke), Natural resources, Survontie 9, FI-40500 Jyväskylä, Finland E-mail: timo.saksa@luke.fi
• Store, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Teknologiakatu 7, FI-67100 Kokkola, Finland E-mail: ron.store@luke.fi
• Kärkkäinen, E-mail: kauko.karkkainen@gmail.com
• Härkönen, Tornator Oyj, Pielisentie 2–6, FI-81700 Lieksa, Finland E-mail: mika.harkonen@tornator.fi

• Uotila, Finnish Forest Research Institute, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: karri.uotila@metla.fi
• Saksa, Finnish Forest Research Institute, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: timo.saksa@metla.fi
• Rantala, Metsä Group, Lielahdenkatu 10, FI-33400 Tampere, Finland E-mail: juho.rantala@metsagroup.com
• Kiljunen, Metsähallitus, Asemakatu 7, FI-70107 Kuopio, Finland E-mail: nuutti.kiljunen@metsa.fi

• Uotila, Finnish Forest Research Institute, Suonenjoki Unit, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: karri.uotila@metla.fi
• Rantala, Metsä Group, Tampere, Finland E-mail: juho.rantala@metsagroup.com
• Saksa, Finnish Forest Research Institute, Suonenjoki Unit, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: timo.saksa@metla.fi

• Uotila, Finnish Forest Research Institute, Suonenjoki, Finland E-mail: karri.uotila@metla.fi
• Rantala, Finnish Forest Research Institute, Suonenjoki, Finland E-mail: jr@nn.fi
• Saksa, Finnish Forest Research Institute, Suonenjoki, Finland E-mail: ts@nn.fi
• Harstela, Finnish Forest Research Institute, Suonenjoki, Finland E-mail: ph@nn.fi