Karri Uotila, Jari Miina, Timo Saksa, Ron Store, Kauko Kärkkäinen, Mika Härkönen. (2020). Low cost prediction of time consumption for pre-commercial thinning in Finland. Silva Fennica vol. 54 no. 1 article id 10196. https://doi.org/10.14214/sf.10196

Keywords: forest vegetation management; early cleaning; release treatment; linear mixed model; topographic wetness index; work productivity

Highlights: Time consumption (TC) in pre-commercial thinning (PCT) can be predicted by variables describing site and stands conditions and previous silvicultural management; Applying variables available in forest resources data the field-assessment of worksite difficulty factors is not needed; The TC model could facilitate the predictions of the labour costs of PCT in forest information systems.

Abstract | Full text in HTML | Full text in PDF | Author Info

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

article id 982, category Research article

Karri Uotila, Timo Saksa, Juho Rantala, Nuutti Kiljunen. (2014). Labour consumption models applied to motor-manual pre-commercial thinning in Finland. Silva Fennica vol. 48 no. 2 article id 982. https://doi.org/10.14214/sf.982

Keywords: productivity; pre-commercial thinning; forest vegetation management; early cleaning; release treatment; mixed linear regression

Highlights: When a young stand grows and gets older, the work time needed to make pre-commercial thinning increases. The stands of Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.) and hardwoods (Betula spp.) required an additional 8.2%, 5.2%, and 3.3% work-time per year, respectively.

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Labour models were developed to estimate the time required to Pre-Commercially Thin (PCT) with a clearing saw 4- to 20-year-old stands of the main commercial tree species in Finland. Labour (i.e., work-time consumption) was estimated from the density and stem diameter of the removal of 448 stands via an existing work productivity function. The removal based estimator attained was used as the basis for a priori mixed linear regression models. The main finding was that when a young stand grows and gets older, the work time needed to make a PCT increases. The stands of Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.) and hardwoods (Betula spp.) required an additional 8.2%, 5.2%, and 3.3% work-time per year, respectively. Site fertility also played a role in that the most fertile site (mesic OMT) had an estimated labour requirement 114% higher than that for dryish VT. We also note that, per unit area, small stands require less labour than large ones and soil preparation method had a minor effect on the labour estimate. The stands which had previously gone through PCT were separately analysed. In those stands, the only significant variable concerning the labour estimate was age. The a priori models described here can help foresters to develop economic management programmes and issue quotes for forestry services.

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

article id 919, category Research article

Karri Uotila, Juho Rantala, Timo Saksa. (2012). Estimating the need for early cleaning in Norway spruce plantations in Finland. Silva Fennica vol. 46 no. 5 article id 919. https://doi.org/10.14214/sf.919

Keywords: cleaning; conifer release; cost-effectiveness; forest vegetation management; early cleaning

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Effective management of Norway spruce (Picea abies (L.) Karst.) plantations requires detailed information on stand development, which is costly to measure. However, estimating the need for early stand management from site attributes that persists stabile after ones measured, may provide an inexpensive alternative. This study compared hardwood competition in spruce plantations of varying ages and tested the usability of this information in estimating the need for early cleaning. The data included 197 spruce plantations (4–7 years old) inventoried in southern Finland in 2007. The level (Low, Substantial, High) of need for early cleaning was subjectively determined by contrasting location and size of competing hardwoods to a conifer crop tree. Then the stage of the need for early cleaning was modelled according to site and stand attributes. Nearly 60% of the conifer crop trees in the plantations were subjectively judged to require early cleaning (Substantial 37.2%, High 21.2%), but only 10 per cent of the evaluated area was cleaned. Need for cleaning was intense on peatlands or damp soils, whereas it was mild on unprepared soils or cleaned sites. Traditional site characteristics used in forest management planning can be useful for recognising the peripheral cases, where need for cleaning is probably high or low. However, on a typical mineral soil plantation (uncleaned, soil prepared) the model indicates the differences in the need for early cleaning weakly. The need for early cleaning was already high in 4-year-old plantations, why stand age did not have significant effect on development of the need. Thus, the timing of an operation can not be predicted with the model. Nonetheless, early cleaning very likely opens growth space of crop trees in a 4–7-year-old spruce plantation. Therefore, from an aspect of crop growth, an uncleaned Norway spruce plantation in this age group is quite consistently worth cleaning.

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

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