Articles by Jari Miina

A spatial growth model is presented for Scots pine (Pinus sylvestris L.) on a dwarf-shrub pine mire drained 14 years earlier. The growth model accounts for the variation in tree diameter growth owing to the competition between trees, the distance between tree and ditch, and the time passed since drainage. The model was used to study the effect of tree arrangement on the post-drainage growth of a pine stand. Clustering of trees decreased the volume growth by 9–20% as compared to a regular spatial distribution. Stand volume growth, for a given number of stems, was at its maximum and variation in diameter growth at its minimum when the stand density on the ditch border was 1.5–5 higher than midway between two adjacent ditches.

• Miina, E-mail: jm@mm.unknown

Mixed forests are known for their ability to provide a wide range of ecosystem services. Such forests have higher biodiversity compared to monocultures, are resilient against disturbances and may mitigate the effects of climate change. Despite well-known benefits, there is still little information on how these forests should be established and managed. The aim of this study was to describe the early growth dynamics of current boreal young mixed stands of planted Norway spruces (Picea abies (L.) Karst.) and naturally regenerated birches (Betula spp.). We collected data from 9  stands planted for spruce 8–14 years ago in Southern and Central Finland. Stem analysis was conducted to 144 spruces and to 144 birches to determine previous growth. We modelled the height and diameter development of individual trees in relation to tree age at stump height using non-linear mixed Chapman-Richards model. There were no significant differences between spruce and seed-origin birch in diameter growth at stump height, but the initial height increments of natural birches were larger than those of planted spruces. However, planted spruces were able to keep up with the height development of birches, if spruces received a head start over naturally regenerated seed-origin birch for two growing seasons. Thus, naturally regenerated birch admixture can be utilized to establish single-storied spruce-birch mixtures, and the admixture should be retained during the early cleaning of planted spruce stands.

• Männistö, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0009-0009-0213-1972 E-mail: lauri.mannisto@luke.fi
• Miina, Natural Resources Institute Finland (Luke), Natural resources, Yliopistokatu 6 B, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-8639-4383 E-mail: jari.miina@luke.fi
• Huuskonen, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0001-8630-3982 E-mail: saija.huuskonen@luke.fi

• 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

Bilberry (Vaccinium myrtillus L.) and lingonberry (V. vitis-idaea L.) can be a part of healthy diet and are important for many animals. Two approaches are described to assessing their vegetation cover and berry yield via national forest inventory (NFI) observations. The aim was to provide estimates and predictions of the abundance and yield of the species at regional and national levels in Finland and Sweden. In Finland, the model-based predictions are used in evaluating the impacts of cutting intensity on forest berries needed in forest-related decision making. In Sweden, seasonal inventory-based estimates are used to evaluate the annual national and regional berry yields, and in a forecasting system aimed at large public and berry enterprises. Based on the NFI sample plots measured between 2014 and 2018, the total annual yields are estimated to be 208 Mkg of bilberry and 246 Mkg of lingonberry on productive forest land (increment at least 1 m³ ha^–1 year^–1) in Finland, and 336 and 382 Mkg respectively in Sweden (average of NFI inventories in 2015–2019). The predicted development of berry yields is related to the intensity of cuttings in alternative forest management scenarios: lower removals favoured bilberry, and higher removals lingonberry. The model-based method describes the effects of stand development and management on berry yields, whereas the inventory-based method can calibrate seasonal estimates through field observations. In providing spatially and timely more accurate information concerning seasonal berry yields, an assessment of berry yields should involve the elements of both inventory-based and model-based approaches described in this study.

• Miina, Natural Resources Institute Finland (Luke), Yliopistokatu 6 B, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-8639-4383 E-mail: jari.miina@luke.fi
• Bohlin, Swedish University of Agricultural sciences (SLU), Department of Forest Resource Management, Skogsmarksgränd, S-901 83 Umeå, Sweden E-mail: inka.bohlin@slu.se
• Lind, Swedish University of Agricultural sciences (SLU), Department of Forest Resource Management, Skogsmarksgränd, S-901 83 Umeå, Sweden E-mail: torgny.lind@slu.se
• Dahlgren, Swedish University of Agricultural sciences (SLU), Department of Forest Resource Management, Skogsmarksgränd, S-901 83 Umeå, Sweden E-mail: jonas.dahlgren@slu.se
• Härkönen, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: kari.harkonen@luke.fi
• Packalen, Natural Resources Institute Finland (Luke), Yliopistokatu 6 B, FI-80100 Joensuu, Finland; Ministry of Agriculture and Forestry of Finland, P.O. Box 30, FI-00023 Government, Finland E-mail: tuula.packalen@mmm.fi
• Tolvanen, Natural Resources Institute Finland (Luke), Paavo Havaksentie 3, FI-90014 University of Oulu, Finland E-mail: anne.tolvanen@luke.fi

Young, dense forest in Finland and Sweden urgently need to receive first thinning. In such stands, conventional selective thinning methods make the harvester work time consuming and, thus, costly. To make small-sized trees economically competitive as raw material for bioenergy and biorefining, new harvesting technologies and/or thinning methods need to be developed. A potential solution is boom-corridor thinning (BCT), rendering effective cutting work. The aim of this study was to describe and compare the stand structure of two Scots pine stands (Pinus sylvestris L.) and one birch-dominated (Betula pendula Roth with natural downy birch, B. pubescens Ehrh.) stand after BCT and selective thinning at the first thinning phase. Furthermore, simulations were conducted to predict the future stand development after the first thinning treatments. The density of the growing stock was 16–46% higher after BCT treatment than after selective thinning because BCT stands included more small and supressed trees with a dbh < 100 mm. However, the numbers of future crop trees with a dbh > 140 mm per hectare were at the same level in both treatments. The stem volume removal per hectare did not differ between treatments. However, simulation of stand development and intermediate thinning and clearcutting revealed that the total removal volume was 10–18% higher in BCT stands compared to selectively thinned ones. The saw log volumes harvested did, however, not differ between treatments. This study shows that BCT generates stands with higher biodiversity compared to conventional thinning as higher levels of biomass removal can be reached throughout stand rotations.

• Nuutinen, Natural Resources Institute Finland (Luke), Production systems, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: yrjo.nuutinen@luke.fi
• Miina, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jari.miina@luke.fi
• Saksa, Natural Resources Institute Finland (Luke), Natural resources, FI-77600 Suonenjoki, Finland E-mail: timo.saksa@luke.fi
• Bergström, Swedish University of Agricultural Sciences (SLU), Dept of Forest Biomaterials and Technology, Section of Forest Operations, SE-90183 Umeå, Sweden E-mail: dan.bergstrom@slu.se
• Routa, Natural Resources Institute Finland (Luke), Production systems, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: johanna.routa@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

Operating conditions affecting the quality of spot mounding by Bracke continuously advancing mounders were investigated on 66 regeneration areas (124 ha) in eastern Finland. The quality of mounds was classified as suitable (good or acceptable after additional compression) or unsuitable for planting. Models were constructed for the number of suitable planting spots obtained per hectare (good and acceptable mounds), the probability of successful mounding (≥1600 planting spots ha^–1) and the probability of creating a suitable mound as a function of terrain, site and soil characteristics, as well as slash conditions (removed, fresh or dry logging residues). The average number of mounds created was 1892 ± 290 mounds ha^–1, of which 1398 ± 325 mounds ha^–1 (74%) were classified as suitable for planting. The quality of spot mounding was reduced by steep terrain, a thick humus layer and fresh logging residues. Stoniness and soil texture also affected the number of planting spots created. Mounding after logging residues had dried increased the number of planting spots by 191 spots ha^–1 compared with mounding in the presence of fresh residues. Removing residues did not significantly increase the number of planting spots compared with mounding amongst dry residues. A thick humus layer, very stony soil, steep slopes and valley terrain decreased the number of planting spots by 150–450 spots ha^–1. The number and quality of mounds varied considerably according to the operating conditions, but with careful selection of timing and sites the quality obtained by a continuously advancing mounder can be improved.

• Saksa, Natural Resources Institute Finland (Luke), Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: timo.saksa@luke.fi
• Miina, Natural Resources Institute Finland (Luke), Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: jari.miina@luke.fi
• Haatainen, Faculty of Science and Forestry, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: hilkka.haatainen@storaenso.com
• Kärkkäinen, Tornator Oyj, Muuntamontie 2, FI-80100 Joensuu, Finland E-mail: kauko.karkkainen@tornator.fi

• Turtiainen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: marjut.turtiainen@uef.fi
• Miina, Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jari.miina@metla.fi
• Salo, Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: kauko.salo@metla.fi
• Hotanen, Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: juha-pekka.hotanen@metla.fi

• Miina, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jari.miina@metla.fi
• Hotanen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jph@nn.fi
• Salo, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: ks@nn.fi

• Saksa, Finnish Forest Research Institute, Suonenjoki Unit, Juntintie 154, FI-77600 Suonenjoki, Finland E-mail: timo.saksa@metla.fi
• Miina, Finnish Forest Research Institute, Joensuu Unit, P.O.Box 68, FI-80101 Joensuu, Finland E-mail: jm@nn.fi

• Pukkala, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: timo.pukkala@joensuu.fi
• Miina, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jm@nn.fi

• Pukkala, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: timo.pukkala@joensuu.fi
• Miina, Finnish Forest Research Institute, Joensuu Research Centre, P.O. Box 68, FIN-80101 Joensuu, Finland E-mail: jm@nn.fi
• Palahí, European Forest Institute, Torikatu 34, FIN-80100 Joensuu, Finland E-mail: mp@nn.fi

• Peltola, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: heli.peltola@forest.joensuu.fi
• Miina, Finnish Forest Research Institute, Joensuu Research Centre, P.O. Box 68, FIN-80101 Joensuu, Finland E-mail: jm@nn.fi
• Rouvinen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: ir@nn.fi
• Kellomäki, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: sk@nn.fi

• Vettenranta, Kivirinnanpolku 4, FIN-40950 Muurame, Finland E-mail: vettenr@cc.joensuu.fi
• Miina, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: jm@nn.fi

• Nuutinen, Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6 B, FI-80100 Joensuu, Finland https://orcid.org/0000-0003-3360-4444 E-mail: yrjo.nuutinen@luke.fi
• Miina, Natural Resources Institute Finland (Luke), Natural resources, Yliopistokatu 6 B, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-8639-4383 E-mail: jari.miina@luke.fi

The sap yield of birches (Betula pendula Roth and B. pubescens Ehrh.) was modelled as a function of tree diameter (girth) at breast height, as well as site and stand characteristics measured and reported by citizen scientists representing mainly non-industrial private forest owners in the South Savo, North Karelia, and Northern Ostrobothnia regions in Finland. Birches (tree species not recorded) growing on both mineral and peatland sites were tapped during the springs of 2019 and 2020. Citizen scientists were mainly voluntary forest owners who received the instructions and equipment (spouts, drop lines and buckets) for collecting sap from three birches of different diameters in the same birch stand. Citizen scientists were instructed to measure and report the sap yield and girth of the trees, as well as stand characteristics from the forest resource data, if available. Based on the linear mixed model fitted to the data, the sap yield increased with the increasing tree diameter and mean stand height, and varied between years, stands, and trees; between-region variation was not significant. In a birch stand, the simulated total sap yield ha^–1 was depended on the average tree size and the stem number ha^–1 and was at its highest just before the first commercial thinning and again before the second thinning. The sap model can be used to predict the necessary sap yield in profitability analyses for sap tapping.

• Miina, Natural Resources Institute Finland (Luke), Yliopistokatu 6 B, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-8639-4383 E-mail: jari.miina@luke.fi
• Kurttila, Natural Resources Institute Finland (Luke), Yliopistokatu 6 B, FI-80100 Joensuu, Finland https://orcid.org/0000-0001-5290-4771 E-mail: mikko.kurttila@luke.fi

The coverage of bilberry (Vaccinium myrtillus L.) was modelled as a function of site and stand characteristics using the permanent sample plots of the National Forest Inventory (NFI) (Model 1). The sample sites consisted of mineral soil forests as well as fells and peatland sites. Annual variation in the bilberry yield (Model 2) was analysed based on measurements over 2001–2014 in the permanent sample plots (so-called MASI plots) in various areas of Finland. We derived annual bilberry yield indices from the year effects of Model 2 and investigated whether these indices could be used to estimate annual variation in bilberry crops in Finland. The highest bilberry coverage was found in mesic heath forests and fell forests. On peatlands the coverage was, on average, lower than on mineral soil sites; the peatland sites with most bilberry coverage were meso-oligotrophic and oligotrophic spruce mires and oligotrophic pine mires. Our bilberry yield indices showed similar variation to those derived from the mean annual berry yields reported and calculated earlier using the MASI plots; the correlation between the indices was 0.795. This approach to calculating annual berry yield indices is a promising way for estimating total annual bilberry yields over a given period of time. Models 1 and 2 can be used in conjunction with the Miina et al.’s (2009) bilberry yield model when bilberry coverage, average annual yield and annual variation in the yield are to be predicted in forest planning.

• Turtiainen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: marjut.turtiainen@uef.fi
• Miina, Natural Resources Institute Finland (Luke), Management and Production of Renewable Resources, Box 68, FI-80101 Joensuu, Finland E-mail: jari.miina@luke.fi
• Salo, Natural Resources Institute Finland (Luke), Bio-based Business and Industry, Box 68, FI-80101 Joensuu, Finland E-mail: kauko.salo@luke.fi
• Hotanen, Natural Resources Institute Finland (Luke), Management and Production of Renewable Resources, Box 68, FI-80101 Joensuu, Finland E-mail: juha-pekka.hotanen@luke.fi

• Saksa, The Finnish Forest Institute, Suonenjoki Research Station, FI-77600 Suonenjoki, Finland E-mail: ts@nn.fi
• Heiskanen, The Finnish Forest Institute, Suonenjoki Research Station, FI-77600 Suonenjoki, Finland E-mail: jh@nn.fi
• Miina, The Finnish Forest Institute, Joensuu Research Centre, P. O. Box 68, FI-80101 Joensuu, Finland E-mail: jm@nn.fi
• Tuomola, The University of Joensuu, Mekrijärvi Research Station, FI-82900 Ilomantsi, Finland E-mail: jt@nn.fi
• Kolström, The University of Joensuu, Mekrijärvi Research Station, FI-82900 Ilomantsi, Finland E-mail: tk@nn.fi