Articles containing the keyword 'mixed model'

Models for individual-tree basal area growth were constructed for Scots pine (Pinus sylvestris L.), pubescent birch (Betula pubescens Ehrh.) and Norway spruce (Picea abies (L.) Karst.) growing in drained peatland stands. The data consisted of two separate sets of permanent sample plots forming a large sample of drained peatland stands in Finland. The dependent variable in all models was the 5-year basal area growth of a tree. The independent tree-level variables were tree dbh, tree basal area, and the sum of the basal area of trees larger than the target tree. Independent stand-level variables were stand basal area, the diameter of the tree of median basal area, and temperature sum. Categorical variables describing the site quality, as well as the condition and age of drainage, were used. Differences in tree growth were used as criteria in reclassifying the a priori site types into new yield classes by tree species. All models were constructed as mixed linear models with a random stand effect. The models were tested against the modelling data and against independent data sets.

• Hökkä, E-mail: hh@mm.unknown
• Alenius, E-mail: va@mm.unknown
• Penttilä, E-mail: tp@mm.unknown

Semiparametric models, ordinary regression models and mixed models were compared for modelling stem volume in National Forest Inventory data. MSE was lowest for the mixed model. Examination of spatial distribution of residuals showed that spatial correlation of residuals is lower for semiparametric and mixed models than for parametric models with fixed regressors. Mixed models and semiparametric models can both be used for describing the effect of geographic location on stem form.

• Kangas, E-mail: ak@mm.unknown
• Korhonen, E-mail: kk@mm.unknown

Much of forestry data is characterized by a longitudinal or repeated measures structure where multiple observations taken on some units of interest are correlated. Such dependencies are often ignored in favour of an apparently simpler analysis at the cost of invalid inferences. The last decade has brought to light many new statistical techniques that enable one to successfully deal with dependent observations. Although apparently distinct at first, the theory of Estimating Functions provides a natural extension of classical estimation that encompasses many of these new approaches. This contribution introduces Estimating Function Theory as a principle with potential for unification and presents examples covering a variety of modelling issues to demonstrate its applicability.

• Schabenberger, E-mail: os@mm.unknown
• Gregoire, E-mail: tg@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

The widespread cork oak (Quercus suber L.) mortality and reduced afforestation /regeneration are causing an overall reduction in cork production. To enhance trees’ growth and vitality, afforestation techniques using fertirrigation were tested. The main objective was the promotion of trees’ growth on new dense plantations using minimum water requirements until reaching productive forests. The experimental plot – Irricork – was installed in 2017 in a ≈1 ha stand with 14 years’ age cork oaks summer-fertirrigated since plantation. Four fertirrigation treatments were applied during fertirrigation campaigns. Radial growth, meteorological parameters and fertirrigation volume were measured every 15–30 days over four years. It was observed that weather, tree size, debarking and trees’ intra-competition had a significant effect on radial increments. Fertirrigation significantly enhanced growth during summer drought and decoupled increments from air vapor pressure deficit constraints. There was a linear relationship between trees’ radial increments and fertirrigation volume up to 140 m³ week^–1. Above this value, increments were smoother. In conclusion, summer fertirrigation of 140 m³ week^–1 efficiently enhanced the radial growth of trees with 50–75 circumference at breast height, under the particular edaphoclimatic conditions of the stand. This study showed to be, therefore, promising in the use of efficient fertirrigation the enhance cork oaks’ radial growth.

• Camilo-Alves, MED – Mediterranean Institute for Agriculture, Environment and Development & CHANGE – Global Change and Sustainability Institute, Institute for Advanced Studies and Research, University of Evora, Pólo da Mitra, Ap. 94, 7006-554 Évora, Portugal https://orcid.org/0000-0001-5156-172X E-mail: calves@uevora.pt
• Nunes, Department of Plant Science, School of Science and Technology, University of Evora, Pólo da Mitra, Ap. 94, 7006-554 Évora, Portugal https://orcid.org/0000-0002-6144-3484 E-mail: jain@uevora.pt
• Poeiras, MED – Mediterranean Institute for Agriculture, Environment and Development & CHANGE – Global Change and Sustainability Institute, Institute for Advanced Studies and Research, University of Evora, Pólo da Mitra, Ap. 94, 7006-554 Évora, Portugal https://orcid.org/0000-0002-6049-807X E-mail: apcp@uevora.pt
• Ribeiro, Department of Plant Science, School of Science and Technology, University of Evora, Pólo da Mitra, Ap. 94, 7006-554 Évora, Portugal https://orcid.org/0000-0001-7242-5866 E-mail: jmrpr@uevora.pt
• Dinis, https://orcid.org/0000-0001-6984-1033 E-mail: dinis.cati@gmail.com
• Barroso, MED – Mediterranean Institute for Agriculture, Environment and Development & CHANGE – Global Change and Sustainability Institute, and Department of Plant Science, School of Science and Technology, University of Evora, Pólo da Mitra, Ap. 94, 7006-554 Évora, Portugal https://orcid.org/0000-0002-0160-3845 E-mail: jmmb@uevora.pt
• Vaz, MED – Mediterranean Institute for Agriculture, Environment and Development & CHANGE – Global Change and Sustainability Institute, and Department of Biology, School of Science and Technology, University of Evora. Pólo da Mitra, Ap. 94, 7006-554 Évora, Portugal https://orcid.org/0000-0002-3368-757X E-mail: mvaz@uevora.pt
• Almeida-Ribeiro, ICT – Institute of Earth Sciences and Department of Plant Science, School of Science and Technology, University of Evora, Pólo da Mitra, Ap. 94, 7006-554 Évora, Portugal https://orcid.org/0000-0002-0160-3845 E-mail: nmcar@uevora.pt

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

The aim of this study was to develop individual-tree diameter and height growth models for Scots pine, Norway spruce, and pubescent birch growing in drained peatlands in Finland. Trees growing in peatland sites have growth patterns that deviate from that of trees growing in mineral soil sites. Five-year growth was explained by tree diameter, different tree and stand level competition measures, management operations and site characteristics. The drainage status of the site was influencing growth directly or in interaction with other variables. Site quality had a direct impact but was also commonly related to current site drainage status (need for ditch maintenance). Recent thinning increased growth of all species and former PK fertilization increased growth of pine and birch. Temperature sum was a significant predictor in all models and altitude for spruce and birch. The data were a subsample of the 7th National Forest Inventory (NFI) sample plots representing northern and southern Finland and followed by repeated measurements for 15–20 yrs. Growth levels predicted by the models were calibrated using NFI11 data to remove bias originating from the sample of the modelling data. The mixed linear models technique was used in model estimation. The models will be incorporated into the MOTTI stand simulator to replace the current peatlands growth models.

• Repola, Natural Resources Institute Finland (Luke), Natural resources, Eteläranta 55, FI-96300 Rovaniemi, Finland E-mail: jaakko.repola@luke.fi
• Hökkä, Natural Resources Institute Finland (Luke), Natural resources, Paavo Havaksen tie 3, FI-90014 University OF Oulu, Finland E-mail: hannu.hokka@luke.fi
• Salminen, Natural Resources Institute Finland (Luke), Natural resources, Eteläranta 55, FI-96300 Rovaniemi, Finland E-mail: hannu.salminen@luke.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

The present research focuses on the productivity of energy wood chipping operations at several sites in Italy. The aim was to assess the productivity and specifically the effect attributed to the operator in the chipping of wood biomass. The research included 172 trials involving 67 operators across the country that were analysed using a mixed model approach, in order to assess productivity, and to isolate the operator effect from other potential variables. The model was constructed using different predictors aiming to explain the variability due to the machines and the raw-materials. The final model included the average piece weight of raw material chipped as well as the power of the machine. The coefficients of determination (R²) were 0.76 for the fixed part of the model, and 0.88 when the effects due to the operators were included. The operators’ performance compared to their peers was established, and it was compared to a subjective classification based on the operator’s previous experience. The results of this study can help to the planning and logistics of raw material supply for bioenergy, as well as to a more effective training of future forest operators.

• Mola-Yudego, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland; NIBIO Norwegian Institute of Bioeconomy Research, P.O. Box 115, 1431 Ås, Norway http://orcid.org/0000-0003-0286-0170 E-mail: blas.mola@uef.fi
• Picchi, CNR IVALSA, Via Madonna del Piano 10, I-50019 Sesto Fiorentino, Italy E-mail: picchi@ivalsa.cnr.it
• Röser, Forest Feedstocks Group, FPInnovations, Vancouver, British Columbia, Canada E-mail: dominik.roser@fpinnovations.ca
• Spinelli, CNR IVALSA, Via Madonna del Piano 10, I-50019 Sesto Fiorentino, Italy E-mail: spinelli@ivalsa.cnr.it

• 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

• Pukkala, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: timo.pukkala@uef.fi
• Hokkanen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: th@nn.fi
• Nikkanen, Finnish Forest Research Institute, Finlandiantie 18, FI-58450 Punkaharju, Finland E-mail: tn@nn.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

• Repola, Finnish Forest Research Institute, Rovaniemi Research Unit, Eteläranta 55, FI-96300 Rovaniemi, Finland E-mail: jaakko.repola@metla.fi

• Mehtätalo, Finnish Forest Research Institute, Joensuu Research Centre, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: lauri.mehtatalo@metla.fi

• Calama, CIFOR-INIA, Grupo Selvicultura Mediterranea, Apdo. 8111, 28080 Madrid, Spain E-mail: rcalama@inia.es
• Montero, CIFOR-INIA, Grupo Selvicultura Mediterranea, Apdo. 8111, 28080 Madrid, Spain E-mail: gm@nn.es

• Jutras, Département des sciences du bois et de la forêt, Université Laval, Ste-Foy, Québec, G1K 7P4, Canada E-mail: sj@nn.ca
• Hökkä, Finnish Forest Research Institute, Rovaniemi Research Station, P.O. Box 16, FIN 96301 Rovaniemi, Finland E-mail: hannu.hokka@metla.fi
• Alenius, Finnish Forest Research Institute, Rovaniemi Research Station, P.O. Box 16, FIN 96301 Rovaniemi, Finland E-mail: va@nn.fi
• Salminen, Finnish Forest Research Institute, Rovaniemi Research Station, P.O. Box 16, FIN 96301 Rovaniemi, Finland E-mail: hs@nn.fi

• Ihalainen, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: marjut.ihalainen@joensuu.fi
• Salo, The Finnish Forest Research Institute, Joensuu Research Centre, P.O. Box 68, FIN-80101 Joensuu, Finland E-mail: ks@nn.fi
• Pukkala, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: tp@nn.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