Articles by Urban Nilsson

Models that predict forest development are essential for sustainable forest management. Constructing growth models via regression analysis or fitting a family of sigmoid equations to construct compatible growth and yield models are two ways these models can be developed. In this study, four species-specific models were developed and compared. A compatible growth and yield stand basal area model and a five-year stand basal area growth model were developed for Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.). The models were developed using data from permanent inventory plots from the Swedish national forest inventory and long-term experiments. The species-specific models were compared, using independent data from long-term experiments, with a stand basal area growth model currently used in the Swedish forest planning system Heureka (Elfving model). All new models had a good, relatively unbiased fit. There were no apparent differences between the models in their ability to predict basal area development, except for the slightly worse predictions for the Norway spruce growth model. The lack of difference in the model comparison showed that despite the simplicity of the compatible growth and yield models, these models could be recommended, especially when data availability is limited. Also, despite using more and newer data for model development in this study, the currently used Elfving model was equally good at predicting basal area. The lack of model difference indicate that future studies should instead focus on model development for heterogeneous forests which are common but lack in growth and yield modelling research.

• Goude, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, SE-230 53 Alnarp, Sweden https://orcid.org/0000-0002-2179-292X E-mail: martin.goude@slu.se
• Nilsson, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, SE-230 53 Alnarp, Sweden E-mail: urban.nilsson@slu.se
• Mason, School of Forestry, University of Canterbury, Private Bag 4800, Christchurch, New Zealand E-mail: euan.mason@canterbury.ac.nz
• Vico, Department of Crop Production Ecology, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden E-mail: giulia.vico@slu.se

Investing in planting genetically improved silver birch (Betula pendula Roth) in Swedish plantations requires understanding how birch stands will develop over their entire rotation. Previous studies have indicated relatively low production of birch compared to Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.). This could result from using unrepresentative basic data, collected from unimproved, naturally-regenerated birch (Betula spp.) growing on inventory plots often located in coniferous stands. The objective of this study was to develop a basal area development function of improved silver birch and evaluate production over a full rotation period. We used data from 52 experiments including planted silver birch of different genetic breeding levels in southern and central Sweden. The experimental plots were established on fertile forest sites and on former agricultural lands, and were managed with different numbers of thinnings and basal area removal regimes. The model best describing total stand basal area development was a dynamic equation derived from the Korf base model. The analysis of the realized gain trial for birch showed a good stability of the early calculated relative differences in basal area between tested genotypes over time. Thus, the relative difference in basal area might be with cautious used as representation of the realized genetic gain. On average forest sites in southern Sweden, improved and planted silver birch could produce between 6–10.5 m³ ha^–1 year^–1, while on fertile agriculture land the average productivity might be higher, especially with material coming from the improvement program. The performed analysis provided a first step toward predicting the effects of genetic improvement on total volume production and profitability of silver birch. However, more experiments are needed to set up the relative differences between different improved material.

• Liziniewicz, The Forestry Research Institute of Sweden, Ekebo, SE-268 90 Svalöv, Sweden E-mail: mateusz.liziniewicz@skogforsk.se
• Barbeito, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Alnarp, Sweden; Université de Lorraine, AgroParisTech, INRAE, UMR Silva, Nancy, France E-mail: ignacio.barbeito@slu.se
• Zvirgzdins, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Box 49, 23053 Alnarp, Sweden E-mail: andis.zvirgzdins@slu.se
• Stener, The Forestry Research Institute of Sweden, Ekebo, SE-268 90 Svalöv, Sweden E-mail: lg.stener@telia.com
• Niemistö, Natural Resources In-stitute Finland (Luke), Natural resources, Seinäjoki, Finland E-mail: pentti.niemisto@luke.fi
• Fahlvik, The Forestry Research Institute of Sweden, Ekebo, SE-268 90 Svalöv, Sweden E-mail: nils.fahlvik@skogforsk.se
• Johansson, Tönnersjöheden Experimental Forest, SLU, Simlångsdalen, Sweden E-mail: ulf.johansson@slu.se
• Karlsson, The Forestry Research Institute of Sweden, Ekebo, SE-268 90 Svalöv, Sweden E-mail: curly.birch@gmail.com
• Nilsson, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Box 49, 23053 Alnarp, Sweden E-mail: urban.nilsson@slu.se

New mortality models were developed for the purpose of improving long-term growth and yield simulations in Finland, Norway, and Sweden and were based on permanent national forest inventory plots from Sweden and Norway. Mortality was modelled in two steps. The first model predicts the probability of survival, while the second model predicts the proportion of basal area in surviving trees for plots where mortality has occurred. In both models, the logistic function was used. The models incorporate the variation in prediction period length and in plot size. Validation of both models indicated unbiased mortality rates with respect to various stand characteristics such as stand density, average tree diameter, stand age, and the proportion of different tree species, Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.), and broadleaves. When testing against an independent dataset of unmanaged spruce-dominated stands in Finland, the models provided unbiased prediction with respect to stand age.

• Siipilehto, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland E-mail: jouni.siipilehto@luke.fi
• Allen, Norwegian Institute of Bioeconomy Research (NIBIO), Division of Forest and Forest Products, NO-1431 Ås, Norway; Larson and McGowin Inc., Mobile, AL 36607, USA https://orcid.org/0000-0002-7824-2849 E-mail: micky.allen@nibio.no
• Nilsson, Swedish University of Agricultural Sciences (SLU), Southern Swedish Forest Research Centre, SE-23053 Alnarp, Sweden https://orcid.org/0000-0002-7624-4031 E-mail: urban.nilsson@slu.se
• Brunner, Norwegian University of Life Sciences (NMBU), Faculty of Environmental Sciences and Natural Resource Management, NO-1432 Ås, Norway https://orcid.org/0000-0003-1668-9714 E-mail: andreas.brunner@nmbu.no
• Huuskonen, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland https://orcid.org/0000-0001-8630-3982 E-mail: saija.huuskonen@luke.fi
• Haikarainen, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland https://orcid.org/0000-0001-8703-3689 E-mail: soili.haikarainen@luke.fi
• Subramanian, Swedish University of Agricultural Sciences (SLU), Southern Swedish Forest Research Centre, SE-23053 Alnarp, Sweden https://orcid.org/0000-0003-2777-3241 E-mail: narayanan.subramanian@slu.se
• Antón-Fernández, Norwegian Institute of Bioeconomy Research (NIBIO), Division of Forest and Forest Products, NO-1431 Ås, Norway https://orcid.org/0000-0001-5545-3320 E-mail: clara.anton.fernandez@nibio.no
• Holmström, Swedish University of Agricultural Sciences (SLU), Southern Swedish Forest Research Centre, SE-23053 Alnarp, Sweden https://orcid.org/0000-0003-2025-1942 E-mail: emma.holmstrom@slu.se
• Andreassen, Norwegian Institute of Bioeconomy Research (NIBIO), Division of Forest and Forest Products, NO-1431 Ås, Norway https://orcid.org/0000-0003-4272-3744 E-mail: kjellandreassen@gmail.com
• Hynynen, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland E-mail: jari.hynynen@luke.fi

Genetically improved Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.) are extensively used in operational Swedish forestry plantations. However, relatively little is known about the stem slenderness (height-diameter ratio) of genetically improved material. Thus, in this study we investigated effects of plus-tree selection on stem slenderness of Norway spruce and Scots pine in Sweden by evaluating both the plus-tree selection and a large number of progeny trials. Species-specific models for predicting the height-diameter ratio were estimated using regression and mixed model approach. Our results show that phenotypic plus-tree selection promoted less slender Norway spruce trees and more slender Scots pine trees compared to neighboring trees. Similar results were also found for the progeny trials which indicated that genetics played a prominent role in the phenotypic appearance. Compared to the progeny of neighboring trees, Norway spruce plus-tree progenies had a 5.3% lower height-diameter ratio, while Scots pine plus-tree progenies had a 1.5% greater height-diameter ratio. The narrow sense heritability for height-diameter ratio was 0.19 for Norway spruce and 0.11 for Scots pine, indicating that it is possible to modify the height-diameter ratio by breeding. Correlation coefficients between breeding values for height-diameter ratio and diameter were negative for Scots pine (–0.71) and Norway spruce (–0.85), indicating that selection for diameter only would result in less slender stems of both species. Similar correlations were also found between breeding values for height-diameter ratio and height of Scots pine (–0.34) and Norway spruce (–0.74).

• Egbäck, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, 230 53 Alnarp, Sweden E-mail: samuel.egback@slu.se
• Karlsson, Skogforsk, Ekebo, 268 90 Svalöv, Sweden E-mail: bo.karlsson@skogforsk.se
• Högberg, Skogforsk, Ekebo, 268 90 Svalöv, Sweden E-mail: karl-anders.hogberg@skogforsk.se
• Nyström, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, 901 83 Umeå, Sweden E-mail: kenneth.nystrom@slu.se
• Liziniewicz, Skogforsk, Ekebo, 268 90 Svalöv, Sweden E-mail: Mateusz.Liziniewicz@skogforsk.se
• Nilsson, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, 230 53 Alnarp, Sweden E-mail: urban.nilsson@slu.se

Genetically improved Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.) are used extensively in operational Swedish forestry plantations to increase production. Depending on the genetic status of the plant material, the current estimated genetic gain in growth is in the range 10–20% for these species and this is expected to increase further in the near future. However, growth models derived solely from data relating to genetically improved material in Sweden are still lacking. In this study we investigated whether an individual tree growth model based on data from unimproved material could be used to predict the height increment in young trials of genetically improved Norway spruce and Scots pine. Data from 11 genetic experiments with large genetic variation, ranging from offspring of plus-trees selected in the late 1940s to highly improved clonal materials selected from well performing provenances were used. The data set included initial heights at the age of 7–15 years and 5-year increments for almost 2000 genetic entries and more than 20 000 trees. The evaluation indicated that the model based on unimproved trees predicted height development relatively well for genetically improved Norway spruce and there was no need to incorporate a genetic component. However, for Scots pine, the model needed to be modified. A genetic component was developed based on the genetic difference recorded within each trial, using mixed linear models and methods from quantitative genetics. By incorporating the genetic component, the prediction errors were significantly reduced for Scots pine. This study provides the first step to incorporate genetic gains into Swedish growth models and forest management planning systems.

• Egbäck, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, 230 53 Alnarp, Sweden E-mail: samuel.egback@slu.se
• Nilsson, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, 230 53 Alnarp, Sweden E-mail: urban.nilsson@slu.se
• Nyström, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, 901 83 Umeå, Sweden E-mail: kenneth.nystrom@slu.se
• Högberg, Skogforsk, Ekebo, 268 90 Svalöv, Sweden E-mail: karl-anders.hogberg@skogforsk.se
• Fahlvik, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, 230 53 Alnarp, Sweden E-mail: nils.fahlvik@slu.se

• Hedwall, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences (SLU), P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: per-ola.hedwall@slu.se
• Grip, Department of Forest Ecology and Management, SLU, SE-901 83 Umeå, Sweden E-mail: harald@grip2.se
• Linder, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences (SLU), P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: sune.linder@slu.se
• Lövdahl, Department of Forest Ecology and Management, SLU, SE-901 83 Umeå, Sweden E-mail: ll@nn.se
• Nilsson, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences (SLU), P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: urban.nilsson@slu.se
• Bergh, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences (SLU), P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: johan.bergh@slu.se

• Nilsson, Swedish University of Agricultural Sciences (SLU), Southern Swedish Forest Research Centre, Alnarp, Sweden E-mail: urban.nilsson@slu.se
• Elfving, SLU, Forest Ecology and Management, Umeå, Sweden E-mail: be@nn.se
• Karlsson, SLU, Unit of Field Based Research, Asa, Sweden E-mail: kk@nn.se

• Bergh, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: johan.bergh@ess.slu.se
• Nilsson, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: un@nn.se
• Grip, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: hg@nn.se
• Hedwall, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: poh@nn.se
• Lundmark, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: tl@nn.se