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Silva Fennica 1926-1997
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Articles containing the keyword 'regression'.

Category: Research article

article id 10269, category Research article
Annika Kangas, Helena M. Henttonen, Timo P. Pitkänen, Sakari Sarkkola, Juha Heikkinen. (2020). Re-calibrating stem volume models – is there change in the tree trunk form from the 1970s to the 2010s in Finland? Silva Fennica vol. 54 no. 4 article id 10269. https://doi.org/10.14214/sf.10269
Highlights: TLS data showed that trunk form has changed in Finland from the 1970s; Significant differences were observed for all tree species; The trees in TLS data are on average more slender than in the old data.

The tree stem volume models of Norway spruce, Scots pine and silver and downy birch currently used in Finland are based on data collected during 1968–1972. These models include four different formulations of a volume model, with three different combinations of independent variables: 1) diameter at height of 1.3 m above ground (dbh), 2) dbh and tree height (h) and 3) dbh, h and upper diameter at height of 6 m (d6). In recent National Forest Inventories of Finland, a difference in the mean volume prediction between the models with and without the upper diameter as predictor has been observed. To analyze the causes of this difference, terrestrial laser scanning (TLS) was used to acquire a large dataset in Finland during 2017–2018. Field-measured predictors and volumes predicted using spline functions fitted to the TLS data were used to re-calibrate the current volume models. The trunk form is different in these two datasets. The form height is larger in the new data for all diameter classes, which indicates that the tree trunks are more slender than they used to be. One probable reason for this change is the increase in stand densities, which is at least partly due to changed forest management. In models with both dbh and h as predictors, the volume is smaller a given h class in the data new data than in the old data, and vice versa for the diameter classes. The differences between the old and new models were largest with pine and smallest with birch.

  • Kangas, Natural Resources Institute Finland (Luke), Yliopistokatu 6 B, FI-80100 Joensuu, Finland ORCID ID: https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi (email)
  • Henttonen, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland ORCID ID:E-mail: helena.henttonen@luke.fi
  • Pitkänen, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland ORCID ID: https://orcid.org/0000-0001-5389-8713 E-mail: timo.p.pitkanen@luke.fi
  • Sarkkola, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland ORCID ID:E-mail: sakari.sarkkola@luke.fi
  • Heikkinen, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland ORCID ID: https://orcid.org/0000-0003-3527-774X E-mail: juha.heikkinen@luke.fi
article id 10247, category Research article
Agnese Marcelli, Walter Mattioli, Nicola Puletti, Francesco Chianucci, Damiano Gianelle, Mirko Grotti, Gherardo Chirici, Giovanni D' Amico, Saverio Francini, Davide Travaglini, Lorenzo Fattorini, Piermaria Corona. (2020). Large-scale two-phase estimation of wood production by poplar plantations exploiting Sentinel-2 data as auxiliary information. Silva Fennica vol. 54 no. 2 article id 10247. https://doi.org/10.14214/sf.10247
Highlights: A two-phase sampling for large-scale assessment of fast-growing forest crops is developed; Vegetation indices from Sentinel-2 are exploited in a linear regression estimator; The linear regression estimator turns out to be better than the estimator based on the sole sample information; The approach represents a reference for supporting outside-forest resource monitoring and assessment.

Growing demand for wood products, combined with efforts to conserve natural forests, have supported a steady increase in the global extent of planted forests. Here, a two-phase sampling strategy for large-scale assessment of the total area and the total wood volume of fast-growing forest tree crops within agricultural land is presented. The first phase is performed using tessellation stratified sampling on high-resolution remotely sensed imagery and is sufficient for estimating the total area of plantations by means of a Monte Carlo integration estimator. The second phase is performed using stratified sampling of the plantations selected in the first phase and is aimed at estimating total wood volume by means of an approximation of the first-phase Horvitz-Thompson estimator. Vegetation indices from Sentinel-2 are exploited as freely available auxiliary information in a linear regression estimator to improve the design-based precision of the estimator based on the sole sample data. Estimators of the totals and of the design-based variances of total estimators are presented. A simulation study is developed in order to check the design-based performance of the two alternative estimators under several artificial distributions supposed for poplar plantations (random, clustered, spatially trended). An application in Northern Italy is also reported. The regression estimator turns out to be invariably better than that based on the sole sample information. Possible integrations of the proposed sampling scheme with conventional national forest inventories adopting tessellation stratified sampling in the first phase are discussed.

  • Marcelli, University of Tuscia, Department for Innovation in Biological, Agro-food and Forest systems, Viterbo, Italy; Fondazione Edmund Mach, Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, San Michele all’Adige, Italy ORCID ID:E-mail: agnese.marcelli@student.unisi.it (email)
  • Mattioli, University of Tuscia, Department for Innovation in Biological, Agro-food and Forest systems, Viterbo, Italy; CREA, Research Centre for Forestry and Wood, Arezzo, Italy ORCID ID:E-mail: walter.mattioli@crea.gov.it
  • Puletti, CREA, Research Centre for Forestry and Wood, Arezzo, Italy ORCID ID:E-mail: nicola.puletti@crea.gov.it
  • Chianucci, CREA, Research Centre for Forestry and Wood, Arezzo, Italy ORCID ID:E-mail: fchianucci@gmail.com
  • Gianelle, Fondazione Edmund Mach, Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, San Michele all’Adige, Italy ORCID ID:E-mail: damiano.gianelle@fmach.it
  • Grotti, CREA, Research Centre for Forestry and Wood, Arezzo, Italy; University of Roma La Sapienza, Department of Architecture and Design, Rome, Italy ORCID ID:E-mail: mirkogrotti@gmail.com
  • Chirici, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy ORCID ID:E-mail: gherardo.chirici@unifi.it
  • D' Amico, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy ORCID ID:E-mail: giovanni.damico@unifi.it
  • Francini, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy; University of Molise, Department of Agricultural, Environmental and Food Sciences, Campobasso, Italy ORCID ID:E-mail: saverio.francini@gmail.com
  • Travaglini, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy ORCID ID:E-mail: davide.travaglini@unifi.it
  • Fattorini, University of Siena, Department of Economics and Statistics, Siena, Italy ORCID ID:E-mail: lorenzo.fattorini@unisi.it
  • Corona, CREA, Research Centre for Forestry and Wood, Arezzo, Italy ORCID ID:E-mail: piermaria.corona@crea.gov.it
article id 10217, category Research article
Xingji Jin, Timo Pukkala, Fengri Li, Lihu Dong. (2019). Developing growth models for tree plantations using inadequate data – a case for Korean pine in Northeast China. Silva Fennica vol. 53 no. 4 article id 10217. https://doi.org/10.14214/sf.10217
Highlights: The permanent sample plots of Chinese plantation trees have not been designed for producing data for growth modeling; We used various methods to deal with the inadequacies of sample plot data; Optimization was used to fit diameter increment and survival models using data with varying measurement intervals and tree identification errors; Quantile regression was used to model self-thinning limit.

Korean pine (Pinus koraiensis Siebold & Zucc.) is economically the most important tree species in northeast China. Korean pine plantations are established and managed for the production of timber and seeds. Despite the importance of the species, few models have been developed for the comparison of alternative management schedules. Model development is affected by the fact that permanent sample plots and thinning experiments have not been designed and managed for modeling purposes. The permanent sample plots include few non-thinned plots, and weak trees are removed in thinning treatments, leading to low mortality rate. Moreover, the measurement interval is irregular. This study used optimization-based modeling approach in tree-level diameter increment and survival modeling to deal with the above problems. Models for self-thinning limit were developed to alleviate the problem of underestimated mortality arising from the features of the data. In addition, improved site index and individual-tree height models were developed. The model of Lundqvist and Korf was used as the site index model and the model proposed by Schumacher as the height model. Quantile regression was used to model the maximum stand basal area and maximum number of trees as a function of mean tree diameter and site index. Tree diameter, stand basal area, basal area in larger trees and site index were used as the predictors of diameter increment and tree survival. The models developed in this study constitute a model set that is suitable for simulation and optimization studies. The models produced simulation results that correspond to measured stand development.

  • Jin, Key Laboratory of Sustainable Forest Ecosystem Management - Ministry of Education, School of Forestry, Northeast Forestry University, Harbin 150040, Heilongjiang, People’s Republic of China ORCID ID: http://orcid.org/0000-0003-2971-2709 E-mail: xingji_jin@163.com
  • Pukkala, Key Laboratory of Sustainable Forest Ecosystem Management - Ministry of Education, School of Forestry, Northeast Forestry University, Harbin 150040, Heilongjiang, People’s Republic of China; University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: timo.pukkala@uef.fi (email)
  • Li, Key Laboratory of Sustainable Forest Ecosystem Management - Ministry of Education, School of Forestry, Northeast Forestry University, Harbin 150040, Heilongjiang, People’s Republic of China ORCID ID: http://orcid.org/0000-0002-4058-769X E-mail: fengrili@126.com
  • Dong, Key Laboratory of Sustainable Forest Ecosystem Management - Ministry of Education, School of Forestry, Northeast Forestry University, Harbin 150040, Heilongjiang, People’s Republic of China ORCID ID: http://orcid.org/0000-0002-3985-9475 E-mail: ldonglihu2006@163.com
article id 1680, category Research article
Liisa Kulmala, Indre Žliobaitė, Eero Nikinmaa, Pekka Nöjd, Pasi Kolari, Kourosh Kabiri Koupaei, Jaakko Hollmén, Harri Mäkinen. (2016). Environmental control of growth variation in a boreal Scots pine stand – a data-driven approach. Silva Fennica vol. 50 no. 5 article id 1680. https://doi.org/10.14214/sf.1680
Highlights: High water potential and carbon gain during bud forming favoured height growth; High water potential during the elongation period favoured height growth; A spring with high carbon gain favoured diameter growth; The obtained regression models had generally low generalization performance.

Despite the numerous studies on year-to-year variation of tree growth, the physiological mechanisms controlling annual variation in growth are still not understood in detail. We studied the applicability of data-driven approach i.e. different regression models in analysing high-dimensional data set including continuous and comprehensive measurements over meteorology, ecosystem-scale water and carbon fluxes and the annual variation in the growth of app. 50-year-old Scots pine stand in southern Finland. Even though our dataset covered only 16 years, it is the most extensive collection of interactions between a Scots pine ecosystem and atmosphere. The analysis revealed that height growth was favoured by high water potential of the tree and carbon gain during the bud forming period and high water potential during the elongation period. Diameter growth seemed to be favoured by a winter with high precipitation and deep snow cover and a spring with high carbon gain. The obtained models had low generalization performance and they would require more evaluation and iterative validation to achieve credibility perhaps as a mixture of data-driven and first principle modeling approaches.

  • Kulmala, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: liisa.kulmala@helsinki.fi (email)
  • Žliobaitė, Aalto University, Department of Computer Science and Helsinki Institute for Information Technology, P.O. Box 11000, FI-00076 Aalto, Finland; University of Helsinki, Department of Geosciences and Geography, P.O. Box 64, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: zliobaite@gmail.com
  • Nikinmaa, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: eero.nikinmaa@helsinki.fi
  • Nöjd, Natural Resources Institute Finland (Luke), Bio-based business and industry, Tietotie 2, FI-02150 Espoo, Finland ORCID ID:E-mail: pekka.nojd@luke.fi
  • Kolari, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland; University of Helsinki, Department of Physics, P.O. Box 64, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: pasi.kolari@helsinki.fi
  • Kabiri Koupaei, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: kourosh.kabiri@helsinki.fi
  • Hollmén, Aalto University, Department of Computer Science and Helsinki Institute for Information Technology, P.O. Box 11000, FI-00076 Aalto, Finland; University of Helsinki, Department of Geosciences and Geography, P.O. Box 64, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: jaakko.hollmen@aalto.fi
  • Mäkinen, Natural Resources Institute Finland (Luke), Bio-based business and industry, Tietotie 2, FI-02150 Espoo, Finland ORCID ID:E-mail: harri.makinen@luke.fi
article id 1567, category Research article
Eetu Kotivuori, Lauri Korhonen, Petteri Packalen. (2016). Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland. Silva Fennica vol. 50 no. 4 article id 1567. https://doi.org/10.14214/sf.1567
Highlights: Pooled data from nine inventory projects in Finland were used to create nationwide laser-based regression models for dominant height, volume and biomass; Volume and biomass models provided regionally different means than real means, but for dominant height the mean difference was small; The accuracy of general volume predictions was nevertheless comparable to relascope-based field inventory by compartments.

The aim of this study was to examine how well stem volume, above-ground biomass and dominant height can be predicted using nationwide airborne laser scanning (ALS) based regression models. The study material consisted of nine practical ALS inventory projects taken from different parts of Finland. We used field sample plots and airborne laser scanning data to create nationwide and regional models for each response variable. The final models had one or two ALS predictors, which were chosen based on the root mean square error (RMSE), and cross-validated. Finally, we tested how much predictions would improve if the nationwide models were calibrated with a small number of regional sample plots. Although forest structures differ among different parts of Finland, the nationwide volume and biomass models performed quite well (leave-inventory-area-out RMSE 22.3% to 33.8%, mean difference [MD] –13.8% to 18.7%) compared with regional models (leave-plot-out RMSE 20.2% to 26.8%). However, the nationwide dominant height model (RMSE 5.4% to 7.7%, MD –2.0% to 2.8%, with the exception of the Tornio region – RMSE 11.4%, MD –9.1%) performed nearly as well as the regional models (RMSE 5.2% to 6.7%). The results show that the nationwide volume and biomass models provided different means than real means at regional level, because forest structure and ALS device have a considerable effect on the predictions. Large MDs appeared especially in northern Finland. Local calibration decreased the MD and RMSE of volume and biomass models. However, the nationwide dominant height model did not benefit much from calibration.

  • Kotivuori, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: eetu.kotivuori@uef.fi (email)
  • Korhonen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: lauri.korhonen@uef.fi
  • Packalen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: petteri.packalen@uef.fi
article id 1559, category Research article
Karol Bronisz, Mike Strub, Chris Cieszewski, Szymon Bijak, Agnieszka Bronisz, Robert Tomusiak, Rafał Wojtan, Michał Zasada. (2016). Empirical equations for estimating aboveground biomass of Betula pendula growing on former farmland in central Poland. Silva Fennica vol. 50 no. 4 article id 1559. https://doi.org/10.14214/sf.1559
Highlights: We developed equations for aboveground biomass components of young silver birch stands on post-agricultural lands in central Poland for single tree level; Simplified equations were based exclusively on diameter at ground level or breast height, while expanded ones were based on the appropriate diameter and tree height; For large trees, diameter at breast height is a more appropriate explanatory variable than diameter at ground level; Biomass estimations based on models from neighboring countries were consistent with our results.

We determined empirical models for estimating total aboveground as well as stem, branches, and foliage dry biomass of young (age up to 16 years) silver birch (Betula pendula Roth.) growing on the post-agricultural lands. Two sets of allometric models for trees with a height below or above 1.3 m (small and large trees respectively) were developed. Simplified models were elaborated based exclusively on appropriate tree diameter (diameter at ground level for small trees, diameter at breast height for large trees), while expanded models also included tree height. Total aboveground biomass was estimated as the sum of biomass of all tree components. To assure additivity of the developed equations, the seemingly unrelated regression approach for the final model fitting was used. Expanded models in both tree groups were characterized by a better fit to the data (R2 for total aboveground biomass for small and large trees equaled 0.8768 and 0.9752, respectively). Diameter at breast height appeared to be a better predictor than diameter at ground level – simplified models had better fit for large trees (R2 for total aboveground biomass equals 0.9611) than for small ones (R2 = 0.7516). The developed equations provide biomass predictions consistent with available Latvian, Estonian, Finnish, Swedish, and Norwegian models for silver birch.

  • Bronisz, Laboratory of Dendrometry and Forest Productivity, Faculty of Forestry, Warsaw University of Life Sciences – SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland ORCID ID:E-mail: karol.bronisz@wl.sggw.pl (email)
  • Strub, Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA, 30605, USA ORCID ID:E-mail: strub@mcfns.com
  • Cieszewski, Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA, 30605, USA ORCID ID:E-mail: thebiomat@gmail.com
  • Bijak, Laboratory of Dendrometry and Forest Productivity, Faculty of Forestry, Warsaw University of Life Sciences – SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland ORCID ID:E-mail: szymon.bijak@wl.sggw.pl
  • Bronisz, Laboratory of Dendrometry and Forest Productivity, Faculty of Forestry, Warsaw University of Life Sciences – SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland ORCID ID:E-mail: agnieszka.bronisz@wl.sggw.pl
  • Tomusiak, Laboratory of Dendrometry and Forest Productivity, Faculty of Forestry, Warsaw University of Life Sciences – SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland ORCID ID:E-mail: robert.tomusiak@wl.sggw.pl
  • Wojtan, Laboratory of Dendrometry and Forest Productivity, Faculty of Forestry, Warsaw University of Life Sciences – SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland ORCID ID:E-mail: rafal.wojtan@wl.sggw.pl
  • Zasada, Laboratory of Dendrometry and Forest Productivity, Faculty of Forestry, Warsaw University of Life Sciences – SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland ORCID ID:E-mail: michal.zasada@wl.sggw.pl
article id 1405, category Research article
Lauri Korhonen, Daniela Ali-Sisto, Timo Tokola. (2015). Tropical forest canopy cover estimation using satellite imagery and airborne lidar reference data. Silva Fennica vol. 49 no. 5 article id 1405. https://doi.org/10.14214/sf.1405
Highlights: The fusion of airborne lidar data and satellite images enables accurate canopy cover mapping; The zero-and-one inflated beta regression is demonstrated in large area estimation; Forest/non-forest classification should be done directly, for example by using logistic regression.

The fusion of optical satellite imagery, strips of lidar data and field plots is a promising approach for the inventory of tropical forests. Airborne lidars also enable an accurate direct estimation of the forest canopy cover (CC), and thus a sample of lidar strips can be used as reference data for creating CC maps which are based on satellite images. In this study, our objective was to validate CC maps obtained from an ALOS AVNIR-2 satellite image wall-to-wall, against a lidar-based CC map of a tropical forest area located in Laos. The reference CC values which were needed for model training were obtained from a sample of four lidar strips. Zero-and-one inflated beta regression (ZOINBR) models were applied to link the spectral vegetation indices derived from the ALOS image with the lidar-based CC estimates. In addition, we compared ZOINBR and logistic regression models in the forest area estimation by using >20% CC as a forest definition. Using a total of 409 217 30 × 30 m population units as validation, our model showed a strong correlation between lidar-based CC and spectral satellite features (root mean square error = 12.8%, R2 = 0.82). In the forest area estimation, a direct classification using logistic regression provided better accuracy than the estimation of CC values as an intermediate step (kappa = 0.61 vs. 0.53). It is important to obtain sufficient training data from both ends of the CC range. The forest area estimation should be done before the CC estimation, rather than vice versa.

  • Korhonen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland; (current) University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID: http://orcid.org/0000-0002-9352-0114 E-mail: lauri.z.korhonen@helsinki.fi (email)
  • Ali-Sisto, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: dheikkil@student.uef.fi
  • Tokola, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland. ORCID ID:E-mail: timo.tokola@uef.fi
article id 1405, category Research article
Lauri Korhonen, Daniela Ali-Sisto, Timo Tokola. (2015). Tropical forest canopy cover estimation using satellite imagery and airborne lidar reference data. Silva Fennica vol. 49 no. 5 article id 1405. https://doi.org/10.14214/sf.1405
Highlights: The fusion of airborne lidar data and satellite images enables accurate canopy cover mapping; The zero-and-one inflated beta regression is demonstrated in large area estimation; Forest/non-forest classification should be done directly, for example by using logistic regression.

The fusion of optical satellite imagery, strips of lidar data and field plots is a promising approach for the inventory of tropical forests. Airborne lidars also enable an accurate direct estimation of the forest canopy cover (CC), and thus a sample of lidar strips can be used as reference data for creating CC maps which are based on satellite images. In this study, our objective was to validate CC maps obtained from an ALOS AVNIR-2 satellite image wall-to-wall, against a lidar-based CC map of a tropical forest area located in Laos. The reference CC values which were needed for model training were obtained from a sample of four lidar strips. Zero-and-one inflated beta regression (ZOINBR) models were applied to link the spectral vegetation indices derived from the ALOS image with the lidar-based CC estimates. In addition, we compared ZOINBR and logistic regression models in the forest area estimation by using >20% CC as a forest definition. Using a total of 409 217 30 × 30 m population units as validation, our model showed a strong correlation between lidar-based CC and spectral satellite features (root mean square error = 12.8%, R2 = 0.82). In the forest area estimation, a direct classification using logistic regression provided better accuracy than the estimation of CC values as an intermediate step (kappa = 0.61 vs. 0.53). It is important to obtain sufficient training data from both ends of the CC range. The forest area estimation should be done before the CC estimation, rather than vice versa.

  • Korhonen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland; (current) University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID: http://orcid.org/0000-0002-9352-0114 E-mail: lauri.z.korhonen@helsinki.fi (email)
  • Ali-Sisto, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: dheikkil@student.uef.fi
  • Tokola, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland. ORCID ID:E-mail: timo.tokola@uef.fi
article id 1337, category Research article
Leszek Bujoczek, Małgorzata Bujoczek, Jan Banaś, Stanisław Zięba. (2015). Spruce regeneration on woody microsites in a subalpine forest in the western Carpathians. Silva Fennica vol. 49 no. 3 article id 1337. https://doi.org/10.14214/sf.1337
Highlights: The occurrence probability of Picea abies seedlings on fallen deadwood was found to increase with diameter and decay stage of deadwood and with the volume of living trees, and to decrease with the density of living trees, sapling density, and land slope. It was also higher on stumps with greater diameter and in plots with higher sapling density, but decreased with increasing stump height.

The density of Picea abies [L.] Karst. regeneration on different microsites, the quantity and quality of woody microsites, and seedling occurrence probability on stumps and fallen deadwood were studied in a subalpine forest that has been under protection for approximately 30–40 years (Gorce Mountains in the western Carpathians). Thirty percent of seedlings and 29% of saplings grew on stumps and fallen deadwood, while the remaining regeneration occurred on soil surface and mounds created by uprooted trees. The occurrence probability of Picea seedlings on fallen deadwood increased with deadwood diameter and decay stage and with the volume of living trees, and decreased with increased density of living trees, sapling density, and land slope. Furthermore, seedlings were more likely to grow on stumps with a greater diameter and in plots with higher sapling density, but less likely to grow on higher stumps. Stumps and fallen deadwood covered about 4% of the forest floor, but the material that is most important for promoting regeneration (strongly decomposed logs and those of a diameter exceeding 30 cm) took up only about 22 m2 ha-1. We have concluded that in a subalpine forest that has been protected for 30–40 years regeneration processes take place mostly on soil surface and stumps. The role of fallen deadwood increases over time as a greater number of suitable logs (in terms of size and decay stage) become available.

  • Bujoczek, University of Agriculture in Krakow, ORCID ID:E-mail: lbujoczek@gmail.com (email)
  • Bujoczek, University of Agriculture in Krakow, ORCID ID:E-mail: bujoczek.m@gmail.com
  • Banaś, University of Agriculture in Krakow, ORCID ID:E-mail: rlbanas@cyf-kr.edu.pl
  • Zięba, University of Agriculture in Krakow, ORCID ID:E-mail: rlzieba@cyf-kr.edu.pl
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
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.
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 ORCID ID:E-mail: karri.uotila@metla.fi (email)
  • Saksa, Finnish Forest Research Institute, Juntintie 154, FI-77600 Suonenjoki, Finland ORCID ID:E-mail: timo.saksa@metla.fi
  • Rantala, Metsä Group, Lielahdenkatu 10, FI-33400 Tampere, Finland ORCID ID:E-mail: juho.rantala@metsagroup.com
  • Kiljunen, Metsähallitus, Asemakatu 7, FI-70107 Kuopio, Finland ORCID ID:E-mail: nuutti.kiljunen@metsa.fi
article id 952, category Research article
Lauri Korhonen, Inka Pippuri, Petteri Packalén, Ville Heikkinen, Matti Maltamo, Juho Heikkilä. (2013). Detection of the need for seedling stand tending using high-resolution remote sensing data. Silva Fennica vol. 47 no. 2 article id 952. https://doi.org/10.14214/sf.952
Seedling stands are problematic in airborne laser scanning (ALS) based stand level forest management inventories, as the stem density and species proportions are difficult to estimate accurately using only remotely sensed data. Thus the seedling stands must still be checked in the field, which results in an increase in costs. In this study we tested an approach where ALS data and aerial images are used to directly classify the seedling stands into two categories: those that involve tending within the next five years and those which involve no tending. Standard ALS-based height and density features, together with texture and spectral features calculated from aerial images, were used as inputs to two classifiers: logistic regression and the support vector machine (SVM). The classifiers were trained using 208 seedling plots whose tending need was estimated by a local forestry expert. The classification was validated on 68 separate seedling stands. In the training data, the logistic model’s kappa coefficient was 0.55 and overall accuracy (OA) 77%. The SVM did slightly better with a kappa = 0.71 and an OA = 86%. In the stand level validation data, the performance decreased for both the logistic model (kappa = 0.38, OA = 71%) and the SVM (kappa = 0.37, OA = 72%). Thus our approach cannot totally replace the field checks. However, in considering the stands where the logistic model predictions had high reliability, the number of misclassifications reduced drastically. The SVM however, was not as good at recognizing reliable cases.
  • Korhonen, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: lauri.korhonen@uef.fi (email)
  • Pippuri, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: inka.pippuri@uef.fi
  • Packalén, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: petteri.packalen@uef.fi
  • Heikkinen, School of Computing, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: ville.heikkinen@uef.fi
  • Maltamo, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: matti.maltamo@uef.fi
  • Heikkilä, Finnish Forest Centre, Public Services, Maistraatinportti 4 A, FI-00240 Helsinki, Finland ORCID ID:E-mail: juho.heikkila@metsakeskus.fi
article id 100, category Research article
Annika Kangas, Lauri Mehtätalo, Antti Mäkinen, Kalle Vanhatalo. (2011). Sensitivity of harvest decisions to errors in stand characteristics. Silva Fennica vol. 45 no. 4 article id 100. https://doi.org/10.14214/sf.100
In forest planning, the decision maker chooses for each stand a treatment schedule for a predefined planning period. The choice is based either on optimization calculations or on silvicultural guidelines. Schedules for individual stands are obtained using a growth simulator, where measured stand characteristics such as the basal area, mean diameter, site class and mean height are used as input variables. These characteristics include errors, however, which may lead to incorrect decisions. In this study, the aim is to study the sensitivity of harvest decisions to errors in a dataset of 157 stands. Correct schedules according to silvicultural guidelines were first determined using error-free data. Different amounts of errors were then generated to the stand-specific characteristics, and the treatment schedule was selected again using the erroneous data. The decision was defined as correct, if the type of harvest in these two schedules were similar, and if the timings deviated at maximum ±2 for thinning and ±3 years for clear-cut. The dependency of probability of correct decisions on stand characteristics and the degree of errors was then modelled. The proposed model can be used to determine the required level of measurement accuracy for each characteristics in different kinds of stands, with a given accuracy requirement for the timing of treatments. This information can further be utilized in selecting the most appropriate inventory method.
  • Kangas, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: annika.kangas@helsinki.fi (email)
  • Mehtätalo, University of Eastern Finland, School of Forest Sciences, Joensuu, Finland ORCID ID:E-mail:
  • Mäkinen, Simosol Oy, Riihimäki, Finland ORCID ID:E-mail:
  • Vanhatalo, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
article id 100, category Research article
Annika Kangas, Lauri Mehtätalo, Antti Mäkinen, Kalle Vanhatalo. (2011). Sensitivity of harvest decisions to errors in stand characteristics. Silva Fennica vol. 45 no. 4 article id 100. https://doi.org/10.14214/sf.100
In forest planning, the decision maker chooses for each stand a treatment schedule for a predefined planning period. The choice is based either on optimization calculations or on silvicultural guidelines. Schedules for individual stands are obtained using a growth simulator, where measured stand characteristics such as the basal area, mean diameter, site class and mean height are used as input variables. These characteristics include errors, however, which may lead to incorrect decisions. In this study, the aim is to study the sensitivity of harvest decisions to errors in a dataset of 157 stands. Correct schedules according to silvicultural guidelines were first determined using error-free data. Different amounts of errors were then generated to the stand-specific characteristics, and the treatment schedule was selected again using the erroneous data. The decision was defined as correct, if the type of harvest in these two schedules were similar, and if the timings deviated at maximum ±2 for thinning and ±3 years for clear-cut. The dependency of probability of correct decisions on stand characteristics and the degree of errors was then modelled. The proposed model can be used to determine the required level of measurement accuracy for each characteristics in different kinds of stands, with a given accuracy requirement for the timing of treatments. This information can further be utilized in selecting the most appropriate inventory method.
  • Kangas, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: annika.kangas@helsinki.fi (email)
  • Mehtätalo, University of Eastern Finland, School of Forest Sciences, Joensuu, Finland ORCID ID:E-mail:
  • Mäkinen, Simosol Oy, Riihimäki, Finland ORCID ID:E-mail:
  • Vanhatalo, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
article id 164, category Research article
Aki Suvanto, Matti Maltamo. (2010). Using mixed estimation for combining airborne laser scanning data in two different forest areas. Silva Fennica vol. 44 no. 1 article id 164. https://doi.org/10.14214/sf.164
Airborne laser scanning (ALS) data have become the most accurate remote sensing technology for forest inventories. When planning new inventories the costs of fieldwork could be reduced if datasets of old inventory areas are effectively reused in the new area. The aim of this study was to apply mixed estimation using a combination of existing and new field datasets in area-based approach. Additionally, combining datasets with mixed estimation was compared with constructing new local models with smaller datasets. The two forest study areas were in Juuka and Matalansalo, which are located about 120 km apart in eastern Finland. ALS-based regression models were constructed using datasets of Matalansalo (472 reference plots) and Juuka (10–212 reference plots). Models were developed for the basal area median tree diameter and height, mean tree height, stem number, basal area and volume. The work was based on a simulation approach which involved five methods for approximating the regression coefficients. The first method merged the datasets using ordinary least squares (OLS) regression models, whereas the second and third methods combined datasets using mixed estimation on different weighting principles, and the final two estimated local models with predetermined and new independent variables. The results indicate that mixed estimation can improve the accuracy of derived stand variables compared with basic OLS models. Additionally, a sample of 40–50 plots was enough to build local models for basal area and volume and produce at least the equal accuracy of results than any other methods in this study.
  • Suvanto, Blom Kartta Oy, Teollisuuskatu 18, FI-80100 Joensuu, Finland ORCID ID:E-mail: aki.suvanto@blomasa.com (email)
  • Maltamo, University of Eastern Finland, School of Forest Sciences, P.O. Box, FI-80101, Joensuu, Finland ORCID ID:E-mail:
article id 244, category Research article
Georg E. Kindermann, Ian McCallum, Steffen Fritz, Michael Obersteiner. (2008). A global forest growing stock, biomass and carbon map based on FAO statistics. Silva Fennica vol. 42 no. 3 article id 244. https://doi.org/10.14214/sf.244
Currently, information on forest biomass is available from a mixture of sources, including in-situ measurements, national forest inventories, administrative-level statistics, model outputs and regional satellite products. These data tend to be regional or national, based on different methodologies and not easily accessible. One of the few maps available is the Global Forest Resources Assessment (FRA) produced by the Food and Agriculture Organization of the United Nations (FAO 2005) which contains aggregated country-level information about the growing stock, biomass and carbon stock in forests for 229 countries and territories. This paper presents a technique to downscale the aggregated results of the FRA2005 from the country level to a half degree global spatial dataset containing forest growing stock; above/below-ground biomass, dead wood and total forest biomass; and above-ground, below-ground, dead wood, litter and soil carbon. In all cases, the number of countries providing data is incomplete. For those countries with missing data, values were estimated using regression equations based on a downscaling model. The downscaling method is derived using a relationship between net primary productivity (NPP) and biomass and the relationship between human impact and biomass assuming a decrease in biomass with an increased level of human activity. The results, presented here, represent one of the first attempts to produce a consistent global spatial database at half degree resolution containing forest growing stock, biomass and carbon stock values. All results from the methodology described in this paper are available online at www.iiasa.ac.at/Research/FOR/.
  • Kindermann, International Institute for Applied Systems Analysis, Laxenburg, Austria ORCID ID:E-mail: kinder@iiasa.ac.at (email)
  • McCallum, International Institute for Applied Systems Analysis, Laxenburg, Austria ORCID ID:E-mail:
  • Fritz, International Institute for Applied Systems Analysis, Laxenburg, Austria ORCID ID:E-mail:
  • Obersteiner, International Institute for Applied Systems Analysis, Laxenburg, Austria ORCID ID:E-mail:
article id 262, category Research article
Julian C. Fox, Huiquan Bi, Peter K. Ades. (2008). Modelling spatial dependence in an irregular natural forest. Silva Fennica vol. 42 no. 1 article id 262. https://doi.org/10.14214/sf.262
The spatial dependence present in a natural stand of Eucalyptus pilularis (Smith) dominated mixed species forest was characterised and modelled. Two wildfires imposed a significant spatial dependence on the post disturbance stand. It was hypothesised that spatial variation in the intensity of the wildfires generated the observed structures. The influence of patch formation, micro-site variability and competitive influences were also noted in the residuals of a distance-dependent individual-tree growth model. A methodology capable of modelling these complicated patterns of observed dependence was sought, and candidates included the spatial interaction, direct specification and Papadakis methods. The spatial interaction method with a moving average autoregression was identified as the most appropriate method for explicitly modelling spatial dependence. Both the direct specification and Papadakis methods failed to capture the influence of competition. This study highlights the possibility that stand disturbances such as natural and artificial fires, insect and fungal attacks, and wind and snow damage are capable of imposing powerful spatial dependencies on the post disturbance stand. These dependencies need to be considered if individual tree growth models are to provide valid predictions in disturbed stands.
  • Fox, School of Forest and Ecosystem Science, University of Melbourne, Burnley Campus, 500 Yarra Blvd, Richmond, Victoria 3121 Australia ORCID ID:E-mail: jcfox@unimelb.edu.au (email)
  • Bi, Forest Resources Research, New South Wales Department of Primary Industries, PO Box 100, Beecroft, NSW 2119 Australia ORCID ID:E-mail:
  • Ades, School of Forest and Ecosystem Science, University of Melbourne, Burnley Campus, 500 Yarra Blvd, Richmond, Victoria 3121 Australia ORCID ID:E-mail:
article id 275, category Research article
Lauri Korhonen, Kari T. Korhonen, Pauline Stenberg, Matti Maltamo, Miina Rautiainen. (2007). Local models for forest canopy cover with beta regression. Silva Fennica vol. 41 no. 4 article id 275. https://doi.org/10.14214/sf.275
Accurate field measurement of the forest canopy cover is too laborious to be used in extensive forest inventories. A possible alternative to the separate canopy cover measurements is to utilize the correlations between the percent canopy cover and easier-to-measure forest variables, especially the basal area. A fairly new analysis technique, the beta regression, is specially designed for modelling percentages. As an extension to the generalized linear models, the beta regression takes into account the distribution of the model residuals, and uses a logistic link function to ensure logical predictions. In this study, the beta regression method was found to perform well in conifer dominated study area located in central Finland. The same model shape, with basal area, tree height and an additional predictor (Scots pine: site fertility, Norway spruce: percentage of hardwoods) as independent variables, produced good results for both pine and spruce dominated sites. The models had reasonably high pseudo R-squared values (pine: 0.91, spruce: 0.87) and low standard errors (pine: 6.3%, spruce: 5.9%) for the fitting data, and also performed well in a cross validation test. The models were also tested on separate test plots located in a different geographical area, where the prediction errors were slightly larger (pine: 8.8%, spruce: 7.4%). In pine plots, the model fit was further improved by introducing additional predictors such as stand age and density. This improved also the performance of the models in the cross validation test, but weakened the results for the external data set. Our results indicated that the beta regression method offers a noteworthy alternative to separate canopy cover measurements, especially if time is limited and the models can be applied in the same region where the modelling data were collected.
  • Korhonen, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: lauri.korhonen@joensuu.fi (email)
  • Korhonen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Stenberg, Univ. of Helsinki, Dept of Forest Resource Management, P.O. BOX 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Maltamo, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Rautiainen, Univ. of Helsinki, Dept of Forest Resource Management, P.O. BOX 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
article id 301, category Research article
Sanni Raiskila, Minna Pulkkinen, Tapio Laakso, Kurt Fagerstedt, Mia Löija, Riitta Mahlberg, Leena Paajanen, Anne-Christine Ritschkoff, Pekka Saranpää. (2007). FTIR spectroscopic prediction of Klason and acid soluble lignin variation in Norway spruce cutting clones. Silva Fennica vol. 41 no. 2 article id 301. https://doi.org/10.14214/sf.301
Our purpose was to develop a FTIR spectroscopic method to be used to determine the lignin content in a large number of samples and to apply this method studying variation in sapwood and heartwood lignin content between three fast-growing cutting clones grown in three sites. Models were estimated with 18 samples and tested with 6 samples for which the Klason lignin + acid soluble lignin content had been determined. Altogether 272 candidate models were built with all-subset regressions from the principal components estimated from differently treated transmission spectra of the samples; the spectra were recorded on KBr pellets of sieved and unsieved unextracted wood powder and subjected to four different preprocessings and two different wavenumber selection schemes. The final model showed an adequate fit in the estimation data (R2 = 0.74) as well as a good prediction performance in the test data (R2P = 0.90). This model was based on the wavenumber range of 1850–500 cm–1 of the line-subtraction-normalised spectra recorded from sieved samples. The model was used to predict lignin content in 64 samples of the same material. One of the clones had a slightly lower sapwood lignin content than the two other clones. The fertile growing site with fast growing trees showed slightly higher sapwood lignin content compared with the other two sites. The model was also used to predict the lignin content in the earlywood of 45 individual annual rings. Variation between individual stems and between annual rings was found to be large. No correlation was found between the lignin content and density of earlywood.
  • Raiskila, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail:
  • Pulkkinen, Department of Forest Ecology, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Laakso, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail:
  • Fagerstedt, Department of Biological and Environmental Sciences, Plant Biology, P.O. Box 65, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Löija, VTT Building and Transport, P.O. Box 1806, FI-02044 VTT, Finland ORCID ID:E-mail:
  • Mahlberg, VTT Building and Transport, P.O. Box 1806, FI-02044 VTT, Finland ORCID ID:E-mail:
  • Paajanen, VTT Building and Transport, P.O. Box 1806, FI-02044 VTT, Finland ORCID ID:E-mail:
  • Ritschkoff, VTT Building and Transport, P.O. Box 1806, FI-02044 VTT, Finland ORCID ID:E-mail:
  • Saranpää, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: pekka.saranpaa@metla.fi (email)
article id 300, category Research article
Jouni Siipilehto, Sakari Sarkkola, Lauri Mehtätalo. (2007). Comparing regression estimation techniques when predicting diameter distributions of Scots pine on drained peatlands. Silva Fennica vol. 41 no. 2 article id 300. https://doi.org/10.14214/sf.300
We compared different statistical methods for fitting linear regression models to a longitudinal data of breast height diameter (dbh) distributions of Scots pine dominated stands on drained peatlands. The parameter prediction methods for two parameters of Johnson’s SB distribution, fitted to basal-area dbh distributions, were: 1) a linear model estimated by ordinary least squares (OLS), 2) a multivariate linear model estimated using the seemingly unrelated regression approach (SUR), 3) a linear mixed-effects model with random intercept (MIX), and 4) a multivariate mixed-effects model (MSUR). The aim was to clarify the effect of taking into account the hierarchy of the data, as well as simultaneous estimation of the correlated dependent variables on the model fit and predictions. Instead of the reliability of the predicted parameters, we focused on the reliability of the models in predicting stand conditions. Predicted distributions were validated in terms of bias, RMSE, and error deviation in the generated quantities of the growing stock. The study material consisted of 112 successively measured stands from 12 experimental areas covering the whole of Finland (total of 608 observations). Two independent test data sets were used for model validation. All the advanced regression techniques were superior to OLS, when exactly the same independent stand variables were included. SUR and MSUR were ranked the overall best and second best, respectively. Their ranking was the same in the modeling data, whereas MSUR was superior in the peatland test data and SUR in the mineral soil test data. The ranking of the models was logical, but may not be widely generalized. The SUR and MSUR models were considered to be relevant tools for practical forest management planning purposes over a variety of site types and stand structures.
  • Siipilehto, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: jouni.siipilehto@metla.fi (email)
  • Sarkkola, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail:
  • Mehtätalo, University of Joensuu, Faculty of Forestry, P.O. Box 111, 80101 Joensuu, Finland ORCID ID:E-mail:
article id 473, category Research article
Ulla Mattila, Tuula Nuutinen. (2007). Assessing the incidence of butt rot in Norway spruce in southern Finland. Silva Fennica vol. 41 no. 1 article id 473. https://doi.org/10.14214/sf.473
The aim of this study was to analyze the occurrence of butt rot damage to Norway spruce in different parts of southern Finland and to quantify the associated loss of quality. The data used in the study are from the 9th National Forest Inventory and consist of 5998 sample plots and 8007 spruce sample trees of saw-timber size. To predict the probability of damage to stands and trees, logistic regression models were constructed. Separate models were made for the whole study area, for the area where the general risk of Heterobasidion root and butt rot damage is high and for the area where the damage frequency is relatively low. In the high-risk area, the probability of damage decreased with increasing elevation and increased with increasing temperature sum. In addition, damage was more common on fertile sites and less common on peatlands; and thick peat layer decreased the risk of damage. The probability of damage was also higher in stands where special or selective cuttings had been carried out. In the sample tree data, the probability of damage increased slightly with increasing diameter and age of the tree. In the low-risk areas, elevation was the only variable that explained the probability of damage to a spruce tree. Site fertility and previous cuttings (more than ten years ago) explained the probability of damage to stands only weakly. For spruce damaged by butt rot, the saw-timber volume was reduced, on average, by 60% both in the high-risk area and in the low-risk area.
  • Mattila, The Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Nuutinen, The Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail:
article id 316, category Research article
Sonja Vospernik. (2006). Probability of bark stripping damage by red deer (Cervus elaphus) in Austria. Silva Fennica vol. 40 no. 4 article id 316. https://doi.org/10.14214/sf.316
Bark stripping by red deer (Cervus elaphus) causes considerable damage to Austrian forests, however, the incidence of bark stripping was never examined from large scale survey data. In this manuscript we present a logistic regression model for bark stripping damage (static model) and a model for recent (5-year period) bark stripping damage to previously undamaged trees (dynamic model) developed from Austrian National Forest Inventory data. Both models showed bark stripping damage to be most frequent in core red deer habitat areas and less frequent in less suitable habitat. Damage was concentrated at elevations of 400–1200 m and in alluvial forests (only static model). Norway spruce (Picea abies), European ash (Fraxinus excelsior), Sweet chestnut (Castanea sativa) and Sorbus spp. had 11–12 times more injuries than all the other species. Red deer preferred the smallest trees with a breast height diameter of 5 cm for bark stripping and damage probability decreased rapidly for trees with a breast height diameter greater than 25 cm. Our static model showed a maximum of bark stripping damage in stands with a mean height of 20 m. In the dynamic model the probability for bark stripping damage decreased with decreasing mean height. Also, in the static model the probability for bark stripping damage increased with increasing spruce proportion and with increasing stand density whereas in the dynamic model the proportion of previous bark stripping damage was a good predictor. Goodness of fit and discrimination of both models were good. In combination with forest growth models, the bark stripping models can be used to predict the risk of damage associated with different forest and habitat management options.
  • Vospernik, University of Natural Resources and Applied Life Sciences, Institute of Forest Growth Research, Department of Forest and Soil Sciences, Peter-Jordan-Stra§e 82, A-1190 Vienna, Austria ORCID ID:E-mail: sonja.vospernik@boku.ac.at (email)
article id 382, category Research article
Steen Magnussen, René I. Alfaro, Paul Boudewyn. (2005). Survival-time analysis of white spruce during spruce budworm defoliation. Silva Fennica vol. 39 no. 2 article id 382. https://doi.org/10.14214/sf.382
Mortality and defoliation (DF%) in 987 white spruce (Picea glauca (Moench) Voss) trees were followed from 1992 to 2003 during an outbreak of the spruce budworm Choristoneura fumiferana (Clem.) in 15 white-spruce-dominated uneven-aged stands in the Fort Nelson Forest District near Prince George, British Columbia. Four stands were aerially sprayed with Bacillus thuringiensis (Bt). Defoliation and mortality levels were elevated in non-sprayed stands. The relationship between defoliation and survival-times was captured in a Cox proportional hazard model with a defoliation stress index (DSI), diameter (DBH), crown class (CCL), a random stand effect, Bt-treatment, and number of years of exposure to stand-level defoliation (DYEAR) as predictors. The DSI, optimized for discrimination between survivors and non-survivors, is the discounted sum of five lagged DF% values. Survival probabilities were predicted with a maximum error of 0.02. Hazard rates increased by 0.06 for every one point increase in DSI. CCL and random stand effects were highly significant. Bt-treatment effects were fully captured by DSI, CCL, and DYEAR.
  • Magnussen, Canadian Forest Service, Victoria, BC, Canada. V8Z 1M5 ORCID ID:E-mail: smagnussen@pfc.forestry.ca (email)
  • Alfaro, Canadian Forest Service, Victoria, BC, Canada. V8Z 1M5 ORCID ID:E-mail:
  • Boudewyn, Canadian Forest Service, Victoria, BC, Canada. V8Z 1M5 ORCID ID:E-mail:
article id 519, category Research article
Magnus Lindén, Gudmund Vollbrecht. (2002). Sensitivity of Picea abies to butt rot in pure stands and in mixed stands with Pinus sylvestris in southern Sweden. Silva Fennica vol. 36 no. 4 article id 519. https://doi.org/10.14214/sf.519
Repeatedly sampled data from permanent experimental plots in southern Sweden were used to model butt rot development in Norway spruce growing in pure stands and in mixed stands with Scots pine. The data come from 29 sites with pure spruce, altogether 100 plots, and from 15 sites of mixed spruce and pine, altogether 22 plots. A logistic model provided the best fit to the data. The study material revealed that in mixed stands the proportion of spruce trees with butt rot is lower than in pure Norway spruce stands. The difference in the incidence of butt rot cannot be explained by silviculture or windthrow since both factors are accounted for in the study. The most significant effect on butt rot development in Norway spruce by an admixture of Scots pine, was found when the Scots pine admixture was 50%. In order to reduce the incidence of butt rot in Norway spruce, the study material indicate that there is little to be gained by increasing the Scots pine admixture to much more than 50%.
  • Lindén, Southern Swedish Forest Research Centre c/o Asa Experimental Forest, SLU, S-360 30 Lammhult, Sweden ORCID ID:E-mail: magnus.linden@ess.slu.se (email)
  • Vollbrecht, Southern Swedish Forest Research Centre c/o Asa Experimental Forest, SLU, S-360 30 Lammhult, Sweden ORCID ID:E-mail:
article id 579, category Research article
Matti Maltamo, Kalle Eerikäinen. (2001). The Most Similar Neighbour reference in the yield prediction of Pinus kesiya stands in Zambia. Silva Fennica vol. 35 no. 4 article id 579. https://doi.org/10.14214/sf.579
The aim of the study was to develop a yield prediction model using the non-parametric Most Similar Neighbour (MSN) reference method. The model is constructed on stand level but it contains information also on tree level. A 10-year projection period was used for the analysis of stand growth. First, the canonical correlation matrix was calculated for the whole study material using stand volumes at the beginning and at the end of the growth period as independent variables and stand characteristics as dependent variable. Secondly, similar neighbour estimates were searched from the data categories reclassified according to thinnings. Due to this, it was possible to search for growth and yield series which is as accurate as possible both at the beginning and at the end of the growth period. The reliability of the MSN volume predictions was compared to the volumes predicted with the simultaneous yield model. The MSN approach was observed to be more reliable volume predictor than the traditional stand level yield prediction model both in thinned and unthinned stands.
  • Maltamo, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail: matti.maltamo@forest.joensuu.fi (email)
  • Eerikäinen, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
article id 593, category Research article
Anneli Jalkanen. (2001). The probability of moose damage at the stand level in southern Finland. Silva Fennica vol. 35 no. 2 article id 593. https://doi.org/10.14214/sf.593
The probability of moose damage was studied in sapling stands and young thinning stands in southern Finland. Data from the eighth National Forest Inventory in 1986–92 were used for modelling. The frequency of damage was highest at the height of two to five meters and at the age of ten to twenty years (at the time of measurement). Moose preferred aspen stands the most and least preferred Norway spruce stands. Scots pine and silver birch were also susceptible to damage. Logistic regression models were developed for predicting the probability that moose damage is the most important damaging agent in a forest stand. The best predictive variables were the age and dominant species of the stand. Variables describing the site were significant as cluster averages, possibly characterizing the area as a food source (fertility and organic soil), as well as the lack of shelter (wall stand). When sample plot, cluster and municipality levels were compared, it was found that most of the unexplained variance was at the cluster level. To improve the model, more information should be obtained from that level. The regression coefficients for aspen as supplementary species, and for pine as dominant species, had significant variance from cluster to cluster (area to area). It was also shown that the occurrence of aspen is closely connected to the occurrence of moose damage in pine sapling stands.
  • Jalkanen, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland ORCID ID:E-mail: anneli.jalkanen@metla.fi (email)

Category: Research note

article id 269, category Research note
Christian Kiffner, Elisabeth Rössiger, Oliver Trisl, Rainer Schulz, Ferdinand Rühe. (2008). Probability of recent bark stripping damage by red deer (Cervus elaphus) on Norway spruce (Picea abies) in a low mountain range in Germany – a preliminary analysis. Silva Fennica vol. 42 no. 1 article id 269. https://doi.org/10.14214/sf.269
Red deer (Cervus elaphus) can cause considerable damage to forest stands by bark stripping. Here, we examined the probability of bark stripping of susceptible Norway spruce (Picea abies) during winter in relation to local environmental characteristics in the western Harz Mountains, Lower Saxony, Germany. We present the results of a multiple logistic regression model for recent bark stripping damage by red deer which we developed from two systematic cluster sampling inventories after two winter periods along with associated meteorological data and records of bagged deer. Our model suggests that the risk of bark stripping increased significantly (P  0.05) with rising slope angle, cumulating snow depth and increasing index values of red deer population density. Spruces growing in closed forest stands were debarked at a higher probability than spruces located close to forest edges. Further on, spruce stands on eastern slopes had a lower probability of bark damage than spruce stands on northern slopes. Other tested variables (altitude, length of daily solar irradiation, duration of snow cover, age of spruce stand within the age range of 16–50 years) had no significant effect on the probability of new bark stripping. We conclude that red deer in the western Harz Mountains seem to use bark as food resource at preferred locations and in times of low food availability. To improve fit and predictive power of bark stripping models we recommend including stand characteristics. We propose to reduce the population size of red deer in order to diminish bark stripping damages to an economically acceptable level.
  • Kiffner, University Göttingen, Büsgen-Institute, Department of Forest Zoology and Forest Protection incl. Wildlife Biology and Game Management, Büsgenweg 3, 37077 Göttingen, Germany ORCID ID:E-mail: ckiffne@gwdg.de (email)
  • Rössiger, University Göttingen, Büsgen-Institute, Department of Forest Zoology and Forest Protection incl. Wildlife Biology and Game Management, Büsgenweg 3, 37077 Göttingen, Germany ORCID ID:E-mail:
  • Trisl, Planungsbüro Trisl, In der Schleene 7, 36037 Waake, Germany ORCID ID:E-mail:
  • Schulz, University Göttingen, Büsgen-Institute, Department of Ecological Informatics, Biometry and Forest Growth, Büsgenweg 4, 37077 Göttingen, Germany ORCID ID:E-mail:
  • Rühe, University Göttingen, Büsgen-Institute, Department of Forest Zoology and Forest Protection incl. Wildlife Biology and Game Management, Büsgenweg 3, 37077 Göttingen, Germany ORCID ID:E-mail:

Category: Article

article id 7138, category Article
Kullervo Kuusela, Pekka Kilkki. (1963). Multiple regression of increment percentage on other characteristics in Scots pine stands. Acta Forestalia Fennica vol. 75 no. 4 article id 7138. https://doi.org/10.14214/aff.7138

The objective of this study has been to discover some of the basic principles on which an increment for a large forest area might be forecast. Because the stands in a large forest area vary considerably in density and are subject to different kinds of treatment, the main interest falls on the stand characteristics which determine the increment percentage in such forest conditions as these. The material used in the study has been published earlier, it consisted of sample plots of Scots pine (Pinus sylvestris L.) stands (Nyyssönen 1954).

Increment functions are of great importance in the increment forecast for cutting budget. Because 60-80% of the variation in the increment percentage can be explained by stand characteristics in circumstances where the age of the stand is 40-130 years and the volume vary with a coefficient of variation 0.6-0.7, regression equations for increment percentage may be based on a number of sample plots smaller than in a growing stock inventory in the same conditions. It is possible to get accurate results with relatively small number of sample plots. Furthermore, the smaller amount of increment sample plots makes it possible to develop measurement techniques.

The increment functions enable study of increment as a biological process. However, conclusions about biological process on the basis of regression equations should be made with caution. Still, regression analysis is a powerful tool in yield studies.

The PDF includes a summary in Finnish.

  • Kuusela, ORCID ID:E-mail:
  • Kilkki, ORCID ID:E-mail:
article id 5573, category Article
Ilkka Vanha-Majamaa, Raili Suominen, Tiina Tonteri, Eeva-Stiina Tuittila. (1996). Seedling establishment after prescribed burning of a clear-cut and a partially cut mesic boreal forest in southern Finland. Silva Fennica vol. 30 no. 1 article id 5573. https://doi.org/10.14214/sf.a9218

The prescribed burning of a 7.3 ha clear-cut and a 1.7 ha partially cut forest (volume 150 m3/ha) was carried out in Evo (61 °12'N, 25°07'E) on 1 June 1992. The forest was a mesic Myrtillus site type forest dominated by Norway spruce (Picea abies (L.) H. Karst.). Practically all the trees and the above-ground parts of the understorey vegetation died in the fire, while the mor layer was thinned by an average of 1.5 cm.

A study was made on the change of germinated seedling population in time and their dependence on environmental factors. Seedlings of Norway spruce, Scots pine (Pinus sylvestris L.), silver birch (Betula pendula Roth), pubescent birch (B. pubescens Ehrh.) and rowan (Sorbus aucuparia L.) were inventoried in 1993 and in 1994 on permanent plots, four times per growing season. Autoregression models were used to compare regeneration of tree species in the burned forest with regeneration in the burnt clear-cut area, and to study the effect of distance from nearest seed source to regeneration.

The average number of seedlings germinating in 1993 was higher than in 1994, probably because of differences between these consecutive years in regard to the amount of seed rain and weather conditions. The number of Norway spruce and rowan seedling was higher inside the forest area than in the clear-cut area. The distance to the bordering forest and to the closest seed tree did not explain the result. It is suggested that the more stable microclimatic conditions under the shade of dead tree promote germination and seedling establishment in the forest area. As rowan is a bird-dispersed species, it is likely that dead trees help the dispersal of rowan seed by providing birds place to sit and defecate. The shade provided by dead trees may influence the further succession of the tree stand and vegetation composition and diversity.

  • Vanha-Majamaa, ORCID ID:E-mail:
  • Suominen, ORCID ID:E-mail:
  • Tonteri, ORCID ID:E-mail:
  • Tuittila, ORCID ID:E-mail:
article id 5555, category Article
Mauno Pesonen, Arto Kettunen, Petri Räsänen. (1995). Modelling non-industrial private forest landowners’ strategic decision making by using logistic regression and neural networks: Case of predicting the choice of forest taxation basis. Silva Fennica vol. 29 no. 2 article id 5555. https://doi.org/10.14214/sf.a9206

In this study, logistic regression and neural networks were used to predict non-industrial private forests (NIPF) landowners’ choice of forest taxation basis. The main frame of reference of the study was the Finnish capital taxation reform of 1993. As a consequence of the reform, landowners were required to choose whether to be taxed according to site-productivity or realized-income during the coming transition period of thirteen years.

The most important factor affecting the landowners’ choice of taxation basis was the harvest rate during the transition period, i.e. the chosen timber management strategy. Furthermore, the estimated personal marginal tax rate and the intention to cut timber during next three years affected the choice. The descriptive landowner variables did not have any marked effect on the choice of forest taxation basis.

On average, logistic regression predicted 71% of the choices correctly; the corresponding figure for neural networks was 63%. In both methods, the choice of site-productivity taxation was predicted more accurately than the choice of realized-income taxation. An increase in the number of model variable did not significantly improve the results of neural networks and logistic regression.

  • Pesonen, ORCID ID:E-mail:
  • Kettunen, ORCID ID:E-mail:
  • Räsänen, ORCID ID:E-mail:
article id 5528, category Article
Pekka Tamminen, Michael Starr. (1994). Bulk density of forested mineral soils. Silva Fennica vol. 28 no. 1 article id 5528. https://doi.org/10.14214/sf.a9162

Relationships between bulk density and organic matter (OM) content, textural properties and depth are described for forested mineral soils from Central and Northern Finland. Core samples were taken of 0–5, 30–35 and 60–65 cm layers at 75 plots. Three measures of bulk density were calculated: the bulk density of the < 20 mm fraction (BD20), the bulk density of the < 2 mm fraction (BD2), and laboratory bulk density (BDl). BDl was determined from the mass of a fixed volume of < 2 mm soil taken in the laboratory. All three measures of bulk densities were strongly correlated with organic matter content (r ≥ -0.63). Depth and gravel (2–20 mm) content (in the case of BD2) were also important variables. BDl was sensitive to clay contents > 7% but did significantly improve the prediction of both BD2 and BD20 in coarse soils (clay contents ≤ 7%). Predictive models were derived for coarse soils.

  • Tamminen, ORCID ID:E-mail:
  • Starr, ORCID ID:E-mail:
article id 5270, category Article
Pekka Kilkki, Risto Päivinen. (1986). Weibull function in the estimation of the basal area dbh-distribution. Silva Fennica vol. 20 no. 2 article id 5270. https://doi.org/10.14214/sf.a15449

The paper demonstrates the possibility of using data from small relascope sample plots in the derivation of the regression models which predict the Weibull function parameters for the dbh-distribution. The Weibull parameters describing the basal area dbh-distribution were estimated for relascope sample plots from the Finnish National Forest Inventory. In the first stage of the estimation nonlinear regression analysis was employed to derive initial parameter estimates for the second stage, in which the maximum likelihood method was used. The parameter estimates were employed as dependent variables for the derivation of the regression models; the independent variables comprised of the compartment-wise stand variables generally estimated in ocular inventories.

The PDF includes an abstract in Finnish.

  • Kilkki, ORCID ID:E-mail:
  • Päivinen, ORCID ID:E-mail:
article id 5265, category Article
J. Ross, S. Kellomäki, P. Oker-Blom, V. Ross, L. Vilikainen. (1986). Architecture of Scots pine crown. Silva Fennica vol. 20 no. 2 article id 5265. https://doi.org/10.14214/sf.a15444

Dimensions (length, width and thickness) of needles in crowns of young Scots pine (Pinus sylvestris L.) were found to be related linearly to each other. Similarly, the needle area was linearly correlated with the needle biomass. In the lower crown, needle length was linearly correlated with the length of the shoot, but in the upper crown needle length did not vary according to any regular pattern. Needle density was negatively correlated with shoot length. In the lower crown the needle density varied 20–40 cm-1 and in the upper crown 15– 20 cm-1. The increasing angle of aging needles seemed to be characteristic for Scots pine shoots.

The PDF includes an abstract in Finnish.

  • Ross, ORCID ID:E-mail:
  • Kellomäki, ORCID ID:E-mail:
  • Oker-Blom, ORCID ID:E-mail:
  • Ross, ORCID ID:E-mail:
  • Vilikainen, ORCID ID:E-mail:
article id 7514, category Article
Pekka Ripatti. (1996). Factors affecting partitioning of private forest holdings in Finland. Acta Forestalia Fennica no. 252 article id 7514. https://doi.org/10.14214/aff.7514

Questions of the small size of non-industrial private forest (NIPF) holdings in Finland are considered and factors affecting their partitioning are analysed. This work arises out of Finnish forest policy statements in which the small average size of holdings has been seen to have negative influence on the economics of forestry. A literature survey indicates that the size of holdings is an important factor determining the costs of logging and silvicultural operations, while its influence on the timber supply is slight.

The empirical data are based on a sample of 314 holdings collected by interviewing forest owners in 1980–86. In 1990–91 the same holdings were resurveyed by means of a postal inquiry and partly by interviewing the forest owners. The principal objective was to collect data to assist in quantifying ownership factors that influence partitioning among different kinds of NIPF holdings. Thus, the mechanism of partitioning was described and a maximum likelihood logistic regression model was constructed using seven independent holding and ownership variables.

One out of four holdings had undergone partitioning in conjunction with a change in ownership, one fifth among family owned holdings and nearly a half among jointly owned holdings. The results of the logistic regression model indicate, for instance, that the odds on partitioning is about three times greater for jointly owned holdings than for family owned ones. Also, the probabilities of partitioning were estimated and the impact of independent dichotomous variables on the probability of partitioning ranged between 0.02 and 0.01. The low value of Hosmer-Lemeshow test statistics indicates a good fit of the model, and the rate of correct classification was estimated to be 88% with a cut-off point of 0.5.

The average size of holdings undergoing ownership changes decreased from 29.9 ha to 28.7 ha over the approximate interval 1983–90. In addition, the transition probability matrix showed that the trends towards smaller size categories mostly concerned the small size categories. The results can be used in considering the effects of the small size holdings for forestry and if the purpose is to influence partitioning through forest or rural policy.

  • Ripatti, ORCID ID:E-mail:
article id 7505, category Article
Rauno Väisänen, Kari Heliövaara. (1994). Assessment of insect occurrence in boreal forests based on satellite imagery and field measurements. Acta Forestalia Fennica no. 243 article id 7505. https://doi.org/10.14214/aff.7505

The presence/absence data of 27 forest insect taxa (Retinia resinella, Formica spp., Pissodes spp., several scolytids) and recorded environmental variation were used to investigate the applicability of modelling insect occurrence based on satellite imagery. The sampling was based on 1,800 sample plots (25 m by 25 m) placed along the sides of 30 equilateral triangles (side 1 km) in a fragmented forest area (approximately 100 km2) in Evo, Southern Finland. The triangles were overlaid on land use maps interpreted from satellite images (Landsat TM 30 m multispectral scanner imagery 1991) and digitized geological maps. Insect occurrence was explained using either environmental variables measured in the field or those interpreted from the land use and geological maps. The fit of logistic regression models carried between species, possibly because some species may be associated with characteristics of single trees while other species with stand characteristics. The occurrence of certain insect species at least, especially those associated with Scots pine, could be relatively accurately assessed indirectly on the basis of satellite imagery and geological maps. Models based on both remotely sensed and geological data better predicted the distribution of forest insects except in the case of Xylechinus pilosus, Dryocetes sp. and Trypodendron lineatum, where the differences were relatively small in favour of the models based on field measurements. The number of species was related to habitat compartment size and distance from the habitat edge calculated from the land use maps, but logistic regressions suggested that other environmental variables in general masked the effect of these variables in species occurrence at the present scale.

  • Väisänen, ORCID ID:E-mail:
  • Heliövaara, ORCID ID:E-mail:
article id 7675, category Article
Erkki Tomppo. (1992). Satellite image aided forest site fertility estimation for forest income taxation. Acta Forestalia Fennica no. 229 article id 7675. https://doi.org/10.14214/aff.7675

Two operative forest site class estimation methods utilizing satellite images have been developed for forest income taxation purposes. For this, two pixelwise classification methods and two post-processing methods for estimating forest site fertility are compared using different input data. The pixelwise methods are discriminant analysis, based on generalized squared distances, and logistic regression analysis. The results of pixelwise classifications are improved either with mode filtering within forest stands or assuming a Markov random field type dependence between pixels. The stand delineation is obtained by using ordinary segmentation techniques. Optionally, known stand boundaries given by the interpreter can be applied. The spectral values of images are corrected using a digital elevation model of the terrain. Some textural features are preliminary tested in classification. All methods are justified by using independent test data.

A test of the practical methods was carried out and a cost-benefit analysis computed. The estimated cost saving in site quality classification varies from 14% to 35% depending on the distribution of the site classes of the area. This means a saving of about 2.0–4.5 million FMK per year in site fertility classification for income taxation purposes. The cost savings would rise even to 60% if that version of the method were chosen where field checking is totally omitted. The classification accuracy at the forest holding level would still be similar to that of traditional method.

The PDF includes a summary in Finnish.

  • Tomppo, ORCID ID:E-mail:
article id 7606, category Article
Kari Heliövaara, Rauno Väisänen, Auli Immonen. (1991). Quantitative biogeography of the bark beetles (Coleoptera, Scolytidae) in northern Europe. Acta Forestalia Fennica no. 219 article id 7606. https://doi.org/10.14214/aff.7606

Biogeographical patterns of the Scolytidae in Fennoscandia and Denmark, based on species incidence data from the approximately 70 km x 70 km quadrats (n = 221) used by Lekander et al. (1977), were classified to environmental variables using multivariate methods (two-way indicator species analysis, detrended correspondence analysis, canonical correspondence analysis).

The distributional patterns of scolytid species composition showed similar features to earlier presented zonations based on vegetation composition. One major difference, however, was that the region was more clearly divided in an east-west direction. Temperature variables associated with the location of the quadrat had the highest canonical coefficient values on the first axis of the CCA. Although these variables were the most important determinants of the biogeographical variation in the beetle species assemblages, annual precipitation and the distribution of Picea abies also improved the fit of the species data.

Samples with the most deviant rarity and typicality indices for the scolytid species assempblages in each quadrat were concentrated in several southern Scandinavian quadrats, in some quadrats in northern Sweden, and especially on the Swedish islands (Öland, Gotland, Gotska Sandön) in the Baltic Sea. The use of rarity indices which do not take the number of species per quadrat, also resulted high values for areas near Stockholm and Helsinki with well-known faunas. Methodological tests in which the real changes in the distribution of Ips acuminatus and I. amitinus were used as indicators showed that the currently available multivariate methods are sensitive to small faunal shifts even, and thus permit analysis of the fauna in relation to environmental changes. However, this requires more detailed monitoring of the species’ distributions over longer time spans.

Distribution of seven species (Scolytus intricatus, S. laevis, Hylurgops glabratus, Crypturgus cinereus, Pityogenes salasi, Ips typographus, and Cyleborus dispar) were predicted by logistic regression models using climatic variables. In spite of the deficiencies in the data and the environmental variables selected, the models were relatively good for several but not for all species. The potential effects of climate change on bark beetles are discussed.

The PDF includes a summary in Finnish.

  • Heliövaara, ORCID ID:E-mail:
  • Väisänen, ORCID ID:E-mail:
  • Immonen, ORCID ID:E-mail:

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