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Articles containing the keyword 'modeling'.

Category: Research article

article id 1599, category Research article
Andrew McEwan, Michal Brink, Raffaele Spinelli. (2017). Factors affecting the productivity and work quality of chain flail delimbing and debarking. Silva Fennica vol. 51 no. 2 article id 1599. https://doi.org/10.14214/sf.1599
Highlights: Machine productivity averaged 59 m3 ub SMH–1, with a 19% incidence of delay time; Productivity increased 70% if tree volume increased from 0.1 to 0.4 m3 ub; Debarking quality was good for 58% of the trees, medium for 29% and poor for 13%; The more trees in a bunch and the higher BWBS, the lower debarking quality.

Chain flail delimbing and debarking may improve value recovery from small tree harvests, without renouncing the benefits of multi-tree processing. The technology is mature and capable of excellent performance, which has been documented in many benchmark studies. This paper offers new insights into the relationship between the performance of chain flail delimbing and debarking and such factors as tree volume, load volume, tree form and bark-wood bond strength (BWBS). The study was conducted in Chile, during the commercial harvesting of a Eucalyptus globulus Labill. plantation. In an observational study, researchers collected production data from over 780 work cycles, and work quality data from over 1000 individual trees. The analysis of these data shows that productivity is affected primarily by load volume. Work quality is affected by BWBS and by the number of trees in a load. Work quality degrades with increasing BWBS and tree number, since more trees tend to shield each other. Tree form has no effect on either productivity or work quality. Regression and probability functions are provided, and can be used for predictive purposes when trying to optimize current operations or to prospect the introduction of chain flail technology to new work environments.

  • McEwan, Postgraduate Forest Programme, Faculty of Natural and Agricultural Sciences, University of Pretoria, Private Bag X20 Hatfield, Pretoria, 0028, South Africa ORCID ID:E-mail: Andrew.McEwan@nmmu.ac.za
  • Brink, Postgraduate Forest Programme, Faculty of Natural and Agricultural Sciences, University of Pretoria, Private Bag X20 Hatfield, Pretoria, 0028, South Africa ORCID ID:E-mail: michal@cmo.co.za
  • Spinelli, CNR IVALSA, Via Madonna del Piano 10, I-50019 Sesto Fiorentino (FI), Italy ORCID ID: http://orcid.org/0000-0001-9545-1004 E-mail: spinelli@ivalsa.cnr.it (email)
article id 1448, category Research article
Andrew McEwan, Natascia Magagnotti, Raffaele Spinelli. (2016). The effects of number of stems per stool on cutting productivity in coppiced Eucalyptus plantations. Silva Fennica vol. 50 no. 2 article id 1448. https://doi.org/10.14214/sf.1448
Highlights: Double- and single stem coppice stools were harvested mechanically; Stem size had the strongest impact on productivity; An experienced operator performed equally well with both stool treatments; Cost was ~10% higher with double stems for the less experienced operator; Operator experience may play a major role when cutting coppice stands.

A time study was conducted to determine whether stem crowding had any impact on harvester productivity in Eucalyptus grandis stands. This represents an important element when trying to balance the advantages and disadvantages of coppice management in fast growing plantations designated for mechanized harvesting (i.e. machine felling, delimbing, debarking and cross-cutting). The study material consisted of 446 coppice stems, half of which grew as single stems per stool and half as double stems per stool as a result of different coppice reduction strategies. The dataset was balanced and randomized, with both subsets replicating exactly the same stem size distribution and the single and double stems alternating randomly. Harvester productivity ranged between 6 and 50 m3 under bark per productive machine hour, following the variation of tree diameter from 10 to 40 cm at breast height (1.37 m according to South African standards). Regression analysis indicated that both tree size and stem crowding (e.g. one or two stems per stool) had a significant effect on harvester productivity, which increased with stem size and decreased with stem crowding. However, operator experience may overcome the effect of stem crowding, which was not significant when the harvester was manned by a highly experienced operator. In any case, the effect of stem size was much greater than that of stem crowding, which resulted in a cost difference of less than 10%. However, this figure excludes the possible effects of stem crowding on volume recovery and stem development, which should be addressed in the future.

  • McEwan, Nelson Mandela Metropolitan University – George Campus, Saasveld, 6529, George, South Africa ORCID ID:E-mail: Andrew.McEwan@nmmu.ac.za
  • Magagnotti, CNR IVALSA, Via Madonna del Piano 10, I-50019 Sesto Fiorentino (FI), Italy ORCID ID:E-mail: magagnotti@ivalsa.cnr.it
  • Spinelli, CNR IVALSA, Via Madonna del Piano 10, I-50019 Sesto Fiorentino (FI), Italy ORCID ID:E-mail: spinelli@ivalsa.cnr.it (email)
article id 1395, category Research article
Joseph Buongiorno. (2015). Income and time dependence of forest product demand elasticities and implications for forecasting. Silva Fennica vol. 49 no. 5 article id 1395. https://doi.org/10.14214/sf.1395
Highlights: Elasticities of demand with gross domestic product and prices were stable over time and income level for sawnwood and particleboard only; Other product elasticities differed with income and time, leading in conjunction with a sector model to higher projected world demand and prices than obtained by ignoring differences between countries and over time.

In view of improving multi-country forest sector models, this study investigated to what extent the price and income elasticity of demand for forest products had changed in the past two decades, and how much they depended on the countries income level. For each of seven major product groups annual observations were divided between high-income (top 20% in gross domestic product per capita) and low-income, and between recent (2004–2013) and older (1992–2003) observations. The results indicated that for sawnwood and particleboard the data could be pooled across all countries and years. For the other commodity groups (veneer & plywood, fiberboard, newsprint, printing & writing paper, other paper & paperboard), there were statistically significant differences in gross domestic product or price elasticity between high and low-income levels or old and recent observations. Efficient elasticities were obtained by pooling the maximum number of observations while respecting the statistically significant differences. The resulting GDP elasticities were the same, or very close, across income levels for all products. The price elasticities differed by income level only for newsprint and for veneer and plywood. International forest sector projections to 2065 obtained with these elasticities compared with those based on pooling all data across time and income levels gave less than 3% difference for world consumption of sawnwood, particleboard, fiberboard, and newsprint, but 19% higher consumption for veneer and plywood, 31% for printing and writing paper, and 18% for other paper and paperboard. The world price was 1% to 11% higher for end products and 3% to 22% higher for raw materials and intermediate products.

  • Buongiorno, University of Wisconsin-Madison, Department of Forest and Wildlife Ecology, 1630 Linden Drive, Madison, WI 53706, USA ORCID ID:E-mail: jbuongio@wisc.edu (email)
article id 1087, category Research article
Ilkka Korpela, Lauri Mehtätalo, Lauri Markelin, Anne Seppänen, Annika Kangas. (2014). Tree species identification in aerial image data using directional reflectance signatures. Silva Fennica vol. 48 no. 3 article id 1087. https://doi.org/10.14214/sf.1087
Highlights: Multispectral reflectance data showed a strong and spectrally correlated tree effect; There was no gain in species classification from using species-specific differences of directional reflectance in real data and only a marginal improvement in simulated data; The directional signatures extracted in multiple images are obscured by the intrinsic within-species variation, correlated observations and inherent reflectance calibration errors.
Tree species identification using optical remote sensing is challenging. Modern digital photogrammetric cameras enable radiometrically quantitative remote sensing and the estimation of reflectance images, in which the observations depend largely on the reflectance properties of targets. Previous research has shown that there are species-specific differences in how the brightness observed changes when the viewing direction in an aerial image is altered. We investigated if accounting for such directional signatures enhances species classification, using atmospherically corrected, real and simulated multispectral Leica ADS40 line-camera data. Canopy in direct and diffuse illumination were differentiated and species-specific variance-covariance structures were analyzed in real reflectance data, using mixed-effects modeling. Species classification simulations aimed at elucidating the level of accuracy that can be achieved by using images of different quality, number and view-illumination geometry. In real data, a substantial variance component was explained by tree effect, which demonstrates that observations from a tree correlate between observation geometries as well as spectrally. Near-infrared band showed the strongest tree effect, while the directionality was weak in that band. The gain from directional signatures was insignificant in real data, while simulations showed a potential gain of 1–3 percentage points in species classification accuracy. The quality of reflectance calibration was found to be important as well as the image acquisition geometry. We conclude that increasing the number of image observations cancels out random observation noise and reflectance calibration errors, but fails to eliminate the tree effect and systematic calibration inaccuracy. Directional reflectance constitutes a marginal improvement in tree species classification.
  • Korpela, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland ORCID ID:E-mail: ilkka.korpela@helsinki.fi (email)
  • Mehtätalo, Faculty of Science and Forestry, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: lauri.mehtatalo@uef.fi
  • Markelin, Department of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, Finland ORCID ID:E-mail: lauri.markelin@fgi.fi
  • Seppänen, Faculty of Science and Forestry, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: anne.seppanen@arbonaut.com
  • Kangas, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland ORCID ID:E-mail: annika.kangas@helsinki.fi
article id 44, category Research article
Anabel Aparecida de Mello, Leif Nutto, Karla Simone Weber, Carlos Eduardo Sanquetta, Jorge Luis Monteiro de Matos, Gero Becker. (2012). Individual biomass and carbon equations for Mimosa scabrella Benth. (bracatinga) in southern Brazil. Silva Fennica vol. 46 no. 3 article id 44. https://doi.org/10.14214/sf.44
Mimosa scabrella Benth. is an important native species of southern Brazil widely used for energy and promising for reforestation carbon offsets. Quantification of biomass and carbon stock is valuable for both purposes. From a forest inventory conducted in southern Brazil, data of M. scabrella were analyzed. Thirty sample trees were felled, excavated and weighed in the field and brought to laboratory for biomass and carbon determination. The total aboveground biomass represented 85% of the tree biomass, while roots corresponded to 15%. Correlation matrix of diameter at 1.3 m height (D), tree height (H) versus total and compartment biomass (P) indicated strong association between tree dimensions and biomasses. Five regression models were tested and equations were fitted to data of five biomass compartments and total tree biomass. The best fitting model for total biomass was P = –0.49361 + 0.034865 x D2H whereas for the partial biomass of the compartments was lnP = β0 + β1 x ln(D) + β2 lnH. Carbon concentration was statistically significantly different in foliage than in other compartments. Three approaches of calculating carbon stocks were evaluated and compared to actual data: 1) Estimated total biomass x weighted mean carbon concentration; 2) Estimated partial (compartment) biomass x compartment average carbon concentration; and 3) Carbon regression equations. No statistical difference was detected among them. It was concluded that biomass equations fitted in this study were accurate and useful for fuelwood and carbon estimations.
  • de Mello, Federal University of Sergipe, Brazil ORCID ID:E-mail:
  • Nutto, Federal University of Paraná, Brazil ORCID ID:E-mail: lnutto.ufpr@gmail.com (email)
  • Weber, Federal University of Paraná ORCID ID:E-mail:
  • Sanquetta, Carlos Eduardo Sanquetta ORCID ID:E-mail:
  • Monteiro de Matos, Jorge Luis Monteiro de Matos ORCID ID:E-mail:
  • Becker, University of Freiburg, Institute of Forest Utilization and Work Science, Germany ORCID ID:E-mail:
article id 156, category Research article
Ilkka Korpela, Hans Ole Ørka, Matti Maltamo, Timo Tokola, Juha Hyyppä. (2010). Tree species classification using airborne LiDAR – effects of stand and tree parameters, downsizing of training set, intensity normalization, and sensor type. Silva Fennica vol. 44 no. 2 article id 156. https://doi.org/10.14214/sf.156
Tree species identification constitutes a bottleneck in remote sensing-based forest inventory. In passive images the differentiating features overlap and bidirectional reflectance hampers analysis. Airborne LiDAR provides radiometric and geometric information. We examined the single-trees-level response of two LiDAR sensors in over 13 000 forest trees in southern Finland. We focused on the commercially important species. Our aims were to 1) explore the relevant LiDAR features and study their dependencies on stand and tree variables, 2) examine two sensors and their fusion, 3) quantify the gain from intensity normalizations, 4) examine the importance of the size of the training set, and 5) determine the effects of stand age and site fertility. A set of 570 semiurban broad-leaved trees and exotic conifers was analyzed to 6) examine the LiDAR signal in the economically less important species. An accuracy of 88 90% was achieved in the classification of Scots pine, Norway spruce, and birch, using intensity variables. Spruce and birch showed the highest levels of confusion. Downsizing the training set from 30% to 2.5% of all trees had only a marginal effect on the performance of classifiers. The intensity features were dependent on the absolute and relative sizes of trees, especially for birch. The results suggest that leaf size, orientation, and foliage density affect the intensity, which is thus not affected by reflectance only. Some of the ecologically important species in Finland may be separable, since they gave rise to high intensity values. Comparison of the sensors implies that performance of the intensity data for species classification varies between sensors for reasons that remained uncertain. Both range and gain receiver normalization improved species classification. Weighting of the intensity values improved the fusion of two LiDAR datasets.
  • Korpela, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: ilkka.korpela@helsinki.fi (email)
  • Ørka, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O.Box 5003, NO-1432 Ås, Norway ORCID ID:E-mail:
  • Maltamo, University of Eastern Finland, School of Forest Science, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Tokola, University of Eastern Finland, School of Forest Science, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Hyyppä, Finnish Geodetic Institute, Department of Photogrammetry and Remote Sensing, P.O.Box 15, FI-02431 Masala, Finland ORCID ID:E-mail:
article id 199, category Research article
R. Edward Thomas. (2009). Modeling the relationships among internal defect features and external Appalachian hardwood log defect indicators. Silva Fennica vol. 43 no. 3 article id 199. https://doi.org/10.14214/sf.199
As a hardwood tree grows and develops, surface defects such as branch stubs and wounds are overgrown. Evidence of these defects remain on the log surface for decades and in many instances for the life of the tree. As the tree grows the defect is encapsulated or grown over by new wood. During this process the appearance of the defect in the tree’s bark changes. The defect becomes flatter and its dimension changes. This progressional change in appearance is predictable, permitting the size and location of the internal defect to be reliably estimated. This paper concerns the development and analysis of models for the prediction of internal features. With the advent of surface scanning and external detection systems, the prediction of internal features promises to significantly improve the quality, yield, and value of sawn wood products.
  • Thomas, USDA Forest Service, 241 Mercer Springs Road, Princeton, WV 24740, USA ORCID ID:E-mail: edthomas@gmail.com (email)
article id 197, category Research article
Veli-Pekka Ikonen, Seppo Kellomäki, Heli Peltola. (2009). Sawn timber properties of Scots pine as affected by initial stand density, thinning and pruning: a simulation based approach. Silva Fennica vol. 43 no. 3 article id 197. https://doi.org/10.14214/sf.197
The aim of this work was to analyze how different management schedules with varying initial stand density, thinning and artificial pruning of branches affect the quality, quantity and value of sawing yield in Scots pine (Pinus sylvestris L.). For this purpose, an integrated model system was employed and further developed to simulate: i) the three dimensional structure of the crown and stem of an average tree grown in a stand related to the changes in the within-stand light conditions as caused by the stand management, and ii) the sawing of logs into pieces and their quality grading based on the size and number of living and dead knots on the surfaces of sawn pieces. To maximize the quality of sawn timber, relatively dense stand is desired in the early phase of the rotation to reduce, especially in the lower part of stem, the growth of branches, and to increase the rate of dying and pruning-off of branches. In the later phase, a relatively sparse stand is desired to increase the self-pruning of branches and the occlusion of knots. However, in any case, artificial pruning is needed to maximize the knot-free zone of the stem. Also the value optimization of individual sawn pieces affects the quality and value of sawn timber. Because, only average tree was simulated, the differences between scenarios for stem volume were small. In the future, further model development is needed to analyze the development of crown and stem properties of trees with different status in a stand.
  • Ikonen, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: veli-pekka.ikonen@joensuu.fi (email)
  • Kellomäki, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Peltola, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
article id 241, category Research article
Hailemariam Temesgen, Tara M. Barrett, Greg Latta. (2008). Estimating cavity tree abundance using Nearest Neighbor Imputation methods for western Oregon and Washington forests. Silva Fennica vol. 42 no. 3 article id 241. https://doi.org/10.14214/sf.241
Cavity trees contribute to diverse forest structure and wildlife habitat. For a given stand, the size and density of cavity trees indicate its diversity, complexity, and suitability for wildlife habitat. Size and density of cavity trees vary with stand age, density, and structure. Using Forest Inventory and Analysis (FIA) data collected in western Oregon and western Washington, we applied correlation analysis and graphical approaches to examine relationships between cavity tree abundance and stand characteristics. Cavity tree abundance was negatively correlated with site index and percent composition of conifers, but positively correlated with stand density, quadratic mean diameter, and percent composition of hardwoods. Using FIA data, we examined the performance of Most Similar Neighbor (MSN), k nearest neighbor, and weighted MSN imputation with three variable transformations (regular, square root, and logarithmic) and Classification and Regression Tree with MSN imputation to estimate cavity tree abundance from stand attributes. There was a large reduction in mean root mean square error from 20% to 50% reference sets, but very little reduction in using the 80% reference sets, corresponding to the decreases in mean distances. The MSN imputation using square root transformation provided better estimates of cavity tree abundance for western Oregon and western Washington forests. We found that cavity trees were only 0.25 percent of live trees and 13.8 percent of dead trees in the forests of western Oregon and western Washington, thus rarer and more difficult to predict than many other forest attributes. Potential applications of MSN imputation include selecting and modeling wildlife habitat to support forest planning efforts, regional inventories, and evaluation of different management scenarios.
  • Temesgen, Department of Forest Resources, Oregon State University, Corvallis, OR, USA ORCID ID:E-mail: hailemariam.temesgen@oregonstate.edu (email)
  • Barrett, Pacific Northwest Research Station, Anchorage, AK, USA ORCID ID:E-mail:
  • Latta, Department of Forest Resources, Oregon State University, Corvallis, OR, USA ORCID ID:E-mail:
article id 386, category Research article
Jouni Kalliovirta, Timo Tokola. (2005). Functions for estimating stem diameter and tree age using tree height, crown width and existing stand database information. Silva Fennica vol. 39 no. 2 article id 386. https://doi.org/10.14214/sf.386
The aim was to investigate the relations between diameter at breast height and maximum crown diameter, tree height and other possible independent variables available in stand databases. Altogether 76 models for estimating stem diameter at breast height and 60 models for tree age were formulated using height and maximum crown diameter as independent variables. These types of models can be utilized in modern remote sensing applications where tree crown dimensions and tree height are measured automatically. Data from Finnish national forest inventory sample plots located throughout the country were used to develop the models, and a separate test site was used to evaluate them. The RMSEs of the diameter models for the entire country varied between 7.3% and 14.9% from the mean diameter depending on the combination of independent variables and species. The RMSEs of the age models for entire country ranged from 9.2% to 12.8% from the mean age. The regional models were formulated from a data set in which the country was divided into four geographical areas. These regional models reduced local error and gave better results than the general models. The standard deviation of the dbh estimate for the separate test site was almost 5 cm when maximum crown width alone was the independent variable. The deviation was smallest for birch. When tree height was the only independent variable, the standard deviation was about 3 cm, and when both height and maximum crown width were included it was under 3 cm. In the latter case, the deviation was equally small (11%) for birch and Norway spruce and greatest (13%) for Scots pine.
  • Kalliovirta, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Tokola, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: timo.tokola@helsinki.fi
article id 559, category Research article
Juho Pennanen. (2002). Forest age distribution under mixed-severity fire regimes – a simulation-based analysis for middle boreal Fennoscandia. Silva Fennica vol. 36 no. 1 article id 559. https://doi.org/10.14214/sf.559
A simulation model was used to study the age structure of unmanaged forest landscapes under different fire regimes. Stand age was defined as the age of the oldest tree cohort in a stand. When most fires are not stand-replacing, the theoretical equilibrium stand age distribution is either bell-shaped or bimodal and dominated by old age-classes. Old-growth forests (oldest cohort > 150 y) dominate the landscape unless fires are both frequent and severe. Simulation results and analytical calculations show that if a regime of frequent fires (about every 50 y) maintains landscapes dominated by old-growth forests, then old-growth dominance persists when the number of fires is decreased, despite the associated increase in fire severity. Simulation results were applied to Pinus sylvestris-dominated landscapes of middle boreal Fennoscandia, which according to empirical results were dominated by old-growth forests when fires were frequent during the 19th century. Since the changes in the fire regime can be plausibly explained by changes in the number of human-caused ignitions, old-growth forests have evidently also dominated the landscapes earlier when fires were less frequent. The simulation model is used to produce plausible age distributions of middle boreal Fennoscandian forest landscapes under different historical fire regimes. In summary, the frequency of large-scale disturbance alone predicts forest landscape dynamics poorly, and the roles played by fire severity and residual stands need to be considered carefully. Maintaining and restoring old-growth structures is essential to regaining the natural variability of Fennoscandian forest landscapes.
  • Pennanen, Department of Forest Ecology, P.O. Box 27, FIN-00014 University of Helsinki, Finland ORCID ID:E-mail: juho.pennanen@helsinki.fi (email)
article id 585, category Research article
Meinrad Rohner, Klaus Böswald. (2001). Forestry development scenarios: timber production, carbon dynamics in tree biomass and forest values in Germany. Silva Fennica vol. 35 no. 3 article id 585. https://doi.org/10.14214/sf.585
The dynamics of the age class structure stands at the center of modeling long-run forestry scenarios. This insight has been applied to the construction of the Forest Development and Carbon Budget Simulation Model (ForCaBSiM), a model which is used for the study of several interrelated questions: the development of timber stocks and the potential level of sustainable harvests, the stocks and fluxes of tree carbon in managed forests, the economy-wide effects of management practices on the value of forest lands and timber stocks. The combined study of these issues allows to assess development scenarios with regard to the productive potential of forestry, the carbon cycle, and forest values. At present, the model is adapted to German data, but it is designed for use with other data sets as well. This paper provides a description of core mechanisms in ForCaBSiM. On this background, the choice and impact of crucial assumptions is examined. Illustrative results are used to demonstrate the use of the model. The paper focuses on the impact of varying rotation ages and the tree species composition. Particular attention is given to the concept of steady states.
  • Rohner, Renewable Resource Modeling, D-63477 Maintal, Germany ORCID ID:E-mail: rohner@rrmodeling.de (email)
  • Böswald, Factor Consulting + Management AG, CH-8045 Zurich, Switzerland ORCID ID:E-mail:

Category: Special section

article id 290, category Special section
Mikko Peltoniemi, Esther Thürig, Stephen Ogle, Taru Palosuo, Marion Schrumpf, Thomas Wutzler, Klaus Butterbach-Bahl, Oleg Chertov, Alexander Komarov, Aleksey Mikhailov, Annemieke Gärdenäs, Charles Perry, Jari Liski, Pete Smith, Raisa Mäkipää. (2007). Models in country scale carbon accounting of forest soils. Silva Fennica vol. 41 no. 3 article id 290. https://doi.org/10.14214/sf.290
Countries need to assess changes in the carbon stocks of forest soils as a part of national greenhouse gas (GHG) inventories under the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol (KP). Since measuring these changes is expensive, it is likely that many countries will use alternative methods to prepare these estimates. We reviewed seven well-known soil carbon models from the point of view of preparing country-scale soil C change estimates. We first introduced the models and explained how they incorporated the most important input variables. Second, we evaluated their applicability at regional scale considering commonly available data sources. Third, we compiled references to data that exist for evaluation of model performance in forest soils. A range of process-based soil carbon models differing in input data requirements exist, allowing some flexibility to forest soil C accounting. Simple models may be the only reasonable option to estimate soil C changes if available resources are limited. More complex models may be used as integral parts of sophisticated inventories assimilating several data sources. Currently, measurement data for model evaluation are common for agricultural soils, but less data have been collected in forest soils. Definitions of model and measured soil pools often differ, ancillary model inputs require scaling of data, and soil C measurements are uncertain. These issues complicate the preparation of model estimates and their evaluation with empirical data, at large scale. Assessment of uncertainties that accounts for the effect of model choice is important part of inventories estimating large-scale soil C changes. Joint development of models and large-scale soil measurement campaigns could reduce the inconsistencies between models and empirical data, and eventually also the uncertainties of model predictions.
  • Peltoniemi, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: mikko.peltoniemi@metla.fi (email)
  • Thürig, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland; European Forest Institute, Joensuu, Finland ORCID ID:E-mail:
  • Ogle, Natural Resources Ecology Laboratory, Colorado State University, Fort Collins, USA ORCID ID:E-mail:
  • Palosuo, European Forest Institute, Joensuu, Finland ORCID ID:E-mail:
  • Schrumpf, Max-Planck-Institute for Biogeochemistry, Jena, Germany ORCID ID:E-mail:
  • Wutzler, Max-Planck-Institute for Biogeochemistry, Jena, Germany ORCID ID:E-mail:
  • Butterbach-Bahl, Institute for Meteorology and Climate Research, Forschungszentrum Karlsruhe GmbH, Garmisch-Partenkirchen, Germany ORCID ID:E-mail:
  • Chertov, St. Petersburg State University, St. Petersburg-Peterhof, Russia ORCID ID:E-mail:
  • Komarov, Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy of Sciences, Pushchino, Russia ORCID ID:E-mail:
  • Mikhailov, Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy of Sciences, Pushchino, Russia ORCID ID:E-mail:
  • Gärdenäs, Dept. of Soil Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden ORCID ID:E-mail:
  • Perry, USDA Forest Service, Northern Research Station, St. Paul, MN USA ORCID ID:E-mail:
  • Liski, Finnish Environment Institute, Helsinki, Finland ORCID ID:E-mail:
  • Smith, School of Biological Sciences, University of Aberdeen, Aberdeen, UK ORCID ID:E-mail:
  • Mäkipää, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: raisa.makipaa@metla.fi

Category: Article

article id 5425, category Article
Hannu Saarenmaa. (1990). Frame- and rule-based knowledge representation in an expert system for integrated management of bark beetles. Silva Fennica vol. 24 no. 2 article id 5425. https://doi.org/10.14214/sf.a15579

Decision making in the forest protection involves diagnosing the pest, making predictions of the effects of the pest on forest, knowing the possible control tactics, and cost/benefit integration. To cope with all that, a generalist forest manager needs a tool like an expert system to support decisions.

This paper presents an expert system that approaches the goals of integrated pest management. With the systm, the user can make diagnosis and predictions of 12 North European bark beetles. Written in Common LISP and Flavors, the expert system has a combined frame- and rule-based knowledge representation. Frames are used to represent the hierarchy of insect taxonomy in diagnosis. Prediction is made with qualitative reasoning with rules. The interface engine applies both forward and backward chaining. The system has a graphical user interface that supports exploring the sensitivity of advice on input.

It is concluded that expert systems and artificial intelligence have high applicability everywhere in forestry where complicated decisions have to be made. Especially, an integrated pest management system in forestry is largely equivalent to a computerized decision-making aid.

The PDF includes an abstract in Finnish.

  • Saarenmaa, ORCID ID:E-mail:

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