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Articles containing the keyword 'diameter distribution'.

Category: Research article

article id 1568, category Research article
Jouni Siipilehto, Harri Lindeman, Mikko Vastaranta, Xiaowei Yu, Jori Uusitalo. (2016). Reliability of the predicted stand structure for clear-cut stands using optional methods: airborne laser scanning-based methods, smartphone-based forest inventory application Trestima and pre-harvest measurement tool EMO. Silva Fennica vol. 50 no. 3 article id 1568. https://doi.org/10.14214/sf.1568
Highlights: An airborne laser scanning grid-based approach for determining stand structure enabled bi- or multimodal predicted distributions that fitted well to the ground-truth harvester data; EMO and Trestima applications needed stand-specific inventory for sample measurements or sample photos, respectively, and at their best, provided superior accuracy for predicting certain stand characteristics.

Accurate timber assortment information is required before cuttings to optimize wood allocation and logging activities. Timber assortments can be derived from diameter-height distribution that is most often predicted from the stand characteristics provided by forest inventory. The aim of this study was to assess and compare the accuracy of three different pre-harvest inventory methods in predicting the structure of mainly Scots pine-dominated, clear-cut stands. The investigated methods were an area-based approach (ABA) based on airborne laser scanning data, the smartphone-based forest inventory Trestima app and the more conventional pre-harvest inventory method called EMO. The estimates of diameter-height distributions based on each method were compared to accurate tree taper data measured and registered by the harvester’s measurement systems during the final cut. According to our results, grid-level ABA and Trestima were generally the most accurate methods for predicting diameter-height distribution. ABA provides predictions for systematic 16 m × 16 m grids from which stand-wise characteristics are aggregated. In order to enable multimodal stand-wise distributions, distributions must be predicted for each grid cell and then aggregated for the stand level, instead of predicting a distribution from the aggregated stand-level characteristics. Trestima required a sufficient sample for reliable results. EMO provided accurate results for the dominating Scots pine but, it could not capture minor admixtures. ABA seemed rather trustworthy in predicting stand characteristics and diameter distribution of standing trees prior to harvesting. Therefore, if up-to-date ABA information is available, only limited benefits can be obtained from stand-specific inventory using Trestima or EMO in mature pine or spruce-dominated forests.

  • Siipilehto, Natural Research Institute Finland (Luke), Management and Production of Renewable Resources, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: jouni.siipilehto@luke.fi (email)
  • Lindeman,  Natural Research Institute Finland, Green Technology, Kaironiementie 15, 39700 Parkano ORCID ID:E-mail: harri.lindeman@luke.fi
  • Vastaranta, University of Helsinki, Department of Forest Sciences, P.O. Box 62 (Viikinkaari 11), FI-00014 University of Helsinki ORCID ID:E-mail: mikko.vastaranta@helsinki.fi
  • Yu, Finnish Geospatial Research Institute (FGI), Department of Remote Sensing and Photogrammetry, National Land Survey of Finland, P.O. Box 15 (Geodeetinrinne 2), FI-02431, Masala, Finland ORCID ID:E-mail: xiaowei.yu@maanmittauslaitos.fi
  • Uusitalo,  Natural Research Institute Finland, Green Technology, Kaironiementie 15, 39700 Parkano ORCID ID:E-mail: jori.uusitalo@luke.fi
article id 1057, category Research article
Jouni Siipilehto, Lauri Mehtätalo. (2013). Parameter recovery vs. parameter prediction for the Weibull distribution validated for Scots pine stands in Finland. Silva Fennica vol. 47 no. 4 article id 1057. https://doi.org/10.14214/sf.1057
Highlights: A parameter recovery method (PRM) was developed for forest stand inventories and compared with previously developed parameter prediction methods (PPM) in Finland; PRM for the 2-parameter Weibull function provided compatibility for the main stand characteristics: stem number, basal area and one of the four optional mean characteristics; PRM provided comparable and at its best, superior accuracy in volume characteristics compared with PPM.
The moment-based parameter recovery method (PRM) has not been applied in Finland since the 1930s, even after a continuation of forest stand structure modelling in the 1980s. This paper presents a general overview of PRM and some useful applications. Applied PRM provided compatibility for the included stand characteristics of stem number (N) and basal area (G) with either mean (D), basal area-weighted mean (DG), median (DM) or basal area-median (DGM) diameter at breast height (dbh). A two-parameter Weibull function was used to describe the dbh-frequency distribution of Scots pine stands in Finland. In the validation, PRM was compared with existing parameter prediction models (PPMs). In addition, existing models for stand characteristics were used for the prediction of unknown characteristics. Validation consisted of examining the performance of the predicted distributions with respect to variation in stand density and accuracy of the localised distributions, as well as accuracy in terms of bias and the RMSE in stand characteristics in the independent test data set. The validation data consisted of 467 randomly selected stands from the National Forest Inventory based plots. PRM demonstrated excellent accuracy if G and N were both known. At its best, PRM provided accuracy that was superior to any existing model in Finland – especially in young stands (mean height < 9 m), where the RMSE in total and pulp wood volumes, 3.6 and 5.7%, respectively, was reduced by one-half of the values obtained using the best performing existing PPM (8.7–11.3%). The unweighted Weibull distribution solved by PRM was found to be competitive with weighted existing PPMs for advanced stands. Therefore, using PRM, the need for a basal area weighted distribution proved unnecessary, contrary to common belief. Models for G and N were shown to be unreliable and need to be improved to obtain more reliable distributions using PRM.
  • 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)
  • Mehtätalo, University of Eastern Finland, School of Computing, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: lauri.mehtatalo@uef.fi
article id 956, category Research article
Michał Zasada. (2013). Evaluation of the double normal distribution for tree diameter distribution modeling. Silva Fennica vol. 47 no. 2 article id 956. https://doi.org/10.14214/sf.956
The double normal distribution consists of two normal distributions truncated at their means and then combined in such a way, that points of truncation now become the overall distribution mode. So far, parameters of the double normal distribution have been estimated exclusively using the method of moments. This study evaluates the maximum likelihood method for the estimation of the double normal distribution parameters in Scots pine stands in Poland, and compares it to the results of the method of moments and the two-parameter Weibull distribution fitted using the maximum likelihood method and the method of moments. Presented results show that it is not recommended to use the maximum likelihood method of parameter fitting with Nelder-Mead and quasi-Newton optimization algorithms for the double normal distribution for small samples. However, it can be used for large samples, giving the fit comparable to the two-parameter Weibull distribution and providing parameters having sound practical and biological meaning. In the case of smaller samples for the double normal distribution it is recommended to apply the maximum likelihood method with the alternative simulated annealing optimization algorithm, use the method of moments or substitute the described distribution with more the flexible and robust Weibull distribution. For the smaller samples, the method of moments was superior to the maximum likelihood method.
  • Zasada, Warsaw University of Life Sciences, Faculty of Forestry, Laboratory of Dendrometry and Forest Productivity, Nowoursynowska 159, 02-776 Warsaw, Poland ORCID ID:E-mail: michal.zasada@wl.sggw.pl (email)
article id 99, category Research article
Jouni Siipilehto. (2011). Local prediction of stand structure using linear prediction theory in Scots pine-dominated stands in Finland. Silva Fennica vol. 45 no. 4 article id 99. https://doi.org/10.14214/sf.99
This study produced a family of models for eight standard stand characteristics, frequency and basal area-based diameter distributions, and a height curve for stands in Finland dominated by Scots pine (Pinus sylvestris L.). The data consisted of 752 National Forest Inventory-based sample plots, measured three times between 1976 and 2001. Of the data, 75% were randomly selected for modelling and 25% left out for model evaluation. Base prediction models were constructed as functions of stand age, location and site providing strongly average expectations. These expectations were then calibrated with the known stand variables using linear prediction theory when estimating the best linear unbiased predictor (BLUP). Three stand variables, typically assessed in Finnish forest management planning fieldwork, were quite effective for calibrating the expectation for the unknown variable. In the case of optional distributions, it was essential to choose the weighting of the diameter distribution model such that the available input variables and the model applied were based on the same scale (e.g. arithmetic stand variables for frequency distribution). Additional input variables generally improved the accuracy of the validated characteristics, but the improvements in the predicted distributions were most noteworthy when the arithmetic mean and basal area-weighted median were simultaneously included in the BLUP estimation. The BLUP method provided a flexible approach for characterising relationships among stand variables, alternative size distributions and the height–diameter curve. Models are intended for practical use in the MOTTI simulator.
  • 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)
article id 237, category Research article
Jussi Peuhkurinen, Matti Maltamo, Jukka Malinen. (2008). Estimating species-specific diameter distributions and saw log recoveries of boreal forests from airborne laser scanning data and aerial photographs: a distribution-based approach. Silva Fennica vol. 42 no. 4 article id 237. https://doi.org/10.14214/sf.237
The low-density airborne laser scanning (ALS) data based estimation methods have been shown to produce accurate estimates of mean forest characteristics and diameter distributions, according to several studies. The used estimation methods have been based on the laser canopy height distribution approach, where various laser pulse height distribution -derived predictors are related to the stand characteristics of interest. This approach requires very delicate selection methods for selecting the suitable predictor variables. In this study, we introduce a new nearest neighbor search method that requires no complicated selection algorithm for choosing the predictor variables and can be utilized in multipurpose situations. The proposed search method is based on Minkowski distances between the distributions extracted from low density ALS data and aerial photographs. Apart from the introduction of a new search method, the aims of this study were: 1) to produce accurate species-specific diameter distributions and 2) to estimate factual saw log recovery, using the estimated height-diameter distributions and a stem data bank. The results indicate that the proposed method is suitable for producing species-specific diameter distributions and volumes at the stand level. However, it is proposed, that the utilization of more extensive and locally emphasized reference data and auxiliary variables could yield more accurate saw log recoveries.
  • Peuhkurinen, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, 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:
  • Malinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail:
article id 282, category Research article
Annika Kangas, Lauri Mehtätalo, Matti Maltamo. (2007). Modelling percentile based basal area weighted diameter distribution. Silva Fennica vol. 41 no. 3 article id 282. https://doi.org/10.14214/sf.282
In percentile method, percentiles of the diameter distribution are predicted with a system of models. The continuous empirical diameter distribution function is then obtained by interpolating between the predicted values of percentiles. In Finland, the distribution is typically modelled as a basal-area weighted distribution, which is transformed to a traditional density function for applications. In earlier studies it has been noted that when calculated from the basal-area weighted diameter distribution, the density function is decreasing in most stands, especially for Norway spruce. This behaviour is not supported by the data. In this paper, we investigate the reasons for the unsatisfactory performance and present possible solutions for the problem. Besides the predicted percentiles, the problems are due to implicit assumptions of diameter distribution in the system. The effect of these assumptions can be somewhat lessened with simple ad-hoc methods, like increasing new percentiles to the system. This approach does not, however, utilize all the available information in the estimation, namely the analytical relationships between basal area, stem number and diameter. Accounting for these, gives further possibilities for improving the results. The results show, however, that in order to achieve further improvements, it would be recommendable to make the implicit assumptions more realistic. Furthermore, height variation within stands seems to have an important contribution to the uncertainty of some forest characteristics, especially in the case of sawnwood volume.
  • Kangas, Department of Forest Resources Management, P.O.Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Mehtätalo, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Maltamo, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
article id 321, category Research article
Jori Uusitalo, Anne Puustelli, Veli-Pekka Kivinen, Tapio Nummi, Bikas K. Sinha. (2006). Bayesian estimation of diameter distribution during harvesting. Silva Fennica vol. 40 no. 4 article id 321. https://doi.org/10.14214/sf.321
This research aims to combine two different data sets with Bayesian statistics in order to predict the diameter distribution of trees at harvest. The parameters of prior distribution are derived from the forest management plans supplemented by additional ocular information. We derive the parameters for the sample data from the first trees harvested, and then create the posterior distribution within the Bayesian framework. We apply the standard normal distribution to construct diameter (dbh) distributions, although many other theoretical distributions have been proved better with dbh data available. The methodology developed is then tested on nine mature spruce (Picea abies) dominated stands, on which the normal distribution seems to work well in mature spruce stands. The tests indicate that prediction of diameter distribution for the whole stand based on the first trees harvested is not wise, since it tends to give inaccurate predictions. Combining the first trees harvested with prior information seems to increase the reliability of predictions.
  • Uusitalo, The Finnish Forest Research Institute, Parkano unit, FI-39700 Parkano, Finland ORCID ID:E-mail: jori.uusitalo@metla.fi (email)
  • Puustelli, University of Tampere, Department of Mathematics, Statistics and Philosophy, FI-33014 University of Tampere, Finland ORCID ID:E-mail:
  • Kivinen, University of Helsinki, Department of Forest Resource Management, Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Nummi, University of Tampere, Department of Mathematics, Statistics and Philosophy, FI-33014 University of Tampere, Finland ORCID ID:E-mail:
  • Sinha, Stat-Math Division, Indian Statistical Institute, 203 B.T. Road, Kolkata - 700 108, India ORCID ID:E-mail:
article id 522, category Research article
Annika Kangas, Matti Maltamo. (2002). Anticipating the variance of predicted stand volume and timber assortments with respect to stand characteristics and field measurements. Silva Fennica vol. 36 no. 4 article id 522. https://doi.org/10.14214/sf.522
Several models and/or several variable combinations could be used to predict the diameter distribution of a stand. Typically, a fixed model and a fixed variable combination is used in all conditions. The calibration procedure, however, makes it possible to choose the measurement combination from among many possibilities, although the model used is fixed. In this study, the usefulness of utilizing additional stand characteristics for calibrating the predicted diameter distribution is examined. Nine measurement strategies were tested in predicting the total stand volume, sawlog volume and pulpwood volume. The observed errors of these variables under each strategy were modeled as a function of basal area, basal area median diameter and number of stems. The models were estimated in three steps. First, an Ordinary Least Squares (OLS) model was fitted to the observed errors. Then, a variance function was estimated using the OLS residuals. Finally, a weighted Seemingly Unrelated Regression (SUR) analysis was used to model the observed errors, using the estimated variance functions as weights. The estimated models can be used to anticipate the precision and accuracy of predicted volume characteristics for each stand with different variable combinations and, consequently, to choose the best measurement combination in different stands.
  • Kangas, University of Helsinki, Dept. of Forest Resources Management, P.O. Box 27, 00014 University of Helsinki, Finland ORCID ID:E-mail: annika.kangas@helsinki.fi (email)
  • Maltamo, University of Joensuu, Faculty of Forestry, P.O. Box 111, 80101 Joensuu, Finland ORCID ID:E-mail:
article id 620, category Research article
Annika Kangas, Matti Maltamo. (2000). Performance of percentile based diameter distribution prediction and Weibull method in independent data sets. Silva Fennica vol. 34 no. 4 article id 620. https://doi.org/10.14214/sf.620
Diameter distribution is used in most forest management planning packages for predicting stand volume, timber volume and stand growth. The prediction of diameter distribution can be based on parametric distribution functions, distribution-free parametric prediction methods or purely non-parametric methods. In the first case, the distribution is obtained by predicting the parameters of some probability density function. In a distribution-free percentile method, the diameters at certain percentiles of the distribution are predicted with models. In non-parametric methods, the predicted distribution is a linear combination of similar measured stands. In this study, the percentile based diameter distribution is compared to the results obtained with the Weibull method in four independent data sets. In the case of Scots pine, the other methods are also compared to k-nearest neighbour method. The comparison was made with respect to the accuracy of predicted stand volume, saw timber volume and number of stems. The predicted percentile and Weibull distributions were calibrated using number of stems measured from the stand. The information of minimum and maximum diameters were also used, for re-scaling the percentile based distribution or for parameter recovery of Weibull parameters. The accuracy of the predicted stand characteristics were also compared for calibrated distributions. The most reliable results were obtained using the percentile method with the model set including number of stems as a predictor. Calibration improved the results in most cases. However, using the minimum and maximum diameters for parameter recovery proved to be inefficient.
  • Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland ORCID ID:E-mail: annika.kangas@metla.fi (email)
  • Maltamo, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
article id 619, category Research article
Annika Kangas, Matti Maltamo. (2000). Percentile based basal area diameter distribution models for Scots pine, Norway spruce and birch species. Silva Fennica vol. 34 no. 4 article id 619. https://doi.org/10.14214/sf.619
Information about diameter distribution is used for predicting stand total volume, timber volume and stand growth for forest management planning. Often, the diameter distribution is obtained by predicting the parameters of some probability density function, using means and sums of tree characters as predictors. However, the results have not always been satisfactory: the predicted distributions practically always have a similar shape. Also, multimodal distributions cannot be obtained. However, diameter distribution can also be predicted using distribution-free methods. In the percentile method, the diameters at certain percentiles of the distribution are predicted with models. The empirical diameter distribution function is then obtained by interpolating between the predicted diameters. In this paper, models for diameters at 12 percentiles of stand basal area are presented for Scots pine, Norway spruce and birch species. Two sets of models are estimated: a set with and one without number of stems as a predictor. Including the number of stems as a predictor improved the volume and saw timber volume estimates for all species, but the improvements were especially high for number of stems estimates obtained from the predicted distribution. The use of number of stems as predictor in models is based on the possibility of including this characteristic to measured stand variables.
  • Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland ORCID ID:E-mail: annika.kangas@metla.fi (email)
  • Maltamo, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail:

Category: Research note

article id 310, category Research note
Timo Tahvanainen, Kalle Kaartinen, Timo Pukkala, Matti Maltamo. (2007). Comparison of approaches to integrate energy wood estimation into the Finnish compartment inventory system. Silva Fennica vol. 41 no. 1 article id 310. https://doi.org/10.14214/sf.310
The harvesting of energy wood from young stands is increasing as the demand for renewable wood fuel is growing. Energy wood consists of stems, tree tops, branches and needles, depending on the size of the trees and the logging method used. The current forest inventory and planning systems used in private forests in Finland do not produce estimates of energy wood components. In stands typical for energy wood harvesting, a large share of energy wood consists of trees smaller than the minimum size for pulpwood. In this study, energy wood was included into the calculation system of compartment inventory, and a procedure for simulating the thinning treatments in young stands was developed. The results for six inventory alternatives and prediction of energy wood were compared with the use of inventory material from 37 young stands that have plenty of energy wood. The measurement of additional stand characteristics and the use of a calibration estimation method was tested, as well as the use of plot-level inventory data instead of stand level data. The results showed that the measurement of the number of trees per hectare, in addition to stand basal area and mean diameter, improved the energy wood estimates. The additional minimum and maximum diameters improved the precision of the estimates, but did not affect bias. The removal estimates were more precise when plot-level data was used, rather than stand-level data. The removal estimates were higher with plot-level data. The results suggest that, in heterogeneous young stands, plot by plot prediction would give more accurate removal estimates than the calculation of a corresponding prediction at the stand-level.
  • Tahvanainen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: timo.tahvanainen@metla.fi (email)
  • Kaartinen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuun yliopisto, Finland ORCID ID:E-mail:
  • Pukkala, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuun yliopisto, Finland ORCID ID:E-mail:
  • Maltamo, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuun yliopisto, Finland ORCID ID:E-mail:

Category: Article

article id 5532, category Article
Anu Honkanen. (1994). Selection of Salix myrsinifolia clones for biomass forestry in Finland. Silva Fennica vol. 28 no. 3 article id 5532. https://doi.org/10.14214/sf.a9172

For biomass forestry in the inland parts of Southern and Central Finland, the obvious choice of willow species is Salix myrsinifolia. However, selection of clones of indigenous species has not yet been completed and more research and selection is needed. In the Piipsanneva old peatland trial, indigenous species of willow, mostly clones of S. myrsinifolia and S. phylicifolia, were compared in terms of biomass production, coppicing, height growth and diameter distributions. In this trial, the mean annual biomass production was not particularly high; more important results were attained in the ranking of clones. The trial strengthens the hypothesis that, over the long-term, the biomass production of S. myrsinifolia is higher than that of S. phylicifolia. It was supposed that behind the highest yield there was a clone with uniform quality, one whose diameter distribution would be narrow and positively skewed. Comparisons of parameters of Weibull functions showed that the distributions of the best clones were wide, indicating that those clones use the whole growth space better than those with narrow distribution.

  • Honkanen, ORCID ID:E-mail:
article id 5419, category Article
Timo Pukkala, Owen Mubita, Jussi Saramäki. (1990). Management planning system for tree plantations. Silva Fennica vol. 24 no. 2 article id 5419. https://doi.org/10.14214/sf.a15573

The paper presents a simple model of long-term forest management planning in tree plantations. The model is particularly suitable for developing countries where the research resources are limited. The management plan is prepared in two steps. First, one or several treatment schedules are simulated for each calculation unit (age class, compartment, etc.) over the selected planning period. Second, an optimal combination treatment schedules according to the selected objectives and constraints is searched by mathematical programming. The simulation of growth is based on the prediction of the diameter distribution at the desired time point. All stand characteristics are derived from this distribution. The models needed in the yield simulation can be estimated from temporary sample plots. A case study management plan for 13,000 ha of Pinus kesiya (Royle ex Gordon) plantations in Zambia is presented to demonstrate the system.

The PDF includes an abstract in Finnish.

  • Pukkala, ORCID ID:E-mail:
  • Mubita, ORCID ID:E-mail:
  • Saramäki, ORCID ID:E-mail:
article id 5375, category Article
Timo Pukkala. (1989). Prediction of tree diameter and height in a Scots pine stand as a function of the spatial pattern of trees. Silva Fennica vol. 23 no. 2 article id 5375. https://doi.org/10.14214/sf.a15532

The study presents two methods of predicting tree dimensions in a Scots pine (Pinus sylvestris L.) stand if only the location of trees is known. The first method predicts the tree diameter from the spatial location of neighbours. In the second method the diameter distribution of a subarea is estimated from the local stand density. This distribution is then sampled to obtain diameters. In both methods the tree height is predicted with a spatial model on the basis of diameters and locations of trees. The main purpose of the presented models is to generate realistic stands for simulation studies.

The PDF includes an abstract in Finnish.

  • Pukkala, ORCID ID:E-mail:
article id 5341, category Article
Hannu Hökkä, Jukka Laine. (1988). Suopuustojen rakenteen kehitys ojituksen jälkeen. Silva Fennica vol. 22 no. 1 article id 5341. https://doi.org/10.14214/sf.a15498
English title: Post-drainage development of structural characteristics in peatland forest stands.

The effect of drainage on structure of tree stands is analysed by comparing the average structural characteristics (e.g. diameter distribution) of stands in the data for different drainage age classes and selected site types. The material consists of ca. 4,400 relascope sample plots, which are part of a large drainage area inventory project. The uneven-aged structure of the virgin peatland forest is preserved for several decades after drainage. This is enhanced by the post-drainage increase of small-diameter trees, especially birch. The number of trees per hectare increased during a period of ca. 30 years and levelled off thereafter. The increase in the number of saw log stems is clearly related to the fertility of the site and its geographical location.

The PDF includes a summary in English.

  • Hökkä, ORCID ID:E-mail:
  • Laine, 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 7519, category Article
Jori Uusitalo. (1997). Pre-harvest measurement of pine stands for sawing production planning. Acta Forestalia Fennica no. 259 article id 7519. https://doi.org/10.14214/aff.7519

To enhance the utilization of the wood, the sawmills are forced to place more emphasis on planning to master the whole production chain from the forest to the end product. One significant obstacle to integrating the forest-sawmill-market production chain is the lack of appropriate information about forest stands. Since the wood procurement point of view in forest planning systems has been almost totally disregarded there has been a great need to develop an easy and efficient pre-harvest measurement method, allowing separate measurement of stands prior to harvesting. The main purpose of this study was to develop a measurement method for Scots pine (Pinus sylvestris L.) stands which forest managers could use in describing the properties of the standing trees for sawing production planning.

Study materials were collected from ten Scots pine stands located in North Häme and South Pohjanmaa, in Southern Finland. The data comprise test sawing data on 314 pine stems, diameter at breast height (dbh) and height measures of all trees and measures of the quality parameters of pine sawlog stems in all ten study stands as well as the locations of all trees in six stands. The study was divided into four sub-studies which deal with pine quality prediction, construction of diameter and dead branch height distributions, sampling designs and applying height and crown height models. The final proposal for the pre-harvest measurement method is a synthesis of the individual sub-studies.

Quality analysis resulted in choosing dbh, distance from stump height to the first dead branch, crown height and tree height as the most appropriate quality characteristics of Scots pine. Dbh and dead branch height are measured from each pine sample tree while height and crown height are derived from dbh measures by aid of mixed height and crown height models. Pine and spruce diameter distribution as well as dead branch height distribution are most effectively predicted by the kernel function. Roughly 25 sample trees seem to be appropriate in pure pine stands. In mixed stands the number of sample trees needs to be increased in proportion to the intensity of pines in order to attain the same level of accuracy.

  • Uusitalo, ORCID ID:E-mail:
article id 7676, category Article
Jussi Saramäki. (1992). A growth and yield prediction model of Pinus kesiya (Royle ex Gordon) in Zambia. Acta Forestalia Fennica no. 230 article id 7676. https://doi.org/10.14214/aff.7676

The study presents a growth and yield prediction model for a Pinus kesiya (Royle ex Gordon) stand by diameter classes. The material consists of temporary sample plots taken from a plantation inventory, of permanent sample plots established in commercial compartments and of an espacement trial. The mean basal area of the stand, variance and skewness of the diameter distribution are predicted. From these variables the parameters of the Weibull function are derived. Site class is assumed to be known or is calculated from measured information. Mortality is also predicted by estimating the number and mean size of dead trees. Thinnings are defined by the number of trees removed and by their relative size. If measured tree level data at the initial situation is available it can be utilized in the predictions, however, simulations can also be performed with stand level information. The minimum information needed for the prediction is planting density, site class as well as the times and removals of thinnings.

The calculations show that by decreasing the planting density of P. Kesiya from the present 1,330 stems/ha or by conducting early precommercial thinning both the relative and absolute amount of large sawlogs in the total production increase. An increase in the present planting density only slightly increases total yield. It is obvious that the presently recommended rotation of 25 years is too short for producing large sawlogs, especially on poor sites. This rotation period is suitable for small sawlog production while for pulpwood regimes shorter rotation periods can be used. If thinnings are done before the maximum current annual growth is reached stands will react well, but later on the ability to respond to thinnings decreases rapidly. Thinnings from below accelerates the production of large sawlogs more than thinning from above or systematic thinning. If all sawlog sizes are considered no great differences between thinning type exist. The study recommends different thinning regimes according to site class. Separate programs are recommended for the production of sawlogs and pulpwood.

The used thinning reaction model needs refinement and further studies with annual measured thinning trial material.

The PDF includes a summary in Finnish.

  • Saramäki, ORCID ID:E-mail:

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Committee on Publication Ethics A Trusted Community-Governed Archive