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Silva Fennica 1926-1997
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Acta Forestalia Fennica
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Articles by Jouni Siipilehto

Category : Article

article id 5545, category Article
Jouni Siipilehto, Olavi Lyly. (1995). Weed control trials with fibre mulch, glyphosate and terbuthylazine in Scots pine plantations. Silva Fennica vol. 29 no. 1 article id 5545. https://doi.org/10.14214/sf.a9196
Keywords: Pinus sylvestris; herbicides; glyphosate; terbuthylazine; weed control; seedling stands; mulches
Abstract | View details | Full text in PDF | Author Info

The following treatments were compared in three Scots pine (Pinus sylvestris L.) reforestation areas on a scarified moist mineral-soil site in southern Finland, planted with 1+1 bareroot stock in spring 1987: (a) no weed control treatment; (b) mulching with a fibre slurry produced by mixing wastepaper with water and applied 1 cm deep to an area of 60 cm in diameter around the seedling soon after planting; (c) glyphosate (at 2 kg ha-1) sprayed on a 1 m2 spot around the seedling in early August 1987; (d) terbuthylazine (at 10 kg ha-1) applied as (c). Monitoring of the trials over a 4-year period between 1987–90 showed that none of the treatments reduced surface vegetation to an extent that would have benefited pine. The percentage cover development of the vegetation, dominated by Agrostis capillaris, Calamagrostis arundinaceae, Deschampsia flexuosa, Festuca ovina, Epilobioum angustifolium and Pteridium aquillinum, followed much the same pattern in all treatments, with (c) slightly favouring forbs. Survival of pine at the end of the study period was about 90%, with non-significant differences between treatments. Mulching and terbuthylazine treatment slightly reduced seedling height growth in the second year. Growth was better in glyphosate treatment than in terbuthylazine treatment in the lowest (<30%) and the highest (>60%) pre-treatment weed cover classes, and in the latter also better than in untreated control. Mulching gave variable results; at its best it provided also good control of weeds for several years, without, however, improving the initial development of pine in these trials.

  • Siipilehto, E-mail: js@mm.unknown (email)
  • Lyly, E-mail: ol@mm.unknown

Category : Research article

article id 10612, category Research article
Daesung Lee, Jouni Siipilehto, Jari Hynynen. (2021). Models for diameter distribution and tree height in hybrid aspen plantations in southern Finland. Silva Fennica vol. 55 no. 5 article id 10612. https://doi.org/10.14214/sf.10612
Keywords: Näslund’s height curve; Weibull distribution; parameter recovery; Populus tremula × P. tremuloides; clonal plantation; nonlinear mixed-effects model
Highlights: Parameter recovery method for the Weibull function fitted diameter distributions well by means of sum and mean forest stand characteristics for hybrid aspen plantations; Arithmetic and weighted mean diameters performed better for the recovery method than the corresponding median diameters; Two alternative Näslund’s height curve models with stand characteristics and tree dbh predictors provided unbiased tree height predictions.
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Hybrid aspen (Populus tremula L. × P. tremuloides Michx.) is known with outstanding growth rate and some favourable wood characteristics, but models for stand management have not yet been prepared in northern Europe. This study introduces methods and models to predict tree dimensions, diameter at breast height (dbh) and tree height for a hybrid aspen plantation using data from repeatedly measured permanent sample plots established in clonal plantations in southern Finland. Dbh distributions using parameter recovery method for the Weibull function was used with Näslund’s height curve to model tree heights. According to the goodness-of-fit statistics of Kolmogorov-Smirnov and the Error Index, the arithmetic mean diameter (D) and basal area-weighted mean diameter (DG) provided more stable parameter recovery for the Weibull distribution than the median diameter (DM) and basal area-weighted median diameter (DGM), while DG showed the best overall fit. Thus, Näslund’s height curve was modelled using DG with Lorey’s height (HG), age, basal area (BA), and tree dbh (Model 1). Also, Model 2 was tested using all predictors of Model 1 with the number of trees per ha (TPH). All predictors were shown to be significant in both Models, showing slightly different behaviour. Model 1 was sensitive to the mean characteristics, DG and HG, while Model 2 was sensitive to stand density, including both BA and TPH as predictors. Model 1 was considered more reasonable to apply based on our results. Consequently, the parameter recovery method using DG and Näslund’s models were applicable for predicting tree diameter and height.

  • Lee, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, FI-00790 Helsinki, Finland ORCID https://orcid.org/0000-0003-1586-9385 E-mail: daesung.lee@luke.fi (email)
  • Siipilehto, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: jouni.siipilehto@luke.fi
  • Hynynen, Natural Resources Institute Finland (Luke), Natural resources, Vipusenkuja 5, FI-57200 Savonlinna, Finland ORCID https://orcid.org/0000-0002-9132-8612 E-mail: jari.hynynen@luke.fi
article id 10496, category Research article
Jouni Siipilehto, Harri Mäkinen, Kjell Andreassen, Mikko Peltoniemi. (2021). Models for integrating and identifying the effect of senescence on individual tree survival probability for Norway spruce. Silva Fennica vol. 55 no. 2 article id 10496. https://doi.org/10.14214/sf.10496
Keywords: forest dynamics; model comparison; between-tree competition; mortality model
Highlights: The effect of senescence was integrated into an individual tree survival model; The best model showed good fit for managed, unmanaged and old-growth stands; The probability for a large tree to survive decreased with increasing stand age; The best performed model included an interaction term between stem diameter and stand age and also stand age as a separate independent variable.
Abstract | Full text in HTML | Full text in PDF | Author Info

Ageing and competition reduce trees’ ability to capture resources, which predisposes them to death. In this study, the effect of senescence on the survival probability of Norway spruce (Picea abies (L.) Karst.) was analysed by fitting alternative survival probability models. Different model formulations were compared in the dataset, which comprised managed and unmanaged plots in long-term forest experiments in Finland and Norway, as well as old-growth stands in Finland. Stand total age ranged from 19 to 290 years. Two models were formulated without an age variable, such that the negative coefficient for the squared stem diameter described a decreasing survival probability for the largest trees. One of the models included stand age as a separate independent variable, and three models included an interaction term between stem diameter and stand age. According to the model including stand age and its interaction with stem diameter, the survival probability curves could intersect each other in stands with a similar structure but a different mean age. Models that did not include stand age underestimated the survival rate of the largest trees in the managed stands and overestimated their survival rate in the old-growth stands. Models that included stand age produced more plausible predictions, especially for the largest trees. The results supported the hypothesis that the stand age and senescence of trees decreases the survival probability of trees, and that the ageing effect improves survival probability models for Norway spruce.

  • Siipilehto, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, P.O. Box 2, FI-00790 Helsinki, Finland E-mail: jouni.siipilehto@luke.fi (email)
  • Mäkinen, Natural Resources Institute Finland (Luke), Production systems, Latokartanonkaari 9, P.O. Box 2, FI-00790 Helsinki, Finland ORCID https://orcid.org/0000-0002-1820-6264 E-mail: harri.makinen@luke.fi
  • Andreassen, Norwegian Institute of Bioeconomy Research (NIBIO), NO-1431 Ås, Norway E-mail: kjellandreassen@gmail.com
  • Peltoniemi, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Latokartanonkaari 9, P.O. Box 2, FI-00790 Helsinki, Finland ORCID https://orcid.org/0000-0003-2028-6969 E-mail: mikko.peltoniemi@luke.fi
article id 10414, category Research article
Jouni Siipilehto, Micky Allen, Urban Nilsson, Andreas Brunner, Saija Huuskonen, Soili Haikarainen, Narayanan Subramanian, Clara Antón-Fernández, Emma Holmström, Kjell Andreassen, Jari Hynynen. (2020). Stand-level mortality models for Nordic boreal forests. Silva Fennica vol. 54 no. 5 article id 10414. https://doi.org/10.14214/sf.10414
Keywords: Norway spruce; Scots pine; simulation; broadleaved species; logistic function; period length; plot size
Highlights: Models were developed for predicting stand-level mortality from a large representative NFI data set; The logistic function was used for modelling the probability of no mortality and the proportion of basal area in surviving trees; The models take into account the variation in prediction period length and in plot size; The models showed good fit with respect to stand density, developmental stage and species structure, and showed satisfying fit in the independent data set of unmanaged spruce stands.
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New mortality models were developed for the purpose of improving long-term growth and yield simulations in Finland, Norway, and Sweden and were based on permanent national forest inventory plots from Sweden and Norway. Mortality was modelled in two steps. The first model predicts the probability of survival, while the second model predicts the proportion of basal area in surviving trees for plots where mortality has occurred. In both models, the logistic function was used. The models incorporate the variation in prediction period length and in plot size. Validation of both models indicated unbiased mortality rates with respect to various stand characteristics such as stand density, average tree diameter, stand age, and the proportion of different tree species, Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.), and broadleaves. When testing against an independent dataset of unmanaged spruce-dominated stands in Finland, the models provided unbiased prediction with respect to stand age.

  • Siipilehto, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland E-mail: jouni.siipilehto@luke.fi (email)
  • Allen, Norwegian Institute of Bioeconomy Research (NIBIO), Division of Forest and Forest Products, NO-1431 Ås, Norway; Larson and McGowin Inc., Mobile, AL 36607, USA ORCID https://orcid.org/0000-0002-7824-2849 E-mail: micky.allen@nibio.no
  • Nilsson, Swedish University of Agricultural Sciences (SLU), Southern Swedish Forest Research Centre, SE-23053 Alnarp, Sweden ORCID https://orcid.org/0000-0002-7624-4031 E-mail: urban.nilsson@slu.se
  • Brunner, Norwegian University of Life Sciences (NMBU), Faculty of Environmental Sciences and Natural Resource Management, NO-1432 Ås, Norway ORCID https://orcid.org/0000-0003-1668-9714 E-mail: andreas.brunner@nmbu.no
  • Huuskonen, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland ORCID https://orcid.org/0000-0001-8630-3982 E-mail: saija.huuskonen@luke.fi
  • Haikarainen, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland ORCID https://orcid.org/0000-0001-8703-3689 E-mail: soili.haikarainen@luke.fi
  • Subramanian, Swedish University of Agricultural Sciences (SLU), Southern Swedish Forest Research Centre, SE-23053 Alnarp, Sweden ORCID https://orcid.org/0000-0003-2777-3241 E-mail: narayanan.subramanian@slu.se
  • Antón-Fernández, Norwegian Institute of Bioeconomy Research (NIBIO), Division of Forest and Forest Products, NO-1431 Ås, Norway ORCID https://orcid.org/0000-0001-5545-3320 E-mail: clara.anton.fernandez@nibio.no
  • Holmström, Swedish University of Agricultural Sciences (SLU), Southern Swedish Forest Research Centre, SE-23053 Alnarp, Sweden ORCID https://orcid.org/0000-0003-2025-1942 E-mail: emma.holmstrom@slu.se
  • Andreassen, Norwegian Institute of Bioeconomy Research (NIBIO), Division of Forest and Forest Products, NO-1431 Ås, Norway ORCID https://orcid.org/0000-0003-4272-3744 E-mail: kjellandreassen@gmail.com
  • Hynynen, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland E-mail: jari.hynynen@luke.fi
article id 10062, category Research article
Jouni Siipilehto, Miika Rajala. (2019). Model for diameter distribution from assortments volumes: theoretical formulation and a case application with a sample of timber trade data for clear-cut sections. Silva Fennica vol. 53 no. 1 article id 10062. https://doi.org/10.14214/sf.10062
Keywords: bucking; optimization; simplex method; truncated Weibull function
Highlights: The Weibull distribution was solved successfully from assortment volumes using optimization; The solved distribution provided accurate assortment volume when the input variables were correct; Goodness-of-fit tests indicate the compatibility between the solved distribution and the cut trees, according to harvester data; Timber trade contracts showed overestimated average merchantable tree sizes, which resulted in an underestimation of the number of cut trees; The reason for underestimation seemed to be in the decreasing distributions.
Abstract | Full text in HTML | Full text in PDF | Author Info

This study examined a theoretical model for stand structures from the volumes of pulpwood and saw logs of clear-cut stands. The average stem size was used to estimate the number of cut trees. The distribution was solved using nonlinear derivative-free optimization. The truncated 2-parameter Weibull distribution was used to describe the stand structure of the commercial stems. This method was first tested with harvester data collected from seven clear-cut stands in southern Finland. Validation included reliability in the stand characteristics and goodness-of-fit of the species-specific distributions. The distributions provided unbiased estimates for the saw log volume, while the bias in the estimated pulpwood volume was 2%. The standard stand characteristics from the Weibull distributions corresponded notably well with the harvester data. A Kolmogorov-Smirnov (KS) test rejected two distributions out of 21 cases, when the accurate input variables were available for the theoretical model. The results of the study suggest that the presented method is a relevant option for predicting the stand structure. In practice, the reliability of the presented method was dependent on the quality of the information available from the stand prior to cutting. With a timber trade data set, the solution for the distribution for a clear-cut section was found. The goodness-of-fit was dependent on the accuracy of the visually assessed timber trade variables. Especially the average stem size proved difficult to assess due to high number of understorey pulpwood stems. Due to overestimated average stem sizes, the solved number of harvested trees was underestimated. Less than 50% of the distributions predicted for clear-cut sections passed the KS test.

  • Siipilehto, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, P.O. Box 2, FI-00790 Helsinki, Finland E-mail: jouni.siipilehto@luke.fi (email)
  • Rajala, Metsä Group, Revontulenpuisto 2, P.O. Box 10, 02020 METSÄ, FI-02100 Espoo, Finland E-mail: miika.rajala@metsagroup.com
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
Keywords: forest inventory; diameter distribution; Weibull; area-based approach; parameter recovery; k-NN estimation
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.
Abstract | Full text in HTML | Full text in PDF | Author Info

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 E-mail: jouni.siipilehto@luke.fi (email)
  • Lindeman,  Natural Research Institute Finland, Green Technology, Kaironiementie 15, 39700 Parkano 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 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 E-mail: xiaowei.yu@maanmittauslaitos.fi
  • Uusitalo,  Natural Research Institute Finland, Green Technology, Kaironiementie 15, 39700 Parkano 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
Keywords: linear prediction; diameter distribution; Weibull; stand characteristics; parameter recovery
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.
Abstract | Full text in HTML | Full text in PDF | Author Info
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 E-mail: jouni.siipilehto@metla.fi (email)
  • Mehtätalo, University of Eastern Finland, School of Computing, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: lauri.mehtatalo@uef.fi
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
Keywords: Pinus sylvestris; linear prediction; diameter distribution; Weibull; Johnson’s SB; height curve; stand characteristics
Abstract | View details | Full text in PDF | Author Info
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 E-mail: jouni.siipilehto@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
Keywords: Pinus sylvestris; drained peatland; dbh distribution; Johnson’s SB function; regression estimation methods
Abstract | View details | Full text in PDF | Author Info
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 E-mail: jouni.siipilehto@metla.fi (email)
  • Sarkkola, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: ss@nn.fi
  • Mehtätalo, University of Joensuu, Faculty of Forestry, P.O. Box 111, 80101 Joensuu, Finland E-mail: lm@nn.fi
article id 334, category Research article
Jouni Siipilehto. (2006). Linear prediction application for modelling the relationships between a large number of stand characteristics of Norway spruce stands. Silva Fennica vol. 40 no. 3 article id 334. https://doi.org/10.14214/sf.334
Keywords: Picea abies; stand characteristics; prediction; calibration estimation; interdependence
Abstract | View details | Full text in PDF | Author Info
The aim was to produce models for a large number of stand characteristics of Norway spruce dominated stands. A total of 227 national forest inventory based permanent stand plots, dominated by Norway spruce (Picea abies), were used in modelling eight stand variables as a function of the stand mean biological age and site characteristics. The basic models were able to characterize the average development of the modelled stand variables, but resulted in a relatively high RMSE. Basal area (G) and stem number (N) were the most inaccurate, having a RMSE of 34–41%, while that of mean diameter and height characteristics varied between 16–20%. The expectations and error variances of the basic models were calibrated with known stand variables using linear prediction theory. The best linear unbiased predictor (BLUP) with a single stand variable used for calibration proved to be ineffective for unknown G and N, but relatively effective for the unknown mean characteristics. However, calibration with one sum and one mean characteristic proved to be effective, and additional calibration variables enhanced the precision only marginally. The BLUP method provided a flexible approach when characterizing the relationships between a large number of stand variables, thus enabling multiple use of these models because they were not fixed to a specific inventory system.
  • Siipilehto, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: jouni.siipilehto@metla.fi (email)
article id 331, category Research article
Jouni Siipilehto. (2006). Height distributions of Scots pine sapling stands affected by retained tree and edge stand competition. Silva Fennica vol. 40 no. 3 article id 331. https://doi.org/10.14214/sf.331
Keywords: Pinus sylvestris; retention; height distribution; Weibull function; percentile prediction; edge effect
Abstract | View details | Full text in PDF | Author Info
The paper focused on the height structure of Scots pine saplings affected by (1) retained solitary pine trees or (2) a pine-dominated edge stand. The study material in (1) and (2) consisted of ten separate regeneration areas in southern Finland. In (1) 2-m radius study plots were located at 1, 3, 6 and 10 m distances from 10 systematically selected, solitary retained trees in each stand. In (2) the study plots were systematically located within 20 m from the edge stand. Competition of the individual trees was modelled using ecological field theory. The 24th and 93rd sample percentiles were used for estimating the height distribution using the two-parameter Weibull function. The models incorporated the effect of varying advanced tree competition on the predicted percentiles. Competition free dominant height was used as a driving variable for the developmental phase. Competition resulted in retarded height development within a radius of about 6 m from the retained tree, while it extended up to roughly half of the dominant height of the edge stand. The height distribution without external competition was relatively symmetrical, but increasing competition resulted in a more peaked and skewed distribution. Slight differences were found between northern sunny and southern shaded stand edges, while the least retarded height occurred at the north-western edge receiving morning sunlight. Kolmogorov-Smirnov goodness-of-fit tests showed acceptable and equal fit for both data sets; 2% and 8% of the distributions did not pass the test at the alpha 0.1 level when the Weibull distribution was estimated with the observed or predicted percentiles, respectively.
  • Siipilehto, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: jouni.siipilehto@metla.fi (email)
article id 410, category Research article
Jouni Siipilehto, Juha Siitonen. (2004). Degree of previous cutting in explaining the differences in diameter distributions between mature managed and natural Norway spruce forests. Silva Fennica vol. 38 no. 4 article id 410. https://doi.org/10.14214/sf.410
Keywords: Picea abies; stand structure; naturalness; Johnson’s SB distribution
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The degree of naturalness was assessed in 37 mature (stand age 80 198 yrs) Norway spruce dominated stands located in southern Finland by measuring the number (0 610 ha–1) and basal area (0 33 m2 ha–1) of cut stumps. The Johnson’s SB distribution was fitted for living spruce trees to describe the dbh-frequency and basal area-dbh distributions. Regression models were constructed for predicting the parameters of the SB distribution using traditional stand parameters (median diameter, basal area, stem number) and the cut stump variables (number, basal area). Stump variables improved the models and enabled to explain the differences in diameter distributions between stands with varying intensity of past cutting. Model for basal area-dbh distribution was more accurate than dbh-frequency model in terms of regression statistics, but less accurate in terms of generated stand variables. The number and basal area of cut stumps seem to be useful and simple measures of stand naturalness which have potential uses in stand modelling and biodiversity-oriented forestry planning.
  • Siipilehto, Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: jouni.siipilehto@metla.fi (email)
  • Siitonen, Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: juha.siitonen@metla.fi
article id 577, category Research article
Jouni Siipilehto. (2001). Effect of weed control with fibre mulches and herbicides on the initial development of spruce, birch and aspen seedlings on abandoned farmland. Silva Fennica vol. 35 no. 4 article id 577. https://doi.org/10.14214/sf.577
Keywords: Populus tremula; Betula pendula; Picea abies; glyphosate; dichlobenile; herbicide; mulching; terbuthylazine; weed control
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Post-planting weed control methods on abandoned farmland were studied in three field trials in southern Finland using a completely randomized design with four treatments and 30 to 40 replications. Mulches of 60 x 60 cm [sheet mulch – strips of plane waste and plastic fibre, newspaper – waste paper slurry, wood chips, pure wood fibre slurry], herbicides [i.e. glyphosate or terbuthylazine alone or mixed and dichlobenile applied to 1 m2 spots] and hoeing treatments were compared to an untreated control plot. The study material consisted of two-year-old containerized aspen (Populus tremula L.), silver birch (Betula pendula (L.) Roth) and Norway spruce (Picea abies (L.) Karst.) seedlings planted in spring 1996. The ground vegetation was dominated by Elymys repens, Deschampsia cespitosa, Cirsium arvense and Epilobium angustifolium. Monitoring of the trials over a 3-year period showed a moderate effect of weed control, which varied according to the method used and by the crop species. Significant growth responses were found with herbicide in spruce, wood chips in spruce and birch and with sheet mulch in aspen seedlings. Sheet mulch also encouraged vole nesting thus increasing damages. Generally, slurry mulches proved to be insufficiently durable. Mulching had a clear insulating effect, which may increase the risk of winter drought.
  • Siipilehto, Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FIN-01301 Vantaa, Finland E-mail: jouni.siipilehto@metla.fi (email)
article id 617, category Research article
Jouni Siipilehto. (2000). A comparison of two parameter prediction methods for stand structure in Finland. Silva Fennica vol. 34 no. 4 article id 617. https://doi.org/10.14214/sf.617
Keywords: Pinus sylvestris; Picea abies; parameter prediction; dbh and height distribution; Johnson’s SBB distribution; Näslund’s height curve
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The objective of this paper was to predict a model for describing stand structure of tree heights (h) and diameters at breast height (dbh). The research material consisted of data collected from 64 stands of Norway spruce (Picea abies Karst.) and 91 stands of Scots pine (Pinus sylvestris L.) located in southern Finland. Both stand types contained birch (Betula pendula Roth and B. pubescent Ehrh.) admixtures. The traditional univariate approach (Model I) of using the dbh distribution (Johnson’s SB) together with a height curve (Näslund’s function) was compared against the bivariate approaches, Johnson’s SBB distribution (Model II) and Model Ie. In Model Ie within-dbh-class h-variation was included by transforming a normally distributed homogenous error of linearized Näslund’s function to concern real heights. Basal-area-weighted distributions were estimated using the maximum likelihood (ML) method. Species-specific prediction models were derived using linear regression analysis. The models were compared with Kolmogorov-Smirnov tests for marginal distributions, accuracy of stand variables and the dbh-h relationship of individual trees. The differences in the stand characteristics between the models were marginal. Model I gave a slightly better fit for spruce, but Model II was better for pine stands. The univariate Model I resulted in clearly too narrow marginal h-distribution for pine. It is recommended applying of a constrained ML method for reasonable dbh-h relationship instead of using a pure ML method when fitting the SBB model.
  • Siipilehto, Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FIN-01301 Vantaa, Finland E-mail: jouni.siipilehto@metla.fi (email)
article id 650, category Research article
Jouni Siipilehto. (1999). Improving the accuracy of predicted basal-area diameter distribution in advanced stands by determining stem number. Silva Fennica vol. 33 no. 4 article id 650. https://doi.org/10.14214/sf.650
Keywords: dbh distribution; parameter prediction; Johnson’s SB distribution; Weibull distribution
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The objective of this paper was to study to what extent the accuracy of predicted basal-area diameter distributions (DDG) could be improved by means of stem number observations in advanced (H > 10 m) stands. In the Finnish forest management planning (FMP) inventory practice, stem number is determined only in young stands; in older stands stand basal area is used. The study material consisted of sixty stands of Norway spruce (Picea abies Karst.) and ninety-one stands of Scots pine (Pinus sylvestris L.) with birch (Betula pendula Roth and B. pubescens Ehrh.) admixtures in southern and eastern Finland. For test data, 167–292 independent, National Forest Inventory-based, permanent sample plots were used. DDGs were estimated with the maximum likelihood method. Species-specific models for predicting the distribution parameters were derived using regression analysis. The two-parameter Weibull distribution was compared to the three-parameter Johnson’s SB distributions in predicting DDGs. The models were based on either predictors that are consistent with current FMP (model G), or assuming an additional stem number observation (model G+N). The predicted distributions were compared in terms of the derived stand variables: stem number, total and timber volumes. The results were similar in modelling and test data sets. Methods, based on the SB distribution obtained with model (G+N), proved to give the most accurate description of the stand structure. Differences were marginal in stand total volumes. However, the error variation in stem number was 20% to 80% lower than when applying model (G). SB and Weibull distributions gave very much the same results if model (G) was applied.
  • Siipilehto, Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FIN-01301 Vantaa, Finland E-mail: jouni.siipilehto@metla.fi (email)

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