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Articles containing the keyword 'Johnson’s SB distribution'

Category: Research article

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
Abstract | View details | Full text in PDF | Author Info
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 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
Abstract | View details | Full text in PDF | Author Info
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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