Current issue: 54(2)

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Silva Fennica 1926-1997
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Acta Forestalia Fennica
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Articles by Marjut Ihalainen

Category: Research article

article id 513, category Research article
Marjut Ihalainen, Kauko Salo, Timo Pukkala. (2003). Empirical prediction models for Vaccinium myrtillus and V. vitis-idaea berry yields in North Karelia, Finland. Silva Fennica vol. 37 no. 1 article id 513. https://doi.org/10.14214/sf.513
Forest berries and the outdoor experiences related to berry collection are important goods and services provided by Finnish forests. Consequently, there is a need for models which facilitate the prediction of the impacts of alternative forest management options on berry yields. Very few such models are available. In particular, empirical models are lacking. Models used in forest management should express the effect of variables altered in forest management such as stand density and mean tree size. This study developed empirical models for bilberry and cowberry yields in North Karelia. The data consisted of 362 measurements of 40 m2 sample plots. The plots were located in clusters. The same plot was measured over 1 to 4 years. Besides berry yield some site and growing stock characteristics of each plot were measured. A random parameter model was used to express the berry yield as a function of site fertility, growing stock characteristics, and random parameters. The random part of the models accounted for the effect of plot, measurement year, and cluster. The fixed predictors of the model for bilberry were stand age and forest site type. Stand basal area, mean tree diameter and forest site type were used to predict cowberry yields. The most significant random parameter was the plot factor. The fixed model part explained only a few per cent of the variation in berry yields. The signs of regression coefficients were logical and the model predictions correlated rather well with the predictions of earlier models.
  • Ihalainen, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail: marjut.ihalainen@joensuu.fi (email)
  • Salo, The Finnish Forest Research Institute, Joensuu Research Centre, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
  • Pukkala, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
article id 588, category Research article
Marjut Ihalainen, Timo Pukkala. (2001). Modelling cowberry (Vaccinium vitis-idaea) and bilberry (Vaccinium myrtillus) yields from mineral soils and peatlands on the basis of visual field estimates. Silva Fennica vol. 35 no. 3 article id 588. https://doi.org/10.14214/sf.588
This study presents new models for predicting bilberry and cowberry yields from site and stand characteristics. These models enable one to evaluate the future states of forests in terms of berry yields. The modelling data consisted of visual field estimates of site and tree stand characteristics, as well as berry yields from 627 forest stands. Berry yields were estimated using a scale from 0 to 10. Using these data, models were prepared which predict the berry yield scores from those site and stand characteristics which are usually known in forest planning calculations. The model predictions correlated positively and often quite strongly with earlier models. The results were in line with previous studies on the effects of site and tree cover on berry production. According to the models, sites of medium and rather poor fertility produce the highest bilberry yields. Increasing tree height increases, and the basal area of spruce and proportion of deciduous trees decrease, bilberry yield. With mineral soils, cowberry yields are best on poor sites. A high proportion of pine improves cowberry yields. The yields are the highest in open areas and very young stands, on the one hand, and in sparsely populated stands of large and old trees, on the other hand. In pine swamps, the yields are best on rather poor sites. Increasing basal area of deciduous trees decreases cowberry yields.
  • Ihalainen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail: marjut.ihalainen@forest.joensuu.fi (email)
  • Pukkala, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail:

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