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Articles containing the keyword 'multilevel logistic regression'

Category : Research article

article id 593, category Research article
Anneli Jalkanen. (2001). The probability of moose damage at the stand level in southern Finland. Silva Fennica vol. 35 no. 2 article id 593. https://doi.org/10.14214/sf.593
Keywords: National Forest Inventory; Alces alces; multilevel logistic regression; risk management
Abstract | View details | Full text in PDF | Author Info
The probability of moose damage was studied in sapling stands and young thinning stands in southern Finland. Data from the eighth National Forest Inventory in 1986–92 were used for modelling. The frequency of damage was highest at the height of two to five meters and at the age of ten to twenty years (at the time of measurement). Moose preferred aspen stands the most and least preferred Norway spruce stands. Scots pine and silver birch were also susceptible to damage. Logistic regression models were developed for predicting the probability that moose damage is the most important damaging agent in a forest stand. The best predictive variables were the age and dominant species of the stand. Variables describing the site were significant as cluster averages, possibly characterizing the area as a food source (fertility and organic soil), as well as the lack of shelter (wall stand). When sample plot, cluster and municipality levels were compared, it was found that most of the unexplained variance was at the cluster level. To improve the model, more information should be obtained from that level. The regression coefficients for aspen as supplementary species, and for pine as dominant species, had significant variance from cluster to cluster (area to area). It was also shown that the occurrence of aspen is closely connected to the occurrence of moose damage in pine sapling stands.
  • Jalkanen, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland E-mail: anneli.jalkanen@metla.fi (email)

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