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Articles containing the keyword 'zero-inflated negative binomial distribution'

Category : Research article

article id 9918, category Research article
Ari Nikula, Vesa Nivala, Juho Matala, Kari Heliövaara. (2019). Modelling the effect of habitat composition and roads on the occurrence and number of moose damage at multiple scales. Silva Fennica vol. 53 no. 1 article id 9918. https://doi.org/10.14214/sf.9918
Keywords: forestry; Alces alces; damage probability; forest damage; forest plantation; habitat selection; habitat modelling; zero-inflated negative binomial distribution
Highlights: The occurrence and number of moose damage were modelled with a zero-inflated count model; An admixture of mature forests within plantations increased the number of damage; Vicinity of inhabited areas and roads reduced damage; Plantations in landscapes with a large amount of pine-dominated thinning forests had less damage in Lapland; Damage risk assessment should include characteristics specific to each region.
Abstract | Full text in HTML | Full text in PDF | Author Info

We modelled the effect of habitat composition and roads on the number and occurrence of moose (Alces alces L.) damage in Ostrobothnia and Lapland using a zero-inflated count model. Models were developed for 1 km2, 25 km2 and 100 km2 landscapes consisting of equilateral rectangular grid cells. Count models predict the number of damage, i.e. the number of plantations and zero models the probability of a landscape being without damage for a given habitat composition. The number of moose damage in neighboring grid cells was a significant predictor in all models. The proportion of mature forest was the most frequent significant variable, and an increasing admixture of mature forests among plantations increased the number and occurrence of damage. The amount of all types of plantations was the second most common significant variable predicting increasing damage along with increasing amount of plantations. An increase in thinning forests as an admixture also increased damage in 1 km2 landscapes in both areas, whereas an increase in pine-dominated thinning forests in Lapland reduced the number of damage in 25 km2 landscapes. An increasing amount of inhabited areas in Ostrobothnia and the length of connecting roads in Lapland reduced the number of damage in 1 and 25 km2 landscapes. Differences in model variables between areas suggest that models of moose damage risk should be adjusted according to characteristics that are specific to the study area.

  • Nikula, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, Ounasjoentie 6, FI-96200 Rovaniemi, Finland E-mail: ari.nikula@luke.fi (email)
  • Nivala, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, Ounasjoentie 6, FI-96200 Rovaniemi, Finland E-mail: vesa.nivala@luke.fi
  • Matala, Natural Resources Institute Finland (Luke), Natural resources, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: juho.matala@luke.fi
  • Heliövaara, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: kari.heliovaara@helsinki.fi

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