Future browsing damage in seedling stands according to projected forest resources and moose population density

Abstract

An important modifier of forests and forestry practices is browsing by cervids. As high populations of moose (Alces alces L.) cause extensive forest damage in the Fennoscandian boreal forests, models should be able to predict the susceptibility of projected forest structures to browse damage. We augmented the European Forestry Dynamics Model (EFDM) for the area of seedling stands damaged by moose. The augmented model was tested in projecting both forest resources and moose damage for 18 million hectares of forest land in Finland, based on input data from the National Forest Inventory (NFI). Modeling the area of seedling stands damaged as a function of moose population density, forest characteristics, and region-specific interactions of these variables was found to work realistically for 30 years, predicting that the area of seedling stands damaged by moose would increase by up to a third from the last NFI observation. Our work lays the groundwork for modeling consequential, large-scale ecological and socio-economic effects of moose browsing.

Keywords

• forest management planning; forest development simulation; forest projection; markov chain; scenario analysis; transition matrix model