Jari Vauhkonen, Juho Matala, Ari Nikula. (2023). Future browsing damage in seedling stands according to projected forest resources and moose population density. Silva Fennica vol. 57 no. 2 article id 23012. https://doi.org/10.14214/sf.23012

Keywords: forest management planning; forest development simulation; forest projection; Markov chain; scenario analysis; transition matrix model

Highlights: Projections of forest resources and seedling stands damaged by moose browsing; Damaged seedling stand area modelled by moose population and forest characteristics; Moose damage predicted by the age class structure of simulated future forests.

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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.

Vauhkonen, University of Eastern Finland, School of Forest Sciences, Yliopistokatu 7, FI-80101 Joensuu, Finland; University of Helsinki, Department of Forest Sciences, Latokartanonkaari 7, FI-00014 Helsingin yliopisto, Finland E-mail: jari.vauhkonen@uef.fi
Matala, Natural Resources Institute Finland (Luke), Natural resources, Yliopistokatu 6 B, FI-80100 Joensuu, Finland E-mail: juho.matala@luke.fi
Nikula, Natural Resources Institute Finland (Luke), Natural resources, Ounasjoentie 6, FI-96200 Rovaniemi, Finland https://orcid.org/0000-0001-8372-8440 E-mail: ari.nikula@luke.fi

article id 562, category Research article

Tero Kokkila, Annikki Mäkelä, Eero Nikinmaa. (2002). A method for generating stand structures using Gibbs marked point process. Silva Fennica vol. 36 no. 1 article id 562. https://doi.org/10.14214/sf.562

Keywords: spatial distribution; stand simulation; Gibbs point process; Markov chain Monte Carlo

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Stand growth modelling based on single tree responses to their surroundings requires a description of the spatial structure of a stand. While such detailed information is rarely available from field measurements, a method to create it from more general stand variables is needed. A marked Gibbs point potential theory combined with Markov chain Monte Carlo (MCMC) random process was used to create a spatial configuration for any given number of trees. The trees are considered as charges rejecting each other and building ‘potential energy’. As an analogue of the potential energy in physical systems, the potential of a stand is defined in terms of size-dependent tree-to-tree interactions that can be thought of as related to resource depletion and competition. The idea that bigger trees induce larger potentials brings 3-dimensional effects into the system. Any feasible spatial structure is a state of the system, and the related potential can be calculated. The probability that a certain state occurs is assumed to be a decreasing function of its potential. Because more regular structures have lower potentials, by adjusting the steepness of the probability distribution the spatial structure can be allowed to have a lot of randomness (naturally regenerated stands) or forced to be very regular (planted stands). The MCMC algorithm is a numerical method of finding stand configurations that correspond to the expected level of the potential, given the size distribution of trees and the shape of the probability density function. The method also allows us to take into account spatial variation in the terrain. Some spots can be defined to have lower basic potential than others (ditch, planting furrow, etc.) in order to create areas of higher than average stocking density. A preliminary test of the method was conducted on two measured stands. The results suggest that the method could provide an efficient and flexible means of mimicking variable stand structures.

Kokkila, University of Helsinki, Department of Forest Ecology, P.O. Box 27, FIN-00014 Helsingin yliopisto, Finland E-mail: tero.kokkila@helsinki.fi
Mäkelä, University of Helsinki, Department of Forest Ecology, P.O. Box 27, FIN-00014 Helsingin yliopisto, Finland E-mail: am@nn.fi
Nikinmaa, University of Helsinki, Department of Forest Ecology, P.O. Box 27, FIN-00014 Helsingin yliopisto, Finland E-mail: en@nn.fi

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