Modelling the spatial structure of forest stands by multivariate point processes with hierarchical interactions
Artikel i vetenskaplig tidskrift, 2009
A stochastic model is applied to describe
the spatial structure of a forest stand. We aim at quantifying the
strength of the competition process between the trees in terms of
interaction within and between different size classes of trees using
multivariate Gibbs point processes with hierarchical interactions
introduced by Högmander and Särkkä (1999). The new model
overcomes the main limitation of the traditional use of the Gibbs
models allowing to describe systems with non-symmetric interactions
between different objects. When analyzing interactions between
neighbouring trees it is natural to assume that the size of a tree
determines its hierarchical level: the largest trees are not
influenced by any other trees than the trees in the same size class,
while trees in the other size classes are influenced by the other
trees in the same class as well as by all larger trees. In this
paper, we describe a wide range of Gibbs models with both
hierarchical and non-hierarchical interactions as well as a
simulation algorithm and a parameter estimation procedure for the
hierarchical models. We apply the hierarchical interaction model to
the analysis of forest data consisting of locations and diameters of
tree stems.
forest ecosystem
hierarchical interaction function
Markov chain Monte Carlo simulation
pseudo-likelihood
inter-tree competition
marked Gibbs point processes
spatial point processes
spatial patterns