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Spatio-Temporal Modelling of Swedish Scots Pine Stands
Chalmers University of Technology, Göteborg.
Centre of Biostochatics, SLU.
Forest Resource Management, SLU.
2011 (English)Report (Other academic)
Abstract [en]

Considering measurements of locations and radii at breast height made at three different time points of the individual trees in ten Swedish Scots pine plots, we employ the so called growth-interaction (GI) process for the spatio-temporal modelling of the plots. The GI-process places trees at random locations in the study region and assigns radii (sizes) to the trees, which interact and grow with time. It has been used to model Scots pine plots in previous studies, and to improve the fit we suggest some modifications of the model: A different location assignment strategy and a different function for the open-growth (growth in absence of competition). We believe also that the space-time data contain too small trees to reflect the open-growth properly, which primarily affectsthe carrying capacity parameter. We evaluate the open-growth froma separate set of data which consists of size and age measurements ofolder and larger single Scots pines. This data set better represents the open-growth of Scots pines than the space-time data sets. A linear relationship is found between the estimated site indexes of the plots and the sizes, and this relationship is exploited in the estimation of the carrying capacity. For each of the ten space-time data sets (plots) we estimate the remaining parameters of the GI-process and finally, by means of some Monte Carlo tests, we test the goodness-of-fit of simulated predictions from the fitted model.

Place, publisher, year, edition, pages
2011. , 31 p.
, Research Report, Centre of Biostochastics, SLU, ISSN 1651-8543 ; 2011:3
Keyword [en]
Basal area, Carrying capacity, Goodness-of-fit, Growth- Interaction process, Immigration-death process, L-function, Mark-correlation function, Open-growth, Richards growth function, Scots pines, Site productivity index, Spatio-temporal point process.
National Category
Probability Theory and Statistics Forest Science
URN: urn:nbn:se:umu:diva-65439OAI: diva2:604087
Available from: 2013-02-07 Created: 2013-02-07 Last updated: 2013-02-07

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Yu, Jun
Probability Theory and StatisticsForest Science

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