Predicting tree death for Fagus sylvatica and Abies alba using permanent plot data
Authors: Wunder, Jan; Reineking, Björn; Matter, Jean-François; Bigler, Christof; Bugmann, Harald
Source: Journal of Vegetation Science, Volume 18, Number 4, August 2007 , pp. 525-534(10)
Publisher: Opulus Press
Abstract:Question: How well can mortality of deciduous trees (Fagus sylvatica) and conifers (Abies alba) be predicted using permanent plot data that describe growth patterns, tree species, tree size and site conditions?Location: Fagus forests in the montane belt of the Jura folds (Switzerland).Method: Permanent plot data were used to develop and validate logistic regression models predicting survival probabilities of individual trees. Backward model selection led to a reduced model containing the growth-related variable 'relative basal area increment' (growth-dependent mortality) and variables not directly reflecting growth such as species, size and site (growth-independent mortality).Results: The growth-mortality relationship was the same for both species (growth-dependent mortality). However, species, site and tree size also influenced mortality probabilities (growth-independent mortality). The predicted survival probabilities of the final model were well calibrated, and the model showed an excellent discriminatory power (area under the receiver operating characteristic curve = 0.896).Conclusion: Mortality probabilities of Fagus sylvatica and Abies alba can be predicted with high discriminatory power using a well calibrated logistic regression model. Extending this case study to a larger number of tree species and sites could provide species- and site-specific tree mortality models that allow for more realistic projections of forest succession.
Document Type: Research article
Publication date: 2007-08-01
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