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arXiv · 1805.09216

Spatio-temporal modelling of forest monitoring data: Modelling German tree defoliation data collected between 1989 and 2015 for trend estimation and survey grid examination using GAMMs

Nadine Eickenscheidt·Nicole H. Augustin·Nicole Wellbrock
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Abstract

Spatio-temporal modelling of tree defoliation data of German forest condition survey is presented. In the present study generalized additive mixed models were used to estimate the spatio-temporal trends of defoliation of the main tree species from 1989 to 2015 and to examine the suitability of different monitoring grid resolutions. Although data has been collected since 1989, this is the first time the spatio-temporal modelling for entire Germany has been carried out. Besides the space-time component, stand age showed a significant effect on defoliation. The mean age and the species-specific relation between defoliation and age determined the general level of defoliation whereas fluctuations of defoliation were primarily related to weather conditions. The study indicates a strong association between drought stress and defoliation of all four main tree species. Besides direct effects of weather conditions, indirect effects seem to play a further role. Defoliation of the comparably drought-tolerant species pine and oak was primarily affected by insect infestations following drought whereas considerable time for regeneration was required by beech following drought stress and recurring substantial fructification. South-eastern Germany has emerged as the region with the highest defoliation since the drought year 2003. This region was characterized by the strongest water deficits in 2003 compared to the long-term reference period. The present study gives evidence that the focus has moved from air pollution to climate change. Furthermore, the spatio-temporal model was used to carry out a simulation study to compare different survey grid resolutions. This grid examination indicated that an 8 x 8 km grid instead of the standard 16 x 16 km grid is necessary for spatio-temporal trend estimation and for detecting hot-spots in defoliation in space and time, especially regarding oak.

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Nadine Eickenscheidt, Nicole H. Augustin, Nicole Wellbrock. 2018-05-23. Spatio-temporal modelling of forest monitoring data: Modelling German tree defoliation data collected between 1989 and 2015 for trend estimation and survey grid examination using GAMMs. https://doi.org/10.3832/ifor2932-012

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