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

TL;DR
This study employs generalized additive mixed models to analyze German forest defoliation data from 1989 to 2015, revealing climate change impacts, regional drought effects, and optimal survey grid resolutions for monitoring trends and hotspots.
Contribution
First comprehensive spatio-temporal modeling of German forest defoliation data over 26 years using GAMMs, assessing grid resolutions and climate change effects.
Findings
Strong link between drought stress and defoliation across species
South-eastern Germany shows highest defoliation post-2003 drought
An 8x8 km grid improves trend detection over 16x16 km grid
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…
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