From single trees to country-wide maps: Modeling mortality rates in Germany based on the Crown Condition Survey

e-journal

200211959

Most years in the period from 2018 to 2022 have been exceptionally dry in Central Europe. In Germany’s forests, this long-lasting drought has caused unprecedented tree mortality. Systematic ground-based surveys, such as the annual Crown Condition Survey, provide information on the vitality status of the different tree species and their mortality rates. However, models are needed to be able to map the spatial patterns of mortality for each tree species based on cause-effect relationships derived from field observations. In this study, logistic regression models were used to identify the most important drivers of mortality for the most important tree species in Germany. For this purpose, the dead and surviving trees from the Crown Condition Survey were combined with a large set of potential predictor variables from the domains of climate, topography, soil, land cover and deposition. After feature selection, the models were evaluated using the area under the curve (AUC) statistic.
Keywords: Tree mortality; Drought; Logistic regression; Mapping; Crown condition survey; Forest monitoring