Does one model fit all? Patterns of beech mortality in natural forests of three European regions.

Large uncertainties characterize forest development under global climate change. Although recent studies have found widespread increased tree mortality, the patterns and processes associated with tree death remain poorly understood, thus restricting accurate mortality predictions. Yet, projections of future forest dynamics depend critically on robust mortality models, preferably based on empirical data rather than theoretical, not well-constrained assumptions. We developed parsimonious mortality models for individual beech (Fagus sylvatica L.) trees and evaluated their potential for incorporation in dynamic vegetation models (DVMs). We used inventory data from nearly 19,000 trees from unmanaged forests in Switzerland, Germany, and Ukraine, representing the largest dataset used to date for calibrating such models. Tree death was modelled as a function of size and growth, i.e., stem diameter (dbh) and relative basal area increment (relBAI), using generalized logistic regression accounting for unequal re-measurement intervals. To explain the spatial and temporal variability in mortality patterns, we considered a large set of environmental and stand characteristics. Validation with independent datasets was performed to assess model generality. Our results demonstrate strong variability in beech mortality that was independent of environmental or stand characteristics. Mortality patterns in Swiss and German strict forest reserves were dominated by competition processes as indicated by J-shaped mortality over tree size and growth. The Ukrainian primeval beech forest was additionally characterized by windthrow and a U-shaped size-mortality function. Unlike the mortality model based on Ukrainian data, the Swiss and German models achieved good discrimination and acceptable transferability when validated against each other. We thus recommend these two models to be incorporated and examined in DVMs. Their mortality predictions respond to climate change via tree growth, which is sufficient to capture the adverse effects of water availability and competition on the mortality probability of beech under current conditions.

Stand inventory data from the 10-ha forest research plot in Uholka: 15 yr of primeval beech forest development.

Forests dominated by European beech (Fagus sylvatica L.) are among both the most widespread in Europe and the most intensely exploited globally. One of the largest remnants of unmanaged beech forests in Europe is the Uholka-Shyrokyi Luh forest in Transcarpathia, Ukraine, covering 8,800 ha of primeval forest. In 2000, a permanent forest plot of 10 ha has been established in the Uholka massif. All living and dead trees with a diameter at breast height (DBH) ≥ 60 mm were identified to species, DBH measured, stems tagged and mapped. Since then, the plot has been remeasured in 2005, 2010, and 2015. In total, 4,820 individual trees were measured with 14,116 individual measurements throughout all four inventories. In spring 2018, an Airborne Laser Scan was carried out, covering the Uholka-Shyrokyi Luh forest. This data set allows us to derive a high-resolution digital elevation model (DEM) of the plot area. European beech covers a share of ≈ 95% of the basal area (BA) of all living stems. While BA was relatively stable throughout all inventories (≈ 38 m2 /ha), the number of stems increased considerably between 2010 and 2015 from 290 to 430 stems/ha. Additionally, the proportion of beech stems decreased from 95% in 2010 to 86% in 2015. The continuity of the share of beech on BA and the decrease in number of stems can be traced back to disturbance events, which led to an increase of more light demanding species in the recruitment but did not alter the distribution of BA as these small trees contribute very little to BA. The data set allows for important insights into the development and the spatial and temporal dynamics of primeval beech forests. It can be used to quantify the demographic processes growth, mortality, and recruitment, and to study inter- and intraspecific effects on demographic rates, stand structure, and species composition. No copyright or proprietary restrictions are associated with the use of this data set other than citation of this Data Paper.