Since 2002, ash dieback caused by the invasive fungus Hymenoscyphus fraxineus has been observed in Germany. The pathogen and its associated symptoms have fatal consequences for the vitality and survival of European ash (Fraxinus excelsior L.), an economically and ecologically important tree species. This study analyses the ash monitoring results of eleven intensive monitoring plots of the FraxForFuture research network distributed across Germany and focuses on within-stand differences of symptoms in dependence of small-scale site and tree properties. A cohort of 1365 ash trees was surveyed six times over three years, testing and applying a summer and a winter version of a nationally standardised ash dieback assessment key. The main disease symptoms (crown dieback and basal lesions) were more pronounced in areas with higher ash density, in edaphically moist areas (hydromorphic soils), on younger/smaller ash trees, and generally increased over time. However, the trend over time differed between single plots. In case of considering only the surviving part of the ash populations, crown condition even improved in 6/11 plots, indicating a selection process. Large basal lesions at the beginning of the observation period were a very good predictor for deadfall probability, especially on trees with lower stem diameter. Generally, ash dieback related symptoms at stem and crown were highly correlated. Silvicultural management practice in the past that actively pushed ash towards the moister end of its water demand spectrum has to be questioned in the light of ash dieback. Cost-intensive ash re-cultivation in the future—possibly with less dieback-susceptible progenies—should avoid pure ash stands and hydromorphic soil conditions.

Zum zweiten musste es vor der Zielsetzung späterer bundeslandübergreifender

Background Forest soils are an important reservoir of organic carbon (OC) and a potential source or sink for atmospheric CO2. Prediction of OC stock changes under ongoing climatic and management changes requires a spatial explicit base. Knowledge of the vertical distribution of OC stocks is very important, since varying soil layers may be affected differently by environmental change. Aim Three-dimensional regionalization of OC stocks of the forest floor (FFC) and 5 cm depth increments of the mineral soil (SOC) of Hesse, Germany. Methods Datasets of the second National Forest Soil Inventory (NFSI II) were used for parametrization of hierarchical generalized additive models (hGAM). Validation was performed by a 10 times repeated 10-fold cross-validation, and spatial model uncertainty was assessed. Results Depth-dependent validation indicated that model performance was best between 15 and 60 cm (amount of variance explained approximate to 0.5). All covariates showed plausible partial effects. FFC stocks were predicted to be highest under coniferous forest with a high influence of N deposition. Climate and potential cation exchange capacity affected SOC stocks markedly, whereas soil class and parent material were most important for the depth distribution. Overall, average predicted OC stocks were between 78.0 and 92.5 t ha(-)(1), amounting to 67.6 to 80.1 Mt for all forest soils of Hesse. Between 16% and 24% were stored in the forest floor. Sixty-eight percent to 69% of predicted SOC stocks were stored in the upper 30 cm. Model uncertainty was highest at locations with high elevation or ground water influence. Conclusions This work provides the first spatial explicit database for OC stocks of forest soils in Hesse at an intermediate scale. Stocks can be assessed flexibly for varying depth from the forest floor down to 100 cm. Uncertainty analysis informs about locations, where the model results have to be handled with care.

The management of forests needs well informed decisions by stakeholders to fulfil the goals of sustainability, stability, and productivity. Decisions are guided by forest site maps. The forest site map of Hesse, Germany, consists of six soil nutrient index (SNI) classes (poor, moderate-weak, moderate, moderate-good, rich, carbonatic). Three major challenges regarding the currently available site information exist: (i) the spatial proportion of "moderate" sites is exceptionally high (65% of mapped forest area) and while there is differentiation between parent materials, topography is neglected. (ii) As 80% of Hesse's forests were mapped, there is demand to fill the gaps without site information. (iii) The existing SNI does not take soil analysis into account, which is required to detect finer differences in morphologically similar soil profiles. Objectives were to regionalize soil chemical variables and derive a more differentiated SNI for Hesse's forest soils with complete forest coverage. Stocks of intermediately available Ca, Mg, and K, base saturation, effective cation exchange capacity, and C/N ratio of 380 profiles from the National Forest Soil Inventory were used to characterize the SNI. Regionalization of soil chemical variables was successfully performed (R-2 values from 0.54 to 0.79, root mean square deviation 5 to 17%) using generalized additive models. SNI classes were inferred by fuzzy logic for dealing with soil chemical variables. The results were highly sensitive towards parent material and topography. The modelled SNI map provides a much more differentiated and complete map for Hesse, Germany, which mirror actual expectations across landscape units. The approach is transparent and inter-subjectively reproducible. The new map will be used to guide the management and reforestation of sites, which were damaged by biotic or abiotic threats due to recent climatic extreme events. (C) 2020 Published by Elsevier B.V.

Forests face considerable pressure from climate change, while demand of provided ecosystem services is high. Managing and planting forests need well informed decisions by practitioners, to fulfill the goal of sustainability. In Germany, informed decisions are derived from forest site evaluation maps, integrating biogeoecolocigal conditions (climate, soil water, nutrients). Here, we focus on mapping of nutrients in the federal state Hesse, Germany. For Hesse, a forest site map exists, which indicates a soil nutrient regime (SNR) index (classes very poor, poor, medium, rich, very rich). Site mapping was done in the field by experts, considering ground vegetation and soil morphology. Guidelines exist for choosing management options (i.e. suitable species composition, harvest restrictions, etc.), but if spatial information is not accurate, management decisions will be misguided. Three major challenges regarding the currently available site information exist: (1) the spatial proportion of “medium” sites is exceptionally high (65% of mapped forest area) and while there is differentiation between parent materials, topography is neglected. (2) Whereas 80% of Hesse’s forests were mapped, there is need to fill the gaps. (3) The existing SNR index does not take analytical measurements of soil nutrients into account. Objectives were (1) to refine and expand the existing map of SNR by (2) including soil chemical properties from the second National Forest Soil Inventory (NFSI), (3) which have to be regionalised beforehand. Stocks of Ca, Mg and K, base saturation, effective cation exchange capacity (90cm depth and organic layer), and C/N ratio (organic layer or 0-5 cm) of 380 profiles from the NFSI were chosen to characterise the SNR. Regionalisation was performed with generalised additive models (GAM) by using environmental relationships of the target variables with variables of climate, vegetation, parent material and soil properties (soil map 1:50,000). Ten-fold cross validation revealed R² values from 0.54 to 0.79, with low relative root mean square deviation (5 to 17%) and slopes not significantly different from 1. From the six successfully modelled target variables, we inferred a single SNR for each soil map polygon. This was challenging, because variables provided contrasting information regarding the SNR. We addressed this by using the Soil Inference Engine (SIE), which bases on fuzzy logic. Each variable received an optimality value for each SNR class. Using an expert-driven weighting system a SNR membership was inferred, whereas highest membership defined the SNR class. The result was highly sensitive towards parent material and topography. For instance, acidic parent material had lower SNR classes compared to base rich parent material. Within a given parent material, ridges where judged less nutrient rich compared to planes and topographic positions, where material is accumulated. The results provide a much more differentiated and complete map for SNR, which mirror actual expectations of nutrient distribution across Hesse’s landscape units. The approach is transparent and inter-subjectively reproducible. The new map will be used to guide reforestation activities in Hesse after the severe forest disturbances by recent climatic extremes (e.g. drought, storms) and the approach can be transferred to other regions.

Increased deposition of reactive nitrogen (N) since pre-industrial times has dramatically altered the conditions for forest growth and decomposition of organic material in Germany. The second National Forest Soil Inventory (NFSI II, 2006–2008) shows the status of N accumulation in forest soils. A median N stock of 6.3 t ha–1 has been found in the soil profile down to a depth of maximum 90 cm, whereof 50% is stored in the upper 30 cm of the mineral soil. The high regional variability of N stocks is explained by forest type, parent material, soil acidity, annual mean temperature, and adjacent agricultural land use. C/N ratios of the top soil were on average higher (24.0) than those during NFSI I (22.4, 1989–1992), which may be seen as a first effect of slowly decreasing deposition rates. Observations on limed plots suggest that acidification inhibits soil biological activity and thereby reduces N-storage in the mineral soil. The median annual N balance for German forest soils between NFSI I and II varies between +2.9 and +7 kg ha–1, depending on the harvest regime assumed. Negative N balances occurred mainly in mountain ranges like the Black Forest or the Rhenish Slate Mountains. N stocks in the upper 30 cm of the soil generally increased, while there are indications for losses of N from deeper soil layers, potentially linked to progressing acidification in these layers. Irrespective of existing measurement uncertainties, the findings indicate the vulnerability of forest N stocks under changing conditions. Further reductions of N deposition should be strived for to reduce the risk of nitrate leaching from forest soils.

Forest soils play an important role in the active carbon (C) cycle of terrestrial ecosystems as they store one third of the global organic carbon. Therefore, the sequestration of atmospheric carbon in soils as stable organic matter is discussed as a potential contribution to mitigate atmospheric CO2 concentrations. The carbon dynamic in forest ecosystems is expected to be a result of environmental as well as human-induced factors. Germany’s forest soils contained in the organic layer and the mineral soil down to 90 cm on average 117.1 ± 1.7 Mg C ha–1 which has been increased significantly since the NFSI I by 0.75 ± 0.09 Mg C ha–1 year–1 resulting in a total increase of 11.3 Mg C ha–1. Structural equation modelling was performed to analyze direct and indirect factors affecting organic carbon stocks and organic carbon stock changes. The pathway analyses revealed a variation of carbon stocks in the organic layer that was especially controlled by tree species. Organic layers under broadleaf trees stored less carbon than under coniferous trees, while tree species effects on carbon stocks of mineral soil were comparatively less pronounced. Soil carbon stocks were furthermore affected by site conditions. An effective selection of tree species combined with specific site conditions may therefore enhance carbon sequestration potential of soils. We found specific effects of nitrogen deposition and forest liming on carbon stock changes. The additional nitrogen has the potential to increase sequestering carbon by an increase in productivity and accumulation of soil organic matter through increased litter production, while liming may both stimulate and inhibit soil respiration depending on various environmental conditions. Altogether, the results showed that further research is needed to identify the most important factors affecting turnover of soil organic matter in respect to the impact of anthropogenic effects as forest stand management, liming, or atmospheric nitrogen deposition especially on dynamics of microbial communities as well as on recalcitrance and stabilization of soil organic matter.

Der Eintrag von Stickstoff- und Schwefelverbindungen in Waldokosysteme seit der Industrialisierung hat die naturlicherweise auserst langsam ablaufende Bodenversauerung deutlich beschleunigt. Eine standortsangepasste Kalkung ermoglicht es, der fortschreitenden Bodenversauerung entgegenzuwirken. Dabei kann die Bodenzustandserhebung als ein standortsdifferenzierendes Instrument zur Steuerung und Erfolgskontrolle der Kalkung dienen.