From 2016 to 2019, 128 organic and conventional spring and winter pea fields in Germany were surveyed to determine the effects of cropping history and pedo-climatic conditions on pea root health, the diversity of Fusarium and Didymella communities and their collective effect on pea yield. Roots generally appeared healthy or showed minor disease symptoms despite the frequent occurrence of 4 Didymella and 14 Fusarium species. Soil pH interacted with the occurrence of the Fusarium oxysporum species complex (FOSC) and F. tricinctum that correlated with reduced or increased soil pH values, respectively. While legumes in the cropping history or reduced time between legumes correlated with occurrence of D. pinodella and to a lesser degree with the members of the F. solani species complex (FSSC), the reverse was true at least in organic spring peas for F. redolens. Only in conventional systems increased root infections with F. redolens and the FSSC were linked to root rot incidence whereas yields negatively correlated with the FOSC and positively with F. tricinctum isolation frequencies. Overall, this study shows that pea root rot pathobiome is rather stable and that the damage caused is mostly due to the interaction with environmental conditions.

Winter storms cause severe damage in German forests. Different modelling approaches have already been used to try and map endangered areas to minimize the risk of wind damage by stand adaption. Prevalent models for Germany include empirical-statistical and hybrid-mechanistic models, such as ForestGALES (FG). As of yet, FG is not extensively used in Germany as its parametrization requires extensive experimental efforts to derive regionally sensitive species-specific parameters. Here, we implement a statistical calibration approach for German forest conditions with observed damage from single tree data, soil types, topography (topex) and gust speed data. We use simulated annealing to generate new species-specific values for the tree species, Norway spruce, European beech, and Douglas fir from within the range of all coniferous (deciduous) species for Norway spruce and Douglas fir (European beech) and an additional 10 % buffer around the default species-specific values for each species. We compare two optimization approaches: First, we aim to maximize the Matthew's correlation coefficient (MCC), which is calculated from the confusion matrix, applying a fixed classification threshold of 0.5. In comparison to the optimization at a fixed threshold, we optimized the species-specific parameters by maximizing the area-under-curve (AUC) value directly generated from the receiver-operator characteristic (ROC) analysis. We compare our statistical parametrizations for the considered species to those currently implemented in FG and validate the resulting damage probabilities based on confusion matrices and related performance measures. We created separate parametrizations for a single-tree and stand-wide analysis of storm damage risk, which we validated with gust speed data for Germany. Our results show, that for the single-tree method, MCC improved for all species: By 0.26 (0.22) for the calibration (validation) subset for Douglas fir, by 0.22 (0.18) for Norway spruce and by 0.08 (0.05) for European beech. The optimization for the stand-method shows an increase in MCC as well, with results not being considered due to low numbers of observation data. We show that for German forests, FG's predictive capability can be improved by statistical optimization when no tree-pulling data is available, which could be valuable for creating further regionalizations of FG.

Among climate-change related effects, drought, heat, and waterlogging are the most important adversely affecting the production of potatoes in Europe. As climate change progresses, agricultural practices must adapt to maintain potato yields. This study is based on a European-wide survey. It presents potato growers' perception of climate change, its impact, and possible adaptation strategies, focusing on the results from Germany, Switzerland, and Austria. Potato growers strongly agreed that climate change had affected their potato production in the last ten years, as indicated by 98% of German and more than 90% of Swiss and Austrian respondents. Drought caused the most severe impact, and to varying extents damage was caused by heat and the occurrence of pests and pathogens. The most preferred adaptation measure was the planting of adapted varieties. In line with the comparably low access to at least partial irrigation that Austrian potato growers reported, Austria appeared to be the country most affected by drought. Other more pronounced challenges were late spring frost, flash floods, and soil erosion. The study highlights and discusses specific differences between the countries, as well as between conventional and organic potato production based on the Austrian responses. The results underline that to successfully develop effective climate change mitigation strategies, country-specific and local challenges and needs should be considered.