The impacts of climate change pose one of the main challenges for agriculture in Central Europe. In particular, an increase of extreme and compound extreme climate events is expected to strongly impact economic revenues and the provision of ecosystem services by agroecosystems. A highly relevant, still open question is how grassland farming systems can cope best with these climate risks to adapt to climate change. A prominently discussed economic instrument to relieve income risks is the formal insurance, but natural and social insurances are newly under discussion as well. Natural insurances include specific grassland management practises such as maintaining species-rich grasslands. Social insurances, in our terminology, comprise all forms of societal support for farmers’ climate risk management. This includes in particular arrangements of community-supported agriculture that reduce income risks for farmers, or payments for ecosystem services if their design takes risk into account. Formal, natural and social insurances may be substitutes or complements, and affect farmer behaviour in different ways. Thus, policy support for any of the three forms of insurance will have effects on the others, which need to be understood. InsuranceGrass takes an innovative interdisciplinary view and assesses formal, natural and social insurances: on how to cope best with impacts of climate extremes on grasslands, integrating social and natural sciences perspectives and feedbacks between them. Based on this holistic analysis, InsuranceGrass will provide recommendations for policy and insurance design to ensure effective risk-coping of farmers and to enhance sustainable grassland farming, considering economic, environmental and social aspects. Impacts of extreme and compound extreme events on the provision of ecosystem services (e.g. magnitude and quality of yield, climate regulation via carbon sequestration, plant diversity) by permanent grasslands in Germany and Switzerland are quantified based on long-term observations and field experiments. Cutting-edge model-based approaches will be based on behavioural theories and empirically calibrated. With the help of social-ecological modelling, InsuranceGrass explicitly incorporates feedbacks between farmers’ and households’ decision, grassland management options, and ecosystem service provision in a dynamic manner. The contributions of different insurance types are developed, discussed and evaluated jointly with different groups of stakeholders (i.e., farmers, insurance companies, public administration). A scientifically sound and holistic assessment of the role of formal, natural, and social insurances for the sustainability of grassland farming under extreme events requires both disciplinary excellence and seamless interdisciplinary collaboration. InsuranceGrass brings together four groups from Zürich and Leipzig, with unique disciplinary expertise and a track record of successful collaboration.
In dem Vorhaben soll auf technische Möglichkeiten zur Effizienzverbesserung bzw. Energieeinsparung eingegangen werden (bspw. Nutzung der Windkraft) und eruiert werden, in welcher Höhe Energieeinsparungen realistisch zu erwarten sind, für welche Schiffstypen diese jeweils in Frage kommen, wie weit der Energiebedarf des internationalen Seeverkehrs sich damit senken ließe und ob bzw. unter welchen Bedingungen diese Maßnahmen wirtschaftlich sind oder einer Förderung bedürfen. In die Betrachtung sollen bestehende und zukünftige Maßnahmen auf EU- und internationaler Ebene einfließen. In einem zweiten Arbeitspaket sind die Treibhausgasminderungsmöglichkeiten durch Carbon Capture on board (OCC) zu beleuchten. Es soll (beschränkt auf das System Schiff) eine detaillierte Betrachtung des Energieaufwands zur Abscheidung, Speicherung und Transport des CO2 sowie den dadurch verursachten zusätzlichen CO2eq-Emissionen erfolgen. Darüber hinaus sollen zudem auch die Auswirkungen auf die schiffsspezifische Energieeffizienz betrachtet werden und für welche Schiffstypen dies wirtschaftlich darstellbar ist. Es sind Beratungsleistungen für die Verhandlungen unter der Klimarahmenkonvention zu dem Agendapunkt der 'bunker fuels' und ein Ad-hoc-Beratungsbudget für den See- und Luftverkehr vorzusehen.
Hedgerows play an important role in maintaining biodiversity, carbon sequestration, soil stability and the ecological integrity of agricultural landscapes. In this dataset, hedgerows are mapped for the whole of Bavaria. Orthophotos with a spatial resolution of 20 cm, taken in the period from 2019 to 2021, were used in a deep learning approach. Hedgerow polygons of the Bavarian in-situ biotope mapping from 5 districts (Miltenberg, Hassberge, Dillingen a.d. Donau, Freyung-Grafenau, Weilheim-Schongau) as well as other manually digitized polygons were used for training and testing as input into a DeepLabV3 Convolutional Neural Network (CNN). The CNN has a Resnet50 backbone and was optimized with the Dice loss as a cost function. The generated hedgerow probability tiles were post-processed by merging and averaging the overlapping tile boundaries, shape simplification and filtering. For more details, see Huber Garcia et al. (2025). The dataset has been created within the project FPCUP (https://www.copernicus-user-uptake.eu/) in close cooperation with Bayerisches Landesamt für Umwelt (LfU).