The Wadden Sea off the coast of the southern North Sea is the largest coherent area of tidal flats worldwide. As a highly productive ecosystem it is of global importance, e.g. as nursery for fish and as a feeding and resting area for 10 – 12 million migratory birds following the East Atlantic Flyway. The outstanding ecological significance of this region corresponds to a high level of protection by EU directives and national law and by inscription as UNESCO World Heritage Site, all of which requires regular monitoring and assessment. Apart from the ecological aspects, the Wadden Sea is also of great importance for coastal protection. To survey the extensive, often inaccessible tidal area, remote sensing is essential and while mainly airborne techniques have been carried out for decades, now high-resolution satellite-borne sensors open up new possibilities relevant for monitoring and long-term ecological research. Especially satellite synthetic aperture radar (SAR) sensors offer a high availability of acquisitions as they operate largely independently of daylight and weather. The aim of the studies presented here was to explore the use of data from the TerraSAR-X satellite to record geomorphological structures and habitats for Wadden Sea Monitoring. More than 100 TerraSAR-X acquisitions from 2009 to 2016 were analyzed to distinguish various and variable surface types continuously influenced by tidal dynamics in the main study area, the tidal flats near the island of Norderney. Visual image interpretation supported by extensive in-situ verification proved to be a suitable and unsophisticated approach which is unspecific enough to identify mussel beds, fields of shell-detritus, gully structures, mud fields, and intertidal bedforms in the upper flats of the East Frisian Islands. The method proved to be robust against changes in geometry of acquisition and environmental influences. Several time series of TerraSAR-X data enabled to follow inter-annual and seasonal dynamics as well as event effects (Adolph et al. 2018). The high-frequency TerraSAR-X data revealed novel evidence of an intertidal bedform shift in an easterly direction during the study period. To this aim, an unsupervised ISODATA classification of textural parameters was developed to vectorize and compare the bedforms positions in a GIS (Adolph et al. 2017a). The same intertidal bedform area was chosen as test-site for comparison of different remote sensing methods, namely airborne lidar, satellite-based radar (TerraSAR-X) and electro-optical sensors (RapidEye) (Adolph et al. 2017b). High-resolution SAR data offer a relevant component for Wadden Sea Monitoring and Research, as they provide reliable, regular data with a high repetition rate. In particular, habitats with noticeable surface roughness, specific structures and textures are well reflected. Geomorphic Structures and their dynamics can be observed indirectly via detection of residual water trapped within. A comprehensive concept for Wadden Sea Monitoring however, requires automatized classifications and an integrative, multi-sensor approach (SAR, LIDAR, multi-spectral data, drones) in which different and complementary information, coverage and resolutions (spatial and temporal) contribute to an overall picture. The studies were carried out as part of the joint research project “Scientific monitoring concepts for the German Bight” (WIMO), jointly funded by the Ministry of Environment, Energy and Climate Protection (NMU) and the Ministry of Science and Culture (NMWK) of the Federal State of Lower Saxony. The findings have been published in Geo-Marine Letters 37/2 (2017) and in Remote Sensing 10/7 (2018).

Livestock grazing is the most important type of land-use in arid and semi-arid regions. In these regions, uncertain and highly variable climate conditions cause scarce and spatio-temporally variable resource availability. The major challenge to livestock grazing is the efficient utilisation of these resources without running the risk of degradation. Therefore, well adapted grazing strategies that consider both local environmental characteristics and the farmers' individual needs and perceptions are crucial for sustaining human livelihoods. Particularly, rotational grazing is presumed to render adaptation to spatio-temporal heterogeneities possible. A systematic investigation, however, that analyses the interrelations between the major components of rotational grazing systems on appropriate spatial and temporal scales was missing so far. This doctoral thesis investigates different management strategies for sustainable livestock grazing in semi-arid rangelands. Using an integrated modelling approach, it enters into the question: how to adapt grazing systems to spatio-temporal heterogeneous rangeland conditions, variable and changing climate conditions, and different individual needs and goals of livestock farmers? In order to address these issues, the taken approach tackles both methodical challenges and applied concerns. In the first part of this study, a generic modelling framework is developed that incorporates important components of grazing systems on appropriate spatial and temporal scales. To parameterise the model, a pattern-oriented approach is developed that uses qualitative patterns to derive a broad range of plausible parameter sets supporting a general model analysis. In the second part, a variety of management strategies is explored under different climatic, ecological, and economic conditions. The research focuses in particular on combined effects between and relative importance of different management components. The question how the results of different management strategies depend on the type of vegetation is investigated. Furthermore, the performance of rotational grazing strategies is analysed under different economic requirements and rainfall conditions. The study also identifies management strategies that are suitable to adapt a grazing system to spatio-temporally variable rangeland conditions. Overall, this thesis contributes to a general understanding of basic principles for adaptation to spatio-temporal heterogeneities as well as the interplay of different management components. The results allow an evaluation of management strategies for specific situations and the identification of strategies that are robust to a broad range of situations including different aspects of global change.

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