Institut für Geoökologie
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The development of rural areas concerning food security, sustainability and social-economic stability is key issue to the globalized community. Regarding the current state of climatic change, especially semi-arid regions in uenced by monsoon or El Niño are prone to extreme weather events. Droughts, ooding, erosion, degradation of soils and water quality and deserti cation are some of the common impacts. State of the art in hydrologic environmental modeling is generally operating under a reductionist paradigm (Sivapalan 2005). Even an enormous quantity of process-oriented models exists, we fail in due reproduction of complexly interacting processes in their effective scale in the space-time-continuum, as they are described through deterministic small-scale process theories (e.g. Beven 2002). Yet large amounts of parameters - with partly doubtful physical expression - and input data are needed. In contradiction to that most soft information about patterns and organizing principles cannot be employed (Seibert and McDonnell 2002). For an analysis of possible strategies on the one hand towards integrated hydrologic modeling as decision support and on the other hand for sustainable land use development the 512 km2 large catchment of the Mod river in Jhabua, Madhya Pradesh, India has been chosen. It is characterized by a setting of common problems of peripheral rural semi-arid human-eco-systems with intensive agriculture, deforestation, droughts and general hardship for the people. Scarce data and missing gauges are adding to the requirements of data acquisition and process description. The study at hand presents a methodical framework to combine eld scale data analysis and remote sensing for the setup of a database focusing plausibility over strict data accuracy. The catena-based hydrologic model WASA (Güntner 2002) employes this database. It is expanded by a routine for crop development simulation after the de Wit approach (e.g. in Bouman et al. 1996). For its application as decision support system an agentbased land use algorithm is developed which decides on base of site speci cations and certain constraints (like maximum pro t or best local adaptation) about the cropping. The new model is employed to analyze (some) land use strategies. Not anticipated and a priori de ned scenarios will account for the realization of the model but the interactions within the system. This study points out possible approaches to enhance the situation in the catchment. It also approaches central questions of ways towards due integrated hydrological modeling on catchment scale for ungauged conditions and to overcome current paradigms.
To characterise the habitat preferences of ring ouzel (Turdus torquatus) and blackbird (T. merula) in Switzerland, we adopt species distribution modelling and predict the species’ spatial distribution. We model on two different scales to analyse in how far downscaling leads to a different set of predictors to describe the realised habitat best. While the models on macroscale (grid of one square kilometre) cover the entire country, we select a set of smaller plots for modelling on territory scale. Whereas ring ouzels occur in altitudes above 1’000 m a.s.l. only, blackbirds occur from the lowlands up to the timber line. The altitudinal range overlap of the two species is up to 400 m. Despite both species coexist on macroscale, a direct niche overlap on territory scale is rare. Small-scale differences in vegetation cover and structure seem to play a dominant role for habitat selection. On macroscale however, we observe a high dependency on climatic variables mainly representing the altitudinal range and the related forest structure preferred by the two species. Applying the models for climate change scenarios, we predict a decline of suitable habitat for the ring ouzel with a simultaneous median altitudinal shift of +440 m until 2070. In contrast, the blackbird is predicted to benefit from higher temperatures and expand its range to higher elevations.