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Tropospheric ozone (O3) is known to have various detrimental effects on plants, such as visible leaf injury, reduced growth and premature senescence. Flux models offer the determination of the harmful ozone dose entering the plant through the stomata. This dose can then be related to phytotoxic effects mentioned above to obtain dose-response relationships, which are a helpful tool for the formulation of abatement strategies of ozone precursors. rnOzone flux models are dependant on the correct estimation of stomatal conductance (gs). Based on measurements of gs, an ozone flux model for two white clover clones (Trifolium repens L. cv Regal; NC-S (ozone-sensitive) and NC-R (ozone-resistant)) differing in their sensitivity to ozone was developed with the help of artificial neural networks (ANNs). White clover is an important species of various European grassland communities. The clover plants were exposed to ambient air at three sites in the Trier region (West Germany) during five consecutive growing seasons (1997 to 2001). The response parameters visible leaf injury and biomass ratio of NC-S/NC-R clone were regularly assessed. gs-measurements of both clones functioned as output of the ANN-based gs model, while corresponding climate parameters (i.e. temperature, vapour pressure deficit (VPD) and photosynthetic active radiation (PAR)) and various ozone concentration indices were inputs. The development of the model was documented in detail and various model evaluation techniques (e.g. sensitivity analysis) were applied. The resulting gs model was used as a basis for ozone flux calculations, which were related to above mentioned response parameters. rnThe results showed that the ANNs were capable of revealing and learning the complex relationship between gs and key meteorological parameters and ozone concentration indices. The dose-response relationships between ozone fluxes and visible leaf injury were reasonably strong, while those between ozone fluxes and NC-S/NC-R biomass ratio were fairly weak. The results were discussed in detail with respect to the suitability of the chosen experimental methods and model type.
In addition to flood disasters on major rivers, damage caused by the flooding of smaller and medium-sized tributaries is also of considerable significance. To ensure that flood protection measures are effective, engineering flood prevention measures on the rivers must be supported by integrated catchment management. This includes decentralised water retention measures implemented in the sectors of forestry, agriculture and in residential areas. Within this scope new instruments have to be elaborated and introduced, such as GIS-based systems and systems for the evaluation of economic consequences and eco-efficiency of flood damage precaution measures associated with land-use. These are extremely significant for improving information management, the prevention of advice to the general public and for the acceptance of flood precaution measures. The conference intends to promote scientific exchange between specialists working on all areas concerning integrated catchment management. This includes the methodology for identification of catchment types prone to flooding hazards, the control and validation of land-use concepts for decentralised water retention as well as its combination and upscaling procedures up to mesoscale catchments. As catchment management is not only the concern of natural scientists the strategies for enhancing catchment management and the development of decision-support tools will also be important topics of the conference. ***Addenda *1. The articles from page 136 to 161 belong to session 5 *2. Article page 107: Ancient irrigation strategies: land use and hazard mitigation in Ma-´rib, Yemen (New list of authors: Ueli Brunner (a) , Michael Schütz (b), Dana Pietsch (c), Peter Kühn (c), Thomas Scholten (c), Iris Gerlach (d))