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Small mountain glaciers have short mass balance response times to climate change and are consequently very important for short‐term contributions to sea level. However, a distinct research and knowledge gap exists between (1) wider regional studies that produce overview patterns and trends in glacier changes, and (2) in situ local scale studies that emphasise spatial heterogeneity and complexity in glacier responses to climate. This study of a small glacier in central Austria presents a spatiotemporally detailed analysis of changes in glacier geometry and changes in glaciological behaviour. It integrates geomorphological surveys, historical maps, aerial photographs, airborne LiDAR data, ground‐based differential global positioning surveys and Ground Penetrating Radar surveys to produce three‐dimensional glacier geometry at 13 time increments spanning from 1850 to 2013. Glacier length, area and volume parameters all generally showed reductions with time. The glacier equilibrium line altitude increased by 90 m between 1850 and 2008. Calculations of the mean bed shear stress rapidly approaching less than 100 kPA, of the volume–area ratio fast approaching 1.458, and comparison of the geometric reconstructions with a 1D theoretical model could together be interpreted to suggest evolution of the glacier geometry towards steady state. If the present linear trend in declining ice volume continues, then the Ödenwinkelkees will disappear by the year 2040, but we conceptualise that non‐linear effects of bed overdeepenings on ice dynamics, of supraglacial debris cover on the surface energy balance, and of local topographically driven controls, namely wind‐redistributed snow deposition, avalanching and solar shading, will become proportionally more important factors in the glacier net balance.

Abstract. This paper focuses in particular on clastic sediment fluxes on talus slopes. Using orthophoto interpretation, field measurements and GIS-techniques, a quantification of areas and volumes of active sediment transfer related to specific landform units was achieved for different spatial scales. Closer investigation of a single landform complex, more specifically a talus sheet/ debris cone-complex, brought to light that remobilisation can overbalance sediment input by a factor of 57. This could be an indication of what may be expected in the whole catchment. At present. approximately 9% of the research area (3 km2), comprising talus slopes and valley bottom, is characterised by sediment transfer mainly through gravilational and fluvial processes. A comparison of the vast volumes (117.174 m3) derived from these active areas of recent sediment transfer and the volume of the entire valley fill (0.07 km3) indicates, however, that the largest part must be related to remobilised sediments and cannot be considered as sediment input from the adjacent rockwalls. This conclusion is also supported by direct measurements of sediment input.

Fungal leaf diseases cause economically important damage to crop plants. Protective treatments help producers to secure good quality crops. In contrast, curative treatments based on visually detectable symptoms are often riskier and less effective because diseased crop plants may develop disease symptoms too late for curative treatments. Therefore, early disease detection prior symptom development would allow an earlier, and therefore more effective, curative management of fungal diseases. Using a five-lens multispectral imager, spectral reflectance of green, blue, red, near infrared (NIR, 840 nm), and rededge (RE, 720 nm) was recorded in time-course experiments of detached tomato leaves inoculated with the fungus Botrytis cinerea and mock infection solution. Linear regression models demonstrate NIR and RE as the two most informative spectral data sets to differentiate pathogen- and mock-inoculated leaf regions of interest (ROI). Under controlled laboratory conditions, bands collecting NIR and RE irradiance showed a lower reflectance intensity of infected tomato leaf tissue when compared with mock-inoculated leaves. Blue and red channels collected higher intensity values in pathogen- than in mock-inoculated ROIs. The reflectance intensities of the green band were not distinguishable between pathogen- and mock infected ROIs. Predictions of linear regressions indicated that gray mold leaf infections could be identified at the earliest at 9 h post infection (hpi) in the most informative bands NIR and RE. Re-analysis of the imagery taken with NIR and RE band allowed to classify infected tissue.