The exact cause of population dieback in nature is often challenging to identify retrospectively. Plant research in northern regions has in recent decades been largely focussed on the opposite trend, namely increasing populations and higher productivity. However, a recent unexpected decline in remotely-sensed estimates of terrestrial Arctic primary productivity suggests that warmer northern lands do not necessarily result in higher productivity. As large-scale plant dieback may become more frequent at high northern latitudes with increasing frequency of extreme events, understanding the drivers of plant dieback is especially urgent. Here, we report on recent extensive damage to dominant, short, perennial heath and tundra plant populations in boreal and Arctic Norway, and assess the potential drivers of this damage. In the High-Arctic archipelago of Svalbard, we recorded that 8-50% of Cassiope tetragona and Dryas octopetala shoots were dead, and that the ratios of dead shoots increased from 2014 to 2015. In boreal Norway, 38-63% of Calluna vulgaris shoots were dead, while Vaccinium myrtillus had damage to 91% of shoots in forested sites, but was healthy in non-forested sites. Analyses of numerous sources of environmental information clearly point towards a winter climate-related reason for damage to three of these four species. In Svalbard, the winters of 2011/12 and 2014/15 were documented to be unusually severe, i.e. insulation from ambient temperature fluctuation by snow was largely absent, and ground-ice enforced additional stress. In boreal Norway, the 2013/14 winter had a long period with very little snow combined with extremely low precipitation rates, something which resulted in frost drought of uncovered Calluna plants. However, extensive outbreaks of a leaf-defoliating geometrid moth were identified as the driver of Vaccinium mortality. These results suggest that weather and biotic extreme events potentially have strong impacts on the vegetation state of northern lands.

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Remote sensing is a suitable candidate for monitoring rapid changes in Polar regions, offering high-resolution spectral, spatial and radiometric data. This paper focuses on the spectral properties of dominant plant species acquired during the first week of August 2015. Twenty-eight plots were selected, which could easily be identified in the field as well as on RapidEye satellite imagery. Spectral measurements of individual species were acquired, and heavy metal contamination stress factors were measured contemporaneously. As a result, a unique spectral library of dominant plant species, heavy metal concentrations and damage ratios were achieved with an indication that species-specific changes due to environmental conditions can best be differentiated in the 1401-2400 nm spectral region. Two key arctic tundra species, Cassiope tetragona and Dryas octopetala, exhibited significant differences in this spectral region that were linked to a changing health status. Relationships between field and satellite measurements were comparable, e.g., the Red Edge Normalized Difference Vegetation Index (RENDVI) showed a strong and significant relationship (R 2 = 0.82; p = 0.036) for the species Dryas octopetala. Cadmium and Lead were below detection levels while manganese, copper and zinc acquired near Longyearbyen were at concentrations comparable to other places in Svalbard. There were high levels of nickel near Longyearbyen (0.014 mg/g), while it was low (0.004 mg/g) elsewhere.

Heavy metals and radioactive compounds are potentially hazardous substances for plants, animals and humans in the Arctic. A good knowledge of the spatial variation of these substances in soil and primary producers, and their sources, is therefore essential. In the samples of lichen Thamnolia vermicularis, Salix polaris and Cassiope tetragona, and the soil samples collected in 2014 in Svalbard near Longyearbyen, the concentrations of the following heavy metals were determined: Mn, Ni, Cu, Zn, Cd, Pb and Hg, as well as the activity concentrations of the following: K-40, Cs-137, Pb-210, Pb-212, Bi-212, Bi-214, Pb-214, Ac-228, Th-231 and U-235 in the soil samples. The differences in the concentrations of the analytes accumulated in the different plant species and soil were studied using statistical methods. Sea aerosol was indicated as the source of Pb, Hg, Cs-137, Pb-210 and Th-231 in the studied area. A relatively high concentration of nickel was determined in the biota samples collected near Longyearbyen, compared to other areas of Svalbard. It was supposed that nickel may be released into the atmosphere as a consequence of the local coal mining around Longyearbyen.

Contemporary satellite Earth Observation systems provide growing amounts of very high spatial resolution data that can be used in various applications. An increasing number of sensors make it possible to monitor selected areas in great detail. However, in order to handle the volume of data, a high level of automation is required. The semi-automatic change detection methodology described in this paper was developed to annually update land cover maps prepared in the context of the Geoland2. The proposed algorithm was tailored to work with different very high spatial resolution images acquired over different European landscapes. The methodology is a fusion of various change detection methods ranging from: (1) layer arithmetic; (2) vegetation indices (NDVI) differentiating; (3) texture calculation; and methods based on (4) canonical correlation analysis (multivariate alteration detection (MAD)). User intervention during the production of the change map is limited to the selection of the input data, the size of initial segments and the threshold for texture classification (optionally). To achieve a high level of automation, statistical thresholds were applied in most of the processing steps. Tests showed an overall change recognition accuracy of 89%, and the change type classification methodology can accurately classify transitions between classes.