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Alpine ecosystems are particularly sensitive to climate change, and therefore it is of significant interest to understand the relationships between phenology and its seasonal drivers in mountain areas. However, no alpine-wide assessment on the relationship between land surface phenology (LSP) patterns and its climatic drivers including snow exists. Here, an assessment of the influence of snow cover variations on vegetation phenology is presented, which is based on a 17-year time-series of MODIS data. From this data snow cover duration (SCD) and phenology metrics based on the Normalized Difference Vegetation Index (NDVI) have been extracted at 250 m resolution for the entire European Alps. The combined influence of additional climate drivers on phenology are shown on a regional scale for the Italian province of South Tyrol using reanalyzed climate data. The relationship between vegetation and snow metrics strongly depended on altitude. Temporal trends towards an earlier onset of vegetation growth, increasing monthly mean NDVI in spring and late summer, as well as shorter SCD were observed, but they were mostly non-significant and the magnitude of these tendencies differed by altitude. Significant negative correlations between monthly mean NDVI and SCD were observed for 15–55% of all vegetated pixels, especially from December to April and in altitudes from 1000–2000 m. On the regional scale of South Tyrol, the seasonality of NDVI and SCD achieved the highest share of correlating pixels above 1500 m, while at lower elevations mean temperature correlated best. Examining the combined effect of climate variables, for average altitude and exposition, SCD had the highest effect on NDVI, followed by mean temperature and radiation. The presented analysis allows to assess the spatiotemporal patterns of earth-observation based snow and vegetation metrics over the Alps, as well as to understand the relative importance of snow as phenological driver with respect to other climate variables.

Grasslands cover up to 40% of the mountain areas globally and 23% of the European Alps and affect numerous key ecological processes. An increasing number of optical sensors offer a great opportunity to monitor and address dynamic changes in the growth and status of grassland vegetation due to climatic and anthropogenic influences. Vegetation indices (VI) calculated from optical sensor data are a powerful tool in analyzing vegetation dynamics. However, different sensors have their own characteristics, advantages, and challenges in monitoring vegetation over space and time that require special attention when compared to or combined with each other. We used the Normalized Difference Vegetation Index (NDVI) derived from handheld spectrometers, station-based Spectral Reflectance Sensors (SRS), and Phenocams as well as the spaceborne Sentinel-2 Multispectral Instrument (MSI) for assessing growth and dynamic changes in four alpine meadows. We analyzed the similarity of the NDVI on diverse spatial scales and to what extent grassland dynamics of alpine meadows can be detected. We found that NDVI across all sensors traces the growing phases of the vegetation although we experienced a notable variability in NDVI signals among sensors and differences among the sites and plots. We noticed differences in signal saturation, sensor specific offsets, and in the detectability of short-term events. These NDVI inconsistencies depended on sensor-specific spatial and spectral resolutions and acquisition geometries, as well as on grassland management activities and vegetation growth during the year. We demonstrated that the combination of multiple-sensors enhanced the possibility for detecting short-term dynamic changes throughout the year for each of the stations. The presented findings are relevant for building and evaluating a combined sensor approach for consistent vegetation monitoring.

Climate change vulnerability assessments are an essential instrument to identify regions most vulnerable to adverse impacts of climate change and to determine appropriate adaptation measures. Vulnerability assessments directly support countries in developing adaptation plans and in identifying possible measures to reduce adverse consequences of changing climate conditions. Against this background, this paper describes a vulnerability assessment using an integrated and participatory approach that builds on standardized working steps of previously developed ‘Vulnerability Sourcebook’ guidelines. The backbone of this approach is impact chains as a conceptual model of cause–effect relationships as well as a structured selection of indicators according to the three main components of vulnerability, namely exposure, sensitivity and adaptive capacity. We illustrate our approach by reporting the results of a vulnerability assessment conducted in Burundi focusing on climate change impacts on water and soil resources. Our work covers two analysis scales: a national assessment with the aim to identify climate change ‘hotspot regions’ through vulnerability mapping; and a local assessment aiming at identifying local-specific drivers of vulnerability and appropriate adaptation measures. Referring to this vulnerability assessment in Burundi, we discuss the potentials and constraints of the approach. We stress the need to involve stakeholders in every step of the assessment and to communicate limitations and uncertainties of the applied methods, indicators and maps in order to increase the comprehension of the approach and the acceptance of the results by different stakeholders. The study proved the practical usability of the approach at the national level by the selection of three particularly vulnerable areas. The results at a local scale supported the identification of adaption measures through intensive engagement of local rural populations.

PurposeClimate risk assessments (CRAs) become more and more necessary to prepare and prioritise adaptation action. On a policy level, the results of CRAs offer the foundation for national adaptation strategies. However, existing CRAs oftentimes do not exploit their full potential by means of an integrated assessment, i.e. to illustrate the complexity of cascading risks, provide cross-sectoral results, integrate adaptive capacity and demonstrate spatial patterns. This paper seeks to fill this gap by dissecting integrated assessment approaches of national CRAs.Design/methodology/approachThe paper focuses on the integrated analyses of the results of CRAs. Based on a review of selected national, multi-sectoral CRAs, the authors explore the application of such analyses. Additionally, drawing on the latest climate impact and risk assessment for Germany, the authors highlight latest approaches and their implications.FindingsThe authors show that even though progress in establishing integrated assessment methods has been made, no common framework exists so far and only few national CRAs include extensive integrated analyses. Nevertheless, the German example demonstrates that integrated analyses can provide a comprehensive overview over risk dynamics, (spatial) patterns and needs for action thus providing practical advice for decision-making on a national adaptation policy level.Originality/valueWhile it is common knowledge that CRAs in general provide better results, if the models applied are integrated (i.e. combining climate, geo-physical, economic, etc. factors), little attention has been given to the integrated analyses of their results. This paper provides valuable new insight on this aspect which will become far more important in the future.

The European Alps, home to a blend of permanent residents and millions of annual tourists, are found to be particularly sensitive to climate change. This article employs the impact chain concept to explore the interplay between climate change and health in Alpine areas, offering an interdisciplinary assessment of current and future health consequences and potential adaptation strategies.Rising temperatures, shifting precipitation patterns and increasing extreme weather events have profound implications for the Alpine regions. Temperatures have risen significantly over the past century, with projections indicating further increases and more frequent heatwaves. These trends increase the risk of heat-related health issues especially for vulnerable groups, including the elderly, frail individuals, children and recreationists. Furthermore, changing precipitation patterns, glacier retreat and permafrost melting adversely impact slope stability increasing the risk of gravity-driven natural hazards like landslides, avalanches and rockfalls. This poses direct threats, elevates the risk of multi-casualty incidents and strains search and rescue teams.The environmental changes also impact Alpine flora and fauna, altering the distribution and transmission of vector-borne diseases. Such events directly impact healthcare administration and management programmes, which are already challenged by surges in tourism and ensuring access to care.In conclusion, Alpine regions must proactively address these climate change-related health risks through an interdisciplinary approach, considering both preventive and responsive adaptation strategies, which we describe in this article.