Government of Lower Austria

Managing a green transition to a sustainable economic system will fundamentally affect the organization of labor markets. To ensure that this green transition is also a just transition it is essential to better understand which employees are vulnerable to these labor market disruptions due to an outdated or inflexible skill set. In other words, knowing what it takes for workers to transition from brown to green requires insights on which of their skills can make this transition with them. To address this gap, I propose a text-based indicator to measure any worker's degree of skill transferability for the green transition based on occupational skills and tasks. This indicator utilizes cosine similarities between sentence embeddings of green tasks and non-green tasks required in specific occupations. It performs equally well across fine-grained levels of occupational classifications, thus paving the way for cross-sectional comparisons. Moreover, the indicator serves as a complement to existing measures of greenness of labor markets as it allows for a more fine-grained analysis of the potential transferability of skills in the green transition. The developed method can augment future research on labor market mobility in light of economic transformations by directly assessing the transition potential of specific skills. Thereby, it can assist policymakers in the design of tailored up- and re-skilling programs to ensure that labor market participants meet the skill requirements for a transition to sustainable and decent jobs. • Green skill transferability indicator applicable across occupational classifications. • Application of the Sentence BERT to create vectorized representations of tasks. • Text-based comparison of tasks between green and non-green occupations. • Combination of US and European skill assessments. • Low skill transferability in high emission sectors key challenge for policy makers.

Negative campaigns can have different effects on voting behavior and political attitudes. While recent work has differentiated between contexts and campaigns, few have investigated the mechanisms underlying the effects of negative campaigns. We argue that negative campaigning may affect whether citizens understand voting as supporting one candidate or party (positive meanings of voting), as opposing another (negative meanings of voting), or even as something useless, unpleasant or undesirable (anti-voting meanings). Using preregistered cross-sectional analyses in the 2022 Hungarian and US elections, we confirm that negative and anti-voting meanings are pervasive, and related to political parties’ use of negative and “dirty” campaigns. Two preregistered survey experiments, however, only confirm the effects of the most outrageous campaign messages. We conclude that meanings of voting are important democratic attitudes that are related to parties’ campaigning behavior. However, they are relatively stable attitudes that are only affected by relatively extreme stimuli.

The COVID-19 pandemic not only posed unprecedented threats to public health and economic stability but also triggered a crisis of information, described by the World Health Organization as an “infodemic.” Against this backdrop, this study explores the dynamics of COVID-19 misperceptions through the lens of Appraisal Theory and the Reinforcing Spirals Model, examining how perceived threats and media exposure shaped belief updating and reinforcement over time. Drawing on a two-year panel survey conducted in Austria (April 2020 to March 2022), we use a mixed Markov chain model to analyze one of the most persistent and widely believed conspiracy narratives—the claim that COVID-19 was a deliberately engineered bioweapon. The results reveal two opposing types of belief trajectories: an upward trajectory of belief stability, reinforcement of accurate beliefs, and correction, driven by perceived health-related threats and exposure to high-quality media, such as public broadcasters and broadsheets; and a downward trajectory marked by heightened belief instability, reinforcement of misperceptions, and an erosion of belief accuracy, associated with perceived economic threats and the use of low-quality media—including tabloids, commercial TV, and social media. Overall, the findings highlight the value of the theoretical frameworks for a more nuanced understanding of belief dynamics in times of crisis and underline the vital role of high-quality media in fostering a well-informed democratic public.

Sea and estuarine breezes (SEB) play a critical role for cooling air temperatures and enhancing thermal comfort during summer in coastal urban areas. This research investigates the dynamics and impacts of SEB in Lisbon (Portugal) by combining data from a mesoscale meteorological network comprising 80 stations with high-resolution wind field simulations during the thermal summer of 2022 (June 10 to October 8). SEB episodes were identified using criteria based on wind direction shifts: the disruption of prevailing northerly winds in the morning (Nortada), transitions to easterly or southerly directions (rotation between 22,6 and 292,5º), and the resumption of regional flow by late afternoon. Wind fields were modeled using GRAMM-SCI, initialized with ERA5 reanalysis data. Finally, air temperature, absolute humidity and thermal comfort (Universal Thermal Climate Index) anomalies (ΔT/Ha/UTCIurb) were calculated to a reference site (the airport weather station) according to the distance to the riverfront area. SEB at 10 m height, occurred on 31% of summer days, peaking in July and August, with an average duration of six hours (10:00AM – 4:00PM). Considering only the roughness effect of the city and the terrain, these breezes reduced air temperatures up to 4 km inland, with maximum cooling effects (-1.7°C) observed within 500m of the Tagus estuary. Absolute humidity increased by 4.2 g/m³ near the estuary, and UTCI values dropped by 2.2°C on typical breeze days, reaching 5.1°C during heatwave events, substantially reducing heat stress within 1.5 km of the riverfront. However, some riverside areas still experienced moderate heat stress, highlighting the importance of preserving SEB corridors through climate-sensitive urban planning. This study reinforces the importance of integrating natural ventilation processes into urban design to foster cooler and more liveable cities.

The three-spined stickleback Gasterosteus aculeatus was introduced into Lake Constance in the 1940s and occupied a limited range until late 2012. Since then the species has expanded from a solely littoral habitat in Upper Lake Constance, but now makes seasonal migrations into the pelagic zone. This behavioral change has been accompanied by a drastic increase in stickleback abundance. In order to integrate information about feeding of sticklebacks in Upper Lake Constance over two consecutive years, stomach content analysis was combined with seasonal stable isotope analysis on two types of tissue (muscle and liver). Isotope values were also obtained for zooplankton, whitefish larvae and eggs. We calculated the contribution of potential food sources for sticklebacks’ diet using a Bayesian mixing model (SIMMR). Furthermore, we determined stickleback trophic position, and δ15N and δ13C values were compared with those of other fish species of Lake Constance. The results of the Bayesian model as well as the stomach content analysis showed clear evidence of stickleback predation on fish eggs and larvae. Stickleback δ15N values were elevated during winter and comparable to those of piscivorous pike, while δ15N values of zooplankton were reduced, and those of whitefish larvae were similar to those of sticklebacks after accounting trophic fractionation of N isotopes. Trophic position calculations further identified sticklebacks as piscivorous, while the δ13C values of the liver and stomach content analysis suggests that a benthic-pelagic species pair may exist in Lake Constance. These findings support the hypotheses that sticklebacks in Lake Constance can display piscivorous feeding behaviour on sympatric fish species, most likely whitefish larvae and eggs.

Sediment-laden flows with significant amounts of large wood can impact alluvial fans and seriously damage infrastructure and property which makes a profound knowledge of exposure an essential requisite for risk mitigation. To investigate its spatial variability, we executed experiments on a simplified physical model and assessed the observed spatial process and exposure patterns by quantifying synthetic indexes and geostatistically analysing spatial probabilities. We systematically varied the loading conditions, i.e. total flow volume, solid fraction and the tank opening controlling water release, and repeated each experimental configuration eight times. Two alluvial fan layouts were considered, one equipped with a guiding channel and a bridge and one with a guiding channel only. First, we tested the hypothesis, that water released though the fully opened tank outflow valve induces a sediment-laden flow which is associated with higher exposure and lower spatial uncertainty of exposure if compared to flows generated by a half-opened tank outflow valve. Second, we tested whether a higher flow volume is associated with higher exposure on the alluvial fan and with lower spatial uncertainty. It turned out that neither of the aforementioned hypotheses is verified for the whole set of tested flow conditions. The first hypothesis is rejected in the majority of the considered conditions. The second hypothesis is prevailingly corroborated when the exposed areas due to both sediment and water were considered. Instead, when only the areas of sediment deposition are considered, this hypothesis is prevailingly corroborated on the alluvial fan featuring the presence of the bridge. We provided exposure probability maps for all experimental conditions and presented the variability of exposure by standard deviation ellipses. Although solely indicative for the adopted alluvial fan layouts, a variation of the loading parameters led to remarkable changes in the patterns of exposure probability and the parameters of the standard deviation ellipses. Our results urge decision makers to fully acknowledge the potential variability of geomorphic responses on alluvial fans in their risk management practices as to avoid underestimating the impacts for the built environment.

Comprehensive field investigations into the axial cyclic loading behaviour of open steel pipe piles driven and aged in low-to-medium-density chalk identify the conditions under which behaviour is stable, unstable or metastable. Post-cycling monotonic tests confirmed that stable cycling enhanced pile capacity marginally, while unstable cases suffered potentially large losses of shaft capacity. Metastable conditions led to intermediate outcomes. The patterns by which axial deflections grew under cyclic loading varied systematically with the normalised loading parameters and could be captured by simple fitting expressions. Cyclic stiffnesses also varied with loading conditions, with the highest operational shear stiffnesses falling far below the in situ seismic test values. The monotonic and cyclic axial responses of the test piles were controlled by the behaviour of, and conditions within, the reconsolidated, de-structured, chalk putty annuli formed around pile shafts during driving. Fibre-optic strain gauges identified progressive failure from the pile tip upwards. Large factors of safety were required for piles to survive repetitive loading under high-level, two-way conditions involving low mean loads, while low-amplitude one-way cycling had little impact. A simple ‘global’ prediction procedure employing interface shear and cyclic triaxial tests is shown to provide broadly representative predictions for field behaviour.

Multi-temporal digital terrain models (DTMs) derived from airborne or uncrewed aerial vehicle (UAV)-borne light detection and ranging (LiDAR) platforms are frequently used tools in geomorphic impact studies. Accurate estimation of mobilized sediments from multi-temporal DTMs is indispensable for hazard assessment. To study volumetric changes in alpine environments it is crucial to identify and discuss different kind of error sources in multi-temporal data. We subdivided errors into those caused by data acquisition, data processing, and spatial properties of the terrain. In terms of the quantification of surface changes, the propagation of errors can lead to high uncertainties. Three alpine catchments with different LiDAR point clouds of different origins (airborne laser scanning [ALS], UAV-borne laser scanning [ULS]), varying point densities, accuracies and qualities were analysed, and used as basis for interpolating DTMs. The workflow was developed in the Schöttlbach area in Styria and later applied to further catchments in Austria. The main aim of the presented work is a comprehensive DTM uncertainty analysis specially designed for geomorphic impact studies, with a resulting uncertainty analysis serving as input for a change detection tool. Our findings reveal that geomorphic impact studies need the careful distinction between actual surface changes and different data uncertainties. ULS combines the benefits of terrestrial laser scanning with all the benefits of ALS. However, the use of ULS data does not necessarily improve the results of the analysis since the high level of detail is not always helpful in geomorphic impact studies. In order to make the different point clouds and DTMs comparable the quality of the ULS point cloud had to be reduced to fit the accuracy of the reference data (older ALS point clouds). Using a point cloud with a high point density with a regular planimetric point spacing and less data gaps, in the best case collected during leaf-off conditions (e.g., cross-flight strategy) turned out to be sufficient for our geomorphic research purposes.