Vestlandsforsking

Abstract Introduction The use of Saccharomyces cerevisiae to ferment alcoholic beverages is an ancient tradition, with genetic evidence indicating origins in Neolithic Asia, although the domestication process of the species is not fully understood. Kveik is a group of traditional yeasts used in farmhouse brewing in western Norway preserved through generations of rural brewing practice. While recent studies have highlighted the distinctiveness of kveik, its precise phylogenetic position, genetic diversity, and domestication history remain unclear. Results We performed whole-genome sequencing on 62 samples representing 25 unique Norwegian strains selected using cultural heritage criteria, and generated telomere-to-telomere (T2T) assemblies for representative isolates. Phylogenomic and population genetic analyses reveal that kveik forms a paraphyletic and early diverging group with respect to other domesticated S. cerevisiae strains. Most strains exhibit low within-strain diversity, strong geographic clustering, and little evidence of gene-flow or admixture. Mitochondrial genomes and Ty1 retrotransposon profiles corroborate this distinct lineage history. We further show that previously reported signals of gene flow between kveik and Asian fermentation strains are likely artifacts caused by population structure and selection. Divergence time estimates suggest that the common ancestor of beer, kveik, and other liquid-phase fermenting strains originated from ancestral populations 4,000 to 8,000 years ago. Conclusion Kveik yeasts represent a relic of early S. cerevisiae domestication, shaped by ancient human practices, migrations, and the spread of agriculture. Our genomic resource sheds light on yeast evolution and domestication. They likely comprise some of the oldest domesticated lineages in continuous use until today, connecting endangered intangible cultural heritage to an early genetic origin.

Glacier surface mass balance observations are highly heterogeneous, with point glaciological measurements spanning decadal timescales being limited to a few well-monitored regions, while geodetic observations are available globally with a multi-annual baseline and almost full glacier coverage. Existing surface mass balance modelling approaches can only calibrate their parameters for individual glaciers or regions with available observations. This often implies that a big part of the available observations per glacier (generally glaciological data) cannot be exploited for calibration since they play the role of independent data for validation. There is a need to move towards flexible surface mass balance models, capable of leveraging in a coherent fashion both glaciological and remote sensing data.To address this challenge, we introduce a new version of MassBalanceMachine, a neural network-based model that predicts monthly surface mass balance using topographical features and monthly climate forcing as inputs. The pointwise nature of the model, combined with the global availability of input features thanks to OGGM and ERA5, enables the implementation of custom loss functions to train the model. This loss function allows the model to align with both glaciological measurements and geodetic mass balance observations over multiple decades.By leveraging the interannual variability and point-wise nature from glaciological data and correcting long term biases with geodetic data, MassBalanceMachine can generate reliable high-resolution monthly mass balance predictions for unmonitored glaciers, and correct existing predictions where previous training strategies are known to fail, e.g. in the Alps. This approach exploits data from data-rich sparse regions to make predictions for other unmonitored regions or glaciers, offering a scalable solution for global glacier mass balance estimation.

ABSTRACT The tourism industry is likely to face significant challenges stemming from climate change and fluctuations in travel costs. This study investigates the potential impacts of these factors on tourism demand in Fjord Norway, and shows that both environmental conditions and travel expenses play a substantial role in influencing tourism demand. However, tourists exhibit a higher sensitivity to variations in travel costs compared to changes in climatic conditions. The findings also indicate that Norwegian tourists, who possess a strong awareness of environmental issues, are less affected by the ramifications of climate change than their domestic counterparts with lower levels of environmental consciousness. In contrast, domestic tourists with high environmental awareness do not demonstrate significant differences in their responsiveness to economic changes compared to those with lower awareness. These insights hold considerable implications for the effective management of tourism in the Fjord Norway region.

Social factors profoundly shape the bereavement process for individuals who have lost someone to a drug-related death. In this study, we integrate qualitative (n = 19), quantitative (n = 5), and mixed-methods (n = 2) results from a large research project on drug-related bereavement and utilise Bronfenbrenner and Morris’s bioecological model as an analytical framework. The results of the project demonstrate that bereavement following a drug-related death is deeply rooted in social context, and they highlight that the process of grieving a drug-related death requires the navigation of complex personal, familial, and societal challenges. Sociocultural understandings of addiction and societal stigma must be addressed to create a more supportive environment for bereaved individuals. A more cohesive and responsive support system can be developed by understanding and acting at all levels of Bronfenbrenner and Morris’s model, encompassing individual competencies, organisational structures, broader social environments, and systemic policies. Focusing on a family and compassionate community approach, our research promotes an inclusive and empathetic societal response to these multifaceted losses. Furthermore, the importance of enhanced professional competencies, interdisciplinary collaboration, and the implementation of organisational change is emphasised in order to meet the needs of those affected by a drug-related death. Ultimately, social work can play a pivotal role in this context.

Abstract. Glacier recession gives rise to changes in land surface type and topography that are poorly represented in atmospheric models but may have important local impacts on climate. Implementing these changes in the Weather Research and Forecasting (WRF) model for the Jostedalsbreen ice cap in western Norway results in warmer and drier regional climate with less snow that can amplify glacier recession through a positive feedback effect. Most of the climatic response to glacier recession is related to the surface lowering associated with ice melt, resulting in reduced orographic lifting of moist air masses and higher surface pressure. The climatic response to glacier recession is largest where the ice melts but is also evident in adjacent valleys several kilometers away from the ice cap. While the warming by glacier recession amplifies effects of global warming, reduced precipitation counteracts the projected regional increase in precipitation. These findings should be included in estimates of glacier mass balance and have implications for agriculture, hydropower, tourism, and biodiversity around glacierised landscapes.

<strong class="journal-contentHeaderColor">Abstract.</strong> This study presents the first systematic field evaluation of dock-based UAV (Uncrewed Aerial Vehicle) systems for geohazard monitoring in mountainous terrain. We tested their potential across three different environments: (1) a fast-moving glacier icefall (Supphellebreen, Norway), (2) an unstable rock slope (Skj&oslash;ld, Norway), and (3) a post-failure landscape resulting from a catastrophic rock-ice avalanche (Blatten, Switzerland). Effective hazard management requires timely detection of displacement patterns and terrain change. To address these issues, we introduce an automated workflow integrating multitemporal UAV dock data acquisition with an end-to-end processing pipeline for displacement field generation and change detection. The results show that this workflow has the potential to provide data at centimetre-level accuracy before, during, and after hazard events, supporting both precautionary risk assessments and timely decision-making in critical phases of potential hazard evolution. Wider adoption will depend on supportive regulatory frameworks, reliable power and communication infrastructure, and sufficient expertise to ensure effective operation, maintenance, data interpretation and risk management. Overall, dock-based UAV systems represent a significant technological advancement in efficient geohazard monitoring, facilitating rapid response in critical situations, thereby contributing to increased resilience of communities living in vulnerable mountain environments.

The discourse on prefigurative politics often revolves around politics and political actions, especially political actions that are actively and consciously engaging with certain tenets of prefiguration. While several scholars have advocated for blurring the boundaries between knowledge and praxis, the implications of prefigurative politics and its (im)possibilities in contemporary modes of funded and participatory research have still not been mapped, barring a few exceptions. The paper will draw from a series of auto/ethnographic vignettes spread between 2014 to 2019 encompassing my sporadic fieldwork (2019–2025) with an autonomous worker’s collective active in Faridabad—an old industrial town in North India to explore the contours and dilemmas of thinking/doing prefigurative politics in research in the contemporary. The paper will weave auto/ethnographic insights that oscillate between situated and experimental knowledge(s) that redefine the epistemological boundaries and the grounds of knowledge production to explore where, when and how prefigurative politics begins and ends in contemporary research and writing practices reflecting on moments of transition, transformation, and crises.

Abstract In 2023, a 54,000 m 3 large rock section failed catastrophically from the unstable rock slope Stampa (Western Norway). The failure occurred in a multistage process with two major failure events on July 1 st and 3 rd . In this study, we present a detailed analysis of the pre-failure displacement patterns, the failure mechanisms, and failure events. After exponential acceleration, the base (12,200 m 3 ) of the rock section failed, leading to a further destabilization of the remaining rock column (41,800 m 3 ), which failed 2 days later. The monitoring data includes in situ displacement sensors, a robotic total station, and close range and remote sensing data spanning over 14 years. The rock section showed seasonal displacement patterns clearly influenced by meteorological factors: (1) late spring (May–July) accelerations, controlled by positive temperatures, thawing ground, and meltwater infiltration, followed by (2) summer stabilizations characterized by low displacement, and (3) autumn (October–November) accelerations driven by precipitation events over a longer period, followed by (4) winter stabilizations approaching zero displacement. The deformation rates increased from 0.06 m a −1 in 1991–2019 more than a tenfold to 0.78 m a −1 in 2022 and indicate progressive damage and weakening of the rock section, which increased its sensitivity to rainfall and infiltration. Our findings highlight the importance of long-term, high-resolution monitoring using different, independent sensors, alongside detailed failure analyses, in understanding the evolution of unstable rock slopes. This study contributes to the understanding of progressive medium-scale rock slope failures, aiding in the prediction and mitigation of potential failures.