Labour in a single shot: critical perspectives on Antje Ehmann and Harun Farocki's global video project

This collection of essays offers a critical assessment of Labour in a Single Shot, a groundbreaking documentary video workshop. From 2011 to 2014, curator Antje Ehmann and film- and videomaker Harun Farocki produced an art project of truly global proportions. They travelled to fifteen cities around the world to conduct workshops inspired by cinema history’s first film, Workers Leaving the Lumière Factory, shot in 1895 by the Lumière brothers in France. While the workshop videos are in colour and the camera was not required to remain static, Ehmann and Farocki’s students were tasked with honouring the original Lumière film’s basic parameters of theme and style. The fascinating result is a collection of more than 550 short videos that have appeared in international exhibitions and on an open-access website, offering the widest possible audience the opportunity to ponder contemporary labour in multiple contexts around the world.https://library.oapen.org/handle/20.500.12657/5163

Frequency Trend Analysis of Heavy Rainfall Days for Germany

Climate change is expected to affect the occurrence of heavy rainfall. We analyzed trends of heavy rainfall days for the last decades in Germany. For all available stations with daily data, days exceeding daily thresholds (10, 20, 30 mm) were counted annually. The Mann–Kendall trend test was applied to overlapping periods of 30 years (1951–2019). This period was extended to 1901 for 111 stations. The stations were aggregated by natural regions to assess regional patterns. Impacts of data inconsistencies on the calculated trends were evaluated with the metadata and recent hourly data. Although the trend variability depended on the chosen exceedance threshold, a general long-term trend for the whole of Germany was consistently not evident. After 1951, stable positive trends occurred in the mountainous south and partly in the northern coastal region, while parts of Central Germany experienced negative trends. The frequent location shifts and the recent change in the time interval for daily rainfall could affect individual trends but were statistically insignificant for regional analyses. A case study supported that heavy rains became more erosive during the last 20 years. The results showed the merit of historical data for a better understanding of recent changes in heavy rainfall

Recent and Future Changes in Rainfall Erosivity and Implications for the Soil Erosion Risk in Brandenburg, NE Germany

The universal soil loss equation (USLE) is widely used to identify areas of erosion risk at regional scales. In Brandenburg, USLE R factors are usually estimated from summer rainfall, based on a relationship from the 1990s. We compared estimated and calculated factors of 22 stations with 10-min rainfall data. To obtain more realistic estimations, we regressed the latter to three rainfall indices (total and heavy-rainfall sums). These models were applied to estimate future R factors of 188 climate stations. To assess uncertainties, we derived eight scenarios from 15 climate models and two representative concentration pathways (RCP), and compared the effects of index choice to the choices of climate model, RCP, and bias correction. The existing regression model underestimated the calculated R factors by 40%. Moreover, using heavy-rainfall sums instead of total sums explained the variability of current R factors better, increased their future changes, and reduced the model uncertainty. The impact of index choice on future R factors was similar to the other choices. Despite all uncertainties, the results indicate that average R factors will remain above past values. Instead, the extent of arable land experiencing excessive soil loss might double until the mid-century with RCP 8.5 and unchanged land management

Soil erosion modelling: a global review and statistical analysis

To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and 2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named ‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’, includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, and make future expansions.</p

Soil erosion modelling: a bibliometric analysis

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper