Reinventing the Wheel: Perpetual Innovation in Sinhalese Potter Assemblages

This paper describes a linked series of potter’s wheel reinventions and abandonments from the mid-20th century through 2013. The wheel is analysed as one element in a complex and dynamic assemblage of people, resources, technologies, meanings, places, and time. Primary data come from ethnographic observations and interviews in a Sinhalese Sri Lankan potter community followed since 1974. As they shifted from one potter’s wheel to another, these potters have altered social and physical supporting technologies for procuring and preparing clay, acquiring fuel, organising labour, and marketing pottery. Some, having reached the limits of a wheel’s capabilities and their own bodies, have abandoned the wheel in favour of moulds and mechanical presses, setting off more cascades of change. Their experiences help to clarify the adaptive capacities and limitations of both potter’s wheels and their users. As this story unfolds in often unanticipated ways, it reveals the importance of attending to spatiotemporal scale. Locally, the wheel highlights the relatively fast-changing affordances and constraints with which individual potters, households, and communities engage. But the wheel also brings into focus the slower moving consequences of regional heterogeneities and paths laid down by national colonial and post-colonial policies decades ago.

Revealing the Relevant Spatiotemporal Scale Underlying Whole-Brain Dynamics

The brain rapidly processes and adapts to new information by dynamically transitioning between whole-brain functional networks. In this whole-brain modeling study we investigate the relevance of spatiotemporal scale in whole-brain functional networks. This is achieved through estimating brain parcellations at different spatial scales (100–900 regions) and time series at different temporal scales (from milliseconds to seconds) generated by a whole-brain model fitted to fMRI data. We quantify the richness of the dynamic repertoire at each spatiotemporal scale by computing the entropy of transitions between whole-brain functional networks. The results show that the optimal relevant spatial scale is around 300 regions and a temporal scale of around 150 ms. Overall, this study provides much needed evidence for the relevant spatiotemporal scales and recommendations for analyses of brain dynamics.

Does the American mink displace the European polecat? A need for more research on interspecific competition between invasive and native species

Introduced alien species can negatively affect native competitors by reducing their populations or eliminating them from ecosystems. However, studies do not always find evidence for anticipated impacts, and changes in native populations can be difficult to estimate. Interactions between the invasive American mink Neovison vison and native European polecat Mustela putorius have been studied in several countries, but the mink’s impact on polecat populations at a large spatiotemporal scale remains unclear. In the years 1995–2018, we live-trapped mink and polecats at 60 study sites in Poland, and we analysed hunting bags of mink and polecats from the years 2009–2018. During 13,766 trap-nights, we captured 905 individuals. Mink comprised 91.2% and polecats 8.8% of trapped animals. The mean mink and polecat trappability was 6 and 0.6 individuals per 100 trap-nights, respectively. At rivers, polecat and mink trappability were negatively correlated, whereas at lakes, they were not correlated. The sex ratio of trapped polecats was more skewed toward males than that of mink. Mink comprised 63.6% and polecats 36.4% of 59,831 animals killed by hunters. Over 10 years, the numbers of mink shot annually increased slightly, whereas the numbers of polecat decreased slightly. There was a positive correlation between numbers of mink and polecats shot annually. We found weak evidence that at a large spatiotemporal scale, the invasion of mink has led to a decline in polecat numbers. Although the datasets we analysed were based on large samples, they were insufficient to show evidence of competitive interactions between these two mustelids.

Rescaling the Weather Experience: From an Object of Aesthetics to a Matter of Concern

This paper analyses the cluster of aesthetic features involved in the common experience of the weather. Perceptual features (framelessness, chromatics, texture, synaesthesia, ephemerality, proteism) are accompanied by ‘atmospheric’ moods that are irreducible to physiological well-being. Representation and imagination reach their limits due to the more-than-human spatiotemporal scale of the atmosphere. Finally, some ‘transaesthetic’ aspects include the agency of an active matter and the longing for an elemental alterity. The aesthetics of the weather has to account for the interdependence between aesthetic and ethical values, between bodily engagement and appropriate knowledge, individual contemplation and social commitment, in order to develop ecological responsibility.

Predicting the future distribution of antibiotic resistance using time series forecasting and geospatial modelling

Background: Increasing antibiotic resistance in a location may be mitigated by changes in treatment policy, or interventions to limit transmission of resistant bacteria. Therefore, accurate forecasting of the distribution of antibiotic resistance could be advantageous. Two previously published studies addressed this, but neither study compared alternative forecasting algorithms or considered spatial patterns of resistance spread. Methods: We analysed data describing the annual prevalence of antibiotic resistance per country in Europe from 2012 – 2016, and the quarterly prevalence of antibiotic resistance per clinical commissioning group in England from 2015 – 2018. We combined these with data on rates of possible covariates of resistance. These data were used to compare the previously published forecasting models, with other commonly used forecasting models, including one geospatial model. Covariates were incorporated into the geospatial model to assess their relationship with antibiotic resistance. Results: For the European data, which was recorded on a coarse spatiotemporal scale, a naïve forecasting model was consistently the most accurate of any of the forecasting models tested. The geospatial model did not improve on this accuracy. However, it did provide some evidence that antibiotic consumption can partially explain the distribution of resistance. The English data were aggregated at a finer scale, and expected-trend-seasonal (ETS) forecasts were the most accurate. The geospatial model did not significantly improve upon the median accuracy of the ETS model, but it appeared to be less sensitive to noise in the data, and provided evidence that rates of antibiotic prescription and bacteraemia are correlated with resistance. Conclusion: Annual, national-level surveillance data appears to be insufficient for fitting accurate antibiotic resistance forecasting models, but there is evidence that data collected at a finer spatiotemporal scale could be used to improve forecast accuracy. Additionally, incorporating antibiotic prescription or consumption data into the model could improve the predictive accuracy.